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Autosomal recessive retinal degenerative diseases cause visual impairment and blindness in both humans and dogs . Currently , no standard treatment is available , but pioneering gene therapy-based canine models have been instrumental for clinical trials in humans . To study a novel form of retinal degeneration in Labrador retriever dogs with clinical signs indicating cone and rod degeneration , we used whole-genome sequencing of an affected sib-pair and their unaffected parents . A frameshift insertion in the ATP binding cassette subfamily A member 4 ( ABCA4 ) gene ( c . 4176insC ) , leading to a premature stop codon in exon 28 ( p . F1393Lfs*1395 ) , was identified . In contrast to unaffected dogs , no full-length ABCA4 protein was detected in the retina of an affected dog . The ABCA4 gene encodes a membrane transporter protein localized in the outer segments of rod and cone photoreceptors . In humans , the ABCA4 gene is associated with Stargardt disease ( STGD ) , an autosomal recessive retinal degeneration leading to central visual impairment . A hallmark of STGD is the accumulation of lipofuscin deposits in the retinal pigment epithelium ( RPE ) . The discovery of a canine homozygous ABCA4 loss-of-function mutation may advance the development of dog as a large animal model for human STGD .
Inherited retinal dystrophies are a genetically and clinically heterogeneous group of eye diseases leading to severe visual impairment in both humans and dogs [1–6] . These diseases include various forms of retinitis pigmentosa ( RP ) , Leber congenital amaurosis ( LCA ) , age-related macular degeneration ( AMD ) , cone-rod dystrophies ( CRD ) , and Stargardt disease ( STGD ) and are caused by many different mutations leading to deterioration of neuroretinal and retinal pigment epithelial ( RPE ) function . Over 100 years ago , progressive retinal atrophy ( PRA ) was described as a canine equivalent of human RP [7] and is today the most common inherited retinal degenerative disease in dogs [8] . The shared phenotypic similarity of inherited retinal dystrophies in dogs and humans has made canine models attractive for gene discovery and for experimental treatments , including gene therapy [6 , 9–13] . The development of gene therapy for RPE65-mediated LCA is an example where a canine comparative model has been instrumental for proof-of-principle trials [9 , 11 , 14–16] . The identification of the p . C2Y mutation ( OMIM: 610598 . 0001 ) in the PRCD gene is another illustrative example of the benefits of using canine genetics to find homologous candidate genes for human retinal dystrophies; the PRCD gene was initially mapped and identified in PRA-affected dogs and subsequently in a human family with RP [17] . This mutation segregates in multiple dog breeds , including the Labrador retriever , where no other causative genetic variants for inherited retinal degenerations have been identified . In this study , a Labrador retriever sib-pair , one male and one female , negative for the p . C2Y mutation , was diagnosed with a form of retinal disease which until now had not been characterized clinically . To identify genetic variants associated with this novel canine retinal disease , we performed whole-genome sequencing ( WGS ) of the two affected individuals and their unaffected parents .
The affected sib-pair ( LAB3 and LAB4 , see S1 Fig ) was visually impaired under both daylight and dimlight conditions when examined at 10 years of age . Their pupils were dilated under daylight conditions and pupillary light and dazzle reflexes were abnormal , whereas menace responses were present . On indirect ophthalmoscopy , the tapetal reflectivity varied between normal to grayish hyporeflection when the indirect ophthalmoscopy lens was tilted slightly back and forth , both in the visual streak , as well as in the more peripheral parts of the tapetal fundus in both eyes of the affected dogs . The visual streak is an area of high photoreceptor cell density in the canine retina , located superior to the optic disc and extending horizontally from the nasal to the temporal region [18] . Furthermore , a mild to moderate vascular attenuation was observed , as seen in the fundus photograph , taken at the age of 10 years , of the affected male ( LAB4 ) and compared to a fundus photograph of an unaffected , age-matched Labrador retriever dog ( LAB27 ) ( Fig 1 ) . These ophthalmoscopic findings were symmetrical between the eyes of the affected dogs , diffusely spread over the tapetal fundus and not strictly confined to the visual streak or area centralis . The WGS of the family quartet ( LAB1 , LAB2 , LAB3 and LAB4 , see S1 Fig ) resulted in an average coverage of 18 . 2x ( S1 Table ) and the identification of 6 . 0 x 106 single nucleotide variants ( SNVs ) and 1 . 9 x 106 insertions/deletions ( INDELs ) , of which 48 , 299 SNVs and 5 , 289 INDELs were exonic . We used conditional filtering to identify 322 SNVs ( of which 117 were nonsynonymous ) and 21 INDELs that were consistent with an autosomal recessive pattern of inheritance ( S2 Table ) . To further reduce the number of candidate variants , we compared the positions of the variants to 23 additional dog genome sequences to identify 18 nonsynonymous SNVs in 13 different genes and four INDELs in four genes that were private to the Labrador retriever family ( S2 and S3 Tables ) . Fourteen of these genes were not strong candidates based on reported function and predicted effect and were not considered further . The remaining three genes , KIAA1549 , Usherin ( USH2A ) , and ATP binding cassette subfamily A member 4 ( ABCA4 ) are listed in the Retinal Information Network ( RetNet ) database as associated with human retinal diseases and thus considered as causative candidates for canine retinal degeneration [19] . However , the variant in the KIAA1549 gene was predicted to have a neutral effect on the protein structure ( PROVEAN score -2 . 333 , Polyphen-2 score 0 . 065 ) and was therefore discarded . The genetic variants in the USH2A ( exon 43; c . 7244C>T ) and ABCA4 ( exon 28; c . 4176insC ) genes were validated by Sanger sequencing . Mutations in the human USH2A gene are associated with Usher syndrome and RP , resulting in hearing loss and visual impairment [20] . The identified nonsynonymous substitution in the USH2A gene was scored as “probably damaging” using Polyphen-2 ( score of 0 . 97 ) and as “deleterious” using PROVEAN ( score of -4 . 933 ) ( S3 Table ) . The insertion in the ABCA4 gene was predicted to result in a premature stop-codon at amino acid position 1395 . Next , we evaluated if the genetic variants of USH2A and ABCA4 were concordant with the disease by genotyping eight additional clinically affected and fourteen unaffected Labrador retrievers . Out of these 22 dogs , 16 were related to the family quartet used in the WGS ( S1 Fig ) . The USH2A variant was discordant with the disease phenotype and was therefore excluded from further analysis ( S4 Table ) . In contrast , all eight affected individuals were homozygous for the ABCA4 insertion and the 14 unaffected individuals were either heterozygous or homozygous for the wild-type allele ( S4 Table ) . The identified variant in the ABCA4 gene is a single base pair ( bp ) insertion of a cytosine ( C ) in a cytosine mononucleotide-repeat region in exon 28 , where the canine reference sequence consists of seven cytosines ( CanFam3 . 1 Chr6:55 , 146 , 550–55 , 146 , 556 ) ( Fig 2A ) . The single bp insertion in this region results in a non-synonymous substitution at the first codon downstream of the repeat , and subsequently leads to a premature stop codon ( p . F1393Lfs*1395 ) ( Fig 2C ) . If translated , this would result in a truncation of the last 874 amino acid residues of the wild-type ABCA4 protein ( Fig 2B and 2C ) . Both the human and the dog ABCA4 gene consists of 50 exons and encodes a ~250 kDa ABC transporter protein ( Fig 2D ) ( human and dog ABCA4 consists of 2 , 273 and 2 , 268 amino acid residues , respectively ) [21–23] . ABCA4 is a flippase , localized to the disc membranes of photoreceptor outer segments and facilitates the clearance of all-trans-retinal from the photoreceptor discs [24–26] . To compare retinal ABCA4 gene expression in the affected male ( LAB4 ) , his heterozygous sibling ( LAB6 ) , and a wild-type Labrador retriever ( LAB24 ) , we performed quantitative RT-PCR ( qPCR ) . Primers were designed to amplify three different regions of the gene . The amplicons spanned the 5´-end ( exons 2–3 ) , the identified insertion ( exons 27–28 ) and the 3´-end of the ABCA4 gene ( exons 47–48 ) ( S5 Table ) . Each of the three primer pairs amplified a product of expected size in all three individuals . This suggests that despite the insertion leading to a premature stop codon in exon 28 , the transcripts are correctly spliced . Relative levels of ABCA4 mRNA were lower for the allele with the insertion in comparison to the wild-type allele ( Fig 3A ) . This is consistent with nonsense-mediated decay ( NMD ) degrading a fraction of the transcripts with premature translation stop codon [27] . Transcripts not targeted by NMD could potentially be translated into a truncated protein of only 1 , 394 amino acid residues including the first extracellular domain ( ECD1 ) and the first nucleotide-binding domain ( NBD1 ) ( Fig 2B ) but lacking most of the second extracellular domain ( ECD2 ) and the second nucleotide-binding domain ( NBD2 ) [28–30] ( Fig 2B–2D ) . The NBDs are conserved across species and the NBD2 , which is also referred to as the ATP binding cassette of the ABCA4 protein , has been shown to be particularly critical for its function as a flippase [28 , 30] . To investigate the presence of full-length protein , we performed western blot analysis using an anti-ABCA4 antibody recognizing a C-terminal epitope and detecting a protein product with an approximate size of ~250 kDa . We observed a single , correctly-sized band in samples prepared from both wild-type ( LAB24 ) and heterozygous ( LAB6 ) dogs . The intensity of staining in retinal protein samples from the heterozygous individual was markedly lower in comparison to the samples from the wild-type retina ( Fig 3B ) . In contrast , no band was detected in the retinal sample from the affected dog ( LAB4 ) . To confirm the presence of photoreceptor cells , we used an anti-RHO antibody and detected rhodopsin in all three samples ( Fig 3B ) . These results suggest that no full-length ABCA4 protein product is produced as a result of the insertion leading to a frameshift and a premature stop codon . Fluorescence histochemistry was used to analyze the ABCA4 and rhodopsin protein expression in retinas from three dogs with different ABCA4 genotypes . In addition , we used peanut agglutinin ( PNA ) as it selectively binds to cone photoreceptors [31] . Consistent with the western blot results , rhodopsin immunoreactivity ( IR ) was detected in the outer segments of rod photoreceptors in all three retinas ( S2 Fig ) . In the wild-type ( LAB26 ) and the heterozygous dog ( LAB6 ) , the ABCA4 IR was seen in the outer segments of the neural retina and in the RPE ( Fig 4A and 4B ) . The ABCA4 IR was partially overlapping with the PNA staining , observed in both the inner and outer segments of the cone photoreceptor cells ( Fig 4A and 4B ) . In sharp contrast , ABCA4 expression was absent and only a limited PNA staining was observed in the retina of the affected dog ( LAB4; Fig 4C ) . The observed staining pattern in the fluorescence histochemistry thus suggested loss of cone photoreceptors . To quantify photoreceptor degeneration in the retina of the affected dog ( LAB4 ) , we counted nuclei in the outer and inner nuclear layers and compared the results from the three genotypes . The photoreceptor nuclei are positioned in the outer nuclear layer ( ONL ) and the inner nuclear layer ( INL ) is composed of the horizontal , bipolar , amacrine and Müller glia cell nuclei . Approximately , a 46% reduction of the number of nuclei in the ONL was observed in the affected retina compared to the wild-type ( LAB26 ) and heterozygous ( LAB6 ) retinas ( Fig 4D ) . Thus , the reduction of nuclei in the ONL supported a reduction of the number of photoreceptors . The results from the IR and PNA stainings had already shown a profound reduction of cone photoreceptors , but to assess whether rods were also degenerated in the affected retina , we inferred the number of rod photoreceptors in the wild-type and heterozygous retinas by substracting the number of cone nuclei from the total number of nuclei in the ONL . Approximately , a 41% reduction of rod nuclei was observed in the affected retina , consistent with a retinal degeneration involving also rod photoreceptors ( S2 Fig ) . The corresponding reduction of nuclei was not seen in the INL , suggesting that photoreceptors were affected but not neurons in the INL . Taken together , we observed loss of ABCA4 protein , profound reduction of cone outer segment PNA staining , and a reduction of photoreceptor nuclei in the affected retina . The observed reduction in both cone and rod nuclei imply that not only cone photoreceptors but also rod photoreceptors degenerate in the ABCA4-/- retina of these dogs . The RPE layer of the affected retina was autofluorescent ( Fig 4C ) , indicating accumulation of lipofuscin [32] . We estimated the intensity of autofluorescence in RPE from retinas representing the three ABCA4 genotypes ( LAB4 , LAB6 and LAB26 ) . The autofluorescence in the affected retina was approximately seven-fold higher compared to the retinas of the other genotypes ( Fig 4G and 4H ) . Light microscopic histopathology ( Fig 5 ) was performed on retina from the affected dog ( LAB4 ) , a heterozygote ( LAB6 ) and an unaffected dog ( German spaniel ) . We examined plastic embedded thick sections taken from tapetal and non-tapetal regions superior and nasal to the optic nerve . An accumulation of round lipophilic bodies was found in the RPE overlying the tapetal region of the affected retina ( Fig 5B ) . In contrast to the pigmented RPE in humans , dogs have a reflective area , the tapetum lucidum , in the choroid , where the overlying RPE is not pigmented [33] . The observed round lipophilic bodies predominantly seen in the affected dog are therefore not likely to be melanosomes , but rather an accumulation of lipofuscin . This is consistent with the increased intensity of autofluorescence observed in affected retina as described above ( Fig 4G and 4H ) . In the nasal , non-tapetal part of the retina of the affected male , we observed multifocal RPE hyperplasia and hypertrophy , accompanied by overlying retinal atrophy in some , but not all of these foci ( S3 Fig ) . Consistent with the reduction of cone photoreceptors observed in the frozen sections ( Fig 4D; S2 Fig ) , cone nuclei were markedly reduced in the affected dog ( Fig 5A ) compared to heterozygote and control retinas . Reduced ONL thickness could not be unambiguously confirmed , however it should be noted that very short segments of retina were used for plastic embedding , and that regional ONL atrophy could therefore not be ruled out . In conclusion , histopathologic comparison identified increased lipofuscin accumulation in the RPE , cone loss in central superior retina and focal RPE hypertrophy and hyperplasia in nasal retina of the affected dog . We used flash-electroretinography ( FERG ) to study the photoreceptor function in four dogs at the age of 10 years . The inclination of the first part of the a-waves of the dark-adapted FERG in response to a bright stimulus was less steep and the amplitudes of the a-waves were lower in both affected dogs ( LAB3 and LAB4 ) and their heterozygous sibling ( LAB6 ) , as compared to the age-matched , unaffected dog ( LAB22 ) ( Fig 6A ) , suggesting abnormal photoreceptor function in the affected dogs . The light-adapted FERG responses were subnormal for the affected dogs , showing profoundly impaired cone function ( Fig 6B and 6C ) . The light-adapted responses of the heterozygous dog were closer to the wild-type dog , although amplitudes were slightly lower and b-wave and flicker implicit times slightly longer ( Fig 6B and 6C ) . Furthermore , dark-adaptation reflecting rod photoreceptor function , was clearly delayed in the affected dog ( Fig 6D ) . After 20 minutes , the time commonly used for dark-adaptation [34] , the rod responses of the affected dogs had very low amplitudes . After one hour of dark-adaptation , the affected male ( LAB4 ) reached near normal amplitudes , whereas the amplitudes of his female sibling ( LAB3 ) remained clearly subnormal ( Fig 6D ) , showing that the rod photoreceptors were also affected , but their function was better preserved than the function of the cone photoreceptors . Optical coherence tomography ( OCT ) was performed along the visual streak in three Labrador retriever dogs ( S4 Fig ) . The affected dog ( LAB4 ) had a thinner retina with marked reduction in ONL thickness . Furthermore , we observed some areas of full-thickness retinal atrophy , where the retinal layers could not be distinguished . We were unable to link the areas of alternating normal to grayish hyporeflectivity observed ophthalmoscopically ( Fig 1 ) to localized retinal lesions on OCT . The abnormal and variable tapetal reflectivity seen on ophthalmoscopy was therefore considered to be a sign of a diffusely spread degeneration altering the translucency of the retina overlying the tapetum lucidum . Additional examinations using confocal scanning laser ophthalmoscopy ( cSLO ) and OCT imaging of two affected dogs at the age of 10- and 12-years ( LAB10 and LAB16 , respectively ) confirmed a thinning of the outer retina along the visual streak as compared to two age-matched wild-type dogs ( LAB22 and LAB23 ) ( Figs 7 and 8 ) . Compared to the wild-type dog ( LAB22 ) ( Fig 7A ) , a more irregular tapetal reflection with a hyporeflective visual streak and vascular attenuation was observed on the cSLO of the affected dog ( LAB10 ) ( Fig 7B ) . The thickness of the INL was similar in both the wild-type and the affected dogs ( Fig 7C and 7D ) . The external limiting membrane was thickened and hyperreflective ( Fig 7D ) , whereas the ellipsoid zone ( EZ ) , which corresponds to the junction between the outer and inner segments of the photoreceptors , was fragmented ( Fig 7D ) . The total retinal thickness ( Fig 8A ) was markedly reduced in both affected Labrador retriever dogs ( LAB10 and LAB16 ) compared to the wild-type dogs ( LAB22 and LAB23 ) . However , measurements of the inner retina ( Fig 8B ) showed similar thickness in this part of the retina in all four dogs analyzed . Total photoreceptor length ( REC+; Fig 8C ) and the thickness of the ONL ( Fig 8D ) were markedly reduced both nasally and temporally in the affected dogs , showing that the degeneration of the outer retina is not confined only to the area centralis . The average distance from the EZ to the RPE/Bruch’s membrane ( the innermost layer of the choroid ) was similar in both genotypes ( Fig 8E ) . Taken together , vision of the affected dogs at the age of 10 to 12 years was impaired in both daylight and dimlight conditions , but they still retained some vision throughout their lifetime . The clinical features included ophthalmoscopic signs of bilateral diffuse retinal degeneration and in vivo morphology indicaded a reduction of the number of photoreceptors . The cone function was profoundly abnormal , whereas rod function was better preserved . A hallmark of human ABCA4-mediated diseases such as STGD , is the accumulation of autofluorescent lipofuscin in the RPE throughout the fundus [32 , 35] . This is also seen in mouse models [36 , 37] as well as in the canine retinal degenerative disease described here . In addition , cone photoreceptors are typically affected prior to rods [38] . Furthermore , human RPE cells have been shown to be hypertrophic , and at more advanced stages of the disease , RPE is lost in the perifovea [39 , 40] . Similar to the human histopathology , we observed accumulation of autofluorescent lipofuscin , regions of RPE hypertrophy and hyperplasia , as well as thinning of ONL in the affected dog . Mutations in the human ABCA4 ( ABCR ) gene cause several clinically different diseases ranging from autosomal recessive STGD and autosomal recessive forms of CRD to RP [41–43] . The severity of the disease phenotype is suggested to be dependent on the severity of the mutations [41] . The gene was first cloned and characterized in 1997 [21] , and to date , 873 missense and 58 loss-of-function variants have been reported in the ExAC database [44 , 45] , many of which are associated with visual impairment [46–48] . The ABCA4 protein functions as an ATP-dependent flippase in the visual cycle , transporting N-retinylidene-phosphatidylethanolamine ( N-Ret-PE ) from the photoreceptor disc lumen to the cytoplasmic side of the disc membrane [49 , 50] . N-Ret-PE is a reversible adduct spontaneously formed between all-trans-retinal and phosphatidylethanolamine ( PE ) , and is unable to diffuse across the membrane by itself . Once transported by ABCA4 , N-Ret-PE is dissociated and all-trans-retinal will re-enter the visual cycle [51] . Defective ABCA4 leads to accumulation of N-Ret-PE , which together with all-trans-retinal , will form di-retinoid-pyridinium-phosphatidylethanolamine ( A2PE ) that is further hydrolyzed to phosphatidic acid ( PA ) and a toxic bis-retinoid , di-retinal-pyridinium-ethanolamine ( A2E ) [52] . This will lead to an accumulation of A2E in RPE cells when photoreceptor discs are circadially shed and phagocytosed by the RPE [36 , 53 , 54] . A2E is a major component of RPE lipofuscin , accounts for a substantial portion of its autofluorescence , and has a potentially toxic effect on the RPE leading to photoreceptor degeneration [36 , 55–57] . Currently , there is no standard treatment for STGD in humans and mouse is the only available animal model [58 , 59] . Both the Abca4 knockout mouse [36] and the recently generated Abca4 p . Asn965Ser ( N965S ) knockin mouse [37] models have been significant for the functional characterization of ABCA4 and the lipofuscin fluorophore A2E . Mice , however , lack the macula , the area primarily affected in STGD patients and no significant retinal degeneration has been observed in any of the mouse models [37 , 60 , 61] . Unlike the mouse retina , the dog has a cone rich , fovea-like area functionally more similar to human fovea centralis [2 , 10 , 11] . The canine eye is also comparable in size to the human eye , and dog models have successfully been used for experimental gene therapy for retinal degenerative diseases , such as LCA , RP , and rod-cone dysplasia type 1 ( rcd1 ) [12 , 14 , 16 , 62] . For over a decade there has been interest in finding a canine model for ABCA4-mediated diseases [23 , 63 , 64] . The loss-of-function mutation identified here can be used to develop a large animal model for human STGD .
A family quartet of Labrador retriever dogs ( sire , dam , and two affected offspring numbered LAB1 , LAB2 , LAB3 , and LAB4 , respectively ) were used in the whole-genome sequencing ( WGS ) . In addition , 16 related individuals ( LAB5 to LAB20 , see S1 Fig ) as well as six unrelated Labrador retrievers ( LAB 21 to LAB26 ) were used to validate the WGS findings . Whole blood samples from these dogs were collected in EDTA tubes and genomic DNA was extracted using 1 ml blood on a QIAsymphony SP instrument and the QIAsymphony DSP DNA Kit ( Qiagen , Hilden , Germany ) . We obtained eyes from the affected male ( LAB4 ) and his unaffected sibling ( LAB6 ) at the age of 12 , as well as from two unrelated , unaffected female Labrador retrievers ( LAB24 and LAB26 , 11- and 10-year-old , respectively ) and one 10-year-old male German spaniel ( GS ) after euthanasia with sodium pentobarbithal ( Pentobarbithal 100 mg/ml , Apoteket Produktion & Laboratorier AB , Stockholm , Sweden ) for reasons unrelated to this study . All samples were obtained with informed dog owner consent . Ethical approval was granted by the regional animal ethics committee ( Uppsala djursförsöksetiska nämnd; Dnr C12/15 and C148/13 ) . Ophthalmic examination of all the dogs included in the study included reflex testing , testing of vision with falling cotton balls under dim and daylight conditions , as well as indirect ophthalmoscopy ( Heine 500 , Heine Optotechnik GmbH , Herrsching , Germany ) and slit-lamp biomicroscopy ( Kowa SL-15 , Kowa Company Ltd . , Tokyo , Japan ) after dilation of pupils with tropicamide ( Mydriacyl 0 . 5% , Novartis Sverige AB , Täby , Sweden ) . Genomic DNA from four Labrador retriever dogs ( LAB1 , LAB2 , LAB3 and LAB4 ) was fragmented using the Covaris M220 instrument ( Covaris Inc . , Woburn , MA ) , according to the manufacturer’s instructions . To obtain sufficient sequence depth , we constructed two biological replicates of libraries with insert sizes of 350 bp and 550 bp following TruSeq DNA PCR-Free Library Prep protocol . The libraries were multiplexed and sequenced on a NextSeq500 instrument ( Illumina , San Diego , CA ) for 100 x 2 and 150 x 2 cycles using the High Output Kit and High Output Kit v2 , respectively . The raw base calls were de-multiplexed and converted to fastq files using bcl2fastq v . 2 . 15 . 0 ( Illumina ) . The two sequencing runs from each individual were merged , trimmed for adapters and low-quality bases using Trimmomatic v . 0 . 32 [65] , and aligned to the canine reference genome CanFam3 . 1 using Burrows-Wheeler Aligner ( BWA ) v . 0 . 7 . 8 [66] . Aligned reads were sorted and indexed using Samtools v . 1 . 3 [67] and duplicates were marked using Picard v . 2 . 0 . 1 . The BAM files were realigned and recalibrated with GATK v . 3 . 7 [68] . Multi-sample variant calling was done following GATK Best Practices [69] using publicly available genetic variation Ensembl Variation Release 88 in dogs ( Canis lupus familiaris ) . We filtered the variants found by GATK using the default values defining two groups of analyses: trio 1 and 2 , both consisting of the same sire and dam , and one of their affected offspring . Variants annotated in the exonic region with ANNOVAR v . 2017 . 07 . 16 [70] , presenting an autosomal recessive inheritance pattern and shared between the two trios were selected for further evaluation . To predict the effects of amino acid changes on protein function , we evaluated SNVs using PolyPhen-2 v2 . 2 . 2r398 [71] and PROVEAN v . 1 . 1 . 3 [72] and non-frameshift INDELS using PROVEAN v . 1 . 1 . 3 . Frameshift INDELs were manually inspected using The Integrative Genomics Viewer ( IGV ) [73 , 74] . The sequence data were submitted to the European Nucleotide Archive with the accession number PRJEB26319 . To validate the WGS results , we designed primers amplifying the variants c . 7244C>T in USH2A gene and c . 4176insC in ABCA4 gene with Primer3 [75 , 76] ( S5 Table ) and sequenced the family quartet using Applied Biosystems 3500 Series Genetic Analyzer ( Applied Biosystems , Thermo Fisher Scientific , Waltham , MA ) . To test if the variants were concordant with the disease , 22 additional ophthalmologically evaluated Labrador retrievers were genotyped by Sanger sequencing ( S1 Fig ) . Eight of these dogs were clinically affected and fourteen were unaffected , showing no signs of retinal degeneration by seven years of age . Neuroretinal samples were collected from the affected dog ( LAB4 ) , the heterozygous sibling ( LAB6 ) , and the unaffected female ( LAB24 ) . The samples were immediately preserved in RNAlater ( SigmaAldrich , Saint Louis , MO ) , homogenized with Precellys homogenizer ( Bertin Instruments , Montigny-le-Bretonneux , France ) and total RNA was extracted with RNAeasy mini kit ( Qiagen ) according to the manufacturer’s instructions . RNA integrity and quality were inspected with Agilent 6000 RNA Nano kit with the Agilent 2100 Bioanalyzer system ( Agilent Technologies , Santa Clara , CA ) . cDNA was synthesized using RT2 First Strand kit ( Qiagen ) with random hexamers provided in the kit . cDNA concentration was inspected with Qubit ssDNA Assay kit ( Life Technologies , Thermo Fisher Scientific ) . RT2 qPCR Primer Assay ( Qiagen ) was used to amplify the reference gene GAPDH . To amplify the target gene ABCA4 , we designed custom primers with Primer3 [75 , 76] targeting three different regions spanning exons 2 to 3 , 27 to 28 , and 47 to 48 ( S5 Table ) . We amplified the cDNA fragments encoding regions of interest using RT2 SYBR Green ROX qPCR Mastermix ( Qiagen ) with StepOnePlus Real-Time PCR system ( Applied Biosystems , Thermo Fisher Scientific ) , according to the manufacturer’s instructions . Target gene expression was normalized to expression of GAPDH , and shown relative to the unaffected female ( LAB24 ) using the △△CT method . The results were confirmed in two independent experiments . We extracted protein from the neuroretinal samples of the individuals used in qPCR ( see above ) by homogenization in Pierce RIPA lysis buffer ( Thermo Scientific ) supplemented with phosphatase inhibitor cocktail ( Sigma , P8340 ) using the Precellys homogenizer ( Bertin Instruments ) . Protein concentration was determined using the Pierce BSA Protein Assay kit ( Thermo Fisher Scientific ) . 50 μg of protein samples were resolved by SDS-PAGE , transferred to nitrocellulose membrane , and immunoblotted with the following primary antibodies: ABCA4 ( Novus Biologicals , NBP1-30032 , 1:1000 ) , GAPDH ( Thermo Scientific , MA5-15738 , 1:1000 ) , Rhodopsin ( Novus Biologicals , Littleton , CO , NBP2-25160H , 1:5000 ) , followed by Anti-Mouse IgG horseradish peroxidase-conjugated secondary antibody ( R&D Systems , HAF007 , 1:5000 ) . Binding was detected using the Clarity western ECL substrate ( Bio-Rad , Hercules , CA ) . Tapetal fundus from the affected male ( LAB4 ) , his unaffected heterozygous sibling ( LAB6 ) , and an unaffected 10-year-old female Labrador retriever ( LAB26 ) were fixed in 4% PFA in 1x PBS on ice for 15 minutes , washed in 1x PBS for 10 minutes on ice , and cryoprotected in 30% sucrose overnight at 4°C . The central part of the fundus was embedded in Neg-50™ frozen section medium ( Thermo Scientific ) , and 10 μm sections from the tapetal part of the eye were collected on Superfrost Plus slides ( J1800AMNZ , Menzel-Gläser , Thermo Fisher Scientific ) . The sections were re-hydrated in 1x PBS for 10 minutes , incubated in blocking solution ( 1% donkey serum , 0 . 02% thimerosal , and 0 . 1% Triton X-100 in 1x PBS ) for 30 minutes at room temperature , and incubated in primary antibody ABCA4 ( 1:500 , NBP1-30032 , Novus Biologicals ) or rhodopsin ( 1:5000 , NBP2-25160 , Novus Biologicals ) , and FITC-conjugated lectin PNA ( 1:400 , L21409 , Molecular Probes ) solution at 4°C overnight . Following overnight incubation , the slides were washed 3 x 5 minutes in 1x PBS and incubated in Alexa 568 secondary antibody ( 1:2000 , A10037 , Invitrogen , Thermo Fisher Scientific ) solution for at least 2 hours at room temperature and washed 3 x 5 minutes in 1x PBS . The slides were mounted using ProLong Gold Antifade Mountant with DAPI ( P36931 , Molecular Probes , Thermo Fisher Scientific ) . Fluorescence images were captured using a Zeiss Axioplan 2 microscope equipped with an AxioCam HRc camera . Ten micrometer retinal sections were stained and mounted as described under Fluorescence histochemistry , and the number of nuclei within a region with a width of 67 μm that was perpendicular to and covered both the outer and inner nuclear layers were counted . Nuclei in the outer nuclear and inner nuclear layers were counted separately . We inferred the number of rod photoreceptors by subtracting the number of cones , as identified by PNA staining , from the number of nuclei in the ONL . We analyzed six images from each of the three dogs ( LAB4 , LAB6 , and LAB26 ) . Note that cones were so rare in the affected retina , that all the nuclei in the ONL represent rod photoreceptors . Bar graphs were generated and statistical analysis of the technical replicates ( one-way ANOVA with Tukey’s post hoc multiple comparison analysis ) was performed in GraphPad Prism 7 . Retinal sections were washed , incubated in blocking solution , and mounted as described under Fluorescence histochemistry . The exposure times for the excitation at 488 nm and 568 nm were fixed for all images taken ( 150 ms and 80 ms , respectively ) . Outlines of the retinal pigment epithelium ( RPE ) , as well as adjacent background regions , were drawn using the polygon selection tool in ImageJ ( v1 . 51 , NIH ) , and the area and mean fluorescence intensity were measured . The mean intensity of the autofluorescence in the RPE was calculated by subtracting the background intensity from the adjacent regions . We analyzed six images from each of the three individuals used in the fluorescence histochemistry . Bar graph generation and statistical analysis were performed as described under Counting nuclei . Light microscopic examination was performed on plastic embedded thick sections from 4% PFA fixed posterior sections from eyes of the affected male ( LAB4 ) and his heterozygous sibling ( LAB6 ) , as well as from an unaffected 10-year-old German spaniel dog . The samples were post-fixed in 2 . 5% glutaraldehyde-2% formaldehyde ( 2 hours ) , 2% glutaraldehyde-1% osmium tetroxide ( 1 . 5 hours ) , and 2% osmium tetroxide ( 1 . 5 hours ) . The posterior segments were then trimmed into segments 2–5 mm in length , taken from the superior retina ( three sections located 0 . 5 cm to 1 . 5 cm dorsal to the optic nerve ) , and the nasal retina ( two sections from non-tapetal retina ) . These were dehydrated , and embedded in epoxy resin ( PolyBed 812; Polysciences , Warrington , PA ) . Tissues were sectioned at 1μm and stained with azure II-methylene blue/paraphenylenediamine counterstain . Sections were examined with a 40× objective on a light microscope ( Axioplan; Carl Zeiss Meditec GmbH Oberkochen , Germany ) and images collected with an AxioCam MrC digital camera ( Carl Zeiss Meditec GmbH Oberkochen , Germany ) . We recorded full-field FERG from the four dogs ( LAB3 , LAB4 , LAB6 and LAB22 ) examined with OCT under general anaesthesia . Sedation with intramuscular acepromazine 0 . 03 mg/kg ( Plegicil vet . , Pharmaxim Sweden AB ) was followed by induction with propofol 10 mg/kg intravenously ( Propovet , Orion Pharma Animal Health AB , Danderyd , Sweden ) . After intubation , inhalation anaesthesia was maintained with isoflurane ( Isoflo vet . , Orion Pharma Animal Health AB ) . Corneal electrodes ( ERG-JET , Cephalon A/S , Aalborg , Denmark ) were used with isotonic eye drops ( Comfort Shield , i . com medical GmbH , Munich , Germany ) as coupling agent . Gold-plated , cutaneous electrodes served as ground and reference electrodes ( Grass , Natus Neurology Inc . Pleasanton , CA ) at the vertex and approximately 3 cm caudal to the lateral canthi , respectively . Light stimulation , calibration of lights , and processing of signals were performed as described by Karlstam et al . , 2011 [77] . We used a slightly modified ECVO protocol [34] , where the process of dark-adaptation was monitored for 1 hour before a dark-adapted response intensity series was performed . The affected male ( LAB4 ) , his unaffected sibling ( LAB6 ) and an unaffected , age-matched , female Labrador retriever ( LAB22 ) were examined with spectral-domain OCT ( Topcon 3D OCT-2000 , Topcon Corp . , Tokyo , Japan ) . The examination was done after pupillary dilation , but without sedation , using repeated horizontal single line scans ( 6 mm , 1024 A-scans ) along the visual streak area . Additional cSLO- and OCT-imaging was performed in two affected ( LAB10 and LAB16 ) and two unaffected , wild-type dogs ( LAB22 and LAB23 ) using a Spectralis HRT + OCT Heidelberg Engineering GmbH , Germany ) . The dogs were lightly sedated with 0 . 01 mg medetomidine per kg intramuscularly ( Sedator vet . , Dechra Veterinary Products AB , Upplands-Väsby , Sweden ) , and corneas were kept moist using artificial tears ( Aptus SentrX , Orion Pharma Animal Health , Danderyd , Sweden ) . | Stargardt disease ( STGD ) is the most common inherited retinal disease causing visual impairment and blindness in children and young adults , affecting 1 in 8–10 thousand people . For other inherited retinal diseases , the dog has become an established comparative animal model , both for identifying the underlying genetic causes and for developing new treatment methods . To date , there is no standard treatment for STGD and the only available animal model to study the disease is the mouse . As a nocturnal animal , the morphology of the mouse eye differs from humans and therefore the mouse model is not ideal for developing methods for treatment . We have studied a novel form of retinal degeneration in Labrador retriever dogs showing clinical signs similar to human STGD . To investigate the genetic cause of the disease , we used whole-genome sequencing of a family quartet including two affected offspring and their unaffected parents . This led to the identification of a loss-of-function mutation in the ABCA4 gene . The findings of this study may enable the development of a canine model for human STGD . | [
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"experim... | 2019 | An ABCA4 loss-of-function mutation causes a canine form of Stargardt disease |
In Toxoplasma gondii , cis-acting elements present in promoter sequences of genes that are stage-specifically regulated have been described . However , the nuclear factors that bind to these cis-acting elements and regulate promoter activities have not been identified . In the present study , we performed affinity purification , followed by proteomic analysis , to identify nuclear factors that bind to a stage-specific promoter in T . gondii . This led to the identification of several nuclear factors in T . gondii including a novel factor , designated herein as TgNF3 . The N-terminal domain of TgNF3 shares similarities with the N-terminus of yeast nuclear FK506-binding protein ( FKBP ) , known as a histone chaperone regulating gene silencing . Using anti-TgNF3 antibodies , HA-FLAG and YFP-tagged TgNF3 , we show that TgNF3 is predominantly a parasite nucleolar , chromatin-associated protein that binds specifically to T . gondii gene promoters in vivo . Genome-wide analysis using chromatin immunoprecipitation followed by high-throughput sequencing ( ChIP-seq ) identified promoter occupancies by TgNF3 . In addition , TgNF3 has a direct role in transcriptional control of genes involved in parasite metabolism , transcription and translation . The ectopic expression of TgNF3 in the tachyzoites revealed dynamic changes in the size of the nucleolus , leading to a severe attenuation of virulence in vivo . We demonstrate that TgNF3 physically interacts with H3 , H4 and H2A/H2B assembled into bona fide core and nucleosome-associated histones . Furthermore , TgNF3 interacts specifically to histones in the context of stage-specific gene silencing of a promoter that lacks active epigenetic acetylated histone marks . In contrast to virulent tachyzoites , which express the majority of TgNF3 in the nucleolus , the protein is exclusively located in the cytoplasm of the avirulent bradyzoites . We propose a model where TgNF3 acts essentially to coordinate nucleolus and nuclear functions by modulating nucleosome activities during the intracellular proliferation of the virulent tachyzoites of T . gondii .
Toxoplasma gondii has long been a major medical and veterinary problem capable of causing abortion , or congenital birth defects in both humans and livestock . The advent of AIDS has drawn even more attention to T . gondii as a serious opportunistic pathogen . T . gondii is distinct from nearly all of the other members of the phylum Apicomplexa , owing to the exceptional range of all warm-blooded animals and humans that serve as hosts . The infection is incurable because of its ability to differentiate from the rapidly replicating tachyzoite stages into latent cysts containing the bradyzoite stages that are impervious to immunity and current drugs . T . gondii cysts and dormant bradyzoites persist in the brain of the infected host and also play key roles in pathogenesis because they can convert to virulent tachyzoites in immune compromised individuals with AIDS and in transplant patients . This stage conversion is triggered by the host immune response and impairment of the immune system in HIV infected individuals can lead to lethal toxoplasmic encephalitis . Although the basal core transcriptional machinery , the protein-coding genes involved in nucleosome assembly and chromatin remodelling machinery were found to be conserved in T . gondii genome ( http://www . toxodb . org ) , a surprising finding was the identification of a relatively low number of genes encoding transcription factors in the parasite [1]–[6] . This has led to the proposal that gene regulation in T . gondii and other apicomplexan parasites is controlled mainly by epigenetic mechanisms [7]–[9] . However , bioinformatics searches for DNA-binding domains identified , in Plasmodium spp and in all apicomplexan parasite genomes sequenced to date , a family of proteins homologous to the plant transcription factor Apetala2 , named ApiAP2 for apicomplexan AP2-like factors [10] . De Silva et al . have demonstrated the DNA-binding specificities of two ApiAP2 proteins that have a high specificity for unique DNA sequence motifs found in the upstream regions of distinct sets of genes co-regulated during asexual development [11] . One Plasmodium ApiAP2 factor has a major role in stage-specific gene regulation by activating a set of genes , including genes reported to be required for midgut invasion . It has also been described that this ApiAP2 factor binds to specific six-base sequences in the proximal promoters [12] . Our current knowledge from T . gondii transcriptome indicates that mRNA pools are dynamic and transcriptional control is also a primary means to regulate the developmental transitions of the parasites , suggesting that gene regulation occurs mostly at the transcriptional level [13] , [14] . Microarray studies have demonstrated that transcriptional regulation required timed expression of clusters of genes during the bradyzoite development and that for most genes changes in transcription are tied to modulations in protein expression [15]–[18] . Further confirmatory data is provided by the Serial Analysis Gene Expression ( SAGE ) , which supports the notion that transcriptional regulation plays a key role in the developmental program of T . gondii [19] . We and others have previously established that T . gondii stage conversion is accompanied by the expression of a variety of genes that displayed diverse functions , suggesting that parasite differentiation is clearly regulated in part at the transcriptional level [20]–[28] . In addition , several promoter sequences have been characterized in T . gondii [29]–[31] . We have shown that the promoter regions of two stage-specifically expressed genes displayed promoter autonomy that can be exploited to achieve developmental expression of reporter genes [31] . Yet almost nothing is known about the nature of nuclear factors that can specifically bind to T . gondii promoters and regulate transcriptional activity . Here , we report the isolation and characterization of a novel T . gondii promoter-specific binding factor designated herein as TgNF3 , which shares similarities with yeast nuclear FK506-binding protein ( FKBP ) , known to be a histone chaperone regulating rDNA silencing . We demonstrate that TgNF3 protein is predominantly a nucleolar , chromatin-associated protein that binds specifically to T . gondii gene promoters in vivo , leading to a direct role in transcriptional regulation . ChIP-seq and genome-wide analysis of TgNF3 targets identified gene promoters mainly involved in parasite metabolism , transcription and translation . Importantly , TgNF3 interacts directly to core and nucleosome-associated histones in the context of gene silencing . Furthermore , we show that TgNF3 is a dynamic chromatin-associated factor , a modulator of nucleolus biogenesis , parasite replication and virulence . Taken together , our findings suggest a major role of TgNF3 in nucleosome activity that may regulate nucleolar and nuclear functions during the intracellular proliferation of T . gondii .
To test the suitability of using a stage-specific promoter to purify and determine the identity of nuclear factors that interact and control the activity of a T . gondii stage-specific promoter , we performed affinity chromatography using biotinylated DNA sequence ( Figure S1 ) from the previously reported bradyzoite-specific ENO1 promoter [31] used as bait ( experimental strategy outlined in Figure 1A ) . After biotinylation , we checked whether the probe still binds to parasite nuclear factors . As shown in Figure 1B , the biotinylated probe strongly interacts specifically with nuclear factors in gel retardation . The specificity of the DNA-protein complexes visualized ( lane 2 ) was demonstrated by a competition assay using unlabelled probe ( lane 3 ) , confirming the presence of bound parasite nuclear factors . To determine the nature of these nuclear factors , large-scale affinity purification was carried out using the biotinylated bait incubated with a nuclear extract containing about 17 mg of total nuclear proteins obtained from 4×1010 tachyzoites . Thirty-five nuclear proteins were identified and isolated after SDS-PAGE and silver staining ( Figure 1C ) . These proteins were excised as gel slices and subjected to proteomics analyses . Using mass spectrometry and database searches , we identified thirty nine putative nuclear factors , which are presented as three groups in Supplementary Table 1 ( Table S1 ) : 1 ) A class of 11 proteins , which displayed significant similarities to known nuclear factors . These include a protein possessing a RNA-specific DEAD/DEAH box helicase domain ( genbank identifier ( gi ) number 211966692 ) and a protein having a pinin domain ( genbank identifier ( gi ) number 211966969 ) . Members of the pinin family have various localisations ( including nuclear location ) within eukaryotic cells and are thought to regulate protein-protein interactions [32] . A protein ( gi number 211962881 ) , which shares similarities with a nuclear FK506-binding protein ( Spodoptera frugiperda FKBP46 ) , is also found in this group . The FKBP46 homologue in Saccharomyces pombe , SpFKBP39 , was reported to be involved in transcription repression of ribosomal DNA [33] . Other nucleolar factors and nuclear proteins containing DNA-binding motifs were also present . 2 ) A second class of 7 proteins corresponds to kinases , phosphatases and heat shock proteins . 3 ) Finally , 21 hypothetical proteins , more than half of the total number of factors discovered , displayed no obvious similarity to known factors . However , our further bioinformatics analyses identify two proteins in this group ( genbank identification ( gi ) numbers 211967631 and 211968320 in Table S1 ) as homologues of Alba , ancient archaeal chromatin-associated factors . The Alba factors are known to be involved in gene silencing operating through chromatin regulation in Archaea [34] , [35] . Several proteins identified during the proteomics analyses could clearly be expected to be present in the nucleus of the parasite , for example those with strong similarities to known nucleolar factors . However , the majority of enzymes and hypothetical proteins identified could not be obviously considered as genuine parasite nuclear factors . Therefore , we decided to verify whether some of these factors are truly localized in the nucleus of T . gondii . We have chosen 7 candidate proteins and used two distinct tagged constructs to examine the presence of these factors in the parasite's nucleus . The full-length cDNAs of these candidate proteins were fused to YFP or HAFLAG tags and their expression was driven by tubulin ( Tub 1 ) and dense granule 1 ( GRA1 ) promoters , respectively . We compared the location of YFP tagged proteins relative to ENO2 , a glycolytic enzyme known to be predominantly detected in the nucleoplasm but not in the nucleolus of active replicated intracellular tachyzoites [36] . Figure 2A illustrates four YFP-tagged candidate proteins with convincing nuclear location assessed by direct fluorescence microscopy . These candidate proteins were therefore named TgNFs for T . gondii nuclear factors . TgNF1 ( gi number 211966692 ) and TgNF2 ( gi number 211966969 ) , containing a DEAD/DEAH box helicase domain and a pinin domain , respectively , showed perfect overlapping fluorescence signals with anti-ENO2 staining , suggesting that these two factors localized in the parasite nucleoplasm ( Figure 2A ) . In contrast , two distinct patterns of fluorescence were observed for TgNF3 ( gi number 211962881 ) and TgNF4 ( gi number 211965453 ) with strong fluorescence in the parasite nucleolus in addition to a faint signal , which co-localized with ENO2 signal in the nucleoplasm ( Figure 2A ) . In a similar approach , we confirmed the location of TgNF1 and TgNF2 in the parasite nucleoplasm ( Figure 2B ) . Both diffuse nucleoplasm and strong nucleolar patterns were confirmed for TgNF3 and TgNF4 in transgenic HAFLAG-tagged protein , whose expression was driven by another promoter ( Figure 2B ) . In contrast , using polyclonal antibodies specific to the two homologues of ancient archaeal chromatin-associated factors named Alba1 and Alba2 ( Table S1 ) , and here designated TgNF5 and TgNF6 , fluorescence signals were mainly detected in the parasite cytoplasm ( Figure 3A ) . However , we cannot rule out the presence of TgNF5 and TgNF6 in the parasite nucleus , as superimposition of ENO2 signal ( red ) and DAPI ( blue ) with TgNF5 or TgNF6 fluorescence ( green ) showed profiles , which significantly overlap on the nucleus periphery ( Figure 3B ) , suggesting that these Alba homologues may have regulatory functions in both nucleus and cytoplasm , as previously described [34] , [35] , [37] . Antibodies specific to the candidate factor TgNF7 that has no known functions ( Table S1 ) also showed dual cytoplasm and nuclear localization , which is similar to TgNF5 and TgNF6 ( Figure 3A and 3B , lower panels ) . In addition , TgNF5 , TgNF6 and TgNF7 were also detected in both nuclear and cytoplasm-enriched materials after sub-cellular fractionation followed by Western blots . Thus , we conclude that all seven factors experimentally tested herein are capable of entering the nucleus of T . gondii . To investigate whether any of these candidate factors can directly bind to T . gondii promoter , E . coli produced recombinant proteins fused to GST ( Figure 4A , stars ) were tested in gel shift assays ( Figure 4B ) . Out of the five recombinant proteins , rTgNF7 strongly binds to the biotinylated ENO1 promoter ( Figure 4B , lane 6 ) , whereas TgNF1 appears to only weakly interact ( Figure 4B , lane 4 ) , as expected for a protein containing a putative DEAD/DEAH box helicase domain . Neither GST alone ( Figure 4B , lane 1 ) , nor the other three recombinant factors bound the probe ( Figure 4B , lanes 3 , 5 and 7 ) . We have extensively scanned the whole ENO1 promoter sequence ( Figure S1 ) for retarded DNA-protein complexes using purified rTgNF7 lacking GST ( Figure 4C , lane 1 ) . We identified a 47-bp DNA fragment ( Figure S1 , red ) that specifically binds to rTgNF7 ( Figure 4D , lane 2 ) . The specific motif that binds rTgNF7 was then determined by successive mutations or replacements that lead to the identification of GGGGG ( Figure S1 , blue ) as the genuine target motif of rTgNF7 . The presence of the GGGGG motif is sufficient for rTgNF7 binding , and was proportional to the number of GGGGG motifs present ( Figure 4E–4G ) . The direct binding of TgNF7 to the GGGGG motif present in T . gondii promoters suggested that only one of the three candidate factors with dual cytoplasm and nuclear localization has the DNA binding characteristics of a genuine nuclear factor , whose precise regulatory functions in the parasite await further investigation . With the exception of TgNF1 that contains a DEAD/DEAH box helicase domain , the other candidate factors are probably involved in protein-protein interactions required for promoter binding . We decided to investigate in more detail TgNF3 , which shares similarities with nuclear FK506 binding proteins ( FKBP ) , known in yeast as a histone chaperone that regulates rDNA silencing [33] . Because TgNF3 was selected for further detailed molecular and functional characterization , we wanted to determine whether this putative homologue of fungi , nuclear FK506-binding protein is a genuine member of this family , and consequently is essential for nucleolar/nuclear functions in the parasite . A first analysis of the TgNF3 protein sequence using Hydrophobic Cluster Analysis ( HCA ) [38] indicated that it contains two globular domains ( boxes , Figure 5A ) , separated by a linker sequence , rich in acidic residues ( unboxed area , Figure 5A ) . A PSI-BLAST search using the first domain ( aa 1–100 ) of TgNF3 as query indicated significant similarity with the histone deacetylase 2 ( HD2 ) /nuclear FK506-binding protein ( FKBP ) family , which was first reported by Aravind & Koonin [39] ( Figure 5B ) . The N-terminal domain of nuclear members of the FKBP family found in yeasts and insects has nucleosome assembly activity , which is independent of the activity of their C-terminal FKBP domain , having peptidyl-prolyl isomerase ( PPIase ) activity [33] . This N-terminal domain shares significant similarities with the N-terminal domain of HD2 proteins , which are described as plant-specific histone deacetylases ( HDACs ) [39]–[41] . Following the HD2 N-terminal domain alignment , it has been described that the two conserved polar residues , namely an invariant aspartic acid and a histidine ( arrows on Figure 5B ) , may play a key role in lysine deacetylation [40] , a prediction that was partly supported by a further experimental investigation [41] . The HD2/nuclear FKBP family , encompassing the N-terminal domains of plant HD2 and nuclear FKBPs found in fungi and insects , also includes the N-terminal domains of parasitic apicomplexan proteins . This family includes TgNF3 , which also possesses the two conserved polar residues H25 and D67 ( blue and red arrows on Figure 5B ) but intriguingly , does not include vertebrate members [40] . Remarkably , after further PSI-BLAST iterations , we found significant similarities with the N-terminal ( Np ) core domain of the nucleoplasmin/nucleophosmin ( NPM ) family , which are nuclear chaperones from vertebrates involved in chromatin remodelling [42] ( Figure 5B ) . Reciprocal searches using sequences from the NPM family also highlighted the similarity with the whole HD2/nuclear FKBP family . Thus , the N-terminal domains of the HD2/nuclear FKBP and nucleoplasmin/nucleophosmin ( NPM ) families form a unique large structural superfamily , sharing a common ability to bind histones . For all members of the family , the N-terminal Np core is followed by acidic stretches , thought to play an important role in histone binding ( Figure 5B ) , but only in few cases , a C-terminal globular domain follows this acidic stretches as for nuclear FKBP , in which this domain has peptidyl-prolyl isomerase ( PPIase ) activity . For TgNF3 , a small domain consisting of α-helices is also present , but it shares no obvious similarity with any other known domain . We thus present in this study a refined alignment between these two families , which contain well-conserved amino acids in some positions , in particular those occupied by hydrophobic amino acids ( Figure 5B ) . Worth noting is that two basic and acidic residues thought to participate in the deacetylase activity in the HD2/nuclear FKBP family ( arrows on Figure 5B ) are not conserved in the NPM family , suggesting that the deacetylase function , if it is proven to be conserved in the HD2/nuclear FKBP family , might be lost in the NPM family . In addition , we provide a structural interpretation of the HD2/nuclear FKBP alignment using the data from crystal structures of NPM family members . These have revealed that the Np core adopts an eight-stranded beta-barrel structure and organizes itself into pentameric or decameric structures [43]–[45] . These decameric structures ( dimers of pentamers ) appeared to have direct relevance to histone binding . It has been proposed that histone octamers dock around the NPM decamer periphery , the binding especially involving an acidic stretch ( NPM A1 tract ) and a signature β-hairpin of the Np core ( pink and orange in Figure 5B and 6A ) . However , the examination of our alignment showed that the NPM-specific acidic A1 tract is not present in the HD2/nuclear FKBPs . Instead , acidic stretches of variable length within the β-hairpin linking strands β4 and β5 are present in the nuclear FKBPs ( FKBP acidic tract , Figure 5B ) . This insertion would be located in close proximity to the loop integrating the NPM A1 tract ( Figure 5A ) . Moreover , we showed that the two residues that may play a key role in lysine deacetylation , namely an invariant aspartic acid and a histidine ( arrows on Figure 5B ) [39] , [43]–[45] , are located in close proximity on the NPM Np core ( blue and red in Figure 6A ) , at the end of the funnel shaped cavity formed by the different subunits , and on the subunit distal face ( thus opposite to the pentamer-pentamer interface ) . The two residues are also close to the positions of the acidic stretches and of the β-hairpin . We thus hypothesize here from this 3D mapping that the binding of histones on the NPM/HD2 scaffold may not involve the decamer periphery as previously suggested . Rather the distal ends with the pentameric organization may be probably important for histone binding . Even though the HD2/nuclear FKBPs would adopt a NPM-like quaternary association will require further experimental proofs , the recent electron microscopy observations showed that histones do truly interact with the NPM chaperone distal face [46] . These data are in good agreement with our hypothesis , and the schematic representation of Figure 6B also highlights that SpFKBP39 and TgNF3 have a common N-terminal domain with NPM/HD2 , but differ in their C-terminal extremities . The C-terminal globular domain of T . gondii TgNF3 , which is specific of apicomplexan parasites , has no similarity with the C-terminal propyl peptidyl isomerase of nuclear FKBPs and to other known proteins . Therefore , we embarked in the functional characterization of TgNF3 protein . Towards the identification of the potential nuclear functions of TgNF3 during intracellular development of the parasite , we analyzed the pattern TgNF3 gene expression in the two invasive life stage forms of T . gondii present in intermediate hosts . Specific transcript coding TgNF3 were amplified by quantitative real-time RT-PCR using total RNA isolated from the rapidly replicating tachyzoites and the dormant encysted bradyzoites ( Figure 7A ) . A comparison of the amount of specific transcripts between virulent tachyzoites and dormant bradyzoites was assessed by real-time qRT-PCR using a normalization step with transcript coding the housekeeping β-tubulin . Figure 7A showed that the level of TgNF3 mRNA is at least 5-fold more abundant in the persistent and dormant bradyzoites than in the virulent rapidly replicating tachyzoites . To investigate the functions of TgNF3 in T . gondii , we initially attempted to knockout the gene , but failed even in the Δku80 parasite strain that lacks random DNA integration [47] , or when using the inducible-anhydrotretracyline system [48] , suggesting that the TgNF3 gene codes for an essential function and the locus may also be inaccessible to double homologous recombination . Therefore , we decided to ectopically express the TgNF3 gene in transgenic parasites . Moreover , the quantitative real-time RT-PCR data ( Figure 7A ) , which indicates that TgNF3 transcript level is 5-fold lower in the rapidly replicating tachyzoites relative to the persistent dormant bradyzoites is not only pertinent to this alternative strategy , but also to investigate its biological relevance . We generated transgenic tachyzoites , which ectopically express TgNF3 fused to YFP . Polyclonal antibodies were also raised against purified recombinant TgNF3-GST fusion protein and Figure 7B shows the specificity of the anti-TgNF3 purified sera tested by Western blots using the recombinant nonfusionTgNF3 ( lane 2 ) , GST-TgNF3 fusion expressed in E . coli ( lane 1 ) , total extract proteins from T . gondii tachyzoites ( lane 3 ) , from uninfected human fibroblast ( lane 4 ) and from brain cells ( lane 5 ) . The sera specifically recognized a single band corresponding to a 43-kDa protein in tachyzoites ( lane 3 ) , which is in good agreement with the expected molecular mass of TgNF3 . This observation is also supported by the co-migration between the bacterial recombinant non-fusion TgNF3 protein ( lane 2 ) and the native parasite TgNF3 protein ( lane 3 ) . Neither anti-GST antibodies nor the pre-immune mice sera reacted with T . gondii proteins on Western blots . To determine the pattern of expression of TgNF3 in the different life stages of the parasite , cell lysates of tachyzoites and bradyzoites were resolved by SDS-PAGE and probed by Western blots using purified antisera . Figure 7C illustrates the detection of similar levels of TgNF3 protein in tachyzoites and bradyzoites ( upper panel ) , as immunoblots in parallel with monoclonal antibody anti-Toxoplasma actin provided loading controls ( lower panel ) . These data suggest that the difference in TgNF3 transcript level does not correlate with the amount of protein detected in the two invasive life stage forms of T . gondii . We also transfected parasites with a vector expressing TgNF3 tagged to YFP under the control of the constitutive TUB1 promoter ( pTUB1-TgNF3-YFP ) . These and other expression vectors used in this study are depicted schematically in Figure 2 ( on the top ) and the stable parasites were selected by chloramphenicol and cloned . Western blot analysis of total protein extracts from transgenic parasites expressing TgNF3 ( Figure 7D , arrowheads ) confirmed that both native TgNF3 ( 43-kDa protein ) and transgenic TgNF3-YFP fusion protein ( ∼70-kDa protein ) were detected with anti-TgNF3 antibodies ( lane 7 ) . As anticipated , only TgNF3 was recognized in the wild type parasites ( lane 6 ) . The monoclonal antibody specific to GFP recognized only the TgNF3-YFP fusion protein in the transgenic tachyzoites ( lane 9 ) whereas no protein was detected in wild type tachyzoites ( lane 8 ) , as expected . It should be noticed that we choose to study a transgenic line where ectopic levels of TgNF3-YFP were roughly equivalent to endogenous ones ( Figure 7D , lane 7 ) , as we did not want over-expression of TgNF3-YFP to lead to down-regulation of endogenous TgNF3 levels . Nonetheless , in these transgenic parasites the sum of TgNF3 levels is made up of both ectopically expressed TgNF3-YFP plus endogenous TgNF3 . As a consequence , overall TgNF3 protein levels are approximately 2-fold higher than in wild type parasites . We next compared the localization of TgNF3 in parental and TgNF3-YFP ectopically expressing tachyzoites using purified anti-TgNF3 antibodies , YFP-direct fluorescence detection or both anti-TgNF3 and YFP signals . Figure 8A shows confocal images of extracellular transgenic tachyzoites that ectopically express TgNF3-YFP . In contrast to nucleoli with weaker fluorescence signal in the parental tachyzoites , stained with the anti-TgNF3 antibodies ( Figure 8A , upper panels ) , the ectopically TgNF3-YFP expressers contain nucleoli with strong fluorescent signals , which occupied an important proportion of the nuclear volume of the parasites ( Figure 8A , middle panels ) . This conclusion is further supported by an even stronger signal of enlarged nucleoli observed in transgenic TgNF3-YPF expressers , stained with the anti-TgNF3 antibodies ( Figure 8A , lower panels ) , thereby confirming the relative over-expression of TgNF3 protein in the ectopically expressing TgNF3-YFP parasites as described by Western blot experiments ( Figure 7 ) . In addition , Figure 8B shows confocal images of intracellular transgenic tachyzoites ectopically expressing TgNF3-YFP ( lower panel ) , which contain nucleoli with stronger fluorescent signals , which often occupied a large proportion of the nucleus volume as compared to parental tachyzoites ( upper panels ) . These data confirm that TgNF3 is most prominent in the nuclear areas , which defines T . gondii nucleoli and the protein contains itself all the sequence information required for nucleolar retention after being targeted into the nucleus . Having observed the presence of TgNF3 in the parasite nucleoli , we determined the dynamics of its expression by live imaging using time-lapse video-microscopy . The direct fluorescence collected for TgNF3-YFP in the intracellular tachyzoites revealed in some cases the presence of two smaller nucleoli in close vicinity of one larger nucleolus ( Figure 8C , blue arrows ) , suggesting a dynamic biogenesis of the nucleolus in T . gondii . To determine the precise location of smaller sized nucleoli in the nucleus , we simultaneously introduced hydroethidine ( HET ) , a live nuclear dye staining during time-lapse imaging . Tracking three sets of independent vacuoles containing actively replicating TgNF3-YFP expressing tachyzoites confirmed two smaller sized and spherical nucleoli that positioned separately in the nucleus stained by HET ( Figure 8D , red arrows ) although a less intense staining was observed in the entire nuclear areas , which defines the nucleoplasm surrounding the nucleolus . In some cases , only one very small and spherical nucleolus was also detected . These two complementary approaches revealed the dynamics of nucleolar biogenesis during the intracellular replication of T . gondii tachyzoites in vitro , a phenomenon that so far has not been reported . Collectively , these data demonstrate that TgNF3 is predominantly a resident factor of the parasite's nucleolus even if it is also convincingly detected in the other areas of the nucleus , likely in the nucleoplasm . The nucleolar localization of TgNF3 was also demonstrated using electron microscopy and cryo-immunogold labeling performed using intracellular tachyzoites ectopically expressing TgNF3-YFP and a monoclonal antibody specific to GFP ( Figure 9 ) . Using immuno-gold staining and electron microscopy , we also discovered that the expression of the YFP-tagged version of TgNF3 induced profound changes in morphology of the parasite nucleus with a considerable increase of nucleolus size ( Figure 9A and 9B ) . This increased nucleolus size also represents an unusual feature caused by TgNF3 over-expression in the parasites . These observations were confirmed in all transgenic extracellular or intracellular tachyzoites , which ectopically expressed TgNF3-YFP . Using confocal acquisitions that allow 3D-reconstruction of the whole tachyzoite's body , we showed that tachyzoites ectopically expressing TgNF3-YFP contain nucleoli with a remarkable increase in size ( Video S2 ) relative to that of the parental parasite ( Video S1 ) . We conclude that the most direct effect of ectopic expression of TgNF3-YFP in all cases is the presence of huge nucleoli very close to nuclear membrane with a protuberance at one pole of the nucleus , thus deforming the nuclear shape externally ( Figure 9B ) . As a negative control , the nucleolus in the wild type parasite incubated with anti-GFP show no gold labelling and the nucleolus consistently appeared normal in size and was often centrally positioned in the nucleus ( Figure 9C ) . We estimate that ectopic expression of TgNF3 protein induces about 4–5 fold-increase in nucleolar size of transgenic parasites ( Figure 9B ) , relative to that of the wild type tachyzoites ( Figure 9C ) . In addition , when the anti-TgNF3 antibodies were incubated with the wild type tachyzoites , following by gold labelling , the nucleolus remained normal in size and position . In this case , the nucleolus of the ectopic expressing TgNF3-YFP again appeared larger and positioned towards the periphery of the nucleus . Figure 10A shows that ectopic expression of TgNF3-YFP in tachyzoites of T . gondii induces a faster replication rate relative to the parental parasites . Ectopic expression of TgNF3 protein harbouring a C-terminal HA-FLAG tag leads to a similar increase in replication rate in vitro as TgNF3-YFP transgenic tachyzoites . The increased replication rate is not correlated to the elevation of host cell invasion since there is no significant difference in fibroblast cells or macrophage cells entry between these transgenic lines and wild type parasites . In addition , neither stable transgenic tachyzoites ectopically expressing another nuclear factor TgNF2 nor transgenic tachyzoites ectopically expressing the nuclear enolases ( ENO1 and ENO2 ) displayed changes in nucleoli morphology and in replication rate relative to wild type parasites using the same type II 76K strain ( our unpublished data ) . This suggests that the increased replication rate may be specific to TgNF3 . Therefore , we conclude that TgNF3 may be involved in nucleolar dynamics and in functions that are important for the replication rate of T . gondii growing inside the host cells . To assess the influence of stable TgNF3-YFP expressers in vivo , the transgenic TgNF3-YFP and parental wild type parasites were used to inoculate a group of 10 mice at doses up to 104 tachyzoites . After 4–5 days of infection , all mice from two genetically distinct groups ( Balb/c and CBA/J ) , infected with the parental tachyzoites show the same characteristic symptoms of disease and succumbed approximately 12–14 days ( Figure 10B and 10C ) . Surprisingly , all mice ( Balb/c or CBA/J ) infected with tachyzoites ectopically expressing TgNF3-YFP displayed only mild symptoms of disease and recovered faster than those infected with the parental tachyzoites . In this case , 100% of mice survival was obtained with the two groups infected with TgNF3-YFP expressers ( Figure 10B and 10C ) . In order to ensure that the mice that survived had truly been infected , immune sera of each group of infected mice were collected 30 days post-inoculation and were tested in Western blots . All mice infected with the TgNF3-YFP expressers were positive and they also survived a subsequent challenge with 104 RH ( type I strain ) and 105 76K ( type II strain ) wild type tachyzoites , doses that confer 100% mortality in the primo-infected mice used as controls ( Figure 10B and 10C ) . These data were confirmed when a group of mice was respectively infected with 104 , 105 and 106 tachyzoites ectopically expressing TgNF3-YFP , again no mice succumbed and all reacted positively against T . gondii total protein extracts as above . All sera from surviving mice recognized parasite antigens ranging mostly from 15–35 kDa whereas the sera from non-infected mice failed to detect any T . gondii antigens , as expected ( Figure 10D ) . These results demonstrated that the mice were truly infected with tachyzoites TgNF3-YFP expressers and consequently , positive immune responses have been developed . Therefore , we conclude that ectopic expression of TgNF3-YFP attenuates T . gondii virulence in mice and induces live vaccination in mice that can confer protection against T . gondii challenge . To examine if the attenuated TgNF3-YFP expressers were able to establish a chronic infection in mice , we searched for the presence of cysts using specific staining with the Dolichos biflorus lectins , which specifically labeled the cyst wall [49] . The presence of few cysts per brain with fluorescently positive cyst-wall stained with the lectin and the presence of YFP-expressing encysted dormant bradyzoites ( Figure 11A ) was indicative of a chronic infection in all survived mice monitored and analyzed . Movies representing cysts at different depth and created with the Zen software , at a rate of 5 frames per second , confirmed the presence of encysted bradyzoites that expressed YFP-TgNF3 proteins ( Video S3 ) . These observations were also validated by direct confocal imaging of lectin-unlabelled cysts by Z-stacks acquisitions enabling the 3D localization of fluorescent signals ( Video S4 ) . Interestingly , all cysts analyzed in TgNF3-YFP infected mice , which were challenged with either RH or 76K parental tachyzoites contained only YFP-positive encysted bradyzoites , suggesting that mice infection with transgenic tachyzoites expressing TgNF3-YFP raises an efficient sterile protection against T . gondii . The confocal observations described above confirmed the presence of TgNF3-YFP expression in the encysted bradyzoites during chronic infection of mice . We next determined whether TgNF3-YFP factor actually displayed the dual nucleolar/nuclear localization in the dormant encysted bradyzoites of T . gondii . Surprisingly , we found that bradyzoites isolated from brains of infected mice expressed TgNF3-YFP proteins exclusively in the cytoplasm , as demonstrated by ten Z-stack acquisitions , which allows the whole bradyzoite's body to be visualized at different depth ( Figure 11B ) . Interestingly , when the bradyzoites were used to infect fibroblast cells and growth in vitro for 36 hours , TgNF3-YFP factor was again relocated in the nucleoli of all intracellular newly transformed tachyzoites ( Figure 11C ) . The location of native TgNF3 in the cytoplasm of bradyzoites from the wild type of T . gondii 76K strain was also validated using anti-TgNF3 antibodies ( Figure 12 ) . We invariably detected native TgNF3 in the cytoplasm of all wild type bradyzoites and the signals varied from very intense fluorescent signal ( panels 1–3 ) to weaker cytoplasmic signal ( panel 4–7 ) and to very focused signal close to the nucleus [8]–[9] . Despite the presence of some apparent overlapping signal between the cytoplasm and nucleus ( panel 1–3 ) , 3D constructions of panels 1 and 2 from Figure 12 showed that TgNF3 signal is exclusively localized to the cytoplasm of the bradyzoites ( Video S5 and S6 ) . This novel localization of TgNF3 becomes obviously apparent when TgNF3 signal decreased in some dormant encysted bradyzoites ( panels 6–7 ) . During the course of the confocal imaging , we discovered that the nucleus , which is more posterior in bradyzoites , displays a half reduction in size relative to nucleus of tachyzoites . In some cases , profound alterations ( panels 8–10 ) and a total absence of nucleus were observed in few bradyzoites ( panels 11 and 12 ) . The alterations of nuclear morphology and the complete lack of nucleus always correlated with the strong decrease in TgNF3 signals . In the meantime , we also observed the striking absence of nucleoli in all bradyzoites analyzed ( Figure 12 ) . 3D-reconstructions of confocal imaging of the entire bodies of all bradyzoites investigated confirmed the exclusive presence of TgNF3 in the cytoplasm of these dormant encysted T . gondii forms , suggesting that the nucleolar and nuclear functions of TgNF3 are only operating in the rapidly replicating and virulent tachyzoites . Therefore , we decided to further investigate in more detail how TgNF3 protein functions biochemically in vitro and in vivo . Because we found a striking structural similarity between TgNF3 , nuclear FKBP and nucleoplasmin-like proteins , which function as chaperones binding directly to histones and assemble histone octamers involved in nucleosome activity [42]–[46] , [50] , we asked whether TgNF3 can associate with purified mammalian core histones . To this goal , purified recombinant GST-tagged TgNF3 and GST alone produced in E . coli were purified and immobilized on glutathione-Sepharose , which was used to perform a series of pull-down experiments . To ensure that equal amount of TgNF3 and GST proteins were being used , aliquots of bound TgNF3-GST and GST alone to beads were eluted in SDS buffer and analyzed by SDS-PAGE ( Figure 13A ) . Afterwards , the beads containing TgNF3-GST or GST alone were incubated with purified core histones from HeLa cells , which were tested for quality before use ( Figure 13B ) . Only TgNF3-GST was found to specifically pull down the core histones of HeLa cells , as shown by SDS-PAGE and silver staining of Figure 13C ( lane 2 ) . No binding was observed when the GST alone was used ( Figure 13C , lane 5 ) . In addition , the level of core histones pulled down by TgNF3 was significantly reduced by direct competition assay in which the core histones were incubated with recombinant non-fusion TgNF3 protein prior to pull down experiments ( Figure 13C , lane 3 ) . No significant decrease of bound core histones was observed by competing with the GST alone ( Figure 13C , lane 4 ) . The specific binding of TgNF3 to histones was also confirmed when the same pulled down material analyzed by silver staining above was also subjected to Western blots using anti-H3 antibodies ( Figure 13D ) . We found that approximately 25% of the original input bound specifically to TgNF3 ( Figure 13D , lane 2 ) . We confirmed the specificity of the competition with non-fusion recombinant TgNF3 ( Figure 13D , lane 3 ) . In addition , no binding of core histones to GST alone was observed ( Figure 13D , lane 1 ) . Next , we showed that T . gondii histone H3 ( here named TgH3 , lane 2 ) and TgNF3 ( lane 1 ) are present in nuclesomes , which were purified from isolated nuclei of T . gondii ( Figure 13E ) . In addition , we further demonstrated that histone TgH3 cannot be pulled down by GST-TgNF3 beads , suggesting that its association with native TgNF3 in the parasite nucleosome prevents binding site recognition and histone TgH3-TgNF3 complex formation ( Figure 13F ) . This conclusion is supported by reciprocal immunoprecipitation using anti-TgNF3 antibodies , which validated TgNF3 as a genuine nucleosome-associated factor that interacts directly and specifically to T . gondii histone H3 , present in parasite nucleosomes ( Figure 13G ) . Altogether , these data support the notion that T . gondii TgNF3 has histone binding activity that is likely required for nucleosome functions in T . gondii . We next investigated the direct and physical interactions of TgNF3 with promoter sequences in vivo using chromatin immunoprecipitation followed by high-throughput sequencing ( ChiP-seq ) . Towards this goal , intracellular and actively dividing tachyzoites of wild type T . gondii 76K strain were fixed by formaldehyde , released from host cells before chromosome fragmentation by sonication and chromatin was immunoprecipitated using specific anti-TgNF3 antibodies , or pre-immune sera used as ChIP negative control . Both immunoprecipitates from specific anti-TgNF3 and pre-immune sera were subjected to high-throughput sequencing and bioinformatics analyses using genome data from http://www . toxodb . org . After comparison of sequences and removal of common genes targeted by both pre-immune and specific anti-TgNF3 sera , 5'untranslated regions corresponding to putative promoters of 516 genes were found to be exclusively pulled down by the anti-TgNF3 antibodies ( Table S2 ) . Figure S2 shows the schematic representations of TgNF3 hits on all 14 chromosomes of T . gondii . Among genes identified were 50% ( 264 ) of gene promoters expressing hypothetical proteins , 15% of metabolic enzymes , 5% of translation factors and 2 . 5% of transcription proteins . Interestingly , ChIP-seq also identified gene promoters corresponding to putative NADP-specific glutamate dehydrogenase with the highest hits ( 11 hits ) , DEAD/DEAH box helicase containing protein ( 5 hits ) , nucleolar phosphoprotein and histone deacetylases ( Figure 14 and Table S2 ) . It is worth noting that theses enzymes or factors have also been identified as candidate nuclear factors during the affinity purification of nuclear factors that bind to ENO1 promoter and the proteomics analyses reported in this study ( Table S1 ) . In addition , several gene promoters regulating expression of proteins involved in RNA metabolism and protein synthesis such as essential amino-acyl tRNA ( histidine , lysine , tyrosine , methionine ) were also found . The presence of several gene promoters of nucleolar factors , ribosomal proteins and RNAs is consistent with TgNF3 localization and its functions in the nucleolus . In addition , the presence of DNA-directed RNA polymerase II and RNA polymerase II subunits also supported the notion that TgNF3 is likely involved in the regulation of genes , which are present in other areas of the nucleus . Finally , several promoters of genes coding for kinases , Ras family and related regulatory factors , and factors involved in cell division were also found , suggesting that binding and regulation of genes of these later factors may be part of mechanisms involved in the rapid replication rate of TgNF3-YFP ectopic expressers . However , the regulation of the numerous parasite metabolic processes , protein synthesis through the control of translation might underlie the growth rate of the transgenic ectopically expressing TgNF3-YFP . It is worth noting that excepting a few putative and yet uncharacterized promoters of genes coding for putative kinases of rhoptries , the vast majority of promoters of genes potentially controlling parasite-specific organelles such as dense granules , micronemes and major surface proteins were absent ( Table S2 ) . Thus , TgNF3 is probably important to nuclear/nucleolar functions linked to transcription and translation of genes involved parasite metabolism . Having observed that TgNF3 is probably involved in functions related to cellular metabolism and protein synthesis through control of translation , we decided to validate in vivo the binding of TgNF3 to two gene promoters , which are markers of nucleomorph and nucleolus , ENO1 and ribosomal DNA 18S . To address this , polyclonal antibodies specific TgNF3 and monoclonal anti-GFP antibody were used for chromatin immunoprecipitation using wild type T . gondii 76K and TgNF3-YFP transgenic parasites . Figure 15 shows that all anti-TgNF3 polyclonal antibodies individually collected from five immunized mice ( designated immune sera IS1 to IS5 ) can positively pull down the ENO1 promoter from the chromatin extract of wild type tachyzoites ( Figure 15A ) . Moreover , the monoclonal anti-GFP antibody immunoprecipitated the ENO1 promoter from the chromatin extracts of transgenic tachyzoites ectopically expressing TgNF3-YFP ( Figure 15A ) . We next showed that the strongest positive polyclonal anti-TgNF3 antibody ( IS3 ) and the anti-GFP monoclonal antibody also specifically pulled down the ribosomal DNA 18S chromatin in vivo ( Figure 15B ) . A pool of pre-immune sera ( lanes labelled NS on the top ) is not able to immunoprecipitate chromatin DNA of the ENO1 promoter and 18S rDNA in both independent experiments described in Figure 15A and 15B , and irrelevant DNA encompassing the coding region of ENO1 can not be precipitated using both anti-GFP and anti-TgNF3 antibodies ( Figure 15C ) . Neither anti-GFP , nor anti-TgNF3 can immunoprecipitate the ENO2 promoter that is active in the virulent tachyzoites using ChIP assays performed on the chromatin extracts from tachyzoites ectopically expressing TgNF3-YFP and parental parasites , respectively ( Figure 15D ) . This indicates that TgNF3 is capable of binding to ENO1 promoter that is silent in the tachyzoites [31] . Indeed , we confirmed the silent status of ENO1 promoter in tachyzoites by probing this promoter with three distinct epigenetic histone marks such as acetylated and methylated histones [7] , [8] . The data showed that these three epigenetic histone marks are absent on ENO1 promoter , which is consistent with this promoter being silent in tachyzoites ( Figure 15F ) . In contrast , the ENO2 promoter is readily modified by all three acetylated histone marks ( Figure 15E ) , which confirmed data previously reported for active promoters [7] , [8] . Furthermore , we have used quantitative reverse-transcriptase PCR ( qRT-PCR ) to validate the expression profiles of eight genes identified by ChIP-seq , including the gene promoters shown in Figure 14 ( Table S2 and Figure 14 ) . For qRT-PCR analysis , RNA was purified from extracellular ( 48 h post-infection ) and intracellular ( 24 h post-infection ) tachyzoites and mRNA levels of both wild type and ectopic TgNF3-YFP over-expressing tachyzoites were compared . The results of the qRT-PCR revealed that eight genes tested were positively regulated in the extracellular tachyzoites as the RNA levels of these genes were 2- to 4-fold higher in the TgNF3 overexpressers than that of the wild type tachyzoites ( Figure 15G ) . As a control , the levels of the housekeeping gene , β-tubulin was unchanged . In sharp contrast , we noticed that four up-regulated genes in the extracellular tachyzoites ( TGME49_093180 ( NADP-specific glutamate dehydrogenase , putative ) , TGME49_093190 ( endonuclease/exonuclease/phosphatase domain-containing protein ) , TGME49_008720 ( phosphatase , putative ) and TGME49_020120 ( hypothetical protein ) ) , with greater hits of promoter binding by TgNF3 in ChIP-seq experiments , were also negatively regulated in the intracellular tachyzoites , as the levels of their mRNA in TgNF3 overexpressers were 2- to 10-fold less than that of wild type tachyzoites ( Figure 15G ) . These data suggest that TgNF3 can either up-regulate or down-regulate gene expression and this depends principally on the extracellular to intracellular status of the parasite . Taken together , we propose a model for TgNF3 function ( Figure 15H ) , which we define as a truly chromosome-associated factor that is probably involved in gene regulation , either repression or activation depending on its interacting partners , probably the promoter context and extracellular and intracellular niche of the parasite . The molecular mechanisms underlying its activity could involve modulation of nucleosome assembly and/or disassembly .
In this study , we sought novel nuclear factors that bind to a parasite stage-specific promoter , because almost nothing is known about transcription factors or other nuclear components involved in T . gondii gene regulation . Since it is very difficult to obtain enough nuclear protein from the persistent and dormant bradyzoites , we focused our efforts on the characterization of nuclear factors that bind to the ENO1 promoter , which is transcriptionally silent in the rapidly replicating tachyzoites . Several factors isolated from nuclear extracts of T . gondii tachyzoites have either putative DNA-binding motifs and/or putative nuclear localization sequences . Consistent with the ENO1 gene being transcriptionally silent in tachyzoites , two candidate nuclear factors appear to be homologues of the chromatin associated protein called Alba . This factor is known to be involved in transcription repression , a process requiring Sir2 and acetylation/deacetylation of a specific lysine residue for DNA-binding in Archaea [51] . Another candidate displays high sequence similarity in its N-terminal domain to yeast nuclear FK506-binding protein ( FKBP ) , whose translocation into the nucleolus is associated with the transcriptional silencing of ribosomal RNA genes [33] . The identification in T . gondii of proteins sharing similarities with yeast and archaeal proteins , known as transcriptional repressors , is in good agreement with the silencing of the ENO1 promoter in the rapidly replicating tachzyoites . We have validated that these candidate factors are capable of entering the nucleus of T . gondii tachyzoites when fused to either YFP , or HA-FLAG tags , or revealed by specific antibodies . Furthermore , we demonstrated that TgNF7 physically interacts with the GGGGG motif present in the bradyzoite silenced ENO1 promoter . It is interesting to note that this GGGGG motif is the homologue of the yeast stress-responsive element ( STRE ) that we have previously reported to specifically interact with T . gondii nuclear extract [31] . Here , we report that TgNF7 displays dual cytoplasm/nuclear localization and is a genuine binding factor for the GGGGG motif in the ENO1 promoter . In addition , we showed that TgNF3 , a homologue of the yeast nuclear FKBP39 , is largely present in the parasite nucleolus , even if the factor can also be detected in the nucleoplasm , the other nuclear compartment surrounding the nucleolus . This dual nucleolar/nucleoplasm location of TgNF3 is also consistent with the behaviour of yeast FKBP39 , which displays a similar dual sub-nuclear distribution [33] , suggesting that these two factors may share similar nuclear functions . The Saccharomyces pombe SpFKBP39 is a novel chromatin-modulating factor that acts as a histone chaperone regulating rDNA silencing . Furthermore , SpFKBP39 is a bi-partite protein with its N-terminal domain having the chaperone activity required in nucleosome assembly and disassembly and this involves interactions with chromatin-remodelling factors and chromatin-modifying enzymes . Our bioinformatics analyses provide evidence that the N-terminal domain of TgNF3 belongs to the HD2/nuclear FKBP family , including nuclear FKBP factors previously found only in yeasts and insects , plant-specific histone deacetylase 2 ( HD2 ) and proteins from parasitic apicomplexans such as Plasmodium falciparum , the causative agent of malaria [39] , [40] . Whether TgNF3 has a deacetylase activity towards histones awaits further investigation . It worth noting that the genome-wide analyses of gene promoter occupancy by TgNF3 also identified several histone deacetylases , suggesting these deacetylases may be TgNF3 partners , given that this enzymatic activity is likely absent from the factor . In fact , we were unable to demonstrate any histone deacetylase activities for TgNF3 using the recombinant protein and commercially available kits . In contrast to its yeast homologues nuclear FKBP and plant HD2 , TgNF3 also lacks the propyl peptidyl isomerase domain at the C-terminus . Instead , a divergent C-terminal domain with no predicted functions is present in TgNF3 protein , supporting the notion that this novel C-terminal domain may be involved in protein-protein interactions , for instance , an interaction with histone deacetylases required to ensure transcriptional repression through its chaperone functions involved in nucleosome activities [33] . Moreover , the nuclear partners that interact with the yeast homologue FKBP ( SpFKBP39p ) have not been identified to date . Therefore , the transgenic parasites expressing HA-FLAG described in this study may be a useful tool for the identification of nuclear/nucleolar partners that interact with TgNF3 in T . gondii . This will also shed light on the regulatory networks that involve TgNF3 functions and will also define the precise biological roles of the two distinct domains of TgNF3 in binding to chromatin remodelling components and/or to transcription factors . Nevertheless , we have been able to demonstrate that TgNF3 can specifically bind to both mammalian core histones containing H3 , H4 and H2A/H2B complexes and to parasite nucleosome-associated histones . Consistent with its presence in the nucleolus , TgNF3 also specifically interacts in vivo to the 18S ribosomal RNA gene promoter of T . gondii , which is consistent to the nucleolar functions previously described for its homologue FKBP in yeast [33] . In contrast , TgNF3 is also significantly present in other areas of the nucleus and binds to numerous gene promoters that cannot be considered as genuine nucleolar resident factors . It is tempting to hypothesize that the C-terminal divergent domain of TgNF3 may be involved in other transcriptional activities distinct from ribosomal RNA gene promoter regulation . Knockout mutants complemented with truncation versions of TgNF3 will be of great help to decipher the precise functions of the C- and N-terminal domain of the protein . Ectopic expression of TgNF3 in transgenic parasite lines described here has , however , demonstrated its direct role as a positive or negative regulator of transcriptional activity of genes present in both the nucleolus and nucleoplasm of T . gondii . The generation of TgNF3 knock out mutants combined with microarray analysis will also be useful to clarify the transcriptional functions of this novel factor . Unfortunately , our attempts to knockout the TgNF3 gene in T . gondii have failed so far , suggesting that the TgNF3 gene codes for an essential protein . The new methods for conditional knockdown described by Hudson et al [52] , the alternative replacement of endogenous gene promoter by homologous anhydrotetracyclin inducible promoter [53] or fusion to the ligand-controlled destabilization domain ( DD-FKBP ) to achieve conditional expression [54] might be helpful in the future to understand how TgNF3 controls gene expression and parasite virulence . Ectopic expression of TgNF3-YFP did not appear to be toxic , even though the size of parasite nucleoli was increased in size . The YFP-tagged TgNF3 expression allowed us to investigate the dynamics of the nucleolus in T . gondii during the parasite development inside the host cell , an issue that has not been investigated previously . Time-lapse images and movies consistently showed a dynamic nucleolar biogenesis with the appearance of two smaller sized nucleoli , or one small nucleolus close to a larger one during parasite replication , suggesting either fragmentation and/or de novo synthesis of the parasite nucleolus . TgNF3-YFP , ectopically expressed in tachyzoites , induced a severe attenuation of parasite virulence in vivo . However , the molecular mechanisms involved in the virulence attenuation of over-expressing transgenic parasites remain to be determined . We believe that the identification of genes transcriptionally regulated by TgNF3 , using comparative microarray studies between wild type parasites and the transgenic over-expressers , will likely reveal the putative virulence factors that are controlled by TgNF3 . Interestingly , the presence of abundant levels of both TgNF3-YFP and wild type TgNF3 protein only in the cytoplasm of avirulent bradyzoites strongly suggests that this factor is exclusively required for nuclear functions in the virulent tachyzoites . We noticed that the decrease of TgNF3 signal in the cytoplasm correlates with a profound size reduction and degeneration in some cases of bradyzoite nuclei . The exclusive location of TgNF3 in the cytoplasm of dormant bradyzoites also suggests that nucleolar functions may be important for the replication of T . gondii tachyzoites . Because TgNF3 and the other nuclear factors were identified through their binding to a transcriptionally silent gene in tachyzoites , we conclude that silencing of bradyzoite-specific ENO1 gene and other genes may activate expression of tachyzoite-specific genes and promote the rapid parasite replication and growth in vitro . Furthermore , genome-wide analyses revealed that TgNF3 binds to numerous gene promoters mainly involved in cellular metabolism and nucleolar functions linked to translation such as ribosomal and protein synthesis . It is worth noting that TgNF3 is also substantially present outside the nucleolus , namely in the nucleoplasm , where it can interact with the bradyzoite-specific ENO1 and other gene promoters controlling expression of cellular metabolism , translation and transcription . Since the ENO1 gene is transcriptionally silent in tachyzoites and its promoter has been used to isolate TgNF3 and the other novel nuclear factors , an attractive model , which is schematically presented in Figure 15H , is that TgNF3 may be a T . gondii nuclear chaperone involved in altering chromatin structure and function [55] . TgNF3 could also affect protein translation and ribosomal synthesis , both of which are known to be involved in diverse cellular pathways and metabolism during growth of metazoan and protozoan species . Our findings that TgNF3 regulates ribosomal protein synthesis is consistent with recent descriptions of a pathway involved in the regulation of the cell cycle and ribosomal proteins , which is controlled by apetela2 ( AP2 ) transcription factors in T . gondii [52] , [56] . In addition to transcriptional regulation of nucleolar genes , as validated by ChIP-seq and qRT-PCR , we discovered that TgNF3 can positively or negatively regulate the expression of numerous genes present in other areas ( the nucleoplasm ) of the nucleus , and these genes are upregulated or downregulated according to the extracellular or intracellular niche of the parasite . This is in sharp contrast with the function of the yeast homologue FKBP ( SpFKBP39p ) where transcriptional repression of ribosomal DNA has only been described [33] . In conclusion , we propose that the nuclear functions of TgNF3 involve changes in chromatin structure and this may link TgNF3 activity to the control of the expression of genes that regulate parasite proliferation , virulence , as well as differentiation and cyst formation .
Human foreskin fibroblasts ( HFFs ) were maintained in Dulbecco's modified Eagle's medium ( DMEM , BioWhittaker , Verviers , Belgium ) supplemented with 10% fetal calf serum , 2 mM glutamine ( Sigma ) , and 0 . 05% gentamycin ( Sigma ) . Tachyzoites from T . gondii 76K strain were grown in monolayers of HFF cells until they lysed the host cells spontaneously . Freed tachyzoites were harvested and purified using glass wool columns and 3-µm pore filters . Encysted bradyzoites were released from cysts purified from brains of mice chronically infected by T . gondii 76K strain using the percoll gradient method and 0 . 05% of pepsin/HCl , as previously described [23] . Nuclear extracts were obtained from about 4×1010 purified tachyzoites of T . gondii 76K strain , as previously described [31] . The parasite nuclear extracts were aliquoted and stored at −80°C before use . The nucleotide sequence corresponding to ENO1 promoter was amplified by PCR and cloned into BlueScript . The 200 µg DNA fragment was sequentially digested with EcoRI and HincII enzymes at 37°C for 2 hours . The released DNA fragment was purified by GeneClean after electrophoresis on agarose gel . The purified DNA fragment was biotinylated using Klenow enzyme , 1 mM of dATP , 1 mM dCTP , 1 mM dGTP and 8 µl of dUTP 16-Biotin at 37°C for 2 h . The biotinylated DNA was purified by High Pack PCR kit ( Roche ) . Total nuclear extract of about 17 mg of proteins was diluted with 7 ml of binding buffer ( 12% glycerol , 1 . 5 mM MgCl2 , 12 mM Hepes pH 7 . 9 , 4 mM Tris . HCl pH 7 . 9 , 60 mM KCl , 1 mM EDTA , 1 mM DTT ) and incubated with 800 µl of Streptavidine-agarose at 4°C for 1 h . After centrifugation , the supernatant was mixed with 350 µl of biotinylated DNA and the mixture was incubated at room temperature for 30 minutes . The DNA-protein complexes were isolated by affinity purification using 800 µl of Streptavidine-agarose for 4 h at 4°C . The beads were washed with binding buffer 10 times and eluted with 3 ml of elution buffer ( 12% glycerol , 20 mM Tris . HCl pH 6 . 8 , 1 M KCl , 5 mM MgCl2 , 1 mM EDTA , 1 mM DTT ) at 4°C for 40 min . The eluted proteins were dialyzed and concentrated by centrifugation using Centricon tubes ( MWCO10 , Millipore ) and analyzed by SDS-PAGE followed by silver staining . Silver stained gels were systematically cut into slices , and in-gel digestion was performed with an automated protein digestion system , MassPREP Station ( Waters , Milford , MA ) . The gel slices were washed three times in a mixture containing 25 mM NH4HCO3: CH3CN ( 1∶1 , v/v ) . The cysteine residues were reduced with 50 µL of 10 mM dithiothreitol at 57°C and alkylated with 50 µL of 55 mM iodoacetamide . After dehydration with acetonitrile , the proteins were cleaved in gel with 40 µL of 12 . 5 ng/µL of modified porcine trypsin ( Promega , Madison , WI , USA ) in 25 mM NH4HCO3 at 37°C for 4 hours . The tryptic peptides were extracted with 60% acetonitrile in 0 . 1% formic acid . NanoLC-MS/MS analyses were performed using an Agilent 1100 series nanoHPLC-Chip/MS system ( Agilent Technologies , Palo Alto , USA ) coupled to a HCT Plus ion trap ( Bruker Daltonics , Bremen , Germany ) . The chip contained a Zorbax 300SB-C18 column ( 43 mm×75 µm , 5 µm particle size ) and a Zorbax 300SB-C18 enrichment column ( 40 nL , 5 µm particle size ) . The solvent system consisted of 2% acetonitrile , 0 . 1% formic acid in water ( solvent A ) and 2% water , 0 . 1% formic acid in acetonitrile ( solvent B ) . 2 µL of each sample was loaded into the enrichment column at a flow rate set to 3 . 75 µL/min with solvent A . Elution was performed at a flow rate of 300 nl/min with a 8–40% linear gradient ( solvent B ) in 7 minutes followed by a 3 min stage at 70% of solvent B before reconditioning the column at 92% of solvent A . The system was fully controlled by ChemStation Rev B . 01 . 03 . SRI ( Agilent Technologies ) . The MS instrument was operated with the following settings: source temperature was set to 320°C while cone gas flow was at 3 l/min . The capillary voltage was optimized to −1850 V . The MS spectra were acquired in the positive ion mode on the mass range 250 to 2500 m/z using the standard enhanced resolution mode at a scan rate of 8 . 100 m/z/s . The Ion Charge Control was fixed at 100000 with a maximum accumulation time of 200 ms and the number of averages was set to 4 . For tandem MS experiments , the system was operated with automatic switching between MS and MS/MS modes . The 3 most abundant peptides were selected on each MS spectrum for further isolation and fragmentation with a preference for doubly charged ions ( absolute threshold of 2000 and a relative of 5% ) . Ions were excluded after the acquisition of 2 MS/MS spectra and the exclusion was released after one minute . The Smart Parameters Setting option was used for the selected precursor ions . The MS/MS spectra were acquired on the mass range 50 to 2800 m/z using the ultrascan resolution mode at a scan rate of 26 . 000 m/z/s . The Ion Charge Control was fixed at 300000 and 6 scans were averaged to obtain a MS/MS spectrum . The MS/MS fragmentation amplitude was set to 1 . 5 V . The system was fully controlled by the Esquire Control 5 . 3 Build 11 . 0 software ( Bruker Daltonics ) . Mass data collected during the nanoLC-MS/MS analyses were processed and converted into * . mgf files using the DataAnalysis 3 . 3 Build 146 software ( Bruker Daltonics ) . The MS/MS data were analyzed using the MASCOT 2 . 2 . 0 . algorithm ( Matrix Science , London , UK ) and Open Mass Spectrometry Search Algorithm ( OMSSA ) [57] for search against an in-house generated protein database [58] , which is composed of protein sequences of Apicomplexa downloaded from http://www . ncbi . nlm . nih . gov/sites/entrez ( on may 25 , 2009 ) concatenated with reversed copies of all sequences ( total 307386 entries ) . Searches were performed with a mass tolerance of 0 . 25 Da in both MS and MS/MS mode and with the following parameters: full trypsin specificity with one missed cleavage , methionine oxidation , protein amino-terminal acetylation and cystein carbamidomethylation . The Mascot and OMSSA results were loaded into the Scaffold software ( Proteome Software , Portland , USA ) . To minimize false positive identifications , results were subjected to very stringent filtering criteria as follows . For the identification of proteins with two peptides or more , a Mascot ion score above the identity score or an OMSSA E-value below −log ( e2 ) was required . The target-decoy database search allowed us to control and estimate the false positive identification rate of our study [59] , [60] . Thus , the final catalogue of proteins presents an estimated false positive rate below 1% . The full-length cDNAs corresponding to several proteins identified by proteomic analysis were fused to YFP using pTub1-YFP and pGRA1-HAFLAG plasmids , which were generously provided by Dr Dzierszinski F & Roos DS ( University of Pennsylvania , USA ) and Dr Hakimi MA ( University of Grenoble , France ) , respectively . The expression vectors were transiently transfected in the tachyzoites and processed for IFA after 24 h post-infection . For stable transformation of T . gondii , Tub1-TgNF3-YFP plasmid was transfected in 107 tachzyoites of T . gondii 76K strain and grown in the presence of 20 µg/ml of chloramphenicol until emerged resistant and stable parasites were cloned . For recombinant protein expression , the full-length cDNA of TgNF3 was cloned in pGEX and used to transform E . coli . The recombinant TgNF3 was induced by IPTG and the soluble recombinant protein was purified using GST column according to the manufacturer's recommendations . A lot of five mice were immunized by 100 µg of recombinant protein per mouse in the presence of complete Freund adjuvant ( Sigma ) . After two boosts with 50 µg of recombinant TgNF3 per mouse in the presence of incomplete adjuvant ( Sigma ) , the sera were tested by Western blots before a final challenge . For qRT-PCR , the RNA from 108 tachyzoites purified from infected HFF cells and 106 bradyzoites isolated from 2 , 000 cysts of brains of chronically infected mice were used . The total RNA were reverse transcribed for one hour at 42°C in a buffer containing 1 M oligo ( dT ) 18 primer , 2 mM dNTPs , 40 U of rRNasin ( Promega ) and 25 U of AMV reverse transcriptase ( Roche ) . The primers used for RT-PCR were as follows: T . gondii β-tubulin gene , forward , 5′-TCCTCGCTCCTTTTGATGTC-3′ , and reverse , 5′- ATTGGAGACAATCCCGTCAG-3′; and T . gondii TgNF3 , forward , 5′-CACCACGCCAGAAAGCACATC-3′ , reverse , 5-CCTCGTCGTCCTCATCGTCAT-3′ . We checked that each primer pair amplified a single fragment , identified as a single band in acrylamide gel and as a single peak within the qPCR dissociation curve . The primer pairs displayed an amplification efficiency of greater than 90% . The qPCR was then performed with the Maxima TM SYBR Green qPCR Master Mix Kit ( Fermentas ) and using the Mx3005P TM real-time PCR System ( Stratagene ) . ROX Solution was used as a passive reference for all analyses and the qPCR was repeated three times , each time in duplicate . Gene expression in tachyzoite is represented as a percentage of bradyzoite gene expression after normalisation . For GST-pull down experiments , 100 µg of purified recombinant GST-TgNF3 and GST alone were resuspended in binding buffer ( 20 mM Hepes pH 7 . 9 , 150 mM NaCl , 0 . 5 mM EDTA , 10% glycerol , 0 . 1% Tween 20 and a cocktail of protease inhibitor and PMSF ) and incubated with 100 µl of glutathione-Sepharose 4B ( Amersham Pharmacia Biotech ) at 4°C overnight . The beads were washed three times with the binding buffer without protease inhibitors . Five µg of purified core histones from HeLa cells ( Upstate , Millipore ) or purified nucleosomes from isolated nuclei of T . gondii [7] , kindly provided by Dr Hakimi MA , were resuspended with the binding buffer and added to 10 µl of GST-TgNF3 , GST and to anti-TgNF3 antibodies coupled to Sepharose beads . For competition assays , 5 µg of core histones or purified T . gondii nucleosomes were incubated with recombinant non-fusion TgNF3 or GST for one hour at room temperature prior pull down assays . After incubation at room temperature and four washes , pulled down proteins were eluted by boiling in 25 µl of Laemmli sample buffer and analyzed by SDS-PAGE for silver staining or Western blots using rabbit polyclonal anti-Histone H3 antibody ( Upstate , Amersham ) . Total protein extracts from T . gondii tachyzoites ( 5×106 tachyzoites per lane ) or purified T . gondii nucleosomes were also boiled in Laemmli's buffer , separated by SDS-PAGE and transferred to Hybond ECL nitrocellulose ( Amersham ) . Immunoblots were carried out using murine immune sera , non-immune sera as control , monoclonal antibodies specific to GFP ( Clontech ) or with mouse polyclonal antibody raised against recombinant anti-TgNF3 . The blots were incubated with peroxidase conjugated secondary antibodies followed by chemiluminescence detection . For immuno-electron microscopy , the intracellular transgenic tachyzoites expressing TgNF3-YFP grown in HFF cells were fixed overnight at 4°C in 8% paraformaldehyde in PBS buffer , thoroughly washed in the same buffer and infused in sucrose 2 . 3 M containing 20% polyvinyl pyrrolidone 10000 in phosphate buffer 0 . 1 M . The pellets were mounted on ultracryotome supports and rapidly frozen in melting nitrogen . Ultrathin sections of about 90–100 nm were obtained using Reichert UltraCut E ultramicrotome equipped with a FC4 device . Before mounting in methyl cellulose , sections were incubated in blocking medium ( 0 . 05 M glycine , 5% fish gelatine in 0 . 1 M PBS buffer ) for 30 min . The grids were incubated with the monoclonal antibody anti-GFP for 1 hour at 37°C or overnight at 4°C . After washing , sections were incubated at room temperature for 30 min in the corresponding secondary gold conjugates ( Jackson ImmunoResearch Laboratories Inc . ) diluted in the same buffer . Following a final thorough wash in PBS alone , the grids were fixed in 4% paraformaldehyde for 10 min at room temperature and washed in water . After staining with 0 . 5% uranyl acetate in 1 . 5% methyl cellulose , sections were observed on a Hitachi H600 transmission electron microscope at 75 kV accelerating voltage . For immunofluorescence assays ( IFA ) , intracellular tachyzoites were fixed with 4% paraformaldehyde in PBS for 15 minutes on ice , followed by two PBS washes and dried on Teflon slides . Intracellular parasites were permeabilized with 0 . 1% Triton X-100 in PBS containing 0 . 1% glycine for 10 minutes at room temperature . Samples were blocked with 3% BSA in the same buffer and mice immune sera diluted at 1∶1000 were added on parasites in the same buffer for one hour at 37°C . Rabbit secondary antibody coupled to Alexa-488 ( Molecular Probes ) diluted at 1∶1000 was added in addition to DAPI for nucleus staining . For co-localization assay , the rabbit anti-enolase serum and the goat secondary antibody coupled to Alexa-594 ( Molecular Probes ) were used at the same dilution . Fluorescence was visualized with a ZEISS Axiophot microscope . Confocal imaging was performed with a LSM710 microscope ( Zeiss ) and a Plan Apochromat objective ( Plan-Apochromat 63×/1 . 40 Oil DIC M27 , Zeiss ) . The associated software ( Zen 2008 ) enabled the adjustment of acquisition parameters . YFP was excited at 514 nm and its fluorescence emission was collected from 520 to 620 nm . The Alexa-488 signal was excited at 488 nm and emission was collected from 500 to 580 nm . Nuclear DAPI signal were excited at 405 nm and emission was collected from 410 to 500 nm . Fluorescent signals were collected sequentially , with a 4 lines average , a zoom factor ( varying between 2 and 4 ) and resulting images are 512×512 pixels in size , and 8 bits in resolution ( 256 gray levels ) . By setting the photomultiplier tubes and the pinhole size ( 1 AU ) correctly , there was no signal bleed-through . The images were treated with ImageJ ( NIH ) . Z-stack acquisitions enabled to visualize the 3D localization of fluorescent signals . Rotation ( 360° around the y axis ) movies were created with the Zen software , at a rate of 5 frames per second . Images were obtained from an AxioObserver Z1 ( Zeiss ) , equipped with a regulation chamber for temperature and CO2 , through a Plan Apochromat objective ( Plan-Apochromat 100×/1 . 46 Oil , Zeiss ) . Samples were excited with a Colibri source ( Zeiss ) and fluorescence signal was collected with an Axio mRm Camera ( Zeiss ) , through different filters sets ( Filter Set 38HE , 60HE , Zeiss ) . Experiments were performed by exposing the sample at a rate of one image every 30 minutes during 72 h . Z-stack acquisitions were performed , and resulting images , which correspond to the projections of these stacks , were shown . The images were treated using ImageJ ( NIH ) . ChIP was performed as described [7] with slight modifications . Briefly , chromatin from extracellular or intracellular parasites grown in HFF cells was cross-linked for 10 min with 1% formaldehyde at room temperature and purified . Chromatin extract was obtained after sonication yielding fragments of 500–1 , 000 bp . Immunoprecipitations were performed with the monoclonal antibody anti-GFP or the mouse serum anti-TgNF3 at 4°C overnight and washed as described [7] . DNA was then subjected to proteinase K digestion for 2 h and purified using the Qiagen PCR purification kit ( http://www . qiagen . com ) . As a negative control , pre-immune sera were used . For PCR , specific primers of ENO1 gene promoter , forward 5′-ATGTGCTGCTGGTTTTTGTTTC-3′ , reverse , 5′-TTAAGGCGTCCGCAAGACTAGTG-3′ and ribosomal RNA 18S gene promoter , forward , 5′-GGGGTGGTGGATGGGGACGGGCGC-3′ , reverse 5′-GCCCGTTCCTTGACCCCGCTGCC-3′ were used . ChIP products amplified by PCR using these specific primers were electrophoresed on agarose gels , stained with ethidium bromide , and photographed using UV-light scanner . Chromatin immunoprecipitated by anti-TgNF3 as above was amplified using GenomePlex Amplification of ChIP DNA kit ( Sigma-Aldrich ) . The amplified ChIP products were electrophoresed on agarose gels and stained with ethidium bromide . The fragments of DNA length up to 500 bp were purified and processed for high-throughput sequencing ( GenoScreen , Pasteur Institute of Lille ) . The GsFLX bead adaptors and specific tag ( MID ) were introduced to the flanking 5′ and 3′ end of each purified DNA sample according to manufacturer's instructions . The ChIP-seq GsFLX libraries were controlled on a BioAnalyzer 2100 using Agilent RNA 6000 Pico methods and quantified by Quant-iT TM RiboGreen ( Invitrogen ) . Equimolar librairies were mixed , fixed on beads and amplified by GS FLX Titanium emPCR Kit ( 454 Life Sciences , Roche Diagnostics ) . The amplified beads were purified , enriched , counted using Beckman Coulter Z1 and deposited on the GS FLX Titanium PicoTiterPlate ( 454 Life Sciences , Roche Diagnostics ) . The pyrosequencing reaction was performed using GS FLX Titanium Sequencing Kit ( 454 Life Sciences , Roche Diagnostics ) on Genome Sequencer FLX Instrument ( 454 Life Sciences , Roche Diagnostics ) . Sequence similarity searches were performed using PSI-BLAST at the National Center for Biological Information ( NCBI , nonredundant ( nr ) database , default parameters ) . Fold recognition was performed using Phyre [61] . Hydrophobic Cluster Analysis ( HCA , [39] ) was used to analyze protein domain architecture and refine sequence alignments . For ChIP-seq bioinformatics analyses , the GSMapper software v 2 . 3 ( Roche ) was used to align reads for each sample using the updated T . gondii ME49 genome databases downloaded from http://www . toxodb . org v 6 . 0 of 15 July 2010 . The sequences of a minimum overlapping length of 40 nucleotides with at least 90% identity were only considered for further analyses . The ChIP-seq data specific to TgNF3 was subtracted from non-specific sequences obtained by the pre-immune sera used as negative control and data collected for specific sequences immunoprecipitated by anti-TgNF3 antibodies were grouped into 4 sub-groups of associated contigs . SignalMap software was used to schematically represent the number of reads per contig and their corresponding positions , which allowed to visualizing putative gene promoters occupancy by TgNF3 defined by ChIP-seq for all chromosomes of T . gondii . All animal experiments were performed following the guidelines of the Pasteur Institute Pasteur of Lille animal study board , which conforms to the Amsterdam Protocol on animal protection and welfare , and Directive 86/609/EEC on the Protection of Animals Used for Experimental and Other Scientific Purposes , updated in the Council of Europe's Appendix A ( http://conventions . coe . int/Treaty/EN/Treaties/PDF/123-Arev . pdf ) . The animal work also complied with the French law ( n°87-848 dated 19-10-1987 ) and the European Communities Amendment of Cruelty to Animals Act 1976 . All animals were fed with regular diet and all procedures were in accordance with national regulations on animal experimentation and welfare authorized by the French Ministry of Agriculture and Veterinary committee ( Permit number: 59-009145 ) . The Pasteur Institute of Lille and the CNRS Committee on the Ethics of Animal Experiments specifically approved this study . Purified tachyzoites from the parental and transgenic ectopically expressing TgNF3-YFP were inoculated into group of 10 female 6–8-week-old BALB/c or CBA/J mice at 104 per mouse ( otherwise stated ) and monitored until death or survival for 2–3 months . To check that surviving mice were infected and the immune response had developed in the infected mice , the serum of each mouse was tested against the total extract antigens prepared from the parental parasites using Western blots . To assess whether the primary infection of mice with tachyzoites ectopically expressing TgNF3-YFP conferred protection against the parental 76K and the highly virulent RH strains , infected mice that survived after 42 days post-inoculation were challenged with lethal parasite doses . In vivo cyst formation was determined by harvesting mouse brain at 6–8 weeks after infection . Cysts were purified using Percoll gradients , washed with PBS , and observed by inverted phase and confocal microscopy . Statistical differences between groups of mice used in this study were evaluated by the Student's t-test . The Mann-Whitney test was also used for counting intracellular growth of TgNF3-YFP and wild type tachyzoites after colorimetric staining and microscopic observation , and also for the test for mice survival curves . | Apicomplexa including Toxoplasma gondii are responsible for a variety of deadly infections . These intracellular parasites have complex life cycles within different hosts and their infectivity relies on their capacity to regulate gene expression in response to different environments . However , to date , little is known about nuclear factors that regulate their gene expression . Here , we have characterized parasite nuclear factors that bind to a stage-specific promoter . We identified several nuclear factors including a novel factor , designated herein as TgNF3 . The N-terminal domain of TgNF3 shares similarities with the N-terminus of yeast nuclear FK506-binding protein ( FKBP ) , known as a histone chaperone regulating gene silencing . We show that TgNF3 is predominantly a nucleolar , chromatin-associated protein that specifically binds to T . gondii nucleosome-associated histones and promoters . Genome-wide analysis identified promoter occupancies by TgNF3 and we demonstrated a direct role for this factor in transcriptional control of genes involved in parasite metabolism , transcription and translation . Ectopic expression of TgNF3 induces dynamic changes in the size of the nucleolus , and a severe attenuation of parasite virulence in vivo . In avirulent bradyzoites , TgNF3 is found exclusively in the cytoplasm , suggesting a potential role in regulating nucleolar and nuclear functions in the virulent tachyzoites of T . gondii . | [
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] | [
"infectious",
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] | 2011 | A Novel Toxoplasma gondii Nuclear Factor TgNF3 Is a Dynamic Chromatin-Associated Component, Modulator of Nucleolar Architecture and Parasite Virulence |
We have previously demonstrated that B cells can shape the immune response to Mycobacterium tuberculosis , including the level of neutrophil infiltration and granulomatous inflammation at the site of infection . The present study examined the mechanisms by which B cells regulate the host neutrophilic response upon exposure to mycobacteria and how neutrophilia may influence vaccine efficacy . To address these questions , a murine aerosol infection tuberculosis ( TB ) model and an intradermal ( ID ) ear BCG immunization mouse model , involving both the μMT strain and B cell-depleted C57BL/6 mice , were used . IL ( interleukin ) -17 neutralization and neutrophil depletion experiments using these systems provide evidence that B cells can regulate neutrophilia by modulating the IL-17 response during M . tuberculosis infection and BCG immunization . Exuberant neutrophilia at the site of immunization in B cell-deficient mice adversely affects dendritic cell ( DC ) migration to the draining lymph nodes and attenuates the development of the vaccine-induced Th1 response . The results suggest that B cells are required for the development of optimal protective anti-TB immunity upon BCG vaccination by regulating the IL-17/neutrophilic response . Administration of sera derived from M . tuberculosis-infected C57BL/6 wild-type mice reverses the lung neutrophilia phenotype in tuberculous μMT mice . Together , these observations provide insight into the mechanisms by which B cells and humoral immunity modulate vaccine-induced Th1 response and regulate neutrophila during M . tuberculosis infection and BCG immunization .
It has recently been demonstrated that B cells can shape the development of the immune response to Mycobacterium tuberculosis [1] , [2] . The lungs of M . tuberculosis-infected B cell-deficient mice display exacerbated inflammation , with enhanced neutrophil recruitment [1] . Neutrophils are among the earliest cells to migrate to the site of M . tuberculosis infection and evidence exists that these phagocytes participate in the granulomatous reaction [3] , [4] . Enhanced neutrophil infiltration has been associated with excessive lung pathology and with poor bacillary control in genetically susceptible mice [5] , [6] . It has been proposed that neutrophilia is indicative of failed Th1 immunity in response to aerosol M . tuberculosis challenge [7] . There is also evidence suggesting that interaction of M . tuberculosis with neutrophils enhances DC migration to the draining lymph nodes thereby promoting the initiation of adaptive immune response in an aerogenic tuberculous infection [8] . Studies examining the significance of neutrophils in protection against M . tuberculosis have yielded conflicting results [3] , [5] , [9] , [10] , [11] , [12] , [13] , [14] , and the role of these professional phagocytes in TB remains to be clearly defined . The cytokine IL-17 plays an important role in the recruitment of neutrophils to the site of inflammation [15] , [16] , [17] , [18] , including the airways , during infection [19] , [20] . In autoimmune diseases and infection , IL-17 is produced by a variety of host cells , including myeloid cells [21] , invariant natural killer ( iNK ) T cells [22] , NK cells [23] , [24] , γδ T cells [25] , [26] , [27] , and Th17 cells , a subset of helper CD4+ T lymphocytes [17] , [28] . In a BCG immunization model , IL-17 produced by Th17 cells can downregulate IL-10 production and subsequently drives Th1 responses [29] . BCG vaccination induces Th17 cells that populate the lungs of immunized mice [30] . Upon challenge with M . tuberculosis , the Th17 cells recruit Th1 cells to the site of infection to restrict mycobacterial growth [30] . IL-17 can , however , promote tissue damage during M . tuberculosis infection [17] , [31] and in the context of other infectious and autoimmune diseases [15] , [16] , [32] , [33] , [34] . It has been shown that repeated BCG vaccinations enhanced IL-17 production that is associated with increased neutrophil recruitment and exacerbated lung tissue pathology [35] . Therefore , a protective immune response against M . tuberculosis should promote Th17-mediated protection while mitigating the tissue damaging effects . Ample evidence support the notion that B cells and the humoral immune response modulate T cell immunity [36] , [37] , including the development of memory T cell responses during infection [36] , [37] and vaccine-induced protection against secondary challenge with intracellular pathogens such as Chlamydia [38] and Francisella [39] . Experimental evidence suggests that humoral immunity plays a role in regulating the Th1 response in TB [2] . Results derived from an X-linked immune-deficient ( xid ) B cell-deficient mouse model suggest that neutrophilia may adversely affect BCG vaccine efficacy [40] . Recent studies involving the B cell-depleting agent rituximab have revealed that B cells may enhance or diminish the IL-17/Th17 response [41] , [42] , [43] , [44] . It has recently been reported that a subset of B cells in the blood of humans with tuberculous infection can suppress Th17 response [45] . These observations on B cells have prompted us to examine the role of B cells in regulation of IL-17 and neutrophilic responses to mycobacteria using an acute aerosol infection model as well as an ear ID BCG immunization model . The results provide evidence that B cells regulate neutrophilia during M . tuberculosis infection and BCG immunization by modulating the IL-17 response . The study also revealed that neutrophilia at the site of immunization adversely affects the development of BCG-induced Th1 response by diminishing DC migration to draining lymph nodes , thereby attenuating T cell immunity against M . tuberculosis . This latter observation suggests that B cells can optimize BCG-elicited Th1 immunity by regulating the IL-17/neutrophilic response . Finally , the lung neutrophilia and enhanced Th17 response seen in M . tuberculosis-infected B cell-deficient mice could be reversed by passive immune serum therapy , raising the possibility that immunoglobulins ( Igs ) may contribute to the regulation of these phenotypes .
The aberrant immune response to M . tuberculosis , including excessive neutrophilia [1] , has yet to be mechanistically explained . Emerging evidence suggest neutrophils play a significant role in modulating the immune response to M . tuberculosis [3] , [4] , [5] , [6] , [7] , [8] We initiated studies to characterize the neutrophilic response in acute TB in the B cell-deficient μMT mouse [1] . Flow cytometric analysis of lung cells procured from M . tuberculosis-infected μMT mice revealed a neutrophilic response that was significantly higher than that observed in infected wild-type controls . At as early as 7 days post-infection ( p . i . ) , the difference in lung neutrophilia between the two groups of mice was , albeit small , significant ( p<0 . 05 ) ( Figure 1A; Right Panel ) . By 21 days p . i . , the absolute number of neutrophils in the lungs of μMT mice was over two fold that observed in wild-type animals ( p<0 . 005 ) . The proportion of neutrophils in the total lung cell population was also higher in tuberculous μMT mice relative to wild-type ( Figure 1A; Left Panel & data not shown ) . This pulmonic neutrophilia of M . tuberculosis-infected μMT mice was also apparent histologically ( Figure 1D&E ) , and was associated with an overall enhanced inflammatory response as assessed by histological examination of infected tissues ( Figure 1B&C ) and by quantifying the total number of cells infiltrating the lungs throughout the first month after infection ( Figure 1F ) . Thus , the previously observed enhanced pulmonic neutrophil and exacerbated granulomatous inflammatory response of tuberculous μMT mice at 1 month p . i . , when adaptive immunity sets in , is similarly observed in early acute TB , when the predominant anti-tuberculous response is mediated via innate immunity [1] . These data suggest that B cells can regulate the pulmonic inflammatory response , including that involving neutrophils , in the early acute phase of TB . The link between IL-17 and neutrophil recruitment [15] , [16] , as well as the observation suggesting a role for B cells and humoral immunity in modulating Th1 response in TB [2] and Th17 response in autoimmune diseases [41] , [42] , [43] , [44] , [45] prompted us to examine whether the neutrophilia observed in the lungs of μMT mice could be due to an aberrant Th17/IL-17 response as a result of B cell-deficiency . Flow cytometric analyses of lung cells , in conjunction with intracellular staining , revealed that on day 21 p . i . , the numbers of IL-17-producing lung cells were elevated in tuberculous μMT mice compared to infected wild-type controls ( Figure 2A ) , a subset of which is CD4+ Th17 cells ( Figure 2B ) . The lung neutrophilia of tuberculous μMT mice could be significantly reversed by IL-17 neutralization ( Figure 2C ) . Lung bacterial burden in μMT mice treated with IL-17 neutralizing antibodies ( Abs ) was comparable to those treated with isotype controls , excluding bacillary loads as a variable that may confound data interpretation ( Figure 2D ) . These results suggest that IL-17 , produced locally by lung cells including Th17 cells , plays a significant role in recruiting neutrophils to the lungs of B cell-deficient μMT mice in the early phase of acute M . tuberculosis infection and that B cells and humoral immunity play a role in regulating the IL-17/Th17 response in TB . The previously reported B cell deficiency-associated phenotypes , which include lung neutrophilia at 1 month after aerogenic M . tuberculosis challenge [1] , were observed in the μMT strain rendered B cell-deficient by targeted disruption of the membrane exon of the μ chain gene [46] . That these observations are B cell-specific is strongly supported by reversal of the B cell deficiency phenotypes by adoptive B cell transfer [1] . Nevertheless , to rigorously test the B cell-specificity of the Th17/IL-17/neutrophilia phenotype observed in the μMT strain in acute TB ( Figures 1&2 ) , we conducted experiments involving B cell depletion via administration of CD22-cal , an effective B cell-depleting agent [47] , [48] ( Figure S1A ) , in wild-type C57BL/6 mice . In agreement with the results of the μMT studies , neutrophilic infiltration in the lungs of tuberculous B cell-depleted C57BL/6 mice was higher compared to that observed in undepleted controls ( Figure 3A ) . Neutrophilia in B cell-depleted mice was apparent as early as 7 days after aerogenic challenge , and increased steadily over the next 2 weeks , peaking at day 21 to day 28 post-inoculation ( Figure 3A ) . This neutrophilia was associated with an increase in IL-17-producing lung cells ( Figure 3B ) . As in the μMT study , IL-17 neutralization reversed the neutrophilia phenotype in M . tuberculosis-infected , B cell-depleted mice ( Figure 3C ) . The congruency of the B cell-depletion and μMT studies strongly support that the IL-17/Th17/neutrophila phenotype is B cell-specific , supporting a role for B cells in regulating neutrophilia in acute TB through modulation of the IL-17 response . It has been suggested that neutrophilia in the B cell-deficient xid mouse may diminish anti-TB vaccine efficacy , although the B cell-specificity of the phenotypes and the mechanisms underlying the enhanced neutrophilic response was not examined [40] . This observation , together with the Th17/neutrophilia phenotype observed in M . tuberculosis-infected B cell-deficient mice ( Figures 1–3 ) , led us to hypothesize that B cells and humoral immunity , by virtue of their ability to modulate the IL-17 response and neutrophilia ( Figures 1–3 ) upon exposure to mycobacteria , may affect the efficacy of anti-TB vaccine . To begin testing this hypothesis , we assessed the effects of B cell deficiency on the BCG-induced Th1 response in mice . The results showed that upon subcutaneous ( SC ) BCG immunization , B cell-deficient mice , compared to wild-type mice , developed a significantly attenuated Th1 response ( Figure 4A ) . This attenuated Th1 response was also apparent in C57BL/6 mice treated with 5D2 ( Figure 4B ) , a highly effective B cell-depleting anti-CD20 Ab ( Figure S1B ) . Together , the μMT and the 5D2 vaccination studies have provided compelling evidence that B cells are required for optimal development of BCG-induced Th1 response . A limitation of the SC BCG immunization mouse model , which involves administration of the vaccine at the scruff of the neck of the animal , is the variability in the anatomic location of the lymph nodes to which immune cells ( e . g . , DCs ) migrate from this site of vaccination . In addition , it is difficult to locate the precise area of vaccination to procure immune cells for analysis . These problematic features of the SC immunization model complicate the analysis of local immunological events that ensue upon immunization . Consequently , we adopted an ear ID vaccination model to circumvent this hindrance , since the anatomical location of the draining lymph nodes of the ear ( the superficial cervical lymph nodes ) is well defined , and the site of immunization in the pinna can be readily localized [49] . In this model , the level of neutrophil infiltration was higher in the ears of vaccinated μMT mice relative to that detected in wild-type animals as early as 7 days post-vaccination ( Figure 5A ) . The number of neutrophils at the site of vaccination was also higher in immunized μMT mice relative to wild-type mice ( Figure 6A , Right Panel ) . Neutrophilia was similarly observed in BCG vaccinated sites in the ear of mice rendered B cell-deficient via 5D2 treatment ( Figure 5B ) . These data revealed that in B cell-deficient mice , pulmonic neutrophilia observed during the acute phase of M . tuberculosis infection occurs also at the site of ID BCG vaccination in the ear . Since B cell deficiency is associated with sub-optimal development of BCG-elicited Th1 response ( Figure 4 ) , and since DC priming of CD4+ T cells is critical to the development of vaccine-induced protection , we initiated studies to characterize the kinetics of DC migration to the draining lymph nodes following BCG vaccination . The results revealed that μMT or B cell-depleted C57BL/6 mice exhibited diminished numbers of CD11c+ DCs in the superficial cervical lymph nodes compared to wild-type controls starting at as early as day 2 and continuing through day 7 post-vaccination ( Figure 5D&F ) . The BCG-induced Th1 response of the two B cell-deficient mouse groups , as assessed by the number of interferon ( IFN ) -γ-producing CD4+ T cells in the draining superficial cervical lymph nodes , was diminished compared to that detected in vaccinated wild-type animals ( Figure 5C&E ) . These data suggest that B cell deficiency results in impaired T cell priming following BCG immunization . The decreased number of BCG-induced DC migrated to the draining lymph nodes in the B cell-deficient animals could be a factor that contributes to the impairment of CD4+ T cell priming observed in the μMT and B cell-depleted mice . The enhanced pinna neutrophilia and the impaired Th1 response observed in B cell-deficient mice upon BCG immunization ( Figure 5 ) prompted us to investigate the relationship between these two observations . Based on the finding that lung neutrophilia in M . tuberculosis-infected mice is Th17/IL-17 driven ( Figures 2 & 3 ) , we first examined the effect of IL-17 neutralization on BCG-induced Th1 response in the ear immunization model . In agreement with results obtained from the lung infection model ( Figures 2 & 3 ) , IL-17 neutralization significantly attenuated the BCG-induced neutrophilic response in the ear inoculation model , reducing the number of neutrophils in the BCG-vaccination site of C57BL/6 and B cell-deficient animals by 78% and 49% , respectively ( Figure 6A ) . The results indicate that IL-17 is involved , at least in part , in neutrophil recruitment to the site of BCG immunization in both B cell-deficient and B cell-sufficient states . IL-17 neutralization modulates BCG-elicited Th1 response in wild-type and B cell-deficient μMT mice , albeit in opposing fashion ( Figure 6B ) . Concomitant with the decrease in neutrophilia at the site of immunization upon IL-17 neutralization , there was an increased BCG-elicited Th1 response in the B cell-deficient mice ( Figure 6B ) . By contrast , IL-17 neutralization in immunized wild-type C57BL/6 mice resulted in a diminished Th1 response ( Figure 6B ) . The incongruent effects of IL-17 neutralization on the BCG-induced Th1 response among wild-type and μMT mice were also apparent on DC migration to the draining cervical lymph nodes following vaccination ( Figure 6C ) . IL-17 neutralization during BCG immunization of μMT mice did not alter the number of DCs in the draining cervical lymph nodes 7 days post-immunization , but decreased that in wild-type mice ( Figure 6C ) . These data suggest that i ) IL-17 modulates the BCG-elicited Th1 response; and ii ) the enhanced IL-17/Th17 response in B cell-deficient μMT mice upon BCG immunization contributes to the diminished vaccine-elicited Th1 immunity . This effect could be mediated by IL-17/Th17 per se and/or through the level of neutrophilic infiltration at the site of vaccination . The discrepant effects of IL-17 neutralization on vaccination-induced Th1 response in wild-type C57BL/6 and μMT mice warrant further investigation . IL-17 neutralization resulted in only partial attenuation of the neutrophilic response in the ear vaccination model ( Figure 6A ) . Due to this partial effect and the link between IL-17 and neutrophilic recruitment , the IL-17 depletion approach does not allow clear determination of the relative contribution of this cytokine and neutrophils to the observed B cell-deficiency-associated Th1 and DC phenotypes . To begin to address this issue , we conducted neutrophil depletion experiments using the Ly6G-specific Ab , clone 1A8 [14] . 1A8 completely depleted neutrophils at the site of BCG immunization of both wild-type C57BL/6 and μMT mice ( Figure 7A ) . Neutrophil depletion reverses the DC and Th1 phenotypes in BCG-vaccinated μMT mice ( Figure 7B&C ) . Treatment with 1A8 increased the number of IFN-γ-producing CD4+ T cells in the draining lymph nodes of μMT mice on day 7 post-immunization by over two fold ( Figure 7C ) . Neutrophil depletion increased the number of DCs in the draining lymph nodes of the μMT mice by three fold ( Figure 7B ) . Similar enhancing effects of neutrophil depletion on the number of Th1 cells and DCs were observed in the draining lymph nodes of BCG-vaccinated C57BL/6 mice ( Figure 7B&C ) , albeit to a lesser extent than μMTs . To stringently test the B cell-specificity of these observations , we examined the effects of neutrophil depletion on C57BL/6 mice rendered B cell deficient using the anti-CD20 Ab 5D2 . Results derived from the 5D2-based model are similar to those obtained using the μMT mice ( Figure 7D&E ) . These results strongly suggest that in the ear vaccination model , B cells contribute significantly to the development of vaccine-induced Th1 immunity by modulating the IL-17 driven neutrophilic response . In the absence of B cells , neutrophils play a dominant role in down-regulating the development of vaccine-induced Th1 response . The mechanisms by which neutrophils adversely affect the development of BCG-induced Th1 response remained to be defined . One possibility is the ability of neutrophils to internalize BCG , thereby competing with DCs ( the primary antigen presenting cell ( APC ) responsible for the initiation of the anti-TB immune response ) for antigens , which could result in a sub-optimal antigen dose required for T cell priming in lymph nodes . In support of this notion , bacterial load in the draining cervical lymph nodes of B cell-deficient μMT and 5D2-treated mice is lower than that of wild-type C57BL/6 mice ( Figure 7F ) . Previously we have shown that adoptively-transferred B cells ( derived from M . tuberculosis-infected wild-type C57BL/6 mice ) into μMT mice with TB effectively reverses the lung phenotypes associated with B cell-deficiency ( including neutrophilia ) during acute TB [1] . That the transferred B cells are able to reverse pulmonic phenotypes of infected μMT mice without homing to the lungs suggests regulation via a soluble factor ( s ) . In that same study , the transfer of B cells resulted in the appearance of Igs in the recipient μMT mice [1] . These results suggest the possibility that Igs may be one factor that can reverse the B cell-deficiency phenotypes , including neutrophilia . In support of this possibility , results generated from an M . tuberculosis infection model involving FcγR knockout mouse strains strongly suggest that humoral immunity can regulate host responses ( including tissue neutrophilia ) to the tubercle bacillus [2] . To begin testing the Ig hypothesis , we conducted serum therapy study , which revealed that treatment of tuberculous B cell-deficient μMT mice with immune sera derived from M . tuberculosis-infected wild-type animals reversed the lung neutrophilia phenotype ( Figure 8A ) . This serum therapy also resulted in a decrease in the number of Th17 cells in the lungs of treated tuberculous μMT mice ( Figure 8B ) . The data suggest that components of the immune serum , possibly Igs , may play a role in regulating the neutrophil and Th17 response during acute M . tuberculosis infection .
Cell-mediated immunity is well established as critical in defense against M . tuberculosis [50] , [51] , [52] . By contrast , the significance of B cells and humoral immunity in shaping the immune response to the tubercle bacillus is less clear [37] , [53] , [54] . Studies using B cell-deficient μMT mice , in conjunction with B cell transfer , have provided evidence that B cells and the humoral immune response can modulate anti-tuberculous immunity , including the level of granulomatous inflammation and neutrophilic infiltration in lungs [1] . FcγR knockout mouse studies suggest that humoral immunity can influence development of Th1 responses during M . tuberculosis infection [2] . The data of the present study add the IL-17/Th17/neutrophils axis to the list of immunological factors regulated by B cells and humoral immunity in TB . The results generated in two different models ( lung M . tuberculosis infection and the ear ID BCG vaccination ) involving μMT and C57BL/6 mice rendered B cell-deficient via treatment with two independent B cell-depleting agents , revealed B cell-dependent tissue neutrophilia at the site of interaction between mycobacteria and the host . These observations , together with data yielded by the IL-17 neutralization and neutrophil depletion experiments , provided strong evidence that i ) B cells regulate neutrophilia during M . tuberculosis infection and BCG immunization; ii ) exuberant early neutrophilia can adversely affect vaccine-induced Th1 response by impairment of DC migration to draining lymph nodes , thereby compromising CD4+ T cell priming; and as a result , iii ) B cells can optimize BCG-elicited Th1 immunity by regulating the IL-17/neutrophil response . Neutrophilia in the lungs of tuberculous μMT mice is apparent as early as 7 days p . i . , which is prior to an increase in the number of total lung IL-17-producing cells ( observed on day 21 post-aerosolization ) , suggesting the possibility that IL-17-independent mechanisms are involved in the regulation of B cell dependent lung neutrophilia [55] . The decrease in the number of DCs in the draining lymph nodes of vaccinated B cell-deficient mice suggests that excess neutrophilia at the site of vaccination can result in competition between neutrophils and DCs for BCG , thereby affecting vaccine dosage and likely DC maturation and hence migration to the lymph nodes . This notion is supported by the decrease in bacterial burden in the draining lymph nodes of immunized B cell-deficient mice . It is , however , possible that the antigen uptake and migration capacity of the DCs at the site of immunization of a B cell-deficient host , is adversely affected , directly or indirectly , by the excessive neutrophilia ( independent of the BCG competition theory ) that occurs in the dermis of the vaccinated ear . The results that IL-17 neutralization with concomitant decrease in neutrophilia improves Th1 response in BCG-vaccinated μMT mice without affecting the number of lymph node DCs suggest the possibility that the immunization site in the ear of the μMT mice provides a local environment , of which excessive neutrophilia is a feature , can qualitatively compromise the capacity of DCs to effectively prime CD4+ T cells . The opposing effects of IL-17 neutralization on BCG-elicited Th1 response in vaccinated wild-type and μMT mice are intriguing . The results generated by the IL-17 neutralization experiments involving wild-type mice are , in fact , in agreement with a previous study reporting that IL-17 can drive BCG-elicited Th1 response [29] . The discrepant effects of IL-17 neutralization observed among wild-type and μMT mice in the BCG vaccination model could be secondary to differences in the level of the IL-17 response and to the dissimilarities in the quantity and quality of neutrophils at the immunization site among the two mouse groups , with the level of neutrophilia in the ear dermis of B cell-deficient μMT strain being significantly greater than that detected in the C57BL/6 wild-type mice . These same variables could result in the differential effect of IL-17 neutralization on the number of DCs in the draining lymph nodes of the two mouse groups . It will be of interest to determine the functional properties of the neutrophils infiltrating the immunization sites of the μMT and wild-type mice . Collectively , the IL-17 neutralization studies have provided evidence that B cells can optimize BCG-induced Th1 immunity by modulating the IL-17/neutrophil response . Results of the neutrophil depletion experiment support a role for these cells in regulating development of Th1 responses during vaccination . It has been reported recently that neutrophils enhance CD4+ T cell priming in the early phase of an aerogenic M . tuberculosis lung infection by promoting DC migration to draining mediastinal lymph nodes [8] . In the ear ID BCG immunization model employed here , neutrophil depletion enhances the vaccine-induced Th1 response . The discrepant data regarding the role of neutrophils in modulating CD4+ T cell priming could be due to the obvious multiple variables in the two models employed , including but not limited to the differences in the strains of mycobacteria studied ( BCG versus M . tuberculosis ) , in the quality of the DCs ( lungs versus skin ) , and in the conditions in which the mycobacteria interact with the host ( lungs parenchyma versus dermis ) . In a Leishmania major model involving ID ear infection of metacyclic promastigotes , neutrophil depletion also results in enhanced priming of pathogen-specific CD4+ T cells [56] . By contrast and worthy of note , the observation that IL-17-neutralized C57BL/6 mice displayed a decrease in BCG-induced Th1 response and in the number of DCs in draining lymph nodes lends indirect support to the recently reported role for neutrophils in promoting T cell priming in acute TB [8] , since IL-17 neutralization decreases the number of neutrophils at the site of immunization in the ear vaccination model . These contrasting observations of the IL-17 neutralization and the neutrophil depletion studies could be due to differences in the immunological environment resulting from IL-17 neutralization versus neutrophil depletion . For example , IL-17 neutralization results in partial decrease in the degree of neutrophilia at the site of immunization and in the level of IL-17 , while 1A8 treatment results in virtually complete depletion of neutrophils without apparent interference with the amounts of IL-17 . Together , the results also suggest that the complex roles of neutrophils in development of immune response to M . tuberculosis could depend on the characteristics of the site of immunological reaction , the level of neutrophilia as well as the interaction with other immune molecules . Understanding the mechanisms underlying the differential effects of neutrophil depletion on the development of the Th1 response in the lung infection and ear immunization model may shed light on the requisites for the development of optimally efficacious anti-TB vaccines . The precise mechanisms by which B cells regulate the IL-17 response remain to be determined . The effects of IVIG ( intravenous immunoglobulins ) treatment on M . tuberculosis-infected mice [57] and results obtained from the FcγRIIB- and Fcγ chain-deficient mouse TB models strongly support a role for Igs in regulating anti-TB immunity , including the Th1 response [2] . The notion is further supported by the ability of adoptively transferred B cells from infected C57BL/6 mice to reverse neutrophilia in the lungs of infected μMT mice without having to home to the lungs [1] . In the current study , we demonstrate that immune sera from infected mice can reverse the lung neutrophilia and Th17 phenotypes in B cell-deficient mice with TB . It is thus tempting to speculate that Igs , known effective modulators of inflammation [53] , [58] , are a factor in the immune sera with the capacity to ameliorate the B cell-deficiency associated neutrophilia and Th17 phenotypes . We are cognizant of the complex nature of sera and as such , much work needs to be done in order to establish or refute a role for Igs in regulating the neutrophilic response in a tuberculous host . Experiments designed to address this issue are currently underway . In summary , results of the present study provide strong evidence that B cells can regulate tissue neutrophilia during M . tuberculosis infection and BCG vaccination by modulating the IL-17 response . In addition , the study has provided evidence that the compromised BCG-induced Th1 response associated with B cell-deficiency is secondary to neutrophilia . These observations suggest that B cells can optimize BCG-elicited Th1 immunity by regulating the IL-17/neutrophilic response . It appears that optimally effective immunization protocols should achieve a balanced level of IL-17/neutrophilic response , which can only be achieved through a comprehensive understanding of the biology of these two immunological elements . Elucidation of the mechanisms by which B cells regulate the IL-17/neutrophilia response in M . tuberculosis-host interaction may help the design of novel effective TB vaccines and of protocols for the treatment of inflammatory disorders . Last but not least , the overall congruent results of the μMT and B cell depletion experiments suggest the validity of the use of the μMT mouse to investigate the role of B cells and humoral immunity in the development of anti-mycobacterial immune responses [1] .
Animal studies were conducted in accordance to the National Institutes of Health guidelines in compliance with assurance of the well being of laboratory animals . All protocols used in the study have been approved by the Institutional Animal Care and Use Committee of Albert Einstein College of Medicine ( protocol # 20110602 ) . Female C57BL/6 mice ( Charles River Laboratories ) and B cell-deficient mice ( μMT; Jackson Laboratories ) [46] , 8–10 weeks old , were used in all experiments . Infected mice were housed in our biosafety level-3 laboratory and kept pathogen-free by routine serological and histopathological examinations . Animal protocols employed in this study were approved by the Institutional Animal Care and Use Committee of Albert Einstein College of Medicine . Bacterial stocks of M . tuberculosis strain Erdman ( Dr . Frank Collins , Trudeau Institute , Saranac Lake , NY ) were generated by passaging through mice to maintain virulence as previously described [1] . Bacteria were stored at −80°C in aliquots until use . Mice were infected with 100–300 colony forming units ( CFU ) of M . tuberculosis via aerosol inhalation using a Glas-Col inhalation chamber to deliver the desired inoculum [59] . For each experiment , the accuracy of inoculum dose was confirmed by assessing the number of bacterial colonies upon plating serial dilutions of whole lung homogenates on 7H10 agar plates ( Difco ) as previously described [1] . Tissue bacterial burden was quantified as previously described by plating serial dilutions of lung , liver , and spleen homogenates onto 7H10 agar plates at appropriate intervals after infection [1] . Tissue bacterial load was determined by counting the number of colonies on 7H10 agar plates after incubation at 37°C for 4 to 6 weeks . Single cell suspensions were prepared as previously described [1] . Briefly , aseptically procured lungs , spleen , or lymph nodes were dissected at appropriate times after exposure to mycobacteria , then minced using sterile razor blades ( Fisher Scientific ) in cold RPMI 1640 with L-glutamine supplemented with 25 mM HEPES , 10% fetal bovine serum ( FBS; GIBCO ) , and 55 µM 2-mercaptoethanol ( complete RPMI ) . Minced lung tissues were then incubated in 1 mg/mL collagenase and 30 µg/mL DNase ( Sigma Aldrich ) at 37°C for 30 min . Digested tissues were passed through a 70-µm pore nylon cell strainer ( Falcon; BD Biosciences ) using the flat end of a sterile syringe plunger . The resultant cell suspensions were then treated with ACK lysis buffer ( Invitrogen ) to lyse red blood cells . Cells were then washed twice with complete RPMI . The method of trypan blue exclusion was used to enumerate live cells . For the ID model of immunization , ear dermal sheets were split along the cartilage and placed skin-side up in RPMI complete supplemented with 10% FCS and collagenase ( 1 mg/mL ) , followed by an one-hour incubation at 37°C and 5% CO2 to prepare suspensions of cells . Single cell suspensions were obtained by filtering through a 70-µm cell strainer ( BD Falcon ) . Single cell suspensions prepared from various tissues as described above , were washed in Flow Cytometry Staining Buffer ( eBioscience ) . Flow cytometric analysis and intracellular staining was conducted as previously described [1] , [2] . For each sample , approximately 106 cells were suspended in Flow Cytometry Staining Buffer . Cellular Fcγ receptors were blocked by incubating cells in Fc block ( BD Biosciences ) on ice for 10 min . Cells were then immunostained for flow cytometric analysis with the following fluorochrome-conjugated Abs: anti-CD4-PE-Cy7 ( clone RM4-5 ) , anti-CD11c-FITC ( clone HL3 ) , anti-CD11b-PE-Cy7 ( clone M1/70 ) , anti-Ly6G-FITC ( clone 1A8 ) , B220-PerCP ( clone RA3-6B2 ) , CD22-PE ( clone Cy34 . 1 ) , CD19-FITC ( clone 1D3 ) , anti-IFN-γ-PE ( clone XMG1 . 2 ) , and anti-IL-17A-PE ( clone TC11-18H10 ) , all from BD Pharmingen; and anti-CD3-APC ( clone 145-2C11; eBioscience ) . Dead cells were excluded from analysis using the LIVE/DEAD Fixable Violet Dead Cell Stain Kit ( Invitrogen ) according to manufacturer's protocol . Samples were collected on an LSRII ( BD Biosciences , San Jose , CA ) , and data analysis was performed using FlowJo software ( TreeStar , Ashland , OR ) . To stain for intracellular cytokines , single lung cell suspensions prepared as described above were stimulated in wells of 96-well plates in RPMI-1640 with 10% ( vol/vol ) FBS for 2 hours at 37°C and 5% CO2 in the presence of PMA ( 50 ng/mL ) and ionomycin ( 500 ng/mL ) . Brefeldin A ( 1 µg/mL; eBioscience ) was then added to the wells , and incubation was continued for another 2 hours at 37°C and 5% CO2 . Following stimulation , the FoxP3 staining buffer kit ( eBioscience ) was used according to the manufacturer's protocol for intracellular cytokine staining . For B cell depletion studies , two different reagents were used to deplete this lymphocytes population from wild-type C57BL/6 mice . The first reagent , CD22-cal ( Pfizer ) , is an immunoconjugate consisting of a monoclonal antibody ( mAb ) that reacts specifically with mouse CD22 ( a B cell-specific surface molecule ) , conjugated to N-acetyl-calicheamicin dimethyl acid , an enediyne anti-tumor agent [47] , [48] that mediates dose-dependent cytotoxicity upon internalization [60] , [61] . CD22-cal was administered at a dose of 160 µg/kg intraperitoneally ( i . p . ) at 12 and 7 days before M . tuberculosis infection , and then at 9 and 14 days post-inoculation . This regimen has been shown in various mouse models to effectively deplete B lymphocytes without affecting other immune cells [47] . This CD22-cal protocol routinely attains ∼95% of splenic B cell-depletion in treated mice at the time of M . tuberculosis infection and subsequent time intervals of analysis ( Figure S1A and data not shown ) . 5D2 , an anti-CD20 mAb ( Genentech ) , was another B cell-depleting agent used . Mice received a dose of 10 mg/kg of Ab intravenously two days prior to ID ear or SC BCG immunization . Two weeks after the initial dose , anti-CD20 5D2 was then given i . p . at a dose of 5 mg/kg every other week for maintenance . This 5D2 protocol was shown in pilot experiments to be highly effective in B cell-depletion in mycobacteria-infected mice ( Figure S1B ) . BCG immunization was administered either subcutaneously or intradermally . For the conventional SC vaccination model , 106 BCG Pasteur were inoculated subcutaneously in the scruff of the back of the neck in 100 µl of PBS containing 0 . 05% Tween-80 ( Sigma Aldrich ) . For the ID vaccination model , an inoculum of 106 BCG ( determined in standardization experiments to be the optimal dose ) , in 10 µl of PBS containing 0 . 05% Tween-80 ( Sigma Aldrich ) , was injected intradermally into the ear pinna of anesthetized mice using a Hamilton Microlitre syringe . Single cell suspensions of splenocytes and of the pinna and draining lymph nodes were obtained as described above and subjected to the IFN-γ ELISPOT assay ( see below ) and flow cytometric analysis . The IFN-γ ELISPOT assay was used to assess the CD4+ T cell response upon exposure to mycobacteria as previously described [62] . T cells were purified from appropriate tissues at the desired time intervals using the Mouse Pan T Cell Isolation Kit II ( Miltenyi Biotech ) . Detection of IFN-γ-producing T cells was conducted using the Mouse IFN-γ ELISPOT Ready-Set-Go Kit ( eBioscience ) according to manufacturer's instructions . Briefly , T cells ( 1×105 and 3×105 ) were seeded in wells of 96-well ELISPOT plates ( Millipore ) that had been coated overnight with IFN-γ capture Ab . Peptide 25 ( aa 240–254 ) of M . tuberculosis antigen 85B ( P25-Ag85B ) was used to stimulate CD4+ T cells [62] . Splenocytes from naïve uninfected mice were used asAPCs . The APCs were pulsed with P25-Ag85B ( 10 µg/mL ) for 1 hour at 37°C and 5% CO2 , washed twice , and added to T cell-seeded wells ( 2×105 cells per well ) . T cells co-cultured with unpulsed APCs served as controls . After a thirty-six-hour incubation at 37°C and 5% CO2 , cells were removed and the captured cytokine was detected using a biotinylated anti-mouse IFN-γ Ab ( clone R4-6A2; eBiosciences ) . Avidin-horseradish peroxidase ( eBioscience ) was added to the wells for 45 minutes at room temperature and colorization was achieved using AEC substrate solution ( eBioscience ) . The substrate reaction was stopped by washing the plate with distilled water . Spots were enumerated using an automated ELISPOT reader . Two anti-mouse IL-17 mAb's were used . One was obtained from R & D systems ( 50104; IgG2 ) and another from Genetech ( IgG1; Gift of Dr . Wenjun Ouyang , Genentech ) . The mAb's were administered was administered i . p . at a dose of 100 µg per mouse ( in 200 µl of sterile PBS ) every 3–4 days starting one day before M . tuberculosis infection or BCG immunization for the duration of the study . This regimen has been shown to effectively neutralize IL-17 in various experimental models [63] . Control groups received matched IgG isotypes . For neutrophil depletion , the anti-mouse Ly6G Ab ( BioXcell; clone 1A8 ) or Rat IgG2 a isotype control ( BioXcell; clone 2A3 ) , 200 µg per mouse in 100 µl of sterile PBS , was administered i . p . every 3–4 days as previously described [64] starting one day before BCG immunization for the duration of the study . Blood was collected retro-orbitally from C57BL/6 mice infected with 100 CFU M . tuberculosis Erdman at 1 month p . i . . Sera were collected after clarification by centrifugation of clotted blood and stored at −80°C until use . Sera thus collected are referred to as immune sera . One hundred µl of immune sera were administered i . p . every 3–4 days into μMT mice , starting 1 day before infection with 100–300 CFU of M . tuberculosis Erdman , and continued for 1 month thereafter . At 1 month p . i . , lung cells were procured from mice and subjected to intracellular staining and flow cytometric analysis . Where appropriate , the statistical significance of data points was determined using the unpaired Student t test or ANOVA analysis , assessed using GraphPad Prism 5 software . A p value of <0 . 05 was considered significant . | Mycobacterium tuberculosis poses a serious threat to public health globally . It has been well established that T cells are critical in protection against M . tuberculosis . The role of B cells and humoral immunity in the process is less well understood . We previously showed that B cells and humoral immunity regulate the immune response against M . tuberculosis . The present study examined the mechanisms by which B cells regulate the host neutrophilic response upon exposure to mycobacteria and how neutrophilia may modulate the development of vaccine-induced protective immunity . The data reveal that B cells can regulate neutrophilia during M . tuberculosis infection and BCG vaccination by modulating the IL-17 response . Vaccination studies show that excess neutrophilia adversely affects the development of BCG-elicited Th1 response . These observations suggest that B cells can optimize the development of protective immunity upon BCG vaccination by regulating the IL-17/neutrophilic response . Understanding the mechanisms by which B cells and humoral immunity modulate the immune response during M . tuberculosis infection and BCG immunization , particularly those that regulate IL-17 levels and neutrophilia , may lead to the development of novel strategies for the control of the tubercle bacillus , including efficacious vaccines . | [
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"bi... | 2013 | B Cells Regulate Neutrophilia during Mycobacterium tuberculosis Infection and BCG Vaccination by Modulating the Interleukin-17 Response |
Disease surveillance in rural regions of many countries is poor , such that prolonged delays ( months ) may intervene between appearance of disease and its recognition by public health authorities . For infectious disorders , delayed recognition and intervention enables uncontrolled disease spread . We tested the feasibility in northern Uganda of developing real-time , village-based health surveillance of an epidemic of Nodding syndrome ( NS ) using software-programmed smartphones operated by minimally trained lay mHealth reporters . We used a customized data collection platform ( Magpi ) that uses mobile phones and real-time cloud-based storage with global positioning system coordinates and time stamping . Pilot studies on sleep behavior of U . S . and Ugandan medical students identified and resolved Magpi-programmed cell phone issues . Thereafter , we deployed Magpi in combination with a lay-operator network of eight mHealth reporters to develop a real-time electronic map of child health , injury and illness relating to NS in rural northern Uganda . Surveillance data were collected for three consecutive months from 10 villages heavily affected by NS . Overall , a total of 240 NS-affected households and an average of 326 children with NS , representing 30 households and approximately 40 NS children per mHealth reporter , were monitored every week by the lay mHealth team . Data submitted for analysis in the USA and Uganda remotely pinpointed the household location and number of NS deaths , injuries , newly reported cases of head nodding ( n = 22 ) , and the presence or absence of anti-seizure medication . This study demonstrates the feasibility of using lay mHealth workers to develop a real-time cartography of epidemic disease in remote rural villages that can facilitate and steer clinical , educational and research interventions in a timely manner .
Disease outbreaks in remote rural populations of Africa and elsewhere are often detected late by public health entities . Reasons include dependence on traditional remedies and healers , low village literacy and knowledge of how to report a disease outbreak , lack of distributed health professionals , poor communication systems and difficulties in transportation of patients to clinics . Examples abound but come into focus most dramatically from two outbreaks of Ebola hemorrhagic fever ( EHF ) in sub-Saharan countries . In an example from northern Uganda ( Acholiland ) , several weeks elapsed between the presumptive index case ( August 30 , 2000 ) and virus confirmation ( October 15 , 2000 ) of an outbreak of EHF that persisted for 6 months ( January 9 , 2001 ) and resulted in 425 presumptive case patients [1] . Second , a major 2014–2016 West African EHF epidemic appears to have begun in rural southeastern Guinea but months elapsed before the illness was recognized as EHF , during which the virus spread to multiple neighboring countries . As of June 2016 , 28 , 616 suspected , probable , and confirmed cases with a total of 11 , 310 deaths were recorded in Guinea , Liberia , and Sierra Leone [2–3] . These examples illustrate the urgent need to develop improved health surveillance of remote rural communities for emerging and extant diseases . Timely discovery of outbreaks cannot be accomplished by periodic visits by healthcare workers to the scattered villages where disease can begin and spread . Needed is a health surveillance system that in real-time can pinpoint and track disease cases longitudinally , such that clinical , education and research resources can be rapidly and efficiently dispatched to affected villages . To this end , we have tested the feasibility of using software-coupled mobile phones operated with minimal training by village-based lay mHealth reporters charged with repeatedly assessing the status of children with a non-infectious and easily recognized idiopathic neurologic disease ( Nodding syndrome ) [4–5] . Their weekly reports , transmitted by simple smartphones , were instantaneously aggregated , analyzed and mapped by data collection centers locally ( Gulu , Uganda ) and remotely ( Oregon , USA ) . While lay health aides have been used successfully to amplify health coverage in remote regions of Asia ( Nepal , Bangladesh , Indonesia ) [6–9] , and mHealth projects are legion [10–12] , we are unaware of prior initiatives that have used the reports of lay mHealth operators to populate a real-time medical cartography that can guide clinical , research , and educational interventions to respond to epidemic disease .
We undertook a feasibility study in remote regions of northern Uganda to determine whether minimally trained lay reporters , resident within rural villages , could collect and reliably transmit health-related information at regular intervals using simple smart phones equipped with network-linked software that integrates data sets from multiple settings across time . The study was not designed or approved to conduct or implement a medical intervention . This study was conducted in Acholiland , the northernmost region of Uganda . The region is recovering from a brutal conflict ( 1986–2009 ) between the Lord’s Resistance Army and the forces of the Ugandan government , which from approximately 1996 to 2008 required an estimated 2 million people to leave their villages for the relative safety of internal displacement camps . Focus was placed on families with children with Nodding syndrome ( NS ) , a chronic epileptic encephalopathy of unknown etiology that was regionally epidemic between 1997 and 2012 , with peaks in 2003–2005 and 2008 , 5–6 years after peaks in the number of wartime conflicts and deaths . The largest number of NS cases followed 5–7 years after the peak of population translocation to internal displacement camps [13] . Selected for study were 2 rural districts heavily affected by NS , namely Pader and Omoro , including 2 sub-counties , 4 parishes and 10 villages therein ( Table 1 ) . A manageable sample of households ( n = 240 ) with one or more children with NS was recruited in equal proportion for each district . Most if not all children had a prior physician-diagnosis of NS that allowed them to receive , under the treatment program of the Ugandan government [14] , a supply of nutritional supplements ( Mamas Nutritional Supplement Ltd , Mbale , Uganda ) and anticonvulsant medication . A medical diagnostician ( DLK ) physically examined a sample of households reporting existing and newly reported NS cases , the large majority of which had longstanding but unregistered NS . In agreement with the First International Scientific Meeting of NS in Kampala ( July 30th-August 1st 2012 ) , a probable NS case was identified by an age of onset between 3 and 18 years of age , a frequency on unprovoked head nodding of 5-20/minute ( triggered by food and/or cold weather ) and at least one of the following minor criteria: a ) other neurological abnormalities ( other seizures , cognitive decline/behavioral problems with or without school dropout , psychiatric symptoms ) , b ) developmental abnormalities ( stunting or wasting , delayed sexual or physical development ) and/or c ) clustering in space or time with similar cases . In undertaking this feasibility study , we customized a data collection platform named Magpi that uses mobile phones and real-time cloud-based storage with global positioning system ( GPS ) coordinates and time stamping [15] . The decision to use Magpi was based on several factors , including its widespread acceptance ( Magpi has been used by organizations such as the WHO , CDC , UNICEF , UNFPA , CARE and the IFRC ) , proven track record and because the software supports: a ) a wide variety of question types ( text/numeric entry , multiple choice , etc . ) ; b ) customized questions; c ) off-line data collection ( data can be collected off-line and submitted to a central server whenever an active connection becomes available ) ; d ) GPS stamping and display of data-points on an electronic map; and e ) instantaneous data integration from multiple users . In addition , Magpi is f ) user friendly; g ) easy to learn; h ) requires no programing experience ( the software allows non-technically trained users to create data collection forms , messaging systems and interactive reports ) ; and i ) offers free and paid premium versions with an excellent technical support team . A pilot study in the USA used Magpi-programmed basic mobile flip phones , while the pilot and feasibility studies in Uganda used similarly programmed smartphones . The two pilot studies ( USA and Uganda ) were conducted using the free version of Magpi whereas we used the Magpi Pro version ( $500/month or $417/month if bought annually ) to operate the feasibility study in Uganda , which required more than 500 survey uploads/storage per month . Technical and subject-use issues with Magpi software-enabled equipment were identified by conducting two pilot studies among: a ) university students in the USA Pacific Northwest and b ) students attending Uganda’s Gulu University ( GU ) School of Medicine . Briefly , each student ( n = 12 per study population , with equal numbers of males and females of similar age randomly selected at each site ) was provided with a Magpi-programmed cell phone , instructed on its functions , and asked to respond to a 10-question personal sleep-health survey daily for 14 consecutive days . After completion , participants were asked to attend a final meeting , share their experiences , return their cell phones , and receive a vendor gift card or small compensation . While not designed to conduct a scientifically defensible survey of sleep patterns , the data were analyzed using Microsoft Excel to assess sleeping trends across the 14-day span . Minor technical difficulties ( duplicate questions , duplicate surveys , error messages , etc . ) were referred to Magpi’s technical support team , and modifications were made to the software feature to ensure these issues were eliminated . The pilot studies also provided valuable information on network connectivity and reporter reliability , perception , and experience in using the application and surveys . Such information fed into the design of the mHealth feasibility study in Uganda . The study was carried out in northern Uganda from July to October 2017 . Eight male and female Ugandan lay mHealth reporters , age 20–30 years , were recruited and trained . The training covered basic concepts of health and disease , the purpose and content of the program , clinical and social aspects of NS , use and maintenance of the equipment ( cell phones , solar batteries , bicycles ) , questionnaire presentation , data collection and submission , home and community entry , informed consent administration and patient confidentiality . Focus was placed on some typical mistakes , such as mistyping or duplicated forms; time spent collecting and transmitting the surveys; WiFi and Internet accessibility; GPS stamping; and other technical issues such as how to turn off/on the WiFi/GPS to help improve cell-phone battery life . One local field coordinator and two community health nurses ( one from each sub-county ) , in the role of field supervisors , were appointed and registered with the study to closely monitor the training and operations in the field and to provide onsite supervision to each sub-county mHealth team ( 4 reporters per sub-county ) . mHealth reporters were pilot-tested and evaluated for satisfactory performance before they returned to their respective villages to commence weekly reporting . Before engaging in data collection , the mHealth reporters signed the Hope for Humans’ Child Protection protocol to ensure adherence with their Child Protection Policy and information confidentiality . Supportive supervision was made available to mHealth reporters by phone ( 24/7 ) and in-person every week during the first month of program implementation and biweekly throughout the end of the program . Biweekly meetings of the lay mHealth operators and field supervisors allowed mHealth staff to share field experiences , lessons learned , challenges , barriers and how they could be overcome . Payment of mHealth reporters was made in the form of a stipend for training , a regular monthly salary , and small economic incentives . For instance , provided weekly mHealth data were uploaded on time to the Magpi server , we placed no restrictions on the phones regarding the apps that could be accessed/installed or the use of airtime for personal communication . The phones were loaded with a shared bundle ( Kazi , MTN Service Center , Gulu; approx . $97 . 1/month ) from the local mobile operator MTN which included MTN minutes , minutes to other networks , MTN SMS , SMS to other networks , data/internet , and free calling among each number in the bundle . Inexpensive , locally purchased airtime-loaded smartphones ( MTN Smart Mega; approx . $30/phone ) supported by the local telecommunication company MTN , were individually programmed with Magpi software over 1 week and distributed to the mHealth reporters and field supervisors . With every phone , a portable power supply consisting of a solar energy panel/bulb and a battery with dual USB charging ports ( approx . $30/set ) was also provided . Paper forms were distributed as a backup alternative to mHealth data collection ( e . g . in case of cell phone loss or failure ) . In addition , mountain bicycles ( Phoenix single frame , approx . $80/bike ) and raingear ( raincoats and boots , approx . $11/set ) were supplied to facilitate access and travel to and within the communities ( typically with poor or no road infrastructure , particularly during the rainy season ) . Reserve equipment ( two software-equipped smartphones , two solar panels and chargers , and two bicycles ) was also available for immediate use in both sub-counties . A simple structured questionnaire was designed using the Magpi web-interface to measure the feasibility and practicalities of the Magpi application-based reporting system . The Magpi application works with the Magpi website to deploy data collection surveys to basic smartphones . The survey , which was applied once weekly , included information on coded household location , number of NS children/household , seizure frequency , availability of anti-seizure medication , and injuries and deaths . After obtaining informed consent from the participant household caregivers , a unique ID code was assigned to each household to preserve confidentiality and anonymity . Data collection via the Magpi’s mobile platform took place for 12 consecutive weeks , from August 1st throughout October 31st 2017 . During this period , the mHealth reporters were asked first to complete and store the surveys locally on their mobile devices in the field , and subsequently , depending on WiFi availability , upload them daily or weekly to a secure web-hosted database . Day-to-day technical support was provided by the local field coordinator and supervisors; support included: troubleshooting the phone system , applications , survey forms and dealing with any queries from the mHealth workers . Any issues the local research team could not resolve were passed to the program manager at OHSU for investigation . Online software-integrated village-based survey forms , transmitted by smart phone to the Magpi data management website , were monitored weekly and analyzed by the program manager ( RVA ) located at Oregon Health & Science University ( OHSU ) . Data were later imported into a local data center established at Gulu University ( GU ) School of Medicine . During the 12-week data collection period , any mistyping , duplicated reports , data inconsistencies or doubtful information were reported by phone or email to the field coordinator and from there to the corresponding field supervisor for double-checking , fixing , and resending if necessary . On-site monitoring trips were also organized biweekly during the implementation phase to some randomly chosen households , to ensure compliance with data transmission instructions and consistency across different sites and different data collectors . While the goal of this intervention was to test the feasibility of NS-related data collection and integration using Magpi , cartographic information from the mHealth syndromic surveillance within the study area was offered to supervisors and health bureaus in support of their public mandate and with the aim of increasing understanding on how convulsive disorders , such as NS , impact families and children . These data were analyzed qualitatively ( using Magpi and Excel ) and reports were mainly descriptive . All cell phones were password-protected , and the survey was developed to avoid subject-specific identifiable information . As mentioned earlier , each household was assigned a specific identification code and each reporter was given a unique identification email . Hence , the data collected and transmitted daily did not disclose information about specific individuals . All connections between the cell phone and the server were made using modern encryption methods to transfer data , including Extended Validation Secure Sockets Layer ( EV-SSL ) and AES-256 bit encryption . In addition , Magpi uses Rackspace Cloud Storage in the U . S . for primary data storage , which has a robust security policy of its own . Access to the surveys and databases was strictly controlled and only available to authorized personnel . Administrative rights to view data were given to the leadership at GU . Neither the analytics dashboard nor the mobile phone forms gave users any access to edit or change data . This ensured data integrity and eliminated the possibility of data tampering . A secondary goal of this project was to a ) incentivize and empower young adults with modest education to raise awareness in their communities of the importance of healthcare , disease early detection and disease monitoring , and b ) expose GU medical students to community-specific health challenges . The interaction of mHealth reporters and GU medical students with members of the USA team , GU faculty , and health personnel at the HfH care facility , was expected to raise their interest in pursuing and/or expanding upon a health-sector career , whether as a research assistant , nurse , or community health worker , thereby helping to alleviate the health-manpower shortage , building capacity and strengthening a weak primary health care system . Hence , at the end of the program , we evaluated with short questionnaires the impact of this exploratory mHealth study on mHealth reporters ( future healthcare interest ) , medical students ( future research interest ) , and health workers ( acceptability of mHealth and eHealth approaches and compatibility with regional/national systems ) . As part of the qualitative evaluation , we sought to elicit the views of participants on their acceptability of the intervention and research procedures , as well as potential demand and integration into primary healthcare settings . The Ugandan study was reviewed and approved by the Institutional Review Board of St . Mary’s Lacor Hospital in support of Gulu University , the Uganda National Council for Science and Technology , and the Office of the President of Uganda . The USA and Uganda studies were reviewed and approved by the Institutional Review Board of Oregon Health & Science University . Written or fingerprinted consent for participation was obtained for each household , and families were informed about their right to withdraw from the study at any time . At the end of the study , each household received financial compensation ( $10 ) for their time and cooperation .
We used two pilot studies to test the feasibility of using customized network-linked software ( Magpi ) that integrates data sets from multiple geographically dispersed reporters via mobile phones . The first pilot study employed 12 students from Oregon Health & Science University ( Portland , OR ) and Washington University ( Seattle , WA ) as reporters of their own sleep-related behaviors . We used Magpi-programmed flip phones to collect and integrate data , develop a real-time sleep pattern topography , and test the hypothesis that 85% of daily sleep surveys , over a 14-day span , would be completed on time . We reproduced the pilot study in Gulu , northern Uganda , with 12 medical students from Gulu University ( GU ) and basic smartphones locally purchased and supported by the local telecommunication company MTN . Overall , respondents in the USA completed a mean of 77% of surveys administered , compared to a 96% survey completion rate for Ugandan respondents . Completion percentages in the USA dropped in the middle of each week and were strongest at the beginning and end of each trial . In Uganda , completion percentages remained high throughout the entire trial . The American students averaged 7 . 5 hours of sleep per night , felt well rested on 53% of days , used sleeping aids 21% of nights , and 27% of them reported caffeine use . Participants in Uganda averaged 6 . 4 hours of sleep per night , felt well rested over 85% of the time , none reported using a sleeping aid , and only 3% reported caffeine use . Both pilot studies allowed us to conclude that Magpi is an effective and powerful tool to build a real-time geography of health data . In addition , these studies provided valuable information on reporter consistency and desirable training , as well as detecting minor technical issues that were referred , troubleshot and eliminated by Magpi’s technical support team . We next used Magpi in combination with the lay operator mHealth network of eight village-based lay mHealth reporters ( vide supra ) to develop a real-time electronic map of child health , injury and illness relating to NS in northern Uganda . Surveillance data were collected for three consecutive months ( August to October 2017 ) in a convenient sample of villages ( n = 10 ) from two rural sub-counties ( Odek in Omoro District and Awere in Pader District ) heavily affected by NS ( Table 1 ) . The accuracy and completeness of the surveys submitted were assessed by a ) daily remote data monitoring and b ) periodic quality-control visits made to a randomly selected sub-set of households . One of the major advantages of using Magpi was the ability to visualize , through the Magpi web-interface , outputs such as survey start and end times , average survey completion time , survey completion count , etc . ( Fig 1 ) . Survey quality checks were thus performed in real-time and inconsistencies were detected , reported , rectified , and cleaned in a timely manner . The monitoring potential of Magpi also allowed for the rapid recognition of fabricated data , based upon our expectations about the amount of time it would reasonably take to move from household to household , obtain informed consent and complete the survey . All mHealth workers were informed their movements and data authenticity could be tracked . Almost all mHealth reporters had experience using smartphone devices prior to the surveillance feasibility project and were not intimidated by the technology . Half of them felt comfortable using the Magpi app within a week , and none of them found it difficult to use after a month . Despite the many implementation challenges described below , data collection proceeded in a timely and efficient manner . Overall , a total of 240 households ( 30 households per mHealth reporter ) and an average of 326 children with NS ( 40 . 7 ± 4 . 57 children per mHealth reporter ) were monitored every week by the mHealth team . With the exception of one reporter ( targeting Ludok and Olam villages ) who abandoned the program on week 6 due to health-related issues , the mHealth team completed a mean of 97 . 3% of surveys administered per week ( 29 . 2 ± 0 . 63 of 30 surveys assigned per mHealth reporter ) . All data acquired and integrated into the Magpi database could be exported , with no particular conversion problems , from the platform into statistical ( Excel ) or spatial ( Magpi maps ) analysis software . To illustrate the system’s interoperability and quality , Fig 2 displays the surveillance area and includes a close-up of two villages ( Paikat Akidi and Bolo Lapeta ) at week-6 of data collection . With the map interface , it is possible to zoom in and observe the geographic distribution of NS health-related data in a particular village , and even in a specific household . For instance , the close-up in Fig 2 highlights those households with at least one child with NS that did not have anti-seizure medication ( Fig 2E1 , green color ) , was injured ( Fig 2E2 , green color ) or died ( Fig 2E3 ) that week . The Magpi interface also made it possible to visualize NS health-related data over a defined period of time ( Fig 3 ) with the goal to assess fluctuations and carry out temporal interpretations . However , after comparing our maps ( Fig 3 ) and the data collected ( Table 2 ) , it became readily apparent that many geotracers malfunctioned or , most likely , many remote areas had weak or no coverage of cellular communication , causing limitations in acquiring GPS stamps and compromising the ability to produce maps using GPS coordinates . While the purpose of this study was to test the feasibility of NS-related data collection and integration using Magpi , we used descriptive statistical analyses to assess the health impact of NS with the aim of guiding future clinical , educational and research interventions . Of the 326 affected children monitored by the mHealth team , 17 died over the 12-week study time frame and 22 siblings were reported to have nodding spells for the first time . Lack of appropriate anti-seizure medication and injuries were also registered on Magpi 688 times and 186 times , respectively ( S1 Tables ) . After normalizing the number of NS children monitored per village to 100% for comparison purposes ( Fig 4 , red section in each pie chart ) , several findings emerged . For instance , access to anti-seizure medication was extremely limited in Awere sub-county , particularly in Paikat Akidi , Bolo Juklebi/Bolo Agweng , and Bolo Lapeta , where the percentage of children without medication ( Fig 4 , blue section in each pie chart ) was 585 . 1% , 341 . 6% , and 233 . 3% , respectively . We would like to highlight that the pie charts in Fig 4 display health-related information across the 12-week study and percentages above 100% are indicative of repeated ( the sum of ) health outcomes . For instance , the blue pie chart sections with percentages above 100% in the Paikat Akidi , Bolo Juklebi/Bolo Agweng , and Bolo Lapeta graphs denote that several children with NS in those villages did not have access to medication for a number of weeks . However , the charts do not allow the reader to discern whether , for example , 10 children did not have medication for 1 week or whether 1 child did not have medication for 10 weeks ( this information is made available in the weekly S1 Tables ) . The goal of the pie charts was simply to provide a quick snap shot of those villages that required immediate attention . In the particular case of lack of anti-seizure medication , higher percentages indicated a greater need for medication supply . Along the same lines , villages like Paikat Akidi and Ajan/Akoyo had the highest percentage of injured children ( 146 . 3% and 75 . 1% , respectively ) , compared to only 11 . 8% in Lukee . The highest mortality percentages were associated with Atede West ( 28 . 4% ) and Ajan ( 7 . 3% ) . Ajan was also the village where respondents reported a surprisingly large percentage of children with nodding spells for the first time ( 16 . 9% ) , alongside Paikat Akidi ( 16 . 0% ) and Lukee ( 8 . 8% ) . While most of these newly identified subjects proved to be longstanding NS cases in the sample given a medical evaluation , there is a possibility that the one potentially new case portends others . The possibility that the NS epidemic has not ended merits prioritized study . While we noticed some improvement on a few health outcomes ( e . g . provision of medication , reduction of injuries , clinical referrals , etc . ) across the 12-week study , such progress resulted exclusively from the cooperative effort by individuals on the mHealth team ( including members of the local non-profit organization Hope for Humans ) , who organized themselves to further serve their communities beyond the scope of the mHealth project . Physical examination of the sample of newly reported and existing NS cases confirmed a diagnosis of NS . On examination , children newly reported by mHealth workers to have NS were found to have longstanding disease . Only one new case of Suspected NS was found in the sample , a boy aged 3 years with an older brother with registered NS . Around 2 . 5 years of age , at the sight of food , the new case developed episodes of head nodding lasting for minutes . The child was unresponsive during these periods and usually fatigued and irritable thereafter . Otherwise , on examination , he was grossly neurologically intact . The boy was registered with the Ministry of Health as a Suspected NS case and started on anti-seizure medication by a government healthcare worker . Other children that had not been registered with NS and who were identified as newly reported cases in the mHealth survey were referred to a primary health center for observation , NS confirmation and treatment . The foregoing observations were made in the face of numerous technical , logistical and institutional problems that were met with innovative solutions but nevertheless substantially delayed progress . The most common technical issues were frequent power cuts , poor network coverage , slow upload speeds and unreliable GPS satellites . Inconsistent connectivity led to difficulties in survey uploading ( e . g . , some mHealth workers reported traveling to a specific hotspot or even climbing a particular tree to access satisfactory signal strength and network coverage ) . Instrument charging issues were traceable to an inability to charge phones in the field , failure to charge overnight , and short battery life of cell phones possibly exacerbated by heat . On the first day of September , all mobile phones ran out of data because the network provider failed to renew the monthly phone bundle on time . Although the surveys collected during this period were stored on the memory of the cell phone and could have been uploaded later , some reporters stopped working when they realized their data bundles were exhausted . Other reporters used hard-copy forms and entered the data in the Magpi app later . This last practice resulted in no data loss but large single entries ( e . g . , > 10 households ) with only one GPS stamp . Thanks to ongoing remote monitoring , the program manager discovered there were no entries on the Magpi server that day and notified the problem to the field coordinator for immediate clarification . Occasional technical problems with Magpi software and human errors ( e . g . , duplicates , outliers , etc . ) during daily data collection and transmission were also detected and rapidly addressed . Some technical problems were exacerbated by logistical challenges . Some monitored households had to be replaced due to accessibility issues and poor road conditions during the rainy season . Others were replaced because of outdated household records ( deceased children , relocation ) . A handful of householders showed some reluctance to consent and required a follow-up visit by the field supervisor . Family absences during the harvest season forced mHealth reporters to follow the subjects to their gardens . This not only slowed the process of data collection but also changed some GPS coordinates , introducing undesired variability and therefore hindering the ability to produce maps using GPS stamps . In addition , our research partner Hope for Humans ceased Ugandan operations on December 30th , 2017 . Lastly , research performed by U . S . researchers abroad poses many administrative challenges including registration , research ethics training , acquisition of research approvals from university human subjects review boards , approvals from local ( Gulu ) , national ( Uganda ) and international ( USA ) agencies , and requirements for foreign investigators that are not user-friendly , lengthy and time-consuming . Institutional inefficiency and suboptimal cooperation consumed more than half of the 2-year grant that funded this feasibility study . All mHealth workers rated the intervention , mHealth team , and outcomes very positively . The resulting gain in skills made them feel confident , enthusiastic and motivated to participate in future healthcare programs . Everyone ( 100% ) expressed their desire to help people be healthy ( e . g . , as doctors , nurses , community health workers , etc . ) in the future . Three of 11 ( 27 . 3% ) expressed that they would also like to work in technology ( e . g . , cell phone manufacturing ) ; two of 11 ( 18 . 2% ) stated they would like to “sell things”; and the 2 field supervisors indicated a desire for further studies to improve their health careers ( the two field supervisors have been admitted into the Lacor School of Nursing and Midwifery in Gulu ) . Everyone ( 100% ) stated that money was a barrier to fulfilling their respective dreams . One mHealth reporter added that she didn’t know where to start , another expressed the lack of inadequate guidance and career mentorship , and a third added he did not have enough time , appropriate means or support from the community . GU medical students also expressed some interest in research and future research opportunities . Healthcare providers and professionals from Gulu University , St . Mary Lacor Hospital and Awere Health Center III showed enthusiastic support for the potential of mHealth and eHealth systems ( see Acknowledgments ) to improve health outcomes . However , they noted funding , regulatory , and technological challenges that might hinder the integration of these approaches into primary healthcare settings .
One of the most remarkable examples of real-time case surveillance of neurological disease occurred during the 1991–94 Cuban epidemic of optic and peripheral neuropathy , which affected approximately 50 , 000 residents . Because the health system had deployed physicians across the island and required them to report unusual illnesses to the Cuban Ministry of Public Health , it was possible not only to identify the origin and track the spatial-temporal distribution and decreasing incidence of disease ( from west to the east ) but also to follow its clinical evolution ( from pure optic to mixed and purely peripheral neuropathy forms ) [16–17] . However , this extraordinary example of real-time public health surveillance is unavailable in many low-income countries , such that other solutions must be found for early disease identification and tracking . In 1998 , the African regional office of the World Health Organization ( WHO ) started promoting the Integrated Disease Surveillance and Response ( IDSR ) framework for strengthening national public health surveillance capabilities at all levels in Africa [18] . This groundbreaking program was , however , largely paper-based and has been reported to be generally inefficient and error-prone with low completeness and poor timely reporting . Considering that mobile networks have reached far more people than any other advanced communication technology in sub-Saharan Africa , data collection initiatives that use mobile phone applications to deliver life-saving information , even in the most remote and resource-poor settings , offer a new horizon for public health surveillance . To date , most of the studies that have analyzed the use of mobile phones in the field of surveillance have combined the use of mobile technologies with trained staff ( e . g . community health workers , nurses , midwives , health surveillance assistants , sentinel general practitioners , epidemiologist , veterinarians , pharmacists , etc . ) [19–22] . In 2013 , Braun and colleagues published a systematic review of mHealth tools being employed by community health workers ( CHWs ) in low-resource settings , mainly in Africa [23] . The findings of this review demonstrated that CHWs were using mHealth strategies with increasing effectiveness to improve delivery of maternal and child health , HIV and reproductive health services , and other general services such as immunizations and treatment of infectious diseases such as tuberculosis and malaria . In 2015 , another systematic review by Agarwal and colleagues analyzed the feasibility and efficacy of mHealth strategies by frontline health workers ( FHWs ) as an attempt to circumvent several of the structural and systemic barriers they face in delivering health care [24] . In particular , twenty‐five studies included in this review had data collection as one of the primary mHealth functions being performed by FHWs , and several of them suggested that mobile phones are an effective way to collect and report data from the community , transfer patient‐relevant information to a centralized database and reduce the need for face‐to‐face communication between FHWs and other members of the health delivery system . Conversely , lay health workers have been scarcely described in the literature [25] and , to our knowledge , no one has explored the use of village lay health aides as local reporters of disease . This option has the potential to support not only the early detection of disease signals ( syndromic surveillance ) happening within remote communities , but also near-real-time responses that might likely prevent small outbreaks from becoming large-scale emergencies . Furthermore , the lay operators in our study were stimulated by their experience with mHealth to seek additional local healthcare opportunities . The surveillance system described herein relied on weekly inputs of neurological ( NS ) health data via basic smartphones operated by minimally trained lay mHealth reporters dispersed widely and resident within the communities under scrutiny . mHealth reporters needed only minimum education and experience to operate the system , with usability mostly affected by their previous level of experience with mobile phones . This approach has numerous advantages over the current paper-based documentation system , the most important of which is the accurate monitoring of events at the household level ( GPS coordinates ) that allows for more targeted disease control by location . Displayed on a map , the data collected provided a real-time health geography that helped identify and track disease hotspots , drug availability , injuries , deaths , and missed and new/newly reported cases of NS with no more than 1–7 days of delay . While each and every report requires medical confirmation , this is an extraordinary improvement in a region where major disease outbreaks have been recognized very slowly , monitoring is unavailable , and the distribution and utilization of vaccines and drugs are unclear . For instance , the 12-week feasibility survey identified several previously unreported longstanding cases of NS and at least one case of Suspected NS , indicating that further investigation of this epidemic is mandated . Since NS is not a recognized Neglected Tropical Disease ( NTD ) and , consequently NS research is poorly funded , NTD recognition and increased research funding and collaboration are needed to advance understanding of the NS epidemic in East Africa [26–27] . In addition , since the Magpi software supports a customized question set , the system has wide applicability for data collection across a vast array of readily recognizable health-related conditions , including dangerous infectious diseases such as EHF . Using a single system that gathers information about multiple diseases or behaviors of interest to several intervention programs may facilitate integration ( at the local , regional and national level ) and broad-scale surveillance and response . Collaboration among practitioners , researchers , nations , and international organizations is necessary to address the global needs of public health surveillance , provide accountability for local health status and deliver real-time early warning of potentially devastating outbreaks . Overall , through the development , implementation , and evaluation of this syndromic surveillance system of ( neurological ) disease in northern Uganda , we have demonstrated the significant value and feasibility for mobile technologies to overcome health communication barriers , even in adverse weather conditions , across desperately impoverished , war-traumatized populations living in remote rural areas . Critical factors that largely influenced the success of the program included careful planning , meticulous team selection , thorough training , vigilant monitoring , supportive supervision , and effective communication between the local research team and the USA program manager . This modus operandi enabled problems , such as technical issues ( e . g . , hardware and/or software failures using the smartphones ) , improper handling and maintenance of equipment ( e . g . inadequate cleaning/charging of solar panels ) , and human errors ( e . g . , data entry errors ) , to be detected and resolved as soon as they arose . In addition , we sought to create a highly motivating work environment by clearly defining roles and responsibilities ( e . g . , number of households to be served , frequency , geographic distance to be covered , etc . ) ; offering fair salaries and incentives ( e . g . free airtime for personal use ) ; providing travel assistance ( e . g . , travel reimbursement for attended meetings , bicycles and rain gear ) ; providing personalized certificates of excellence as a sign of appreciation; and providing recommendations for additional training and programs with the goal of building the reporters’ capacity , knowledge base , and standing in the community . However , our study also identified several limitations . First , mobile and information communication platforms are based and dependent on technology , which is inadequately available or weak in Uganda and in many sub-Saharan African countries . Second , many barriers to implementation and sustainability limit the success of mHealth solutions beyond the pilot or feasibility stage [28–29] . In fact , a large set of the mHealth studies described in the literature are pilots and provide little or no information about the effectiveness or impact of the use of mobile technologies when included in large-scale implementations of electronic health strategies . In our particular case , full deployment may require policies that support the integration of mHealth surveillance into national strategies for health system strengthening ( the potential for successful scale-up of mHealth tools increases when there is strong government ownership of the process ) [30] and the commitment of local and national health agencies to invest in the cost of cell phones , cellular bundles , Magpi software , training , and oversight . Most importantly , because syndromic surveillance is designed to detect population patterns of disease and cannot be used to establish individual diagnoses , it is important to assess whether the healthcare workforce may have the capacity to absorb additional mobile-based responsibilities ( e . g . , data management and processing , clinical examination of suspect cases , deployment of clinical/educational/research interventions , etc . ) before any attempt is made to scale-up . The etiology of Nodding syndrome is unknown . The medical condition was first described in Tanzania in the 1960s [31] but may have been present decades earlier [32] . In the early 1990s , an epidemic of NS impacted then-southern Sudan and , circa 1997 , a second began in northern Uganda , affecting over 3000 children with a case fatality of 6 . 7% [33 , 34] . Both epidemics were in association with civil conflict , population displacement , food shortages and malnutrition , disruption of vaccination campaigns , and lack of medical care [13 , 35] . Although families may have multiple children with NS [35] , which raises questions of hereditable factors , the overwhelming evidence points to one or more environmental impacts that selectively prevailed during or immediately prior to the epidemic periods . Exposure to toxic food plants or environmental chemicals was ruled out in Sudan NS cases [36] . These children were shown to be more heavily infested with the nematode Onchocerca volvulus ( OV ) than village children without the neurological disease [37] . The association with OV was confirmed in Tanzania and Ugandan NS but evidence for entry of the worm into the cerebrospinal fluid or central nervous system was lacking in all cases . This led to the hypothesis that NS is an autoimmune disorder in which there was molecular mimicry between OV antigens and leiomodin-1 [38] , an actin-binding protein associated with smooth muscle and present in all tissues , including relatively small amounts in brain . While leiomodin-1 antibodies were present to a greater extent in NS cases than healthy controls , they were not specific for NS and immunotherapy failed to benefit NS-affected children . Thus , instead of causing NS , the presence of nematode microfilaria may represent opportunistic infection of a host immunocompromised by malnutrition or other immunosuppressive factors [39] , such as measles infection ( especially in crowded displaced-person camps ) and mycotoxins in moldy corn , both of which were statistically associated with NS cases versus village controls prior to onset of head nodding in the former [40] . Infantile infection with measles or rubella virus can lead to the appearance of progressive brain disorders with some similarities to NS but the search for a neurotropic virus has yet to begin . Meanwhile , recently performed electroencephalographic studies of Ugandan children with established NS have concluded that head nodding episodes are likely late-onset epileptic spasms [41] , and neuropathological investigation has revealed a unique neurodegenerative disorder comparable to frontotemporal degeneration with tauopathy [42] . Consistent with the guiding principles of the Health Data Collaborative ( https://www . healthdatacollaborative . org/what-we-do/ ) , this study contributes to the growing body of evidence that supports the feasibility of real-time mHealth data collection on rare diseases to support local decision-making in resource-limited settings . Expanded access by local health authorities to data on NS from affected areas will increase accountability and encourage continuous improvement of data needed for unified monitoring and evaluation of access to new cases , seizure medication and deaths . In anticipation of these long-term needs , we hope to test the ability to collect full clinical details on NS cases to track disease progression and medication adherence in real time within familial clusters of NS using WOOP , an etablet application developed in Kenya for single point-of-care collection of commodities data and clinical data by lay operators to elicit protocol-driven SMS-reminders tailored to different patients by risk cohort , and thereby improve adherence to treatment in the absence of specialized medical providers . | Absence of health monitoring of rural populations in low-income countries allows diseases to emerge and spread for months before their detection by public health authorities . We tested the feasibility of using smartphones operated by lay villagers to report health information in real time from the populations in which they reside . Eight young lay adults from remote rural regions of northern Uganda were trained to administer questions and transmit answers using pre-programmed mobile phones . Weekly , over a 3-month period , each lay reporter monitored an average of 40 children suffering from an epileptic disorder known as Nodding syndrome ( NS ) . For each child , episodes of head nodding , convulsions , injuries , deaths and availability of anti-seizure medication were reported weekly and the data instantaneously assembled by customized software for analysis in Uganda and the USA . This system not only provided a real-time map of the health status of children with established NS but also discovered children previously unknown to have head nodding . While logistical hurdles had to be overcome , the study demonstrates the feasibility of using lay workers operating software-equipped mobile smartphones to build a current and continuously updatable medical geography of the rural populations in which they reside . Wide application of such systems could result in the early detection and control of disease . | [
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... | 2018 | A real-time medical cartography of epidemic disease (Nodding syndrome) using village-based lay mHealth reporters |
Compartment boundary formation plays an important role in development by separating adjacent developmental fields . Drosophila imaginal discs have proven valuable for studying the mechanisms of boundary formation . We studied the boundary separating the proximal A1 segment and the distal segments , defined respectively by Lim1 and Dll expression in the eye-antenna disc . Sharp segregation of the Lim1 and Dll expression domains precedes activation of Notch at the Dll/Lim1 interface . By repressing bantam miRNA and elevating the actin regulator Enable , Notch signaling then induces actomyosin-dependent apical constriction and epithelial fold . Disruption of Notch signaling or the actomyosin network reduces apical constriction and epithelial fold , so that Dll and Lim1 cells become intermingled . Our results demonstrate a new mechanism of boundary formation by actomyosin-dependent tissue folding , which provides a physical barrier to prevent mixing of cells from adjacent developmental fields .
During development , an organism is progressively divided into discrete fields that develop into different organs or parts of an organ . In many cases , the adjacent developmental fields develop distinct morphological , functional and molecular characteristics and are often divided by a sharp boundary that function to prevent lineage-related cells originating from one compartment from crossing into the adjacent compartment . Such lineage-restricting boundaries were first described in the fruitfly Drosophila wing and the milkweed bug Oncopeltus abdomen , using mitotic clones and cuticle markers to trace lineage distributions [1 , 2] . The same phenomenon was then reported for other parts of the fly body and in vertebrates [3–10] . Nevertheless , not all boundaries have been analyzed for lineage restriction at single cell resolution . Compartment boundaries generally coincide with the expression borders of the selector genes that determine the fates of developmental fields . For example , in the fly wing disc , the anterior-posterior ( A/P ) boundary correlates with the border of engrailed ( en ) expression in the posterior compartment , whereas the dorsal-ventral ( D/V ) boundary correlates with the border of apterous ( ap ) expression in the dorsal compartment . The expression domain of the selector genes does not begin as a sharply defined pattern ( e . g . [11] ) , and usually evolves from a weak and fuzzy to a strong and sharply defined pattern through positive and negative regulation with other genes . Mutual repression between two selector genes , either direct or indirect , can force a cell at the expression border to express only one of the two selector genes . However , the cell-autonomous cell fate may result in a rough border of two cell types . A smooth and sharp alignment may require additional mechanisms to coordinate the cells at the expression border . Hence , the expression border and the lineage-restricting boundary are two phenomena characterized by different , though coinciding , processes . Therefore , the relationship between gene expression borders and lineage-restricting boundaries needs to be considered with respect to their temporal progression . We define ‘boundary’ as indicating lineage restriction , ‘compartment boundary’ to indicate absolute lineage restriction , ‘field boundary’ for incomplete lineage restriction , and ‘border’ to refer to expression domains . Three types of mechanisms have been shown to play a role in boundary formation and maintenance . First , differential cell affinities modulated by cadherin interactions are responsible for various boundary formations [12–15] . Second , reduced cell proliferation found at the vertebrate somite and Drosophila D/V boundary can minimize movements resulting from mitosis [16–18] . However , whether reduced cell proliferation or bias in mitosis orientation is important for the maintenance of the boundary is unclear [11 , 19 , 20] . Third , mechanical forces provided by the intracellular cytoskeletal network can sharpen boundaries in both the vertebrate and invertebrate system [11 , 19 , 21–30] . For instance , actomyosin cables are responsible for cell partitioning in Drosophila A/P and D/V boundaries , as well as zebrafish rhombomeric boundaries [19 , 21 , 25 , 26] . Actomyosin cables bind to adherens junctions to form belt-like supracellular structures [31 , 32] . These cables are enriched for cells along the boundary , serving as physical barriers that restrict cells in adjacent compartments from mixing , with or without morphological changes [19 , 25–27] . We used the larval eye-antenna disc ( EAD ) to explore the mechanism of boundary formation in the Drosophila head , with an emphasis on the boundaries in the proximal-distal ( P/D ) axis , i . e . the boundary between the antennal segments . The EAD is a sac-like tissue composed of monolayered epithelial cells covered by peripodial cells . It contributes to the majority of the adult head organs , including compound eyes , antennae , ocelli , maxillary palps and the head cuticle ( Fig 1A ) . These organs abut each other , with smooth and clear boundaries . The antenna is further divided into six segments , A1-A5 and the most distal arista ( Ar ) . Patterning of P/D antennal segments by critical transcription factors is achieved by hedgehog ( hh ) -dependent decapentaplegic ( dpp , in dorsal ) and wingless ( wg , in ventral ) inductions [33] . In the center and marginal antennal disc , which are destined to be the distal and proximal antennal segments , respectively , Distal-less ( Dll ) and homothorax ( hth ) are activated upon high and low levels of Dpp and Wg [33–36] . Cells that coexpress hth and Dll become the A2 to A4 segments [37] . The LIM-homeodomain protein Lim1 , which is regulated by EGFR signaling , specifies the A1 and Ar segments [38–40] . Here , by examining the temporal sequence of Dll and Lim1 gene expressions , lineage restriction , and tissue morphogenesis , we report that the boundary separating the most proximal segment ( Lim1-expressing , A1 ) , from the more distal parts ( Dll-expressing ) of the antenna involves a Notch-dependent downregulation of bantam microRNA and de-repression of Enable ( Ena ) . Strikingly , this pathway produces an epithelial fold that not only acts as a boundary to ensure cells stay within their respective fields , but also reinforces Notch signaling , thereby safeguarding boundary integrity . Thus , our results have uncovered a novel mechanism for the establishment of a field boundary that involves the formation of folded epithelial structures .
The EAD undergoes a series of progressive epithelial folds from the early third instar stage ( e-L3 , S1A Fig ) . EAD cells are cuboidal in the early second instar stage ( e-L2 ) . From the late second instar ( l-L2 ) ( S1B Fig ) , epithelial cells in the antennal and eye fields become columnar , but medial cells remain cuboidal and have a concave morphology in lateral view ( S1B and S1B’ Fig ) . During e-L3 , a ring fold ( hereafter termed the ‘A1 fold’ ) is formed to separate the prospective A1 antennal segment from the distal A2-Ar antennal segments ( S1C Fig ) . Also during e-L3 , an E/C fold that separates the eye and head cuticle partially extends from the lateral to medial regions ( S1C–S1C Fig ) , becoming complete by the late third instar ( l-L3 ) ( S1D–S1D” Fig ) . A fold that separates the most distal arista segment ( Ar , termed the ‘Ar fold’ hereafter ) and the other antennal segments forms during l-L3 ( S1D Fig ) . In the l-L3 antennal disc , the A1 fold correlates with the border separating the Dll and Lim1 expression domains ( Fig 1B ) . Dll is expressed in the A2-Ar segments , whereas Lim1 is specifically expressed in the A1 segment and the head cuticle . In the mid second instar ( m-L2 ) EAD ( Fig 1C , dashed line , 1F ) , before the A1 fold has been formed , Dll and Lim1 expressions are weak and partially overlap ( co-expression ) , exhibiting a fuzzy border due to two to three rows of cells co-expressing Dll and Lim1 . From l-L2 ( Fig 1D and 1G ) to e-L3 ( Fig 1E and 1H ) , levels of Dll and Lim1 gradually increase and become sharply confined . At e-L3 , the border between the Lim1 and Dll expression domains sharpens and the genes are rarely co-expressed ( S2A–S2C Fig ) . The sharp cell-autonomous segregation of Dll and Lim1 expression begins before formation of the A1 fold , suggesting that the epithelial fold is not the cause of segregated the expression . The distal A2-Ar segments specified by the Dll gene correspond to the evolutionarily conserved telopodite in arthropod appendages . Therefore , the A1 fold separates the proximal coxopodite from the distal telopodite . We hypothesize that the folded tissue architecture at the A1 fold may act as a lineage-restricting boundary between the proximal Lim1-dependent coxopodite and the distal Dll-dependent telopodite . Next , we tested whether the A1 fold serves as a lineage-restricting boundary . The classical definition of a compartment boundary in Drosophila depends on cuticular markers ( e . g . yellow ( y ) and multiple wing hair ( mwh ) ) for wing , leg and antenna , or pigmentation ( white , w ) for compound eye . These markers can only be used on adult tissues . No single marker can be used for both eye and other head structures . We used Twin-Spot MARCM ( TSM ) to induce sister clones with different fluorescent proteins [41] . The fluorescent markers allowed analysis of clone distribution covering the entire head structure of both larval and adult stages ( S3 Fig ) . Pairing of the sister clones allowed us to determine if a clone was indeed from a single origin . The TSM clones were induced at indicated time-points , and their distributions were analyzed in l-L3 discs ( S3C–S3F Fig , and Fig 2 ) . TSM clones in wing and antennal discs determined the timing of A/P and D/V boundary formation ( S3C–S3F Fig ) . For example , in the wing disc , clones induced in L2 cross the D/V boundary ( marked by Cut-expressing cells ) but those induced at e-L3 do not , indicating that the D/V boundary is formed at e-L3 and not L2 ( S3C–S3D Fig ) . These results are consistent with previous reports , and validate our TSM clonal analysis for the study of lineage restrictions . We examined the distribution of the TSM clones relative to the A1 fold . All clones at the folds were examined in different focal planes to check whether they crossed or were restricted by the A1 fold . Even clones for which 1–2 cells crossed the A1 fold were counted as having crossed it . Therefore , our clonal analysis is defined by a very sharp border at single cell resolution . When clones were induced at m-L2 , all except one of the TSM clones crossed the A1 fold ( Fig 2A , red arrow; 2E; 2F , 2 . 94% restricted by boundary ) . The frequency of clones that were restricted by the epithelial fold increased when clones were induced at l-L2 ( Fig 2B and 2C , blue arrow; 2E; 2F , 18 . 92% restricted by boundary ) , and they occurred at the A1 fold and the lateral part of the E/C fold ( Fig 2E , blue triangle ) . Most of the clones induced at e-L3 were restricted by the A1 fold ( Fig 2D , blue arrow; 2E; 2F , 85 . 71% restricted by boundary ) , and crossed the Ar fold ( Fig 2E , red cross; the Ar fold forms in m-L3 ) . The E/C boundary was established progressively , laterally to medially ( S1C–S1D Fig , and Fig 2E ) because , at e-L3 , most lateral clones were restricted by this boundary ( 6/7 ) , but the medial clones crossed it ( 2/2 ) . Our TSM clonal analysis showed that the A1 boundary is not an absolute lineage-restricting boundary . Even if we count clones with a single cell crossing as having been restricted by the A1 fold boundary , the frequency of e-L3 clones respecting the it is less than 100% ( 88 . 6% for TSM clones ) . In contrast , clones induced during the first instar ( L1 ) absolutely respected the A/P boundary in wing disc at a single cell resolution ( S3F Fig , marked by Patched , Ptc , 31/31 ) . Since the A1 fold boundary does not fit the classical definition of a compartment boundary , we term it a ‘field boundary’ to differentiate it from a compartment boundary . In summary , lineage restriction at the A1 fold correlates temporally with the formation of the epithelial fold . This supports our hypothesis that the epithelial fold serves as a lineage-restricting boundary . Since the epithelial fold strongly correlated temporally and spatially with the establishment of lineage restriction and the gene expression border , we investigated the process of epithelial fold in the EAD development . Previous studies have shown that apical actomyosin triggers apical constriction to initiate fold [42–44] . Spaghetti-squash ( Sqh ) —a non-muscle myosin regulatory light chain—is a key component of the actomyosin network [45] . Therefore we examined whether the EAD fold arises from apical constriction by live imaging ex vivo-cultured Sqh-GFP from l-L2 EAD ( Fig 3A–3C ) [46] . Based on their dynamics in the apical area , three groups of cells could be distinguished; namely , constant , fluctuating and decreasing cells ( Fig 3B and 3C ) . Cells exhibiting a significant decrease in apical area coverage over the 5-hour period were located primarily along the A1 fold ( Fig 3B and 3C ) . Fluctuating cells in the apical area were scattered close to the A1 fold ( Fig 3B ) . Cells constant within the apical area were located further away from the A1 fold ( Fig 3B and 3C ) . The extent of EAD apical area reduction is similar to that described for embryonic cells in mesoderm formation ( Fig 3D ) [42] . Cell height and volume before ( l-L2 ) and after ( e-L3 ) A1 fold formation were measured from fixed EAD for better Z resolution ( Fig 3E , details in S1 Table ) . For cells in the A1 fold , the heights of the apical domains ( defined by aPKC ) of folded cells were similar to non-folded cells , but the apical volumes were significantly smaller ( 20% those of non-folded cells ) , likely due to constriction of the apical area ( Fig 3C and 3D ) . For the basolateral domains ( defined by FasIII ) of cells in the A1 fold , height and volume were both lower ( by 50% ) than for non-folded cells , but the difference were not as drastic as for apical volumes and dimensions ( Fig 3C–3E ) . Cells surrounding the A1 fold ( i . e . 1 or 2 rows away from the A1 fold ) were slightly taller and larger than folded cells , but these dimensions were still less than those for non-folded cells . Sqh protein is distributed as junctional and medial-apical species in the EAD . Junctional Sqh was present in all cells , whereas medial-apical Sqh was observed in cells undergoing apical constriction ( Fig 3F , arrow , and S1 Movie ) . Medial-apical Sqh accumulated periodically as apical size decreased ( S1 Movie ) , probably through a mechanism similar to that reported to drive cell invagination during mesoderm formation [42 , 43] . In cells at the A1 fold , junctional Sqh was uniformly presented ( Fig 3G , marked by stars ) , unlike the cable-like structure of actomyosin that is enriched at opposing interfaces of cells along the A/P boundary [27] . Mitotic cells were frequently observed in the A1 fold ( Fig 3H , arrow ) , suggesting that lineage restriction at the A1 fold is not likely due to a zone of quiescent cells . We next tested whether actomyosin is responsible for the apical constriction and formation of the A1 fold . Actomyosin is composed of actin , non-muscle myosin II heavy chain ( Zipper , Zip ) , and regulatory light chain ( Spaghetti-squash , Sqh ) . Spaghetti-squash activator ( Sqa ) is a myosin like chain kinase ( MLCK ) -like kinase required for non-muscle myosin activation [47] . Both zip2 and sqaf01512 mutant clones at the A1 and Ar folds showed reduced fold ( S4A–S4C Fig , compare yellow and white arrows ) , while maintaining apical-basal polarity . Larger mutant clones showed apical swelling and/or delamination , as has been previously reported ( S4D Fig ) [48] . We then examined if lineage restriction is affected when epithelial fold is disrupted . Lim1- and Dll-expressing cells are well segregated in the L3 antenna ( Fig 1E ) . In zip2 MARCM and sqaf01512 clones that span the A1 fold , mixing of Dll- and Lim1- expressing cells was observed within the clones ( Fig 4A and 4B , 18/23 in zip2 and 11/15 in sqaf01512 ) and occasionally outside of the clones ( S4E–S4E’ Fig , arrow ) , implying a breakdown of the boundary . zip2 or sqaf01512 clones located exclusively within the A1 or A2-Ar domains did not show altered expression of Lim1 or Dll ( S4F Fig ) , suggesting that cell mixing in these mutant clones was not due to altered cell fates , but to loss of positional restriction . The mislocalized cells were maintained in the epithelial sheet and were not sorted out basally for elimination ( S4G Fig ) . Cleaved caspase 3 in the mutant larval EAD was rarely detected ( S4H Fig ) . Together , these finding imply that the cell mixing phenotype may be observed in adults . It was difficult to observe cell mixing between antennal segments in the adult head . However , adult heads with zip2 or sqaf01512 clones consistently showed mislocalized ommatidia in head cuticle and antennae ( Fig 4C and 4D , highlighted in red ) , and antennal-like tissue at the borders of compound eyes ( Fig 4E ) , indicating a breakdown of the E/C boundary , which is also characterized by an epithelial fold ( Fig 2E ) . We occasionally observed necrotic scar-like cells in zip2 or sqaf01512 adults ( Fig 4F ) , suggesting that some elimination of mutant cells takes place during or after the pupal stage . Knocking down ( KD ) of zip and sqh by hth-GAL4 from the L2 stage , which covers the A1-A3 region in the antennal disc ( Fig 4G ) [36] , revealed disorganization and mixing of Lim1 and Dll cells ( Fig 4H and 4I , frequency of cell mixing in zip KD: 100%; sqh KD: 95 . 5% ) . Again , these mislocalized cells were properly integrated in the epithelial sheet for both zip and sqh knockdown ( S4I–S4J Fig ) . We observed Dll cells in the Lim1 field ( Fig 4I and S4G–S4I Fig ) and Lim1 cells in the Dll field ( Fig 4A , 4B , 4H and S4J Fig ) , so mislocalization between different fields due to disruption of the A1 fold is reciprocal . Collectively , these results support a role for the epithelial fold in acting as a boundary to separate different cells in the EAD . We also tested a number of proteins known to interact with actomyosin and that are involved in boundary formation to clarify their roles in the A1 fold formation . Knockdown by hth-GAL4 of the basal focal adhesion components integrin ( encoded by myospheroid , mys ) and talin ( encoded by rhea ) ( S5A–S5D Fig ) , the Hippo-regulating LIM protein Ajuba ( jub ) ( S5E–S5F Fig ) [49] , and the adherens junction component Echinoid ( ed ) [50] ( S5G–S5H Fig ) did not affect formation of the A1 fold or segregation of Lim1 and Dll cells . These results show that integrin , talin , Ajuba , and Ed are not likely to be involved in A1 boundary formation . However , these mutant cells showed various morphological defects ( e . g . swelling , enlargement or delamination ) to a similar extent as zip2 cells ( compare S4D Fig to S5I–S5L Fig; quantitation in S5M Fig ) . Our results imply that drastic changes in cell shape per se do not affect cell segregation at fold-mediated boundaries . Therefore , the mixing of Dll and Lim1 cells in zip , sqh , and sqa mutants is not due to altered cell size or morphology , but due to disruption of the epithelial fold . To assess the effect of acute blockage of Sqh on the formation of the A1 boundary , we used chromophore-assisted laser inactivation ( CALI ) [27 , 51 , 52] to specifically inactivate Sqh-GFP in ex vivo e-L3 EAD . Indeed , Sqh-GFP inactivation by CALI caused a significant reduction in the extent of epithelial fold in the A1 fold ( Fig 5A–5A’ , compare aPKC and Coracle signals in the boxed regions for CALI and control ) . In contrast , the same CALI treatment on Moe-ABD::GFP did not cause a similar effect ( Fig 5B–5B’ ) , indicating the high specificity of CALI [27 , 53] . Clones expressing RFP were induced at L2 . Cells adjacent to , but not including RFP-labeled clones , were subjected to CALI treatment ( S2 Movie ) . When CALI was applied to the A1 fold ( Fig 5C , yellow boxed region ) , a few cells from an adjacent RFP clone crossed the disrupted A1 fold to the adjacent field ( S2 Movie ) . Cells that crossed the A1 fold still maintained their Dll expression ( yellow arrow in Fig 5C and 5D ) , indicating that cell fate had not changed ( at least for the time span of our observations ) . Due to the EAD curvature , some RFP-labeled cells from the peripodial membrane appeared in several time points that may confuse the observation ( white arrow head in Fig 5C”; cross section in 5F and 5G , ) . Individual cell tracking was performed over time to unambiguously show border crossing ( S2 Movie , overall trajectory in Fig 5E ) . The CALI inactivation of Sqh-GFP only lasted less than 5–6 hours , after which the endogenous Sqh-GFP expression was recovered and the A1 fold was reformed ( S6A Fig , arrow ) . Hence the time window for RFP cell across boundary was less than the first 6 hours post CALI treatment ( Fig 5E , S2 Movie ) . In the EAD ex vivo culture , we also noticed some small nuclei appeared at later time points ( from post CALI 10h ) , probably result from impaired growth and gross morphological changes under ex vivo condition [46] . Indeed , the EAD cultured for more than 12 hours showed notable cellular architectural and morphological alterations , which was not observed at 6h post-CALI time point ( compare S6A–S6B Fig ) . Therefore , the EAD deterioration after long-term culture is unlikely to contribute to border crossing . RFP clones in the EAD without CALI treatment was unable to cross the A1 fold ( S3 Movie ) . We also analyzed the trajectory of RFP clones that crossed ( CALI ) or not crossed ( non-CALI ) the A1 fold ( S6C Fig ) . The orientation and displacement are comparable between crossed and not crossed cells , indicating that CALI treatment did not cause significant side effects and further lead to additional behavior changes . Since Notch ( N ) signaling is involved in the wing D/V boundary , mediated through intercellular actomyosin cables , we checked whether N might also be involved in formation of the A1 fold . N activity , based on anti-Nintra and N reporters E ( spl ) mβ-lacZ and Su ( H ) Gbe-lacZ , showed ring like patterns in l-L2 antenna discs ( Fig 6A , 6C and 6E ) . In e-L3 , N activity was enhanced in the A1 fold ( Fig 6B and 6D ) . We examined in detail the relative timing of segregated expression of Dll , Lim1 and the N ligands , Delta ( Dl ) and Serrate ( Ser ) in l-L2 . Disc sizes in groups 1 , 2 , and 3 ( see material and methods ) were 4835 ± 328 , 6058 ± 231 , and 7065 ± 309μm2 ( mean ± stdev ) , respectively . Dl was mostly expressed in the central region , whereas Ser was expressed at the periphery of discs ( S7A–S7C Fig cross-sections ) . These patterns echo the expressions of Dll and Lim1 during l-L2 , respectively ( Fig 6F ) . Lim1/Dll segregation is apparent in group 1 , whereas segregated expression of Dl/Ser begins later in group 2 and is more pronounced in group 3 ( Fig 6F; S7A’–S7C’ Fig ) . Fringe ( Fng ) is a glycosyltransferase that can modulate the interaction between N and its ligands [54] . Timing of fng-lacZ differential expression correlated with Dl/Ser segregation ( Fig 6F and S7D’–S7F’ Fig ) . We further analyzed expression levels of these proteins in single cells from different groups . The correlation of Dll/Lim1 segregation and Dl/Ser segregation within single cells increased significantly with increasing disc size ( Fig 6G ) . Taken together , these results suggest that sharp segregation of Dll and Lim1 expression precedes the differential expression of Ser , Dl and Fng , and thereby define the localization of N activation . N is activated during e-L3 at the A1 fold , hence we tested whether N signaling is responsible for the epithelial fold formation . An N dominant-negative ( NDN ) mutant was expressed by hth-GAL4 and examined at l-L3 . The A1 fold of this mutant was disrupted with high penetrance ( Fig 7A , arrow , 86% ) and was always accompanied by mixing of Dll and Lim1 cells ( Fig 7A’ ) . NDN clones that did not span the A1 fold presented normal Dll and Lim1 expressions ( Fig 7B–7B’ ) , indicating that reduced N activation did not alter cell fates . The cell morphology of ex vivo-cultured hth>NKD EAD was monitored by Sqh-GFP for more than 5 hours ( Fig 7C–7D , compare to Fig 3B ) . These EAD failed to form the A1 fold . Most antennal cells exhibited a fluctuating apical area ( Fig 7C , blue cells; 7D , quantitation ) , and a few scattered cells underwent apical constriction ( Fig 7C , red cells ) . Since the N ligands Dl and Ser are differentially expressed in the Dll and Lim1 domains , respectively , we generated DlRevF10 SerRX82 double mutant clones so that for any clone spanning the A1 fold , no N ligand could activate Notch . Indeed , in such mutant clones , the A1 fold failed to form ( Fig 7E , compare white and yellow arrows ) . Cells in the NDN clones showed less apical constriction ( Fig 7G ) , and the cell volumes of their apical and basolateral domains were similar to those of non-folded cells ( Fig 7H , compare with Fig 3E ) . These results indicate that N signaling is required for the formation of the A1 fold . In contrast , clonal expression at l-L2 of constitutively-activated N ( Nact , the Notch intracellular domain [55] ) caused ectopic tissue fold when located in a non-fold region ( Fig 7F–7F’ , arrow , 76% ) . The cells at the ectopic fold showed apical constriction and reduced apical and basolateral volumes similar to cells at the A1 fold ( Fig 7G , 7H , and Fig 3E ) . The reduced cell volume in Nact cells is likely due to shrinkage , since the volume of these cells in L3 ( Fig 7H ) is smaller than normal cells in L2 ( Fig 3E ) . Prolonged N activation did not cause further changes in cell volume ( Fig 7H , compare 48h and 72h ) , suggesting that these drastic changes in cell morphology were stable upon N activation . Together , these loss-of-function and gain-of-function results show that N signaling drives the formation of stable tissue folds in the antennal disc . N signaling is important for the establishment of the D/V boundary in wing disc [56 , 57] . There , it represses the micro-RNA bantam , which itself represses its target Enabled ( Ena ) , that is a positive regulator of actin polymerization . By repressing bantam , N enhances Ena expression , thereby establishing the actomyosin cable-based D/V boundary [19] . We assessed endogenous bantam level by RNA in situ hybridization in combination with a N activity reporter , Su ( H ) Gbe-lacZ , and Ena to study their relative expressions in the EAD . The bantam RNA in situ signals recapitulated the patterns reported previously in the wing D/V boundary [19] ( S8A Fig ) . In l-L2 antennal discs , bantam and Ena levels were generally low , with little correlations with Su ( H ) Gbe-lacZ level ( S8C Fig ) . In e-L3 , a relatively lower bantam level was observed in the A1 fold region , whereas Su ( H ) Gbe-lacZ and Ena level were both elevated ( S8D and S8D” Fig arrows ) . bantam-overexpressing clones showed significantly reduced Ena levels and inhibited EAD fold ( Fig 7I ) , as well as mixing of Lim1 and Dll cells ( Fig 7J ) . The bantam-overexpression clones within a single field did not exhibit altered Lim1 and Dll expression , indicating that the cell mixing phenotype was not the result of a changed cell fate ( Fig 7K ) . Concomitant blocking of N signaling ( through NDN ) and a reduction of bantam ( by expressing bantamsponge ) in hth>NDN+bantamsponge mutants rescued the disrupted A1 fold and the lineage mixing phenotype ( Fig 7I and 7K , 23% phenotype , compared to 81% in hth>NDN in Fig 7A ) . The Notch/bantam axis has been shown to regulate cell proliferation and apoptosis [58 , 59] . We further tested if such regulation also exists and may potentially affect A1 fold formation . Mitosis ( phospho-Histone H3 ) and apoptosis ( cleaved caspase 3 , S8E and S8F Fig ) were examined in NDN or bantam overexpression mutants driven by dpp-GAL4 from L2 ( dppL2 ) . Cell proliferation was reduced by about 30% in both mutants , whereas there were no significant changes in apoptosis . In contrast to the nearly complete absence of proliferation reported in the DV boundary of wing disc [17 , 60] , this 30% reduction may not significantly affect the formation of epithelial folds . Our results suggest that N acted through bantam and Ena ( possibly by repressing bantam to allow Ena expression ) to induce actomyosin assembly and thus epithelial constriction and formation of the A1 fold . Even after formation of the A1 fold , N activity is sustained during e-L3 ( Fig 6D ) . We found that blocking epithelial fold , by knock down of zip and sqh in the dpp expression domain that spans the dorsal A1 fold reduced the expression level of the N reporter Su ( H ) Gbe-lacZ ( Fig 8A–8C; 8G , quantitation ) . Interestingly , levels of the same N reporter were not affected in conditions where D/V boundaries were disrupted in wing discs ( Fig 8D–8F; 8G ) . This suggests that N activity is sustained by the epithelial fold , possibly representing positive feedback regulation .
In this study , we tried to unravel the molecular and cellular mechanisms of boundary formation in the Drosophila head . We focused our analysis on the antennal A1 fold that separates the A1 and A2-Ar segments . Our results showed that the expression of the selector genes Lim1 and Dll , which are expressed in A1 and A2-Ar , respectively , was sharply segregated . This step was followed by differential expression of Dl , Ser and Fng , as well as activation of N signaling at the interface between A1 and A2 ( Fig 9 ) . N signaling then induced apical constriction and epithelial fold , possibly through repression of bantam to allow levels of the bantam target Ena to become elevated , with this latter inducing the actomyosin network . The actomyosin-dependent epithelial fold then provided a mechanical force to prevent cell mixing . When N signaling or actomyosin was disrupted , or when bantam was overexpressed , the epithelial fold was disrupted and Dll and Lim1 cells become mixed . Thus we describe a clear temporal and causal sequence of events leading from selector gene expression to the establishment of a lineage-restricting boundary . Sharp segregation of Dll/Lim1 expressions began before formation of the A1 fold , suggesting that fold formation is not the driving force for segregation of Dll/Lim1 expression . Instead , the fold functions to safeguard the segregated lineages from mixing . Whether Dll/Lim1 segregated expression is due to direct or indirect antagonism between the two proteins is not known . Actomyosin-dependent apical constriction is an important mechanism for tissue morphogenesis in diverse developmental processes , e . g . gastrulation in vertebrates , neural closure and Drosophila gastrulation , as well as dorsal closure and formation of the ventral furrow and segmental groove in embryos ( see reviews [61 , 62] ) . Our study describes a new function of actomyosin , i . e . , the formation of lineage-restricting boundaries via apical constriction during development . This actomyosin-dependent epithelial fold provides a mechanism distinctly different from other known types of boundary formation . We found that the cells at the A1 fold still undergo mitosis , suggesting that mitotic quiescence is not involved . Perhaps epithelial fold as a lineage barrier is needed in situations in which mitotic quiescence does not happen . Mechanically and physically , epithelial folds could serve as stronger barriers than intercellular cables when mitotic activity is not suppressed . The drastic and sustained morphological changes , including reduced apical area and cell volume , may be accompanied by increased cortical tension of cells along the A1 fold [63 , 64] , with such high interfacial tension then preventing cell intermingling and ensuring Dll and Lim1 cell segregation [30 , 65] . Although similar to actomyosin boundaries , the epithelial fold in the A1 boundary is distinctly different from the supracellular actomyosin cable structure in fly parasegmental borders , the wing D/V border , and the interrhombomeric boundaries of vertebrates [19 , 25–27] ( see review [66] ) . The adherens junction protein Ed , which is known to promote the formation of supracellular actomyosin cables [50] , is not involved in A1 fold formation ( S5G Fig ) . Although actomyosin is enriched in a ring of cells in the A1 fold , it does not exert a centripetal force to close the ring , unlike the circumferential cable described in dorsal closure and wound healing ( see review [67] ) . In the A1 fold , the constricting cells become smaller in both their apical and basolateral domains , thus differing from ventral furrow cells where cell volume remains constant [68 , 69] . A tissue fold probably provides a strong physical or mechanical barrier to prevent cell mixing . In addition , whereas in a flat tissue where the boundary involves only one to two rows of cells , the tissue fold involves more cells engaging in cell-cell communication . The close apposition of cells within the fold may allow efficient signaling within a small volume [70] . This may be an evolutionarily conserved mechanism for boundary formation that corresponds to stable morphological constrictions such as the joints in the antennae and leg segments ( see below ) . Although N signaling has been reported to be involved in many developmental processes , a role in inducing actomyosin-dependent apical constriction and epithelial fold is a novel described function for N . For the A1 boundary , N activity is possibly mediated through repression of bantam and consequent upregulation of Ena . In the wing D/V boundary , N signaling is also mediated through bantam and Ena , but the outcome is formation of actomyosin cables , i . e . , without apical constriction and epithelial fold [19] . Thus , the N/bantam/Ena pathway for tissue morphological changes is apparently context-dependent . Tissue constriction also occurs later in joint formation of the legs and antennae . N activation also occurs in the joints of the leg disc and is required for joint formation [71–74] . This role is conserved from holometabolous insects like the fruitfly Drosophila melanogaster and the red flour beetle Tribolium castaneum [75] to the hemimetabolous cricket Gryllus bimaculatus [76] . It is possible that for segmented structures that telescope out in the P/D axis , like the antennae , legs , proboscis and genitalia , N signaling is used to demarcate the boundaries between segments , which are characterized by tissue constriction . N-dependent epithelial fold morphogenesis has also been reported in mice cilia body development without affecting cell fate [77] , suggesting that such N-dependent regulation in morphogenesis is evolutionarily-conserved . We propose that N signaling is important in all boundaries that involve stable tissue morphogenesis . For those boundaries corresponding to stable morphological constrictions , e . g . the joints in insect appendages , N acts via actomyosin-mediated epithelial fold . The wing D/V boundary represents a different type of stable tissue morphogenesis . It becomes bent into the wing margin and involves N signaling via actomyosin cables , rather than apical constriction . In contrast , actomyosin-dependent apical constrictions do not involved N signaling and are involved in transient tissue morphogenesis , such as gastrulation in vertebrates , neural closure , Drosophila gastrulation , dorsal closure , as well as formation of the ventral furrow , eye disc morphogenetic furrow , and segmental groove in embryos ( see review [61] ) . N signaling is also involved in the boundary between new bud and the parent body of Hydra , where it is required for sharpening of the gene expression boundary and tissue constriction at the base of the bud [78] . Whether the role of N in these tissue constrictions is due to actomyosin-dependent apical constriction and epithelial fold is not known . Boundaries may be established early in development . As the tissue grows in size through cell divisions and growth , boundary maintenance become essential . We found that N activity is maintained by actomyosin , suggesting feedback regulation to stably maintain the boundary . Mechanical tension generated by actomyosin networks has been suggested to enhance actomyosin assembly in a feedback manner ( see review [79] ) . Interestingly , the N-mediated wing A/P and D/V boundaries , which form actomyosin cables rather than tissue folds , did not exhibit such positive feedback regulation ( Fig 8D–8F ) . Instead , the stability of the Drosophila wing D/V boundary is maintained by a complex gene regulatory network involving N , Wg , N ligands and Cut [80 , 81] . Perhaps this is necessary for a boundary not involving tissue morphogenesis . The segmented appendages of arthropods ( antennae , legs , mouth parts ) are homologous structures of common evolutionary origin ( [82 , 83] ) . Snodgrass ( 1935 ) proposed that the generalized arthropod appendage is composed of a proximal segment called the coxopodite and a distal segment called the telopodite , either of which can further develop into more segments . The coxopodite is believed to be an extension of the body wall , whereas the telopodite represents the true limb , and thus represents an evolutionary addition [84 , 85] . Dll mutants lack all distal segments except for the coxa in legs and the A1 segment in antennae [84 , 86 , 87] . Lineage tracing studies have shown that Dll-expressing cells contributed to all parts of the legs except the coxa [87 , 88] . These results indicate that the leg coxa and antenna A1 segment correspond to the Dll-independent coxopodite , and that Dll is the selector gene for the telopodite . Therefore , the antennal A1 fold is the boundary between the coxopodite and telopodite . We postulate that the same N-mediated epithelial fold mechanism also operates in the coxopodite/telopodite boundary of legs and other appendages .
Flies were cultured in 25°C according to standard procedure unless otherwise noted . w1118 larvae were used for expression pattern analysis . Fly stocks were: sqhAX3; sqh-SqhGFP42 ( Sqh–GFP ) [89] , Moe-ABD::GFP ( also known as sGMCA [53] ) was from Dan Kiehart ( Duke University , North Carolina ) , hth-GAL4 [90] was from Richard Mann ( Columbia University , New York ) , tub-GAL4 [91] was from Tzumin Lee ( Janelia Farm Research Campus , HHMI , Virginia ) , dpp-GAL4c40 . 6 . was from Jessica Treisman ( New York University ) , fng-lacZ [92] , Su ( H ) Gbe-lacZ was from Sarah Bray ( University of Cambridge , UK ) , E ( spl ) mβ-lacZ [93] , UAS-Nact [55] , UAS-NDN [94] , UAS-bantam and UAS-bantamsponge [19] were from Marco Milán ( Institute for Research in Biomedicine , Barcelona ) . UAS-RNAi stocks were from VDRC ( zip: 7819 , sqh: 7916 , mys: 29613 , rhea: 40399 , jub: 38442 , ed: 104279/3087 ) , NIG ( N: 3936-R2 ) , and Bloomington ( N: 7870 , zip: 36727 , sqh: 32439 , mys: 27735 , rhea: 28950 ) . Genotypes for the mutant and MARCM clonal analysis were: hs-FLP1; UAS-rCD2-RFP , UAS-miR-GFP , FRT40A/ UAS-mCD8-GFP , UAS-miR-CD2 , FRT40A; tub-GAL4/+ [41] , hs-FLP; FRT42B , zip2/FRT42B , ubi-GFP , hs-FLP; FRT42B , zip2/FRT42B , tub-GAL80; tub-GAL4/ UAS-GFP [48] , hs-FLP; FRT42D , sqaf01512/FRT42D , ubi-GFP ( DGRC114526 , sqaf01512 is a PiggyBac insertion in sqa [95] ) , hs-FLP; tub-GAL4 , UAS-mCD8GFP/+; FRT82B , DlRevF10 , SerRX82/FRT82B , tub-GAL80 ( Bloomington 6300 ) . Positive labeled clones were induced using hs-FLP122; +; Act5C>CD2>GAL4 , UAS-RFP [96] . Induction of hs-FLP122 was conducted at 38°C for 8 min at 24 or 48h after egg-laying ( AEL ) . For lineage tracing experiments using Twin-Spot MARCM [41] , newly-hatched first instar larvae were collected every two hours from juice plates , and kept in 25°C before heat shock ( 38°C for 10min ) . Larvae were raised under conditions of 25°C except for heat-shock at the indicated stage . Clonal induction was performed at L1 ( AEH 18-20h ) , mL2 ( AEH 26-28h ) , l-L2 ( AEH 38-40h ) , or e-L3 ( AEH 48-50h ) stage . The discs were dissected and examined at l-L3 . We use AEH ( after egg-hatching ) for Twin-spot MARCM , and Dll/Lim1 expression pattern analysis , for which more precise timings are required . AEL ( after egg-laying ) was used for genomic mutant ( zip2 , sqaf01512 , and DlRevF10 , SerRX82 , induced at L1 ) , Ay ( induced at L1/ L2 ) , and tub-GAL80ts experiments . Antibody staining was performed according to a procedure described previously [36] . Primary antibodies from DSHB ( Developmental Studies Hybridoma Bank , University of Iowa ) were mouse-anti-Coracle ( C615 . 16 , 1:20 ) , mouse-anti Cut ( 2B10 , 1:100 ) , mouse-anti-Dl ( C594 . 9B , 1:300 ) , mouse-anti-Dlg ( 4F3 , 1:200 ) , mouse-anti-Ena ( 5G2 , 1: 100 ) , mouse-anti-FasIII ( 7G10 , 1:50 ) , mouse-anti-GFP ( 12A6 , 1:100 ) , mouse-anti-Nintra ( C17 . 9C6 , 1:200 ) , mouse-anti-Ptc ( Apa1 , 1:100 ) . Other primary antibodies included rabbit anti-Lim1 ( 1:400 , from Dr . Juan Botas ) , rat-anti-Serrate ( 1:1000 , preabsorbed , from Dr . Kennith Irvine ) , rabbit anti-aPKC ( C-20 , 1:50 , Santa Cruz ) , rabbit-anti-caspase3 ( cleaved ) ( 1:200 , Cell Signaling ) , goat-anti-Dll ( F-20 ) ( 1:100 , Santa Cruz ) , rabbit-anti-GFP ( 1:1000 , Invitrogen ) , rabbit-anti-β-gal ( 1:5000 , Cappel ) , rabbit-anti-phospho-Histone 3 ( 1:200 , Millipore ) , rat-anti-RFP ( 5F8 ) ( 1:1000 , Chromotek ) , Phalloidin ( F-actin , Alexa 488-/555- or 647-conjugated ) ( 1:100 , Life Technologies ) . Species-matched Alexa 488-/561- or 633-conjugated secondary antibodies were from Jackson ImmunoResearch . Alexa Fluor 405-donkey anti-rabbit was from Abcam ( ab175651 ) . Images were acquired using a Zeiss LSM 780 or 710 with appropriate GaAsP detectors . Objectives were Plan-Apochromat 20x/0 . 8 , Plan-Apochromat 40x/1 . 4 Oil , C-Apochromat 40x/1 . 2W Korr , and Plan-Apochromat 63x/1 . 4 Oil ( Zeiss ) . All the images in this study were oriented dorsal-face up and with the posterior end to the right . Optical sections were oriented with the apical face of the disc proper to the right or top . Images were processed with ZEN ( Zeiss ) with minimal brightness/contrast adjustments . To analyze the pixel intensities of Dll , Lim1 and N related ( Dl , Ser and fng-lacZ ) expression patterns , optical sections of 60μm were manually positioned with the center ( 0 in the X axis ) placed at the fold ( eL3 ) or at the Dll-Lim1 overlapping regions ( L2 ) . Although the larvae were collected at 1 hour intervals , there were still variations in developmental timing . Therefore , more than ten EADs were imaged , and only those of similar size were chosen for further analysis . Disc sizes in groups 1 , 2 , and 3 were , respectively: 4835 ± 328 , 6058 ± 231 , and 7065 ± 309μm2 ( mean ± stdev ) . More than five EADs were quantified and 2–3 optical sections were analyzed per EAD . The signal intensity was established from the histogram analysis module in ZEN ( Zeiss ) and normalized to the basal level in non-expressing cells . The center ( 0 in the X axis ) was manually positioned at the center of the Dll-Lim1 overlapping region . Correlations of ratios between Dll/Lim1 and Delta/Serrate were achieved by individual mean intensities from single cells . The stack images of 16–18μm were projected to ensure coverage of ligands and to identity genes . Cells with Dll-only , Dll+Lim1 , and Lim1-only expressions were collected from the three groups . To establish Su ( H ) Gbe-lacZ levels in sqh and zip knockdown experiments , the pixel intensity of lacZ from optical sections across the A1 fold was quantified using the average pixel intensity of dpp-expressing regions normalized with non dpp-expressing regions in the same discs . Time-lapse imaging to track cell morphology ( Sqh-GFP and Sqh-mCherry ) from l-L2 EAD ex vivo cultures was processed in Imaris software ( Bitplane ) . 3D-projected images from time-lapse stacks were acquired using the surpass mode . A total of 5 hours of stack images were rotated and cropped in 3D to remove the peripodial membrane and basolateral regions . Segmentation of individual cells was carried out using the filament module with minimal manual corrections . The surface module was further applied to the post-filament images to obtain cell sizes and automatic tracking over time . Each cell was pre-processed for its absolute apical area value over time to determine whether it belonged to the constant ( δArea < 10μm2 ) , fluctuating ( δArea ≥ 10μm2 ) , or decreasing ( initial apical area around 20–40μm2 , and final < 10μm2 ) groups . For individual cells ( as indicated by “i” ) , apical areas at each time point ( Ati ) were subtracted from the respective mean area over time ( Aavgi ) before normalization with the respective mean ( ( Ati-Aavgi ) /Aavgi ) to represent the proportional change . Proportional changes of cells in the same group were plotted as total mean and stdev . Trajectories of RFP clones in Sqh-GFP were accessed by spot tracking module in Imaris software ( S2 and S3 Movie ) . The spot detection diameter was set to 1μm ( shown as center point ) , with maximum distance between time points for 2μm . Autoregression motion algorithm were used to track RFP signal over time . 3D surpass time-lapse images were shown in spot center point with trajectory in dragon tail mode ( for 20 time points ) . The overall trajectories of individual cells were presented in color-coded time map . Apical ( aPKC ) and basolateral ( FasIII ) cell volumes were acquired from serial sections of fixed EAD using the Imaris surface module . Individual cell contours along the XY plane were outlined using the autofit module through all stack images , with settings of full accuracy and least impact . Stack contours from single cells were further processed to generate a 3D surface render and to acquire apical and basolateral volumes . For the basolateral domain , pinhole = 0 . 9 μm , optical interval = 0 . 47μm ( total z = 30–40μm ) . For the apical domain , pinhole = 0 . 5 μm; optical interval = 0 . 27 μm ( total z = 4–7μm ) . Data sets were analyzed and plotted in Prism 6 using two-tailed un-paired t tests ( S2C Fig , S6C Fig ) , linear regression analyse ( Fig 6G ) , ANOVA-Tukey’s multiple comparisons ( Fig 7G ) , and ANOVA-Dunnett’s multiple comparisons ( Fig 8G; S5M Fig; S8E and S8F Fig ) . Adult flies were fixed in Bouin’s solution , followed by serial dehydrations in 25% , 50% , 75% , and then 100% ethanol solutions before being transferred to 100% acetone . The samples were further processed by critical-point drying with liquid CO2 , followed by sputter-coating with gold . Images were acquired using an Environmental Scanning Electron Microscope ( FEI Quanta 200 ) . Ex vivo culturing and live imaging of EAD were as described [46] . For l-L2 and e-L3 EAD , the discs were embedded in 0 . 6% and 0 . 75% low gelling agarose , respectively . Sqh-GFP and Moe-ABD::GFP were used as target molecule for CALI . CALI was carried out using an LSM710 inverted confocal microscope ( Zeiss ) with a 488nm laser ( 25mW ) set at 100% of its power for a total of five cycles with 300 iterations per cycle ( 20–25 minutes break between each cycle , total of CALI treatment for 2 . 5 hours ) . The numerical zoom was set to 5 using a 40x objective . The region for CALI treatment was 3μm x 20μm with differential Z adjusted manually each time . Time-lapse images were acquired pre- and post-CALI treatment , with Z-stack set to a mean of 35μm . The time interval between each stack was 6 min as indicated in the S2 Movie . The parameters were: scan speed: 6 arbitrary units; number of scans per frame: 1; scanning: bi-directional; pinhole: 1 . 2μm; objectives: C-Apochromat 40x/1 . 2W Korr ( Zeiss ) . The EAD was dissected in DEPC-PBS , followed by fixation ( 4% PFA and 1% DMSO in PBS ) for 20 min . Samples were washed in PBT ( 0 . 1% Tween20 in PBS ) before proteinase K permeabilization ( 2 μg/mL in digestion buffer for 3 min , digestion buffer: 50 mM Tris-HCl , pH7 . 5 and 50 mM EDTA ) . After proteinase K inactivation ( 0 . 2% of glycine in PBS ) , samples were post-fixed with 4% PFA for 20 min . Samples were prehybridized in hybridization buffer ( HYB: 50% formamide , 5x SSC , 0 . 1% Tween20 , 100 μg/mL denatured salmon DNA , 100 μg/mL yeast tRNA , and 50 μg/mL heparin ) for more than 1 hour at 60°C . The DIG-labeled probe ( stock: 50 ng/μL , dilute stock 1:250 in HYB ) was hybridized overnight at 60°C . After hybridization , samples were washed in 100% HYB , 66% HYB-PBT , 33% HYB-PBT , then PBT at 60°C for 1 hour each , then at room temperature for 4 more washes in PBT ( 5 min each ) . Samples were treated with 3% H2O2 in PBS to reduce endogenous HRP activity . Samples were then blocked in blocking solution ( 2% blocking reagent , 20% normal horse serum in PBT ) for 30 min before overnight incubation with anti-Dig-HRP ( POD Roche 1207–733 , 1:100 dilute in blocking solution ) at 4 oC . TSA amplification ( PerkinElmer , NEL745001KT ) was used to enhance the hybridization signals before protein detection . Protein immunofluorescence was performed after RNA in situ hybridization as described previously [36] , except all steps were conducted in the dark . The 5’- or 3’-DIG-labeled probes for bantam detection and the control sequence were: aatcagctttcaaaatgatctcacttgtatg ( bantam ) , and gtgtaacacgtctatacgccca ( scramble-miR , EXIQON ) . | During development , boundary formation between adjacent developmental fields is important to maintain the integrity of complex organs and tissues . We examined how boundaries become established between adjacent developmental fields—which are defined by expression of distinct selector genes and developmental fates—using the Drosophila eye-antennal disc as a model . We show that boundary formation is a progressive process . We focused our analysis on the antennal A1 fold that separates the A1 and A2-Ar segments , corresponding to the evolutionarily conserved segregation between coxopodite and telopodite segments of arthropod appendages . We describe a clear temporal and causal sequence of events from selector gene expression to establishment of a lineage-restricting boundary . We found that Notch activation at the boundary between adjacent fields of selector gene expression triggers actomyosin-mediated cell apical constriction , which induces the formation of an epithelial fold and prevents intermixing of cells from adjacent fields . Our findings describe a novel mechanism by which epithelial fold provides a physical barrier for cell segregation . | [
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"experimenta... | 2017 | Notch-dependent epithelial fold determines boundary formation between developmental fields in the Drosophila antenna |
Gene regulatory circuits drive the development , physiology , and behavior of organisms from bacteria to humans . The phenotypes or functions of such circuits are embodied in the gene expression patterns they form . Regulatory circuits are typically multifunctional , forming distinct gene expression patterns in different embryonic stages , tissues , or physiological states . Any one circuit with a single function can be realized by many different regulatory genotypes . Multifunctionality presumably constrains this number , but we do not know to what extent . We here exhaustively characterize a genotype space harboring millions of model regulatory circuits and all their possible functions . As a circuit's number of functions increases , the number of genotypes with a given number of functions decreases exponentially but can remain very large for a modest number of functions . However , the sets of circuits that can form any one set of functions becomes increasingly fragmented . As a result , historical contingency becomes widespread in circuits with many functions . Whether a circuit can acquire an additional function in the course of its evolution becomes increasingly dependent on the function it already has . Circuits with many functions also become increasingly brittle and sensitive to mutation . These observations are generic properties of a broad class of circuits and independent of any one circuit genotype or phenotype .
Gene regulatory circuits are at the heart of many fundamental biological processes , ranging from developmental patterning in multicellular organisms [1] to chemotaxis in bacteria [2] . Regulatory circuits are usually multifunctional . This means that they can form different metastable gene expression states under different physiological conditions , in different tissues , or in different stages of embryonic development . The segment polarity network of Drosophila melanogaster offers an example , where the same regulatory circuit affects several developmental processes , including embryonic segmentation and the development of the fly's wing [3] . Similarly , in the vertebrate neural tube , a single circuit is responsible for interpreting a morphogen gradient to produce three spatially distinct ventral progenitor domains [4] . Other notable examples include the bistable competence control circuit of Bacillus subtilis [5] and the lysis-lysogeny switch of bacteriophage lambda [6] . Multifunctional regulatory circuits are also relevant to synthetic biology , where artificial oscillators [7] , toggle switches [8] , and logic gates [9] are engineered to control biological processes . The functions of gene regulatory circuits are embodied in their gene expression patterns . An important property of natural circuits , and a design goal of synthetic circuits , is that these patterns should be robust to perturbations . Such perturbations include nongenetic perturbations , such as stochastic fluctuations in protein concentrations and environmental change . Much attention has focused on understanding [1] , [2] , [4] , [10] , [11] and engineering [12]–[14] circuits that are robust to nongenetic perturbations . Equally important is the robustness of circuit functions to genetic perturbations , such as those caused by point mutation or recombination . Multiple studies have asked what renders biological circuitry robust to such genetic changes [15]–[20] . With few exceptions [21] , [22] , these studies have focused on circuits with one function , embodied in their gene expression pattern . Such monofunctional circuits tend to have several properties . First , many circuits exist that have the same gene expression pattern [17]–[19] , [23]–[28] . Second , these circuits can vary greatly in their robustness [16] , [18] , [29] . And third , they can often be reached from one another via a series of function-preserving mutational events [18] , [19] , [30] . Taken together , these observations suggest that the robustness of the many circuits with a given regulatory function can be tuned via incremental mutational change . Most circuits have multiple functions , but how these observations translate to such multifunctional circuits is largely unknown . In a given space of possible circuits , how many circuits exist that have a given number of k specific functions ( expression patterns ) ? What is the relationship between this number of functions and the robustness of each function ? Do circuits with any combination of functions exist , or are some combinations “prohibited ? ” Pertinent earlier work showed that there are indeed fewer multifunctional circuits than monofunctional circuits [21] , but this investigation had two main limitations . First , it considered circuits so large that the space of circuits and their functions could not be exhaustively explored , and restricted itself to mostly bifunctional circuits . Second , it included only topological circuit variants ( i . e . , who interacts with whom ) , and ignored variations in the signal-integration logic of cis-regulatory regions . These regions encode regulatory programs , which specify the input-output mapping of regulatory signals ( input ) to gene expression pattern ( output ) [31]–[33] . Variations in cis-regulatory regions [34] , such as mutations that change the spacing between transcription factor binding sites [35] , are known to impact circuit function [36] , [37] , and their inclusion in a computational model of regulatory circuits is thus important . Here , we overcome these limitations by focusing on regulatory circuits that are sufficiently small that an entire space of circuits can be exhaustively explored . Specifically , we focus on circuits that comprise only three genes and all possible regulatory interactions between them . Small circuits like this play an important role in some biological processes . Examples include the kaiABC gene cluster in Cyanobacteria , which is responsible for circadian oscillations [38] , the gap gene system in Dropsophila , which is responsible for the interpretation of morphogen gradients during embryogenesis [19] , and the krox-otx-gatae feedback loop in starfish , which is necessary for endoderm specification [39] . Additionally , theoretical studies of small regulatory circuits have provided several general insights into the features of circuit design and function . Examples include biochemical adaptation in feedback loops [40] and response delays in feed-forward loops [41] , among others [16] , [19] , [23] , [42]–[45] . Lastly , there is a substantial body of evidence suggesting that small regulatory circuits form the building blocks of larger regulatory networks [34] , [46]–[48] , further warranting their study . For two reasons , we chose Boolean logic circuits [49] as our modeling framework . First , they allow us not only to vary circuit topology [45] , but also a circuit's all-important signal-integration logic [44] . Second , Boolean circuits have been successful in explaining properties of biological circuits . For example , they have been used to explain the dynamics of gene expression in the segment polarity genes of Drosophila melanogaster [50] , the development of primordial floral organ cells of Arabidopsis thaliana [51] , gene expression cascades after gene knockout in Saccharomyces cerevisiae [52] , and the temporal and spatial expression dynamics of the genes responsible for endomesoderm specification in the sea urchin embryo [53] . We consider a specific gene expression pattern as the function of a circuit like this , because it is this pattern that ultimately drives embryonic pattern formation and physiological processes . Multifunctional circuits are circuits with multiple gene expression patterns , and here we study the constraints that multifunctionality imposes on the robustness and other properties of regulatory circuits . The questions we ask include the following: ( i ) How many circuits have a given number k of functions ? ( ii ) What is the relationship between multifunctionality and robustness to genetic perturbation ? ( iii ) Are some multifunctional circuits more robust than others ? ( iv ) Is it possible to change one multifunctional circuit into another through a series of small genetic changes that do not jeopardize circuit function ?
We consider circuits of genes ( Fig . 1A ) . We choose a compact representation of a circuit's genotype G that allows us to represent both a circuit's signal-integration logic and its architecture by a single binary vector of length ( Fig . 1B ) . Changes to this vector can be caused by mutations in the cis-regulatory regions of DNA . Such mutations may alter the binding affinity of a transcription factor to its binding site , thereby creating or removing a regulatory interaction [34] . Alternatively , they may affect the distance of a transcription factor binding site from the transcription start site , changing its rotational position on the DNA helix . In turn , this may alter the regulatory effect of the transcription factor [54] , and change the downstream gene's signal-integration logic . Lastly , such mutations may change the distance between adjacent transcription factor binding sites , enabling or disabling a functional interaction between proximally bound transcription factors [35] . We note that mutations in G could also be conceptualized as changes in the DNA binding domain of a transcription factor . However , evolutionary evidence from microbes suggest that alterations in the structure and logic of regulatory circuits occurs preferentially via changes in cis-regulatory regions , rather than via changes in the transcription factors that bind these regions [55] . The dynamics of the expression states of a circuit's N genes begin with a prespecified initial state , which represents regulatory influences outside or upstream of the circuit , such as transcription factors that are not part of the circuit but can influence its expression state . The initial state reflects the fact that small circuits are typically embedded in larger regulatory networks [34] , [46]–[48] , which provide the circuit with different regulatory inputs under different environmental or tissue-specific conditions . Through the regulatory interactions specified in the circuit's genotype , the circuit's gene expression state changes from this initial state , until it may reach a stable ( i . e . , fixed-point ) equilibrium state . We consider a circuit's function to be a mapping from an initial expression state to an equilibrium expression state ( Fig . 1C ) . In the main text , we consider only circuit functions that involve fixed point equilibria , but we consider periodic equilibrium states in the Supporting Online Material . A circuit could in principle have as many as functions , as long as the initial expression states are all different from one another , and the equilibrium expression states are all different from one another ( Material and Methods ) . The circuits we study may map multiple initial states to the same equilibrium state , but our definition of function ignores all but one of these initial states . While a definition of function that includes many-to-one mappings between initial and equilibrium states can be biologically sensible , our intent is to investigate specific pairs of inputs ( i . e . , ) and outputs ( i . e . , ) , as is typical for circuits in development and physiology [56]–[58] . We emphasize that a circuit can express its k functions individually , or in various combinations , such that the same circuit could be said to have between one and k functions . For brevity , we refer to a specific set of k functions as a multifunction or a k-function and to circuits that have at least one function as viable . The space of circuits we explore here contains possible genotypes . We exhaustively determine the equilibrium expression states of each genotype for all initial states , thereby providing a complete genotype-to-phenotype ( function ) map . We use this map to partition the space of genotypes into genotype networks [17]–[19] , [21] . A genotype network consists of a single connected set of genotypes ( circuits ) that have identical functions , and where two circuits are connected neighbors if their corresponding genotypes differ by a single element ( Fig . 1D ) . Note that such single mutations may correspond to larger mutational changes in the cis-regulatory regions of DNA . For example , mutations that change the distance between binding sites , or between a binding site and a transcription start site , may involve the addition or deletion of large segments of DNA [26] , [59]–[62] . We first asked how the number of genotypes that have k functions depends on k . Fig . 2 shows that this number decreases exponentially , implying that multifunctionality constrains the number of viable genotypes severely . For instance , increasing k from 1 to 2 decreases the number of viable genotypes by 34%; further increasing k from 2 to 3 leads to an additional 39% decrease . However , there is always at least one genotype with a given number k of functions , for any . In other words , even in these small circuits , multiple genotypes exist that have many functions . Thus far , we have determined the number of genotypes with a given number k of functions , but we did not distinguish between the actual functions that these genotypes can have . For example , there are 64 variants of function , since there are potential initial states and potential equilibrium states ( ) . Analogously , simple combinatorics ( Text S1 ) shows that there are 1204 variants of functions , and the number of variants increases dramatically with greater k , up to a maximum of variants of functions . This is possible because individual functions can occur in different possible combinations in multifunctional circuits ( Material and Methods ) . The solid line in the inset of Fig . 2 indicates how this number of possible different functions scales with k . We next asked whether there exist circuits ( genotypes ) for each of these possible combinations of functions , or whether some multifunctions are prohibited . The open circles in the inset of Fig . 2 show the answer: These circles lie exactly on the solid line that indicates the number of possible combinations of functions for each value of k ( Text S1 ) . This means that no multifunction is prohibited . In other words , even though multifunctionality constrains the number of viable genotypes , there is always at least one genotype with k functions , and in any possible combination . As gene regulatory circuits are often involved in crucial biological processes , their functions should be robust to perturbation . We therefore asked whether the constraints imposed by multifunctionality also impact the robustness of circuits and their functions . In studying robustness , we differentiate between the robustness of a genotype ( circuit ) and the robustness of a k-function . We assess the robustness of a genotype as the proportion of all possible single-mutants that have the same k-function , and the robustness of a k-function as the average robustness of all genotypes with that k-function [17] , [18] , [51] , [63] ( Material and Methods ) . We refer to the collection of genotypes with a given k-function as a genotype set , which may comprise one or more genotype networks . We emphasize that a genotype may be part of several different genotype sets , because genotypes typically have more than one k-function . Fig . 3A shows that the robustness of a k-function decreases approximately linearly as k increases , indicating a trade-off between multifunctionality and robustness . However , some degree of robustness is maintained so long as . For larger k , some functions exist that have zero robustness ( Text S1 ) , that is , none of the circuits with these functions can tolerate a change in their regulatory genotype . The inset of Fig . 3A reveals a similar inverse relationship between the size of a genotype set and the number of functions k , implying that multifunctions become increasingly less “designable” [64] — fewer circuits have them — as k increases ( Text S1 ) . For example , for as few as functions , the genotype set may comprise a single genotype , reducing the corresponding robustness of the k-function to zero . For each value of k , the maximum proportion of genotypes with a given k-function is equal to the square of the maximum proportion of genotypes with a function , explaining the triangular shape of the data in the inset . This triangular shape indicates that the genotype set of a given k-function is always smaller than the union of the k constituent genotypes sets . Additionally , we find that the robustness of a k-function and the size of its genotype set are strongly correlated ( Fig . S1 ) , indicating that the genotypes of larger genotype sets are , on average , more robust than those of smaller genotype sets . This result is not trivial because the structure of a genotype set may change with its size . For example , large genotype sets may comprise many isolated genotypes , or their genotype networks might be structured as long linear chains . In either case , the robustness of a k-function would decrease as the size of its genotype set increased . We have so far focused on the properties of the genotype sets of k-functions , but have not considered the properties of the genotype networks that make up these sets . Therefore , we next asked how genotypic robustness varies across the genotype networks of k-functions . In Figs . 3B–D , we show the distributions of genotypic robustness for representative genotype networks with functions . These distributions highlight the inherent variability in genotypic robustness that is present in the genotype networks of multifunctions , indicating that genotypic robustness is an evolvable property of multifunctional circuits . Indeed , in Fig . S2 , we show the results of random walks on these genotype networks , which confirm that it is almost always possible to increase genotypic robustness through a series of mutational steps that preserve the k-function . In Fig . S3 , we show in which dynamic regimes ( Material and Methods ) the circuits in these same genotype networks lie . We have shown that the genotype set of any k-function is non-empty ( Fig . 2 ) , meaning that there are no “prohibited” k-functions . We now ask how the genotypes with a given k-function are organized in genotype space . More specifically , is it possible to connect any two circuits with the same k-function through a sequence of small genotypic changes where each change in the sequence preserves this k-function ? In other words , are all genotypes with a given k-function part of the same genotype network , or do such genotypes occur on multiple disconnected genotype networks ? Fig . 4 shows the relationship between the number of genotype networks in a genotype set and the number of circuit functions k . For monofunctional circuits ( ) , the genotype set always consists of a single , connected genotype network . This implies that any genotype in the genotype set can be reached from any other via a series of function-preserving mutational events . In contrast , for circuits with functions , the genotype set often fragments into several isolated genotype networks , indicating that some regions of the genotype set cannot be reached from some others without jeopardizing circuit function . The most extreme fragmentation occurs for functions , where some genotype sets break up into more than 20 isolated genotype networks . Fig . S4 provides a schematic illustration of how fragmentation can occur in a k-function's genotype set , despite the fact that the genotype sets of the k constituent monofunctions consist of genotype networks that are themselves connected . Fig . S5 provides a concrete example of fragmentation , depicting one genotype from each of the several genotype networks of a bifunction's genotype set . The proportion of k-functions with genotype sets that comprise a single genotype network is shown in the inset of Fig . 4 . This proportion decreases dramatically as the number of functions increases from to , such that only 16% of genotype sets comprise a single genotype network when . Figs . 4B–D show that the distributions of the number of genotype networks per genotype set are typically left-skewed . This implies that when fragmentation occurs , the genotype set usually fragments into only a few genotype networks . However , the distribution of genotype network sizes across all genotype sets is heavy-tailed and often spans several orders of magnitude ( Fig . S6 ) . This means that the number of genotypes per genotype network is highly variable . We next ask whether the number of genotypes in the genotype set of a k-function can be predicted from the number of genotypes in the genotype sets of the k constituent monofunctions . To address this question , we define the fractional size of a genotype set as the number of genotypes in the set , divided by the number of genotypes in genotype space . We first observe that the maximum fractional size of a genotype set of a k-function is equal to ( Fig . S6 ) , which is the maximum fractional size of a genotype set for monofunctional circuits [44] raised to the kth power . In general , we find that the fractional size of a genotype set of a k-function can be approximated with reasonable accuracy by the product of the fractional sizes of the genotype sets of the k constituent monofunctions , but that the accuracy of this approximation decreases as k increases ( Fig . S7 ) . While these fractional genotype set sizes may be quite small , we note that their absolute sizes are still fairly large , even in the tiny circuits considered here . For example , for functions the maximum genotype set size is 262 , 144 . For functions , the maximum is 32 , 768 . In evolution , a circuit may acquire a new regulatory function while preserving its pre-existing functions . An example is the highly-conserved hedgehog regulatory circuit , which patterns the insect wing blade . In butterflies , this regulatory circuit has acquired a new function . It helps form the wing's eyespots , an antipredatory adaptation that arose after the insect body plan [65] . This example illustrates that a regulatory circuit may acquire additional functions incrementally via gradual genetic change . The order in which the mutations leading to a new function arise and go to fixation can have a profound impact upon the evolution of such phenotypes [66] . In particular , early mutations have the potential to influence the phenotypic effects of later mutations , which can lead to a phenomenon known as historical contingency . We next ask whether it is possible for a circuit to incrementally evolve regulatory functions in any order , or whether this evolutionary process is susceptible to historical contingency . In other words , is it possible that some sequence of genetic changes that lead a circuit to have k functions also preclude it from gaining an additional function ? The genotype space framework allows us to address this question in a systematic way , because it permits us to see contingency as a result of genotype set fragmentation . Specifically , contingency means that , as a result of fragmentation , the genotype network of a new function may become inaccessible from at least one of the genotype networks of a k-function's genotype set . To ask whether this occurs in our model regulatory circuits , we considered all permutations of every k-function . These permutations reflect every possible order in which a circuit may acquire a specific combination of k functions through a sequence of genetic changes . To determine the frequency with which historical contingency occurs , we calculate the number of genotype networks per genotype set , as the k functions are incrementally added . This procedure is outlined in Fig . S4 and detailed in the Material and Methods section . We note that historical contingency is not possible when because all monofunctions comprise genotype sets with a single connected genotype network . Historical contingency is also not possible when , because there is only one genotype that yields this combination ( Fig . 2 ) . In Fig . 5 , we show the relationship between the proportion of k-functions that exhibit historical contingency and the number of functions k . For as few as functions , 43% of all k-functions exhibit historical contingency . This percentage is highest for , where 94% of combinations are contingent . The inset of Fig . 5 shows the proportion of the permutations of a k-function in which genotype set fragmentation may preclude the evolution of the k-function . Again , this proportion is highest for functions . These results highlight an additional constraint of multifunctionality . Not only does the number of genotypes with k functions decrease as k increases , but the dependence upon the temporal order in which these functions evolve tends to increase . In the Supporting Online Material , we repeat the above calculations to show how our results scale to equilibrium expression states with period ( For the sake of computational tractability , we restrict our attention to the case where all equilibrium expression states have the same period P ) . We show that the exponential decrease in the number of circuits with k functions also holds for periodic equilibrium expression states , but that the maximum number of functions per circuit decreases with increasing ( Fig . S8 ) . So long as , it is possible for a circuit to have more than one function . In this case , the inverse relationship between robustness to genetic perturbation and the number of functions k also holds ( Fig . S9 ) . Similarly , the results pertaining to genotype set fragmentation hold so long as ( Fig . S10 ) . Lastly , the results pertaining to historical contingency only hold when . This is because it is not possible for a circuit with an equilibrium expression pattern of period to have more than functions , which is a prerequisite for historical contingency ( Material and Methods ) . Taken together , these additional observations show that the results obtained for fixed-point equilibrium expression states can also apply to periodic equilibrium expression states , so long as is not too large .
We have used a Boolean model of gene regulatory circuits to exhaustively characterize the functions of all possible combinations of circuit topologies and signal-integration functions in three-gene circuits . The most basic question we have addressed is whether multifunctionality is easy or difficult to attain in regulatory circuits . Our results show that while the number of circuits with k functions decreases sharply as k increases , there are generally thousands of circuits with k functions , so long as k is not exceedingly large . Thus , multifunctionality is relatively easy to attain , even in the tiny circuits examined here . It is worth considering how this result might translate to larger circuits . In a related model of gene regulatory circuits with genes , the genotype sets of bifunctions comprised an average of circuits [21] , which is over an order of magnitude more circuits per bifunction than observed here ( Fig . 3 , inset ) . For a greater number of functions k , we expect the number of circuits per k-function to increase as the number of genes N in the regulatory circuit increases . This is because the maximum number of circuits with a given k-function is , which is the total number of circuits with N genes ( ) multiplied by the maximum proportion of circuits per multifunction ( ) . For a given number of functions k , this quotient will increase hyper-exponentially as N increases , indicating a dramatic increase in the maximum number of circuits per k-function . More generally , because the fractional size of a k-function's genotype set can be approximated as the product of the fractional sizes of the genotype sets of its k constituent monofunctions ( Fig . S7 ) and because the total number of circuits increases exponentially with N , our observation that there are many circuits with k functions is expected to scale to larger circuits . The next question we asked is whether there is a tradeoff between the robustness of a k-function and the number of functions k . We found that the robustness of a k-function decreases as k increases . However , some degree of robustness is generally maintained , so long as k is not too large . These observations suggest that the number of circuit functions generally does not impose severe constraints on the evolution of circuit genotypes , unless the number of functions is very large . Our current knowledge of biological circuits is too limited to allow us to count the number of functions per circuit . However , we can ask whether the functional “burden” on biological circuits is very high . If so , we would expect that the genes that form these circuits and their regulatory regions cannot tolerate genetic perturbations , and that they have thus accumulated few or no genetic changes in their evolutionary history . However , this is not the case . The biochemical activities and regulatory regions of circuit genes can diverge extensively without affecting circuit function [55] , [59] , [61] , [67] , and the very different circuit architectures of distantly related species can have identical function [24] , [28] . Further , circuits are highly robust to the experimental perturbation of their architecture , such as the rewiring of regulatory interactions [20] . More indirect evidence comes from the study of genes with multiple functions , identified through gene ontology annotations . The rate of evolution of these genes is significantly but only weakly correlated with the number of known functions [68] . Thus , the functional burden on biological genes and circuits is not sufficiently high to preclude evolutionary change . Previous studies of monofunctional regulatory circuits have revealed broad distributions of circuit robustness to genetic perturbation [16] , [18] , [29] . We therefore asked if this is also the case for multifunctional circuits . We found that circuit robustness was indeed variable , but that the mean and variance of the distributions of circuit robustness decreased as the number of functions k increased . Thus , variation in circuit robustness persists in multifunctional circuits , so long as k is not too large . This provides further evidence that robustness to mutational change may be considered the rule , rather than the exception , in biological networks [1] , [18] , [20] , [29] . However , to make the claim that robustness to genetic perturbation is an evolvable property in multifunctional regulatory circuits requires not only variability in circuit robustness , but also the ability to change one circuit into another via a series of mutations that do not affect any of the circuit's functions . We therefore asked whether it is possible to interconvert any two circuits with the same function via a series of function-preserving mutational changes . We showed that this is always possible for monofunctions , but not necessarily for multifunctions , because these often comprise fragmented genotype sets . Genotype set fragmentation has also been observed at lower levels of biological organization , such as the mapping from RNA sequence to secondary structure [69] . Such fragmentation has two evolutionary implications , as has recently been discussed for RNA phenotypes [70] . First , the mutational robustness of a phenotype ( function ) depends upon which genotype network its sequences inhabit , as we have also shown for regulatory circuits ( Fig . S11 ) . Second , it can lead to historical contingency , where the phenotypic effects of future mutations depend upon the current genetic background . Such contingency indeed occurs in our circuits , because the specific genotype network that a circuit ( genotype ) occupies may be influenced by the temporal order in which a circuit's functions ( phenotypes ) have evolved . This order in turn may affect a circuit's ability to evolve new functions . These observations hinge on the assumption that the space between two ( disconnected ) parts of a fragmented genotype set is not easily traversed . For example , in RNA it is well known that pairs of so-called compensatory mutations can allow transitions between genotype networks [71] , thus alleviating the historical contingency caused by fragmentation . To assess whether an analogous phenomenon might exist for regulatory circuits , we calculated the average distance between all pairs of genotypes on distinct genotype networks for circuits with the same k-function . We found that this distance decreases as the number of functions k increases , indicating an increased proximity between genotype networks ( Fig . S12 ) . However , those pairs of genotypes in any two different genotype networks that had the minimal distance of two mutations never exceeded 1% of all pairs of genotypes on these networks , and was as low as 0 . 03% for functions ( Fig . S12A , inset ) . This means that transitions between genotype networks through few mutations are not usually possible in these model regulatory circuits . Thus , the multiple genotype networks of a genotype set can indeed be considered separate from one another . Using a Boolean model of gene regulatory circuits comes with several caveats that are worth highlighting . First , the mutational distance between certain logical functions may not correspond to their distance in a biological context . For example , the signal-integration logic of a gene can mutate from an OR function to an XOR function by changing only a single bit . In contrast , research in synthetic biology suggests that these logical functions are separated by greater mutational distances . While the OR function can be encoded as a simple two-input circuit [37] , the XOR function has necessitated cascading signals between distinct circuits [37] or cells [72] , [73] , or chemically-induced DNA inversions [74] . In some biological circuits , such as the lac operon in E . coli , it may not be possible to transform an OR function into an XOR function at all [32] . However , experimental investigations of the cis-regulatory codes of synthetic and natural circuits are far from exhaustive , and it is therefore possible that there exist alternative implementations of these logical functions that more closely resemble their Boolean representations [31] . Second , the model makes the simplifying assumptions that gene expression states are binary and that regulatory interactions are static . In biological circuits , gene expression is continuous and regulatory interactions are dynamic , varying in both time and space . Despite these limitations , the assumption of binary expression often provides a reasonable approximation [32] and numerous studies have demonstrated the model's ability to precisely replicate the expression dynamics of biological circuits , even under the assumption of static regulatory interactions [50]–[53] . Third , we assume that gene states are updated synchronously [49] , which is clearly not the case in biological circuitry . Asynchronous updating can affect the transient dynamics of a circuit [75] and its equilibrium expression patterns [76] , and may therefore impact circuit function . This becomes especially problematic when the equilibrium expression pattern is periodic [77] . However , the fixed-point equilibrium expression states of Boolean circuits do not vary between asynchronous and synchronous updating schemes [78] , so we did not consider asynchronous updating . While it is possible that some of our results depend upon this assumption , we stress that this study could not have been performed without it . The exhaustive enumeration of genotype space is not computationally feasible under asynchronous updating because all possible orderings of updates have to be considered for each genotype . Fourth , we did not explicitly consider gene expression noise . While this is an important aspect of genetic regulation [79] , robustness to gene expression noise is correlated with robustness to genetic perturbation in model regulatory circuits [18] . Thus , we used the latter as a proxy for the former . Lastly , we only considered small , three-gene circuits . This allows for the exhaustive enumeration of all possible circuit topologies and signal-integration functions , but limits the direct applicability of our results to similarly sized circuits . However , we expect our results to also apply to larger circuits , as we have discussed . We emphasize that our observations are not derived from one circuit and its functions , but from an enormous circuit space , comprising a class of circuits that capture biological phenomena in diverse organisms .
We consider fully connected Boolean circuits with genes . The binary state of a gene i at time t is a function of the states of all genes at time : ( 1 ) The function maps all of the possible combinations of input expression states to an output expression state . This function represents the gene's signal-integration logic and can be represented as a look-up table ( Fig . 1A ) . The circuit is initialized with an initial expression state and all genes are updated synchronously according to their individual functions f until a steady-state expression pattern is reached . The expression pattern can be a fixed-point ( ) or a cycle ( ) . The update functions f of all N genes can be represented as a single vector of length ( Fig . 1B ) . We measure the equilibrium expression states for all possible vectors for each of the possible initial expression states . In doing so , we not only enumerate all signal-integration functions , but also all circuit topologies . This is because some functions f make a gene independent of one or more of its N regulatory inputs . For example , in Fig . 1A , the regulatory interaction is inactive because for any combination of regulatory inputs , the expression state of gene a is unaffected by the expression state of gene b . Boolean circuits exhibit three dynamic regimes that have been called ordered , critical , and chaotic [49] . The ordered regime is characterized by a general insensitivity to perturbation that results from having few equilibrium states , each with large basins of attraction , whereas the chaotic regime is characterized by extreme sensitivity to perturbation that results from having many equilibrium states with small basins of attraction . The critical regime lies at the interface of these two extremes . Several studies have focused on characterizing the dynamic regimes of biological circuits [80]–[83] and on understanding how these regimes influence circuit dynamics in silico [49] , [84] . The dynamic regime of a circuit can be determined by calculating its sensitivity , where z is the average number of regulators per gene and is the average probability of gene expression per gene ( i . e . , the proportion of the genotype G that is nonzero ) [85] , [86] . The ordered regime corresponds to , the critical regime to , and the chaotic regime to . Since for all circuits considered here , the dynamic regime is determined solely by . The maximum number of functions a circuit can produce is because we require the equilibrium expression states of any multifunction to be unique ( i . e . , ) . We also require that the initial expression states are unique ( i . e . , ) . While the deterministic nature of the model makes this latter requirement superfluous — different equilibrium states require different initial states — we specify it to highlight the fact that each function pertains to a specific input signal , which may differ between environments or tissue-specific conditions . A circuit may produce various combinations of k functions , as shown in Fig . 1 . We note that some combinations of functions are not feasible . As an example , consider a hypothetical combination where , . This combination is not feasible because the equilibrium expression state of is a transient state of . Our usage of the word function differs from existing terminology for describing the mapping of initial to equilibrium states in Boolean circuits . For a given circuit , an attractor is an equilibrium state ( fixed-point or periodic ) that can be reached from at least one initial state . An attractor's basin of attraction is the set of initial states that lead to that attractor . The attractor landscape is the set of all attractors and their basins of attraction . These terms are distinct from our use of the words function and k-function , which are concerned with specific pairs of initial and equilibrium states , because specific initial states provide key inputs to most biological circuits in development and physiology . The only equivalence between terms occurs when . Such a k-function is equivalent to the circuit's attractor landscape , because each of the initial states map onto themselves . In this case , the entire attractor landscape is embodied in the function . We measure the robustness of circuits and of k-functions . The robustness of a circuit is calculated as the proportion of its mutational neighbors that have the same k-function , as follows . First , we remove the entries in the circuit's genotype G that correspond to inactive regulatory interactions . This results in a new vector that may differ from G . Second , we determine the fraction of single mutants of that produce the same multifunction . This is achieved by flipping each bit in , one at a time , and determining whether the resulting genotype has the same k-function . We refer to this measure of circuit robustness as , which is the measure that is used throughout the main body of the text . The robustness of a k-function is calculated as the average robustness of all circuits with that k-function . Alternatively , the robustness of a circuit can be calculated as the connectivity of its genotype G in a genotype network of a k-function , divided by the maximum possible connectivity L . We refer to this measure of circuit robustness as . In Fig . S13 , we show that these two calculations result in measures of k-function robustness that are highly correlated ( Spearmans ) . The fact that the data are always below the identity line indicates that is a more conservative measure of robustness than . To detect whether a combination of k functions may exhibit historical contingency , we consider all permutations of those functions . We define a combination of k functions to be contingent if there exists at least one permutation that violates , and at least one other permutation that satisfies , the following condition: For the functions in the permutation , there exists a such that the number of genotype networks in the genotype set of function is greater than the number of genotype networks in the genotype set of function . For example , in Fig . S4 , the permutation satisfies this condition because the genotype set of comprises two genotype networks while the genotype set of comprises only one genotype network . All other permutations violate this condition . Therefore this combination of k-functions exhibits historical contingency . Since all monofunctions comprise a single , connected genotype network , it is impossible for any bifunction to satisfy the condition above . Thus , in these model regulatory circuits , historical contingency can only occur for . | Many essential biological processes , ranging from embryonic patterning to circadian rhythms , are driven by gene regulatory circuits , which comprise small sets of genes that turn each other on or off to form a distinct pattern of gene expression . Gene regulatory circuits often have multiple functions . This means that they can form different gene expression patterns at different times or in different tissues . We know little about multifunctional gene regulatory circuits . For example , we do not know how multifunctionality constrains the evolution of such circuits , how many circuits exist that have a given number of functions , and whether tradeoffs exist between multifunctionality and the robustness of a circuit to mutation . Because it is not currently possible to answer these questions experimentally , we use a computational model to exhaustively enumerate millions of regulatory circuits and all their possible functions , thereby providing the first comprehensive study of multifunctionality in model regulatory circuits . Our results highlight limits of circuit designability that are relevant to both systems biologists and synthetic biologists . | [
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] | 2013 | Constraint and Contingency in Multifunctional Gene Regulatory Circuits |
The type III receptor tyrosine kinase ( RTK ) KIT plays a crucial role in the transmission of cellular signals through phosphorylation events that are associated with a switching of the protein conformation between inactive and active states . D816V KIT mutation is associated with various pathologies including mastocytosis and cancers . D816V-mutated KIT is constitutively active , and resistant to treatment with the anti-cancer drug Imatinib . To elucidate the activating molecular mechanism of this mutation , we applied a multi-approach procedure combining molecular dynamics ( MD ) simulations , normal modes analysis ( NMA ) and binding site prediction . Multiple 50-ns MD simulations of wild-type KIT and its mutant D816V were recorded using the inactive auto-inhibited structure of the protein , characteristic of type III RTKs . Computed free energy differences enabled us to quantify the impact of D816V on protein stability in the inactive state . We evidenced a local structural alteration of the activation loop ( A-loop ) upon mutation , and a long-range structural re-organization of the juxta-membrane region ( JMR ) followed by a weakening of the interaction network with the kinase domain . A thorough normal mode analysis of several MD conformations led to a plausible molecular rationale to propose that JMR is able to depart its auto-inhibitory position more easily in the mutant than in wild-type KIT and is thus able to promote kinase mutant dimerization without the need for extra-cellular ligand binding . Pocket detection at the surface of NMA-displaced conformations finally revealed that detachment of JMR from the kinase domain in the mutant was sufficient to open an access to the catalytic and substrate binding sites .
Regulation of physiological functions in the cell is mostly governed by phosphorylation – a crucial mechanism in cell signaling – catalyzed by protein kinases [1]–[5] . Stem cell factor ( SCF ) receptor or CD117 , also known as human receptor tyrosine kinase ( RTK ) KIT ( according to the nomenclature defined in [6] ) , belongs to the type III RTK family [7]–[10] . Type III RTKs consist of a glycosylated extra-cellular ligand-binding domain ( ectodomain ) connected to a cytoplasmic region by means of a single transmembrane helix . The cytoplasmic region of KIT is composed of an auto-inhibitory juxta-membrane region ( JMR ) and a protein tyrosine kinase ( PTK ) that is subdivided into proximal and distal lobes separated by an insert sequence of variable length ( 70–100 amino acids ) . In human KIT , the 77-amino acid kinase insert domain ( KID ) possesses phosphorylation sites and provides an interface for the recognition of pivotal signal transduction proteins [11]–[13] . Binding of SCF to KIT leads to receptor dimerization [14] , [15] , intermolecular auto-phosphorylation of specific tyrosine residues [16] and PTK activation [8] , [17] , [18] . The activation process involves a large rearrangement of the activation loop ( A-loop , ∼20–25 residues ) situated in the C-lobe of PTK ( Figures 1a , b ) . Conformational switch of A-loop from an inactive packed position ( Figure 1a ) to an active extended form ( Figure 1b ) releases access for Mg2+-ATP and protein substrate ( s ) to the kinase catalytic site [19] , [20] . The inactive form of A-loop is maintained by JMR , which inserts directly in the domain interface between the N- and C-lobes of PTK ( Figure 1a ) . JMR is composed of four fragments , namely JM-Proximal at the N-extremity ( residues 547–552 ) , the most buried JM-Binder ( residues 553–559 ) , JM-Switch ( residues 560–570 ) and JM-Zipper ( residues 571–581 ) [11] , [21] . Phosphorylation of its primary sites Y568 and Y570 lifts the auto-inhibition ( Figure 1b ) . Active KIT binds to intra-cellular substrates and phosphorylates them , thereby switching on multiple signaling pathways by interacting with enzymes and adaptor proteins [11] , [22] , [23] . For instance , the SCF-KIT interaction is essential for the development of melanocytes , erythrocytes , germ cells , mast cells and interstitial cells of Cajal ( ICCs ) [24]–[27] . The deactivation of tyrosine kinases or their oncogenic activation relates with mutations ( point mutations as well as deletions and gene fusions ) which affect the primary structure of the protein [28] , [29] . A variety of mutations in the gene encoding the proto-oncogene KIT were found in different types of human cancer , in gastrointestinal stromal tumors ( GISTs ) [30] , acute myeloid leukemia ( AML ) [31] , mast cell leukemia ( MCL ) [32] and human germ cell tumors [33] , among others . Mutations inducing tumorigenic effects were identified in the membrane-proximal Ig-like domain D5 , in the auto-inhibitory juxtamembrane region and in the protein tyrosine kinase [34] , [35] . Longley et al . [36] early proposed a classification of KIT gain-of-function mutations according to their structural and functional locations . The JMR mutations , frequently found in GISTs , are considered regulatory as they disrupt the auto-inhibitory mechanism which negatively regulates the activity of the protein [29] , [37] , [38] . The PTK mutations are considered catalytic as they directly affect the configuration of the enzymatic site probably by stabilizing the A-loop extended conformation [39]–[41] . To this category belongs the mutation of D in position 816 ( indicated as a black sphere on Figure 1 a , b ) , most frequently substituted by V , found in most patients with mastocytosis , leukemia and germ cell tumors [42] . D816V is also resistant to Imatinib ( Gleevec™ ) treatment [35] , which has motivated to study its role in KIT activation mechanisms . Biochemical studies of KIT gave insights into the molecular mechanism of the ligand-independent activation of the D816V mutant receptor [43] but whether dimerization is required remains unclear [15] , [44] . Crucial for kinase regulation is the orientation of the highly conserved Asp-Phe-Gly ( D810-F811-G812 ) motif positioned at the N-extremity of A-loop , within the active site ( Figures 1a , b ) . In the inactive state , the DFG triad adopts a “DFG-out” orientation for D810 points out of the ATP-binding pocket , while F811 is oriented toward the site and JMR is bound to PTK; in the active state , a canonical “DFG-in” conformation positions the catalytic D810 in the back of the site for chelation of magnesium while F811 is buried away and A-loop extends toward a completely solvent-exposed JMR . A-loop conformational switch is part of a global movement involving a tilt of the N-lobe towards the C-lobe and the rearrangement of several regions of the receptor such as the glycine-rich P-loop ( residues 596–601 , in yellow ) and C-helix ( residues 631–647 , in lime ) placed in the N-lobe ( Figure 1 ) . The link between the conformational changes of the DFG motif and a set of distinctive structural elements of the kinase core has recently been assessed through evolutionary analysis of PKs [45] . In addition , a surface comparison of PKs crystal structures has highlighted the role of F-helix ( residues 766 to 786 , labeled HF on Figure 1 ) in the C-lobe as a central scaffold for the dynamic assembly of the active kinase form [46] . The structural properties of PTKs were characterized mainly by X-ray analysis . Although crystallographic data yield valuable insights into such structural rearrangements , they represent only average conformation for a given set of crystallization conditions . Alternative experimental techniques , such as NMR spectroscopy , and computational approaches , such as molecular dynamics ( MD ) and normal mode analysis ( NMA ) , provide a way to better understand the structure-dynamics-function relationships at the atomic level and further characterize the alteration of protein structure and internal dynamics induced by cancer mutations [47] . These theoretical methods also enable to describe intermediate conformational states , that can be used to guide the design of specific inhibitors acting as modulators of the enzymatic function by targeting putative allosteric sites [48] , [49] . Recent ( classical or advanced ) molecular dynamics studies have begun to elucidate the molecular mechanisms of conformational transitions of PTKs [50]–[54] and to investigate the thermodynamic and mechanistic catalysts of kinase activation by cancer mutations [55]–[57] . Regarding drug-design oriented perspective , the inclusion of normal mode-based descriptions of protein flexibility was shown to improve the prediction of small molecules binding mode to PKs [58]–[61] . A combination of both methods , MD simulations and NMA ( elastic network ) , was employed very recently to elucidate the inactive-to-active state transition of protein kinase B [62] . Early studies , including from our laboratory , shed light on the molecular mechanism by which the D816V mutation destabilizes A-loop inactive conformation , corresponding to a constitutive phosphotransferase activity [40] , [63] , [64] . This effect was then described in the context of Imatinib-induced resistance [65] , [66] . The structure of KIT D816V mutant has not yet been determined . Nevertheless , recent crystallographic data [67] have suggested that the JMR auto-inhibitory conformation is destabilized in the D816H mutant , advocating a regulatory impact of this catalytic mutation . The mechanistic role of JMR in the initiation of the activation process was described by Zou et al . using classical and targeted MD [68] . The authors found that JMR is likely to detach from PTK before the A-loop conformational switch , due to electrostatic repulsion between the C-lobe and phosphorylated tyrosines in JMR . In this study , we have carried out a detailed analysis of KIT receptor cytoplasmic region structural and dynamic changes related to D816V mutation through extensive description of the protein motions combining MD simulations and NMA . We first applied bioinformatics structural-based tools to accurately assign the secondary structure elements of JMR and A-loop and to characterize the hydrogen bonds stabilizing the active and inactive forms . We then employed homology modeling , MD simulations and free energy calculations to further evaluate the impact of the mutation on the stability of KIT cytoplasmic region auto-inhibited state . We observed both a local structural alteration and long-range structural and recognition effects on A-loop and JMR respectively , induced by the mutation . We then further explored the accessible motions of JMR relative to PTK with NMA and found that JMR is allowed larger amplitude motions in the mutant , promoting its triggering role for the inactive-to-active state transition . Displacements of MD conformations along chosen normal modes combined with pocket detection at the surface of the protein revealed that motions of JMR away from PTK in the mutant lead to the opening of an access to the catalytic and substrate binding sites . Consequently , we reveal D816V-induced alterations of KIT juxta-membrane region structure , dynamics and thermodynamics that were not previously described at an atomic level . We believe that our results may bridge experimental evidence of a regulatory activating role of the mutation and an alternative molecular recognition pattern determining the mutant dimerization .
The crystallographic structures of KIT auto-inhibited inactive and active enzymatic forms ( PDB codes: 1T45 [69] and 1PKG [40] ) were carefully analyzed to correctly assign their secondary structure and characterize their stabilizing interactions ( Figures 1c , d ) . In the inactive state ( Figure 1c ) , JMR adopts a twisted hairpin ( V-shaped ) conformation , with the well-structured elements on the external part . The main predicted structural element is an anti-parallel β-sheet ( β1–β2 ) . The backbone of β1 ( residues 558–561 ) interacts with the backbone of β2 ( residues 569–571 ) and the backbone of β6 ( residues 788–789 ) from the C-lobe of PTK , through strong and multiple H-bonds . A-loop inactive conformation shows a mixed structure composed of two 310-helices ( residues 812–814 and 817–819 ) adhered by a short coil and an anti-parallel β-sheet ( β9–β10 ) stabilized by backbone-backbone H-bonds . In the active state ( Figure 1d ) , JMR forms an extended coil that is fully solvent-exposed . A-loop is also positioned differently compared to the inactive state and displays a distinct secondary structure . Indeed the 810–820 sequence , featuring two helical motifs in the packed state , forms a β9' sheet ( residues 815–816 ) separated from β10' ( residues 823–824 ) by a turn in the extended conformation . The anti-parallel β-sheet β9'–β10' interacts with β6 . This structural-based analysis reveals that JMR and A-loop , two segments of KIT receptor cytoplasmic region capable of large conformational changes , exhibit distinct structural elements in the inactive and active forms of the enzyme , which are stabilized by peculiar hydrogen bonds . These elements are organized in such a way that residues from JMR and A-loop take the part of each other in the two structures interaction networks . The inactive packed conformation of A-loop is stabilized by intra-loop H-bond binding , whereas the active extended form is stabilized by interactions with the other regions of the receptor . Noticeably , JMR and A-loop are the preferred regions of gain-of-function point mutations [11] ( residues encircled in Figures 1c , d ) . The majority of these mutational hot spots participates in the stabilization of either the inactive ( 1T45 ) ( Figure 1c ) or active ( 1PKG ) conformation ( Figure 1d ) . For example , in the inactive form , V559 and V560 of β1 establish H-bonds with I571 of β2 and N787 of β6 , respectively ( Figure 1c ) . D816 serves as a negative capping for the 817–819 helix in 1T45 whereas it is a non-interacting residue of β9' in 1PKG , representing the active conformation ( Figure 1d ) . D820 and N822 interact through their side-chains and participate in the formation of the 820–823 β-turn in the inactive state ( Figure 1c ) . Y823 is involved in intra-loop interactions that stabilize turns in both states . Furthermore , this tyrosine is positioned in the catalytic site and H-bonded either to R787 or to the catalytic residue D792 in 1T45 ( Figure 1c ) , whereas it bridges the anti-parallel β-sheet β10'–β11 by interacting with Y846 in 1PKG ( Figure 1d ) . Its aromatic side chain was shown to be essential for the stabilization of the inactive conformation [70] . Mutation of any of these residues , except for V560 , also confers resistance to Imatinib [35] . This analysis thus highlights the polymorphous structural properties of JMR and A-loop , tolerating mutations which provoke the deregulation of the kinase activity without altering the integrity of its structure . Four 50-ns MD simulations of full-length KIT receptor cytoplasmic region ( CR ) , in wild-type ( WT547-935 , crystallographic ) and D816V-mutated ( MU547-935 , modeled ) forms , were run to explore and compare the protein internal dynamics and energetics . Two additional 50-ns simulations were carried out for KIT domains ( WT567-935 and MU567-935 ) , where residues 547–566 of JMR – disordered in the active structure 1PKG – were removed . Further we shall refer to these different forms of KIT CR as full-length ( 547–935 ) and truncated ( 567–935 ) and we shall identify the two MD simulations of WT547-935 by indices 1 and 2 , and the same for MU547-935 . To analyze the global behavior of the studied systems , the root mean square deviations ( RMSDs ) of the nitrogen and carbon atoms of protein backbone with respect to the initial frame were plotted versus simulation time ( Figure 2a ) . All four trajectories of full-length KIT CR , WT547-935 and MU547-935 , display comparable backbone conformational drifts with RMSD mean values in the range 2 . 35–2 . 77±0 . 33–0 . 54 Å . Corresponding values for the truncated forms tend to be larger and vary much more , mean values of 3 . 39±0 . 74 Å and 3 . 59±1 . 05 Å for WT567-935 and MU567-935 , respectively ( Figure S1a ) . The evolution of RMSD during the course of the MD trajectories indicates a reasonable stability of the systems after a 2-ns relaxation period . Hence , the last 48 ns of each trajectory were considered as productive simulation time for further analyses . To find out which parts of the protein deviate most from the initial template , the RMSDs of backbone atoms were monitored for the N-lobe , C-lobe , A-loop and JMR , separately . The RMSDs of the N-lobe remained stable along all simulations except for simulation 1 of WT547-935 where it increased by 1 . 5 Å after 16 ns ( Figure 2b ) . Also in this simulation , the RMSD of the C-lobe reached a stable level earlier than in the other runs ( Figure 2c ) . The RMSD curves for N- and C-lobes of the truncated forms show comparable profiles to those of the full-length CRs ( Figures S1 , b–c ) . A-loop displays a rather small deviation in both simulations of WT547-935 and in simulation 1 of MU547-935 , with mean values in the range 1 . 26–1 . 43±0 . 25–0 . 35 Å , but the drift increased after 27 ns in simulation 2 of MU547-935 to reach a maximum of 4 . 58 Å ( Figure 2d ) . The deviations of JMR are significantly larger than those of the other regions , with mean values in the range 5 . 26–5 . 90±1 . 07–1 . 65 Å , and their fluctuation profiles are unstable ( Figure 2e ) . The conformational stability of the studied systems was investigated through a convergence analysis of the trajectories [71] . Briefly , a set of reference structures are picked up randomly among the MD conformational ensemble and reference groups are formed , composed of conformations from the two halves of the trajectory ( see Materials and Methods ) . A good convergence quality can be assessed when each reference structure is more or less equally represented in both halves of the trajectory . One defines a lone reference structure as a reference structure that is not represented in one half of the trajectory ( one empty reference group ) ( insert in Table 1 ) . To ensure the robustness of the method , the analysis was run with five different random seeds for the reference structure picking up ( Table 1 ) similarly as we performed early [72] . Lone reference structures were found in almost all runs for the full-length forms , indicating a mean convergence quality for these simulations . The results were much improved for the truncated forms , especially regarding the wild-type . KIT wild-type cytoplasmic domain appears thus less stable in its full-length form than when the JMR is cleaved . The use of a 2 . 5 Å RMSD cutoff led to the identification of more reference structures in WT547-935 trajectories , indicative of a greater conformational diversity , than in MU547-935 trajectories ( Table 1 ) . By contrast , the optimal cutoff for WT567-935 ( r = 3 Å ) was smaller than that of MU567-935 ( r = 3 . 5 Å ) . Consequently the D816V mutation seems to reduce the conformational variability of the full-length form but enhance that of the truncated form . The thermodynamic effect of the activating D816V mutation could be quantified by combining the equilibrium MD simulations with the Molecular Mechanics Generalized Born Surface Area ( MM-GBSA ) analysis [73] of KIT stability changes . Free energies were averaged over 2 , 400 conformations taken at 20-ps time interval along simulations 1 and 2 of WT547-935 and MU547-935 ( Figure 3a ) . Errors on estimates were calculated using the method of Straatsma [74] , useful for evaluating the uncertainty of finite correlated series [75] , [76] . Predicted errors for the entropy components ( TStrans , TSrot , TSvib , TS ) were small in all simulations ( up to 1 . 87 kcal/mol ) , reflecting very good convergence properties . Predicted errors for the enthalpic components ( Eele , Evdw , Eint , Egas , Gsa , Ggb , H ) were larger ( up to 24 . 84 kcal/mol ) . Nevertheless , error compensation occurred between large quantities and the auto-correlation functions suggested good convergence properties for the total enthalpy contribution H in simulation 2 of WT547-935 and simulation 1 of MU547-935 . These two time series were thus retained to illustrate KIT enthalpic , entropic and total energy changes upon mutation on Figure 3a , although one should keep in mind that energy changes between WT547-935 and MU547-935 show the same trend whatever simulations considered . We observed that the D816V mutation induced a significant decrease in the thermodynamic stability of KIT receptor cytoplasmic region autoinhibited inactive state ( Figure 3a , on the right ) . This detrimental energetic effect was mainly due to loss of electrostatic interactions ( Eele ) , whereas favorable van der Waals contributions were gained ( Evdw ) ( Figure 3a , on the left ) . A slight reduction in conformational entropy ( TStot ) was observed . To qualitatively estimate the energetic impact of D816V mutation on KIT active versus inactive states , free energies were computed on the equilibrated inactive and active conformations of KIT truncated CR in wild-type and mutant forms ( Figure S2 , and Materials and Methods ) . We observed that the D816V mutation has a deleterious effect on both inactive and active conformations . However , the decrease in thermodynamic stability is smaller for the active form , so that the free energy difference between inactive and active conformations is reduced in the mutant compared to the wild-type . Our free energy calculations thus indicate a deleterious impact of the D816V mutation on the stability of KIT receptor autoinhibited inactive state and enable to quantitatively relate the associated energy changes . They further suggest that the mutation may modify the energetic balance between inactive and active conformations . This finding is in excellent agreement with the data supporting a regulatory role for the D816V mutation [67] and correlates with similar results obtained for other kinases [55] , [56] . We analyzed the MD conformations in details to investigate the mutational effects of D816V on the internal structure and dynamics of KIT cytoplasmic region and understand what changes induced by this mutation promote the increased exchange rate between inactive and active states experimentally evidenced in [67] . MD snapshots taken at regular time intervals show that the A-loop position is systematically shifted between wild-type and mutated proteins ( Figure 4a ) . For instance the small 817–819 helix , identified in our structural-based analysis of the inactive state is preserved in WT547-935 ( Figure 4a , see in particular 38-ns snapshots ) whereas it is unfolded in MU547-935 . Secondary structure assignments averaged on MD trajectories confirm a 8% loss of helical structure ( 42% total structure loss ) between residues 817 and 819 induced by the mutation ( Figure 4b , right panel ) . This local destabilization results from the replacement of the negative capping D816 by a hydrophobic valine . Indeed H-bonds were recorded between the backbone and side-chain oxygen atoms of D816 and the backbone nitrogen atoms of K818 , N819 and D820 for 22 , 25 and 13% of WT547-935 total 96-ns productive simulation time whereas no H-bond was observed between V816 and residues 815–820 in MU547-935 simulations . Consistently , the computed solvent accessible surface area ( SASA ) of R815 , mutated V816 and I817 were increased by 53 , 31 and 84% in MU547-935 compared to WT547-935 . The 817–819 helix unfolding was also assessed in the truncated form MU567-935 . In addition , the helical contribution for residues 812–814 following the DFG motif is significantly larger ( by 37% ) in MU547-935 ( Figure 4a , see in particular 26-ns snapshots ) compared to WT547-935 . This structural gain is counter-balanced by an equivalent decrease in the contribution of partially organized structure ( turn ) ( Figure 4b , right panel ) . As a result , the proportion of helical/turn structures in this region are nearly identical in MU547-935 , whereas it is displaced to the turn structure in WT547-935 . The remaining part of A-loop ( residues 820–835 ) shows a conserved structure between wild-type and mutated KIT . Consequently , we evidenced that the mutation D816V provokes an important alteration of the local structural organization of A-loop adjacent sequence regions . Apart from this local effect , we noted that the distantly positioned JMR rapidly adopted a well-shaped anti-parallel β-sheet structure in MU547-935 , moving from a position packed to the C-lobe toward an axial position , whereas it retained its non well-ordered structure in WT547-935 ( Figure 4a ) . Effective structural re-organization of residues 568–572 upon mutation can be assessed based on secondary structure assignment performed on the MD trajectories ( Figure 4b , left panel ) . To clarify this observed long-range structural effect , the interaction network between JMR and PTK was characterized by recording H-bonds and hydrophobic contacts in WT547-935 ( Figure 5 , upper panel ) and MU547-935 ( Figure 5 , lower panel ) . To describe in details JMR interaction network , we considered its fragments separately , JM-Proximal ( JM-P ) , JM-Buried ( JM-B ) , JM-Switch ( JM-S ) and JM-Zipper ( JM-Z ) . To visualize the established contacts occupancy , we used a color gradient from red to blue for strong to weak interactions , respectively . Upon mutation , both types of interactions , H-bonds and hydrophobic , vanish between JM-P/JM-B ( residues 550–553 ) and the N-extremity of C-helix ( residues 632–633 ) ( Figure 5 ) . H-bonds between JM-Z ( residues 573–576 ) and C-helix ( residues 640–642 ) ( Figure 5a ) and hydrophobic contacts between JM-P/JM-B ( residues 551–553 ) and both P-loop and A-loop ( Figure 5b ) are weakened in the mutant . Noticeably , in the mutant JM-S also interacts less strongly with the C-lobe , including with β6 . The two primary phosphorylation sites ( JM-S ) apparently swap their role in the interaction network between wild-type and mutated forms . Indeed Y846 in the C-lobe establishes a H-bond either with Y570 ( 46% ) in WT547-935 or with Y568 ( 27% ) in MU547-935 ( Figure 5a ) . Moreover a hydrophobic contact between Y570 and I789 ( β6 ) persistently exists in WT547-935 ( 55% ) , while it is not observed in MU547-935 . Consequently , the long-range effect of the D816V mutation leading to noticeable structural re-organization and shifted position of JMR , is accompanied by an alteration of the interaction network between JMR and PTK . The Cα atomic fluctuations depicted by ellipsoids on the averaged MD conformations ( Figure 5 ) show two highly flexible clusters , with fluctuations between 2 . 4 and 4 . 5 Å corresponding to JM-S and A-loop in both wild-type ( residues 563–567 and 827–829 ) and mutant ( residues 563–567 , 817 , and 825–830 ) . By contrast , JM-Z ( residues 581–582 ) , the loop preceding C-helix ( residues 630–632 ) and the loop preceding G-helix in the C-lobe ( residues 871–873 and 877–878 ) display high flexibility with values above 2 . 4 Å up to 3 . 6 Å in WT547-935 ( Figure 5 , upper panel ) , whereas their fluctuations are much reduced in MU547-935 ( Figure 5 , lower panel ) . To further characterize KIT receptor cytoplasmic region motions in the inactive state , principal component analysis ( PCA ) of the MD trajectories was performed . 26 and 28 PCA modes are sufficient to describe 90% of the total backbone fluctuations of WT547-935 and MU547-935 , respectively . The first three PCA modes cumulative contribution is 56% for the wild-type and 53% for the mutant ( Figure 6a ) . Computed scalar products between the first ten PCA modes from the two proteins indicate that the correspondence is not straightforward between the two ensembles . However , the second principal modes share a high degree of 66% similarity ( Figure 6b ) . Noticeably , mode 2 of WT547-935 bears a significantly larger contribution ( 20% ) than mode 2 of MU547-935 ( 14% ) ( Figure 6a ) , and displays a two-fold higher degree of collectivity k ( see Materials and Methods ) . Indeed , it illustrates atomic motions of JMR coupled to deformations of PTK in the N-lobe – interface with JM-Z and residues 627–633 preceding C-helix , and in the C-lobe – A-loop and residues 868–886 including G-helix ( Figure 6c , left panel ) , whereas mode 2 of MU547-935 describes atomic motions of JMR independent from PTK ( Figure 6c , right panel ) . Consequently , the D816V mutation alters the global dynamics of KIT receptor cytoplasmic region , in particular regarding the participation of JMR in the main motions of the protein . The coupling between JMR and the N-lobe revealed by the PCA in wild-type KIT can be related to the large atomic fluctuations observed in the N-lobe of this form . By contrast in the mutant , no coupling is observed and fluctuations in the N-lobe are much smaller . These findings are also in agreement with the greater conformational variability of the wild-type over the mutant evidenced by the convergence analysis . PCA applied on the MD trajectories of the truncated proteins ( WT567-935 and MU567-935 ) reveals that independent motions of the residues 567–581 of the JMR portion ( JM-Z and part of JM-S ) are dominant in the total backbone fluctuations of the protein , contributing up to 52% and 74% , respectively . Indeed , the reduced JMR is highly solvent-exposed and flexible . It displays larger fluctuations in MU567-935 than in WT567-935 ( Figure S3 ) and thus appears to be responsible for the greater conformational variability of the cleaved mutant over the cleaved wild-type evidenced by the convergence analysis . Noticeably , the A-loop is not further destabilized in these cleaved forms and its positions at the end of the simulations superimpose well between WT547-935 and WT567-935 on the one hand , MU547-935 and MU567-935 on the other hand ( Figure S3 ) . This observation is consistent with a recent biochemical characterization of KIT cytoplasmic domain showing that the cleavage of JMR does not automatically promote inactive-to-active transition of the A-loop [70] . To elucidate the thermodynamic origin of the structural and dynamics changes induced by the mutation in the remote JMR , we evaluated binding free energy changes between the equilibrated conformations of wild-type and mutated KIT ( Figures 3c ) , where no structural re-organization of JMR was yet observed . Single-point MM-GBSA calculations were performed following the thermodynamic cycle shown on top of Figure 3c to estimate the relative attachment of JMR to PTK . We found a global binding free energy change ( ΔΔG ) of −42 . 68 kcal/mol , indicating that JMR is more tightly attached to PTK in the wild-type than in the mutant , due to a largely more favorable ( mainly caused by the vibrational component ) entropy ( Figure 3c , table at the bottom ) . The greater conformational variability displayed by WT547-935 compared to MU547-935 in the simulations may enlighten this entropic effect . Indeed , the penalty endorsed by JMR and PTK upon binding due to reduction of their intrinsic vibrational entropy may be balanced in the wild-type by an emerging cooperativity between the two domains , as suggested by the PCA . By contrast in the mutant , the absence of cooperativity may lead to a larger entropic penalty upon binding . Binding free energy changes computed for the different JMR fragments show a dominant entropic penalty for JM-B and JM-S binding to MU547-935 compared to WT547-935 . The largest energy change is observed for JM-Z – covalently bound to PTK , due to both large enthalpic and entropic penalties in mutated KIT . The smallest energy change is obtained for the solvent-exposed extremity JM-P . Overall , these calculations reveal the thermodynamic determinants responsible for the alteration of JMR structure and dynamics upon mutation and they enable to formulate the hypothesis that JMR is less tightly attached to PTK in the mutant than in the wild-type . To further explore the motions accessible to JMR , all-atom Normal Mode Analysis ( NMA ) was conducted on representative MD conformations . Based on our convergence quality assessment ( Table 1 ) , we retained simulations 1 of WT547-935 and MU547-935 as they displayed the smallest number of lone reference structures . Two sets of four MD conformations – extracted through clustering analysis ( see Materials and Methods ) , were considered , taken at: 4217 , 34238 , 42356 , 49260 ps for WT547-935 and 2531 , 19157 , 30160 , 36987 ps for MU547-935 . These sets enabled to get the best convergence quality and thus were the most representative of the MD conformational ensemble . For comparison , NMA was also performed on the static crystallographic structure 1T45 [69] . The 97 non-zero lowest-frequency modes ( ω<20 cm−1 ) obtained from each NMA were considered , leading to a total of 97 values for the X-ray structure and 388 values for the wild-type and the mutant respectively . On this ensemble , the degrees of collectivity of JMR atomic motions , , were computed , with values ranging from ( only one atom among the total n involved in the motion ) to 1 ( high collectivity ) . The mean value is 0 . 57 for WT547-935 and 0 . 60 for MU547-935 , with 48% and 54% of the values above 0 . 6 respectively ( Figure S4 ) . This indicates that JMR atomic motions illustrated by the normal mode ensemble are overall more collective in the mutant than in the wild-type . For comparison , a significantly lower mean value = 0 . 51 is found for the X-ray structure , underlining the relaxation of the protein in the MD simulations . All calculated normal modes represent a limited ensemble of motions , as several modes significantly overlap . We describe qualitatively some of the modes which exhibit motions of JMR relatively to PTK . Three modes from WT547-935 and three modes from MU547-935 were picked up for their displaying of JM-Z and/or JM-S large displacements ( Figure 7 and Table 2 ) . In WT547-935 , mode 18{42356-ps} shows a collective motion of JMR of especially large amplitude for JM-Z ( Table 2 ) , coupled to a rigid-body motion of C-helix ( Figure 7 , upper left panel ) . In MU547-935 , mode 7{30180-ps} displays an even larger resultant displacement of JM-Z but a rather low ( Table 2 ) , indicative of disparities in the mode atomic components ( Figure 7 , lower left panel ) . Large displacements of JM-S are displayed in modes 21{49260-ps} of WT547-935 and 17{2531-ps} of MU547-935 ( Table 2 ) . JM-S concerted atomic motions are rather coupled to JM-P and the loop preceding C-helix in mode 21{49260-ps} of the wild-type ( Figure 7 , upper right panel ) and to JM-P and G-helix in mode 17{2531-ps} of the mutant ( Figure 7 , lower right panel ) . Modes 29{34238-ps} of WT547-935 and 16{30180-ps} of MU547-935 illustrate combined displacements of JM-Z and JM-S with above 0 . 6 ( Table 2 ) . Concerted JMR atomic motions are oriented toward the back of PTK in mode 29{34238-ps} of the wild-type ( Figure 7 , upper middle panel ) while the arrows representing JMR atomic motions in mode 16{30180-ps} of the mutant point away from PTK and are more numerous ( Figure 7 , lower middle panel ) , corresponding to a very high degree of collectivity ( Table 2 ) . The selected normal modes reveal differences in the motions accessible to JMR in wild-type and mutated KIT . Consistent with the PCA results , the JMR atomic displacements in the wild-type are coupled to deformations in PTK , in particular to motions of C-helix and its preceding loop; in the mutant , the JMR atomic motions are more independent from PTK . In particular , mode 16{30180-ps} represents a possible way-out of JMR from PTK through a highly collective motion . The wild-type and mutated structures were displaced up to 4 Å with a step of 0 . 1 Å along each selected normal mode in both positive and negative directions ( Figure S5 ) . The extreme conformations obtained from the 4-Å displacements of JMR away from PTK enable to produce JMR atomic motions ( Figures 8c–h ) . Based on visual inspection of the modes components , C-helix appears more attached to JMR in wild-type conformations , resulting in deformations of PTK , than in mutated conformations ( Figure 8 ) . Furthermore , some extreme conformations show a coil structure of A-loop in the wild-type and mutant ( Figure 8d , h ) . A close inspection of the surface of wild-type and mutated proteins permitted to identify pockets on the NMA-displaced conformations and on the crystallographic structures 1T45 and 1PKG ( Figure 8a , b ) . According to X-ray data , in the inactive state the extended catalytic region shows two adjacent pockets ( Figure 8a , the areas colored in red and orange ) ; while in the active state , we observed the occurrence of three adjacent pockets form the ATP-binding site and the substrate binding site ( Figure 8b , the areas colored in red , green and purple , respectively ) . These three pockets are also detected in some extreme conformations obtained from the 4-Å displacement in mutant ( Figure 8g and h ) . A more fragmented pocket profile is observed in conformations ( f ) of the mutant and ( e ) of the wild-type , with an additional small pocket ( in olive ) . Consequently , pocket search applied to conformations obtained from NMA reveals that displacing JMR relative to PTK leads to the opening of a “path” to the catalytic site , even though A-loop remains in its inactive state . The access to the catalytic site is particularly facilitated in mutated KIT , whose structure ( g ) displaced along mode 16{30180-ps} displays a “path-of-pockets” very similar to that observed in X-ray structure 1PKG , in terms of volumes and shapes . Consistently , pocket search performed at the surface of the 50-ns MD conformations of WT567-935 and MU567-935 revealed a similar “path-of-pockets” in the mutant truncated CR ( Figure S6 ) . Overall these thorough normal mode analyses suggest that the D816V mutation may promote spontaneous detachment of JMR from PTK and concomitant access release to the substrate and ATP-binding sites , hence reinforcing the triggering role of JMR in the inactive-to-active state transition of the protein .
This study represents a detailed description at the atomic level of the impact of the D816V mutation on KIT cytoplasmic region structure , internal dynamics and thermodynamic stability and contributes to the basic concepts of the activating/deactivating mechanisms of RTKs . Unlike for many other kinases , the activation of type III RTKs such as KIT does not require the phosphorylation of the activation loop [70] . Instead , the primary phosphorylation sites are located in the juxta-membrane region , whose detachment from its auto-inhibitory position is likely to trigger the inactive-to-active state transition , due to repulsive negative charges [68] . Our structural-based bioinformatics analysis of KIT receptor auto-inhibited inactive and active states highlighted the strong polymorphous character of both A-loop and JMR and their crucial stabilizing roles for either conformation . We also found that mutational hot spots located in these two elements of the receptor play important role in the secondary structure stabilization and H-bond patterns of the protein . In particular , residue D816 in A-loop serves as a negative capping for a helical motif in the inactive form whereas it stands within a β-sheet in the active form . Inspired by these preliminary observations , we were interested in characterizing the effect of the mutation on the auto-inhibition mechanism of KIT receptor cytoplasmic region . Hence we chose to explore the conformational space around KIT auto-inhibited inactive state , in wild-type and mutated forms , using multiple 50-ns MD simulations . The striking similarity between wild-type KIT ( 1T45 [69] ) and the mutant D816H ( 3G0F [67] ) suggested that the folding of the protein would be similar in the context of the mutant D816V . In our simulations , A-loop demonstrated high flexibility , consistently with NMR studies [77] . We also evidenced a local structural alteration induced by D816V on A-loop inactive conformation . In particular , we observed unfolding of the small 817–819 310 helix in the mutant . As we pointed out in the introduction , this local effect has been previously characterized [40] , [63] , [64] , [67] . By contrast , the behavior of the juxta-membrane region had not yet been explored in the context of the mutant . Our simulations revealed a long-range structural re-organization of JMR and a conformational drift of JM-Switch segment , from a position packed to the C-lobe to an axial arrangement , in the mutated form . Comparing our data with those obtained during the first third of a targeted MD simulation of the inactive-to-active state transition of wild-type KIT cytoplasmic region [68] ) , we propose that the drift we observed could be the first step towards the ligand-independent activation of D816V mutant . Our recording of the hydrogen bonds and hydrophobic contacts gave a possible justification for this long-range effect , through the weakening of the interaction network between JMR and both N-lobe and C-lobe of PTK upon mutation . Furthermore , quasi-harmonic analysis ( PCA ) of the trajectories and computed free energy changes revealed that the mutation has a deleterious impact on the thermodynamic stability of the inactive state and on the coupling between JMR and catalytic domain . In the literature , differences between homology models of active wild-type KIT receptor kinase domain and the mutant D816V early suggested a strong influence of JMR on the folding of wild-type PTK but not on that of D816V-mutated PTK [64] . Moreover , it was reported recently that mutation in position 816 shifts the conformational equilibrium of the kinase away from the auto-inhibited state toward JMR being released to solvent and disordered [67] . These in silico and in vitro results are in good agreement with the coupling/decoupling balance put in light here between the wild-type and mutated proteins . In an attempt to go beyond crystallographic structures or homology models static view and to get a qualitative insight into the modification of the protein energetic landscape upon mutation , we have conducted normal mode analysis on representative conformations sampled in our MD simulations . This method is inscribed in the same philosophy as consensus normal modes theoretical framework [78] . Including the well equilibrated first hydration shell from MD simulations permitted to obtain modes with good accuracy regarding JMR , which is located at the surface of the protein . Statistics computed on the NMA ensembles revealed more collective motions of JMR in the mutant . On one side , the overlap between different starting points reflects conformation population equilibrium; on the other side , the identification of particular modes for particular conformations relates to the search for a discrete transition path between inactive and active states . In this regard , several modes were chosen that described possible ways-out for JMR to depart from catalytic domain . A pocket search at the surface of the conformations displaced along these modes revealed that JMR accessible displacements relative to mutant PTK were sufficient to open a path of adjacent pockets to the substrate-binding sites . This observation was also confirmed by the MD simulations of the truncated proteins , where JMR was cleaved . Noticeably , proto-oncogenic mutations located downstream of the DFG motif in the A-loop , as is the case of D816V , were identified in at least seven other kinases , including BRAF ( V600 ) and EGFR ( L858/L861 ) [79] . MD studies of EGFR evidenced a deleterious impact of mutation L858R on the thermodynamic stability of the protein inactive state [55] , [79] , the effect described here for KIT mutation D816V . It was also revealed that conformational changes in L858R and L861Q EGFR mutant , taking place in the A-loop and C-helix , may facilitate the inactive-to-active state transition . Regarding BRAF , Xie et al . proposed a mechanism by which mutation V600E mimics the effect of phosphorylation events in the A-loop , thus disrupting the kinase inactive conformation toward the active state [80] . These results match with our observations , according to which KIT mutation D816V favors departure of JMR from PTK , a process that is normally induced by phosphorylation events in the wild-type protein . Another topic can be considered in the discussion: the question of whether dimerization is mandatory for D816V mutant activity . Kanakura et al . proposed that the D814V mutant of murine KIT ( equivalent to D816V mutant of human KIT ) acts as a dimer , the dimerization interface is not located in the ectodomain and the last exerts only negative regulation on the ligand-independent dimerization process [44] . Later , structural studies of KIT ectodomain illustrated this supposed negative regulation by revealing a large conformational change between monomeric and dimeric forms [14] , [15] . Monomeric ectodomains encounter electrostatic repulsion through their domain D4 , maintaining receptors at a minimum distance from each other . Upon SCF binding , domains D4 and D5 twist and form a contacting interface ( Figure 9a ) . Recently , Bougherara et al . showed that D816V mutant was able to induce downstream oncogenic signaling without the need to reach the cell surface [43] . Our results shed new light on these experimental data . Our description of the molecular mechanism by which the activating D816V mutation promotes spontaneous detachment of JMR from PTK , the triggering first step of the enzyme inactive-to-active state transition , may reconcile the views of a functioning dimeric mutant , yet a mutant activated without the need for extra-cellular ligand binding . Indeed , the greater freedom of movement of JMR in the mutant implies an increased longest dimension of KIT cytoplasmic region , suggesting that JMR could act as an arm able to extend from PTK toward other interacting partners such as another KIT kinase monomer ( Figure 9b ) . Under such hypothesis , dimerization and transphosphorylation of KIT kinase would still hold as the activation mechanism of the mutated enzyme . Recent biochemical and structural characterization of RTK dimers has shown a great variety of interfaces [81] . It was suggested that FGFR1 – another receptor tyrosine kinase – ectodomain dimer formation imposes steric constraints that reduce the number of possible interaction modes between kinase domains [82] . As a consequence , loss-of-function mutation located in the interface prevents in vivo activation of the receptor . In a reciprocal manner in KIT , according to the model we propose , the gain-of-function mutation D816V could permit the kinase domains to bypass the repulsion between ectodomains in the absence of ligand , allowing for receptor activation . This study proposes atomic level description of the regulatory impact of the D816V mutation , through local and remote structural/dynamic changes . The conformational exploration of the kinases – particularly the receptor tyrosine kinase KIT - specific inactive states presents an obvious therapeutic interest . Understanding of the regulation/deregulation of kinase activation contributes to the design of novel generation of inhibitors targeting KIT and other structurally or functionally related kinases . As an illustration , the efficiency of Gleevec™ to treat chronic myelogenous leukemia ( CML ) and gastrointestinal stromal tumors ( GIST ) is a consequence of its capacity to bind to and stabilize the inactive form of KIT and its binding preferences are governed by conformational selection [83] . The multi-approach procedure we applied on KIT inactive structure enabled us to postulate a model where the mutated kinase is able to dimerize without the enlisting of the extra-cellular domain . Very recent unpublished data ( Schlessinger , personal communication , 2010 ) suggest that two populations of wild-type KIT dimers coexist in the cell , both showing a symmetric arrangement of the extra-cellular domain but an asymmetric arrangement of the kinase domain . Those data could be used in the future to construct reliable models for the homo ( mutant/mutant ) or hetero ( wild-type/mutant ) dimers of KIT receptor . The extensive NMA study of both wild-type and mutant KIT we conducted and the careful selection of a set of relevant modes could be further exploited to determine a plausible conformational transition pathway between the inactive and active states . The pocket profiles we obtained also encourages us to search for putative allosteric binding sites that could be targeted by small molecules that would trap the enzyme in an active conformation . Compared to orthosteric sites , allosteric sites are less-well conserved and thus ligands acting at allosteric sites have a greater potential to achieve receptor selectivity .
The crystallographic structures representing the auto-inhibited inactive and active states of KIT cytoplasmic region ( PDB entries: 1T45 [69] and 1PKG [40] ) were analyzed using the bioinformatics tools DSSP [84] and Stride [85] . ( i ) The secondary structure elements were assigned with the two algorithms , based either on the inter-molecular H-bonds ( DSSP ) or on both backbone geometry and inter-molecular H-bonds ( Stride ) . ( ii ) Hydrogen bond networks ( interactions D–H•••A , where D is the H-donor atom , A is the H-acceptor atom ) were characterized with HBPLUS 3 . 2 [86] and visualized with PyMOL 1 . 2 [87] and Maestro ( Schrödinger LLC , New York NY ) . The H-bond assignment was made using geometrical criteria [88] , [89] . Free energies were evaluated using the Molecular Mechanism Generalized Born Surface Area ( MMGBSA ) method – implemented in AMBER 10 [73] , [103]–[105] which proposes to express the total free energy of the protein as a sum of contributions ( 1 ) where H is the enthalpy and TS is the configurational entropy of the solute . Egas is the molecular mechanics energy of the solute , obtained by summing the internal energy Eint , the electrostatics interactions Eele and the van-der-Waals contacts Evdw; Ggb is the polar solvation term whose evaluation is based on the continuum generalized Born solvent model; Gsa is the non-polar solvation term , proportional to the solvent accessible surface area ( SASA ) , and was evaluated using the Linear Combinations of Pairwise Overlaps ( LCPO ) method . The translational TStrans , rotational TSrot and vibrational TSvib entropies , were evaluated through normal mode calculations with the NMODE module , using a dielectric constant of , where is the distance between atoms i and j . In principle , considering a two-state model , the calculation of the free energy difference between the wild-type and the mutant inactive-folded and unfolded states would be required to evaluate the protein stability changes . Following the assumption that , in the unfolded state , individual residues may not interact and hence the contributions of all the residues except the one under mutation ( D816V ) are the same in the wild-type and the mutant , we considered that this difference between one-residue contributions should be small compared to the difference between the total energies of the wild-type and mutated folded states . We thus evaluated the thermodynamic stability difference for the inactive state directly from our MD simulations of WT547-935 and MU547-935 , as: ( 2 ) The quantities and were averaged over 2400 snapshots selected at 20-ps intervals along the four 50-ns MD simulations and the protein stability change was then approximated based on the free energy difference . Statistical errors on estimates were calculated from their variance and auto-correlation function using the method of Straatsma [74]: ( 3 ) where var ( G ) is the variance of the estimate , is the correlation length from the relaxation of the autocorrelation , and is the total length of the time series . The relative free energies of active versus inactive equilibrated conformations were also evaluated for wild-type and mutant KIT truncated CR ( single-point calculations ) . The free energy of binding a ligand to a receptor is defined as: ( 4 ) Here we computed the binding free energy of JMR and its fragments , the remaining parts of the protein being considered as the receptor , to get estimates of the different energetic contributions involved in the attachment of JMR to PTK . The binding free energies were evaluated on the equilibrated conformations of WT547-935 and MU547-935 ( single-point calculations ) . The change in JMR ( or its fragments ) relative stability within the protein was then approximated based on the difference between the binding energies and . ( 5 ) Normal mode analyses ( NMA ) were conducted using the DIMB method [106] of the VIBRAN module of CHARMM 35b3 [107] , [108] on ( i ) the crystallographic structure 1T45 [69] , ( ii ) MD conformations from WT547-935 taken at 4217 , 34238 , 42356 , 49260 ps , ( iii ) MD conformations from MU547-935 taken at 2531 , 18157 , 30180 , 36987 ps . The selected MD conformations were found to be the most representative of the trajectories , according to the convergence analysis . The first hydration shell ( <5 Å , 2200 water molecules ) around the MD conformations was kept to help prevent the solvent-exposed regions of the protein from collapsing during the minimization procedure [78] . During initial steepest descent energy minimization of the system , mass-weighted harmonic constraints ( 250 kcal/mol/A2 ) were applied to the starting structure and reduced by a factor of 2 every 1000 minimization steps until they fell below a threshold value of 5 kcal/mol/A2 . The constraints were then removed and the system was minimized by conjugate gradient and adopted-basis Newton-Raphson steps until the RMS energy gradient fell below 10−5 kcal/mol/A . The Cα RMS deviations of the minimized conformations from their initial position were limited to less than 1 Å ( Table S2 ) . Normal modes were computed by diagonalizing the mass-weighted Hessian matrix of the energy-minimized conformations and the 97 non-zero lowest-frequency modes were analyzed . The degree of collectivity of the JMR motions in a given mode l was calculated as [109] , [110]: ( 6 ) where n = 596 is the number of atoms belonging to JMR . The quantity is defined as: ( 7 ) where , and are the components of mode l that correspond to the three degrees of freedom of atom i and such that . The degree of collectivity is comprised between 0 and 1 . A value of indicates that only one atom is involved in the motion while a value close to 1 indicates high collectivity . The resultant displacement , i . e . the norm of the resultant displacement vector , of any fragment of the protein was calculated as: ( 8 ) over the ensemble M of the m atoms belonging to the fragment – 172 for JM-Switch and 181 for JM-Zipper . Displacements along selected normal modes , in both positive and negative directions , were performed with the VMOD facility in CHARMM 35b3 . The range of displacement was set from −4 Å to 4 Å with steps of 0 . 1 Å with respect to the initial conformations extracted from WT547-935 and MU547-935 MD trajectories . Intermediate conformations were obtained using a restraint potential added to the internal standard potential [111] , [112] . Pockets were detected at the surface of the crystallographic structures 1T45 and 1PKG and the 4-Å displaced conformations using fpocket [113] , with the default parameters . This geometry-based algorithm was found to perform best on accurate binding site prediction in a recent large-scale comparison study [114] . Pockets were selected by visual inspection with PyMOL 1 . 2 . | Protein kinases are involved in a huge amount of cellular processes through phosphorylation , a crucial mechanism in cell signaling , and their misregulation often results in disease . The deactivation of protein tyrosine kinases ( PTKs ) or their oncogenic activation arises from mutations which affect the protein primary structure and the configuration of the enzymatic site apparently by stabilizing the activation loop ( A-loop ) extended conformation . Particularly , mutation D816V of receptor tyrosine kinase ( RTK ) KIT , found in patients with pediatric mastocytosis , acute leukemia or germ cell tumors , can be considered as the archetype of mutation inducing a displacement of the population equilibrium toward the active conformation . We present a comprehensive computational study of the activating mechanism ( s ) of this mutation . Our multi-approach in silico procedure evidenced a local alteration of the A-loop structure , and a long-range structural re-organization of the juxta-membrane region ( JMR ) followed by a weakening of the interaction network with the kinase domain . Our results provided a plausible conception of how the observed departure of JMR from kinase domain in the mutant promotes kinase mutant dimerization without requiring extra-cellular ligand binding . The pocket profiles we obtained suggested putative allosteric binding sites that could be targeted by ligands/modulators that trap the mutated enzyme . | [
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] | 2011 | Mutation D816V Alters the Internal Structure and Dynamics of c-KIT Receptor Cytoplasmic Region: Implications for Dimerization and Activation Mechanisms |
We utilized abundant transcriptomic data for the primary classes of brain cancers to study the feasibility of separating all of these diseases simultaneously based on molecular data alone . These signatures were based on a new method reported herein – Identification of Structured Signatures and Classifiers ( ISSAC ) – that resulted in a brain cancer marker panel of 44 unique genes . Many of these genes have established relevance to the brain cancers examined herein , with others having known roles in cancer biology . Analyses on large-scale data from multiple sources must deal with significant challenges associated with heterogeneity between different published studies , for it was observed that the variation among individual studies often had a larger effect on the transcriptome than did phenotype differences , as is typical . For this reason , we restricted ourselves to studying only cases where we had at least two independent studies performed for each phenotype , and also reprocessed all the raw data from the studies using a unified pre-processing pipeline . We found that learning signatures across multiple datasets greatly enhanced reproducibility and accuracy in predictive performance on truly independent validation sets , even when keeping the size of the training set the same . This was most likely due to the meta-signature encompassing more of the heterogeneity across different sources and conditions , while amplifying signal from the repeated global characteristics of the phenotype . When molecular signatures of brain cancers were constructed from all currently available microarray data , 90% phenotype prediction accuracy , or the accuracy of identifying a particular brain cancer from the background of all phenotypes , was found . Looking forward , we discuss our approach in the context of the eventual development of organ-specific molecular signatures from peripheral fluids such as the blood .
One important goal in systems medicine is to develop molecular diagnostics that can accurately and comprehensively report health and disease states of an organ system [1] , [2] . The discovery of organ-level molecular signatures [3] from global biomolecule expression measurements would mark a significant advance toward this goal . In this regard , genome-wide transcriptomic data are readily available , making this a promising source for molecular signatures as well as a good means to study the robustness of signatures across different studies . During the past decade , transcriptomics analyses on clinical patient samples have been widely used to uncover cancer-associated genes [4] and to discover biomarkers for diagnosis , prognosis prediction , or optimal therapy selection [5]–[7] . Recently , RNAs measured in blood have also been used as serum-based molecular fingerprints of neurological disease [8] . While many molecular signature studies have focused on identifying differences between case ( e . g . , cancer ) and control ( e . g . , normal ) , a more clinically relevant and challenging task is the multi-category classification problem . This task pertains especially to identifying signatures for molecular screening and monitoring purposes . Such signatures need to detect and stratify various pathological conditions simultaneously; they must therefore be highly specific for a particular disease as well as tissue of origin . The successful identification of more reliable and efficient molecular signatures will also be critical for the blood-based , organ-specific diagnostics envisioned for the future [9] . Data-driven , hierarchical approaches to multi-category classification have been investigated extensively in machine learning [10] , [11] . The basic idea of these methods is first to construct a classification framework in the form of a hierarchy , so that multi-category classifications can be reformulated into a series of binary decision sets ( i . e . , discriminating one class or group of classes from a second class or group of classes ) . The next step is to identify binary classifiers for all decision points ( i . e . , nodes and/or edges ) of the hierarchy . This principle can be applied directly towards molecular disease classification , wherein all diseases can be organized into a global hierarchy of disease sets , where the diseases in each set share common expression patterns . The sets of binary classifiers can further be aggregated into a classifier marker-panel , which can direct diagnosis of an unlabeled patient sample down the hierarchical structure towards a particular label . Therefore , the cumulative expression patterns constitute “hierarchically-structured” molecular signatures . A significant drawback to the use of molecular signatures derived from high-throughput—particularly transcriptomic—data is limited reproducibility and performance accuracy , which is often observed across independent studies of what are considered the same disease phenotype . This drawback holds true for both binary and multi-category classification problems . The lack of robustness , even for promising results , can be attributed to molecular heterogeneity within tumors or other diseased tissue-samples [12] , [13] , complex disease subtypes , various patient demographics , and/or other biologically relevant factors . Another major issue is batch effects , which arise from differences or inconsistencies in experimental protocols , data quality , data-processing techniques , and laboratory conditions and personnel [14] . A promising method to address some of these limitations in robustness is to accumulate and combine data from many independent studies into large meta-analyses [15] , [16] . This integrated strategy naturally expands sample sizes across diverse sources and conditions and can therefore provide more reliable disease signatures as phenotype-associated signals become stronger relative to noise from batch effects and other sources of variance . In this study , we developed a computational approach called Identification of Structured Signatures And Classifiers ( ISSAC ) to identify molecular signatures that simultaneously distinguish major cancers of the human brain . From an integrated dataset of publicly available gene expression data , ISSAC provides a global diagnostic hierarchy and corresponding structured brain cancer signatures composed of sets of gene-pair classifiers . The signal in the transcriptomics data was sufficient to develop accurate , comprehensive signatures , as long as the training set was sampled from the same population as the validation set ( i . e . , cross validation ) . In contrast , training on one dataset and testing against an independent set ( i . e . , an independent study measured from another lab ) generally failed to reach the same performance due to biological and technical sources of dataset variation . To address this issue , we found that integration of datasets from multiple studies enhanced the disease signal sufficiently to mitigate batch effects and greatly improve independent validation results for brain cancers .
Here , we summarize the overall method of ISSAC into three main steps ( Figure S1 ) ; a detailed algorithm and step-by-step guide are presented in the Materials and Methods section and Text S1 , respectively . First , ISSAC constructs the framework for brain cancer diagnosis ( Figure 3A and Figure S2 ) —a tree-structured hierarchy of all brain phenotypes including ependymoma ( EPN ) , glioblastoma multiforme ( GBM ) , medulloblastoma ( MDL ) , meningioma ( MNG ) , oligodendroglioma ( OLG ) , pilocytic astrocytoma ( PA ) , and normal brain , built using an agglomerative hierarchical clustering algorithm on gene expression training data . The construction of the hierarchy relies on iteratively identifying pairs of phenotype groups based on shared features in gene expression . As shown in Figure 3A , the cumulative set of different phenotypes is partitioned into smaller and more homogeneous subsets , thereby decomposing the multi-class diagnosis problem into more tractable sub-problems of class prediction . Second , ISSAC identifies gene-pair classifiers corresponding to the nodes and edges of the diagnostic hierarchy ( Figures 1 and 2 and Tables 2 and 3 ) . Both types of classifiers are binary , i . e . , attempt to distinguish between two sets of phenotypes . The objective of a node classifier is to distinguish the set of phenotypes associated with the node from all other phenotypes . For example , the classifiers of node 6 in Figure 1 and Table 2 can predict the class label of a particular transcriptome sample as either glioma ( EPN , GBM , OLG , and PA ) or non-glioma ( MNG , MDL , and normal ) . In the case of an edge-based , decision-tree classifier , the objective is to distinguish the two sets of phenotypes associated with the two child nodes , analogous to rules of an ordinary decision tree . In the case of the two genes PRPF40A and PURA in Figure 2 and Table 3 , this classifier determines the label of a sample as either brain cancer or normal phenotype . All classifiers are based on comparing the relative expression values ( i . e . , ranks ) between two genes or several pairs of genes within a gene expression profile ( Figures 1 and 2 and Tables 2 and 3 ) . The chosen pairs are those that best differentiate between the phenotype sets and are based entirely on the reversal of relative expression ( Materials and Methods ) , as previously reported [31] . Briefly , the decision rule by Geman et al . is based on two genes ( e . g . , gene i and gene j ) for distinguishing between two phenotypes ( e . g . , class A and class B ) : If the expression of gene i is greater than that of gene j for a given profile , then the phenotype is classified as class A; otherwise , class B . It has been shown that using such simple decision rules with only a small number of gene pairs can lead to highly accurate supervised classification of human cancers [32] , [33] . We describe the advantages of using relative expression reversals in Text S2 . In addition , we provide a summary of the expression differences between classifier genes i and j in Table S5 . Overall , the collection of node classifiers represent a series of coarse-grained to fine-grained explanations of the hierarchical groupings and are used in diagnosis to screen for phenotype-specific expression patterns ( described below ) . Thus , the hierarchy of binary predictors guides classification of an expression profile in a dynamic coarse-to-fine fashion: a classifier is executed if and only if all of its ancestor classifiers have been executed and have returned a positive response—i . e . , predicted the phenotypes in each node . The cumulative outcome of the node classifiers for a given expression profile is the set of its candidate phenotypes , corresponding to all the leaves of the hierarchy that were reached and tested positively . This property means that it is possible to traverse multiple paths to multiple leaf nodes , and thus multiple diagnoses may be made in this step ( though in practice it is usually just one ) . For tie-breaking purposes , the decision-tree classifiers at the edges of the diagnostic hierarchy are used to reach a unique diagnosis . Finally , ISSAC uses the gene-pair classifiers for class prediction ( Figure 3B ) . Given a transcriptome sample , ISSAC executes the node classifiers in a hierarchical , top-down fashion within the disease diagnostic hierarchy to identify the phenotype ( s ) whose class-specific signature ( s ) is present . As shown in Figure 3B , transcriptome samples 4–7 all have expression signatures of at least one class , i . e . , a sample is classified ( positive ) as at least one terminal node ( leaf ) phenotype . In contrast , samples 1–3 do not have any class-specific signatures , i . e . , samples are not positive for any leaf , and are labeled as “Unclassified” . In case of multiple class candidates , i . e . , node classifiers for multiple leaves are positive as in samples 6 and 7 , the ambiguity is resolved by aggregating all the decision-tree classifiers into a classification decision-tree , thereby leading any expression signature down one unique path toward a single phenotype . Once the hierarchy and classifiers were determined , ISSAC distinguished brain cancer phenotypes with an accuracy of 90% in ten-fold cross-validation ( discussed below ) . When the individual transcriptomic samples used in the training set were re-examined , ISSAC correctly observed all samples with an apparent ( resubstitution ) accuracy of 94% . This gives a sense for the relatively small degree of over-fitting compared to the cross-validation accuracy estimate . To estimate the robustness of signature accuracy , it is best to test molecular signatures against datasets ( i . e . , patient samples ) that are truly independent of the training set ( e . g . , drawn from a different patient population , clinical laboratory , etc . ) . To study the effects of training across multiple studies , we used glioblastoma ( GBM ) , where we had the highest number of transcriptomic datasets for the phenotype . We trained ISSAC on each of the five transcriptomic datasets ( i . e . , GSE # ) of GBM , coupled in each case to all the data from the other brain phenotypes . The full multi-class signatures were completely relearned ( every step ) with the only difference in each case being which single GBM dataset was included in the training stage . We then assessed the accuracy of correctly classifying GBM transcriptomes measured in the four held-out datasets from all other possible phenotypes . We term this evaluation method as “hold-one-lab-in validation” . The overall hold-one-lab-in validation performance , or the average of all classification accuracies in Figure 3a , was 38% . This shows that , in general , individual datasets do not consistently yield robust molecular signatures . For example , GBM signatures from GSE8692 ( 6 samples , ref . 21 ) and GSE9171 ( 13 samples , ref . 22 ) led to average accuracies of 22% and 0% for classifying independent GBM samples from other studies , respectively . These significantly low performance results are not surprising for these sets given the very small sample numbers . To an extent , relatively larger datasets could indeed yield disease signatures of higher average accuracy . However , sample size was not the sole determining factor of signature performance . For example , training on GSE4412 ( 59 samples , ref . 19 ) gave an average accuracy of 23% ( Figure 4a ) on the remaining GBM samples from the other studies . As a notable exception , training on GSE4271 ( 76 samples , ref . 20 ) alone resulted in the best overall average accuracy ( 87% ) in correctly classifying samples from the four held-out GBM datasets , with individual validation set accuracies ranging from 78% to 100% ( Table S6 ) . However , when GSE4290 ( 77 samples , ref . 23 ) was used as the training set , there was over a 30% lower average GBM classification accuracy ( 56% ) despite the nearly identical sample size with GSE4271 . We found considerable discrepancy between the minimum and maximum validation set accuracies for training sets GSE4412 ( 0% and 83% , respectively ) and GSE4290 ( 17% and 92% ) ( Table S6 ) . This indicates that batch effects , as well as potential biological discrepancies between populations studied at different sites , can lead to remarkable variation among transcriptomic datasets of supposedly the same phenotype . This “dataset variation” is widespread in large-scale expression studies , causing inconsistencies in molecular signature identification and performance reproducibility [34] . Large variation within and across transcriptomic datasets of GBM is perhaps not surprising , given that GBM is known to have various molecular subtypes [35] . Therefore , as mentioned above , molecular signatures from any single dataset need to be approached with caution in terms of their generalization . We next analyzed how the multi-study integration approach affects performance robustness . One of each of the five datasets of GBM was sequentially withheld as the validation set , while all remaining gene expression data ( including those from all other phenotypes ) were used for training . The GBM signature was then evaluated on the held-out validation set . We term this strategy as “leave-one-lab-out validation” . Classification accuracies using this approach ranged from 63% ( GBM training set: 155 samples across four datasets; validation set: GSE4271 , 76 samples ) to 100% ( GBM training set: 225 samples across four datasets; validation set: GSE8692 , 6 samples ) ( Figure 4b ) . The average accuracy of the five leave-one-lab-out validations was 83% , which was considerably higher than that obtained from training on individual GBM datasets ( 38% ) . We conjecture that this result is due to the underlying variation in the training sets better representing the true variation in the population , both by achieving a greater sample size , as well as by having the samples come from a broader range of situations . To evaluate how multi-study dataset integration alone affects performance robustness independent of sample size , we performed hold-one-lab-in and leave-one-lab-out validations for the studies with the largest number of samples , GSE4412 , GSE4271 , and GSE4290 ( 59 , 76 , and 77 samples , respectively ) while training on the same number of samples for GBM . More specifically , the same steps in the analyses of Figure 4a and Figure 4b were used , while GBM signatures were learned from a training set of exactly 50 samples chosen randomly from either an individual dataset or across four combined datasets ( with the fifth data set left out for validation ) . This process was conducted ten times for each GBM training set . The average performances of hold-one-lab-in and leave-one-lab-out validations were 47% and 70% , respectively . Overall , the results were consistent with our two aforementioned conclusions: 1 ) when a molecular signature is learned from an individual dataset , its ability to accurately and precisely represent phenotype features across a broad population highly varies depending on the particular dataset used for training ( Figure 4c and Table S7 ) ; and 2 ) combining datasets considerably increased average accuracy ( Figure 4d and Table S7 ) . Thus , dataset integration across multiple studies , even without change in sample size , can lead to significant improvements in predictive performance . Lastly , we used the results in Figure 4c and Figure 4d to compare performances of different GBM signatures on the same validation set ( Figure 4e ) . In all cases , signatures from combined datasets had , on average , higher classification accuracy than those from any of the individual datasets—even though the same number of samples was used in the training sets and were tested on a validation set independent of the training set . These results were then used to evaluate the precision of a GBM signature's classification accuracy by calculating its “signal-to-noise ratio ( SNR ) ” . SNR in the accuracy estimate was calculated herein as the ratio of average classification accuracy to standard deviation in the accuracy estimate across studies . We found that , for all validation set cases , GBM signatures developed on the basis of multiple datasets had SNRs greater by at least two fold than those from individual data sets . This clearly shows that learning on integrated datasets leads to molecular signatures that have higher and more consistent ( i . e . less variable ) predictive performance ( Figure 4f ) , and motivated our choice in developing the brain cancer ISSAC signature to only use cases where we had at least 2 independent studies to learn across . Overall , we have shown that when a broader range of conditions within a particular phenotype is presented during the classifier-learning stage , ISSAC can better distinguish the true disease signal from noise prior to independent validation . However , single and/or smaller training sets that were used to define the classifiers might not be representative of , or generalizable to , larger populations – leading to poor validation results . Therefore , the utilization of all currently available datasets from various sources and conditions may be a promising approach to finding novel diagnostic markers , and eventually bringing the successful adaptation of genomic biomarkers into clinical practice . Also , prospective design of studies is generally best when they utilize multiple sites to avoid over-fitting to particular contexts . It is worth mentioning that in some cases , molecular signatures from a single source can have ( or at least appear to have ) superior performance , as demonstrated by the molecular signatures from GSE4271 . Specifically , training on a single GSE4271 data set provided higher accuracy ( 87% , Figure 4a ) than learning on any of the four sets combined ( average 83% , Figure 4b ) . Indeed , when such surprisingly robust single datasets are identified , they potentiate significant new insight into the underlying heterogeneities present in a patient population of a disease phenotype . Such data sets can be utilized for follow-up studies , and hence serve as a valuable resource to the scientific and medical communities . It is , however , difficult in practice to predict in advance data set robustness , which must be ensured through careful sample collection and data set preprocessing techniques . To help ensure the production of reliable omics-based data sets , we recommend the following: 1 ) Good experimental design , such as clearly defining clinical phenotypes of interest; 2 ) When collecting new experimental data , sufficient sample size must be obtained; 3 ) All aspects of the experimental and analytical procedures must be carefully controlled to avoid batch effects; and 4 ) No confounding from factors unrelated to phenotype ( s ) of interest must occur . As shown by our leave-one-lab-out validations , learning signatures across multiple datasets significantly improved average classification accuracy with concomitant reduction in performance variance . In this regard , the brain cancer marker-panel obtained using all currently available microarray data simultaneously ( Tables 2 and 3 ) should represent more robust phenotype signatures . The classification performance of this comprehensive brain cancer marker-panel was evaluated by ten-fold cross-validation ( Figure S3 ) . Our marker-panel achieved a 90% average of phenotype-specific classification accuracies ( Table 4 ) , showing strong promise against a multi-category , multi-dataset background at the gene expression level . In addition , we observed higher classification accuracy ( 93% ) among the expression profiles for which a unique diagnosis was obtained without subsequent disambiguation from the decision-tree ( Table S8 ) . Furthermore , the glioblastoma ( GBM ) classification accuracy previously seen in our leave-one-lab-out analysis ( 83% ) is comparable to that seen in cross-validation ( 85% ) . Indeed , that these two accuracies are so close suggests that , for GBM , the effects of variability among the datasets from different institutions and time-points have been mostly overcome by integration across multiple training studies . Four other brain cancers ( ependymoma , medulloblastoma , meningioma , and pilocytic astrocytoma ) have estimated accuracies of at least 91% , suggesting clear differences between them and the other phenotypes at the transcriptomic level . The anatomical region specificity of these four cancers may have contributed toward their highly accurate separation , as there are regional areas of unique gene expression patterns . Roth et al . analyzed gene expression of 20 anatomically distinct regions of the central nervous system [30] and clustered all anatomical sites into distinct groups , providing evidence of region-specific expression patterns . However , results from another study analyzing gene expression data from distinct brain regions suggested that clustering disparities might also be due to activity of distinct brain cell types , rather than solely on region [36] , [37] . Furthermore , if region specificity played a dominant role in classification , we would expect to see a high number of misdiagnoses to occur between the normal brain , which was derived from 25 different locations ( Text S3 ) , and the six cancers . Such a trend was not observed in Table 4 . Therefore , our predictive results suggest a stronger contribution from underlying cell-type specific and disease-intrinsic elements than from region effects alone . Compared to the cross-validation accuracies of other phenotypes , lower performance was observed for GBM and oligodendroglioma ( OLG ) ( 85% and 75% , respectively ) . This could have been mainly a consequence of the limited ability of the marker-panel to correctly differentiate these two cancers from each other . Indeed , the distinction of these two phenotypes from transcriptomics seems to be rather difficult in general , and our accuracies here are comparable to those reported previously in two-phenotype comparison studies [38] , [39] . Furthermore , our signatures did show an excellent degree of sensitivity ( 96% ) and specificity ( 97% ) for distinguishing these two well-progressed gliomas as a set from all other brain phenotypes . There exist genetic tests and methods that differentiate GBM and OLG well , such as the combined loss of chromosome arms 1p and 19q [40] , and over-expression of the transcription factor protein Olig2 [41] , but our goal in this particular study was to evaluate molecular discriminatory power as represented in transcriptomes across multiple brain cancers . Several genes in our marker panel are strongly associated with brain cancers , suggesting putative relationships to the underlying pathophysiology of their corresponding phenotypes . One such gene is NRCAM ( nodes 4 and 5 of Figure 1 and Table 2 ) , which was reported as a marker for high-risk neuroblastoma [42] and poor prognostic ependymoma [43] . NRCAM was also found to be over-expressed in cell lines derived from pilocytic astrocytomas and glioblastoma multiforme tumors [44] . The receptor tyrosine kinase DDR1 , a predicted marker gene for PA when expressed higher than TIA1 and MAB21L1 ( nodes 6 and 7 ) , was found to be over-expressed in high-grade gliomas and to promote tumor cell invasion [45] . FLNA was detected in the serum of high-grade astrocytoma ( grade 3 and GBM ) patients [46] , and ANXA1 , a gene that encodes an anti-inflammatory phospholipid binding protein , was implicated in astrocytoma progression [47] . These reports are consistent with our identification of FLNA and ANXA1 as two classifier genes expressed higher in GBM than in oligodendroglioma ( nodes 12 and 13 ) . The basic helix-loop-helix ( bHLH ) transcription factor OLIG2 is innately expressed in oligodendrocytes and was recently characterized as a key antagonist of p53 function in neural stem cells and malignant gliomas [48] . In accordance with lower expression of OLIG2 as an EPN classifier in this study ( node 8 ) , OLIG2 expression was used as a negative marker to differentiate EPN from other gliomas [49] . SEMA3E , one of several classifier genes for PA ( node 11 ) , has been reported to drive invasiveness of melanoma cells in mice [50] . And finally , mutation to IDH2 ( node 4 ) in GBM is well known , with occurrence reported in 80% of secondary glioblastomas [51] , [52] . That the genes in our marker panel have previously confirmed ties to brain cancers raises the question of what is the underlying molecular framework surrounding the generation of gene-pair classifiers , which would be an interesting direction for future studies . Among the gene pairs in our marker panel , we focus on two pairs ( below ) in which the genes' common functional roles or relevance to cancer suggest putative relationships to corresponding pathology . Our discussions below point to potential biological relationships underlying the observed gene expression reversals , representing hypotheses that require further experimental validation . One of the classifier gene pairs involved in the differentiation between meningioma and the remaining five brain cancers ( EPN , GBM , MDL , OLG , PA ) are two metabolic enzymes , IDH2 and GMDS ( node 4 ) . IDH2 converts isocitrate to α-ketoglutarate within the TCA cycle . This reaction produces NADPH , which not only is an essential cofactor for many metabolic reactions , but also helps to protect the cell against oxidative damage [53] . Moreover , GMDS aids the biosynthesis of GDP-fucose from GDP-mannose in mannose metabolism , in which NADPH is produced [54] . That the enzymatic activities of both IDH2 and GMDS participate in the conversion between NADP+ and NADPH is interesting , considering the well-known alteration to cellular metabolism and deregulated redox balance in cancer [55] . Possible MNG-specific mutations in IDH2 and/or GMDS , or changes in the regulatory network that controls the expression of these two genes , may affect cellular redox balance and functions of other metabolic enzymes . The TLE4 and OLIG2 gene pair is used to differentiate EPN from GBM , OLG , and PA ( node 8 ) . TLE4 , a human homolog of the Drosophila Groucho protein , represses the Wnt and FGF developmental signaling pathways [56]–[58] by recruiting deacetylases to histones H3 and H4 [59] . FGF receptor signaling was reported to control neuronal and glial cell development by regulating OLIG2 expression in zebrafish [58] . This connection between these two genes in regards to brain cell development could be reflective of the extent of cell-type differentiation ( a hallmark of cancer ) , or lack thereof , unique to EPN compared with the other gliomas . To develop further hypotheses of the functional relationships between the classifiers and pathophysiological traits , we looked for statistical enrichment of biological properties ( e . g . biological processes , chromosome numbers ) on an exhaustive list of gene pairs discriminating GBM and OLG ( Text S4 ) . Our statistical enrichment of biological processes of gene-set i and gene-set j ( the union of genes in each gene-pair classifier that are expressed relatively higher and lower in GBM , respectively ) showed that the genes reflect disease properties . Specifically , the genes that are in gene-set i , or those expressed higher in GBM compared to OLG , were the most enriched in the biological process of ‘Immunity and Defense’ ( Figure S4 ) ; this is in concordance with clinical observations showing high degree of inflammation inside malignant tumors ( such as GBM ) , as well as the subsequent high number of immune cells . Our additional reports on the statistical enrichment of certain chromosome numbers link our classifiers to known genomic aberrations of their respective brain cancers , providing further insight as to why certain genes might have been selected as classifiers . The work reported herein has focused on identifying a structured molecular signature that can separate major brain cancers simultaneously , as well as on evaluating issues related to reproducibility in molecular signatures . However , our long-term motivation for wanting molecular signatures of an organ system is ultimately to find corresponding signatures in the blood , where they can be assayed non-invasively . Blood bathes virtually all organs , which secrete proteins and nucleic acids . Subsets of these secreted biomolecules can potentially constitute disease signatures for molecular diagnostics , as measurement technologies mature . Moreover , the blood is easily accessible in contrast to biopsies of diseased organs for obtaining transcript or protein profiles . In this regard , the brain represents an organ system where a critical need exists to develop non-invasive techniques to monitor its health state through secreted proteins . Previously , organ-specific proteins have been detected in blood; when these proteins changed in concentration or chemical structure , the tissue origin of this change was identified [60] . For blood-based , organ-specific diagnostics , molecular signatures need to detect and stratify various possible cancers and other pathological conditions simultaneously . In the context of this current study , an intriguing question is if training ISSAC on shed or secreted blood borne biomolecule measurements identifies molecular signatures that allow us to distinguish health from disease; and if diseased , which one and how far has it progressed ? Thus , the approach laid out herein for transcriptomics is a foundation for identifying similar signatures from blood proteins as these measurements become more abundant . As proof of concept and to provide candidates for targeted proteomics analysis , we performed the above transcriptomic analysis of finding brain cancer signatures using only the genes that are annotated to encode extracellular proteins ( Materials and Methods ) . We trained ISSAC on a total of 767 genes that matched this criterion , which led to a new brain cancer marker-panel composed of 41 gene-pair classifiers from 71 unique features ( Figure S5 ) . When looking at the case of GBM gene-pair classifiers , i . e . 59 node-based genes involved in the detection of either GBM or phenotype groups that include GBM , 11 were previously identified as potential GBM-specific serum markers ( detected either from GBM cell-line secretome experiments or in human plasma ) : APOD [61] , CALU [62] , CD163 [63] , [64] , CHI3L1 [65]–[67] , CSF1 [68] , [69] , EGFR [68] , [70] , [71] , IGFBP2 [62] , [72]–[75] , NID1 [76] , PDGFC [77] , [78] , PSG9 [72] , and PTN [79] . We provide the functional roles of these genes in Table S9 . None of these previous studies performed relative abundance comparisons or measured expression ratios , so we are unable to answer at this time whether the particular relative expression reversal patterns would be observed in serum . We were not able to find any direct available evidence associating the remaining GBM classifier genes to potential serum-based markers . Nevertheless , we were encouraged that ISSAC was able to verify some previously identified potential GBM markers , which provides support for its use towards a blood-based test since there is currently no clinically approved GBM-specific , serum-based biomarker . Our marker-panel , composed entirely of genes encoding extracellular products , obtained an average classification accuracy of 87% in 10-fold cross-validation ( Table S10 ) , which compares favorably to the average accuracy we previously achieved using all the genes in the microarray ( 90% ) . This suggests that strong signal may possibly persist for phenotype distinction even when using only secreted biomolecules from diseased organs . If indeed there are enough biomolecules secreted into the blood at concentrations that can be accurately and consistently detected by e . g . , targeted mass spectrometry , then there is the very exciting possibility that organ-specific pathologies , such as those described above , can be detected from the blood . This would truly make blood a powerful window into health and disease .
All transcriptomic data used in our analysis are publicly available at the NCBI Gene Expression Omnibus ( GEO ) . We integrated 921 microarray samples of six brain cancers ( ependymoma , glioblastoma multiforme , medulloblastoma , meningioma , oligodendroglioma , pilocytic astrocytoma ) and normal brain across 16 independent studies into a transcriptome multi-study dataset . Importantly , we obtained the raw data ( . CEL files ) from each of these studies and preprocessed them uniformly using identical techniques to greatly reduce extraneous sources of technical artifacts ( discussed below ) . All data manipulation and numerical calculations were performed using MATLAB ( MathWorks ) . To ensure data quality and to help control for systemic bias and batch effects ) , we used the following strict criteria and reasoning for brain phenotype selection: 1 ) Expression profiles must have been conducted on either the Affymetrix Human Genome U133A or U133 Plus 2 . 0 microarray platform . This allowed maximum microarray sample collection without considerable reduction in number of overlapping classifier features ( i . e . , microarray probe-sets ) . 2 ) Transcriptomic datasets ( i . e . , GSE # ) for each phenotype must have been collected from at least two independent sources to help mitigate batch effects . 3 ) All datasets must have consisted of no fewer than 5 microarray samples . 4 ) All datasets must have originated from primary brain tumor or tissue biopsies . Expression profiles from cell-lines or laser micro-dissections were not used in our study to better ensure sample consistency . 5 ) Raw microarray intensity data ( . CEL files ) must have been available on GEO for consensus preprocessing ( described below ) . 6 ) Sample preparation protocols must have been fully disclosed on GEO . 7 ) All microarray samples in a dataset of a given phenotype were used in order to take into consideration all sources of heterogeneity . That is , no samples were excluded because their gene expression profiles were abnormal for their associated phenotypes . We are aware that this may allow mislabeled samples , e . g . samples that were originally misclassified by the histopathologist upon class labeling ( Text S5 ) , to be used in the classifier-learning stage , and thereby limit the biological “purity” of a phenotype in the training set . This can pose a serious challenge in interpreting misclassified samples that actually seem to be a much better match ( or even perfect match ) to a different phenotype , leading to questions of whether a misclassification is due to ISSAC's limitation in distinguishing phenotypes , or whether a re-evaluation of the original tumor biopsy is required . Despite these concerns , we concluded this to be the most stringent test . After an exhaustive search on GEO , we identified 921 microarray samples from 16 studies that met the above criteria ( as of January 2011 ) . Information on all datasets ( e . g . , publication sources , Affymetrix platforms , GEO dataset IDs , and microarray sample IDs ) , studies , and GEO microarray sample IDs used in our study is available in Table 1 , Table S1 , and Table S2 , respectively . Raw microarray intensity data ( . CEL files ) were obtained online from GEO and preprocessed uniformly . More specifically , common probe-sets were found across all transcriptome samples , and consensus preprocessing was performed on all the raw microarray image data to build a consensus dataset . This step removes one major non-biological source of variance between different studies . These preprocessed samples were used to build a multi-study integrated dataset of human brain cancer and normal brain transcriptomes . Finally , stringent probe-set filtering was used to remove spurious classifier features . Our consensus preprocessing and probe-set filtering methods are explained in further detail below . Our integrated and uniformly pre-processed dataset is available on our group's webpage ( http://price . systemsbiology . net/downloads ) as a community resource for those who wish to conduct their own analyses . All gene expression data used in our study were measurements conducted on either the Affymetrix Human Genome U133A or U133Plus2 . 0 oligonucleotide microarrays . The expression level of a target gene on these two platforms is measured by first quantifying the total intensity of fluorescently labeled RNA fragments ( from patient specimens ) that bind to a probe set , or the set of complementary 25-mer oligonucleotide probe sequences . The intensities of all probe sets ( raw measurements in the form of . CEL files ) are then adjusted for background variability and normalized across all samples to obtain the target genes' final expression values . Raw . CEL data files were downloaded directly from GEO . Probe set information used in this study were based on the latest Affymetrix annotations . Raw intensity measurements of all microarray samples considered in our study were preprocessed collectively ( consensus preprocessing ) using the MATLAB implementation of the microarray preprocessing GCRMA [80] . Only the probe sets that map to known genes and exist on both Affymetrix platforms ( same oligonucleotide sequences ) were considered for preprocessing . The use of individual Affymetrix probe sets as classifiers ( and not the mean or median of their expression values as demonstrated in other microarray-based studies ) imposes limitations in the classifiers' multi-platform compliance , as discussed in Text S6 and Text S7 . Probe sets of Affymetrix microarrays have “perfect match” probes that are exactly complementary to the target gene's mRNA sequence . They also have “mismatch” probes that contain a mismatched nucleotide halfway along the probe sequence , and are used to estimate the degree of non-specific binding . To ensure that a probe set is reliably detected , the measurements of the “perfect match” probes must be significantly greater than those of the “mismatch” probes . This is usually assessed based on statistical measures . The MAS5 preprocessing software makes expression quality calls based on the nonparametric Wilcoxon signed-rank test . The “absent” call is made when the p-value is greater than 0 . 06 , representing no significant difference between the measurements of the “perfect match” and those of the ‘mismatch’ probes [81] . We eliminated probes that were determined to be “absent” in all samples of the consensus dataset . After this probe set filtering step , 19 , 656 probe sets ( corresponding to target genes ) within each microarray sample were kept for further analysis . All GCRMA preprocessing and MAS5 probe set filtering procedures were conducted separately for training and test set samples , i . e . , inside each cross-validation or hold-out loop , in order to avoid possible cross-talk between the two datasets . Genes that were excluded based on the MAS5 “absent” calls on the training data were also removed from the corresponding test data . Using Gene Ontology ( GO ) annotations , we have identified a list of 767 genes ( mapped on 1 , 085 total probes ) in every transcriptome sample that encode for possible blood-borne proteins . Specifically , we selected only the genes whose products are annotated to be in either the ‘Extracellular Space’ or the ‘Extracellular Region’ cellular locations . We use this gene set as a starting point for targeted blood diagnostics . All computational steps and analyses in regards to molecular signature discovery are identical to those discussed above . | From a multi-study , integrated transcriptomic dataset , we identified a marker panel for differentiating major human brain cancers at the gene-expression level . The ISSAC molecular signatures for brain cancers , composed of 44 unique genes , are based on comparing expression levels of pairs of genes , and phenotype prediction follows a diagnostic hierarchy . We found that sufficient dataset integration across multiple studies greatly enhanced diagnostic performance on truly independent validation sets , whereas signatures learned from only one dataset typically led to high error rate . Molecular signatures of brain cancers , when obtained using all currently available gene-expression data , achieved 90% phenotype prediction accuracy . Thus , our integrative approach holds significant promise for developing organ-level , comprehensive , molecular signatures of disease . | [
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] | 2013 | Multi-study Integration of Brain Cancer Transcriptomes Reveals Organ-Level Molecular Signatures |
Rabies is a zoonotic disease that is endemic in many parts of the developing world , especially in Africa and Asia . However its epidemiology remains largely unappreciated in much of these regions , such as in Nepal , where limited information is available about the spatiotemporal dynamics of the main etiological agent , the rabies virus ( RABV ) . In this study , we describe for the first time the phylogenetic diversity and evolution of RABV circulating in Nepal , as well as their geographical relationships within the broader region . A total of 24 new isolates obtained from Nepal and collected from 2003 to 2011 were full-length sequenced for both the nucleoprotein and the glycoprotein genes , and analysed using neighbour-joining and maximum-likelihood phylogenetic methods with representative viruses from all over the world , including new related RABV strains from neighbouring or more distant countries ( Afghanistan , Greenland , Iran , Russia and USA ) . Despite Nepal's limited land surface and its particular geographical position within the Indian subcontinent , our study revealed the presence of a surprising wide genetic diversity of RABV , with the co-existence of three different phylogenetic groups: an Indian subcontinent clade and two different Arctic-like sub-clades within the Arctic-related clade . This observation suggests at least two independent episodes of rabies introduction from neighbouring countries . In addition , specific phylogenetic and temporal evolution analysis of viruses within the Arctic-related clade has identified a new recently emerged RABV lineage we named as the Arctic-like 3 ( AL-3 ) sub-clade that is already widely spread in Nepal .
Rabies virus ( RABV ) is the prototype species of the genus Lyssavirus , in the family Rhabdoviridae [1] . Members of this viral genus encompass single-stranded , negative sense viruses with a genome size of nearly 12 kb . Among the 12 species of lyssaviruses identified to date , RABV has the broadest geographic distribution and the widest spectrum of vectors or reservoir hosts within the orders Carnivora and Chiroptera [2] , [3] . This zoonotic virus remains the main etiological agent of rabies , an acute and almost invariably fatal form of encephalomyelitis , which can affect almost all terrestrial mammals , including humans . Infection occurs after contamination with infected saliva by bites , scratches and mucous membrane exposure . Despite the availability of an effective post-exposure prophylaxis , it is estimated that approximately 55 , 000 people die every year due to rabies , with more than 95% of human deaths occurring in Asia and Africa [4] . To date , no effective treatment exists when clinical disease is declared [3] . The domestic dog remains the main reservoir and vector of rabies in developing countries , and is responsible for almost all human deaths . Various wild carnivores are also involved in the maintenance of RABV and transmission of sylvatic rabies in limited geographic regions , with a small contribution in the burden of human rabies . Other terrestrial mammal species including livestock species are susceptible to rabies but do not transmit the disease further , acting as epidemiological dead-end hosts [2] . The dog has also been identified as the probable main vector involved in interspecies RABV transmission . Indeed , phylogeographic analyses indicated that current RABV from non-flying mammals cluster into six major geographically distinct clades with a strong indication that these clades share a common ancestor originating from domestic dogs in the southern parts of the Indian subcontinent , and that the subsequent evolutionary diversification probably occurred within the last 1500 years [5] . This study and others highlight the important role that improved knowledge of the biodiversity of the disease and especially potential routes of spread play in helping to design control and prevention strategies [5]–[7] . However , the global burden of rabies remains largely underestimated in most of enzootic areas , particularly in Africa and Asia [4] , [8] , [9] . The real incidence of human rabies is poorly documented , and data related to the epidemiological cycle of rabies in domestic and wildlife animal populations in some Asian countries are spare . This is particularly true for Nepal , where rabies is endemic . Incidence of human rabies is estimated to 100–200 documented deaths every year , but most of the cases are diagnosed on clinical signs and history of dog bite , and rarely confirmed by laboratory tests . In 2010 , a total of 41 , 200 people received free post-exposure prophylaxis , a tissue culture inactivated rabies vaccine [10] , [11] . Hyperimmune serum ( horse and human ) against rabies is only available in Kathmandu city . Surveillance and prevention of animal rabies remain limited; in 2010 , administration of 12 , 426 vaccinations to animals was conducted [12] . Meanwhile the Veterinary Epidemiology Centre in Kathmandu recorded 143 animal deaths for the entire country during the same period , but laboratory diagnosis of rabies was only made on a limited portion of these at the Central Veterinary Laboratory ( CVL ) in Kathmandu due to difficulties in transportation of clinical samples from the countryside . In the absence of an active national surveillance plan and difficulties in sample transport , passive rabies surveillance often occurs only when a dead and/or infected animal is brought to the CVL . Therefore information and characterization of representative viruses from Nepal remain limited . A better understanding of the dynamics of RABV circulation and potential exchanges with neighboring countries is necessary and valuable for future control plans and prevention strategies . In this study , we performed the molecular characterisation of RABV isolates circulating in Nepal , based on the complete nucleoprotein ( N ) and glycoprotein ( G ) genes sequences of new isolates . We also compared the study isolates to representative viruses from other regions to place them in an international context . The combined database of rabies virus sequences has yielded insights into their phylogeography and enabled a specific examination of the timeframe of emergence of the Arctic-related clade , allowing the identification of a new and emerging Nepalese phylogenetic group of RABV .
The human clinical sample described in this paper was collected in 2003 and following informed oral consent from the child's parents , was sent to the National Reference Centre for Rabies housed in the Lyssavirus Dynamics and Host Adaptation ( LDHA ) Unit , Institute Pasteur in 2009 . This sample had been registered for research purpose in the LDHA Unit biobank and declared according to the French regulations ( article L . 1243-3 in relation to the French Public Health Code ) to both the French Ministry for Research and a French Ethics Committee which both approved and registered the biobank ( declaration number DC-2009-1067; collection N°12 ) . Twenty-four clinical rabies samples were collected from seven districts in Nepal between 2003 and 2011 and included domestic dogs ( n = 14 ) , livestock with goat ( n = 4 ) , cattle ( n = 3 ) and buffalo ( n = 1 ) , and 1 each of human and mongoose ( Table 1 and Table S1 ) . These samples were collected either at the Regional Veterinary Laboratory or CVL from dead animals that had shown clinical signs prior to death . These samples were tested at the CVL for rabies confirmation by a rapid antigen detection and fluorescent antibody test ( FAT ) [13] . As part of this study , all confirmed rabies positive samples were shipped as either fresh frozen tissue or dried tissue smears on FTA Cards ( Whatman , USA ) to the Australian Animal Health Laboratory or Institut Pasteur , Paris ( IPP ) for further phylogenetic analyses ( Table 1 ) . One human sample originated from a 12 year-old girl who had passed away after being bitten by a dog in 2003 [14]; this sample was analysed at IPP . All samples were subjected to molecular characterization , and a viable subset was also used for virus isolation . Additionally , a number of new or partially characterized isolates from other countries were also included in this study , originating from Afghanistan ( n = 5 ) , Greenland ( n = 2 ) , Iran ( n = 4 ) , Russia ( n = 2 ) and USA ( n = 1 ) . Host animal origins and dates of collection are indicated in Table 1 and Table S1 , when available . In addition , a vaccine strain used in Nepal and historically supplied by IPP was also analysed in this study . Brain samples received by the Australian Animal Health Laboratory were processed for virus isolation . Briefly , a 10% homogenate of each brain was prepared in PBSA pH 7 . 4 , using a blunt end 18 g needle and syringe in a class II cabinet . Cellular debris was removed by centrifugation at 1000 g for 3 min at room temperature . The brain homogenate ( 200 µl ) was added to Neuro-2a cells in HMEM medium with 10% fetal calf serum in a 25 cm2 flask . The cell culture was incubated for 4–7 days at 37°C in a CO2 incubator and regularly inspected for evidence of cytopathic effect . Cells with evidence of cytopathic effect were removed from the flask and harvested by centrifugation . Total RNA was extracted using either Magmax Viral Isolation Kit ( Applied Biosystems , Foster City , USA ) or Tri-Reagent ( Molecular Research Center , Inc . , Cincinnati , USA ) , both according to the manufacturer's instructions . Extraction of RNA was performed from the original brain samples , from cell suspension after virus isolation or from FTA cards . For the latter , RNA recovery was achieved from hole-punched card material according to manufacturer's instructions or after incubation for 30 min in 100 µl Ambion RNA Rapid Extraction Solution ( Applied Biosystems , Foster City , USA ) . RT-PCR amplification and DNA sequencing of the N and G genes were performed as described previously [5] , [15]–[19] . Analysis of sequence data and contig assembly were performed using either the SeqMan module of the Lasergene v8 . 0 software suite ( DNASTAR ) or Sequencher 5 . 0 ( Gene Codes Corporation ) software . GenBank accession numbers for the complete N and G gene sequences newly acquired in this study are designated JX944565-JX944602 and JX987718-JX987749 . Complete N and G gene coding sequences determined in this study were analysed with respective full-length sequence datasets comprising rabies N gene sequences ( n = 173 , 1350 nt ) and G gene sequences ( n = 92 , 1575 nt ) available from GenBank ( Table S1 ) . Multiple sequence alignments and amino acid residue analysis were performed using Clone Manager v . 9 ( Science & Educational software ) or ClustalX 2 . 1 [20] . Maximum-likelihood ( ML ) phylogenies were inferred for each dataset using the GARLI v2 . 0 [21] and PAUP* v4 . 0 programs [22] . The general time reversible model with proportion of invariable sites plus gamma distributed rate heterogeneity ( GTR+I+ Γ4 ) as generated by the Akaike information criterion using the program MODELTEST v3 . 7 [23] , was used as the best-fit nucleotide substitution model in all cases . Reliability of the ML tree topologies was tested using both neighbour-joining ( NJ ) and ML methods with 1 , 000 and 100 bootstrap replicates respectively . Using a select RABV Arctic-related clade dataset of 67 N gene sequences , we inferred a maximum clade credibility ( MCC ) tree by using the Bayesian Markov chain Monte Carlo ( MCMC ) method available in the BEAST package [24] . Sequences were dated with the year of isolation , and identical sequences with the same year were excluded . The alignment used is available from the authors on request . Posterior probability values provide an assessment of the degree of support for each node on the tree . This analysis utilized the GTR+I+Γ4 model of nucleotide substitution . All chains were run for a sufficient length to ensure convergence , with 10% removed as burn-in . After comparison of the log likelihood values calculated for several runs through the TRACER program ( http://tree . bio . ed . ac . uk/software/tracer/ ) , a relaxed ( uncorrelated exponential ) molecular clock was the best supported under Bayes Factors . As well as generating the MCMC tree , this analysis also allowed us to estimate both the rate of nucleotide substitution per site ( substitutions per site per year ) and the time to the most recent common ancestors ( TMRCA ) in years . The degree of uncertainty in each parameter estimate was provided by 95% highest posterior density ( HPD ) values . Assignment of lineages used for the description of the different phylogroups described in this study has been previously defined at the clade level [5] and within the Arctic-related sub-clades [25] .
The 24 Nepalese RABV specimens received for this study were collected during the period 2003–2011 from seven districts in Nepal , all classified as hill terrains and localized in the Central and Western regions of the country ( Table 1 , Table S1 and Figure 1 ) . All except two of the samples from Nepal have been collected from dogs or livestock . Both NJ ( data not shown ) and ML ( Figure 2 ) trees of N gene sequences exhibited similar clustering patterns , each with strong bootstrap support . In particular , all these newly sequenced specimens from Nepal were grouped into two of the six main phyloclades of canine rabies previously defined ( i . e . the Indian subcontinent , Asian , Africa 2 , Africa 3 , Cosmopolitan and Arctic-related clades ) [5] . No correlation between the geographical district source and host of the isolates to clade designation was apparent . Five isolates ( 4403-14 , 4403-17 , 3878-73 , 09029NEP and 11001NEP ) clustered into the Indian subcontinent clade , previously only occupied by viruses from Sri-Lanka and India ( mainly from southern regions for the latter ) ( Figures 2 and 3A ) . Within this clade , viruses grouped with a clear separated spatial structure according to their geographical origin . The other 19 specimens clustered within the Arctic-related clade , which exhibited three distinct sub-clades as previously defined , the first being the Arctic sub-clade subdivided into four lineages A-1 , A-2 , A-3 , and A-4 [25]–[27] . The two other sub-clades are represented by the Arctic-like 2 sub-clade ( AL-2 ) , and the Arctic-like 1 ( AL-1 ) sub-clade , split into the AL-1a and AL-1b lineages , and [25]–[27] . Two of the Nepalese viruses ( 3878-09 and 3878-78 collected in 2010 ) were clustered into the AL-1a lineage , with viruses from India ( Figures 2 and 3B ) . The remaining isolates ( n = 17 ) formed a new and strongly supported monophyletic group , which was designated as the Arctic-like 3 ( AL-3 ) sub-clade ( Figures 2 and 3B ) . These isolates had 99–100% pairwise nucleotide sequence similarity to each other and to isolate 9901NEP , a virus that was isolated in Nepal from a dog in 1998 [5] . Isolates in the AL-3 sub-clade displayed 94–95% and only 86–87% pairwise nucleotide sequence similarities compared with Nepalese viruses in the AL-1a sub-clade and the Indian subcontinent clade , respectively . A single RABV isolate from Iran ( V704IRN ) [28] was found to be the only previously sequenced non-Nepalese representative of AL-3 . This virus had 95% pairwise nucleotide sequence similarity to the viruses from Nepal , suggesting a geographical clustering . The translated nucleoprotein sequence revealed 99–100% sequence similarity for all Arctic-like sub-clade viruses , regardless of country of origin , whilst the Indian subcontinent clade viruses displayed at least 2–4% protein sequence dissimilarity to the Arctic-like viruses . Several positions with distinctive amino acid differences were observed for the Nepalese viruses between these two major N gene phylogroups ( Indian subcontinent and Arctic-related clades ) which could potentially be useful as clade or sub-clade markers ( Table 2 ) . Based on complete N sequences analysis of all available RABV viruses from Nepal , all were phylogenetically relatable to canine rabies regardless of lineage . In particular , virus of two samples collected from mongoose , 3878-05 and 9903NEP were indistinguishable from viruses originating from dogs or livestock , and could probably be from spill-over transmissions of canine rabies . In addition to the Nepalese isolates , phylogenetic analysis of the N gene sequences in this study showed that viruses from Afghanistan ( n = 5 ) clustered with RABV isolates from Pakistan into the AL-1b lineage ( Figures 2 and 3B ) . Isolates from Iran ( n = 4 ) were found to be grouped in the Cosmopolitan clade ( Figure 2 ) . The other new isolates belonged to the Arctic sub-clade , grouped in the lineage A-1 for isolates 9104USA and 9105USA , the lineage A-2 for 9141RUS and 9143RUS , and the lineage A-3 for 8683GRO and 8684GRO . The vaccine reference strain ( 4403-12 ) used in Nepal and historically originated from IPP grouped with other vaccine viruses within the Cosmopolitan clade ( Figure 2 ) . Phylogenetic NJ ( data not shown ) and ML ( Figure S1 ) trees of complete G gene sequences confirmed the results obtained with N gene . Despite the smaller G gene sample size , similar topologies were found , indicating that the distribution of Nepalese RABV within both Indian subcontinent ( n = 5 ) and Arctic-related ( n = 19 ) clades are defined equivalently with strong bootstrap support by both N and G gene phylogenies . Clustering patterns of the non-Nepalese RABV were also similar between N and G gene trees . The translated glycoprotein sequences showed that the Nepalese AL-3 viruses had 99–100% amino acid sequence similarity with each other , 97–98% sequence similarity to the Nepalese viruses from AL-1a , and 94% sequence similarity to the Nepalese viruses within the Indian subcontinent clade . As for N gene , positions of distinctive amino acid differences were identified between the Indian subcontinent and Arctic-related G gene phylogroups ( Table 3 ) . Using Bayesian approaches , MCC trees were produced based on data subsets comprising 67 complete N gene sequences ( Figure 4 ) to further clarify the relationships among the Arctic-related clade . Four major clusters were identified with good Bayesian posterior probability support , the Arctic and the Arctic-like sub-clades AL-1 , AL-2 and AL-3 . The time of most recent common ancestor ( TMRCA ) for the Arctic-related clade was estimated around 1823 ( 95% HPD 1686–1924 ) . The AL-2 sub-clade , regrouping isolates from China ( Inner Mongolia ) , Mongolia , Russia ( Siberia ) , and South Korea appeared to be first evident around the year 1918 ( 95% HPD 1861–1959 ) ( Figure 4 ) . The subdivision between AL-1 and AL-3 sub-clades appeared around the year 1924 ( 95% HPD 1871–1968 ) , leading to their emergence in 1952 ( 95% HPD 1922–1976 ) and 1962 ( 95% HPD 1923–1989 ) , respectively . The AL-1 sub-clade later diverged into two lineages , AL-1a ( TMRCA 1967 , 95% HPD 1947–1982 ) that encompassed isolates from India and Nepal , and AL-1b ( TMRCA 1965 , 95% HPD 1944–1982 ) that included viruses from Afghanistan and Pakistan . Subdivision of the AL-3 sub-clade into two branches was also clearly evident , one represented only by a single Iranian isolate collected in the far east of the country , and a second distinct branch encompassing only RABV isolates from Nepal with TMRCA estimated at 1994 ( 95% HPD 1987–1998 ) . The four Arctic lineages ( A-1 , A-2 , A-3 , and A-4 ) evolved from a common progenitor that dated back to around 1939 ( 95% HPD 1897–1970 ) ( Figure 4 ) . The mean rate of nucleotide substitution estimated among the Arctic-related clade was 3 . 8×10−4 per site per year ( 95% HPD , 2 . 3–5 . 4×10−4 per site per year ) , which is in agreement with previously determined rate for the overall RABV species [5] .
This study provides for the first time a comprehensive analysis of the genetic diversity of RABV circulating in Nepal . Despite Nepal possessing a relatively small land area ( 800×200 km , 147 , 181 km2 ) represented by a huge variety of landscapes ranging from tropical humid regions in the south to the world's highest mountains to the north ( with the presence of eight mountain summits among the ten highest in the world ) , a high diversity of RABV was found and a rapid spread of new variants were identified in this country . Indeed , two RABV phylogenetic clades have been identified in Nepal , the Indian subcontinent and the Arctic-related clades as well as the presence of two Arctic-related sub-clades AL-1 and AL-3 . The Indian subcontinent RABV clade contains phylogenetically related viruses from Sri Lanka and India , in addition to the Nepalese isolates described in our study [29]–[33] . Due to the limited number of representative sequences , the relevant time-frames of emergence of the Indian subcontinent clade and its subsequent geographical diversification were not further determined in our study . A previous study based on the complete N gene sequences of several Sri Lankan viruses and only one Indian isolate , suggested that both diverged from their common ancestor around the year 1854 ( 95% HPD 1760–1918 ) [31] . However , the large time range associated with this estimation indicates that this result clearly needs to be confirmed on a larger dataset of sequences , which should include Nepalese viruses . Previous description of a single Nepalese RABV isolate V120 suggested that this lineage was already present in Nepal in 1989 [34] . Our characterization of a further five viruses from Nepal isolated between 2003 and 2009 has confirmed that this distinct regional sub-group of Indian subcontinent clade viruses have circulated in Nepal for at least the last 24 years . The RABV Arctic-related clade has been relatively well described with characterization of RABV from Russia , Alaska and India in recent studies [25] , [26] , [35] . This clade emerged and spread relatively recently , with the most recent common ancestor dated back approximately 200 years ago [26] . This Arctic-related clade includes the so-called Arctic and the Arctic-like sub-clades . Although RABV belonging to the Arctic-like sub-clade was already known to circulate in Nepal [5] , [35] , this study has identified for the first time the presence of two Arctic-like sub-clades of RABV ( AL-1 and AL-3 ) in this country . Within the AL-1 sub-clade , we identified two Nepalese isolates belonging to the AL-1a lineage , which encompassed virus strains from India but also probably from Bangladesh and Bhutan , although for the latter phylogenetic information contained in only partial N gene sequences available in public databases was not informative enough to classify strains into either AL-1a or AL-1b lineages ( data not shown ) [36] , [37] . AL-1a viruses have been present in India , which forms the largest immediate border with Nepal , since at least 1988 and represent currently the main phylogroup of RABV circulating in the country [26] , [38] ( Figures 1 , 2 and S1 ) . However , without further representation , it is unknown whether AL-1a is also an established and stable lineage in Nepal . Within this cluster , viruses originating from Nepal and India were interspersed , suggestive of the existence of movement of RABV infected domestic animals between these countries . This adds to evidence suggesting the existence of a degree of long-distance , human mediated transborder dissemination of RABV as previously also reported in Africa and hypothesized in some South East Asian countries [7] , [16] , [37] , [39] , [40] . The high prevalence of rabies in India has been suggested to be an important source of rabies outbreaks into neighboring regions [26] . Indeed , trade exchanges take place between Nepal and India , in addition to movement of people for tourism or religious purposes . The second lineage AL-1b included interspersed isolates originated from Afghanistan and Pakistan . A single Indian isolate collected from Jodhpur had also been associated to this cluster , reflecting a probable translocation of this virus from the Pakistani border ( Figures 2 and 3B ) [26] . However , this strain was not included in our study due to the absence of a complete publicly available N gene sequence . The predominant group of Nepalese viruses of our study belonged to a new Arctic-like sub-clade which we designated as AL-3 . This phylogroup shared a common ancestor with the AL-1 sub-clade dating back to 1924 ( 95% HPD 1871–1968 ) , differing from a previous estimation of as recent as 50 years ago [26] . Within this AL-3 sub-clade , only a single virus V704IRN from the far north-eastern region of Iran , did not originate from Nepal , and was positioned as a stable immediate outlier of the Nepalese group [26] , [38] . It may be a hint to its source origin possibly being Central Asian derived Arctic-related RABV . Surprisingly , the N gene phylogeny demonstrated that the group of AL-3 Nepalese isolates , which included samples collected from 1998 to 2011 , emerged as recently as the mid-1990's . The lack of political stability in countries such as Nepal is known to represent a major drawback for the implementation of any programs for disease control . This is particularly true for rabies , which demands a fully integrated approach to achieve its control [41]–[43] . Currently , several critical components to reaching this goal are lacking in Nepal , such as a strong political commitment , the implementation of a coordinated national program for surveillance and control of rabies , dedicated financial resources , and general or widespread public awareness and reporting . Similar factors have been associated with the spread of fox RABV in Europe after the second world war [6] , and the high incidence of rabies in the most afflicted regions of the world which encompasses countries presenting with the lowest income , such as sub-Saharan Africa and some countries of south-east Asia [8] , [44] . The recent emergence of AL-3 viruses in Nepal further illustrates how the epidemiology of rabies can rapidly change in a country and that a new variant of RABV can rapidly spread in an enzootic country with at least two other genotypic variants already present . The epidemiological fitness of this new lineage and whether it will outcompete the other lineages present in Nepal in the coming years will be of great interest . A rabies vaccine strain used in Nepal was also phylogenetically characterized and found to be closely related to another vaccine strain from France isolate 93127FRA within the RABV Cosmopolitan clade , thus confirming its historical origin from IPP , France . This vaccine strain had 97% protein sequence similarity to the nucleoprotein of Nepalese viruses in both the Arctic-like and Indian subcontinent clades , whilst the glycoprotein from the vaccine strain had 91–92% similarity to these Nepalese viruses . However cross-protection of isolates belonging to the species RABV in the genus Lyssavirus is quite broad and studies have shown vaccine candidates to elicit protective immunity to many varied rabies strains [45] , [46] . Physical barriers such as mountains and rivers influence the genetic pool of viruses that circulate in a region as previously highlighted in different settings [5] , [6] , [47] , [48] . Nepal consists of 75 districts which are classified as low , hill and mountain terrains , and is also dominated to the north by the Great Himalayan mountain range . This natural barrier between Nepal and China could be one of the explanations for the absence in Nepal of RABV from the Asian or Cosmopolitan clades [49] , although an extensive geographic representation of rabies in Nepal remains difficult to achieve due to the difficulties in transportation and other contributing factors . The Nepalese RABV samples examined in this study originated from seven different districts , all classified within the hill regions of the country . This may explain the uncorrelated distribution of the different RABV lineages in Nepal both within the same , and in multiple districts within the country . In addition , human interference towards facilitating the movement of dogs and other potential rabies hosts to different locations would negate any barriers imposed by moderate terrain . In particular , our study demonstrated the existence of movement of lineage AL-1a related-RABV across the Indian and Nepalese borders . Evolutionary studies have added to recent knowledge of the Arctic-related clade , especially of the temporal and regional diversification of the Arctic-like sub-clade , and future studies of RABV within the Indian subcontinent could further elucidate the time of introduction of these viruses to Nepal . RABV is a continuing concern in many developing countries such as Nepal , and the increase in knowledge of RABV phylodynamics and epidemiology in these regions would contribute to the development of public awareness and disease control strategies . In particular , our results strongly suggested that the domestic dog is the main reservoir and vector of rabies in Nepal , which is important for the further implementation of surveillance and elimination programs devoted to this disease . Indeed , our observation did not reveal the existence of a sylvatic epidemiological cycle of rabies in Nepal , unlike previously suggested [50] , although this observation has to be extended and further confirmed on a larger number of rabies samples from wildlife collected over different parts of the country . Currently , reported incidence of rabies remains largely underestimated in Nepal . Active surveillance of rabies in domestic and wild animals should be increased and extended to all of the different districts , in an attempt to obtain the most comprehensive picture of the disease epidemiology in the country and to be able to identify spatiotemporal replacement of lineages and the epidemiological causes . Implementation of such a surveillance program represents an achievable goal , through the presence of a large existing network of local veterinary offices ( 75 district livestock service offices and 999 livestock service centers ) throughout the country . However , an effort will be needed to train technical staff in rabies surveillance and on conditions for often challenging sample transportation . In parallel , the incidence of nearly 100 human deaths per year in Nepal has to be more precisely evaluated , as it also appears largely underestimated [51] . Validated laboratory techniques are now available that will contribute to more accurate insights into the incidence and spread of human rabies in developing countries [52] . Such information remains a key step towards the implementation of control measures in endemic countries such as Nepal , contributing to achieving the final goal of elimination of this neglected disease [41] , [42] . | Rabies is endemic in most Asian countries and represents a serious public health issue , with an estimated 31 , 000 people dying each year of this disease . The majority of human cases are transmitted by domestic dogs , which act as the principal reservoir host and vector . However , molecular epidemiology and evolutionary dynamics of the main etiological agent , the rabies virus ( RABV ) , remains largely unappreciated in some regions such as in Nepal . Based on a subset of 24 new Nepalese isolates collected from 2003 to 2011 and representative RABV strains at a global scale , phylogenetic analysis based on the complete nucleoprotein and glycoprotein genes sequences revealed the presence of a surprising wide genetic diversity of RABV circulating in this country . The presence of three different co-existing phylogenetic groups was identified: an Indian subcontinent clade and two different Arctic-like sub-clades within the Arctic-related clade , namely Arctic-like ( AL ) -1 , lineage a ( AL-1a ) , and AL-3 . Among these clusters , the AL-3 sub-clade appears as the major Nepalese phylogroup which emerged relatively recently in this country , within the last 30 years . These data has raised some concerns about the exchange of RABV between different countries , and provided key elements for implementation of effective control measures of rabies in Nepal . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [] | 2013 | Recent Emergence and Spread of an Arctic-Related Phylogenetic Lineage of Rabies Virus in Nepal |
The Cop9 signalosome ( CSN ) is an evolutionarily conserved multifunctional complex that controls ubiquitin-dependent protein degradation in eukaryotes . We found seven CSN subunits in Neurospora crassa in a previous study , but only one subunit , CSN-2 , was functionally characterized . In this study , we created knockout mutants for the remaining individual CSN subunits in N . crassa . By phenotypic observation , we found that loss of CSN-1 , CSN-2 , CSN-4 , CSN-5 , CSN-6 , or CSN-7 resulted in severe defects in growth , conidiation , and circadian rhythm; the defect severity was gene-dependent . Unexpectedly , CSN-3 knockout mutants displayed the same phenotype as wild-type N . crassa . Consistent with these phenotypic observations , deneddylation of cullin proteins in csn-1 , csn-2 , csn-4 , csn-5 , csn-6 , or csn-7 mutants was dramatically impaired , while deletion of csn-3 did not cause any alteration in the neddylation/deneddylation state of cullins . We further demonstrated that CSN-1 , CSN-2 , CSN-4 , CSN-5 , CSN-6 , and CSN-7 , but not CSN-3 , were essential for maintaining the stability of Cul1 in SCF complexes and Cul3 and BTB proteins in Cul3-BTB E3s , while five of the CSN subunits , but not CSN-3 and CSN-5 , were also required for maintaining the stability of SKP-1 in SCF complexes . All seven CSN subunits were necessary for maintaining the stability of Cul4-DDB1 complexes . In addition , CSN-3 was also required for maintaining the stability of the CSN-2 subunit and FWD-1 in the SCFFWD-1 complex . Together , these results not only provide functional insights into the different roles of individual subunits in the CSN complex , but also establish a functional framework for understanding the multiple functions of the CSN complex in biological processes .
The Cop9 signalosome ( CSN ) is a multiprotein complex that was initially discovered in Arabidopsis thaliana as an important regulator of photomorphogenesis , and was later found to participate in a wide range of processes in eukaryotes [1] . The CSN usually contains eight subunits ( CSN1–CSN8 ) in higher eukaryotes , and each CSN subunit has evolutionarily conserved counterparts in the 26S proteasome lid complex and eukaryotic translation initiation factor 3 ( eIF3 ) [2] , [3] . All known CSNs regulate ubiquitin-dependent protein degradation [4] . The ubiquitin–proteasome system is the major pathway responsible for the degradation of intracellular proteins . In this pathway , proteins targeted for rapid degradation are conjugated to ubiquitin , a small conserved protein with 76 amino acids [5] . The attachment of ubiquitin to its target proteins is mediated by a cascade of enzymatic reactions involving the ubiquitin-activating enzyme ( E1 ) , ubiquitin-conjugating enzyme ( E2 ) , and ubiquitin ligase ( E3 ) . After recruiting the specific substrate , the ubiquitin ligase ( E3 ) complex bridges the targeted protein and E2-ubiquitin to form a polyubiquitinated protein , which is subsequently degraded by the 26S proteasome [6] . Cullin-RING ubiquitin ligases ( CRLs ) are the major group of E3s . A typical CRL complex consists of a cullin subunit ( Cul1 , Cul3 , or Cul4 ) , a RING protein ( Hrt1/Roc1/Rbx1 ) , an adaptor protein ( Skp1 in SCF complexes , DDB1 in Cul4-based E3 ) , and a substrate-recognition subunit such as F-box proteins ( FBPs ) in SCF complexes [7] , BTB proteins in Cul3-type E3 complexes [8] , and DCAFs in Cul4-DDB1 E3 complexes [9]–[11] . In eukaryotic systems , CRLs play essential roles in many processes , including cell division , cell proliferation , cell differentiation , and circadian clock function [12] . The CRLs are activated by the neddylation process , in which Nedd8 , a ubiquitin-like protein , is attached to a conserved lysine site on cullin proteins . The neddylated cullin may accelerate assembly of the CRL E3 complex , which promotes the ubiquitination of its substrate . The CSN negatively regulates the activity of CRLs by deneddylation , in which Nedd8 is cleaved from cullin proteins [4] , [13] . Disruption of CSN subunits generally causes hyperneddylation of Cul1 and other cullins in many organisms [4] , [12]–[16] . Genetic evidence indicates that CSN promotes CRL-mediated degradation of substrates in vivo [4] , [17] , [18] . Therefore , CSN has been proposed to mediate the assembly/disassembly of CRLs [17] , and recent studies demonstrate that a major function of the CSN complex is to control the stability of CRL ubiquitin ligases in vivo [19]– . Eight subunits of CSN are present in higher eukaryotes , as well as in Dictyostelium discoideum and Aspergillus nidulans . Interestingly , three CSN subunits are missing in Saccharomyces cerevisiae ( CSN4 , CSN6 , and CSN8 ) [22] and two are missing in Schizosaccharomyces pombe ( CSN6 and CSN8 ) [23] , while both Caenorhabditis elegans [24] and N . crassa [20] lack CSN8 . The absence of one or more CSN complex subunits in lower eukaryotes suggests that the composition of the CSN complex is species specific . The role of each CSN subunit may differ in some species , and different CSN subunits may not contribute equally to the function of the CSN complex . For example , in S . pombe , mutants with different CSN subunits deleted display distinct phenotypes [14] . In Drosophila melanogaster , both csn4 and csn5 mutants have defects in oogenesis and embryo patterning , as well as larval lethality . However , csn4-null flies exhibit molting defects , while csn5-null flies develop melanotic tumors [25] . In addition , csn4 and csn5 mutants show different gene expression patterns [26] . Compared to yeast and higher organisms , the functions and roles of the individual CSN subunits are poorly understood in filamentous fungi . To date , only four out of the eight subunits in A . nidulans and one out of the seven subunits in N . crassa have been investigated [20] , [27] . Furthermore , the functions of individual CSN subunits within the CSN complex are largely unknown in eukaryotes . Therefore , to further understand the functions and roles of the CSN complex with regard to the regulation of CRLs , we performed a systematic functional analysis of each subunit in the N . crassa CSN complex .
Recently , the purification of Myc-His-CSN-2 protein expressed in a csn-2KO mutant led to the identification of the N . crassa CSN complex , which contains seven subunits ( CSN-1 to CSN-7a ) ( Table S1 ) [20] . Like most other fungi , the N . crassa genome does not encode a csn-8–like gene . Protein sequence alignment indicated that the N . crassa CSN subunits were more closely related to the CSN subunits of animals and A . thaliana than to those of yeast . Bioinformatics analyses further showed that N . crassa CSN-3 was the least-conserved subunit in the CSN complex , with a lower e-value PCI ( proteasome , COP9 signalosome , eukaryotic initiation factor 3 ) domain . Similarly , in A . nidulans , CsnC ( CSN-3 ) and CsnH ( CSN-8 ) are also less-conserved subunits in the CSN complex [28] . Interestingly , we also found that there is another csn-7–like gene ( csn-7b , NCU02813 ) in the N . crassa genome that encodes a protein with a highly conserved PCI domain . However , this hypothetical protein was not detected in purification products of the CSN complex [20] . Thus , the N . crassa CSN complex consists of seven subunits: five PCI domain proteins ( CSN-1 , CSN-2 , CSN-3 , CSN-4 , and CSN-7 ) and two MPN ( Mpr-Pad1-N-terminal ) domain proteins ( CSN-5 and CSN-6 ) ( Table S1 ) . Of the seven CSN subunits in N . crassa , only CSN-2 has been functionally characterized [20] . To systematically analyze the function of each CSN subunit , we generated deletion mutants for each of the remaining six csn genes by gene replacement with a hygromycin resistance gene ( hph ) . As with the csn-2KO mutant , we obtained homokaryotic deletion strains of each single csn gene , indicating that none of the seven csn genes was essential for the cell viability of N . crassa . However , attempts to generate homokaryotic mutants for the csn-7–like gene csn-7b ( NCU02813 ) were unsuccessful , suggesting that this gene is essential for cell viability . The failure to generate csn-7b homokaryotic deletion mutants suggests a functional difference between csn-7b and the other csn genes . This result , together with the absence of CSN-7b in Myc-His-CSN-2 purification products , further suggests that the product of the csn-7b gene is not a component of the N . crassa CSN complex . We recently showed that the CSN-2 subunit plays important roles in N . crassa growth and development [20] . The csn-1KO , csn-4KO , and csn-7KO strains produced fewer conidia and aerial hyphae on slants than the csn-2KO mutant ( Figure 1A ) , while the csn-5KO and csn-6KO strains exhibited similar phenotypes to the csn-2 mutant ( Figure 1B ) . These results suggest that these subunits are important for N . crassa development . In addition , the growth rates of the csn-1KO , csn-2KO , csn-4KO , csn-5KO , csn-6KO , and csn-7KO strains were markedly slower than that of the wild-type strain at normal temperature ( Figure 1D ) . The severity of the growth defects was gene dependent . Compared with that of the csn-2KO mutant , the growth rates of csn-1KO , csn-4KO , csn-5KO , csn-6KO , and csn-7KO were slower ( Figure 1D ) . This indicates that these subunits are important for N . crassa growth . Unexpectedly , the csn-3 mutant exhibited hyphal formation and conidiation that was the same as the wild-type strain ( Figure 1C ) . Furthermore , growth of the csn-3KO strain was slightly faster than that of the wild-type strain ( Figure 1D ) , suggesting that CSN-3 is not a key regulator of growth and development in N . crassa . Taken together , these observations demonstrate that the seven subunits of the CSN complex play different roles in the growth and development of N . crassa . CSN-2 was found to be a regulator of the N . crassa circadian clock [20] . To find out whether other CSN subunits have a similar role , we examined the conidiation rhythm of csn knockout mutants by race tube assays . After entrainment by light , the wild-type strain exhibited a robust circadian conidiation rhythm with a period of about 22 hours at 25°C in constant darkness ( Figure 2A ) , while conidiation was very irregular in the csn-1KO , csn-2KO , csn-4KO , csn-5KO , csn-6KO , and csn-7KO strains ( Figure 2A ) , suggesting that these subunits are essential for circadian rhythms . In contrast , the csn-3 mutant grew faster on race tubes than the wild-type strain , and exhibited a robust and precise period of conidiation identical to that of the wild-type strain ( Figure 2B ) , indicating that the CSN-3 subunit was not essential for normal conidiation rhythms in N . crassa . Taken together , these observations demonstrate that , of the seven CSN subunits , all but CSN-3 play an important role in circadian rhythm . The CSN complex regulates photomorphogenesis in plants [1] , and CSN-2 is required for light entrainment of conidiation rhythms in N . crassa [20] . To test whether the rest of the CSN subunits have a similar function , we examined the conidiation rhythms of each csn mutant in light–darkness cycles ( 12 h light/12 h darkness ) . As shown in Figure 2C , the conidiation rhythms of the csn-1KO , csn-2KO , csn-4KO , csn-5KO , csn-6KO , and csn-7KO strains were not entrained by light–darkness cycles , indicating that these six CSN subunits play key roles in light regulation of the circadian clock . As expected , like the wild-type strain , the csn-3KO mutant could be entrained by light–darkness cycles ( Figure 2D ) , demonstrating that CSN-3 is not required for the light-response process in N . crassa . These results further confirm that each CSN subunit contributes unequally to light-dependent processes in N . crassa . Because the temperature-regulated conidiation process is affected in the csn-2 mutant [20] , we examined the responses of the other CSN subunit mutants to temperature entrainment using race tube assays . In 12 h 25°C/12 h 20°C temperature cycles , the conidiation rhythm of the wild-type strain was synchronized , with conidial peaks in the cold phase ( Figure 3A ) . As expected , temperature cycles failed to entrain the conidiation rhythm in the csn-1KO , csn-4KO , csn-5KO , csn-6KO , and csn-7KO strains , as was the case with the csn-2 mutant ( Figure 3A ) [20] , suggesting that these CSN subunits play important roles in the temperature response of N . crassa . In contrast , the conidiation rhythm of the csn-3KO mutant ( Figure 3B ) could be synchronized by temperature cycles , similar to the wild-type strain , indicating that the CSN-3 subunit is not required for the temperature-response process . Very similar results were seen with 12 h 28°C/12 h 25°C temperature cycles ( Figure 3C and 3D ) . These results suggest that the CSN complex is involved in the regulation of temperature response , and that all of the subunits except for CSN-3 may play key roles . CSN negatively regulates the activities of cullin-based E3 ubiquitin ligases by cleaving the Nedd8 modification from cullins [4] , [13] . The distinct phenotypes of each csn mutant suggest that they may contribute differently to this particular CSN function . To test this possibility , we examined the neddylation status of three N . crassa cullin proteins: Cul1 , Cul3 , and Cul4 . The neddylation status of these cullin proteins reflects the functional activity of the CSN complex in each strain . To monitor the neddylation state of cullins in vivo , we introduced a construct expressing Myc-tagged Cul1 , Cul3 , or Cul4 into the wild-type strain and into each csn knockout strain , respectively . Expression of Myc-Cul1 , Myc-Cul3 , or Myc-Cul4 proteins with the predicted molecular weight was confirmed by western blot analysis . Neddylated Myc-tagged cullins were distinguished from unneddylated Myc-tagged cullins based on their slower migration in an SDS-PAGE gel compared to the unneddylated forms . In the wild-type strain , neddylated Myc-Cul1 ( upper bands in Figure 4 ) represented less than 10% of the total of Myc-Cul1 ( Figure 4A ) . We demonstrated previously that disruption of the csn-2 gene causes the hyperneddylation of Cul1 [20] ( Figure 4A ) , confirming that normal functioning of the CSN complex is severely impaired in csn-2 mutants . Similarly , csn-1KO , csn-4KO , csn-5KO , csn-6KO , and csn-7KO mutants displayed increased Cul1 neddylation levels ( Figure 4A ) . The Csn5 subunit in S . pombe and D . melanogaster underlies the Nedd8 isopeptidase activity of the CSN [15] . Our results suggest that the N . crassa CSN-5 subunit performed a similar Nedd8 isopeptidase function , and that the other five subunits were also functional subunits for Cul1 deneddylation in N . crassa . However , the neddylated/deneddylated Cul1 levels in the csn-3KO mutant were similar to the pattern in the wild-type strain ( Figure 4A ) , suggesting that CSN-3 is not required for Cul1 deneddylation activity in N . crassa . The same Cul1 neddylated/deneddylated patterns were also observed in a csn-3 deletion mutant ( non-band background ) derived from FGSC11275 ( Fungal Genetics Stock Center ) using the Cul1 detection approach described above ( unpublished ) , further confirming that N . crassa CSN-3 is not required for the Cul1 deneddylation activity of the CSN complex . We further examined the neddylation states of two other N . crassa cullin proteins , Cul3 and Cul4 , in the wild-type strain and csn mutants . As shown in Figure 4B , the csn-3KO mutant had a Myc-Cul3 neddylated/deneddylated pattern that was similar to that in the wild-type strain , whereas in the other csn knockout mutants , Myc-Cul3 was hyperneddylated . The neddylated/deneddylated pattern of Myc-Cul4 was similar to the patterns of Cul1 and Cul3 in each strain ( Figure 4C ) . Taken together , these results indicate that CSN-3 is not critical for CSN deneddylation activity , suggesting that CSN-3 is not a key subunit in the CSN complex in N . crassa . This molecular evidence , together with the genetic data , strongly suggests that CSN-1 , CSN-2 , CSN-4 , CSN-5 , CSN-6 , and CSN-7 form the functional core of the CSN complex for cleavage of Nedd8 from cullins in N . crassa . Recent studies demonstrated that a major function of the CSN complex is to control the stability of E3 ubiquitin ligases in vivo [19]–[21] . To determine whether the CSN subunits contribute unequally to the stability control of CRLs in N . crassa , we examined the stabilities of Cul1 , SKP-1 , and FWD-1 , the major components of the SCFFWD-1 complex , in each of the csn strains . As shown in Figure 5A , Myc-Cul1 was very stable in the wild-type strain and the csn-3KO mutant , with a half-life of more than 9 h in the presence of cycloheximide ( CHX ) . In contrast , Myc-Cul1 in the csn-1 , csn-2 , csn-4 , csn-5 , csn-6 , and csn-7 mutants was unstable , with a half-life of less than 3 h ( Figure 5A and 5D ) . These results demonstrate that the functional core subunits of CSN are responsible not only for Cul1 deneddylation , but also for maintenance of Cul1 stability . In N . crassa , SKP-1 is an adaptor protein in the SCF complex that becomes very unstable in csn-2 mutants [20] . As shown in Figure 5B , Myc-SKP-1 remained very stable in the csn-3KO mutant and the wild-type strain , with a half-life of approximately 12 h . However , Myc-SKP-1 was unstable in the csn-1 , csn-4 , csn-6 , and csn-7 mutants , with a half-life of approximately 1 . 5–3 h ( Figure 5B and 5E ) . Interestingly , as in the wild-type strain and csn-3KO mutant , the stability of Myc-SKP-1 was not affected in the csn-5KO mutant ( Figure 5B and 5E ) , indicating that the key deneddylation isopeptidase subunit of the CSN functional core was dispensable for maintaining SKP-1 stability in the SCF complex . The F-box domain-containing protein FWD-1 is a component of the SCFFWD-1 complex; it specifically recognizes phosphorylated FRQ protein and targets it for ubiquitination , which is a key process for circadian clock control in N . crassa [20] , [29] . As shown in Figure 5C , FWD-1 levels were drastically reduced in the core csn subunit knockout mutants and in the csn-3 mutant , with a half-life of less than 3 h . In contrast , the FWD-1 protein remained very stable in the wild-type strain , with a half-life of more than 12 h ( Figure 5C and 5F ) . Together , these results indicate that the CSN is important for maintaining the stability of F-box domain–containing proteins , such as FWD-1 , in N . crassa . Although CSN-3 in the CSN complex was not required for deneddylation of Cul1 or for maintaining the stability of Cul1 and SKP-1 , it was required for preventing the degradation of FWD-1 . These observations suggest that CSN-3 is also required to maintain normal functioning of the intact CSN complex . Taken together , the differing stability of Cul1 , SKP-1 , and FWD-1 in the csn mutants indicates that each subunit of the CSN complex functions differently in maintaining the stability of SCF complexes in N . crassa . In N . crassa , Cul3-binding proteins have not been reported previously; therefore , we searched for BTB domain protein coding genes in the N . crassa genome and found eight predicted proteins with highly conserved BTB domains . To test the interactions between Cul3 and the BTB domain proteins , we created Myc-tagged BTB domain proteins and co-expressed each of them in the wild-type strain with Flag-tagged Cul3 . As shown in Figure 6A , BTB1 protein ( NCU04838 ) strongly interacted with Cul3 in the immunoprecipitation reaction , indicating that they may form a Cul3-BTB ubiquitin ligase complex in N . crassa . We next examined whether the stability of Myc-Cul3 was affected in each csn mutant . As shown in Figure 6B , Myc-Cul3 was very stable in the wild-type strain and the csn-3KO mutant , with a half-life of more than 12 h in the presence of CHX . In contrast , this protein was very unstable in the other csn mutants , with a half-life of approximately 1 . 5–3 h ( Figure 6B and 6D ) . These results indicate that the CSN functional core subunits were necessary for maintaining the stability of Cul3 in N . crassa . We then investigated the stability of BTB1 protein in the wild-type stain and csn mutants . Myc-BTB1 was very stable in the wild-type strain and the csn-3KO mutant , with a half-life of more than 12 h after CHX treatment; however , it was very unstable in other csn mutants , with a half-life of about 3 h ( Figure 6C and 6E ) . Taken together , these results further demonstrate that the functional core subunits of CSN were important for Cul3 deneddylation and maintaining the stability of the entire Cul3-BTB E3 complex in N . crassa . N . crassa Cul4 was previously shown to interact with DDB1 [30] . Therefore , we tested the effect of loss of different CSN subunits on the regulation of Cul4-DDB1 E3s . We showed above that the neddylation/deneddylation pattern of Cul4 in the csn-3 knockout strain was similar to that of the wild-type strain , in which the half-life of Myc-Cul4 was 12 h in the presence of CHX ( Figure 7A and 7C ) . Unexpectedly , Myc-Cul4 was very unstable in all of the csn mutants , with a half-life of approximately 3 h after CHX treatment ( Figure 7A and 7C ) . These results suggest that although CSN-3 is not in the deneddylation core of the CSN complex , it was necessary for maintaining the stability of Cul4 in N . crassa . We next measured the stability of DDB1 in the wild-type strain and csn mutants . As expected , Myc-DDB1 was very unstable in the csn mutants , with a half-life of approximately 3 h after CHX treatment ( Figure 7B and 7D ) , while it remained very stable in the wild-type strain , with a half-life of more than 12 h ( Figure 7B and 7D ) . Therefore , unlike in Cul1- or Cul3-based E3 complexes , all of the CSN subunits are required for maintaining the stability of Cul4-DDB1 ubiquitin ligases . We previously showed that in N . crassa , DCAF11 is an adaptor protein in a Cul4-DDB1 E3 ligase complex by association with DDB1 protein [31] . In the present study , we performed an immunoprecipitation assay to detect interactions between Myc-DCAF11 and Flag-Cul4 . As shown in Figure 8A , Myc-DCAF11 interacted with Flag-Cul4 , confirming that it forms an E3 complex with Cul4 and DDB1 proteins . To examine whether the adaptor protein DCAF11 is unstable in the csn mutants , we compared DCAF11 degradation rates in the wild-type and seven csnKO strains . As shown in Figure 8B , DCAF11 was stable in the wild-type strain , as a majority of DCAF11 was still present after 12 h of CHX incubation . In contrast , DCAF11 became undetectable after only 3 h of CHX treatment in the core csn mutants and in the csn-3KO strain , indicating that it was very unstable ( Figure 8B and 8G ) . The accelerated DCAF11 degradation rate in the csn mutants was likely due to its increased autoubiquitination , which is counteracted by normal CSN activity . If this is indeed the case , mutation of a conserved arginine in the WDXR motif of DCAF11 ( Figure 8C ) should disrupt binding of DCAF11 to the Cul4-DDB1 complex , thus preventing its autoubiquitination and degradation . As shown in Figure 8D , interactions between DDB1 and DCAF11 were disrupted by substitution of the conserved arginine with alanine in the DCAF11 WDXR motif . This point mutation also abolished interactions between DCAF11 and Cul4 ( Figure 8E ) . Indeed , Myc-tagged DCAF11 with an arginine-to-alanine point mutation was very stable and accumulated to reach high steady-state levels in all csn mutants , including the csn-3KO strain ( Figure 8F and 8H ) . Taken together , these data indicate that CSN is important for maintaining the stability of DCAF11 in N . crassa , probably by preventing its autoubiquitination . DCAF11 levels were also low in the csn-3 mutant , indicating that the functional core complex alone was not sufficient to protect Cul4-DDB1 E3 ligase complexes from autoubiquitination and degradation . Because the adaptor proteins FWD-1 and DCAF11 are very unstable in the csn-3 strain , maintenance of functional E3 ligase complexes may rely mostly on newly synthesized FWD-1 and DCAF11 proteins . These observations suggest that the CSN-3 subunit is also required to maintain the function of intact CSN complexes in protecting cullin-RING E3 ligase adaptor proteins from autoubiquitination . We next investigated whether loss of the CSN-3 subunit affects the protein levels of other CSN subunits and proper assembly of the CSN complex . Recent studies demonstrated that downregulation of CSN1 and CSN3 causes a proportional reduction in all CSN subunits and a decrease in levels of the holocomplex [32] . We first introduced a Myc-His-tagged CSN-1– , CSN-2– , CSN-4– , CSN-5– , CSN-6– , or CSN-7–expressing construct into a csn-3 mutant and a wild-type strain , respectively . Western blot analyses showed that Myc-His-CSN-2 became very unstable in the csn-3KO mutant , with a half-life of less than 3 h in the presence of CHX ( Figure 9A ) . In contrast , Myc-His-CSN-2 was very stable in the wild-type strains , with a half-life of more than 12 h ( Figure 9A ) . Other five Myc-His-CSN proteins remained very stable in the wild-type strain and in the csn-3KO mutant , with a half-life of more than 12 h ( Figure 9A ) . These results indicate that CSN-3 is required for maintaining the stability of the CSN-2 subunit in N . crassa . Expression of Myc-His-tagged CSN did not affect the phenotype of the csn-3KO mutant , suggesting that the CSN fusion protein may function similar to the endogenous counterpart subunit . Thus , we used above transformants to purify the CSN complex in the absence of the CSN-3 subunit . Myc-His-tagged CSN-1 , CSN-4 , CSN-5 , or CSN-7 protein was purified on a nickel column followed by immunoprecipitation using a c-Myc monoclonal antibody , respectively . As shown in Figure 9B , several major protein bands were detected in the Myc-His-CSN-4 , Myc-His-CSN-5 or Myc-His-CSN-7 sample , but not in Myc-His-CSN-1 sample and the wild-type strain ( a negative control ) . Liquid chromatography–mass spectrometry/mass spectrometry ( LC-MS/MS ) analysis of excised gel bands led to the identification of CSN-5 and CSN-6 in the Myc-His-CSN-4 purified products , CSN-4 and CSN-6 in the Myc-His-CSN-5 purified products , while CSN-4 , CSN-5 , and CSN-6 in the Myc-His-CSN-7 purified products , but no CSN-1 and CSN-2 were detected in any of these purifications ( Figure 9B ) . However , there was substantially more CSN-4 , CSN-5 or CSN-7 than other CSN subunits in the purification products from csn-3KO , as revealed by a silver-stained SDS-PAGE gel ( Figure 9B ) ; in contrast , the amount of Myc-His-CSN-2 was similar to that of other CSN subunits in a csn-2KO , QA-Myc-His-CSN-2 transformant ( Figure 9C ) . These results suggest that under this purification condition , CSN-4 , CSN-5 and CSN-6 formed a more stable subcomplex , while Myc-His-CSN-7 incorporated subcomplex with CSN-4 , CSN-5 , and CSN-6 . To test whether Myc-His-tagged CSN subunit incorporates into larger molecular mass complex in the absence of the CSN-3 subunit , we performed gel filtration using above purified Myc-His-tagged CSN proteins . As shown in Figure 9D , CSN-7 and CSN-5 fusion proteins were eluted in larger molecular mass fractions and lower molecular mass fractions , while CSN-2 fusion protein remain in high molecular mass fractions . These results confirmed that both Myc-His-CSN-7 and Myc-His-CSN-5 participate in the formation of CSN and the lower molecular mass form . These data indicate that although proper assembly of the N . crassa CSN complex is not affected in the csn-3KO mutant , the amount of CSN complex is decreased and subcomplexes such as CSN4/5/6 and CSN4/5/6/7 are formed in the absence of the CSN-3 subunit , further suggesting that the phenotypes we observed in csn-3 mutants are due to functional CSN subcomplexes .
In general , CSN complexes contain 7–8 subunits . Accurate assessment of the contribution of individual CSN subunits to the function of the complex as a whole in plants and animals has been difficult , because deletion of any CSN subunit can lead to lethality . Phenotypic features among plants with mutations in different CSN subunit genes are indistinguishable , and plant CSN mutants display almost overlapping misregulation of hormone and other response pathways [33]–[37] , indicating that plant CSN subunits function coordinately to support critical deneddylation activity . Fortunately , CSN subunit genes are not essential genes in fungi , such as yeast and N . crassa , which are therefore excellent model systems in which to investigate the function of individual CSN subunits . We successfully created knockout mutants of all of the individual csn subunits in N . crassa . Of the seven CSN subunits , deletion of CSN-1 , CSN-2 , CSN-4 , CSN-5 , CSN-6 , or CSN-7 caused similar defects in growth , development , circadian clock , light response , and temperature-entrained conidiation , while deletion of CSN-3 did not cause the defects detected in the other CSN mutants . Similar results were found for other organisms in previous studies . For example , in S . pombe , mutations of different CSN subunits cause distinct phenotypes [14] . In D . melanogaster , csn4- and csn5-null flies display different phenotypes [25] and different gene expression patterns [26] . These results , together with the findings of the present study , indicate that different subunits may have different roles in the CSN complex . Consistent with phenotypic analysis results , our molecular analyses demonstrated that CSN-3 was not required for cullin deneddylation , while deletion of any of the other six csn genes caused hyperneddylation of all three cullins , indicating that in N . crassa , these six CSN subunits were essential for cleavage of Nedd8 from the cullins of CRLs in vivo . Nedd8 modification of cullin positively regulates the activities of CRLs . Recent genetic and biochemical analyses demonstrated that the CSN complex is required for removal of Nedd8 from cullin proteins [4] , [13] , [17] , [18] . Thus , the differences in the growth and developmental phenotypes between csn-3 and the other csn mutants are due to the unequal contributions of different subunits to the CSN deneddylation function . Six of the conserved CSN subunits , CSN-1 , CSN-2 , CSN-4 , CSN-5 , CSN-6 and CSN-7 , likely act as a functional core for CSN deneddylation activity . This idea is supported by the finding that A . thaliana plants with an N-terminal deletion in the CSN1 subunit ( CSNCSN1–C231 ) exhibit a wild-type pattern of Cul1 neddylation , suggesting that these mutants have normal deneddylation activity [38] . Moreover , the core composition of the CSN complex may also explain why some lower eukaryotes , such as Candida albicans , Cyanidioschyzon merolae , and Saccharomyces cerevisiae , have fully functioning CSN complexes that lack individual subunits [2] , [39] . Because CSN is a highly conserved complex that is necessary for regulating the function of CRLs in higher eukaryotes , we propose that a basic functional CSN complex core may exist in these organisms , similar to that found in lower eukaryotes . CSN3 was first identified in A . thaliana as an essential regulator of light-mediated development [1] , [40] . Although it is the least-conserved subunit , CSN3 is a component of CSN complexes from plants to mammals . In A . nidulans , deletion of genes encoding CSN subunits 1 , 2 , 4 , or 5 resulted in identical blocks in fruit body formation [28] . However , the two nonconserved subunits C ( CSN-3 ) and H ( CSN-8 ) did not interact in a yeast two-hybrid experiment , suggesting that they may require other subunits or posttranslational modifications for stable interactions [28] . We found that deletion of csn-3 from the genome of N . crassa did not affect the neddylation of cullins and slightly increased the growth rate in the mutant strain compared to the wild-type strain . These findings suggest that the role of CSN-3 in the CSN complex is different from those of the other subunits . Hemizygous deletion of human chromosome 17 , band p11 . 2 results in a multiple congenital anomalies/mental retardation syndrome called Smith–Magenis syndrome ( SMS ) [41]–[43] . The deleted region spans 1 . 5–2 . 0 Mb of DNA , which contains about 20 genes , including CSN3 . To investigate the role of CSN3 in mammalian development and in Smit–Magenis syndrome , csn3 was disrupted in mice [44] . Interestingly , there are no visible defects in heterozygous csn3-disrupted mice , although the protein level was reduced . Embryonic development of homozygous Csn3−/− mice is arrested at an early developmental stage [44] . Although Csn2+/− heterozygous mice are phenotypically healthy , loss of Csn2 causes embryonic lethality [45] . These studies imply that CSN3 , the least-conserved subunit in the CSN complex , may not be important to the function of the CSN complex compared to CSN2 in mice . In the present study , we demonstrate that the six core subunits of CSN , but not CSN-3 , were essential for maintaining the stability of Cul1 in SCF complexes and of Cul3 and BTB proteins in Cul3-BTB E3 ubiquitin ligasess , while five subunits , but not CSN-3 or CSN-5 , were required for maintaining the stability of SKP-1 in the SCF complex . This molecular evidence further supports the idea that individual subunits of the CSN complex contribute differently to CSN functions . Consistent with the phenotype of the csn-3 mutant , CSN-3 does not appear to play an important role in maintaining the stability of these E3s in N . crassa . In mutants lacking different CSN subunits , autoubiquitination of FBPs is enhanced , resulting in increased instability . Several FBPs in fission yeast , N . crassa , and humans are under the protection of the CSN complex [19] , [20] , [46] . We further show that FWD-1 stability and levels were drastically reduced in the csn-3 mutant and other csn mutants , confirming that CSN-3 was required for preventing autoubiquitination of FBPs after destruction of their substrates . The modular architecture of SCF complex is apparently shared by several other cullin-RING E3 complexes , such as Cul3 , that directly interact with a family of substrate receptors through their common BTB domain , which has a Skp1-like structural fold [12] . Our results show that CSN-3 was not required for maintaining the stability of Cul1 , SKP-1 , Cul3 , or BTB protein in the SCF and SCF-like E3s . We further confirmed that CSN-3 was required for maintaining the stability of CSN-2 in the presence of CHX , and for normal levels of the CSN functional core complex . These data provide evidence that the functional core complex efficiently cleaved Nedd8 from cullins and protected scaffold components of the SCF and SCF-like E3s from autoubiquitination; however , it was not sufficient to protect the FBPs from autoubiquitination . Although FBP levels were also low in the csn-3 strain , levels of Cul1 and SKP-1 were not affected; some functional SCF complexes formed , most likely by incorporating newly synthesized FBPs , and mediated the degradation of their substrates . These data may explain the normal circadian rhythms that were observed in the csn-3 mutant , but not in other csn mutants . In contrast , all seven subunits of the CSN , including CSN3 , were required to maintain the stability of Cul4-DDB1 E3s in the presence of CHX . The difference in stability compared to SCF and SCF-like E3s is most likely due to architectural differences between Cul4-DDB1 E3s and SCF E3s; recent studies show that DDB1 displays a flexible linkage between the major protein binding domain ( BPA-BPC ) and the cullin binding domain ( BPB ) [10] , while SCF and SCF-like E3s exhibit more rigid architectures [47] . In support of this possibility , we found that autoubiquitination of DCAF11 was enhanced in all seven csn mutants . However , disruption of the interactions between DCAF11 and DDB1 completely abrogated the autoubiquitination and degradation of DCAF11 in csn mutants . These data suggest that the instability of Cul4-DDB1 E3s in csn mutants could also be due to the strong interactions among their components , which are more powerful than those in the SCF and SCF-like E3s . In this regard , the function of CSN-3 is similar to that of the functional core subunits . These results provide new insight into how CSN functions to protect different CRLs . Based on these data , we speculate that the different subunits play different roles in maintaining the stability of different CRLs , and that the biochemical functions of the CSN subunits are distinct from one another . Although CSN-3 is the least-conserved subunit , it is found in all of the CSN complexes studied to date , from fungi to mammals [28] , [40] , [44] . Thus , we propose that CSN-3 may have a similar role in regulating the function of CRLs in higher eukaryotes .
The N . crassa strain 87-3 ( bd , a ) was used as the wild-type strain in this study . The bd ku70RIP strain , which was generated previously [48] , was used as the host strain for creating the csn knockout mutants . The csn-2KO and csn-2KO , his-3 strains used in the present study were also created previously [20] . The newly created csn knockout strains were csn-1KO , csn-3KO , csn-4KO , csn-5KO , csn-6KO , and csn-7KO strains; his-3 strains were also created for each csn deletion . The 301-6 ( bd , his-3 , A ) strain and csn , his-3 strains were the host strains for the his-3 targeting construct transformation . Liquid culture conditions were the same as described previously [49] . For quinic acid–induced protein expression , 0 . 01 M QA ( pH 5 . 8 ) was added to liquid medium containing 1× Vogel's medium , 0 . 1% glucose , and 0 . 17% arginine [50] . The medium for the race tube assays contained 1× Vogel's medium , 0 . 1% glucose , 0 . 17% arginine , 50 ng/ml biotin , and 1 . 5% agar . To generate csn gene knockout strains , the entire open reading frames ( ORFs ) of csn genes were deleted by replacement with the hph gene [51] . The gene replacement cassette containing hph was introduced into the bd , ku70RIP strain by electroporation . The transformants with hph at the csn locus were crossed with 301-6 ( bd , his-3 , A ) . Ascospores of the crosses were germinated on plates containing hygromycin and histidine . PCR analyses for hph and csn the ORF region were used to confirm the csn knockout strains . Full-length ORFs and the 3′-UTR for Cullin3 , BTB1 , CSN-1 , CSN-4 , CSN-5 , CSN-6 , or CSN-7 protein were amplified from genomic DNA by PCR and cloned into the pqa-5Myc-6His and pqa-3Flag plasmids . The previously constructed plasmids pqa-Myc-Cul1 , pqa-Myc-His-SKP-1 , pqa-Myc-His-CSN-2 [20] , pqa-Myc-His-Cul4 , pqa-Myc-His-DDB1 , pqa-3Flag-Cul4 , pqa-3Flag-DDB1 [30] and pqa-Myc-His-DCAF11 were also used for the his-3 targeting transformation in 301-6 and csnKO , his-3 strains . Protein extraction , quantification , western blot analysis , protein degradation assays , and immunoprecipitation assays were performed as described previously [20] , [30] . Western blot analyses using a monoclonal c-Myc antibody ( 9E10 , Santa Cruz Biotechnology ) or Flag antibody ( F3165-5MG , Sigma ) were performed to identify the positive transformants . Immunoprecipitates or equal amounts of total protein ( 40 µg ) were loaded into each protein lane . After electrophoresis , proteins were transferred onto PVDF membrane , and western blot analysis was performed using c-Myc antibody , Flag antibody , or FWD-1 antiserum . The csn-3KO Myc-His-CSN-1 , 4 , 5 , or 7 strain , wild-type strain ( negative control ) , and csn-2KO Myc-His-CSN-2 strain ( positive control ) were cultured for approximately 24 h in constant light ( LL ) in liquid medium containing QA ( 0 . 01 M QA , 1× Vogel's medium , 0 . 1% glucose , and 0 . 17% arginine ) . Approximately 15 g of tissue from each strain grown in LL was harvested . The purification procedure was the same as described previously [20] . Fractions containing purified Myc-His-CSN proteins were immunoprecipitated by adding 30 µL of c-Myc monoclonal antibody–coupled agarose beads ( 9E10AC , Santa Cruz Biotechnology ) . The precipitates of Myc-His-CSN samples were analyzed by SDS-PAGE ( 4%–20% and 15% acrylamide , respectively ) , which was subsequently silver stained following the manufacturer's instructions ( ProteoSilver Plus , Sigma ) . Specific bands were excised and subjected to tryptic digestion and LC-MS/MS . The protocol of gel filtration chromatography was the same as described previously [52] . Briefly , purified proteins ( 400 µg ) were loaded onto a Superdex 200 ( GE ) gel filtration column that was equilibrated with 25 mL ( 150 mM NaCl , 20 mM Tris Cl pH 7 . 4 ) . The proteins were eluted in the same buffer at a flow rate of 0 . 3 mL/min . Fractions of 0 . 4 mL were collected starting from the onset of the column void volume ( 8 . 0 mL ) and finishing at 18 mL ( 25 fractions ) . 20 µL of each fraction were prepared in 20 µL of 2× SDS loading buffer , separated by 7 . 5% SDS-PAGE , then transferred onto PVDF membrane . Western blot analysis was performed using c-Myc antibody ( 9E10 , Santa Cruz Biotechnology ) . | Protein degradation is precisely controlled in cells . The ubiquitin-mediated protein degradation pathway is highly conserved in eukaryotes , and the activity of ubiquitin ligases is regulated by the Cop9 signalosome ( CSN ) , a multisubunit complex that is evolutionarily conserved from yeast to humans . Determining how the CSN complex functions biologically is crucial for understanding regulation of the ubiquitin-mediated protein degradation pathway . The filamentous fungus N . crassa is commonly used to study protein degradation . Its CSN complex contains seven subunits ( CSN-1 to CSN-7 ) . In this study , we generated knockout mutants of individual CSN subunits and observed the phenotypes of each mutant . We demonstrated that six of the seven CSN subunits were essential for cleaving the ubiquitin-like protein Nedd8 from cullin proteins ( which act as scaffolds for ubiquitin ligases ) . In contrast , loss of the CSN-3 subunit had no effect on cullin neddylation . We also found that each CSN subunit had distinct roles in maintaining the stability of key components of cullin-based ubiquitin ligases . In summary , we systematically investigated the unequal contributions of CSN subunits to deneddylation and the maintenance of cullin-based ubiquitin ligases in N . crassa . Our work establishes a framework for understanding the function of CSN subunits in other eukaryotes . | [
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] | 2010 | Role of Individual Subunits of the Neurospora crassa CSN Complex in Regulation of Deneddylation and Stability of Cullin Proteins |
Diabetic kidney disease ( DKD ) is the most common etiology of chronic kidney disease ( CKD ) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus . Approximately 45% of U . S . patients with incident end-stage kidney disease ( ESKD ) have DKD . Independent of glycemic control , DKD aggregates in families and has higher incidence rates in African , Mexican , and American Indian ancestral groups relative to European populations . The Family Investigation of Nephropathy and Diabetes ( FIND ) performed a genome-wide association study ( GWAS ) contrasting 6 , 197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American , African American , Mexican American , or American Indian ancestry . A large-scale replication and trans-ethnic meta-analysis included 7 , 539 additional European American , African American and American Indian DKD cases and non-nephropathy controls . Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25 . 2 in American Indians ( P = 5 . 74x10-9 ) . The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 ( rs955333; P = 1 . 31x10-8 ) , with directionally consistent results across ethnic groups . These 6q25 . 2 SNPs are located between the SCAF8 and CNKSR3 genes , a region with DKD relevant changes in gene expression and an eQTL with IPCEF1 , a gene co-translated with CNKSR3 . Several other SNPs demonstrated suggestive evidence of association with DKD , within and across populations . These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD .
Diabetic kidney disease ( DKD ) is a devastating complication in patients with diabetes mellitus ( DM ) and is associated with high risk for cardiovascular disease and death . [1 , 2] DKD is the leading cause of end-stage kidney disease ( ESKD ) requiring renal replacement therapy in developed nations; these procedures incur high healthcare costs with great personal , family and societal burden . [3] The prevalence of DKD continues to rise in the United States in proportion to the growing prevalence of DM . Unfortunately , intensification of glycemic , lipid and blood pressure control have not dramatically impacted the prevalence of DKD . [3 , 4] Hyperglycemia alone is insufficient to cause DKD . Genetic factors appear critical in its pathogenesis based upon variable incidence rates of DKD between population groups , aggregation of DKD-associated ESKD in families , and the highly heritable nature of diabetic renal histologic changes , estimated glomerular filtration rate ( eGFR ) and proteinuria . [5] Genome-wide association studies ( GWAS ) have identified multiple loci for kidney function and chronic kidney disease ( CKD ) in population- and community-based cohorts , primarily of European ancestry . [6–10] However , CKD phenotypes in many studies included minimally to moderately reduced eGFR , not fully reflective of the progressive forms of CKD seen in kidney disease clinics . In early reports , published GWAS signals for DKD were equivocal , confounded by small sample sizes and failure to consistently replicate . Recently , the GEnetics of Nephropathy: an International Effort ( GENIE ) consortium identified genome-wide significant , replicated signals in a meta-analysis of over 12 , 000 type 1 ( T1 ) DM patients with DKD of European ancestry . [9] Type 2 ( T2 ) DM is far more prevalent than T1DM , accounting for 90% of cases worldwide and for the majority of prevalent cases of DKD . Relative to European Americans ( EAs ) with T2DM , African American ( AA ) , American Indian ( AI ) , and Mexican American ( MA ) patients with T2DM are disproportionately affected by severe DKD , [3] yet under-represented in genetic analyses . Defining the underlying genetic architecture responsible for advanced T2DM-associated kidney disease in multiple populations could provide critical insights into pathogenesis and identify new molecular targets for therapy . We report the results of a GWAS in AA , EA , MA , and AI patients with DKD enrolled in the National Institute of Diabetes and Digestive and Kidney Diseases ( NIDDK ) -sponsored “Family Investigation of Nephropathy and Diabetes” ( FIND ) [11] and the corresponding large replication study and trans-ethnic meta-analysis .
The only locus that reached genome wide significance for DKD in the trans-ethnic meta-analysis encompassing all FIND Discovery and Replication samples was rs955333 on chromosome 6 ( minimum p-value 1 . 31x10-8 [additive]; minimum p-value 9 . 02x10-11 [dominant] ) ( Table 2 ) . Fig 1 contains the Manhattan plot for the meta-analysis across all ancestries included in the Discovery and Replication samples . Consistent directions of association were present in three ethnic groups ( only AA samples did not pass QC ) and several supporting single nucleotide polymorphisms ( SNPs ) were detected in the region ( regional plot in Fig 2 ) . This SNP lies between the SR-like carboxyl-terminal domain associated factor 8 gene ( SCAF8 ) and the connector enhancer of KSR family of scaffold proteins gene ( CNKSR3 ) , suggesting a possible role in transcription regulation . CNKSR3 is a direct mineralocorticoid receptor target gene involved in regulation of the epithelial sodium channel ( ENaC ) on the apical membrane of cells in the distal nephron . [12] CNKSR3 is highly expressed in the renal cortical collecting duct and upregulated in response to physiologic aldosterone concentrations . ENaC precisely regulates renal sodium absorption and plays important roles in maintenance of plasma volume and blood pressure . Ziera et al . [12] suggested that CNKSR3 , a PSD-95/DLG-1/ZO-1 ( PDZ ) domain containing protein , inhibits the RAS/ERK signaling pathway , stimulating ENaC activity with enhanced renal sodium absorption . More recently , CNKSR3 was shown to function as an aldosterone-induced scaffolding platform that orchestrated assembly of ENaC and its regulators Nedd4-2 , Raf-1 and SGK-1 and was essential for stimulation of ENaC function by aldosterone . [13] Clinically , renin-angiotensin-aldosterone system ( RAAS ) blockade serves as a mainstay of therapy for patients with DKD and other proteinuric kidney diseases . [14 , 15] Inhibition of aldosterone may further limit renal fibrosis , independent of natriuretic effects . [16 , 17] Hence , significant association between DKD and markers near CNKSR3 is consistent with clinical trial data demonstrating that blockade of the renin angiotensin system or the aldosterone receptor slows DKD progression . However , further experiments are needed to demonstrate that the associated SNP regulates the pathogenesis of progressive DKD . Further studies will be necessary to assess if the CNKSR3 regulates DKD pathogenesis indirectly by its effects on ENaC activity or directly by promoting aldosterone-dependent fibrosis . Less is known about the function of SCAF8 , also known as RBM16 . SCAF8 is a RNA maturation factor recruited to the carboxy-terminal domain of RNA polymerase II in a phosphorylation-dependent manner . [18] It also is a target for ataxia telangiectasia mutated ( ATM ) kinase , a crucial component of the DNA damage response required for DNA repair and cell cycle control . [19] ATM kinase is associated with responsiveness of patients with DM to the insulin sensitizer metformin in some but not all studies . [20 , 21] Thus , genes in the region of rs955333 are suggestive of DKD-related pathogenesis . GWAS loci identify elements that may regulate gene expression , and recent data indicate GWAS associations are located in regions bounded by recombination hot spots near non-coding causal variants , which regulate transcription . [22 , 23] We next contrasted transcript abundance of the genes within the megabase region centered on rs955333 , TIAM2 , SCAF8 , CNKSR3 , IPCEF1 and OPRM1 , in DKD and living donor kidney biopsies . DKD biopsies were obtained from European and AI cohorts and were analyzed separately . All five genes show statistically significant differential expression in at least one kidney tissue compartment of one population . SCAF8 steady state mRNA levels show increased expression in DKD compared to living donor biopsies in glomerular and tubulo-interstitial compartments of both populations ( S2B Table ) ; TIAM2 and OPRM1 show glomerular-specific differential expression; IPCEF1 is repressed in both tissue compartments of AI subjects; and CNKSR3 is increased in the tubulo-interstitial compartment of AIs ( S2B Table ) . Normalized tubulo-interstitial expression of CNKSR3 correlated with urine albumin ( r = 0 . 78 , q = 0 . 0056 ) and urine albumin:creatinine ratio ( UACR ) ( r = 0 . 74 , q = 0 . 0107 ) . In addition , IPCEF1 , located downstream of CNKSR3 , has been reported to be translated with CNKSR3 as one protein , [24] and has a tubulo-interstitial expression quantitative trait locus ( eQTL ) ( NM_001130699 , rs249964 , P = 2 . 34E-04 ) ( S2A Table ) . LD between this SNP and the sentinel variants in the region significantly associated with DKD in the trans-ethnic ( rs955333 ) and AI association analysis ( rs12523822; see below ) is negligible ( D’ = 0 . 43 , r2 = 0 . 01 in AI ) . However , tubulo-interstitial expression of IPCEF1 in kidney tissue from AIs was significantly correlated with the DKD phenotype UACR ( r = -0 . 54 , q = 0 . 031 ) . These studies were limited by the small number of available biopsies the narrow criteria used to define the region of interest ( see Methods ) . As proxies , disease-dependent differential gene expression and the rs249964 eQTL demonstrate DKD regulatory activity in the locus . Significant results of eQTL and differential gene expression analyses for other loci in Table 2 are also sown in S2A Table and S2B Table , respectively . No SNP reached genome-wide significance ( P<5x10-8 ) in the AA GWAS; however , a number provided suggestive evidence for association with DKD ( Table 3; S5A Table and S6A Table summarize the top 200 SNP associations in the discovery GWAS and replication study , respectively ) . The strongest associations were found within the apolipoprotein L1 ( APOL1 ) and non-muscle heavy chain 9 gene ( MYH9 ) region on 22q ( Table 2 , Discovery + FILR meta-analysis: rs5750250 , P = 7 . 7x10-8; rs136161 , P = 5 . 23x10-7 ) . Since G1 and G2 variants of APOL1 are strongly associated with non-diabetic nephropathy in AA patients , [25–27] the G1/G2 compound risk was modeled under a recessive genetic model and these variants accounted for the associations on 22q in Table 2 ( rs5750250 P = 7 . 70x10-8 , OR = 1 . 27; rs136161 P = 5 . 23x10-7 , OR = 1 . 36 ) . Association with G1/G2 within APOL1 likely exists due to inclusion of non-FIND AA cases with coincident DM and unrecognized non-diabetic kidney disease . [28] APOL1 was not associated with T2D-ESKD in a logistic regression analysis adjusting for age , gender and global ancestry restricted to FIND MALD and CHOICE ( Choices for Healthy Outcomes In Caring for End-stage renal disease ) study cases meeting the original FIND DKD case definition ( rs73885319 P = 0 . 1098; rs71785313 P = 0 . 1182 ) . [29] Regions beyond 22q provided suggestive evidence of association in the AA Discovery + FILR meta-analysis including rs1298908 on 10q22 ( OR = 1 . 36 , P = 8 . 83x10-7 ) between MAT1A and ANXA11 , in a region dense with regulatory elements and transcription factors . There was also an association on 3p26 ( rs304029 , OR = 1 . 26 P = 1 . 10x10-6 ) within inositol 1 , 4 , 5-trisphosphate receptor , type 1 ( ITPR1 ) , a gene involved in cerebellar and autoimmune disorders but not renal involvement . [30] The genes in these other candidate regions ( ANXA11 , MAT1A and ITPR1 ) also show statistically significant differential expression in at least one population and compartment; as do IGSF22 near candidate rs11766496 on chromosome 11 , and TNFRSF19 near rs95107795 on chromosome 13 . Other top AA associated regions in Table 2 do not have clear connections to kidney disease . Since APOL1 association likely reflected inclusion of non-FIND cases with non-diabetic nephropathy , a GWAS was re-computed within AAs in the discovery sample , which only included subjects lacking two APOL1 risk variants . The top 200 associations from this GWAS are summarized in S7 Table . The correlation between the–log10 ( p-value ) for GWAS with and with AA subjects with and without two APOL1 risk variants is r = 0 . 82 ( S4 Fig ) . The top association in this subset GWAS was rs2780902 on 1p31 ( OR = 0 . 52 , P = 2 . 98x10-7 ) within Janus kinase 1 ( JAK1 ) , a member of the protein-tyrosine kinases . [31] The ENCODE data shows that this SNP resides within a region with numerous transcription factors and DNase I hypersensitivity sites . JAK1 is a widely expressed membrane associated phosphoprotein and is involved in interferon transduction pathway . This kinase links cytokine ligand binding to tyrosine phosphorylation of various known signaling proteins and the signal transducers and activators of transcription ( STATs ) . Another interesting association among the top 10 associations is rs2596230 on 15q14 ( OR = 1 . 56 , P = 9 . 36x10-6 ) within ryanodine receptor 3 ( RYR3 ) . [32] The protein encoded by RYR3 functions to release calcium from intercellular storage in many cellular processes and the gene is expressed in the kidney . The closely related gene , RYR2 , is associated with albuminuria . [33] Our prior analyses of transcript expression in DKD biopsies provide additional support for the associations . Both JAK1 and RYR3 ( and RYR2 ) show differential expression that is restricted to the European subjects with Stage III and Stage IV CKD . JAK1 expression is increased in DKD in both compartments , while RYR3 and RYR2 are depressed in the glomerulus . [34] We also recomputed the genome wide discovery and trans-ethnic meta-analysis removing AA subjects with APOL1 . The top 200 associations are summarized in S8 Table . Several regions provided evidence of association with DKD in AIs ( Table 3; S5B Table and S6B Table summarize the top 200 SNP associations in the discovery GWAS and replication study , respectively ) . The strongest association was with rs12523822 on 6q . 25 in the SCAF8-CNKSR3 gene region ( OR = 0 . 57 , P = 5 . 74x10-9 ) . This SNP is in strong LD with rs955333 , the top hit in the trans-ethnic meta-analysis ( r2 = 0 . 96 in AI unrelated controls ) ; S5 Fig graphically illustrates the extended linkage disequilibrium in this region in all but the AA samples . The A allele at rs955333 is the ancestral allele and confers susceptibility to DKD ( as the G allele has OR<1 in Table 2 ) ; the A allele has a frequency of 0 . 76 in the American Indian samples and 0 . 85 in European American samples , but is nearly monomorphic in African American samples . The allele frequencies are very similar in population-based samples: 0 . 85 in HapMap CEU , 1 . 00 in YRI , 0 . 77 in MEX and 0 . 76 in full-heritage American Indians from the southwestern United States ( R Hanson , personal communication ) . Thus , the high risk allele at this locus does not appear to be Amerindian specific . The p-value for association in European Americans is 0 . 0013 and 1 . 3x10-6 in American Indian , suggesting that the signal does not come entirely from American Indians samples . Further fine-mapping or sequencing will be necessary to fully characterize the association signal within and across ethnic groups . Another association that approached genome-wide significance was rs13254600 ( OR = 0 . 58 , P = 5 . 54x10-8 ) on 8q24 within WD repeat domain 67 ( WDR67 ) . This gene is expressed in a wide variety of tissues , including kidney , and may affect cellular membrane functions by regulating Rab GTPase activity . [35] TBC1D31 ( WDR67 ) mRNA is increased in both compartments of kidney tissue from AIs , but only in the glomerulus for European subjects with more advanced DKD . Another SNP of interest is rs10019835 ( OR = 0 . 70 , 5 . 47x10-7 ) on 4q32 within guanylate cyclase 1 , soluble , alpha 3 ( GUCY1A3 ) ; the protein encoded by GUCY1A3 serves as a receptor for nitric oxide , [36] which through its role in endothelial function may be a mediator of DKD . [37] GUCY1A3 is differentially expressed in both tissue compartments and both DKD biopsy cohorts , and shows one of the strongest differences of all genes in candidate regions ( especially among the European subjects who have more advanced DKD ) ( S3A Table and S3B Table; S6 Fig ) . In addition , the candidate SNP rs10019835 has a tubulo-interstitial specific eQTL with the full-length isoform of GUCY1A3 ( NM_000856 , P = 4 . 97x10-4 ) . The shortest isoform of the gene ( NM_001130687 ) has a glomerular eQTL with rs12504357 ( P = 2 . 63x10-5 ) , an intronic SNP that is 5kb upstream of the associated variant . These two eQTL SNPs have D’ = 1 in some populations , likely reflecting low allele frequencies in the reference populations . Integrin alpha 6 ( ITGA6 , rs13421350 , 2q31 , OR = 0 . 58 , P = 5 . 54x10-8 ) is involved in cell adhesion and is expressed in the kidney . The gene shows negative differential expression in Europeans with DKD , and it has both glomerular and tubulo-interstitial eQTL . The glomerular eQTL is with the SNP rs6758468 ( P = 5 . 41x10-4 ) , which is 143kb from the candidate; while the tubulo-interstitial eQTL is with rs12469788 ( P = 3 . 26x10-4 ) , which is 5kb from the candidate with D’ = 1 , but negligible r2 . Finally , rs10952362 on 7q36 near XRCC2 ( rs10952362 , OR = 1 . 91 , P = 7 . 99x10-8 ) , a gene involved in DNA repair was strongly associated with DKD . [38] We find that XRCC2 is repressed in the tubulo-interstitial kidney tissue from AIs . EA subjects comprised the smallest group within FIND and power to detect variants associated with DKD was limited ( S3 Fig ) . None of the associations in the EA Discovery + FILR meta-analysis had a p-value <10−5 ( Table 3; S5C Table and S6C Table summarize the top 200 SNP associations in the discovery GWAS and replication study , respectively ) . Several suggestive associations were identified in the MA Discovery GWAS ( Table 3; S5D Table summarizes the top 200 SNP associations in the GWAS ) . No replication cohort was available to be genotyped in FILR , so only the Discovery GWAS and trans-ethnic meta-analysis are reported ( Tables 2 and 3 ) . The strongest association was on 12q24 for rs7975752 , located ~242 kb downstream of the mediator complex subunit 13-like ( MED13L ) gene ( OR = 1 . 76 , P = 1 . 67 x 10−6 ) . MED13L functions as a transcriptional coactivator for RNA polymerase II-transcribed genes . While its functional significance in DKD is unclear , gene variants 4 Mb downstream ( rs614226 ) and upstream ( rs653178 ) on 12q24 show genome-wide significant association with ESKD [9] and CKD [39] in Europeans . We see that MED13L is repressed in both compartments in kidney tissue from AIs but only in the glomerular transcriptome in the European subjects . Association was observed between DKD and rs731565 ( P = 4 . 06 x 10−6 ) residing within an intronic region of the contactin-associated protein-like 2 ( CNTNAP2 ) gene on 7q36 . SNP rs7805747 , approximately 4 Mb downstream from rs731565 has been associated with CKD in European populations [39] Finally , rs4849965 , 1 . 2 Mb upstream of the SRY-related HMG-box 11 ( SOX11 ) gene on 2p25 . 2 trended toward association with DKD ( OR 1 . 50 , 95% CI 1 . 26–1 . 79; P = 6 . 18x10-6 ) and has previously been associated with CKD in Europeans . [39] We find that absolute tubulo-interstitial expression of SOX11 in AIs is correlated with ACR ( r = 0 . 66 , q = 0 . 029 ) . The current FIND GWAS comprises the largest genetic analysis for severe DKD based upon risk for progression to ESKD in EA and high-risk non-European ethnic groups including AAs , AIs , and MAs . As in other GWAS , results support a role for multiple DKD susceptibility genes , each with weak effects . A number of the SNPs most strongly associated with DKD had additional support from compartment-specific gene expression measures and eQTL analysis obtained in European and American Indian populations . A novel chromosome 6q25 . 2 DKD locus was identified in AI samples; SNPs in this region had genome-wide significant association and consistent directions of effect in the meta-analysis across all ethnic groups . Independent support for this region comes from an association with serum creatinine/eGFR in a GWAS in East Asian populations ( P = 2 . 6 x 10−5 at rs4870304 ) [40] . Strengths of the FIND GWAS were the severe phenotype in cases , focus on DKD in T2D , and inclusion of non-European populations . The 6q25 . 2 locus requires fine mapping and additional replication in independent sample sets of diabetic subjects with and without DKD that has sufficient power to detect associated , common variants with moderate effect size . Once localized and replicated , functional studies in animal and cell culture models will be necessary to discover the biological mechanisms responsible for the association of DKD with the underlying genetic architecture . As in other GWAS for complex disease , many previously identified DKD loci were not replicated in the FIND analyses . The inconsistency between our data and published DKD GWAS could reflect that FIND limited the DKD case group to subjects with ESKD and DKD with heavy proteinuria felt to be at high risk for progression to ESKD . FIND did not include microalbuminuric participants as “cases” in the Discovery cohort , choosing instead to focus on advanced nephropathy . However , some microalbuminuric participants with ACR<100 mg/g were included in the replication analysis . Prior GWAS focused on European and Asian DKD populations , often enriched for T1D-associated DKD . Genetic associations may not replicate across other populations; for example , association of APOL1 variants with non-diabetic kidney disease is limited to populations with recent African ancestry . Another possible interpretation is the variants , which regulate DKD pathogenesis , are distinct for T1D and T2D , although a meta-analysis including both T1D and T2D subjects may identify shared loci . Finally , the DKD phenotype in the FIND GWAS relied on standard , stringent clinical criteria for advanced DKD . This approach limited phenotypic heterogeneity but potentially minimized the utility of cross-study comparisons . Although heavy proteinuria is a hallmark of DKD , recent analyses suggest approximately one third of patients with diabetes and an eGFR <60 ml/min per 1 . 73 m2 had normal urinary protein excretion . [4] This would justify the focus of FIND on advanced DKD . Although not the only DKD phenotype with a genetic component , several investigators recently proposed using ESKD as the optimal DKD phenotype in genetic association studies . [41 , 42] The availability of bio-samples from patients with advanced DKD is limited . Therefore , entry criteria in the present replication cohorts were loosened to increase sample size; this likely included a small number of participants with non-diabetic CKD ( or DKD less likely to progress to ESKD ) . The AA non-FIND cases used in our replication cohort appear to have included individuals with DM and coincident focal segmental glomerulosclerosis ( FSGS ) , an effect addressed via partitioning based on APOL1 G1 and G2 . [28] As in all GWAS , some non-nephropathy controls may develop DKD . This effect would bias results toward the null making it less likely to detect significant association . FIND was well-powered to detect common risk variants with moderate effect sizes shared across ethnic groups . It was also well powered to use differences in effect sizes to help localize the region of association via transracial mapping . However , it was not powered to detect modest ethnic-specific effects that are not shared with another ethnicity or gene-gene interactions . Thus , these ethnic-specific scans provide important hypothesis generating results for subsequent meta-analyses , pathway enrichment analyses and hypothesis generation .
The FIND was completed in accordance with the principles of the Declaration of Helsinki . Written informed consent was obtained from all participants . The Institutional Review Board at each participating center ( Case Western Reserve University , Cleveland , OH , Harbor-University of California Los Angeles Medical Center , Johns Hopkins University , Baltimore , National Institute of Diabetes and Digestive and Kidney Diseases , Phoenix , AZ , University of California , Los Angeles , CA , University of New Mexico , Albuquerque , NM , University of Texas Health Science Center at San Antonio , San Antonio , TX , Wake Forest School of Medicine , Winston-Salem , NC ) approved all procedures , and all study subjects provided written informed consent . A certificate of confidentiality was filed at the National Institutes of Health . See Supplementary Methods ( S1 Text ) . The DNA samples that comprise the Discovery cohorts , plus an additional 244 blind duplicates were genotyped on the Affymetrix Genome-Wide Human 6 . 0 SNP array ( see S1 Text Supplemental Methods for details ) . The FILR replication samples were genotyped for 3 , 937 SNPs selected based on the strength of the statistical association from the Discovery GWAS . Additional SNPs were included based on the FIND eQTL association and candidate gene SNPs previously reported to be associated with DKD ( see S1 Text Supplemental Methods for details ) . Specifically , within each ancestry group , the SNPs with the strongest statistical evidence of association were identified; a few additional SNPs from each region with supportive but weaker evidence of association were also identified ( i . e . , associations due to LD but r2<0 . 95 with the primary associated SNP ) . This redundancy was designed to limit the number of regions not represented in the replication study due to genotyping failure . In total , 3 , 019 SNPs ( 821 AA , 790 AI , 608 EA , and 800 MA ) were genotyped for FILR based solely on statistical association with DKD within an ethnicity . The trans-ethnic meta-analysis of the discovery cohort identified another 436 SNPs nominally associated with DKD ( p<0 . 0003 ) . In addition , 482 SNPs ( 121 AA , 133 AI , 122 EA , 14 MA , meta-analysis 92 ) were chosen with the smallest L2-norm ( i . e . , Euclidean distance ) of the–log10 ( p-values ) from GWAS and eQTL association analyses , provided that p <0 . 01 from GWAS . Here , the L2-norm was defined relative to the maximum of the–log10 ( p-values ) from the GWAS and eQTL and provides an ordering of the combined evidence for eQTL and association with DKD . SNP associations in FILR were considered “replicated” if both the association reached statistical significance and direction of the association was consistent with the Discovery analysis . Finally , 278 AIMs were genotyped to allow for adjustment of potential population substructure . Thus , FILR was designed as a replication study and not a large-scale trans-ethnic fine-mapping study . Subsequent studies will complete fine-mapping to localize associations . | Type 2 diabetes is the most common cause of severe kidney disease worldwide and diabetic kidney disease ( DKD ) associates with premature death . Individuals of non-European ancestry have the highest burden of type 2 DKD; hence understanding the causes of DKD remains critical to reducing health disparities . Family studies demonstrate that genes regulate the onset and progression of DKD; however , identifying these genes has proven to be challenging . The Family Investigation of Diabetes and Nephropathy consortium ( FIND ) recruited a large multi-ethnic collection of individuals with type 2 diabetes with and without kidney disease in order to detect genes associated with DKD . FIND discovered and replicated a DKD-associated genetic locus on human chromosome 6q25 . 2 ( rs955333 ) between the SCAF8 and CNKSR genes . Findings were supported by significantly different expression of genes in this region from kidney tissue of subjects with , versus without DKD . The present findings identify a novel kidney disease susceptibility locus in individuals with type 2 diabetes which is consistent across subjects of differing ancestries . In addition , FIND results provide a rich catalogue of genetic variation in DKD patients for future research on the genetic architecture regulating this common and devastating disease . | [
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] | [] | 2015 | Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND) |
Meiosis is a specialized eukaryotic cell division that generates haploid gametes required for sexual reproduction . During meiosis , homologous chromosomes pair and undergo reciprocal genetic exchange , termed crossover ( CO ) . Meiotic CO frequency varies along the physical length of chromosomes and is determined by hierarchical mechanisms , including epigenetic organization , for example methylation of the DNA and histones . Here we investigate the role of DNA methylation in determining patterns of CO frequency along Arabidopsis thaliana chromosomes . In A . thaliana the pericentromeric regions are repetitive , densely DNA methylated , and suppressed for both RNA polymerase-II transcription and CO frequency . DNA hypomethylated methyltransferase1 ( met1 ) mutants show transcriptional reactivation of repetitive sequences in the pericentromeres , which we demonstrate is coupled to extensive remodeling of CO frequency . We observe elevated centromere-proximal COs in met1 , coincident with pericentromeric decreases and distal increases . Importantly , total numbers of CO events are similar between wild type and met1 , suggesting a role for interference and homeostasis in CO remodeling . To understand recombination distributions at a finer scale we generated CO frequency maps close to the telomere of chromosome 3 in wild type and demonstrate an elevated recombination topology in met1 . Using a pollen-typing strategy we have identified an intergenic nucleosome-free CO hotspot 3a , and we demonstrate that it undergoes increased recombination activity in met1 . We hypothesize that modulation of 3a activity is caused by CO remodeling driven by elevated centromeric COs . These data demonstrate how regional epigenetic organization can pattern recombination frequency along eukaryotic chromosomes .
During meiosis homologous chromosomes pair and undergo reciprocal exchange , to produce crossovers ( COs ) . COs are initiated by SPO11-catalyzed DNA double strand breaks ( DSBs ) , which are resected to generate single-stranded 3′ tails on either side of the break ( ssDNA ) [1] . The ssDNA can invade a non-sister chromatid to form an intermediate D-loop structure , which may proceed to form a double Holliday junction that can be resolved into a CO [1] , [2] , [3] . The D-loop can also participate in an alternative pathway to form non-crossovers ( NCOs ) , which in Saccharomyces cerevisiae involves synthesis dependent strand annealing [1] , [2] , [3] . Concurrently with DSB generation a chromosome axis forms and physically connects the homologues with loops of chromatin projecting laterally [4] , [5] , [6] . DSBs arise on chromatin loops tethered to the axis , and changes to axis structure can dramatically alter recombination patterns [4] , [6] , [7] . A greater number of DSBs are generated than mature into COs , with the excess DSBs repaired as NCOs , some of which can be detected as gene conversions [8] , [9] . COs occurring between homologous chromosomes can show distance-dependent interference causing them to be more widely spaced than expected by chance [9] , [10] . For example , in A . thaliana 85–90% of COs form via the MSH4-dependent interfering pathway ( type-I ) and the remaining 10–15% form via the MUS81-dependent non-interfering pathway ( type-II ) [11] , [12] , [13] , [14] , [15] . Additional CO pathways must also exist in A . thaliana since residual COs or chiasmata have been observed in msh4 mus81 double mutants [11] , [14] . A process related to interference , called homeostasis , maintains CO frequency when DSBs are reduced [16] . Interference and homeostasis cause CO number per chromosome to be distributed closer to a mean than expected from the Poisson distribution [13] , [17] . Tight control of CO frequency is thought to be important because balanced homologue segregation at meiosis-I is dependent , in most organisms , on each pair of homologues having at least one CO [18] . CO frequency is variable along the length of A . thaliana chromosomes , for example the centromeres are CO suppressed , whereas gene-dense regions are active [19] , [20] , [21] , [22] . A . thaliana chromosomes also display region-specific epigenetic modifications of DNA and histones that are associated with differential transcription [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] . DNA cytosine methylation is an epigenetic modification that can be heritably maintained through DNA replication and in A . thaliana occurs in two major epigenomic contexts . First , the majority of DNA methylation overlaps with RNA polymerase II ( Pol II ) repressed repetitive sequences including transposons and also with histone H3K9me2 , H3K27me1 , H4K20me1 ( me = methylation ) [23] , [24] , [25] , [26] , [29] , [30] , [31] , [32] . Repeats are DNA methylated in all sequence contexts ( CG , CHG and CHH ) and show a marked increase in density towards the centromeres [23] , [24] , [25] , [29] , [30] ( Figure 1 ) . In the second context , the open reading frames of Pol II transcribed genes contain CG methylation , coincident with overlapping peaks of histone H3K4me , me2 , me3 , H3K36me3 , H3K56ac and H2Bub ( ac = acetylation , ub = ubiquitination ) [26] , [27] , [29] , [30] , [33] , [34] . Epigenetic information is known to influence patterns of meiotic recombination . For example , in S . cerevisiae and mammals CO hotspots associate with ‘accessible’ chromatin modifications , including histone H3K4me3 [35] , [36] , [37] , [38] , [39] , [40] , [41] , and DNA methylation can directly repress COs in Ascobolus immersus [42] . Here we investigate the role of DNA methylation in organizing patterns of meiotic recombination frequency in the A . thaliana genome . Maintenance of CG DNA methylation in A . thaliana requires the cytosine methyltransferase METHYLTRANSFERASE1 ( MET1 ) [43] , [44] , [45] , [46] . A . thaliana met1 mutants show dramatic loss of DNA methylation and associated histone modifications , leading to increased Pol II transcription of repetitive sequences [25] , [29] , [30] , [44] , [45] , [46] , [47] , [48] . Gene body DNA methylation is also lost in met1 , though expression of these genes is maintained [25] , [29] , [30] . Self-fertilization and inbreeding of met1 mutants leads to stochastic generation of epialleles and transposon mobilization [44] , [45] , [46] , [49] , [50] , [51] , [52] , [53] , [54] . Epigenetic divergence is observed in within met1+/− segregating populations , even without met1 homozygosity , as plant haploid gametophytes undergo post-meiotic DNA replication and in met1 gametophytes this causes cytosine demethylation [44] , [46] , [52] . Here we demonstrate extensive remodeling of CO distributions in met1 mutants , with elevated centromere-proximal COs coupled to pericentromeric decreases and distal increases . Importantly total CO numbers are similar between wild type and met1 , suggesting that interference and homeostasis may act to drive regional changes . We generate a fine-scale map of euchromatic recombination frequency close to the telomere of chromosome 3 and identify a novel , intergenic CO hotspot 3a . We observe an elevated recombination topology across this region in met1 and higher 3a CO frequency , consistent with remodeling modulating hotspot activity . Together this work reveals the importance of domains of epigenetic organization in determining chromosomal patterns of meiotic CO frequency .
Because CO frequency is decreased close to the A . thaliana centromeres we investigated its relationship with DNA methylation in these regions [19] , [20] , [21] , [22] . To obtain a genome-wide map of CO frequency we analyzed published genotype data for 17 F2 populations , providing a total dataset of 55 , 497 COs [22] , [55] . Genetic maps for individual populations were created using R/qtl and merged using MergeMap , which yielded map lengths comparable to those previously published ( Table S1 ) [21] , [22] , [56] , [57] , [58] , [59] . We then calculated recombination frequency ( cM/Mb ) , gene , H3K4me3 , LND ( low nucleosome density ) , repeat and DNA methylation densities within marker intervals of the merged map . Meiosis-specific epigenomic maps are not currently available in A . thaliana , so bisulfite sequencing data ( DNA methylation ) and ChIP-chip data ( H3K4me3 and LND ) generated from somatic tissues were used [23] , [27] , [28] ( Table S2 ) . We defined pericentromeres as the intervals flanking the genetically defined centromeres that showed gene densities lower than the chromosome average , and defined the remaining regions as chromosome arms ( Figure 1 and Table S2 ) [19] . The pericentromeres contain fewer genes , higher repetitive DNA content and denser DNA methylation compared to the chromosome arms ( averages for chromosome arms vs pericentromeres are 286 . 9 vs 123 . 6 genes/Mb , 153 . 4 vs 556 . 4 repeats/Mb , 0 . 027 vs 0 . 147 for methylation ) . Gene density is positively correlated with H3K4me3 and LND density in all regions , consistent with the known function of these chromatin features in promoting gene expression ( Figure 1B ) [27] , [28] . Gene , H3K4me3 and LND density are negatively correlated with DNA methylation , most strongly in the pericentromeres , consistent with dense DNA methylation associating with Pol II silenced repeats ( Figure 1B ) [23] , [24] , [25] , [29] , [30] . Mean CO frequencies within the chromosome arms ( 3 . 95 cM/Mb ) and pericentromeres ( 3 . 83 cM/Mb ) were similar , though within the pericentromeres CO frequency was strongly elevated towards the region boundaries ( Figure 1A ) , and showed positive correlations with genes/Mb ( r = 0 . 508 , p = 1 . 29×10−06 ) , H3K4me3/Mb ( r = 0 . 439 , p = 4 . 15×10−05 ) , LND/Mb ( r = 0 . 418 , p = 1 . 03×10−04 ) and a negative correlation with DNA methylation ( r = −0 . 551 , p = 9 . 88×10−08 ) ( Figure 1B ) . In contrast , cM/Mb in the chromosome arms was weakly correlated with genes/Mb , H3K4me3/Mb , LND/Mb and methylation ( Figure 1B ) . This indicates that pericentromeres represent chromosomal domains with distinct patterns of epigenetic information and CO frequency control relative to the chromosome arms . Given the negative correlation between DNA methylation and CO frequency within the pericentromeres we decided to test CO patterns in hypomethylated met1–3 mutants [23] , [25] , [29] , [30] . To measure COs in proximity of the centromeres in met1 we analyzed the segregation of polymorphic markers ( Figure 2A ) . We backcrossed the null met1–3 allele from the Columbia ( Col ) accession into Landsberg erecta ( Ler ) for 8 generations , maintaining met1–3 as a heterozygote to limit epigenetic divergence . met1–3+/− Ler and met1–3+/− Col heterozygotes were crossed to generate F1 individuals homozygous for met1–3 and heterozygous for Col/Ler polymorphisms . To generate recombinant populations these F1 individuals were backcrossed as males to Col , as were wild type Col/Ler heterozygotes ( Figure 2A ) . We designed insertion-deletion Col/Ler PCR markers to centromere proximal positions that show CO suppression and dense DNA methylation ( Figure 2B and 2C ) . We observed significantly elevated centromere-proximal CO frequency in the mutant met1–3−/− population relative to wild type ( 1 . 21 cM/Mb vs 0 . 38 cM/Mb , pmod = 2 . 0×10−4 ) ( Figure 2C ) . As expected wild type recombination rates within these densely DNA methylated regions were lower than the chromosome averages ( Figure 2C and Table S1 ) . These data demonstrate elevated centromere-proximal COs in met1–3−/− , correlating with extensive DNA demethylation and increased Pol II transcription previously observed in these regions [23] , [25] , [29] , [30] . We sought to test CO frequency in wild type and met1–3−/− across a wider pericentromeric interval . The FTL system uses segregation of heterozygous transgenes expressing distinct colors of fluorescent proteins in pollen to measure COs between insertion sites [60] ( Figure 3 ) . FTL segregation in the quartet1–2 ( qrt1–2 ) mutant background , where sister pollen grains remain physically attached , allows tetrad analysis for male meioses [60] ( Figure 3B and 3C ) . We used FTL lines located on chromosome 3 defining a 5 . 405 Mb interval that we call CEN3 , which spans the centromere and includes the region previously measured in the backcross populations , in addition to flanking pericentromeric DNA ( Figure 3A ) . CEN3 is repeat and methylation dense ( 650 . 8 repeats/Mb , 0 . 183 methylation ) and gene-poor ( 75 . 1 genes/Mb ) compared to the chromosome 3 averages ( 240 . 7 genes/Mb , 273 . 7 repeats/Mb , 0 . 056 methylation ) . In Col that has never been crossed to met1–3 ( naïve wild type ) CEN3 has a genetic distance of 11 . 04 cM , corresponding to 2 . 05 cM/Mb , compared to the 4 . 76 cM/Mb chromosome 3 male average ( Figure 3D and Tables S1 and S3 ) [21] . Although CEN3 is relatively suppressed for COs , this interval shows increasing CO frequency towards its boundaries , correlating with higher gene densities and lower DNA methylation ( Figure 3A ) . We self-fertilized CEN3/−− met1–3+/− qrt1–2−/− plants to generate populations segregating for met1–3 and measured CEN3 COs in MET1 , met1–3+/− and met1–3−/− individuals . We observed significant decreases in CEN3 genetic distance in all groups relative to naïve wild type , with mean distances of MET1 9 . 76 cM ( pt = 0 . 01 ) , met1–3+/− 7 . 32 cM ( pt = 4 . 31×10−5 ) and met1–3−/− 6 . 68 cM ( pt = 0 . 002 ) ( Figure 3D and Table S3 ) . After self-fertilization met1–3−/− maintained a significantly decreased CEN3 mean genetic distance of 6 . 37 cM ( pt = 0 . 001 ) ( Figure 3D and Table S3 ) . The met1–3+/− and met1–3−/− self-fertilized segregant groups also exhibited significantly greater variability in CO frequency compared to naïve wild type ( F-test: met1–3+/− p = 0 . 0152 and met1–3−/− p = 4 . 32e-3 ) ( Figure 3D and Table S3 ) . Increased variance is consistent with stochastic epigenetic divergence observed in segregating met1 and ddm1 populations [44] , [46] , [50] , [52] , [61] , [62] , [63] . These data are consistent with increased centromere-proximal COs in met1–3−/− ( met1–3−/− 1 . 21 cM/Mb vs wild type 0 . 38 cM/Mb ) decreasing CO frequency in pericentromeric regions ( met1–3−/− 1 . 24 cM/Mb vs wild type 2 . 05 cM/Mb ) , potentially via CO interference . We investigated whether centromeric DNA methylation correlates with CEN3 genetic distance in this population . To analyze centromeric DNA methylation we used methyl-sensitive restriction digestion of genomic DNA with HpaII followed by Southern blotting and hybridization with the A . thaliana 180-bp satellite repeat CEN180 ( Figure 3E ) [48] . The 180-bp satellite repeats occur in tandem arrays of megabase length within centromeres and are densely DNA methylated in wild type [19] , [48] , [64] . In met1–3−/− mutants the satellite repeats lose methylation and are digested by HpaII , whereas wild type Col DNA is undigested ( Figure 3E ) . We analyzed leaf DNA from met1–3+/− and met1–3−/− individuals for which we had measured CEN3 genetic distance . We observed that greater satellite demethylation was associated with decreased CEN3 recombination , though two met1–3+/− individuals ( 5 . 6 cM and 5 . 0 cM ) deviated from this trend ( Figure 3E ) . This may be explained by chromosome 3 being demethylated to a greater extent than other chromosomes in these lines . These data demonstrate decreased pericentromeric CO frequency in met1–3 mutants , coincident with DNA demethylation of the satellite repeats . This is consistent with CO interference from elevated centromere-proximal COs reducing events closer to the boundaries of CEN3 . Total CO numbers in A . thaliana do not follow the Poisson distribution , indicating homeostatic control [12] , [13] , [21] , [57] . We therefore tested whether total genetic map length in met1–3−/− was different from wild type , given our observations that regional frequencies close to the centromeres were altered . To measure map length we genotyped 95 male backcross individuals , generated from wild type or met1–3−/− Col/Ler heterozygotes , for 35 Col/Ler SNPs spaced across the 5 chromosomes using KASPar technology ( Figure 4A and Table S4 ) [65] , [66] . Total CO numbers were not significantly different between wild type and met1–3−/− populations ( pmod = 0 . 13 ) ( Figure 4A and Table S4 ) . Therefore , despite regional alterations in CO frequency , total genetic map length is similar between met1–3−/− and wild type . To investigate meiotic progression in more detail we performed DAPI staining of anther meiocytes in wild type and met1–3−/− . The major cytological stages of meiosis in met1–3−/− lacked dramatic alterations to chromosome morphology or segregation ( Figure 4B ) . At leptotene replicated chromosomes were present as thin threads , which condensed during zygotene , and became fully synapsed by pachytene ( Figure 4B ) . At pachytene the centromeres , pericentromeres and nucleolar organizing regions ( NORs ) cluster into densely DAPI-staining regions , which remain evident in met1–3−/− [67] ( Figure 4B ) . During diplotene desynapsis occurs and homologues begin to separate , which further condense during diakinesis , when chiasma connecting the homologues are evident ( Figure 4B ) . At metaphase-I bivalents are maximally condensed with homologous centromeres segregating to opposite cell poles . Segregation forms cell dyads , each containing 5 homologues , which partially decondense at telophase-I ( Figure 4B ) . The second meiotic division separates chromatids , which decondense to form haploid tetrads at telophase-II ( Figure 4B ) . This analysis demonstrates that overall meiotic chromosome morphology and segregation are similar between wild type and met1–3−/− . As an independent measure for CO numbers we immunostained wild type and met1–3−/− meiocytes for MLH1 , which is a homolog of bacterial MutL DNA repair proteins and localizes to foci corresponding to type-I ( interference sensitive ) COs ( Figure 4C and Table S5 ) [17] . MLH1 foci are first detected at pachytene and increase to maximal numbers during diplotene and diakinesis ( Figure 4C ) [17] . MLH1 foci are closely associated with the chromosomes , visualized by either DAPI-staining or immunostaining for the axis component ASY1 ( Figure 4C and 4E ) [68] . We counted MLH1 foci from diplotene and diakinesis stage meiocytes in wild type and met1–3−/− . At diplotene there were significantly more MLH1 foci in met1–3−/− relative to wild type ( wild type mean = 7 . 26 , met1–3−/− mean = 9 . 32 , pmod = 9 . 1 e-4 ) ( Figure 4F and Table S5 ) , though by diakinesis MLH1 numbers were not significantly different ( wild type mean = 9 . 32 , met1–3−/− mean = 8 . 63 , pmod = 0 . 39 ) ( Figure 4F and Table S5 ) . These data are consistent with total MLH1 foci numbers being similar between met1–3−/− and wild type , though maximal numbers may be reached slightly earlier in met1–3−/− . Previous work demonstrated that MLH1 foci show differential localization on chromosome arms ( 77% ) versus DAPI-dense regions ( 23% ) at diakinesis [17] . We confirmed that these DAPI-dense regions contain the centromeres using fluorescent in situ hybridization for the CEN180 satellite repeats ( Figure 4D ) . We scored MLH1 foci distributions in wild type Col and observed similar results at diplotene ( 81 . 2% arms vs 18 . 8% DAPI-dense regions ) and diakinesis ( 71 . 8% arms vs 28 . 2% DAPI-dense regions ) ( Figure 4E ) . In contrast , there were significantly fewer MLH1 foci in the DAPI-dense regions in met1–3−/− at both diplotene ( 98 . 7% arms vs . 1 . 3% DAPI-regions , chi-square p = 2 . 2 e-16 ) and diakinesis ( 90 . 5% arms vs . 9 . 5% DAPI-regions , chi-square p = 6 . 0 e-4 ) ( Figure 4E ) . Together we interpret these data as indicating that although overall MLH1 foci numbers are similar between wild type and met1–3−/− , there are significantly fewer foci in the DAPI-dense regions in met1–3−/− . As DAPI-dense regions contain the pericentromeres , we interpret reduced MLH1 foci in these regions as reflecting the reduced pericentromeric genetic distance we observe over CEN3 ( Figure 3 ) . As we propose that CO interference mediates CO frequency remodeling in met1–3−/− we investigating whether interference occurred to a similar degree between wild type and met1–3−/− . To compare CO interference strength we calculated the average distance between pairs of COs identified from marker segregation occurring on the same chromosome ( Double COs , DCOs ) in the male backcross population described above ( Table S4 ) . The inter-CO distances and therefore the strength of CO interference were not significantly different between wild type and met1–3−/− ( pw = 0 . 67 ) ( Table S4 ) . As an additional measure of CO control we tested our MLH1 foci data for deviation from the Poisson distribution , which may indicate the action of CO interference [13] , [69] . Using a goodness-of-fit test we observed significant deviations in all cases , with more MLH1 counts close to the mean than expected from the Poisson distribution ( Table S5 ) . This is consistent with interference acting in both wild type and met1–3−/− , supporting the idea that CO interference could contribute to the observed CO frequency remodeling in met1–3−/− . Together these data demonstrate that despite alteration of regional CO frequencies , total CO numbers and interference strength are similar between wild type and met1–3−/− . This is consistent with CO interference mediating inhibition of pericentromeric COs in met1–3−/− , due to elevated centromeric COs . Given that we observed remodeling of centromere-associated CO frequencies in met1–3−/− , we next measured genetic distance in the euchromatic chromosome arms . The 1 . 85 Mb FTL I1b interval is relatively gene dense ( 310 . 8 genes/Mb ) and repeat and methylation poor ( 84 . 3 repeats/Mb , 0 . 022 methylation ) compared to the chromosome 1 averages ( 246 . 8 genes/Mb , 233 . 5 repeats/Mb , 0 . 048 methylation ) ( Figure 5A ) . I1b in naïve wild type measures 8 . 16 cM , and has a recombination rate in male meiosis of 4 . 41 cM/Mb , close to the chromosome 1 average ( 4 . 88 cM/Mb ) ( Figure 5D and Tables S1 and S6 ) [21] . In a population segregating for I1b and met1–3 we observed that met1–3−/− individuals showed significantly increased genetic distance of 11 . 00 cM ( 5 . 95 cM/Mb ) compared to naïve wildtype , MET1 and met1–3+/− ( pt = 0 . 001 , 0 . 03 and 0 . 08 respectively ) ( Figure 5D and Table S6 ) . Elevated CO frequencies were stable when met1–3−/− plants were self-fertilized and measured in the next generation ( Figure 5D and Table S6 ) . Mean I1b CO frequencies of met1–3+/− ( 9 . 07 cM ) segregants were higher than naïve wild type , though not significantly ( pt = 0 . 27 ) . The met1–3+/− , met1–3−/− and met1–3−/− self-fertilized groups also had significantly higher variance relative to naïve wild type , consistent with epigenetic divergence ( F-test: met1–3+/− p = 0 . 011 , met1–3−/− p = 0 . 0447 and met1–3−/− self-fertilized p = 0 . 0445 ) ( Figure 5D and Table S6 ) . We confirmed these observations after backcrossing I1bc qrt1–2−/− to either Col or met1–3−/− to complement with QRT1 and used flow cytometry to measure the fluorescence of individual pollen grains ( Figure 5C , 5E and Figure S1 ) . The I1b FTL transgenes are cis-linked , meaning pollen from I1b/−− heterozygotes expressing red-alone or yellow-alone represent single CO events ( Figure 5E and Figure S1 ) . The recombination rate is calculated by the ratio of yellow-alone pollen grains to an adjusted total ( Text S1 and Figure S1 ) . In naïve wild type this technique measured an I1b genetic distance ( 8 . 16 cM ) close to that observed from qrt1–2−/− tetrad scoring ( 8 . 20 cM ) ( Figure 5D and 5E ) . Both met1–3+/− and met1–3−/− plants showed significantly increased genetic distances of 9 . 10 cM ( pt = 6 . 85×10−4 ) and 14 . 16 cM ( pt<2 . 20×10−16 ) respectively , whereas MET1 segregants were not significantly different from naïve wild type ( Figure 5D and 5E ) . These results confirm that met1–3 CO frequency is elevated within I1b . To test the effect of met1–3 on a second euchromatic interval we used a seed reporter system ( Col3–4/20 , hereafter referred to as 420 ) [70] ( Figure 6A , 6B and 6C ) . The 420 interval is defined by transgene insertions on chromosome 3 expressing GFP or RFP in seed from the NapA promoter [70] ( Figure 6A ) . 420 spans 5 . 105 Mb and is relatively gene dense ( 311 . 9 genes/Mb ) and repeat and methylation poor ( 71 . 5 transposons/Mb , 0 . 022 methylation ) compared to the chromosome 3 averages ( 240 . 7 genes/Mb , 273 . 7 repeats/Mb , 0 . 056 methylation ) . In naïve , self-fertilised Col 420 has a mean genetic distance of 19 . 71 cM and recombination rate of 3 . 86 cM/Mb ( chromosome 3 average 3 . 73 cM/Mb ) ( Figure 6D and Tables S1 and S7 ) [21] . We observed significant increases in mean 420 cM in met1–3+/− segregants to 23 . 32 cM ( pt = 0 . 004 ) , relative to naïve wild type ( Figure 6D and Table S7 ) . These data confirm that CO frequency is elevated in the distal chromosome arms in met1–3+/− populations . To compare wild type and met1–3 CO distributions at higher resolution we generated recombination frequency maps within the 420 interval . 420/−− Col/Ler F1 hybrids , that were wild type or met1–3−/− , were backcrossed to Col as males and seed expressing red or green fluorescence alone were selected to identify recombinants within the 420 interval ( Figure 6B and 6C ) . The 420 interval is strongly heterochiasmic with significantly higher male CO frequency ( 4 . 82 cM/Mb ) than female ( 2 . 57 cM/Mb ) ( pt = <2 . 20×10−8 ) ( Table S8 ) [70] , [71] . Male and female 420 genetic distances are reduced in Col/Ler heterozygotes compared to Col/Col homozygotes , potentially due to inhibition of recombination by polymorphisms ( Table S8 ) [72] . CO frequency within 420 is significantly elevated by met1–3−/− in both Col/Col and Col/Ler backgrounds ( Figure 6D , Tables S7 and S8 ) , indicating that euchromatic remodeling is not dependent upon polymorphism levels . We used an Illumina BeadArray to genotype 91 internal Col/Ler SNPs ( average interval 56 , 067 bp ) in 337 wild type and 268 met1–3−/− 420 recombinants ( Table S9 ) . Pronounced heterogeneity in cM/Mb was observed between intervals ( range = 0–17 . 03 cM/Mb ) with overall CO rate elevated in the met1–3−/− map relative to wild type ( Figure 6E , 6F and Table S9 ) . Recombination frequency topology was similar in both maps and showed significant correlation ( r = 0 . 513 , p = 1 . 95×10−7 ) , and this correlation was stronger when comparisons were made over 255 Kb intervals ( r = 0 . 789 , p = 2 . 07×10−8 ) . Elevated CO rates were observed towards the telomere in both populations ( correlation between interval start coordinate and cM/Mb: wild type r = −0 . 496 , p = 5 . 82×10−7; met1–3−/− r = −0 . 533 , p = 5 . 21×10−7 ) , consistent with higher telomeric CO rates observed in A . thaliana male meiosis relative to female ( Figure 6A and Table S9 ) [20] , [21] , [57] , [71] , [73] , [74] , [75] . No significant correlations were detected between wild type cM/Mb and gene ( r = −0 . 008 , p = 0 . 94 ) or repeat ( r = 0 . 005 , p = 0 . 96 ) density at this scale . The similarity in overall recombination topology between wild type and met1–3−/− maps is consistent with remodeling acting to elevate existing CO patterns within 420 . Mammalian and fungal meiotic recombination hotspots are typically ∼1–2 kb and display higher DSB and CO frequencies than surrounding regions [40] , [41] , [76] , [77] . To identify CO hotspots within 420 we designed dCAPs PCR markers to define CO distributions at finer-scale within an active interval ( interval 8 , 10 . 37 cM/Mb ) ( Figure 7A ) [78] . This defined a 6 , 708 bp sub-interval with a CO frequency of 76 . 15 cM/Mb ( Figure 7A ) . To identify CO locations within this interval we used a ‘pollen-typing’ strategy , whereby nested allele-specific PCR primers are used to amplify CO molecules from Col/Ler F1 pollen genomic DNA ( Text S1 and Figure S2 ) [79] , [80] . We amplified and quantified parental versus CO molecules within a subinterval we call 3a ( Figure 7B , 7C and Table S10 ) . In naïve wild type 3a has a genetic distance of 0 . 164 cM ( S . D . = 0 . 0171 ) and a CO rate of 28 . 24 cM/Mb ( S . D . = 2 . 94 ) ( Figure 7B , 7C and Table S10 ) . We amplified single CO molecules and genotyped for internal Col/Ler polymorphisms to identify CO locations . Within the 3a amplicon we observe a complex distribution of CO frequency , with three distinct CO hotspots , each separated by at least one marker interval with 0 CO ( hotspot #1: 634109–636119 bp; hotspot #2: 636199–638483 bp; hotspot #3: 638687–639664 bp ) ( Figure 7B and Table S10 ) . The hotspot peaks overlap with low nucleosome density regions located at the 5′- and 3′-ends of a pair of convergently transcribed genes At3g02880 and At3g02885 ( Figure 7B ) [28] . The central hotspot has a width of 2 , 284 bp and a peak activity of 80 . 81 cM/Mb ( Figure 7B , 7C and Table S10 ) , which is 17 fold greater than the chromosome 3 male average ( 4 . 76 cM/Mb ) ( Table S1 ) [21] . We used epigenomic annotation of this region to investigate the presence of chromatin features associated with 3a ( Figure 7B ) . The genes associated with 3a are Pol II transcribed and At3g02875 , At3g02880 and At3g02890 posses H3K4me , me2 and me3 within their open reading frames ( Figure 7B and 7D ) [25] , [27] . Low levels of DNA methylation are detected within 3a , though At3g02890 shows gene-body DNA methylation , consistent with active transcription ( Figure 7B ) [23] . We next tested met1–3−/− Col/Ler F1 pollen genomic DNA and observed a significant increase in 3a CO frequency to 39 . 79 cM/Mb ( S . D . = 3 . 70 ) compared to wild type 28 . 24 cM/Mb ( S . D . = 2 . 94 ) ( pt = 5 . 66×10−5 ) ( Figure 7B , 7C and Table S10 ) . Although hotspots locations are similar between wild type and met1–3−/− the relative proportions of COs observed between the three hotspots are significantly different ( Figure 7B and Table S10 ) . Hotspot #1 shows significantly more COs ( chi-square p = 0 . 037 ) , hotspot #2 showed significantly less COs ( chi-square p = 0 . 011 ) , whereas hotspot #3 showed no significant difference ( chi-square p = 0 . 560 ) . This demonstrates that although the 3a region has a significantly elevated overall CO frequency in met1–3−/− , the individual hotspots within this region respond differently . This may indicate compensatory interactions , related to observations in S . cerevisae where changes in local DSB frequency can alter DSB activity in adjacent regions [81] , [82] , [83] , [84] , [85] , [86] . Importantly , the genes associated with 3a do not show significant expression changes in met1–3−/− relative to wild type in floral tissue , indicating that local Pol II accessibility is unlikely to be altered ( Figure 7D ) [25] . This is consistent with elevated 3a hotspot activity in met1–3−/− being mediated via remodeling driven by increased centromere-proximal COs .
CO frequency is highly variable within the genomes of eukaryotes and local rates are determined by hierarchically interacting mechanisms . Here we demonstrate that domains of epigenetic information , specifically heterochromatic DNA methylation , are important for determining chromosomal patterns of CO frequency in A . thaliana . Wild type COs are less frequent in densely DNA methylated , transcriptionally silent regions close to the A . thaliana centromeres . These regions show dramatic elevations in Pol II transcription in met1–3−/− [23] , [25] , [29] , [30] . We speculate that SPO11 accessibility similarly increases in met1–3−/− , leading to elevated DSBs and COs in the centromeric regions . Immunohistochemistry in A . thaliana indicates that SPO11 recruitment to the chromosome and the formation of DSBs , as indicated by γH2A . X foci , are temporally distinct [68] . This may reflect activation of the DSB machinery during axis maturation and tethering of chromatin loops [4] , [6] , [68] . Hence , it will be important to determine the dynamics of axis maturation to fully understand the changes in CO frequency observed in met1−/− . It is also possible that additional steps in the recombination pathway are sensitive to chromatin state . For example , if interhomolog strand invasion mediated by the recombinase DMC1 were inhibited by DNA methylation , this might lead to increased use of the homologous centromeric region as a repair template in met1−/− . Additionally , SPO11 is recruited to DNA following pre-meiotic S-phase and heterochromatin replicates later than euchromatin in A . thaliana mitotic cells [87] , [88] , [89] . Therefore , if heterochromatin also replicates earlier in met1–3−/− meiotic S-phase , SPO11 recruitment close to the centromeres may also advance , and thus altered temporal progression could contribute to CO remodeling . Hence , a complete understanding of the changes in CO frequency in met1–3−/− will require future study of many aspects of the meiotic recombination mechanism . COs frequency and distribution are finely controlled . For example , the CO interference pathway inhibits the formation of adjacent CO events in a distance-dependent manner . In Caenorhabditis elegans strong interference leads to one CO per bivalent , independent of the physical length of the chromosome [90] . In A . thaliana the majority ( 85–90% ) of COs ( type-I ) are derived from an interference-sensitive pathway , while the remaining events ( type-II ) are distributed randomly . In met1–3−/− we observe an increase in centromere-proximal COs , coupled to pericentromeric decreases and distal euchromatic increases , though total CO numbers are similar to wild type . As DNA methylation is most dramatically lost in the centromeric regions , we hypothesize that increases in recombination in these regions drive CO frequency remodeling . Specifically , increases in met1–3−/− centromeric COs would inhibit adjacent events in the pericentromeric regions via CO interference . In addition to interference , COs are known to be controlled by a homeostatic pathway . For example , reductions of DSB frequency in S . cerevisiae do not lead to proportional reductions in CO frequency , indicating compensatory mechanisms that maintain CO numbers close to a mean [16] . We hypothesize that increases in distal CO frequency in met1–3−/− arise as a consequence of related homeostatic mechanisms maintaining total CO numbers , at the expense of the pericentromeric regions . Extensive data in S . cerevisiae demonstrate that DSB frequency can also be influenced by changes in DSB activity in adjacent regions , over distances up to 60 kb [81] , [82] , [83] , [84] , [85] , [86] . Similar effects could also contribute to the observed changes in met1–3−/− CO frequencies , driven by elevated DSB frequency in hypomethylated regions . Therefore , changes in met1–3−/− recombination frequency could be caused by both additional and redistributed DSBs . Although , DNA methylation , gene density and gene-associated chromatin strongly correlate with CO frequency in the pericentromeres , this is not the case in the chromosome arms . Other levels of meiotic chromosome organization may be dominant in the distal chromosome arms , for example the meiotic axis [4] , [6] , [7] , [91] . However , it is also possible that loss of DNA methylation from gene bodies or local repeats contributes to changes in met1–3−/− CO frequency in the chromosome arms [23] , [25] , [29] , [30] . Our 420 genetic maps provide evidence of pronounced heterogeneity of CO rate within A . thaliana gene-rich euchromatin . We identify a novel CO hotspot 3a within this region , which overlaps with intergenic regions of low nucleosome density . Although our hotspot comparisons are made with mitotic epigenomic datasets , in yeast and mammals the majority of low nucleosome density regions are similar between meiotic and mitotic cells [92] , [93] , [94] . The 3a hotspot shows elevated activity in met1–3−/− , though without local change in Pol II transcription . Elevated 3a activity is consistent with CO remodeling driven by increased centromere-proximal COs in met1–3−/− . The 3a hotspot shares many similarities with DSB hotspots defined in S . cerevisiae , which occur at LNDs with high SPO11 accessibility and active epigenetic modifications including H3K4me3 [37] , [40] , [41] , [95] . However , low nucleosome density regions and H3K4 methylation are shared between 3a and many genes . Therefore , we predict that these features are necessary but not sufficient for hotspot activity . Specifically , regional factors such as axis structure or proximity to the telomere may predispose locally permissive chromatin to undergo CO . In humans and mice the PRDM9 zinc-finger H3K4 histone methyltransferase positions CO hotspots to specific cis-sequences [36] , [96] , [97] , [98] , [99] , [100] , [101] . As PRDM9 has yet to be identified outside of animals , CO hotspots in yeast and plants may represent a more ancestral pattern within eukaryotes [102] . Although the logic of epigenetic control is conserved throughout the eukaryotes , the distributions and uses of specific chromatin marks can vary . As meiosis originated early during eukaryotic evolution it will be interesting to determine similarities in hotspot specification and the relative contributions of epigenetic information to control of CO frequency within distinct lineages . Together our data demonstrates how epigenetic organization contributes to the hierarchy of CO control mechanisms in plant genomes . Note added in proof: Decreased pericentromeric and elevated euchromatic CO frequencies have been observed in ddm1 and met1 mutant backgrounds , consistent with our observations [103] , [104] .
The R Statistical Language was used for analysis and graphs [105] . Correlations were performed using Pearson's product moment correlation . Comparisons between groups were made using t-tests ( pt ) or , in the case of inter-CO distances , the Wilcoxon-rank sum test ( pw ) . Comparisons between proportions were made using chi-square tests . Comparisons of variance between groups were made using F-tests . Using glm , a model was fitted to the counts in Figure 2C including the effects of genotype and chromosomes and with the number of plants and chromosome lengths as offsets . Backward elimination was used to arrive at a parsimonious model , which included the effect of genotype and chromosomes 3 and 4 . The p-value for genotype from this final model is given in Figure 2C . The R function glm was used to fit a quasi-Poisson model to the data presented in Tables S4 and S5 , using genotype as the predictor . The p-value ( pmod ) for genotype is presented in the tables . The fit of MLH1 count data to the Poisson distribution was performed using the R goodfit function within the vcd package . All plants were cultivated on commercial soil and grown in controlled environment chambers at 20°C , 60% humidity with a long day photoperiod ( 16 hours light ) with a light intensity of 150 µmols . Pollen tetrad and seed fluorescence were assayed as described [60] , [70] . For a detailed discussion of pollen flow cytometry see Text S1 and Figure S1 . Genomic DNA was extracted from leaves using the CTAB method and genotyped using either PCR , an Illumina Beadarray or KASPar technology . Pollen genomic DNA was extracted as described [79] . For a detailed discussion of pollen-typing experiments see Text S1 , Figure S2 and Table S11 . Meiotic cells were analyzed from staged anthers by immunostaining as described [17] . | The majority of eukaryotes reproduce via a specialized cell division called meiosis , which generates gametes with half the number of chromosomes . During meiosis , homologous chromosomes pair and undergo a process of reciprocal exchange , called crossing-over ( CO ) , which generates new combinations of genetic variation . The relative chance of a CO occurring is variable along the chromosome , for example COs are suppressed in the centromeric regions that attach to the spindle during chromosome segregation . These patterns correlate with domains of epigenetic organization along chromosomes , including methylation of the DNA and histones . DNA methylation occurs most densely in the centromeric regions of Arabidopsis thaliana chromosomes , where it is required for transcriptional suppression of repeated sequences . We demonstrate that mutants that lose DNA methylation ( met1 ) show epigenetic remodeling of crossover frequencies , with increases in the centromeric regions and compensatory changes in the chromosome arms , though the total number of crossovers remains the same . As crossover numbers and distributions are subject to homeostatic mechanisms , we propose that these drive crossover remodeling in met1 in response to epigenetic change in the centromeric regions . Together these data demonstrate how domains of epigenetic organization are important for shaping patterns of crossover frequency along eukaryotic chromosomes . | [
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"modificat... | 2012 | Epigenetic Remodeling of Meiotic Crossover Frequency in Arabidopsis thaliana DNA Methyltransferase Mutants |
The emergence following gene duplication of a large repertoire of Hox paralogue proteins underlies the importance taken by Hox proteins in controlling animal body plans in development and evolution . Sequence divergence of paralogous proteins accounts for functional specialization , promoting axial morphological diversification in bilaterian animals . Yet functionally specialized paralogous Hox proteins also continue performing ancient common functions . In this study , we investigate how highly divergent Hox proteins perform an identical function . This was achieved by comparing in Drosophila the mode of limb suppression by the central ( Ultrabithorax and AbdominalA ) and posterior class ( AbdominalB ) Hox proteins . Results highlight that Hox-mediated limb suppression relies on distinct modes of DNA binding and a distinct use of TALE cofactors . Control of common functions by divergent Hox proteins , at least in the case studied , relies on evolving novel molecular properties . Thus , changes in protein sequences not only provide the driving force for functional specialization of Hox paralogue proteins , but also provide means to perform common ancient functions in distinct ways .
Hox genes encode homeodomain ( HD ) containing transcription factors widely used for diversifying animal body plans in development and evolution [1]–[3] . The Hox gene repertoire most likely arose from tandem duplication events of ancestral genes , followed by sequence divergence that promoted the emergence of up to 14 paralogous groups in vertebrates [4] . The emergence of a large repertoire of Hox proteins certainly underlies the importance the Hox gene family has acquired in promoting morphological diversification of most animal body parts in higher eukaryotes . Sequence conservation/divergence within the HD allows grouping paralogue proteins in three classes [5]–[8] . These classes correlate with the A–P deployment of Hox gene expression patterns as well as with the location within Hox clusters , and were accordingly termed anterior , central and posterior . Anterior class Hox genes ( Hox1-3 ) are expressed most anteriorly and are located 3′ in the Hox clusters; central class Hox genes ( Hox4-8 ) are expressed in medial region of the embryo and are located centrally in the clusters; posterior class Hox genes ( Hox9-13 ) are expressed most posteriorly and are located most 5′ in the clusters . The sequence divergence of Hox proteins , including within the HD that constitutes the unique DNA binding domain of the Hox transcription factors , allows Hox paralogue proteins to display distinct regulatory functions , promoting axial morphological diversification in all bilaterian animals [3] , [5] , [9] , [10] . Yet , in addition to having specialized biological functions , distinct Hox paralogue proteins also perform common ( identical ) functions . A striking example is provided by the functional equivalence of most Drosophila Hox paralogue proteins in specifying tritocerebral commissure in the embryonic brain [11] . Such common biological functions may represent remanent functions already assumed by the Hox gene from which the paralogue genes originate , which may then rely on ancestral properties still present in the divergent paralogue proteins . Alternatively common functions may rely on evolving novel properties . We aimed at addressing this so far poorly investigated issue by comparing in Drosophila the mode of action of central and posterior class Hox proteins , which display the most extreme divergence within Hox paralogues [4] . Ultrabithorax ( Ubx ) and AbdominalA ( AbdA ) , two central class Hox proteins , were proposed to arise from a recent gene duplication , have highly conserved HDs ( 8% of divergence within the HDs ) and share additional protein domains , including the Hexapeptide ( HX ) motif upstream of the HD , as well as a short peptide downstream of the HD , termed UbdA [3] . Although not limited to this function , both motifs have been shown to promote the recruitment of the PBC class cofactor Extradenticle ( Exd ) [12]–[15] . In contrast , AbdB that arose from a more ancient duplication has a HD that largely diverges from that of Ubx and AbdA ( 41% of divergence within the HDs ) . In addition AbdB lacks the Ubx/AbdA specific UbdA domain , and lack a canonical HX motif , although a key Exd interacting residue within this domain remains conserved [16] . To assess molecularly how divergent Hox proteins as Ubx/AbdA and AbdB can perform identical functions , we focused on limb suppression . As all insects , Drosophila harbors limbs exclusively in the thorax and not in the abdomen . This morphological distinction relies on the regulation of the limb-promoting gene Distalless ( Dll ) , expressed in the thoracic limb primordia , but not in the abdomen . Thoracic specific expression of Dll relies on abdominal repression by Ubx and AbdA in the anterior abdomen ( segments A1-A7 ) and by AbdB in the posterior abdomen ( segments A8-9 ) [17] . Localized thoracic Dll expression was shown to be mediated by multiple enhancers . This includes two enhancers in the 5′ and a distant one in the 3′ of the gene [17] , [18] . Each of this enhancer displays distinct temporal and spatial specificities , which likely contribute to the developmental dynamic expression pattern in the leg primordia . One of the 5′ enhancer , Dll304 , has been extensively analyzed , leading to a good molecular understanding of Dll repression by Ubx and AbdA [13]–[15] , [19]–[21] . The Ubx/AbdA-mediated transcriptional repression is mediated within a 57-base-pair ( bp ) repressor element ( DMX-R ) . This element harbors functional binding sites for Ubx/AbdA proteins , for two TALE proteins ( a special class of HD containing proteins with a Three Amino acid inserted in between Helix 1and 2 ) , the PBC class cofactors Extradenticle ( Exd ) and the Meis/Prep class cofactor Homothorax ( Hth ) , and for the compartment specific proteins Engrailed ( En ) and Sloppy paired ( Slp ) . As is the case for the regulation of other Hox target genes , Exd and Hth were shown to cooperatively bind DNA with Ubx and AbdA , while En and Slp , which both harbor a Groucho interacting domain , may in turn recruit a Groucho containing corepressor complex . In this study , we dissected the molecular modalities underlying AbdB-mediated repression of Dll , which allows addressing how posterior and central class Hox proteins perform similar functions .
Loss and gain of function data supports a role of AbdB in repressing Dll expression ( Figure S1; [17] ) . To explore further the mechanism of AbdB mediated Dll repression , we first asked if AbdB is present in cells with the potential to express Dll . Dll expression and regulation was followed using Dll reporter genes , DMX or DME ( when the experiments involved the paired ( prd ) -Gal4 driver , see material and methods ) , that both accurately reproduce Dll expression ( Figure 1A ) and that only differs in the 3′ sequence by a few nucleotides that provide DMX with a second Hox binding site [20] ) . We first took advantage of the DMX ( X2X5 ) that bears mutations in binding sites for the En ( X5 ) and Slp ( X2 ) proteins [20] . DMX ( X2X5 ) drives lacZ reporter expression in the thorax , as wild type DMX ( Figure 1A ) , but also in the abdomen , including segments A8 and A9 ( Figure 1B ) . Co-staining with AbdB antibodies showed that cells normally repressing DMX in A8 and A9 , identified by DMX ( X2X5 ) activity , accumulate AbdB ( Figure 1C ) . The AbdB gene produces two isoforms: AbdBm in segments A8 ( also expressed in A5–A7 albeit at lower levels ) and AbdBr in segment A9 [22] . In the absence of Ubx and AbdA proteins but in the presence of an intact AbdB gene , DMX activity is de-repressed in abdominal segments A1–A7 , but not in A8 and A9 ( Figure 1D , 1E ) . Removing in addition the AbdBm isoform results in expanding the derepression of DMX to A8 ( Figure 1F , 1G ) , while further deleting the AbdBr isoform results in full abdominal derepression , including A9 ( Figure 1H , 1I ) . Taken together , these results indicate that the AbdBm and AbdBr isoforms are responsible for DMX repression in A8 and A9 segments respectively . The repressive activity of AbdB isoforms was further investigated in gain of function experiments . AbdB isoforms were ectopically expressed in every other segments with the paired ( prd ) -Gal4 driver [19] . Results indicate that both isoforms are equally efficient in repression ( Figure 1J–1M ) , further validating repression by AbdB m and r isoforms . To investigate in more depth the repression of Dll by AbdB we focused on the AbdBm isoform that for simplicity will be referred to as AbdB in the remaining text . Repression of DMX by Ubx and AbdA was shown to rely on the compartment specific proteins En and Slp . We first asked whether de-repression in A8 and A9 segments occurs both in anterior and posterior compartment cells . This was achieved by following the distribution of En , that identifies posterior compartment cells , and LacZ driven by the DMX ( X2X5 ) , in the posterior abdomen . Results unambiguously show that as in the anterior abdomen , derepression in A8-9 occurs both in En negative and positive cells ( Figure 2A ) , indicating that AbdB-mediated repression occurs both in anterior and posterior compartments . Next we investigated the contribution of En and Slp proteins for AbdB-mediated DMX repression . The requirement of En and Slp for proper Dll activation in thoracic segments precludes a loss of function approach . The question was addressed in gain of function experiments , making use of DMX enhancers mutated either on the Slp or on the En binding sites [20] . Regarding the contribution of En to AbdB-mediated repression , the rational behind the experiment was to assay the role of En in anterior compartment cells . Upon mutation of the Slp binding site ( DMX ( X2 ) ) , expression of AbdB in T2 using the prd-Gal4 driver represses DMX ( X2 ) exclusively in posterior compartment cells . This repression uses the endogenous En protein and the intact En binding site within DMX ( X2 ) ( Figure 2B , upper panel ) . In contrast , repression in anterior compartment cells does not occur as the endogenous Slp protein can not bind DMX ( X2 ) . However , if En is crucial for AbdB-mediated DMX repression , the lack of repression in these anterior compartment cells should be compensated if En is provided in anterior compartment cells , as repression then could occur by use of the En cofactor , for which the binding site in DMX ( X2 ) is not mutated . Co-expression of AbdB and En in T2 results in repression of DMX ( X2 ) both in anterior and posterior compartment cells ( Figure 2B , middle panel ) . No repression was observed when En is expressed in the absence of AbdB ( Figure 2B , lower panel ) . Taken together these experiments provide functional support for a role of En in AbdB-mediated DMX repression . Through a similar strategy , using DMX ( X5 ) mutated in the En binding site , and comparing the repressive effect of AbdB in the presence or absence of Slp in posterior compartment cells , we also establish a requirement of Slp for AbdB-mediated DMX repression ( Figure 2C ) . We concluded , as previously shown for Ubx/AbdA , that AbdB-mediated repression of DMX occurs in anterior and posterior compartment cells and uses the En and Slp co-repressors . AbdA and Ubx efficiently bind DMX-R only in the presence of Exd and Hth , and binding sites for these two TALE proteins are required for efficient repression by Ubx and AbdA [19] , [20] . To address the contribution of Exd/Hth to AbdB-mediated Dll repression , we first examined the distribution of Exd . Consistent with previous reports [23] , we found that while being expressed at high levels in the thorax and anterior abdomen , nuclear protein accumulation decreases starting from segment A3 , with no or barely detectable levels present in A8 and A9 , where AbdB is expressed at high levels and represses Dll ( Figure S2 ) . We also examined the expression of Hth , and found that it follows Exd protein accumulation , consistent with its known function in promoting nuclear accumulation of Exd ( Figure 3A ) . These observations indicate that unlike Ubx and AbdA , AbdB may not require the TALE cofactors Exd and Hth for binding DMX-R and repressing Dll . The requirement of Exd and Hth for AbdB binding to DMX-R element was investigated by EMSA . Results showed that AbdB binds efficiently Dll cis sequences in the absence of Exd and Hth ( Figure 3B ) , and that full AbdB binding requires the integrity of the Hox1 and Hox2 binding sites , but also that of the “Exd” binding site ( Figure S3A , S3B ) . Addition of Exd , Hth as well as En either separately or in combination does not improve AbdB binding , and does not allow the assembling of an AbdB-Exd-Hth ( or AbdB-Exd-Hth-En ) on Dll sequences ( Figure 3B and Figure S3C ) . It was rather found that the presence of the Hth protein , either alone or within a trimeric Exd-Hth-En complex , inhibits AbdB monomer binding ( Figure 3B ) . These results reveals a Hox/TALE partnership distinct from that seen for Ubx and AbdA , with Exd , En and Hth being dispensable for AbdB binding , and Hth and Hth-containing complexes ( Hth-Exd and Exd-Hth-En ) providing an inhibitory effect on AbdB binding ( similar results are shown in [24] ) . To further investigate the molecular bases of this competitive partnership , we first investigated the DNA binding requirement of Hth and Exd for proper competitive effect . Results showed that mutation of the Hth or Exd binding sites do not impair the Hth-mediated inhibition of AbdB binding . Normalizing AbdB binding with reference to its binding to the mutated DII probes in absence of Hth further showed the efficiency of AbdB binding is not weaker than that observed with wild type probe ( Figure 3C and Figure S4 ) , indicating that AbdB binding inhibition by Hth does not require the Hth or Exd binding sites . This was further confirmed by the observation that a HD deleted form of Hth , HthHM , that does not bind DNA , still efficiently inhibits AbdB binding ( Figure 3D and Figure S4 ) . Surprisingly however , the presence of Exd increases the inhibitory role of HthHM , while it decreases that of full length Hth ( Figure 3D and Figure S4 ) . This could be explained by the assembling of a Exd-Hth-DNA complex only in the case of the HD containing Hth protein ( Figure S4 ) , which lowers the availability of free Hth for competing AbdB DNA binding . Similar experiments were conducted by adding the Hth and Exd proteins , in order to assess the inhibitory role of the Hth-Exd complex ( Figure 3C , 3D and Figure S4 ) . Results showed that as for Hth alone , inhibition of AbdB binding by the Hth-Exd complex does not require the Exd and Hth binding sites , although in the case of the Hth mutated probe , inhibition is weaker than on the wild type probe . We concluded that Hth and Hth-Exd mediated inhibition of AbdB binding relies on a mechanisms that do not require Hth or Hth-Exd binding to DNA , indicating that AbdB-Hth ( or AbdB-Hth-Exd ) interaction occurring outside DNA prevents AbdB binding ( similar results are reported in [24] ) . These results however do not exclude that Hth ( and Exd-Hth ) also inhibits AbdB DNA binding by competing for overlapping binding sites , as is the case for Exd . The repressive function of DMX was shown to rely on a 57 bp element , named DMX-R , which was scanned for mutations affecting its capacity to mediate repression [20] . Among the 23 scanning mutations ( 2 to 5 base pair substitution ) , 8 were shown to result in strong abdominal derepression , identifying binding sites for the Hox proteins Ubx and AbdA , for the Hox TALE cofactors Exd and Hth , as well as for the corepressors En and Slp . In addition , mutations in the distal part of DMX-R result in weak abdominal derepression , identifying a second Hox binding site ( Hox2 ) . This Hox2 binding site is dispensable for proper repressive activity as the DME element conveys full abdominal repression . To see if the AbdB-mediated repression in A8-9 segments relies on the use of the same cis sequences as repression by Ubx and AbdA in the anterior abdomen ( A1-7 ) , we re-examined the effect associated to mutations spanning the DMX-R ( 19 of the 23 initial mutations ) by exploring if any of these result in distinct effects in anterior abdominal segments , where repression is mediated by Ubx/AbdA , and posterior abdominal segments where repression is mediated by AbdB . This was achieved by quantifying the level of derepression associated to each mutation , focusing on segments A1 and A8 , as representatives of anterior and posterior abdominal segments respectively . Results summarized in Figure 4 ( see Figures S5 , S6 for full data ) show that no qualitative differences for cis requirements in A1 and A8 are seen: all positions of DMX-R not involved in repression in A1 are also not involved in repression in A8; all positions of DMX-R required for proper repression in A1 are also required for proper repression in A8 . In one instance however , mutation of the Hox1 binding site , the level of derepression is distinct in A1 and A8 , with a stronger derepression in A1 than A8 . This quantitative distinction suggests that AbdB binds to additional cis sequences in DMX-R . In support of this , we found that mutation of the “Exd” binding site affects AbdB binding to DMX-R ( see Figure 3C and Figure S3 ) . We thus concluded that the same cis sequences in DMX-R are used for abdominal repression by AbdB in A8 and Ubx/AbdA in anterior abdominal segments . Yet this common requirement of cis sequences does not imply that these cis sequences are bound by the same proteins , as illustrated by the requirement of the “Exd” binding site for AbdB binding to DMX-R . The inhibitory role of Hth on AbdB binding to DMX-R suggests that down regulating the levels of Hth in the posterior abdomen is essential for proper AbdB-mediated Dll repression . Since Hth levels decrease dramatically in the posterior abdomen , we asked if AbdB itself mediates this down regulation . We found that depleting the AbdBm ( AbdBm3 ) or AbdBm and r proteins ( Df ( P9 ) ) results in increasing the level of Hth to a level similar to the anterior abdomen and thorax region , from segment A4 and including segments A8 and A9 respectively ( Figure 5A ) . Although we do not visualize AbdB protein in segments as anterior as A4 where Exd and Hth start decreasing , AbdB transcripts are present till A4 and the functional domain of AbdB was delineated to segments A4–A9 [25] , consistent with derepression of Hth in AbdB mutants starting from A4 . The repressive role of AbdB on Hth expression was further confirmed in gain of function experiments , where it was found that AbdB has a strong repressive capacity on hth transcription ( Figure S7 ) and Hth protein accumulation , when compared to Ubx ( Figure 5B ) or AbdA ( Figure S8 ) . Consistent with previous reports , similar conclusions could be reached for Exd nuclear accumulation in loss and gain of function experiments ( Figure S2 ) . Finally , the importance of Hth downregulation for proper AbdB-mediated Dll repression was assessed by driving hth expression in the posterior abdomen , using the arm-Gal4 driver ( Figure S9 ) . In this condition however , we failed to efficiently induce high level of Hth protein accumulation in the posterior abdomen . This may suggest that low or absence of Hth protein accumulation in the posterior abdomen may be ensured by a double lock mechanism , one mediated by transcriptional repression , and the second one through a post-transcriptional mechanism , both potentially under AbdB control . Only a few embryos displayed a moderate level of Hth protein accumulation in the posterior abdomen and exhibited posterior derepression of DMX ( Figure S9 ) , indicating that absence of Hth is required for proper AbdB-mediated repression . These data demonstrate that unlike Ubx and AbdA , AbdB binds DMX-R and represses Dll in cells where Hth and Exd have been dramatically down regulated , avoiding a competitive AbdB/Hth-Exd partnership . To further examine the mode of AbdB-mediated Dll repression , we aimed at identifying residues of AbdB that would be critical for its repressive function . Sequence alignment of arthropod AbdB proteins revealed sequence conservation immediately adjacent to the HD ( Figure 6 ) . This includes a stretch of amino-acids flanking the HD N-terminally ( EWTGQVS ) , with the W possibly representing a residual degenerated HX motif , which has only retained the core residue required for PBC class protein interaction [16] , [26]–[28] . While dispensable for Ubx-mediated repression , the HX was shown to contribute to AbdA-mediated Dll repression [13] , [15] , [29]–[31] . In addition , the region separating the HX from the HD , termed the linker region ( LR ) , was shown to control the efficiency of Dll repression by Ubx and AbdA [14] . Sequence conservation also includes a QRQA sequences C-terminally adjacent to the HD . Interestingly , this highly conserved sequence follows positions with lower sequence conservation . The sequence is in a position similar to the UbdA motifs , a motif shared by Ubx and AbdA , which is either essential or contribute to Dll repression in Ubx and AbdA respectively [13] , [15] , [31] . To address the functional importance of these regions for AbdB-mediated Dll repression , mutations in these domains were engineered in the Drosophila protein and transgenic lines allowing the expression of these variants under UAS control were generated . prd-Gal4 driven expression showed that single mutation of the W residue , or combined mutation of several residues within this region ( TG , EWTG ) do not alter AbdB potential to repress DME activity ( Figure 6 and Figure S6 ) . We also mutated the position that immediately precedes the initiation of the HD , that is flanked by conserved residues , and whose identity , an S in Drosophila or a T in some other arthropods , may suggest a potential for post-translational modification by phosphorylation . As other HD N-terminal located mutations , this mutation does not affect AbdB repressive potential ( Figure 6 and Figure S6 ) . In contrast , altering the QR sequence lying C-terminal to the HD ( AbdBCter ) results in a strong reduction of the AbdB repressive potential ( Figure 6 and Figure S10 ) . We next investigated the importance of AbdB HD sequences for DME repression . We first aimed at generating mutations that would alleviate AbdB DNA binding . Based on DNA contacts seen in the HoxA9-Pbx1-DNA crystal structure [16] , we targeted position 50 and 51 the HD recognition helix 3 ( Figure 6 and Figure S10 ) . Individual mutation of these positions ( AbdBH3a , AbdBH3b ) resulted in a complete loss of repressive activity , demonstrating the essential character of AbdB DNA binding for proper Dll repression ( Figure 6 and Figure S10 ) . We then generated mutations in the HD N-terminal arm that in some Hox proteins was shown to be crucial for functional specificity [32]–[34] . This region of the HD contains all paralogue specific signatures of posterior and central class Hox proteins , defined by positions whose identity is shared by all members of a paralogue group , but not by any other paralogue group [3] . A first set of mutations aimed at altering the posterior class specific signature was achieved by changing two lysines in positions 3 and 4 of HD to alanines ( AbdBKK ) . Results showed that AbdBKK fails to properly repress DME , with a loss of 60% of its repressive potential ( Figure 6 and Figure S10 ) . We next asked if endowing the AbdB N-terminal arm with the specificity of central Hox protein ( Ubx and AbdA ) would allow a significant restoration of the repressive function . Central Hox proteins display a paralogue specific signature made of three residues , G , Q , and T , at positions 4 , 6 and 7 respectively . These positions were changed to the identity of central Hox proteins , which in part compromise the posterior class signature , while grafting the central class signature ( AbdBCEN ) . Results showed that AbdBCEN has a very weak repressive potential , even lower than that of AbdBKK ( Figure 6 and Figure S10 ) , indicating that HD paralogue specific signatures are not sufficient to confer DME repression . This result is consistent with the contribution of sequences outside the HD for Ubx/AbdA-mediated Dll repression [13] , [15] , [31] . Taken together , this functional dissection of AbdB protein domain requirement for DME repression demonstrates the dispensability of sequences immediately N-terminal to the HD ( the HX and linker region ) , establishes a contribution of the HD N-terminal arm and residues immediately C-terminal to the HD , and reveals a strict requirement for AbdB DNA binding . Mutations of helix 3 of the HD at positions 50 and 51 , known to provide strong DNA contacts in the DNA major groove , highlight the strict requirement of AbdB DNA binding for proper Dll repression . To address if the conclusion also holds true for central Hox proteins , we investigated the requirement of position 50 within helix 3 of the Ubx HD for proper DME repression . Mutation of position 50 of the HD was previously shown to be essential for Ubx binding to DMX-R [35] , [36] . Yet , expression of this helix 3 mutated Ubx protein ( UbxH3 ) showed that it still represses DME , with a limited loss ( 30% ) of repressive potential . ( Figure 7 and Figure S11 ) . Taken together with the strict requirement in AbdB of residues contacting DNA within AbdB helix 3 , we concluded that a major difference in the mode of DME repression by AbdB and the central Hox protein Ubx lies in the requirement/dispensability of DNA binding in the absence of the Exd and Hth TALE cofactors . We next studied whether we could endow the Ubx protein with an AbdB like mode of DME repression . We used as a recipient protein a Ubx protein bearing a UbdA mutation , as well as a mutation in the HX , which slightly enhance the loss of repressive potential resulting from the UbdA mutation [15] . The first chimera consisted in swapping the Ubx HD by that of AbdB ( UbxHX , UAAbdB ( HD ) ) , which significantly restored repressive potential ( 68% instead of 17% for UbxHX , UA; ( Figure 7 and Figure S11 ) ) . As we found that sequences immediately Cter adjacent to the AbdB HD contributed to full AbdB repressive activity , we also generated a chimera which in addition included the AbdB QRQA Cter residues . This addition did however not significantly enhanced the repressive activity of the chimera ( 71% for UbxHX , UAAbdB ( HD+Cter ) instead of 68% for Ubx HX , UAAbdB ( HD ) ; ( Figure 7 and Figure S11 ) . These results suggest that swapping the HD is sufficient to endow Ubx with an AbdB like repressive mode . To confirm this , we next asked if the UbxHX , UAAbdB ( HD ) and UbxHX , UAAbdB ( HD+Cter ) use an AbdB like mode of repression , by investigating if DNA binding is critical for the activity of these chimeras . Mutations of position 51 of the HD within the context of these two chimeras were generated , and the resulting chimeras were assayed for DME repression . Results showed that UbxHX , UAAbdB ( HDH3 ) and UbxHX , UAAbdB ( HDH3+Cter ) are fully deficient in DME repression ( Figure 7 and Figure S11 ) , indicating that these chimeras use a mode of repression that strictly requires DNA binding . We concluded that swapping the HD is sufficient to endow Ubx with an AbdB mode of DME repression .
As AbdB lacks motifs known in Ubx and AbdA to mediate Dll repression [13]–[15] , [31] , we searched for AbdB intrinsic determinants responsible for Dll repression in A8 and A9 . Our results highlight that , as for Ubx , a short sequence immediately Cter to the HD is required for full repression . The Cter peptides in Ubx/AbdA and AbdB are however distinct , and serve different functions: in the case of Ubx , its role is to recruit Exd , while in AbdB its role must be different as Dll repression by AbdB does not require Exd activity . Most strikingly , we found that mutations that alleviate DNA binding results in different outputs in Ubx and AbdB . A Ubx protein that lacks DNA binding activity still represses Dll efficiently , while a DNA binding deficient AbdB protein does not . We interpret this difference as resulting from Ubx binding DNA within the context of a multiprotein complex involving the Exd and Hth proteins [14] , [15] , [19] , [20] , which are also DNA binding proteins that may compensate the loss of Ubx binding to DNA . In contrasts , AbdB binds DNA in the absence of these potential compensating partners . Such compensatory roles were recently reported for other Hox/TALE complexes [37] . The importance of the AbdB HD for Dll repression was further demonstrated by the ability of a HD swap between Ubx and AbdB . Thus , the intrinsic requirements for Ubx and AbdB mediated Dll repression are different , supporting that distinct molecular mechanisms are used for Dll repression . We tested the role of the four protein partners previously identified as crucial for Dll repression by Ubx and AbdA [20] . En and Slp expressed at similar levels in the anterior and posterior abdomen are required for AbdB-mediated repression of Dll , while Exd and Hth are absent or present at very low levels in the posterior abdomen where AbdB represses Dll . The differential expression of Hth and Exd in the abdomen results from a strong down regulation by AbdB , while Ubx and AbdA cause weaker effects on Hth and Exd expression ( this study and [23] ) . These distinct properties of central and posterior class Hox proteins Ubx/AbdA and AbdB allow to set up a pattern where Hth/Exd are present in the anterior abdomen , in places where Dll repression [19] as well as other Ubx/AbdA functions [30] , [38]–[40] require these cofactors , and absent or at weak/barely detectable levels in the posterior abdomen . Taken together with the dispensability of Hth and Exd for proper posterior spiracle morphogenesis [39] , [41] , this indicates that AbdB , at least in the embryo , functions without the aid of the Hth and Exd cofactors . The dispensability of Exd/Hth needs to be correlated with the effects of mutations in the Exd and Hth binding sites which in DMX ( or DME ) results in de-repression all abdominal segments including in A8 and A9 [19] , [20] . Mutation of the Exd binding sites strongly reduces AbdB binding to DMX-R , providing a basis for derepression in the posterior abdomen . Mutation of the Hth binding site does not impact on AbdB binding , suggesting it may serve binding to a protein that remains to be identified . Of note mutations of the “Hth binding sites” result in posterior specific de-repression [20] , suggesting that it may affect binding/function of the En compartment specific repressor . Beyond dispensability , the absence of Exd and Hth in the embryo may be required for proper AbdB function . This view is supported by our in vitro EMSA's on DMX-R showing a competition effect of Hth and Hht/En/Exd complexes on AbdB binding , and by de-repression of Dll in posterior segments A8 and A9 following increased levels of Hth expression . Functional antagonism between AbdB and the TALE cofactors Exd and Hth is further demonstrated in the specification of several AbdB-dependent specific features , including the posterior spiracle and the suppression of ventral denticle belts [24] . While this set of data support antagonistic AbdB/Exd/Hth partnership , cooperative partnership may also exists , as suggested by the co-expression of AbdB and Exd/Hth in the genital disc [42] and the assembling of AbdB-Exd-Hth-DNA complexes in vitro [43] . The functional significance of AbdB/TALE cooperative partnership remains however to be established , and its contribution to AbdB mode of action clarified , as this partnership decreases the binding selectivity of AbdB , while it increases that of anterior and central Hox proteins [43] . Our results also provide additional support for developmental functions performed independently by Hox proteins and their usual cofactors Exd and Hth . In Drosophila , some aspect of Hox protein function do not require Exd , including the function of the central Hox protein Ubx in specifying haltere development [44] and reversely , Exd and Hth have functions that are not Hox dependent , as illustrated by the control of embryonic trachea development [45] and antennal identity [46] . Such independent functions have also been described in vertebrates , for example during face morphogenesis , a situation where Pbx proteins acts in a Hox-free domain [47] . Altogether , this emphasizes that Hox proteins and their cofactors may use in a context specific manner multiple mode of interactions , ranging from cooperativity to dispensability . Although generally conserved , the mode of HD/DNA contacts significantly varies between anterior/central and posterior paralogue groups [48] . In particular , it was shown that posterior paralogue proteins possess enhanced DNA binding affinities that in part result from the ability to make extensive contacts with the DNA backbone . Hox proteins of the anterior/central paralogue bear residues critical for functional specificity within the N-terminal arm of the HD [32]–[34] . Proper folding of the N-terminal arm necessary for efficient binding requires the interaction with Exd [28] . Our results are consistent with such distinct mode of DNA binding: AbdB efficiently binds the Dll enhancer on its own , while binding by Ubx or AbdA requires the assistance of the Exd and Hth cofactors . Taken together with previous data on Dll regulation by Ubx and AbdA [13]–[15] , [19]–[21] , [31] , our results indicate that Dll repression in abdominal segments needs to accommodate the repression by different molecular complexes . This relies on the plastic usage of the same Dll cis sequences in the anterior and posterior abdomen . First , Hox binding sites may accommodate binding by Hox proteins displaying significantly divergent mode of DNA binding , as shown by the use of Hox1 and Hox2 binding site for Ubx/AbdA and AbdB DNA binding . Second , the same cis sequence binds distinct proteins , as shown for the initially labeled “Exd binding site” that also mediates AbdB binding to DMX-R . The current mode of Dll cis sequence usage may reflect the evolutionary history of Dll repression: Dll repression may have initially been achieved by AbdB , and have later been extended to repression by Ubx/AbdA by the acquisition/cooptation of Exd and Hth binding sites , enabling Ubx and AbdA to bind the enhancer , despite having a HD not optimized for efficient binding to the Dll gene .
The following stocks were used for the study: UAS-Ubx::HA [49] , UAS-Ubx , UAS-AbdA , UAS-AbdBm [50] , UAS-AbdBr ( received from James Castelli-Gair Hombria ) , UAS-Slp and UAS-En ( received from Richard Mann ) , UAS-Exd and UAS-Hth ( received from Natalia Azpiazu ) , DMX-lacZ [20] , prd-Gal4 [51] and arm-Gal4 [52] . Transgenic flies were generated using P-element germline transformation either in yw flies [53] or in flies with site specific integration sites ( attb ) [54] . All constructs were cloned in pUAST vector and sequence verified . AbdB variants and AbdB/Ubx chimeras were generated using the SOE method , starting form UbxIa and AbdBm cDNAs , and cloned into pUAST vector ( EcoRI , XhoI ) . Primers were as follows: AbdB variants: AbdB m ( 5′ AAAAGAATTCATGCAGCAGCACCATCTGCA; 5′ CGGCGGTTCTACGTGGTTGAGCTCAAAA ) AbdB w ( 5′ CCCGGACTGCACGAGGCAACGGGC; 5′ GGGCCTGAGGTGCTCCGTTGCCCG ) AbdB TG ( 5′ GAGTGGGCAGCACAGGTGTCCGTC CG; 5′ CCTGACGTGCTCACCCGTGTCCAC ) AbdB EWTG ( 5′ AATCCCGGACTGCACGCAGCAGCCGCACAGGTG; 5′ TTAGGGCCTGACGTGCGTCGTTGG CGTGTCCAC ) AbdB S ( 5′ GGTCAGGTGGCAGTCCGGAAAAAGCGC; 5′ CCACTGCACCGTCAGGCCTTTTTCGCG ) ABdB KK ( 5′ CAGGTGTCCGTCCGGGCAGCACGCAAGCC5; 5′ GTCCACAGGCAGGCCCGTCGTGCGTTCGG ) AbdB CEN ( 5′ GTCCGGAAAGGACGCGAAACCTACTCCAAG; 5′ CAGGCCTTTCCTGCGCTTTGGATGAGGTTC ) AbdB H3a ( 5′ ATATGGTTCGCAAATCGCCGCATG; 5′ CAGTTCTATACCAAGCGTTTAGCC ) AbdB H3b ( 5′ ATATGGTTCCAGGCACGGCGGATGAAGAAC; TATACCAAGGTCCGTGCCGCCTACTTCTTG ) AbdB Cter ( 5′ TCACAGGCAGCACAGGCGAATCAG; 5′ TTCTTGAGTGTCCGTCGTGTCCGC ) Ubx/AbdB chimeras ( Ubx HXUA and AbdBm were used as templates ) : AbdB HD amplification ( 5′ ACAAATGGTCTGGTCCGGAAAAAG; 5′ GATCGCCTGTGAGTTCTTCTT ) Ubx N-Ter amplification ( 5′ AAAAGAATTCATGAACTCGTACTTT; 5′ TGTTTACCAGACCAGGCCTTTTTC ) Ubx C-Ter amplification ( 5′AAGAAGAACTCACAGGCGATCAAGGTG; 5′ GTGAATCTAGTCGAGCTCAAAA ) For Ubx HXUA ( AbdB H3 ) template used for AbdB HD amplification was AbdB H3b . For Ubx HXUA ( AbdB HD+Cter ) and Ubx HXUA ( AbdB HDH3+Cter ) , the procedure was similar using the AbdB HDCter 3′ ( 5′ TTCTTCTTGAGTGTCGCGGTCCGGCTCTTCGTC ) instead of ( 5′ GATCGCCTGTGAGTTCTTCTT ) . P insertions were genetically mapped . For each variant , two lines were crossed with the prd-Gal4 and arm-Gal4 driver at 22 , 25 , or 29°C . Collected embryos were stained with anti-Ubx ( FP3 . 38 , dilution 1/1000 ) , anti-AbdB ( DSHB , I/10 ) or anti-HA tag ( Eurogentec , dilution 1/1000 ) to select the conditions ( line and temperature ) that result in expression levels similar ( +/−15% ) to Ubx and AbdB wild-type levels in A1 and A8 , respectively [14] , [31] . Levels of Ubx and AbdB in wild-type embryos were assessed in a sized region in the middle of A1 and T2 , respectively . The mean luminosity values for these regions were established by using the AxioVision LE4 . 5 measurement tool . Hth and Dll Digoxigenin RNA-labelled probes were generated by in vitro transcription from plasmid containing hth and Dll cDNA . RNA in situ hybridization were performed according to standard methods . Embryo collections and immunostaining of embryos were performed according to standard procedures . Quantification of DME repression was achieved following anti-β-galactosidase immunostainings ( rabbit anti-β-galactosidase ( Cappel , 1/1000 ) by using the same DME-lacZ insertion . The levels of DME enhancer repression were estimated by quantifying the surface reduction in T2 of the DME-positive cell cluster by using the AxioVision LE4 . 5 measurement tool . Quantification was done on five individual experiments for each genotype . In case of de-repression observed in DMX binding sites mutants , the area of de-repressed β-gal was measured in A1 and A8 in at least 10 embryo's . The average was taken and compared to levels of DMX-lacZ de-repression levels observed in A1 and A8 segments in Df P9 ( BX-C mutant ) embryos . AbdB variants and AbdB/Ubx chimeras generated as described above were cloned into pcDNA3 ( EcoRI , XhoI ) for protein synthesis . Exd and Hth were full-length , and En protein was lacking the 60 N-terminal amino acids . AbdB and AbdB with HD mutations were cloned in pCDNA3 vector and sequence verified . Proteins were produced with the TNT ( T7 ) -coupled in vitro transcription/translation system ( Promega ) . The following double stranded oligos ( only one strand is specified ) spanning the Dll repressive sequences were used: DMX-R containing Slp , Hox1 , Exd , En , Hth and Hox2 binding sites: GACAATATTTGGGAAATTAAATCATTCCCGCGGACAGTTTTATAGTGC DIIRL: containing Hox1 , Exd , En , and Hth and Hox2 binding sites: TTTGGGAAATTAAATCATTCCCGCGGACAGTTTTATAGTGC DIIR containing Hox1 , Exd , En , and Hth binding sites: TTTGGGAAATTAAATCATTCCCGCGGACAGT Mutations in Hox1 , Hox2 , Exd and Hth were previously described ( Gebelein et al , 2004 ) and are: Hox1: AAATTAA to AAGCCCG Hox2: TTTATAG to GGGCTAG Exd: AAATCAT to AAAGGAT Hth: GGACAG to GGCCGG | Animal body plan diversity is controlled by transcription factors that select within each cell of a multi-cellular organism the set of genes to be expressed , eventually allowing distinct fate to emerge according to spatial coordinates . Transcription factors can be grouped based on their DNA binding domains in a few classes that likely arise from a common ancestral protein . This raises the question of how , within each class , transcription factors have gained specific function , and while doing so how they still continue performing ancient functions . Hox proteins , which play key roles in diversifying animal morphology , have largely been used to unravel the mechanisms underlying functional diversification of transcription factors . Here we use this family of transcription factors to investigate how common functions are achieved by divergent transcription factors . Results suggest that changes in protein sequences not only provide the driving force for defining novel and specific functions , but also provide means to perform common ancient functions in distinct ways . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"developmental",
"biology",
"genetics",
"biology",
"evolutionary",
"biology",
"genetics",
"and",
"genomics"
] | 2013 | Distinct Molecular Strategies for Hox-Mediated Limb Suppression in Drosophila: From Cooperativity to Dispensability/Antagonism in TALE Partnership |
Most epithelial tubes arise as small buds and elongate by regulated morphogenetic processes including oriented cell division , cell rearrangements , and changes in cell shape . Through live analysis of Drosophila renal tubule morphogenesis we show that tissue elongation results from polarised cell intercalations around the tubule circumference , producing convergent-extension tissue movements . Using genetic techniques , we demonstrate that the vector of cell movement is regulated by localised epidermal growth factor ( EGF ) signalling from the distally placed tip cell lineage , which sets up a distal-to-proximal gradient of pathway activation to planar polarise cells , without the involvement for PCP gene activity . Time-lapse imaging at subcellular resolution shows that the acquisition of planar polarity leads to asymmetric pulsatile Myosin II accumulation in the basal , proximal cortex of tubule cells , resulting in repeated , transient shortening of their circumferential length . This repeated bias in the polarity of cell contraction allows cells to move relative to each other , leading to a reduction in cell number around the lumen and an increase in tubule length . Physiological analysis demonstrates that animals whose tubules fail to elongate exhibit abnormal excretory function , defective osmoregulation , and lethality .
Our tissues and organs are built up around arrays of tubes that allow the exchange of nutrients , ions , and gases vital for bodily function . These tubules have precise architectures tailored to their physiological activities . It is important that appropriate tubule dimensions are established during development and maintained throughout life and where this fails , as for example in human polycystic kidney diseases , in which nephron diameters are grossly enlarged [1] , physiological function is severely compromised , often leading to organ failure . Many tissues are sculpted during development by convergent extension ( CE ) movements . This process describes the concomitant narrowing of a tissue in one axis while it elongates along a perpendicular axis ( Figure 1A ) [2]–[4] . CE is brought about by changes in cell-neighbourhood relationships produced by cell intercalation . These changes can be driven by a variety of force-generating processes , such as lamellipodial protrusion , that allow cells to crawl over one another [5] or by cell-junction remodelling [5]–[7] . In both cases cell intercalation is highly organised and is polarised in the plane of the tissue [2] , [8] . The insect renal or Malpighian tubules ( MpTs ) eliminate metabolic and foreign toxins and maintain the animal's ionic , acid-base , and water balance [9] , [10] . They are long , narrow , single cell-layered epithelial tubes with a distinct distal-to-proximal ( D-P ) axis in which the distal regions are secretory in function and proximal regions have reabsorptive roles [11] . In Drosophila the tubules evert from the embryonic hindgut as short buds . During mid-embryogenesis they undergo a dramatic transformation in a period of just a few hours—increasing in length approximately 4-fold whilst narrowing substantially around their circumference . Tubule extension occurs in the absence of cell division and is accompanied by substantial rearrangement of cells within the plane of the epithelium [12] . This morphological transformation appears to be a dramatic example of CE and , because it occurs in the absence of cell proliferation that might complicate analysis , it is an attractive model to study the process of CE and its regulation . How CE is controlled at the tissue level is still poorly understood in terms of the mechanisms and signals that orchestrate local cell behaviours to bring about orderly morphogenesis in the tissue as a whole . During Drosophila germband extension the segmentation genes that pattern the anterior-posterior axis are important in establishing planar polarity [13] . However , it is not known whether the influence of the segmentation genes is direct , nor have the mechanisms by which these genes control cell intercalation been established [4] , [14] , [15] . In other tissues the core planar cell polarity ( PCP ) genes regulate both oriented cell divisions [16]–[19] and polarised cell movements that underlie tissue extension [20]–[22] , but details of the mechanisms involved remain elusive [23] , [24] . Here we address the fundamental question of how cell intercalation is controlled at the tissue level , using the developing fly renal system as a model . We analyse cell movements during tubule extension and show that elongation results from circumferential cell intercalation associated with pulsatile and planar polarised accumulation of the motor protein , Myosin II in the basal cortex of cells . We consider the spatial cues that direct these oriented cell intercalation events as the tubule lengthens . We show that a polarised signal within the tubule organises cell rearrangement during CE . Using a combination of genetic manipulation , laser ablation , and live imaging we provide evidence that the epidermal growth factor ( EGF ) pathway ligand Spitz provides this cue . Spitz is expressed in the distal tubule tip , activating graded EGF signalling along the tubule , which is required for coordinated cell intercalation . EGF signalling acts to establish an axis of planar polarity in tubule cells at the onset of cell intercalation , which is independent of the activity of planar polarity genes . Perturbation of EGF signalling results in disorganised Myosin II dynamics , failure of cell intercalation , and defective elongation , leading to impaired tubule function and the failure of fluid homeostasis .
By mid embryogenesis ( stage 13 ) the tubules are short and stubby in shape , measuring approximately 80 µm in length ( Figure 1A , 1C , and 1E ) with between 10 and 12 cells surrounding the lumen ( Figure 1A and 1D ) . Over approximately 5 hours , they undergo a 4-fold elongation to approximately 320 µm in length ( Figure 1A , 1C , and 1E; Movie S1 ) whilst the number of cells surrounding the lumen reduces progressively to just 2 cells ( Figure 1D ) . Imaging this morphogenetic transformation in real time and tracking individual cells reveals that rings of cells around the tubule lumen ( as shown in Figure 1G′ and 1G″ ) intercalate circumferentially , becoming more spread out in the orthogonal , distal-to-proximal axis ( Figures 1F and 1G; Movies S2 and S3 ) . Cell intercalations can be followed ( Figure 1H and 1H″; Movies S2 and S4 ) , and we were able to confirm previous observations that tubule extension occurs sequentially with CE occurring in the distal half of the tubule earlier than in the proximal half [25] . Focussing on the distal region of the anterior tubules shown in Figure 1B and 1F we found that individual intercalation events took between 24 and 49 minutes , with an average of 42 . 2 min ( ±6 . 1 min , n = 4 intercalations ) with cells moving at an average of 1 . 14 µm min−1 ( ±0 . 02 µm min−1 , n = 9 cells ) . Our observations confirm the hypothesis that tubule elongation results primarily from oriented CE movements , in which cell intercalation around the circumferential axis produces orthogonal extension in the D-P axis of the tubule ( Figure 1I ) . Previous work [26] , [27] has shown that tubules cultured in vitro from stage 11 are able to elongate outside their normal environment , suggesting that tubule CE movements are regulated by mechanisms intrinsic to the tubule . Our previous work has also indicated that the distal-most cells in the tubule , the tip cell ( TC ) and its sibling ( SC ) ( Figure 2A ) , are important for tubule elongation [12] , [26] , [28] . Both terminal cells secrete the EGF signal Spitz ( Spi ) during stage 12 to promote tubule cell proliferation [29]–[31] . However EGF signalling from the TC lineage persists beyond stage 12 throughout the period of tubule elongation , as revealed by the expression of the protease Rhomboid that cleaves Spi to produce its secreted and active form ( sSpi ) ( Figure 2B ) . Staining for a read-out of signalling , diphosphosphorylated extracellular signal-regulated kinase ( dpERK ) [32] , shows that the EGF pathway is activated in tubule cells through to stage 16 and it appears that activation is stronger in distal ( close to the TC ) compared to proximal tubule regions ( Figure 2C and 2C′ ) . Quantitative analysis of dpERK levels confirms graded activation in response to signalling , highest closest to the TC and declining towards the point of tightest tubule curvature ( the kink ) approximately half way along its D-P length ( Figure 2E and 2F ) . These observations were confirmed using a second assay for pathway activation . Capicua is localised to the nuclei of quiescent cells but is translocated to the cytoplasm upon activation , where it is processed for degradation [33] , [34] . Confirming our findings for di-phosphorylated ERK , expression of a tagged Capicua::Venus construct is diminished distally but remains high in the proximal tubule ( Figure 2D and 2D′ ) . We ablated both the TC and SC either genetically or physically using a laser . In embryos mutant for the proneural genes [35] or components of the JAK/STAT pathway ( BD , unpublished data ) , the TC lineage is not specified , tubules lack TCs and SCs and fail to undergo elongation ( Figure 2G and 2G′ ) . However the late phase of tubule cell proliferation also fails in the absence of the TC lineage [26] , [35] . To test whether the reduced cell number contributes to elongation defects we laser ablated the TC and SC in late stage 12 embryos when tubule cell proliferation is complete . We used ctB>UAS-CD8-GFP to mark all tubule cells and centred our ablation on the distal three or four cells to ensure TC/SC removal . By stage 16 , tubule elongation had failed completely in tubules lacking a TC and SC ( Figure 2H and 2H′ ) , whereas the contralateral ( non-ablated ) tubules underwent normal elongation ( Figure 2I and 2I′ ) . Together these experiments show that the TC lineage is required for tubule elongation . To test the role of EGF signalling in tubule extension we abrogated signalling after the completion of EGF-dependent tubule cell division using the temperature sensitive allele of the epidermal growth factor receptor ( EGFRf7 ) [29] , [36] . In the majority of embryos shifted to the restrictive temperature at mid-stage 13 , tubule elongation is severely disrupted ( 87% , n = 15 cf controls raised at the permissive temperature 5% , n = 18 ) . The tubules remain short and the number of cells encircling the lumen fails to reduce as in sibling control embryos ( Figure 3A and 3B ) . Similar defects in tubule elongation occur when EGF signalling is disrupted by expressing a dominant negative receptor [37] using the Gal4 driver ctB , which represses signalling only after all tubule cell divisions have ceased ( Figure 3C , 3D , and 3G; Movies S5 and S6 ) [31] . The analysis of tracked cells from movies of tubules expressing the dominant negative receptor reveals that very few cells complete intercalation in contrast to the wild type ( Figure 1H; Movies S2 and S4 ) . Cell movement is strongly reduced; the average speed of movement is 0 . 5±0 . 07 µm min−1 n = 42 distal cells ( cf wild type intercalating cells 1 . 14±0 . 02 µm min−1 ) . Surprisingly , experiments in which EGF pathway signalling is hyperactivated in all tubule cells , either by expressing the constitutively activated receptor λTop/EGFRact [38] or active ligand sSpi [39] , also produce striking defects in tubule extension , strongly reminiscent of the loss of function phenotypes; 64% ( n = 28 ) of tubules expressing the activated receptor fail to elongate , remaining short and thick ( Figure 3E–3H; Movies S7 and S8 ) . Tracking cells in activated tubules shows that , as in the loss of EGF pathway function , the number of cell intercalations is reduced , although those in the most distal region close to the source of ligand still occur at near the wild type rate with intercalations taking 37±4 . 3 min , n = 10 distal cells ( Figure 3F and 3F′; Movies S7 and S8 ) . However overall cell movement is much reduced ( 0 . 6±0 . 06 µm min−1 , n = 38 cells cf wild type 1 . 14±0 . 02 µm min−1 ) . In contrast , enhanced expression of sSpi from the TC lineage , which is likely to induce higher than normal levels of EGF pathway activity whilst retaining its spatial asymmetry , does not lead to defective tubule elongation ( Figure 3I ) . Together these experiments show that the TC lineage is the source of the EGF ligand , Spitz . They also reveal that asymmetric , signalling from a localised source is crucial for tubule elongation , as either loss of receptor activation or hyperactivation along the whole tubule length disrupts CE movements . These data suggest the idea that the Spitz signal establishes an axis of polarity along the tubule length , about which directed cell rearrangements , required for orderly cell intercalation , occur . We therefore asked if tubule cells exhibit planar polarised features , which are dependent on EGF signalling . As tubule cells lack visible polarity landmarks we relied on a technique that has revealed polarity in other tissues: the expression of the membrane-associated Slam protein . During germ band extension Slam assumes a bipolar distribution on the vertical cell membranes orthogonal to the A-P axis that presages cell intercalation [6] , [13] . Expression of a tagged form of Slam ( Slam-HA [40] ) in tubule cells ( Figure 4A–4D ) reveals that it becomes planar polarised at the onset of CE . In wild type tubules prior to CE ( before stage 13 ) Slam accumulates in a single central clump in the basal cortex of each cell ( Figure 4B ) . At stage 13 ( Figure 4C ) , Slam relocates towards the basal proximal cortex . The proximal localisation is maintained throughout the period of intercalation during stages 14 and 15 ( Figure 4A and 4D ) where it appears to spread down the lateral cell membrane . To show conclusively that Slam localises preferentially to the proximal cortex we induced Slam expression in single cells ( Figure 4A ) where it accumulates on the proximal side and is virtually absent from the distal cortex ( Figure 4A and 4A″ ) . These data provide the first evidence that tubule cells are polarised within the plane of the epithelium and reveal that aspects of planar polarity are established before the initiation of tubule extension . Slam is not normally expressed in the tubules [41] . Thus while Slam localisation reveals latent polarity in the tissue , it does not contribute to the mechanism by which the tissue is normally polarised . Using ectopic Slam as a marker for tissue planar polarity , we assessed tissue polarity in tubules in which EGF signalling was perturbed . Before stage 13 , Slam-HA localisation is unaltered in conditions of either loss- or gain-of-function EGF signalling; Slam is found in a central cluster in the basal cortex of tubule cells ( Figure 4G″ ) . However , Slam fails to redistribute to the proximal cortex and becomes severely disorganised as development proceeds . At the time when Slam would normally relocate proximally , it either fails to relocate or spreads around the entire cell ( Figure 4E–4G ) . These results show that in the absence of EGF signalling , or under conditions of global pathway activation , tubule cells are unable to polarise within the plane of the tissue , supporting the hypothesis that EGF signalling is the source of vectorial information that establishes and/or maintains planar polarity in the tubule . Other studies have shown that EGF signalling is required for the maintenance of apicobasal cell polarity and also for cell survival [42] . Defects in either could account for defective tubule development and so we analysed these parameters after perturbing EGF signalling in tubules . Neither driving a dominant negative EGF receptor nor activating the pathway in all tubule cells alters their apicobasal polarity , as revealed by the distribution of the apical marker Bazooka and the lateral membrane protein FasII ( Figure S1A–S1C ) . There is no cell death in control tubules during stage 15 detected by cleaved Caspase 3 staining ( Figure S1D , see S1G and S1H for positive control ) , and we find no increase in cell death in the tubules either when the EGF pathway is abrogated or hyperactivated ( Figure S1E and S1F ) . These data indicate that the primary response of tubule cells to asymmetric and graded EGF signalling is the acquisition of PCP . The so-called PCP genes play key roles in regulating tissue polarity in diverse organisms [43] , [44] . Furthermore , PCP signalling has been implicated in some [21] , [22] , [24] , but not all [13] , tissues undergoing CE movements . We therefore asked whether the PCP genes contribute to tubule planar polarity and elongation . There is evidence for two independently acting PCP systems , the Dachsous ( Ds ) and Starry night ( Stan ) systems [45] . For this reason we examined mutations in genes for each system independently ( removing maternal and zygotic contributions ) and double mutant combinations that remove the function of both systems together ( see Table S1 for the lines examined ) . No defects in tubule extension were found for any of the mutants or double mutants we tested ( Figure 4H and 4H′; Table S1 ) , indicating that the PCP genes are not required for CE movements in the tubules . Furthermore , we found that Slam localises normally in the absence of PCP gene function ( Figure 4I and 4J ) , revealing that the PCP genes we have tested are also dispensable for planar polarity in the developing tubule . Previous studies have shown that the normal activity of non-muscle Myosin II is required for tubule elongation [46] , [47] . However the phenotypes reported were quite weak perhaps because both Zipper ( Zip , Myosin heavy chain ) and spaghetti squash ( Sqh , myosin light chain ) are supplied maternally ( http://insitu . fruitfly . org/cgibin/ex/report . pl ? ftype=1&ftext=CG15792 ) . We therefore assessed the effects of perturbing Myosin II activity in tubule cells by driving the expression either of a dominant negative Zipper ( YFP-ZipDN ) ( Figure 5B ) [48] or of constitutively active Sqh ( SqhE20E21 ) , which is known to result in an increase in Myosin II activity ( Figure 5C ) [49] , [50] . Compared to wild type tubules , those with altered Myosin II activity fail to extend normally but remain short with more than two cells around the circumference of the lumen ( Figure 5A–5C and 5G , Movie S13; YFP-ZipDN 95% and SqhE20E21 75% of embryos showed elongation defects by stage 15 [n = 20 in each case] ) . These data show that normal levels of Myosin II activity are required for cell intercalation and tubule elongation . Expression of a tagged Myosin II light chain , Sqh::GFP , in a sqh mutant background allowed us to analyse the activity of myosin in tubule cells during elongation . This construct rescues the embryonic sqh mutant phenotype [6] , [49] indicating that endogenous levels of expression are maintained . Movies of the basal-most side of cells during tubule extension reveal regular pulses of Myosin II activity , in which cytoplasmic spots of myosin move to the proximal cortex of cells ( Figure 5D; Movies S9 and S10 ) . Analysis of 63 pulses in 37 tubule cells from eight different embryos indicates that the duration of pulses ranges from 0 . 9 to 4 . 1 min ( average 1 . 98±0 . 08 min ) with 0 . 13 to 3 . 6 min ( average 1 . 78±0 . 2 min ) between pulses ( interpulse ) . Of 61 pulses analysed , 49 showed basal , proximal enrichment and only 12 showed proximal-to-medial or proximal-to-distal movement of myosin . It is striking that although spots of myosin fluorescence can be seen at the orthogonal , circumferential cortices , enriched crescents are almost never seen in these regions . In order to follow the localisation of Myosin II more precisely we double labelled tubule cells with Sqh::mCherry [51] and GAP43::GFP to label cell membranes . Movies show dynamics identical to those using Sqh::GFP ( Figure 5E; Movie S11 ) . When driving a dominant negative EGFR construct , where cells fail to intercalate and tubule extension is lost ( Figure 3C , 3D , and 3G ) , the pulses of active myosin completely fail ( Figure 5F; Movie S12 ) . Actomyosin dynamics are associated in other systems with alterations in cell shape , cell movement , and rearrangement [6] , [51]–[53] . We analysed fluctuations in the basal shape of tubule cells by measuring their area , D-P , and circumferential lengths . This analysis reveals that cell shape is in a constant state of flux ( Figures 5G , S2 , and S3A-S3C ) . We compared the dynamics of fluctuations during a Myosin II pulse with interpulse periods in individual cells but found no obvious correlation with cell shape ( Figure S2 ) . However , averaging measurements from multiple cells ( n = 10 ) revealed that while pulses caused no significant change in the D-P axis , there is a small but significant decrease in circumferential length associated with Myosin II pulses ( Figure 5H ) . In contrast , driving the expression of YFP-ZipDN in tubules results in a strong reduction in cell dynamics with much reduced fluctuations in cell area ( Figures 5G and S3A″ ) and little change in either the circumferential or D-P axial length of cells ( cf shaded areas in Figure S3B , S3C , with S3B″ and S3C″ ) . The dynamic fluctuations in cell shape are also dramatically reduced when EGF signalling is compromised; in tubules expressing EGFRDN the basal area of cells ( Figures 5G and S3A′ ) and their axial lengths ( Figure S2B′ and S2C′ ) scarcely alter compared with the fluctuations seen in wild type tubule cells ( Figure S2A–S2C ) . Tracking cell trajectory over time ( Figure 5I ) shows that control cells move in a circumferential direction ( ± approximately 50° ) . In tubules expressing either EGFRDN or YFP-ZipDN the small cell movements that occur fail to show any bias towards the circumferential axis ( Figures 5I and S3D ) . Together our analysis of cell behavour in control and mutant tubules in which EGF signalling is deranged or where the normal activity of Myosin II is compromised indicates that proximally directed pulses of cortical Myosin II are essential for cell intercalation but occur only in cells that have been planar polarised by asymmetric EGF signalling . In control tubule cells these pulses produce a transient , small but significant reduction in the circumferential length of cells enabling them to move in this axis ( Figure 5J ) , resulting in the cell rearrangements that produce tubule elongation . Without polarised EGF signalling the pulses fail , cells dynamics are dampened and intercalation is either much reduced ( pathway activation ) or fails ( loss of the pathway activity ) so that tubule elongation is compromised . Our analysis of the response to EGF signalling in tubules has established graded activity but only in the distal half of the tubuels ( Figure 2E and 2F ) . We therefore wondered whether cells in the proximal part of tubules become planar polarised . Expression of Slam-HA in tubules from stage 13–16 embryos reveals that the protein in the proximal tubule , in contrast to the distal half , is not asymmetrically distributed at any stage during elongation ( stage 15 shown in Figure S4A and S4A″ ) . As we have correlated the acquisition of planar polarity in cells with the development of dynamic , asymmetric subcellular activity of Myosin II , we wondered whether cells in the proximal region exhibit similar cytoskeletal dynamics . Imaging tubules expressing Sqh::mCherry ( Figure S4B and S4B″; Movies S14 and 15 ) reveals that in contrast to distal regions , where repeated , proximally localised crescents of Myosin form , there is no apparent asymmetric Myosin activty in the proximal half of the tubules . These data suggest that the mechanism by which cells in the proximal half of the tubules intercalate differs radically from the distal half and might not depend on polarised cytoskeletal activity , resulting in circumferential cell movements . MpTs are the major organ for excretion , ionic balance , and osmoregulation in the majority of insects [9] , [10] . Toxins are cleared from the haemolymph by active transport and primary urine is secreted into the tubule lumen by two cell types in the distally placed transitional and main segments . Homeostasis is accomplished by modification of primary urine as it passes down more proximal regions of the tubule before emptying into the hindgut via the ureters . We asked whether the final tubule shape is important for its function . Embryonic tubules persist through larval life and metamorphosis and so are retained in the adult . As there are some escapers when ctBGal4 is used to drive the activated EGF receptor we examined tubules from adult flies of this genotype . Their tubules are abnormal in shape compared to controls , being shorter and wider with conspicuous bulges ( Figure 6A ) . This shows that embryonic tubule defects are not rectified during later developmental stages . In the distal two-thirds of wild type tubules stellate cells , responsible for anion and water movement in the secretion of primary urine , are regularly interspersed with the cation-transporting principal cells ( PCs ) ( Figure 6B ) . Stellate cells are present in the abnormally shaped ctB>UAS-EGFRact tubules but their regular spacing is severely disrupted ( Figure 6C ) . Defects in tubule shape and in the organisation of specialised secretory cell types could well compromise renal physiology . To test this possibility , we compared tubule secretion in control and ctB>UAS-EGFRact tubules using an established in vitro tubule secretion assay [54] , [55] . In control tubules the unstimulated , basal rate of primary urine secretion was 0 . 59 nl min−1 ( n = 10 ) . In contrast 4/11 ctB>UAS-EGFRact tubules did not secrete at all . The average basal rate of secretion for the remaining ctB>UAS-EGFRact tubules was 0 . 2 nl min−1 ( n = 7 ) . After stimulation with the diuretic activators cAMP and Leukokinin ( LK ) control tubules increased their secretory rate to 1 . 39 nl min−1 while ctB>UAS-EGFRact tubules failed to show any increase in secretory rate ( Figure 6D ) . These data clearly demonstrate that secretory rate , a direct measure of tubule function , is either abolished or significantly reduced when tubule morphogenesis is disrupted . The impact of defective tubule elongation on the physiology of adults can be seen within 24 hours of eclosion . Compared with control animals , ctB>UAS-EGFRact adults have grossly distended abdomens and mouthparts ( Figure 6E ) , indicative of fluid retention through defective osmoregulation . We confirmed that distention was due to fluid retention ( and not gas ) firstly by pricking submerged flies , which led to abdominal deflation without gas bubbles . Secondly , we compared wet weight versus dry weight in experimental and control flies . ctB>UAS-EGFRact adults are over twice as heavy as control flies when measured wet , while dry weight measurements are not significantly different ( Figure 6E; data for females , equivalent results were obtained for males ) . These data indicate that osmoregulation is severely compromised in ctB>UAS-EGFRact adults . Together our data illustrate the critical importance of tubule shape both for effective physiological function of the organ system and homeostasis in the whole animal .
In many situations tissue morphogenesis results from orderly cell rearrangements , which require the integration of positional information and oriented cell intercalation . Our data show that in fly renal tubules axial information is provided by an asymmetric EGF signal from a localised source , which acts to polarise cells in the distal half of the tubule just as elongation is about to start . The acquisition of D-P PCP leads to asymmetric , proximally directed pulses of myosin , which in turn result in repeated small contractions of the cell in the circumferential axis . Over time this results in the intercalation of cells around the tubule circumference to produce tubule elongation . While previous reports in other systems have focussed on parts of this sequence of events [6] , [7] , [13] , [21] , [56] , [57] , we have identified the source of polarisation , established the axis of planar polarity at the cellular level , and shown that it is required for the asymmetric behaviour of Myosin II motors that ensure oriented cell rearrangements ( Figure 7 ) . Polarity in the plane of an epithelium is frequently conferred by the activity of PCP genes [43] , [44] , [58] , and in many cases CE movements depend on the expression of these genes [24] . However the patterning of cell movements during tissue morphogenesis or collective migration have also been shown to require the activity of other pathways . In Drosophila the extension of the germ band depends on the expression of the early patterning pair rule genes [8] , [13] , Drosophila hindgut elongation depends on JAK-STAT pathway activity [56] , and border cell migration in the egg chamber is polarised by gradients of receptor tyrosine kinase ( RTK ) signalling [59] , [60] . The sensitivity of border cells to differences in ligand levels across a single cell diameter is enhanced by spatially regulated receptor endocytosis and processing . This depends on Cbl ( a RTK-associated E3 ubiqitin ligase ) and Sprint ( a pathway activated Rab5GEF ) , which together act to down-regulate RTK receptors asymmetrically , leading to enhanced levels of pathway activation at the leading ( higher ligand ) cell face [61] . We find that both Cbl and Sprint are required for normal CE movements during renal tubule elongation [62] , [63] , showing that the enhancement of polarised RTK activation also occurs in this tissue . The gradient of pathway activation is clear in the distal half of the tubules during elongation , as revealed by dpERK staining or Capicua::Venus expression and quantification suggests that the graded response extends over a considerable distance , approximately 60 µm ( ten cell diameters ) . Such a comparatively long-range effect could result from the secretion of ligand from a localised source , particularly if diffusion of ligand into the haemolymph were restricted either by the extracellular matrix , known to ensheath the tubules [64] , or by secretion of ligand through an apical route into the tubule lumen . The ultrastructure of the TC is consistent with apical secretion ( [26] and HS , unpublished data ) , and the distribution of Rhomboid , which is enriched apically in both TCs and SCs , favours this hypothesis ( Figure 2B ) [31] . Alternatively , short-range signalling from the TC lineage might act to break axial symmetry , followed by local interactions between cells to propogate polarity . We hoped that it would be possible to distinguish between these models by generating clones of cells with altered EGFR activity or ectopic ligand secretion in order to assess non-cell autonomous effects of altered signalling on cell polarity . However clones generated even at syncytial stages of embryogenesis yield tubule clones that do not exceed two to three suitably labelled cells , ruling out the validity of this approach ( see Figure S5 ) . Our analysis also revealed that there is little discernible expression of dpERK or modulation of Capicua::Venus in the proximal half of the tubules and this is reflected in the lack of any polarisation in the distribution of cortical Slam-HA or of asymmetric actomyosin activity . These findings indicate that , although tubule extension in the proximal regions , as in the distal , results from circumferential intercalation of cells , underlying movements must be regulated by different processes in the two halves . Our analysis has focussed on the anterior tubule pair , whose forward movement through the body cavity is regulated by guidance cues expressed by specific target tissues [64] , and we suggest that extension of the distal tubule results in sufficient forward movement to deliver the cue-responsive kink region close to target tissues that promote continued forward movement of the whole tubule . As the tubule is tethered both to the ureter/hingut proximally and distally , by TCs/alary muscle contacts [65] , forward tubule movement will produce mechanical forces that could promote circumferential intercalation in the proximal tubule half . In the distal tubule , one important consequence of cell polarisation is asymmetry in the activity of Myosin II to the proximal side of tubule cells , which leads to transient circumferential cell contraction . Oriented Myosin II accumulation has been shown to result from EGF signalling in the tracheal placode; in the absence of signalling , Myosin II accumulation remains punctate and dispersed [66] . We find a similar phenotype . When EGF signalling is perturbed , Slam fails to become localised and Myosin II remains dispersed in unpolarised cells so that pulses fail altogether . A novel observation of this study is that planar Myosin II pulses are required in the basal cortex of MpT cells for CE . This contrasts with findings in the extending germ-band where adherens junction remodelling resulting from apical planar actomyosin enrichment has been proposed as a major motive force for cell rearrangements [6] , [7] , [15] . In MpT cells , asymmetric Myosin II activity within 4 µm of the basal surface correlates with cell shape change and is required for CE movements . We have examined the apical side of tubule cells for actomyosin dynamics and do not detect repeated or polarised Myosin II cresents in this region of the cell cortex ( see Movie S15 ) , but we have not been able to live image the apical regions deeper in the tubules with sufficient reliability to assess whether junctional remodelling precedes or follows the basal changes . He and colleagues [53] have shown that oocyte elongation depends on pulsatile basal contractions of follicle cells , oriented in the circumferential axis . Similarly elongation of the Caenorhabditis elegans embryo results from the intercalation of hypodermal cells led by basal , medially directed protrusions [67] . It is possible that intercalating cells commonly initiate movements basally and that in epithelia junctional remodelling follows , also contributing actively to tissue morphogenesis [24] . A remaining question is how the acquisition of PCP relates to asymmetry in cytoskeletal activity . Slam localisation during cellularisation of the Drosophila embryo or in the extending germ band is known to highlight sites of Myosin II accumulation [6] , [13] , [68] . Like the extending germ band , tubule cells do not express Slam endogenously; its localisation therefore must reflect asymmetry in a binding partner , such as RhoGEF2 , to which it is known to bind during cellularisation [68] . An antibody against RhoGEF2 revealed that its expression is scarcely detectable in tubule cells and it does not appear to be asymmetrically localised . However , mutants for RhoGEF2 show CE defects in tubule elongation [69] . This suggests that RhoGEF2 might provide a link between EGF signalling , tubule cell polarity and asymmetric cytoskeletal activity . The duration of myosin pulses and cell circumferential contraction is approximately 2 min , while cell intercalation takes an average of 42 min . During tubule elongation the diameter of cells is around 5 µm ( see Figure 5 ) yet our measurements indicate that cells move an average of 1 µm min−1 . Are these measurements consistent with the dynamics and timing of tubule morphogenesis as a whole ? If one assumes that cells move in a consistent direction during intercalation this would suggest a serious overshoot so that cells would move past their neighbours . However cell movement relative to neighbouring cells is not uniform ( see Movie S4 ) and the movements we measure result from multiple factors; ( a ) the displacement of the whole tubule as a result of gut morphogenesis ( for example; hindgut elongation during stages 13–16 [70] ) ; ( b ) the concerted movement of tubule cells as a result of cell rearrangements in more distal regions; and finally ( c ) movements of individual cells relative to their neighbours that produce cell intercalation . The first two tend to produce distal-to-proximal movement , which would explain the deviation in total cell movement from the circumferential axis seen in Figure 5I . Our observations concerning circumferential movement suggest that cell intercalation results from repeated , transient , and very tiny movements ( Figure 7iii ) —which must be stabilised perhaps by adhesion either to the basement membrane or to adjacent cells—in which a small but consistent circumferential bias eventually achieves cell rearrangement ( Figure 7iv ) . Concerning timing; tubules increase in length 4-fold with the reduction of eight to 12 cells around the lumen to just two cells ( Figure 1A , 1C , and 1D ) . Simple calculation suggests that this would require that every cell intercalates twice , with some undergoing a third cell rearrangment . Tubule extension takes approximately 5 hours and each intercalation an average of 42 min , indicating that three intercalation events could be accommodated in the time-frame of elongation . The mechanisms known to drive tubule elongation include oriented cell division and polarised changes in cell shape , as well as CE cell rearrangements [16] , [19] , [22] , [71] . Here we show that fly renal tubules elongate predominantly by cell intercalation . In frog and mouse embryos renal tubule extension also depends primarily on cell rearrangements as the orientation of cell division is random [16] , [22] . As in Drosophila CE depends on Myosin II activity that is polarised in the plane of the tubule epithelium to bring about mediolateral cell intercalation . But in contrast to our findings , nephron elongation results not from cell intercalation directed by graded EGF signalling but from PCP gene-regulated formation and resolution of multicellular rosettes [22] . However , EGF signalling does play an important role during mouse embryonic kidney development in regulating both nephron cell proliferation and morphogenesis and in collecting duct extension [72] , [73] . The mature shape of tubular epithelial tissues is critical for their effective function . Abnormalities in the morphogenesis of renal tubules in mammals , for example in cystic kidney disease , results in defective excretory physiology leading to premature death [1] , [24] , [74] . Flies lacking the normal polarising signals that regulate renal tubule morphogenesis similarly suffer renal malfunction leading to lethality [75] . The identification of a genetically manipulable system in which to study the molecular interactions that lead from cell polarity to asymmetric cytoskeletal regulation , polarised cell movement and tissue shaping provides a powerful model for future analysis of tubule morphogenesis in health and disease .
Flies were cultured on standard media at 18°C or 25°C with ectopic expression at 29°C . Embryos were collected overnight at 25°C ( 29°C for dual colour imaging ) on apple-juice agar plates with yeast paste . The following stocks were used: Oregon-Red ( wild type ) ; ctB-Gal4; UAS-RedStinger6; UAS- ( EGFP ) Stinger2; Capicua::Venus ( gift of E . Wieschaus ) ; UAS-EGFRDN ( gift of M . Freeman ) ; UAS-λtop4 . 2/4 . 4 ( UAS-EGFRact , gift of T . Shupbach ) ; EGFRf7; UAS-SqhE20E21; UAS-YFP-ZipDN and sqhAX3 , sqh-Sqh::GFP , sqh-Sqh::GFP ( gift of T . Lecuit ) ; sqh-Sqh::mCherry [51] ( gift of A . Martin ) ; UAS-GAP43::GFP; sqhAX3 , sqh-Sqh::GFP , sqh-GAP43::mCherry [76] ( gift of B . Sanson ) ; A37-LacZ ( nrmLacZ ) ; Df ( os ) 1A; UAS-Slam::HA [40] ( gift of J . Zallen ) ; hs-flp122 ( gift of J . Castelli-Gair Hombría ) , tub>stop>Gal4 ( gift of M . Landgraf ) , FRT dsUA071; dsUAO71 , stanE5; dsUAO71 , stan3; dsh1; fz1; stbm6; ftG-rv ( gifts of J . Casal and D . Strutt ) . hs-flp122; tub>stop>Gal4/UAS-Slam::HA; embryos were collected for 2 hours at 25°C and heat-shocked in a 37°C water bath for 10 minutes . Embryos were aged to stage 15 at 25°C , fixed and processed for antibody staining . Embryos were dechorionated in 50% bleach , washed extensively with double-distilled water , and oriented dorso-laterally to visualise anterior Malpighian tubules ( aMpTs ) . Oriented embryos were mounted on type-1 coverslips with an evenly spread layer of glue ( 3M Scotch tape glue-Heptane ) . Care was taken not to compress the embryos . Mounted embryos were covered with Voltalef-3S or Halocarbon-10S oil . For dual colour imaging of Myosin II and membrane dynamics , embryos of the following genotypes were used: w−;ctB>UAS-GAP43::GFP , sqh-Sqh::mCherry/sqh-Sqh::mCherry;+; sqhAX3;sqh-Sqh::GFP;sqh-GAP43::mCherry; w−;ctB>UAS-GAP43::GFP , sqh-Sqh::mCherry/UAS-EGFRDN;sqh-Sqh::mCherry/+ . Images were acquired on Leica SP5 or Olympus FV1000 confocal microscopes with 488 nm and 561 nm lasers . An Argon ion laser was used for imaging GFP; dsRed and mCherry were imaged with a 561 nm diode laser . z-Stacks were acquired every 45 seconds for 5–6 hours with a water immersion 20×/0 . 7 NA objective to capture aMpT elongation ( Figure 1C , 1F , 3D , and 3F ) . 60×/1 . 4 NA ( Figure 5A ) or 63×/1 . 4 NA ( Figure 5B and 5C ) . Oil immersion objectives were used to visualise Myosin II and membrane dynamics in the basal-most 2–4 µm z-sections every 8–15 sec . Dual colour imaging was performed using previously established excitation band-pass settings [51] with Leica-SP5 Hybrid detectors . All images except those in Figure 5A were acquired on a Leica-SP5 confocal microscope . For Sqh::GFP in Figure 5A an Olympus-FV1000 confocal was used . All embryos completed development and hatched as L1 post-imaging . aMpT lengths and cell shape changes were analysed using ImageJ ( http://imagej . nih . gov/ij/ ) . Cell tracking was performed using SIMI-Biocell ( SIMI reality motion systems ) . Origin ( OriginLab ) and SigmaPlot ( Systat Software ) were used for statistical analysis , independent t-test , and for generating graphs . Cell-tracking and speed measurements were performed as described previously [77] , with minor modifications . SIMI-Biocell ( version 4 . 0 built 155 , SIMI reality motion systems ) was used for tracking cell movements and for the generation/colouring of 4-D reconstructions . 3-D positions of fluorescently labelled aMpT nuclei were tracked over time manually . 3-D coordinates of the nuclei were saved every 9 minutes ( or every 1 minute in Figure 1H and 1H″ ) during the course of a movie . Cell speeds were measured by calculating the distance moved by aMpT nuclei every 9 minutes ( or every 1 minute in Figure 1H and 1H″ ) . Movies and 4-D reconstructions were annotated and represented in their final form using ImageJ ( Rasband WS , National Institutes of Health , http://imagej . nih . gov/ij/; 1997–2012 ) . Cell shape analysis was performed using ImageJ . Single z-slices at 12–18 second intervals were used to manually trace basal cell outlines with the polygon selection tool . Traces were saved using the ROI manager . The centre and total area for each trace was determined with the in-built “centroid” and “area” measurement tools . Cell length was measured by drawing lines through the centroid that connected edges in axes either parallel ( distal-proximal ) or perpendicular ( circumferential ) to the distal to proximal tubule length . Area and lengths of a cell were normalised with their average represented as 1 . 0 . aMpT lengths were calculated by drawing and measuring a segmented line along the distal to proximal tubule length in ImageJ . Dechorionated ctB>UAS-CD8-GFP embryos were mounted on double-sided Scotch tape in PBS solution . The TC and surrounding two or three cells were ablated ( to ensure removal of both TC and SC ) in late 12/early 13 stage embryos . Cell ablation was performed using a 63×/0 . 9 NA water immersion lens on a Yokogawa spinning disk ( CSU-10 ) confocal microscope fitted with a pulsed nitrogen laser ( MicroPoint ) . Image acquisition and microscope control were by MetaMorph ( version 7 . 0 ) software ( Molecular Devices ) . Embryos were allowed to develop to stage 16 under humid conditions at 25°C , fixed and processed for immunostaining . Embryos were fixed in 4% paraformaldehyde and devitellinised by vigorous shaking in 1∶1 heptane/methanol . Immunostaining was performed using standard techniques . For pMLC staining ( Figure S5 ) , embryos were fixed in 37% formaldehyde for 3–5 minutes and devitellinised using a fine glass needle . The primary antibodies used were: mouse anti-FasII ( 1∶10 , DSHB ) ; mouse anti-Cut ( 1∶50 , DSHB ) ; rabbit anti ß-gal ( 1∶10 , 000 , ICN Biomedicals ) ; rabbit anti-Rhomboid ( 1∶500 , gift of E . Bier ) ; rabbit anti-dpERK ( 1∶50 Cell Signaling technology ) ; rabbit anti-Bazooka ( 1∶500 , gift of A . Wodarz ) ; rabbit anti-Cleaved Caspase3 ( 1∶20 , Cell Signaling technology ) ; goat anti-GFP ( 1∶500 , Abcam ) ; mouse anti-Futsch/22c10 ( 1∶200 , DSHB ) ; rat anti-HA ( 1∶200 , Roche ) , rabbit anti-phospho-Myosin Light Chain 2 ( [Ser19]; 1∶20 , Cell Signaling technology ) . Secondary antibodies were used at 1∶200 . Appropriate biotinylated secondary antibodies were used with the Vector Elite ABC Kit ( Vector Laboratories ) for DAB staining . FITC- or Cy3-conjugated secondary antibodies were used for fluorescent labelling . When required , streptavidin-conjugated FITC/Cy3 amplification was used . TSA-Biotin amplification system ( Perkin-Elmer ) was used for dpERK detection . DNA was stained with DAPI ( 1∶1 , 000 , Molecular Probes ) . Embryos and tissue were mounted in Vectashield ( Vector Laboratories ) and viewed on a Leica SP5 confocal microscope . Image processing was performed using ImageJ and Adobe Photoshop . To measure dpERK staining levels , stage 13 tubules were traced using the segmented line tool in ImageJ with a line width approximately equal to tubule width . The plot profile tool was used to quantify staining intensity along the line . Values were binned into 1 µm bins and averaged for n = 7 tubules . Figures were assembled in Adobe Illustrator . Embryos of the appropriate stage were fixed and stained with anti-FasII , dehydrated , and mounted in Araldite resin . Transverse sections approximately 2 . 5 µm in thickness were made midway along the distal region of aMpTs using a Reichert microtome . Embryos of the appropriate genotype were collected overnight and aged for a further 6 hours at 29°C . 40 first instar larvae were transferred to a vial of standard food and incubated at 25°C until adults eclosed . Secretory assays were performed as described previously [55] at 23–24°C using 3–5 day old adults . cAMP and LK1 ( Sigma ) were added to a final concentration of 1 mM and 100 µm at approximately 30 and 60 min , respectively . To measure wet and dry body weights , flies were briefly anaesthetized with CO2 , transferred to Eppendorf tubes on ice , three flies were pooled and weighed on a Mettler Toledo precision balance ( wet weight ) . The flies were killed by freezing for 20 minutes and transferred to a 50°C oven containing a tray of silica crystals , allowed to desiccate for ∼24 hours , and weighed again ( dry weight ) . | Many of the tissues in our bodies are built up around complex arrays of elongated cellular tubes , which permit the entry , exit , and transport of essential molecules such as oxygen , glucose , and water . These tubes often arise as short buds , which elongate dramatically as the organ grows . We sought to understand the mechanisms that govern such transformations of shape using the fly renal tubule as a model . We find that elongation of this tissue is predominantly driven by cell rearrangement . Cells move around the circumference of the tubule , intercalating with each other so that the cell number around the lumen reduces , while increasing along the length of the tube . Our next question was how cells sense the direction in which they should move . We show that cells orient their position in the tissue by reading a signal sent out by a specific pair of cells at the tip of each tube . Cells use this directional information to make polarised movements through the asymmetric activity of the cell's contractile machinery . We find that the activity of myosin—the motor protein that regulates contraction—is pulsatile and polarised within the cell . This activity shortens the cells' circumferential lengths , so that cells move past each other around the tube circumference , thereby intercalating and producing tube elongation . We go on to show that excretory physiology is severely impaired when elongation fails , underlining the importance of sculpting organs with appropriate dimensions . | [
"Abstract",
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] | [
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] | 2014 | Epidermal Growth Factor Signalling Controls Myosin II Planar Polarity to Orchestrate Convergent Extension Movements during Drosophila Tubulogenesis |
Trypanosoma cruzi is exposed during its life to exogenous and endogenous oxidative stress , leading to damage of several macromolecules such as DNA . There are many DNA repair pathways in the nucleus and mitochondria ( kinetoplast ) , where specific protein complexes detect and eliminate damage to DNA . One group of these proteins is the DNA polymerases . In particular , Tc DNA polymerase β participates in kinetoplast DNA replication and repair . However , the mechanisms which control its expression under oxidative stress are still unknown . Here we describe the effect of oxidative stress on the expression and function of Tc DNA polymerase β To this end parasite cells ( epimastigotes and trypomastigotes ) were exposed to peroxide during short periods of time . Tc DNA polymerase β which was associated physically with kinetoplast DNA , showed increased protein levels in response to peroxide damage in both parasite forms analyzed . Two forms of DNA polymerase β were identified and overexpressed after peroxide treatment . One of them was phosphorylated and active in DNA synthesis after renaturation on polyacrylamide electrophoresis gel . This phosphorylated form showed 3-4-fold increase in both parasite forms . Our findings indicate that these increments in protein levels are not under transcriptional control because the level of Tc DNA polymerase β mRNA is maintained or slightly decreased during the exposure to oxidative stress . We propose a mechanism where a DNA repair pathway activates a cascade leading to the increment of expression and phosphorylation of Tc DNA polymerase β in response to oxidative damage , which is discussed in the context of what is known in other trypanosomes which lack transcriptional control .
Trypanosoma cruzi , a flagellated protozoan , is the causative agent of Chagas´ disease ( CD ) , which constitutes a major public health problem in Latin America . In endemic regions 10 million people are infected by the parasite and another 25 million are at risk of acquiring the infection [1] . There is currently no vaccine against Trypanosoma cruzi and the treatment of CD has limited efficacy and cause severe side effects [2] . Therefore there is a critical need to develop new chemotherapeutic agents and vaccines to control CD . Knowledge of the basic cellular processes of this parasite will help the development of new compounds to target specific processes of this parasite . T . cruzi has a complex life cycle which includes different stages that alternate between invertebrate ( insect vector ) and vertebrate hosts , including humans . Epimastigote forms and infective metacyclic trypomastigotes occur in the insect vector and intracellular amastigotes and bloodstream trypomastigotes in the mammalian host [3] . Each stage of differentiation expresses a pattern of stage-specific proteins involved in the process of invasion and survival of the parasite . The current chemotherapy for Chagas´ disease is based on benznidazole and nifurtimox , which are nitroheterocycle compounds; according to several studies they generate oxidative stress by T . cruzi nitroreductases [4 , 5 , 6] . Both type I nitroreductase in anaerobic and type II nitroreductase in aerobic conditions [5 , 7] , have been proposed for drug activation and promotion of DNA damage . Reactive oxygen species ( ROS ) and reactive nitrogen species ( RNS ) derive from partly molecular oxygen and nitrogen reactants respectively , when produced in physiological quantities , play critical roles in the normal developmental process , and control signal transduction mechanisms that regulate cell proliferation , differentiation and death in higher eukaryotes [8 , 9] . However , when ROS/RNS are produced in excess or for sustained periods they can rapidly oxidize proteins , lipids and DNA . ROS/RNS species and electrophilic metabolites can react with DNA , breaking bases and sugars , and cause nucleic acid chain cleavage [10] . However , several DNA repair mechanisms exist that restore DNA integrity , i . e . nucleotide excision repair ( NER ) , base excision repair ( BER ) and a recombination system using the sister chromatid to repair DNA single and double stranded breaks [11 , 12] . Most of the DNA repair processes need several DNA enzyme systems , but one of the last steps involves DNA polymerases that fill the gaps in the damaged DNA . The susceptibility of trypanosomes to ROS/RNS in limiting T . cruzi replication and survival in infected cells and experimental animals has been reported [13] . The production of ROS/RNS is one of the most efficient mechanisms involved in the killing of T . cruzi bloodstream trypomastigotes by macrophages [14 , 15 , 16 , 17] and also by cardiomyocytes in vitro [18] , and to control T . cruzi infections in vivo [19] . Epimastigotes in the insect vector are exposed to ROS by the non-enzymatic Fenton reaction caused by Fe+2 of heme [20 , 21] . T . cruzi , like other trypanosomatids , are exposed to several rapid changes since their life cycle occurs in different hosts exposed to various stresses , including oxidative stress . Unlike other eukaryotic organisms , trypanosomes lack the ability to control transcription [22] . However , potential components of signal transduction pathways have been described in trypanosomatids [23] , which control translation and protein modification . Different DNA polymerases have been described in T . cruzi which are related to DNA repair and oxidative stress: DNA polymerase β involved in the BER system and mitochondrial DNA replication , and the nuclear DNA polymerase v involved in the BER system . DNA polymerase v , DNA polymerase κ and DNA polymerase ζ participate in bypassing DNA lesions . The role of DNA polymerase β is poorly understood but it appears to be involved in DNA repair after oxidative stress , since its overexpression in transfected parasites after hydrogen peroxide treatment [24] , and benznidazole oxidative stress increased parasite survival [25] . We have previously purified and characterized the native and recombinant DNA polymerase β from T . cruzi epimastigotes and generated polyclonal antibodies [26 , 27] . To gain insights into the role of DNA polymerase β in T . cruzi , we have studied the effect of the oxidative stress induced by hydrogen peroxide on the expression and activity of DNA polymerase β in epimastigote and trypomastigote forms . Our results indicate that DNA polymerase β is overexpressed in those conditions . However , the mRNA levels of the enzyme do not change and the increasing levels seem to be at the post-translational level .
Tc DNA beta polymerase has been immunolocalized inside the mitochondria of T . cruzi organisms . However , there are no supporting studies indicating a physical interaction between Tc DNA polymerase β and kinetoplast DNA and whether or not this interaction is affected by H2O2 stress . To investigate this interaction , immunoprecipitated DNA from epimastigote and trypomastigote cultures treated or not with H2O2 were amplified by end point PCR with specific primers either for the kinetoplast or nuclear DNA ( Table 1 ) . As can be seen in Fig 1 , either from H2O2-treated and from untreated cells , kinetoplast DNA was successfully precipitated by Tc DNA β polymerase antibody , since positive PCR amplification was observed . However , no positive amplification was observed with nuclear DNA , indicating a negative interaction with Tc DNA polymerase β antibody . These results suggest that there is a direct interaction between Tc DNA polymerase β and kinetoplast DNA in epimastigote and trypomastigote developmental forms , which is in agreement with the mitochondrial localization described elsewhere [28] . To investigate the effect of oxidative stress in the DNA repair function of DNA polymerase β , we treated both epimastigote and trypomastigote cells with H2O2 for different periods of time and proteins were analyzed by western blot . As can be seen in Fig 2A and 2B , protein levels of Tc polymerase β were increased in both epimastigote and trypomastigote forms and the increment was dependent on the treatment time . The high ( H ) and low ( L ) molecular weight protein forms identified were quantified and the results are indicated in Fig 2B . In epimastigote and trypomastigote forms the H-form showed an increment of >4-fold compared to the control ( 0 hours treatment ) . However , the L-form showed an increment of >4-fold after 1 hour of peroxide treatment in epimastigotes , whereas in trypomastigotes a 2-fold increment was observed after 2 hours of peroxide treatment . A control protein , tubulin , did not show increase upon treatment either in trypomastigote or epimastigote forms , indicating that there is a selective increase of the Tc DNA polymerase β enzyme after treatment with hydrogen peroxide and not a global change in protein synthesis . To evaluate post-translational modification that explains the presence of two protein forms in epimastigote and trypomastigote cells , we first evaluated the phosphorylation state of Tc DNA polymerase β in protein extracts . For this we prepared protein extracts from epimastigotes and trypomastigotes and Tc DNA polymerase β was immunopurified from these extracts . The resulting material was subjected to western blot analysis . In the precipitated material , the slower migrating polypeptide ( H ) is phosphorylated in trypomastigote cells , since it can react with antibodies against phosphoaminoacids ( Fig 2C ) . These observations agree with previous results in epimastigotes [27] . We did not detect a change in the mobility of the slower migrating band upon treatment with N- or O- glycosidases , suggesting the enzyme does not contain sugar moieties . Earlier observations indicated that the native Tc DNA polymerase β could be purified as a doublet and only the slower migrating form is active in DNA synthesis [26] . To investigate which form of the enzyme is the active one , we purified Tc DNA polymerase β from crude cell extracts using affinity chromatography with antibodies covalently attached to protein A-agarose . The extracts were incubated with the resin , washed and the bound enzyme was eluted with a buffer containing SDS and urea . The eluted fractions were analyzed through SDS-PAGE and polymerase activity was evaluated in an activity gel . As can be seen in Fig 3 , only one polypeptide from the purified fraction is active and co-migrates with the high molecular weight band of Tc DNA polymerase β ( H ) . In crude epimastigote extracts there is a main active polypeptide , which migrates along with the active polypeptide from the affinity-purified fraction , and a weak active polypeptide , which is larger than Tc DNA polymerase β . This protein band might correspond to the Tc DNA polymerase ζ catalytic subunit ( Accession EKF26846 . 1 ) , which is composed of 980 amino acids and has a calculated MW of 108 kDa . The recombinant Tc DNA polymerase β is also active in this assay and migrates slightly below the native enzyme as it is detected in western blot analysis . The presence of only one active polypeptide in the affinity-purified fractions is not because only one polypeptide was retained by the antibodies , since a western blot analysis revealed that both polypeptides are present in both affinity purified and crude extracts ( Fig 3B ) . Also , the activity of the 45 KDa polypeptide increased in both epimastigote and trypomastigote developmental forms treated with H2O2 ( Fig 3C and 3D ) . To investigate the levels of Tc DNA polymerase β mRNA in H2O2-treated epimastigotes , we isolated RNA from treated cells and it was reverse transcribed and quantified by qRT-PCR . The levels of Tc DNA polymerase β mRNA from epimastigotes cells at 0 , 2 and 4 hours of treatment with H2O2 are shown in Fig 4A . It can be seen that the levels of mRNA for the enzyme tend to decrease upon treatment with hydrogen peroxide ( 60% after 2 hours of treatment and 40% after 4 hours ) . However , we do not know whether or not there is a change in the total mRNA or if it is the result of peroxide damage to the mRNA and this is not able to serve as a template for the reverse transcriptase . To test the effect of peroxide treatment on mRNA integrity we evaluated Tc DNA polymerase β levels by Northern blot . Fig 4B and 4C show that mRNA levels decreased nearly 20% after 2 hours of treatment and 10% after 4 hours . These results correlate with results from RT-qPCR , although the differences were greater than the Northern blot results . In addition , the levels of Tc DNA polymerase β mRNA from trypomastigote cells at 0 and 4 hours of treatment with H2O2 were also measured by qRT-PCR ( Fig 4D ) . It can be seen that the mRNA levels for the enzyme decrease near 15% after 4 hours of peroxide treatment , unfortunately the amount of total RNA obtained in those experiments was not enough to analyze Tc DNA polymerase β mRNA levels by Northern blot . Altogether , these results indicate that there is not a transcriptional control of the expression of the Tc DNA polymerase β gene since the mRNA levels did not increase considerably .
Eukaryotic cells contain multiple DNA repair pathways that maintain genomic DNA integrity . The Base Excision Repair ( BER ) pathway protects DNA by removing oxidized , methylated or deaminated bases by the action of glycosylases [29] . These DNA sites are called apurinic/apyrimidinic ( AP ) sites and arise mainly as base oxidation from reactive oxygen species ( ROS ) , among others . The BER pathway is distinguished from other DNA repair pathways by the removal of the base lesion . Several steps are necessary to accomplish DNA repair; one of the final steps involves DNA synthesis to fill the gap to ligate DNA strands . In mammalian systems DNA polymerase β contributes to filling the gap , removing the 5´deoxiribose phosphate ( dRP ) termini by a dRP lyase activity to later make single-nucleotide gap-filling DNA synthesis . DNA polymerase β belongs to the X family of DNA polymerases and is found in all vertebrate species as a 39-kDa protein lacking proofreading 3´-or 5´-exonuclease activity but containing 5´-dRP lyase and AP lyase activities [30] . A homologous DNA pol β gene has been found in yeast [31 , 32] . Lower eukaryotic organisms such as Trypanosomatids also possess a DNA polymerase β and it might be involved in DNA repair . DNA pol β is considered the simplest naturally occurring DNA polymerase , making it an ideal model for studies to develop substrates/inhibitors that could specifically inhibit it . In this study we examined the effect of oxidative stress on T . cruzi ( Tc ) DNA polymerase β expression , showing the increment of protein levels of a phosphorylated form of this DNA polymerase during H2O2 treatment , although mRNA levels evaluated by qRT-PCR and Northern blot did not show significant differences . The oxidative stress effect in T . cruzi has been documented in vitro [13 , 33] and in vivo [19] . It is estimated that BER is the main DNA repair pathway acting upon ROS [34] and it has been described that this pathway is active in nuclei and mitochondria under oxidative stress [33] . In addition , transfected parasites overexpressing Tc DNA pol β showed increased survival after treatment with benznidazole ( BZ ) , the classic anti-Chagas drug and a potent oxidative stressor , compared to non-treated cells [25] . These results also suggest that Tc DNA pol β exerts the DNA repair function on kDNA rather than on the nuclear DNA as previously suggested [24] and according to our results . Other DNA polymerases associated with DNA repair can to synthetize DNA bypassing DNA lesions , i . e . DNA polymerase ζ , DNA polymerase η and DNA polymerase κ . DNA polymerase ζ has not been characterized in parasites yet . However , overexpression of polymerases η and κ in transfected parasites displayed resistance to benznidazole and hydrogen peroxide in the same way as polymerase β [25 , 35] . Oxidative stress with hydrogen peroxide diminishes cell viability of T . cruzi epimastigotes and trypomastigotes [33] . T . cruzi DNA damage and repair of epimastigotes in the presence of Nifurtimox or BZ induces nuclear DNA and kDNA damage but the effect is reversed when the drugs are removed , and the parasites are incubated in fresh medium [36] . The results presented in this work suggest the presence of a robust DNA repair machinery in T . cruzi . Major mechanisms of gene regulation in T . cruzi and other kinetoplastids appear to be post-transcriptional since transcriptional units are polycistronic and promoters do not have regulatory sequences as in higher eukaryotic organisms [37] , therefore signaling pathways regulating gene expression might target molecules regulating RNA processing/turnover and protein modification . Our results showed the presence of an active phosphorylated form of Tc DNA polymerase β , which correlates with a high molecular weight active form of this DNA polymerase whose levels are increased when parasite cells are exposed to peroxide . The protein levels of this DNA polymerase form are increased during peroxide treatment in the epimastigote and trypomastigote forms despite mRNA levels tend to decrease , suggesting a post-transcriptional regulation and a possible phosphorylation-mediated pathway dependent on oxidative stress . Interestingly , only the high molecular weight form of the polymerase has DNA synthesis activity suggesting that phosphorylation assist to the proper refolding of the protein . The identification of the pathway associated with oxidative stress found in our experimental approach is part of the projections of this work . One of the putative pathways that could be related is MAP kinase pathways , which have been identified regulating cell growth , apoptosis and stress responses in higher eukaryotics [38] . In yeast and other fungus-related organisms , a conserved pathway has been described called the SPAK-pathway ( stress protein activated kinases ) , which involves MAPK proteins and AP-1-like transcription factor [39] . In the case of trypanosomatids , they must respond to extracellular and intracellular signals as they adapt rapidly to new environments within their varied hosts . However , the molecular mechanisms of parasite responses to environmental changes are still unknown . Recent studies in trypanosomatids have described stress-response mechanisms involving post-transcriptional regulation . For example , rapid shifts to low temperatures in the presence of cis-aconitate allow differentiation of bloodstream to procyclic forms of Trypanosoma brucei [40] . A protein phosphatase PIP39 and a potential RNA-binding protein are involved in this process [41 , 42] . Studies in the same parasite from procyclic differentiation to mammalian infective forms after heat shock show changes in the compartmentalization of mRNA , predominantly untranslated and associated with proteins from the cytosolic fraction to polysomal fraction after 1 hour of heat shock treatment [43] . Several proteins such as the zinc-finger ZC3H11 , polyA binding proteins , helicase , aggregation-prone protein and a 5–3 exonuclease are involved in this mechanism of mRNA storage and degradation of non-translated mRNAs . These factors are RNA-binding proteins ( RBPs ) and are the hallmark of mRNA stabilization , affecting the whole gene expression process in Trypanosomatids [44] . ZC3H11 binds to the 3’-UTRs of chaperone mRNAs and is required both for target mRNA retention and for cell survival after heat shock [45] . This zinc finger protein also binds to MKT1 , which is a protein associated with stress resistance , and two polyA binding proteins required for translation initiation [46] . Several reports have shown that ZC3H11 is phosphorylated and the most likely protein kinase is casein kinase 1 [47] . Finally , according to our results a phosphorylated form of Tc DNA polymerase β is present in epimastigote and trypomastigote cells . This protein form is associated with a slower migrating band detected by SDS-PAGE and western blot . Overexpression of the phosphorylated form of Tc DNA polymerase β is observed in both epimastigote and trypomastigote cells , indicating a putative stress response that could lead to stress-related pathway activation where protein kinase induction could be involved . This induction would lead to two putative responses: 1 . function modulation of Tc DNA polymerase β by direct phosphorylation; and 2 . changes in mRNA stabilization by phosphorylation of mRNA chaperones associated with 3’ or 5’ UTR , leading to high/low translation rate . However , further studies must be performed to identify the exact mechanism involved in phosphorylation of Tc DNA polymerase β and what are the stress-related pathways activated during this process and to evaluate the mechanisms recently described involving post-transcriptional mRNA stabilization and protein kinases such as casein kinase 1 .
Epimastigote cells ( 6 x 108 ) were harvested and washed with PBS . Cells were then resuspended in 5 ml of lysis buffer ( 50 mM Tris-HCl ( pH 8 . 0 ) , 1 mM EDTA , 1 mM EGTA , 500 mM KCl , 5 mM DTT , 0 . 5% v/v NP-40 , 0 . 1 v/v Triton X-100 , 10% v/v glycerol , 0 . 5 mM PMSF , 10 mM TSK ) supplemented with a tablet of protease inhibitor and Phospho-Stop ( Roche , Germany ) . Lysed cells were mildly sonicated at 4°C and centrifuged at 15000 rpm . Supernatants were collected and dialyzed against the lysis buffer without NP-40 or Triton X-100 but containing 50 mM KCl . Usually the extract contained 5 mg/ml of total protein as measured by the method of Bradford [48] . The extract was stored at -80°C until used to purify Tc DNA β polymerase by affinity chromatography . Cell extract from hydrogen peroxide-treated trypomastigotes ( 50 x 106 cells ) was done exactly as described before , except that the cells were resuspended in 500 μl of buffer . Extracts were dialyzed and stored to -80°C until use . Green Monkey ( Cercopithecus aethiops ) renal fibroblast-like cells ( VERO cells , ATCC CCL-81 , USA ) were grown in RPMI medium enriched with 5% fetal bovine serum ( FBS ) and antibiotics ( penicillin-streptomycin ) . Cells were grown at 37°C in a humid atmosphere at 5% CO2 for 96 hours , replacing the medium every 24 hours . After confluence , VERO cells were incubated with a culture of epimastigotes in late stationary phase ( strain Y ) , which increases the percentage of trypomastigotes to approximately 5% . Trypomastigotes then invaded fibroblasts and replicated intracellularly as amastigotes . After 72 hours , amastigotes transform back to trypomastigotes that lyse host cells . Parasites were recovered by low-speed centrifugation ( 500 x g ) , thus obtaining trypomastigotes in the supernatant and amastigotes in the sediment . The cells were suspended at 5 x 105 cells/ml in RPMI medium and treated with 100 μM final concentration of hydrogen peroxide for 0 , 1 , 2 and 4 hours . Cells were harvested and stored at -80°C until used to purify Tc DNA polymerase β , western blot analysis , activity gels and mRNA purification . Epimastigote cells were grown to log phase in LIT media as described [49] . The cells were centrifuged and resuspended at 2 x 108 epimastigotes/ml in fresh media with 10% fetal bovine serum . Hydrogen peroxide was added at a final concentration of 100 μM with incubation for 0 , 1 , 2 or 4 hours at 28°C . After incubation , the cells were harvested and stored at -80°C until used to obtain cell extracts for activity gels , western blot analysis , Tc polymerase β purification and mRNA purification . Samples containing epimastigote or trypomastigote cells were resuspended in 20 μl of 20 mM Tris-HCl ( pH 7 . 5 ) , 0 . 5 mM EDTA , 0 . 1% v/v Triton X-100 , 0 . 1% v/v NP-40 , 200 mM NaCl and 0 . 5 mM PMSF . The cells were broken by mild sonication and centrifuged at 12000 rpm for 15 minutes . The supernatant was collected and mixed with Laemli sample buffer and heated at 100°C for 5 minutes . Proteins were separated in 8 . 5% SDS-PAGE gels and transferred to PVDF membranes ( Immobilon , USA ) ; T . cruzi DNA β polymerase was detected using anti-DNA β polymerase or anti-phospho aminoacid ( Abcam , UK ) . Detection of the antibodies was performed by anti-rabbit IgG conjugated to alkaline phosphatase ( Promega , USA ) followed by chemiluminescence ( Novex , USA ) or colorimetric assay ( BioRad , USA ) . Detection of DNA synthesis on SDS-PAGE was done according to the literature [50] , with slight modification . Briefly , protein samples from 1 x 106 epimastigote and 2 , 5 x 106 trypomastigote cells treated or not with 100 μM H2O2 , were mixed with fetal calf serum ( 10% v/v final concentration ) and 0 , 2 volumes of Laemmli sample buffer containing 10 mM DTT . Then , samples were heated at 37°C for 5 minutes . Proteins were separated on an 8 . 5% SDS-PAGE gel containing 100 μg/ml activated calf thymus DNA , and after the run was complete , the gels were washed twice with 50 mM Tris-HCl ( pH 8 . 0 ) at room temperature . Then the proteins in the gel were renatured at room temperature for 3 hours in a folding buffer ( 50 mM Tris–HCl pH 8 . 0 , 0 . 5 mM EDTA , 5 mM DTT , 0 . 5 mg/ml BSA , 15% v/v glycerol , 0 . 01% v/v NP-40 and 4 mM Mg-Acetate ) . Then the gel was incubated at 4° overnight with folding buffer to renature the proteins further . After this step the gel was incubated overnight in folding buffer supplemented with 250 mM KCl , 25 μM dTTP , dGTP , dCTP , 1 μM dATP , 1 μl/ml P32 dATP ( 250 μCi/mMol ) and 3 mM MnCl2 . The incubation was done at room temperature with gentle agitation . Then the gel was washed at least five times with 5% v/v TCA and 2% w/v potassium pyrophosphate for 30 minutes at room temperature each wash . A final wash was done with the above solution at 50°C for 45 minutes and the gels were exposed to X-ray film for autoradiography . Those SDS-PAGE activity gels used to analyze the H2O2 response were supplemented with 4 mM MnCl2 in order to obtain a better activity of the enzyme . Epimastigote ( 63 x 106 cells ) and trypomastigote ( 5 x 106 cells ) incubated by 4 hours with 100 μM H2O2 were washed with sterile PBS , resuspended in 10 ml PBS and treated with 200 μl formaldehyde ( 37% w/v ) for 4 minutes at room temperature . Crosslinking of the proteins to the DNA was quenched by adding 1 ml 1 M glycine . The cells were centrifuged and washed with PBS . After washing , cells were resuspended in 600 μl RIPA buffer ( 1% v/v NP-40 , 0 . 5% w/v deoxycholate , 0 . 1% w/v SDS , 150 mM NaCl , 1 mM EDTA , 1 mM EGTA and 50 mM Tris-HCl pH 8 . 0 ) and the mix was left to stand for 15 minutes at room temperature . The mix was sonicated to produce DNA fragments of approximately 1 Kb average length . An aliquot of 100 μl was kept to purify the input DNA . Another aliquot of 500 μl was precleared with 40 μl of protein A–agarose ( Invitrogen , USA ) beads previously washed in RIPA buffer . The mix was incubated for 3 hours at 4°C . After centrifuging the extract , the supernatant was incubated with 2 μg of anti-Tc DNA polymerase β antibodies and 40 μl Protein A–agarose beads previously washed in RIPA buffer . Incubation was performed at 4°C for 8 hours . Then the mix was centrifuged and the beads were washed 4 times with 50 mM Tris-HCl ( pH 8 . 0 ) containing 1 mM EDTA , 150 mM NaCl and 0 . 1% v/v Triton X-100 . A final wash was made with PBS . The beads were resuspended in 200 μl 60 mM Tris-HCl ( pH 6 . 8 ) , 200 mM NaCl , 2% w/v SDS and 10 mM DTT . The beads were finally incubated for 8 hours at 65°C to reverse the crosslink . Supernatants containing DNA were extracted once with phenol-chloroform and once with chloroform to eliminate proteins . Precipitated DNA was obtained by adding 0 . 1 volume Na-acetate pH 5 . 2 and 3 volumes ethanol and after centrifuging the pellet was washed with 80% ethanol , dried and resuspended in 10 μl TE buffer . The DNA was amplified by PCR using specific primers as indicated in Table 1 . Total RNA was isolated from 63 x 106 epimastigote cells or 5 x 106 trypomastigote cells previously treated with hydrogen peroxide for 0 , 2 or 4 hours . Cells were resuspended in 1 ml of TRizol Reagent ( Ambion , USA ) and the RNA was isolated as indicated by the manufacturer . The precipitated RNA was resuspended in 20 μl of TE buffer and digested with 1 unit of DNAase free of RNAase ( Promega , USA ) . The DNAase was inactivated at 70°C for 20 minutes . Reverse transcription was performed using 1 μg of RNA as template and following manufacturer’s instruction ( NEB , USA ) . Tubuline ( internal control ) and T . cruzii DNA polymerase β were amplified using equal amounts ( 50 ng ) of cDNA from each treatment as template and using Brillant II Sybr Green GPR Master Mix ( Agilent , USA ) . PCR reactions were performed in the following conditions: initial denaturation of 10 minutes at 95°C , 35 cycles of 10 seconds at 95°C , 10 seconds at 53°C and 30 seconds at 72°C , with a final elongation at 72°C for 5 minutes . The primers used are described in Table 1 . The integrity of 2 μg of RNA of each sample was analyzed on a 1% agarose-formaldehyde gel . RNA samples were then transferred to a Hybond membrane according to manufacturer’s instructions ( GE Healthcare Life Sciences , USA ) . Nucleic acids were crosslinked to membranes using UV light ( UV Stratalinker 2400 , Stratagene , USA ) . Membranes containing RNA samples were washed for 10 minutes with 4X SSC buffer ( 600 mM NaCl , 60 mM sodium citrate pH = 7 . 2 ) and then incubated for 2 hours at 48°C with pre-hybridization buffer ( 750 mM NaCl , 75 mM sodium citrate , 50% formamide , 0 . 2% SDS , 200 μg/ml salmon sperm DNA , 5X Denhart’s solution [0 . 1% Bovine serum albumin , 0 . 1% ficoll 400 , 0 . 1% polyvinylpyrrolidone] , pH = 7 . 2 ) . Then membranes were incubated overnight at 48°C with probes to detect Tc DNA pol β or actin previously labeled with dUTP-digoxigenin according to manufacturer’s instructions ( Roche , Germany ) and denatured at 110°C for 10 minutes and mixed with ultrahyb ( Thermofisher , USA ) at 50 ng/ml each probe . Primers used to generate probes are listed in Table 1 . Membranes were washed twice for 5 minutes at 48°C , first with 2X SSC/SDS ( 300 mM NaCl , 30 mM sodium citrate , 0 . 4% SDS , pH = 7 . 2 ) and then with 0 . 5X SSC/SDS ( 75 mM NaCl , 0 . 75 mM sodium citrate , 0 . 4% SDS , pH = 7 . 2 ) . Then membranes were washed twice at room temperature for 5 minutes with maleic acid buffer supplemented with Tween-20 ( 50 mM maleic acid , 150 mM NaCl , 0 . 3% Tween-20 , pH = 7 . 5 ) . Membranes were blocked with 1% non-fat milk in maleic acid buffer for 1 hour at room temperature . Then , membranes were incubated with anti-digoxigenin alkaline phosphatase ( AP ) conjugated ( Roche , Germany; diluted 1/10000 in maleic buffer alone ) for 1 hour at room temperature . After this , membranes were washed twice for 5 minutes with maleic acid buffer supplemented with Tween-20 . Then after incubation for 2 minutes with AP buffer ( 100 mM Tris pH = 9 . 5 , 100 mM NaCl , 5 mM MgCl2 ) , membranes were incubated with AP substrate for chemiluminisence ( Novex , USA ) for 5 minutes . Membranes were exposed on an X-ray film ( Santa Cruz Biotechnology , USA ) for different times to evaluate signals , which were quantified using Image J software ( NIH , USA ) . Purified antibodies against Tc DNA polymerase β/27] were crosslinked in a 1 mg/ml settled protein A-agarose using dimethyl pimelimidate ( Pierce , USA ) . After crosslinking the resin was treated with 0 . 1 M glycine-HCl ( pH 2 . 5 ) and quickly neutralized with 0 . 5 M Tris-HCl ( pH 8 . 0 ) followed by incubation in equilibration buffer ( 50 mM Tris-HCl ( pH 8 . 0 ) , 500 mM KCl , 0 . 5 M EDTA , 0 . 5 mM EGTA , 1 mM DTT , 0 . 1% v/v NP-40 and 10% v/v glycerol ) . Epimastigote cell extract ( 2 ml ) containing 4 mg of protein was incubated with 0 . 4 ml of the affinity resin at 4°C for 8 hours . Then the resin was packed into a disposable Bio-Rad column and extensively washed with equilibration buffer . A final wash was given using 8 ml of TE buffer supplemented with 0 . 5 mM DTT . Bound Tc DNA polymerase β was eluted using a buffer containing 25 mM Tris–HCl ( pH 6 . 8 ) , 3 M urea , 1% w/v SDS and 1 mM DTT . Fractions of 300 μl were collected and concentrated to 50 μl using a Speed-Vac ( Savant , USA ) . These fractions were analyzed by Western blot or used in activity gels . Differences between means in all data presented in this work were analyzed for statistical significance using Student’s t-tests in the Prism software ( GraphPad Software , USA ) . Significance was considered when p < 0 , 05 . | Exposure of Trypanosome cruzi to oxidative stress leads to damage of several macromolecules such as DNA . DNA polymerases play a very important role in DNA repair after oxidative damage . One of them is Tc DNA polymerase β . In this work , two form of this DNA polymerase were identified and overexpressed in T . cruzi cells after hydrogen peroxide treatment been one of them a phosphorylated and highly active form . The increment of Tc DNA polymerase β was not correlated with changes in mRNA levels , indicating absence of transcriptional control . We propose a mechanism where hydrogen peroxide treatment activates a pathway leading to expression and phosphorylation of Tc DNA polymerase β in response to oxidative damage . | [
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... | 2018 | Endogenous overexpression of an active phosphorylated form of DNA polymerase β under oxidative stress in Trypanosoma cruzi |
Streptococcus pyogenes , also known as Group A Streptococcus ( GAS ) , is an important human bacterial pathogen that can cause invasive infections . Once it colonizes its exclusively human host , GAS needs to surmount numerous innate immune defense mechanisms , including opsonization by complement and consequent phagocytosis . Several strains of GAS bind to human-specific complement inhibitors , C4b-binding protein ( C4BP ) and/or Factor H ( FH ) , to curtail complement C3 ( a critical opsonin ) deposition . This results in diminished activation of phagocytes and clearance of GAS that may lead to the host being unable to limit the infection . Herein we describe the course of GAS infection in three human complement inhibitor transgenic ( tg ) mouse models that examined each inhibitor ( human C4BP or FH ) alone , or the two inhibitors together ( C4BPxFH or ‘double’ tg ) . GAS infection with strains that bound C4BP and FH resulted in enhanced mortality in each of the three transgenic mouse models compared to infection in wild type mice . In addition , GAS manifested increased virulence in C4BPxFH mice: higher organism burdens and greater elevations of pro-inflammatory cytokines and they died earlier than single transgenic or wt controls . The effects of hu-C4BP and hu-FH were specific for GAS strains that bound these inhibitors because strains that did not bind the inhibitors showed reduced virulence in the ‘double’ tg mice compared to strains that did bind; mortality was also similar in wild-type and C4BPxFH mice infected by non-binding GAS . Our findings emphasize the importance of binding of complement inhibitors to GAS that results in impaired opsonization and phagocytic killing , which translates to enhanced virulence in a humanized whole animal model . This novel hu-C4BPxFH tg model may prove invaluable in studies of GAS pathogenesis and for developing vaccines and therapeutics that rely on human complement activation for efficacy .
Streptococcus pyogenes , also known as Group A Streptococcus ( GAS ) is an important human bacterial pathogen that is widespread and responsible for more than 700 million infections globally each year [1] . GAS causes a spectrum of diseases , ranging from milder pharyngitis and superficial skin infections to more severe illnesses that include acute rheumatic fever ( that may be complicated by rheumatic heart disease ) , post-streptococcal glomerulonephritis and invasive infections . The latter may be accompanied by life-threatening sepsis , streptococcal toxic shock syndrome and/or necrotizing fasciitis [2 , 3] . The burden , worldwide , of invasive GAS infection is high , with at least 663 , 000 new cases and 163 , 000 deaths each year ( 25% mortality ) . In the absence of effective vaccines against GAS , the outcome of streptococcal infection is determined by the status of the host’s immune system [4] . A key first line of defense against bacterial pathogens involves the complement system , which comprises over 30 soluble proteins and several membrane-associated complement receptors and inhibitors . Complement can be activated on ‘non-self’ cells , such as bacteria , by one or more of three different activation pathways . The classical pathway is initiated by binding of antibodies to the microbial surface , the lectin pathway is triggered by binding of one or more lectins to specific carbohydrate structures and the alternative pathway is activated by a ‘tickover’ mechanism followed by amplification through a positive feedback loop [5] . All three pathways converge at the level of C3 deposition; formation of C3 convertases generates chemoattractant anaphylatoxins and further amplifies deposition of C3 fragments on microbes , which opsonizes the microbial target for efficient phagocytosis . Formation of the lytic membrane attack complex ( MAC ) may result in direct lysis of gram-negative bacteria . Gram-positive bacteria such as GAS are resistant to MAC-mediated lysis , but are eliminated by phagocytes following opsonization with C3b and iC3b . The complement cascade is tightly regulated by surface bound and soluble inhibitors ( or regulators ) ; C4b-binding protein ( C4BP ) and Factor H ( FH ) are two examples of the latter which serve to prevent damage to host tissues . GAS has evolved several virulence factors , which allow the pathogen to colonize its human host , escape the immune system and successfully establish infection [6 , 7] . GAS infection is human-specific; in the context of its interaction with the innate immune system , GAS interacts with several human proteins , including fibrinogen , albumin and the Fc portion of IgG . Fibrinogen binding to GAS reduces opsonization , while IgG Fc binding to GAS may prevent recognition by phagocyte Fc receptors [8 , 9] . GAS surface molecules that are important for these interactions include the M protein and other members of the M protein family [10] . M protein family members share high DNA sequence identity ( >70% ) , but are encoded by different genes ( enn , mrp , fcrA , arp , protH and others; reviewed in [11] ) . Certain M or M-like proteins mediate GAS binding of human C4BP and/or human FH [12 , 13] . A particularly virulent GAS strain called AP1 binds human C4BP and FH through protein H , which is a member of M protein family [14–16] . Studies in vitro have shown that inhibition of complement activation through surface bound human FH and C4BP enables GAS to evade opsonization [17] . However , in vivo evidence implicating C4BP and Factor H in GAS infections has been lacking because a suitable animal model has not been tested . Several GAS bind only human , but not mouse C4BP and/or FH [18] . Thus , wild-type mouse models are not suitable to evaluate the roles of these human complement inhibitors in GAS infection . To circumvent these limitations in vivo [19] , we have employed novel transgenic mice that express human C4BP and FH .
Complement activation plays a key role in clearance of certain GAS by phagocytes [20] . The binding of serum complement inhibitors to bacterial surfaces regulates complement activation . Certain GAS bind human C4BP ( hu-C4BP ) and human FH ( hu-FH ) exclusively , but not the corresponding mouse complement inhibitors . Therefore , we hypothesized that mice that express these human complement inhibitors would manifest increased severity of infection with GAS compared to wild type mice . The α-chain of hu-C4BP was cloned into a pCAGS vector ( Fig 1A ) , which was then used to generate hu-C4BP transgenic animals in a BALB/c background . Using a similar approach , previously we had generated hu-FH tg mice in a BALB/c background , ( Fig 1A and [21] ) . Hu-C4BPxFH tg animals were generated by crossing hu-C4BP and hu-FH single transgenic animals . These mice also express endogenous mouse FH and C4BP . Genotyping confirmed the presence of the human genes in the respective tg animals ( Fig 1B; C4BP , upper panel and FH , lower panel ) . Western blot analysis confirmed expression of the human proteins in the corresponding strains of mice ( Fig 1C; C4BP , upper panel and FH , lower panel ) . As expected , hu-C4BP protein in tg mouse serum displayed a lower molecular mass compared to C4BP in normal human serum ( NHS ) because these mice lack the human C4BP β-chain gene . The hu-C4BP molecule lacking the β-chain ( as expressed by our tg animals ) is fully functional as a complement inhibitor ( see below; [22] ) . Human FH expressed by tg mice migrated in a manner similar to FH present in NHS on SDS-PAGE . ELISA measurements of both human inhibitors in mouse serum with antisera specific for human FH and C4BP revealed levels that were comparable to those in NHS ( Fig 1D; C4BP , upper panel and FH , lower panel ) . To ensure that activation of the mouse complement system in hu-C4BPxFH tg serum was relatively unimpaired on a complement activator surface , we compared mouse C3 deposition on zymosan particles ( zymosan is an activator of the alternative pathway of complement [23] ) using BALB/c and hu-C4BPxFH tg serum . Both sera at concentrations of 20% deposited similar amounts of mouse C3 on zymosan , indicating that the complement system in ‘double’ transgenic mouse serum was not unduly inhibited by concomitantly expressed human complement inhibitors ( Fig 1E ) . Experiments using 50% and 100% serum concentrations also did not show any differences between wt and tg sera . To exclude major defects in the major innate immune pathways in the tg animals , we compared the ability of wt and C4BPxFH tg macrophages to respond to infection by culturing peritoneal macrophages with several different TLR and cGAS stimulating ligands including LPS ( TLR4 ligand ) , Pam2CSK4 ( TLR2 ligand ) , cytosolic dsDNA ( lipofectamine + dAdT , STING ligand ) , Sendai virus ( RIG-I ligand ) , live Gram-positive ( GAS AP1 ) and Gram-negative bacteria ( Neisseria gonorrhoeae; N . G . ) . We collected supernatants after 18h and measured IL-6 secretion to assess NF-κB activation and RANTES ( an IFN-stimulated gene ) secretion to assess TRIF/STING activation . Levels of IL-6 and RANTES were similar in all tested animals ( S1 Fig ) confirming that expression of the human tg proteins did not affect innate immune signaling networks for cytokine synthesis . Taken together , expression of hu-C4BP and hu-FH in tg mice does not result in any apparent immune defects . Evading complement attack through binding of host inhibitors to prevent opsonization can be an early and crucial step in the pathogenesis of GAS ( reviewed in [6] ) . Activation of the complement system marks the pathogen for removal . Certain GAS bind hu-C4BP and hu-FH but not the mouse counterparts ( Fig 2A and 2B ) . Wild-type mouse serum complement is activated on GAS strain AP1 and results in C3 fragment ( C3b/iC3b ) deposition on the bacterial surface in a dose-dependent manner ( Fig 2C ) . GAS strain AP1 binds hu-C4BP and hu-FH to its surface via protein H , a member of the M-protein family [12 , 15] . Consistent with prior data , bacteria incubated in sera from both hu-C4BP and hu-C4BPxFH tg animals bound hu-C4BP in a dose dependent manner ( Fig 2D ) . Similarly , we detected surface bound hu-FH on bacteria incubated in hu-FH and hu-C4BPxFH tg sera ( Fig 2E ) . As expected , neither hu-C4BP nor hu-FH were detected on GAS incubated in wild type BALB/c serum ( Fig 2D and 2E; blue line ) . Consistent with the ability of hu-C4BP and hu-FH to inhibit mouse complement , bacteria incubated in hu-C4BP , hu-FH or hu-C4BPxFH tg mouse sera showed significantly reduced C3 fragment deposition compared to wt BALB/c serum at serum concentrations ≥5% ( Fig 2F ) . These results provide evidence in vitro of the importance of the binding of soluble human complement inhibitors to limit C3 deposition and opsonization . The data above demonstrates that hu-C4BP and hu-FH limit C3 deposition on GAS strain AP1 . To assess the impact of these two human complement inhibitors on phagocytosis , we infected mouse bone marrow derived macrophages in vitro with GAS strain AP1 in the presence of mouse sera with and without different human complement inhibitors . The presence of hu-C4BP or hu-FH decreased phagocytosis by more than 65% . Both inhibitors together reduced bacterial uptake by 75% compared to wild type mouse serum lacking human complement inhibitors ( Fig 3A ) . To determine whether the presence of hu-C4BP and hu-FH affected GAS opsonophagocytosis in vivo , we infected wt and hu-C4BPxFH tg mice with strain AP1 i . p . and harvested peritoneal cells 2 hours post-infection . Using flow cytometry we identified the proportion of neutrophils in peritoneal exudate cells ( S2 Fig shows the gating strategy ) . We found that in wt BALB/c animals infected with GAS strain AP1 , more than 55% of all cells obtained were neutrophils , while significantly fewer neutrophils were recruited in hu-C4BPxFH tg animals during infection ( S3A Fig ) . As a control we infected wt and hu-C4BPxFH tg mice infected with GAS mutant strain BM27 . 6 that is unable to bind either hu-C4BP or hu-FH ( Table 1 ) . Strain BM27 . 6 recruited similar amounts of neutrophils in both types of animals ( S3B Fig ) . Notably , AP1 uptake by neutrophils from BALB/c mice was significantly higher than that seen in hu-C4BPxFH tg mice ( S3C Fig ) while BM27 . 6 uptake by neutrophils was similar in BALB/c and hu-C4BPxFH tg mice ( S3D Fig ) . We calculated a phagocytic index , which multiplies the proportion of neutrophils recruited to the peritoneum times the percent of neutrophils that ingest bacteria . The phagocytic index of AP1 infected BALB/c wild type mice was 2-fold higher than the index in hu-C4BPxFH tg animals , indicating that binding of the complement inhibitors influences the uptake of AP1 ( Fig 3B ) . The phagocytic indices of the two mouse strains that were infected with BM27 . 6 were similar ( Fig 3C ) , consistent with the inability of BM27 . 6 to bind to hu-FH or hu-C4BP ( S3 Fig and [15] ) . Taken together , hu-C4BP and hu-FH expressed in mouse serum bind to strain AP1; decrease mouse C3 fragment deposition on the bacterial surface , which leads to diminished recruitment of phagocytes and reduced phagocytosis both in vitro and in vivo . We next asked whether human complement inhibitors affected the survival of mice infected with GAS . We infected single transgenic hu-C4BP , hu-FH mice and double tg hu-C4BPxFH tg mice intravenously ( i . v . ) and monitored animals for signs of disease for 8 days . Based on in vitro data and the results of in vivo phagocytosis experiments , we hypothesized that double tg mice would be more susceptible to GAS infection with human complement inhibitor binding GAS strains ( hu-FH- and hu-C4BP-binding ) than single tg and normal control mice . Indeed , we observed significant differences across single hu-tg and double-C4BPxFH tg mouse strains: C4BPxFH tg mice were the most susceptible to lethal GAS disease caused by hu-inhibitor binding strains . At a dose of 5x106 CFU/mouse ( i . v . ) , both single C4BP tg and wt animals survived for 8 days and showed no signs of disease ( Fig 4A , blue and dotted black line , respectively ) ; hu-FH tg animals were more susceptible than wt or C4BP tg mice with a median survival of 6 . 5 days and a 50% fatality rate at 8 days ( Fig 4A , brown line ) . At high-dose infection with strain AP1 GAS ( 5x107 CFU/mouse i . v . ) , ~83% of wt mice survived for 8 days compared to 20% survival of C4BP ( single ) tg mice ( Fig 4B ) . Hu-C4BP tg mice showed a median survival of only 4 days . Notably , BALB/c mice are relatively resistant to infections with GAS , necessitating high inocula to induce disease in wt [24] and single C4BP tg mice . Transgenic animals that expressed both hu-FH and hu-C4BP were the most susceptible and all mice given the lower dose ( 5x106 CFU/mouse i . v ) , died within 6 days of inoculation ( Fig 4A , red line ) . These data indicate that simultaneous inhibition of the classical and alternative pathways on the bacterial surface by hu-C4BP and hu-FH , respectively , greatly enhances GAS strain AP1 virulence and highlights the importance of regulation of complement activation by the bacteria . Because hu-C4BP and hu-FH together displayed an additive effect in down-regulating complement in mice and were the most susceptible to lethal infection , we performed all subsequent experiments using hu-C4BPxFH tg mice . We hypothesized that the increased lethality observed in the experiments above would not be unique to GAS strain AP1 ( binds hu-C4BP and hu-FH through protein H ) and tested additional GAS strains in our animal model ( listed in Table 1 ) . We also examined whether the mortality-enhancing effects of the two human complement inhibitors were restricted only to GAS strains that bound hu-C4BP and hu-FH and determined the ability of these bacterial strains to survive infection . We first infected BALB/c and hu-C4BPxFH tg animals with GAS strain BM27 . 6 , an isogenic mutant of AP1 , lacking both M protein and protein H , or with the wild-type strain AP3 strain ( Table 1 ) . Neither BM27 . 6 nor AP3 bind hu-C4BP or hu-FH ( S4 Fig ) . All 10 BALB/c and 9 out of 10 hu-C4BPxFH tg mice infected with 5x107 CFU BM27 . 6 survived ( Fig 4C ) . Infections with either 1x107 or 5x108 CFU BM27 . 6 also revealed no difference in mortality between 10 BALB/c and 10 hu-C4BPxFH tg mice ( S5A and S5B Fig ) . Although infections with GAS AP3 at an inoculum of 5x107 CFU/animal produced disease in both wt and hu-C4BPxFH tg mice , differences in survival across groups was not significant ( 67% mortality at day 8 in BALB/c and 100% in hu-C4BPxFH tg; Fig 4D ) . Lower ( 2x107 ) and higher ( 1x108 ) inocula of AP3 also showed similar mortality in both groups ( S5C and S5D Fig ) . By contrast , GAS AP18 , which like AP1 , binds both hu-C4BP and hu-FH , showed significantly increased virulence in hu-C4BPxFH tg compared to wt mice; like AP1 , all AP18-infected animals had died by 6 days , while all wt BALB/c control mice survived ( Fig 4E ) and did not show signs of morbidity . Using 4 strains of GAS ( 2 that bind C4BP and FH and 2 that do not ) , these results indicate that GAS strains that bind these complement inhibitors show significantly increased virulence in mice that express human transgenes for both of the inhibitors , singly or in combination . We next quantified the bacterial burden in the blood , kidneys , liver and spleen of hu-C4BPxFH and BALB/c mice infected with AP1 GAS . Mice were sacrificed either at 2h or 24h post-infection and organs were homogenized and plated to enumerate bacterial CFUs . As early as 2h , we noted significantly higher bacterial loads ( up to 1 . 5 log10 higher ) in blood , kidney and spleen of hu-C4BPxFH ( ‘double’ ) tg mice compared to wt BALB/c animals; liver samples from both strains showed similar bacterial loads ( CFUs ) ( Fig 5A ) . At 24h post-infection , the liver , spleen and kidneys of hu-C4BPxFH tg mice showed significantly greater bacterial loads compared to loads in BALB/c mice ( Fig 5B ) . In contrast to bacterial loads in the organs , bacterial loads from wt BALB/c blood were similar to levels in the blood of hu-C4BPxFH mice ( Fig 5B ) . The greater bacterial burden in hu-C4BPxFH mice early in the course of infection points to altered innate immune defenses , which may have been the result of decreased opsonophagocytotic potential of GAS in tg animals ( Fig 3 and S3 Fig ) . Taken together , GAS avoids early phagocytic clearance and establishes a more severe invasive infection in the transgenic animals . Sepsis typically is associated with highly elevated levels of serum cytokines that lead to the systemic inflammatory response syndrome ( SIRS ) or cytokine storm , which often precedes multi-organ failure and eventually death [30] . We analyzed serum cytokines during the course of infection . Based on initial screening for 23 different serum cytokines in infected BALB/c and C4BP tg animals , we selected the following 11 cytokines for further analysis: IL-1β , IL-6 , IL-13 , G-CSF , IFN-γ , KC , MCP-1 , MIP-1α , MIP-1β , RANTES and TNF-α . Using a multiplex analysis for these 11 cytokines , we analyzed serum samples from C4BPxFH tg and BALB/c wt mice 24h prior to , as well as 2h and 24h post infection . At 2h after infection we identified significantly increased serum levels of MIP-1β , MCP-1 , TNF-α and MIP-1α in hu-C4BPxFH compared to wt mice ( Fig 6A–6D ) . After 24h we observed a shift in the cytokine pattern with MIP-1β , MCP-1 , TNF-α , KC and MIP-1α becoming strongly down regulated . In addition to KC and RANTES , which remained significantly higher in transgenic mice both at 2h and 24h post-infection ( Fig 6E and 6F ) , MIP-1β , MCP-1 , TNF-α , MIP-1α and KC peaked at 2h post-infection; levels of MIP-1β , MCP-1 , TNF-α , MIP-1α and KC were also significantly increased in hu-C4BPxFH tg compared to wt mice ( Fig 6A–6E ) at 2h post-infection . G-CSF , IFN-γ and IL-6 , exhibited similar levels in BALB/c and C4BPxFH tg mice at 2h but were elevated significantly at 24h in hu-C4BPxFH tg compared to wt BALB/c mice ( Fig 6G , 6H and 6I ) .
GAS can bind both hu-C4BP and hu-FH like other pathogens , including Neisseria meningitidis and Neisseria gonorrhoeae [31 , 32] , Moraxella catarrhalis [33] , Candida albicans [34] and Haemophilus influenzae [35 , 36] . Based on studies in vitro that have shown down-regulation of C3 fragment deposition mediated by binding of FH and/or C4BP [17 , 37 , 38] , it has been presumed that GAS may exploit these soluble inhibitors to escape complement attack in vivo , although direct evidence has been lacking . Here we present evidence that bacteria-bound complement inhibitors increase virulence and accelerate fatal infections in vivo . We have employed a novel mouse model that expresses hu-C4BP and/or hu-FH and have infected these animals with several GAS strains that differ in their ability to bind to these complement inhibitors . Our data provide evidence to support a general mechanism whereby recruitment of C4BP and FH to the GAS surface protects bacteria from clearance by phagocytes in vivo and contributes to increased morbidity and mortality in the infected experimental host . Mice are not natural hosts for GAS infection , but can be experimentally infected with relatively high bacterial inocula [39] . We hypothesized that a GAS strain such as AP1 , which binds human complement inhibitors via surface protein H , an M-like protein [14 , 15] , would show enhanced virulence in mice that expressed hu-C4BP and hu-FH . Indeed , the ‘double’ tg animals sustained higher bacterial burdens , displayed symptoms of bacterial sepsis and died more quickly than wt animals . Of note , the inoculum required to induce a lethal infection in the ‘double’ tg mice was reduced by more than 1 log10 compared to the inoculum required to kill wild-type animals . A second GAS strain ( AP18 ) with similar hu-C4BP and hu-FH binding capacity as AP1 yielded similar survival results as AP1 . In this case AP18 bind hu-C4BP and hu-FH directly via surface M protein [27 , 29] . As a result , hu-C4BP and hu-FH binding GAS strains produced significantly more disease in hu-C4BPxFH tg animals than in wt mice . As ‘negative’ controls , we used GAS strains that were unable to bind hu-C4BP and hu-FH . We showed reduced mortality even at high inocula in the ‘double’ tg mice when compared to hu-C4BP and hu-FH-binding GAS strains in this model . Furthermore , we did not detect any differences in survival between wild type and hu-C4BPxFH tg animals that were challenged with strains unable to bind to these inhibitors ( strain AP3 and the isogenic mutant derived from AP1 , BM27 . 6 ) . Taken together , these data strongly suggest that complement inhibitors exacerbate disease by binding GAS , but do not influence the course of GAS infection if the bacteria cannot recruit C4BP or FH to their surface . Increased mortality of the double tg mice that were challenged with hu-C4BP/hu-FH-binding strains , AP1 and AP18 , was not attributed to generalized defects in the immune systems caused by introduction of the human complement inhibitor transgenes for the following reasons . First , analysis of innate immune ligand-dependent cytokine release from peritoneal exudate cells ( PECs ) did not demonstrate differences between tg and wild type mice . Second , complement deposition on zymosan that resulted from incubation of zymosan with tg or wt mouse sera did not demonstrate differences between the sera . These findings suggest that our mouse model does not suffer from an apparent immune defect . Second , and as discussed above , the double tg mice did not suffer increased mortality compared to wt mice when challenged with strains that did not bind to hu-C4BP and hu-FH . We postulate that exacerbation of infection in tg mice infected with GAS strains that bound complement inhibitors , resulted in impaired opsonization with mouse C3 fragments . We have shown previously that purified hu-C4BP injected in wt mice decreases complement activation via the classical pathway [22] , which confirms that hu-C4BP regulates mouse complement . The β-chain of C4BP is not required for binding to GAS [26] and is not required for complement inhibition [40]; therefore the hu-C4BP molecule that lacks the β-chain—the form expressed by our tg animals , was fully functional as a complement inhibitor on the surface of GAS . [41] . Similarly , hu-FH bound to bacteria also inhibits non-human complement via the alternative pathway[42 , 43] . Most pathogens activate complement via a combination of classical , lectin and alternative pathways ( reviewed in [44] ) . Upon using hu-C4BPxFH double tg mice , we observed an additive effect of the two complement inhibitors , compared to using either hu-C4BP or hu-FH transgenic mice singly . Infection of singly transfected mice resulted in increased mortality in the respective mice but time to death was accelerated in the double tg mice . Opsonization with C3 fragments is required for efficient uptake by phagocytes ( reviewed in [20] ) . Thus , inhibiting complement activation impairs opsonization , results in diminished phagocytic uptake and decreases killing of pathogens . We showed that GAS strain AP1 recruited hu-C4BP and hu-FH to its surface , which reduced C3b/iC3b deposition on the bacterial surface and resulted in decreased phagocytosis of GAS both in vitro and in vivo . We saw diminished recruitment of neutrophils by GAS inoculated into the peritoneal cavity of ‘double’ tg mice and decreased uptake of bacteria by neutrophils that had been recruited . Diminished production of C3b results in decreased generation of both C5 convertase and C5a , a potent chemoattractant for neutrophils [45] . Impaired clearance of hu-C4BP and hu-FH-binding GAS was also reflected by greater CFU recovered from blood and other organs . Several of the cytokine levels that we measured were elevated in tg compared to wt mice , consistent with greater loads of organisms in tg mice [46] . Cytokines generated early , may be important in controlling bacterial dissemination but excessive and persistent production may be detrimental [47] . High levels of G-CSF in particular , generated within the first 24h have been reported to confer protection in mice infected with GAS [48] but in children , higher levels of pro-inflammatory cytokines generally , correlate with higher mortality from invasive GAS infections [49] . Infection of hu-C4BPxFH tg animals with strain AP1 resulted in elevation of most cytokine levels early at 2 hours , compared to wt animals; G-CSF levels at two hours were not different in C4BPxFH tg vs . wt mice but increased markedly in double tg animals at 24h . Cytokine levels , morbidity and fewer days to death , accompanied by increased bacterial burdens , were more pronounced in hu-C4BPxFH tg compared to wt mice . We hypothesize that failure to opsonize GAS and consequent reduced phagocytosis results in uncontrolled replication of GAS , which kills the host . A number of bacterial virulence factors are released , which lead to systemic toxicity , coagulopathy , hypotension , septicemia , tissue damage and finally multi organ failure [11 , 50 , 51] . Our data differ from a previously published study that did not demonstrate accelerated mortality during acute GAS infection in C57BL/6 , mouse-FH KO , transgenic ( tg ) mice that expressed only chimeric human/mouse FH ( SCRs 6–8 were derived from human FH ) [28] . Mortality was not affected despite evidence of binding of hu-SCR 6–8 to the M protein ( M5 ) of the infecting strain [28] . This study used a C57BL/6 tg mouse model whose levels ( 200–210 μg/ml ) of chimeric FH had been reported earlier [52] to be similar to FH levels in wt C57BL/6 mice . These FH levels were lower than those in our tg mice; 379 . 9 μg/ml in FH tg mice and 291 . 5 μg /ml in ‘double’ tg C4BPxFH . These levels were similar to levels reported in human ( 320 ± 71 . 4 μg/ml in plasma taken from 358 individuals [53] ) . The higher levels may have been important to display the completely virulent phenotype in mice . Furthermore , chimeric FH , expressing hu-SCRs 6–8 [28] , may also have undergone unique conformational changes , distinct from those that occur with native hu-FH [54] , which may be important in maintaining physiologic function . Differences in mouse strains ( C57BL/6 mice were used in the chimeric FH study [28]; we used BALB/c mice ) , bacterial strains and routes of inoculation all could have contributed to differences in our results compared to those of the previous study [28] . In conclusion , we have demonstrated a detrimental influence of human complement inhibitors FH and C4BP in overcoming experimental GAS sepsis in vivo . Our data suggest a pivotal role for complement inhibitors on GAS strains that bind these inhibitors to their surface . Our novel hu-C4BPxFH tg animal infection model may prove invaluable in studies of GAS pathogenesis and in the development of vaccines and therapeutics that incorporate a ‘human’ context .
The following antibodies were used for ELISA measurements: 10 μg/ml rabbit anti hu-C4BP PK9008 , ( homemade , capture Ab ) ; 0 . 5 μg/ml mouse anti hu-C4BP MK104 , ( homemade , detection Ab ) ; 10 μg/ml mouse anti hu-fH MRC OX24 , ( homemade [55] , capture Ab ) ; 5 μg/ml sheep anti human-Factor H ( Abcam , ab8842; detection Ab ) . C4BP and FH detection antibodies were secondarily detected using anti sheep IgG-HRP or anti mouse IgG-HRP ( DAKO , P0163 and P0260 ) . For flow cytometry analysis , the following antibodies were used: mouse anti human-C4BP MK104 either unconjugated or conjugated to biotin; mouse anti human-Factor H MRC OX24 unconjugated or conjugated to biotin; rabbit anti mouse-C4BP ( homemade ) conjugated to Dylight 647; mouse monoclonal anti mouse-Factor H ( Hycult , HM1119 ) conjugated to biotin; goat anti mouse-C3c ( Nordic Immunology , GAM/C3c/7S ) ; anti mouse C3 FITC ( MP Biomedicals #0855500 ) anti mouse Ly-6G brilliant violet 421 ( BioLegend , #127627 ) ; anti mouse Ly-6C PerCP/Cy5 . 5 ( BioLegend , #128011 ) ; anti mouse CD11c ( BioLegend , #117317 ) ; anti mouse I-A/I-E brilliant violet 510 ( BioLegend , #107635 ) ; anti mouse CD64 APC ( BioLegend , #139305 ) ; anti mouse/human CD11b APC/Cy7 ( BioLegend , #101225 ) . Unlabeled primary antibodies used for detection of the nominal targets in FACS were themselves bound and detected using donkey F ( ab’ ) 2-anti mouse IgG-PE ( Thermo , #31860 ) or donkey F ( ab’ ) 2-anti goat-IgG-PE ( eBioscience , #12-4012-87 ) . Final reactions that measured biotin labeled antibody binding were disclosed with streptavidin-Dylight 650 ( Pierce , #84547 ) or streptavidin-PE ( eBioscience , #12-4317-87 ) . For western blot analysis of human C4BP in mouse serum we used mouse anti hu-C4BP MK104 coupled to biotin detected by Dylight 649 Streptavidin ( BioLegend , 405224 ) . Hu-FH in mouse serum was detected using goat anti human FH ( Calbiochem , #341276 ) and Alexa Fluor 647 donkey anti goat IgG ( Life Technologies , A21447 ) . Western blots were read using Typhoon FLA 9500 ( GE Healthcare ) . Streptococcus pyogenes AP1 ( strain 40/58 , serotype M1 ) , AP3 ( strain 4/55 , serotype M3 ) and AP18 ( strain 8/69 , serotype M18 ) were obtained from the WHO Collaborating Centre for Reference and Research on Streptococci , Prague , Czech Republic . BM27 . 6 is an isogenic mutant of AP1 lacking protein H [56] . Binding of human soluble complement inhibitors , C4BP and FH , to each strain is summarized in Table 1 . Streptococcal strains were grown in Todd-Hewitt broth ( THB ) and Moraxella catarrhalis RH4 ( control strain ) in brain-heart infusion ( BHI ) broth overnight at 37°C and 5% CO2 without shaking . Cultures were then diluted to OD600 = 0 . 1 in corresponding fresh medium and incubated again at 37°C and 5% CO2 without shaking , until exponential growth at OD600 = 0 . 3–0 . 4 was achieved . Bacteria were harvested and washed with 1× PBS prior to use . Genomic DNA from GAS AP1 , AP3 and AP18 strains was isolated using a DNeasy blood and tissue kit ( Qiagen ) according to manufacturers instructions . The covRS operon was amplified ( for primers used see S1 Table ) by PCR and subsequently subjected to Sanger sequencing . All animals were housed and bred under SPF conditions in the animal facility at the University of Massachusetts Medical School Worcester ( UMMS ) , USA . Production of hu-FH transgenic mice has been described previously [21] . To generate human C4BP transgenic mice , full-length cDNA encoding human C4BP ( 1 . 8 kbp ) was subcloned into the EcoRI site of the expression vector pCAGGS [57] . A CMV enhancer and chicken β-actin promoter sequences are located upstream of the EcoRI site in pCAGGS and a rabbit β-globin polyA sequence is located downstream of the EcoRI site . The resultant plasmid , pCAGGS-human C4BP , was digested with SalI and HindIII to isolate the transgenic cassette fragment that consisted of the CMV enhancer , the chicken β-actin promotor , the human C4BP cDNA and the rabbit β-globin poly ( A ) sequence . The isolated 4 kb SalI and HindIII fragment was purified and microinjected into mouse embryos from BALB/c mice . Mouse embryos were implanted into pseudo-pregnant female BALB/c mice ( Charles River Breeding Laboratories ) at the UMMS Transgenic Facility . Human C4BP transgenic mice initially were identified by PCR analysis using genomic DNA prepared from mouse-tails . A region inside human C4BP was amplified by PCR using primers C4BP-EcoRI and C4BP-NotI to yield a 383-bp product ( Fig 1B; for primer sequence see S1 Table ) . Amplified products were resolved by electrophoresis on 2% TAE agarose gels and visualized with ethidium bromide staining under UV light . Expression of human C4BP in sera of pups was detected by Western blotting using affinity purified rabbit anti-human C4BP . FH and C4BP transgenic mice were bred together to create double transgenic mice . To assess serum levels of hu-C4BP and hu-FH sandwich ELISAs ( see antibodies ) were performed . Animals were anesthetized with Isoflurane and blood was drawn by cardiac heart puncture . Blood samples were kept on ice for 30 min and allowed to clot before centrifuging for 10min at 1700 x g , 4°C . Serum was separated , aliquoted and directly frozen at -80°C until use . Bone marrow was extracted from femurs and tibias of 3 euthanized mice and plated onto DMEM/high glucose supplemented with 10% FCS , 5% horse serum and 2500U/ml M-CSF . Bone marrow was incubated for 7 days at 37°C , 5% CO2 to allow differentiation into bone marrow derived macrophages ( BMDM ) . Cells were washed 3x with ice cold PBS , pooled and frozen in DMEM/high glucose supplemented with 10% FCS , 5% horse serum , 2500U/ml M-CSF and 10%DMSO until further use . Flow cytometry analysis showed a uniform population of CD11bhigh , F4/80high MHClow cells , indicating macrophages . Harvested bacteria were incubated with increasing amounts of either normal human serum or mouse serum for 1 h at 37°C , 5% CO2 . Bacteria were washed three times with 1× PBS before and after each staining step . Bacteria were stained as indicated for either human or mouse C4BP , FH and C3b . Unconjugated primary antibodies were detected either with secondary antibodies or streptavidin coupled to PE or Dylight 649 ( Pierce ) . The amount of surface bound complement was measured using a Cyflow space flow cytometer ( Partec ) . Complement deposition on zymosan particles was performed as described previously [58] . Briefly , zymosan was incubated in either wt or hu-C4BPxFH tg mouse sera ( final serum concentration 20% ) for 30 min at 37°C . Controls included zymosan incubated with wt mouse serum containing 10 mM EDTA to block activation of all pathways of complement . After washing , particles were stained for deposited C3 and analyzed using an LSRII flow cytometer ( BD ) . Statistical analysis was performed using GraphPad Prism 5 . 0f software . Samples were tested for normal distribution using a D’Agostino and Pearson omnibus normality test . According to the result , samples were then analyzed either using a parametric or non- parametric test as indicated in corresponding figure legends . The Institutional Animal Care and Use Committee in Worcester , MA , USA , approved all animal experiments . Human serum was prepared from venous blood of healthy volunteers according to the recommendations of the local ethical Committee in Lund , Sweden . Written informed consent was obtained; all investigations were conducted according to the principles of the Declaration of Helsinki . | Streptococcus pyogenes is an important cause of human infections worldwide , ranging from mild and superficial disease to life-threatening invasive infections . Development of new and efficient therapies for infections requires animal models that faithfully recapitulate infection in humans . Humans are the only natural host of S . pyogenes; thus , infection in wild-type mice may not reflect infection in humans . Mice that are humanized in ways that are relevant to the studied pathogen would better reproduce human infection . Because S . pyogenes bind only human , but not mouse complement inhibitors , we used novel strains of humanized mice that produce two human complement inhibitory proteins which allowed us to analyze the impact of human-specific human complement inhibition on the severity of S . pyogenes infections in mice . Here , we show that expression of human complement inhibitors significantly worsens the outcome of infection in humanized mice . This animal model will permit studies of infection and disease and aid the development of novel therapies and vaccines against S . pyogenes infections , with emphasis on the human complement system . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | Virulence of Group A Streptococci Is Enhanced by Human Complement Inhibitors |
When incorporated into a polypeptide chain , proline ( Pro ) differs from all other naturally occurring amino acid residues in two important respects . The φ dihedral angle of Pro is constrained to values close to −65° and Pro lacks an amide hydrogen . Consequently , mutations which result in introduction of Pro can significantly affect protein stability . In the present work , we describe a procedure to accurately predict the effect of Pro introduction on protein thermodynamic stability . Seventy-seven of the 97 non-Pro amino acid residues in the model protein , CcdB , were individually mutated to Pro , and the in vivo activity of each mutant was characterized . A decision tree to classify the mutation as perturbing or nonperturbing was created by correlating stereochemical properties of mutants to activity data . The stereochemical properties including main chain dihedral angle φ and main chain amide H-bonds ( hydrogen bonds ) were determined from 3D models of the mutant proteins built using MODELLER . We assessed the performance of the decision tree on a large dataset of 163 single-site Pro mutations of T4 lysozyme , 74 nsSNPs , and 52 other Pro substitutions from the literature . The overall accuracy of this algorithm was found to be 81% in the case of CcdB , 77% in the case of lysozyme , 76% in the case of nsSNPs , and 71% in the case of other Pro substitution data . The accuracy of Pro scanning mutagenesis for secondary structure assignment was also assessed and found to be at best 69% . Our prediction procedure will be useful in annotating uncharacterized nsSNPs of disease-associated proteins and for protein engineering and design .
Proline ( Pro ) is unique among the 20 naturally occurring amino acid residues . On the one hand , because Pro lacks an amide proton the main chain amide N is incapable of forming H-bonds ( hydrogen bonds ) . Hence , substituting a residue involved in a main chain H-bond with Pro could destabilize the protein . This property has previously been exploited to obtain information about residues involved in secondary structure [1–3] . On the other hand , the rigid pyrrolidine ring constrains the main chain dihedral angle φ to a narrow range of values close to −65° . It has also been observed [4–6] that Pro restricts the conformation of the residue preceding it in a protein sequence . The Ramachandran map of the pre-proline residue has a large excluded area between −40° < ψ < 50° . This restricts the conformation of the αL and α regions . There is also a small leg of density in the β region that is unique to pre-proline residues . Hence , Pro can potentially increase protein stability because it decreases the conformational entropy of the denatured state . In addition , Pro is usually conserved in proteins and often plays an important role in protein structure and function [5 , 7 , 8] . Previous studies on Pro mutants of different proteins have shown that the thermodynamic effects of introducing Pro depend on various factors including residue position ( accessibility and secondary structure ) , φ value of the original residue , H-bonding of the amide group of the original residue , and electrostatic or hydrophobic interactions of the original residue [1 , 5 , 9–12] . However , it is not yet clear whether the introduction of Pro at a given position in a protein will have a perturbing ( destabilizing ) or nonperturbing effect on the thermodynamic stability of the protein . The aim of the present work is to generate an algorithm based on Pro scanning mutagenesis data which can be used to predict the perturbing/nonperturbing effect of Pro substitution at a given position for any globular protein . We also examine the utility of Pro scanning mutagenesis to infer protein secondary structure . The experimental system used in this study , controller of cell division or death B protein ( CcdB ) , is a 101 residue , homodimeric protein encoded by F plasmid . The protein does not contain any disulfides or metal ions . The protein is an inhibitor of DNA gyrase and is a potent cytotoxin in Escherichia coli ( E . coli ) . Transformation of normal E . coli cells with plasmid expressing the wild-type ( WT ) CcdB gene results in cell death . If the protein is inactivated through mutation , cells transformed with the mutant genes will survive . In this work we attempted to replace each of 101 amino acids of homodimeric CcdB with Pro using high throughput mega-primer based site-directed mutagenesis . A total of 77 mutants could be generated . Mutant phenotype was assayed as a function of expression level by monitoring the presence or absence of cell growth as a function of inducer ( arabinose ) concentration . Based on an analysis of CcdB Pro scanning mutagenesis , phenotypic data , and its correlation with various structural parameters , a decision tree was created to classify Pro substitutions of a protein into perturbing ( those which destabilize the protein ) and nonperturbing ( nondestabilizing ) mutations . The decision tree was further validated on a large phenotypic dataset of 163 Pro mutants of T4 lysozyme at two different temperatures ( 37 °C and 25 °C ) , a nonsynonymous single nucleotide polymorphism ( nsSNP ) database of Pro substitutions which are associated with various diseases and on Pro substitutions extracted from the ProTherm database and literature .
A total of 77 single site Pro mutants were generated out of the possible 97 ( four of the 101 WT residues are Pro ) positions of CcdB . Individual phenotypes for each mutant are shown in Figure 1 and Table S1 . The phenotype of the Pro mutants was observed to be sensitive to expression level . At the lowest level of expression ( 0% arabinose ) , 45% of the mutants showed an active phenotype , while at the highest level of expression ( 0 . 1% arabinose ) , it increased to 74% . However , 50% and 80% of the mutants showed an active phenotype at the lowest and highest expression levels , respectively , if active site mutants were not considered . Table 1 summarizes the mutant phenotypes at low ( 0% arabinose ) and high levels of expression ( 0 . 1% arabinose ) along with their solubilities , examined as a function of ACC ( percentage side chain solvent accessible surface area of a residue ) . We have previously shown that Ala and Asp scanning mutagenesis of CcdB can be used to identify active site residues [13] . At such sites , either the corresponding Ala and Asp mutants are inactive at both low and high inducer concentrations ( residues 24 , 98 , 99 , 100 , and 101 ) or Ala is active but corresponding Asp is inactive and expression/solubility is unaffected ( residues 25 , 95 ) . Analysis of the CcdB:DNA gyrase crystal structure [14] shows that residues 24 , 25 , 26 , 87 , 88 , 91 , 92 , 95 , 99 , 100 , and 101 are within 4 Å of DNA gyrase using the Structure Analysis module of CCP4 [15] . Thus , scanning mutagenesis data identifies a subset of these residues as being crucial for the CcdB:Gyrase interaction . Mutants belonging to this subset ( residues 24 , 25 , 95 , 98 , 99 , 100 , and 101 ) were not considered for further analysis as Pro mutations at such active site residues can result in loss in activity without affecting stability . Sixteen residues at positions 2 , 20 , 21 , 22 , 25 , 27 , 32 , 66 , 68 , 69 , 94 , 95 , 97 , 98 , 99 , and 100 are at the dimeric interface . Pro mutations at 12 of these 16 positions were inactive . These residues were not excluded from the analysis , as mutating dimerization interface residues can affect the stability of a protein and there is no good justification for treating dimerization interface residues differently from other buried residues . Of the ten mutants at buried positions but not at dimerization interface , all were inactive . Solubility data of Pro mutants ( Table 1 and Figure 2D ) was found to correlate with activity [13] . Seventy-seven percent ( 27 out of 35 ) of nonactive site mutants that showed an inactive phenotype at 0% arabinose were insoluble . Not surprisingly , the lowest fraction of active mutants were those with ACC < 5% and the highest fraction was for residues with ACC > 40% ( Table 1 ) . Pro mutants were divided into two classes , active ( A ) and inactive ( I ) , depending on their phenotype at low and high expression levels . The correlations of Pro mutant activity with secondary structure and with involvement of the main chain amide of the WT residue in an H-bond were analyzed . Pro substitutions which show an active phenotype at both low and high expression levels are designated as nonperturbing ( Class 1 , Table 2 ) . Those which show an inactive phenotype at low expression levels and either an active or an inactive phenotype at high expression levels are designated as perturbing ( Class 2 , Table 2 ) . CcdB is a moderately stable protein ( Tm = 61 °C , ΔGu° ( 298K ) = 21 kcal/mol ( 1 cal ≈ 4 . 184 J ) of dimer ) [16] . It is assumed that the loss of activity upon mutating nonactive site residues implies that the mutant protein is thermodynamically less stable than the WT . This is supported by the observation that a large fraction of these mutants go into inclusion bodies when overexpressed . For stereochemical reasons , it is generally thought that Pro mutations are poorly tolerated in regions of secondary structure [5] . However , previous studies have demonstrated that Pro can be found at edge strands in non–H-bonded sites of antiparallel β sheets [17] , and , indeed , aromatic-Pro interactions occur in sheets [18 , 19] . In addition , although Pro does not have the amide NH group , CH-O interactions can substitute for the normal H-bond to accommodate a Pro in the interior of the helix [20] . In case of CcdB , 12 of the 35 ( 34% ) Pro mutations in regions of helix or β strand ( as defined in the crystal structure—PDB [21] code 3vub [22] ) —are nonperturbing . Residues at the first three positions of helices typically do not have their amide protons involved in H-bonds . Even if these positions are ignored , nine of 32 Pro mutations in strands and helices are nonperturbing . Of these , two are the N-terminal residues and three are the C-terminal residues of strands . Pro mutations can therefore be nonperturbing even in regions of secondary structure . This is probably because Pro residues can be accommodated close to the ends of secondary structural regions where adjacent turns/loops can rearrange without high energetic cost . For example , Pro mutations at residues 8 , 16 , 38 , 76 , 82 ( at either the ends or beginning of β strands ) and residues 87 , 88 , 89 ( at the N-terminus of an α helix ) are all nonperturbing . Several H-bonded residues not in regions of secondary structure , e . g . , residues 2 , 3 , 20 , 21 , 22 , 25 , 50 , 51 , 64 , and 67 are intolerant to Pro substitution . Phenotypes of Pro mutants have previously been used to infer information about residues involved in secondary structure in proteins where no homology model or other structural information is available [1–3] . The present studies show that Pro scanning mutagenesis alone cannot be reliably used to obtain secondary structural information ( Table 2 and Table S1 ) . The accuracy of secondary structure assignment from Pro scanning mutagenesis was calculated in two different ways . In the first approach , it was assumed that at each of the 70 nonactive site residues , wherever substitution by Pro leads to loss of activity , the WT residue is in a region of secondary structure ( helix or strand ) . Conversely , where Pro substitution is nonperturbing , the WT residue is in a region lacking secondary structure . The accuracy using this approach was 63% ( Table S1 ) . If secondary structure is assigned to regions by considering the average mutant phenotype in a three-residue window , the assignment accuracy is 69% . For example , if in a stretch of three nonactive site residues , two or more of the Pro substitutions are inactive , the middle residue is assigned to be in a region of secondary structure , else it is assumed to be in a region lacking secondary structure . These figures are lower than values of 75%–78% obtained from existing sequence-based computational methods of secondary structure predictions [23] , although it should be noted that PSIPRED [24] , a widely used secondary-structure prediction program only yielded a prediction accuracy of 42% when applied to CcdB . The figure of 69% described above masks the fact that the bounds of all secondary-structure elements are incorrectly assigned and one strand is missed out entirely . The accuracy of secondary-structure assignment is far lower than 69% if the accuracy measure were to combine measures of number of correctly predicted segments with correctness of predicted segments . It was recently shown [25] that Ala scanning combined with Pro scanning mutagenesis gives useful information about backbone conformation in amyloid fibrils . The Ala mutants were shown to be useful to identify cases where Pro mutations destabilized the fibril because of changes in side chain hydrophobicity rather than changes in the main chain backbone configuration . However , we find that for CcdB , Ala scanning mutagenesis results did not correlate with hydrophobicity changes as most Ala mutants at nonactive site positions showed an active phenotype [13] . If the WT residue amide proton is involved in H-bonding , then substitution with Pro should lead to appreciable destabilization of the protein [26] . This is indeed the case ( last column of Table 2 ) . The data in Table 2 suggest that Pro scanning mutagenesis can provide information about a ) a subset of residues that are not in regions of secondary structure or are at the ends of secondary structural elements , b ) a subset of residues whose main chain amide protons form H-bonds . This information is useful in the absence of the 3D structure of a protein and can be used to discriminate between various model structures . However , Pro scanning mutagenesis has limitations when applied to precisely define regions of secondary structure as discussed above . Assuming no main chain rearrangement , the number of short contacts formed by introduction of Pro at different sites in CcdB and the nonbonded energy due to these short contacts were calculated using XTOPROMAKE ( as described in Materials and Methods ) and examined for their correlation with Pro mutant activity data . Only at six positions ( residues 10 , 11 , 43 , 44 , 53 , and 55 ) was it possible to introduce Pro with small or negligible steric hindrance . Of these six positions , Pro mutants were experimentally available at four positions ( residues 10 , 11 , 43 , and 55 ) . At all four positions , mutants were soluble and showed a WT-like phenotype . All other residues showed unfavorable nonbonded energy upon Pro substitution , and at 23 sites the Pro coordinates could not be geometrically fixed . These results were not consistent with experimental data as Pro was tolerated at 45% and 74% of residues in CcdB at the lowest and highest expression levels , respectively . We purified two of the mutants 10P and 43P , which were predicted to have a small number of short contacts , for further thermodynamic characterization . We also purified 101P . Residue 101 is adjacent to a Gly residue at position 100 . The presence of a flexible Gly residue preceding Pro should permit the necessary main chain rearrangements required to accommodate Pro . Both 10P and 43P showed an active phenotype at 0% arabinose . 101P showed an inactive phenotype at both 0% and 0 . 1% arabinose , because it is a known active site residue [27] . The corresponding Ala mutant is also inactive [13] . Equilibrium unfolding studies using GdnCl were carried out for WT and these three mutants , and data was analyzed using a global fit with a common m value ( Figure S1 ) . Unfolding parameters ΔGu° ( free energy change upon protein unfolding at zero denaturant concentration ) and Cm ( denaturant concentration at which fraction of unfolded protein is 0 . 5 ) obtained from these denaturation studies are listed in the Figure S1 caption . 10P and 43P showed a 9% decrease in ΔGu° while 101P had identical stability to WT . The above results demonstrate that while the XTOPROMAKE program correctly identifies a few nonperturbing sites , it fails to identify the majority of such sites . Hence , mutant models were generated by a procedure that minimizes the overall energy of the protein by rearranging a backbone and side chain using the program MODELLER . Attempts were made to correlate the activity data with various structural parameters related to the WT protein and/or the Pro mutant models . Figures 2 and S2 show some correlations between the activity of the Pro mutant at each residue position and various structural parameters calculated from either WT native ( crystal structure 3vub ) or mutant model structures . Five models of each mutant were constructed and the average value of each of the structural parameters was calculated . Pro mutants of the seven active site residues ( see earlier secondary structure section ) were not considered in this study . Correlation of activity of Pro mutants with the following structural parameters were examined ( Figure 2 ) : a ) WT residue ACC , b ) depth , c ) |φ ( WT ) − ( −65° ) | , d ) solubility , and e ) whether WT main chain amide is H-bonded to another protein atom and if WT amide is H-bonded , whether the corresponding acceptor is H-bonded in a mutant model . The statistical significance of correlation for parameters a ) –c ) was assessed by a nonparametric two-tailed Mann-Whitney test and for parameters d ) and e ) by Fisher's test using the software GraphPad Prism . p-Values in all cases were <0 . 05 , showing that the activity data and the structural parameters are significantly correlated . While most of the nonperturbing mutants were at residues with higher ACC and lower depth than perturbing mutants ( Figure 2A and 2B ) , it was not possible to apply an ACC cutoff to distinguish between perturbing and nonperturbing mutants . However , for most of the nonperturbing mutants , the φ value of the WT residue was close to the PDB average Pro φ value of ( −65° ± 15° ) , and in several of the perturbing mutants |φ ( WT ) − ( −65° ) | was >15° . Most perturbing mutants were insoluble ( Figure 2D ) . There was also a significant correlation observed between activity and H-bonding of the amide proton of the WT residue . Twenty-six out of 35 nonperturbing mutants did not have the main chain amide involved in H-bonding , and 26 of 30 residues where the WT main chain amide is not H-bonded ( class 1 , Figure 2E ) were active . For 28 out of 35 perturbing mutants , the main chain amide of the WT residue was H-bonded to another protein atom , and 31 of 40 residues where the WT main chain amide is H-bonded were inactive ( Figure 2E ) . Additional parameters examined are shown in Figure S2 as follows: a–c ) mutant Pro contact area ACC ( total , main chain only , side chain only , respectively ) , d ) MODELLER objective function value , e ) average φ of mutant Pro , f ) Average ψ of mutant Pro , g ) |φ ( WT ) − φ ( mut ) | , h ) |ψ ( WT ) − ψ ( mut ) | , i ) RMSD ( φ ( WT ) − φ ( mut ) ) , j ) RMSD ( ψ ( WT ) − ψ ( mut ) ) for an 11-residue window centered at the position of mutation , and k ) number of neighboring residues . The two-tailed Mann-Whitney test yielded p-values less than 0 . 0001 only for the accessibility data ( a–c ) and p-values less than 0 . 05 for the φ ( WT ) − φ ( mut ) , ψ ( WT ) − ψ ( mut ) , and Ngh ( WT ) − Ngh ( mut ) data ( g , h , k ) . The remaining structural parameters did not show a clear correlation with activity data . In the present studies , we did not observe any preference for particular amino acid residues to precede nonperturbing Pro mutants . A significant correlation of the perturbing/nonperturbing nature of the CcdB Pro mutants was observed primarily with the φ value and H-bonding of the WT amide NH group . A decision tree ( Figure 3 ) was generated taking into account these two correlations to discriminate between active and inactive mutants . Five nodes were defined in this model decision tree based on the following criteria: a ) inactive , if |φ ( wt ) − φ ( mut ) | > 50° as large main chain rearrangements are likely to be associated with a significant energetic penalty; b ) inactive , if WT residue has H-bonded , buried polar side chain as the replacement of a buried polar side chain with Pro will result in unsatisfied H-bond acceptors/donors; c ) active , if WT amide NH group is not H-bonded; d ) inactive , if acceptor of WT amide H-bond is buried in mutant models . The acceptor could be either main chain or side chain depending on the location of the acceptor atom and is considered as buried if the corresponding average accessibility from five mutant models is <5%; e ) active , if acceptor of WT amide H-bond is exposed in mutant models ( solvent-exposed acceptor can form H-bond with a water molecule ) and |φ ( mut ) − ( −65 ) |< 15° ( since the difference between φ ( mut ) and average Pro φ is within 15° little energetically unfavorable main chain rearrangements are expected ) ; f ) inactive , if acceptor of WT amide H-bond is exposed and |φ ( mut ) – ( −65° ) |> 15° . The number of active and inactive CcdB mutants satisfying each of the criteria is also indicated in Figure 3 . Out of 35 nonperturbing mutants , 29 were predicted correctly as active/nonperturbing ( true positives , TP ) , and six were incorrectly predicted as perturbing ( false negatives , FN ) , whereas out of 35 perturbing mutants , 30 were correctly predicted as inactive/perturbing ( true negatives , TN ) and five were predicted as nonperturbing ( false positives , FP ) . The accuracy is defined as a fraction of total correct predictions , ( TP + TN ) / ( TP + TN + FP + FN ) . The accuracy of the model decision tree is therefore 84% for CcdB activity data ( with active site and WT Pro residues excluded ) . The accuracy drops slightly to 81% if active site residues are also considered . Of the seven Pro mutants at active site residues , three are correctly predicted as inactive . To examine if it was possible to obtain accurate phenotypic predictions in the absence of mutant models , a second ( WT ) decision tree was considered ( Figure 4 ) . This was closely based on the model decision tree ( Figure 3 ) with differences primarily localized to nodes a , e , and f . At node a , since φ ( mut ) is not available , instead of |φ ( wt ) − φ ( mut ) | the value of |φ ( wt ) − ( −65 ) | is calculated , assuming that the actual value of φ ( mut ) will be close to −65° . Similarly , at nodes e and f , since φ ( mut ) is not available , the value of φ ( wt ) is used instead . This WT decision tree has an accuracy of about 76% ( TP = 23 , TN = 30 , FP = 5 , FN = 12 ) , and here the accuracy remains approximately the same ( 75% ) if active site mutants are included . Both the decision trees accurately predicted the nonperturbing nature of Pro at all positions where the WT residue was Pro . Thus , in the case of CcdB , using structural parameters from mutant modeled proteins is somewhat more accurate than using just the native structure in predicting the effect of Pro substitution , although the WT decision tree also gives satisfactory predictions . Since Pro can potentially occur in either a cis or a trans conformation , cis Pro mutant models were built in addition to the trans Pro mutant models at all residue positions . The only potential benefit of models with cis Pro residues would be in cases where the trans Pro residues were predicted as inactive , while the prediction conferred activity to models with cis Pro mutants . No such cases exist for the present CcdB dataset . The large conformational changes associated with introduction of cis Pro make reliable modeling of this residue difficult . Coupled with the lack of significant improvement in prediction accuracy upon incorporation of cis Pro , this suggests that it is not appropriate to include cis Pro models into the current prediction scheme at the present time . To validate the decision trees described above , they were applied to predict effects of Pro mutations on the activity of T4 lysozyme . In a previous study [28] , each of the 163 codons of T4 lysozyme was individually replaced by an amber stop codon . The resulting mutant plasmids were transformed into 13 different suppressor strains , one of which incorporated Pro in place of the stop codon . Plaque-forming phenotypes of these mutants were reported at both 25 and 37 °C . Phenotypic data acquired from suppressor strains have some limitations because suppression efficiency is variable and context-dependent . Nevertheless , this is a large independent dataset acquired with different experimental methodology on a different protein and therefore useful for evaluating the decision trees . This dataset contains 110 active and 53 inactive mutants at 37 °C and 121 active and 42 inactive mutants at 25 °C ( Table S2 ) . The model decision tree works reasonably well with an accuracy of 77% with 37 °C data ( TP = 84 , TN = 41 , FP = 12 , FN = 26 ) , whereas the WT decision tree yields an accuracy of 73% ( TP = 76 , TN = 43 , FP = 10 , FN = 34 ) . Similar results were also obtained when the model and WT decision trees were applied to the phenotypic data acquired at 25 °C . The model decision tree has an accuracy of 74% ( TP = 87 , TN = 33 , FP = 9 , FN = 34 ) , whereas the WT decision tree has an accuracy of 70% ( TP = 79 , TN = 35 , FP = 7 , FN = 42 ) . There are about 400 , 000 known nonsynonymous single nucleotide polymorphisms ( nsSNPs ) in the protein coding sequence of the human genome [29] . Prediction of their functional effects is a crucial aspect of current genomic science . An nsSNP can alter protein function by changing the stability of its native structure and/or its binding properties . Several studies have attempted to predict the functional effects of uncharacterized nsSNPs using empirically derived rules that distinguish disease-associated SNPs and neutral SNPs . These rules were based on 3D structural parameters , sequence-based properties , and multiple alignment of homologous sequences [30–37] . The strongest correlations of perturbing nsSNPs are observed with structural parameters such as packing , H-bonds , and residue solvent accessibility . Approximately , 70%–80% of disease-associated nsSNPs could be explained using features of protein structure . One problem with previous studies is the paucity of validated negative controls , i . e . , nsSNPs that definitely do not perturb protein stability/function . Therefore , these programs predict a large number of false positives ( 10%–30% ) [33 , 36] . Most prior studies of nsSNPs have considered all types of substitutions and were based on structural parameters derived from analyzing the WT native structure . Such an approach does not take into account changes in protein structure that may occur to accommodate the mutation . Pro has unique conformational properties and a rigid structure . Hence , modeling and prediction of functional consequences of Pro containing nsSNPs is qualitatively different from those of other nsSNPs . In the present work , we have generated a decision tree to predict effects of Pro substitution based on our experimental studies on CcdB . About 8% of 14 , 250 disease-associated nsSNPs ( listed at http://ca . expasy . org/cgi-bin/lists ? humsavar . txt ) involve Pro substitutions . However , in many of these , the structure of the region of the protein containing the Pro mutation had not been determined . Single nucleotide substitutions of the following seven amino acid codons can potentially result in introduction of Pro: Leu , Ser , Thr , Ala , His , Gln , and Arg . We extracted 74 Pro disease-associated nsSNPs in 17 proteins ( with known 3D structure ) from the above SNP database to evaluate our algorithm . Five mutant models were generated for each of these 17 proteins having a Pro substitution at positions mentioned in Table S3 . Mutants were assessed as perturbing or nonperturbing using the decision tree ( Figure 3 ) . The perturbing nature of the Pro nsSNPs could be correctly predicted in 56 out of 74 cases , i . e . , 76% accuracy ( TP = 0 , TN = 56 , FP = 18 , FN = 0 ) . In comparison , accuracy of WT decision tree was 77% ( TP = 0 , TN = 57 , FP = 17 , FN = 0 ) . In seven of the cases in Table S3 ( examples 5 , 24 , 45 , 46 , 47 , 61 , 63 ) , we misclassified disease-associated nsSNPs as nonperturbing . This was because the acceptor of the amide NH of WT residue was observed to be exposed and the mutant models did not show significant main chain rearrangements from the average Pro φ value ( verbar;φ ( mut ) − ( −65 ) | < 15° ) . In 11 of the remaining cases in Table S3 ( examples 9 , 10 , 16 , 20 , 32 , 39 , 41 , 50 , 55 , 60 , and 72 ) , |φ ( mut ) − φ ( WT ) | < 50° ( average value was ∼12° for these residues ) and the WT amide NH group was also not involved in H-bonding . Hence these mutants were predicted to be nonperturbing even though the nsSNPs were associated with diseases . It should be noted that for the disease-associated nsSNPs we have not incorporated any active site information . For example , four of the CcdB Pro mutants at active site positions ( residues 24 , 25 , 95 , and 101 ) were predicted incorrectly as nonperturbing using the decision tree . If any of the Pro containing nsSNPs are at active/functional sites , the activity will be altered even if Pro has been accommodated without perturbing the overall structure/stability of the protein . Moreover , for many of the nsSNPs , the correlation with disease is based on small-size population-based studies and no functional characterization has been done . Hence in at least some of the cases the nsSNPs may actually be nonperturbing , even though they have been classified as disease-associated . The algorithm was also assessed using Pro substitutions from the ProTherm database ( http://gibk26 . bse . kyutech . ac . jp/jouhou/protherm/protherm_search . html ) and literature [38–40] . We analyzed 52 Pro mutants corresponding to 19 different proteins for which thermodynamic parameters for stability changes are either reported in the ProTherm database or are taken from the literature ( Table S4 ) . A Pro substitution was defined as perturbing if Tm ( mutant ) − Tm ( WT ) was < −10 °C or ΔG ( mutant ) − ΔG ( WT ) < −0 . 5 kcal/mol where Tm and ΔG are the temperature at midpoint of thermal unfolding and free energy of unfolding , respectively . Our predictions were correct in 37 out of 52 cases ( accuracy is 71% , TP = 32 , TN = 5 , FP = 4 , FN = 11 ) . In comparison , the accuracy of WT decision tree was 69% ( TP = 30 , TN = 6 , FP = 3 , FN = 13 ) . The overall prediction results for all datasets in terms of accuracy , precision , and recall are summarized in Table 3 . Precision is the ratio of the correctly identified positives to all positives identified ( TP ) / ( TP + FP ) , and recall is the ratio of the correctly identified positives to all positives ( TP ) / ( TP + FN ) . The accuracy and recall values are reasonably high for all the datasets tested except for nsSNPs . In this case , since only perturbing mutations are available ( TP = 0 ) , it is not meaningful to calculate precision and recall values . We have constructed a decision tree to predict whether mutating any residue in a protein to Pro will perturb its activity or not . The decision tree uses stereochemical criteria that were derived from protein activity data obtained from a Pro scanning mutagenesis study on CcdB . Predictions were made on 77 Pro mutations in CcdB , 163 Pro mutations in T4 lysozyme , 74 Pro nsSNPs in 17 human proteins , and 52 Pro mutations extracted from the ProTherm database and literature . On average , excluding the CcdB data , the prediction accuracy was 75% . The study also shows that the introduction of Pro within regions of regular secondary structure is not necessarily destabilizing and that introduction of Pro into regions lacking secondary structure can be destabilizing . Hence use of Pro scanning mutagenesis to assign secondary structure has limitations . Previous studies that predict the effects of nsSNPs on protein function have often employed multiple complex correlations and cannot easily ascribe a physical reason for a prediction . The decision tree described in this study is able to attribute physical cause for the perturbing or nonperturbing nature of a Pro mutation . The essential input required is the crystal structure or an accurate homology model of the WT protein . In most previous studies of predicting the effects of mutations , the lack of nonperturbing mutants has led to a significant degree of overprediction of the negative impact . Our CcdB dataset has an almost equal number of perturbing and nonperturbing mutants , making it ideally suited for benchmarking methods that predict the structural effects of mutations . All of these features make the decision tree described in this study an attractive method for protein engineering and design and to validate and predict the effect of Pro mutations , especially in unannotated Pro nsSNPs of proteins associated with disease . The decision tree when combined with experimental data could also contribute to the evaluation of models of protein structure .
The CcdB gene was cloned under the control of the arabinose inducible PBAD promoter in the vector pBAD24 to yield the construct pBAD24CcdB . In this plasmid , the level of CcdB expression can be regulated by varying the inducer concentration [41] . Three E . coli host strains were used: TOP10 , XL1 Blue , and CSH501 , as described previously [13] . TOP10 is sensitive to the action of CcdB and used for screening the phenotype . XL1Blue is able to tolerate low levels of CcdB protein expression because of the presence of the antidote CcdA , which is encoded by the resident F plasmid , and was used for plasmid propagation . CSH501 is completely resistant to the action of CcdB because the strain harbors the GyrA462 mutation in its chromosomal DNA and prevents gyrase from binding to CcdB . CSH501 was kindly provided by Dr . M . Couturier ( Universite Libre de Bruxelles , Belgium ) and was used for monitoring expression of mutant proteins . Thirty-nucleotide-long primers to generate CcdB mutants were designed using OLIGO version 6 . 0 and were obtained in 96-well format from the PAN Oligo facility at Stanford University . Each residue in CcdB was replaced with Pro using a mega-primer–based method of site-directed mutagenesis as described previously [13 , 42] . Templates for sequencing to confirm mutations in CcdB were isolated directly from a colony of mutant plasmid transformed in XL1Blue and were amplified by rolling circle amplification using phi 29 DNA polymerase as described in [43] . 3′-protected thiophosphate random hexamer primers and yeast pyrophosphates were obtained from Sigma and phi 29 DNA polymerase from New England Biolabs . The entire coding region of CcdB was subjected to automated DNA sequencing . After sequence confirmation , plasmids were isolated from XL1Blue grown in 96-deep-well plates . Mutant CcdB plasmids were transformed in TOP10 E . coli in 96-well format using PCR strips , and activity was assayed by plating 5 μl of transformation mix on square LB-amp plates ( 120 × 120 mm ) placed on 96-well grids in the absence of arabinose at 37 °C [13] . Since active CcdB is toxic to E . coli , only cells transformed with inactive mutants will survive . The phenotype of all mutants that were inactive at 0% arabinose was also examined at 0 . 001% , 0 . 01% , and 0 . 1% of arabinose . Expression level was monitored for all inactive mutants in CSH501 in the presence of 0 . 1% arabinose . Cultures were grown in 96-deep-well plates . Following cell lysis by a freeze-thaw method [44] , expression and solubility of all Pro mutants of CcdB in CSH501 was monitored using SDS-PAGE as described previously [13] . An in-house software , XTOPROMAKE , was used to fix prolyl residues to the backbone at all residue positions of CcdB where the backbone conformation was compatible with closure of the Pro ring . The atoms of the Pro ring , ( viz . , Cβ , Cγ , and Cδ , and their associated hydrogen atoms Hβ1 , Hβ2 , Hγ1 , Hγ2 , Hδ1 , and Hδ2 ) were examined for short contacts with spatial neighbors in the protein structure using the Ramachandran contact criteria [45–47] . In addition , nonbonded van der Waals energy of interaction between these atoms and those which occur within a sphere of 4 . 0 Å , was computed using standard constants [45] . The choice between endo and exo configurations of Cγ was decided using the energetic criteria . The software ordered the Pro-mutations at all sites , in the order of increasing nonbonded energy arising due to the mutated-prolyl residue . Hence the best sites for Pro introduction could be chosen in conjunction with other criteria ( such as H-bonding of the WT residue , accessibility , polarity , etc . ) . Three Pro mutants which were predicted to have favorable nonbonded energy from XTOPROMAKE were selected for further studies mentioned below . WT CcdB and three of its Pro mutants ( R10P , S43P , and I101P ) were purified to homogeneity as described previously [16] . Equilibrium unfolding as a function of GdnCl concentration at 25 °C was monitored by fluorescence spectroscopy at a concentration of 2 μM ( dimeric ) protein concentration . Fluorescence measurements were done using a SPEX Fluoromax-3 spectrofluorimeter with a 1 cm water-jacketed cell . The excitation and emission wavelengths were fixed at 280 nm and 385 nm , respectively , with slit widths of 2 nm for both excitation and emission monochromators . Each measurement was an average of four readings . The unfolding data was fitted to a two-state unfolding coupled to subunit dissociation model as described earlier [16] . The unfolding data for all three proteins was globally fitted using a single m value . Five models of each of the CcdB Pro mutants ( targets ) , in trans and cis conformations , were generated by comparative structure modeling using MODELLER 9v1 [48] . MODELLER implements comparative protein structure modeling by satisfaction of spatial restraints that include ( i ) homology-derived restraints on the distances and dihedral angles in the target sequence , extracted from its alignment with the template structures; ( ii ) stereochemical restraints such as bond length and bond angle preferences , obtained from the CHARMM-22 molecular mechanics force-field [49]; ( iii ) statistical preferences for dihedral angles and nonbonded interatomic distances , obtained from a representative set of known protein structures; and ( iv ) optional manually curated restraints . The spatial restraints , expressed as probability density functions , are combined into an objective function that is optimized by a combination of conjugate gradients and molecular dynamics with simulated annealing . This model-building procedure is similar to structure determination by NMR spectroscopy . The WT–CcdB dimeric structure ( PDB code 3vub ) was used as template . Target–template alignments are trivially generated by replacing the WT residues by Pro at the position of mutation in a self-alignment of the sequence of 3vub . For each of the mutants , five different models were built from different random initial starting conformations by satisfying the same set of restraints . Models were built using the “automodel” class of MODELLER , with default parameters . For cis Pro mutants , the torsion angle ω was explicitly restrained to a value of 0° . A comprehensive description of comparative protein structure modeling using MODELLER is described in the manual ( http://salilab . org/modeller/manual/ ) and several review articles [48 , 50 , 51] . Typically , the five models of the same mutant are all within a 0 . 5 Å Cα RMSD of each other . MODELLER was also used to compute structural properties of the models , including dihedral angles , solvent-accessible surface areas , H-bonds , and residue neighbors . Residue contact accessible surface areas in WT-CcdB and in Pro mutant models were calculated using a probe radius of 1 . 4 Å . Residue accessibilities for each Pro mutant were averaged over the five models . Main chain dihedral angles of the mutant models ( φ and ψ ) were similarly averaged . In the five models , the RMSD of the spread of the dihedral angle φ is within 1° . The RMSD of the φ and ψ angles for each residue for an 11-residue window centered around the mutant Pro was computed . The number of neighbors of a residue is the number of residues that have at least one of its atoms within 6 Å of any atom of the residue . H-bonds are detected if the donor–acceptor distance is less than 3 . 5 Å and the angle donor–acceptor–acceptor antecedent is 120° or greater [52] . The average ( in five models ) number of H-bonds satisfied by the acceptor ( of the amide N in the WT ) was calculated . Based on these data , a decision tree was devised to predict the effect ( perturbing/nonperturbing ) of a Pro substitution at a specified location for any globular protein . Using this algorithm , the activity of CcdB Pro mutants was predicted at 70 nonactive site residue positions mutated . Seven mutants were part of the active site as obtained from Ala and Asp scanning mutagenesis [13] and were therefore excluded from the actual analysis . The accuracy of prediction was calculated by comparison to observed activity data from experiments . Activity was also predicted using another decision tree that was built considering only the WT crystal structure , ( i . e . , without using mutant models ) . A nonparametric two-tailed Mann-Whitney test was performed to assess the significance of correlation between the activity data and various structural parameters using GraphPad Prism ( version 5 . 01 for Windows , GraphPad Software , http://www . graphpad . com ) . In case of solubility and H-bonding , there are a large number of identical values in the distribution , and hence the Mann-Whitney test could not be used . Instead , Fisher's test was performed to test the association of the parameter and the activity . In all cases , the correlation is considered to be significant if the p-value is <0 . 05 . Accuracy is calculated as the ratio of all correct predictions to total predictions , ( TP + TN ) / ( TP + TN + FP + FN ) where TP , TN , FP , and FN denote true positives , true negatives , false positives , and false negatives , respectively . Precision is the ratio of the correctly identified positives to all positives identified , i . e . , ( TP ) / ( TP + FP ) , and recall is the ratio of the correctly identified positives to all positives , i . e . , ( TP ) / ( TP + FN ) . Five models for each of 163 Pro substitution mutants were generated from the alignment between WT and mutant sequence using MODELLER 9v1 [48] . The WT protein structure ( pdb id 2lzm ) was used as the template in each case to generate the models . The models were analyzed using the decision tree derived from the CcdB scanning mutagenesis data , and the mutation was predicted to be either active/nonperturbing ( P ) or inactive/perturbing ( N ) . The correctness of the prediction is judged by comparison with experimental phenotypic activity data . Seventy-four SNPs with Pro substitutions in 17 different proteins of known 3D structure were selected from the SNP database for validating the algorithm generated from CcdB Pro scanning mutagenesis . Five models for each SNP mutant protein were generated using the WT structure as a template as described above . The models were analyzed using the decision trees as described above and the mutation was predicted to be either perturbing or nonperturbing . If a disease-associated SNP was found to be perturbing , the prediction was assumed to be correct . 52 neutral/stabilizing and destabilizing Pro mutants from 19 different proteins were selected from the ProTherm database and literature , and five models of each mutant were generated using the WT structure as a template as described above . Models were analyzed using the decision trees as described above . Predictions were assumed to be correct if predicted perturbing mutations were experimentally found to be destabilized or if predicted nonperturbing mutations were experimentally found to be neutral or stabilizing . | Unlike other amino acids that constitute proteins , Proline is missing a vital hydrogen atom and also bestows local structural rigidity to the three-dimensional ( 3D ) structure of proteins . In some locations , proline can be introduced with little or no detrimental effect to protein function , while at others it is destabilizing and can result in significant degradation or aggregation of the protein . To determine the features of protein 3D structure that tolerate the introduction of prolines , each of the 101 amino acid residues of the protein CcdB were replaced with Proline , and the functional consequence of the mutations were observed . On correlating these data to features of protein 3D structure , a decision tree was generated to predict the functional consequences of proline mutations in proteins of known ( or accurately modeled ) 3D structure . The performance of the tree was assessed on three different datasets that contained a total of 289 proline mutants in 37 different proteins . The average accuracy of prediction was 75% . The decision tree will be useful in predicting if known but uncharacterized proline mutations in disease-related proteins are likely to have adverse effects . It will also be useful in engineering and designing new proteins and peptides . | [
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] | [
"biophysics",
"eubacteria",
"computational",
"biology"
] | 2007 | Stereochemical Criteria for Prediction of the Effects of Proline Mutations on Protein Stability |
The ILEP Nerve Function Impairment in Reaction ( INFIR ) is a cohort study designed to identify predictors of reactions and nerve function impairment ( NFI ) in leprosy . Antibodies to mycobacteria , nerve components and serum cytokine were measured as potential markers for their possible association with reactions and NFI . 303 newly diagnosed leprosy patients from two centres in North India were enrolled . Antibodies to PGL-1 , LAM ( IgG1 and IgG3 ) , ceramide , S100 and TNFα levels were measured using ELISA techniques . S-100 , PGL IgG and IgM antibody levels were lowest in patients with BT leprosy and highest in patients with lepromatous leprosy . LAM IgG1 and LAM IgG3 antibody levels were highest in patients with BL leprosy . Ceramide antibody levels were not correlated with type of leprosy . Levels of all the antibodies tested and TNF α were lowest in patients with only skin reaction . PGL IgM antibody levels were elevated in patients with skin reactions and NFI . Old sensory NFI is associated with significant elevation of PGL IgG , LAM IgG and S100 antibody levels . These results reveal that the antibody response to mycobacterial antigens , nerve antigens and cytokines are in a dynamic flux and could collectively contribute to NFI in leprosy . The association of multiple markers with old NFI may indicate the contribution of different pathological processes .
Leprosy is a chronic granulomatous disease affecting skin and nerve . There is a range of clinical and immunological responses to infection with Mycobacterium leprae and the disease manifests as a spectrum . At the tuberculoid end of the spectrum there is a well developed immune response and mycobacteria are eliminated with a granulomatous response in skin and nerve which may produce severe destruction of peripheral nerves[1] . At the lepromatous end of the spectrum there is little cell mediated immunity and mycobacteria proliferate in skin and nerves and macrophages infiltrate skin and nerve but with no organised response . Most patients have one of the borderline types of disease in which some mycobacteria are present with a lymphocytic and macrophage infiltration of skin and nerve . Mycobacterial antigens are presented to the immune system and initiate a T cell response with macrophage activation and the production of pro-inflammatory cytokines . This inflammation in peripheral nerves produces local destruction of nerve structures , with subsequent loss of nerve function , which puts patients at risk of developing impairments . The pathogenesis of leprosy reactions and nerve damage involves either cell-mediated immunity at sites of localisation of mycobacteria ( reversal reaction ) [2] or immune-complex syndrome due to precipitation of antigen and antibody complexes in tissue spaces and in blood and lymphatic vessels ( ENL ) [3] . Identifying patients who are at risk of developing nerve damage is therefore a key challenge in leprosy . Various cohort studies have identified clinical risk factors for the development of nerve damage . Studies in Bangladesh [4] , Ethiopia [5] and Thailand [6] have shown that multibacillary leprosy ( MB ) , increasing age and the presence of nerve damage at the time of diagnosis are risk factors for the development of further nerve damage . However , few studies have looked at laboratory parameters as risk factors . Phenolic glycolipid ( PGL-1 ) is a M . leprae specific antigen and 90% of lepromatous , but only 50% of tuberculoid patients have antibodies to PGL-1 in proportion to their mycobacterial load [7] . A study in Nepal showed that seropositivity for PGL-1 IgG antibodies when anti-leprosy treatment is started was a significant risk factor for the development of Type 1 reactions ( T1R ) [8] . However this finding has not been confirmed in other small studies in Nepal [9] and Brazil [10] . We hypothesised that raised PGL-1 levels would be a risk factor for developing reactions and nerve damage as well as being correlated with bacterial load . Lipoarabinomannan ( LAM ) is a polysaccharide antigen present in M . leprae and is involved in initiating a specific humoral response in leprosy patients [11] . As a B cell immunogen it might have a role in part of the pathogenesis of nerve damage . LAM antigen persists in the body after the completion of antibacterial treatment and has been shown to be associated with leprosy reactions in skin and nerve biopsies [2] . One study has shown an association between raised LAM antibody levels and the occurrence of T1R [12] . LAM was considered as a potential candidate antigen in the pathogenesis of leprosy reactions , especially the late reversal reactions because it may persist in skin and nerve lesions [2] . We hypothesised that LAM antibody levels would be increased in patients with a high bacterial load and in patients with reactions . Humoral responses against nerve antigens are pathogenic in some peripheral and sensory peripheral neuropathies [13] and may also have a role in leprosy nerve damage . Ceramide and other sphingolipids are recognised as lipid mediators of the immune response and high concentrations of auto-antibodies to neural proteins and lipid antigens have been demonstrated in leprosy patients [14] , [15] , [16] . It has been reported that leprosy patients across the Ridley-Jopling spectrum show antibodies against ceramide in their sera [17] , [18] . S100 is a specific nerve tissue protein . Narayan et al looked for S100 antigen levels in serum and found that 87 . 5% of the patients had elevated S100 antigen levels . The studies of Vemuri et al [18] , Narayan et al [17] and Eustis-Turf et al [14] , although important in suggesting a pathogenic role for antibodies in the development of nerve damage , all lack information on the neurological status of the patients thus making it impossible to confirm the association with clinical nerve damage . Tumour necrosis factor α ( TNFα ) is a pro-inflammatory cytokine that is particularly implicated in the pathogenesis of mycobacterial infections . Previous studies have shown that TNFα is produced in skin and nerve during leprosy T1R [19] . Raised serum TNFα levels have been reported in Erythema Nodosum Leprosum ( ENL ) reactions and one could hypothesise that TNFα might leak from sites of inflammation into the circulation and so be a marker of acute leprosy related inflammation . Serum TNFα levels are found to be high in LL and low/undetectable in BT-TT patients [20] . The INFIR cohort comprised 303 newly diagnosed patients with MB in North India who were recruited to a study looking for risk factors for nerve damage and reactions in leprosy patients [21] . After recruitment they were assessed monthly for a year and then every two months until 24 months after diagnosis . This study design enabled us to correlate serological and clinical findings . At recruitment , patients were asked about the presence of new nerve damage which was defined as nerve damage occurring within the last six months . This then allowed us to look at pathological associations of recent or long-term nerve damage . We were therefore able to test the following hypotheses: Here we report the findings from the baseline when patients were recruited into the study .
No financial incentives were given to participants . However , travel expenses were refunded on occasion and , where relevant , lost earnings of daily labourers compensated . The study adhered to the International Ethical Guidelines for Biomedical Research Involving Human Subjects ( CIOMS/WHO , 1993 ) . Permission for the study was obtained from the Indian Council of Medical Research and ethical approval was given by the Research Ethics Committee of the Central JALMA Institute for Leprosy in Agra . This included permission for the skin and nerve biopsies . Written consent was obtained from individual subjects before inclusion in the study , using a standard consent form . This was a cohort study of 303 newly registered MB patients . The patients were followed up monthly for one year and every second month during the second year . Recruitment of subjects took place in The Leprosy Mission ( TLM ) hospitals in Naini and Faizabad , specialist leprosy referral centres in Uttar Pradesh , North India . The immunological and histopathological investigations were carried out at the LEPRA Society Blue Peter Research Centre in Hyderabad , Andhra Pradesh and at the TLM Stanley Brown Laboratories formerly located in Miraj , Maharashtra . Normal control sera were obtained from the Department of Transfusion Medicine , Nizam's Institute of Medical Sciences ( NIMS ) , Hyderabad and Miraj Medical Centre ( Wanless Hospital ) , Miraj . The study population comprised newly registered MB patients requiring a full course of Multi Drug Therapy . A detailed description of the study design has already been published [22] . Nerve function assessment: Nerve function impairment ( NFI ) was present when a patient had either or both of motor or sensory loss which were assessed by voluntary muscle testing and testing with Semmes –Weinstein monofilaments as described previously [21] . NFI was categorised as old when signs and symptoms had been present for more than six months and new when signs and symptoms had been present for six months or less . Type 1 or Reversal Reaction ( T1R ) : T1R was diagnosed when a patient had erythema and oedema of skin lesions . This may have been accompanied by neuritis and oedema of the hands , feet and face . A patient could have a skin reaction only , or a nerve reaction , or a skin and nerve reaction . Erythema Nodosum Leprosum ( ENL ) : ENL was diagnosed when a patient had crops of tender subcutaneous skin lesions . There may have been accompanying neuritis , iritis , arthritis , orchitis , dactylitis , lymphadenopathy , oedema and fever . All the data obtained in the study , including the clinical , neurophysiological , serological and histopathological data , were entered on computer locally and subsequently merged into a single Microsoft Access database . Further details of the study plans , methods , definitions , documentation and the status of the cohort at baseline have been published [21] . S100 protein , Anti-human IgG Peroxidase conjugate , Monoclonal Anti-human IgG1 , Anti-human IgG3 , Anti-mouse IgG ( gamma chain specific ) Ceramide , Anti-human IgM ( peroxidase conjugated ) , Avidin peroxidase , Orthophenyl Diamine ( OPD ) tablet , Tween 20 , Carbonate-bicarbonate buffer capsules , Phosphate citrate buffer tablets and bovine serum albumin ( BSA ) were obtained from Sigma Aldrich , USA . ManLAM and disaccharide conjugate of PGL was kindly provided by Prof . Patrick Brennan , Colorado State University . Monoclonal antibodies to TNFα ( capture antibody ) , secondary antibody ( detection antibody ) and recombinant TNFα standard were obtained from R & D Systems , London . Chemicals for phosphate buffer were obtained from Merck , the Immulon-2B ELISA plates from Thermo Labsystems , Finland and the plate sealers from Linbro , ICN , USA . Serum samples from the patients at the time of recruitment ( baseline samples ) were tested for various parameters . The different serological parameters tested using ELISA technique were: antibodies to the M . leprae – PGL and LAM; antibodies against nerve components S100 and ceramide and the proinflammatory cytokine TNFα . ELISA for antibodies against S100 , PGL-I , LAM and ceramide: Antigens against which the antibodies were to be tested were dissolved in suitable solvent like deionised water ( S-100 and PGL-I ) , or 70% methanol in PBS ( ManLAM ) or PBS ( ceramide ) . ELISAs were carried out as follows: briefly 96well microtitre plates ( Dynatech ) were coated with the antigen at a concentration of 0 . 1 µg/well in 0 . 05 M carbonate-bicarbonate buffer pH 9 . 6 by incubating overnight at 37 °C ( for S-100 , PGL-I and LAM ) . For anticeramide the antigen in PBS was sonicated prior to coating to obtain uniform suspension . The plates were washed 4 times ( 4× ) in phosphate buffered saline with Tween 20 ( PBS-T ) and then blocked with 2%BSA in PBS for 1½ hr at 37 °C in a humidified chamber . After washing 4× with PBS-T , test sera ( 1∶100 dilution ) were added ( 100 µl/well ) in triplicate . Standard pooled sera ( sera showing high antibody titre against the antigen to be tested ) were used for the S-100 , PGL-I and LAM ELISAs . Twofold dilutions were used ( 1∶25 to 1∶800 for S-100 and LAM ELISAs , 1∶100 to 1∶3200 for PGL-I IgG and 1∶200 to 1∶6400 for PGL-I IgM ) . The dilutions were assigned arbitrary units . The lowest dilution of the sera was assigned 200 AU whereas subsequent dilutions were assigned AU values accordingly e . g . 1∶100 dilution for PGL-I IgG was assigned 200 AU whereas 1∶200 dilution was assigned 100 AU and so on . The O . D . values of different dilutions of the standard pooled sera were then plotted against the assigned AU values to get a standard graph . Thus using the same standard pooled sera we could prepare a standard graph to test the antibody levels for all the samples tested so that we could compare the results . Plates were incubated at 37 °C for 1½ hr in a humidified chamber and then washed 4× with PBS-T . For S-100 , PGL-I IgG and ceramide ELISAs 100 µl of anti-human IgG- horse radish peroxidase ( HRPO ) was added to the wells whereas for PGL-I IgM ELISA anti-human IgM-HRPO was used . Plates were incubated at 37 °C for 1½ hr . For LAM IgG1 and IgG3 antibody ELISA the procedure used was as described earlier by Beuria et al [12] i . e . after the steps of addition of test / standard sera and plate washing , and prior to addition of enzyme conjugated antibody , 100 µl of mouse anti-human IgG1or mouse anti-human IgG3 monoclonal antibody ( 1∶3000 and 1∶2000 diluted respectively ) was added to the plate and incubated at 37C for 1½ hr in a humidified chamber and then washed 4× with PBS-T . Then 100 µl goat anti-mouse IgG-HRPO conjugate was added at dilution of 1∶3000 for LAM-IgG1 ELISA or 1∶2000 for LAM-IgG3 ELISA . Plate was incubated at 37 °C for 1½ hr in a humidified chamber and then washed 4× with PBS-T . After washing , OPD substrate ( in phosphate citrate buffer with perborate pH 5 . 0 ) at a final concentration of either 0 . 4 mg/ml ( S-100 , PGL-I ) or 1 mg/ml ( LAM-IgG1 and IgG3 ) was added . For anti-ceramide antibody ELISA OPD substrate ( 1 mg/ml ) in phosphate citrate buffer containing 0 . 06% H2O2 was added . The reaction was stopped with 3N HCl ( for S-100 , LAM and PGL-I ) or 3N H2SO4 ( for anticeramide ) after incubating at 37 °C for 15 minutes . The optical density ( OD ) was measured using a dual filter at the wavelength of 490/630 nm ( Dynatech ) . Estimation of serum TNFα: Sandwich ELISA development kit from R&D was used to detect serum TNFα . Briefly , the monoclonal antibodies to TNFα were coated onto the ELISA plate ( Immulon-2B ) at a concentration of 300 ng/well and incubated overnight at room temperature ( 26 °C ) . The next day , the plate was blocked in 2% BSA and incubated with 200 µl of test sera for 2 hr which are then detected by biotinylated secondary antibodies . The plate was then treated with Avidin peroxidase diluted according to manufacturers' instructions and developed by adding substrate OPD at a concentration of 1 mg/ml in Phosphate Citrate buffer pH 5 . 0 containing 0 . 06% H202 for 15 minutes in dark . The reaction was terminated with 50 µl of 3N H2SO4 and the colour was read at 490 nm . Every step until substrate addition was followed by five washing cycles programmed in Biorad plate washer with PBS pH 7 . 4 containing 0 . 1% BSA and 0 . 05% Tween 20 . For TNFα , OD values were entered into the database . For the full data set TNF concentrations ( pg/ml ) were then computed by applying the manufacturer's standard transformation based on a straight line relationship between the logarithm of the inverse OD and the logarithm of the inverse concentration . Statistical analysis was performed using Stata . The significance of association between outcome and predictor variables was tested using chi-squared tests or Fisher's exact test as appropriate . Differences between means or medians were tested with Student's t test or the Kruskal-Wallis test .
PGL IgG and IgM antibody levels increased significantly across the Ridley-Jopling spectrum groups with lowest levels in the BT patients and the highest in LL patients ( Table 2 ) ( p<0 . 001 ) . Levels of LAM IgG1 and IgG3 were also significantly higher in BL than BT patients ( p<0 . 01 ) . S100 levels increased across the Ridley-Jopling spectrum with LL patients having higher levels than BT patients ( p<0 . 01 ) . TNFα levels were highly variable with a tendency to be lower in LL patients than patients with BT and BL; however , because of the wide variation , none of the apparent differences reached statistical significance . Antibody and cytokine levels in control sera collected from normal subjects were also tested . Levels of all the antibodies and TNFα were significantly low in controls compared to patients . As shown in Table 2 , patients were also classified by bacterial load . PGL IgG and IgM levels were significantly higher ( p<0 . 001 ) in patients with higher bacterial loads , as were LAM levels in patients with higher bacterial loads . PGL IgG and IgM levels were also significantly higher in smear negative BL compared with smear negative BT patients ( p<0 . 001 ) ( data not shown ) . S100 levels were also significantly higher in patients with higher bacterial loads . In Table 3 the antibody and cytokine marker levels for patients with and without reactions and NFI are compared . PGL-1 IgG and IgM levels tended to be raised in the presence of nerve damage or reactions but the differences did not reach statistical significance . The lowest mean levels of all seven markers were found when T1R occurred only in the skin with no NFI . A significant decrease in the levels of anti-ceramide antibody levels also occurred when there were T1R with and without new NFI ( p<0 . 01 ) . This might be indicative of a marker that is altered when only skin pathology is occurring . TNF levels were highest in patients with NFI but these differences were not significant . We found no statistically significant association between Ridley-Jopling classification and reaction type . In Table 4 patients were grouped according to the type of NFI that they had . Patients with old sensory NFI had significantly increased levels of PGL IgG , LAM IgG1 and S100 antibody ( p<0 . 05 or less ) . There were far more patients with sensory NFI ( 154 ) compared to motor NFI ( 59 ) . It was observed that 136 patients did not have any NFI at the time of recuitment . There were 149 patients with no sensory NFI . But out of these 149 patients , 13 patients were with motor NFI ( old/new ) . Similarly there were 244 patients with no motor NFI , out of which 108 patients had sensory NFI ( old/new ) . Patients with no old or new sensory loss . None of the markers were significantly elevated in patients with old and new motor NFI . TNFα levels were non-significantly elevated in patients in both sensory NFI and new motor NFI . An analysis of antibody levels in the 192 smear negative group patients showed that patients with new sensory nerve damage had significantly higher PGL-1 IgG and LAM IgG1 levels ( p<0 . 01 and p = 0 . 01 , respectively ) ( data not shown ) . PGL-1 IgM and S100 levels were higher , but the significance level was borderline ( p = 0 . 08 and p = 0 . 056 , respectively ) . There were no differences between anti-ceramide and TNFα levels in the groups with or without sensory or motor nerve impairment .
The INFIR cohort study was a prospective study with carefully designed case definitions and outcomes , which were supported by clinical measurements . The large database has enabled us to analyse the data and correlate the serological findings to specific patient groups . The aim was to detect association between laboratory findings and clinical parameters in a large patient group . Trends of antibody response in relation to leprosy type and bacterial index were as expected and reported earlier by Schwerer et al [23] . One of the specific objectives was to identify new markers for nerve damage . We found an association between bacterial load , mycobacterial antigens , auto-immunity and inflammation and the development of nerve damage . Our strongest finding was confirming the association between PGL-1 antibody levels and the occurence of reactions and nerve damage . This association is also seen in the association between Ridley-Jopling type leprosy and the presence of reactions or new nerve damage . This association was also present in smear negative patients . This finding has been reported before in a study done in Nepal looking at risk factors for the development of leprosy reactions [8] . It has also been recently reported from a large cohort study in Bangladesh looking for predictive factors for nerve damage [24] . Here the strength of the predictive model was increased from 72% to 80% in the presence of PGL-1 antibodies . One of the limitations for comparison of results with that of normal control sera in this study was that though we used sera from the subjects without neurological disease from the leprosy endemic area , it was not from the same area as that from where the patients were recruited . We had predicted that S100 and anti-ceramide antibodies would be raised in acute nerve damage but found no evidence of this . However , both antibodies were elevated in patients with old sensory nerve damage . One explanation for this might be that auto-antibodies are not implicated in the initiation of new nerve damage , but once the nerve is damaged , then various nerve antigens may be presented to the immune system , initiating an auto-immune response . This may be one mechanism whereby nerve damage is perpetuated . The ongoing nerve damage seen in treated leprosy patients is an important clinical problem and this association should be investigated further . Antibodies against LAM were associated with leprosy type , but not with reactions , except with the presence of old sensory NFI . This suggests that LAM might have some role in the initiation of nerve damage , but has little immunogenic role in the ongoing process of nerve damage . We also found a non-significant association between elevated TNFα levels and new sensory and motor nerve damage . TNFα is a cytokine crucial for granuloma formation and also in the mediation of local tissue damage [25] . TNFα has been reported to cause demyelination and death of oligodendrocytes in a dose dependent manner in in-vitro studies [26] . A previous study has demonstrated TNFα in reactional skin and nerve lesions and this finding suggests that TNFα might leak from the nerve lesions into the circulation [19] . A variable elevation of TNFα has been found in ENL reactions [27] , [28] and given the close association of TNFα with the pathology of T1R , we predicted that TNFα levels would be elevated . However , the TNF assay detected a wide range of TNFα values . These levels were not easily explicable either in terms of the patients' leprosy pathology or other possible ongoing pathologies . Other reports also document a range of TNF values and a lack of correlation with clinical outcome in leprosy patients [29] . Maybe this is an inherent problem of studying this cytokine in the circulation . We had expected that , with a large number of patients , a tighter range of values might be found . Skin and nerve are very different compartments and it may be that in the context of the leprosy damaged peripheral nerve TNFα leaks more easily into the circulation than from inflamed skin lesions . Andersson et al has shown that in T1R there is marked compartmentalisation of pathology and that cytokines may not leave the skin site for the circulation [29] . This finding will be further tested when the longitudinal data on patients in this cohort who developed reactions and nerve damage during follow up are analysed . One explanation for the absence of an association between serological markers and motor damage might be that sensory nerve damage is readily detected with monofilaments , whereas motor nerve loss has to be quite advanced before it is detected by the voluntary muscle testing as was used here . In further analyses of the data , more sensitive tests of nerve function such as nerve conduction studies will be analysed and associations between mild motor damage with antibody levels can then be tested [30] . This study did not find a new serological marker for the detection of leprosy reactions . However , a pattern of associations between markers and nerve damage has been shown . These would be consistent with a model of nerve damage which is initiated by mycobacterial antigens such as PGL-1 , is maintained by ongoing inflammation through cytokines such as TNFα and then perhaps extended by auto-antibody-mediated nerve damage . It is important that further work should be done to identify markers associated with these different aspects of nerve damage . A small study from Brazil showed that plasma levels of CXCL10 ( Inflammatory protein 10 ) and IL6 were raised in 10 patients with T1R [31] . It would be useful to test these marker and other future markers in this well-characterised cohort to evaluate their role in the diagnosis of leprosy reactions . There are several implications arising from this work . The association of nerve damage with a marker for bacterial load emphasises the need to detect and treat patients as early as possible . However , we also need a marker for nerve damage in patients who are bacteriologically negative , since this study shows that there is also substantial nerve damage occurring in patients who are slit skin smear negative . | Leprosy is one of the oldest known diseases . In spite of the established fact that it is least infectious and a completely curable disease , the social stigma associated with it still lingers in many countries and remains a major obstacle to self reporting and early treatment . The nerve damage that occurs in leprosy is the most serious aspect of this disease as nerve damage leads to progressive impairment and disability . It is important to identify markers of nerve damage so that preventive measures can be taken . This prospective cohort study was designed to look at the potential association of some serological markers with reactions and nerve function impairment . Three hundred and three newly diagnosed patients from north India were recruited for this study . The study attempts to reflect a model of nerve damage initiated by mycobacterial antigens and maintained by ongoing inflammation through cytokines such as Tumour Necrosis Factor alpha and perhaps extended by antibodies against nerve components . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [
"immunology/cellular",
"microbiology",
"and",
"pathogenesis"
] | 2011 | Analysis of Antibody and Cytokine Markers for Leprosy Nerve Damage and Reactions in the INFIR Cohort in India |
Target repurposing utilizes knowledge of “druggable” targets obtained in one organism and exploits this information to pursue new potential drug targets in other organisms . Here we describe such studies to evaluate whether inhibitors targeting the kinase domain of the mammalian Target of Rapamycin ( mTOR ) and human phosphoinositide-3-kinases ( PI3Ks ) show promise against the kinetoplastid parasites Trypanosoma brucei , T . cruzi , Leishmania major , and L . donovani . The genomes of trypanosomatids encode at least 12 proteins belonging to the PI3K protein superfamily , some of which are unique to parasites . Moreover , the shared PI3Ks differ greatly in sequence from those of the human host , thereby providing opportunities for selective inhibition . We focused on 8 inhibitors targeting mTOR and/or PI3Ks selected from various stages of pre-clinical and clinical development , and tested them against in vitro parasite cultures and in vivo models of infection . Several inhibitors showed micromolar or better efficacy against these organisms in culture . One compound , NVP-BEZ235 , displayed sub-nanomolar potency , efficacy against cultured parasites , and an ability to clear parasitemia in an animal model of T . brucei rhodesiense infection . These studies strongly suggest that mammalian PI3/TOR kinase inhibitors are a productive starting point for anti-trypanosomal drug discovery . Our data suggest that NVP-BEZ235 , an advanced clinical candidate against solid tumors , merits further investigation as an agent for treating African sleeping sickness .
The pathogenic protozoans Leishmania major , L . donovani , Trypanosoma brucei , and T . cruzi are the causative agents for a collection of diseases that primarily affect the developing world , and are potentially lethal when untreated . Taken together , visceral and cutaneous leishmaniases , human African trypanosomiasis ( HAT , or sleeping sickness ) and Chagas disease affect over 22 million patients annually , causing nearly 100 , 000 deaths per year . Transmitted by the bite of infected insects , these diseases are treated by agents that are far from optimal in terms of safety , efficacy , and dosing methods [1] , [2] , [3] . Resistance to many of these therapies is emerging [4] , [5] , [6] . Since these diseases affect the poorest parts of the world , there is little opportunity to recover drug discovery research costs , and thus they are largely “neglected” by the biopharmaceutical industry . The discovery of new therapeutic agents is expensive and time consuming , and various strategies have been implemented in order to mitigate costs and speed drug discovery [7] . While the pharmaceutical industry frequently begins drug discovery programs with high-throughput screening and extended medicinal chemistry research programs , this paradigm remains unaffordable for most not-for-profit endeavors to implement . Therefore , the approach of “target repurposing” is frequently employed , where molecular targets in parasites are matched with homologous human targets that have been previously pursued for drug discovery [8] , [9] , [10] , [11] . In the best case , drugs that are selective for these human targets will have been carried into human clinical studies , strongly suggesting that the homologous parasite target is likely “druggable” [12] , that is , that compounds can be designed to inhibit the target that are safe and orally bioavailable . With an eye towards target repurposing for anti-trypanosomal drug discovery , we have identified the trypanosomal phosphoinosotide 3-kinases ( PI3Ks ) as a promising class of targets for pursuit . In humans , inhibition of members of the PI3K family has attracted significant interest as targets in the discovery of new anticancer and anti-inflammatory agents [13] , [14] , [15] . This kinase family provides critical control of cell growth and metabolism , and is comprised of three classes ( I–III ) , as determined by structure , regulation , and substrate specificity . The Target of Rapamycin ( TOR ) kinase ( a member of the PI3K-related kinase ( PKK ) subfamily ) has received particular interest due to its central role in fundamental processes such as growth , cell shape and autophagy . The TOR kinases were first identified through inhibition studies with the natural product rapamycin and related compounds . This inhibition is now known to be mediated through interactions of the TOR FKBP12-rapamycin-binding ( FRB ) domain with the rapamycin-binding protein FKBP12 [16] , [17] . More recently , inhibitors targeting the mammalian TOR ( mTOR ) kinase domain have been developed [18] , [19] , [20] , [21] , [22] , [23] . In addition , significant effort has been employed to discover inhibitors targeting specific PI3K family members [24] . Thus far , while some agents show selectivity for mTOR or for various specific PI3Ks , selectivity is rarely absolute . Many inhibitors show broad activity against a spectrum of PI3K or TOR family members . Nonetheless , both selective mTOR and these so-called “mixed” PI3K inhibitor classes have shown promise as cancer therapeutics , suggesting that absolute specificity may not be required for therapeutic efficacy [25] , [26] . Some key examples of these mTOR-selective and mixed inhibitors are shown in Table 1 and Figure 1 . Database mining of trypanosomatid genomes has revealed the presence of at least 12 proteins belonging to the PI3K protein superfamily ( PFAM PF00454 ) , many of which are unique to the parasites . Notably orthologous proteins are highly divergent from those of the human host . These include predicted kinases related to the eukaryotic class I and II PI3Ks , PI4Ks , and PIKKs including TOR , ATM and ATR ( [27] , [28] , and data not shown ) . Where tested , PI3Ks appear to be essential for viability and/or virulence in trypanosomatids . Two PIK subfamily members have been examined in T . brucei . The trypanosome Class III PI3K TbVps34 has an essential function in membrane trafficking and in Golgi segregation during cell division [29] . These authors suggested that , similar to yeast , T . brucei possesses only one genuine PI3K . TbPI4Kβ is also an essential protein in T . brucei , required for maintenance of Golgi structure , protein trafficking , and cytokinesis [29] . Trypanosomatids possess four distinct genes belonging to the TOR family , in contrast to mammals , which possess a single mTOR protein [30] , . TORs act in concert with other proteins in complexes referred to as TORCs , which have different protein subunit compositions , and cellular functions [34] . In T . brucei , the two conserved signaling complexes , TORC1 and TORC2 , whose functions appear analogous to that described in mammalian or yeast TORCs , mediate the essential functions of TOR1 and TOR2 for cell growth [33] , [35] . While TbTORC1 regulates protein synthesis , cell cycle progression and autophagy , TbTORC2 plays a key role in maintaining the polarization of the actin cytoskeleton , which is required for the proper functioning of endocytic processes , cell division , and cytokinesis [30] , [36] . Correspondingly , TOR1 and TOR2 are essential genes in Leishmania major [31] . Recent work has characterized a third TOR protein , TOR3 , in Leishmania major and T . brucei , that is implicated in the formation of acidocalcisomes and participation in stress response [31] , [32] . A fourth TOR in T . brucei and Leishmania ( TOR4 ) lacks the FRB domain responsible for binding rapamycin-binding proteins , yet possesses all other characteristic domains of TOR kinases [30] , [31] . The essentiality of several PIKs and TOR1 and TOR2 and the requirement for TOR3 for virulence in both trypanosomes and Leishmania provide genetic validation of these essential kinases as potential drug targets . Since rapamycin analogs are relatively modest inhibitors of trypanosomatid TORs and/or parasite growth [30] , [31] , [37] and difficult to synthesize , we focused in this work on kinase domain inhibitors under development . As these kinase domain inhibitors are generally more drug-like , soluble , and synthetically accessible than rapamycin analogs , we anticipate these properties could facilitate future optimization efforts .
The animal experimental protocol ( 2010102/1 ) used for African trypanosome studies was reviewed and approved by the Ethical Committee IPBLN-CSIC of the Spanish Council of Scientific Research ( CSIC ) . For T . cruzi , animal studies were approved by the Institutional Animal Care and Use Committee of New York University School of Medicine ( protocol #81213 ) , which is fully accredited by the Association For Assessment and Accreditation Of Laboratory Animal Care International ( AAALAC ) . For L . major , animal studies were approved by the Animal Studies Committee at Washington University ( protocol #20090086 ) in accordance with the Office of Laboratory Animal Welfare's guidelines and AAALAC . Inhibitor compounds were received from commercial vendors and used as received . PI-130 , NVP-BEZ235 , Ku-0063794 , Pp242 , and WYE-354 were obtained from Chemdea , Inc . ( Ridgewood , NJ ) . LY294002 , LY303511 , and Compound 401 were obtained from Tocris Biosciences ( Ellisville , MO ) . Assays were performed using the strain of T . brucei brucei Lister 427 adapted to the laboratory , and the human-infective strain T . b . rhodesiense ( EATRO3 ETat1 . 2 TREU164 [38] ) . Both strains were grown and tested as bloodstream forms . To establish the EC50 , cultures of Trypanosoma brucei and T . b . rhodesiense were treated with two-fold increasing concentrations of compounds ( with similar DMSO increasing concentration as control ) . We also utilized T . b . gambiense strain Eliane MHOM/CI/52/ITMAP 2188 , and another T . b . brucei , strain 927/4 GUTat10 . 1 [38] . Cell populations were measured at 72 hours with an Infinite F200 microplate reader ( Tecan Austria GmbH , Austria ) ; the determination of cell viability was carried out by the established colorimetric technique AlamarBlue® with modifications , a 96-well plate format spectrophotometric assay which measures the ability of living cells to reduce resazurin [39] , [40] . Data obtained with T . b . brucei Lister 427 were confirmed by manual counting in a Neubauer chamber for a direct microscopic examination to rule out multinucleated phenotypes that could mask the colorimetric assays , as well as the subtraction of solvent background to dismiss a potential solvent-derived fluorescence . Pentamidine was used as drug control for potency comparison , and T . b . brucei Lister 927 strain was included in our experiments to evaluate the adaptation to medium for the different strains as a variable condition . Flow cytometry was used to assess cell size and DNA content , to reveal a G1 or G2 arrest and multinucleated cells . Briefly , bloodstream cells of T . brucei brucei Lister 427 strain in early log phase culture were treated with high dose ( 1 µM for PI-103 , 2 µM for WYE-354 and Pp242 and 100 nM for NVP-BEZ235 ) of compounds for 16 hours , when the cells were pelleted and washed to remove all traces of drug . After permeabilization with 1 µL saponin ( 0 . 5 mg/mL final concentration ) , the culture was RNAse treated for 30 minutes ( 10 µg/mL final concentration ) and stained with 20 µg/mL propidium iodide immediately before its acquisition in a FACscan cytometer . Cells incubated with equivalent concentration of drug solvent ( DMSO ) were included in each experiment as control population . T . cruzi trypomastigotes from the Tulahuen strain stably expressing the β-galactosidase gene [41] were obtained from the supernatant of infected cultures of LLC-MK2 cells harvested between days 5 and 7 . To remove amastigotes , trypomastigotes were allowed to swim out of the pellet of samples that had been centrifuged for 7 min at 2500 rpm . For measurement of intracellular replication , 5×104 NIH/3T3 cells and 5×104 trypomastigotes per well were seeded in 96-well plates in DMEM supplemented with 2% FBS and Pen-Strep-Glut . DMEM did not contain phenol red to avoid interference with the assay absorbance readings at 590 nM . After 3 hours , compounds were added to a final volume of 200 µL/well at the indicated concentrations and mixed by pipetting . A 4 µM Amphotericin B solution ( Sigma-Aldrich ) was used as positive control . After 4 days of incubation at 37°C 5% CO2 , 50 µL of PBS containing 0 . 5% of NP40 and 100 µM chlorophenol red-β-D-galactoside ( CPRG ) ( Fluka ) were added to each well . Plates were incubated at 37°C for 4 hours and absorbance was read at 590 nm . For evaluation of extracellular survival , free trypomastigotes were rinsed once and placed in 96-well plates at 100 , 000/well with the compounds in a final volume of 200 µL of DMEM ( without phenol red ) supplemented with 2% FBS , Pen-Strep-Glut and 100 µM CPRG . Plates were incubated for 24 h at 37°C and absorbance was read at 590 nm . Leishmania major strain FV1 ( MHOM/IL/80/Friedlin ) was grown in M199 media [42] . Leishmania donovani strain LdBob ( MHOM/SD/62/1S-CL2D ) were grown in modified M199 media as promastigotes ( 26°C ) [43] . Amastigote specific media ( 37°C ) was used for growth and differentiation of amastigotes [43] . L . donovani axenic amastigotes were passed once following differentiation prior to use . Cells were enumerated using a Coulter Counter ( BD Biosciences ) ; as amastigotes tend to grow in clumps , L . donovani axenic amastigotes were passed gently through a blunt 27-gauge needle prior to counting . For determination of EC50 values , log phase cells were inoculated at concentration of 105/ml into appropriate media with compounds as indicated , and counted when the controls lacking drug had reached late logarithmic phase . The EC50 is defined as the concentration of drug inhibiting 50% of control growth , and was calculated by linear regression analysis using SigmaPlot 2000 . L . major log phase promastigotes were inoculated at a concentration of 106 cells/ml into media with compounds as indicated , and incubated overnight with varying drug concentrations to assess cell size and DNA content . For cell size , forward scatter of live promastigotes was measured by a FACS flow cytometer ( Becton Dickinson ) , utilizing dye exclusion with 5 µg/ml propidium iodide ( PI ) to gate for live cells . DNA content was determined by flow cytometry using fixed and permeabilized L . major stained with PI as previously described [44] , [45] , but reducing the incubation time with PI and RNase A from 1 hour to 30 minutes . Histogram analysis was performed using CellQuest 3 . 1 software ( BD Bioscience ) . The targeted dosage of inhibitors was determined based on the pharmacokinetic studies disclosed by Maira , et al . [46] . Our goal was to test NVP-BEZ235 in the animal models at the highest dose achievable without inducing toxicity . For L . major , 12 . 5 mg/kg orally was the highest tolerable dose while 30 mg/kg intraperitoneally ( ip ) was used for the T . cruzi infections . A lower dose was initially used in T . brucei , 5 or 10 mg/kg intraperitoneally . Female Balb/C mice ( Jackson Laboratories , Bar Harbor , ME ) were infected with 104 cells of an early log phase culture of T . b . rhodesiense EATRO3; 72 hours after infection the mice were arbitrarily separated into three independent groups , daily treated with 5 or 10 mg/kg NVP-BEZ235 , 20 mg/kg pentamidine , or DMSO , via intraperitoneal injection for four days . The parasitemia was checked at days 3 , 5 , 7 , 11 and 14 post-infection in alive mice: in those cases the parasitemia was too low to detect by Neubauer chamber count , the extracted blood was incubated in a 24-well plate with HMI-9 medium supplemented with 20% SBFi at 37°C with 5% CO2 , and positive wells were confirmed by direct visualization of parasites . Humanitarian sacrifice was executed , according to Ethic Commission of Animal Welfare directions , and necropsies were done in order to identify any physical side effect related to administration . Balb/c mice were inoculated intraperitoneally with 105 trypomastigotes from T . cruzi Y strain expressing firefly luciferase ( kindly provided by Dr . Barbara Burleigh , Harvard University ) . On day 7 post infection , mice were anesthetized with ketamine/xylazine and injected with 3 mg of D-Luciferin Potassium Salt ( Gold Biotechnology ) at 20 mg/ml in PBS and imaged in the IVIS Lumina II ( Caliper Life Sciences ) . On day 8 , groups of five mice were injected intraperitoneally with either 30 mg/kg of NVP-BEZ235 in DMSO or only DMSO , as control . Mice were treated for 5 days and imaged again on day 13 . Data is expressed as the ratio between luciferase units in day 13 versus day 7 to determine the progression of infection with and without drug treatment . Mice were infected with luciferase expressing L . major ( LmFV1LucTK-1 ) and analyzed by bioluminescent imaging as described [47] . Balb/c mice were infected with 105 L . major metacyclic stage parasites purified by gradient centrifugation [48] . Luminescence was measured using an IVIS 100 instrument and analyzed with Living Image software version 2 . 60 . NVP-BEZ235 was resuspended in DMSO and applied at 12 . 5 mg/kg/day by oral gavage for 10 days , with treatment starting day 17 post infection . At this dose the mice showed significant weight loss , suggesting that this dosage was the highest practicable , as dosing intraperitoneally at 25 mg/kg/day was lethal . The following trypanosomatid enzymes are discussed in the text: LmjF36 . 6320 ( LmjTOR1 ) , LmjF34 . 4530 ( LmjTOR2 ) , LmjF34 . 3940 ( LmjTOR3 ) , LmjF20 . 1120 ( LmjTOR4 ) , Tb927 . 8 . 6210 ( TbVps34 ) , Tb927 . 4 . 1140 ( TbPI4K beta ) , Tb927 . 3 . 4020 ( TbPI4K alpha ) , Tb927 . 10 . 8420 ( TbTOR1 ) , Tb927 . 4 . 420 ( TbTOR2 ) , Tb927 . 4 . 800 ( TbTOR3 ) Tb927 . 1 . 1930 ( TbTOR4 ) , Tb11 . 01 . 6300 ( TbATR ) , Tb927 . 2 . 2260 ( TbATM ) .
We selected eight commercially-available compounds ( Figure 1 , Table 1 ) to profile for activity against Trypanosoma brucei , T . cruzi and two species of Leishmania , cutaneous L . major and visceral L . donovani . In order to identify potential inhibitors of trypanosome TORs or PI3Ks , we selected a range of compounds with varied potencies and selectivities against mTOR/PI3K . In mammalian cells , compounds Ku-0063794 [22] , [23] , Pp242 [19] , and WYE-354 [49] inhibit the kinase domain of mTOR selectively with low nanomolar IC50 values . LY294002 is a mixed inhibitor targeting both mTOR/PI3K [50] , and many analogs have been made ( including LY303511 , which inhibits mTOR-dependent and independent pathways , but does not inhibit PI3Ks [51] , [52] ) . PI-103 inhibits PI3Ks with high potency and mTOR with a reported 20 nM IC50 [53] , [54] , [55] . Compound 401 , a compound structurally related to LY303511 , inhibits mTOR and cellular growth at low micromolar concentrations [56] , while NVP-BEZ235 inhibits both PI3Ks and mTOR with sub-nanomolar IC50 values [57] , [58] . We first tested these compounds against parasites grown in vitro . For T . brucei and Leishmania donovani , it is possible to cultivate free parasites in vitro as the infective stage forms: bloodstream form ( BSF ) for T . brucei , and axenic amastigotes for L . donovani . Compounds were also tested against L . major promastigotes ( the stage carried normally by the insect vector ) . To study infective forms of T . cruzi , compounds were added simultaneously with trypomastigotes to 3T3 fibroblast host cells and incubated for four days . This protocol thus monitors all steps of the T . cruzi infective cycle ( entry , differentiation and replication as amastigotes ) as well as potential effects mediated through host cell PI3Ks . The results of the in vitro assessment of this inhibitor collection are shown in Table 2 . The most potent compound against all the species tested was NVP-BEZ235 , showing nanomolar potency against BSF T . brucei brucei ( Lister 427 ) and sub-nanomolar activity ( 730 pM ) against the human-infective EATRO3 strain of T . b . rhodesiense ( Figure 2A , F ) . Interestingly , the BSF T . brucei gambiense , ELIANE strain [38] was even more sensitive , with an EC50 of 179 pM . PI-103 showed good activity against T . b . brucei and T . b . rhodesiense cultures ( 200 and 100 nM , respectively ) . The other inhibitors showed micromolar activity against T . brucei brucei , and , as observed with NVP-BEZ235 , these inhibitors are approximately ten-fold more potent against T . b . rhodesiense . The variation in potency of NVP-BEZ235 across different strains of T . brucei , ( including the T . brucei brucei 927/4 GUTat10 . 1 strain ) is comparable to that seen in similar studies of pentamidine , an established drug ( Table 3 ) . In infections of host cell fibroblasts by infective trypomastigotes , T . cruzi was refractory to all the inhibitors tested , except for NVP-BEZ235 ( EC50 = 120 nM , Figure 2E ) . For this compound amastigotes lysis within host cells was observed after three days when the drug was dosed at 350 nM ( ∼3× the EC50; Figure 3A ) . In contrast , NVP-BEZ235 showed little activity ( EC50 >50 µM ) against free trypomastigotes , which do not replicate outside of host cells . This suggests that NVP-BEZ235 could act specifically against the amastigotes stage , or by activation of host cell responses . For Leishmania , NVP-BEZ235 and PI-103 showed submicromolar inhibition across both species and stages ( 70–140 or 320–1050 nM respectively ) , while Pp242 and WYE-354 showed modest activity ( 0 . 4–2 . 4 µM or 4–6 µM respectively , Figure 2B–D ) . The remaining four inhibitors ( LY294002 , LY303511 , Compound 401 and Ku-63794 ) were inactive against L . major promastigotes and L . donovani axenic amastigotes at the highest concentration tested and were not tested against L . donovani promastigotes . While some compounds showed statistically significant differences amongst the Leishmania strains/species , the differences were modest and not studied further . We examined effects of several of the strongest inhibitors on cell size , shape and/or DNA content , since mTOR and PI3K inhibitors affect the size of both mammalian and T . brucei cells and induce characteristic growth phase arrests [30] , [59] . While these studies cannot determine unambiguously which of the numerous members of the trypanosomatid PI3K family may be targeted , they provide a preliminary sense of the mode of action . Indeed , the molecular target in each parasite may actually be different . Sixteen hour treatment of BSF T . brucei brucei with drug at an effective concentration ( described below ) produced two different types of effects on cellular DNA content ( Figure 3B ) . Two drugs , ( PI-103 and Pp242 , tested at 1 µM and 2 µM , respectively ) induced G1 arrest , an effect maintained even at low concentrations of Pp242 ( 200 nM , data not shown ) . While the inhibitor PI-103 showed a clearly defined profile in cell cycle progression , NVP-BEZ235 produced a combination of effects on the cell cycle progression at 0 . 1 µM , including the appearance of zoids ( anucleated cells ) [60] and multinucleated cells . This relatively high dose of NVP-BEZ235 ( 10× the EC50 ) produced a reduction of G1 and G2 cells . Finally , treatment of T . b . brucei cells with WYE-354 resulted in no significant variations in cell cycle , with a small but noticeable reduction in cell size . We examined the effect on cell size and DNA content for the four compounds that displayed activity against L . major promastigotes , using drug concentrations ( EC60-EC90 ) that were strongly inhibitory , but without inducing complete growth arrest or cellular toxicity ( as evidenced by PI exclusion tests , not shown ) . For all concentrations tested , both PI-103 and WYE-354 treatment induced a G1 arrest and a decrease in cell size ( Figure 3C ) as seen for mTORC1 inhibitors in mammalian cells . In contrast , NVP-BEZ235 treatment induced G2 growth arrest and increased promastigote size in a manner similar to the cell phenotype observed in mammalian cells exposed to mTORC2 inhibitors . Microscopy data suggests that the G2 arrest was actually due to altered cytokinesis , as evidenced by the abundance of individual cells that contain 2 nuclei and kinetoplasts ( data not shown ) , again consistent with known effects of mTORC2 inhibition in mammalian cells . Though PI-103 , WYE-354 and NVP-BEZ235 generated single phenotypes , Pp242 generated two different phenotypes depending on the drug concentration . At lower concentrations , Pp242 induced a decrease in cell size and a G1 arrest , while at higher concentrations a G2 arrest and increase in cell size was observed ( Figure 3C ) . This suggests the likelihood of inhibition of multiple targets with various affinities within the parasite . We chose the most active inhibitor , NVP-BEZ235 , for testing in appropriate animal models of T . brucei rhodesiense , T . cruzi , and L . major infection . Using the highest tolerable doses appropriate for each infection model , no efficacy was observed against either T . cruzi ( 30 mg/kg , 5 days , intraperitoneal ) or L . major ( 12 . 5 mg/kg/day , 10 days , oral gavage ) ( data not shown ) . Weight loss was observed in drug-treated mice infected with L . major and higher drug doses were lethal . In contrast , a marked decrease in parasitemia was observed by intraperitoneal dosage ( 5 or 10 mg/kg ) of NVP-BEZ235 in T . brucei rhodesiense infected mice . Drug was administered once per day , for four days . A dramatic decrease in parasitemia was observed within two days , below the detection limit of 104 parasites/mL . All mice in the untreated group died the 6th day post-inoculation , while the mean survival day ( MSD ) for animals treated with 5 mg/kg of NVP-BEZ235 was extended to 10 . 8 ( ±2 . 4 ) days . The MSD of mice treated with 10 mg/kg increased to 13 . 4 ( ±3 . 3 ) days , doubling the survival of the control group ( Figure 4 ) . In comparison , parasitemia was below detectable limits after two days of treatment with pentamidine ( 20 mg/kg , ip [61] ) , and parasite counts remained below these limits for 30 days past dosing ( data not shown ) .
In summary , by application of the target repurposing approach , we have identified a series of established mTOR and mTOR/PI3K inhibitors that display a range of activity against the trypanosomatid parasites T . brucei , T . cruzi , and Leishmania . These compounds provide a promising starting point for discovery of new drugs for trypanosomal infections . While additional study is needed to determine the exact mechanism of action of these agents , these results indicate promising inroads to a new class of therapeutics . Encouragingly , the most potent and effective compound identified in these studies , NVP-BEZ235 , is in clinical testing as an anticancer agent , and , if approved for this primary indication , may also warrant exploration as an anti-trypanosomal agent . | In our study we describe the potency of established phosphoinositide-3-kinase ( PI3K ) and mammalian Target of Rapamycin ( mTOR ) kinase inhibitors against three trypanosomatid parasites: Trypanosoma brucei , T . cruzi , and Leishmania sp . , which are the causative agents for African sleeping sickness , Chagas disease , and leishmaniases , respectively . We noted that these parasites and humans express similar kinase enzymes . Since these similar human targets have been pursued by the drug industry for many years in the discovery of cellular growth and proliferation inhibitors , compounds developed as human anti-cancer agents should also have effect on inhibiting growth and proliferation of the parasites . With that in mind , we selected eight established PI3K and mTOR inhibitors for profiling against these pathogens . Among these inhibitors is an advanced clinical candidate against cancer , NVP-BEZ235 , which we demonstrate to be a highly potent trypanocide in parasite cultures , and in a mouse model of T . brucei infection . Additionally , we describe observations of these inhibitors' effects on parasite growth and other cellular characteristics . | [
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"transduction",... | 2011 | The Susceptibility of Trypanosomatid Pathogens to PI3/mTOR Kinase Inhibitors Affords a New Opportunity for Drug Repurposing |
Stimulus-induced perturbations from the steady state are a hallmark of signal transduction . In some signaling modules , the steady state is characterized by rapid synthesis and degradation of signaling proteins . Conspicuous among these are the p53 tumor suppressor , its negative regulator Mdm2 , and the negative feedback regulator of NFκB , IκBα . We investigated the physiological importance of this turnover , or flux , using a computational method that allows flux to be systematically altered independently of the steady state protein abundances . Applying our method to a prototypical signaling module , we show that flux can precisely control the dynamic response to perturbation . Next , we applied our method to experimentally validated models of p53 and NFκB signaling . We find that high p53 flux is required for oscillations in response to a saturating dose of ionizing radiation ( IR ) . In contrast , high flux of Mdm2 is not required for oscillations but preserves p53 sensitivity to sub-saturating doses of IR . In the NFκB system , degradation of NFκB-bound IκB by the IκB kinase ( IKK ) is required for activation in response to TNF , while high IKK-independent degradation prevents spurious activation in response to metabolic stress or low doses of TNF . Our work identifies flux pairs with opposing functional effects as a signaling motif that controls the stimulus-sensitivity of the p53 and NFκB stress-response pathways , and may constitute a general design principle in signaling pathways .
Eukaryotic cells must constantly recycle their proteomes . Of the approximately 109 proteins in a typical mouse L929 fibrosarcoma cell , 106 are degraded every minute [1] . Assuming first-order degradation kinetics , this rate of constitutive protein turnover , or flux , imposes an average half-life of 24 hours . Not all proteins are equally stable , however . Genome-wide quantifications of protein turnover in HeLa cells [2] , [3] and 3T3 murine fibroblasts [4] show that protein half-lives can span several orders of magnitude . Thus while some proteins exist for months and even years [5] , others are degraded within minutes . Gene ontology terms describing signaling functions are highly enriched among short-lived proteins [3] , [6] , [7] , suggesting that rapid turnover is required for proper signal transduction . Indeed , defects in protein turnover are implicated in the pathogenesis of cancer and other types of human disease [8] , [9] . Conspicuous among short-lived signaling proteins are those that regulate the p53 and NFκB stress response pathways . The p53 protein itself , for example , has a half-life of less than 30 minutes [10] , [11] . Mdm2 , the E3 ubiquitin ligase responsible for regulating p53 , has a half-life of 45 minutes [4] . And the half-life of unbound IκBα , the negative feedback regulator of NFκB , is less than 15 minutes [12] , [13] ( see Figure S1 ) , requiring that 6 , 500 new copies of IκBα be synthesized every minute [13] . Given the energetic costs of protein synthesis , we hypothesized that rapid turnover of these proteins is critical to the stimulus-response behavior of their associated pathways . To test our hypothesis we developed a method to systematically alter the rates of protein turnover in mass action models without affecting their steady state abundances . Our method requires an analytical expression for the steady state of a model , which we derive using the py-substitution method described in a companion manuscript . From this expression , changes in parameter values that do not affect the steady state are found in the null space of the matrix whose elements are the partial derivatives of the species abundances with respect to the parameters . We call this vector space the isostatic subspace . After deriving a basis for this subspace , linear combinations of basis vectors identify isostatic perturbations that modify specific reactions independently of all the others , for example those that control protein turnover . By systematic application of these isostatic perturbations to a model operating at steady state , the effects of flux on stimulus-responsiveness can be studied in isolation of changes to steady-state abundances ( see Methods ) . We first apply our method to a prototypical negative feedback module in which an activator controls the expression of its own negative regulator . We show that reducing the flux of either the activator or its inhibitor slows the response to stimulation . However , reducing the flux of the activator lowers the magnitude of the response , whereas reducing the flux of the inhibitor increases it . This complementarity allows the activator and inhibitor fluxes to exert precise control over the module's response to stimulation . Given this level of control , we hypothesized that rapid turnover of p53 and Mdm2 must be required for p53 signaling . A hallmark of p53 is that it responds to DNA damage in a series of digital pulses [14]–[18] . These pulses are important for determining cell fate [19]–[21] . To test whether high p53 and Mdm2 flux are required for p53 pulses , we applied our method to a model in which exposure to ionizing radiation ( IR ) results in oscillations of active p53 [17] . By varying each flux over three orders of magnitude , we show that high p53 flux is indeed required for oscillations . In contrast , high Mdm2 flux is not required , but rather controls the refractory time in response to transient stimulation . If the flux of Mdm2 is low , a second stimulus after 22 hours does not result in appreciable activation of p53 . In contrast to p53 , the flux of NFκB turnover is very low , while the flux of its inhibitor , IκB , is very high . Prior to stimulation , most NFκB is sequestered in the cytoplasm by IκB . Upon stimulation by an inflammatory signal like tumor necrosis factor alpha ( TNF ) , IκB is phosphorylated and degraded , resulting in rapid but transient translocation of NFκB to the nucleus and activation of its target genes [22]–[24] . Two separate pathways are responsible for the turnover of IκB [12] . In one , IκB bound to NFκB is phosphorylated by the IκB kinase ( IKK ) and targeted for degradation by the ubiquitin-proteasome system . In the other pathway , unbound IκB is targeted for degradation and requires neither IKK nor ubiquitination [25] , [26] . We call these the “productive” and “futile” fluxes , respectively . Applying our method to a model of NFκB activation , we show that the futile flux acts as a negative regulator of NFκB activation while the productive flux acts as a positive regulator . We find that turnover of bound IκB is required for NFκB activation in response to TNF , while high turnover of unbound IκB prevents spurious activation of NFκB in response to low doses of TNF or ribotoxic stress caused by ultraviolet light ( UV ) . As with p53 then , juxtaposition of a positive and negative regulatory flux govern the sensitivity of NFκB to different stimuli , and may constitute a common signaling motif for controlling stimulus-specificity in diverse signaling pathways .
To examine the effects of flux on stimulus-responsiveness , we built a prototypical negative feedback model reminiscent of the p53 or NFκB stress-response pathways ( Figure 1A ) . In it , an activator “X” is constitutively expressed but catalytically degraded by an inhibitor , “Y” . The inhibitor is constitutively degraded but its synthesis requires X . Activation is achieved by instantaneous depletion of Y , the result of which is accumulation of X until negative feedback forces a return to steady state . The dynamics of this response can be described by two values: , the amplitude or maximum value of X after stimulation , and , the time at which is observed ( Figure 1B ) . Parameters for this model were chosen such that the abundances of both X and Y are one arbitrary unit and X achieves its maximum value of at time , where the units of time are also arbitrary . To address the role of these parameters in shaping the response of the activator , we first performed a traditional sensitivity analysis . We found that increasing the synthesis of X ( Figure 1C ) , or decreasing the degradation of X ( Figure 1D ) or the synthesis of Y ( Figure 1E ) , all result in increased responsiveness . However , these changes also increase the abundance of X . To distinguish between the effects caused by changes in flux and those caused by changes in abundance , we developed a method that alters the flux of X and Y while maintaining their steady state abundances at . Using this method , we found that increasing the flux of X increases responsiveness ( Figure 1G ) , but not to the same extent as increasing the synthesis parameter alone ( Figure 1C ) . In contrast , reducing the flux of Y yields the same increase in responsiveness as decreasing the synthesis of Y ( Figure 1E ) or the degradation of X ( Figure 1D ) . These observations suggest that both the flux and abundance of X are important regulators of the response , as is the flux of Y , but not its abundance . This conclusion is supported by the observation that when the abundance of Y is increased by reducing its degradation , there is little effect on signaling ( Figure 1F ) . To further characterize the effects of flux on the activator's response to stimulation , we applied systematic changes to the fluxes of X and Y prior to stimulation and plotted the resulting values of and . Multiplying the flux of X over the interval showed , as expected , that the value of increases while the value of deceases ( Figure 2A ) . In other words , a high activator flux results in a strong , fast response to stimulation . If we repeat the process with the inhibitor , we find that both and decrease as the flux increases; a high inhibitor flux results in a fast but weak response ( Figure 2B ) . This result illustrates that fluxes of different regulators can have different but complementary effects on stimulus-induced signaling dynamics . Complementarity suggests that changes in flux can be identified such that is altered independently of , or independently of . Indeed , if both activator and inhibitor fluxes are increased in equal measure , is held fixed while the value of decreases ( Figure 2C ) . Increasing both fluxes thus simultaneously reduces the timescale of the response without affecting its magnitude . An equivalent relationship can be found such that remains fixed while is affected ( Figure 2D ) . Because an increase in either flux will reduce , to alter without affecting requires an increase in one flux but a decrease in the other . Also , is more sensitive to changes in the inhibitor flux versus the activator flux; small changes in the former must be paired with larger changes in the latter . This capability to achieve any value of or indicates that flux can precisely control the response to stimulation , without requiring any changes to steady state protein abundance . Given that flux precisely controls the dynamic response to stimulation in a prototypical signaling module , we hypothesized that for p53 , oscillations in response to DNA damage require the high rates of turnover reported for p53 and Mdm2 . To test this , we applied our method to a published model of p53 activation in response to ionizing gamma radiation ( IR ) , a common DNA damaging agent ( Figure 3A ) [17] . Because the model uses arbitrary units , we rescaled it so that the steady state abundances of p53 and Mdm2 , as well as their rates of synthesis and degradation , matched published values ( see Table S1 ) . We note that these values are also in good agreement with the consensus parameters reported in [16] . Next we implemented a multiplier of Mdm2-independent p53 flux and let it take values on the interval . For each value we simulated the response to IR using a step function in the production of the upstream Signal molecule , , as previously described [17] . To characterize the p53 response we let be the amplitude of stable oscillations in phosphorylated p53 ( Figure 3B ) , and use this as a metric for p53 sensitivity . Where , we say the module is sensitive to IR stimulation . We find that is greater than zero only when the flux of p53 is near its observed value or higher ( Figure 4A ) . If the flux of p53 is reduced by 2-fold or more , p53 no longer stably oscillates in response to stimulation , but exhibits damped oscillations instead . Interestingly , repeating this analysis with a multiplier for the Mdm2 flux over the same interval reveals that Mdm2 flux has little bearing on p53 oscillations ( Figure 4B ) . For any value of the multiplier chosen , . As with p53 , this multiplier alters the Signal-independent flux of Mdm2 but does not affect Signal-induced Mdm2 degradation . If oscillations are already compromised by a reduced p53 flux , no concomitant reduction in Mdm2 flux can rescue the oscillations ( Figure 4C ) . We therefore conclude that the flux of p53 , but not Mdm2 , is required for IR-sensitivity in the p53 signaling module . What then is the physiological relevance of high Mdm2 flux ? In the model , signal-mediated Mdm2 auto-ubiquitination [27] is a major contributor to Mdm2 degradation after stimulation . If Signal production is transient , Mdm2 protein levels must be restored solely via Signal-independent degradation . We therefore hypothesized that if the flux of Mdm2 is low , Mdm2 protein levels would remain elevated after stimulation and compromise sensitivity to subsequent stimuli . To test this hypothesis we again let the Mdm2 flux multiplier take values over the interval . For each value we stimulated the model with a 2-hour pulse of Signal production , followed by 22 hours of rest , followed by a second 2-hour pulse ( Figure 3B ) . We defined to be the amplitude of the first peak of phosphorylated p53 and to be the amplitude of the second peak . Sensitivity to the second pulse is defined as the difference between and , with indicating full sensitivity . As seen in Figures 4D and E , the flux of p53 has no bearing on the sensitivity to the second pulse while the flux of Mdm2 strongly affects it . At one one-hundredth the observed Mdm2 flux – corresponding to protein half-life of 3-days – over 20 , 000 fewer molecules of p53 are phosphorylated , representing more than a two-fold reduction in sensitivity ( Figure 4E ) . This result is robust with respect to the interval of time chosen between pulses ( Figure S2 ) . If the sensitivity to the second pulse is already compromised by a reduced Mdm2 flux , a concomitant reduction in p53 flux fails to rescue it , while an increase in p53 flux still further reduces it ( Figure 4F ) . We therefore conclude that the flux of Mdm2 , and not p53 , controls the system's refractory time , and a high Mdm2 flux is required to re-establish sensitivity after transient stimulation . A second major stress-response pathway is that of NFκB . NFκB is potently induced by the inflammatory cytokine TNF , but shows a remarkable resistance to internal metabolic perturbations or ribotoxic stresses induced by ultraviolet light ( UV ) [13] , or to triggers of the unfolded protein response ( UPR ) [28] . Like p53 , the dynamics of NFκB activation play a major role in determining target gene expression programs [29] , [30] . Although NFκB is considered stable , the flux of IκBα – the major feedback regulator of NFκB – is conspicuously high . We hypothesized that turnover of IκB controls the stimulus-responsiveness of the NFκB signaling module . Beginning with a published model of NFκB activation [13] , we removed the beta and epsilon isoforms of IκB , leaving only the predominant isoform , IκBα ( hereafter , simply “IκB”; Figure 5A ) . Steady state analysis of this model supported the observation that almost all IκB is degraded by either of two pathways: a “futile” flux , in which IκB is synthesized and degraded as an unbound monomer; and a “productive” flux , in which free IκB enters the nucleus and binds to NFκB , shuttles to the cytoplasm , then binds to and is targeted for degradation by IKK ( Figure 5B ) . These two pathways account for 92 . 5% and 7 . 3% of the total IκB flux , respectively . The inflammatory stimulus TNF was modeled as before , using a numerically-defined IKK activity profile derived from in vitro kinase assays [30] ( Figure 5A , variable ) . Stimulating with TNF results in strong but transient activation of NFκB . A second stimulus , ribotoxic stress induced by UV irradiation , was modeled as 50% reduction in translation and results in only modest activity [13] . As above , we let be the amplitude of activated NFκB in response to TNF and the time at which is observed . Analogously , we let be the amplitude of NFκB in response to UV , and the time at which NFκB activation equals one-half ( see Figure 5C ) . We then implemented multipliers for the futile and productive flux and let each multiplier take values on the interval . For each value we simulated the NFκB response to TNF and UV and plotted the effects on and . The results show that reducing the productive flux yields a slower , weaker response to TNF ( Figure 6A ) . By analogy to Figure 2 , this indicates that the productive flux of IκB is a positive regulator of NFκB activation . In contrast , the futile flux acts as a negative regulator of NFκB activity , though its effects on and are more modest ( Figure 6B ) . Thus , similar to p53 , the activation of NFκB is controlled by a positive and negative regulatory flux . In response to UV , a reduction in either flux delays NFκB activation , but reducing the futile flux results in a significant increase in while reducing the productive flux has almost no effect ( Figure 6C and D ) . Conversely , while an increase in the futile flux has no effect on , an increase in the productive flux results in a significant increase . If we now define NFκB to be sensitive to TNF or UV when or are ten-fold higher than its active but pre-stimulated steady state abundance , then TNF sensitivity requires a productive flux multiplier , while UV insensitivity requires a productive flux multiplier and a futile flux multiplier . This suggests that the flux pathways of IκB may be optimized to preserve NFκB sensitivity to external inflammatory stimuli while minimizing sensitivity to internal metabolic stresses . In contrast to p53 , the negative regulatory flux of IκB dominates the positive flux . We hypothesized that this imbalance must affect the sensitivity of NFκB to weak stimuli . To test this hypothesis we generated dose-response curves for TNF and UV using the following multipliers for the futile flux: , , , and ( see Methods ) . The results confirm that reducing the futile flux of IκB results in hypersensitivity at low doses of TNF ( Figure 7 , Row 1 ) . At one one-hundredth the wildtype flux , a ten-fold weaker TNF stimulus yields an equivalent NFκB response to the full TNF stimulus at the wildtype flux . Similarly , a high futile flux prevents strong activation of NFκB in response to UV ( Figure 7 , Row 2 ) . At and times the futile flux , UV stimulation results in a 20-fold increase in NFκB activity , compared to just a 2-fold increase at the wildtype flux . We therefore conclude that turnover of unbound IκB controls the EC50 of the NFκB signaling module , and that rapid turnover renders NFκB resistant to metabolic and spurious inflammatory stimuli .
Previous studies have shown that the fluxes of p53 [10] , [11] , its inhibitor Mdm2 [31] , [32] , and the unbound negative regulator of NFκB , IκB [12] , are remarkably high . To investigate whether rapid turnover of these proteins is required for the stimulus-response behavior of the p53 and NFκB stress response pathways , we developed a computational method to alter protein turnover , or flux , independently of steady state protein abundance . For p53 , we show that high flux is required for sensitivity to sustained stimulation after ionizing radiation ( Figure 4A ) . Interestingly , inactivating mutations in p53 have long been known to enhance its stability [33] , either by interfering with Mdm2-catalyzed p53 ubiquitination [34] , [35] , or by affecting p53's ability to bind DNA and induce the expression of new Mdm2 [36]–[39] . Inactivation of p53 also compromises the cell's sensitivity to IR [40] , [41]–[43] . Our results offer an intriguing explanation for this phenomenon , that p53 instability is required for oscillations in response to IR . Indeed , IR sensitivity was shown to correlate with p53 mRNA abundance [44]–[46] , a likely determinant of p53 protein flux . In further support of this hypothesis , mouse embryonic fibroblasts lacking the insulin-like growth factor 1 receptor ( IGF-1R ) exhibit reduced p53 synthesis and degradation , but normal protein abundance . These cells were also shown to be insensitive to DNA damage , caused by the chemotherapeutic agent etoposide [32] . Like p53 , increased stability of Mdm2 has been observed in human leukemic cell lines [47] , and Mdm2 is a strong determinant of IR sensitivity [48] , [49] . Again our results suggest these observations may be related . Activation of p53 in response to IR is mediated by the ATM kinase ( “Signal” in Figure 3 ) [50] , [51] . Batchelor et al . show that saturating doses of IR result in feedback-driven pulses of ATM , and therefore p53 [17] . In Figure 4B we show that these are independent of Mdm2 flux . However , sub-saturating doses of IR ( 10 Gy versus 0 . 5 Gy ) [52] , [53] cause only transient activation of ATM [54] , after which constitutive Mdm2 synthesis is required to restore p53 sensitivity ( Figure 4E ) . This suggests that high Mdm2 flux is required for sensitivity to prolonged exposure to sub-saturating doses of IR . Indeed , this inverse relationship between flux and refractory time has been observed before . In Ba/F3 pro-B cells , high turnover of the Epo receptor maintains a linear , non-refractory response over a broad range of ligand concentrations [55] . For NFκB , our method revealed that an isostatic reduction in the half-life of IκB sensitizes NFκB to TNF ( Figure 7A ) , as well as to ribotoxic stress agents like UV ( Figure 7B ) . This observation agrees with previous theoretical studies using a dual kinase motif , where differential stability in the effector isoforms can modulate the dynamic range of the response [56] . For NFκB , the flux of free IκB acts as a kinetic buffer against weak or spurious stimuli , similar to serial post-translational modifications on the T cell receptor [57] , or complementary kinase-phosphatase activities in bacterial two-component systems [58] . In contrast , increasing the half-life of IκBα alone – without a coordinated increase in its rate of synthesis – increases the abundance of free IκBα and actually dampens the activity of NFκB in response to TNF [25] . This difference highlights the distinction between isostatic perturbations and traditional , unbalanced perturbations that also affect the steady state abundances . It also calls attention to a potential hazard when trying to correlate stimulus-responsiveness with protein abundance measurements: observed associations between responses and protein abundances do not rule out implied changes in kinetic parameters as the causal link . Indeed static , and not kinetic measurements , are the current basis for molecular diagnosis of clinical specimens . Thus while nuclear expression of p53 [59]–[66] and NFκB [67]–[69] have been shown to correlate with resistance to treatment in human cancer , the correlation is not infallible [40] , [70]–[74] . If stimulus-responsiveness can be controlled by protein turnover independently of changes to steady state abundance , then correlations between abundance and a therapeutic response may be masked by isostatic heterogeneity between cells . For p53 and NFkB , we show that stimulus sensitivity can be controlled by a paired positive and negative regulatory flux . We propose that this pairing may constitute a common regulatory motif in cell signaling . In contrast to other regulatory motifs [75] , [76] , the “flux motif” described here does not have a unique structure . The positive p53 flux , for example , is formed by the synthesis and degradation of p53 itself , while the positive flux in the NFκB system includes the nuclear import of free NFκB and export of NFκB bound to IκB . For p53 , the negative flux is formed by synthesis and degradation of Mdm2 , while for NFκB it is formed by the synthesis , shuttling , and degradation of cytoplasmic and nuclear IκB . Thus the reaction structure for each flux is quite different , but they nevertheless form a regulatory motif that is common to both pathways ( Figure 8 ) . And since the mathematical models used here are only abstractions of the underlying network , the true structure of the p53 and NFκB flux motifs are in reality even more complex . The identification of a flux motif that controls stimulus-responsiveness independently of protein abundances may prompt experimental investigation into the role of flux in signaling . At a minimum , this could be achieved using fluorescently-labeled activator and inhibitor proteins in conjunction with tunable synthesis and degradation mechanisms . The tet-responsive promoter system [77] , [78] , for example , could provide tunable synthesis , while the CLP-XP system [79] could provide tunable degradation . For the two-dimensional analysis presented here , and to avoid confounding effects on signaling dynamics caused by shared synthesis and degradation machinery [80] , independently tunable synthesis and degradation mechanisms may be required . If these techniques are applied to mutants lacking the endogenous regulators , this would further allow decreases in protein flux to be studied in addition to strictly increases . Finally , in this study we have examined the effects of flux on stimulus-responsiveness , but in a typical signaling module , many other isostatic perturbations exist . For example , the isostatic subspace of our NFκB model has 18 dimensions , of which only a few were required by the analysis presented here . By simultaneously considering all isostatic perturbations , some measure of the dynamic plasticity of a system can be estimated , perhaps as a function of its steady-state . Such an investigation can inform diagnosis of biological samples , and whether information from a single , static observation is sufficient to predict the response to a particular chemical treatment , or whether live-cell measurements are required as well . As we have shown that protein turnover can be a powerful determinant of stimulus-sensitivity , we anticipate that kinetic measurements will be useful predictors of sensitivity to chemical therapeutics .
To begin , we assume that the system of interest has been modeled using mass action kinetics and that the steady state abundance of every biochemical species is a known function of input parameters . In other words , such that ( 1 ) Equation 1 is the well-known steady-state equation; is a vector of independent parameters and is the vector of species abundances . We use an overbar to denote a vector that satisfies Equation 1 . For excellent reviews on mass action models and their limitations , see [81]–[83] . For a method on finding analytical solutions to the steady state equation , see our accompanying manuscript . Next , we wish to find a change in the input parameters such that the resulting change in the species abundances is zero , where is defined as Thus for , we require that The right-hand side of this equation can be approximated by a truncated Taylor series , as follows:where is the Jacobian matrix whose elements are the partial derivatives of each species with respect to each parameter . Thus , for we require that In other words , must lie in the null space of . We call this the isostatic subspace of the model – parameter perturbations in this subspace will not affect any of the steady-state species abundances . If lies within the isostatic subspace , it is an isostatic perturbation vector . Let be a matrix whose columns form a basis for the isostatic subspace . Then a general expression for an isostatic perturbation vector is simply ( 2 ) where is a vector of unknown basis vector coefficients . Finally , Equation 2 can be solved for a specific linear combination of basis vectors that achieves the desired perturbation . In our case we identified those combinations that result in changes to protein turnover . Our prototypical negative feedback model consists of two species , an activator “X” and an inhibitor “Y” , and four reactions , illustrated in Figure 1A . Let denote the abundance of the activator and denote the abundance of the inhibitor . An analytical expression for the steady-state of this model was identified by solving Equation 1 for the rates of synthesis , giving ( 3 ) ( 4 ) To parameterize the model we first let . Degradation rate constants were then calculated such that at time , where again is the maximum amplitude of the response . Activation was achieved by instantaneous reduction of to . To modify the flux , we defined flux multipliers and such that and . Note that by virtue of Equations 3 and 4 , values for and other than result in commensurate changes in and such that steady state is preserved . See file “pnfm . sci” in Protocol S1 for details . Figures 2A and 2B were achieved by letting and vary over the interval , then calculating the altered vector of rate constants and simulating the model's response to stimulation . Figure 2C required letting vary over this same interval while having . Finally , Figure 2D was achieved by letting vary over the same interval , and for each value of , numerically calculating the value of that gave . All species , reactions , and rate equations required by our model of p53 oscillations are as previously described [17] . Our only modification was to scale the parameter values so that the rates of p53 and Mdm2 synthesis and degradation , as well as their steady-state abundances , matched published observations ( see Table S1 ) . Specifically we let To derive a steady-state solution for this model , we solved Equation 1 for the steady-state abundance of Mdm2 and the rate of Mdm2-independent p53 degradation , giving To simulate the response to ionizing radiation we used the ( scaled ) stimulus given in [17] . Namely , at time we let the rate of Signal production , , go to . This stimulus was either maintained indefinitely ( Figure 4A–C ) or for just 2 hours , followed by 22 hours of rest , followed by a second 2 hour stimulation ( Figure 4D–F ) . Changes in p53 or Mdm2 flux were achieved as above , by defining modifiers and such that ( 5 ) ( 6 ) ( 7 ) Prior to stimulation , we let one modifier take values on the interval while holding the other modifier constant . Equations 6 and 7 ensure that the p53-independent flux of Mdm2 is modified without affecting its steady-state abundance . Equation 5 , which is slightly more complicated , results in changes to the rate of Mdm2-independent p53 degradation , , by modifying the independent parameter , which controls the rate of p53 synthesis . This yields the desired Numerical integration was carried out to time . After each integration , we defined to be the minimum vertical distance between any adjacent peak and trough in phosphorylated p53 , and and to be the amplitudes of the first and second peak , respectively . Details of this model can be found in the file “p53b . sci” in Protocol S1 . For more information on the time delay parameters and , and their role in generating oscillations , see [84] , [85] . Our model of NFκB activation is similar to the one described in [13] , except the beta and epsilon isoforms of IκB have been removed . Our model has 10 species and 26 reactions , the majority of which are illustrated in Figure 5A . Rate equations and parameter values are identical to those in [13] . An analytical expression for the steady-state of this model was found by solving Equation 1 for the following dependent variables: , , , , and , and the rate constants , , and . The precise expressions for these variables are extremely cumbersome but may be found in their entirety in the file “nfkb . sci” in Protocol S1 . Activation of NFκB is achieved by either of two , time-dependent numerical input variables , and . modifies the activity of IKK while modifies the efficiency of IκB translation . Both have a finite range of and have unstimulated , wildtype values of and , respectively . The inflammatory stimulus TNF is modeled using a unique function of derived from in vitro kinase assays [30] . Since these assays only measured IKK activity out to 4 hours , we extended each stimulus by assuming the value of at 4 hours is maintained out to 24 hours . Justification for this can be found in the 24-hour kinase assays in [86] , which shows no IKK activity between 8 and 24 hours after TNF stimulation . UV stimulation is modeled using a step decrease in the value of from 1 . 0 to 0 . 5 for the entire 24 hours . This mimics the 50% reduction in translational efficiency observed in [13] . Steady-state analysis of this model revealed that over 99% of all IκB was degraded via either of two pathways , futile ( 92% ) and productive ( 7% ) . See Figure 5B for the composition of these pathways . To modify the flux through either pathway without altering any of the steady-state abundances , the algebraic method described above proved absolutely necessary . Specifically , we solved Equation 2 for the unique set of basis vector coefficients such that the following conditions held: ( 1 ) only reaction rate constants involved in the targeted pathway were modified; ( 2 ) if a reaction on the pathway was reversible , its ratio of forward to reverse rate constants was preserved; and ( 3 ) the magnitude of an alteration was relative to the bottleneck reaction . For the futile flux this was , the degradation of unbound nuclear IκB . For the productive flux it was , the export of NFκB-bound IκB . As in the p53 models above , we then defined multipliers and such that See file “nfkb . sci” in Protocol S1 for the precise effect of and on the other rate constants in the model . Finally , to generate Figure 6 we let the appropriate multiplier take values on the interval prior to stimulation with TNF or UV . Dose response curves in Figure 7 were generated by letting take values in and simulating the response to varying doses of TNF or UV . To vary the TNF dose , we scaled the displacement of the numerical IKK activation curve above its basal value of 1% using log-spaced multipliers on the interval . We call this multiplier the “stimulus strength” . A stimulus strength of , for example , yields the same basal IKK activity as the full TNF dose used in Figure 6 , but a peak activity whose magnitude is just one-tenth that of the full dose . To measure the TNF response , we calculated an area under the curve ( AUC ) by subtracting NFκB basal activity from the TNF-induced NFκB activation curve , then integrated this curve from the point of stimulus to the time at which it becomes less than one-tenth the basal activity . All AUCs were normalized to the full TNF dose . To vary the UV dose we varied the magnitude of the displacement of from unity . A stimulus strength of 0 . 1 , for example , results in a step decrease in from 1 . 0 to 0 . 9 . Because the response to UV is sustained instead of transient , we plotted as a function of stimulus strength instead of the area under the curve . | Eukaryotic cells constantly synthesize new proteins and degrade old ones . While most proteins are degraded within 24 hours of being synthesized , some proteins are short-lived and exist for only minutes . Using mathematical models , we asked how rapid turnover , or flux , of signaling proteins might regulate the activation of two well-known transcription factors , p53 and NFκB . p53 is a cell cycle regulator that is activated in response to DNA damage , for example , due to ionizing radiation . NFκB is a regulator of immunity and responds to inflammatory signals like the macrophage-secreted cytokine , TNF . Both p53 and NFκB are controlled by at least one flux whose effect on activation is positive and one whose effect is negative . For p53 these are the turnover of p53 and Mdm2 , respectively . For NFκB they are the TNF-dependent and -independent turnover of the NFκB inhibitor , IκB . We find that juxtaposition of a positive and negative flux allows for precise tuning of the sensitivity of these transcription factors to different environmental signals . Our results therefore suggest that rapid synthesis and degradation of signaling proteins , though energetically wasteful , may be a common mechanism by which eukaryotic cells regulate their sensitivity to environmental stimuli . | [
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"com... | 2013 | A Protein Turnover Signaling Motif Controls the Stimulus-Sensitivity of Stress Response Pathways |
Northeast Africa has a long history of human habitation , with fossil-finds from the earliest anatomically modern humans , and housing ancient civilizations . The region is also the gate-way out of Africa , as well as a portal for migration into Africa from Eurasia via the Middle East and the Arabian Peninsula . We investigate the population history of northeast Africa by genotyping ~3 . 9 million SNPs in 221 individuals from 18 populations sampled in Sudan and South Sudan and combine this data with published genome-wide data from surrounding areas . We find a strong genetic divide between the populations from the northeastern parts of the region ( Nubians , central Arab populations , and the Beja ) and populations towards the west and south ( Nilotes , Darfur and Kordofan populations ) . This differentiation is mainly caused by a large Eurasian ancestry component of the northeast populations likely driven by migration of Middle Eastern groups followed by admixture that affected the local populations in a north-to-south succession of events . Genetic evidence points to an early admixture event in the Nubians , concurrent with historical contact between North Sudanese and Arab groups . We estimate the admixture in current-day Sudanese Arab populations to about 700 years ago , coinciding with the fall of Dongola in 1315/1316 AD , a wave of admixture that reached the Darfurian/Kordofanian populations some 400–200 years ago . In contrast to the northeastern populations , the current-day Nilotic populations from the south of the region display little or no admixture from Eurasian groups indicating long-term isolation and population continuity in these areas of northeast Africa .
The Nile River Valley and northeast Africa have experienced a long history of human habitation . The region harbored some of the most ancient civilizations in the world and contains fossil finds of the earliest anatomically modern humans [1–3] . Agriculture has a long history in the Nile River valley , and crops of potential Near Eastern origin as well as sorghum found in Sudan have been dated to 3000BC [4] . Livestock was introduced into northeast African and Sudan in the 5th millennium BC ( likely from the North ) and pastoralism spread rapidly across sedentary agriculturalists who lived along the Nile as well as to the nomadic populations inhabiting the drier surrounding regions [4] . Following the introduction of agriculture and pastoralism , settlements started growing , which led to the forming of political units . In Nubia ( roughly the northern parts of current-day Sudan ) , the Kingdom of Kerma emerged around 3000 BC . Nubia has successively been at the center of several ensuing states , and the historical records show interactions with neighboring states through trade and confrontation , possibly reaching back to predynastic times [4–6] . Modern-day Sudan and South Sudan cover parts of the Nile River and the joining of the Blue and the White Nile , areas that link the northern part of the Nile Valley and North Africa with East Africa . Today , these areas display great linguistic diversity , with Sudan and South Sudan housing 137 living languages [7] , which belong to three of the four linguistic macro-families found on the African continent: Afro-Asiatic , Nilo-Saharan , and Niger-Congo . Previous genetic studies focusing on human history in Sudan and South Sudan have used uniparentally inherited markers [8–10] , low density polymorphic autosomal markers [11–17] , or were only covering a limited number of populations [18] . These studies have found substantial genetic differentiation in northeast Africa and indications of migration and admixture . For instance , Tishkoff , Reed [18] investigated more than one hundred African populations using some 800 microsatellites , including six populations from Sudan and South Sudan and showed that eastern Africa harbors substantial amounts of genetic diversity . However , wide ranges of populations , representative of all the main linguistic groupings , in and around Sudan and South Sudan have not been studied in order to decipher population history using high-resolution genome-wide data . In this study we genotyped some 3 . 9 million SNPs in 221 individuals from a total of 18 populations from South Sudan and Sudan to investigate population structure and admixture patterns , which we use to reconstruct the genetic history of this region of northeast Africa . We find a genetic differentiation within the Sudanese and South Sudanese groups that is driven by Eurasian admixture , which may have followed the Nile southward and coincides with the time of the Arab conquest .
Among the populations from Sudan and South Sudan , the four Nilotic populations formed a notable population cluster based on the genome-wide data . They were genetically uniform with little genetic differentiation among themselves ( pairwise FST values ≤ 0 . 0028 , Fig 1B , S7A Fig ) . In the ADMIXTURE analyses , the Nilotic populations retained a specific ancestry component ( blue ) , which is shared with other northeast African groups at low values of K , where most of the Sudanese populations have a substantial fraction of this ancestry ( Figs 2 and S1–S6 ) . Even at higher values of K , the Nilotes formed their own ancestry component , a component found in modest proportions in populations from Sudan and South Sudan . The Nilotes also appeared as one of the most common source populations for other Sudanese and South Sudanese populations ( Figs 2 and 3A ) . We furthermore compare the affinity between the Nilotes and Neolithic European farmers ( represented by an individual from the Linearbandkeramik ( LBK ) ) , using the 4 , 500 year old Mota individual from Ethiopia to represent an East African group that has not been affected by Eurasian admixture in the last 4 , 500 years [25] . Testing the population tree D ( Ju|’hoansi , LBK;Mota , Nilote ) shows no support for an affinity between Neolithic European farmers and Nilotes ( S8A Fig ) , as can also be seen from the f4-ratio estimates of Eurasian ancestry in Nilotes ( Fig 3B , S9A Fig ) . Previous studies of uniparental or few markers also found little support for incoming gene-flow to the Nilotic populations [9 , 11 , 15 , 25] , and , taken together with our results , Nilotic populations appear to have remained relatively isolated over time . The Nilotes are predominantly pastoralist populations , they live in Uganda , Ethiopia , Kenya , Tanzania , and are the most prominent ethnicity in South Sudan . They are traditionally strongly endogamic which could account for low levels of admixture . In terms of specific Nilotic populations , the f3 test showed no significant signal of gene flow with external populations for the Nuer and Baria ( Fig 3A ) , however , we detected indications of external gene flow from West Africa ( YRI ) into Dinka ( f3 = -0 . 001038 , Z = -5 . 283 ) and TSI to Shilluk ( f3 = -0 . 002565 , Z = -7 . 951 , S2 Table ) . These observations taken together , suggest long term isolation and continuity between the current-day Nilotic populations and the ancestral populations of northeast Africa . All the investigated Sudanese and South Sudanese populations , except the Hausa , showed almost no West African ( orange in Fig 2 ) component or , at a higher K , Bantu component ( Fig 2 , yellow in S3 Fig ) in the ADMIXTURE analysis . The Bantu migration that swept over most of sub-Saharan Africa 3–4 thousand years ago ( kya ) [26] did not cause massive admixture in northeast Africa , contrary to what has been found in many other sub-Saharan African regions , e . g . East Africa and southern Africa [18 , 27 , 28] . This expansion seems to have passed south of the Sudanese Nilotic populations in an eastward direction from West-Africa . The strongly endogamic Nilotic populations could have acted as a migration barrier for northeast Africa preventing admixture with Bantu-speaking groups of West African origin during the migrations of the Bantu expansion , potentially in addition to climatic barriers connected to the agriculture of the Bantu-speakers . Although there are a few Bantu speaking populations in South Sudan [29] that likely migrated during the Bantu expansion , they do not appear to have mixed much with local Nilotic groups . The Afro-Asiatic speaking Hausa population from northeastern Sudan was the exception to the observation of little West African affinity in Sudan and South Sudan ( Fig 1 ) . The Hausa , originally of western Africa , comprises the largest West African population that have migrated to Sudan during the past 300 years , traditionally employed mainly in agricultural activities [30 , 31] . In S11 Fig they cluster in between the West African Yoruba and Nzime , and the Darfurian/Kordofanian and Nilotic populations . This finding is consistent with previous analyses [18 , 30 , 32 , 33] . Even though the ADMIXTURE analysis showed some level of local Nilotic genetic material ( ~30% at K11 and higher , Fig 2 , S3 Fig ) , the f3 statistics did not provide significant evidence for admixture with Darfurian/Kordofanian and Nilotic populations . Using LD decay patterns [34] , we estimate an admixture event in the Hausa to 31 . 2 ± 9 . 3 generations ago ( Z = 3 . 34683 ) from a Eurasian source . This is before the historically documented settlement of the Hausa in the Sudan and it is still unknown if the Hausa populations of West Africa also show this admixture signal . These observations point to that the Hausa originated in West Africa and migrated recently to Sudan , where they have stayed relatively isolated from neighboring populations . The Nubians inhabit the Nile valley in the arid desert of northern Sudan and speak Eastern Sudanic languages of the Nilo-Saharan linguistic family that are close to the languages spoken by Nilotic populations ( Table 1 , Fig 1A ) . The Nubian populations have a long history in the region , dating back to dynastic Egypt [5] . They showed little genetic differentiation among individuals and groups , with a maximum ( across all pairwise comparisons ) pairwise FST ( Weir and Cockerham’s estimator ) of 0 . 004513 between the Mahas and the Halfawieen ( Fig 1B , S7A Fig ) . The FST values to the surrounding Arabic and Beja populations were also low , which hints at gene-flow or shared ancestry with the neighboring populations . Even though the Nubians and the Nilotes are linguistically closer to each other than to the Afro-Asiatic groups , the Nubians showed the greatest genetic differentiation ( FST between 0 . 02 and 0 . 04 ) to the Nilotes ( Fig 1 , S7A Fig ) . To investigate whether this signal of genetic differentiation is driven by the Eurasian admixture into the Nubians ( as seen in Fig 2 ) , we created pseudo-‘unadmixed’ ( in terms of not having Eurasian admixture ) allele frequencies ( see SI ) and calculated Wright’s FST , which showed that an ‘unadmixed’ Nubian gene-pool is genetically similar to Nilotes ( S7B Fig ) . The strongest signal of admixture into Nubian populations came from Eurasian populations ( S10 Fig , S2 Table ) and was likely quite extensive: 39 . 41%-47 . 73% ( f4-ratio , Z-scores between 22 . 8 and 26 . 7 Fig 3B , S9 Fig ) . Interestingly , the Nubians showed the highest level of allelic richness , number of private alleles and shared private alleles ( ADZE , between Danagla and Halfawieen , S12 Fig ) among all Sudanese and South Sudanese groups . This observation together with a smaller total length of runs of homozygosity , between lengths of 0 . 5–1 kilobases , points to substantial admixture in Nubians ( Fig 4 ) . Hence , the Nubians can be seen as a group with substantial genetic material relating to Nilotes that later have received much gene-flow from Eurasians ( likely Middle Eastern ) and from East Africans ( Fig 2 ) . All the populations that inhabit the Northeast of Sudan today , including the Nubian , Arab , and Beja groups showed admixture with Eurasian sources and the admixture fractions were very similar . The admixture component in the northeastern groups cluster with the greater European and Middle Eastern group assuming few clusters , and for greater number of assumed clusters , when a predominantly Middle Eastern cluster emerged , the admixture in northeastern Sudan connected to the Middle East ( ADMIXTURE , Fig 2 , f3 , S10 Fig ) . According to historical and linguistic studies , and recent Y-chromosome data it has been suggested that the northeastern Sudanese populations especially Nubians and Beja were strongly affected by Eurasian migrations since the introduction of Islam from the Arabian Peninsula through Egypt and the Red Sea starting around 651 A . D [9 , 35] . Assuming that the Nubian population is a mixture of an incoming Eurasian ( TSI is used as a proxy ) group and a resident group that is genetically similar to the current day Nilotes ( Nuer is used as a proxy ) , first contact is dated using patterns of LD-decay [34] to roughly 56 generations ago for the Danagla ( 54 . 45 ± 10 . 34 , Z = 5 . 26437 ) and the Mahas ( 58 . 35 ± 12 . 2 , Z = 4 . 78402 ) ; the Halfawieen have received Eurasian admixture later , around 19 generations ago ( 19 . 31 ± 3 . 81 , Z = 5 . 05949 , S7 Table , Fig 3C ) . Assuming a generation time of 30 years , the admixture dates for Danagla and Mahas predate the Arab expansion in the 7th century , and may suggest that the migrations and admixture predate Islamic conquest . However , the confidence intervals overlap with the 7th century , and these admixture estimates largely coincide with the Arab expansion into the northeast of Sudan . It is known from historic sources that Arabic groups encountered the Nubians first in the 7th century , and were held back from advancing further into the Sahel until the fall of Dongola in 1315/1316AD [36] and the collapse of the Kingdom of Makuria . This is consistent with the later date for the admixture into Halfawieen and the Arabic populations of Sudan . Previous studies [37 , 38] have found a similar pattern for populations of Maghreb , where admixture times coincide with the time of the historically documented Arab conquest . The Eurasian migrations also appear to have expanded and migrated into northeast Africa where they admixed with local populations giving rise to Arabic-speaking groups ( Shaigia , Gaalien and Bataheen ) that today inhabit areas of central Sudan ( Fig 2 ) . We further tested the source of admixture into the central Sudan Semitic speaking Arab groups ( Shaigia , Gaalien and Bataheen ) using ancient samples from Europe ( LBK ) and East Africa ( Mota ) and the population history of D ( Ju|’hoansi , LBK;Mota , X ) , ( where the Ju|’hoansi is an outgroup Khoe-San population from Namibia ) , which suggested Eurasian admixture into central Sudan Arab groups ( see SI , S8A Fig ) . This migration and admixture occurred later than the events that brought Eurasian gene-flow into the Nubians ( S3 Table , Fig 3C ) . Interestingly , when we overlay the Eurasian genetic component onto a geographic map , it appears as if the expansion could have spread along the Blue Nile ( Fig 3B and 3C ) , showing a gradient of higher to lower admixture proportion and older to younger admixture dates from northern Sudan to South Sudan . The Eurasian admixture proportion in the Arab populations is high , ranging between ~40%–48% ( SI , Fig 3B and S9A Fig ) . The presence of a northeast African genetic signature similar to Nilotic populations and the recent admixture signal from Eurasia indicates that the populations in central Sudan that self-identify as Arab were originally a local northeast African population ( similar to the Nubians and the Beja ) that mixed with a Eurasian population during the Arab expansion , or possibly earlier . However , the mixed groups kept the language and culture of the incoming migrants . Beja groups , who generally reside in eastern areas of Sudan close to the sea , show high non-African admixture in all tests ( Figs 2 and 3B , S1–S6 and S8–S10 Figs ) . The Beni Amer also showed a strong admixture signal with a Eurasian population as well as a shared ancestry component with the Somali population ( pink component in Fig 2 ) , which suggest admixture with the East African Cushitic-speaking populations , perhaps as a result of migration along the coast . We dated the admixture of the Beja populations with the Cushitic-speaking Somalian population [39] , and the admixture dates go far back in time , about 59 generations ago for the Hadendowa and about 68–75 generations for the Beni Amer ( S3 and S4 Tables ) . The large proportion of the East African ( pink in Fig 2 ) component is therefore not a result of recent admixture of East Africans into the Beni Amer . Admixture of non-Africans into the Beni Amer was also dated to an early event about 107 . 7 ± 24 . 4 generations ago ( Z = 4 . 41711 ) and a younger event , 34 . 2 generations ago ( ± 9 . 6 , Z-score = 3 . 55532 Fig 3C , S7 Table ) suggesting an early migration from Eurasian into these coastal African populations , possibly across the sea . However , these old admixture events into the Beni Amer could be driven by admixture from the Cushitic-speaking populations of the Horn of Africa , which themselves have received 30–50% non-African ancestry about 100 generations ago , or 3kya [22 , 40] . The Copts represent a well-known ethnic group , generally practicing Christianity , which migrated from Egypt to Sudan around 200 years ago , settling in a predominately Muslim region . The ADMIXTURE analyses and the PCA displayed the genetic affinity of the Copts to the Egyptian population ( Fig 2 , S1–S6 , S11 and S13–S16 Figs ) . Assuming few clusters , the Copts appeared admixed between Near Eastern/European populations and northeastern Sudanese and look similar in their genetic profile to the Egyptians . Assuming greater number of clusters ( K≥18 ) , the Copts formed their own separate ancestry component that was shared with Egyptians but can also be found in Arab populations ( Fig 2 ) . This behavior in the admixture analyses is consistent with shared ancestry between Copts and Egyptians and/or additional genetic drift in the Copts [41 , 42] . The Copts and the Egyptians have a historically documented shared history . We further investigate the relationships of the Copts and the Egyptians to other groups . All population histories tested in every possible combination of either Copts or Egyptians , and Bedouin and Nuer , with Ju|’hoansi as outgroup to the others were rejected ( D-statistic , |Z|>5 . 5 ) , which points to a non-tree-like history of the Copts and Egyptians . Our results instead indicate that they are an admixed population of at least one sub-Saharan population and one Eurasian population , but had subsequent admixture with additional groups . The population tree that has the most support finds the Nuer ( Nilotic ) as an outgroup to the Bedouin and Copts ( D ( Ju|’hoansi , Nuer;Bedouin , Copts ) = 0 . 0103 , Z = 5 . 550 ) . The Copts were estimated to be of 69 . 54% ± 2 . 57 European ancestry and the Egyptians of 70 . 65% ± 2 . 47 European ancestry ( f4-ratio , Fig 3B , S9A Fig ) . The Egyptians and Copts showed low levels of genetic differentiation ( FST = 0 . 00236 , Fig 1B ) , lower levels of genetic diversity ( S17 Fig ) and greater levels of RoH ( Fig 4 ) compared to other northeast African groups , including Arab and Middle Eastern groups that share ancestry with the Copts and Egyptians ( Fig 2 ) [41] . A formal test ( D ( Ju|’hoansi , X;Egypt , Copt ) ) , did not find significant admixture into the Egyptians from other tested groups ( X ) as the explanation of the ( admittedly low level of ) differentiation between the two groups , and the Copts and Egyptians displayed similar levels of European or Middle Eastern ancestry ( S8A and S8B Fig ) . Taken together , these results point to that the Copts and the Egyptians have a common history linked to smaller population sizes , and that the Copts have remained relatively isolated since the arrival to Sudan with only low levels of admixture with local northeastern Sudanese groups ( S8B Fig ) . The Messiria , a Semitic speaking Arab population , are nomads who inhabit a wide area in the Darfur and Kordofan regions . They were genetically closer to other Darfurian/Kordofanian populations than to the Arab populations of central Sudan ( Fig 2 , S3 Fig ) . The Messiria were clearly genetically differentiated from the Arab populations of northeastern Sudan ( FST values of 0 . 0083–0 . 0229 , compared to 0 . 0–0 . 0056 to Darfurian/Kordofanian populations , Fig 1B ) while the other Arab populations of central Sudan were genetically closer to each other ( FST 0–0 . 0052 , Fig 1B ) . The Messiria showed a significant signal of admixture between Nilotes ( Nuer ) and Eurasians ( TSI ) , but the signal was stronger for other Arabs ( S8 and S10 Figs ) . The Eurasian fraction in the Messiria was about 15% compared to the ( 40%-48% ) in the northeastern Arabic populations ( Fig 3B ) . The admixture was dated to about 7 generations ago ( S3 Table , Fig 3C ) . This points to the Messiria being a local Kordofanian population that has acquired the language and culture from an incoming Semitic population that they mixed with some 200 years ago ( 190–244 years ago assuming a generation time of 30 years , Z = 3 . 19695 ) . The Gemar , a Nilo-Saharan speaking population of Darfur and Kordofan also showed signals of Eurasian admixture ( f3 , S10 Fig ) estimated to ~13% ( Fig 3B , S9A Fig ) . This admixture event was dated at 13 . 36 ± 2 . 99 generations ago ( Malder , S7 Table , Fig 3C ) . However , a proposed population tree of LBK as an outgroup to Mota and Gemar was supported ( S8 Fig ) , suggesting that the Gemar traces much of their ancestry back to ancestral groups of east Africa . The Zaghawa and the Nuba showed very little Eurasian admixture ( Figs 1 , 2 , S8 and S10 ) and they showed low genetic differentiation to the Gemar and the Messiria as well as to the Nilotic populations suggesting common ancestry of Nilotic , Darfurian and Kordofanian populations ( Figs 1B and 2 , S7 Fig ) .
We have shown that there has been long-term migration into Sudan , moving in a southward direction possibly along the Nile and the Blue Nile . From historic documents , we know that the ancient Egyptians were in contact with the ancient Nubians that inhabited the Nile area in the north of modern-day Sudan . Our study suggests that the later migration followed along the Nile , likely being held up by the Nubians until the fall of the Kingdom of Makuria in the 14th Century [4] . Following that historic event , the Arab expansion spread further southward , which can be seen in a succession of admixture events that occur more recent in time as one travels south . Many populations in Sudan that self-identity as Arab , displayed a population history of local Sudanese populations that have admixed with incoming Eurasian populations , and adopted the language and culture of the incoming migrants . In fact most populations from northeast Sudan ( Nubian , Arab and Beja groups ) seem to be a mixture of Middle Eastern and local northeast African genetic components , although only the Arab groups shifted to the Semitic languages . Cultural and linguistic replacement following the Arab conquest has been described previously in populations of the Maghreb [37 , 38 , 43] . The Eurasian admixture had less impact on the populations of western Sudan and South Sudan . The Darfurian and Kordofanian populations showed overall less admixture from non-African groups than the northeastern populations ( and the limited admixture that does exist is more recent in time ) . The Nilotic populations have stayed largely un-admixed , which appears to be the case in Ethiopia too , where a similar observation has been made for the Gumuz [23 , 44] , an Ethiopian Nilotic population that is genetically similar to South Sudan Nilotes . Northeast African Nilotes showed some distinction from an ancient Ethiopian individual ( Mota , found in the Mota Cave in the southern Ethiopian highlands ) , which suggests population structure between northeast and eastern Africa already 4 , 500 years ago . The modern-day Nilotic groups are likely direct descendants of past populations living in northeast Africa many thousands of years ago .
The DNA samples were chosen from a set of individuals that had been typed with 15 forensic microsatellites [11] . Blood samples were collected by Dr . H . Babiker with a permission from the Forensic DNA lab in Khartoum , Sudan , in 2009 . The research purpose of population genomic investigations was described to each participant , and an informed written and oral consent was obtained from all participants . The samples were prepared for analysis using Whatman FTA Protocol BD09 and slightly adjusted Whatman FTA Protocol BD01 ( SI ) . The samples were amplified using Illustra Genomiphi V2 DNA Amplification Kit following the protocol from Pinard , de Winter [45] . Genotyping was performed on an Illumina Human Omni5MExome SNP-array . Data filtering was performed using PLINK v1 . 07 and custom scripts ( S18 and S19 Figs ) . Datasets of different sizes were created to include neighboring and other relevant populations , weighing the amount of SNPs against the number of reference populations . Dataset 1 contains the novel populations and the Nzime [24] ( ~3 . 5 Million SNPs ) , dataset 2 contains the populations of dataset 1 and populations from [19 , 20 , 23] ( 1 . 4 Million SNPs ) , and dataset 3 containing dataset 2 and populations from [22 , 46] ( ~220 thousand SNPS ) ( S17 Fig ) . Due to the risk of allelic drop-out ( for some individuals ) caused by imperfect whole genome amplification , which can result in the appearance of hemizygous stretches ( SI ) , we also created a ‘haploidized’ dataset by randomly picking one allele at each position ( if variable ) . This ‘haploidized’ dataset will avoid underestimating diversity in population samples even in the presence of some level of allelic drop-out ( SI-Summary statistics ) . All results performed on diploid datasets were verified by repeating the analyses with the ‘haploidized datasets’ ( S1–S6 , S13–S17 and S20–S22 Figs ) . The datasets were furthermore merged with the Ju|’hoansi population from Namibia ( to act as an outgroup ) , and two ancient individuals , an ancient Ethiopian ( Mota ) , to provide an African sample with no European admixture [25] , and a European Linearbandkeramik individual ( LBK ) as a European reference of Neolithic times [47] ( S9 , S23 and S24 Figs ) . We computed genetic diversity within populations ( Heterozygosity , runs of homozygosity ) and between populations ( Weir and Cockerham’s estimator of FST , Wright’s FST ) , using plink v1 . 07 , v1 . 9 [48 , 49] and in-house scripts . A Mantel test was performed to calculate the correlation of genetic to linguistic and geographic distances ( S25 Fig ) . Measurements of allelic richness , number of private alleles and uniquely shared alleles were computed using ADZE [50] on allelic and haplotype-based data . S27 Fig shows that the pattern is not driven by ascertainment bias . Patterns of population structure was investigated using ADMIXTURE [51] , CLUMPP ( v . 1 . 1 . 2 , [52] and distruct v . 1 . 1 [53] . Formal tests of admixture ( f3 test , D-statistic ) were performed using admixtools [39] . f3 ( Nuer , TSI;X ) was used to estimate non-African admixture and f3 ( X , Mota;Ju|’hoansi ) was used to estimate ancestral East African affinity . D-statistics were calculated as D ( Ju|’hoansi , LBK; Mota , X ) . The time in generations of admixture was calculated using a haploidized version of the data ( see SI ) with Malder [34] and Rolloff [39] and converted to calendar years assuming 30 years/generation . An ancient individual has shown widespread back admixture into East Africa [25] from Eurasia . To formally quantify the extend of the Eurasian admixture proportion we performed f4-ratios on dat2a , calculated as f4 ( CHB , GBR;X , LBK ) /f4 ( CHB , GBR;Mota , LBK ) similar to Gallego Llorente , Jones [25] . The ancient Ethiopian ( Mota ) [25] was used as an ancestral unadmixed ( in terms of no Eurasian admixture ) East African sample and the LBK individual [47] to substitute for an ancient Eurasian population . | Northeast Africa has geographic and historical links to Eurasia via the Middle East and the Arabian Peninsula , but the demographic history of the region itself has been more elusive . We investigate genomic diversity of northeast African populations and found a clear bimodal distribution of variation , correlated with geography , and likely driven by Eurasian admixture in the wake of migrations along the Nile . This admixture process largely coincides with the time of the Arab conquest , spreading in a southbound direction along the Nile and the Blue Nile . Nilotic populations occupying the region around the White Nile show long-term continuity , genetic isolation and genetic links to ancestral East African people . Compared to current times , groups that are ancestral to the current-day Nilotes likely inhabited a larger area of northeast Africa prior to the migration from the Middle East as their ancestry component can still be found in a large area . Our findings reveal the genetic history of Sudanese and South Sudanese people , broaden our knowledge on demographic history of humans , and quantify the impact of large-scale historic migration events in northeast Africa . | [
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"ge... | 2017 | Northeast African genomic variation shaped by the continuity of indigenous groups and Eurasian migrations |
This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3-D representations and animated transitions . Please note that a Web plugin is required to access this enhanced functionality . Instructions for the installation and use of the web plugin are available in Text S1 .
Cyclophilins are peptidyl-prolyl isomerases ( PPIases: EC 5 . 2 . 1 . 8 ) and are characterized by their ability to catalyze the interconversion of cis and trans isomers of proline [1] . Cyclophilins and the structurally unrelated FK506 binding proteins were initially described as the in vivo receptors for the natural products cyclosporin , FK506/tacrolimus , and rapamycin/sirolimus [2] , [3] . The immunosuppressant effect of these natural products , while revolutionizing the field of organ transplantation , were eventually determined to be unrelated to the inherent isomerase activity of the PPIases [4] . However , these small molecules bind to the active site of PPIases with high affinity and are capable of blocking isomerase activity against peptide substrates , making them a useful tool for biochemical and cellular assays of PPIase function [5] . The physiological function of cyclophilin PPIase activity has been for many years described as a chaperone or foldase [6] , [7] . Certainly this functionality is well documented , for instance in the maturation of steroid receptor complexes ( along with Hsp90/Hsc70 ) [8] or in the interplay between NinaA and rhodopsin in Drosophila [9] . In addition , the isomerase activity of at least two cyclophilin isoforms is crucial for host∶virus interactions and for viral maturation processes , and this activity seems to be mediated through the PPIase active site [10] , [11] . However , it has become increasingly apparent that isomerization of proline is not the sole function of the PPIases , with the first example being the nonimmunophilin Pin1 , a PPIase of the parvulin type . Pin1 is able to catalyze isomerization of the proline bond for target substrates only when a serine or threonine preceding the target proline is phosphorylated [12] . This phosphorylation-dependent isomerization places Pin1 directly in the context of traditional signal transduction pathways , including those involved in cell proliferation and tumorigenesis [13] . The identification of Pin1 substrates revitalized the search for additional functions of the immunophilin-type PPIases; although there is no example of phosphorylation-dependent isomerization for either FK506 binding proteins or for cyclophilins , a subset of substrates for these types of PPIases are certainly also dependent on nonchaperone functions . PPIA , along with classical functions in the chaperone-mediated processes outlined above , interacts with the receptor tyrosine kinase Itk post-translationally and modulates the activity state of the already folded protein in vivo [14] . PPIA also is known to modulate HIV infectivity by interacting with a proline-containing sequence in the capsid protein Gag , also in the context of a well-folded protein module [15] . More recently , PPIA has been shown to interact with CD147 in a manner that is proline-dependent and mediated through the active site of the isomerase , but does not contribute to CD147 folding per se [16] , [17] . In addition , both PPIA and the highly similar PPIB have been shown to interact with NS5B , an RNA-dependent RNA polymerase necessary for hepatitis C viral replication [10] , [18] . The three other single-domain PPIases—which encode only the PPIase domain and , in the case of PPIB and PPIC , a signal sequence—and the 13 multidomain PPIases are less well characterized; most of what is known for these cyclophilins centers not on the isomerase active site but on distinct regions with no known enzymatic function . For instance , the single domain PPIase PPIH ( SnuCyp20 ) participates in the spliceosome through interactions with the 60K component of the tri-snRNP , also known as hPRP4; however , the co-crystal structure of PPIH with a peptide derived from hPRP4 showed that this interaction was mediated exclusively through a face opposite that of the active site [19] . A similar situation was found in another spliceosomal cyclophilin , PPIL1 , which interacts with the protein SKIP; NMR data indicate that the chemical shift perturbations in PPIL1 upon SKIP binding did not involve residues involved in proline turnover , and that binding to SKIP occurred even when PPIL1 was bound to cyclosporin A [20] . Finally , PPIE has an RNA-recognition motif ( RRM ) and has been reported to have RNA-specific isomerase activity [21] . Cyclophilins have been implicated in diverse signaling pathways , including mitochondrial apoptosis [22] , [23] , RNA splicing [24] , [25] , and adaptive immunity [26] . However , the proteins that are substrates for cyclophilins in these pathways have not been identified . Moreover , even basic questions concerning the biochemical properties of these enzymes have not been fully addressed . For instance , of the 17 annotated human cyclophilins only seven have been tested for isomerase activity or for the ability to bind cyclosporin [20] , [27]–[32] . In vitro techniques aimed at delineating substrate specificity for the canonical family member PPIA have been only moderately successful; mutational analysis of short proline-containing motifs has found that PPIA is a very broadly specific enzyme [33] , [34] , despite the relatively small number of in vivo–validated substrates . In the case of phage display , the optimized binding sequence does not correspond to the substrate determinants that have been found in vivo for this isoform , and this sort of randomized screening has not been accomplished for any of the less ubiquitous isoforms [35] . Generally , the issue of in vitro versus in vivo substrate selectivity for the isomerases is problematic: for a given isomerase for which there is no knowledge of in vitro substrate specificity , it is difficult to find and validate in vivo substrates . Even for the isoforms that have been tested in vitro for their substrate preferences , there has been little or no correlation with later discovery of in vivo substrate sequences . Clues in some cases may be derived from the identity of other domains expressed in tandem with the cyclophilin domain; for instance , the RRM domain previously mentioned implies an RNA targeting function for PPIE and PPIL4 , and likewise the U-box motif of PPIL2 implies involvement in ubiquitin conjugation pathways [36] . The WD-40 repeat of PPWD1 most likely confers a protein∶protein interaction function , as this is its main function in other systems; the same holds true for the TPR motifs of RanBP2 and PPID . However , useful comparisons of in vitro activity with in vivo physiology must wait until the cyclophilin family is more fully characterized with data from either or both lines of research . In this study , we have screened 15 of the 17 human cyclophilins for their ability to catalyze proline isomerization against standard tetrapeptide proline motifs . We also have determined binding affinities for each cyclophilin family member for the natural product cyclosporin , and have determined the structures of seven PPIase domains to high resolution using X-ray crystallography . These extensive studies reveal interesting biochemical and enzymatic diversity that is consistent with structural data . The structures also provide an opportunity to assess the cyclophilin family for regions of diversity among all family members . In addition , in silico methods based on a family-wide structural analysis were used to characterize a molecular feature contiguous with the canonical active site that may account for substrate specificity . This new description of the cyclophilin peptidyl-prolyl isomerase family highlights regions of diversity that may prove crucial for future physiologically relevant substrate identification and chemical probe development .
In order to elucidate the function of residues in the extended active site of the PPIase domain of the human cyclophilins , we probed the binding and catalytic function of these domains against either substrate or small-molecule inhibitors ( see Figure 1 and Datapack S1 for graphical and tabular depictions of the active site ) . Three assays were utilized to explore these functions . In the first assay , changes in thermal stability were used to assess cyclosporin binding . This assay has been shown in several studies to be a reliable readout of small molecule binding for kinase and other enzyme families [37] , [38] . Cyclosporin A ( CsA ) and the derivatives cyclosporin C , D , and H were screened against all PPIase domains except for PPIL3 and PPIL4 , for which all constructs were insoluble or unstable in our hands ( Table 1 ) . Because of the inherent thermal stability characteristics of PPID and RanBP2 , this technique was unable to distinguish between apo and cyclosporin-bound forms of those domains . However , data were collected for the remaining 13 isoforms , and binding to CsA , CsC , or CsD was noted for six isoforms published previously ( PPIA , PPIB , PPIC , PPIE , PPIL1 , and PPWD1 ) [20] , [27]–[30] , [32] . In addition , binding of CsA or derivatives was seen for PPIF , PPIG , PPIH , and NKTR . In the case of PPIG and PPIH , this explains previous data describing cyclosporin binding to the tri-snRNP complex that contains PPIH [25] and verifies the finding from a homolog that PPIG is capable of binding cyclosporin [39] . No binding was detected for PPIL2 , PPIL6 , or SDCCAG-10 , making these , to our knowledge , the first set of human cyclophilins that have been found incompetent to ligate cyclosporin ( Table 1 ) . In order to quantify cyclosporin affinity we undertook isothermal calorimetry ( ITC ) analysis of all soluble cyclophilin isoforms; we found that a complete family-wide screen led to a range of binding affinities for CsA , expressed as the dissociation constant Kd , from low nanomolar to near micromolar values . We were also able to confirm that under the experimental conditions we tested there was no evidence of CsA binding to PPIL2 , PPIL6 , or SDCCAG-10 ( Table 1 ) . A two-dimensional NMR experiment ( 1H/1H TOCSY ) described previously [30] , [40] , the only in vitro protease-free method available to probe for both substrate binding and catalytic activity of cyclophilins , was used to assess the commercially available tetrapeptides of sequence AAPF , AFPF , and AGPF [34] . The NMR-based assay confers the advantage of being a highly sensitive assay for the detection of substrate binding in addition to catalytic activity; the standard chymotrypsin-coupled assay can detect only catalysis and does not provide any direct measurement of binding [40]–[42] . A number of articles have documented the drawbacks of the protease-coupled assay [33] , [42]–[44] , an obvious example being that the addition of protease to the reaction mixture in the chymotrypsin-coupled assay requires additional testing to ensure that the enzymes and substrates being screened are not proteolytic targets [43] . Additionally , the NMR-based assay does not require substrates to contain chemical modifications , and can be used to measure effects of amino acid substitutions at regions distal to the target proline not measurable by other methods [42] . We detected binding and turnover for at least one of the tetrapeptide substrates tested for PPIA , PPIB , PPIC , PPID , PPIE , PPIF , PPIG , PPIH , PPIL1 , PPWD1 , and NKTR ( Table 1; see Figure S1 for representative data showing binding and activity ) . This correlated well with previously determined activities [2] , [20] , [21] , [28] , [30] , [45] , [46] , and established activity measurements for PPIF , PPIG , and NKTR . For all isoforms tested there was a strict correlation between the ability to bind cyclosporin and activity against the tetrapeptide substrates ( Table 1 ) . In order to understand the molecular basis of these results , we sought structural coverage of the entire human cyclophilin enzymatic class . We determined crystal structures of seven human PPIase domains—PPIC , PPIE , PPIG , PPWD1 , PPIL2 , NKTR , and SDCCAG-10 ( Figure 2 and Datapack S1 ) . There are six previously determined structures ( PPIA , PPIB , PPIF , PPIH , PPIL1 , and PPIL3 ) . This leaves four structurally uncharacterized human PPIase domains of cyclophilins ( PPID , PPIL4 , PPIL6 , and RanBP2 ) ( Figure 2 and Table S1 ) . However , if we include the highly homologous bovine structure for PPID ( three amino acid substitutions compared to human ) and compare the set of 14 isoforms for which we have experimental data , we find that they have very similar secondary structural elements ( Figure 2 ) . We can therefore use this dataset to provide excellent homology models for the remaining three isoforms ( PPIL4 , PPIL6 , and the PPIase domain of RanBP2 ) ( Figure 2 ) . Models for these three isoforms were generated using the Phyre algorithm [47] , and for all further discussions of the cyclophilin family the structures of all 17 PPIase domains will be considered . All cyclophilins share a common fold architecture consisting of eight antiparallel β sheets and two α-helices that pack against the sheets ( Figures 1 and 2 ) . In addition , there is a short α-helical turn containing the active site residue Trp121 found in the β6-β7 loop region ( Figure 1; all residue identities and numbers correspond to PPIA except where noted ) . RMSD across all atoms for all PPIase domains is less than 2 Å , and sequence identity over the same region varies from 61% to 86% ( Figures 1 , S2 , and S3 ) . The most divergent structures in this set are PPIL1 , which is an NMR-derived structure ( RMSD 1 . 7 Å ) , and the previously described PPWD1 ( RMSD 1 . 4 Å ) [30] . Excepting PPIL1 and PPWD1 , the remaining experimental PPIase domains align over all atoms with RMSD ranging from 0 . 4 Å to 1 . 0 Å ( see Figure 2 and also Figure S5 for a more detailed structural alignment ) . An overlay of the Phyre-derived modeled structures leads to an RMSD over all atoms of 1 Å or less compared to PPIA . The active site of the cyclophilin family includes the invariant catalytic arginine ( Arg55 ) and a highly conserved mixture of hydrophobic , aromatic , and polar residues including Phe60 , Met61 , Gln63 , Ala101 , Phe113 , Trp121 , Leu122 , and His126 [48]–[50] . All of these sidechains contribute to an extensive binding surface along one face of the PPIase domain measuring roughly 10 Å along the Arg55–His126 axis and 15 Å along the Trp121–Ala101 axis ( Figure 1 ) . Many of these residues are well conserved across all PPIase domains and are thought to serve functions in either catalysis or substrate/inhibitor binding [48] , [50] , [51] ( Figures 2 , S2 , and S3 ) . Although there are sites of minor diversity among the family members at the Phe60 , Met61 , and His126 positions , the most striking correlation between cyclosporin binding , tetrapeptide identity , and active site residues is found at the Trp121 position . Our results clearly show that a tryptophan ( as found in PPIA , PPIB , PPIC , PPIE , PPIF , PPIH , PPIL1 , and PPWD1 ) or histidine ( as found in PPID , PPIG , PPIL3 , RANBP2 , and NKTR ) at this position is permissive for cyclosporin binding whilst other naturally occurring residues at this position ( tyrosine in PPIL2 , PPIL4 , and PPIL6 , and glutamic acid in SDCCAG10 ) abrogate cyclosporin binding under our experimental conditions ( Table 1 and Figure 3 ) . It has been shown that mutating Trp121 in PPIA to alanine or phenylalanine has a negative impact on cyclosporin affinity [51]–[53] . Mutation of the naturally occurring histidine in PPID to a tryptophan increases cyclosporin affinity dramatically , altering IC50 for cyclosporin from 1 . 9 mM to 28 nM and the Kdapp to 12 nM [31] , [54] . There are no mutational or computational data for the human cyclophilins that have a tyrosine or glutamic acid substitution at the Trp121 position; we therefore made a set of mutants to both PPIA ( mutating Trp121 to either tyrosine or glutamic acid ) and to PPIL2 ( mutating Tyr389 to either tryptophan or histidine ) . As expected , mutation of Trp121 in PPIA to glutamic acid abolished activity of this protein; however , the tyrosine mutant retained the ability to catalyze proline isomerization , a novel result . More importantly , the single mutation of Tyr389 to tryptophan converted PPIL2 to an active isomerase , thereby illustrating the fundamental importance of this residue in conferring activity to the cyclophilin family ( Figure S1B ) . However , the Tyr389 mutation to histidine did not lead to activity as measured by NMR under the experimental conditions assayed . For this reason , both the Tyr389 mutants were tested for CsA binding using ITC , and both the Tyr389Trp and Tyr389His mutants were found to bind CsA with micromolar affinity ( 1 . 6 µM and 6 . 6 µM for Trp and His respectively ) . Taken together , it is clear that there is some flexibility in the active site with regard to the Trp121 position: a tryptophan is clearly optimal at this position but tyrosine is somewhat permissive for activity , as is histidine . Glutamic acid at this position seems to be incompatible with isomerase activity . Previous computational work with PPIA indicates that the function of Trp121 is mainly to serve to build a hydrophobic pocket for the substrate proline to insert ( along with Phe60 , Met61 , Phe113 , and Leu126 ) [55] , [56] . However , our experimental data do not fully support this notion . To explain these results we modeled the interaction of CsA with the active site of cyclophilins , as the macrocyclic ring of cyclosporin structurally mimics the placement of the substrate residues N terminal and C terminal to the target proline ( where the sequence Xaa-Pro-Yaa is denoted P1 , P1′ , and P2′ respectively ) within the active site [48] , [57]–[59] . Modeling of either CsA into the active site of a histidine containing isoform ( like NKTR ) or computational mutation of the Trp121 in a PPIA∶CsA complex structure indicated that similar hydrogen bond distances can exist between the indole moiety of tryptophan or the imidazole ring of histidine and the carbonyl of methylleucine 9 ( MLE9 ) in CsA ( Figure S4 ) . Therefore either residue would be competent for binding , as we have shown experimentally . Conversely , a tyrosine modeled in the conformation to coordinate with CsA created a steric clash with the carbonyl of MLE9 ( 1 . 75 Å ) ; in addition , there was a close steric conflict with the modeled Tyr residue and Cζ of the highly conserved Phe60 residue that helps form the proline-binding pocket ( Figure S4 ) . Perhaps this is why in our apo PPIL2 structure the tyrosine at this position pointed away from the active surface ( Figure 2 ) . Consistent with this , electron density for Phe71 residue in NKTR indicated that alternative conformations are possible for this residue , which may also explain why the PPIA Trp121Tyr mutant was still capable of coordinating substrate in vitro ( Figure 2 ) . We propose that the function of the residue at this position is to make a specific polar interaction with either the carbonyl of MLE9 in CsA or the carbonyl of a substrate peptide at the P2′ position ( C terminal to the target proline ) . Three cyclophilins neither bound cyclosporin nor tetrapeptide: PPIL2 , PPIL6 , and SDCCAG-10 ( Table 1 ) . It is clear that these three proteins are quite divergent in the active site compared to PPIA ( Figure 1C ) . Perhaps more importantly they are , along with PPIL4 , the only isoforms that substitute the residue Trp121 with a non-histidine residue . Additionally , PPIL4 does not possess the otherwise strictly conserved Arg55 ( there is an asparagine at the equivalent position ) , so it is not surprising that this isoform does not show activity against standard substrates . The molecular function of the PPIase domain for these isoforms is unknown , but our structures suggest that these isoforms could still serve as proline-binding domains . Indeed , our assays show binding to the standard substrate suc-AGPF-pNA even where we do not detect isomerase activity ( Figure S1A ) . PPIL2 , PPIL6 , and SDCCAG-10 are clearly divergent from the rest of the family in terms of in vitro activity . Next , a structural analysis of all family members was undertaken in order to probe for further isoform diversity . Examination of the surface of the PPIase domains near the active site revealed two pockets that potentially contribute to substrate specificity , binding , and turnover . The first pocket is the proline interaction surface ( or S1′ pocket , where the target proline in substrate is again denoted as P1′ ) and is defined by the PPIA residues Phe113 at the base of the pocket and Phe60 , Met61 , Leu122 , and His126 that form the sides of the pocket ( Figure 4 ) . As previously described , these residues are highly conserved across all PPIase isoforms and orthologs , consistent with minor discrimination against commercial substrates or cyclosporin [60] . The second pocket forms a surface that likely interacts with substrate residue P2 or P3 relative to the substrate proline , and so will be named the S2 pocket hereafter . Since the main-chain atoms of the β5-β6 loop define the base of the S2 pocket , the chemical identities of residues found in this region do not have much influence on the size and shape of the S2 pocket ( Figure 4 ) . Indeed , the S2 pocket is extremely uniform across cyclophilins; it is deep and relatively nonspecific , so it can accommodate long , short , polar , or hydrophobic sidechains without penalty . However , the S2 pocket surface is guarded by a set of “gatekeeper” residues whose sidechains are in a position to control access to this pocket . In PPIA , these residues are Thr73 , Glu81 , Lys82 , Ala103 , Thr107 , Ser110 , and Gln111 ( Figure 4C ) . These gatekeeper residues at positions 81 , 82 , and 103 and the secondary gatekeeper at position 73 ( so named because its position in most PPIase structures is pointed away from the S2 pocket ) show major chemical and size variance . For instance , the residue that is at position 103 in PPIA varies from alanine in about half of the cyclophilin isoforms to a serine in PPIE , PPIH , and PPIL2; an arginine in PPIG and NKTR; lysine in PPIL6; asparagine in PPIL3 and PPIL4; and glutamine in RANBP2 ( Figure 4C ) . The identities of the amino acids at positions 73 , 81 , and 82 are equally diverse across the cyclophilin family . The practical effect of this variance can be visualized by examining the surface properties of the cyclophilin family ( Figure 5 and Datapack S1 ) . These surfaces are clearly unique to the individual cyclophilin members , but can generally be classified into gatekeeper surfaces with mixed or neutral charges ( see for example PPIA and several others ) ; gatekeeper surfaces with overall acidic character ( SDCCAG-10 , PPIC , and PPWD1 ) ; and gatekeeper surfaces that occlude access to the S2 pocket ( several; see Figure 5 ) . The occluded set consists of the cyclophilin isoforms with bulky sidechains at the gatekeeper positions; for instance , NKTR has Lys84 , Tyr93 , and Arg114 compared to PPIA residues Thr73 , Lys82 , and Ala103 ( Figures 4 and 5 ) . Finally , residues within this region of PPIA , including Lys82 , have previously been shown to be important for substrate binding as shown by NMR relaxation studies [61] , consistent with a gatekeeper function . The S2 pocket is where conformational divergence throughout the cyclophilin family is greatest ( Figure 2 and Datapack S1 ) . Most of the remaining structural diversity is found in three of the loop regions connecting secondary structural elements . A subset of cyclophilins have a deletion in the β1-β2 loop region ( residues Ala11-Pro16 in PPIA ) that significantly alters the β sheet lengths in this region along with the loop between them . The division between “deleted” β1-β2 loops and “full-length” β1-β2 loops follows a phylogram distribution of PPIase domains , with the more conserved isoforms relative to PPIA ( PPIB , PPIC , PPID , PPIE , PPIF , PPIG , PPIH , PPIL6 , NKTR , and RanBP2 ) encoding full-length loops and the more divergent members by sequence ( PPIL1 , PPIL2 , PPIL3 , PPIL4 , SDCCAG-10 , and PPWD1 ) encoding deleted β1-β2 loops ( Figure 2 and Figure S5 ) . The α1-β3 loop ( Thr41-Gly50 ) is also a region of structural diversity . There are three distinct classes of conformations adopted by this loop: the PPIA α1-β3 loop family , which includes PPIA , PPIB , PPIC , PPIE , and PPIF; a shorter version of the loop represented by the structures of PPIL1 , PPIL2 , PPIL3 , PPIL4 , SDCCAG-10 , and PPWD1; and a longer version found in PPID , PPIG , PPIH , PPIL6 , and NKTR . The short version of the α1-β3 loop changes the orientation of the α1 helix and the β3 sheet , and causes a ∼2 Å displacement of α1 relative to PPIA ( Figure S5 ) . Finally , the α2-β8 loop ( Gly146-Lys155 ) has two distinct groups: the standard conformation found in PPIA , PPIE , PPIF , PPIL6 , and RANBP2 , and the conformation adopted by all other isoforms ( Figure S5 ) . Interestingly , two regions found to have structural divergence ( the β1-β2 and α2-β8 loops ) form a contiguous surface on the “back” face of the cyclophilin fold relative to the active site . Sequence and structural diversity in this region could indicate a preference for different potential binding partners , as the back face of cyclophilins has previously been shown to mediate protein∶protein interactions [19] , [20] . However , it seems that for substrate interactions mediated by the proline-binding pocket isoform selectivity is likely to be determined by the S2 pocket region rather than these distal regions . Thus , the functional significance of the S2 pocket will be further explored with regard to its effect on substrate binding and specificity . Our biochemical data are the latest evidence that molecular determinants for tetrapeptide substrate or cyclosporin binding may not be identical to molecular determinants for physiologically relevant substrates , and supplements other recent publications along these lines [62] , [63] . Additionally , structural analysis suggests that the region surrounding the S2 pocket is an attractive target to design isoform specificity . As commercially available ligands and substrates are unable to effectively probe this region of the cyclophilin family , we turned to in silico techniques to obtain insight into isoform gatekeeper identity and its relationship to accessibility to the S2 pocket . Four hundred test peptides of the general form Xaa-Zaa-Gly-Pro ( corresponding to substrate positions P3-P2-P1-P1′ ) were docked into a subset of cyclophilin family members ( PPIA , PPIL2 , PPIC , PPWD1 , and NKTR ) . These proteins were chosen because of the diversity of the amino acids in the gatekeeper and S2 pocket regions ( Figure 5 ) . Monte Carlo simulations were performed to sample conformational space for each combination of cyclophilin isoform and test peptide , allowing flexibility of the P2 and P3 residues of the potential substrate and of the sidechains of the gatekeepers at positions comparable to PPIA Thr73 ( gatekeeper 1 ) , Lys82 ( gatekeeper 2 ) , and Ala103 ( gatekeeper 3 ) while keeping the rest of the protein rigid [64] . The sidechain of Arg377 in PPIL2 , which is a glycine in the other cyclophilins investigated , was also allowed flexibility as it contributes a unique chemistry to the S2 region . Throughout the Monte Carlo simulations ( 200 , 000 iterations ) tethers were imposed on the Gly and Pro residues to ensure that the tetrapeptides would remain bound to the active site . We made an assumption , based on a number of previous crystallographic and NMR-based studies of the cyclophilins , that the position and coordination of the Gly-Pro sequence of substrate is relatively fixed within the active site of the PPIase . Several structural studies with both synthetic and natural substrate data bound to PPIA support this assumption [30] , [50] , [59] . It was computationally necessary to fix the P1 and P1′ positions upon the enzyme in order to allow for more degrees of freedom at the P2 and P3 positions in our simulations; without these tethers we would have been testing the contribution of these two residues to the overall ability of substrate to bind the entire active site . While this is a very interesting line of study the interaction of proline in the proline binding or P1′ pocket was not the focus of the current work . For each combination of cyclophilin isoform and tetrapeptide , the lowest-energy complex was chosen as the preferred conformation of the bound complex , and an estimate of the binding energy was calculated using ICM [65] . Additionally , since low-energy complexes may or may not include significant interactions at the S2 pocket , the distance between the tetrapeptide and the Cα of the gatekeeper equivalent to PPIA Lys82 was calculated . This metric was designed to query for tetrapeptides that both bind with favorable energy in the S2 pocket , and also fill the S2 pocket if possible . An energetic preference for aromatics interacting with the S2 pocket was found for PPIA , in particular tryptophan or tyrosine ( Figure 6; for scatter plot representation see Figure S6 ) . In addition , there were a few peptides containing methionine , lysine , or arginine at the P2 position that extended deeply into the S2 pocket , albeit with poor predicted binding energies . Peptides with isoleucine , leucine , valine , proline , alanine , glycine , cysteine , threonine , or serine at the P2 position were disfavored , with poor predicted binding energies . We observed much less discrimination for the identity of the P3 position , although there is a clear selection against basic chemistries ( Figure 6 ) . Visual inspection of the top 10 model complexes predicted for PPIA based on the energy metric ( EFGP , EWGP , DYGP , DEGP , DDGP , YWGP , PYGP , EDGP , YFGP , and PWGP ) showed that all of the residues at the P2 position are well positioned to fill the S2 pocket of PPIA , while inspection of some models that scored poorly ( RFGP , ERGP , DFGP ) showed incomplete entry into the S2 pocket . In addition , these models indicated interactions between the residue at the P3 position and the gatekeeper 1 residue , or with the P1′ pocket and the key active site residue Arg55 . The published data on specificity for PPIA are consistent with our findings . Previous in vitro phage display experiments with PPIA ( designed to probe substrate preferences at the P1 to P8′ positions ) found a strong preference for phenylalanine at the P2 and glutamic acid at the P3 position; these residues were provided by the expression vector used in the phage display and therefore biased the pool of samples available for initial selection [35] . Substitution of this glutamic acid/phenylalanine series with any other residues , however , lessened the signal on an array , thereby confirming a preference for these chemistries in solution . Our simulations support this chemical preference for acidic residues at P3 followed by aromatic residues at P2 ( Figure 6 ) . A well-characterized substrate in vivo for PPIA is the HIV capsid; there are several sequence variants that have been studied both in solution and in crystallographic experiments , and all sequences have either methionine or alanine at the P2 position and histidine or alanine at the P3 position [50] , [66] . In the structures of PPIA with these peptides , the alanine does not fill the S2 pocket , and this is likely the reason why it does not score well in our modeling trials . Neither histidine nor alanine at the P3 position is predicted to score highly by our modeling trials , and in the co-crystal structures these residues are not making any significant contacts to the gatekeeper 1 region of PPIA . The validated in vivo substrate CD147 was also investigated . The natural sequence that is acted upon by PPIA is ALWP , which was not predicted to bind tightly to PPIA based on either the phage display data or our simulations , and experimentally was found to have rather weak affinity [17] . Finally , the PPIA substrate Itk contains the targeted sequence ENNP , which is a relatively high-scoring P3 and P2 sequence combination based on our models [14] . Our simulations recapitulate the experimental data that is available , but imply that none of the in vitro or in vivo substrates studied to date for PPIA interact with the S2 pocket with optimized space-filling or energetic properties . In order to begin experimental validation of our in silico predictions , a peptide “test set” composed of the following sequences was synthesized: DEGPF , DFGPF , DYGPF , YGGPF , and VRGPF . We then monitored catalysis of all of these potential substrates using our NMR-based assay ( Figure S1 ) . These peptides were selected in order to allow us to discriminate between cyclophilin isoforms; initial studies were conducted with PPIA in order to optimize experimental conditions for the detection of binding and catalysis . Our data indicated that , although PPIA was competent to bind all five peptides , only those predicted to have significant scores on the binding energy metric were substrates for proline isomerization ( DEGPF , DFGPF , and DYGPF; see Figure 6 and Figure S1 ) . The two peptides that were not efficient substrates for catalysis ( YGGPF and VRGPF ) both yielded poor predicted binding energies in our docking study to PPIA . That there was little discrimination with our NMR assay between DEGPF , DFGPF , and DYGPF was somewhat inconsistent with our simulations , as the model peptide for DFGP did not extend fully into the S2 pocket . It is possible that while tethering the P1 and P1′ Gly-Pro sequence allowed us to obtain a large number of reasonable structures at the P2 and P3 positions , it may have artificially increased our in silico binding affinity in a way that we cannot recapitulate in vitro . It is also possible that this spatial constraint upon our simulations biased our results towards substrates with the key interacting residue at the P2 position . Perhaps in vitro it is the P3 position that contributes significantly to binding energy; therefore the binding contributed by the aspartic acid in the current test set was the significant determinant for binding to PPIA in addition to the identity of the residue at the P2 position . Regardless , these experimental results will allow us to next analyze the capacity of our test set to discriminate among cyclophilin isoforms . Additionally , as all of our test peptides are identical at the P1 , P1′ , and P2′ positions , we can see for the first time that substitutions at amino acids in the P2 and P3 positions have measurable effects on the ability of the broad specificity enzyme PPIA to bind and catalyze proline containing sequences . Distinct patterns of chemical preference were noted for PPIC , PPIL2 , NKTR , and PPWD1 ( Figure 6; for scatter plot representation see Figure S6 ) . Much like PPIA , the PPIase domains of PPIC and PPIL2 showed an energetic preference for tryptophan at the P2 position; and for PPIL2 and NKTR isoleucine , leucine , valine , proline , alanine , glycine , cysteine , threonine , and serine at the P2 position resulted in poor predicted binding energies and little penetration into the S2 pocket ( Figure 6 ) . Indeed , for NKTR there were relatively few tetrapeptide combinations with both favorable predicted binding energy and penetration into the S2 pocket; this is easily rationalized by the extremely narrow gap between the gatekeeper 1 and gatekeeper 3 regions in the NKTR structure , which occlude the S2 pocket and restrict the types of residues that can stably associate with the pocket without steric or charge clashes ( Figures 5 , 6 ) . PPIC showed a distinct preference pattern for aromatic residues at P2 preceded by basic or aromatic residues at P3 ( Figure 6 ) . This is most likely due to the substitution of gatekeeper 2 and the overall acidic character of this region of PPIC relative to PPIA ( Figure 5 ) . In the case of PPIL2 , there was near equivalency between the aromatics at position P2 , with perhaps a slight energetic preference for tryptophan but strong affinities for tyrosine and phenylalanine as well . Likewise there was little discrimination at the P3 position ( Figure 6 ) . Compared to PPIL2 simulations , the results for PPWD1 were striking: the acidic surface characteristics of this isoform selected strongly for an arginine at the P2 position , while lysine and aromatic residues also yielded good predicted binding energies ( Figures 5 and 6 ) . Of the surfaces tested , only PPWD1 provided a surface where strong energy scores were measured for basic residues at this position . Experimentally , the construct used initially for crystallization of PPWD1 contained a sequence AEGP found N-terminal to the PPIase domain , and this sequence was found associated with a neighboring PPIase domain in the crystal structure . NMR-based assays showed that AEGP bound PPWD1 but was not a good substrate for the enzyme , which correlates well with the poor binding energy predicted for the AEGP tetrapeptide in our simulations [30] . Again , the scarcity of experimental data for cyclophilin isoforms limits the ability to validate the simulations; but to the extent that such information exists , it correlates well with our in silico findings . Current efforts are underway to measure binding and/or proline isomerization of our test set peptides with NKTR , PPIC , PPIL2 , and PPWD1; we predict based on our above analysis that several of our test set peptides would bind well to most or all of our test cyclophilins ( see DYGP and DFGP in Figure 6 ) , while others could be selective for some isoforms over others ( VRGP , which has good energy metrics for PPWD1 but not for any other isoform in the current study ) . Although in vitro validation of our in silico results are still ongoing , we believe that the initial data we present here provide the basis for a renewed study of the S2 pocket of the human cyclophilins as a potential locus of chemical and substrate diversity . In conclusion , there are cyclophilin family members that , while sharing overall conservation with active members of the family , do not possess isomerase activity in our assays . For PPIL2 and SDCCAG-10 , both of which have been found associated with spliceosomal complexes , it may be that it is the non-active surface of the PPIase domain that performs the major function as in the cases of PPIH and PPIL1 . Additionally , it may well be that the function of the PPIase domain in these cyclophilins is to simply bind proline-containing motifs . Our NMR data suggest this option , as binding without measurable catalysis to proline sequences is observed for all isoforms we were able to test . Chemical probes such as cyclosporin are unselective with regard to the cyclophilin family ( Table 1 ) [67] . Although a recent report focusing on aryl 1-indanylketones showed binding to PPIA , PPIF , and PPIL1 while not binding to PPIB , PPIC , or PPIH [67] , it seems that any ligand that coordinates exclusively with the S1′ pocket and/or Trp121 region is unlikely to be selective with respect to the entire cyclophilin family . Potentially , the S2′ or S3′ region of the isomerase domain could be a site of selectivity; it is clear from our surface representations ( Figure 5 ) that this is a variable part of the cyclophilin domain . However , our results indicate that a clear virtual chemical fingerprint exists for the S2 and S3 positions of the isomerase domain . For instance , PPIA and PPWD1 seem to have restricted sets of sidechains that are preferred at the P2 position ( and the P3 position in the case of PPIA ) , while PPIC appears to be more promiscuous . The highly occluded nature for the S2 pocket exhibited by NKTR results in a restrictive set of allowed tetrapeptide sequences for this isoform; several other isoforms in the cyclophilin family also exhibit this type of gatekeeper restriction . Because of the very distinct molecular features of the S2 region , both in terms of the highly “druggable” S2 pocket and the chemical diversity seen for the gatekeeper residues , targeting this region of the cyclophilins for pharmacophore design and selection is more likely to result in tight binders with greater specificity for particular isoforms in the family .
Detailed materials and methods for cloning , expression , purification , and crystallization of all novel isomerase domain structures solved as part of the Structural Genomics Consortium are freely available at the Web site http://www . sgc . utoronto . ca/; where methods differ significantly from the following they are noted for each isoform in Text S2 . In general , full-length cDNA clones were obtained from the Mammalian Gene Collection ( accession numbers noted below ) . Constructs based around the predicted isomerase domain boundaries were cloned into pET28a using ligation-independent cloning methods ( LIC ) ( BD Biosciences , San Jose , CA , USA ) and transformed into BL21 Gold DE3 cells ( Stratagene , La Jolla , CA , USA ) . The resulting vectors encode an N-terminal His6 tag with a thrombin cleavage site . Mutants of cyclophilin constructs were created either using standard Quickchange protocols ( Stratagene ) or by LIC-based methods on PCR fused gene products . Cultures were grown in Terrific Broth medium at 37°C to OD600 of 6 and induced at 15°C overnight with the addition of 50–100 µm isopropyl thio-β-D-galactoside ( IPTG ) . Pellets were resuspended in 20 mL of lysis buffer ( 50 mm Tris , pH 8 . 0 , 500 mm NaCl , 1 mm phenylmethanesulfonyl fluoride and 0 . 1 mL of general protease inhibitor ( P2714 , Sigma , St . Louis , MO , USA ) and lysed by sonication; lysates were then centrifuged for 20 min at 69 , 673g . The supernatant was loaded onto nickel nitrilotriacetic acid resin ( Qiagen , Valencia , CA , USA ) , washed with five column volumes of lysis buffer and five column volumes of low imidazole buffer ( lysis buffer+10 mm imidazole , pH 8 ) , and eluted in 10 mL of elution buffer ( lysis buffer+250 mm imidazole , pH 8 , and 10% glycerol ) . If the His6 tag was cleaved for crystallization purposes , then one unit of thrombin ( Sigma ) per milligram of protein was added to remove the tag overnight at 4°C . For gel filtration , a column packed with HiLoad Superdex 200 resin ( GE Healthcare , Piscataway , NJ , USA ) was pre-equilibrated with gel filtration buffer ( lysis buffer+5 mM β-mercaptoethanol and 1 mM ethylenediaminetetraacetic acid ) . Peak fractions were pooled and concentrated using Amicon concentrators ( 10 , 000 molecular mass cut-off; Millipore , Danvers , MA , USA ) . The protein was generally used at 250–500 µM for crystallization screening . Generally , crystal hits were initially prepared in sitting drop 96-well format . Proteins were set up as 1 µL protein+1 µL reservoir solution and incubated at 18°C for 24 h to 1 mo . If crystal optimization was required it was performed in 24-well hanging drop format with 1 µL protein+1 µL reservoir solution . Crystals were cryoprotected with mother liquor with 10%–15% glycerol . Datasets were collected on an in-house FR-E SuperBright Cu rotating anode/Raxis IV++ detector ( Rigaku Americas , The Woodlands , TX , USA ) ; except for PPIC , which was collected at APS 19-BM . Data was integrated and scaled using the HKL2000 program package [68] , [69] . The program PHASER [70] was used as part of the CCP4 suite [71] to find the molecular replacement solution . Manual rebuilding was performed using either O [72] or COOT [73] , and refined using REFMAC [74] in the CCP4I program suite [75] . In most cases ARP/wARP was utilized to assist in model building and iterative refinement of starting phases [76] . Final models were evaluated using PROCHECK [77] and MOLPROBITY [78] , with all models judged to have excellent stereochemistry and no residues in disallowed regions of Ramachandran space . All protein samples used for static light scattering ( StarGazer ) trials were assessed for purity utilizing SDS-PAGE and verified for mass accuracy using mass spectrometry . Methods were generally as described as in [38]; protein at approximately 20 µM concentration was heated from room temperature to 80°C in the presence or absence of small molecules , including cyclosporins A , C , D , or H ( LKT Labs , MN , USA ) . The cyclophilins were originally prepared in 100% DMSO at 50–100 mM concentration , then diluted to 50 µM for screening , thereby ensuring the final DMSO concentration was less than 5% during the experiment . Ligand binding was detected by monitoring the increase in Tagg in the presence of the ligand; and any compound that caused a >2°C increase in Tagg were observed to be outside of the range of experimental error . Each compound was tested at least twice . All experiments were performed using a VP-ITC microcalorimeter ( Microcal , MA , USA ) , and data analysis was performed utilizing the Origin 7 software . All experiments were conducted at 25°C . Methods were roughly based on those in [67] , with modifications as described . Highly pure proteins were dialyzed into ITC buffer ( 50 mM Hepes pH 8 , 0 . 2 M NaCl ) , which was also used to dilute ligand stock to the concentrations used for ITC . In order to obtain strong signal for binding isotherms , proteins were used at concentrations ranging from 50 to 300 µM , with 100 µM being standard for most cyclophilins tested . The proteins were loaded into the syringe , with the ligand ( cyclosporin A , LKT Labs , MN , USA ) in the cell at 5 µM concentration . Generally 5–10 µL injections of protein were made; optimal volumes were determined experimentally to obtain reasonable data for single-site fitting . Ligands were described as not binding protein under these conditions if , at high concentrations of protein ( ∼300 µM ) , no change in isotherm deflection was noted after 10–20 injections ( 275 µL of protein ) . Most protein samples aimed at assessing binding and/or catalysis of tetrapeptide substrates were diluted to 500 µL with 10% D2O and placed into a Shigemi microcell ( Allison Park , PA , USA ) . Typical samples contained 0 . 075 mM protein and 2 mM of suc-AAPF-pNA , suc-AFPF-pNA , or suc-AGPF-pNA ( Bachem ) , along with 100 mM phosphate buffer pH 7 and 100 mM NaCl . Spectra were collected at 25°C on a Varian 600 or 900 MHz spectrometer ( Palo Alto , CA , USA ) . Spectra were acquired using standard Varian BioPack sequences , processed using NMRpipe software [79] and visualized using CCPN software [80] . For samples used to assess binding of PPIA to peptides DEGPF , DFGPF , DYGPF , YGGPF , or VRGPF , samples were as above except protein concentration was 0 . 3 mM and spectra were collected at 10°C . A set of 400 test peptides of the general form X-Z-Gly-Pro were docked to a subset of cyclophilin isoforms ( Protein Data Bank [PDB] codes: PPIA , 1AK4: PPIL2 , 1ZKC; PPIC , 2ESL; PPWD1 , 2A2N; and NKTR , 2HE9 ) using ICM software ( Molsoft LLC ) . Monte Carlo simulations were performed to sample conformational space for each combination of cyclophilin isoform and test peptide , allowing flexibility of the tetrapeptide and the sidechains of the gatekeepers at positions comparable to PPIA Thr73 , Lys82 , and Ala103 , and keeping the rest of the protein receptor rigid [64] . The crystal structure of PPWD1 ( PDB: 2A2N ) was used to determine the initial position of each tetrapeptide in the various cyclophilin isoforms by superimposing the Gly and Pro residues onto the corresponding residues bound to the active site of PPWD1 , and the catalytic arginine was repositioned to align with Arg535 of PPWD1 . Throughout the Monte Carlo simulations ( 200 , 000 iterations ) , tethers were imposed on the C-terminal Gly and Pro residues , to ensure that the tetrapeptides would remain bound to the active site . For each combination of cyclophilin isoform and tetrapeptide , the lowest-energy complex was chosen as the predicted conformation of the bound complex , and an estimate of the binding energy was calculated using ICM ( Molsoft , LLC ) [65] . Additionally , the distance between the tetrapeptide and the Cα of the gatekeeper equivalent to PPIA Lys82 was calculated ( this residue is located at the far end of the S2 pocket; see Figure 4 ) , to determine how well the docked peptide was predicted to fill the S2 pocket . Peptides derived from simulation data were synthesized without modification by the Core Facility at Tufts University ( http://tucf . org/ ) . PDB codes for the novel cyclophilin structures presented within this manuscript are as follows: 2R99 ( PPIE ) , 2ESL ( PPIC ) , 2HE9 ( NKTR ) , 2GW2 ( PPIG ) , 2HQ6 ( SDCCAG-10 ) , 1ZKC ( PPIL2 ) , and 2A2N ( PPWD1 ) . PDB codes for the previously deposited set of structures used to generate figures and analyzed in the text are: 2CPL ( PPIA ) , 2BIT ( PPIF ) , 1CYN ( PPIB ) , 1QOI ( PPIH ) , 1XWN ( PPIL1 ) , and 2OK3 ( PPIL3 ) . GenBank accession numbers for the cyclophilins noted in the methods are: BC003026 ( PPIA ) , BC020800 ( PPIB ) , BC002678 ( PPIC ) , BC030707 ( PPID ) , BC008451 ( PPIE ) , BC005020 ( PPIF ) , BC001555 ( PPIG ) , BC003412 ( PPIH ) , BC003048 ( PPIL1 ) , BC000022 ( PPIL2 ) , BC007693 ( PPIL3 ) , BC020986 ( PPIL4 ) , BC038716 ( PPIL6 ) , NM006267 ( RANBP2 - synthetic template ) , BC015385 ( PPWD1 ) , BC167775 ( NKTR ) , and BC012117 ( SDCCAG-10 ) . | Cyclophilins are proteins that catalyze the isomerization of prolines , interconverting this structurally important amino acid between cis and trans isomers . Although there are 17 cyclophilins in the human genome , the function of most cyclophilin isoforms is unknown . At least some members of this protein family are of interest for clinically relevant drug design , as they are targets of the drug cyclosporin , which is used as an immunosuppressant to treat patients following organ transplantation . The absence of a comprehensive picture of the similarities and differences between the different members of this protein family precludes effective and specific drug design , however . In the current study we undertake such a global structure∶function analysis . Using biochemical , structural , and computational methods we characterize the human cyclophilin family in detail and suggest that there is a previously overlooked region of these enzymes that contributes significantly to isoform diversity . We propose that this region may represent an important target for isoform-specific drug design . | [
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] | [
"biochemistry",
"biophysics/structural",
"genomics",
"biophysics/biomacromolecule-ligand",
"interactions",
"biochemistry/structural",
"genomics",
"biophysics"
] | 2010 | Structural and Biochemical Characterization of the Human Cyclophilin Family of Peptidyl-Prolyl Isomerases |
σ factors endow RNA polymerase with promoter specificity in bacteria . Extra-Cytoplasmic Function ( ECF ) σ factors represent the largest and most diverse family of σ factors . Most ECF σ factors must be activated in response to an external signal . One mechanism of activation is the stepwise proteolytic destruction of an anti-σ factor via Regulated Intramembrane Proteolysis ( RIP ) . In most cases , the site-1 protease required to initiate the RIP process directly senses the signal . Here we report a new mechanism in which the anti-σ factor rather than the site-1 protease is the sensor . We provide evidence suggesting that the anti-σ factor RsiV is the bacterial receptor for the innate immune defense enzyme , lysozyme . The site-1 cleavage site is similar to the recognition site of signal peptidase and cleavage at this site is required for σV activation in Bacillus subtilis . We reconstitute site-1 cleavage in vitro and demonstrate that it requires both signal peptidase and lysozyme . We demonstrate that the anti-σ factor RsiV directly binds to lysozyme and muramidase activity is not required for σV activation . We propose a model in which the binding of lysozyme to RsiV activates RsiV for signal peptidase cleavage at site-1 , initiating proteolytic destruction of RsiV and activation of σV . This suggests a novel mechanism in which conformational change in a substrate controls the cleavage susceptibility for signal peptidase . Thus , unlike other ECF σ factors which require regulated intramembrane proteolysis for activation , the sensor for σV activation is not the site-1 protease but the anti-σ factor .
Cells respond to changes in their environments using signal transduction systems , which transmit information from outside the cell across the membrane to effect transcriptional responses . Regulated Intramembrane Proteolysis ( RIP ) is one mechanism by which cells sense and respond to changes in the environment . The RIP signal transduction system was first described as the mechanism for controlling cholesterol biosynthesis in mammals [1] . In bacteria , RIP processes regulate the activity of several alternative σ factors including multiple Extra Cytoplasmic Function ( ECF ) σ factors . Most RIP signal transduction systems involve sequential cleavages of a membrane-tethered protein . Following site-1 cleavage by an initial protease , a second protease cleaves the substrate within the membrane at site-2 . In most cases the rate-limiting step for activation of the signal transduction system is the cleavage of the substrate at site-1 [2] . Here we describe the role of RIP in regulating the activity of the B . subtilis ECF σ factor σV in response to lysozyme . In bacteria , σ factors combine with RNA polymerase to recognize specific promoter sequences and transcribe mRNA . ECF σ factors represent a large and diverse family of important signal transduction systems in bacteria [3] . RIP regulates the activity of several alternative σ factors including multiple ECF σ factors in the subfamily ECF01 [2] , . In Escherichia coli , activation of the ECF σ factor σE is initiated by site-1 cleavage of the anti-σ factor RseA when unfolded outer membrane β-barrel proteins bind to and activate the site-1 protease DegS [4]–[7] . In Bacillus subtilis activation of the ECF σ factor σW is thought to be controlled by activation of the site-1 protease PrsW , since mutants of PrsW were isolated which resulted in constitutive cleavage of the anti-σ factor RsiW even in the absence of stress [8] . In each of these cases the site-1 protease is thought to sense the signal required for activation of these ECF σ factors . The B . subtilis ECF σ factor , σV , belongs to the ECF30 subfamily of ECF σ factors , members of which are primarily found in firmicutes ( low GC Gram-positive bacteria ) [3] . A subset of the ECF30 homologs are controlled by anti-σ factors homologous to RsiV . σV is activated in response to lysozyme but not to other cell envelope stresses [9]–[11] . Lysozyme is an essential component of the host innate immune system which fights bacterial infection by cleaving cell wall saccharides and σV induces resistance to lysozyme [11]–[13] . We recently demonstrated that activation of σV requires the proteolytic destruction of the membrane tethered anti-σ factor , RsiV , in a RIP dependent mechanism [14] . This degradation requires the site-2 protease RasP [14] . RasP cleavage results in free σV which can complex with RNA polymerase and transcribe genes required for lysozyme resistance [9] , [10] . Here we present evidence that the site-1 protease required for RsiV degradation is none other than signal peptidase . Signal peptidases are an essential component of the cellular secretion apparatus and are conserved from bacteria to eukaryotes . The activity of signal peptidases is not known to be regulated in response to environmental signals . We propose a model in which the sensor for cell envelope stress is the anti-σ factor RsiV . Our data indicate that RsiV is the direct receptor for lysozyme . Thus the anti-σ factor , and not the site-1 protease , is the sensor for lysozyme .
We previously demonstrated that activation of σV required the proteolytic destruction of the anti-σ factor RsiV in a RIP dependent mechanism [14] . Upon exposure to lysozyme we could detect what appeared to be the cleaved extracellular domain of RsiV [14] ( Figure 1 ) . This suggested that the extracellular domain is removed by an unknown protease that cleaves RsiV at site-1 after treatment with lysozyme . To determine the location of the site-1 cleavage , we constructed a B . subtilis strain producing a C-terminal 6×His tagged version of RsiV ( RsiV6×His ) . Protoplasts of this strain were then generated using lysozyme . Following this treatment , we were able to purify the RsiV6×His from the supernatant of these cells using nickel affinity resin ( Figure S1 ) . The sequence of the first 8 amino acids of the partially purified cleaved RsiV6×His was determined by Edman degradation [15] . The N-terminal sequence of the cleaved RsiV domain was ( MSKIPVIG ) which indicates RsiV is cleaved between A66 and M67 ( Figure S1 and Figure 1A ) . Analysis of the RsiV site-1 cleavage site revealed a canonical AXA motif suggestive of a signal peptide cleavage site . In fact subsequent analysis of RsiV in silico using SignalP [16] revealed a putative signal peptidase cleavage site between amino acids 66 and 67 of RsiV ( Figure S2A ) . Furthermore an alignment of 185 RsiV homologs using Multiple Em for Motif Elicitation ( MEME ) a tool for identifying motifs in related sequences [17] , reveals a highly conserved AXA motif just after their predicted transmembrane segment [18] ( Figure S2B ) . In addition , analysis of C . difficile , E . faecalis and B . subtilis RsiV homologs using SignalP revealed the presence of a predicted signal peptidase cleavage site in each of those proteins ( Figure S2A ) . B . subtilis PY79 encodes five type 1 signal peptidases [19] , [20] . SipS and SipT are the two major signal peptidases in B . subtilis and are redundant , but cells lacking both SipS and SipT are not viable [20] . We constructed sipS and sipT mutant strains and tested RsiV degradation and σV activation . We found that RsiV was still degraded in the absence of either SipS or SipT ( Figure S3 ) . We attempted to construct a strain to deplete signal peptidase however we were unsuccessful . Thus , to determine if disruption of cleavage at this site was sufficient to block RsiV degradation and σV activation , the alanine codon at position 66 was mutated to a tryptophan codon and tested for an effect on HEW lysozyme induced degradation . We found that while wild-type RsiV was rapidly degraded , the degradation of the RsiVA66W mutant protein was blocked even in the presence of lysozyme ( Figure 1B ) . This suggests that the RsiVA66W mutant is unable to be cleaved at site-1 . We then tested the effect of RsiVA66W mutant protein on activation of σV in response to lysozyme by measuring expression of the PsigV-lacZ reporter . In cells producing wild type RsiV , expression of PsigV-lacZ was induced 16-fold in the presence of lysozyme ( Figure 1C ) . In contrast , in strains producing RsiVA66W there was no observable lysozyme induction of PsigV-lacZ expression . This indicates that the RsiVA66W protein is resistant to site-1 cleavage , and thus , blocks activation of σV in response to lysozyme by inhibiting RsiV degradation . In addition , a strain producing RsiVA66W is more susceptible to lysozyme than WT RsiV , due to an inability to degrade RsiV and activate σV ( Table 1 ) . Taken together this suggests that cleavage at site-1 is required for σV activation . Our data indicate that RsiV is cleaved at a putative signal peptidase cleavage site . Since signal peptidase activity is essential in B . subtilis [20] we sought to determine if signal peptidases were directly responsible for cleavage of the anti-σ factor RsiV in vitro . The signal peptidase SipS and RsiV both contain transmembrane domains and we hypothesized that these may be important for proper control of RsiV degradation . Thus , we produced SipS and RsiV in vitro using a cell free in vitro transcription/translation system . This method has been used successfully to test the ability of other membrane proteases to cleave their substrates [21] . Briefly , mRNA of sipS and rsiV was produced using SP6 RNAP as previously described [21] . The resulting mRNA served as a translation template using wheat germ extract as a source of ribosomes . Wheat germ extract contains sufficient endogenous lipids that at least some functional membrane proteins can be produced without addition of liposomes [21] . Both SipS and RsiV were produced in sufficient quantities that they could be visualized by Coomassie staining and they are present mostly in the insoluble pellet ( i . e . lipid-containing ) fraction of the in vitro translation reactions ( Figure S4 ) . We combined the SipS and RsiV reactions at 1∶3 molar ratios with or without the presence of HEW lysozyme and incubated the reactions at 37°C for 6 hours . Using anti-RsiV59–285 antibodies we were unable to detect the presence of any cleavage products of 3×Flag-CBP-RsiV when it was incubated alone or in the presence of SipS ( Figure 2 ) . When 3×Flag-CBP-RsiV was incubated with SipS in the presence of HEW lysozyme we observed the production of a cleavage product and a decrease in the amount of full length 3×Flag-CBP-RsiV ( Figure 2 ) . We observed minimal cleavage when 3×Flag-CBP-RsiV was incubated in the presence of HEW lysozyme , likely due to the presence of an eukaryotic signal peptidase in the wheat germ , which also recognizes an AXA motif [22] , [23] ( Figure 2 ) . The cleaved product in vitro was the same size as the cleaved product produced from RsiV6×His in vivo ( Figure 2A ) . We sought to determine if the A66W substitution in RsiV would block site-1 cleavage in vitro as it did in vivo . As seen in Figure 2 we observed only full length 3×Flag-CBP-RsiVA66W when 3×Flag-CBP-RsiVA66W was incubated with both SipS and HEW lysozyme ( Figure 2 ) . This suggests , in agreement with our in vivo results , that altering the signal peptidase recognition site in RsiV blocks site-1 cleavage in vitro . These data suggest that SipS is able to directly cleave RsiV and importantly this cleavage only occurs in the presence of HEW lysozyme . Our data suggest that RsiV is cleaved by the signal peptidase SipS in vitro only in the presence of lysozyme . However there is no peptidoglycan present in the in vitro reactions which raised the question; why is HEW lysozyme required for site-1 cleavage ? We hypothesized that RsiV may directly bind HEW lysozyme . We constructed a 6×His-RsiV59–285 fusion and purified it from E . coli ( Figure S5 ) . We tested the ability of RsiV to bind HEW lysozyme using co-purification . We found that when 6×His-RsiV59–285 was bound to the nickel column HEW lysozyme was co-eluted ( Figure 3A ) . However when HEW lysozyme was loaded on a column treated with the extract of BL21 ( DE3 ) empty vector-containing cells , we found HEW lysozyme in the flow through and wash fractions but not present in the elution fractions ( Figure 3A ) . To confirm RsiV binds to HEW lysozyme in vivo as well as in vitro we performed a co-purification experiment using B . subtilis producing RsiV6×His . We found that when we purified cleaved RsiV6×His after treatment with lysozyme a single band with a similar size to HEW lysozyme co-eluted with RsiV6×His ( Figure 3B ) . We confirmed that this band corresponded to HEW lysozyme by N-terminal sequencing . This suggests that RsiV binds HEW lysozyme both in vitro and in vivo . We used Isothermal Titration Calorimetry ( ITC ) to confirm these observations as well as to determine the affinity of RsiV59–285 for HEW lysozyme . We found that RsiV59–285 binds to HEW lysozyme in an enthalpically-driven reaction with a Kd of 70 nM ( Figure 3C; Table 2 ) . Although it is difficult to determine the precise affinity of HEW lysozyme to peptidoglycan , because peptidoglycan is very heterogeneous , the best data suggest the Kd of PG to lysozyme is ∼50 mM [24]–[26] . This suggests that the HEW lysozyme-RsiV affinity is significantly greater than the affinity of HEW lysozyme for peptidoglycan . Previous work found that lysozyme was able to induce σV activity . In contrast , a variety of antimicrobial compounds that inhibited peptidoglycan synthesis and damaged the cell envelope were unable to induce σV activity [9] . Since RsiV binds HEW lysozyme , we hypothesized that the protein and not the activity of HEW lysozyme was required to activate σV . Mutanolysin cleaves the same β-glycosidic bond as HEW lysozyme , but has an entirely different amino acid sequence and structure [27] . To determine if muramidase activity was sufficient for σV activation we compared the ability of HEW lysozyme , human lysozyme , and mutanolysin to induce expression of the PsigV-lacZ reporter fusion . We found that HEW lysozyme and human lysozyme , both C-type lysozymes with 58% amino acid identity and 76% similarity , produced zones of clearing ( 8 mm and 9 mm respectively ) , and induced expression of PsigV-lacZ as indicated by the blue ring around the disk ( Figure 4A ) . We found that although mutanolysin produced a zone of clearing ( 7 mm ) indicative of killing , it was unable to induce PsigV-lacZ expression . The lack of induction by mutanolysin suggests that muramidase activity is not sufficient for activation of σV . Since σV is activated upon degradation of the transmembrane bound anti-σ RsiV we tested the effect of HEW lysozyme , human lysozyme , and mutanolysin , for their ability to induce RsiV degradation . We expressed rsiV from an IPTG inducible promoter and then treated cells with a sub-lethal concentration of lysozyme for 10 minutes . Using anti-RsiV59–285 antibodies a 32 kDa protein was observed by immunoblot in the absence of lysozyme , indicative of the full length RsiV ( Figure 4B ) . In the presence of HEW lysozyme , the full-length RsiV is rapidly degraded and a smaller product , the released extracellular domain , is visible ( Figure 4B ) . Similarly , treatment with human lysozyme also induces RsiV degradation ( Figure 4B ) . However , treatment with mutanolysin was unable to induce degradation of RsiV ( Figure 4B ) . To further confirm the observation that muramidase activity was insufficient to induce RsiV degradation , we used mutanolysin to generate protoplasts of B . subtilis cells expressing rsiV . These cells were then left untreated or treated with HEW lysozyme and the status of RsiV monitored by immunoblot . We found that the protoplasts still retain full-length RsiV however upon subsequent treatment with lysozyme we observe loss of full-length RsiV ( Figure 4C ) . This provides further evidence that muramidase activity alone is not sufficient to induce degradation of RsiV . Our data indicate that muramidase activity provided by mutanolysin is not sufficient to induce σV activation or RsiV degradation , thus we asked if muramidase activity was required for lysozyme-driven σV activation or RsiV degradation . It has been shown that changing human lysozyme aspartate 53 to serine abolishes muramidase activity to less than 1% [28] . Recombinant human lysozyme ( R-lysozyme ) , and the catalytically inactive form of human lysozyme ( R-lysozymeD53S ) were expressed and purified from the supernatant of Pichia pastoris [29] . Muramidase activity of R-lysozyme and R-lysozymeD53S was assayed against Micrococcus lysodekticus peptidoglycan which confirmed that the R-lysozyme was active and R-lysozymeD53S was muramidase deficient ( Figure S6 ) . We found that when purified R-lysozyme and R-lysozymeD53S were placed on a lawn of B . subtilis containing the PsigV-lacZ reporter fusion both produced a zone of induction ( Figure 4A ) . However only the wild type R-lysozyme produced a zone of clearing ( 9 mm ) while the R-lysozymeD53S did not produce a zone of clearing ( 6 mm – size of the disk ) ( Figure 4A ) . To further confirm that muramidase activity was not required for σV activation we tested the ability of the recombinant active or inactive lysozyme to induce RsiV degradation . Consistent with the zone of clearing results , treatment with human lysozyme , R-lysozyme , and R-lysozymeD52S also induce RsiV degradation ( Figure 4B ) . However , treatment with mutanolysin was unable to induce degradation of RsiV ( Figure 4B ) . Thus , the lack of PsigV-lacZ induction by mutanolysin and the ability of catalytically inactive R-lysozymeD53S to induce PsigV-lacZ suggests that muramidase activity is not required nor is it sufficient for activation of σV . Our data suggests that σV is activated by the C-type lysozymes HEW lysozyme and human lysozyme , but not the unrelated muramidase mutanolysin . Since RsiV can bind HEW lysozyme we sought to determine if σV activation was correlated with the ability of RsiV to bind different proteins . To test this we purified a GST-RsiV59–285 fusion protein . We then loaded 2 mg of GST-RsiV59–285 onto a glutathione column and then 2 mg of either HEW lysozyme , human lysozyme , or mutanolysin were passed over the column . The proteins were eluted and separated by SDS/PAGE ( Figure 5 ) . We found that both HEW lysozyme and human lysozyme were retained on the column when RsiV was present . This suggests that both HEW lysozyme and human lysozyme can bind RsiV59–285 . In contrast , we found when mutanolysin was loaded onto the GST-RsiV-RsiV59–285 containing column mutanolysin was collected almost entirely in either the flow through and wash fractions ( Figure 5 ) . This suggests that RsiV specifically binds C-type lysozymes but not mutanolysin . Both C . difficile and E . faecalis encode homologs of σV and RsiV and in each organism σV is activated by lysozyme and required for lysozyme resistance [11] , [13] , [30] . To determine if the ability of the anti-σ factors to interact with lysozyme was a conserved feature we purified the histidine-tagged extracellular domains of both C . difficile RsiV69–289 ( RsiVCD ) and E . faecalis RsiV72–294 ( RsiVEF ) and conducted binding assays . Briefly , purified C . difficile RsiVCD or E . faecalis RsiVEF protein was loaded onto a nickel column and 2 mg of HEW lysozyme passed over the column bound protein . We found that columns containing either C . difficile or E . faecalis RsiV resulted in retention of HEW lysozyme on the column . Upon elution from the column , we found that HEW lysozyme co-eluted with both RsiVCD and RsiVEF ( Figure 6 ) . This suggests that the ability of the anti-σ factor , RsiV , to bind lysozyme is a conserved feature present in RsiV homologs from other species .
The primary observations of this work are that the anti-σ factor and RIP substrate RsiV acts as a sensor for the presence of lysozyme and that SipS functions as a site-1 protease . This hypothesis is supported by the following observations 1 ) Co-purification experiments in which RsiV binds both human and HEW lysozyme , 2 ) ITC showing direct binding of RsiV and HEW lysozyme , 3 ) RsiV cleavage in vitro at site-1 by SipS only in the presence of lysozyme , 4 ) Insufficiency of muramidase activity for σV activation and RsiV degradation and 5 ) Induction of σV activation and RsiV degradation by catalytically inactive human lysozyme . Taken together this data supports a model in which RsiV is a receptor for lysozyme . We identify the signal peptidase SipS as a site-1 protease for the anti-σ factor RsiV . The evidence to support signal peptidase as the site-1 protease for RsiV is as follows . The site-1 cleavage site of RsiV was identified and found to resemble a signal peptide cleavage site . Mutating this cleavage site blocks RsiV degradation and σV activation . Using a cell free transcription/translation system , we demonstrate in vitro that SipS was sufficient for site-1 cleavage of RsiV only in the presence of lysozyme . Together these data indicate that signal peptidase is the site-1 protease for RsiV . The signal peptidases of B . subtilis are redundant , but cells lacking both SipS and SipT are not viable [20] . RsiV was found to be cleaved at site-1 in the absence of SipS or SipT . Thus we hypothesize that one or more of the B . subtilis signal peptidases can cleave RsiV at site-1 in vivo . Previous work from our lab found that σV was activated only by lysozyme and not by other cell envelope stresses [9] . Here we showed that muramidase activity was not required nor was it sufficient to activate σV or induce RsiV degradation . In fact , we did not detect significant cleavage of RsiV in B . subtilis protoplasts generated by mutanolysin . However , upon addition of HEW lysozyme to these protoplasts RsiV was rapidly cleaved at site-1 . In addition , the catalytically inactive form of lysozyme ( R-lysozymeD53S ) was still able to activate σV and degrade RsiV . Finally , cleavage of RsiV by SipS in vitro was dependent upon HEW lysozyme suggesting RsiV binding to lysozyme is required for RsiV cleavage independent of muramidase activity . Based upon these observations we propose a model of σV activation in which RsiV is a receptor for the C-type lysozymes , HEW lysozyme and human lysozyme ( Figure 7 ) . In the absence of C-type lysozyme RsiV is in a conformation which is resistant to signal peptidase and RsiV inhibits σV activity by sequestering it to the membrane ( Figure 7 ) . In the presence of C-type lysozyme , the C-terminal domain of RsiV binds to lysozyme ( Figure 7 ) . When RsiV is bound to lysozyme , RsiV undergoes a conformational change , which allows signal peptidase to cleave RsiV at site-1 ( Figure 7 ) . This allows the site-2 protease to cleave the truncated form of RsiV leading to release of the RsiV-σV complex ( Figure 7 ) [14] . The cytoplasmic portion of RsiV is then presumably degraded by cytosolic proteases , resulting in free σV which can complex with RNA polymerase and transcribe genes required for lysozyme resistance ( Figure 7 ) [9] , [10] . There are several examples of anti-σ factors directly sensing inducing signals , however in these cases the anti-σ factors are not degraded in RIP dependent manner . For example the anti-σ factor of Streptomyces coelicolor σR , RsrA , is responsible for sensing redox stress [31]–[33] and the anti-σ factor of Rhodobacter sphaeroides σE , ChrR , is responsible for sensing singlet oxygen [34] , [35] . In E . coli regulation of the genes encoding the FecABCDE iron transport system are controlled by the iron responsive FecRI system . Evidence suggests that the anti-σ factor FecR can act indirectly as a sensor for the presence of iron-citrate [36] . However , to our knowledge this is the first example of a RIP controlled anti-σ factor acting as a receptor for the inducing signal . In the most well studied cases , the ECF σ factors that are controlled by RIP , it is the site-1 proteases that are the sensors for cell envelope damage . In particular it is clear that activation of σE in E . coli requires binding of unfolded outer membrane β-barrel proteins to the site-1 protease DegS , which allows DegS to cleave the σE anti-σ factor RseA [4] , [6] , [7] . In addition to DegS , the RseA binding protein , RseB , also contributes to sensing cell envelope stress [37]–[39] . In the case of σW activation in B . subtilis , isolation of mutations in the site-1 protease PrsW which result in constitutive degradation of RsiW again suggest the protease itself is the sensor for the inducing signal [8] . We found that SipS was able to cleave RsiV at site-1 only in the presence of HEW lysozyme . The enzymatic activity of signal peptidase is not known to be regulated by environmental signals . Since lysozyme binds RsiV we hypothesize that the mechanism for controlling site-1 cleavage of RsiV doesn't reside with the site-1 protease , but within the anti-σ factor itself . There are several examples of signal peptidases being required for production of quorum sensing signals . For example , in S . aureus signal peptidase is required for production of the quorum sensing peptide or auto-inducing peptide AIP [40] . In B . subtilis signal peptidases are required for production of the quorum sensing Phr peptides [41] . Once the Phr peptides released from the cell accumulate to sufficient quantities they are thought to directly or indirectly inhibit the Rap phosphatases which control initiation of sporulation and competence processes [42]–[44] . In each of these cases however the role of signal peptidase is not in sensing of a signal but in the production of a signal . There is some recent evidence that signal peptidases may be involved in signal input by cleaving a sensor for detecting β-lactam antibiotics . In Staphylococcus epidermidis it has been observed that the β-lactam sensor domain of BlaR1 ( a protease which degrades the transcription regulator BlaI ) was released in what appears to be a signal peptidase dependent process [45] . Similarly , in Staphylococcus aureus there is recent evidence to suggest that this β-lactam sensor domain is also removed at what appears to be a putative signal peptide cleavage site [46] . However it is not yet clear what impact this processing has on the signal transduction activity of BlaR1 . Homologs of the σV system in E . faecalis and C . difficile are also induced by lysozyme [11] , [13] , [30] . In both of these organisms σV activity is inhibited by RsiV [11] , [30] . We found that the RsiV homologs from both C . difficile and E . faecalis also bind HEW lysozyme , suggesting RsiV from these organisms may also sense lysozyme directly and activate using a similar mechanism . Although the site-1 protease that initiates RsiV degradation in E . faecalis or C . difficile is not known , an alignment of 185 RsiV homologs using MEME [17] reveals a highly conserved AXA motif near the predicted transmembrane domain of these RsiV homologs . Furthermore analysis of C . difficile , E . faecalis and B . subtilis RsiV homologs using SignalP [16] reveals potential signal peptidase cleavage sites in each RsiV homolog ( Figure S2A ) . Future work will be required to see if site-1 cleavage of RsiV in other organisms is also carried out by signal peptidase . Activation of σV in B . subtilis and E . faecalis requires cleavage of RsiV by a site-2 protease [14] , [47] . In addition to cleavage of RsiV and other anti-σ factors , RasP is also able to clear signal peptidase processed signal peptides from the membrane [48] . Thus , it appears that the σV-RsiV signal transduction system has “plugged into” the signal peptide processing system . Interestingly , the σV-RsiV signal transduction system is present primarily in many , but not all firmicutes , suggesting the σV–RsiV system may be transmitted by horizontal gene transfer . Thus the ability of the anti-σ factor to act as a sensor and capitalize on an essential system present in all bacteria , may provide a mechanism to control activation of horizontally acquired ECF σ factors . One of the surprising findings is the specific activation of σV by C-type lysozyme but not mutanolysin . In B . subtilis σV holo RNA polymerase transcribes oatA which encodes an O-acetyl transferase and in C . difficile and E . faecalis σV holo RNA polymerase transcribes a peptidoglycan deacetylase gene [9] , [13] , [49] , [50] . Interestingly both mechanisms increase resistance to C-type lysozymes ( HEW and human lysozyme ) [50]–[54] but not mutanolysin [55]–[57] . Thus rather than relying on peptidoglycan damage or cell envelope stress the RsiV- σV system appears to have evolved to respond to C-type lysozyme through a receptor-ligand interaction . This interaction induces genes which provide resistance to C-type lysozyme but not to other muramidases . An interesting question raised by the ability of B . subtilis to respond specifically to C-type lysozymes is when does B . subtilis encounter these factors . B . subtilis is often viewed simply as a soil organism however recent evidence suggests that it can colonize the intestinal tracts of a number of different organisms including Drosophila melanogaster , chickens , mice and humans [58]–[61] all of which encode C-type lysozymes [62] . Thus while B . subtilis is primarily a soil organism it may also have a more complex life associated with intestinal tract of a diverse number of organisms . It is tempting to hypothesize that lysozyme resistance could be an important trait required for colonization of the intestinal tract of higher organisms .
Strains are isogenic derivatives of PY79 , a prototrophic derivative of B . subtilis strain 168 , and are listed in Table 3 [63] . B . subtilis competent cells were prepared by the one-step method previously described [64] . All plasmid constructs are listed in Table 4 were confirmed by DNA sequencing ( University of Iowa ) . All oligonucleotides are listed in Table S1 . The rsiVA66W mutation was introduced onto the chromosome of PY79 by homologous recombination using the temperature sensitive plasmid pMAD [65] . To clone rsiVA66W we PCR amplified rsiVA66W plus ∼1 kb upstream with CDEP1892 and CDEP1562 and rsiVA66W+∼1 kb downstream using CDEP1561-CDEP1893 . The resulting PCR products were cloned into pMAD digested with SmaI using Isothermal assembly [66] . The resulting plasmid , pCE492 , was transformed into PY79 and the rsiVA66W mutation was introduced onto the chromosome by shifting temperatures as previously described [65] . The presence of the rsiVA66W mutation was confirmed by sequencing rsiV . Site-directed mutagenesis of rsiV was performed using the QuickChange site-directed mutagenesis kit ( Agilent Technologies ) . The rsiVA66W mutation was constructed using primer pairs CDEP1561 and CDEP1562 to generate plasmid pJH219 . For IPTG-inducible expression , the rsiVA66W mutant was moved into pCE292 [11] using LR Clonase II ( Invitrogen ) . The resulting plasmid , pJH224 , places the IPTG-inducible hyper-spank ( Phs ) promoter upstream of rsiVA66W and was transformed into B . subtilis CDE1563 to result in JLH623 . C-terminal 6×His tagged rsiV with an optimized ribosome binding site was PCR amplified from B . subtilis using oligos CDEP1544 and CDEP1430 cloned into pEntrD-TOPO ( Invitrogen ) resulting in pCE363 . For IPTG-inducible expression , the rsiV-6×his was moved into pCE292 using LR Clonase II resulting in pJH215 . The plasmid pJH215 was transformed into CDE1563 resulting in JLH548 . A vector for a 3×Flag-CBP was constructed by PCR amplification of the gene encoding the calmodulin binding peptide ( CBP ) from pMZS3F with CDEP1611 and CDEP1610 [67] , [68] . The resulting PCR was amplified with CDEP1612 and CDEP1610 . The PCR was digested with HindIII and SphI and ligated into pDR111 digested with the same enzymes resulting in pCE417 . The pCE417 was converted to a Gateway destination vector by cloning the RfC . 1 cassette into pCE417 digested with Eco53kI resulting in pCE418 . To construct a plasmid producing 3×Flag-cbp-RsiV+ , rsiV+ was moved from pCE352 onto pCE418 using LR Clonase II resulting in plasmid pCE422 . Vectors for cell free production of RsiV and SipS production were constructed by cloning the genes on a plasmid downstream of an SP6 promoter . The sipS gene was PCR amplified from B . subtilis using CDEP1678 and CDEP1679 . The PCR product was digested with AsiSI and SmaI and cloned into pEU-Flexi-His digested with AsiSI and PmiI using T4 ligase resulting in pCE448 . The 3×flag-cbp-rsiV6×his gene was PCR amplified from pCE422 using CDEP1677 and CDEP1714 . The PCR product was digested with AsiSI and SmaI and cloned into pEU-Flexi-His digested with AsiSI and PmiI using T4 ligase resulting in pCE455 . The 3×flag-cbp-rsiVA66W 6×his for cell free production of RsiVA66W was created by QuikChange mutagenesis resulting in pCE490 . The human lysozyme open reading frame was synthesized by GenScript and the codons were optimized for expression in yeast . Using primers CDEP1888 and CDEP1889 human lysozyme was PCR amplified and cloned into P . pastoris expression vector pICZα ( Invitrogen ) by isothermal assembly [66] resulting in pJH326 . To produce inactive lysozyme a mutation was constructed to change the codon for aspartate 53 to serine ( lysozymeD53S ) using primers CDEP1847 and CDEP1848 and PCR QuickChange site-directed mutagenesis ( Agilent Technologies ) resulting in pJH327 . Expression vectors pJH326 and pJH327 were transformed into P . pastoris GS115 via the lithium chloride method ( Invitrogen [69] ) resulting in JLH1056 and JLH1057 respectively . Appropriate integration of the plasmids was confirmed by zeocin resistance and PCR using the primers CDEP1888 and CDEP1889 . For purification of E . faecalis RsiV , the portion of rsiV encoding the C-terminal extracellular domain ( rsiVEF ) was PCR amplified using CDEP1434 and CDEP1435 . The PCR product was cloned into pEntrD-TOPO resulting in pJH228 . To tag E . faecalis RsiV with 6×His , rsiVEF , was moved into pDEST17 using LR Clonase II resulting in pJH227 . For purification of C . difficile RsiV the portion of the rsiV encoding the C-terminal extracellular domain ( rsiVCD ) was PCR amplified using CDEP928 and CDEP189 . The PCR product was cloned into pEntrD-TOPO resulting in pCE302 . To tag C . difficile RsiV with 6×His , rsiVCD , was moved into pDEST17 using LR Clonase II , resulting in pKBW216 . To tag B . subtilis RsiV with GST , rsiV59–285 , was moved from pCE458 [14] into pDEST15 using LR Clonase II resulting in pKBW204 . Construction of 2×flag-rsiV59–285 was performed by PCR amplification from B . subtilis genomic DNA using CDEP1140 and CDEP952 . The resulting product was used as template in another round of PCR using CDEP950 and CDEP952 and cloned into pEntrD-TOPO , resulting in pKBW101 . This was moved into the IPTG inducible 6×His expression vector pDEST17 using LR Clonase II , resulting in pKBW201 . ΔsipS::cat and ΔsipT::tet were constructed using long flanking homology PCR . Briefly sipS flanking regions were constructed by PCR amplifying with CDEP1697-CDEP1709 and CDEP1710-CDEP1700 . The sipT flanking regions were constructed by PCR amplifying with CDEP1701-CDEP1711 and CDEP1712-CDEP1704 . The resulting PCR products were used as primers to amplify either a chloramphenicol antibiotic cassette generated by PCR from pDG1661 using ( CDEP1954-CDEP1955 ) or tetracycline antibiotic cassette from either pDG1515 respectively . The PCR products were transformed into B . subtilis JLH402 ( amyE::Phs-rsiV+ ( spec ) ΔsigVrsiV::kan ) and confirmed by PCR resulting in JLH933 and JLH953 respectively . Antibiotics were used at the following concentrations: chloramphenicol , 5 µg/ml; erythromycin plus lincomycin , 1 µg/ml and 25 µg/ml; kanamycin , 5 µg/ml; spectinomycin , 100 µg/ml; tetracycline , 10 µg/ml; ampicillin 100 µg/ml . The β-galactosidase chromogenic indicator 5-bromo-4-chloro-3-indolyl β-D-galactopyranoside ( X-Gal ) was used at a concentration 100 µg/ml . Isopropyl β-D-1-thiogalactopyranoside ( IPTG ) was used at a final concentration of 1 mM unless otherwise noted . Cells producing RsiV-6×His were grown to an OD of 1 and then subcultured 1∶100 into 1L LB+IPTG ( 1 mM ) and grown to an OD of 0 . 8 . Cells were pelleted by centrifugation at 5000× g and frozen at −80°C . Cell pellets were thawed on ice and resuspended in 20 mL protoplast buffer ( 0 . 4 M sucrose , 10 mM potassium phosphate , 15 mM MgCl2 ) [70] . HEW lysozyme was added to a final concentration of 8 µg/ml and the cells were incubated at 37°C for 45 minutes . Protoplast formation was confirmed by phase contrast microscopy . Cells were pelleted by centrifugation at 5000× g and RsiV-6×His was purified from the supernatant using Ni resin ( Thermo-Fisher ) . The resulting protein was separated by SDS PAGE and transferred to PVDF membrane ( BioRad ) . The band containing the protein of interest was confirmed by immunoblot with anti-RsiV59–285 antibodies ( Figure S1 ) . The band of interest was cut out from the membrane and submitted for Edman degradation analysis ( Iowa State University ) . Cultures were grown overnight in LB broth at 30°C and 20 µl were spotted onto LB agar + 10 µg/ml lysozyme . Plates were incubated at 37°C for 6 hours . Cells were harvested and resuspended in 500 µl of Z buffer ( 60 mM Na2HPO4 , 40 mM NaH2PO4 , 10 mM KCl , 1 mM MgSO4 , 50 mM β-mercaptoethanol pH 7 . 0 ) . Cells were transferred to a 96 well plate and optical density ( OD600 ) determined . Cells were permeabilized by mixing with chloroform and 2% sarkosyl [9] , [71] . Permeabilized cells ( 100 µl ) were mixed with 10 mg/ml ortho-Nitrophenyl-β-galactoside ( ONPG , RPI , 50 µl ) and OD405 was measured over time . β-galactosidase activity units ( µmol of ONP formed min−1 ) ×103/ ( OD600×ml of cell suspension ) were calculated as previously described [72] . Experiments were performed in triplicate . Mean and standard deviation are shown . To determine lysozyme MIC values , B . subtilis strains were grown 16 h at 30°C and then subcultured 1∶100 in LB . Cells ( 100 µl ) were inoculated into 100 µl of two fold serial dilutions of HEW lysozyme ranging from 200 µg/ml to 0 . 15 µg/ml in a round-bottom 96 well plate . The absorbance at OD600 was taken every 30 minutes using a Tecan F50 ( Tecan ) over a period of 20 hrs . Growth was defined as an OD600 greater than 0 . 1 at 14 hrs . To determine lysozyme zones of clearing , B . subtilis strains were grown 16 h at 30°C and then diluted 1∶100 in 1 . 5 mL LB top agar ( 0 . 75% ) containing X-Gal ( 100 µg/ml ) . Top agar was spread on solid LB+X-Gal and allowed to solidify . Whatman filter disks containing 10 µl of 10 mg/ml HEW lysozyme were placed on the top agar and incubated 16 h at 37°C . Plasmids were purified using QIAprep spin columns according to the manufacturer's instructions and resuspended in 30 µl of Milli-Q water . The concentration of the RNase-free plasmid DNA was determined by absorbance at 260 nm . Small-scale transcription reactions were performed as previously described [21] . Briefly , the reaction mixtures were composed of 80 mM HEPES-KOH pH 7 . 8 , 2 mM magnesium acetate , 2 mM spermidine , 10 mM DTT , 4 mM of each nucleotide triphosphate ( ATP , CTP , UTP and GTP ) , 1 . 6 U/µl SP6 RNA polymerase ( Promega ) , 1 U/µl RNasin ( Promega ) and 0 . 2 mg/mL of RNase-free plasmid DNA in a 10 µl total reaction volume . Each sample was incubated at 37°C for 4 h . The mRNA from each transcription reaction ( 5 µl ) was mixed with 20 µl of the translation mix composed of 25% v/v wheat germ extract ( WEPRO 2240 Cell free Sciences , Yokohama , Japan ) , 13 mM HEPES-KOH pH 7 . 8 , 55 mM KOAc , 1 . 7 mM Mg ( OAc ) 2 , 0 . 22 mM spermidine hydrochloride , 2 . 2 mM DTT , 0 . 7 mM ATP , 0 . 14 mM GTP , 9 mM creatine phosphate , 0 . 003% NaN3 , 1 mg/mL creatine kinase and 2 mM amino acids . The reaction mixtures were added to 12-kDa MWCO dialysis cups . The reservoir buffer contained all the reagents listed above except RNasin and wheat germ extract as previously described [21] . Each reaction was incubated for 16 h at room temperature . The pellet fractions from the above-described translation reactions for SipS , RsiV ( full-length ) , and RsiVA66W were resuspended in 5 mM MES pH 7 . 0 , 50 mM NaCl and mixed at a 1∶3 SipS∶RsiV molar ratio . Reactions were incubated for 6 h at 37°C . The role of HEW lysozyme ( 0 . 3 mg/mL ) as an activator of the RsiV cleavage was also evaluated . The cleavage of RsiV was assessed by the products observed at 26 kDa and 17 kDa and confirmed by Immunoblot analysis . Strains were grown for 16 hours in LB at 37°C . The cells were subcultured 1∶100 in LB+1 mM IPTG at 37°C and grown to an OD600 of 0 . 8–1 . The cells were pelleted by centrifugation and resuspended in 100 µl of 2× Laemmli sample buffer and lysed by repeated sonication . Samples were electrophoresed on a 15% SDS Polyacrylamide gel ( BioRad ) . The proteins were then blotted onto nitrocellulose . The proteins were detected by incubating with a 1∶10 , 000 dilution of anti-RsiV59–285 antibodies [14] or 1∶15 , 000 dilution of anti-σA antibodies followed by 3 washes and incubation in a 1∶10 , 000 dilution of goat anti-rabbit IgG ( H+L ) IRDye 800CW ( Li-Cor ) and imaged on an Odyssey CLx ( Li-Cor ) . Quantification of band intensities was performed using Image Studio software ( Li-Cor ) . P . pastoris was grown overnight in 5 ml BMGY ( Buffered Glycerol Complex Medium; 100 mM potassium phosphate , pH 6 . 0 , 1% yeast extract , 2% peptone , 1 . 34% Yeast Nitrogen Base , 0 . 0004% biotin , 1% glycerol ) at 30°C and then subcultured into 300 ml BMGY overnight 30°C in 2L baffled flasks . Cultures were pelleted and washed with BMMY ( Buffered Methanol Complex Medium; 100 mM potassium phosphate , pH 6 . 0 , 1% yeast extract , 2% peptone , 1 . 34% Yeast Nitrogen Base , 0 . 0004% biotin , 0 . 5% methanol ) [73] . The cell pellet was resuspended in 300 ml BMMY and grown at 30°C for 5 days . Methanol to a final concentration of 5% was added each day . Cultures were pelleted by centrifugation and the supernatant was clarified by filtering through a 0 . 2 µm filter . The supernatant was exchanged into 50 mM sodium acetate pH 6 . 2 , and concentrated by running the supernatant over a 3 kDa carbon fiber filter ( AG Technologies Corporation ) . Further purification was performed by FPLC using a Capto S exchange column ( GE Healthcare Life Sciences ) and a 3 kDa micron filter unit ( Millipore ) . Protein concentration was determined by reading the absorbance at 280 nm . Lysozyme activity was measured by the rate of Micrococcus lysodeikticus peptidoglycan clearing at 450 nm as previously described [74] . Briefly , M . lysodeikticus peptidoglycan was suspended to an OD600 of 0 . 9 and mixed with equal volumes of either buffer alone ( 50 mM NaOAc pH 6 . 2 ) , HUM Lysozyme 20 µg/ml , R-lysozyme 20 µg/ml or R-lysozymeD52S . The rate of peptidoglycan clearing was monitored at 450 nm for 10 minutes . Overnight cultures were subcultured 1∶100 in LB+1 mM IPTG and grown to an OD600 of 0 . 8–1 . Cells were pelleted by centrifugation , washed with PBS , and resuspended in equal parts 1 M sucrose and 60 mM Tris-Cl , 4 mM MgCl2 to form a protoplast buffer [75] , [76] . Mutanolysin was added to a final concentration of 2 µg/ml , and incubated shaking at 37°C for 40 minutes . Protoplast were confirmed by phase contrast microscopy . Protoplast samples were left untreated or treated with lysozyme ( 2 µg/ml ) for 10 minutes . An equal volume of 2× Laemmli sample buffer was added to the sample before for immunoblot analysis as described . Overnight cultures of E . coli BL21λDE3 containing either pKBW201 ( pDEST17-6×his-2×flag-rsiV59–285 ) , pKBW204 ( gst-rsiV59–285 ) , pKBW216 ( pDEST17-6×his-rsiVCD ) or pJH227 ( pDEST17-6×his-rsiVEF ) were grown at 30°C in LB+ampicillin . The cell cultures were diluted 1∶100 into 500 ml of LB+ampicillin in 2 L baffled flasks and incubated at 30°C to an OD600 of 0 . 5–0 . 6 . IPTG was added to a final concentration of 1 mM to induce protein production and the cultures incubated for an additional 4 hours . Cells were chilled on ice and collected by centrifugation at 5000× g . Cell pellets were stored at −80°C until time for purification . Cell pellets were thawed on ice and resuspended in 5 ml lysis buffer ( 50 mM Sodium Phosphate , 250 mM NaCl , 10 mM imidazole , pH 8 . 0 ) per 500 ml of initial culture volume . Cells were lysed by passaging through a Microfluidics LV1 high shear microfluidizer ( Newton , MA ) twice . Lysate was centrifuged at 15 , 000× g , for 30 minutes at 4°C , to pellet cellular debris . Cleared lysate was applied to a nickel affinity column to bind 6×His-tagged protein ( Qiagen ) . The column was washed with 10 column volumes of wash buffer ( 50 mM sodium phosphate , 250 mM NaCl , 20 mM imidazole , pH 8 . 0 ) . Protein was eluted with elution buffer ( 50 mM Sodium Phosphate , 250 mM NaCl , 250 mM imidazole , pH 8 . 0 ) and collected in 0 . 5 ml fractions . Samples from each fraction were analyzed by SDS-PAGE and elution fractions containing the desired protein were combined . Combined fractions were then dialyzed into lysis buffer to remove the excess imidazole . The protein was further purified with a GE Healthcare AKTA FPLC ( GE Healthcare Sciences Pittsburg , PA ) using a HisTrap HP nickel affinity column . Fractions containing the 6×His-2×Flag-RsiV59–285 were again combined and dialyzed into a storage buffer ( 25 mM Tris , 200 mM NaCl , 5% glycerol , pH 8 . 0 ) and flash frozen at −80°C until use . Cell pellets were thawed on ice and resuspended in 2 . 5 ml PBS-EW ( 50 mM NaH2PO4 , 150 mM NaCl , 1 mM DTT , 1 mM EDTA , pH 7 . 2 ) per 250 ml of initial culture volume . Cells were lysed by 2× passage through a Microfluidics LV1 high shear microfluidizer ( Newton , MA ) . Lysate was centrifuged at 15 , 000× g , for 30 minutes at 4°C , to pellet cellular debris . Cleared lysates were then passed over a Glutathione HiCap Matrix column ( Qiagen Valencia , CA ) . The column was washed with 5 column volumes of PBS-EW . Protein was eluted with buffer TNGT ( 50 mM Tris , 0 . 4 M NaCl , 50 mM reduced L-Glutathione , 0 . 1% Triton-x-100 , 1 mM DTT ) and collected in 0 . 5 ml fractions . Samples from each fraction were analyzed by SDS-PAGE and elution fractions containing the desired protein were combined . Purified GST-RsiV59–285 was then dialyzed into a buffer containing 50 mM Tris-HCl pH 7 . 5 , 200 mM NaCl and stored at 4°C until use . For 6×His-tagged proteins , expression and purification was performed described above , with the following alterations . After the initial application of wash buffer 1 , 2 ml of 1 mg/ml HEW lysozyme ( Sigma Aldrich ) was applied to the column and flow through collected . An additional 5 column volumes of wash buffer 1 was applied to remove any unbound HEW lysozyme . Elution of the proteins then proceeded as described . Samples from each fraction were mixed with an equal volume with 2× Laemmli sample buffer and analyzed on 15% SDS-PAGE gels stained with Coomassie brilliant blue . To ensure lysozyme binding was not the result of interactions with contaminating proteins from the expression strain or spurious binding to the Ni resin ( Thermo-Fisher ) , mock-expression cells were used in a pull-down experiment as a negative control . Briefly , BL21λDE3 cells containing no plasmid were grown and processed as described . Cleared lysates from these cells were applied to a Ni affinity column in which lysozyme was then passed over . The column was washed and protein eluted under the same conditions as our normal pull-down assay . Co-purification assays utilizing GST-tagged proteins were completed in a similar manner with the following modifications . Purified GST-tagged protein was dialyzed into PBS-EW and 2 mg of protein was applied to a Glutathione HiCap Matrix column . The column was washed with 5 column volumes of PBS-EW . 2 mg of HEW lysozyme , human lysozyme , or mutanolysin , in PBS-EW , was applied to the column . PBS-EW buffer and TNGT buffer were used as wash and elution buffers , respectively . Samples were analyzed by SDS-PAGE . The affinity of the interaction ( Kd ) between RsiV and HEW lysozyme was determined by isothermal titration calorimetry ( ITC ) . Purified 6×His-2×Flag-RsiV59–285 was purified as described above . HEW lysozyme ≥98% pure was purchased from Sigma Aldrich . The proteins were co-dialyzed three times in 2 liters of 50 mM Na2HPO4 , 200 mM NaCl , and pH 7 . 0 buffer for 8 h ( each ) at 4°C . Final protein concentrations as determined by absorbance at OD280 were adjusted to 6×His-2×Flag-RsiV59–285 ( 0 . 01 mM ) and HEW lysozyme ( 0 . 1 mM ) with filtered dialysate . The protein samples were degassed and ITC measurements recorded using a MicroCal VP-ITC System ( GE Healthcare ) with HEW lysozyme as the injected sample and 6×His-2×Flag-RsiV59–285 as the cell sample . 21 injections of HEW lysozyme were used , with 180 seconds spacing between events . The chamber was kept under constant stirring at 350 rpm and all experiments were performed at 25°C . The binding reaction reached saturation during the experiment and control experiments where HEW lysozyme was injected into buffer showed that the heats of dilution were constant across all injections . The constant heat of dilution , as determined by the average of the last 3–5 injections , was subtracted and the data are analyzed using the single site binding model provided in the ITC analysis package . The values for affinity , stoichiometry ( n ) and change in enthalpy ( ΔH ) and entropy ( ΔS ) obtained from three independent experiments were averaged and the standard deviation determined . | All cells sense and respond to changes in their environments by transmitting information across the membrane . In bacteria , σ factors provide promoter specificity to RNA polymerase . Bacteria encode Extra-Cytoplasmic Function ( ECF ) σ factors , which often respond to extracellular signals . Activation of some ECF σ factors is controlled by stepwise proteolytic destruction of an anti-σ factor which is initiated by a site-1 protease . In most cases , the site-1 protease required to initiate the RIP process is thought to be the signal sensor . Here we report that the anti-σ factor RsiV , and not the site-1 protease , is the sensor for σV activation . Activation of the ECF σ factor σV is induced by lysozyme , an innate immune defense enzyme . We identify the site-1 protease as signal peptidase , which is required for general protein secretion . The anti-σ factor RsiV directly binds lysozyme . Binding of lysozyme to RsiV allows signal peptidase to cleave RsiV at site-1 and this leads to activation of σV . Thus , the anti-σ factor functions as a bacterial receptor for lysozyme . RsiV homologs from C . difficile and E . faecalis also bind lysozyme , suggesting they may utilize this receptor-ligand mechanism to control activation of σV to induce lysozyme resistance . | [
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... | 2014 | Evidence of a Bacterial Receptor for Lysozyme: Binding of Lysozyme to the Anti-σ Factor RsiV Controls Activation of the ECF σ Factor σV |
The activities of the Global Programme for the Elimination of Lymphatic Filariasis have been in operation since the year 2000 , with Mass Drug Administration ( MDA ) undertaken yearly in disease endemic communities . Information collected during MDA–such as population demographics , age , sex , drugs used and remaining , and therapeutic and geographic coverage–can be used to assess the quality of the data reported . To assist country programmes in evaluating the information reported , the WHO , in collaboration with NTD partners , including ENVISION/RTI , developed an NTD Data Quality Assessment ( DQA ) tool , for use by programmes . This study was undertaken to evaluate the tool and assess the quality of data reported in some endemic communities in Ghana . A cross sectional study , involving review of data registers and interview of drug distributors , disease control officers , and health information officers using the NTD DQA tool , was carried out in selected communities in three LF endemic Districts in Ghana . Data registers for service delivery points were obtained from District health office for assessment . The assessment verified reported results in comparison with recounted values for five indicators: number of tablets received , number of tablets used , number of tablets remaining , MDA coverage , and population treated . Furthermore , drug distributors , disease control officers , and health information officers ( at the first data aggregation level ) , were interviewed , using the DQA tool , to determine the performance of the functional areas of the data management system . The results showed that over 60% of the data reported were inaccurate , and exposed the challenges and limitations of the data management system . The DQA tool is a very useful monitoring and evaluation ( M&E ) tool that can be used to elucidate and address data quality issues in various NTD control programmes .
The Global Programme to Eliminate Lymphatic Filariasis ( GPELF ) started its activities in the year 2000 , with the aims of eliminating lymphatic filariasis ( LF ) as a public health problem by the year 2020 , through mass drug administration ( MDA ) in endemic implementation units ( IU ) [1] . In many countries significant progress has been made in controlling the disease; however , many programmatic challenges continue to affect the performance of National LF Control Programmes . Notable among these is the effective implementation of the preventive chemotherapy strategy in endemic communities [2 , 3] . The quality of data reported in healthcare systems is important for evaluating programmes , as such high quality health information is crucial in addressing global health challenges and building strong public health systems [4] . Data Quality Assessment ( DQA ) is a scientific and statistical evaluation of data to determine if they meet the objectives , and are of the right type , quality , and quantity to support their intended use [5] . At present yearly MDA has been undertaken in 53 of the 73 LF endemic countries [6] . During the MDA various data are collected at various levels to help in the planning and improvement of activities . As such high quality becomes the prerequisite for better information , better decision-making and better population health [7] . In all LF endemic Districts in Ghana , various information are collected during MDAs , including number of treatments given , number of people treated , number of tablets used , reasons for non-treatment , place of treatment , individual identification ( name and address ) , name of drug used , age and sex of drug recipients , etc . Public health data can be useful for decision-making , effective service delivery , and evaluating prevailing programmes in order to maintain high quality of healthcare . Poor data quality not only contributes to poor decisions and loss of confidence in the systems , but also affects the validity of impact evaluation studies [8] . Furthermore , variability in data quality from health management information systems in sub-Saharan Africa threatens utility of these data as a tool to improve health systems [9] . Thus , collecting accurate data will aid appropriate intervention for elimination . The WHO , in collaboration with NTD partners , including ENVISION/RTI , developed a DQA tool to identify and characterize challenges with NTD data quality–including incomplete and inaccurate data or data not timely reported–following a recommendation from the WHO Working Group on Monitoring and Evaluation of Preventive Chemotherapy . The DQA tool focuses exclusively on verifying the quality of reported data quantitatively and assessing the underlying data management and reporting systems qualitatively for standard programme-level output indicators . Data quality dimensions include accuracy , reliability , completeness , timeliness , precision , integrity and confidentiality [10] . In 2014 , training was undertaken to introduce the tool to various stakeholders , with field testing to follow [10] . This study was undertaken to evaluate the quality of data reported in selected communities or service delivery points ( SDP ) , and the data management functions and capabilities in three LF endemic Districts in Ghana .
Approval for this study was obtained from the Ethical Review Board of the Noguchi Memorial Institute for Medical Research ( IRB 077/13-14 ) . The District Health Office was informed of the study and permission sought to assess data from the registers . Written informed consent was obtained from all individuals interviewed during the study . This study was undertaken in the Ahanta West , Nzema East and Agona East Districts of Ghana ( Fig 1 ) . The Ahanta West and Nzema East Districts , both located in the Western Region of Ghana , started MDA in the years 2000 and 2002 , respectively . Both districts represent areas with persistent transmission , with MDA ongoing at the time of this study in 2014 . The Agona East District is located in the Central Region of Ghana and started MDA activities in 2002 . By 2010 , LF infection rate in Agona East District was considered to be below the 2% antigenemia and 1% microfilaremia thresholds required to stop MDA [11] . As such , treatment in Agona East ceased in 2010 . Thus , for the purpose of comparing data between sites , the 2010 data registers were analysed for all the sites surveyed . While the DQA tool advocates the selection of sites based on probability proportionate to size ( PPS ) , the survey communities in this study were randomly selected because the population estimates of the communities could not be obtained beforehand . Eight sites were surveyed in the Ahanta West District and 6 sites from the Nzema East and Agona East Districts respectively . A cross sectional study involving the review of data registers and interview of drug distributors , disease control officers and health information officers was done . Data registers at the SDPs capture data during MDA for compilation by health workers . Information contained in these registers includes age , sex , height , number of households , population , drug used , number of tablets used , number of tablets received , etc . While the tool is capable of being used at the SDPs and all intermediate data aggregation levels ( IALs ) , in this study only the SDPs were evaluated for data quality since they represent the first data collection and handling locations . In assessing the data management systems and functions , the intermediate data aggregation level 1 ( IAL-1 ) represents the last point for information dissemination into the SDPs , and the first point of data collection from the SDPs . The interview tool used is a standard questionnaire , developed as part of the DQA tool , with scoring guidelines coded 3 for “Yes , completely” , 2 for “Partly” and 1 for “No , not at all” . These scores take into consideration the response from all the interviewees . The DQA tool and further information can be obtained from the WHO Department of Control of Neglected Tropical Diseases . To evaluate the quality of data reported in the study areas , data registers for SDPs for 2010 were obtained from IAL-1 , for assessment . The assessment verified reported results ( from IAL-1 ) in comparison with recounted values ( from SDPs ) for five indicators , i . e . number of tablets received , number of tablets used , number of tablets remaining , MDA coverage , and population treated . Sources of data for the five indicators were examined to determine the percentage of reports that were available , on-time , completed , collected and measured consistently , protected from deliberate bias , and maintained according to national or international standard . Further , drug distributors , disease control officers and health information officers available at the time of the study ( at the first data aggregation level ) and who were willing , were interviewed using the DQA tool , to determine the M&E structure , functions and capabilities , indicator definitions , links with national reporting system , data management processes and data collection and reporting forms and tools . For each of the five indicators assessed a verification factor ( VF ) was calculated as the ratio of recounted value ( from the data register ) of the indicator to the reported value , expressed as a percentage . A value of 100% indicates a high level of accuracy . Values above 100% indicate under reporting , whiles values below 100 suggest over reporting . In interpreting the results , indicator values between 95–105% across multiple sites were considered as high quality reporting . Indicator values less than 90% and greater than 110% were considered poor quality reporting . Verification factors above 300 were excluded from the analysis . The values were compiled and graphs generated in GraphPad Prism version 6 . 05 . Statistical significance was set at p-values less than 0 . 05 . Scores for the functional areas in the Data Management Assessment were automatically computed by the DQA tool , which also generates a spider chart . At individual sites , functional areas with scores >2 . 5 indicate high quality , whiles scores<2 . 0 reflect low quality . However , when comparing scores across sites , scores> = 2 . 8 indicate good performance and scores < = 1 . 5 indicate that a functional area needs to be improved .
In each District , 3–4 days were spent in reviewing and evaluating the data , and conducting interviews . The SDPs were visited by the study team to review the selected indicators from the community registers . It is worth mentioning that except for being interviewed by the study team , individuals working at any level with the LF control programme were not directly involved in the use of the tool , and the study was undertaken independently by personnel from the Noguchi Memorial Institute for Medical Research ( NMIMR ) –University of Ghana . Further , the evaluation of the tool took advantage of ongoing parasitological and entomological surveys in the Districts . The results showed that 40% ( 40/100 ) of all data examined were over reported while 22% ( 22/100 ) were under reported . The only consistent indicator that was accurately reported across sites was the number of tablets received . For the five indicators assessed , the VF were plotted for comparison between Districts ( Fig 2 ) . Between Districts , there was no significant difference in the indicators assessed , except for the population treated in Agona East . Results of the data management assessment in the Districts are shown in Fig 3 . In Agona Nkwanta , indicator definitions and reporting guidelines were the strongest functional areas followed by data collection and reporting forms and tools . Data management processes was the weakest functional area , followed by M&E structure , function and capabilities . In Axim District Health Directorate , the strongest functional area was indicator definitions and reporting guidelines , followed by M&E structure , functions and capabilities then data-collection and reporting forms and tools . In Konyarko health post , the strongest functional area was the data collection and reporting forms and tools . In terms of the data quality dimensions , the observed values were more or less consistent between sites ( Fig 4 ) . In Ahanta West , the lowest reporting performance was confidentiality ( 75% ) , followed by timeliness ( 79% ) . However , the best reporting performance was reliability ( 88% ) , followed by availability ( 86% ) and integrity ( 86% ) . In Nzema East District , the lowest reporting performance was confidentiality ( 77% ) , followed by completeness ( 79% ) . On the other hand , the best reporting performance was reliability ( 89% ) , followed by integrity ( 86% ) . In Agona East , the lowest reporting performance was availability ( 68% ) , followed by timeliness ( 70% ) , while the best reporting performance was reliability ( 90% ) , and followed by integrity ( 82% ) .
Data are vital to public health , since they signify and provide a documented account of public health practice . The extensive application of data , for the evaluation of public health responsibility and performance , highlights the importance of data quality and how to evaluate it . This study reflected the poor quality of data reported following MDA for LF , indicated as the over reporting or under reporting of the indicators assessed . In particular , is the overestimation of MDA coverage in many of the sites surveyed . Overestimation of MDA coverage in NTD programmes has been reported in many studies [12–14] . MDA coverage is the core indicator required for global reporting on preventive chemotherapy , thereby reflecting the performance of control programmes [14] and must therefore be strictly monitored . It is important to note that before MDA , drug distributors are gathered at the District level for training and orientation . In some of the communities , the drug distributors recalled having supervision support during the MDA , while this was not the case in other communities . In terms of the functional areas of the LF control programme , even though study sites registered a score >2 . 0 , which is considered passable , no site demonstrated a high quality data reporting system , given that no site scored >2 . 5 for all functional areas . However , in some of the surveyed areas , health workers reported that strict guidelines were received , defining the indicator to report on , where , when and to whom to send reports , and these guidelines have been vividly stated and followed . Additionally , this study found that community drug distributors always used a standard data capture tool , made available at the national level . t . Training plans , and trained data management staff were also available in some of the areas . On the other hand , data quality controls , and back-up procedures , confidentiality of personal data and feedback on data quality were not available . Moreover , trained data management staff and training plans were not sufficient , as well as non-availability of M&E organizational structure . Results from this study suggest that data management processes is the weakest functional area across sites . The reasons for this must further be investigated and addressed accordingly . Similar gaps , such as lack of M&E guidelines , poor feedback given to sub-national levels , poor data use and poor general data management capacity , lack of training programmes to build M&E skills , few standard practices related to confidentiality and document storage , have been reported following DQA in other countries [15 , 16] . Overall , data confidentiality , completeness and timeliness require improvement in terms of reporting performance . In the survey sites , data was not managed according to protection and use standard and in most cases data were not reported on time . The completeness of data also needs to be improved as the data examined had missing reports . The data quality dimensions reported in this study are somewhat comparable to those reported elsewhere [17–19] and may indicate the general quality of data in health care systems . The validity of data reported also varied with the various indicators assessed . The most accurately reported indicator was number of tablets received . This is because the supply of drugs to communities was strictly supervised by the Districts . With the renewed commitment from pharmaceutical companies and other NTD partners at the London Declaration on NTDs in 2012 [20] , emphasis must be placed on value for money to ensure that the resources invested are worthwhile . The expanded drug donations and the programme goals presented in the NTD roadmap for implementation point to the importance of having a robust monitoring and reporting system , from the point of treatment by a drug distributor to the national and international levels [10 , 21] . While some communities reported good quality data for some of the indicators assessed in this study , the majority of the indicators assessed were of poor quality , necessitating the need to get all communities up to standard . Thus , an important programmatic application of the DQA is to enable objective identification of context-specific issues that compromise data challenges and thereby trigger corrective action before the subsequent MDAs . For example , the use of the tool in LF may help inform how long to treat communities if measures are put in place to address challenges in order to consistently attain the required 65% MDA coverage rates , thus reducing the cost involved in undertaking further yearly treatment beyond the recommended 5–6 years , as per WHO guidelines [1 , 22] . While Agona East appears to have the poorest data quality , it is the one District where MDA has been stopped . It is plausible that other factors such as baseline disease prevalence , vector competence and non-compliance to MDA may be at play [23–25] , prompting the need for continued treatment in Districts with persistent transmission . As such , the link between data quality and programme success/failure needs to be further evaluated . Nonetheless , this tool may complement the Transmission Assessment Surveys ( TAS ) undertaken to inform on the need to stop MDA [26] , by ensuring that the reported MDA coverage rates have truly been achieved in the evaluation units under assessment . Similarly , donated drugs must be properly accounted for , to ensure that they are put to their intended use , while monitoring the population treated may help in forecasting and budgeting for future MDAs . While other assessment methods rely on the use of questionnaires and ability of the study respondents to recall past events [13 , 14 , 27] , such as having taken the drug , this tool relies on examining and recounting data recorded in community registers . Though the former method may be subject to proper description of the specific MDA by the questionnaire administrator ( considering the various treatment regimen for different NTDs ) and the honesty of the study respondents , the DQA tool relies on data recorded for each individual in the register at the SDP . Thus , the tool may be considered as providing a more reliable estimate of indicators for assessing programme performance , with the ability to compare retrospective to current data . However , it is important to note that the tool is also limited to the raw data recorded , such that incorrect entries ( especially individual records such as age and the number of tablets given to a particular person ) in community registers cannot be detected using the tool . In this study , PPS sampling wasn't used . Thus , the findings are only applicable to the areas under study , even though it is likely that the same findings occur nationwide . Nevertheless this would need to be confirmed by doing DQA with a representative sampling methodology . Further , in the Districts , data from 2010 was evaluated . While the evaluation of retrospective data can provide valuable information , the use of the tool for programme evaluation should consider the most up-to-date data in order for challenges to be resolved in real-time . In addition to these challenges in the study , the WHO protocol requires co-implementation with Ministry of Health ( MoH ) , NTD programme and other NTD partners operating in the country . This study was undertaken as a research activity , with limited funding , taking advantage of on-going surveys in the study areas . As such , future implementations of the tool should involve the MoH , NTD programme and other partners , in order for the outcomes to be owned by the MoH and therefore more likely to be acted upon to improve programme performance . In conclusion , this study revealed that the majority of data reported in LF control programme in the study areas was inaccurate , and highlighted some programmatic challenges that must be addressed . At the time of this study , only five indicators could be assessed at a time using the DQA tool and perhaps provision could be made for many more indicators to be evaluated . The DQA tool holds tremendous value in evaluating NTD control programmes , and its use in indicator assessment points to its usefulness in assisting programme managers to address the issues of inaccurate reporting and data quality , following MDA . Using the tool is quite simple and it is recommended that sub-District , District , regional and national management levels use the tool in assessing their NTD programme performance . However , further sensitization and training on this tool for NTD programme personnel or teams at sub-national levels is recommended to ensure its use in the M&E of NTD control programmes . While the results from this study are informative , a more complete assessment of the LF Control Programme ( involving the MoH , NTD programme and other NTD partners in the country ) must be undertaken at all levels , in order to establish appropriate programmatic responses . All programme activities need to be closely supervised in order to ensure accurate data . | The Global Programme for the Elimination of Lymphatic Filariasis has been conducting yearly treatment of entire communities in endemic countries since the year 2000 . During the treatments various information is collected on the populations , number of medicine tablets distributed and remaining , the number of people treated , etc . that can be used to evaluate the performance of the lymphatic filariasis control programme . For example , information on the number of people treated in a District gives an indication of the success of the programme . In line with this , the World Health Organization in collaboration with other agencies developed a tool for Neglected Tropical Diseases ( NTD ) to help national control programmes assemble and analyse their data . This study was undertaken to evaluate this tool and the information collected from some endemic communities in Ghana . Community registers were reviewed and personnel involved in drug distribution in the communities were interviewed to collect the necessary information . The results showed that more than half of the data reported in the endemic communities surveyed were inaccurate . It also revealed some weaknesses in the data management and reporting system . The tool , however , is good for identifying and quantifying the magnitude of the challenges encountered in the information management for NTD programmes , especially at peripheral levels . | [
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... | 2016 | Assessing Lymphatic Filariasis Data Quality in Endemic Communities in Ghana, Using the Neglected Tropical Diseases Data Quality Assessment Tool for Preventive Chemotherapy |
A major challenge in computational biology is constraining free parameters in mathematical models . Adjusting a parameter to make a given model output more realistic sometimes has unexpected and undesirable effects on other model behaviors . Here , we extend a regression-based method for parameter sensitivity analysis and show that a straightforward procedure can uniquely define most ionic conductances in a well-known model of the human ventricular myocyte . The model's parameter sensitivity was analyzed by randomizing ionic conductances , running repeated simulations to measure physiological outputs , then collecting the randomized parameters and simulation results as “input” and “output” matrices , respectively . Multivariable regression derived a matrix whose elements indicate how changes in conductances influence model outputs . We show here that if the number of linearly-independent outputs equals the number of inputs , the regression matrix can be inverted . This is significant , because it implies that the inverted matrix can specify the ionic conductances that are required to generate a particular combination of model outputs . Applying this idea to the myocyte model tested , we found that most ionic conductances could be specified with precision ( R2 > 0 . 77 for 12 out of 16 parameters ) . We also applied this method to a test case of changes in electrophysiology caused by heart failure and found that changes in most parameters could be well predicted . We complemented our findings using a Bayesian approach to demonstrate that model parameters cannot be specified using limited outputs , but they can be successfully constrained if multiple outputs are considered . Our results place on a solid mathematical footing the intuition-based procedure simultaneously matching a model's output to several data sets . More generally , this method shows promise as a tool to define model parameters , in electrophysiology and in other biological fields .
Mathematical modeling has become an increasingly popular and important technique for gaining insight into biological systems , both in physiology , where models have a long history [1] , [2] , and in biochemistry and cell biology , where quantitative approaches have gained traction more recently [3] , [4] . However , as new models proliferate and become increasingly complex , analysis of parameter sensitivity has emerged as an important issue [5] , [6] . It is clear that to understand a model requires not only knowing the output generated using the published “baseline” set of parameters , but also some knowledge of how changes in the model's parameters affect its behavior . During the development of a mathematical model , the choice of parameters is a critical step . Parameters are constrained by data whenever this is possible , but direct measurements are frequently lacking . Often , however , a situation exists in which values for many parameters are unknown , but a considerable amount is known about the system's emergent phenomena . In such cases , experienced researchers narrow down the values of the unknown model parameters based on how the model “ought to behave . ” Parameter sets that generate grossly unrealistic output are rejected whereas those that produce reasonable output are tentatively accepted until they fail in some important respect . The emergent phenomena considered in this process can be switching or oscillatory behavior in the case of biochemical signaling models [3] , [4] , or outputs such as action potential ( AP ) and calcium transient morphology in models of ion transport [7]–[10] . Computational studies , however , have revealed the limitations of this intuition-based procedure . In particular , work in theoretical neuroscience has shown that when a single output such as neuronal firing rate is considered , many different combinations of model parameters can generate equivalent behavior [11]–[14] . This general problem is illustrated in Figure 1A , which shows results from a popular mathematical model of the human ventricular action potential , that of ten Tusscher , Noble , Noble , and Panfilov ( TNNP; [15] ) . Random variation of model parameters revealed that completely different parameter combinations could produce virtually identical AP morphology . This result is analogous to studies by Prinz et al . examining firing rate in neuronal cell models [13] , [14] . However , an interesting aspect of the simulation is as follows . The two hypothetical cells , although generating nearly identical APs under normal conditions , exhibited intracellular Ca2+ transients that differed with respect to both amplitude and kinetics ( Figure 1B ) . Theoretically , then , a justifiable choice between these two parameter combinations , while impossible based only on the results shown in Figure 1A , could be made by considering the additional information in Figure 1B . Such distinctions are frequently made by researchers with experimental expertise , who either accept or reject models based on how well they recapitulate a range of observed phenomena . This process , although somewhat arbitrary and potentially subject to bias , nonetheless reflects sound reasoning , since a “good” model should successfully reproduce many biological behaviors . Based on results such as those shown in Figure 1 , we sought to formalize and place on a sound mathematical footing the process of choosing parameters by comparing model output with several sets of data . In particular , our hypothesis was that examining a single model output , such as action potential duration ( APD ) , would fail to constrain parameters , but success would be more likely if the number of physiological outputs was similar to the number of free model parameters . We demonstrate that this is true in the case of the TNNP model [15] through two methods . The first , an extension of the use of multivariable regression for parameter sensitivity analysis [16] , consists of inverting a regression matrix and then using this to calculate the changes in model parameters required to generate a given change in outputs . The second method employs Bayes's theorem to estimate the probabilities that model parameters lie within certain ranges . The results , which are generally applicable across different models and different biological systems , can be of great use when building new models , and also provide new insights into the relationships between model parameters and model results .
The overall hypothesis of our study was that if several physiologically-relevant characteristics of a model's behavior were known , this information would be sufficient to constrain some or all of the model's parameters . We tested this idea using two approaches: one based on multivariable regression and the other based on Bayes's theorem . We began by generating a database of candidate models . The parameters that define maximal conductances and rates of ion transport in the TNNP model [15] were varied randomly , and several simulations , defining how the candidate model responded to altered experimental conditions , were performed with each new set of parameters . In general , the simulations reflected experimental tests commonly performed on ventricular myocytes , such as determining the threshold for excitation or changing the rate of pacing . For the first approach , the results of these simulations were collected in “input” and “output” matrices X and Y , respectively . Each column of X corresponded to a model parameter , and each row corresponded to a candidate model ( n = 300 ) . The columns of Y were the physiological outputs extracted from the simulation results , such as action potential duration ( APD ) and Ca2+ transient amplitude . Complete descriptions of the randomization procedure and simulation protocols are provided in the Methods and Text S1 . Outputs are listed in Table 1 and described in detail in Text S1 . Multivariable regression techniques were used to quantitatively relate the inputs to the outputs . In the “forward problem , ” a matrix of regression coefficients B was derived such that the predicted output Y ̂ = XB was a close approximation of the actual output Y . This method has recently been proven useful for characterizing the parameter sensitivity of electrophysiological models [16] . We reasoned that a similar approach could be used to address the question: if the measurable physiological characteristics of a cardiac myocyte are known , can this information be used to uniquely specify the magnitudes of the ionic currents and Ca2+ transport processes ? Specifically , we hypothesized that if: 1 ) Y ̂ = XB was a close approximation of the true output Y , and 2 ) B was a square matrix of full rank , then Xpredicted = YB−1 should be a close approximation of the true input matrix X . This argument is illustrated schematically in Figure 2 . Figure 3A demonstrates the accuracy of the reverse regression method . For four chosen conductances , the scatter plots show the “actual” values , generated by randomizing the baseline parameters in the published TNNP model , versus the “predicted” values calculated with the regression model . The large R2 values ( >0 . 9 ) indicate that the predictions of the regression method are quite accurate . Of the 16 conductances in the TNNP model , 12 could be predicted with R2>0 . 7 . The four that were less well-predicted were the Na+ background conductance ( GNab ) , the rapid component of the K+ delayed rectifier conductance ( GKr ) , the sarcolemmal Ca2+ pump ( KpCa ) and the second SR Ca2+ release parameter ( Krel2 ) . To verify that these encouraging results were not specific to the TNNP model , we performed similar analyses on additional models , the human ventricular myocyte model of Bernus et al . [17] , and the “Phase 1” ventricular cell model of Luo and Rudy [18] . In either case ( Figures S3 and S4 , respectively ) , the reverse regression was highly predictive of most parameters , indicating that this approach is generally applicable . The outputs used for these analyses , listed in Text S1 , differed somewhat from those used for the TNNP simulations because the Bernus et al . [17] and Phase 1 Luo and Rudy [18] models are relatively simple and do not consider intracellular Ca2+ handling in detail . Figure 3B illustrates how the quantity and identity of the outputs in Y affected the accuracy of the predictions . Bar graphs show R2 values for prediction of each model parameter obtained by performing the reverse regression in three ways: 1 ) using all 32 outputs ( blue ) , 2 ) matrix inversion ( green ) , with the 16 best outputs as identified by the output elimination algorithm ( see Methods ) , and 3 ) using only the 16 rejected outputs ( red ) . The R2 values computed using the 16 best outputs were virtually identical to those obtained when all 32 outputs were used whereas R2 values for most conductances were substantially lower when only the 16 rejected outputs were included . These tests validate the algorithm which selected the outputs for matrix inversion . Moreover , since the 16 best outputs performed essentially as well as the full set of 32 outputs , this result implies that the model outputs were not fully linearly independent , and the 16 rejected outputs contained redundant information . Figure 4 displays , as heat maps , the coefficients for both the forward and reverse regression problems . The former indicate how model parameters influence outputs , whereas the latter specify how changes in model outputs restrict the parameters . Parameter sensitivities for selected outputs and conductances are shown as bar graphs to the right . As previously argued for the case of forward regression [16] , these parameter sensitivities help to illustrate the relationships between parameters and outputs . For instance , forward regression coefficients indicate that diastolic [Ca2+] is determined primarily by a balance between SR Ca2+ uptake and SR Ca2+ leak , with other parameters making only minimal contributions . Conversely , for reverse regression , the maximal conductance of L-type Ca2+ current ( GCa ) depends on many model outputs including action potential duration , Ca2+ transient amplitude , and , in particular , how these are altered with changes in extracellular potassium . This result underscores the centrality of intracellular Ca2+ regulation to many cellular processes . The results shown in Figure 3 demonstrated that most of the model parameters used to generate the dataset could be reconstructed using the reverse regression procedure . To provide evidence that this procedure may be more broadly useful , we applied the method to a novel test case by performing simulations with the most recent version of the Hund & Rudy canine ventricular model [19] . Specifically , we considered changes in seven parameters corresponding to the condition of heart failure , as previously modeled by Shannon et al [20] . Figure 5A shows that implementing these parameter changes dramatically alters both AP shape and Ca2+ transient amplitude . After performing simulations under a range of conditions with both normal , healthy cells and pathological , failing cells ( see Methods and Text S1 ) , we asked how well the reverse regression matrix could calculate the parameter changes in the failing cells . We found that this method constrained 5 out of 7 parameters with excellent accuracy , while changes in two parameters ( GKs and Kleak ) were overestimated somewhat by the regression algorithm . This novel test cases validates our approach and suggests that it may indeed prove a useful method for developing new models based on experimental measurements . The second approach for constraining model parameters is based on Bayes's theorem . In statistics , this celebrated result describes the conditional probability of one event given another in terms of: 1 ) the conditional probability of the second event given the first , and 2 ) the marginal probabilities of the two events:In this context , we consider event A that a model conductance lies within a given range , and event B that a model output is within a particular range . When many simulations are performed with randomly varying parameters , the probability P ( A ) is fixed by the user , while the probabilities P ( B ) and P ( B|A ) can be estimated from the results . This allows us to approximate P ( A|B ) , which reflects how well a model parameter is constrained by a particular simulation result . Since our hypothesis was that multiple outputs needed to be considered to constrain model parameters , we were interested in extensions of Bayes's theorem to more than two variables , e . g . P ( A|B∩C ) , where B and C are events related to two model outputs . For instance , B and C could represent , respectively , that APD and Ca2+ transient amplitude are within particular ranges . If the conditional probability of the parameter increases as additional outputs are considered , this validates the thinking underlying the approach . The application of this strategy to our data set is illustrated in Figure 6 . The two rows of histograms display distributions of GNa and GCa , which are typical of the 16 model parameters considered . The leftmost histogram in each row shows the distribution of conductance values in the entire population , and the remaining columns show conductance values for sub-populations that satisfy constraints on one or more model outputs . Successive columns from left to right show distributions with additional model outputs considered , as noted . In either case , the distributions become progressively narrower , and the conditional probability is unity once 3 outputs are considered . This procedure also provides insights into which specific outputs provide the greatest information about particular model parameters . For instance , the distribution of GNa given a certain range of APD appears similar to the overall distribution of GNa because these two variables are not strongly correlated ( i . e . P ( B|A ) ≈ P ( B ) ) . In contrast , inclusion of Vpeak , an output highly dependent on GNa , narrows the distribution significantly . In the case of GCa , restricting APD to a particular range makes the distribution narrower , which is to be expected given the relatively strong correlation between the parameter and the output . Thus , an approach based on Bayes's theorem also supports the idea that model parameters can successfully be constrained if multiple model outputs are considered .
In this study we have presented two methods that can be used to constrain free parameters in complex mathematical models of biological systems . The utility of these methods was demonstrated through simulations with models of ventricular myocytes [15] , [17]–[19] , but with modifications the strategies could also be applied to other classes of models . For instance , these methods could be used to constrain parameters in models of the sinoatrial node [21] , [22] , but in this case more useful outputs would be metrics such as inter-beat interval , diastolic depolarization rate , and maximum diastolic potential [23] . Our results show that model parameters are difficult to specify uniquely using a limited number of model outputs as “targets , ” but parameters can be constrained successfully if numerous model outputs are simultaneously considered [24] . The premise underlying this strategy is therefore similar to ideas advanced by Sethna and colleagues in discussions of model “sloppiness” [25] , [26] . Even if individual parameters are largely unknown or cannot be measured with precision , predictive models can still be built if care is taken to match the model's output to diverse sets of experimental data . The reverse regression method uses matrix multiplication to predict a set of parameters , in this case ionic current maximal conductances , that are most likely to recapitulate a given set of model outputs . In a recent paper [16] , parameter randomization followed by regression was used to quantify parameter sensitivities in electrophysiological models . The method presented here is an extension of this: we added outputs so that the regression matrix B could be inverted . Each element of this inverted matrix , B−1 , therefore indicates how much a physiological output contributes to the prediction of a particular input conductance ( Figure 4 ) . In experimental studies , metrics derived from data are frequently used as indirect semi-quantitative surrogates of ionic conductances . For instance , conventional wisdom holds that action potential upstroke velocity reflects the availability of Na+ current [27] , and the prominence of the Phase 1 “notch” indicates the contribution of transient outward K+ current [28] , [29] . Our reverse regression method is simply a mathematically more formal extension of this general strategy , whereby every output can conceivably influence the prediction of each model parameter . When applied to the simulations with the TNNP model , reverse regression was able to generate accurate predictions of most conductances or rates of ion transport in the model ( R2>0 . 7 for 12 of 16 parameters ) . Of the 4 parameters that were not predicted accurately , two , namely Na+ background conductance ( GNab ) and the sarcolemmal Ca2+ ATPase ( KpCa ) are considered to be relatively unimportant for normal cellular physiology . The parameter Krel2 ( crel in the original TNNP model ) , was also predicted poorly , most likely because it is partially redundant with the parameter Krel1 ( arel in the original TNNP model ) , which was well constrained by the analysis . The surprise in our simulations was the poor prediction of the rapid component of the delayed rectifier current , GKr , since this current contributes to AP repolarization [30] , [31] , and block of IKr is the primary cause of drug-induced long QT syndrome [32] , [33] . It should be noted , however , that our prediction of the conductance corresponding to the slow delayed rectifier , GKs , was accurate . This suggests that in the TNNP model , these conductances serve similar functions and perhaps compensate for each other . A similar conclusion can be drawn from the simulations in which we used the reverse regression procedure to reconstruct the parameters corresponding to heart failure in the Hund & Rudy [19] model ( Figure 5 ) . Five out of the seven parameters altered in the heart failure cell were predicted accurately by the reverse regression procedure . The two that were not predicted accurately , Kleak , and GKs , have relatively minor effects in the Hund & Rudy model , although these are more important in some other models . Thus , these methods are not only useful for constraining parameters; they can provide novel insight into the relative importance of particular model parameters in determining physiological function . Two important factors influencing the accuracy of the conductance predictions are the number and quality of the outputs . Mathematically , inversion of the regression matrix B requires that the columns be linearly independent , which in turn requires independence of the columns of Y , i . e . the outputs . In contrast , linear dependence would imply that the outputs contain redundant information . Since we did not know a priori which outputs would be informative and which would be partially redundant , we implemented an algorithm to remove outputs sequentially and find a set of 16 that yielded the best results . This resulted in the unexpected elimination of seemingly important outputs such as the maximal upstroke velocity , a metric closely related to Na+ conductance . However , it is important to note that this result does not argue against the usefulness of upstroke velocity as a metric , it merely indicates that the information contained in this output has already been captured by the 16 that were selected . These considerations suggest a future application of these techniques , besides their obvious utility in the construction of new mathematical models . Since the regression analyses provide insight into which physiological measures are independent and which are partially redundant , these types of simulation studies can be used to prioritize experiments . Experimental studies consume the valuable resources of reagents , animals , and person-hours , and computational approaches that could reliably distinguish between more informative and less informative experiments would therefore be quite valuable . For example , the pacing cycle length at which a myocyte begins to exhibit APD alternans ( BCLalt ) is an important quantity related to the arrhythmogenic potential of the cardiac substrate [34] , [35] . Determining this threshold , however , requires time-consuming experiments in which myocytes must be paced at many different rates . This output was rejected by our elimination algorithm , suggesting that , at least in the TNNP model , the information provided by this difficult experiment is not different from that contained in other , perhaps simpler , measurements . Our current work is focused on formalizing these ideas and developing methods to quantify the relative information content of different experimental measurements . We should note that the outputs chosen for our analysis are physiologically meaningful metrics that are measured routinely in isolated cardiac myocytes . We purposely excluded measures that quantify how cellular behavior changes after application of a pharmacological agent . Since the explicit purpose of adding a drug is often to deduce the importance of the drug's primary target , we felt that including these metrics would , for an existing model , make the parameter constraint problem fairly trivial . In future studies , however , including these outputs will undoubtedly improve the predictive power of these methods . Similarly , the addition of more columns to the matrix Y corresponding to results from voltage-clamp experiments should also improve the accuracy of the method . These extensions will likely be necessary if maximal conductances are essentially unknown , or if ionic current kinetic parameters are also to be constrained . In the field of cardiac electrophysiology , a few modeling studies have examined issues of parameter sensitivity [6] , [16] , [36] , [37] , parameter estimation [38] , [39] , and model identifiability [40] . For example , Fink and Noble recently assessed the adequacy of whole-cell voltage clamp records for uniquely determining parameters in models of ion channel gating [40] . These analyses suggested that optimized voltage clamp protocols might be more efficient for parameter identification than protocols currently used in experiments . More studies that address these sorts of issues have been performed in computational neuroscience . For instance , analogous to the results shown in Figure 1A , several studies have shown that different combinations of model conductances can produce seemingly identical behavior , either in isolated neurons [11] , [13] or in models of small neuronal networks [14] . Olypher and Calabrese then generalized this result by demonstrating that , close to a particular location in parameter space , infinitely many parameter combinations can produce the same level of activity as the original location , and these authors derived 2×2 sensitivity matrices to demonstrate these compensatory changes [41] . Our reverse regression approach is essentially an extension of this idea to multiple dimensions , with the implicit assumption that considering additional linearly-independent model outputs will increase the likelihood of determining parameters uniquely . Given that parameters in neuronal models cannot be uniquely specified using only a metric such as firing rate , a few studies have combined genetic algorithms with more sophisticated data-matching strategies such as phase-plane analysis [11] or multiple objective optimization [42] . Our methods offer both advantages and disadvantages compared with these alternative strategies . The primary advantage here is that reverse regression is simple and intuitive , and the outputs considered are well-defined metrics that are readily obtainable in the laboratory . We can therefore easily relate , in a way that other techniques do not allow , the observable characteristics of the cardiac myocyte to the membrane densities of the important ion channels . The main drawbacks of our approach are: 1 ) that we only perform a local search around the baseline model and 2 ) that we assume a linear relationship between changes in parameters and changes in outputs . While linear approximations to these input-output relationships have been shown to work well in cardiac models [16] , particularly when conductances are expressed in log-transformed units , this assumption may not hold in all classes of models [43] . This limitation is evident in the simulations shown in Figure 6 in that: 1 ) two parameters were poorly predicted by the regression model; and 2 ) in these simulations , the parameter search was constrained to only seven possibilities rather than allowing any model parameter to contribute to the phenotype . Future studies will likely improve on these strategies and combine aspects of several approaches to refine methods for determining parameters in complex models of biological processes . In summary , we have presented new methods for constraining free parameters in mathematical models , and demonstrated their utility through analyses of a common model of the ventricular myocyte . The approaches we describe have potentially broad implications . Analysis tools such as these can be used to obtain new insight into the relationships between model parameters , model outputs , and experimental data . The ideas offer hope that , even if some model parameters cannot be directly measured , a close comparison of data to model output can still discriminate between possibilities and produce a model with strong predictive power .
This computational study aimed to extend the use of regression to develop methods for constraining free parameters in mathematical models . The ideas were tested through simulations using the TNNP model [15] of the human ventricular action potential ( described in more detail in the Supporting Information ) . First , regression was used to derive a matrix ( B ) whose elements indicate how changes in input parameters , namely maximal ionic conductances , affect physiologically-meaningful model outputs . The regression matrix was then inverted , thereby deriving a new matrix ( B−1 ) that specifies the ionic conductances required to produce a given set of model outputs . In the first stage , the input matrix X was generated by randomly scaling 16 parameters in the TNNP model . A total of 300 random sets of parameters were generated such that X had dimensions 300×16 . To compute the output matrix Y , several simulations were performed with each of the 300 models defined by a given parameter set . These simulations reflected standard electrophysiological tests such as the response of the myocyte to changes in pacing rate or extracellular potassium concentration . The calculation of some of these outputs is illustrated in Figure S1 . The 32 outputs computed from these simulations , listed in Table 1 , ranged from straightforward measures such as action potential duration ( APD ) and Ca2+ transient amplitude to more abstract metrics such as the minimum cycle length required to induce APD alternans [34] . The 16×32 matrix B relates the inputs to the outputs such that Y ̂ = XB is a close approximation of the true output matrix Y . To allow for inputs and outputs expressed in different units to be compared , values in X and Y were converted into Z-scores – i . e . each column was mean-centered and normalized by its standard deviation . The results of the “forward” regression performed in the first stage are shown in Figure S2 . The second stage of the computational experiment aimed to determine if the input matrix X could be inferred , assuming the output matrix Y was known . Since Y ̂ = XB≈Y , we reasoned that YB−1 should be a close approximation of X , provided that B is an invertible matrix . We performed an iterative procedure to determine the 16 most appropriate outputs for this matrix inversion . First , with the full 300×32 matrix Y , “reverse regression” was performed to derive a matrix B′ such that YB′≈X . We then removed each of the columns of Y and performed the reverse regression with the remaining 31 outputs . The output whose removal caused the smallest change in the prediction of X ( quantified by R2 ) was deemed the least essential and was removed permanently . This procedure was repeated to reduce the number of outputs from 31 to 30 , etc . , until Y had dimensions 300×16 . A further set of simulations was performed with the 2008 version of the Hund and Rudy model of the canine action potential [19] . In these simulations , we sought to determine whether changes in model parameters in heart failure could be determined using the reverse regression procedure . We simulated the changes in parameters used by Shannon et al to simulate heart failure in their model of the rabbit action potential [20] . This involved alterations to seven model parameters: GK1 , GKs , Gto , KNCX , KRyR , KSERCA , and Kleak . Simulations were performed under three conditions: normal extracellular [K+]o ( 5 . 4 mM ) , hypokalemia ( [K+]o = 3 mM ) and hyperkalemia ( [K+]o = 8 mM ) . In these simulations , a total of 33 model outputs were calculated to constrain the parameters ( see Text S1 for full list ) . Reverse regression was performed to map the 33 outputs from the simulated failing myocyte to the predicted 7 parameter changes . In the second approach , based on Bayes's theorem , we were interested in estimating P ( A|B ) from P ( B|A ) , P ( A ) , and P ( B ) . In this context , A is that a parameter is in a particular range , and B is that a model output is in a specified range . To estimate P ( B|A ) from the set of 300 simulation results , we sorted the values in each column of X and Y , then computed the percentile ranges . This allowed us to easily select , for instance , 10% of the values of a particular output centered around a given value . To generate histograms such as those shown in Figure 4 , we first plotted the distribution of all the tested values of a given conductance . Then we selected the conductance values corresponding only to those trials for which APD fell within a particular range , and generated the histogram of this set . From this subset of conductances , we then selected the conductance values corresponding to those trials for which Vrest was in a certain range , etc . To allow for visual comparison , each histogram was normalized to the total number of values of the subset . To ensure that this procedure found a set of conductances that actually existed in the data set , we first identified the “best” trial for which the difference between Y and Y ̂ was minimal . The output ranges used to select the subsets of conductances all represented deviations of ±5% around these values . A bundle containing the Matlab™ code used to generate the results presented in the manuscript has been uploaded as Protocol S1 in the Supporting Information . | Mathematical models of biological processes generally contain many free parameters that are not known from experiments . Choosing values for these parameters , although an important step in the construction of realistic computational models , is frequently performed using an ad hoc approach that is a combination of intuition and trial and error . We have developed a novel method for constraining free parameters in mathematical models based on the techniques of linear algebra . We demonstrate this method's utility through simulations with a model of a human heart cell . The underlying premise is that if the model is only asked to recapitulate one or a few biological behaviors , the values of the parameters may be ambiguous; however , if the model must simultaneously match many features of experimental data , the free parameters can be determined uniquely . The results demonstrate that if computational models are to be realistic , they must be compared with several sets of data at the same time . This new method should serve as a valuable tool for investigators interested in developing realistic mathematical models of biological processes . | [
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] | 2010 | Regression Analysis for Constraining Free Parameters in Electrophysiological Models of Cardiac Cells |
Zika virus ( ZIKV ) infection causes diseases ranging from acute self-limiting febrile illness to life-threatening Guillain–Barré Syndrome and other neurological disorders in adults . Cumulative evidence suggests an association between ZIKV infection and microcephaly in newborn infants . Given the host-range restrictions of the virus , a susceptible animal model infected by ZIKV must be developed for evaluation of vaccines and antivirals . In this study , we propose a convenient mouse model for analysis of neurological disorders caused by ZIKV . Six-day-old immunocompetent ICR suckling mice were used in the experiment . Different inoculum virus concentrations , challenge routes , and challenge times were assessed . Viremic dissemination was determined in the liver , spleen , kidney , and brain through Western blot assay , plaque assay , absolute quantification real-time PCR , and histological observation . Azithromycin , a well-characterized anti-ZIKV compound , was used to evaluate the ICR suckling mouse model for antiviral testing . Signs of illness and neurological disease and high mortality rate were observed in mice injected with ZIKV intracerebrally ( 102 to 105 ) and intraperitoneally ( 103 to 105 ) . Viremic dissemination was observed in the liver , spleen , kidney , and brain . ZIKV transmitted , rapid replicated , and induced monocyte infiltration into the brain approximately 5 to 6 days post inoculum . Azithromycin conferred protection against ZIKV-caused neurological and life-threatening diseases . The developed model of ZIKV infection and disease can be used for screening drugs against ZIKV and discovering the underlying mechanism of ZIKV pathogenesis .
Mosquito-borne Zika virus ( ZIKV ) , which belongs to the Flavivirus genus of the Flaviviridae family , is an emerging threat to human health worldwide [1] . The genome of ZIKV consists of a single-stranded positive sense RNA , which encodes a single polypeptide [2 , 3] . The single polypeptide is processed by viral and host proteases to form mature viral proteins , including three structural proteins [core ( C ) , pre-membrane ( prM ) , and envelope ( E ) ] and seven non-structural proteins ( NS1 , NS2A , NS2B , NS3 , NS4A , NS4B , and NS5 ) [4] . ZIKV ( strain MR766 ) was first isolated from sentinel rhesus monkeys in the Zika forest of Uganda in 1947 [5] . ZIKV was also isolated from Aedes africanus mosquito in the Zika forest . Few ZIKV infection cases were reported around African and Asian countries during 1960s–1980s , and ZIKV was neglected for years until 2007 [6] . In 2007 , ZIKV infection attracted global attention due to the outbreak in the Yap Island of Micronesia , which was the first spread of ZIKV infection outside Africa and Asia [7 , 8] . In 2013–2014 , another ZIKV outbreak was reported in French Polynesia , and more than 28 , 800 people were infected by the virus [9] . Thereafter , ZIKV has spread rapidly throughout the Pacific region . Most importantly , in UK , a man who visited French Polynesia at 2014 was diagnosed with ZIKV; in this case , ZIKV RNA was detected in the semen 2 months post onset of the syndromes , which underlined the potential of sexual transmission of the virus [10] . In 2015 , the first ZIKV breakout in America was reported in Brazil; the Brazilian Ministry of Health reported a 20-fold increase in cases of neonatal microcephaly , which was geographically and temporally correlated with the ZIKV outbreak [11 , 12] . Most patients infected by ZIKV present mild symptoms , including moderate fever , headache , myalgia , conjunctivitis , and rash , which are similar to those of infection by other Flavivirus , such as dengue virus or West Nile virus [13–17] . Recent evidence demonstrated that ZIKV infection leads to severe syndromes , such as Guillain–Barré syndrome ( GBS ) and microcephaly in adults and infants , respectively [14–16] . GBS is an autoimmune disorder in which the immune system attacks the nervous system [18] . The key phenomenon of GBS is the infiltration of activated lymphocytes and monocytes in nerve tissues , leading to acute or subacute flaccid paralysis [13 , 19] . At present , ZIKV spreads rapidly in Africa , America , and Asia Pacific [5] . No approved antivirals or vaccines are available for treatment of ZIKV infection . Therefore , a suitable animal model must be developed for investigating therapeutics or vaccines against ZIKV infection and related diseases . Animal models for investigating ZIKV infection include nonhuman primates ( NHPs ) and mice [20] . Although NHPs are suitable for studying ZIKV pathogenesis and therapeutics/vaccine development , they are expensive [21] . In this regard , small animal models are a better choice for studying ZIKV [10 , 21] . In the present study , we established a murine ZIKV infection animal model for evaluation of ZIKV therapeutics .
In initial studies , ICR suckling mice were tested for susceptibility to infection by ZIKV . Six-day-old ICR suckling mice were intracerebrally/intracranially ( i . c . , n = 5 ) and intraperitoneally ( i . p . , n = 5 ) injected with 102 to 105 PFU ZIKV , respectively . Mice injected with heat-inactivated ZIKV ( iZIKV ) were used as mock controls . Survival rate , clinical score , and body weight of ZIKV-injected mice were measured daily for 8 days . As shown in Fig 1A–1D , the i . c . injection of 102 to 105 PFU ZIKV resulted in 80% to 100% mortality rate at 5–7 days post infection ( dpi ) . Meanwhile , the i . p . injection of 103 to 105 PFU ZIKV resulted in high mortality rate at 1 day later than the i . c . injected mice , and that of 102 PFU ZIKV led to 20% mortality rate . Moreover , the i . c . injection caused death approximately 1 day earlier than the i . p . injection . Regardless of inoculation route or concentration of ZIKV , ICR suckling mice showed signs of illness and neurological disease from 2 to 5 dpi . The symptoms included body weight loss , ruffled fur , lethargy , unsteady gait , kinetic tremor , severe ataxia , and limb paralysis ( Fig 1E–1H ) . The incidence time of clinical signs in the i . c . injection groups is approximately 2 days earlier than that in the i . p . injection groups . Interestingly , the i . p . injection groups showed rapid disease process , that is , severe paralysis or death was noted 2 to 3 days after the onset of clinical signs ( Fig 1E–1H ) . In observation of mice morbidity , body weight loss started on 3 dpi , which is approximately the same time when clinical signs were noted ( Fig 1I–1L ) . The ZIKV infection caused neurological syndromes [20 , 22] . Brain tissues were collected from mice that received i . c . ( n = 3 to 5 ) and i . p . ( n = 4 to 5 ) injection of 102 to 105 PFU ZIKV to determine whether the virus can replicate in the brain of ICR suckling mice . The brain tissues were homogenized , and ZIKV protein expression was analyzed by Western blot assay . As shown in Fig 2A , the ZIKV protein was expressed in the i . c . injection group ( 102 to 105 PFU ) , but the expression level was lower in the i . p . injection group ( Fig 2B ) . We conducted absolute quantification real-time PCR to detect ZIKV RNA replication level in the suckling mouse brain . As shown in Fig 2C and 2D , the ZIKV RNA replication level ranged from 109 to 1010 and from 106 to 109 copies/μg RNA in the i . c . and i . p injection groups , respectively . In addition , the ZIKV viral load in the ICR suckling mouse brain was determined . Based on the plaque assay , the ZIKV titer in the i . c . group ( from 107 to 109 PFU/g tissue ) was approximately 2 to 3 log higher than that in the i . p . group ( from 104 to 108 PFU/g tissue ) injected with different concentrations of ZIKV ( Fig 2E and 2F ) . To further characterize ZIKV replication in the suckling mice , we collected , weighed , and homogenized liver , spleen , and kidney tissues . The absolute quantification real-time PCR analysis showed that , regardless of organs or concentrations of ZIKV injected , ZIKV RNA was detected . The RNA replication level ranged from 105 to 108 copies/μg RNA in the liver , from 104 to 107 copies/μg RNA in the spleen , and from 105 to 107 copies/μg RNA in the kidney ( Fig 2G–2L ) . The immune cell infiltration to the brain leads to inflammation , which is associated with ZIKV-caused GBS and other neurological disorders [21] . To investigate whether ZIKV infection can induce monocyte infiltration in the brain of ICR suckling mice , we collected brain tissues , stained them with hematoxylin and eosin ( H&E staining ) , and observed under a photomicroscope . As shown in Fig 3A , the monocyte infiltration in the surrounding adjacent blood vessel in the brain of mice in the ZIKV i . c . injection group gradually increased compared with that in the mock infection group . As predicted , monocyte infiltration in the surrounding adjacent blood vessel was also observed in the brain of mice in the ZIKV i . p . injection group ( Fig 3B ) . We further performed an immunohistochemistry ( IHC ) assay using specific monocytic marker Ly6C to quantify monocyte infiltration ( Fig 3C and 3D ) from the stained image ( S1 Fig ) . Hence , the ICR suckling mouse model can be an immunocompetent model for understanding ZIKV pathogenesis . To further characterize the invasion kinetics of ZIKV in mouse brain , we injected 6-day-old ICR suckling mice through i . p . with 104 PFU ZIKV and collected brain tissues ( n = 3 ) for analyses of ZIKV protein synthesis , RNA replication , viral titration , and monocyte infiltration . ZIKV protein synthesis and RNA replication were analyzed through Western blot and absolute quantification real-time PCR analyses , respectively . Our results showed that the ZIKV protein synthesis gradually increased in the brain tissue and dramatically increased at 6 dpi ( Fig 4A ) . The absolute quantification real-time PCR results also showed that ZIKV RNA replication gradually increased in the brain tissue and dramatically increased at 5 dpi ( Fig 4B ) . As predicted , the ZIKV viral titer also increased in the brain tissue in a time-dependent manner ( Fig 4C ) . These data indicated that ZIKV injected by i . p . can pass through the blood–brain barrier and replicate in the brain tissue . To further investigate the monocyte infiltration kinetics in the brain of ZIKV-infected ICR suckling mice , we first observed the monocyte infiltration by a photomicroscope following H&E staining ( Fig 4D ) . Then , we performed an IHC assay to quantify the monocyte infiltration ( Fig 4E and S2 Fig ) . Collectively , monocyte infiltration was observed at approximately the same time when ZIKV was detected in the brain tissue . To evaluate whether ICR suckling mouse model is suitable for screening drugs for anti-ZIKV and ZIKV-induced disease , we used the well-characterize anti-ZIKV compound , namely , azithromycin ( Az ) [23 , 24] . Six-day-old ICR suckling mice weighing 3 . 5–4 g were randomly divided into four groups . The mice were i . p . injected with ZIKV and Az ( 1 or 10 mg/kg ) at 1 , 3 , and 5 dpi . Survival rate , clinical score , and body weights of ZIKV-injected mice treated with or without Az were measured daily for 7 days . Mice inoculated with heat-inactivated ZIKV ( iZIKV ) or 10 mg/kg of Az ( Az 10 mg/kg ) were used as mock controls . All the mice were sacrificed at 7 dpi , and their brain tissues were collected for analysis of ZIKV protein synthesis , RNA replication , viral titration , and monocyte infiltration . As shown in Fig 5A , ZIKV-infected mice that were not treated with Az developed severe sickness , leading to death within 4–7 dpi , in contrast to iZIKV-infected control mice . Moreover , Az administered at 1 and 10 mg/kg shielded 80% and 100% of mice from the life-threatening ZIKV infection compared with non-Az-treated mice . After 7 days of observation , the ZIKV-infected group showed signs of illness and neurological disease and exhibited 75% body weight loss compared with the iZIKV group ( Fig 5B and 5C ) . The Az-administered group showed slight signs of illness and neurological disease as well as 50% ( 1 mg/kg ) and 15% ( 10 mg/kg ) body weight loss than the iZIKV group ( Fig 5B and 5C ) . Moreover , injection of 1 mg/kg Az decreased the ZIKV RNA copies and viral titer by 1 . 58±0 . 27 and 0 . 81±0 . 18 log10 , respectively . Meanwhile , injection of 10 mg/kg Az decreased the ZIKV RNA copies and viral titer by 2 . 52±0 . 25 and 1 . 55±0 . 16 , respectively , compared with that in ZIKV-infected mice that were not treated with Az ( Fig 6A and 6B ) . As predicted , Az treatment decreased the monocyte infiltration into the brain of ZIKV-infected ICR suckling mice in a dose-dependent manner ( Fig 6C and 6D ) . In addition , mice received 10 mg/kg of Az exhibited no any side effect . These data indicated that ICR suckling mouse model is suitable for screening drugs against ZIKV and ZIKV-induced diseases .
In the present study , we established a ZIKV-infected ICR suckling mice model for investigating the propagation of ZIKV infection and , especially , the antiviral drug development in vivo . The ICR suckling mice model is susceptible for ZIKV infection by using both i . p . and i . c . injection methods and provide infection with high viral loads in the brain , which is consistent with severe neurological symptom in human [12 , 14 , 25] . Our results further clearly illustrated the level of ZIKV propagation in different tissues , including liver , spleen , and kidney , which indicated that ZIKV distributed systemically in the ICR suckling mice and provided the evidence of ZIKV distribution in the infected individuals . Recently , Retallack et al . reported that Az could prevent ZIKV infection in vitro [23] . Consistently , our study further confirmed that Az could protect mice from lethal ZIKV infection in vivo . To date , ZIKV has been already spread out of the world for years , therefore , a therapeutic treatment against ZIKV infection is urgently needed . Retallack et al . and our results provide a potential therapeutics for treatment of ZIKV infection . Recently , most animal models for investigating ZIKV mainly focus on the ZIKV-caused neurological injury and disruption of neural development [26–28] . For instance , Oh et al . revealed that ZIKV not only infected central nervous system but also the peripheral neurons in mouse embryo , and their study demonstrated that ZIKV infection activated cell apoptosis pathway in neuron cells [26] . Li et al . further delineated the comprehensive picture of pathogenesis of ZIKV and microcephaly in mouse embryo [27] , in which they demonstrated that ZIKV infected neural progenitor cells ( NPCs ) to cause cell-cycle arrest , leading to the defective differentiation of NPCs , which resulted in apoptosis of post-mitotic neurons for generation of microcephaly through induction of immune response in brain . In addition , Duggal et al . [29] and Li et al . [28] have established mice model for studying ZIKV infection . However , their reports provided less evidence of the ZIKV-caused monocyte infiltration and did not provide the detail protocol for evaluation of anti-ZIKV agent . In the present study , we provided the evidence of ZIKV distribution in the organs . In addition , we detailedly determined the virus load in different organs and the monocyte infiltration in the suckling mice model by ZIKV infection with different routes and doses . Importantly , we established a fast and easy-performing animal model for evaluation of anti-ZIKV agent in vivo . Animal models for understanding the transmission and infection of ZIKV has been developed in the different strains of mice , such as AG129 , C57BL/6 , and Irf3/5/7 triple knockout ( TKO ) mice [20] . AG129 and Irf3/5/7 TKO mice are the immunocompromised mice which were permissive to different strain ZIKV infection and vulnerable to ZIKV-relative pathology and lethality [10 , 21 , 30 , 31] . Similarly , the ICR suckling mice model allowed the investigation of some aspect of ZIKV-caused symptom including viral-relative mortality , clinical score increasing , and viral propagation rising [22 , 32] . Furthermore , the immune cell infiltration was observed in the ZIKV-infected ICR suckling mice model . There observations in ICR suckling mice may provide the phenomenon for investigation of the efficacy of developing drug or vaccine , and the tissue of the suckling mice may use to underlying the mechanism discovery [20] . However , the limitation of AG129 mice is unable to develop the vaccine or drug that is dependent on the intact interferon pathway [33] . Furthermore , AG129 and Irf3/5/7 TKO mice has been indicated to be uncommonly available in some research laboratories [33 , 34] . The ICR suckling mice model are the immunocompetent mice , which have allowed researchers to investigate the interferon-dependent antiviral compounds or vaccine [20 , 35] . Furthermore , the suckling mice model is much more common and easy to establish in the most research laboratories [36] . However , the age of the suckling mice lead draws some limitations that the viremia in the blood was hard to collect and proceed , and the study of vertical transmission was not available . Collectively , we developed the ZIKV-infected ICR suckling mice model with a productive viral replication accompanied with some clinical manifestation , including symptom kinetic and immune cells infiltration in the brain . The model thus may provide protocols and information for researchers to investigate antiviral effect or the mechanism determination in a time-saving method and easy operation .
Six-day-old ICR suckling mice weighing 3 . 5–4 g and ICR strain breeder mice were purchased from BioLasco Taiwan Co . Ltd ( Taipei City , Taiwan ) . All animal experiments were performed under specific pathogen-free conditions . The experimental methods were carried out according to the Guide for the Care and Use of Laboratory Animals . The experimental procedures were approved by the Animal Research Committee of Kaohsiung Medical University of Taiwan ( IACUC , 105198 ) under the guidance of the Public Health Service Policy on Humane Care and Use of Laboratory Animals . All mice received humane care and were given standard diet and water ad libitum . Prior to the experiment , mice were acclimatized for a week under the standard laboratory condition following the Animal Use Protocol of Kaohsiung Medical University . ZIKV strain MR-766 was amplified in C6/36 mosquito cells and titrated in Vero cells . Six-day-old ICR suckling mice were inoculated with 102 ( 10^2 ) , 103 ( 10^3 ) , 104 ( 10^4 ) , and 105 ( 10^5 ) PFU ZIKV by i . p . and i . c . injection . Mice injected with heat inactivated ZIKV ( iZIKV ) were used as mock control . Survival rate , body weight , and clinical score were measured every day after ZIKV infection . The clinical scores were recorded according to illness symptoms: 0: healthy , 1: body weight loss and ruffled fur , 2: lethargy and unsteady gait , 3: kinetic tremors and severe ataxia , 4: paralysis , and 5: death . The clinical score 5 indicates death , which includes the dead and euthanasia . The criterion for euthanasia is that the mice exhibited no movement , uncontrollable behavior , spastic movements , or do not return to upright position if put on its side . The body weight of the euthanized mice is included in the calculation of body weight , in contrast , the body weight of dead mice is excluded in the calculation of body weight [37–42] . The mice were sacrificed by CO2 asphyxiation at 8 dpi . In brief , 0 . 1g of brain , liver , spleen , and kidney tissues were harvested by R . I . P . A buffer , TRIzol reagent , and RPMI medium for protein , RNA , and virus collection , respectively . Western blot assay was performed as described previously [37 , 43] . In brief , protein from cell lysates was separated by SDS-PAGE and transferred onto PVDF membrane . Signal was detected using an ECL detection kit ( PerkinElmer , CT ) . Antibodies used in the study included anti-ZIKV NS2B antibody ( 1:3 , 000; GeneTex ) and anti-actin antibody ( 1:10 , 000; GeneTex ) . Total cell RNA was extracted by TRIzol™ reagent following the manufacturer’s protocol . Both double- and single-stranded DNA in the RNA samples were denatured by using RQ1 ( RNA Qualified ) RNase-Free DNase ( Promega ) . The RNA samples were reverse transcribed into complementary DNA by using the M-MLV Reverse Transcription System ( Promega ) . Absolute quantitation of ZIKV RNA copies was conducted relative to the standard curves . RT-qPCR analysis was conducted using serially diluted expression plasmids containing the coding sequence of ZIKV NS5 with the following specific primers: forward primer , 5′-aagcaaaaggtagccgcgcc-3′ , and reverse primer , 5′-tgtcccagccagcagtgtca-3′ , targeting the ZIKV NS5 gene . The reactions were performed using ABI Step One real-time PCR-system ( ABI Warrington , UK ) . Vero cells were seeded in 24-well plates at 9 × 104 per well . Virus collected from mouse brain was serially diluted and incubated with Vero cells to a volume of 200 μL at 37 °C . After 2h of incubation , the medium was refreshed with MEM containing 2% FBS and 0 . 8% methyl cellulose ( Sigma–Aldrich ) . At 3 dpi , the cells were fixed with 4% paraformaldehyde for 15 min and stained with the crystal violet solution ( 1% crystal violet and 0 . 64% NaCl ) at 25°C for 1h . Viral titer was calculated by observation of plaque formation . Histopathological observation was performed as previously described [44] . In brief , each tissue was harvested and subjected to H&E or IHC staining to observe tissue injury or monocyte infiltration under a photomicroscope . To quantify the monocyte infiltration in brain tissues , the slices of brain tissues were first received immunohistochemistry ( IHC ) staining with anti-Ly6C antibody ( Abcam ) , and then the degree of monocytes infiltration was digitally quantified by ImageJ software [45–47] . In brief , the staining patterns of Ly6C were detected by EVOS FL Cell Imaging System ( Thermo Fisher Scientific ) , and the blot signals from the digital images were further analyzed by Image J software ( NIH , USA ) . The results were normalized by the scanning area and were presented as the log10 fold-change compared to that of uninfected ( iZIKV ) control defined as 1 . Az was obtained from Sigma ( St . Louis , MO , USA ) . Six-day-old ICR suckling mice were i . p . injected with 104 PFU ZIKV . Three mice were randomly chosen to be sacrificed by CO2 asphyxiation , and brain tissues were collected each day . All mice were sacrificed at 7 dpi . The brain tissues were collected by R . I . P . A buffer , TRIzol reagent , and RPMI medium for protein , RNA , and virus collection , respectively . Six-day-old ICR suckling mice weighing 3 . 5–4 g were randomly divided into four groups: group 1: i . p . injectedwith 104 PFU heat-inactivated ZIKV ( iZIKV ) ; group 2 received 10 mg/kg of Az but without ZIKV infection ( Az 10 mg/kg ) ; group 3: i . p . injected with 104 PFU ZIKV and saline ( ZIKV ) ; group 4: i . p . injected with 104 PFU ZIKV and 1 mg/kg Az ( ZIKV+Az 1mg/kg ) ; and group 5: i . p . injected with 104 PFU ZIKV virus and 10mg/kg Az ( ZIKV+Az 10mg/kg ) . The ZIKV-infected mice were i . p . injected with the tested agents at 1 , 3 , and 5 dpi . Survival rate , body weight , and clinical score were recorded every day post ZIKV infection . The clinical score was recorded according to the illness symptoms: 0: healthy , 1: body weight loss and ruffled fur , 2: lethargy and unsteady gait , 3: kinetic tremors and severe ataxia , 4: paralysis , and 5: death . The mice were sacrificed by CO2 asphyxiation at 7 dpi . The brain tissues were collected by R . I . P . A buffer , TRIzol reagent , and RPMI medium for protein , RNA , and virus collection , respectively . Data were expressed as mean ± SD of at least three independent experiments . Statistical calculations were analyzed by Student’s t-test using GraphPad Prism 6 ( GraphPad Software Inc . ) . | Mosquito-borne Zika virus ( ZIKV ) is an emerging threat to human health worldwide . In 2007 , a ZIKV outbreak was reported in the Yap Island of Micronesia and was the first outbreak outside Africa and Asia . In 2013 and 2014 , another ZIKV outbreak was reported in French Polynesia , and more than 28 , 800 people were infected by ZIKV . In 2015 , the first ZIKV outbreak in America was reported in Brazil; the Brazilian Ministry of Health reported a 20-fold increase in cases of neonatal microcephaly , which was geographically and temporally correlated with the ZIKV outbreak . Recent evidence demonstrated that ZIKV infection leads to severe syndromes , such as Guillain–Barré syndrome and microcephaly in adults and infants , respectively . Thus far , anti-ZIKV drugs and vaccines have not been developed yet . Moreover , the underlying mechanism of ZIKV pathogenesis remains unclear . In this study , we propose a small animal model of wild-type ZIKV infection and associated neurological disorders . In the animal model , ZIKV causes signs of illness and neurological disease , potentially emulating the hallmark of ZIKV infection in human . These features can be used to study the underlying mechanism of ZIKV pathogenesis . The newly developed Zika disease model provides an immunocompetent and time saving framework for development of drugs against ZIKV and ZIKV-caused diseases . | [
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"org... | 2018 | ICR suckling mouse model of Zika virus infection for disease modeling and drug validation |
Leishmania protozoan parasites ( Trypanosomatidae family ) are the causative agents of cutaneous , mucocutaneous and visceral leishmaniasis worldwide . While these diseases are associated with significant morbidity and mortality , there are few adequate treatments available . Sterol 14alpha-demethylase ( CYP51 ) in the parasite sterol biosynthesis pathway has been the focus of considerable interest as a novel drug target in Leishmania . However , its essentiality in Leishmania donovani has yet to be determined . Here , we use a dual biological and pharmacological approach to demonstrate that CYP51 is indispensable in L . donovani . We show via a facilitated knockout approach that chromosomal CYP51 genes can only be knocked out in the presence of episomal complementation and that this episome cannot be lost from the parasite even under negative selection . In addition , we treated wild-type L . donovani and CYP51-deficient strains with 4-aminopyridyl-based inhibitors designed specifically for Trypanosoma cruzi CYP51 . While potency was lower than in T . cruzi , these inhibitors had increased efficacy in parasites lacking a CYP51 allele compared to complemented parasites , indicating inhibition of parasite growth via a CYP51-specific mechanism and confirming essentiality of CYP51 in L . donovani . Overall , these results provide support for further development of CYP51 inhibitors for the treatment of visceral leishmaniasis .
Leishmania are vector-borne protozoan parasites . They have a digenetic lifecycle; promastigotes are transmitted by the sandfly vector to the mammalian host , where they are taken up by phagocytic cells and differentiate into the amastigote stage within the macrophage phagolysososme . Amastigotes proliferate within the phagolysosome and can be taken up by a sandfly during a subsequent bloodmeal . Within the sandfly gut , amastigotes then differentiate into promastigotes , thereby completing the parasite lifecycle [1] . Leishmania parasites cause a range of disease manifestations: cutaneous leishmaniasis in which lesions develop at the site of the sandfly bite , mucocutaneous leishmaniasis with destruction of the mucosal tissues in the nose , mouth and throat , and visceral leishmaniasis in which parasites disseminate to the liver , bone marrow and spleen . Visceral leishmaniasis is the most lethal form of the disease . It is associated with high fever , hepatosplenomegaly and pancytopenia [1] . The infecting species of Leishmania is the major determinant of disease manifestation; parasites from the Leishmania donovani species complex are the main causes of visceral leishmaniasis , while other species , including the Leishmania major species complex , cause cutaneous manifestations [2 , 3] . Leishmania parasites are distributed across tropical and subtropical regions of the world . 350 million people live in endemic areas and are at risk of developing the disease , with 12 million people currently infected [4] . Overall , there are 1 . 6 million new cases per year [5] , associated with a disease burden of 3 . 3 million DALYs and over 50 , 000 deaths per year [6] , making leishmaniasis the second most lethal parasitic infection after malaria [5] . However , treatment options are limited; while recent progress has been made with the development of single-dose amphotericin B therapy in India [7] , this treatment regimen was not effective in East Africa [8] . All other drugs require long treatment regimens; toxicity and drug resistance are also significant concerns [9] . Cell membrane sterols regulate membrane fluidity and contribute to the organization of membrane domains . Unlike mammalian cells , but similar to fungi , Leishmania and Trypanosoma parasite cell membranes contain ergosterol and ergosterol-like sterols rather than cholesterol . Sterols are generated from acetyl-CoA via a multistep metabolic pathway . The first three steps , catalyzed by acetoacetyl-CoA thiolase , HMG-CoA synthase and HMG-CoA reductase , lead to the generation of mevalonate . Mevalonate is the substrate of the isoprenoid pathway that generates farnesyl diphosphate . Squalene synthase then produces squalene from two farnesyl diphosphate molecules . Squalene is oxidized by squalene oxidase , and the resulting product cyclized to lanosterol . Sterol 14alpha-demethylase ( CYP51 , LdBPK_111100 . 1 ) catalyses the removal of a 14alpha-methyl group from lanosterol [10 , 11] . The L . infantum CYP51 enzyme has broad substrate specificity , with the ability to demethylate obtusifoliol , C4-norlanosterol and 14α-methylzymosterol , in addition to lanosterol , although with a preference for the first two substrates [12] . The following steps differ between ergosterol and cholesterol biosynthesis , with variations in the reaction intermediates and enzymes involved depending on species [13] . One of these key latter steps in ergosterol biosynthesis is the methylation of C24 via sterol 24-methyltransferase , leading to the formation of fecosterol , episterol or 5-dehydroepisterol depending on the substrate [14] . Azole antifungals have been investigated for treatment of Leishmania infections , but with large variations in efficacy between species [15] . The first experiments on azole sensitivity in visceral Leishmania species showed efficacy of ketoconazole [16] and oxiconazole [17] on intracellular amastigotes and of ketoconazole on extracellular promastigotes [18] . Posaconazole [19] and ketoconazole [20] were also effective in mouse models of visceral leishmaniasis , albeit less so than amphotericin B or pentavalent antimonial compounds currently used for visceral leishmaniasis treatments . Azoles have also been extensively tested on cutaneous Leishmania species ( see for instance [21 , 22 , 23 , 24] for early work on these parasites ) . Given the importance of CYP51 as a drug target and the severity of disease caused by L . donovani , we investigated the essentiality of L . donovani CYP51 by biological and pharmacological methods .
All vertebrate animal studies were performed in accordance with the USDA Animal Welfare Act and the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocol was approved by the University of California San Francisco Institutional Animal Care and Use Committee ( protocol AN087316 ) . Euthanasia was performed by carbon dioxide inhalation followed by cervical dislocation . L . donovani 1S/Cl2D promastigotes were maintained at 26°C in M199 medium ( Sigma ) supplemented with 10% heat inactivated fetal bovine serum ( FBS , Sigma ) , 25 mM HEPES , penicillin , streptomycin , adenosine , glutamine , hemin , and folic acid at pH 7 . 2 . Axenic amastigote differentiation was performed as described in [25]: promastigotes were resuspended in amastigote media ( M199 medium supplemented with 25% FBS , streptomycin , penicillin , succinic acid , adenine , glycerol , L-proline and folic acid , at pH 5 . 5 ) at a cell density of 5x106 cells/mL and transferred to 37°C , 5% CO2 . THP-1 macrophages were maintained in RMPI 1640 media supplemented with 5% FBS 1% penicillin-streptomycin at 37°C , 5% CO2 . For Leishmania infection , THP-1 cells were treated with 50 ng/mL phorbol 12-myristate 13-acetate ( PMA ) for 48 h and then infected with stationary phase promastigotes . Cells were then fixed with 4% formaldehyde and stained with 4′ , 6′-diamidino-2-phenylindole ( DAPI ) . Images were obtained with an automated InCell 2000 automated imaging system ( G . E . Healthcare ) and parasite levels determined using IN CELL developer 1 . 9 software ( see S1 Methods ) , leading to determination of cell boundaries and counting of parasite inside the boundary but outside the nucleus in an automated fashion . Female BALB/c mice ( 17–20 g , 6 per group ) were purchased from Simonsen Laboratories and maintained in the animal care facility under pathogen-free conditions . Mice were infected intravenously via the tail vein with 5x107 stationary phase promastigotes and sacrificed 28 days post- infection . Liver parasite burden was determined by direct counting of amastigotes on Diff-Quick stained liver impressions and calculated as Leishman-Donovan Units ( LDU ) : number of amastigotes per 1000 cell nuclei × liver weight ( g ) . All sequences were retrieved from TriTrypDB [26] . 3′ L . donovani CYP51 flanking sequences was amplified by PCR from parasite genomic DNA ( LdBPK_111100 . 1 , primers 1 and 2 ) , digested with SpeI and XbaI , and ligated into the XbaI site of vectors pGEM-PAC and pGEM-Hyg . 5′ CYP51 flanking region was amplified with primers 3 and 4 , digested with SpeI XbaI , and ligated into the SpeI site of vectors already containing the CYP51 3′ flanking region . Knockout cassettes were then liberated by restriction enzyme digestion with SpeI XbaI . The CYP51 coding region was amplified by PCR from genomic DNA ( primers 5 and 6 ) , digested with BglII and ligated into the BglII site of the pXNG4 vector [27] . In all cases , constructs were verified by diagnostic digest and sequencing . Transfection was performed as described in [28] by electroporation in cytomix transfection buffer ( 120mM KCl , 0 , 15mM CaCl2 , 10mM K2HPO4 , 25mM HEPES , 2mM EDTA , 2mM MgCl2 ) using a BioRad Gene Pulser Xcell , delivering two pulses at 1500 V and 25 μF . Parasites were transfected first with the hygromycin knockout cassette; HKO clonal lines were selected with 100 μg/ml hygromycin ( Invitrogen ) , then transfected with the empty pXNG4 vector or the pXNG4 vector encoding CYP51 , thereby generating the HKO + C and HKO + CYP lines , respectively . Double transfectants were maintained with a combination of hygromycin and 100 μg/ml nourseothricin ( GoldBio ) . HKO + C or HKO + CYP lines were transfected with the puromycin knockout cassette and clonal HKO + C + PAC and HKO + CYP + PAC lines isolated by limiting dilution under selection with hygromycin , nourseothricin and 20 μg/ml puromycin ( Sigma ) . Correct targeting of CYP51 genes was verified by PCR using primers 7 ( in CYP51 5′UTR ) and 8 ( in hygromycin resistance gene ) or 9 ( in puromycin resistance gene ) . Persistence of CYP51 genes in double resistant , uncomplemented strains and loss of chromosomal CYP51 in complemented strains were verified by PCR ( primers 10 + 11 and primers 12 + 13 , respectively ) . Primer 12 is upstream of CYP51 , outside of the knockout cassette , and primer 13 anneals within the CYP51 gene . 50 μg/mL ganciclovir ( Invivogen ) was added to the parasite cultures . qPCR on extracted DNA to monitor pXNG4 loss and flow cytometry analysis to assess GFP levels were performed weekly ( see below ) . Results shown represent the average of two independent selection experiments on a total of seven independent clonal lines . DNA was extracted as described previously [29] . qPCR reactions containing 100 ng of parasite DNA in Lightcycler 480 Sybr green I Master mix ( Roche ) were run on a Stratagene Mx3005P RT-PCR thermocycler using the following thermal profile: initial denaturation at 95°C for 10 min , then 40 cycles of denaturation at 95°C for 10 s , annealing at 57°C for 20 s and extension at 72°C for 20 s . Melting curve analysis and agarose gel electrophoresis were used to confirm correct PCR product formation . Chromosomal CYP51 ( primers 14 and 15 ) , total CYP51 ( primers 16 and 17 ) , and pXNG4 ( primers 18 and 19 ) relative levels were determined by qPCR using the 2-ΔΔCt method [30] , normalizing to serine acetyltransferase ( SAT , primers 20 and 21 ) or cystathionine beta-synthase ( CBS , primers 22 and 23 ) , previously shown to be present in only two copies in L . donovani [31] . Analyses were performed on a BDFACSDiva LSRII flow cytometer in HTS mode . Cells were stained with 5 μM propidium iodide ( PI , Sigma ) . Quadrant gates were set used PI-stained wild-type parasites ( GFP-negative ) and percentage of GFP+ PI- cells determined using FloJo X software ( Tree Star Inc ) . 1x107 parasites were lysed in 1x LDS buffer ( Invitrogen ) and separated using NuPage bis-tris precast polyacrylamide gels ( Invitrogen ) . Proteins were transferred to a PVDF membrane ( BioRad ) . Western blot was performed as described in [32] . Affinity-purified anti-CYP51 antibodies ( Genescript ) and anti-GAPDH antibody ( from Paul Michels , Université catholique de Louvain , Bruxelles ) were used at 1:5 , 000 dilution . The secondary antibody was a 1:5 , 000 dilution of peroxidase-conjugated anti-rabbit IgG antibody ( GE Healthcare ) . All proteins were visualized using SuperSignal West Pico Chemoluminescent Substrate ( Thermo Scientific ) . Proteins expression levels were quantified with Image J program , normalizing CYP51 levels to GAPDH levels . Sterol extraction was performed as described in [33] . Briefly , the parasite cell pellet was resuspended in chloroform-methanol solution ( 2:1 ratio ) , then dried under nitrogen gas , followed by overnight treatment with chloroform . The organic phase was then washed with water and dried under nitrogen . The dried pellet was resuspended in chloroform-methanol ( 9:1 ratio ) , and washed again with water . Acetonitrile was added to the samples , washing steps were repeated and solvents evaporated under nitrogen . Extracted sterols were then derivatized by resuspending the dried residue in 25 μL hexanes and 75 μL BSTFA ( Sigma-Aldrich , St . Louis MO ) for 2 hr at 37°C to generate the trimethylsilyl ( TMS ) sterols . TMS-derivatized sterols were analyzed using gas chromatography-mass spectrometry ( GC-MS ) on an Agilent HP 6850 GC coupled to a mass selective detector ( Agilent MSD 5973 ) operating at 70 eV in electron impact mode . The sterols were separated using a DB5-MS analytical column ( 30 m x 0 . 25 mm inner diameter , 0 . 25-μm film thickness , Agilent ) with a temperature profile that begins at 200°C for 1 min , increases by 15°C/min up to 300°C , and holds at 300°C for 20 min . The inlet and detector temperatures were held at 200 and 250°C , respectively . The MSD was set to scan the range 50–750 m/z for sterol profiling . Selected Ion Monitoring ( SIM ) was used for ergosterol quantification by using the same GC temperature profile but assaying for fragment ions specific to ergosterol that elute at the same time window as ergosterol standard: m/z 468 . 4 , 378 . 4 , 363 . 4 , 337 . 4 , and 253 . 1 We prepared an 8-point standard curve of ergosterol using serial dilution over a concentration range of 9 pmol to 1 . 2 nmoles . The area under the curve in the SIM assay was then compared to standard samples to calculate ergosterol concentrations . Amphotericin B , ketoconazole and voriconazole were purchased from Sigma . All other CYP51 inhibitors were synthesized in-house ( see supplementary methods and [34 , 35 , 36] ) . Stationary phase promastigotes ( 8x105/mL ) were treated for 72 h with two-fold dilution of inhibitors in 384 well plate format . Resazurin ( 0 . 025 mg/mL , Santa Cruz ) was added for 5 h , cells were fixed , and fluorescence measured at 490 nm excitation and 595 nm emission wavelengths . Data was normalized to the amphotericin B positive control and DMSO vehicle negative control for each plate , and EC50 values calculated using Collaborative Drug Discovery Vault software . T . cruzi cell-based activity was determined by high content screening in triplicate , as previously described [36] .
We generated half knockout L . donovani parasites ( HKO strains ) in which a single CYP51 allele was replaced with either a puromycin or hygromycin resistance marker ( Fig . 1A; see Fig . 2B for the knockout approach ) . CYP51 is located on chromosome 11 , which is disomic in reference L . donovani genomes [37] , but trisomic in some clinical L . donovani isolates [31] . In addition , the Leishmania genome contains many direct and indirect repeats that can promote extrachromosomal element formation under drug pressure or for essential genes [31 , 38] . Prior to targeting another CYP51 allele , we therefore verified CYP51 copy number in parasites transfected with the first knockout cassette , resistant to either hygromycin ( HygR HKO strains ) or puromycin ( PAC HKO strains ) . HKO strains contained half of the CYP51 DNA content found in wild-type , indicating loss of one out of two alleles ( Fig . 1B ) . Furthermore , CYP51 protein levels were decreased two to five fold in half knockout strains . Complementation with an episomal CYP51 gene restored protein expression to levels comparable to wild-type L . donovani ( Fig . 1C ) . Given the importance of ergosterol biosynthesis in trypanosomatid parasites , we assessed the impact of this loss of CYP51 expression before proceeding to targeting of the second CYP51 allele . In vivo and in vitro infectivity was comparable between strains ( Fig . 1D , Fig . 1E , S1 Fig ) ; any differences between wild-type and transfected strains were not due to changes in CYP51 levels since infectivity of HKO , HKO+C and HKO+CYP was comparable . These strains also all had comparable sterol profiles ( Fig . 1F ) and ergosterol levels ( Table 1 ) . Since L . donovani parasites were able to tolerate over two-fold reductions in CYP51 protein levels with no apparent effects on parasite phenotype , we then proceeded to targeting the second CYP51 allele . However , while we obtained correct targeting of CYP51 with hygromycin and puromycin resistance markers , double drug-resistant parasites still retained CYP51 , despite multiple targeting attempts ( Fig . 2A ) . We therefore used a facilitated knockout approach ( Fig . 2B ) [27 , 39 , 40] , targeting the second CYP51 allele in the presence of episomal CYP51 complementation . As a control , we targeted this second allele in parasites transfected with the empty pXNG4 vector [27] ( S2 Fig . ) . We obtained complete loss of chromosomal CYP51 genes only in the presence of episomal CYP51; genomic CYP51 was retained in the parasites transfected with the empty plasmid , supporting essentiality of CYP51 ( Fig . 2C ) . The pXNG4 vector used for complementation also encodes a green fluorescence protein gene ( GFP ) and a herpes virus thymidine kinase gene; cells that contain the plasmid are sensitive to treatment with ganciclovir ( GCV ) . We therefore performed negative selection against the pXNG4 vector by treating transfected parasites with GCV . Plasmid persistence during GCV treatment was monitored by qPCR and by flow cytometry for GFP . The pXNG4 plasmid was lost much faster from parasites transfected with the empty vector ( retain chromosomal CYP51 ) than from parasites transfected with the vector encoding CYP51 ( only source of CYP51 ) , indicating selection for CYP51 persistence ( Fig . 2D , 2E ) . One clonal line ( HKO1 + CYP + PAC2 ) showed greater loss of pXNG4 plasmid , but still retained CYP51 DNA levels comparable to half knockout strains , with 2^ ( -ΔΔCt ) values of 0 . 6 , leading to ergosterol levels similar to wild-type , even after 7 weeks of GCV selection ( S4 Fig ) . Overall , these results support essentiality of CYP51 in L . donovani . The persistence of CYP51-encoding pXNG4 plasmids even under GCV negative selection indicates that CYP51 is essential in L . donovani . Pharmacological inhibition of CYP51 should therefore lead to parasite growth arrest and death . The 4-aminopyridyl-based compound series of CYP51 inhibitors was derived from an initial hit in target-based high-throughput screening , followed by hit-to-lead optimization using structure-activity relationships ( SAR ) , structure-property relationships ( SPR ) , and biological and structural evaluation for T . cruzi CYP51 [34 , 35 , 36 , 41 , 42 , 43 , 44] . We tested 205 compounds from this series on wild-type intracellular L . donovani amastigotes by high content assay . Fifty-four compounds with over 60% activity at 10 μM were then used for dose-response experiments on wild-type L . donovani promastigotes and strains in which we modulated CYP51 expression ( HKO , HKO+C and HKO+CYP ) . Representative compounds with the highest activity on promastigotes are shown in Fig . 3 , Fig . 4 . Activity on intracellular amastigotes is shown in S3 Table . No clear difference in EC50 values were observed between strains with ketoconazole and voriconazole controls , possibly due to their lower activity on L . donovani . In-house compounds were more potent in this assay than the commercial antifungal azoles . Overall , HKO+CYP strains were less sensitive to these 4-aminopyridyl-based inhibitors compared to HKO+C , indicating that these compounds inhibit Leishmania growth via a CYP51-mediated mechanism . This confirms that targeting CYP51 pharmacologically promotes inhibition of parasite growth , further supporting essentiality of CYP51 in L . donovani metabolism .
CYP51 ( sterol 14alpha-demethylase ) belongs to the large cytochrome P450 enzyme family , which contains over 20 , 000 members . While there is significant variation at the sequence level , CYP51 is highly conserved across eukaroytes at the structural level [45] . However , small variations between species and strains can lead to significant variations in sensitivity to CYP51 inhibitors . Indeed , a single amino acid change in CYP51 in T . cruzi Y strain compared to Tulahuen strain was associated with significant decrease in sensitivity to two CYP51 inhibitors , at concentrations that caused 100% inhibition of the Tulahuen enzyme [46] . In vitro side-by-side comparison of azole efficacy on promastigotes between Leishmania species provides conflicting results: two studies observed increased susceptibility of six different L . donovani strains to ketoconazole and itraconazole compared to six different L . major strains [14 , 18] , while other studies on different L . donovani and L . major strains indicated that L . donovani is more resistant to ketoconazole [47] and posaconazole [19] than L . major . In a separate study , intracellular L . donovani amastigotes were more sensitive to ketoconazole than amastigotes from cutaneous leishmaniasis patients [16] . L . major promastigotes were also insensitive to our 4-aminopyridyl-based compound series of CYP51 inhibitors , even with a longer exposure to the compounds ( S2 Table ) . With regards to clinical trials , azoles have shown large variations in clinical efficacy between Leishmania species , from no effect to almost 90% efficacy [15] , although the majority of these studies have focused on cutaneous leishmaniasis . While there is a single case report of successful posaconazole use to treat cutaneous leishmaniasis caused by L . donovani infantum [48] , to our knowledge there has been no clinical trial of azoles for visceral leishmaniasis . Persistent Leishmania growth in the presence of azoles has been tied to tolerance to 14-methyl sterol accumulation in parasite membranes [14 , 18 , 49] as well as increased exogenous cholesterol incorporation [18] . Recent work indicated that CYP51 appears to be dispensable in L . major , albeit at a high fitness cost [14] . In contrast , given ( 1 ) our inability to fully knockout chromosomal CYP51 unless we provide an extrachromosomal episomal source of CYP51 , ( 2 ) the persistence of this CYP51 episome during negative selection under conditions in which it is the only source of CYP51 , and ( 3 ) the CYP51-specific growth inhibition of 4-aminopyridyl-based non-azole CYP51 inhibitors in L . donovani , our results support essentiality of CYP51 in L . donovani . While extrachromosomal episomal-encoded CYP51 could not fully complement the knockout phenotype , it was indeed active , given its ability to substitute for chromosomal CYP51 and to increase resistance to the 4-aminopyridyl-based non-azole CYP51 inhibitors which directly target the CYP51 active site [13 , 34 , 36] . L . donovani and L . major CYP51 are overall very similar . Comparing the L . major and L . donovani CYP51 protein sequences highlights two amino acid substitutions in β helices 1–1 and 1–2 and a single amino acid insertion at the C-terminal in L . donovani compared to L . major ( S5 Fig ) . This suggests that other mechanisms may be responsible for the observed differences in CYP51 essentiality between L . major and L . donovani . Indeed , squalene synthase , which catalyzes the first committed step in ergosterol biosynthesis , has been involved in resistance to itraconazole [50]; differences in sensitivity to some squalene synthase inhibitors were observed between L . major and L . donovani [51] . Likewise , there were differences in sensitivity to sterol 24-methyltransferase inhibitors between L . major and L . donovani [52] . Finally , the activity of L . donovani 3-hydroxy-3-methylglutaryl coenzyme A reductase ( HMG-CoA reductase ) was 50-fold higher than the activity of the L . major enzyme [53] . HMG-CoA reductase catalyzes the third step of sterol synthesis from acetyl-CoA and is the rate-limiting step in human sterol biosynthesis [54] . Finally , another member of the cytochrome P450 family , CYP5122A1 ( LdBPK_270090 . 1 ) , also modulates ergosterol levels in L . donovani [55]; its expression or activity could be altered in CYP51-deficient L . major , to complement for loss of CYP51 . Beyond differences in CYP51 and sterol biosynthetic pathways between L . major and L . donovani , additional factors could also contribute to this observed difference in CYP51 essentiality . Indeed , Xu et al showed that L . major CYP51 is involved in protection against heat shock [14] . L . major is considerably more sensitive to heat shock than L . donovani , but the mechanism of resistance to heat shock differs between these species , with the L . donovani-specific A2 protein family a key contributor to L . donovani survival during heat stress [25 , 32] . Likewise , gp63 and lipophosphoglycan levels were altered in CYP51-deficient L . major [14] . Lipophosphoglycan is structurally different between L . major and L . donovani [56] , and gp63 from members of the L . donovani species complex is less active than L . major gp63 [57] . Overall , our results support further investigation of CYP51 inhibitors for the treatment of visceral leishmaniasis . While recent clinical trial results using posaconazole for the treatment of Chagas disease were disappointing [58] , the enhanced potency we observed in L . donovani for 4-aminopyridyl-based non-azole inhibitors of CYP51 compared to ketoconazole and voriconazole supports the development of novel inhibitor scaffolds , potentially using our 4-aminopyridyl inhibitor series as a starting point . Given the lower efficacy of these inhibitors on Leishmania compared to T . cruzi , efforts should be made through further medicinal chemistry to optimize both pharmacodynamic and pharmacokimetic properties of these compounds for activity against Leishmania . In particular , efficacy was much lower for intracellular wild-type L . donovani amastigotes compared to our transfected promastigote strains ( S3 Table ) , possibly due to additional constraints with regards to drug uptake into the host cell and into the parasite-containing acidic phagolysosome . Finally , this work and the work of others indicate that CYP51-targeted therapies may not be suitable to treat all Leishmania species . This highlights the importance of considering variations between species and strains early during the drug development process . | Visceral leishmaniasis is the second most lethal parasitic infection after malaria . Other forms of leishmaniasis also cause significant morbidity . However , there are few treatments available , and many cause severe side effects or are associated with the development of resistance . A key difference between mammalian cells and Leishmania parasites is the type of sterol in their membranes: while mammalian cell membranes contain cholesterol , Leishmania parasites use ergosterol . There has therefore been considerable interest in developing inhibitors of sterol biosynthesis pathways to target Leishmania parasites . Sterol 14alpha-demethylase ( CYP51 ) is one of the enzymes in the sterol biosynthesis pathway , and the target of significant drug development research in Leishmania . Here we use a double approach to determine whether this gene is essential in Leishmania donovani , the causative agent of visceral leishmaniasis . We demonstrate via gene knockout and drug targeting approaches that loss or inhibition of CYP51 inhibits L . donovani growth . These results validate CYP51 as a drug target in L . donovani and support further work to develop CYP51-directed therapies for visceral leishmaniasis . | [
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] | [] | 2015 | Targeting Ergosterol Biosynthesis in Leishmania donovani: Essentiality of Sterol 14alpha-demethylase |
Ym1 and RELMα are established effector molecules closely synonymous with Th2-type inflammation and associated pathology . Here , we show that whilst largely dependent on IL-4Rα signaling during a type 2 response , Ym1 and RELMα also have IL-4Rα-independent expression patterns in the lung . Notably , we found that Ym1 has opposing effects on type 2 immunity during nematode infection depending on whether it is expressed at the time of innate or adaptive responses . During the lung migratory stage of Nippostrongylus brasiliensis , Ym1 promoted the subsequent reparative type 2 response but once that response was established , IL-4Rα-dependent Ym1 was important for limiting the magnitude of type 2 cytokine production from both CD4+ T cells and innate lymphoid cells in the lung . Importantly , our study demonstrates that delivery of Ym1 to IL-4Rα deficient animals drives RELMα production and overcomes lung repair deficits in mice deficient in type 2 immunity . Together , Ym1 and RELMα , exhibit time and dose-dependent interactions that determines the outcome of lung repair during nematode infection .
Type 2 immunity is an important component of host defense against helminth infections [1] . Murine infection with the lung migrating nematode , Nippostrongylus brasiliensis , elicits a strongly polarised type 2 response , characterised by IL-4 , IL-13 , IL-5 and IL-9 cytokines . This response is induced once larvae migrate through the airways to take up residence in the intestine [2] . Binding of IL-4/IL-13 via the IL-4 receptor subunit alpha ( IL-4Rα ) is essential for the efficient induction of a type 2 response . IL-4Rα-signaling has been shown to be important not only for parasite expulsion [3] but also for restoration of lung tissue integrity following larval migration and acute neutrophilic inflammation [4] . After engagement of IL-4Rα in mice , the expression of chitinase-like protein , Ym1 ( Chil3 ) and resistin-like molecule alpha ( RELMα; Retnla ) are upregulated in many cell types , including epithelial cells . Due to their abundant expression in macrophages , Ym1 and RELMα are hallmarks of the alternatively activated or M ( IL-4 ) phenotype [5–8] . Whilst we do not yet fully understand the interactions and downstream targets of these molecules , it is clear that both Ym1 and RELMα are important regulators of type 2 immunity [9–11] . As such there is a great deal of interest surrounding the function of these effector molecules and their relationship to inflammation and pathology . Chitinase-like proteins ( CLPs ) are structurally related to chitinases , enzymes that are host-protective through their ability to hydrolyse chitin [12] . Loss-of-function mutations following gene duplication of chitinases , rendered CLPs enzymatically inactive and yet mammalian CLPs appear to be major players during inflammation and pathology [13 , 14] . CLPs are highly expressed during arthritis [15] , cancer [16] , fibrosis [17] , asthma/allergy [18 , 19] and helminth infection [20 , 21] , conditions that are often but not exclusively associated with type 2 dominated responses . Along with Ym1 , RELMα , a cysteine-rich secreted protein , is strongly upregulated during type 2 responses [21 , 22] and expression of both proteins is typically indicative of a strongly polarized type 2 response . There are contrasting findings regarding the role of RELMα during pathology , with reports indicating RELMα can promote [23 , 24] or dampen inflammation [10 , 11] suggesting these roles are highly context dependent . RELMα and Ym1 are often co-expressed in macrophages [6] , epithelial cells [25] , dendritic cells [26] and neutrophils [27] and in many scenarios , mutually dependent on IL-4Rα [5] and STAT6 signaling [28 , 29] . Nonetheless , expression of Ym1 ( by macrophages and neutrophils ) and RELMα ( by granulocytes and epithelial cells ) is readily detectable in the lungs in the absence of type 2 inflammation [22 , 30 , 31] and Ym1 and RELMα can be expressed independently of one another [32–35] . Herein , we aimed to explore the relationship between Ym1 and RELMα in the lungs , both during homeostasis and N . brasiliensis infection , with a particular emphasis on the contribution of IL-4Rα signaling . Our results revealed that innate IL-4Rα-independent Ym1 plays a role in initiating an appropriate type 2 response that occurs later during infection . Conversely IL-4Rα-dependent Ym1 limited type 2 immune responses . We additionally found that Ym1 was able to promote epithelial derived RELMα and mediate tissue repair , and that these actions occurred even in the absence of IL-4Rα signaling . RELMα was important for lysyl hydroxylase expression and tissue repair in the lung following infection-induced pathology , consistent with the ability of RELMα to orchestrate collagen cross-linking in the skin [36] . Together these results demonstrate differential roles for Ym1 depending on the stage of nematode infection , with the novel finding that it can directly promote repair and induce the pro-fibrotic protein RELMα .
We examined the IL-4Rα-dependency of Ym1 and RELMα expression in the lung in the naive state and during innate or adaptive type 2 immune responses . Whilst Ym1 and RELMα expression is readily detectable in the uninfected lungs of both wild-type and IL-4Rα-deficient mice ( Fig 1a and 1b ) , Il4ra-/- mice have significantly less RELMα compared to wild-type controls ( Fig 1a and 1b ) . Following infection with N . brasiliensis , the expression and secretion of Chil3 ( Ym1 ) and Retnla ( RELMα ) in the lung and BAL respectively , increased over time in both Il4ra-/- and wild-type mice ( Fig 1a and 1b ) . However , RELMα levels were significantly lower in IL-4Rα-deficient mice at all time points apart from day 4 . In contrast to RELMα , there was no significant difference in Ym1 levels between genotypes in naive animals ( Fig 1b ) , but there was an initial delay in upregulation of Chil3 expression in Il4ra-/- at day 2 post-infection ( Fig 1a ) . By day 6 post-infection , a time coinciding with adaptive immunity and an established type 2 response , both RELMα and Ym1 expression was significantly reduced in IL-4Rα-deficient mice compared to BALB/c wild-type mice ( Fig 1a and 1b ) . Nonetheless , for both proteins there were significant increases in expression during infection independent of IL-4Rα signaling . To determine whether it is specific cell types that maintain expression of Ym1 and RELMα in the absence of IL-4Rα signaling , lung sections were assessed by immunofluorescence ( Fig 1c and S1a Fig ) . Airway epithelial cells are known to make a large contribution to the secreted levels of Ym1 and RELMα during type 2 immune responses in the lungs [10 , 30] . Consistent with this , RELMα was strongly expressed by lung epithelial cells at day 6 post infection . However , few Ym1+ epithelial cells were observed in lung sections and the majority of Ym1 appeared to be expressed in the myeloid compartment ( Fig 1c and S1a Fig ) . RELMα+ myeloid cells could also be identified in lung sections but at a much lower intensity compared to the airway epithelium ( Fig 1c and S1a Fig ) . At day 4 , epithelial derived RELMα was largely independent of IL-4Rα expression ( Fig 1c and 1d ) , coinciding with equivalent RELMα protein levels in the BAL of wild-type and Il4ra-/- mice ( Fig 1b ) . However , by day 6 post-infection , IL-4Rα-dependence of RELMα expression was evident in the airway epithelium ( Fig 1c ) , and areas of RELMα positivity were significantly reduced in lungs from Il4ra-/- compared to wild-type mice ( Fig 1d ) . Similarly , Ym1+ staining was reduced in lung sections from Il4ra-/- compared to wild-type mice at day 6 ( Fig 1e ) . Intracellular flow cytometry of Ym1 and RELMα was used to determine whether specific myeloid cells were affected by the absence of IL-4Ra signaling ( S1b–S1d Fig ) . In uninfected mice , regardless of IL-4Rα expression , alveolar macrophages and neutrophils made up the predominant pool of Ym1+ cells , whilst RELMα expression appeared limited to DC populations and granulocytes ( S1c and S1d Fig ) . Infection led to an unexpected reduction in the frequency of Ym1+ alveolar macrophages and neutrophils likely reflective of active secretion of intracellular proteins ( S1d Fig ) . Notably , the loss of Ym1 expression in neutrophils was dependent on IL-4Rα expression suggesting that signaling through the receptor may mediate Ym1 release . Whilst a significant reduction in Ym1+ monocyte-derived dendritic cells ( MoDCs ) and DCs were observed in IL-4Rα-/- compared to wild-type mice , the overall contribution of these cell types to the pool of secreted Ym1 is likely to be limited ( S1d Fig ) and probably does not explain the overall reduction in the Ym1+ area in stained lung sections ( Fig 1c and 1e ) . However , routine tissue digestion may not release all myeloid cell populations for flow cytometry with some resident myeloid populations only detectable by staining lung sections . Unlike Ym1 , which is predominantly produced by macrophages and neutrophils following infection , many different cell types appear to contribute to RELMα production in the lungs ( S1c and S1d Fig ) . Reduced numbers of RELMα+ interstitial macrophages ( IMs ) , MoDCs , DCs , eosinophils and epithelial cells ( S1a , S1c and S1d Fig ) were together responsible for reduced RELMα secretion in IL-4Rα-/- mice ( Fig 1b ) . Together these results demonstrated that high level expression of both Ym1 & RELMα is IL-4Rα-dependent in the context of nematode infection of the lung , extending other studies [25 , 32 , 37] . However , they also revealed an important contribution of IL-4Rα-independent pathways for Ym1 and RELMα expression , which was particularly evident for Ym1 prior to full establishment of the adaptive type 2 response . Surprisingly , IL-4Rα-independent expression of RELMα and Ym1 was observed in all cell types examined , with the exception of MoDCs , whereby infection-induced Ym1 was strongly IL-4Rα-dependent . We have previously found that IL-4Rα-independent Ym1 expression during the steady state and early N . brasiliensis infection ( days 0–4 ) drives expansion of innate γδ T cell populations expressing IL-17A [9] . In that study we found that increased IL-17A was needed for the induction of a competent type 2 response [9] . We therefore hypothesised that innate Ym1 might regulate the subsequent type 2 response during nematode infection . To test this , N . brasiliensis infected BALB/c wild-type mice were administered intraperitoneally with a neutralising mouse monoclonal antibody against Ym1 or an isotype matched control antibody ( Fig 2a ) [9 , 38] . At day 6 post-infection the increase in Il5 and Il13 mRNA expression in total lung was significantly reduced following anti-Ym1 treatment whilst Il4 was not significantly altered ( Fig 2b ) . As both innate lymphoid cells ( ILCs ) and Th2 cells are major producers of type 2 cytokines during infection in the lung , we examined these two cell populations following PMA and ionomycin stimulation of single cell suspensions . As expected , the absolute number of ILCs and CD4+ T cells expressing type 2 cytokines were increased in the lungs following infection , with approximately 10-fold greater numbers of CD4+ T cells than ILCs ( Fig 2c and 2d ) . Anti-Ym1 significantly reduced the numbers of IL-5- and IL-13-producing ILCs in the lung ( Fig 2c ) . Reduced ILCs together with a significant reduction in the numbers of IL-13+ CD4+ T cells ( Fig 2d ) , likely contributed to the overall reduction in type 2 cytokine expression in the lung ( Fig 2b ) . The effect of Ym1 on the type 2 response was not restricted to the lungs of infected mice , as anti-Ym1 treatment also reduced basal splenocyte cytokine secretion and anti-CD3 stimulated IL-5 and IL-13 but had no effect on IL-4 secretion ( S2a Fig ) . Consistent with the dependence of RELMα expression on IL-4Rα signaling described above ( Fig 1 and S1 Fig ) , RELMα secretion was reduced following anti-Ym1 treatment ( Fig 2e ) . In addition , eosinophil influx in infection , a response highly dependent on IL-5 [39] , was also reduced following anti-Ym1 treatment ( Fig 2f ) . Our data showed that innate sources of Ym1 promoted the development of type 2 immunity leading us to examine whether Ym1 also regulated type 2 immunity once the adaptive type 2 response was initiated ( > day 4 ) . We therefore administered anti-Ym1 to N . brasiliensis infected mice between days 3–5 ( Fig 3a ) . Anti-Ym1 treatment at this later stage of infection had no effect on the expression of Il4 , Il5 and Il13 in whole lung tissue ( Fig 3b ) . In uninfected animals , type 2 cytokine production by ILCs contribute to greater than half IL-13 and IL-5 production in the lungs ( S2b Fig ) . However , in contrast to neutralising innate Ym1 ( Fig 2 ) , neutralising adaptive Ym1 resulted in a significant increase in the absolute numbers , of IL-5+ and IL-13+ ILCs and CD4+ T cells in the lungs of infected mice ( Fig 3c and 3d ) , but did not change the proportion of cells that contributed to IL-5 and IL-13 production ( S2b Fig ) . The effects of anti-Ym1 treatment were not restricted to the lungs , as IL-4 , IL-5 and IL-13 secretion from splenocyte restimulation were also increased in treated mice ( S2c Fig ) . Despite the small but significant increases in type 2 cytokines , the absolute numbers of eosinophils in the lungs were not altered by anti-Ym1 treatment ( Fig 3e ) , nor was there an impact on parasite recovery ( S2d Fig ) . Overall , our results demonstrate that Ym1 regulates type 2 cytokine producing ILCs and Th2 cell numbers in the lungs , but with opposing outcomes depending on the stage of the immune response .
Herein , we have observed that Ym1 can regulate type 2 immunity ( both positively and negatively ) depending on timing . In addition , we found that Ym1 mediated lung repair . RELMα is similarly implicated in both type 2 regulation and tissue repair [36] [10 , 11] . Ym1 and RELMα are often co-expressed and we have previously observed that RELMα production follows increases in Ym1 [34] . These observations together , led us to consider the possibility that Ym1 may act in part through the induction of RELMα . Strongly supporting this hypothesis was our finding that RELMα levels in the BAL fluid of N . brasiliensis infected wild-type mice were significantly reduced following anti-Ym1 treatment ( day 3–5 ) , an effect not observed on whole lung mRNA expression suggesting post transcriptional regulation ( Fig 5a ) . Importantly , this result cannot be explained by an altered type 2 response , as the timing of anti-Ym1 treatment enhanced IL-5 and IL-13 production ( Fig 3 ) , which would be expected to increase RELMα expression . We examined the intracellular expression of RELMα in lung myeloid cells and observed no reduction in RELMα positivity between IgG2a and anti-Ym1 treated infected mice ( Fig 5b and 5c ) . Only a significant increase in the number of RELMα+ MoDCs was seen in the lungs of infected mice following anti-Ym1 treatment . Additionally , anti-Ym1 treatment reduced the proportion of RELMα+ neutrophils ( Fig 5c ) , an effect that likely reflects the reduction in type 2 cytokines as seen in IL-4Rα-/- mice ( S1d Fig ) . In contrast , quantification and visual inspection of RELMα expression by the airway epithelium in histological sections showed that neutralising Ym1 significantly reduced RELMα+ fluorescent intensity ( Fig 5d and 5e ) . Thereby , our data demonstrated an ability of Ym1 to enhance RELMα production , particularly from epithelial cells , independent of altered type 2 cytokine expression . Of note , the enhanced type 2 response itself , may be explained by diminished RELMα in anti-Ym1 treated mice , as RELMα has been shown to suppress Th2 cells [10 , 11] . We next tested whether Ym1 alone was sufficient to induce RELMα using an in vivo transfection approach . Wild-type BALB/c mice were intranasally administered a plasmid encoding Ym1 , which led to a specific upregulation of Chil3 mRNA expression in BAL cells relative to pcDNA3 . 1 transfected control mice [9] . Over-expression of Ym1 into the lungs of wild-type mice resulted in a significant increase in RELMα protein secreted into the BAL fluid 48 hrs post-transfection ( Fig 5f ) suggesting Ym1 expression alone was sufficient to regulate RELMα levels . Type 2 responses are essential for rapid resolution of tissue pathology and as such , lungs from mice deficient in IL-4Rα signaling exhibit a profound failure to repair following N . brasiliensis infection [4] . However , changes to type 2 cytokine responses following anti-Ym1 treatment could not explain reduced RELMα and delayed tissue repair , although the altered immune response may be a consequent of enhanced tissue damage . We therefore asked whether Ym1 could enhance tissue repair and/or alter RELMα expression independently of the type 2 response . Physiologically relevant levels of recombinant Ym1 observed in the BAL during N . brasiliensis infection ( S2e Fig ) and lung inflammation [42] , was delivered to IL-4Rα-deficient animals at the time when repair in wild-type mice would usually occur ( days 4 and 5 ) and responses were examined at day 6 post-infection ( Fig 6a ) . As expected , IL-4Rα-/- mice showed enhanced tissue damage , coinciding with a failure to repair the lungs following infection ( Fig 6b and 6c ) . Remarkably , intranasal administration of Ym1 alone was enough to reverse the effects of loss of IL-4Rα and enhance tissue repair to the levels seen in wild-type mice ( Fig 6b and 6c ) . Importantly , accelerated lung repair in Ym1 treated mice did not reflect altered worm burdens in Il4ra-/- mice ( S2f Fig ) . Furthermore , Ym1 specifically increased expression of epithelial cell derived RELMα independently of the IL-4Rα ( Fig 6d and 6e ) . Total RELMα secretion into the BAL was not significantly increased in IL-4Rα-/- mice treated with Ym1 ( Fig 6f ) despite changes to epithelial RELMα production ( Fig 6d and 6e ) . However , this likely reflects the inability of Ym1 to induce RELMα in myeloid cell populations ( Fig 6g ) . Together , this data confirms the ability of Ym1 to aid tissue repair and stimulate epithelial-derived RELMα independently of IL-4Rα signaling and type 2 cytokines . RELMα is known to be an important player in skin repair [36] , and we find here that Ym1 promotes lung repair ( Figs 4 and 6 ) while inducing RELMα production by epithelial cells ( Figs 5 and 6 ) . It was therefore important to establish the contribution of RELMα to lung repair following N . brasiliensis infection . Early intestinal worm burdens in Retnla-/- versus C57Bl/6 wild-type mice were examined first to ensure the results were not biased by altered numbers of parasites passing through the lungs . At day 4 , we expected similar worm burdens in Retnla-/- compared to wild-type mice [10] and indeed this was the case ( Fig 7a ) . However , when using heterozygous littermate controls , we unexpectedly found significantly fewer parasite numbers , suggesting that the amount of RELMα differentially impacts on parasite burden . Notably , we routinely detect a large variation in RELMα protein levels in the serum of both naive wild-type and heterozygote mice with up to ~20-fold difference between mice of the same genotype . ( S3a Fig ) . Because variation in the host RELMα status prior to parasite exposure may influence infection outcome we included heterozygotes in all our subsequent analysis of repair . We examined infected littermate Retnla deficient , heterozygous and sufficient mice during the initiation of repair ( day 4 ) after acute lung injury [9] , and at a time when IL-4Rα-signaling is thought to be critical for appropriate repair ( day 6 ) [4] . Whilst histological examination of lungs from Retnla +/+ and +/- mice showed small areas of damage at day 4 post-infection ( Fig 7b ) , repair of the lung architecture had been initiated following larval passage . Strikingly , there was extensive alveolar deterioration throughout the lung tissue of Retnla -/- mice , an effect quantitatively measurable by changes in linear mean intercept ( Fig 7c ) . As infection progressed to day 6 , the lung tissue underwent repair in wild-type mice as well as Retnla -/- mice , however , the lungs from Retnla -/- mice remained visibly more damaged ( Fig 7b and 7c ) . In contrast , the lungs from Retnla +/- mice appeared structurally similar to infected wild-type mice at day 4 ( Fig 7b and 7c ) , but failed to maintain the process of repair through day 6 and instead further deteriorated ( Fig 7c ) . Notably , by day 10 post-infection , the lungs of Retnla +/- mice had not deteriorated further , but unlike lungs from wild-type mice exhibited only limited signs of repair ( S3b and S3c Fig ) . This failure of Retnla +/- to repair their lungs was associated with an overall reduced RELMα expression but did not appear to be associated with restricted expression in a particular cell type , such as the epithelium ( S4 Fig ) . Although Ym1 promoted tissue repair alongside epithelial-derived RELMα , the experiments in heterozygote mice do not provide evidence for a specific RELMα-expressing cell type involved in tissue repair . Rather it appears that RELMα quantity has a significant role in the dynamics of repair , and one possibility is that Ym1 is an important regulator of RELMα protein availability . The ability of RELMα to promote pro-fibrotic collagen cross-linking through increased expression of lysyl hydroxylase has been identified as an important pathway in the generation of an effective wound healing response in the skin [36] . Therefore , we examined the levels of lysyl hydroxylase in the lungs of mice following infection-induced injury in relation to Retnla expression . Expression of lysyl hydroxylase 2b ( Lh2b ) in the lungs of N . brasiliensis infected wild-type mice at day 4 and day 6 time points was increased relative to uninfected controls ( Fig 8 ) coinciding with tissue repair ( Fig 7 ) . Quantification of the area of Lh2b staining revealed a significant reduction in the expression of Lh2b in Retnla +/- and -/- mice at day 4 compared to infected wild-type ( +/+ ) mice ( Fig 8b ) . By day 6 , when the lungs of RELMα-deficient animals were undergoing repair ( Fig 7c ) , the level of Lh2b expression was equalised to that of a wild-type mouse ( Fig 8c ) . However , Lh2b levels remained low in Retnla +/- , reflecting a change in the rate of repair in these mice ( Figs 8c and 7c ) . These results show that RELMα regulates Lh2b expression in the lungs as well as the skin and may play an important role in lung repair by regulating collagen cross-linking following mechanical injury and innate inflammatory insult . However , it appears that the amount of RELMα is an essential factor to sustain repair . Finally , because we had unexpected results regarding heterozygote mice , we felt it important to re-evaluate in our system , the reports that RELMα negatively regulates Th2 immunity [10 , 11] . We therefore examined whether type 2 cytokine expression was altered in the lungs of Retnla -/- and Retnla +/- mice compared to wild-type controls . Although infection led to increases in the numbers of IL-5 and IL-13 producing cells at day 4 and 6 , there were no significant differences between Retnla genotypes ( S5a–S5c Fig ) . Assessment of IL-4 , IL-5 and IL-13 secreted from splenocyte cultures also showed no significant differences between Retnla genotypes at day 4 but by day 6 enhanced IL-4 , IL-5 and IL-13 was detected in Retnla -/- compared to wild type mice and Retnla +/- ( S6a–S6c Fig ) . Furthermore , when CD4+ T cell type 2 responses were measured in the lungs at day 10 post-infection , Retnla +/- mice exhibited significantly increased numbers of IL-4+ and IL-13+ CD4+ T cells ( S5d Fig ) . These results support the finding that RELMα can negatively regulate the adaptive type 2 response [10 , 11] , but the effect appears to be dependant on the time of infection and is perhaps reflective of an immune response to control ongoing tissue damage in Retnla +/- mice .
CLPs are intriguing molecules at the forefront of Th2-type immunopathology , yet their biological functions remain mostly conjectural . We show here that Ym1 produced in the lung during the adaptive response to N . brasiliensis infection facilitates rapid tissue repair in a process that does not require IL-4Rα . We also reveal that Ym1 regulates the type 2 immune response in opposite directions depending on whether it is expressed during innate versus adaptive phases . Early in infection , levels of Ym1 were independent of IL-4Rα-signaling . During this phase , Ym1 induces an IL-17A/neutrophilic response but also promotes the development of subsequent type 2 immunity [9] . This finding is consistent with increasing evidence that IL-17A is needed for many type 2 responses [9 , 43 , 44] . In contrast , once the adaptive Th2 response was established , IL-4Rα-signaling vastly increased Ym1 production . In this context , Ym1 now limited type 2 responses and reduced IL-5 and IL-13 expression ( S7 Fig ) . This suggests that in addition to acting directly as a repair molecule Ym1 may be an endogenous regulator of the Th2-type balance , important for avoiding allergic disease or fibrosis , the consequences of an overzealous response [45] . The concept that Ym1 , and CLPs in general , are involved with wound healing and tissue remodeling is not new [30 , 41 , 46] but direct experimental evidence has been lacking . The pro-repair actions of Ym1 likely relate to its ability to bind extracellular matrix ( ECM ) components such as heparin/heparan sulfate proteoglycans [40 , 41] and regulate the availability of reparative proteins [47 , 48] . Consistent with this concept , blockade of Ym1 during the adaptive stage of infection prevented efficient lung repair and delivery of Ym1 to IL-4Rα-deficient mice rescued their failure to rapidly repair . Both these experiments revealed Ym1 as an unexpected driver of epithelial-derived RELMα . RELMα can directly restore skin tissue integrity following sterile wounding [36] and has been implicated in extracellular remodeling [49–51] . It is therefore reasonable to hypothesise that RELMα may be at least in part responsible for the pro-repair effects of Ym1 . Consistent with its role in the skin [36] we found RELMα to be a critical regulator of the collagen cross-linking enzyme lysl hydroxylase 2 ( LH2b , Plod2 ) in the lungs . Notably , the amount of LH2b protein correlated with the degree of lung repair . LH2b is critical for vascular integrity [36] , potentially explaining the microbleeding observed in anti-Ym1 treated animals . Crosslinked collagen mediated by LH2b is more stable and resistant to collagenase cleavage resulting in stiffer tissue structure [52] . Increased Plod2 mRNA expression has been reported during fibrotic conditions [53 , 54] implicating Plod2 as a driver of excessive extracellular matrix remodeling [55 , 56] . Our work here and in the skin [36] , suggest it may also be important for rapid tissue regeneration and repair following injury . Whilst we have not directly explored whether Ym1 influences collagen biosynthesis or degradation , our data suggests Ym1 may regulate collagen fibril formation by controlling the quantity of epithelia-derived RELMα . Interestingly YKL-40 , a CLP expressed in humans that has strong functional similarities to murine Ym1 , not only contains binding motifs for heparin and hyaluronan [57] , major constituents of the extracellular matrix , but also for type I collagen [58] . Moreover , binding of YKL-40 to collagen was shown to alter collagen structure or behaviour in a way that prevented cleavage of fibrils and hence aided collagen stability [58 , 59] . Thus , CLPs in both humans and mice , may play an important regulatory role in collagen formation and turnover either through direct mechanisms or by regulating factors such as RELMα . In addition to its effects on Plod2 , RELMα can both promote IL-17 [23] and suppress Th2 cytokines [10 , 11] and thus downstream actions of RELMα may also contribute to the immune regulatory properties we observed for Ym1 . Inconsistent with this hypothesis , at day 6 post-infection , we did not observe any significant changes to IL-5 and IL-13 mRNA or protein producing CD4 T cells or ILCs in the lungs of infected RELMα-deficient mice during this peak reparative phase . However , at day 10 post-infection our studies using heterozygote mice do support the described negative regulatory function for RELMα . These data are in line with numerous published models of inflammation and remodeling , where the ability of RELMα to negatively regulate type 2 cytokines was clearly evident in some studies [10 , 11] or not detectable in others [60 , 61] . Unfortunately , unlike the use of the anti-Ym1 antibody , the RELMα deficient mice do not allow us to separate potentially disparate effects of RELMα on the early vs late type 2 response , which may account for the variable outcomes on type 2 inflammation reported in the literature [10 , 11 , 60 , 61] . Whilst differences in published results may be explained by timing or the model and tissue involved , our studies using deficient , heterozygote and wild-type littermate mice reveal that the amount of RELMα may be a critical determinant of its function . For example , our parasite recovery data suggested that high or low levels of RELMα were less effective for host resistance than intermediate levels . A search of published data reveals large variations in reported serum levels of RELMα during the steady state , from as little as ~2ng/mL to upward of ~500ng/mL [23 , 24 , 62 , 63] . We observed an average of 200ng/mL RELMα in serum of wild-type mice , but there was enormous variation in protein levels that could not be accounted for by sex , age or cage allocation . It would be interesting in future studies to determine whether Ym1 mediates its effects at least partly through regulating RELMα availability , whose functions may rely on critical quantitative thresholds . The expression of RELMα and Ym1 or related family members during many disease pathologies points toward the breadth of their functions that we are only just starting to uncover . In this study of helminth infection , we have illustrated that one molecule , Ym1 , can perform distinct and even opposing functions at different stages of infection . The data also suggest that RELMα may function differently depending on the stage of infection . For example , because RELMα can suppress Th2 cytokines and Th2-driven pathology mediated pathology [10 , 11] it would be logical to hypothesise that RELMα-deficient mice would exhibit accelerated or enhanced lung repair following N . brasiliensis infection . However , during the period where a heightened repair response is evident , we observed the opposite , consistent with the reported ability of RELMα to mediate collagen turnover [36] and protect against damaging acute lung inflammation [62] . Many of these apparent contradictions may lie with the distinct function of Ym1 and/or RELMα during innate and adaptive stages of an immune response . However , it remains to be seen how tightly linked Ym1’s functions are to its ability to induce RELMα . In addition , recent data suggest that macrophage-derived RELMα is critical for its regulatory function [64] and we have yet to establish whether the ability of Ym1 to induce RELMα is restricted to epithelial cells . Finally , the changes in Ym1 function over time may largely relate to its ability to bind ECM , the properties of which will change over the course of an immune response . Thus , Ym1 interactions within the ECM may enable context-specific biological functions . The details of Ym1-ECM collaboration in vivo remain unexplored and will be an exciting future challenge .
All animal experiments were performed in accordance with the UK Animals ( Scientific Procedures ) Act of 1986 under a Project License ( 70/8548 ) granted by the UK Home Office and approved by the University of Manchester Animal Welfare and Ethical Review Body . Euthanasia was performed by carbon dioxide exposure . Wild-type ( BALB/c or C57BL/6 ) mice , Il4ra -/- ( BALB/c and C57BL/6 ) mice [65] and Retnla +/+ , Retnla +/- or Retnla -/- ( C57BL/6 ) mice [10] were bred at the University of Edinburgh or the University of Manchester . All mice were 7–14 weeks old at the start of the experiment and were housed in individually ventilated cages during experimental procedures . For experiments using Retnla +/+ , Retnla +/- or Retnla -/- , mice were bred as littermates and were randomized in cages with investigators blind to mouse identity during necropsy . All experiments used female mice except Retnla littermate experiments ( Figs 7 & 8 and S3–S6 Figs ) , which used both sexes . Anti-Ym1 and IgG2a isotype matched control antibodies were purified from hybridoma cell lines as described previously [9] . Briefly , anti-Ym1 mouse hybridoma cell line ( clone 4D10 ) was generated by immunising mice with a Ym1 peptide ( IPRLLLTSTGAGIID ) shown to be neutralizing [66] . The hybridoma cell line ( clone 2D12 ) from European Collection of Cell Cultures was used as the IgG2a isotype-matched control antibody . Antibodies were purified by protein G affinity chromatography using an Akta Prime Plus ( GE Healthcare ) . N . brasiliensis was maintained by serial passage through Sprague-Dawley rats , as previously described [2] . Third-stage larvae ( L3 ) were washed ten times with sterile PBS prior to subcutaneous infection of 500 L3’s or 250 L3’s per mouse ( figure legend details N . brasiliensis infection dose in each experiment ) . In some experiments , mice were treated intraperitoneally with 200μg anti-Ym1 or IgG2a isotype on days indicated ( Figs 2a and 3a ) . Additional some mice were treated intranasally with recombinant Ym1 ( R&D Systems ) or PBS on days indicated ( Fig 6a ) . On days 4 , 6 and 10 post-infection BAL was performed with 0 . 25% BSA containing PBS and lungs were taken for further assays and analysis . Single-cell suspensions of splenocytes were stimulated ex vivo with N . brasiliensis excretory secretory product antigen ( 1μg/mL or anti-CD3 1μg/mL ) for 72 hrs . Cell supernatants were collected and stored at -20°C until further analysis . At day 4 and 6 post-infection , the small intestine was removed from mice and stored in Dulbeccos’ PBS . Intestines were then cut longitudinally along the entire length of the gut and parasite numbers counted manually with the aid of a dissecting microscope . Wild-type BALB/c mice were administered 20μg pcDNA3 . 1 ( Control ) or Ym1 plasmid complexed with in vivo JetPEI ( Source Bioscience ) intranasally as described previously [9] . BAL fluid was harvested 48 h after transfection . Mice that were not transfected were excluded from the analysis . A section of the right lung lobe was stored in RNAlater prior to homogenization in Qiazol reagent , or BAL cell pellets were resuspended in Qiazol reagent at the time of necropsy and stored at -80°C until further analysis . RNA was prepared according to manufacturers instructions . Reverse transcription of 0 . 5μg of total RNA was performed using Tetro reverse transcriptase ( Bioline ) [9] . Transcripts of genes of interest were measured by qRT-PCR with the Lightcycler 480 II system and Brilliant III SYBR Master mix ( Agilent ) and specific primer pairs ( Table 1 ) . PCR amplification was analysed by the second-derivative maximum algorithm ( LightCycler 480 Sw 1 . 5; Roche ) and expression of the gene of interest normalized to expression of housekeeping genes Rpl13a or 18srRNA . The levels of RELMα in the BAL were measured by sandwich ELISA , using rabbit anti-mouse RELMα and biotinylated rabbit anti-mouse RELMα ( Peprotech ) . Cytokines IL-5 and IL-13 were measured in single-cell suspensions of splenocytes stimulated with N . brasiliensis excretory secretory antigen or anti-CD3 mitogen for 72hrs . IL-4 levels were measured using rat anti-mouse IL-4 ( 11B11 , Bio X Cell ) and biotinylated rat anti-mouse IL-4 ( BVD6-24G2 , Biolegend ) compared to a recombinant IL-4 standard ( Peprotech ) . IL-5 levels were measured using rat anti-mouse IL-5 ( TRFK4 , home-grown ) and biotinylated rat anti-mouse IL-5 ( Biolegend ) compared to recombinant IL-5 ( Peprotech ) . IL-13 levels were measured using rat anti-mouse IL-13 and biotinylated rat anti-mouse IL-13 ( eBioscience ) compared to a recombinant IL-13 standard ( Peprotech ) . A fragment of the right lung lobe was digested for 30 min at 37°C with 0 . 2U/mL Liberase TL ( Roche ) and 80U/mL DNase ( Life Tech ) in Hanks Balanced Salt Solution ( Sigma ) prior to forcing the tissue suspensions through gauze . Red blood cells were lysed and live cells counted using trypan blue exclusion on an automated Cellometer T4 ( Nexcelom ) . Cells were incubated with Fc block ( CD16/CD32 ( eBioscience ) and mouse serum ) and were stained with fluorescence-conjugated antibodies . Cells were identified by expression of surface markers as follows and as indicated in ( S1b Fig ) : neutrophils Ly6G+ ( 1A8 ) CD11b+ ( M1/70 ) , dendritic cells CD11c+ ( N418 ) MHCII+ ( M5/114 . 15 . 2 ) F4/80- ( BM8 ) , monocyte derived DCs F4/80+ CD11b+ CD11c+ SigF- ( E50-2440 ) alveolar macrophages F4/80+ CD11c+ CD11blo , SigF+ , interstitial macrophages F4/80+ CD11b+ CD11c- SigF- , CD4 T cells CD4+ ( GK1 . 5 ) TCRβ+ ( H57-597 ) CD11b- and ILC2s Lineage- ( CD11b , TCRβ TCRγδ ( GL3 ) Ly6G F4/80 CD11c SigF CD19 ( 6D5 ) ) CD90 . 2+ ( 30-H12 ) ICOS+ ( C398 . 4A ) . Cells were fixed for 10min ( RT ) with 2% paraformaldehyde and stored at 4°C until intracellular staining was performed or cells were acquired . To measure intracellular Ym1 and RELMα , cells were permeabilised ( eBioscience ) and incubated with rabbit anti-mouse RELMα ( Peprotech ) or biotinylated goat anti-mouse Ym1 ( R&D ) followed by Alexa-Fluor 488 rabbit xenon labeling kit ( Life Technologies ) and streptavidin PerCP ( Biolegend ) . Intracellular IL-5 and IL-13 were measured in cells simulated at 37°C for 4h with PMA ( phorbol myristate acetate; 0 . 5μg/mL ) and ionomycin ( 1μg/mL ) and for the last 3h with brefeldin A ( 10μg/mL ) . Cell surfaces were stained according to details above , fixed with 2% paraformaldehyde prior to cell permeabilisation ( eBioscience ) . Cells were then stained with Pe-Cy7 conjugated anti-mouse IL-13 ( eBio13A; eBioscience ) and APC conjugated anti-mouse IL-5 ( TRFK5; Biolegend ) or isotype matched controls ( eBRG1; eBioscience ) prior to acquisition . Live/dead aqua ( Life Technologies ) was used to exclude dead cells from the analysis . Samples were acquired with a FACSCanto II or LSR II ( Becton-Dickinson ) and analysed using FlowJo software ( version 9 . 9 . 5; TreeStar Inc . ) . Lung tissue was fixed-perfused with 10% neutral buffered formalin and incubated overnight prior to placing tissue in 70% ethanol . Lung tissue was processed , embedded in paraffin , and sectioned to slides . Sections were stained with hematoxylin and eosin and linear means intercept ( Lmi ) quantified as a score of lung damage , as described previously [9] . Briefly , lung samples were viewed by microcopy with an original magnification of ×200; 15 random non-overlapping fields per sample were assessed . Six horizontal lines were drawn across each image with ImageJ ( version 1 . 44 ) and the total number of times the alveolar wall intercepted per line was counted . Line length was then divided by the number of intercepts to calculate Lmi . All samples were analyzed by researchers ‘blinded’ to sample identity . Hemosiderin Laden macrophages were assessed in sections stained with Prussian blue according to standard laboratory procedures . The numbers of Prussian blue positive macrophages were counted ( x200 magnification ) by a researcher “blinded” to sample identity . For immunofluorescence imaging , sections were deparaffinized , hydrated and incubated with Retrievagen A pH6 . 0 solution ( BD Bioscience ) for 20min at 98°C for antigen retrieval . Endogenous biotin was blocked ( Life Technologies ) prior to an overnight incubation with primary antibodies rabbit anti-mouse RELMα ( 1:100 ) and biotinylated goat anti-mouse Ym1 ( 1:50 ) or goat anti-LH2b ( 1:100 , Santa Cruz sc-50067 ) followed by a 1hr incubation with Northern Lights 494 ( 1:100 ) and streptavidin NL557 ( 1:800 ) , or Northern Lights 557 anti-goat ( 1:100 ) . Sections were mounted with Fluormount G containing DAPI , for DNA staining . RELMa and Ym1 staining was visualised on a Leica SP5 confocal laser scanning microscope or EVOS™ FL Imaging System ( ThermoFisher Scientific ) . For quantification of RELMα fluorescence intensity , three airways of similar size per sample were selected by visualisation of DNA ( DAPI ) by an investigator blind to sample identity . Fluorescence intensity was calculated with ImageJ software ( version 1 . 44 ) , by setting a threshold measurement to calculate integrated density and area of RELMα positivity corrected for background intensity . Statistical analysis was performed using Prism 7 . 0 ( version 7 . 0c , GraphPad Software ) . Differences between groups were determined by t-test or ANOVA followed by Tukey’s or Sidak multiple comparison-test . In some cases data was log-transformed to achieve normal distribution as determined by optical examination of residuals . Comparisons of different Ym1 and RELMα positive cell populations within the lungs of one experimental animal were considered as paired observations . Differences were assumed statistically significant for P values less than 0 . 05 . | Immune cells produce molecules that limit infections , attract other immune cells or repair tissue damage . Two such molecules , Ym1 and RELMα , are abundantly produced in mice during infection and injury . Related human molecules are strongly associated with many chronic diseases and yet we know very little about their function . Nippostrongylus brasiliensis is a parasitic worm that migrates through the lung causing tissue damage , which is accompanied by a strong early inflammatory response . Subsequently the lung is rapidly repaired , a process that requires an immune response that is characterised by the production of large amounts of Ym1 and RELMα . Here we show that during the early lung injury phase of infection , Ym1 helps direct the immune response towards repair but once repair has been initiated , Ym1 acts to limit excessive immune activation . Additionally , Ym1 enhances RELMα production in the lung and together , these molecules contribute to lung repair . Therefore Ym1 and RELMα have distinct regulatory functions depending on the stage of injury or infection , and additionally can act directly to repair injured tissues . These findings demonstrate the diverse functions of Ym1 and RELMα with wider implications toward understanding the relationship between host immune responses and tissue repair . | [
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"de... | 2018 | Ym1 induces RELMα and rescues IL-4Rα deficiency in lung repair during nematode infection |
Theoretical and empirical investigations of search strategies typically have failed to distinguish the distinct roles played by density versus patchiness of resources . It is well known that motility and diffusivity of organisms often increase in environments with low density of resources , but thus far there has been little progress in understanding the specific role of landscape heterogeneity and disorder on random , non-oriented motility . Here we address the general question of how the landscape heterogeneity affects the efficiency of encounter interactions under global constant density of scarce resources . We unveil the key mechanism coupling the landscape structure with optimal search diffusivity . In particular , our main result leads to an empirically testable prediction: enhanced diffusivity ( including superdiffusive searches ) , with shift in the diffusion exponent , favors the success of target encounters in heterogeneous landscapes .
The random search problem has lately received a great deal of attention [1] , [2] . This is partly due to its broad interdisciplinary range of applications , which include , e . g . , enhanced diffusion of regulatory proteins while “searching” for specific DNA spots [3] , [4] and the finding of binding sites on transmembrane proteins by neurotransmitters in the brain [5] . Recently , this problem has also found interesting connections with human mobility and related topics [6]–[9] . A classical context in which the random search problem has been applied in the last four decades is animal foraging [1] , [2] , [10]–[27] , with the searcher ( i . e . forager ) typically represented by an animal species in quest of target sites ( prey , food , other individuals , shelter , etc . ) in a search landscape . Among the most studied random walk models proposed as plausible search strategies , we cite correlated random walks [12] , [28] , [29] , Lévy flights and walks [13]–[17] , [19] , [20] , [24] , [25] , [27] , [30]–[39] , intermittent walks [40]–[46] , and composite Brownian walks [47] , [48] . In particular , Lévy random searchers , with probability distribution of step lengths , for , have successfully explained [34] the emergence of optimal searches in landscapes with randomly and scarcely distributed target sites . On the other hand , when resources are plentiful Lévy strategies are unnecessary [34] , and efficient Brownian optimal searches may arise with , e . g . , a Poisson-like exponential distribution [24] , [25] . Lévy flights and walks have been also shown to be relevant in several other contexts [1] , such as in proteins searching for specific DNA sites [49] , in which the optimal Lévy mechanism emerges directly from the underlying physics of the problem ( polymer scaling theory in three dimensions ) . In the regime of low density of resources of the random search problem , two limiting situations have been extensively considered [34]: ( i ) non-destructive searches , in which the searcher always departs from a position at the vicinity of the last target found with unrestricted revisits; and ( ii ) destructive searches , in which , once found , the target becomes inaccessible to future visits , so that the starting point of the searcher is , on average , faraway from all targets . In the former case the maximum efficiency is achieved [34] for ( a “compromise” superdiffusive solution ) , whereas in the latter ( ballistic motion ) . It is important to observe , nevertheless , that by varying the searcher's starting point [44] , [48] or the degree of target revisitability or temporal regeneration [50] , [51] , intermediate values of the optimal Lévy exponent arise , . It is also interesting to comment on the effect of an energy cost function on the efficiency of search strategies . Indeed , as reported in [50] , [51] , the range of -values associated with search paths in which the net energy gain ( the balance between the energy income due to the finding of targets and the energy cost of the search process itself ) remains always positive is actually limited . In such a case , low values of giving rise to very large search jumps might not be acceptable , since they imply a high energy cost , with intermediate values of emerging as the best strategy . In addition , we also refer to the study reported in [52] in which exact results for the first passage time and leapover statistics of Lévy flights are presented . In this case , the targets might not be always detected , being thus overshoot by jumps whose length distribution displays infinite variance . Despite the intense progress in the fields of random searches and animal foraging , a number of relevant issues still remain open . A particularly important one is to understand the coupling mechanism between landscape spatiotemporal dynamics and efficient search motility , when resources are scarce and environmental information is limited . In this sense , the pervasiveness of different animal search strategies is expected to strongly depend on a few but essential features of actual landscapes . For instance , targets distributions in realistic search processes usually present heterogeneous properties through time and space , such as diverse degrees of temporal regeneration and spatial aggregation [26] , [53] , [54] . Although the effect of ( global ) resource density on animal foraging behavior is well documented [25] , [26] , [37] , [42] , [55] , much less is known about how spatiotemporal landscape heterogeneity dynamics affects the target revisitability and/or searcher-to-targets distances , both known to be key properties to optimize perception-limited searches [44] , [48] , [50] , [51] . Thus , a mechanistic understanding of how and which landscape features are related to search efficiency should be a relevant step towards a comprehensive view of animal foraging behavior . Here we address the question of how the landscape heterogeneity influences the encounter success and search efficiency under conditions of constant ( global ) density of scarce resources . We develop a random search model in which diverse degrees of inhomogeneities are considered by introducing fluctuations in the starting distances to target sites . We thus ask what happens to the optimal search strategy in an heterogeneous landscape , as the searcher's initial distances to the targets fluctuate along the search . We answer to this query qualitatively for the general case and quantitatively for Lévy random searches in particular , in the constant density regime of scarce resources . In patchy or aggregated landscapes , we find that enhanced diffusivity ( including superdiffusive strategies ) favors the encounter of targets and the success of foraging . Eventually , for strong enough fluctuations in the starting distances to nearby targets a crossover to ballistic strategies might emerge . These predictions are empirically testable through feasible experiments which investigate the dynamics ( e . g . diffusion exponent ) of foraging organisms in specially designed low-density environments of controlled heterogeneity .
We consider a random search model in which diverse degrees of landscape heterogeneity are taken into account by introducing fluctuations in the starting distances to target sites in a one-dimensional ( 1D ) search space , with absorbing boundaries separated by the distance . Every time an encounter occurs the search resets and restarts over again . Thus , the overall search trajectory can be viewed as the concatenated sum of partial paths between consecutive encounters . The targets' positions are fixed – targets are in fact the boundaries of the system . Fluctuations in the starting distances to the targets are introduced by sampling the searcher's departing position after each encounter from a probability density function ( pdf ) of initial positions . Importantly , also implies a distribution of starting ( a ) symmetry conditions regarding the relative distances between the searcher and the boundary targets . This approach allows the typification of landscapes that , on average , depress or boost the presence of nearby targets in the search process . Diverse degrees of landscape heterogeneity can thus be achieved through suitable choices of . For example , a pdf providing a distribution of nearly symmetric conditions can be assigned to a landscape with a high degree of homogeneity in the spatial arrangement of targets . In this sense , the mentioned destructive search represents the fully symmetric limiting situation , with the searcher's starting location always equidistant from all boundary targets . On the other hand , a distribution which generates a set of asymmetric conditions is related to a patchy or aggregated landscape . Indeed , in a patchy landscape it is likely that a search process starts with an asymmetric situation in which the distances to the nearest and farthest targets are very dissimilar . Analogously , the non-destructive search corresponds to the highest asymmetric case , in which at every starting search the distance to the closest ( farthest ) target is minimum ( maximum ) . Finally , a pdf giving rise to an heterogeneous set of initial conditions ( combining symmetric and asymmetric situations ) can be associated with heterogeneous landscapes of structure in between the homogeneous and patchy cases . More specifically , the limiting case corresponding to the mentioned destructive search can be described by the pdf with fully symmetric initial condition , ( 1 ) where denotes Dirac -function . This means that every destructive search starts exactly at half distance from the boundary targets . In this context , it is possible to introduce fluctuations in by considering , e . g . , a Poisson-like pdf [56] exponentially decaying with the distance to the point at the center of the search space , : ( 2 ) where , with the “radius of vision” of the searcher ( see below ) , the normalization constant , and due to the symmetry of the search space . On the other hand , the highest asymmetric non-destructive limiting case is represented by ( 3 ) so that every search starts from the point of minimum distance in which the nearest target is undetectable , . Similarly , fluctuations in regarding this case can be introduced by considering a Poisson-like pdf decreasing with respect to the point : ( 4 ) where , is a normalization constant , and . In Eqs . ( 2 ) and ( 4 ) , the parameter controls the range and magnitude of the fluctuations . Actually , the smaller the value of , the less disperse are the fluctuations around and in Eqs . ( 2 ) and ( 4 ) , respectively . When looking for boundary target sites in a 1D interval , the searcher's step lengths are taken from a general pdf . At each step the probabilities to move to the right or to the left are equal . We define the “radius of vision” as the distance below which a target becomes detectable by the searcher . Thus , if the targets are located at the boundary positions and , the search keeps on as long as the walker's position lies in the range . Here we are interested in searches in environments scarce in targets , i . e . for . In this case , leaving the present position to look randomly for targets should occur much more frequently than simply detecting a site in the close vicinity , a regime favored when targets are plentiful . Suppose initially that , as a target is found , the search always restarts from the same position in the interval . As discussed , the highest asymmetric ( non-destructive ) and fully symmetric ( destructive ) cases correspond respectively to setting ( or , due to symmetry ) and . After the encounter of a statistically large number of targets , the efficiency of the search , , is evaluated [34] as the ratio of the number of sites found to the total distance traversed by the searcher . Since this distance is equal to the product of the number of encounters and the average distance traveled between consecutive findings , , then . Consider now that , instead of always departing from the same location after an encounter , the searcher can restart from any initial position in the range , chosen from a pdf . The fluctuating values of imply a distribution of values . Since searches starting at are statistically indistinguishable from searches starting at ( in both cases the closest and farthest targets are at distances and from the starting location ) , the symmetry of the search space regarding the position implies . The average efficiency thus becomes ( 5 ) where due to the above mentioned symmetry . To study the effect of fluctuations in the starting distances of a searcher , we note that the exact average distance in Eq . ( 5 ) can be formally expressed [57] , [58] as ( 6 ) where the integral operator acts as follows: ( 7 ) and and are , respectively , the unity operator and the average length of a single step starting at . Specifically , we can write for a general pdf ( 8 ) The second and third integrals above represent steps to the left and to the right which are not truncated by the encounter of a target site at the boundaries; the first and last ones concern steps truncated by the detection of the targets at and , respectively ( what actually happens at and , due to the searcher's “radius of vision” ) . Despite the formal aspect of Eq . ( 6 ) , the numerical calculation of with a given can be performed by discretizing [57] , [58] the search interval , i . e . , with integer and . In this procedure , integrals are approximated by summations , and so on . In the next section , we use this model to study the role of landscape heterogeneity on the search efficiency and diffusivity . The presented analysis is qualitative for the general case and quantitative for Lévy random searches .
Consider , first , the limiting case with no fluctuation in the starting distances . The underlying mechanisms of efficient searches with asymmetric and symmetric initial conditions are fundamentally distinct . In the fully symmetric ( destructive ) case the closest sites are located at equal initial distances from the searcher in the low-density regime . Thus , for a general distribution of step lengths characterized by a set of parameters , the one that leads to the largest efficiency must present the fastest possible diffusivity in order to reach these faraway targets . For example , in the case of the single-parameter power-law pdf , is maximized with ballistic strategy [34]: . In contrast , in the highest asymmetric ( non-destructive ) situation or the most efficient search must compromise between performing large steps to access the farthest site and sweeping in detail at the vicinity of the closest site . In the parameter space , this solution , related to a set , displays intermediate diffusivity between normal ( Brownian ) and the fastest possible one , assigned to the set . In the same example , this implies [34] , in contrast with Brownian diffusion resulting from ( see Figs . 1 and 2 ) . When the starting positions are not fixed , heterogeneous landscapes with stronger fluctuations in the distances to nearby targets lead to optimal search strategies with faster dynamics ( enhanced diffusivity ) . The arguments giving rise to this general conclusion are as follows . On one hand , sampling starting positions around corresponds to introduce fluctuations in the initial distances to the faraway boundary targets in the low-density regime , as discussed . In this case , we expect that starting positions far away from are chosen with smaller probabilities . This implies a decreasing pdf from to , such as found in Eq . ( 2 ) . Consequently , both and increase monotonically from to ( Fig . 3 ) . The most relevant contribution to the product in Eq . ( 5 ) thus comes from positions near . No qualitative difference is expected to occur between and , indicating that searches with fully symmetric ( fixed ) initial condition and those comprising fluctuations in the faraway targets present similar optimal dynamics , related to the set , namely ballistic , if supported by . On the other hand , in the asymmetric case fluctuations in the starting distances to the nearby boundary target can be introduced by a decreasing pdf from to , such as in Eq . ( 4 ) . Therefore , as increases and diminishes , the initial position associated with the most relevant contribution to in Eq . ( 5 ) crosses over to somewhere in between and . Indeed , the slower decays , the larger such position becomes . As a consequence , the asymmetric optimal set in the absence of fluctuations might give away the role of the most efficient search strategy to some other intermediate compromising solution , which is closer to the symmetric set in the parameter space and , therefore , presents enhanced dynamics ( e . g . , a larger diffusion exponent ) . Eventually , for some proper choice of encompassing strong fluctuations with large weight near , the justification for such compromising solution might even fade away , so that , with strategies of fastest possible diffusivity becoming optimal . In this uttermost case fluctuations lose their local character , and a crossover from superdiffusive to ballistic search behavior may take place . We observe that the above rationale should also apply , at least qualitatively , to searches in higher-dimensional spaces . In this situation , as the search path can be approximated by a sequence of nearly rectilinear moves , the general qualitative features of 1D random searches usually hold true in higher dimensions [34] , [39] . Nevertheless , the finding of targets in 2D and 3D occurs with considerably lower probability , since the extra spatial directions yield a larger exploration space , resulting in lower encounter rates and search efficiencies . The impact of target spatial fluctuations on high-dimensional search strategies should also reduce [39] . We can thus conclude that , beyond representing the realistic exploration space of some animal species [27] , the 1D analysis presented here is also useful in establishing upper limits for the influence of landscape heterogeneities in random searches . Therefore , the understanding of animal foraging behavior in 2D and 3D , as well as other practical realizations of the random search problem , might also benefit from the present results . We next apply the above arguments , valid for a general pdf , to the particular case of Lévy random searchers . We now specifically consider a random searcher with step lengths chosen from the pdf ( 9 ) and otherwise , with representing a lower cutoff length . We assign a “negative step length” if the searcher moves to the left and take for simplicity . Equation ( 9 ) for corresponds to the long-range asymptotical limit of Lévy -stable distributions with index , characterized by the existence of rare , large steps alternating between sequences of many short-length jumps [13] , [14] , [16] . As its second moment diverges the central limit theorem does not hold , and anomalous ( superdiffusive ) dynamics governed by the generalized central limit theorem takes place . Indeed , Lévy random walks and flights are related to a Hurst exponent [13] , [14] , with ballistic dynamics in the case , whereas diffusive behavior ( ) emerges for . For pdf ( 9 ) is not normalizable and corresponds to the Cauchy distribution . The search path eventually comprises truncated steps due to the encounter of targets , so that the power-law decay of Eq . ( 9 ) cannot extend all the way to infinity , thus implying an effective truncated Lévy distribution [59] . In spite of this , in the regime the search should retain the most relevant properties of a non-truncated Lévy walk to a considerable extent . Indeed , the ratio of the number of truncated steps to the non-truncated ones , essentially equal to the inverse of the average number of steps performed between consecutive targets , is given by and , for , in the highest asymmetric ( non-destructive ) and fully symmetric ( destructive ) cases , respectively [34] , [57] , [58] . Thus , except for ballistic walks , one has that if . Further , the justification for truncated distributions also arises naturally in the context of animal foraging since directional persistence due to scanning is likely to be broken at the finding of targets [19] . Indeed , infinitely long rectilinear paths are not allowed for searching organisms . By inserting Eq . ( 9 ) into Eqs . ( 6 ) and ( 7 ) , we numerically calculate through the discretization of the search space ( see previous section ) . Results are displayed in solid lines in Fig . 3 . Notice first the presence of the symmetry discussed above . In the absence of fluctuations in the initial distances , the existence of a maximum efficiency with an intermediate exponent ( see Fig . 2 ) for searches starting at fixed ( highest asymmetric condition ) can be understood as follows: strategies with might access the farthest target at in a ballistic way after a small number of very large steps , implying a large and low efficiency; in contrast , searches with tend on average to find the closest site at after a great number of small steps , also giving rise to a large ; the efficient compromise between these two trends , leading to the lowest and maximum , is therefore represented by a strategy with an intermediate value , . In the presence of fluctuations in the starting distances , the integral ( 5 ) must be evaluated . Although the explicit expression for , Eq . ( 6 ) , is not known up to the present , a multiple regression can be successfully performed , ( 10 ) as indicated by the nice adjustment shown in Fig . 3 , obtained with and . Thus , the integral ( 5 ) can be done using Eqs . ( 2 ) , ( 4 ) and ( 10 ) , with results displayed in Figs . 1 and 2 for several values of the parameter . By considering fluctuations in the starting distances to faraway targets through Eq . ( 2 ) , we notice in Fig . 1 that the efficiency is qualitatively similar to that of the fully symmetric condition , Eq . ( 1 ) , in agreement with the general arguments of the previous section . Indeed , in both cases the maximum efficiency is achieved as . For the presence of fluctuations only slightly improve the efficiency . These results indicate that ballistic strategies remain robust to fluctuations in the distribution of faraway targets . On the other hand , fluctuations in the starting distances to nearby targets , Eq . ( 4 ) , are shown in Fig . 2 to decrease considerably the search efficiency , in comparison to the highest asymmetric case , Eq . ( 3 ) . In this regime , since stronger fluctuations increase the weight of starting positions far from the target at , the compromising optimal Lévy strategy displays enhanced superdiffusion , observed in the location of the maximum efficiency in Fig . 2 , which shifts from , for the delta pdf and Eq . ( 4 ) with small , towards , for larger ( slower decaying ) . Indeed , both the pdf of Eq . ( 4 ) with a vanishing and Eq . ( 3 ) are very acute at . It is also worth noticing that a lower is related to a larger Hurst exponent [1] , [13] , [14] , and therefore to a larger diffusion exponent , as argued in the previous section . As even larger values of are considered , fluctuations in the starting distances to the nearby target become non-local , and Eq . ( 4 ) approaches the limiting case of the uniform distribution , ( see Fig . 2 ) . In this situation , search paths departing from distinct are equally weighted in Eq . ( 5 ) , so that the dominant contribution to the integral ( and to the average efficiency as well ) comes from search walks starting at positions near . Since for these walks the most efficient strategy is ballistic , a crossover from superdiffusive to ballistic optimal searches emerges , induced by such strong fluctuations . Consequently , the efficiency curves for very large ( Fig . 2 ) are remarkably similar to that of the fully symmetric case ( Fig . 1 ) . We can quantify this crossover shift in by defining a function that identifies the location in the -axis of the maximum in the efficiency , for each curve in Fig . 2 with fixed . As discussed , eventually a compromising solution with cannot be achieved , and an efficiency function monotonically decreasing with increasing arises for . In this sense , the value for which such crossover occurs marks the onset of a regime dominated by ballistic optimal search strategies . The value of for each can be determined from the condition , so that , by considering Eqs . ( 4 ) , ( 5 ) and ( 10 ) , ( 11 ) with . Solutions are displayed in Fig . 4 and also in Fig . 2 as empty symbols , locating the maximum of each efficiency curve . In addition , the crossover value can be determined through . In the case of pdf ( 4 ) , we obtain ( Fig . 4 ) for and ( regime ) . We also note that the scale-dependent interplay between the target density and the range of fluctuations implies a value of which is a function of . For instance , a larger ( i . e . , a lower target density ) leads to a larger and a broader regime in which superdiffusive Lévy searchers are optimal . Nevertheless , the above qualitative picture should still hold as long as low target densities are considered . Moreover , since ballistic strategies lose efficiency in higher dimensional spaces [44] , it might be possible that in 2D and 3D the crossover to ballistic dynamics becomes considerably limited . In spite of this , enhanced superdiffusive searches , with , should still conceivably emerge due to fluctuations in higher-dimensional heterogeneous landscapes . From these results we conclude that , in the presence of Poissonian-distributed fluctuating starting distances with , Lévy search strategies with faster ( enhanced ) superdiffusive properties , i . e . , represent optimal compromising solutions . In this sense , as local fluctuations in nearby targets give rise to landscape heterogeneity , Lévy searches with enhanced superdiffusive dynamics actually maximize the search efficiency in aggregate and patchy environments . On the other hand , for strong enough fluctuations with , a crossover to the ballistic strategy emerges in order to access efficiently the faraway region where targets are distributed . These findings are in full agreement with the general considerations discussed in the previous section . At last , to further test the robustness of these results we have also considered the power-law distribution of starting positions , , with , , and as the normalization constant . Differently from distributions ( 2 ) and ( 4 ) , the long tail in this pdf confers self-affine scale-invariant properties over a long spatial range in the low-density regime , . The evidence of scale-free distributions of targets has been reported in the context of animal foraging , e . g . in [24] . In the present analysis we have essentially verified all the general features previously discussed . In particular , all strategies with are ballistic , with compromising superdiffusive solutions arising for .
The effect of limited resources on animal motility is well documented in ecology . Scarcity coming from resource competition is known to induce higher dispersal rates [60] , [61] and larger home ranges [62] , [63] . Habitat fragmentation also reshapes dispersal kernels , often increasing dispersal distances [64] . In the context of foraging behavior , the role of ( global ) resource density has been considerably investigated , with strong evidence pointing to shifts from Brownian to superdiffusive search strategies as animals move from high to low productive areas . Examples range from microorganisms [37] to large marine predators [25] , [26] , [55] . In contrast , much less is known about the influence of heterogeneity in the resource distribution on the foraging success . Most theoretical efforts relying on core random search theory have by far provided only a limited approach to the issue of optimal searches , since they mostly assume oversimplified landscapes [2] , [40] . Nonetheless , a few simulation studies have addressed the effect of environmental heterogeneity , including target motion , on encounter success for different searcher types [19] , [24] , [39] , [65] , [66] . These works give support to the hypothesis that search processes are linked to target distributions and dynamics , thus agreeing with our results in that the optimal strategy can actually change , e . g . from superdiffusive to ballistic motion , depending on the landscape heterogeneity . In a more recent example , it was shown [65] that Lévy optimal foragers can be evolutionarily optimal in heterogeneous environments , for suitable details of the simulations and definition of efficiency . Our work advances on this topic by pinpointing a very general mechanism which seems essential to understand previous simulation results [19] , [24] , [39] , [65] . By comprehensively describing the key mechanism coupling landscape dynamics and search diffusivity , we have shown that statistical fluctuations in the set of initial search conditions play a crucial role for determining which strategy is optimal . The presence of such fluctuations sets a clear basis for the non-universality of search patterns , and shows that enhanced diffusivity ( including superdiffuse strategies ) favors random encounter success in patchy and aggregated landscapes . As a consequence , the foraging conditions in which Lévy strategies appear as optimal are much broader than previously suggested [40] , [44]–[46] . In dynamic and complex landscapes with scarcity of resources neither ballistic nor Lévy strategies should be considered as universal ( see , e . g . , [45] , [46] ) , since realistic fluctuations in the targets distribution may induce switches between these two regimes . This observation has been confirmed by recent empirical results [25] , [27] , showing that foragers in the wild do not exhibit movement patterns that can be approximated , at all times , by Lévy , ballistic or exponential models . Nevertheless , the relevant finding is that in the low-density regime superdiffusive Lévy strategies remain as the optimal solution in a broad range of heterogeneous landscape conditions , with the optimal exponent dependent on specific environment properties . Crossovers between superdiffusive and ballistic strategies may also emerge depending on whether strong target spatial fluctuations are local or not , and if they depress or boost the presence of nearby targets . For instance , recent data on a species of jellyfish have reported [27] on Lévy flight foraging strategies with optimal index as low as . Moreover , studies on marine predators have also found [24] small values as . Such rather fast , enhanced superdiffusion ( with respect to ) suggests the occurrence of foraging activity in a highly dynamic and heterogeneous landscape , as it is clearly the case for marine prey landscapes [25] , [26] , [67] . In the present work , the question of how the landscape heterogeneity affects the search efficiency in encounter interactions is addressed under conditions of constant global density of scarce resources . In such conditions we predict that efficient strategies with larger diffusion exponents ( including superdiffusive ones ) should arise , as heterogeneous environments with wider distributions of starting distances between the foraging organism and the nearby targets are considered . Similarly to what occurs in homogeneous landscapes [42] , we do not expect density fluctuations in the scarcity regime to modify optimal Lévy solutions per se , but only to the extent that fluctuations in density modify the initial searcher-to-targets distances . In other words , provided that the asymmetry in the searcher-to-targets distances is maintained as density changes , optimal Lévy strategies should result insensitive to target density fluctuations . This means that for a Lévy searcher is less important to have advanced knowledge of the density than of the relative positions of the targets . Clearly , robustness to changes in environmental parameters ( i . e . density ) should be considered as an advantage in non-informed optimal search solutions [42] . If we acknowledge the presence of selective pressures responsible for the evolution and maintenance of non-oriented motility in organisms [68] , our results lead to a neat empirically testable prediction: patchy and heterogeneous landscapes should promote the emergence of enhanced diffusivity and compromising optimal Lévy strategies . Even though the empirical inference of large scale movement patterns from heterogeneity properties of the landscape is a difficult task [26] , specifically designed and controlled large scale experiments are feasible in the laboratory [68]–[71] and even in the field [54] . We hope the present study might shed light on unsettled issues related to the efficiency and associated dynamics of organisms performing random searches . Besides the well documented dependence of search efficiency on resource density [25] , [26] , [34] , [37] , [55] , our results suggest another relevant aspect of non-universal random search behavior: landscape heterogeneity frames optimal diffusivity . | Understanding how animals search for food is crucial for animal ecology . Although much has been learned about the main aspects of the so-called foraging problem , some important questions still remain unanswered . In this work we address the issue of the relevance of heterogeneity in the resources distribution to efficient animal foraging behavior . Our results unveil the key mechanism coupling landscape heterogeneity dynamics with optimal search diffusivity . Indeed , although the effect of ( global ) resource density on animal foraging behavior is well documented , much less has been known about how spatiotemporal landscape heterogeneity affects the efficiency of encounter interactions by foraging organisms . In this sense , we propose a new empirically testable theoretical prediction on the dynamics ( e . g . diffusion exponent ) of foraging organisms in heterogeneous environments . We also show that the conditions in which Lévy strategies are optimal are much broader than previously considered . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [
"theoretical",
"biology",
"biology"
] | 2011 | How Landscape Heterogeneity Frames Optimal Diffusivity in Searching Processes |
Identifying the source of transmission using pathogen genetic data is complicated by numerous biological , immunological , and behavioral factors . A large source of error arises when there is incomplete or sparse sampling of cases . Unsampled cases may act as either a common source of infection or as an intermediary in a transmission chain for hosts infected with genetically similar pathogens . It is difficult to quantify the probability of common source or intermediate transmission events , which has made it difficult to develop statistical tests to either confirm or deny putative transmission pairs with genetic data . We present a method to incorporate additional information about an infectious disease epidemic , such as incidence and prevalence of infection over time , to inform estimates of the probability that one sampled host is the direct source of infection of another host in a pathogen gene genealogy . These methods enable forensic applications , such as source-case attribution , for infectious disease epidemics with incomplete sampling , which is usually the case for high-morbidity community-acquired pathogens like HIV , Influenza and Dengue virus . These methods also enable epidemiological applications such as the identification of factors that increase the risk of transmission . We demonstrate these methods in the context of the HIV epidemic in Detroit , Michigan , and we evaluate the suitability of current sequence databases for forensic and epidemiological investigations . We find that currently available sequences collected for drug resistance testing of HIV are unlikely to be useful in most forensic investigations , but are useful for identifying transmission risk factors .
Phylogenetic trees reconstructed from sequences of pathogens contain information on the past transmission dynamics that would be difficult , if not impossible , to obtain through other means . Over the past two decades , a number of approaches have been proposed to extract epidemiologically relevant information from viral phylogenies , particularly from highly variable RNA viruses such as HIV-1 , hepatitis C virus , and influenza A virus [1] . With the advent of high-throughput sequencing , these approaches can also be applied to help understand bacterial spread [2] . Although many studies have focused on the ‘phylodynamics’ [3] , [4] of infectious disease transmission at the population level , there have been a number of studies that have focused more on the ability of molecular sequence data to inform transmission at the level of pairs or small groups of individuals . Molecular epidemiological analysis of couples with discordant HIV status have demonstrated that infection of the initially uninfected partner may often be from a third party [5] . Sequence data have also been used in a forensic setting [6] , [7] , most famously in the Florida dentist case [8] . Identifying the source of infection from genetic data is known to be confounded by many sources of error . The similarity of pathogen sequence data collected from a transmission pair depends , among other factors , on the time since transmission , immunological pressure on the pathogen , the substitution rate of the pathogen within host , and how the substitution rate changes over time within hosts . Provided a realistic model of how pathogen sequences diverge over time , it is possible to calculate the probability that the consensus sequence in a recipient of infection diverged in a given span of time from a putative source of infection [9]–[11] . Recently , there has been rapid development of methods to identify transmission sources under the assumption of complete sampling , i . e . under the assumption that every infected individual is represented in the phylogeny . These methods have yielded many valuable insights into the spread of nosocomial infections [12] , Mycobacterium tuberculosis [13] , foot-and-mouth disease virus , and avian influenza between farms [14] . Nevertheless , for many human pathogens , incomplete sampling is the rule . In the case of HIV , sequencing of the pol gene is now routine in many countries for surveillance of drug resistance , but even so , sample coverage is far from complete . Figure 1 illustrates errors that can be introduced by incomplete sampling . For example , it is possible that two hosts with genetically similar virus were both infected by a common source who was not sampled . Therefore , calculation of the probability that i infected j should account for the possibility that an unobserved individual k infected both i and j ( second panel ) . Similarly , it is possible that i infected an unsampled individual k who went on to infect j . Due to the uncertainty stemming from incomplete sampling , viral sequence data have often been used as a test to disconfirm a putative transmission pair . For example , in the context of HIV , a phylogeny estimated from a pair of sequences in a putative transmission pair , along with a set of sequences from a suitable background population ( e . g . infected individuals with a matching geographic and risk-behavior profile ) , can be used to detect if the putative donor is relatively distant in evolutionary terms from the recipient [15] . If the putative donor is not monophyletic with the recipient , it is less likely that the putative donor is the true source of infection . However , even if the donor and recipient sequences are not monophyletic , there are scenarios where the putative transmission pair is genuine . For example , it is possible that the putative donor is a common source of infection for all sampled cases in the donor-recipient clade . This is illustrated in Figure 1 , in which donor i infects both j and k , yielding a polyphylous relationship between i and j . As it is impossible to rule out the possibility that an unsampled individual or unobserved chain of transmissions connects a putative donor and recipient , it has been impossible to properly define the statistical power of tests for confirming or disconfirming transmission pairs from phylogenetic data . Due to the problems involved in incomplete sampling , relatively little work has been performed to identify potential sources of infection - i . e . understanding transmission at an individual level - using population-level datasets collected for clinical or surveillance purposes . A notable exception is a study of HIV-positive men who have sex with men ( MSM ) in Brighton , UK [16] , which , through a combination of diagnosis times and sequence data , attempted to identify the source of transmission for 159 cases of recent HIV infection . A single most likely transmission source was inferred in only 41 ( 26% ) cases , and the potential for a transmission source outside of the study population was not quantified . Nevertheless , biologically plausible associations between younger age , higher viral load , recent HIV infection , and a recent sexually transmitted infection were found with the probability of being identified as a source of infection . In the case of incomplete sampling , calculating the probability that a putative transmission pair is real is equivalent to calculating the probability that there are zero unsampled intermediaries between the pair in the viral phylogeny . Calculating this probability is complex , but possible , provided a realistic model of the epidemic process and given good data about incidence and prevalence of infection . This paper is concerned with calculating the probability , henceforth called the infector probability , that a given host is the source of infection for another host from phylogenetic and epidemiological surveillance data . The main contribution of this manuscript is the development of a theoretical framework which realistically accounts for the epidemiological and sampling process , thereby correcting for error due to incomplete sampling . This theory also allows for the possibility that the infected population is heterogeneous , such that some individuals have a higher intrinsic infectiousness than others . This is accomplished by the incorporation of patient-level covariates ( behavior , stage of infection etc . ) into the calculation of infector probabilities . To demonstrate the utility of infector probabilities to the analysis of real epidemic data , we have simulated a dataset based on the real HIV epidemic among MSM in Detroit , Michigan . Through a simulation-based analysis , we use our solution of the infector probabilities to address the following questions:
To give intuition for the method , we first illustrate a simple example of an epidemic within a homogeneous population . The variable s will denote time on a reverse axis ( time before the last sample is taken ) , while t will represent time on a forward axis ( time since some point in the past ) . We calculate the probability that host i infected host j under the conditions that sampling occurs at a single timepoint , and that there is a single type of infected host . We assume that i and j form a ‘cherry’ ( a clade of size 2 ) , and that both the population and sample sizes are sufficiently large such that we can approximate the dynamics of the number of infected individuals in the population , , and the number of lineages in the sample , , using differential equations . At time , we have lineages equal to the number of hosts sampled . All of these assumptions will be relaxed in subsequent sections . What is the probability that i transmitted to j at their most recent common ancestor , which occurs at time ? A necessary condition for this to occur is that the viral lineage at corresponds to virus circulating in host i . This condition will not be satisfied if an unsampled individual k transmits to i before ( retrospectively ) , in which case will correspond to a transmission event involving k . The rate at which an unsampled host k infects i at time s , is ( 1 ) This can be understood as the product of a rate and two probabilities: When an unsampled individual k transmits to i , the viral lineage “jumps” to k ( recalling that we are considering time from the present to the past ) . We can therefore count the number of unique infected individuals along the branch that begins at i and terminates at . We will denote this random variable , which is given by the following expression: ( 2 ) Note that one is added to account for the host i itself . We can also calculate the probability of there being no jumps . ( 3 ) For i to transmit to j , we must have and . This occurs with probability . Finally , as infected individuals are homogeneous and sampled at the same time , the probability that i transmits to j as opposed to j transmitting to i is 1/2 . Hence , the probability that i infected j at time is ( 4 ) where W denotes the matrix of infector probabilities . To demonstrate how sampling plays a central role in determining the extent to which cherries represent direct transmissions , we will consider a large sample size , such that we can model the number of cherries as well as the number of cherries that correspond to direct transmissions as ordinary differential equations . Previously [20] , we have shown that the cumulative number of cherries in a tree at height s , can be written in terms of the rate of coalescence between the leaves of a tree . Let be the number of extant terminal branches of the tree at retrospective time s ( that is , uncoalesced lineages ) . We have ( 5 ) These equations may be understood as the product of a rate ( ) and two probabilities which describe the combination of two lineages at a coalescent event . For example , with probability , a terminal branch will be involved in a transmission event , and with probability an ancestral lineage will also be involved in the transmission event such that a coalescent will occur . With probability , two terminal branches will be involved in a transmission event , and a cherry will form . The total number of cherries in a tree can be calculated by solving for at , the time of the most recent common ancestor of the sampled sequences . To determine the number of cherries that represent direct transmission , , we first derive an equation for the number of leaves of a tree along which no transmissions from an unsampled individual have occurred , , which decreases as a consequence of transmission from others in the sample ( as for ) as well as transmission from unsampled individuals: ( 6 ) These equations are derived as above , but include an additional hazard for an unsampled host transmitting to one of the external lineages . Some analytical insights into how different parameters affect the proportion of cherries that are associated with direct transmission can be obtained under the assumption that the number of infected hosts , Y , and the incidence of infection , f , are constant , i . e . when the system is at equilibrium , and we drop the time index for these variables . If we define the constant , then following [20] , the number of lineages over time , which is a deterministic approximation to the rate of coalescence in a coalescent model of fixed size , and the time to the most recent common ancestor , which is obtained by the solution of . We substitute this expression for and into the equation for to give the following . ( 7 ) This can be solved using separation of variables , with the constant of integration calculating by the initial condition . ( 8 ) Substituting this solution of into the differential equation for gives the following . ( 9 ) Solving the above for is made more simple using integration by substitution with ( i . e . changing the timescale ) , such that , and . ( 10 ) The solution for , the total number of cherries that represent direct transmission , is found by integrating from to ( for ) . The term is a constant , and integration of results in an exponential integral term , , where is the upper incomplete gamma function . ( 11 ) The approximation is for large Y , such that . Similarly , at equilibrium we can substitute and into equation 3 , which yields . If we know the height of the cherry , , then at equilibrium , the probability that i and j are a transmission pair is approximately ( 12 ) These results demonstrate that at equilibrium , the fraction of sequences in cherries is independent of sampling fraction ( ) , while the proportion of sequences in cherries that represent a direct transmission is a function of the ratio of the number of infected in the population to the number of infected in the sample . Note that even when , i . e . all individuals have been sampled , not all cherries represent direct transmissions ( ) . In addition , for more realistic sample fractions , the number of cherries that represent direct transmissions is extremely low; for example , if , then . The very simple expressions in equation 4 and 12 are obtained after applying numerous simplifying assumptions: i and j are sampled at the same time , i and j are monophyletic , and the epidemic is at equilibrium ( Y and f are constant ) . In the next section , we proceed to relax all of these assumptions . Nevertheless , equation 4 may be a good approximation in some situations when is close to the time of sampling and if incidence and prevalence is relatively constant between and the time of sampling . The solutions described below are applicable to a large class of infectious disease process models which describe the incidence and prevalence of infection over time . The host population is not assumed to be homogeneous , but can have arbitrary discrete structure . Each infected host can occupy any of m states ( a compartmental model ) , and an infected host cannot transmit to more than one susceptible at a single point in time . The discrete states that a host may occupy will be indexed by variables k and l . Under these conditions , the model can be decomposed into the following processes ( see [17] for details ) : The process model will be denoted by the tuple . An explicit example of decomposition of a model into is given for an HIV model below . In [17] , master-equations were developed for computing many attributes of conditional on , such as the likelihood . This approach can , for example , be used to fit models to phylogenetic data . A similar approach is taken here , and we will re-use notation where possible . The primary aim is to derive , the probability that a host i directly transmitted infection to host j based on phylogenetic data ( ) . The master equations will describe the dynamics on a reverse time axis . In common with other coalescent models , our solutions will work by integration from the present to the past along the reverse time axis s . The variables and will denote the times of sampling of host i , and the initial conditions will be based on the states of hosts at these times . The coalescent model described here is complex , so a visual aid is provided in Figure 2 . A useful way to conceptualize the organization of this model is to visualize every branch in as having a set of dynamic variables associated with it for every tip of the tree descended from it . Every node will have associated with it the probabilities for every pair of sampled hosts descended from it . At some point in the past , every sampled host i has an ancestral host; in other words , the ancestral host harbors virus which is ancestral to the virus that is sampled from host i at . We will denote the ancestral host of i as . Note that we may have if i became infected at a retrospective time , in which case the ancestral branch of i in at time s corresponds to the host i itself . The variable will denote the probability of this event . will denote the time of most recent common ancestry for virus sampled from hosts i and j . will denote the probability that is in state k . The master equations describing evolution of were derived in [17] . Here , we introduce a similar variable , which is the probability that is in state k conditional on . Derivations of and are provided in subsequent sections . Here , we show how is calculated when and are known . Consider the node in corresponding to the MRCA of i and j at time . In order for i to transmit to j , we must have and , i . e . both daughter lineages of the node correspond to hosts i and j . The probability of this event is , since events are assumed to be independent . That is a good approximation when Y is large . At , the states of host i and j are described by the vectors and . Suppose that at a type k host transmits to a type l host , which occurs at rate . The probability that host i is the transmitter conditional on is , i . e . the probability that i is selected from the infections of type k and the probability that i is type k . Similarly , the probability that j is the recipient of infection conditional on is , i . e . the probability that j is selected from infections of type l and the probability that j is type l . Considering all possible types of transmission k and l , the rate that i transmits to j is as follows . ( 13 ) This can be written with greater economy using matrix notation . ( 14 ) where is an vector with elements . Similarly , the rate that j transmits to i is as follows . ( 15 ) If both daughter lines correspond to i and j , a transmission must have taken place between them . The probability is obtained by taking the ratio of the rate that i transmits to j to the rate that transmission occurs in either direction . ( 16 ) ( 17 ) The function describes the probability that the ancestral host of the sampled host i is in state k at retrospective time s . Equations for the dynamics of are derived in [17] . Here , we derive similar equations for , which describes the probability that the ancestral host of i is type k at time s conditional on i being the ancestral host; in other words , the branch in that is ancestral to i at time s corresponds to the host i itself ( ) . It is assumed that at each time of sampling we know the state of i; this information provides the initial conditions for the set of equations that describes the dynamics of . Suppose that at retrospective time , and i is in state k . In a small time step h , approximately infected hosts will migrate from state l to state k . Then retrospectively , the probability that host i will change state from k to l is approximately , where the factor of is the probability of selecting i if drawing a single individual from infected hosts . Considering the limit , this leads to the following equations . ( 18 ) In matrix notation , the derivative of the vector can be expressed as ( 19 ) where B is a m×m matrix with elements: ( 20 ) Suppose that at a time , there is a node in at the branch that is ancestral to i . At a node , undergoes a discrete change as we incorporate information about the state of the other daughter branch at the node . Let and represent the two state vectors for two daughter branches of the node at the MRCA of i and j , which occurs at retrospective time . Note that we will use the state vector for the ancestral host of j , since we are not conditioning on the event that j corresponds to a daughter branch at . Under the assumptions of this model , a transmission event occurs at this node , either from to or vice versa . The discrete change at will occur after an infinitesimal time . In order for the event to occur , i must be the transmitter at the node . Hence , the probability is simply the probability that the transmission is made by a type k conditional on i being the transmitter . This is ( 21 ) is the probability that . Equations governing are found by considering the hazard of an ‘invisible transmission event’ [20] , [21] , which changes the ancestral host of a branch in the phylogeny without producing a coalescent event . Equations for ψi will have a continuous component for branches and a discrete component for nodes . Suppose that at retrospective time s , and i is in state k . will denote the number of ancestors of the sample at retrospective time s that are in state k . Following the approach taken in [17] , the rate that a transmission leads to a change of isThis is the product of the rate of transmissions , the probability 1/Yk that i is selected as the recipient of transmission , and the expression , which is the probability that the transmitter is not ancestral to the sample ( i . e . that no branch in the tree corresponds to the transmitting host ) . This motivates the following equation for the derivative of ψi: ( 22 ) At an ancestral node of i , ψi undergoes a discrete change by a factor which is simply the probability of i being the host that transmitted at the node: ( 23 ) Software for calculating Wij as described in this paper is available at http://code . google . com/p/colgem/ . We simulated HIV gene genealogies using an individual-based stochastic simulation based on the epidemic model presented in [19] . These simulations were carried out with the objective of replicating a real HIV dataset as closely as possible , while allowing us to know who infected whom . Sample sizes , the times of sampling , and incidence of infection were all chosen to coincide as closely as possible to the dataset of HIV sequences described in [19] , which was based on 662 HIV-1 sequences sampled from men MSM in the Detroit metropolitan area . Simulated sequences and estimated phylogenies were also chosen to mimic the diversity expected for a sample of subtype B sequences . To capture heterogeneity in simulated outcomes , 20 independent simulations were undertaken . The HIV model is illustrated in Figure 3 . The model in [19] was fitted to a combination of surveillance timeseries data , such as HIV/AIDS diagnoses over time and HIV genetic sequences . This provided an estimate of incidence and prevalence over time as well as estimate of the number of transmissions made by infected individuals in different stages of infection . Parameter estimates in the simulations were taken from the maximum likelihood model fit in [19] . In this model , infected individuals progress through five stages of infection and can be undiagnosed or diagnosed . Diagnosed individuals may additionally receive antiretroviral therapy ( ART ) which reduces the rate of progression towards AIDS and death . We assume that ART is available after 1998 to all diagnosed individuals . Chronic infections transmit at rate 87 . 5% smaller than the transmission rate of early HIV infection ( EHI ) , and there are no transmissions from AIDS cases oweing to effective diagnosis and treatment . In this model , the first stage of infection , EHI , lasts year , three chronic stages last years on average each , and AIDS lasts years on average . The total infectious period may be much longer with treatment , which is largely determined by natural mortality , which occurs at the rate m ( t ) of 1 per 27 years . An essential aspect of this model is how incidence f ( t ) and diagnosis rates μ ( t ) vary over time . In this model , both of these rates are described by spline functions , and we re-use the parameters of the spline functions estimated in [19] . In the discrete individual-based simulations , the time to the next transmission event is exponentially distributed with rate f ( t ) . We make the approximation that f ( t ) is constant between transmission events , which is a good approximation since the time between transmissions in the population is quite short relative to the change in f ( t ) . At each transmission event , the transmitting individual is selected randomly from the set of all infected individuals with a weight that depends on the stage of infection of the individual and whether they are diagnosed . For example , someone with undiagnosed chronic infection will transmit at a rate less than an undiagnosed EHI by a factor of as described above , and a diagnosed chronic infection ( pre-treatment ) will transmit at a rate less than an undiagnosed EHI by a factor of . Similarly , the time to the next diagnosis event is exponentially distributed with rate μ ( t ) , and the newly diagnosed individual is selected uniformly at random from the set of all undiagnosed infections . Note that the the simulation may be put in the canonical form described above , which allows simulations to be used to calculate infector probabilities . In this case , m = 10 ( infected may occupy 5 stages and be diagnosed/undiagnosed ) , and Y ( t ) is an vector that describes how many infected are in each state at time t . gives the transmission rate from state k to l at time t , so for example , if k corresponds to undiagnosed chronic infection , and l corresponds to undiagnosed EHI , , where is the relative infectiousness of chronic infections . represents the rate that type k changes state to type l; in this model , this process corresponds to stage progression and diagnosis . For example , if k corresponds to undiagnosed EHI and l corresponds to the first chronic stage , then . To reconstruct a gene genealogy from the simulation , we iteratively build a binary tree by adding a new branch at each transmission . The logic underlying tree reconstruction is given in [21]–[23] . Briefly , if an individual z transmits at time t , we add a new branch to the tree which connects a new node u with an old node v . Each node in the tree has a time associated with it . The time of u is the time of the new transmission event t . The node v that is connected to u corresponds to the last transmission event that involved host z . That event may be another event in which z transmitted , or it may correspond to the event where z became infected . All of the internal branch lengths in the tree therefore correspond to the time between consecutive transmission events . In reality , we do not observe the complete transmission genealogy , but rather a small subsample . To model sampling , we randomly sampled n = 662 branches heterochronously at regular intervals between the 29th and 37th year of the epidemic . At each sampling time , we introduce a terminal node into the tree with a corresponding time of sampling . The sample size and sample window were chosen to mimic the real dataset in [19] . Unsampled branches are then pruned from the tree , which yields a final binary tree with n terminals and internal branches . As noted above , the calculation of in heterochronous samples does not account for the possibility that a sampled lineage is a direct descendent of a previously sampled ancestral lineage . Nevertheless , we allow this event to occur in simulations in order to evaluate if violation of this assumption is a large source of bias . To simulate genetic sequence alignments corresponding to the simulated genealogical relationships described in the previous section , we used the program Seq-Gen v . 1 . 3 . 3 [24] . For each simulated tree , we generated a sequence alignment of 662 sequences , each 1200 nucleotides in length . We used an HKY nucleotide substitution model with a transition-transversion ratio of 4 . 73 , and rate heterogeneity modeled as a mixture of invariant sites ( 47% ) , a mean substitution rate of 1 . 6e-03 per site per year , and a Γ distribution discretized into four categories with a shape parameter of 0 . 714 . These parameters were obtained by a previous phylogenetic analysis of real HIV data [25] . For each sequence alignment , we used relaxed-clock Bayesian methods [26] as implemented in the software BEAST [27] to estimate a posterior distribution of phylogenetic trees . We assumed a GTR substitution model , with rate variation modeled as a mixture of invariant sites and four-category discretized Γ distribution . We used the semi-parametric skyride method [28] to estimate how the effective population size changes through time . Parameters were estimated using a Markov Chain Monte Carlo algorithm which was run for 50 million iterations . We discarded the first 50% of samples as burn-in . To generate estimated infector probabilities from the posterior distribution , we calculated for a sample of 50 trees and report the mean . We also compare between samples from the BEAST posterior to investigate uncertainty in oweing to uncertainty in the underlying phylogeny . Results for the HIV model presented below which are based on a true transmission genealogy utilize 20 independent simulations . Results that utilize simulated sequences are based on only a single simulation , but utilize 50 posterior sampled trees . Text S1 and figures S1 , S2 , S3 describes several additional simulation experiments to validate the numerical accuracy of the approach . These simulations were undertaken using idealized compartmental SIRS models with homochronous samples . The time of sampling ( peak prevalence of endemic equilibrium ) was investigated . DefineIn the absence of bias , the expected residual should be zero where the expectation is taken across all pairs in all simulations . A t-test was performed to test the hypothesis that . Code for all simulation experiments can be found at https://code . google . com/p/inferring-the-source-of-transmission-with-phylogenetic-data/ .
To validate the numerical accuracy of our derivation of , we present additional simulations in Text S1 . In these emperiments , more simulations are carried out and more transmissions are observed so that estimated infector probabilities can be compared with a large sample of transmission events . In all , 1158 SIRS epidemics were simulated , 59194 potential transmission pairs were evaluated , yeilding 3168 within-sample transmission pairs . A sample of 5% of infections was taken at peak prevalence and endemic equilibrium . Bias was not detected for either sampling time ( t-test ) .
We have presented a method for calculating the probability that one host infected another ( the infector probability ) in a pathogen phylogeny . This method makes use of extra epidemiological information , such as the incidence and prevalence of infection over time . The method thereby accounts for the possibility that unsampled infected individuals act as either intermediaries or as a common source of infection for a putative donor and recipient of infection . Any infectious disease model that is used to estimate incidence and prevalence of infection implies a relationship between pathogen gene genealogies and infector probabilities . This is the first method which makes the connection between infector probabilities , infectious disease models , and pathogen genealogies explicit . The practical importance of this method is that it enables the estimation of infector probabilities in situations where there is incomplete sampling , which is more often than not the case for high-prevalence community-acquired pathogens like HIV . Once is calculated , a variety of auxiliary analyses are enabled . The column sum is equivalent to the probability that the infector of j is in the sample . This statistic will be sensitive to the number of patients sampled and the times of sampling . The row sum is equivalent to the expected number of secondary infections for case i which also appear in the sample . Variation of this statistic can be examined with respect to covariates that may influence transmission rates . Such investigations may indicate which clinical , demographic , and behavioral variables have a large impact on transmission rates and thereby guide further model development . We have also demonstrated the method using a simulated HIV dataset in which we know who actually infected whom . The dataset was designed to mimic a real HIV dataset , both in terms how patients are sampled and in the epidemiology of infection in the simulated community; phylogenies were estimated from simulated sequences in order to realistically reproduce phylogenetic error . The method is subject to bias due to finite population size and violation of model assumptions . Nevertheless , we have not detected substantial bias in realistic simulation experiments , which suggests that bias will be quite small for applications provided an appropriate epidemiological model is used . Figure 4 shows that accuracy is not greatly impacted by phylogenetic uncertainty stemming from the simulated sequences in this application . Although there is very high variation in estimated infector probabilities between individual trees in the Bayesian-phylogenetic posterior distribution , the infector probability averaged over a sample of phylogenies has similar performance to infector probabilities calculated from the true tree . As Figure 5 shows , infector probabilities calculated from the true tree are highly correlated with estimated phylogenies , but on an individual basis , there can be huge discrepancies . For example , according to the true tree , an infector probability may be 90% , while according to an estimated tree it may be as low as 35% . Due to the potential for false positive classification , which may occur even if the true genealogy is known , it is more concerning that probabilities calculated from estimated trees can also be much greater than those based on the true tree . It is also important to note that this simulation study assumed perfect knowledge of incidence and prevalence of infection over time as well as perfect knowledge of the stage of infection at the time each infected host is sampled . In reality , there will be substantial uncertainty regarding both , and that would add additional error to estimated infector probabilities . Even though there is very high variance in the infector probabilities based on estimated phylogenies , the infector probability averaged across estimated phylogenies has similar performance as a statistic for classification ( AUC of ROC ) . There has been controversy [29]–[31] regarding whether abundant HIV sequences collected for clinical purposes may be useful for forensic investigations into who acquired infection from whom . Alternatively , such sequence data may be useful for epidemiological investigations only . An obvious temptation is to use the proposed models in forensic cases . At realistic levels of sampling that resemble currently availabe HIV DRM sequence databases , infector probabilities are quite small . In other words , even though the method may give a realistic estimate of the probability that i infected j , we rarely have much confidence that i infected j . In addition , forensic investigations often employ a more targeted approach to sampling and serial sampling of individual hosts [7] , [29] , which violates the assumption of simple random sampling used in our models . Calculating infector probabilities may actually be helpful for protecting patient confidentiality , since sequence data could be screened and stripped of closely linked pairs prior to being deposited in public databases . Our simulation experiments have demonstrated how infector probabilities are sensitive to many factors in addition to the structure of the phylogeny , such as details about who is sampled , when they are sampled , and the state of infected individuals at the time of sampling . Details of the epidemic process such as incidence and prevalence over time also influence infector probabilities . Most clustering methods employ a threshold genetic or evolutionary distance , but , as shown in Figure S5 , there is a noisy relationship between infector probabilities and the cophenetic distance within the HIV gene genealogy . Infector probabilities are highly correlated with phylogenetic distance , yet for a given phylogenetic distance , the infector probabilities may differ by many orders of magnitude . Getting a realistic picture of potential transmission pairs requires consideration of all of the factors included in our solution for the infector probabilities . Even though transmission events could not be inferred with high confidence , the application of infector probabilities to epidemiological investigations of HIV seems promising in light of the results in Figure 6 and S4 . Infector probabilities capture increased transmissions by those with early infection and those who are undiagnosed at the time of sampling relative to those who are diagnosed . We can also detect the effects on transmission rates of covariates that are not explicitly included in the coalescent model . Our models have additional utility beyond the calculation of infector probabilies . Similar methods could be used to calculate the distribution of the number of unsampled infected individuals in a transmission chain between two sample units . For example , this has relevance for studies of the evolution of virulence of HIV [32] , [33] , which is frequently assessed by conducting comparative phylogenetic analyses of set-point viral load and declining slope CD4 . Most comparative phylogenetic analyses are based on diffusion models of a continuous trait , however models which account for discrete transmission events may be more appropriate . One could , for example , use information about the length of a transmission chain to obtain estimates of how set point viral load correlates between epidemiologically linked pairs . This method for calculating infector probabilities is based on a population genetic model that makes assumptions about the epidemiological and immunological process . The model does not account for the potential for superinfection , recombination , or complex within-host evolutionary dynamics which could confuse phylogenetic inference and decrease confidence in putative transmission links . Furthermore , the model does not account for multiple- or serial-sampling of a single infected host . Future research is needed on methods for relaxing these assumptions as well as for quantifying error that may arise from violation of model assumptions in realistic settings . | Molecular data from pathogens may be useful for identifying the source of infection and identifying pairs of individuals such that one host transmitted to the other . Inference of who acquired infection from whom is confounded by incomplete sampling , and given genetic data only , it is not possible to infer the direction of transmission in a transmission pair . Given additional information about an infectious disease epidemic , such as incidence of infection over time , and the proportion of hosts sampled , it is possible to correct for biases stemming from incomplete sampling of the infected host population . It may even be possible to infer the direction of transmission within a transmission pair if additional clinical , behavioral , and demographic covariates of the infected hosts are available . We consider the problem of identifying the source of infection using HIV sequence data collected for clinical purposes . We find that it is rarely possible to infer transmission pairs with high credibility , but such data may nevertheless be useful for epidemiological investigations and identifying risk factors for transmission . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [] | 2013 | Inferring the Source of Transmission with Phylogenetic Data |
The co-evolutionary dynamics of competing populations can be strongly affected by frequency-dependent selection and spatial population structure . As co-evolving populations grow into a spatial domain , their initial spatial arrangement and their growth rate differences are important factors that determine the long-term outcome . We here model producer and free-rider co-evolution in the context of a diffusive public good ( PG ) that is produced by the producers at a cost but evokes local concentration-dependent growth benefits to all . The benefit of the PG can be non-linearly dependent on public good concentration . We consider the spatial growth dynamics of producers and free-riders in one , two and three dimensions by modeling producer cell , free-rider cell and public good densities in space , driven by the processes of birth , death and diffusion ( cell movement and public good distribution ) . Typically , one population goes extinct , but the time-scale of this process varies with initial conditions and the growth rate functions . We establish that spatial variation is transient regardless of dimensionality , and that structured initial conditions lead to increasing times to get close to an extinction state , called ε-extinction time . Further , we find that uncorrelated initial spatial structures do not influence this ε-extinction time in comparison to a corresponding well-mixed ( non-spatial ) system . In order to estimate the ε-extinction time of either free-riders or producers we derive a slow manifold solution . For invading populations , i . e . for populations that are initially highly segregated , we observe a traveling wave , whose speed can be calculated . Our results provide quantitative predictions for the transient spatial dynamics of cooperative traits under pressure of extinction .
Heterogeneity and spatial patterns in population dynamics appear spontaneously in nature , on a wide range of spatial and temporal scales [1 , 2 , 3 , 4] . Populations of reproducing individuals are not randomly dispersed , but aggregate according to climate , predatory stress , and resource levels , all of which can vary in space and time . Structures of this type are , however , not always the result of external factors , but can also arise due to interactions between individuals within the population [5] . Thus , growing cell populations can be simultaneously driven by density-dependent and frequency-dependent selection [6] , and the combination of the two mechanisms can lead to novel phenomena [7 , 8] . Interactions between individual organisms are often mediated by their phenotypes . In terms of reproductive success , the fitness of a certain type often depends on the frequency of other types present in the population . This frequency-dependence sets the stage for game-theoretic explanations of population dynamics , the phenotype becomes a strategy . The ecological public goods game ( PGG ) [3] describes a scenario in which a subpopulation releases costly factors , such as enzymes or growth factors , into the environment , where they benefit both the producers and non-producers ( free-riders ) . The PGG is played between producers of the public good and free-riders . Individuals either produce public good and thus ‘cooperate’ , or only reap the benefits , i . e . free-ride and thus ‘defect’ [9] . This population game has been studied by considering a group of N players [10] , in which producers contribute the good at an individual cost κ > 0 . In the case that the benefit of the good is outweighed by the cost of production , free-riders will invade and outcompete the producers , leading to the tragedy of the commons [11] in which the overall population fitness declines as free-riders take over . This social dilemma-setting may also be observed in cancer cell growth kinetics [12 , 13] , in which a subset of the population produces a growth factor ( e . g . testosterone in prostate , endothelial growth factor in lung cancer , and platelet-derived growth factor in glioma [14] ) . These situations call for explicit modeling of space , since the growth factor tends to be localized to producer cells and is transported by means of diffusion , which can have a limited range . Komarova et . al . discussed different mechanisms that impact the time to which we see the emergence of complex traits ( e . g . the production of a public good ) [15] . These mechanisms may require the accumulation of multiple individual mutations that are individually deleterious . Thus one can investigate the mechanisms of sequential hits vs . the emergence of division of labor based on the occurrence of cheaters and cooperators , with applications in biofilms , cancer and viral infections such as HIV , where the public good could also include advantageous genetic material . In a highly relevant cancer cell setting , Zhang et . al . in [16] employed a three population Lotka-Volterra model that considered cells requiring exogenous androgen ( T+ ) , cells which can produce androgen ( TP ) , and cells which do not require androgen ( T- ) . They showed via mathematical modeling the utility of adaptive therapy to control tumor growth , rather than hitting the tumor with the maximum tolerated dose ( MTD ) . In a pilot clinical trial [16] , the effectiveness was verified by a large improvement in median survival . In this setting , the T+ cells act as free-riders , and the TP cells act as producers . The additional drug-resistant clone cell type T- is relevant in the presence of therapy . In our work here , we consider interactions of the nature described between the two types T+ and TP . The time for one cell type to overtake the other is of importance , as it is renders whether tumor control is feasible in a biologically or clinically relevant time frame . Chemotherapy and targeted therapy protocols advise the MTD , which targets to eliminate drug-sensitive cells and often selects for drug-resistance . Relapse is then caused by proliferation of drug-resistant cells [17 , 18 , 19] . As an alternative , adaptive therapy ( AT ) has recently been used successfully in cancer treatments [20] . AT introduces a variable dosing schedule to control ( in theory ) the diversity of the cancer , and thus its growth , without eradicating it . Proliferation of drug-sensitive cells allows for greater competition ( e . g . contact inhibition , resource allocations ) between cell types , which inhibits the proliferation of drug-resistant tumor cells . Clinical trials in breast [21] , ovarian [22 , 23] and prostate [16] have demonstrated that evolution-based AT strategies can be successfully employed , potentially indefinitely , and can be superior to standard MTD . The success of these approaches might critically depend on knowledge about the time scales of extinction of producer cells . The type of evolutionary game , and also the spatial arrangement can determine the outcomes of population dynamics [24] . Spatial PGGs have been studied mostly in populations of fixed size , as this case resembles the essence of competition and co-evolution , e . g . at carrying capacity . PGG evolutionary dynamics in growing populations has only recently been investigated in a non-spatial setting [8] . The time to reach an equilibrium point , which we denote “ε-fixation time” , or “ε-extinction time” in the case of a monomorphic equilibrium point , may depend critically on differences in net growth rates . Cooperation between cell lines was studied under varying substrate concentrations , and it was observed that segregation occurred more readily when substrate was limited [25] . These spatial pattern formations occurred as the population moved and grew into an unoccupied domain . Once the population approaches capacity , competition should take over and the dominant clone should fixate . The experiments however focused on the behavior of the initial front type and showed that variation in outcome was due to available substrate . The timing of outcomes has not been studied in great detail so far , partly because standard tools in evolutionary game theory–such as the replicator equation–can describe homogeneously growing populations [26] , but do not capture differences in net growth rates that result from frequency-dependent selection , e . g . in context of a PGG [27] . However , these time scales play an important role biologically , especially if the time to reach an equilibrium is longer than the expected lifespan of the system . Tumor growth is a typical example , where the total tumor burden might kill the patient before one cell type outcompetes the other . We take two important steps to extend the logistic population growth model considered in [8] . First , we allow for spatial variability , which can allow for rich dynamics depending on the relative magnitude of population dispersal ( cell type specific diffusion coefficients ) . We analyze spatial heterogeneity in up to three dimensions and show that the ε-extinction time can be influenced by spatial heterogeneity . By spatial heterogeneity and variability we are referring to the initial ( possibly ) uneven distribution of cell and public good concentrations . In particular , non-random initial conditions can cause large increases in the ε-extinction time . We also consider the public good function to be a nonlinear , sigmoidal function . This non-linear relationship can lead to bi-stability and potential polymorphic equilibria [27 , 28 , 29] . We are primarily concerned with how spatial variations impact the time it takes to reach an extinction event . To approximate the ε-extinction time in spatial systems , we show under what conditions the well-mixed ( non-spatial ) model can elucidate a decent approximation through the time it takes to travel along the “slow manifold” . In certain parameter regions , we calculate an estimate of the time spent on this manifold . Numerical simulations are often in good agreement with analytically estimated ε-extinction times , except when the nonlinearity is strong . In cases of highly non-linear growth rate , analytical approximations of the slow manifold become increasingly cumbersome although the non-spatial model provides an accurate estimate of the time . Highly structured situations can occur if producers and free-riders occupy mutually exclusive regions in space . In this case , we observe Fisher-like traveling wave solutions , with an interesting transition between pushed and pulled waves occurring at a critical threshold of the nonlinearity [30] . Thus , one can explore the time a traveling wave of free-riders needs to move across the entire domain . The so determined time scales of the eco-evolutionary PGG dynamics could then effectively be used to infer the underlying fitness functions that drive the co-evolutionary dynamics of producers and free-riders .
Let us assume that producer cells ( U ) and free-riders ( V ) are closely related cell types experiencing the same baseline growth rate α and potentially different death rates μU , μV . Next , we assume that the public good , produced by U cells , has a non-decreasing effect on the growth rates , in the form of a multiplicative benefit to the growth rate . This benefit depends on the local public good or growth factor concentration ( density ) G , which is determined by the local producer cell density: G is produced by U cells , at a rate ρ , at a cost to their growth rate κ , and it is consumed by U and V cells alike at a rate δ . The diffusion rate of the public good is ΓG . We have neglected a decay rate of the public good based on the fact that there are molecules that can serve as public goods , which exhibit low decay rates due to binding and unbinding with cell surface proteins , which enhances persistence of these molecules in the long-term ( see section 1 , SI text ) . The cells are assumed to reside and grow on a spatial domain [ 0 , L ] n ⊂ R n , where n = 1 , 2 , 3 is the dimension of the system . We assume that the domain has no-flux boundary conditions ( e . g . cells cannot enter or leave the domain ) . We assume that growth , death and competition processes are purely local and that migration ( determined by the cell type specific diffusion coefficients ΓU , V ) is isotropic and involved only with nearest neighbors . We then obtain the following set of coupled PDEs that model the concentration of producer cells , free-rider cells , and public good in time and space: U ˙ = Γ U ∇ 2 U + [ λ ( G ) − κ ] [ 1 − ( U + V ) ] U − μ U U , ( 1 ) V ˙ = Γ V ∇ 2 V + λ ( G ) [ 1 − ( U + V ) ] V − μ V V , ( 2 ) G ˙ = Γ G ∇ 2 G + ρ U − δ G ( U + V ) . ( 3 ) Here , the respective growth rate is λ ( G ) = α 1 + e σ 1 + e σ - β G . ( 4 ) A well-mixed version of this model was studied in [27] . It was shown that saddle-node bifurcations and other interesting features are in general impossible for a linear public good . Richer dynamics are possible when the good enters nonlinearly . Here , σ is a concentration-independent parameter , and β is the concentration-dependent parameter . These two parameters modulate the size of the nonlinearities in the growth rates . We can think of β as the per public good “unit” benefit to the growth rate . Whereas σ controls the maximal benefit obtainable . The ratio σ/β defines the location of an inflection point in the growth rates , which is the point that separates regions of synergistic and diminishing return , as a function of increasing growth factor G . In the small benefit-limit , β ≪ 1 , we obtain a linear good λ ( G ) ≈ α ( 1 + sGβ ) , where s = eσ/ ( 1 + eσ ) . Finally , producer cells experience a growth rate detriment in amount of the linear cost κ , as seen in Eq ( 1 ) . All important parameters and their baseline values are summarized in Table 1 . The typical cell size is on the order of micrometers . Thus , in an attempt to simulate many cells , we focused on spatial domain ranges of L = 0 . 1–10 cm . The length of time for a cell cycle is highly variable . A typical cell cycle could range from hours , to days , to weeks , and the PG-independent proliferation ( growth ) rate is typically ( but not always ) higher than the death rate [8] . We can construct the following non-dimensional form of the spatial model . In the original model formulation we have eleven parameters and three initial conditions U0 ( x ) , V0 ( x ) , and G0 ( x ) . With appropriate choices we can reduce the total number of relevant parameters to nine dimensionless parameters . Although there are many choices for the set of dimensionless parameters , we choose this set to exploit the typical fact that the time scale of the dynamics for G are much faster than the time scales of the dynamics of U and V [8 , 36] . This is motivated by the fact that smaller objects ( e . g . IGF-I and II ) tend to have higher diffusion rates than cells . After appropriate rescaling , we can use the dimensionless parameters of the non-dimensional system given in Table 2 . We introduce dimensionless time τ = αt and rescale growth factor concentration by the ratio of its production to consumption rates , G → ( ρ/δ ) G . Space is scaled via Lx = Ly = Lz = ( ΓG/δ ) 1/2 , which leads to non-dimensional domain lengths between 1 and 103 . In our notation , the “dot” then means differentiation with respect to dimensionless time τ ( instead of t ) , and ∇ is the differential operator with respect to the rescaled spatial variables . Then we arrive at the dimensionless system U ˙ = γ U ∇ 2 U + ( λ ( G ) - 1 + a ) [ 1 - ( U + V ) ] U - c U , ( 5 ) V ˙ = γ V ∇ 2 V + λ ( G ) [ 1 - ( U + V ) ] V - c r V , ( 6 ) ϵG˙=∇2G+U−G ( U+V ) . ( 7 ) Turning to a dimensionless framework allows us to more easily exploit the separation of time scales inherent in our system . For example , the public good consumption rate is typically much faster than the proliferation rate , ϵ ≪ 1 , and thus spatial equilibration of the public good G occurs relatively fast . Similarly , we can immediately see from the dimensionless system that the ratio of death rates between cell types , r , is an important quantity that determines the fate of cooperation , especially provided the ratio of death rate to proliferation rate in producer cells , c , is small .
What is the impact of variability in initial conditions ? To address this question , we investigated the dynamics of the system governed by Eqs ( 1 ) – ( 3 ) in one , two and three dimensions in its non-dimensional form Eqs ( 5 ) – ( 7 ) . The non-dimensional length used ranged from L = 10 − 500 for all spatial dimensions ( n = 1 , 2 , 3 ) . To solve Eqs ( 5 ) – ( 7 ) numerically , we discretized the domain into grid points . The grid points were then given initial concentrations of the amount of producer , free-rider and public good present . The distance between grid points , or the spatial step size , was chosen to be no bigger than Δx = 0 . 5 . We tested smaller grid sizes , but found no significant changes in the dynamics , only in total CPU time . We solved the PDE using a Crank-Nicolson scheme with a time step size Δt = 0 . 01 [37] . We also tested the sensitivity of the ε-extinction time to different Δt and found that in all cases , Δt = 0 . 01 was sufficient . Unless specified differently , we set r = 1 , i . e . we assumed that the two types had equal death rates . Then , simulations were used to calculate the time to reach the neighborhood of a stable fixed point , with an exit criterion based on the 1-norm distance to the stable fixed point ( U* , V* ) as d ( U , V ) ≔ |U − U*| + |V − V*| < εexit , where the value εexit = 10−8 was used . If the initial condition was noisy , 100 simulations were used to generate summary statistics . In all settings of different spatial dimension , we were interested in three types of initial conditions that define the initial cell density ( amplitude ) at every grid point: ( 1 ) Uniformly distributed values between 0 and 1 , ( 2 ) domain wall ( step function ) , and ( 3 ) oscillatory . To examine the stability of the more structured density distributions ( 2 ) and ( 3 ) , we also tested the impact of spatial noise by introducing a random deviation of the cell density in each point in space , which was chosen no greater than 10% of the max amplitude at each grid point . Under the assumption of fast diffusion of cells into space , a spatial perturbation typically equilibrates along the spatial domain faster than an average cell cycle length . Fig 1 shows the temporal evolution of a typical simulation run , with a random initial condition being drawn from a standard uniform distribution on each grid point . The oscillations of initial cell densities were rapidly equilibrated during the first few cell cycles . Once the system had become roughly homogeneous , the system began to travel along the slow manifold ( shown as the orange , dashed line in the final snapshot ) , toward free-rider fixation ( producer extinction ) . In this example , the exit condition was met at τ = 489 . 38 . The average cell concentrations are shown in the second subplots and shows the phase diagram for the average cell concentrations . The average quickly reaches the slow manifold and spends most of its time traveling along it . The final snapshot shows the slow manifold , calculated from the ODE model with a dashed , orange curve . Although the model is explicitly spatially dependent , the average cell population rapidly approaches the slow manifold of the spatially averaged cell populations . Random spatial fluctuations do not have a huge impact since on small length scales , they are smoothed rapidly ( see section 6 , SI text ) . All numerical solutions approached spatially homogeneous solutions consisting of only a single population under our parameter assumptions , regardless of dimensionality . We used a superposition of initial conditions defined by u → 0 = p W → + ( 1 - p ) R → where W → ( Fig 2A ) is the segregated initial condition vector and R → is the random initial condition vector . p can then be thought of as a type of spatial correlation measure with p = 0 “unstructured” and p = 1 “structured” . Using random initial conditions , we found that the average time to ε-extinction was also independent of the dimensionality ( Fig 2B ) . We note that the narrowing of the distribution of ε-extinction times is not related to the dimension of the system but rather to the number of grid points . This is easily seen by considering N random numbers drawn from a standard uniform distribution . The mean and variance are 1/2 and 1/ ( 12N ) , respectively . The total number of grid points Ni where i is the dimension of the system was ( N1 , N2 , N3 ) = ( 101 , 441 , 9261 ) . We show that uncorrelated spatial structure evolves roughly as the mean of the initial condition ( section 6 , SI text ) . This is confirmed by the fact that the mean of distributions are all around 211 . 8 ( cell cycles ) , and starting from the uniform state where each population is 1/2 leads to a time of 211 . 66 numerically . Finally , if we compare the ratio of variances of ε-extinction times , we expect that they should be approximately Nj/Ni . The results in Table 3 confirm that the distribution variability is tied to the number of grid points and not to the actual dimensionality of the system . How are ε-extinction times influenced by non-random initial conditions in settings of different dimensions ? The impact of structured initial conditions is particularly relevant to biological processes where spatial assortment can occur in populations with limited dispersal . Therefore , we examined how the ε-extinction or -fixation times were affected by more coherent , non-random starting conditions . Regardless of parameter choices , all final states are homogeneous and correspond to the stable fixed point of the non-spatial model . We thus investigated analytically the time needed to reach an equilibrium , or fixed point , using the non-spatial ODE model . To this end , we extracted an approximation which makes it possible to compare the ODE approach to the spatial PDE model . This approach allowed us to quantify the impact of spatial heterogeneity on timing to ε-extinction . Numerical integration of the spatial model suggested that a non-spatial analysis could be used to determine the time scale of fixation , e . g . when public good producers go extinct . This change to a simple model system is meaningful because all final states are homogenous in space . The spatially invariant version of our dynamical system is given by U ˙ = ( λ ( G ) - 1 + a ) [ 1 - ( U + V ) ] U - c U , ( 8 ) V ˙ = λ ( G ) [ 1 - ( U + V ) ] V - c r V , ( 9 ) ϵG ˙ = U - G ( U + V ) . ( 10 ) First , let us turn to the possible fixed points and their stability in the non-spatial setting . The system described by Eqs ( 8 ) – ( 10 ) exhibits three main steady states which exist over a wide parameter range . Fig 3 shows examples of the dynamics between these steady states in the ( U , V ) plane . Additionally , a sample trajectory is shown , which indicates the approach to a slow manifold that is inherent to all trajectories ( if this manifold exists ) . We can exploit the slow manifold-dynamics to estimate the time to reach the all-free-rider state . In addition , the linear stability conditions of the steady states can be calculated ( see section 1 , SI text ) : It is interesting to note that in the case of equal death rates ( r = 1 ) , the producer-only state is necessarily unstable , since it is assumed that production of the good comes at a cost ( a < 1 ) . It then follows naturally that , even if we unilaterally lower the death rate of producer cell , r ≤ 1 the producer-only state remains unstable . Furthermore , it was shown that a nonlinear good of this particular form has at most one coexistence point [27] . In this system , this coexistence point is in fact always unstable if c ≠ 0 ( section 1 , SI text ) . To investigate the impact of the domain length , we considered uni-modal , domain wall , and random initial conditions for the concentrations of producer and free-rider cells , and for the the public good concentration . Our simulations show that the domain length did not greatly impact the ε-extinction time when given purely random starting conditions ( see Fig 2A with p = 0 ( uncorrelated initial conditions ) and section 10 , SI text ) . However , for the domain-wall and other , more structured conditions , the size of the domain influenced the fixation time substantially . Note that the invasion of free-riders into the space occupied by producers is similar to traveling waves observed in standard Fisher equations [44 , 45] . We showed that total ε-extinction time is modified by the time it takes for this wavefront to reach the end of the unstable region , and the ε-extinction time can be approximated as the superposition τ=τODE+τwave+τwaveformation=τODE+d|η|+τwaveformation , ( 18 ) where d is the distance travelled by the Fisher wave , and |η| the speed of the wavefront ( see section 6 , SI text for details ) .
Here we considered a spatial nonlinear public goods population game model in its deterministic form . We have investigated the impact of spatial arrangement of public good producer cells and free-rider cells on the temporal scales of extinction or coexistence during the co-evolution of these populations on a finite spatial domain . The model typically exhibits fixation of either producers of the public good or free-riders , which critically depends on the frequency-dependent birth and death rates , and on properties of the public good itself , such as the cost of production . While the cost to benefit ratio plays a part in this , the overall dependencies can be more involved . Our analysis has shown that structured ( correlated ) initial conditions have a large impact on the predicted ( ε ) time to fixation . The dynamics of unstructured ( random ) initial conditions can be captured by a non-spatial approach , for which ε-extinction times can be calculated analytically . In certain parameter regions , an approximation to this ε-extinction time can be calculated to decent accuracy . However , the process is cumbersome and when the influence of the public good is strongly nonlinear ( β ≫ 1 ) , the approximation requires a large number of terms to properly capture the shape of the slow manifold that dominates the time scales . The behavior of the ε-extinction time as a function of the death rates ( Fig 4A and 4B ) shows a minimum time to ε-fixation time . The reason for this can be understood with two observations . First , we begin with small death rate c ≪ 1 . As this rate increases , both cell-types exhibit faster death rates and so we expect the time to ε-fixation to go down . However at some point , we observe the reverse , increasing the death rate is leading to an increasingly long time to reach the free-rider only state . The culprit is the death rate has become so high , that the fixed point is now “close” to the extinction state , which is a repeller . This state acts to “slow” the flow towards this point . For the example in Fig 4A , we note that as c → 1 , the free-rider only state: 1 − cr approaches 0 . This is a transcritical bifurcation , and the divergence in time to reach the fixed point is well known [47] . For structured initial conditions , e . g . a domain wall , one type takes over the other with time that increases linearly with the size of the spatial domain . Though this is expected , it is surprising that this time is not solely dependent on the time it takes for the wave to reach the edge of the domain . Rather , the total time depends on a linear superposition of the wavefront time , and the time for the wavefront to equilibrate . We have also shown that the linear Fisher theory that predicts the wave speed is inaccurate for increasing nonlinearity ( large β ) , similar to the breakdown of the linear manifold approximation of the slow manifold . In this case , there exists a transition at a critical βc , which could be a function of all other relevant parameters that determine whether the wave is pushed or pulled . To find this critical value could be an exciting avenue of future analytical and computational work . Our numerical simulations show that all spatial inhomogeneities are ultimately removed , but are not insignificant in regards to the time it takes to reach spatial homogeneity . Our results also highlight a point often ignored in the evolutionary dynamics literature , which typically focuses on the evolutionary stable states ( ESS ) and focuses less on the temporal dynamics of selection . Similar tendencies are apparent in the wider field of the study of ecological systems , where transient behavior has often been secondary to determining long-term stable states [48] . Our analysis shows that both population dynamical parameters , such as death rate , the initial condition , and the spatial extent of the population influence the time it takes to reach the ESS . These results are particularly relevant to cancer , where public goods might be a common feature of tumor-ecological stability , for example as seen by the evolution of autocrine growth factor production [13] . The time to the end of the game may also be quite long , perhaps greater than the lifetime of the patient . We also investigated the possibility of diffusion-driven pattern formations via a Turing bifurcation . A typical requirement is a large difference in the relative magnitude of diffusion coefficients . We tested different scenarios , but we did not observe any pattern formations , all solutions approached homogeneity . Furthermore , we show that Turing bifurcations are not possible in this system ( section 8 , SI text ) . This is in contrast to other work , where heterogeneous spatial solutions and chaos were observed [3 , 4] . In summary , we have considered the spatial growth dynamics of producer and free-riders , determined by a diffusible nonlinear public good , in one , two and three dimensions . Extracting a slow manifold solution , we obtained a good estimate for the time to ε-extinction of a cell type . For invading populations , i . e . for initially highly segregated sub-populations , we observed a traveling wave solution . We calculated an estimate of the wavefront speed and showed that the total time is given by the superposition of the traveling wave speed plus the time the well-mixed ( ODE ) solution needs to equilibrate to the average value of the wave profile . These were in excellent agreement with simulations provided that the nonlinearity was not too strong . The culprit was the strength of the nonlinearity β . When this was large , the wave transitioned from pulled to pushed . Our spatial model can be used to generalize the tumor ecological dynamics presented in [16] , which was used to assess adaptive anti-cancer strategies assuming a well-mixed population . Our spatial considerations can help refine such models and provide more accurate predictions , which could reveal critical new information with regard to the time scales of population transformations . | Evolutionary public good ( PG ) games capture the essence of production of growth-beneficial factors that are vulnerable to exploitation by free-riders who do not carry the cost of production . PGs emerge in cellular populations , for example in growing bacteria and cancer cells . We study the eco-evolutionary dynamics of a PG in populations that grow in space . In our model , PG-producer cells and free-rider cells can grow according to their own birth and death rates . Co-evolution occurs due to public good-driven surplus in the intrinsic growth rates at a cost to producers . A net growth rate-benefit to free-riders leads to the well-known tragedy of the commons in which producers go extinct . What is often omitted from discussions is the time scale on which this extinction can occur , especially in spatial populations . Here , we derive analytical estimates of the ε-extinction time in different spatial settings . As we do not consider a stochastic process , the ε-extinction time captures the time needed to approach an extinction state . We identify spatial scenarios in which extinction takes long enough such that the tragedy of the commons never occurs within a meaningful lifetime of the system . Using numerical simulations we analyze the deviations from our analytical predictions . | [
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"compu... | 2019 | Time scales and wave formation in non-linear spatial public goods games |
Helicobacter pylori , a human pathogen infecting about half of the world population , is characterised by its large intraspecies variability . Its genome plasticity has been invoked as the basis for its high adaptation capacity . Consistent with its small genome , H . pylori possesses only two bona fide DNA polymerases , Pol I and the replicative Pol III , lacking homologues of translesion synthesis DNA polymerases . Bacterial DNA polymerases I are implicated both in normal DNA replication and in DNA repair . We report that H . pylori DNA Pol I 5′- 3′ exonuclease domain is essential for viability , probably through its involvement in DNA replication . We show here that , despite the fact that it also plays crucial roles in DNA repair , Pol I contributes to genomic instability . Indeed , strains defective in the DNA polymerase activity of the protein , although sensitive to genotoxic agents , display reduced mutation frequencies . Conversely , overexpression of Pol I leads to a hypermutator phenotype . Although the purified protein displays an intrinsic fidelity during replication of undamaged DNA , it lacks a proofreading activity , allowing it to efficiently elongate mismatched primers and perform mutagenic translesion synthesis . In agreement with this finding , we show that the spontaneous mutator phenotype of a strain deficient in the removal of oxidised pyrimidines from the genome is in part dependent on the presence of an active DNA Pol I . This study provides evidence for an unexpected role of DNA polymerase I in generating genomic plasticity .
Phenotypic selection from a pool of genetic variants present in their population allows prokaryotes to successfully adapt to specific niches and changing environments . The gram-negative bacterium Helicobacter pylori is one of the most successful human pathogens . Indeed , it colonises the stomach mucosa of about half the human population , triggering pathologies that span asymptomatic chronic gastritis , peptic ulcers and cancer [1] . The study of natural isolates suggests that the genetic diversity of H . pylori exceeds that recorded in all other bacterial species studied . Moreover , it is now clear that even in the course of infection of a single individual , H . pylori strains display high rates of allelic variation [2] , [3] . This enhanced ability to change and the consequent advantage of counting upon a large pool of variants from which to select the most-fit combinations have been proposed to facilitate adaptation within a host as well as colonisation of new hosts [4] , [5] . Therefore , besides its clinical importance , the amazing genetic variability of H . pylori makes it an excellent model for the analysis of the molecular mechanisms underlying microbial phenotype evolution . At the origin of the allelic variability are nucleotide changes that can arise from replication errors either spontaneous or induced by DNA lesions . H . pylori displays a high rate of mutations , accounted not only by the lack of mismatch repair system [6] , [7] but also by the exposure to genotoxic stresses during infection leading to the formation of DNA lesions [8] , [9] . While replicative DNA polymerases are highly accurate and efficient in replicating undamaged DNA , the presence of abasic sites or modified bases will often impede the progression of the replication fork . It is now well established that in most organisms DNA polymerases exist that are capable of substituting for the replicative polymerase and facilitate translesion synthesis ( TLS ) allowing the replication machinery to overcome the blockage . In many cases , TLS is associated with the acquisition of heritable mutations induced by the incorporation by the TLS polymerase of an incorrect nucleotide opposite the lesion [10] . In agreement with the low functional redundancy in its DNA repair pathways , analysis of the H . pylori genome sequences predicts the presence of only two putative DNA polymerases . Indeed , six genes code for the replicative polymerase subunits , while one gene , HP1470 in the reference strain 26695 , codes for a putative DNA Polymerase I . E . coli Pol I was the first DNA polymerase discovered and is the most abundant one [11] . The Pol I bacterial DNA polymerases are multifunctional proteins . In most bacterial species Pol I presents two distinct functional domains , a 5′ - 3′ exonuclease N-terminal domain and a larger C-terminal domain ( Klenow fragment ) harbouring the polymerase and the associated proofreading 3′ – 5′ exonuclease catalytic sites [12] . The 5′-3′ exonuclease activity allows the removal of the RNA primers of the Okazaki fragments during DNA replication [13] . The gap-filling capacity of Pol I not only participates in the replication of the lagging strand but also in DNA excision repair and in recombination . The absence of other predicted DNA polymerases in H . pylori , in particular of those capable of TLS , raises several questions regarding the distribution of roles between the two DNA polymerases during replication and repair . To investigate these issues we characterised the protein coded by H . pylori polA gene and showed that it is able to bypass blocking lesions . Based on our genetic results we conclude that H . pylori DNA polymerase I , albeit its important role in cell viability and DNA repair , contributes to mutagenesis during normal chromosome replication and therefore to the plasticity of the genome .
The inferred absence of specialised TLS polymerases coded by the H . pylori genome [14] , [15] prompted us to study the characteristics of the putative DNA polymerase I , one of the two predicted DNA polymerases of this pathogen . The protein sequence deduced for HP1470 suggested that the protein is a bona fide DNA Polymerase I orthologue . However , closer inspection of the amino acid sequence shows that even though the overall structure of the 3′ – 5′ exonuclease domain is likely to be preserved , at least three conserved residues - Asp355 , Asp424 and Asp501 in E . coli DNA polymerase I - involved in metal binding and essential for the exonuclease catalytic activity [16]–[18] are missing ( Figure S1 ) . In order to verify the activities of the H . pylori DNA Polymerase I ( herein Pol I ) , the protein was expressed in E . coli and purified to apparent homogeneity ( Text S1 and Figure S2 ) . As expected , Pol I displayed DNA–dependent polymerase ( Figure 1A ) and 5′ – 3′ exonuclease ( Figure 1B ) activities . In the polymerisation assays ( Figure 1A ) , extensions beyond the expected full-length product could be detected . This has previously been shown to be characteristic of some DNA polymerases lacking a proofreading activity [19] . To verify the prediction of a lack of 3′- 5′ exonuclease activity , we then tested Pol I mismatch editing capacity . In conditions in which the E . coli Klenow fragment efficiently removed a mispaired base from the primer 3′-end , Pol I showed no exonuclease activity on substrates with different 3′-mismatches ( Figure 1C ) . Moreover , with the possible exception of a G:A after which only one or two bases were incorporated , Pol I was able to extend primers with various mismatches at their 3′-end ( Figure 1D ) . In order to explore the role of Pol I in vivo , we generated H . pylori strains deficient in this protein . The constructs used to disrupt the gene were designed to replace the 2 kb central region of the gene with an antibiotic resistance cassette , leaving only 300 bp of the gene at each extremity . Interestingly , very few clones were obtained and in all cases analyzed , the cassette was inserted downstream of the expected site . Sequencing of five independent insertions showed that the first kilobase of the coding sequence was always preserved ( Figure S3 ) , potentially allowing the 5′ – 3′ exonuclease to be expressed . To rule out a sequence context bias for the insertion , we performed transformations with the same disruption cassette in a strain carrying an extra copy of the polA gene at the ureA locus . In this case the number of clones recovered was several orders of magnitude higher compared to those obtained from transformation of the wild type strain . Analysis of 22 independent insertions showed that 4 were in the ectopic gene and 18 in the hp1470 locus . Interestingly , in all cases the insertion resulted in the expected product , a deletion starting 300 bp from the initiation codon , leading to the truncation of two thirds of the 5′ – 3′ exonuclease domain . Taken together , these observations strongly suggest that the 5′ – 3′ exonuclease activity coded by the N-terminal domain of Pol I is essential for viability . We then assessed the capacity of strains defective in DNA polymerase activity of Pol I ( polA ) to survive to various genotoxic treatments . The polA strains used correspond to those strains where the 3′ – 5′ exonuclease and polymerase domains are replaced by an antibiotic resistance cassette , leaving an intact 5′ – 3′ exonuclease domain , shown above to be essential . polA mutants are extremely sensitive to agents such as ionising radiation , UV light , hydrogen peroxide and the alkylating agent methyl-methanesulfonate ( MMS ) ( Figure 2A–2D ) , all inducing different types of DNA damage . Interestingly , when polA was disrupted in a strain deficient in AP-endonuclease activity ( xth ) [20] there was an additive effect on the sensitivity to MMS , suggesting that Pol I participates in another pathway besides base excision repair . These results underscore the crucial role of Pol I in various DNA repair systems . To better characterise the in vivo functions of the protein , we tested the effect of the deficiency in Pol I on H . pylori spontaneous mutagenesis . The rate of base-pair substitutions was determined by monitoring the appearance of rifampicin-resistant ( Rifr ) colonies [9] ( Figure 3A ) . Surprisingly , even though DNA polymerases I are involved in excision repair , inactivation of the polymerase activity of Pol I not only failed to increase base-pair mutation rates but resulted in a modest but significant hypo-mutator phenotype . Moreover , overexpression of Pol I driven by the strong ureA promoter resulted in a hyper-mutator phenotype thus indicating that Pol I in vivo generates base-substitutions . Since the Rifr mutagenesis test is limited to the detection of specific base substitutions , we used a forward mutation assay to explore a larger spectrum of genetic alterations . For such purpose , we determined the rate of mutations in the rdx gene , leading to resistance to metronidazole ( Mtzr ) [21] . The results showed a much more pronounced effect of Pol I on the Mtzr mutation rates than in the case of Rifr . Indeed , inactivation of polA resulted in a 4-fold decrease in spontaneous mutations while its overexpression increased the rate of mutation by 500-fold ( Figure 3B ) . Sequencing of Mtzr isolates showed that the spectrum of mutations also changed . Indeed , sequencing of Mtzr isolates showed that the 10-fold excess of mutants obtained in a wild type with respect to polA strain was due to 72- and 9-fold increases in the frequency of base substitutions and one base-pair frameshifts respectively , while the frequency of larger deletions or insertions was essentially unmodified ( Table 1 ) . The same trend was observed for the Pol I over-expressing strain where the increase in mutations was accounted for by the increase in base substitutions and one base pair frameshifts , with only 1 out of 36 clones analyzed displaying a change involving more than one base-pair ( −2 deletion ) . Interestingly , in the overproducing strain the enhanced rate of base pair substitutions could essentially be accounted for by the increase in transversions . In conclusion , the excess mutations observed in strains expressing Pol I were essentially base substitutions or one nucleotide frameshifts . Taken together these data confirm that Pol I , although important for DNA repair , contributes to genetic variability mainly through the generation of single nucleotide polymorphisms . The results presented above prompted us to analyse whether , besides the lack of proofreading , Pol I harboured an intrinsic error-prone DNA polymerase activity . The fidelity of Pol I was determined during synthesis to fill a 407-nt single-stranded gap within a circular duplex M13mp2 DNA substrate . The gap contains the lacZ α-complementation sequence that serves as the target for detecting polymerisation errors that are detected as light blue and colourless plaques among blue plaques resulting from correct synthesis [22] . The DNA products of gap filling by Pol I yielded a lacZ mutant frequency of 0 . 15% . This frequency is lower than values obtained after gap filling by several other exonuclease-deficient family A polymerases , including 0 . 57% Klenow fragment polymerase [23] , 0 . 75% for Thermus aquaticus polymerase [24] , 1 . 6% for exonuclease-deficient T7 polymerase [23] , [24] , and 0 . 62% for exonuclease-deficient pol γ [25] . Thus H . pylori Pol I is among the most accurate exonuclease–deficient members of the family A polymerases when copying an undamaged DNA template in vitro . The apparent contradiction between the fidelity of the Pol I DNA polymerase activity on undamaged DNA and its role in the generation of mutations prompted us to further investigate the enzymatic characteristics of Pol I . The lack of proofreading activity , the consequent capacity to elongate from mismatches and the spectrum of mutations it generates are reminiscent of TLS polymerases . We directly addressed this possibility by determining the ability of purified Pol I to bypass DNA lesions present in the template strand . Among the lesions tested , some , like the abasic ( AP ) site analogue tetrahydrofurane ( THF ) and thymine glycol ( Tg ) are known to impose a blockage to normal DNA replication [26] , [27] while others like 8-oxoguanine ( 8-oxoG ) do not , but have a miscoding potential [28] . In the case of E . coli Klenow fragment , DNA synthesis is indeed strongly blocked opposite Tg and THF residues present in the template strand ( estimated bypass efficiencies: 5 and 11% respectively ) . Conversely , albeit also partially blocked , H . pylori Pol I is able to synthesise through these lesions ( Figure 4A ) ( estimated bypass efficiencies: 61 and 48% , for Tg and THF respectively ) . We next examined the single nucleotide insertion profile promoted by Pol I opposite the various lesions . Consistently with the described coding capacity of 8-oxoG , Pol I introduces both A and C opposite the oxidised guanine ( Figure 4B ) . For the other lesions tested DNA Pol I follows the A-rule , introducing preferentially adenine opposite the lesion . In the case of the abasic site analogue addition of G opposite THF is also observed ( Figure 4B ) . To confirm that the Pol I-dependent in vivo mutagenesis could be at least partly related to the presence of DNA lesions , we analysed the effect of Pol I on the spontaneous mutagenesis in strains lacking Nth , the DNA glycosylase responsible for the removal of oxidised pyrimidines from DNA . As previously reported [9] , an nth mutant has a 4-fold higher mutation rate than its parental strain ( Table 2 ) . Inactivation of polA in an nth background resulted in partial reduction of the mutator phenotype induced by the lack of Nth , strongly suggesting that a fraction of unrepaired Nth substrate lesions are normally bypassed by the DNA Pol I . This result is consistent with a contribution of Pol I to mutagenesis through TLS .
The success of H . pylori in colonising a large fraction of the human population has been attributed to its adaptation capacity based , in turn , on the genetic diversity of the species . At the basis of the remarkable genetic variation found in H . pylori are nucleotide polymorphisms that can be rapidly propagated by recombination between strains [29] . In vivo generation of allelic diversity is driven by mutation rates significantly higher than those of most other bacteria [6] . Several mechanisms have been suggested as contributing to the high mutation frequency of this pathogen , starting with the lack of homologues of many DNA repair genes known to be involved in maintaining the genetic stability in other bacterial species [4] . Among the most remarkable absences is probably that of a mismatch repair system [6] , [7] capable of removing incorrect bases introduced during replication . The work presented here unveiled another mechanism contributing to H . pylori high mutation rates . We showed that H . pylori strains deficient in DNA Pol I polymerase activity have reduced mutation rates indicating that DNA polymerase I actively participates in generating allelic diversity . This constitutes a surprising role for a protein associated with DNA repair and replication in all the studied bacterial models . The sensitivity of polA strains to various genotoxic agents confirms that H . pylori Pol I is involved in various DNA repair pathways such as recombination and base excision repair . However , their hypomutator phenotype is in contrast with the 7- to 10-fold-higher spontaneous mutation frequency in E . coli Pol I-deficient strains [30] . Our results , together with the absence of DNA polymerases other than DNA Pol I and Pol III , suggest that the polA gene in this species has been selected for coding a DNA Pol I capable of fulfilling extra functions allowing increased mutation rates . Indeed , we showed that DNA Pol I can not only extend mismatched primers , but also bypass DNA lesions that would normally block the replicative polymerase as well as DNA Pol I homologues from other bacteria . How can those characteristics contribute to increase mutagenesis ? Spontaneous or induced DNA damage is constantly generated in the genome [31] . In most organisms TLS polymerases allow replication across damaged DNA avoiding the blockage of the replication machinery . In E . coli , the SOS response includes the expression of TLS polymerases that allow survival in such situations at the expense of induced mutations . In spite of the lack of evidence for an SOS response system , it is now clear that H . pylori takes advantage of stress-induced DNA damage to mutate [8] , [9] . Such a response necessitates a DNA polymerase capable of performing mutagenic TLS [10] . Unlike what was shown in B . subtilis , where Pol I , also lacking the proofreading function , acts in concert with TLS polymerases PolY1 and PolY2 to bypass lesions [32] , the biochemical activities of H . pylori Pol I unveiled in this work would be sufficient to accomplish the task . The hypo-mutator phenotype of the polA strains and the lack of specialised TLS polymerases are consistent with this view . So is the increased proportion of transversions among base substitutions found in the Pol I overproducing strain with respect to the wild-type ( 13/14 versus 6/19 ) , as expected for the bypass of non-coding lesions . The partial dependence on a functional DNA Pol I of the increased mutagenesis of an nth strain provides further support for this hypothesis . The oxidative stress generated by infection-induced inflammation , the acidic medium of the stomach together with the limited set of H . pylori DNA glycosylases involved in base excision repair [20] , [33] favour the formation and persistence of stress-induced damage in DNA , including modified bases and abasic sites [9] , [34] . Therefore , it is likely that beyond its functions in DNA repair , DNA Pol I plays an important role in the survival of the bacteria during infection by allowing the replication of damaged DNA and , concomitantly , by contributing to generate allelic diversity in response to the stress . From the enzymatic point of view , H . pylori polymerase I combines two antagonistic properties not usually found within the same enzyme . Although it exhibits high accuracy on undamaged DNA , it is able to efficiently bypass several types of lesions and can extend mismatched primers . How can such a plasticity be understood in the context of a single enzyme ? Regarding other Pol I homologues , accuracy was shown to be exquisitely controlled through a closing mechanism of the fingers domain involving a tight packing between the active site residues and the nucleotide to be inserted . Residues in the so-called O-helix were shown to actively disfavour misincorporation [35] , [36] . Mutation Y766S within the O-helix of E . coli Klenow polymerase led to a more open active site and favoured lesion bypass at the expense of fidelity [37] , [38] . Similarly , the more open active site of TLS polymerases , such as that of yeast Polη or the archaeal Dpo4 , is a major determinant to account for their ability to accommodate bulky lesions [39] , [40] . As a first hypothesis , we thought that H . pylori Pol I active site might have a special open structure particularly tolerant to mispairs insertions . However , mapping the conservation of the sequences of both Taq and H . pylori Pol I at the structure of Taq polymerase showed that both sequences are strictly conserved all along the active site groove ( Figure S4 ) . In particular , residues of the O-helix involved in the steric-gate mechanism are identical . Consequently , both the high accuracy of PolA on undamaged DNA and the conserved nature of the active site support that , unlike other TLS polymerases , H . pylori Pol I permissiveness is not due to a more open cavity . Consistently we have not been able to detect a significant mutagenesis induced by UV ( data not shown ) . One might suppose that subtle dynamical properties of the enzyme allow accommodation of small lesions but not necessarily bulky lesions . A large body of evidence suggests that this is the case for other members of the Pol A family , including E . coli Klenow fragment . Indeed , these polymerases were shown to be able to incorporate a nucleotide opposite AP sites and products of cytosine or thymine oxidation ( Tg , urea , uracyl-glycol and others ) although not always to elongate from it [19] , [26] , [41]–[44] . Moreover , inactivation of the proofreading activity of Klenow allows the bypass of most of these lesions [19] , [43] , [45]–[47] . Interfestingly , two higher-eukaryote members of the family lacking a 3′-5′ exonuclease domain , DNA polymerases θ and ν , have been shown to be proficient for bypassing Tg and abasic sites [48]–[50] . Taking into account the strong structural conservation predicted for the active sites of H . pylori Pol I and the other members of the family ( Figure S4 ) , the work cited above supports the notion that the loss of proofreading activity can account for the capacity of Pol I to bypass AP sites and non-bulky damaged bases . In the case of AP sites this activity will contribute to mutagenesis either by incorporating in three out of four events the wrong nucleotide or by inducing frameshifts [47] . Further support for a role of TLS by Pol I in H . pylori mutagenesis , comes from the results showing that inactivation of Pol I partially complements the mutator phenotype of an nth strain ( Table 2 ) . H . pylori Nth is the only DNA glycosylase in this organism capable of removing oxidised pyrimidines from DNA [9] . Many of the products of thymine and cytosine oxidation are pre-mutagenic lesions . In particular , oxidised derivatives from cytosine as 5′-hydroxycytosine , uracyl-glycol and 5′-hydroxyuracyl [46] , [51]–[54] but also from thymine [46] , [51]–[54] have been shown to be bypassed by proofreading-deficient DNA polymerases and to be mutagenic [55] , [56] . Besides TLS , another , non-exclusive , mechanism can be invoked for the role of H . pylori Pol I in mutagenesis . The essential character of the 5′ - 3′ exonuclease domain of H . pylori Pol I strongly suggest that this activity is required for Okazaki fragment processing , even in the absence of the other protein activities . Recently , elegant genetic experiments established that E . coli Pol I proofreading activity plays a crucial role in chromosomal replication fidelity [57] . The model put forward by the authors proposes that Pol I performs 1–2% of lagging strand synthesis . They show that inactivation of the 3′ - 5′ exonuclease activity leads to a mutator phenotype with a strong bias towards lagging strand mutations . The mutator phenotype observed in polA strains even in the absence of all three TLS polymerases is also consistent with a proposed role for E . coli Pol I proofreading activity during replication [58] . In the case of H . pylori , despite accurate polymerase activity of Pol I , its lack of proofreading capacity could contribute to mutagenesis during Okazaki fragment processing . In the absence of Pol I DNA polymerase activity , the replicative polymerase is the only candidate to perform lagging strand synthesis . Because of its high fidelity , lower mutation rates are expected . Conversely , over-expression of Pol I can lead to a more extensive processing of Okazaki fragments , therefore increasing the fraction of lagging strand synthesis performed by this enzyme and leading to a higher level of replication error rates . In conclusion , independently of the relative contributions of Pol I to TLS and lagging strand synthesis , the results presented here strongly support the hypothesis by which in H . pylori the loss of proofreading activity of this DNA polymerase has been selected for increasing genome plasticity .
All H . pylori strains used were in the 26695 genetic background [15] . To generate gene-specific mutants , the corresponding open-reading frame ( ORF ) cloned into pILL570 was disrupted , leaving 5′ and 3′ ends ( 300 bp ) of the gene , by a nonpolar kanamycin- ( Km ) , apramycin- ( Apr ) or chloramphenicol ( Cm ) resistance cassette [59] , [60] . To generate the Pol I over-expressing strain , the HP1470 ORF was inserted into pADC vector , downstream of the ureA promoter , as described [61] . Plasmids were introduced into H . pylori strains by natural transformation and recombinants were selected after 3 to 5 days of growth on either 20 µg/ml Km , 12 . 5 µg/ml Apr or 8 µg/ml Cm . Allelic replacement was verified by PCR . As described in the Results section , the polA mutants used correspond , unless specified , to the replacement of the equivalent of the Klenow fragment by the resistance cassette , leaving the 5′ to 3′ exonuclease domain intact . Double mutants were obtained by plasmid or genomic DNA transformation of single mutant or by mixing two mutant strains together before plating the mix on double selection . H . pylori cultures were grown at 37°C under a microaerobic atmosphere on BAB , blood agar base medium supplemented with an antibiotic mix and 10% defibrillated horse blood . For all experiments , H . pylori strains were initially grown for 24 hr on plates with BAB medium . UV , MMS and gamma irradiation sensitivity assays were performed as described [33] , [62] . For chemical oxidative stress treatment , H pylori ( OD600 = 1 ) cell suspensions were incubated with different concentrations of hydrogen peroxide ( 100 , 200 and 300 mM ) . Cells were washed 10 min later , diluted with peptone broth and plated on BAB plates . Survival was determined as the number of cells forming colonies on plates after a given treatment divided by the number of colonies from non-treated cells . Assays to determine spontaneous mutation rates were performed as described [7] . All assays were performed at 37°C for 30 min in 20 µl reactions containing 10 mM Tris-HCl ( pH 7 . 9 ) , 50 mM NaCl , 10 mM MgCl2 , 1 mM Dithiothreitol , 2 . 5 nM DNA substrate ( see Text S1 and Table S1 ) and variable concentrations of Pol I ( specified in the figure legends ) . 0 . 1 mM of either all four dNTPs or each dNTP individually was included in the reactions except for the exonuclease activity assays . When required as a control , Klenow fragment DNA polymerase ( Roche ) was used . Reactions were stopped by adding loading buffer ( 10 mM EDTA , 95% ( v/v ) formamide , 0 . 03% ( w/v ) bromophenol blue , 0 . 03% ( w/v ) xylene cyanol ) and subjected to electrophoresis in 8 M urea-containing 20% polyacrylamide gels . Gels were visualised and quantified using a Molecular Dynamics PhosphorImager . According to Koskoska et al . [63] , bypass probabilities were calculated as the proportion of DNA synthesis products extended beyond the lesion . Bypass efficiencies were then calculated for each enzyme and each substrate as the ratio of the bypass probability of a specific damaged base with respect to that of an undamaged nucleotide in the same position . The assay was performed as described previously [22] . Gap-filling DNA synthesis was performed in a reaction mixture ( 25 µl ) containing 50 mM Tris ( pH 6 . 8 ) , 50 mM NaCl , 10 mM MgCl2 , 1 mM DTT , 0 . 2 mM each of dNTP and 0 . 2 nM of gapped M13mp2 DNA substrate . Reactions were initiated by adding Pol I , incubated at 37°C for 30 min , and terminated by adding EDTA to 20 mM . When DNA products were analyzed by agarose gel electrophoresis [22] , the majority of the gapped molecules were filled to completion . However , a minority of DNA products migrated as if synthesis had paused at the palindrome just upstream of the open reading frame of the LacZ gene . In this minority population , only about 75% of the template used to score errors had been copied . As a consequence , the lacZ mutant frequency observed for the ensemble reaction products may slightly underestimate the error rate of H . pylori Pol I . | Helicobacter pylori is the main cause of ulcers and gastric cancers . One the characteristics of this bacterial species is that it displays an amazing capacity to change its genetic information . This genetic variability provides H . pylori with an adaptation potential that allows it to successfully colonise the stomach of about half the human population . Here we identified a surprising source of genomic plasticity in an enzyme also involved in the maintenance of DNA integrity . Indeed , we show that DNA polymerase I , one of the only two DNA polymerases that are found in H . pylori , although essential for DNA replication and repair , contributes to mutagenesis due to its biochemical characteristics . | [
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The apicomplexans are a large group of parasitic protozoa , many of which are important human and animal pathogens , including Plasmodium falciparum and Toxoplasma gondii . These parasites cause disease only when they replicate , and their replication is critically dependent on the proper assembly of the parasite cytoskeletons during cell division . In addition to their importance in pathogenesis , the apicomplexan parasite cytoskeletons are spectacular structures . Therefore , understanding the cytoskeletal biogenesis of these parasites is important not only for parasitology but also of general interest to broader cell biology . Previously , we found that the basal end of T . gondii contains a novel cytoskeletal assembly , the basal complex , a cytoskeletal compartment constructed in concert with the daughter cortical cytoskeleton during cell division . This study focuses on key events during the biogenesis of the basal complex using high resolution light microscopy , and reveals that daughter basal complexes are established around the duplicated centrioles independently of the structural integrity of the daughter cortical cytoskeleton , and that they are dynamic “caps” at the growing ends of the daughters . Compartmentation and polarization of the basal complex is first revealed at a late stage of cell division upon the recruitment of an EF-hand containing calcium binding protein , TgCentrin2 . This correlates with the constriction of the basal complex , a process that can be artificially induced by increasing cellular calcium concentration . The basal complex is therefore likely to be a new kind of centrin-based contractile apparatus .
The phylum Apicomplexa contains ∼5 , 000 species of obligate intracellular protozoan parasites , many of which are important human or animal pathogens . Toxoplasma gondii is the most common cause of congenital neurological defects in humans , and an agent for devastating opportunistic infections in immunocompromised patients . Plasmodium falciparum , the most lethal form of malaria , kills more than a million people every year . The pathogenesis of the diseases that these parasites cause absolutely depend on their ability to replicate . In the absence of massive , uncontrolled expansion of the parasite population , the infections are benign . Thus , the understanding of parasite growth and division is crucial for developing effective therapies . The apicomplexan parasite cytoskeletons provide the framework for organellar replication and partition , and are essential for parasite survival and replication , therefore are attractive potential drug targets [1–3] . In addition to their importance in pathogenesis , the apicomplexan parasite cytoskeletons are marvelous structures [4–7] . Thus understanding the cytoskeletal biogenesis of these parasites is also of general interest for cell biology . In spite of the diversity in their host species , host selectivity , and the diseases they cause , the apicomplexan parasites share similar basic cell biology . In particular , all apicomplexans are obligate intracellular parasites . Most of them replicate inside a specialized parasitophorous vacuole within the host cell in an unusual process where the daughter cytoskeletons preform de novo prior to cytokinesis [1–3 , 8] . The daughter cytoskeletons contain several distinct sets of microtubules that are likely involved in different aspects of parasite motility and division [7 , 9 , 10]; the Inner Membrane Complex ( IMC ) , formed of flattened vesicles with a regular intramembranous particle lattice likely associated with the cortical microtubules [5 , 11–13]; a set of proteins weakly homologous to intermediate filaments underlying the IMC [2 , 14]; and a cytoskeletal apical complex that is closely associated with the membrane-bound invasion organelles [6 , 15 , 16] . During parasite division , the membrane bound organelles ( including the nucleus , ER , Golgi apparatus , mitochondrion , apicoplast and a collection of secretory organelles such as rhoptries and micronemes ) will be replicated and partitioned into the growing daughter cytoskeletons , until the end of the cytokinesis when the daughters bud out of the mother and take over mother's plasma membrane [1 , 2] . Compared with other compartments of the parasite body , much less was known about the architecture of the basal end of the parasite . We and others found that the basal end of the parasite contains a specialized compartment with distinct morphology and molecular composition [16 , 17] . It is constructed together with the rest of the daughter cytoskeleton , first as ring-like structures capping the growing ends of the daughters , which then constrict and eventually cap the basal pole of the adult parasite . Because of its distinct localization , organization and molecular composition , we used the term “basal complex” to represent this distinct compartment [16] . In adult parasites , the basal complex occupies the basal gap of the IMC , which , together with the underlying filamentous network , encloses the entire parasite body except for the extreme apical and basal ends ( Figure 1A and 1B ) ( the gap at the apical end of IMC is occupied by the cytoskeletal apical complex , an intricate assembly that includes the conoid , a tubulin-based molecular machine that does not utilize conventional microtubules; three polar rings; and two intra-conoid microtubules [Figure 1A and 1C] [6 , 7] ) . The basal complex is separated by more than 1 . 5 μm from another set of major cytoskeletal elements , the cortical microtubules , which emanate from the most posterior of the three polar rings and extend ∼2/3 of the length of the parasite body ( Figure 1A and 1C ) . The basal complex contains several distinguishable regions organized along its anterior-posterior axis , and is composed of substructures defined by different protein markers , including TgMORN1 , TgCentrin2 and TgDLC , a dynein light chain of T . gondii [16] . Interestingly , these basal complex proteins are also components of the apical complex and the centriole/spindle pole assembly ( Figure 1A–1D ) . The similarity in protein composition among these structurally and spatially distinct cytoskeletal assemblies is particularly intriguing given the de novo nature of the construction of the apical and the basal complex , because the centriole/spindle pole assembly are the only structures inherited by the daughter parasites during cell division , and the centrioles are the only cytoskeletal structure in T . gondii that can self-replicate , thus capable of propagating the structural information for building a new cytoskeleton to the daughters . Much of this study therefore focuses on the spatial-temporal coordination among the origination of the basal complex , the duplication of the centriole/spindle pole assembly , and the construction of the daughter cortical cytoskeleton . ( Throughout this paper , “the cortical cytoskeleton” is used to refer to the entire framework of cytoskeleton elements that aligns the parasite body [i . e . cortical microtubules , the IMC and the filamentous network underlying the IMC] except for the apical and the basal complexes [Figure 1A] ) . The basal complex is a new defining feature of T . gondii , and likely to be conserved in other important apicomplexan parasites [16 , 17] . To understand how this compartment comes into being and develops with the rest of the daughter cytoskeleton is crucial for elucidating how polarity is established in these parasites . It should be noted that the daughter cytoskeletons are built afresh , and the mother's body axis is apparently not used in the polarity determination of the daughters , since each daughter axis is more or less randomly oriented with respect to the mother and the other daughter [1 , 2] . Due to the limited spatial and temporal resolution of previous studies , and the fact that appropriate specific markers were not known , the precise sites and timing of basal complex initiation and maturation are not known . This study focuses on the key organizational changes of the daughter basal complex with respect to the centriole replication cycle as well as the maturation of the daughter parasite cortical cytoskeleton using high resolution wide-field deconvolution light microscopy . It reveals that the daughter basal complex is initiated in the vicinity of the centrioles before the establishment of the daughter cortical cytoskeleton , and that its initiation and construction are likely to be independent of the structural integrity of the daughter cortical cytoskeleton . The constriction of the basal complex that begins at a late stage of cell division correlates with the recruitment of a typical EF-hand containing calcium binding protein , TgCentrin2 , to its posterior compartment , which reveals the compartmentation and polarity of the basal complex in the developing daughter . Further , this constriction can be artificially induced by elevated intracellular calcium concentration . The timing of the recruitment , the localization , and the molecular characteristics of TgCentrin2 make it the most plausible candidate for driving the constriction of the basal complex during its maturation , and the basal complex in T . gondii is likely to be a new kind of centrin-based contractile apparatus .
Two previously identified basal complex components in T . gondii , TgMORN1 and TgCentrin2 [16] , occupy two distinct compartments in the basal complex of mature parasites . The TgMORN1 compartment is shaped into a cone that forms the main body of the basal complex ( Figure 1A–1E ) , whereas TgCentrin2 is concentrated at the posterior tip of the basal complex ( Figure 1D and 1F ) . Both TgCentrin2 and TgMORN1 are also components of the apical complex . In addition , they are localized to the spindle pole and the centrioles , respectively . The spindle pole and the centrioles are juxtaposed to each other during interphase ( Figure 1B–1D ) , but well separated after the daughter cortical cytoskeletons have formed in the mother [7 , 16 , 18 , 19] ( The slight displacement between the spindle pole and the centrioles in each interphase cell is a true spatial displacement , not an artifact of mis-registration induced by lens chromatic aberration or optical misalignment between the GFP and mCherryFP filters , because the shift between the red and green fluorescence of a multi-color 0 . 2 μm bead is clearly much smaller and below the resolution limit of the microscope [Figure S1] ) . The first sign of cell division is the migration of the centriole to the basal pole of the nucleus , where it replicates ( Nishi M , Hu K , Murray J , Roos D , manuscript submitted ) . The replicated centrioles sandwich the spindle pole ( Figure 2 ) , which at this point still appears as one spot . Surprisingly , ring structures containing TgMORN1 are observed forming around the duplicated centrioles even before the separation of the future apical and basal regions of the daughter parasites ( Figure 3 ) . These rings are at the outer edges of the initially planar aggregations of daughter cytoskeletal elements that will later become the daughter cortical cytoskeletons ( Figure 4 ) . The TgMORN1 rings are therefore likely to be the precursor of the future daughter basal ring complex . Two other components of the mature basal complex in adult parasites , TgCentrin2 ( Figure 3B ) and TgDLC ( data not shown ) , however , are not found in these early ring structures . How do these ring structures originate ? Will they really become the basal complex in the daughters ? To address these questions , I followed TgMORN1 distribution together with the daughter cortical cytoskeleton construction and centriole duplication in live parasites expressing EGFP-TgMORN1 and mCherryFP-Tg α1-tubulin ( TgTubA1 ) ( Figure 5; Video S1 ) . The TgMORN1 ring first appears as small extra masses outside the spindle pole , and is located close to the recently duplicated centrioles , which lie on each side of the spindle poles ( t = 10 min ) . 20–30 min later ( t = 30–40 min ) , the fluorescence of mCherryFP-TgTubA1 in the centriole spot increases , likely correlated with the initial assembly of the conoid in the apical complex , of which TgTubA1 is a major component . At this point , the ring-like nature of the TgMORN1 containing structure becomes apparent , and it is centered around the centriole/conoid mass ( t = 40 min ) . At t = 60 min , the centriole/conoid assemblies move apically above the plane of the TgMORN1 ring with the extension of the cortical microtubules , and the recruitment of TgMORN1 to the apical complex becomes clear . At this point the future apical and basal complexes are separated far enough to make it clear that the TgMORN1 rings formed at the beginning of the cell division are indeed precursors of the daughter basal complexes . The TgMORN1 rings remain at the basal ends of the daughter cortical cytoskeletons as the daughters grow ( t = 70–110 min ) . How is the basal complex able to remain at the constantly growing ends of the daughter cortical cytoskeletons ? Studies in mammalian cells have shown that microtubule plus-end ( MT-plus-end ) binding proteins probably maintain their position at the growing ends of microtubules by rapid association and dissociation [20] . Fluorescence Recovery After Photobleaching ( FRAP ) analysis of daughter basal complexes in T . gondii reveals constant protein exchange between the daughter basal complex and the cytoplasm ( Figure 6 ) . Although it is difficult to calculate an exact t1/2 for the fluorescence recovery because of the noise introduced by constant fluctuation of the basal complex position due to daughter cell movement , the recovery is clearly underway by ∼90 sec after photobleaching . This result indicates that the basal complex is intrinsically a dynamic “cap” , thus suggesting a mechanism similar to microtubule association of MT-plus-end binding protein is possibly involved in retaining the basal complex at the growing ends of the daughter cortical cytoskeletons . However , the growth of the daughter cortical cytoskeleton is likely not to be the pre-requisite for the protein exchange in the basal complex , as the fluorescence in the mature basal complex also partially recovers after photobleaching ( Figure S2 ) . The daughter cortical cytoskeleton and the basal complex appear to grow in concert during cell division . Is the construction and growth of the basal complex , a seemingly “downstream” structure , dependent on the structural integrity of the daughter cortical cytoskeleton ? To address this question , the construction of the basal complex was tracked in living parasites whose cortical microtubule extension and the daughter cortical cytoskeleton formation were severely disrupted by treating with oryzalin , a plant herbicide that binds to T . gondii α-tubulin and inhibits the construction of the spindle and the cortical microtubules , but not the centriole replication , during daughter formation ( Figure 7; Video S2 ) [9 , 10 , 21] . As expected , the mother's conoid , cortical microtubules , and basal complex are not affected by the oryzalin treatment , and the overall morphology of the mother cell remains normal until the distorted daughters attempt to bud . Daughter cortical microtubules , however , completely fail to appear . Despite the inhibition of the formation of functional daughter cortical cytoskeleton , the initiation of TgMORN1 ring formation proceeds normally ( Video S2 , 33 and 48 min ) . Furthermore , complete TgMORN1 rings are formed ∼30 min after the initiation ( Video S2; Figure 7 , t = 60 min ) , enlarge to ∼1 . 2 μm ( similar to the diameter of the basal complex in untreated daughters with extending cortical cytoskeletons [cf . Figure 5 , t = 70 min] ) , and retain their ring morphology till “budding” , at which point the organization of the basal complex becomes unclear due to the distorted parasite morphology . The initiation , construction and maintenance of the daughter basal ring complex are therefore independent of the structural integrity of the daughter cortical cytoskeleton . The organization of a growing daughter ring complex is quite different from the basal complex of an adult parasite . The basal complex of growing daughters is an annulus without any clear polarity ( e . g . Figure 5 , t = 70–110 min ) . The mature basal complex in adult parasite , however , is a conical structure , closed at one end , compartmentalized , and stratified along its anterior-posterior axis ( cf . Figure 1 ) . When is the polarity and compartmentation of the basal complex established ? The basal complex starts to constrict before cytokinesis and the constriction continues after cytokinesis when the daughters take over the mother's plasma membrane , thus closing the basal cap in the mature parasite ( cf . Video S1 ) [16 , 17] . Because TgCentrin2 resides in only the most constricted region of the basal complex in the adult parasite ( cf . Figure 1D ) , I investigated the relationships among the recruitment of TgCentrin2 , the constriction of the basal complex and the establishment of the polarity of the basal complex , by examining TgCentrin2 localization at several different stages of cell division . Interestingly , although TgCentrin2 is hardly detectable in the basal ring complex earlier during cell division ( cf . Figure 3B and Figure S3 ) , it is clearly localized to the daughter basal complex as a ring at a late stage when the daughter basal complex appears to be constricted ( Figure 8A ) . Its ring-like localization in the basal complex is also pronounced during cytokinesis when the daughters start to take over mother's plasma membrane ( Figure 8B ) , and after cytokinesis when the basal complex is still open at both ends ( Figure 8C ) . In all cases , the TgCentrin2 basal ring is located to the posterior of the TgMORN1 ring ( Figures 8 and 9 ) . The compartmentation and polarization of the basal complex are thus revealed upon the recruitment of TgCentrin2 prior to the closure of the basal complex . Like the TgMORN1 compartment , the TgCentrin2 basal compartment also undergoes significant constriction , from a ∼1 . 0 μm ring to a diffraction limited spot ( Figures 8 and 9 ) . Consistent with the involvement of centrin homologs in calcium sensitive contractile apparatus in other systems [22–24] , the constriction of the TgCentrin2 basal compartment can be artificially induced in daughter parasites at a late stage of cell division when the intracellular calcium concentration is elevated by treatment with calcium ionophore , A23187 ( Figure 10; Video S3 ) .
The results in this study clearly show that although the basal ring complex later becomes the distal end of the daughter cortical cytoskeletons , it is one of the first cytoskeletal structures assembled rather than the last . In addition , the daughter cortical cytoskeleton is unlikely to provide a structural base or template for the initiation of the basal complex , as the initial construction of the basal complex is largely unaffected when the cortical microtubule construction and the structural integrity of daughter IMC complex is abolished by oryzalin treatment . How is a macromolecular assembly like the basal complex built from scratch ? Although untemplated de novo assembly of huge macromolecular assemblies certainly can occur ( e . g . , T4 phage or other large viral particles ) , templated construction proceeding from an inherited “seed” seems to be the rule for most large structures in eukaryotes . Interestingly , the initiation of the basal complex spatially and temporally coincides with the replication of the self-duplicating cytoskeletal organelle- the centrioles , which makes the centrioles a particularly attractive candidate for providing the structural information to initiate the de novo assembly of the basal complex . However , it is also clear that the centriole itself is unlikely to be continuously responsible for the maintenance of the basal ring complex , as the diameters of the rings grow up to 1 μm , much larger than the size of the centrioles while they still surround the centrioles at an early stage of cell division . Thus if the centrioles play a role in the initiation and construction of the basal ring complex , other structures associated with it probably serve as intermediary . Future high resolution EM experiments will be essential to elucidate structural connections between the centrioles and the basal ring complex . TgMORN1 sometimes is seen to form long fibers in the cytoplasm , suggesting that this protein might have the propensity of interacting with itself and possibly form polymeric structures [16] . It is thus conceivable that the basal ring structure could be a product from a TgMORN1 polymer constrained into a ring form through its interaction with other proteins in the basal complex and/or the IMC . This , of course , is an extremely crude guess based on the scanty experimental data available . The final answer to this question will have to come from in vitro reconstitution experiments after we know enough about the protein composition and protein-protein interactions within the basal complex . Compared with that in daughter parasites under construction , the basal complex of fully mature parasites has constricted by ∼30%–40% . Much of the constriction occurs during the post-cytokinesis phase , as the basal complex is still a ∼1 μm ring when the cytokinesis has completed ( As a reference , the diameter of the mother mitochondria is around 0 . 3–0 . 4 μm [25–27] ) . What drives this constriction ? Actin/myosin containing contractile rings drive the cytokinesis of mammalian cells and yeast . However , although a type XIV Myosin , TgMyoC , was found in the basal complex [28] , so far available evidence does not support the involvement of the actin-myosin apparatus in basal complex constriction , as Gubbels et al . reported that cytochalasin D treatment did not seem to affect the TgMORN1 distribution [17] . A family of EF-hand containing calcium binding proteins , the centrins , underlie another type of contractile apparatus: calcium-sensitive contractile fibers associated with the algal flagella and basal body apparatus [22–24 , 29 , 30] . In this study , I found that TgCentrin2 , one of the four centrin homologs in T . gondii , is recruited to a ring structure at the basal end of the daughter parasites before the onset of cytokinesis , and shrinks to a small spot at the basal tip of the adult parasites . The focused localization of TgCentrin2 at the distal portion of the basal complex also correlates with greater constriction of this region in the adult parasites . Furthermore , a treatment that elevates the intracellular calcium level induces the constriction of the TgCentrin2 basal ring . TgCentrin2 also contains multiple potential phosphorylation sites in its EF hand domains , which could be the key in regulating this contraction process , as centrin dephosphorylation accompanies calcium-flux induced centrin-fiber contraction in algae [31] . TgCentrin2 , therefore , is recruited at the right time , to the right place , and possesses the right molecular characteristics to drive the closure of the basal complex at its posterior end during its maturation . Future experiments exploring conditions affecting the assembly and function of centrin contractile fiber , such as proton concentrations , and other intracellular signals will be crucial to test the role of TgCentrin2 in the basal complex constriction . The basal complex migrates distally away from the apical end of the daughter parasite as the daughter cortical cytoskeleton grows . There are at least two phases to this movement . Before cytokinesis , the basal complex lies at the ends of both the daughter IMC and the cortical microtubules . After cytokinesis , however , it migrates further distally and becomes clearly separated from the cortical microtubules . Therefore although it is plausible that the directional growth of cortical microtubules drives the movement of the basal complex away from the apical pole of the growing daughter before cytokinesis [17] , there is not yet any evidence to suggest a causal relationship between the basal complex distal migration and cortical microtubule growth , and the later distal movement of the basal complex during post-cytokinesis growth of the newly emerged parasites is clearly independent of microtubule growth . On the other hand , the distal migration of the basal complex is in synchrony with the growth of the IMC complex throughout the daughter construction , the directional growth of the IMC complex ( the mechanism of which is yet to be elucidated ) is therefore more likely to act as the driving force for the daughter basal complex migration . To summarize , the daughter basal complex in T . gondii is initiated close to the duplicated centrioles , and its construction is independent of the structural integrity of the daughter cortical cytoskeleton . The daughter basal complex is a dynamic cap , whose compartmentation and polarity is revealed upon the recruitment of TgCentrin2 to its posterior end during late stages of cell division . The stage specific recruitment of TgCentrin2 , its localization to the most constricted region of the basal complex , and the calcium sensitive nature of the basal complex contraction make TgCentrin2 an attractive candidate for driving the closure of the basal complex , which thus is likely to be a new centrin-based contractile apparatus . This study extends our knowledge of the origination , dynamics and coordination of the growth of distinct compartments in the daughter cytoskeletons of T . gondii . These issues are not only important for understanding , and eventually manipulating the cell biology of the apicomplexan parasites , but also of interest to the cell biology field in general , where the rules for the construction of macromolecular assemblies and polarity determination are hotly sought after .
T . gondii tachyzoites ( strain RH ) were cultivated in human foreskin fibroblast ( HFF ) cells , and transfected as previously described [32] . For each transfection , 1/3 of the RH parasites from a T12 . 5 flask culture ( ∼1 × 107 ) were transfected by electroporation with 30 μg of plasmid DNA and allowed to infect a fresh monolayer of host cells . EGFP-TgCentrin2 , EGFP-TgIMC4 , EGFP-TgMORN1 expressing parasites are clonal stable transgenic cell lines , and were cultured with 1μM pyrimethamine selection [16] . pmin-mCherryFP-TgMORN1 was constructed by replacing the TgDLC/BglII-AflII fragment in pmin-mCherryFP-TgDLC with the TgMORN1 BglII-AflII fragment from pmin-EGFP-TgMORN1 [16] . pmin-mCherryFP-TgDLC was constructed by replacing the EGFP/NheI-BglII fragment in pmin-EGFP-TgDLC [16] with mCherryFP/NheI-BglII fragment from ptub-mCherryFP-EGFP . The architectures of all pmin-XFP-TgGeneX plasmids are identical . ptub-mCherryFP-EGFP and ptub-mCherryFP-TgtubA1 were kind gifts from Dr John Murray at University of Pennsylvania . Fixed cells were prepared and observed as previously described [2 , 16 , 33] . Mouse monoclonal antibody anti-IMC1 was a kind gift from Dr . Gary Ward ( University of Vermont ) and it was detected with secondary antibody goat anti-mouse IgG Alexa350 ( #A21049 , Invitrogen-Molecular Probes , 1:1000 dilution ) . For live-cell imaging and time-lapse microscopy , parasites were inoculated into a sub-confluent layer of HFF cells grown in phenol red free DMEM ( #21063 , Invitrogen-Gibco ) with 10% heat-inactivated bovine calf serum in a 35mm plastic dish with #1 . 5 glass coverslip bottom ( MatTek #P35G-1 . 5–14-C , MatTek #P35G-1 . 5–20-C ) . After infection , the medium was changed to DMEM+1% heat-inactivated Fetal Bovine Serum ( FBS ) . Immediately before imaging , the medium was changed to phenol red free CO2 independent medium ( custom order , SKU#: RR050058 , Invitrogen-Gibco ) with 10%FBS and 2mM glutamine ( #25030 , Invitrogen-Gibco ) , 1mM sodium pyruvate ( #11360 , Invitrogen-Gibco ) and 100unit/ml antibiotics and antimycotics ( #1172 , Invitrogen-Gibco ) . The dish was then equilibrated in the humidified microscope environmental chamber [34] for 1–2 hours before imaging . 3D image stacks were collected at z-increments of 0 . 3 μm ( fixed samples ) , or 0 . 3–0 . 5 μm ( live samples ) on an Applied Precision Delta Vision workstation based on an Olympus IX-70 inverted microscope , using a 100× NA 1 . 35 oil immersion lens with immersion oils at refractive indexes of 1 . 524 ( 37°C , ambient humidity ) , 1 . 522 ( 37°C , 70% humidity in the chamber ) , or 1 . 518 ( room temperature , ambient humidity ) . Sedat Quad- ET ( #89000 , Chroma Technology Corp . ) and GFP/mCherry-ET ( #89021 , Chroma Technology Corp . ) filter sets were used for all the imaging in this paper . For estimating mis-registration induced by lens chromatic aberration or optical misalignment between the GFP and mCherryFP filters , 0 . 2 μm Tetraspeck beads ( #T7280 , Invitrogen-Molecular Probes ) attached to a #1 . 5 coverslip were mounted to a slide with a 0 . 12mm spacer ( #S24735 , Invitrogen-Molecular Probes ) in dH2O and imaged at 37°C with the GFP/mCherry ET filter set , using 100× NA 1 . 35 oil immersion lens and immersion oil at refractive index of 1 . 522 . Deconvolved images were computed using the point-spread functions and software supplied by the manufacturer . All fluorescent images in the figures , except for the gray scale images in Figure 6 and Figure S2 , are maximum intensity projections of deconvolved 3D stacks . The gray scale images in Figure 6 and Figure S2 are non-deconvolved single optical planes . The brightness and contrast of images used in the final figures were optimized for color prints . To avoid confusion , a consistent coloring for each T . gondii protein has been adopted throughout the remainder of this paper . This pseudo-color assignment will be maintained regardless of the actual wavelength bands used for detections of fluorescence . TgMORN1 is always colored green , IMC1 is always colored blue , and other molecules are always colored red . FRAP experiments were performed on the same imaging system equipped with a 10mW 488 laser connected to the microscope via a fiber optic . The laser was run at 50% power , using one 50 msec pulse for photobleaching . Pre and post bleaching images were collected using the Photokinetics module integrated in the Applied Precision Softworx software . About 3 × 107 transgenic parasites ( harvested from one T12 . 5 flask culture ) expressing EGFP-TgCentrin2 or EGFP-TgMORN1 were washed , resuspended in 15 μl DPBS ( #14190 , Invitrogen-Gibco ) and absorbed to nickel grids ( 5 μl parasite suspension/grid ) at room temperature for 1 hour . Parasites were then permeabilized in 0 . 5% TritonX-100 in DPBS for 20–25 min , and fixed for 15 min with 3 . 7% formaldehyde in DPBS , and washed 3 × 5 min with DPBS , followed by 10-min blocking in 5% BSA + 0 . 1% fish gelatin . Free aldehyde groups were blocked by incubation with 50mM glycine in DPBS for 15 min ( pH 7 . 5 ) followed by 15-min incubation with 0 . 1% NaBH4 in DPBS . Grids were washed twice with DPBS; blocked again with 5% BSA + 0 . 1% fish gelatin in DPBS for 30 min; washed 2 × 5 min with incubation buffer ( 0 . 8%BSA , 0 . 1% fish gelatin in DPBS plus 10mM NaN3 ) ; incubated for ∼2 h with primary antibody at room temperature by inverting the grids on 20 μl drops of primary antibody ( #A11122 , rabbit anti-GFP polyclonal , Invitrogen-Molecular Probes , diluted 1:800 in incubation buffer ) ; washed 6 × 5 min in incubation buffer; inverted on 15 μl drops of secondary antibody solutions ( anti-rabbit IgG conjugated with 1 . 4 nm gold , Nanoprobes , Yaphank , New York , United States , diluted 1:160 in incubation buffer ) and incubated for ∼19 h at 4 °C; then washed with incubation buffer as follows: 3 × 1 min , 2 × 10 min , 4 × 5 min; and finally washed 5 × 1 min with DPBS . The samples were then post-fixed 5 min with 1% glutaraldehyde in DPBS and washed with distilled water 3 × 5 min . Silver enhancement was carried out using the HQ silver enhancement kit ( Nanoprobes ) by floating grids on mixtures of the initiator , activator , and modulator for 2 min in a light-tight chamber , then washing briefly with dH2O once , followed by 2 × 5 min wash . Grids were negatively stained using 2% phosphotungstic acid ( pH 7 . 0 ) . After taking a set of pretreatment images , 0 . 625 μl 10mM oryzalin diluted in 500 μl CO2 independent medium with 10% FBS ( prewarmed to 37°C in the imaging chamber ) was added immediately to the dish containing 2 . 0 ml medium on the microscope stage . The final concentration of oryzalin was 2 . 5 μM . Imaging of the drug treated parasites started ∼30 min after the addition of oryzalin and continued for 10–12 hours . A23187 treatment experiments were conducted under both 37°C and room temperature conditions , which yielded similar results . The induction of the basal complex constriction however occurred much faster at 37°C , which made it difficult to capture the intermediate images . The result from a room temperature experiment was thus used for this paper ( Figure 10 ) . After taking a set of pretreatment images , 0 . 85 μl 5mM A23187 ( dissolved in DMSO ) diluted in 220 μl CO2 independent medium with 10% FBS was added to the dish containing 1 . 5 ml medium on the microscope stage , which gave a final concentration of A23187 at ∼2 . 5μM . After ∼3 . 5 minutes , additional 1 . 15 μl 5mM A23187 ( dissolved in DMSO ) diluted in 280 μl CO2 independent medium with 10% FBS was added to the dish , which gave a final concentration of A23187 at ∼5μM , and DMSO concentration at ∼0 . 1% . Images were taken at 15 second intervals for the first 105 seconds of acquisition and at ∼30 second intervals for the rest of the experiment . The free calcium concentration in CO2 independent medium +10%FBS was ∼3 . 5mM , determined by Eriochrome Black T dye assay described below . To 1 . 0 ml ammonia buffer ( 0 . 0214% NH4CL+ 0 . 73%NH4OH in dH2O ) , 5 μl Eriochrome Black Dye solution ( 0 . 25% Eriochrome Black T and 2 . 26% hydroxylamine hydrochloride ( NH2OH-HCL ) in dH2O ) was added . 1 . 0 ml of CO2 independent medium +10%FBS was then added to the mixture , which turned the blue-green solution to purple . After adding 35 μl 0 . 1M K2EGTA drop-wise to the solution , the purple color turned back to blue-green due to the chelation of the free calcium by K2EGTA , revealing that there was ∼3 . 5mM free calcium in CO2 independent medium +10%FBS . The result was confirmed by titrating 1 ml 3 . 5mM CaCl2 with 0 . 1M K2EGTA using the same procedure .
List of Tigr_final numbers for genes and proteins mentioned in the text are: TgMORN1 ( 583 . m05359 ) ; TgCentrin2 ( 50 . m03356 ) ; TgCentrin1 ( 50 . m00033 ) ; T . gondii α1 –tubulin ( TgTubA1; 583 . m00022 ) ; TgIMC4 ( 44 . m00031 ) ; T . gondii dynein light chain ( TgDLC; 41 . m01383 ) . The sequences are available for downloading at http://www . toxodb . org/toxo/ . | Toxoplasma gondii is one of the most prevalent parasites in warm-blooded animals and a highly important human pathogen . It is the most common cause of congenital neurological defects in humans and also causes devastating opportunistic infections in immuno-compromised patients . Many of its 5 , 000 relatives in phylum Apicomplexa are also important human or animal pathogens , including Plasmodium sps , which kill more than a million people every year . The pathogenesis of the diseases that these parasites cause absolutely depend on their ability to replicate , which in turn completely depends on the proper assembly of the parasite cytoskeletons . Here I probe how the basal complex , a novel cytoskeletal compartment contained within the basal end of T . gondii , is assembled during daughter cell formation of this parasite . I found that the daughter basal complex is one of the first cytoskeletal structures assembled during T . gondii cell division . In addition , the basal complex is likely to be a new kind of centrin-based contractile apparatus , as its polarization is first revealed upon the recruitment of a calcium binding protein , TgCentrin2 , which correlates with the constriction of the basal complex , a process that can be artificially induced by increasing cellular calcium concentration . | [
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] | 2008 | Organizational Changes of the Daughter Basal Complex during the Parasite Replication of Toxoplasma gondii |
The recent emergence of artemisinin resistance in the Greater Mekong Subregion poses a major threat to the global effort to control malaria . Tracking the spread and evolution of artemisinin-resistant parasites is critical in aiding efforts to contain the spread of resistance . A total of 417 patient samples from the year 2007 , collected during malaria surveillance studies across ten provinces in Thailand , were genotyped for the candidate Plasmodium falciparum molecular marker of artemisinin resistance K13 . Parasite genotypes were examined for K13 propeller mutations associated with artemisinin resistance , signatures of positive selection , and for evidence of whether artemisinin-resistant alleles arose independently across Thailand . A total of seven K13 mutant alleles were found ( N458Y , R539T , E556D , P574L , R575K , C580Y , S621F ) . Notably , the R575K and S621F mutations have previously not been reported in Thailand . The most prevalent artemisinin resistance-associated K13 mutation , C580Y , carried two distinct haplotype profiles that were separated based on geography , along the Thai-Cambodia and Thai-Myanmar borders . It appears these two haplotypes may have independent evolutionary origins . In summary , parasites with K13 propeller mutations associated with artemisinin resistance were widely present along the Thai-Cambodia and Thai-Myanmar borders prior to the implementation of the artemisinin resistance containment project in the region .
Artemisinin combination therapy ( ACT ) has been adopted globally as the first-line treatment for uncomplicated Plasmodium falciparum malaria and has contributed to the reduction in malaria related mortality and morbidity . However , resistance to artemisinin poses a threat to the global effort to control malaria . In 2008–2009 the first verified cases of artemisinin resistance , characterized by delayed parasite clearance , were observed in western Cambodia [1] . Prior to those cases , instances of reduced parasite susceptibility to artemisinin were reported in parts of Thailand bordering Cambodia ( Chantaburi , Trat , Sakaew , Sisaket , Burirum , and Surin provinces ) and Myanmar ( Tak province ) as early as 2003 [2] . The Thai-Cambodian border region has historically been the epicenter of multi-drug resistant ( MDR ) malaria [3] . As resistance to earlier anti-malarial drugs spread from this region to Africa and other parts of Asia through parasite migration , there is a serious concern that a similar scenario may occur with artemisinin resistance [4] . The ACT artesunate-mefloquine ( ASMQ ) has been used as first-line therapy in Thailand since 1995 , beginning in areas where multi-drug resistance had evolved . Use of ASMQ was extended to the rest of the country after the World Health Organization ( WHO ) recommended ACT for global use in the early 2000s [5] . In Thailand , ASMQ was initially introduced as a two-day regimen and in 2008 was extended to three days ( three days of artesunate and two days of mefloquine , but with the same total dose as the two-day regimen ) [6] . The ASMQ regimen has remained generally effective in Thailand despite high levels of mefloquine resistance with a cure rate of greater than 90% [5] . However , in several locations in Cambodia and Thailand , treatment failure rates over 10% have also been observed [7] . To date , the strongest evidence of artemisinin resistance was initially reported in western Cambodia , and subsequently other parts of Southeast Asia [1 , 7–13] . To prevent the spread of artemisinin-resistant P . falciparum , the WHO and other partners initiated an artemisinin resistance containment project for the Greater Mekong Subregion in 2009 [14] . The goal was to identify and prevent artemisinin-resistant parasites from spreading outside of documented hotspot regions along the Thai-Cambodian border by ensuring proper diagnosis and full treatment of reported malaria cases [15] . Subsequently , the WHO , along with other partners , initiated the Global Plan for Artemisinin Resistance Containment and Emergency Response to artemisinin resistance in the Greater Mekong Subregion [5] . Currently , therapeutic efficacy studies ( TES ) are considered the gold standard for determining antimalarial drug efficacy [16] . However , the WHO recommends that TES results be complimented using molecular marker studies [17] . Therefore , it was desirable to identify a molecular marker for artemisinin resistance . Initial studies using a genome-wide association approach found two loci on P . falciparum chromosomes 10 and 13 to be associated with artemisinin resistance [12 , 18] . After a long search to pinpoint a specific gene associated with artemisinin resistance , the K13 gene ( PF3D7_1343700 ) on chromosome 13 was identified as a potential molecular marker [19] . The study identified mutations in the propeller domain of the K13 gene that were associated with artemisinin resistance as measured by ex vivo ring stage survival assays and delayed parasite clearance times [19] . Specifically , the study identified 18 non-synonymous single nucleotide polymorphisms ( SNPs ) in the K13 propeller domain , of which three mutations ( C580Y , R539T and Y493H ) were strongly associated with increased ring stage survival and delayed parasite clearance rates . The C580Y allele accounted for about 85% of all mutant K13 alleles observed in 2011–2012 in western Cambodia [19] . Most recently , a two year multi-site project by Ashley et al . further confirmed that multiple SNPs in the propeller domain of K13 were predictive of slow parasite clearance and that these mutations were found in multiple countries in the Greater Mekong Subregion [20] . That study , along with two other recent studies by Takala-Harrison et al . and Miotto et al . [13 , 21] , showed that the C580Y allele was the predominant allele in Cambodia , Myanmar , and Vietnam . The authors further demonstrated that the C580Y allele may have emerged independently in Cambodia and Myanmar . Although Thailand has historically been an epicenter of resistance to several antimalarial drugs , currently there are limited data on the artemisinin resistance-associated K13 propeller mutations in this region . Here , using historical samples collected during 2007 from ten different sites in Thailand , we set forth to answer the following questions: ( 1 ) Were artemisinin resistance-associated K13 mutant alleles present in Thailand prior to the implementation of the artemisinin resistance containment projects ? ( 2 ) If so , what were the prevalence and distribution of the K13 propeller mutations in Thailand ? ( 3 ) What are the evolutionary histories of the different K13 mutant and wild type alleles ? ( 4 ) Are the K13 mutant alleles evolving locally or are particular mutants spreading across Thailand ? and ( 5 ) Is there evidence for selection of resistant K13 alleles ?
All 417 patient samples were either wild type or had a single mutation in the K13 propeller domain . Twelve percent ( 50/417 ) carried one of seven mutant alleles ( N458Y , R539T , E556D , P574L , R575K , C580Y , S621F ) in the K13 propeller domain , including two mutations ( R575K and S621F ) that have not been reported previously in Thailand . The C580Y mutant allele , which is a predominant allele in Cambodia , accounted for 52% ( 26/50 ) of all mutant alleles identified in our study population . The C580Y allele frequencies were higher along the Thai-Cambodian border , in Chanthaburi ( N = 5/10 , 50% C580Y ) , Trat ( N = 5/12 , 42% C580Y ) , and Sisaket ( N = 8/13 , 62% C580Y ) provinces compared to the provinces along the Thai-Myanmar border , Chumporn ( N = 2/12 , 17% C580Y ) , Ranong ( N = 3/40 , 8% C580Y ) , Kanchanaburi ( N = 6/40 , 15% C580Y ) , and Tak ( N = 1/171 , 1% C580Y ) . Interestingly , the R539T alleles were only found in eastern Thailand near the Cambodian border in Trat ( N = 1/12 , 8% R539T ) and Sisaket ( N = 2/13 , 16% R539T ) provinces . Besides the C580Y mutation , four previously identified mutations ( R575K , P574L , E556D , and N458Y ) as well as one novel K13 propeller allele not reported yet ( S621F ) , were found in western parts of Thailand . The R575K and S621F alleles were only present along the Thai-Myanmar border in Prachuap ( N = 6/33 , 18% R575K ) , Kanchanaburi ( N = 4/40 , 10% R575K ) , and Tak ( N = 1/132 , 1% S621F ) , provinces . The P574L allele was present in Ranong ( N = 4/40 , 10% ) , followed by 8% ( N = 1/12 ) prevalence in Chumporn and 3% ( N = 1/33 ) in Prachuap . All parasite isolates from the northwestern province of Mae Hong Son ( N = 42/42 ) and southeastern province of Yala ( N = 40/40 ) carried the wild type K13 propeller allele . Overall , these results show the presence of parasites harboring single non-synonymous mutations in the K13 propeller domain as early as 2007 in eight Thai provinces ( Fig 1 ) . Microsatellites flanking K13 were used to infer the evolutionary histories of the C580Y alleles . Parasites with the C580Y alleles from eastern and western Thailand shared a similar genetic profile in most loci , with the exception of the 8 . 6kb locus downstream of the gene ( Fig 2 ) . This microsatellite locus clearly separates the C580Y alleles based on geography ( east versus west ) . Moreover , the C580Y alleles in the eastern region had a 194 bp allele size at locus 31 . 5kb , whereas in the western Thailand most of the C580Y alleles had a 198 bp allele size with the exception of three isolates ( Fig 2 ) . In addition , there is a high degree of microsatellite identity among infections with the C580Y allele as compared to the wild type K13 haplotypes both upstream and downstream from K13 ( S1 Dataset ) . Using the nine microsatellite loci flanking the K13 propeller gene , expected heterozygosity ( He ) was calculated for the C580Y and wild type alleles ( Fig 3 ) . The N458Y , R539T , P574L , R575K and S621F alleles were excluded as there were limited samples to carry out the analysis . The C580Y allele ( N = 26 , mean He = 0 . 3526 ± 0 . 08 ) showed a 56% reduction ( p = 0 . 0046 ) in heterozygosity as compared to wild type alleles ( N = 22 , mean He = 0 . 6246 ± 0 . 06 ) ( Fig 3A ) . No significant difference ( p = 0 . 2240 ) in heterozygosity was found when comparing western C580Y alleles ( N = 10 , mean He = 0 . 4360 ± 0 . 03 ) to eastern C580Y alleles ( N = 15 , mean He = 0 . 2755 ± 0 . 05 ) ( Fig 3B ) . Mean He between the wild type and different mutant alleles were compared using the Mann-Whitney U test . The results of the principal component analysis of the neutral and flanking microsatellite data for the C580Y mutants and wild type isolates are plotted in Fig 4 . When considering the flanking microsatellite data for all C580Y mutants , the first principal component separated the isolates into those from the western ( Kanchanaburi , Ranong , and Chumporn ) and eastern ( Chanthanburi , Trat , and Sisaket ) provinces ( Fig 4A ) , with the exception of a single isolate . No clear geographical separation is observed when looking at the flanking K13 microsatellites in the wild type population ( Fig 4B ) . Interestingly , some of the parasites from Sisaket Province clustered together suggesting a recent clonal expansion of these parasites ( Fig 4C ) . Similar results were obtained by a neighbor joining tree analysis ( S1 Fig ) . The genetic dissimilarity between the K13 flanking microsatellites of C580Y mutants was highly associated ( Pearson's correlation coefficient: 0 . 44 , 95% CI: 0 . 34–0 . 52 ) with the geographic distance between the sites where the isolates were collected . Average genetic dissimilarity was lower between pairs of C580Y mutants than between pairs of wild type parasites ( t-test p-value < 0 . 001 ) , and the association between genetic dissimilarity and geographic distance was stronger for C580Y mutants than for wild type parasites ( Fig 5 ) .
To our knowledge , this study is one of the first reports to systematically analyze the artemisinin resistance K13 propeller mutations and flanking microsatellite loci in parasites collected in numerous sites in Thailand shortly before the implementation of the artemisinin resistance containment project in 2009 . The samples were collected from across ten provinces , including the containment zones and areas at highest risk for malaria . This study provides evidence that ( 1 ) artemisinin resistance alleles were present in 8 out of 10 Thai provinces sampled , including two mutant alleles ( R575K and S621F ) not previously reported in Thailand , ( 2 ) artemisinin resistance-associated K13 alleles had evolved along the Thai-Cambodia and Thai-Myanmar border regions at least two years prior to the implementation of the artemisinin resistance containment project , ( 3 ) the artemisinin resistance-associated C580Y mutant alleles were the most common and widespread in Thailand , ( 4 ) there are clear differences in microsatellites that differentiate the C580Y mutant alleles from eastern and western parts of Thailand , and ( 5 ) the C580Y alleles appear to have had two recent , independent origins . Our study provides insight into the prevalence and distribution of K13 mutations in Thailand as early as 2007 . Interestingly , the prevalence of mutant K13 alleles reported in Pailin , Cambodia during 2007 for the C580Y ( 45% ) and R539T ( 5% ) alleles [19] is consistent with our findings . Across the border from Pailin , in the provinces of Chanthaburi , Sisaket and Trat , we observed that more than 42% of the parasites screened carried the C580Y mutant allele ( Fig 1 ) . The C580Y allele has since been associated with delayed parasite clearance in this region [19 , 20] . The highest prevalence of the C580Y ( 62% ) and R539T ( 16% ) mutations is seen in the province of Sisaket , just north of Cambodia . These results are in agreement with the recent study by Ashley et al [20] , which provided compelling evidence that the C580Y and R539T mutations are associated with delayed parasite clearance in both Sisaket and Ranong . Moreover , 78% ( 7/9 ) of the parasite isolates from Sisaket showed a similar clonal genetic profile , suggesting that this may have been a recent clonal expansion event ( Figs 3C and S1 ) . Similar findings were reported by Miotto et al [22] , who demonstrated that three subpopulations associated with clinical resistance to artemisinin may have recently expanded in Cambodia and elsewhere in the region . In eastern Thailand , C580Y and R539T were the only mutations observed; however , this may be due to the limited number of samples analyzed . In contrast , the provinces bordering Myanmar had the following mutations: S621F , C580Y , R575K , P574L , E556D , and N458Y . C580Y , P574L and R575K were the most commonly found alleles along the Thai-Myanmar border region ( i . e . from Kanchanaburi to Chumporn ) . Interestingly , the C580Y and R575K mutations have recently been reported near the Thai-Myanmar border as well [23 , 24] . Other mutant alleles ( N458Y , S621F , and E556D ) were rare and restricted to one or two sites ( Fig 1 ) , suggesting that these K13 mutations may have arisen independently . Although previous studies have confirmed a strong association between select K13 propeller domain mutations and delayed parasite clearance [19 , 20 , 25] , it remains to be determined whether the remaining mutant alleles will have a similar association . Furthermore , it remains to be seen whether the C580Y mutation will trend towards fixation in Thailand , as was seen between 2001 and 2012 in Pailin , Cambodia [19] . Our data show that artemisinin-resistant K13 alleles did not spread to or evolve in the southernmost Yala province or the northern Mae Hong Son province during 2007 . In Yala , the parasites had identical flanking and neutral microsatellite haplotypes , which is consistent with our previously published results [26] , indicating a closely related clonal population . Population differentiation analysis further reveals that parasites with the C580Y allele group together by geography ( Fig 3A ) . Analysis of raw microsatellite haplotype data for these parasites revealed that alleles circulating in the east and west comprise two distinct lineages marked by differences in the 8 . 6kb locus downstream of the K13 gene ( Fig 2 ) . These data suggest the C580Y mutations may have arisen independently along the Thai-Cambodia and Thai-Myanmar borders . The reduced pattern of heterozygosity of C580Y alleles compared to wild type alleles ( Fig 3 ) further suggests recent independent origins along the Thai-Cambodia and Thai-Myanmar borders . This interpretation of our data is consistent with the recently published work by Miotto et al . [21] . The study provided compelling evidence for the selection of the C580Y allele in the Greater Mekong Subregion [21] , which is consistent with our data , and suggested that the selection process may have been under way on both sides of Thailand at the time of this study . One possible interpretation of our findings would be that the parasites migrated across Thailand prior to the independent C580Y emergence events . Recent findings by Takala-Harrison et al . and Miotto et al . are consistent with the independent emergence of the C580Y allele , which was also observed along the Myanmar-Thai border and the lower Mekong region [13 , 21] . The strong association between the genetic dissimilarity and geographic distance of the C580Y mutants further supports the hypothesis that this mutation may have emerged independently in eastern and western Thailand ( Fig 5 ) . Given the history of population movements within this region , some of the mutant alleles in the Thai-Myanmar region ( C580Y and P574L ) and Thai-Cambodia region ( C580Y and R539T ) may share common ancestry . Interestingly , in the work by Miotto et al . [21] , parasites with the most common K13 mutant alleles ( C580Y , I543T , R539T , and Y493H ) were found in multiple countries in the region , indicating that parasite cross-border movement may have already occurred . It remains to be determined if the P574L and R575K alleles , which have been found in Myanmar [13 , 23] , originated in either Thailand or Myanmar . It has been suggested that in the absence of drug pressure , parasites with some resistant mutations are less fit than their ancestral wild type counterparts [27] . However , with continued drug pressure one might expect resistant alleles , such as the C580Y mutation , to eventually become fixed in the population as has occurred with other resistance mutations in the past . The work by Ariey et al . , which identified the K13 propeller as a molecular marker of artemisinin resistance , demonstrated that over the course of 11 years ( 2001–2012 ) , the C580Y allele prevalence increased from 40% to 90% in Pailin , Cambodia [19] . This would suggest that the parasites carrying the C580Y mutation may be nearing fixation in the population , and therefore , no sensitive parasites will remain to outcompete them in the absence of ACT . This is very worrisome , as ACT is one of our last working treatment options for drug resistant P . falciparum . In summary , it is evident from our study that artemisinin-resistant K13 alleles have been evolving along both the Thai-Cambodian border and Thai-Myanmar border long before the artemisinin containment project was implemented . It is further evident that the most commonly found C580Y allele had two distinct haplotypes , suggesting different patterns of origin and migration along the Thai-Cambodia and Thai-Myanmar regions .
This protocol was approved by the Thailand Ministry of Public Health . CDC Human Research Protection Office provided approval for retrospective testing using anonymized samples . Study participants and/or their guardians provided written informed consent . A total of 417 Plasmodium falciparum infected blood samples were used in this study . The samples were collected in 2007 as part of a malaria surveillance study conducted by the Thailand Ministry of Public Health [28] . Finger prick blood samples were collected from ten malaria-endemic provinces of Thailand . Six of these provinces ( Mae Hong Son , Tak , Kanchanaburi , Prachuap , Chumporn , and Ranong ) are on the Myanmar border , and three ( Sisaket , Chanthaburi , and Trat ) are on the Cambodian border , while one ( Yala ) is in southern Thailand bordering Malaysia . In 2007 , the reported malaria incidence rates were 17 . 2 , 9 . 2 , 8 . 7 , and 8 . 5 cases per 1 , 000 residents in Yala , Mae Hong Son , Tak , and Ranong , respectively , and 3 . 9 , 2 . 9 , 1 . 7 and 1 . 2 per 1 , 000 population in Chumporn , Prachuap , Chanthaburi and Kanchanaburi , respectively [29] . The K13 gene was amplified using a nested PCR method that was modified from a previous study [19] . New secondary primers that are species specific for P . falciparum were developed and used . For the primary PCR the same primers as in [19] were used ( K13P1 5’-GGGAATCTGGTGGTAACAGC-3’ and K13R1 5’-CGGAGTGACCAAATCTGGGA-3’ ) . For the secondary PCR , new primers were designed ( K13S1 , 5’ GTAAAGTGAAGCCTTGTTG-3’ and K13S2 5'-TTCATTTGTATCTGGTGAAAAG -3’ ) . Two μl of genomic DNA was amplified using 0 . 5 μM of each primer , 0 . 2 mM dNTP , 3 and 2 mM MgCl2 for the primary and secondary reactions , respectively , and 1 U Expand High Fidelity Taq ( Roche ) . For the primary reaction , the following cycling parameters were used: 5 min at 94°C , 40 cycles of 94°C for 30 s , 60°C for 90s , 72°C for 90s , and final extension for 10 min at 72°C . For the nested PCR , 1 μl of the primary PCR product was used as a template . For the nested PCR reaction , the following cycling parameters were used: 2 min at 94°C , 40 cycles of 94°C for 30 s , 55°C for 30s , 72°C for 90s , and final extension for 10 min at 72°C . PCR products were separated and visualized using 2% agarose gel electrophoresis and Gel red ( Biotium , Hayward CA ) . Sanger sequencing of PCR products was performed using ABI 3730 ( Applied Biosystems , Foster City , CA ) . Sequences were deposited to Genbank ( Accession Numbers:KP334284—KP334700 ) . Twenty-five microsatellite loci flanking the K13 gene on chromosome 13 ( PF3D7_1343700 ) were tested for evidence of selection as indicated by a reduction in heterozygosity around the K13 gene . Three of the loci , L4_165 ( 72 . 3 kb ) , LM_173 ( -3 . 74 kb ) and B1_P1 ( -31 . 9 kb ) were previously described [18] , and the remaining 22 were newly designed for this study . Only 12 out of 25 loci were informative and further analyzed to study the selective sweeps and genetic lineages of resistance K13 alleles ( downstream: 3 . 4kb , 8 . 6kb , 15 . 1kb , 31 . 0kb , 31 . 5kb , 72 . 3kb; upstream: -0 . 15kb , -3 . 7kb , -6 . 36kb , -31 . 9kb , -50 . 0kb , -56 . 0kb ) . The primers used are shown in S1 Table . In addition , eight putatively neutral microsatellite loci located on chromosome 2 ( GenBank UniSTS C2M27 , C2M29 , C2M34 , and C2M33 ) and chromosome 3 ( GenBank UniSTS C3M40 , C3M88 , C3M69 , and C3M39 ) were used as previously described [28] . A previously described protocol [30] for cycling was modified for this study . Briefly , primer pairs with annealing temperature in the 50–60°C range were designed and cycling conditions were adjusted according to each primer pairs melting temperatures ( TMs ) . The sizes of the amplification products were assayed by capillary electrophoresis on an Applied Biosystems 3130 xl sequencer ( Applied Biosystems , Foster City CA ) . To determine genetic diversity , the expected heterozygosity ( He ) was estimated using all K13 flanking or neutral microsatellite loci using the Excel Microsatellite Toolkit , version 3 . 1 . 1 [31] . He was calculated using the formula [n/ ( n-1 ) ][1-Ʃpi2] for He; and 2 ( n-1 ) /n3 {2 ( n-2 ) [Ʃ ( pi3- ( Ʃpi2 ) 2]}for variance , where n is the number of samples genotyped for any locus and pi is the frequency of the ith allele . Any locus for which an allele could not be amplified after two attempts was assigned as DNW , indicating no amplification . Mean He between the wild type and C580Y mutant alleles were compared using the Mann-Whitney U test . Statistical significance was defined as p ≤ 0 . 05 . Sanger sequences were analyzed using Geneious Pro R8 ( www . geneious . com ) to identify specific SNP combinations . A custom pipeline was created using the Geneious workflow feature to automate the SNP analysis ( shared @GitHub ) . Briefly , by selecting a user defined sequence list ( select all raw sequences > create list ) and reference sequence as an input , the workflow will automatically map the input sequences to the reference sequence , identify all SNPs , and export the final SNP calls . Each step creates a sub-folder allowing the user to check the results . SNPs were only called if both the forward and reverse strands had the mutation . Microsatellite fragment analysis was performed using the Geneious Pro R8 microsatellite plugin . For determining genetic lineages of the K13 alleles , the POLYSAT R package was used [32] . Using the built-in functions in POLYSAT R , a pairwise distance matrix and principal component analysis ( PCA ) matrix was calculated using a stepwise mutation model for the flanking and neutral microsatellite markers . The pairwise distance matrix was used to construct a neighbor joining tree via the T-REX web server [33] . The resulting neighbor joining tree was imported into Geneious Pro R8 and colored according to geography . The geographic distance between the ten sampling sites was calculated , and genetic dissimilarity between each pair of isolates using the flanking microsatellites was plotted against the geographic distance between the sites where they were collected . Pearson’s correlation coefficient was calculated to assess the association between genetic dissimilarity and geographic distance . The genetic dissimilarity scatter plots were created and visualized using R 3 . 1 . 1 . All R code used to run the analysis has been uploaded to: GitHub Sequences were deposited to Genbank ( Accession Numbers:KP334284—KP334700 ) . | The Plasmodium falciparum parasites that cause malaria are evolving resistance to our most effective and potent anti-malarial drugs available , called artemisinins . Currently , artemisinin resistance is emerging in a number of countries in the Greater Mekong Subregion , including Cambodia , Thailand , Myanmar , and Vietnam . Historically , the Thai-Cambodia border region has been an epicenter of resistance to several anti-malarial drugs . To prevent the spread of artemisinin resistant parasites from the Greater Mekong Subregion , a global artemisinin resistance project was initiated in 2009 . Here , we show that artemisinin resistance associated mutation in the K13 gene were widely present throughout Thailand , as early as 2007 , primarily along the Thai-Cambodia and Thai-Myanmar border regions . Additional data based on microsatellite markers suggests that the most commonly found K13 C580Y allele may have two recent independent origins in Thailand , on the borders of Cambodia and Myanmar . | [
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] | [] | 2015 | Selection and Spread of Artemisinin-Resistant Alleles in Thailand Prior to the Global Artemisinin Resistance Containment Campaign |
The cyclic GMP-AMP synthase ( cGAS ) , upon cytosolic DNA stimulation , catalyzes the formation of the second messenger 2′3′-cGAMP , which then binds to stimulator of interferon genes ( STING ) and activates downstream signaling . It remains to be elucidated how the cGAS enzymatic activity is modulated dynamically . Here , we reported that the ER ubiquitin ligase RNF185 interacted with cGAS during HSV-1 infection . Ectopic-expression or knockdown of RNF185 respectively enhanced or impaired the IRF3-responsive gene expression . Mechanistically , RNF185 specifically catalyzed the K27-linked poly-ubiquitination of cGAS , which promoted its enzymatic activity . Additionally , Systemic Lupus Erythematosus ( SLE ) patients displayed elevated expression of RNF185 mRNA . Collectively , this study uncovers RNF185 as the first E3 ubiquitin ligase of cGAS , shedding light on the regulation of cGAS activity in innate immune responses .
The innate immune system serves as the first line of host defense against invading microbes . Upon recognition by an array of host germline-encoded pattern recognition receptors ( PRRs ) , including Toll-like receptors ( TLRs ) , RIG-I-like receptors ( RLRs ) and DNA sensors , microbial nucleic acids trigger the initiation of intracellular signaling cascades that lead to the induction of type I interferons as well as pro-inflammatory cytokines , which are a prerequisite for eliciting immediate antiviral responses and adaptive immunity to ultimately eradicate the infection [1 , 2 , 3 , 4] . Microbial RNA-sensing machinery and the corresponding downstream signaling cascade have been well characterized during the past decade , whereas the microbial DNA sensing represents a fast evolving field for understanding the corresponding innate immune signaling pathways [5 , 6 , 7 , 8 , 9] . Various studies have identified several proteins , including Mre11 , DAI , RNA polymerase III , IFI16 , DDX41 as the potential DNA sensors [10 , 11 , 12 , 13 , 14] . However , these proteins are not universally essential for detecting microbial DNAs in distinct cell types or in vivo [6] . Recently , cyclic GMP-AMP synthase ( cGAS ) is characterized as a sequence-independent DNA sensor by classical biochemical fractionation strategies coupled with quantitative mass spectrometry [15] . Analyses of cGAS knockout mice reveal its essential roles in fibroblasts , macrophages , and dendritic cells in response to various DNA stimuli transfections and DNA pathogens ( DNA viruses , retroviruses , Listeria monocytogenes and Mycobacterium tuberculosis ) infection [16 , 17 , 18 , 19 , 20] . In addition , cGas-/- mice are more vulnerable to lethal infection after exposure to herpes simplex virus 1 ( HSV-1 ) than wild-type mice [16] . Notably , cGAS possesses nucleotidyl transferase activity , converting ATP and GTP into noncanonical cyclic dinucleotide 2′3′-cGAMP in the presence of DNA [21 , 22] . As a second messenger , cGAMP directly binds to and activates ER-resident stimulator of interferon genes ( STING ) [23 , 24 , 25] . STING traffics from ER , through the Golgi apparatus , and to the perinuclear microsomes or punctuate structures [25] . During the trafficking processes , the K27-linked poly-ubiquitin chain anchored on STING by AMFR-INSIG1 complex recruits the TANK-binding kinase 1 ( TBK1 ) , which causes STING and TBK1 to congregate simultaneously in the same compartment [26] . Importantly , the DNA-triggered assembly of STING-TBK1 complex is critical for TBK1 activation , followed by activating the transcriptional factor IRF3 , thus inducing expression of type I interferons and pro-inflammatory cytokines . Protein post-translational modifications , such as phosphorylation , ubiquitination , and SUMOylation , are central to the host innate immune regulations [27 , 28] . cGAS is potentially subjected to a couple of modifications [29 , 30 , 31] . For example , the glutamylases TTLL6 catalyzes poly-glutamylation of cGAS and impedes its DNA-binding activity , whereas TTLL4-mediated mono-glutamylation of cGAS blocks its synthase activity . The carboxypeptidases CCP6 and CCP5 reverse the above processes respectively , thus promoting the cGAS activation [29] . The protein kinase Akt phosphorylates cGAS and suppresses its enzymatic activity [30] . However , it remains unknown whether cGAS is modulated by ubiquitination . A thorough study on the regulation of cGAS activity is deserved because the aberrant activation of cGAS causes severe autoimmune or autoinflammatory disorders , such as systemic lupus erythematosus ( SLE ) and Aicardi Goutières syndrome ( AGS ) [32 , 33 , 34] . The E3 ubiquitin ligase RNF185 potentially modulated the osteogenesis or protein quality control on the ER [35 , 36 , 37] . In this study , we characterized the ER-resident RNF185 as a positive regulator of the cGAS-STING signaling . RNF185 interacted with cGAS and catalyzed the K27-linked poly-ubiquitination of cGAS upon HSV-1 challenges , which markedly potentiated the enzymatic activity of cGAS . Additionally , SLE patients exhibited elevated RNF185 mRNA expression .
Because polyubiquitination has emerged as an important regulatory mechanism for cGAS-STING signaling [27 , 28] , we speculated whether additional E3 ubiquitin ligases catalyze the ubiquitination of key signaling molecules and thereby regulate innate antiviral response . We noticed that RNF185 contains a RING domain , a signature of ubiquitin E3 ligases , and shares a high degree of sequence identity ( approximate to 70% ) with RNF5 , which catalyzed the ubiquitin-mediated degradation of STING ( S1A Fig ) . To explore the potential role of RNF185 , we screened out the specific and effective siRNAs ( mouse Rnf185 siRNA 1# and mouse Rnf185 siRNA 2# ) ( Fig 1A ) . As expected , silencing of Rnf185 markedly attenuated the expression of the IRF3-responsive genes ( Ifnb , Ifna4 and Cxcl10 ) in L929 cells , stimulated by the herring testis DNA ( HT-DNA ) transfection ( S2A Fig ) or the DNA virus HSV-1 infection ( Fig 1B , left panel ) . In contrast , the abundance of Ifnb , Ifna4 or Cxcl10 mRNAs induced by RNA mimic poly ( I:C ) transfection ( S2A Fig ) or RNA virus Sendai virus ( SeV ) infection ( Fig 1B , right panel ) was comparable between Rnf185 knockdown and wild-type L929 cells . Similarly , knockdown of Rnf185 in Raw264 . 7 cells also significantly attenuated the expression of the IRF3-responsive genes ( Ifnb , Ifna4 and Cxcl10 ) , when challenging cells with HSV-1 ( S3A Fig ) . In contrast , the induction of the IRF3-responsive genes was marginally affected in Rnf185 knockdown Raw264 . 7 cells when challenging cells with SeV ( S3B Fig ) . To make it more physiologically relevant , we next probed the role of RNF185 in primary cells . We confirmed RNF185 expression was also efficiently reduced in the BMDMs ( bone marrow derived macrophages ) transfected with the indicated siRNAs ( S3C Fig ) . Consistently , silencing of Rnf185 markedly attenuated the expression of the IRF3-responsive genes ( Ifnb , Ifna4 and Cxcl10 ) in BMDMs stimulated by HSV-1 ( S3D Fig ) . In contrast , the abundance of Ifnb , Ifna4 or Cxcl10 mRNAs induced by SeV infection was comparable between Rnf185 knockdown and wild-type BMDMs ( S3E Fig ) . Furthermore , RNF185 knockdown in BMDMs resulted in obvious increase in HSV-1 titer as compared with controls by standard plaque assay ( S3F Fig , left panel ) . However , RNF185 knockdown did not influence Sendai virus replication as checked by qPCR analysis ( S3F Fig , right panel ) . These data suggest that RNF185 specifically regulates cytosolic DNA sensing pathway . To rule out potential off-target effects of the RNF185 siRNA , we generated two RNA interference ( RNAi ) -resistant RNF185 constructs , named rRNF185 WT and rRNF185 C39A , in which silent mutations were introduced into the sequence targeted by the siRNA without changing the amino acid sequence of the corresponding proteins . L929 cells were first transfected with control or RNF185 siRNA followed by introduction of control or indicated rRNF185 plasmids , respectively . Then the induction of IRF3-responsive genes ( Ifnb , Ifna4 and Cxcl10 ) was measured after HT-DNA stimulation . As shown in Fig 1C , the induction of Ifnb , Ifna4 and Cxcl10 was restored by rRNF185 WT , but not rescued by rRNF185 C39A . These data suggest that RNF185 potentially modulates the cytosolic DNA sensing pathway depending on its enzymatic activity . The immune sensing of microbial DNA is critical for triggering immediate immune responses and the subsequent adaptive immunity [3] . However , inappropriate provocation of the immune system by aberrant self-DNA , which should be cleared under normal conditions , contributes to the pathogenesis of certain autoimmune diseases , such as systemic lupus erythematosus ( SLE ) [38 , 39] . Since RNF185 might be involved in regulating cGAS-mediated DNA sensing pathway , we further examined the mRNA expression levels of RNF185 as well as ISG15 and OASL-1 ( type I IFNs inducible genes ) in peripheral blood mononuclear cells ( PBMCs ) isolated from SLE patients and healthy controls by QPCR analysis . The RNF185 mRNA expression was significantly up-regulated in SLE patients as compared with healthy controls ( Fig 1D ) . The ISG15 and OASL-1 mRNA expression were also increased in SLE patients as compared with healthy controls ( Fig 1D ) . Interestingly , ectopic-expression of wild-type RNF185 in PBMCs potentiated the expression of ISG15 and OASL-1 mRNA as well as IFNA2 , IFNA5 and IFNB mRNA , whereas the mutant RNF185 C39A could not ( Fig 1E ) . In addition , we treated PBMCs with purified IFNα2a in different doses , and observed that IFNα2a could efficiently induce the expression of ISG15 and OASL-1 mRNA in early and late time points ( S2B and S2C Fig ) . In contrast , the RNF185 mRNA expression was barely affected at the early and late phase of IFNα2a treatment ( S2B and S2C Fig ) . To make the experiment more physiologically relevant , we stimulated the PBMCs with different titrations of serum isolated from SLE patients and healthy controls . As expected , the cells treated with the serum from SLE patients produced much more ISG15 and OASL-1 mRNA than did those from healthy controls ( S2D and S2E Fig ) . Notably , serum from SLE patients displayed no substantial effect on the expression of RNF185 mRNA as compared with those from healthy controls in early and late time points ( S2D and S2E Fig ) . These data suggest that no positive feedback loop exists between RNF185 mRNA expression and Interferons production . The dimerization and phosphorylation of IRF3 as well as the phosphorylation of TBK1 are hallmarks of the cytosolic DNA-triggered signaling . These processes were apparently inhibited in Rnf185 knockdown L929 cells , when stimulating cells with HT-DNA ( Figs 2A and S4A ) . However , poly ( I:C ) -induced dimerization or phosphorylation of IRF3 as well as the phosphorylation of TBK1 were barely affected when silencing Rnf185 ( Figs 2B and S4B ) . In addition , the nuclear translocation of IRF3 triggered by HT-DNA was markedly crippled when knocking down Rnf185 in L929 cells ( Fig 2C and 2D ) , whereas the nuclear translocation of IRF3 triggered by poly ( I:C ) remained intact in Rnf185 knockdown L929 cells ( Fig 2C and 2D ) . Collectively , these data indicate that RNF185 is essential for the cytosolic DNA-induced IRF3 activation . Interestingly , silencing of RNF185 apparently did not affect the expression of IRF3-responsive genes ( Ifnb , Ifna4 and Cxcl10 ) induced by cGAMP ( Fig 2E ) . Consistently , cGAMP-triggered dimerization and phosphorylation of IRF3 were barely affected when silencing Rnf185 ( Fig 2F ) . Therefore , we reasoned that RNF185 played a role on the upstream of STING ( Fig 2G ) . To substantiate , silencing of Rnf185 markedly attenuated the induction of Cxcl10 and Ifnb as well as the phosphorylation of TBK1 and IRF3 by cGAS in L929 cells , stimulated with or without HT-DNA . ( Figs 2H , S4C and S4D ) , which suggest that RNF185 may modulate the cGAS signalsome . To address the association between RNF185 and cGAS , HA-tagged RNF185 and Flag-tagged cGAS were transfected individually or together into HEK293T cells , followed by coimmunoprecipitation ( coIP ) assays . As expected , HA-tagged RNF185 associated with Flag-tagged cGAS ( Fig 3A and 3B ) . It was predicted that the cysteines in the RING domain of RNF185 are critical for its catalytic activity . Several RNF185 mutants were therefore generated , including RNF185 C39A ( Cys to Ala mutation at 39 residues ) , RNF185 C39/42A ( Cys to Ala mutation at both 39 and 42 residues ) and RNF185 C39/79A ( Cys to Ala mutation at both 39 and 79 residues ) , all of which were deprived of the potential E3 ubiquitin ligase activity ( see below ) . It was observed that cGAS associated with these RNF185 mutants as well as with wild-type RNF185 ( Fig 3A and 3B ) , indicating that the E3 ubiquitin ligase activity of RNF185 was dispensable for its association with cGAS . We further confirmed the weak endogenous association between cGAS and RNF185 ( Fig 3C ) . Notably , the endogenous association between cGAS and RNF185 was substantially enhanced upon HSV-1 infection ( Fig 3C ) . A series of deletion mutants of cGAS and RNF185 were employed to map the domains responsible for RNF185-cGAS interaction ( Fig 3D and 3E , left panel ) . The C-terminal domain of cGAS ( amino acids 201–522 ) and the RING domain of RNF185 ( amino acids 39–80 ) were required for the interaction ( Fig 3D and 3E , right panel ) . Confocal microscope imaging revealed that endogenous RNF185 partially co-localized with endogenous cGAS in resting cells ( Figs 3F and S5A ) , and this co-localization was enhanced after HSV-1 infection ( Figs 3F and S5A ) . Confocal microscopy and subcellular fractionation analysis confirmed that RNF185 were predominantly expressed on ER membrane , but not on mitochondria membrane ( Fig 3G and 3H ) . Taken together , these data indicate that RNF185 is a novel member of the cGAS signalsome in vivo . As an E3 ubiquitin ligase , RNF185 could catalyze the ubiquitin-mediated degradation BNIP1 , CFTR and Dvl2 [35 , 36 , 37] . Our in vitro ubiquitination assays confirmed that RNF185 could catalyze the formation of poly-ubiquitin chains , whereas RNF185 C39A , RNF185 C39/42A or RNF185 C39/79A could not ( Fig 4E ) . Our above data uncovered the importance of the E3 ubiquitin ligase activity of RNF185 for the cytosolic DNA sensing pathway ( Fig 1C ) . Therefore , we wondered whether the cGAS was the authentic substrate of RNF185 . To explore this possibility , Flag-tagged cGAS was co-transfected respectively with RNF185 or other E3 ligases known in the STING pathway . The cell lysates were subjected to immunoprecipitation with anti-Flag , and then the immunoprecipitates were denatured , followed by re-immunoprecipitation again with anti-Flag; the precipitates were finally analyzed by immunoblotting with anti-ubiquitin . Notably , cGAS was markedly poly-ubiquitinated in the presence of RNF185 ( Fig 4A ) . In contrast , other E3 ligases could not catalyze the ubiquitination of cGAS ( Fig 4A ) . Apparently , RNF185 could not catalyze the polyubiquitination of other potential DNA sensors [11 , 13 , 14] ( Fig 4B ) , neither could it catalyze the polyubiquitination of STING , TBK1 or IRF3 ( Fig 4C ) . In addition , the catalytically inactive mutants RNF185 C39A , RNF185 C39/42A or RNF185 C39/79A failed to catalyze the polyubiquitination of cGAS inside cells ( Fig 4D ) . In vitro ubiquitination assay further confirmed that the wild-type RNF185 catalyzed the formation of poly-ubiquitin chains on cGAS , whereas the RNF185 C39A , RNF185 C39/42A or RNF185 C39/79A could not ( Fig 4E ) . Thus , cGAS is a new substrate of the RNF185 . A panel of ubiquitin mutants , including those containing a point mutation at a corresponding lysine and those with all lysines mutated to arginines except for the indicated one , were employed to dissect the polyubiquitin chain linkage on cGAS . As expected , RNF185 catalyzed the poly-ubiquitination of cGAS in the presence of wild-type ubiquitin , whereas the poly-ubiquitination of cGAS was completely abolished when using the ubiquitin K0 mutant ( Ubiquitin with all lysine residues mutated to arginine ) . Notably , the modification reappeared when K27 , rather than other lysines , was reintroduced into the ubiquitin K0 mutant ( Fig 4F ) . Moreover , cGAS was not poly-ubiquitinated when using ubiquitin K27R ( S5B Fig ) , whereas cGAS was polyubiquitinated as well by K6R , K11R , K29R , K33R , K48R and K63R ( S5B Fig ) . Collectively , the data indicate that RNF185 catalyzes the formation of the K27-linked polyubiquitin chains on cGAS . To identify the potential poly-ubiquitination sites on cGAS , we carried out a systematic lysine ( K ) to arginine ( R ) mutation scanning . When the two lysines ( K173 and 384 ) on cGAS were all mutated to arginines , the poly-ubiquitination of cGAS was almost completely abolished ( Fig 4G ) . To substantiate , cGAS mutants could induce the IFN-β-luciferase reporter gene to a much lower level than their wild-type one ( Fig 4H ) . In addition , the expression of Cxcl10 and Ifnb mRNAs as well as the phosphorylation of TBK1 and IRF3 triggered by cGAS K173R/384R mutant were much lower than by wild-type cGAS in L929 cells stimulated with or without HT-DNA ( S5C and S5D Fig ) . There was some background poly-ubiquitination of the endogenous cGAS in resting cells ( Fig 4I ) . The endogenous cGAS was robustly poly-ubiquitinated upon HSV-1 infection . Importantly , the poly-ubiquitination of cGAS was markedly reduced in Rnf185 knockdown L929 cells ( Fig 4I ) . Taken together , these data establish that cGAS is an authentic substrate of RNF185 , which catalyzes the K27-linked poly-ubiquitination of cGAS . To probe the functional role of the ubiquitination of cGAS , L929 cells were transfected with RNF185 siRNA and stimulated with HT-DNA . cGAMP levels in the infected cell lysates were indirectly measured through incubation of PFO-permeabilized fresh L929 cells with those lysates , and the IRF3 dimerization was checked . As expected , knocking down RNF185 in L929 cells resulted in a significant reduction of cGAMP production upon HT-DNA transfection ( Fig 5A ) , which indicate that RNF185 is required for activating cGAS in response to cytosolic DNA challenge . The in vitro enzymatic activity assay was further employed to assess the effect of cGAS ubiquitination on its cGAMP synthetic activity . Briefly , the purified recombinant proteins of cGAS or cGAS mutants from bacteria were subjected to the in vitro ubiquitination reaction , and then they were incubated with the salmon sperm DNA in the presence of ATP and GTP . The production of cGAMP was analyzed by ion exchange chromatography . As expected , recombinant RNF185 ( rRNF185 ) promoted recombinant cGAS to produce much more 2′3′-cGAMP than the rRNF185 C39A mutant ( Fig 5B and 5C ) . In addition , the polyubiquitin-chain-deficient cGAS mutant could marginally synthesize 2’3’-cGAMP in the presence of rRNF185 ( Fig 5B and 5C ) . Taken together , these data reveal that the poly-ubiquitination of cGAS promotes its catalytic activity . The robust induction of IFN-β and interferon-stimulated genes ( ISGs ) represents one of the immediate responses to cytosolic DNA virus infections . ELISA assays indicated that the production of IFN-β was markedly reduced in Rnf185 knockdown L929 cells stimulated with HT-DNA ( Fig 6A ) . Standard plaque assay revealed that RNF185 knockdown resulted in nearly 3-fold increase in HSV-1 virus titer as compared with controls ( Fig 6B and 6C ) . Since IFN-β protects host cells against viruses , we assessed if RNF185 played a role in restricting HSV-1 infection . MEF cells were pretreated respectively with culture supernatants from HT-DNA-stimulated Rnf185 knockdown L929 cells or wild-type L929 cells , followed by HSV-1 infection . Fresh cells pretreated with culture supernatants from Rnf185 knockdown L929 cells were more permissive to HSV-1 infection ( Fig 6D ) . We next investigated whether RNF185 modulated virus replication by challenging cells with HSV-1-GFP . It was observed that the cells with Rnf185 knockdown showed considerably increased numbers of HSV-1-GFP positive cells ( Fig 6E and 6F ) . Taken together , these data indicate that RNF185 is important for innate antiviral responses .
Much is known about the signal transduction triggered by the cytosolic DNAs [24 , 40] . Unlike other sensors ( DAI , IFI16 , DDX41 , Mre11 ) [10 , 11 , 13 , 14] , cGAS was characterized as a universal sensor that initiates the STING signaling in multiple cell types triggered by many stimuli [15] . Although several recent studies have uncovered key structural features associated with DNA recognition by cGAS as well as the catalytic mechanisms of cGAS generating cGAMP [22 , 41 , 42 , 43 , 44] , it is not well understood how the cGAS activity is modulated dynamically in response to pathogenic or self DNA . In this study , we performed unbiased RNAi-based screening ( S6 Fig ) , and identified a novel E3 ubiquitin ligase RNF185 to directly modulate cGAS action . Several lines of evidence substantiate the important function of RNF185 in the cytosolic DNA sensing pathway . ( a ) Knocking down RNF185 specifically attenuated the expression of IRF3-responsive genes induced by DNA mimics transfection or DNA virus HSV-1 infection , but not by RNA mimic transfection or RNA virus SeV infection . ( b ) The effect produced by RNF185 knockdown was reversed by exogenously expressing a siRNA-resistant rRN185 , not by expressing the enzymatic inactive RNF185 mutant , indicating that the regulatory function of RNF185 was dependent on its enzymatical activity . ( c ) The phosphorylation , dimerization and nuclear translocation of IRF3 triggered by cytoslic DNAs were markedly crippled in RNF185 knockdown cells . ( d ) Silencing of RNF185 was more permissive to the HSV-1infection , establishing that RNF185 was important for the innate antiviral responses . In most cases , HSV-1 infection brings about herpetic encephalitis or genital disease in a living host [45 , 46] . In our data , we noticed that RNF185 knockdown resulted in nearly 3-fold increase in HSV-1 virus titer as compared with controls . However , it is worthwhile to explore in the future clinical study whether a 3-fold statistically significant difference in a HSV titer could potentially affect herpetic encephalitis or genital disease in a living host . RNF185 was previously shown to catalyze the ubiquitin-mediated degradation of several proteins ( BNIP1 , CFTR and Dvl2 ) and modulate the protein quality control on ER [35 , 36 , 37] . In this study , we characterized cGAS as a new substrate of RNF185 . ( a ) RNF185 specifically associated with cGAS , and this association was markedly increased upon HSV-1 challenge , indicating that this association was transient and dynamic . ( b ) Wild-type RNF185 , but not its enzymatic inactive mutants , could catalyze the poly-ubiquitination of cGAS , as evidenced by the two-step immunoprecipitation or in vitro ubiquitination assay . ( c ) Site-directed mutagenesis revealed that lysines 173 and 384 on cGAS were major acceptor sites of the polyubiquitin chain . ( d ) RNF185 specifically catalyzed the K27-linked polyubiquitin chain on cGAS . ( e ) DNA virus infection induces the ubiquitination of endogenous cGAS by RNF185 , as evidenced by the observation that RNAi-mediated silencing of RNF185 diminished these effects . ( f ) The ubiquitination of cGAS potentiates its enzymatic activity and boosts the production of cGAMP . Taken together , RNF185 is an authentic E3 ubiquitin ligase for cGAS and promotes its activation . It is recently well established that the aberrant activation of the cGAS-STING signaling by self-DNA causes severe autoimmune or auto-inflammatory disorders , such as SLE [38 , 39 , 47] . We found that RNF185 mRNA expression is substantially elevated in PBMCs from SLE patients . Generation of RNF185-deficient mice in the future will further elucidate the functional relevance of RNF185 in SLE . cGAS-STING signaling is essential for monitoring mitochondrial DNA ( mtDNA ) released into cytoplasm during mitochondrial membrane permeabilization or stress [48 , 49 , 50] . It is also indispensable for sensing damaged DNA leaked into cytoplasm , resulting from ATM ( Ataxia-telangiectasia mutated ) deficiency or exogenous genotoxic stress [51] . In particular , cGAS-STING signaling is important in sensing and responding to tumor cell-derived DNA [52 , 53] . Future investigation is expected to uncover the potential roles of RNF185 in mitochondrial stress , DNA damage , and tumor immunity . Insights from these studies might substantiate RNF185 as a potential therapeutic target for further clinical trials . Ubiquitination is a versatile post-translational modification critical in innate immunity [27 , 54] . Different linkages of polyubiquitin chains anchored on target proteins produce specific physiological or pathological consequences . K48- and K63-linked polyubiquitin chains have been extensively used in regulating the TLR and RLR signaling pathways [27 , 54] . Apparently , ubiquitin-mediated modulation of the cGAS-STING signaling is no exception . For example , RNF5 promotes K48-linked poly-ubiquitination of STING , thus dampening the cytosolic virus-triggered immune responses [55] . Additionally , E3 ubiquitin ligases TRIM56 and TRIM32 respectively facilitate the K63-linked poly-ubiquitination of STING and positively regulate the host anti-microbial responses [56 , 57] . Given the diversity of the STING poly-ubiquitination , it is worthwhile to explore whether cGAS is also modulated by other forms of poly-ubiquitination . It remains to address whether the stability of cGAS is dynamically modulated by the ubiquitin-proteasome system .
Ethical approval for this study was granted by the Clinical Research Ethics Committee of Zhongshan Hospital , Fudan University School of Medicine . All the participants gave written informed consent before enrollment . Age matched 32 healthy volunteers were recruited as controls . All healthy volunteers used as controls also provided written informed consent . We collected 34 patients all fulfilling the American College of Rheumatology classification criteria for SLE [58] . These patients included two male patients and thirty-two female patients , 18 to 48 years old , averaging 37 years old . All patients were new-onset and not being treated before . Patients who coincided with other autoimmune diseases were excluded . All subjects were screened for infectious conditions . Peripheral blood ( 8 ml ) was sampled in 10ml EDTA containing Vacutainer K2E ( BD biosciences ) . Peripheral blood mononuclear cells ( PBMCs ) were separated by density gradient centrifugation using Ficoll-Paque PLUS ( GE Healthcare ) and the RNA was extracted from PBMCs using TRIzol reagent ( Invitrogen ) according to the manufacturer’s instructions . L929 cells ( ATCC ) were cultured in RPMI 1640 medium ( Invitrogen ) supplemented with 10% FBS and 1% penicillin-streptomycin . HEK293T ( ATCC ) , HEK293FT ( kindly provided by Ke Lan’ lab in Shanghai Pasteur Institute ) , MEFs ( ATCC ) and RAW264 . 7 cells ( ATCC ) were maintained in DMEM plus 10% FBS ( Gibco ) , supplemented with 1% penicillin-streptomycin ( Invitrogen ) . Vero cells ( kindly provided by Ke Lan’ lab in Shanghai Pasteur Institute ) were cultured in MEM ( SAFC Biosciences ) supplemented with 10% FBS and 1% penicillin-streptomycin . BMDMs ( bone marrow derived macrophages ) were prepared as described previously [59] . HEK293T cells and HEK293FT cells were transfected by standard calcium phosphate precipitation method . Other cells were transfected by Lipofectamine 2000 ( Invitrogen ) according to the manufacturer’s instructions . The individual SMART pool siRNA probes ( Dharmacon ) against a mouse ubiquitin-E3-ligase sub-library of 43 genes encoding RING finger proteins were transfected into L929 cells . 48h after transfection , cells were left uninfected or infected with HSV-1 for 6h , and then cells were directly collected into lysis buffer and cDNA was obtained according to the manufacturer's instruction ( Cells-to-cDNA II Kit , Invitrogen ) . The quantifications of gene transcripts were performed by real-time PCR . HEK293T/STING cells were originated from HEK293T cells selected by Zeocin ™ ( Invitrogen , 500ug/ml ) following transfection with pCMV-Zeo-STING [60] . L929/cGAS cells and L929/cGAS K173/384R cells were established by transducing the phageflag-cGAS or phageflag-cGAS K173/384R lentiviruses into L929 cells followed by sorting with flow cytometry . Lentiviruses production was performed according to the manufacturer’s instructions . Briefly , HEK293FT cells plated on 100-mm dishes were transfected with the indicated lentiviral expression plasmid ( 15ug ) together with the PSPA ( 10ug ) and the PMD2G ( 5ug ) . The viral particles were collected at 48h , filtered by 0 . 45um membrane filter and used to infect the indicated cells in the presence of polybrene ( 4ug/ml ) . After transfection for 48h , the positive cells were sorted by flow cytometry ( AriaII , BD Biosciences ) , then cultured in complete RPMI 1640 medium . RNF185 , cGAS , STING , TBK1 , IRF3 , AMFR , Trim32 , Trim56 , DDX41 , DAI , IFI16 cDNAs were obtained by standard PCR techniques from thymus cDNA library and subsequently inserted into mammalian expression vectors as indicated . pCMV-Zeo-STING was kindly provided by Fanxiu Zhu ( Florida State University , Tallahassee , USA ) . pET21b-PFO 85–1500 a . a . was a gift from Zhengfan Jiang ( Peking University , Beijing , China ) . The reporter plasmids ( IFNβ-luciferase and pTK-Renilla ) have been described previously [61] . All point mutations were introduced by using a QuickChange XL site-directed mutagenesis method ( Stratagene ) . All constructs were confirmed by sequencing . The rabbit polyclonal antibody against cGAS was from Cell Signaling Technology and Sigma-Aldrich . The polyclonal antibody against RNF185 was from Abcam . The antibodies against hemagglutinin ( HA ) , Myc , GFP , and ubiquitin were purchased from Santa Cruz Biotechnology . Mouse monoclonal Flag antibody and β-actin antibody were obtained from Sigma-Aldrich . The TBK1 antibody was from Abcam . The IRF3 antibody was from Santa Cruz Biotechnology . Phospho-TBK1 and Phospho-IRF3 antibody was from Cell Signaling Technology . The antibodies against CoxIV , Calreticulin and Calnexin were from Abcam . Anti-Flag ( M2 ) -agarose was from Sigma-Aldrich . Herring testis ( HT ) DNA was from Sigma . Salmon sperm DNA was from TREVIGEN . Poly ( I:C ) was purchased from Invivogen . IFNα2a was from PBL Assay Science . cGAMP was obtained from InvivoGen . In some experiments , cGAMP was delivered into cultured cells by digitonin permeabilization method as previously described [62] . Chemically synthesized 21-nucleotide siRNA duplexes were obtained from Invitrogen and Gene-Pharma , and transfected using Lipofectamine 2000 ( Invitrogen ) according to the manufacturer’s instructions . RNA oligonucleotides used in this study are as follows: N . C . : 5-UUC UCC GAA CGU GUC ACG UTT-3; RNF185 #1: 5′- AAU CUU CCC UGG AAG CUU UTT-3′; RNF185 #2: 5′- GCC ACA GCA UUU AAC AUA ATT -3′ . Luciferase reporter assays were performed as described previously [63] . Total RNA was isolated from cultured cells using TRIzol reagent ( Invitrogen ) according to the manufacturer’s instructions , and then subjected to reverse transcription with PrimeScript RT Master Mix ( Takara ) . The quantifications of gene transcripts were performed by real-time PCR using Power SYBR GREEN PCR MASTER MIX ( ABI ) . GAPDH served as an internal control . PCR primers used to amplify the target genes were shown as follows: Gapdh: sense ( 5′-GAA GGG CTC ATG ACC ACA GT-3′ ) , antisense ( 5′-GGA TGC AGG GAT GAT GTT CT-3′ ) ; Rnf185: sense ( 5′-AGC AGA CTG GGA TTG TCT TG-3′ ) ; antisense ( 5′-CCA TTG CTG CTG CCA CTG GG -3′ ) ; Ifnb: sense ( 5′-AGA TCA ACC TCA CCT ACA GG-3′ ) , antisense ( 5′-TCA GAA ACA CTG TCT GCT GG-3′ ) ; Ifna4: sense ( 5′-ACC CAC AGC CCA GAG AGT GAC C-3′ ) , antisense ( 5′-AGG CCCT CTT GTT CCC GAG GT-3′ ) ; Cxcl10: sense ( 5′-CCT GCC CAC GTG TTG AGA T-3′ ) , antisense ( 5′-TGA TGG TCT TAG ATT CCG GAT TC-3′ ) ; GAPDH: sense ( 5′-CGG AGT CAA CGG ATT TGG TC-3′ ) , antisense ( 5′-GAC AAG CTT CCC GTT CTC AG-3′ ) ; RNF185: sense ( 5′-AGG ACC CCA GAG AGA AGA CC -3′ ) , antisense ( 5′-CAA TTC CAA AAG ACA TCT GG-3′ ) ; IFNB: sense ( 5′-ATT GCC TCA AGG ACA GGA TG-3′ ) , antisense ( 5′-GGC CTT CAG GTA ATG CAG AA-3′ ) ; IFNA2: sense ( 5′-CCT GAT GAA GGA GGA CTC CAT T-3′ ) , antisense ( 5′-AAA AAG GTG AGC TGG CAT ACG-3′ ) ; IFNA5: sense ( 5′-TCC TCT GAT GAA TGT GGA CTC T-3′ ) , antisense ( 5′-GTA CTA GTC AAT GAG AAT CAT TTC G-3′ ) ; ISG15: sense ( 5′-GAG AGG CAG CGA ACT CAT CT-3′ ) , antisense ( 5′-CTT CAG CTC TGA CAC CGA CA-3′ ) ; OASL-1: sense ( 5′-CCA TCA CGG TCA CCA TTG TG-3′ ) , antisense ( 5′-ACC GCA GGC CTT GAT CAG-3′ ) . Two-step immuno-precipitation and ubiquitination assays were performed as described previously [64] . For the first-round immunoprecipitation assay , cells were lysed by using Lysis buffer ( 50 mM Tris-Cl pH 7 . 4 , 150 mM NaCl , 1% Triton X-100 , 1 mM EDTA ) supplemented with a protease inhibitor cocktail ( Roche ) . Lysates were incubated with the anti-Flag ( M2 ) -agarose for two hours . The immunoprecipitates were washed three times with the same buffer . For the second-round immunoprecipitation assay , the immunoprecipitates were denatured by heating for 5 min in the Lysis buffer containing 1% SDS . The elutes were diluted by 10-fold with Lysis buffer followed by reimmunoprecipitating with the anti-Flag ( M2 ) -agarose . After extensive wash , the immunoprecipitates were subjected to immunoblot analysis . For denaturing immunoprecipitation , cells were lysed in 1% SDS buffer ( 50 mM Tris-HCl pH 7 . 5 , 150 mM NaCl , 1% SDS , 10 mM DTT ) and denatured by heating for thirty minutes . The lysates were centrifuged and diluted with Lysis buffer ( 50 mM Tris-HCl pH 7 . 5 , 150 mM NaCl , 1 mM EDTA , 1% Triton X-100 ) until the concentration of SDS was decreased to 0 . 1% . The diluted lysates were immunoprecipitated with the indicated antibodies for four hours to overnight at 4°C before adding protein A/G agarose for two hours . After extensive wash , the immunoprecipitates were subjected to immunoblot analysis . SDS-polyacrylamide gel electrophoresis ( SDS-PAGE ) and immunoblotting were performed as previously described[65] . Native gel electrophoresis for IRF3 dimerization was carried out as described previously [66] . The cGAMP activity assay was performed as described previously [21] . Briefly , L929 cells transfected with siRNAs were untreated or treated with HT-DNA for 6 hr and homogenized by douncing in the hypotonic buffer ( 10 mM Tris-HCl , pH 7 . 5 , 10 mM KCl , 1 . 5 mM MgCl2 , 1 mM DTT , 1mM PMSF ) at 4°C . The homogenates were centrifuged at 100 , 000 RPM for 20 min at 4°C . After heated at 95°C for 5 min , the supernatant was centrifuged again at 12 , 000 RPM for 10 min to remove any precipitants . The heat-resistant lysates were mixed with fresh 106 L929 cells in a 12 . 5 μl reaction containing 2 mM ATP , 1 U/μl of Benzonase and 2 ng/μl of PFO for 1 . 5 hr at 30°C . The cells were then subjected to the Native PAGE assay . For the synthesis of polyUb chains , purified GST-RNF185 or mutants , His-Flag-cGAS , was incubated with E1 ( 50 nM ) , E2 ( 0 . 3 mM ) , ubiquitin ( 10 μM ) ( Boston Biochem ) in a reaction buffer containing 50 mM Tris–HCl , pH 7 . 5 , 5 mM MgCl2 , 2 mM ATP , 2 mM DTT . The reaction was carried out at 37°C for 1 hr and then resolved by SDS-PAGE . Ubiquitinated products were detected by immunoblotting with indicated antibodies . RNF185 WT or RNF185 C39A catalyzed ubiquitinated cGAS or mutant was mixed with reaction buffer ( 20 mM HEPES , pH 7 . 5 , 5 mM MgCl2 , 2 mM ATP , 2 mM GTP ) in the presence of Salmon sperm DNA . After incubation at 37°C for 45 min , the samples were centrifuged at 16 , 000 × g for 10 min . The product in the supernatant was separated from cGAS and DNA by passing through a 10kD ultrafiltration filter ( Millipore ) . The samples were diluted by 5-fold and loaded onto a MonoQ ion exchange column ( GE Healthcare ) equilibrated with the running buffer ( 50 mM Tris-HCl pH 8 . 5 ) and eluted with a NaCl gradient of 0 to 0 . 5 M in the running buffer . HSV-1 and HSV-1-GFP were kindly provided by Dr . Wentao Qiao ( Nankai University , Tianjin , China ) and Dr . Chunfu Zheng ( Suzhou University , Suzhou , China ) , respectively . HSV-1 was propagated and titered by plaque assays on Vero cells . SeV replication were measured as viral RNA expression using quantitative PCR with the following specific primers: sense ( 5′- GCT GCC GAC AAG GTG AGA GC -3′ ) , antisense ( 5′- GCC CGC CAT GCC TCT CTC TA -3′ ) . The MEF cells infected by HSV-1-GFP were quantified using a FACS Calibur ( BD Biosciences ) and the data was analyzed using Flowjo software ( Tree Star ) . Concentrations of the cytokine in culture supernatants were measured by VeriKine Kit ( PBL Assay Science ) according to the manufacturer's instructions . Confocal microscopy was performed as previously described [67] . Briefly , cells seeded onto glass coverslips were fixed with 4% paraformaldehyde in PBS for 20min , and then permeabilized with 0 . 1% Triton X-100 and blocked with 5% bovine serum albumin at room temperature . Then , the cells were incubated with the indicated primary antibodies followed by staining with fluorescent-conjugated secondary antibodies ( Jackson Immuno-Research Laboratories ) . Nuclei were counterstained with DAPI ( Sigma-Aldrich ) . For mitochondria staining , living cells were incubated with 300 nM Mito Tracker Red ( Invitrogen ) for 10 min at 37°C . Slides were mounted with fluorescent mounting medium ( Dako ) . Imaging of the cells was carried out using Leica laser scanning confocal microscopy under a 64× oil objective . Mitochondria and ER membranes were purified on discontinuous sucrose gradients as previously described , with some modifications [24 , 68] . Briefly , MEF cells in ice-cold MTE buffer ( 0 . 27M mannitol , 10mM Tris-HCl , pH 7 . 4 , 0 . 1mM EDTA ) were lysed by using a dounce homogenizer . Lysed cells were centrifuged at 700g for 10 min , and the supernatant was collected . The supernatant was then centrifugated at 15 , 000g for 10 min to obtain the crude Mitochondria fraction , and post mitochondrial supernatant was used for purification of ER fractions . The crude mitochondria pellet was resuspended in MTE buffer , and was layered on top of the discontinuous sucrose gradients ( 1 . 0M and 1 . 7M sucrose in 10mM Tris-HCl , pH 7 . 5 ) and centrifugated at 40 , 000g for 22 min . Mitochondria fraction was collected and pelleted by centrifugation at 15 , 000g for 10 min . Purified mitochondria were resuspended in PBS and prepared for western blot analysis . To isolate ER fractions , post-mitochondrial supernatant was layered on discontinuous sucrose gradients ( 1 . 3 M , 1 . 5M and 2 . 0M sucrose in 10mM Tris-HCl , pH 7 . 6 ) and centrifugated at 100 , 000g for 70 min . The ER fraction at the interface between the supernatant and the 1 . 3M sucrose was collected , and pelleted by centrifugation at 100 , 000g for 45 min . The purified ER membranes were resuspended in PBS and prepared for western blot analysis . Student’s t test was used for the statistical analysis of two independent treatments . The difference in RNF185 mRNA level , ISG15 mRNA level or OASL-1 mRNA level between subject groups was analyzed by Mann-Whitney test . For all tests , a P value of < 0 . 05 was considered statistically significant . | Ubiquitination has been demonstrated to serve as an effective means to catalyze the rapid , dynamic and versatile regulatory processes that are activated when hosts face microbes . Given the critical functions of cytosolic DNA sensing pathway in anti-viral innate immune responses and the pathogenesis of autoimmune diseases , they are subjected to manifold spatial and temporal modulations shaping the strength and duration of the signaling pathways . Recent progress has characterized the cyclic GMP-AMP synthase ( cGAS ) as the primary DNA sensor that initiates stimulator of interferon genes ( STING ) -dependent signaling pathway . However , it remains poorly understood how cGAS activity is modulated dynamically . In this study , we identify E3 ubiquitin ligase RNF185 as a positive regulator of cGAS-STING signaling . Knockdown of RNF185 significantly attenuates IRF3-responsive gene expression . ER-resident RNF185 interacts with cGAS and catalyzes the K27-linked poly-ubiquitination of cGAS upon HSV-1 challenges , which thus potentiates cGAS enzymatic activity . Notably , systemic lupus erythematosus ( SLE ) patients have elevated expression of RNF185 mRNA . Our study uncovers RNF185 as the first E3 ubiquitin ligase of cGAS and suggests RNF185 as an important target for modulating antiviral response . | [
"Abstract",
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... | 2017 | The E3 ubiquitin ligase RNF185 facilitates the cGAS-mediated innate immune response |
HIV and related primate lentiviruses possess single-stranded RNA genomes . Multiple regions of these genomes participate in critical steps in the viral replication cycle , and the functions of many RNA elements are dependent on the formation of defined structures . The structures of these elements are still not fully understood , and additional functional elements likely exist that have not been identified . In this work , we compared three full-length HIV-related viral genomes: HIV-1NL4-3 , SIVcpz , and SIVmac ( the latter two strains are progenitors for all HIV-1 and HIV-2 strains , respectively ) . Model-free RNA structure comparisons were performed using whole-genome structure information experimentally derived from nucleotide-resolution SHAPE reactivities . Consensus secondary structures were constructed for strongly correlated regions by taking into account both SHAPE probing structural data and nucleotide covariation information from structure-based alignments . In these consensus models , all known functional RNA elements were recapitulated with high accuracy . In addition , we identified multiple previously unannotated structural elements in the HIV-1 genome likely to function in translation , splicing and other replication cycle processes; these are compelling targets for future functional analyses . The structure-informed alignment strategy developed here will be broadly useful for efficient RNA motif discovery .
RNA plays a direct role in most biological processes [1] , and multiple examples of RNA function are found in the replication cycles of positive-strand RNA lentiviruses [2] . Viral RNA genomes function at two distinct levels: in the linear encoding of protein sequences and in functional higher-order RNA structures . Constrained by a small genome size , these viruses make efficient use of limited genome space in terms of both sequence allocation and densely arranged regulatory RNA structures . RNA elements in the human immunodeficiency virus ( HIV ) genome play important regulatory roles throughout the replication cycle . During transcription of the integrated viral genome , a stem-loop structure in the 5ʹ untranslated region ( UTR ) , called TAR , binds the Tat protein to recruit proteins involved in transcription [3 , 4] . In the env gene , the Rev response element ( RRE ) binds the viral Rev protein , allowing unspliced and partially spliced viral mRNA to be exported out of the nucleus [5] . During translation , the gag-pol frameshift element modulates the reading frame of the ribosome , tightly regulating production of the Gag-Pol polypeptide [6 , 7] . Stem-loop structures in the Psi packaging element are required for efficient packaging of viral genome into nascent virions [8] . Multiple pseudoknots modulate replicative functions [9] . Although most structural characterization of HIV-related RNA genomes has focused on the 5ʹ and 3ʹ untranslated regions , recent analyses make clear that the central coding region of HIV genomes has extensive potential to base pair and form higher-order RNA structures [10 , 11] . Although the importance of many structured RNA elements is supported by direct experimental validation , the functional significance of many other RNA structures is unknown . More broadly , it remains difficult to rigorously identify conserved RNA structure motifs when sequence conservation is low without meticulous hand-alignment of annotated sequences . SHAPE chemical probing makes possible powerful and direct experimental interrogation of higher-order RNA structure . In the SHAPE approach , a structurally selective electrophile is used to acylate the 2ʹ-hydroxyl of unstructured or conformationally dynamic RNA nucleotides [12] . The extent of modification is roughly inversely proportional to the tendency of an RNA nucleotide to participate in an RNA base pair or other structural interaction . SHAPE has recently been adapted to readout by massively parallel sequencing using mutation profiling . Mutational profiling , or MaP , exploits the ability of reverse transcriptase to extend through the site of a chemical lesion in RNA and to record the RNA modification as a sequence change in the synthesized cDNA [9] . Chemical adduct-induced sequence changes can then be related to SHAPE reactivities on an absolute scale . The combined approach , called SHAPE-MaP , allows facile SHAPE-based structural characterization of complex RNA molecules and has thus far been applied to the RNA genomes of both HIV-1 [9] and hepatitis C virus [13] . To address the functional significance of RNA structures in HIV-related genomes , we characterized the conservation of structural features across the genomes of HIV-1 ( strain NL4-3 ) [14] and two related primate lentiviruses , SIVcpz MB897 [15] and SIVmac239 [16 , 17] . Fig 1 illustrates the analysis workflow . Using comprehensive SHAPE-MaP chemical probing data from each of the three RNA genomes , structure-dependent sequence alignments were generated . We then identified areas in which chemical modification patterns were statistically correlated . Finally , we generated secondary structure models taking into account both SHAPE reactivities and sequence covariation . This analysis identified multiple regions of structural similarity across the three HIV-related strains that included all previously identified well-characterized RNA elements . Strikingly , we also identified multiple previously undescribed structural elements that are clearly conserved among HIV-1 and related viruses . These elements are compelling sites for follow-up functional studies and are potential therapeutic targets . Analysis is fully automated , and we anticipate that our structure-based sequence comparison strategy will see broad application as whole-transcriptome chemical probing data become available .
Viral strains were selected based on epidemiological importance and with respect to their divergence from reference strain NL4-3 , a member of HIV-1 group M . SIVcpz MB897 ( SIVcpz ) infects chimpanzees , and the SIVcpz virus is thought to have given rise to the HIV-1 strains responsible for the worldwide AIDS epidemic [18 , 19] . SIVmac239 ( SIVmac ) is derived from a virus that infects sooty mangabeys and is capable of infecting macaques . This strain is widely used as the reference strain for the SIVsm/HIV-2 lineage . Of the two strains studied , SIVmac is the more distantly related to HIV-1 group M strains [20] . SIVcpz and SIVmac have sequence identities of 77 . 4% and 54 . 6% , respectively , when compared to NL4-3 using standard sequence-based alignments . Whole-genome SHAPE data for HIV-1 were obtained previously [9] , and SHAPE data for SIVcpz and SIVmac were generated for this work . Authentic SIVcpz and SIVmac genomic RNAs were purified from mature virions using a non-denaturing approach [21] . To preserve secondary and tertiary structures in the RNAs , no heating steps or chaotropic agents were used during RNA genome purification . Chemical modification of the viral RNAs with SHAPE reagent 1-methyl-7-nitroisatoic anhydride ( 1M7 ) was performed under physiological-like ion conditions [12 , 22] . Following chemical probing , the extent of SHAPE-adduct formation at each nucleotide was determined by massively parallel sequencing using mutational profiling [9] . SHAPE reactivity values were determined at each position by comparing mutation rates of a 1M7-modified sample relative to background controls . SHAPE reactivity is correlated with the flexibility of a given nucleotide; nucleotides with low SHAPE reactivity tend to participate in base pairs or other interactions , whereas nucleotides with high SHAPE reactivity tend to be in unstructured regions of the RNA . SHAPE reactivity measurements were made for an average of 98% of the nucleotides in each RNA genome ( Supporting Information ) . Pairwise whole-genome alignments of HIV-1 , SIVcpz , and SIVmac RNAs were determined by a SHAPE-dependent dynamic programming algorithm [23] ( see preceding companion article in this issue ) . From these structurally-directed pairwise alignments , we generated a single , multiple-sequence alignment [24] ( Fig 2A ) . All regions previously shown to contain functional RNA structures were aligned correctly by this fully automated approach . Aligned elements fell in both untranslated regions ( for example , 5' and 3' TAR stems and the Psi packaging element ) and coding regions ( gag-pol frameshift element and the RRE ) . In addition , the polypurine tracts in the pol and nef genes ( cPPT and PPT , respectively ) [25 , 26] aligned precisely . The fully automated pairwise HIV-1 and SIVcpz alignment is highly accurate relative to the manually edited alignments in the Los Alamos National Laboratory ( LANL ) HIV database [27] . Despite not explicitly considering codon alignment , our pairwise SHAPE-structure based alignments have sum-of-pairs and column scores of 95 . 6% and 94 . 5% , respectively , relative to LANL alignments ( sum-of-pairs and column scores report similarity to a reference alignment considering aligned position pairs and aligned columns , respectively ) . Relative to LANL alignments , the three-sequence SHAPE-dependent alignment considering HIV-1 , SIVcpz , and SIVmac show sum-of-pairs and column scores of 75 . 5% and 56 . 9% , respectively . In general , areas of disagreement between the SHAPE-structure and the LANL alignments , based on windowed column scores , lie in regions of the HIV-1 sequence with multiple overlapping reading frames and in regions encoding the variable loops in the env gene ( S1 Fig ) . It is not clear which alignments are actually superior in these regions . In addition , RNA structure and codon alignments may not be strongly conserved in these areas , due to the selective pressure of multiple reading frames or to high mutation rates in the variable sequence regions . To evaluate the relationships among SHAPE data for the three RNA genomes , multi-variable linear regression was performed across the three-genome multiple sequence alignment over 200-nucleotide windows ( Fig 2 ) . By identifying areas with correlated SHAPE reactivities ( Fig 2A ) , we sought to find areas in the sequence alignment with conserved RNA structures . SHAPE data were fit to a three-dimensional linear regression model , and the correlations among the three HIV-related strains were evaluated using the F-test . Based upon F-statistic measurements , p-values defining the significance of the correlation were determined for SHAPE values over the entire alignment ( see Methods ) . These p-values were used to identify structural elements conserved among all three RNA genomes ( Fig 2B ) . In addition , a t-test was used to gauge the pairwise correlations between HIV-1 and SIVcpz or SIVmac ( Fig 2C ) . Multiple regions across the three-genome alignments showed significant interdependences in SHAPE reactivities ( Fig 2B; defined as F-test p-value ≤ 0 . 01 ) . Regions with statistically significant SHAPE reactivity correlations occurred both at the 5ʹ and 3ʹ ends and in internal coding regions . Without exception , all previously identified functional elements are located in regions with correlated SHAPE reactivities . Critically , there are also multiple regions of similarity where no functional RNA structures had previously been identified . These newly identified regions lie in the gag , pol , and env genes . Generally , regions that are statistically significant by both pairwise t-test analyses coincided with regions that correlated across all three genomes by F-test ( Fig 2C ) . As expected , the pairwise t-test analyses showed that statistically significant SHAPE reactivity correlations are more widespread for the HIV-1 and SIVcpz comparison than for the more distantly related HIV-1 and SIVmac viruses . There are defined regions where correlations by F-test across the three-genome alignment are not recapitulated in HIV-1 and SIVmac pairwise t-test analyses , most conspicuously near NL4-3 residues 4400 and 7900 . These are likely areas of structural conservation between HIV-1 and SIVcpz that are not shared between HIV-1 and SIVmac . Using the SHAPE-directed multiple sequence alignment , we developed consensus secondary structure models based on both nucleobase identity and SHAPE reactivity data [23] ( Figs 3 and 4 ) . Secondary structure models were generated for areas with statistically significant correlations ( F-test p-value < 0 . 01 ) . Consecutive regions with significant correlations were combined into single regions for structure modeling . Based on this criterion , eleven areas were selected from the three-genome alignment , ranging in length from 255 to 1285 nucleotides and collectively covering 68 . 4% of the HIV-1 NL4-3 genome . Consensus secondary structures of regions with structural similarity implied by correlated SHAPE data were generated using three orthogonal inputs: RNA nearest-neighbor free energy rules , sequence covariation , and SHAPE reactivities [28–31] . For each region , two consensus structures were developed: one incorporating sequence alignment and SHAPE data for all three genomes and the other using pairwise information for only HIV-1 and SIVcpz , the two more closely related genomes . Consensus base pairs with pairing probabilities greater than 95% that did not disagree between the two consensus structures were then used to restrain a SHAPE-directed secondary structure model for HIV-1 [28 , 32] . Consensus base pairs from the three-genome and HIV-1/SIVcpz comparisons are shown on the final constrained HIV-1 model ( Figs 3 and 4 ) . Consensus base pairs are highly over-represented in known functional elements ( Fig 5 ) . Importantly , consensus base pairs are also found in multiple areas with no previously identified function . In general , consensus base pairs occur more frequently at the 5ʹ and 3ʹ ends of the genome , though regions with notable consensus base pairing also occur in the central coding region .
Cellular and viral RNAs encode information in the form of higher-order RNA structures . The structures of a vast majority of transcribed RNAs are uncharacterized , and new strategies are needed to efficiently and rigorously search for functionally important structural elements . Here we applied an approach that makes possible motif discovery for elements whose function is implied by structural conservation; the approach is described in detail in the preceding companion manuscript [23] . First , model-free RNA structure comparisons were performed using whole-genome structure information experimentally derived from nucleotide-resolution SHAPE reactivities . Consensus secondary structures were then constructed for strongly correlated regions by taking into account both SHAPE probing structural data and nucleotide covariation information from structure-based alignments . We identified 314 base pairs with pairing probabilities greater than 95% that are shared between the two distinct consensus models developed in this work , one generated considering HIV-1 , SIVcpz , and SIVmac RNA genomes and the other considering only the more closely related HIV-1 and SIVcpz sequences . Of these base pairs about half ( 171 base pairs , 54 . 5% ) are in previously described elements . Strikingly , however , nearly as many base pairs with strong consensus support exist in regions with no known function ( 143 base pairs , 45 . 5% ) . That these structures are conversed across diverse HIV-related strains implies critical , if currently unknown , functionality . The structural model developed in this work accurately reflects most of what is known about the genomic RNA structure of HIV-1 and related lentiviruses . Known functional elements are recapitulated precisely and are enriched with conserved base pairs ( Fig 5 ) . Our analysis provides additional perspective on these well-studied elements . For example , the TAR secondary structure for SIVmac forms two similar , but distinct , stem-loops [33] . The single stem-loop TAR elements from HIV-1 and SIVcpz align specifically with the second of the two stem-loops in SIVmac , suggesting greater structural similarity . Structural conservation as evidenced by correlated SHAPE reactivities is found throughout the HIV-1 genome including in the env and pol genes ( Fig 2 ) , consistent with studies implicating conserved RNA structure in these regions [34 , 35] . A conserved structural element in the pol gene , at the protein domain junction between protease and reverse transcriptase , shares structural features with a previously identified structural element ( Fig 3; nucleotides 2015–2121 in structure 3 ) [36] . This work also expands on the results of previous SHAPE-based analyses of HIV genomic RNAs . Recently , SHAPE-MaP studies focused on HIV-1 alone were used to model the whole-genome secondary structure [9] . Though that study and the work described here both ultimately resulted in secondary structure models , each approach has unique advantages . The prior work introduced the melded use of SHAPE reactivities and Shannon entropies to identify de novo regions with well-determined stable RNA structures based on information from a single sequence . This work uses evolutionary conserved sequence and structural alignment to identify regions with conserved structure and , additionally , to identify specific regions within larger motifs that are the most conserved structurally . The SIVmac genome has also been previously analyzed by SHAPE [11] , and the resulting secondary structure model was compared to a SHAPE-directed secondary structure model for HIV-1 [10] . Model-based comparisons were made by hand , guided by manually edited sequence alignments . From this model-based manual comparison , 71 base pairs were identified as directly conserved between HIV-1 and SIVmac [11] . These base pairs are largely recapitulated in this work , including a stem-loop structure present at splice acceptor site one ( called A1 ) ; perturbation of this structure dramatically impacts splicing at this site [11] . We do not see evidence of the shifting pairing partners in the RRE described in the prior SIVmac study . Despite not explicitly considering protein sequence , our structure-informed alignment preserves codon alignment at the RRE and accurately predicts its accepted secondary structure [11] . The strategy for structural motif discovery directed by fully automated SHAPE-based structure alignment created in this work is notably more successful than prior manual analyses , both at recapitulating known functional structures and in discovering new elements whose structures are conserved across diverse viral strains . This success is attributable to three features . First , the SHAPE-MaP approach itself is fully automated and avoids systematic errors or biases introduced by manual data processing required by prior capillary electrophoresis-based approaches . Second , sequence comparisons performed in this work directly consider a first-order metric of RNA structure—SHAPE reactivity—as opposed to base identity alone . Third , the approach created in this work performs these comparisons in a model-free way , avoiding complications arising from the complexity of large RNA secondary structure modeling . Ultimately , the biological relevance of structure motifs identified in genome-wide studies must be examined and validated by direct experimentation . This work strongly constrains regions that merit such investigation . For example , in one recent study , four RNA hairpins were selected for mutational studies to determine their effects on viral replication [37] . Mutations in these four hairpins did not affect viral replication . Two of the four hairpins evaluated in the recent study ( termed POL1 and POL3 ) fall in areas of insignificant structural correlation . A third ( NEF1 ) has a different consensus-supported structure . The remaining hairpin ( POL2 ) appears in the final HIV-1 structure model; however , this hairpin is not conserved in either the three- or two-genome consensus predictions . Thus , none of these hairpins would have been good candidates for mutagenesis studies and functional characterization based on the models developed in this work . In contrast and as described below , this work identifies multiple motifs that are compelling targets for future functional studies . Proteins fold co-translationally , and RNA structural stability affects ribosomal pausing during translation [38 , 39] . Given that the extent of RNA structure formation influences pausing of the ribosome , local RNA structure could in turn modulate protein structure and associated activity [40] . Prior analysis of the HIV-1 genome revealed a potential relationship between highly structured regions of the RNA genome and the junctions between protein domains in HIV-1 polyprotein precursors [10]; however , it was not then possible to identify specific RNA structures that might define the relationship between RNA structure and translation . Here we observed that multiple conserved structured elements occur at or near protein-protein junctions and at protein inter-domain boundaries . Conserved structured elements occur in gag at the junction between p17 ( matrix ) and p24 ( capsid ) ( Fig 6A , upper left ) , in gag-pol at the junction between protease and reverse transcriptase ( Fig 6A , lower left ) , and between RNase H and integrase coding domains ( Fig 6A , right ) . Base pairs in these regions show conservation in both the HIV-SIVcpz comparison and in the three-genome consensuses ( Fig 6 ) . In each proposed conserved structure element , conserved helices are present near the domain junction with a stable conserved helix occurring 3' of the protein domain junction . Automated SHAPE-based alignment also identified structural elements that are clearly conserved among the three HIV-related strains but for which it is currently difficult to propose functions . Most strikingly , there are two regions that contain long helical elements with extensive conservation of base pairing ( Fig 6B ) . Including potential stacking interactions , these elements contain helical elements extending for 20 or more base pairs . Polypurine tracts are functionally critical retroviral sequence elements that act as RNA primers for positive-strand DNA synthesis [41] . How these elements function mechanistically is unknown . Following first-strand DNA synthesis , the PPT RNA-DNA hybrid duplex is preserved , and the rest of the RNA genome is degraded . Each of the retroviruses studied here has two distinct PPT sequences: the PPT sequence in the nef gene and the central polypurine tract ( cPPT ) in the pol gene . The cPPT and PPT regions were previously noted to have similar patterns of SHAPE reactivity based on analysis of SHAPE probing data for HIV-1 and SIVmac [11] . Consistent with this prior finding , we found that the polypurine sequences have a consistent SHAPE reactivity pattern across all three genomes: Adenines show high reactivity , and the guanine nucleotides are unreactive ( Fig 7A ) . The RNA regions spanning the cPPT and PPT also showed strong statistical interdependencies in whole genome alignments ( Fig 2 ) . Both the cPPT and PPT , contain conserved base pairs in consensus structural models ( Fig 7B ) , and the cPPT and PPT regions show striking structural similarities in their predicted models . The 3ʹ end of the G-rich region forms a structurally conserved helix . The helix forms the boundary for a single-stranded region containing the A-rich 5ʹ end of the polypurine sequence . This single-stranded region contains short helical elements that are conserved in consensus models for the PPT ( Fig 7B ) . This conserved structure may contribute to the known function of the PPT tract as an RNA primer for second-strand DNA synthesis . Consensus cPPT/PPT structures are conspicuously positioned near the RNase H cleavage site , suggesting a possible connection between RNA structure and recognition of the PPT by the RNase H domain of reverse transcriptase . The 3ʹ end of the PPT is within a helical element . RNA secondary structure has been shown to influence polymerization-dependent RNA cleavage by inducing pausing of the reverse transcriptase [42 , 43] . Although this element would not account for cleavage precisely at the 3ʹ end of the PPT [41] , secondary structure-dependent cleavage during reverse transcription may be a first step in the processing of the PPT RNA primer . These conserved RNA structures may also have additional functions . With advances in high-throughput chemical probing , interrogation of RNA structure at the transcriptome level is now possible . Structured motif discovery and annotation requires rigorous and accurate approaches for automated RNA structure characterization and motif discovery . Using structure-based alignments derived from SHAPE reactivities , we identified statistically correlated RNA structure motifs conserved across related viral genomes and then modeled secondary structures for these regions based on both sequence covariation and chemical probing-derived structural information . The resulting structures recapitulated all known functional elements in the HIV-1 RNA genome . Consensus base pairs were also discovered in structural elements with no currently known function; these are outstanding targets for future functional analysis . The ideas and general approaches described here provide a framework for functional RNA structure discovery at the RNA genome and transcriptome levels . All SHAPE-MaP data , alignments , and secondary structure models developed in this work are fully available both in the Supporting Information and at the corresponding author's web page http://www . chem . unc . edu/rna/ .
Viruses were produced and genomic RNA purified as described [21] . Virus inocula were generated by transfection of the following plasmids into 293T cells ( using TransIT 293 , Mirus Bio ) . HIV-1 was derived from pNL4-3 ( GenBank accession no . AF324493; obtained through the NIH AIDS Reagent Program , Division of AIDS , NIAID , NIH , from Dr . Malcolm A . Martin ) [14] . The proviral plasmid containing SIVcpz MB897 ( GenBank accession no . JN835461 ) was a gift from Brandon F . Keele , AIDS and Cancer Virus Program [15] . The plasmid containing the SIVmac239 provirus ( GenBank accession no . M33262 ) was obtained through the NIH AIDS Reagent Program , Division of AIDS , NIAID , NIH , from Dr . Ronald C . Desrosiers ) [16 , 17] . During genomic RNA extraction , care was taken to avoid denaturation of RNA structure by heat or treatment with chaotropic agents . Following lysis with SDS and proteinase K , viral RNA was extracted three times using 25:24:1 phenol/chloroform/isoamyl alcohol , followed by two extractions with pure chloroform . Viral RNA was precipitated in 70% ( vol/vol ) ethanol with 300 mM KCl and stored at -80°C until use . Tubes containing roughly 10 μg of precipitated SIVcpz or SIVmac RNA in 70% ethanol were spun in a microfuge at 4°C for 45 min to pellet RNA . Ethanol was removed , and the pellets incubated at room temperature for 10 min to allow remaining ethanol to evaporate . The pellets were resuspended in 20 μL genome resuspension buffer [50 mM HEPES ( pH 8 . 0 ) , 200 mM potassium acetate] , and the resulting solution was characterized by absorption spectroscopy at 260 nm to determine RNA concentration . To determine SHAPE reactivities , three experiments were performed with SIVcpz and SIVmac samples: 1M7 modification of natively-folded RNA , a no-modification background control , and 1M7 modification of denatured RNA [9] . For 1M7 modification of natively-folded RNA and no-modification background controls , aliquots containing 1 μg of SIVcpz or SIVmac RNA were taken from precipitated RNA stocks . To these 1-μg aliquots , 3 μL of 100 mM MgCl2 were added , and the RNA solution was brought up to a volume of 90 μL using genome resuspension buffer . The RNA solution was then incubated at 37°C for 15 min before adding 10 μL of 100 mM 1M7 in DMSO ( 1M7 modification of natively folded RNA ) or 10 μL neat DMSO ( background control ) . The RNA solution was then incubated at 37°C for 3 min to allow complete reaction of 1M7 . The RNA solution was then held on ice until purification . For 1M7 modification of denatured RNA , an aliquot containing 1 μg of SIVcpz or SIVmac RNA was taken from precipitated RNA stocks . To this aliquot , 25 μL of 4 denatured control buffer was added [200 mM HEPES ( pH 8 . 0 ) , 16 mM EDTA] , and the RNA solution was brought to a volume of 40 μL using nuclease-free water . To this RNA solution , 50 μL of deionized formamide was added . The RNA solution was held at 95°C for 1 min and then added to 10 μL 100 mM 1M7 in DMSO . The reaction was held at 95°C for 1 min before transferring the reaction to ice . The RNA solution was held on ice until purification . RNA was then purified by affinity binding ( RNeasy Min-Elute kit; Qiagen ) . Following purification , sequencing libraries were generated as described [9] , and sequencing output was analyzed using the SHAPE-MaP pipeline [9] . Background mutation rates were high for the first 200 nucleotides of the SIVmac genome , resulting in unusual negative peaks for this region; SHAPE values for the first 200 nucleotides of SIVmac239 were therefore taken from prior work [11] . SHAPE-structure dependent alignments were performed as described [23] . Pairwise sequence alignments were generated by dynamic programming , using a SHAPE value comparison scoring metric . Pairwise sequence alignments were then used to create a multiple sequence alignment using T-Coffee [24] by considering only the pairwise SHAPE-dependent alignments . This approach does not use sequence identity and , instead , relies on matched sequence positions in the input alignments . SHAPE data were fit using least squares , where Y represents HIV-1 SHAPE values and X1 and X2 represent SIVcpz and SIVmac SHAPE values , respectively: Y=β0+β1X1+β2X2+εi Correlations between the three HIV-related strains were evaluated using the F-test , which evaluates the interdependency of data sets based upon a linear regression model . The F-test evaluates the following null hypothesis by the sum of squares due to lack-of-fit for the model: β1=β2=0 Based on the derived F-statistic measurements , p-values defining the significance of the interdependence of SHAPE values were determined over the entire alignment . In addition , t-tests were used to evaluate pairwise correlations between HIV-1 and either SIVcpz or SIVmac . Statistical analyses were performed over 200-nt windows in the multiple sequence alignment . Over each window , only positions with SHAPE values for each genome were considered; no gapped positions were included . Multi-variable linear regression analyses were performed using the NumPy , SciPy , and statsmodels Python modules [44 , 45] . Multi-variable linear models were created using least squares fitting . F-tests and t-tests were performed over each window using statsmodels [45] . We note that there are regions in the whole-genome alignment where the F-test is not significant but where one of the pairwise t-tests is significant . This disagreement likely reflects , in part , correlation between the SIVcpz and SIVmac data sets ( collinearity ) . A manually edited alignment considering diverse primate lentiviruses was taken from the 2012 HIV Compendium ( section “Alignment of Primate Lentivirus Complete Genomes” ) [27] . A reference multiple sequence alignment containing the NL4-3 sequence was generated by inserting this sequence into the HIV Compendium alignment using MAFFT [46] . Agreement between SHAPE-dependent and reference alignments was evaluated using sum of pairs and column score analyses [47] . Sum of pairs is the percentage of reference matched position pairs recapitulated in an alignment , and column score is the percentage of vertical columns that are shared with a reference alignment . Areas of interest for secondary structure modeling were selected based on F-test statistics of multi-variable linear regression models . If a given 200-nt window had an F-test p-value less than 0 . 01 , the corresponding 200-nt region was selected as an area of interest . Consecutive areas of interest were combined in the same secondary structure element . Secondary structures for the reference HIV-1 sequence were generated with a two-step procedure using RNAalifold and RNAfold , both of the Vienna-RNA software package [29 , 32 , 48] . First , consensus based pairs were generated using RNAalifold based on the SHAPE-directed sequence alignment . Two consensus secondary structures were predicted for each F-test-defined element . The first consensus considered HIV-1 , SIVcpz , and SIVmac sequences . The second consensus considered ( the more closely related ) HIV-1 and SIVcpz sequences only . Consensus structures were generated using the ribosum substitution matrix and a max base pairing distance of 600 nucleotides [49] . Consensus structure prediction incorporated SHAPE reactivities using a pseudo-free energy change potential [31] . Following consensus model generation , consensus base pairs were used to constrain a single-genome secondary structure prediction for HIV-1 . Base pairs from each consensus structure with pairing probabilities greater than 95% were added to a constraint list . The constraint list was curated such that consensus pairs were excluded if either ( i ) pairs with shared nucleotides contradicted each other in terms of base pairing partners or ( ii ) pairs from two consensuses were non-nested . HIV-1 structure predictions constrained by consensus pairs were performed with RNAfold . Predictions were constrained such that curated consensus pairs were maintained in the final structure . SHAPE reactivities were incorporated into secondary structure model using a pseudo-free energy potential [31]; the maximum allowed base pairing distance was 600 nucleotides . | Human immunodeficiency virus ( HIV ) is a persistent and critical threat to human health . Replication and pathogenesis of HIV is governed by information encoded in its single-stranded RNA genome . In addition to coding for viral proteins , the HIV genomic RNA forms base paired and higher-order structures that are critical for viral replication . It is likely that only a subset of functional RNA motifs has been identified . Here , we interrogate the structures of three diverse HIV-related viral genomes by nucleotide-resolution chemical probing . The three genomes include HIV-1 , the virus that infects humans , and SIVcpz and SIVmac , which are progenitors for the main branches of the two HIV evolutionary groups . We used a structure-informed alignment approach to generate consensus models for base-paired secondary structures that are shared by these three HIV-related genomes . With this approach , we were able to recapitulate all known RNA structures and , additionally , discovered multiple previously undescribed structural elements that are clearly conserved among major HIV groups . We anticipate that the methods described here will be broadly useful for RNA structure motif discovery and , more immediately , for identification of RNA targets in HIV that are promising sites for therapeutic intervention . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2015 | Structure-Based Alignment and Consensus Secondary Structures for Three HIV-Related RNA Genomes |
Early diagnosis of reactivated Chagas disease in HIV patients could be lifesaving . In Latin America , the diagnosis is made by microscopical detection of the T . cruzi parasite in the blood; a diagnostic test that lacks sensitivity . This study evaluates if levels of T . cruzi antigens in urine , determined by Chunap ( Chagas urine nanoparticle test ) , are correlated with parasitemia levels in T . cruzi/HIV co-infected patients . T . cruzi antigens in urine of HIV patients ( N = 55: 31 T . cruzi infected and 24 T . cruzi serology negative ) were concentrated using hydrogel particles and quantified by Western Blot and a calibration curve . Reactivation of Chagas disease was defined by the observation of parasites in blood by microscopy . Parasitemia levels in patients with serology positive for Chagas disease were classified as follows: High parasitemia or reactivation of Chagas disease ( detectable parasitemia by microscopy ) , moderate parasitemia ( undetectable by microscopy but detectable by qPCR ) , and negative parasitemia ( undetectable by microscopy and qPCR ) . The percentage of positive results detected by Chunap was: 100% ( 7/7 ) in cases of reactivation , 91 . 7% ( 11/12 ) in cases of moderate parasitemia , and 41 . 7% ( 5/12 ) in cases of negative parasitemia . Chunap specificity was found to be 91 . 7% . Linear regression analysis demonstrated a direct relationship between parasitemia levels and urine T . cruzi antigen concentrations ( p<0 . 001 ) . A cut-off of > 105 pg was chosen to determine patients with reactivation of Chagas disease ( 7/7 ) . Antigenuria levels were 36 . 08 times ( 95% CI: 7 . 28 to 64 . 88 ) higher in patients with CD4+ lymphocyte counts below 200/mL ( p = 0 . 016 ) . No significant differences were found in HIV loads and CD8+ lymphocyte counts . Chunap shows potential for early detection of Chagas reactivation . With appropriate adaptation , this diagnostic test can be used to monitor Chagas disease status in T . cruzi/HIV co-infected patients .
Chagas disease , caused by the protozoan Trypanosoma cruzi , affects an estimated 7 . 8 million people in the Americas [1] . Similar to HIV infection , Chagas disease is most prevalent in the adult population [2] . Massive rural-to-urban migration throughout has brought many cases of chronic Chagas disease into the city where patients are at risk for acquisition of HIV . This has created conditions for emergence of T . cruzi/HIV co-infection as a significant public health problem in the Americas . Bolivia has the highest prevalence of T . cruzi infection in the world; with adult seroprevalence figures of up to 30% in urban areas and up to 80–90% in some rural areas [3 , 4] . HIV infection remains under-diagnosed in Bolivia and there are no data about the epidemiology of T . cruzi/HIV co-infection in this country . After infection with T . cruzi , immunocompetent patients enter the acute phase , this phase is characterized by high parasitemia , mild and nonspecific febrile illness , and , rarely , life-threatening myocarditis and/or meningoencephalitis [5] . After 2 to 3 months , patients pass into the chronic phase , which is characterized by positive serology but microscopically undetectable parasitemia . The chronic phase persists life-long in the absence of successful treatment . Many people in the chronic phase will remain asymptomatic throughout life , but 20% will develop cardiomyopathy or mega-syndromes of the digestive tract [6] . Chagas disease is usually acquired during childhood in endemic regions , in contrast to HIV infection [7] . However , the chronic manifestations are not seen until adulthood . An estimated 20% of T . cruzi/HIV co-infected individuals develop T . cruzi reactivation . Presentation includes high levels of parasitemia and severe clinical manifestations; usually involving CNS syndromes ( 50–85% ) and/or myocarditis ( 10–55% ) [7–12] . Alterations in the CNS include meningoencephalitis and/or brain accesses that appear very similar , by neuroimaging , to those produced by Toxoplasma gondii reactivation . As such , direct detection of the parasite is needed to confirm the diagnosis . Mortality in patients with meningoencephalitis reaches 80–100% , partly as a consequence of late diagnosis and treatment [7] . Some studies suggest that early diagnosis and treatment with both benznidazole and combination antiretroviral therapy ( cART ) could be lifesaving in patients with CNS reactivation [7 , 13–14] . However , there are no well accepted criteria to identify patients at risk of reactivation . Serology is the standard diagnostic modality in the chronic phase , but does not distinguish between T . cruzi infection with and without reactivation . Current criteria for reactivation are based on microscopic observation of the parasite in blood , but because of its low sensitivity , this technique detects reactivation when the parasitemia is high [15] . By this time , symptoms may be severe and rescue treatment is likely to fail [15 , 16] . Furthermore , microscopy requires extensive training in specimen preparation , and discordant readings by microscopists are frequent . Blood culture and xenodiagnosis have higher sensitivity but take 20–60 days to give conclusive results; both are rarely used for diagnosis [15] . Quantitative polymerase chain reaction ( qPCR ) has been suggested as a highly efficient method for monitoring levels of parasitemia in T . cruzi/HIV co-infected patients [15] . The qPCR is used to monitor levels of parasitemia as well as risk of reactivation in immunocompromised individuals after organ transplantation in the USA [17 , 18] . However , in Latin America , qPCR is not routinely used . A study with T . cruzi/HIV co-infected patients from Brazil demonstrated that the majority of T . cruzi/HIV co-infected patients have substantially higher parasitemia levels when compared to immunocompetent T . cruzi-infected individuals . Some of these patients had detectable parasitemia by microscopy even in the absence of symptoms [15] . These asymptomatic patients do not appear to have greater short-term mortality , but they are hypothesized to be at increased risk of developing symptomatic reactivation [15] . High levels of parasitemia may represent an intermediate phase that precedes clinical reactivation . In such circumstances , preemptive treatment may be justified [10 , 15] . However , systematic data on this hypothesis is lacking . Detection of urine T . cruzi antigens has been shown to correlate with parasitemia levels in animals [19] and could be a convenient , non-invasive tool to monitor levels of parasitemia in HIV patients . However , antigens in urine exist at very low concentrations; below the limit of detection of conventional immunoassays . Furthermore , antigens are masked by highly abundant resident proteins , and are rapidly degraded by endogenous and exogenous enzymes [20–25] . A novel nanotechnology based on the use of nano-porous particles that contain high affinity chemical baits ( trypan blue ) in the inner core is proposed for concentration and preservation of antigens in urine [20–25] . This technology ( Chagas urine nanoparticle test , Chunap ) has been applied in the direct diagnosis of congenital Chagas disease with excellent agreement with standard diagnostic tests [26] . Nano-porous particles are synthetized with poly ( N-isopropyl acrylamide ) ( pNIPAm ) and N , N′-methylenebisacrylamide ( BAAm ) and coupled with chemical baits via amidation reaction . The nano-porous structure of the particles performs size sieving , allowing proteins to penetrate inside the particles , depending on their molecular weight and their dimensional shape . The trypan blue inside the particles captures proteins with extremely high affinity ( KD < 10−12 M ) within minutes [20–26] . A sensitive but relatively simple noninvasive test for monitoring T . cruzi infection in HIV co-infected is needed . This tool could lead to early treatment and may be lifesaving . In this study , we demonstrate that levels of T . cruzi antigens determined by Chunap are associated with levels of parasitemia in T . cruzi/HIV co-infected patients and could be a valuable non-invasive tool for monitoring Chagas disease reactivation in HIV co-infected patients .
The protocols were approved by the institutional review boards of the study hospitals ( Hospital Clínico Viedma , Centro de Vigilancia y Referencia de HIV/AIDS , the Instituto de desarrollo Humano and the Colectivo de Estudios Aplicados , Desarrollo Social , Salud y Medio ambiente in Cochabamba , and the Universidad Catolica in Santa Cruz , Bolivia ) , Asociacion Benefica Prisma ( Lima , Peru ) and the Johns Hopkins University ( Baltimore , MD ) . We evaluated 55 samples of HIV patients ( 31 T . cruzi-infected and 24 T . cruzi uninfected ) from Cochabamba and Santa Cruz , Bolivia . A written informed consent was obtained from all participants . The diagnosis of HIV infection was performed according to the Bolivian National Control Program of HIV/AIDS , and was based on detection of specific antibodies by an ELISA test ( Vironostika HIV UNIformII Ag/Ab , Biomerieux ) and Western blot ( New Lab Blot I , BioRad ) . Blood and urine samples were obtained early on in hospitalization and none had received T . cruzi treatment . Confirmation of T . cruzi infection was based on positive results by 2 or more of the following commercial tests: Chagatest ELISA ( Wienner Lab , Rosario- Argentina , sensitivity: 98 . 81% and specificity: 99 . 62% ) , Chagatest ELISA recombinant v 3 . 0 ( Wienner Lab , Rosario , Argentina; sensitivity: 99 . 3% and specificity: 98 . 7% ) , and the indirect hemagglutination test ( IHA ) ( PolyChaco . Sensitivity: 98% , Specificity: 99% ) . Medical records of each participant were reviewed to obtain data on HIV load , CD4+ and CD8+ T-cell counts . Most patients were recently diagnosed with HIV and were not receiving ART at the time of diagnosis . As a result , high viral loads were observed in patients with and without Chagas disease ( mean: 220969 . 5 and 84960 . 6 copy number/ml blood , respectively ) . We therefore used a classification of high HIV load as follows: 1 ) <5000 copies/ml , 2 ) ≥5000–30 000 copies/ml , and 3 ) >30 000 copies/ml [27 , 28] . The immunosuppression status was determined by the levels of CD4+ T-cell counts according to CDC classification system as follow: 1 ) ≤ 200 , 2 ) 201–500 and 3 ) ≥ 500 [29] . Reactivation of T . cruzi infection was determined by detection of circulating parasites by micromethod . In this technique , blood samples are collected in 4–6 heparinized microhematocrit tubes , centrifuged and the buffy coat layer is examined microscopically for parasites [30] . Quantification of the number of copies of DNA of the parasite in blood was performed by quantitative PCR [31–34] . Patients with Chagas disease were considered to be in one of three categories according to the levels of parasitemia: High parasitemia or cases with reactivation of Chagas disease ( n = 7 , patients with positive micromethod and PCR ) , moderate parasitemia ( n = 13 , patients with positive PCR but negative micromethod ) and negative parasitemia ( n = 12 , patients with negative PCR but positive by serology ) . Patients were asked to provide the first urine of the day before ingestion of liquids , where midstream specimens were collected . Urinalysis was done using urine test strips ( Multistik 10 SG , Siemens , NY-USA ) . Mean values of urine specific gravity was within normal levels ( mean: 1 . 022 , SD: 0 . 008 ) . Urine samples ( 10 mL ) were immediately centrifuged after collection at 3000 rcf for 10 min and the supernatant was stored in liquid nitrogen or -80°C until use . For antigen detection the supernatant was adjusted to pH 5–6 with 1M HCl . Poly N-isopoprylacrylamide ( NIPAm ) particles coupled with trypan blue dye ( Poly ( NIPAm/TB ) ) were synthesized as previously described [20–26] . Urine samples ( 10 mL ) were incubated with 1 mL of poly ( NIPAm/TB ) particle suspension ( 7 . 2 mg/ml dry weight ) for 30 min at room temperature under rotation . Capturing , concentration , and elution of antigens from the particles was done as previously described [26] . Eluates were mixed with 10 μl of 250 mg/mL trehalose ( Fluka Chemicals , MO-USA ) solution and 10 μl of 1% ( v/v ) red food dye ( McCormick , MD-USA ) in MilliQ water and dried under nitrogen flow ( Organomation ) . Dried eluates were suspended in 40 μl of SDS sample buffer ( 50 mM TrisHCl pH 6 . 8 , 2% SDS , 1% 2-mercaptoethanol , 10% glycerol and 0 . 02% bromophenol blue ) . The effective concentration factor is 250 fold based on volumetric ratio ( initial volume / final volume = 10000 μl /40 μl ) . Aliquots of 20 μl of re-suspended antigens were heated to 100°C for 7 min . Electrophoresis and Western Blot analysis of the antigens were performed as previously described [26] . Briefly , antigens were detected with an anti-T . cruzi lipophosphoglycan ( LPG ) mouse monoclonal antibody ( Cedarlane Laboratories USA Inc , NC-USA ) , diluted 1:250 in PBS with 0 . 2% I-Block and 0 . 1% Tween 20 . After six washing steps with PBS supplemented with 0 . 1% Tween 20 , antigens were incubated with peroxidase conjugated goat anti-mouse IgM ( Invitrogen Corporation , CA-USA ) diluted 1:5000 in PBS supplemented with 0 . 2% I-Block and 0 . 1% Tween 20 , for 60 minutes at room temperature . The molecular weight was determined using MagicMark XP Western Protein Standard ( Invitrogen Corporation , CA-USA ) . Each sample was run twice . Visualization of antigenic bands was done using an enhanced chemiluminescence system ( Supersignal West Dura , Thermo Fisher Scientific , MA-USA ) . The trypomastigote excretory-secretory antigen ( TESA ) was used to develop a calibration curve . This antigen was harvested from cell cultures of T . cruzi Y strain in LLC-MK2 cells , as previously described [31] . The calibration curve was established using the following TESA antigen concentrations: 5 pg , 10 pg , 50 pg , 250 pg and 500 pg ( R2 = 0 . 95 ) ( S1 Fig ) . Antigen levels were determined by densitometry of western blots using myImageAnalysis Software ( Thermo Scientific , USA ) of five specific bands ( 22 kDa , 42 kDa , 58 kDa , 75 kDa and 82 kDa ) that were detected by Western blot . The limit of detection of the test in normal urine samples spiked with T . cruzi antigens was 10 pg/ml . The presence of any of the five diagnostic bands ( 22 kDa , 42 kDa , 58 kDa , 75 kDa and 82 kDa ) was considered as a positive result . In each experiment we included a negative control ( urine sample of healthy volunteer ) and a positive control ( 10 ml of healthy volunteer urine sample containing 1 ng of TESA antigen ) . The Chunap was carried out by a laboratory biologist who was blinded to the Chagas status of the patient . qPCR was performed to evaluate levels of parasitemia . DNA was purified from 500 μl of blood clot samples as previously described [32 , 33] . The quantification of DNA was determined by spectrophotometry using a Nanodrop 2000 instrument ( Thermo Scientific , Delaware , USA ) and only samples with a ratio of 260nm/280nm of ~1 . 8 were used for PCR analysis . qPCR was performed using published methods [34] with the modifications detailed before [35] . The qPCR was carried out by a laboratory biologist who was blinded to the Chagas status of the patient . STATA 13 software was used for all statistical analysis . Parasitemia levels determined by qPCR were evaluated in a logarithmic scale . Differences in mean levels of parasitemia , CD4+ and CD8+ T cell counts , and HIV load between patients with and without reactivation were evaluated by Student’s t-test with equal and unequal variances . Receiver Operating Characteristic ( ROC ) analysis was used to determine the sensitivity and specificity of different cut-offs of antigenuria and parasitemia levels for the diagnosis of reactivation of Chagas disease using microscopy as gold standard . The association between urine T . cruzi antigen concentration and parasitemia levels was evaluated using a linear regression model unadjusted and adjusted by sex , age ( years ) , antiretroviral treatment ( yes versus no ) , HIV load and immune status ( CD4+ and CD8+ T cell counts ) . The use of a sample size of 31 T . cruzi/HIV co-infected patients with a significance level of 0 . 05 gives a statistical power of 72% to determine associations between levels of antigenuria and parasitemia . This sample size gives a power below 70% to determine other statistical associations .
The nested-case control study consisted of 55 HIV patients ( 31 T . cruzi infected and 24 T . cruzi non-infected ) . Mean age was 36 . 8 years ( SD: 15 . 1 years ) . Mean levels of HIV loads were considerably higher ( 187387 . 5 copies/ml , SD: 549436 . 2 copies/ml ) [27 , 28] , which could be explained by the short duration of HIV diagnosis ( mean: 28 . 3 months , SD: 24 . 9 months ) . Mean levels of CD4+ cell and CD8+ cell counts were within normal limits according to the CDC classification ( 301 . 3 cells , SD: 226 . 2 cells , and 765 . 9 cells , SD: 543 . 4 cells , respectively ) [29] . Tuberculosis was the most frequent co-infection in these patients ( n = 6 cases ) . Characteristics of patients stratified by Chagas status are shown in Table 1 . There were no significant differences in sex , HIV load , CD4+ cell count , CD8+ cell count , weight , time of HIV diagnosis , and presence of co-infections . There was however a strong trend for HIV patients co-infected with Chagas to be older ( p = 0 . 06 ) . In this study poly ( NIPAm ) /TB nanoparticles were used to increase the effective sensitivity of western blot analysis in the detection of T . cruzi antigens by 100 fold as previously described [26] . Bands of 22 kDa , 42 kDa , 58 kDa , 75 kDa and 82 kDa were detected in nanoparticle-concentrated urine samples of T . cruzi/HIV co-infected patients ( Fig 1 ) . Bands of 22 kDa , 42 kDa and 55 kDa were also detected in 2 ( 2/24 ) urine samples of T . cruzi-uninfected/HIV+ patients yielding a specificity of 91 . 7% . One of these two Chagas negative patients also had a co-infection with M . tuberculosis . Other bands were also recognized in urine samples of T . cruzi infected patients , but the specificity was below 60% and were therefore excluded as potential diagnosis criteria . The percentage of positive results detected by Chunap was 100% ( 7/7 ) among the cases with reactivation or high parasitemia , 91 . 7% ( 11/12 ) among cases with moderate parasitemia , and 41 . 7% ( 5/12 ) among patients with negative parasitemia ( Table 2 ) . The percentage of T . cruzi-infected patients detected by Chunap , compared to those positive by microscopy , PCR , and ELISA , was 100% ( 7/7 ) , 95% ( 18/19 ) and 74% ( 23/31 ) , respectively . See S1 Diagram . Mean levels of parasitemia were significantly different between patients with reactivation of Chagas disease ( 3 . 28 logarithm copy number of parasites/ml , 95% CI: 1 . 56 to 5 . 00 ) and patients without reactivation but with positive qPCR ( 1 . 43 logarithm copy number of parasites/ml , 95% CI: 1 . 13 to 1 . 72 ) ( p = 0 . 003 ) ( Table 3 ) ( Fig 2A ) . Similarly , mean levels of antigenuria were significantly higher in patients with high parasitemia or reactivation of Chagas disease ( mean = 242 . 21pg , 95% CI: 125 . 45 to 358 . 95 ) compared to patients with moderate parasitemia ( mean = 43 . 32 pg , 95% CI: 25 . 06 to 61 . 58 ) ( p<0 . 001 ) ( Fig 2B ) . Using 105 pg as a cut-off , Chunap could detect all patients with reactivation ( 7/7 ) . The best balance between specificity ( 90 . 62% , 3/29 ) and sensitivity ( 71 . 43% , 5/7 ) for determination of reactivation by qPCR was obtained with the cut-off of 2 log ( parasites/ml blood ) , this cut-off was used for categorization of parasitemia levels in the regression model . High variability of parasitemia levels measured by qPCR was observed , even in a logarithmic scale . A linear relationship was observed between antigenuria and parasitemia levels in both the unadjusted and adjusted regression model ( Table 3 ) . Interestingly , when levels of parasitemia were less than two logarithms , the expected increase in levels of antigenuria was 31 . 52 pg ( 95% CI: 17 . 04 to 46 . 01 ) per each increase in one logarithm of parasitemia ( p<0 . 001 , adjusted r2 = 0 . 84 ) ( Table 3 ) . Similarly , when levels of parasitemia were higher than two logarithms , the expected increase in antigenuria levels was 106 . 00 pg ( 95% CI: 85 . 13 to 126 . 85 ) per each increase in one logarithm of parasitemia ( p<0 . 001 , adjusted r2 = 0 . 84 ) ( Table 3 ) . Among patients with Chagas disease , mean levels of CD4+ T-cell counts were significantly lower in patients with reactivation ( 131 cells , 95% CI: -56 . 54–318 . 54 ) compared to patients without reactivation ( 322 . 46 cells , 95% CI: 229 . 45–415 . 47 ) ( t-test with unequal variances: p = 0 . 046 ) ( Fig 3A ) . Clinical manifestations , parasitemia levels and immunosuppression status of each patient are shown in Table 4 . Among patients with reactivation of Chagas disease , 3 showed clinical manifestations related with Chagas neurological disease , 1 patient had an intestinal perforation , and 3 patients did not show any clinical manifestations . An increase in levels of antigenuria of 36 . 08 pg ( 95% CI: 7 . 28 to 64 . 88 , p = 0 . 016 ) in patients with < 200 CD4+ T-cell counts was observed in the adjusted linear regression model as compared to patients with >500 CD4+ T-cell counts ( Table 3 ) , but no differences were observed in the unadjusted model . No statistical associations were observed between antigenuria levels and CD+8 cells counts , HIV load , and ART in the regression model . There was a trend to lower mean levels of CD8+ T-cell counts between the two groups ( reactivation group = 429 . 6 cells , Non-reactivation groups = 838 . 42 cells , t-test with unequal variances: p = 0 . 064 ) ( Fig 3B ) . HIV viral loads were not statistically significantly different between patients with reactivation ( mean: 134 , 303 copies/ml , 95% CI: -35 , 516 to 304 , 122 ) and without reactivation ( mean: 121 , 761 copies/ml , 95% CI: -62 , 834 to 306 , 355 ) ( Student’s t-test with unequal variances: p = 0 . 901 ) .
No differences were observed in HIV loads , CD4+ cell and CD8+ cell count , and presence of other co-infections between HIV patients with and without Chagas disease . Among patients with positive serology for Chagas disease , patients with reactivation of Chagas disease had low levels of CD4+ T-cells counts compared to patients without reactivation , as previously observed [15] . The percentage of mortality attributed to Chagas disease was 16 . 12% ( 5/31 ) , which is similar to the reported in longitudinal studies ( 15 . 09% , 8/53 ) [10] . Clinical manifestations related to Chagas disease were observed in the nervous system [7 , 10] . In the case of the patient with intestinal perforation we were not able to perform a biopsy analysis to make the confirmatory diagnosis; however , intestinal perforation is a complication described in patients with digestive system abnormalities associated with Chagas disease [36] . The presence of asymptomatic reactivation has been previously described and is thought to be an early stage of Chagas reactivation and a risk factor of HIV progression [10 , 37] . An IgM monoclonal antibody against T . cruzi lipophosphoglycan ( LPG ) was used in this study for antigen detection . The T . cruzi LPG is a surface glycoconjugate which is composed mainly of glucosamine , sialic acid and galactosamine in the carbohydrate portion , and of alkylacylphosphatidylinositol in the lipid portion [38] . Although this antigen has been primarily characterized in the epimastigote form , it could be an important component of the trypomastigote form , and could be used during cell recognition , invasion , and immune suppression of the host [38] . This antibody recognizes two bands of 42 kDa and 82 kDa in the trypomastigote secretory-excretory antigen and crude sonicated trypomastigotes [26] . The percentage of antigenuria positives detected by Chunap ( 74% ) among those with positive serology is similar to that reported before in chronic infected patients ( 60%-84% ) [39–40] . Two false positive results were found in urine samples of patients with negative serology; one of whom was also co-infected with M . tuberculosis . We hypothesize that the presence of false positives could be explained by the existence of other co-infections . In the case of tuberculosis , the mycobacterial lipoarabinomannan has been detected in urine samples of HIV co-infected patients [41] . The lipophosphoglycan is also found in other infectious agents such as Leishmania , Trichmonas , and Pneumocystis , but the anti-IgM LPG antibody used in this study does not show cross-reaction with the LPG from Leishmania and Trichomonas species [38] . However , further studies are needed in order to assess cross-reaction with other parasites that are commonly present in HIV , such as Toxoplasma gondii , and bacteria and fungi such as M . tuberculosis and Cryptococcus neoformans . Definition of a parasite load threshold for prediction of reactivation could be used as a guide in the use of anti-trypanosomal therapy . The early increase in parasitemia may not be symptomatic as previously described in one prospective study [10] , so monitoring for asymptomatic parasitemia may permit early detection of reactivation . This could lead to accelerating the initiation of anti-trypanosomal therapy , which could prevent irreversible damage or death . Levels of parasitemia , determined by qPCR , were higher in patients that had reactivated Chagas disease than in those without reactivation . However , there was a high variability of parasitemia levels between individuals . This observation was also reported by a previous study ( mean ± SD in reactivation cases VS non-reactivation: 12 , 584 . 96 ± 11 , 368 . 35 VS 10 . 43 ± 3 . 53 , respectively ) [15] . The high variability in parasitemia levels detected by qPCR could be explained by differences in the strains of T . cruzi , and by the inability to distinguish DNA from living and dying parasites [15] . Although there was a wide SD found among antigenuria levels , the variability was less than that seen in parasitemia . This could be explained due to lipophosphoglycan only being excreted by living parasites [38] . In this study , reactivation was defined as the detection of circulating parasites in blood by microscopy with or without the presence of clinical manifestations [10] . This definition has limitations because of the lack of sensitivity and reproducibility of microscopy . As observed by us and others , patients with positive microscopy could have low levels of parasitemia by qPCR ( and vice-versa ) , suggesting a poor correlation between microscopy and qPCR . For example , in the case of patient number 9 in Table 4 , the levels of parasitemia and viremia were high , and the CD4+ counts was low . Yet this patient had undetectable parasitemia by microscopy , thus not meeting the reactivation criteria . A better definition of Chagas reactivation is needed so that immunosuppression status and HIV load are also taken into consideration . This will guide clinicians in case management . In the guinea pig model of Chagas disease and congenital Chagas disease , the presence of antigens in urine is correlated with high levels of parasitemia [19 , 26] . In this study we demonstrate that antigenuria levels are positively related with parasitemia levels in humans . Interestingly , the increase in levels of antigenuria was greater among patients with higher levels of parasitemia ( > 2 logarithm copy number parasites/ml ) . All patients with levels of antigenuria higher than 105 pg were patients that showed reactivation . In this cross-sectional study , we have evaluated patients that have reactivated Chagas disease , a longitudinal study will be necessary to determine a cut-off of antigenuria that predicts reactivation and could be used in low-resource settings where serial evaluations of samples are logistically difficult [15] . Antigenuria levels were significantly higher in patients with < 200 CD4+ T-cells , but only in the adjusted model , suggesting possible confounding effects of HIV loads , treatment , age , and sex . In contrast to a previous study , we could not find statistically significant differences between levels of parasitemia or antigenuria , and HIV load and CD8+ T-cells levels [15] . Limitations of this study include possible confounding effects of HIV treatment and the small sample size . Although we adjusted by the use of ART to make statistical comparisons , we could not account for the duration of ART . ART drugs have a direct and more immediate effect on HIV loads as compared to levels of CD4+ T-cells and CD8+ T-cells [15] . Among patients with Chagas disease , young age was found to be a risk factor for high antigenuria levels in the adjusted model . However , this association could be influenced by the time of diagnosis of HIV infection and ART . The Chunap reached sensitivity levels comparable to the more expensive and time consuming standard of care micromethod and qPCR . The feasibility data presented herein provide evidence that Chunap is a promising tool to improve current Chagas diagnostic algorithm in clinical settings . Furthermore , in a previous study we demonstrated that Chunap protect T . cruzi antigens from degradation [26] . In future studies , poly ( NIPAm/TB ) particles will be magnetized in order to simplify the clinical diagnostic process and extend accessibility . Sensitivity can be further improved by increasing the volume of urine analyzed . In conclusion , an antigen urine test for monitoring Chagas reactivation in HIV patients would be highly desirable for these reasons: a ) levels of antigens in urine are related to levels of parasitemia b ) antigenuria levels are less variable compared to levels of parasitemia c ) urine is a preferred , less-infectious , non-invasively collected biological fluid that is more acceptable by patients ( especially if continuous samples are needed ) , and d ) antigen testing can be scaled to a rapid , point of care test that can be performed in low-equipped laboratories . Jean Cabeza , Roni Colanzi , Daniel Lozano , Gonzalo Borda , Gerson Galdos , Lisbeth Ferrufino , Louisa Messenger , Rosmery Gross , Leny Sanchez , Omar Gandarilla , Maurus Dorn , and Helena Jahuira . | Reactivation of Chagas disease in people living with HIV is a serious clinical condition that is associated with high mortality . Hence , early diagnosis and treatment can be lifesaving . Although there are not well accepted criteria to identify patients at risk of reactivation , parasitemia levels are usually considered as the best predictor . Microscopy is used in Latin America for detection of parasitemia levels . However , this has low sensitivity , which usually leads to a delay in diagnosis and treatment . Quantitative PCR is used only for research proposes in endemic areas . Antigens in urine ( antigenuria ) are correlated with parasitemia levels in animal models , as well as in cases of congenital Chagas disease . We believe that antigenuria can also be used for prediction of parasitemia levels in T . cruzi/HIV co-infected patients . In this study , Chunap ( Chagas urine nanoparticle test ) was used for concentration and quantification of T . cruzi antigens in urine of T . cruzi/HIV co-infected patients . Values of more than 105 pg of T . cruzi antigens in urine were observed only in patients with reactivation of Chagas disease . This study shows that antigenuria levels are highly correlated to levels of parasitemia and can be used as a non-invasive technique for monitoring parasitemia levels in T . cruzi/HIV co-infected patients . | [
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"protozoans",
"parasito... | 2016 | Use of a Chagas Urine Nanoparticle Test (Chunap) to Correlate with Parasitemia Levels in T. cruzi/HIV Co-infected Patients |
At the imprinted Rasgrf1 locus in mouse , a cis-acting sequence controls DNA methylation at a differentially methylated domain ( DMD ) . While characterizing epigenetic marks over the DMD , we observed that DNA and H3K27 trimethylation are mutually exclusive , with DNA and H3K27 methylation limited to the paternal and maternal sequences , respectively . The mutual exclusion arises because one mark prevents placement of the other . We demonstrated this in five ways: using 5-azacytidine treatments and mutations at the endogenous locus that disrupt DNA methylation; using a transgenic model in which the maternal DMD inappropriately acquired DNA methylation; and by analyzing materials from cells and embryos lacking SUZ12 and YY1 . SUZ12 is part of the PRC2 complex , which is needed for placing H3K27me3 , and YY1 recruits PRC2 to sites of action . Results from each experimental system consistently demonstrated antagonism between H3K27me3 and DNA methylation . When DNA methylation was lost , H3K27me3 encroached into sites where it had not been before; inappropriate acquisition of DNA methylation excluded normal placement of H3K27me3 , and loss of factors needed for H3K27 methylation enabled DNA methylation to appear where it had been excluded . These data reveal the previously unknown antagonism between H3K27 and DNA methylation and identify a means by which epigenetic states may change during disease and development .
In mammals , imprinted loci are expressed from only one allele . Accompanying and controlling monoallelic expression are allele-specific epigenetic modifications influenced by an imprinting control region ( ICR ) . Within this region , there is a differentially methylated domain ( DMD ) that is subject to acquisition of epigenetic modifications , typically DNA methylation and histone modifications . These modifications are placed in a parent-of-origin specific manner and impose an epigenetic state that dictates allele-specific gene expression at imprinted loci [1] . Previously , we characterized the mechanisms by which the ICR controls allele-specific methylation and expression at the imprinted Rasgrf1 locus . The ICR , located 30 kbp upstream of the transcriptional start site , is a binary switch consisting of a repeated element and the DMD . The repeated element functions as a methylation programmer , that is necessary for the establishment and maintenance of DNA methylation at the DMD on the paternal allele and sufficient for establishing gametic imprints in both germlines ( [2] , [3] and YJP , HH , AML , Ying Gao and PDS , in preparation ) . The DMD is a methylation sensitive enhancer blocker that binds CTCF on the unmethylated maternal allele and limits enhancer to promoter interactions , silencing the maternal allele [4] . DNA methylation that is directed to the paternal DMD by the repeats prevents CTCF binding , allowing expression of the paternal allele . The repeats constitute the first identified , and one of only a few known , naturally occurring DNA methylation programmers in mammals [5]–[8] . Epigenetic analysis of Rasgrf1 done by others examined DNA methylation across an expanded region centered on the ICR ( [9] and Hisato Kobayashi and Hiroyuki Sasaki unpublished data ) and histone modifications at the ICR [10] . The DNA methylation data suggested that a broader DMD exists in somatic tissue and in the male germline than was previously appreciated [9] . The histone methylation data indicated that several allele-specific histone modifications accompany the DNA methylation differences , including H3K27me3 and H4K20me3 on the maternal allele and H3K9me3 on the paternal allele [10] . The Rasgrf1 locus presents some unusual paradoxes: The paternal allele is active yet it carries DNA methylation and other repressive marks , whereas the maternal allele is silent and lacks DNA methylation but carries other repressive marks . It is unclear if and how the primary DNA sequence controls each of these parent-specific marks . We have identified the DNA sequences that are necessary and sufficient for programming the establishment and maintenance of DNA methylation on the paternal allele , however , nothing is known about the cis-acting DNA sequences that control placement of repressive histone modifications in this region , or whether there is any coordination between the histone and DNA methylation modifications . In many organisms , distinct epigenetic marks coordinately determine the transcriptional status of genes . For instance , recruitment of DNA methylation can depend upon pre-established histone H3 methylation at lysine 9 [11]–[13]; histone modifications can be lost when DNA methylation is impaired [14]; and some histone modifications become redistributed in histone methyltransferase mutants [15] . Here we report the analysis of a 12 kbp region at Rasgrf1 for locations bearing histone modifications and DNA methylation . Our data reveal the mutual exclusion of the repressive H3K27 methylation and DNA methylation modifications . Furthermore , by experimentally manipulating the levels of DNA and H3K27 methylation possible at the locus , we demonstrate that these two marks are mutually antagonistic , whereby the placement of one mark prevents the placement of the other , and removal of one mark allows the encroachment of the other . Additionally , we found that the tandem repeat sequences , which are necessary and sufficient for programming DNA methylation marks , are also important for directing H3K27 and H3K9 modifications to the proximal DMD and that H3K9 methylation is needed for optimum establishment of DNA methylation on the paternal allele .
There are two regions rich in C and G residues and CpG dinucleotides over a 200 kbp interval at the Rasgrf1 locus . One CpG cluster is in the ICR and the other in the promoter region of Rasgrf1 ( Figure S1A , B , C ) . By analyzing the DNA methylation pattern of these two CpG clusters in somatic DNA using methylation sensitive restriction enzymes , we found that only the DMD CpG cluster is methylated while the one in the promoter is not ( Figure S1D ) . When Kobayashi et al . performed a comprehensive analysis of allele-specific DNA methylation at the Rasgrf1 ICR in embryonic day 12 . 5 DNA and in the male germline , they observed that the somatic and germline DMD was larger than had been previously appreciated ( [9] and Hisato Kobayashi and Hiroyuki Sasaki unpublished data ) . We expanded upon this by characterizing the distribution of both histone modifications and DNA methylation over a 12 kbp region centered on the DMD within the ICR , and also by evaluating the influence of the tandem repeats within the ICR on these epigenetic marks ( Figure 1 ) . We performed bisulfite sequencing to characterize DNA methylation in 86 CpGs present in eight segments ( labeled D1 through D8 in Figure 1 ) containing 4 , 118 bp from the 12 , 020 bp interval . Our analysis of methylation in the soma used DNA from neonatal brain and our analysis in the male germline used DNA isolated from sperm . Somatic DNAs were from F1 progeny of 129S4Jae and PWK strains . Polymorphisms between these strains allowed us to determine which bisulfite sequences were from the maternal and paternal alleles in the soma . The 129S4Jae-derived allele was either wild type or lacked the Rasgrf1 tandem repeats constituting the DNA methylation programmer ( Figure 2A ) . Sperm DNAs were from mice homozygous for wild type or tandem repeat-deficient alleles of Rasgrf1 . Our characterization of the somatic methylation states from animals carrying the wild type 129S4Jae allele was in strong agreement with the results of Kobayashi , even though sources of somatic DNAs differed: Kobayashi used midgestation embryos . In neonatal brain DNA , we detected paternal allele-specific DNA methylation , which covers at least the 7 . 6 kbp interval between segments D4 through D7 and includes the ICR . We also found a region of methylation on both alleles over a 1 . 4 kbp interval upstream of the ICR containing segments D1 and D2 . None of the somatic DNA methylation patterns changed on either the paternal or maternal alleles in mice harboring a deletion of the tandem repeats on the maternal allele ( Figure 2C , D ) . In contrast , all paternal allele-specific DNA methylation we detected in regions D4 to D8 was lost from somatic DNA when the tandem repeats were absent from the paternal allele ( Figure 2D ) . This indicates that the range of action of the Rasgrf1 DNA methylation programmer within the tandem repeats is not confined to the narrowly defined 400 nt DMD previously studied , but its reach spans at least 7 kbp in somatic tissue . Imprinted DNA methylation patterns that are established in the germlines are typically maintained and can even spread during somatic development . To determine the extent of the methylation in sperm DNA and the range of action of the DNA methylation programmer in the male germline , we performed bisulfite analysis on sperm DNA from mice carrying an intact repeat element and also from mice carrying a deletion of the repeats . In mice with the intact repeats , we found that Rasgrf1 methylation in sperm DNA was present not only the originally defined 400 bp DMD , but it extended an additional 1 . 6 kbp upstream , in agreement with results from Hisato Kobayashi and Hiroyuki Sasaki ( unpublished ) . However , in mice bearing a deletion of the repeats that constitute the Rasgrf1 DNA methylation programmer , only the DNA methylation at the originally defined DMD was lost . The DNA methylation on the additional 1 . 6 kbp was unaffected , indicating that the range of action of the Rasgrf1 DNA methylation programmer in the tandem repeats is limited to the 400 bp proximal DMD in the male germline ( Figure 2B ) . Because loss of DNA methylation on that narrowly defined sequence was sufficient to disrupt imprinted expression of Rasgrf1 [2] , we infer that this differentially methylated portion of the locus is essential for its imprinting and we refer to it as the core DMD . We next characterized histone methylation status across the same 12 kbp interval over which the DNA methylation was characterized . Specifically , we sought to determine where histone modifications were distributed , if any modifications were allele-specific , if their placement required the same DNA methylation programmer that imprinted DNA methylation requires , and if there is any coordination between modification states on histones and DNA . We limited our analysis to di- , and tri-methylation of histone H3 at lysine 9 and 27 because they are associated with gene silencing and DNA methylation , which are observed at the maternal and paternal alleles respectively . For this analysis , we performed chromatin immunoprecipitation ( ChIP ) using mouse embryonic fibroblasts ( MEFs ) and antibodies specific to H3K9me2 , H3K9me3 , H3K27me2 , and H3K27me3 . Our initial tests were controls to verify that the antibodies detected histone modifications with proper specificity ( Figure S2 ) . For these tests , we amplified immunopreciptates using primers from Charlie , Actin and Hoxa9 . H3K9me2 and H3K27me2 are known to reside at Charlie [16] , H3K9me3 at Actin , and H3K27me3 at Hoxa9 [17] . The expected PCR products were observed for each immunoprecipitation , indicating the antibodies were indeed specific . In addition , PCRs done using DMD primers detected only H3K9me3 and H3K27me3 at the DMD; therefore , subsequent ChIP studies primarily used antibodies recognizing these marks ( Figure S2 ) . We then extended our H3K27me3 and H3K9me3 analysis to six segments ( labeled C1 through C6 in Figure 1 ) that included 10 , 451 bp surrounding the core DMD and methylation programmer using two separate immunopreciptates from wild type MEFs , and MEFs carrying a deletion of the DNA methylation controlling repeats ( RepΔ . Because we used two immunoprecipitates , these analyses report the general distribution of histone marks in the region rather than providing reliable quantification of their abundance . Our PCRs in regions C1 , C2 , C4 , C5 and C6 did not distinguish the parental alleles and our PCR of the DMD at C3 used wild type allele-specific primers . The ChIP analysis of wild type MEFs indicated that both H3K9me3 and H3K27me3 were most abundant at the core DMD at region C3 with some H3K27me3 signal extending downstream of the tandem repeats ( Figure 3 ) . Analysis of MEFs carrying a deletion of the DNA methylation controlling repeats suggested that the repeats could influence the distribution of histone modifications at the DMD and elsewhere in the region . To provide statistically significant measures of methylated H3K9 and H3K27 at the DMD and to assess if any modifications were allele-specific , we analyzed a total of six to twelve independent immunoprecipitations by quantitative PCR using primers spanning the DMD at region C3 ( Figure 2A ) . Our data confirmed that the DMD is enriched for trimethylated lysines but lacks dimethylated ones ( Figure 4A ) . To determine if these histone marks over the DMD were on the maternal or paternal alleles , we repeated the ChIP assays using mice carrying the engineered polymorphisms shown in Figure 2A that enabled us to amplify the wild type maternal and paternal DMD sequences separately . Results demonstrated that the maternal allele has H3K9me3 and H3K27me3 , whereas the paternal DMD has only the H3K9me3 mark ( Figure 4B and C ) . This is in partial agreement with other data describing H3K27me3 as being maternal allele specific and H3K9me3 as being paternal allele specific at Rasgrf1 [10] . H3K9me3 that we detect on the two alleles may be placed by different mechanisms . Our data correlate well with previous findings that DNA methylation can be coregulated with H3K9me3 [11] , [13] , [18] , [19] , but generally not with H3K27me3 [20] , [21] . Because the tandem repeats act as a DNA methylation programmer , playing an essential role both in establishment and maintenance of DNA methylation at the DMD ( [2] , [3] and YJP , HH , AML , Ying Gao and PDS , in preparation ) , we wanted to determine if they also influence placement of methylated histone marks at the DMD . We did this by repeating the ChIP analysis using MEFs carrying a deletion of the repeats ( RepΔ ) and amplifying the wild type allele and the mutated allele separately . Our analysis showed that the repeat element indeed has a significant influence of histone modification status at the DMD , in addition to controlling its DNA methylation ( Figure 4D ) : When the repeats were absent from the maternal allele , the levels of maternal allele-specific H3K27me3 and H3K9me3 were respectively 1/2 and 1/6th the levels seen when the repeats were present . Similarly , when the repeats were absent from the paternal allele , the level of paternal allele-specific H3K9me3 was 1/3rd that seen when the methylation programmer was absent . Interestingly , deletion of the repeats from the paternal allele led to a three-fold increase in the accumulation of H3K27me3 on the paternal allele . This is consistent with our locus wide ChIP analysis spanning intervals C1 to C6 , which suggested H3K27me3 can encroach into areas where it is normally absent , both 5′ and 3′ of the DMD , when the paternal repeats are deleted ( see sites C2 , C5 , C6 in Figure 3B ) . These observations provide evidence that DNA methylation and H3K27me3 are mutually exclusive epigenetic marks at Rasgrf1 . When we superimposed the DNA and H3K27 methylation data for wild type animals and animals carrying a deletion of the paternal methylation programmer from Figures 2 and 3 , the mutual exclusion of H3K27me3 and DNA methylation over the core DMD was apparent ( shown separately in Supporting Figure S3A and B for clarity ) . Mutual exclusion of H3K27me3 and DNA methylation can arise by different mechanisms . In one scenario , the two marks may be placed in different compartments of the nucleus and the DNA cannot reside in both places . Alternatively , distinct factors needed for H3K27me3 and DNA methylation may require the same DNA binding site , which cannot be simultaneously occupied by the two sets of factors . A third possibility is that DNA and H3K27 methylation are mutually antagonizing , whereby one inhibits placement of the other . This last possibility is mechanistically different from mere mutual exclusion . If antagonism between these two marks is occurring , then we can predict what happens to one mark if the other is experimentally manipulated . In order to explore more directly the possible antagonism between DNA methylation and H3K27me3 , we repeated our allele-specific ChIP studies using MEFs that had been treated with the DNA methyltransferase inhibitor 5-azacytidine . If DNA methylation can antagonize H3K27 methylation , then we expected that 5-azacytidine treatments should increase the levels of H3K27me3 at the DMD as assayed by ChIP . This is precisely what we observed . 5-azacytidine treatments increased the signals from our ChIP analysis by more than six fold when we assayed H3K27me3 on the two parental alleles ( Figure 5A ) . Although the maternal allele lacks imprinted DNA methylation , there is DNA methylation at sites D1 , D2 and D8 . Reductions in methylation at those sites might augment accumulation of H3K27me3 across the entire region . If DNA methylation antagonizes H3K27 methylation , then an additional expectation is that inappropriate placement of DNA methylation on the maternal DMD should exclude accumulation of H3K27me3 marks . To test this , we took advantage of a transgenic system we developed to test if the tandem repeats , which are necessary for programming DNA methylation at Rasgrf1 , are sufficient to impart imprinted methylation to the DMD at an ectopic location in the genome . Independent transgenic founders harboring three to five ectopic copies of the Rasgrf1 ICR underwent proper establishment of DNA methylation at the transgenic DMD in the male germline and erasure of that methylation in the female germline , recapitulating the essential features of imprinted methylation establishment seen at the endogenous locus ( YJP , HH , AML , Ying Gao and PDS in preparation ) . We were able to distinguish the transgenic ICR from the endogenous copy because the transgenic repeats were flanked with loxP sites and had the same structure as the WT-flox allele shown in Figure 2A . This allowed us to assay DNA methylation and perform ChIP analysis of the transgene . The transgene was useful for the studies we describe here because the unmethylated state that was established on the transgene after female transmission could not be maintained if there was any history in the pedigree of transmission through a male ( Figure 5B ) . This system of transgenerational epigenetic memory allowed us to generate two different sets of MEFs , both of which were derived by maternal transmission of the transgene from a common founder . For one set of MEFs , the transgene was unmethylated at the transgenic DMD , whereas in the second set , the same transgene was methylated on the DMD ( Figure 5B , upper two panels ) . If there is antagonism between H3K27me3 and DNA methylation at Rasgrf1 , then we predicted our MEFs with a methylated transgene should exclude H3K27me3 , whereas our MEFs with an unmethylated transgene should allow its placement . This is also precisely what we observed ( Figure 5B , lower panel ) , providing additional independent evidence that DNA methylation antagonizes placement of H3K27me3 . We next wondered if the antagonism between DNA methylation and H3K27me3 might be reciprocal , meaning; H3K27me3 is able to exclude DNA methylation . To test this possibility we analyzed the DNA methylation state of the Rasgrf1 DMD in ES cells , embryoid bodies or trophoblast outgrowths that lack either of two factors needed for H3K27me3 by the PRC2 complex . PCR2 includes SUZ12 , EED and EZH2 , the H3K27 methyltransferase . YY1 , the mammalian ortholog of the Drosophila PHO protein , is a DNA binding factor that binds to EED and recruits PRC2 to sites of action [22]–[24] . Mice and cells with deficiencies in either SUZ12 or YY1 fail to acquire normal levels of H3K27me3 genome wide [22] , [25] , [26] , and the deficiency is lethal for mice , but SUZ12-deficient ES cells are viable [26] , [27] . If conditions necessary for proper placement of H3K27me3 are in fact required to antagonize placement of DNA methylation on the maternal DMD of Rasgrf1 , then DNA methylation at the DMD will increase in the absence of SUZ12 and YY1 . Because DNA methylation at the Rasgrf1 DMD is normally restricted to the paternal allele , which is completely methylated , any increase in DNA methylation would arise on the maternal allele . To monitor the level of Rasgrf1 DMD methylation in SUZ12- and YY1-deficient materials , we used COBRA [28] . This involved treating DNAs with bisulfite and amplifying them using primers not overlapping with CpG dinucleotides , which will amplify templates without bias for either methylation state . We then digested the PCR products with BstUI . Methylated templates will retain the BstUI recognition site ( CGCG ) after amplification and will be digested , whereas unmethylated templates that underwent bisulfite conversion of either CG in the recognition site to TG will resist digestion . There should be an equal amount of digested and undigested PCR product when the maternal allele is completely unmethylated and the paternal allele is completely methylated . This is what we saw in embryoid bodies and blastocysts that were heterozygous respectively for the Suz12 and Yy1 mutations . This indicated that our COBRA assays accurately reported the presence of both methylated and unmethylated templates expected in these Suz12 and Yy1 expressing materials; however , it is not clear why Suz12 heterozygous ES cells did not show this pattern . When we performed COBRA analysis on SUZ12-deficient embryoid bodies ( EB ) that had differentiated for six ( P6 ) or nine ( P9 ) days in vitro ( Figure 6A , B ) or on trophoblast outgrowths from YY1-deficient blastocysts ( Figure 6C ) , we found a dramatic increase in the levels of the digested PCR product in three out of four samples of Suz12 −/− material and in the Yy1 −/− material , indicating that loss of SUZ12 or YY1 resulted in increased Rasgrf1 DMD methylation . The near complete acquisition of DNA methylation in P9 EB lacking SUZ12 was confirmed by bisulfite sequencing ( Figure 6B lower panel ) , whereas unmethylated DNA was present in EB with a single functional allele of Suz12 , though it is possible there is a quantitative increase in Rasgrf1 DNA methylation when only one functional copy of Suz12 is present . We do not know why only three out of four of the Suz12 −/− DNAs show hypermethylation . This could be an artifact of cell cultures , which can exhibit frequent and cyclic changes in DNA methylation [29] . Also , mutation of Eed , another component of PRC2 , is known to cause hypermethylation and hypomethylation simultaneously , depending upon which CpGs are queried [30] . Given these precedents , it is possible that the eight CpGs we assayed in the BstUI sites are predominantly hypermethylated in cultured cells lacking SUZ12 . Nonetheless , our data provide evidence that the antagonism between DNA and H3K27 methylation is reciprocal and that H3K27me3 antagonizes placement of DNA methylation . Furthermore , this mutual antagonism exists in at least three DNA sources: MEFs , embryoid bodies and trophoblast outgrowths . We also explored the relationship between H3K9 and DNA methylation at Rasgrf1 . H3K9 methylation has been strongly correlated with DNA methylation ( reviewed in [31] ) : Loss of the SUV39H1 and SUV39H2 H3K9 methyltransferases in mice simultaneously impairs accumulation of H3K9me3 across the genome [32] and accumulation of DNA methylation at pericentric major satellite repeats , but not at minor satellite or C-type retroviral repeats [13] . DNA methylation deficiencies were also noted in plants lacking H3K9 methyltransferases [12] , [19] with one study reporting that maintenance of DNA methylation was affected [18] . To investigate the relationship between H3K9me3 and DNA methylation at Rasgrf1 , we asked if H3K9me3 controlled by SUV39H1 and SUV39H2 affected imprinted DNA methylation at Rasgrf1 . To address this , we performed methylation analysis on adult testes DNA using COBRA , bisulfite sequencing and a PCR assay that detected methylation status at a series of five HhaI sites in the DMD . Testes primarily contain cells of the germline , which will carry paternal epigenotypes , but some somatic cells are also present , which will carry both paternal and maternal epigenotypes . The COBRA analysis suggested that the DNA was hypomethylated in the SUV39H1- and SUV39H2-doubly deficient testes ( Figure 7A ) . When we measured the extent of DNA methylation using HhaI site-spanning Q-PCR assays , it was clear that the loss of Rasgrf1 DNA methylation was significant ( Figure 7B ) . Bisulfite sequencing provided additional confirmation with higher resolution – there was a significant decrease in the number of DNA templates that were more than 80–100% methylated and an increase in the number that were 40–80% methylated in SUV39H1- and SUV39H2-doubly deficient testes ( Figure 7C ) but there was no change in the abundance of DNAs that were completely unmethylated . The reduction in DNAs with the 80–100% methylated paternal epigenotype , and the increase in DNAs with the 40–80% methylated epigenotype suggests that SUV39H1 and SUV39H2 control the efficiency with which imprinted DNA methylation is established in mice . In Arabidopsis , the SUVH4 H3K9 methyltransferase is known to control maintenance of DNA methylation [18] .
We report here the epigenetic states that exist within a 12 kbp interval centered on the Rasgrf1 ICR . Both parental alleles were marked by DNA methylation in somatic tissue on a 1 . 4 kbp segment at the very 5′ end of this 12 , 020 nt interval ( D1–D2 , Figure 2C , D ) . Downstream of this were segments that spanned the ICR that were paternally methylated in somatic DNA ( D3–D8 ) , and sperm DNA as well ( D3–D5 , Figure 2B , D ) . Not every CpG was assayed in this 12 , 020 interval , including those within the tandem repeats that constitute the DNA methylation programmer . H3K9me3 was present on both parental alleles at the core DMD immediately 5′ of the tandem repeats and within the ICR . H3K27me3 was present at this same location , but exclusively on the maternal allele . There was no appreciable dimethylation of these H3 residues at the core DMD ( Figure 4A , B , C ) . The tandem repeats , consisting of approximately 40 copies of a 41 nt unit , influenced the placement of histone and DNA methylation ( Figures , 2B , D , 3 and 4D ) and can be considered a cis-acting methylation programming sequence , one of only a few naturally occurring ones known in mammals . Paternal allele DNA methylation was particularly sensitive to these tandem repeats , which control establishment of DNA methylation in the male germline at a 400 nt core DMD lying just 5′ of the repeats ( Figure 2B and [2] ) . The repeats also control spreading and maintenance of paternal allele DNA methylation in somatic tissue over a broader domain ( Figure 2B , D and [3] ) . Marking the core DMD with DNA methylation on the paternal allele and H3K27me3 on the maternal allele are coordinated and mutually exclusive events in wild type cells with DNA methylation largely confined to the core DMD on the paternal allele and H3K27me3 on the maternal allele ( Figures 2D , 3B and 4 ) . The mutual exclusion arises because one epigenetic mark antagonizes the placement of the other . Five independent lines of evidence led to this conclusion . First , MEFs taken from mice lacking DNA methylation on the paternal DMD inappropriately accumulated H3K27me3 on the paternal allele ( Figure 4D ) . Second , MEFs treated with the DNA methyltransferase inhibitor , 5-azacytidine , accumulate elevated levels of H3K27me3 marks ( Figure 5A ) . Third , MEFs taken from mice with a maternally transmitted Rasgrf1 ICR transgene that lacked DNA methylation had H3K27me3 on the transgenic DMD , whereas H3K27me3 was excluded by manipulations that inappropriately placed DNA methylation on the transgene ( Figure 5B , lower panel ) . Fourth , mutation of the Suz12 component of PRC2 , which is needed for activity of the EZH2 H3K27 methyltransferase in PRC2 , ablated normal placement of H3K27me3 and enabled the maternal allele to inappropriately acquire DNA methylation ( Figure 6A , B ) . Fifth , mutation of the Yy1 gene , which is needed to recruit PRC2 to DNA and , like Suz12 , is needed for effective placement of H3K27me3 also enabled the maternal allele to inappropriately acquire DNA methylation ( Figure 6C ) . Other studies have documented the cross-dependency of some histone modifications and DNA methylation [11] , [13] , [14] , [19] , [33]–[37] , and it has also been observed that H3K27me3 and DNA methylation can be mutually exclusive [21] . The studies described here provide evidence that H3K27me3 and DNA methylation are in fact mutually antagonizing epigenetic marks and that H3K27me3 facilitates allele-specific DNA methylation that exists at imprinted loci . H3K9me3 was detected on both parental alleles indicating this mark is controlled differently from H3K27me3 . However , it too participates in imprinted DNA methylation because the H3K9 methyltransferases , SUV39H1 and SUV39H2 , are needed for optimal establishment of DNA methylation at the DMD in the male germline ( Figure 7 ) . We do not know how DNA and H3K27 methylation antagonize each other's placement; however , the literature highlights several molecular and developmental events , as well as protein factors that may be involved . Among these is the transcriptional state that is known to influence which of two mutually exclusive histone modifications is placed by the competing activities of polycomb ( PcG ) and trithorax ( Trx ) group proteins [38] . Additionally , differentiation state is known to influence genome wide epigenetic patterns in ES , MEF and neuronal progenitor cells [39] . At Rasgrf1 , developmental stage also influences epigenetic states [40]; the methylation programmer controls establishment of DNA methylation in the germline and maintenance in peri-implantation embryos [2] , [3] , but not later in development . Interestingly , this same period is a critical interval for control of H3K27 methylation [41] . Finally , there may be a role for CTCF in the mutual exclusion of H3K27 and DNA methylation at Rasgrf1 . CTCF and its binding sites have been shown to influence H19 DNA methylation [42]–[47] and CTCF binds at Rasgrf1 as well [4] . Genome-wide ChIP analysis identified locations enriched for CTCF [48] and H3K27me3 [49] in MEFs and Chi squared analysis reveals a significant co-localization of these marks at imprinted versus non-imprinted loci ( Table S3 ) . This raises the possibility that , in addition to its role in preventing DNA methylation at other imprinted loci , CTCF helps to place H3K27me3 at Rasgrf1 . CTCF functions in coordination with its binding partner , YY1 , in activating the X chromosome [50] and YY1 also inhibits DNA methylation at Rasgrf1 ( Figure 6C ) , most likely through its ability to recruit PRC2 [22]–[24] . Depending upon the consensus sequence considered , between one and twelve YY1 sites are predicted to lie within the DMD and repeat region ( data not shown ) . Like CTCF , YY1 sites are enriched at other imprinted loci as well [51] . CTCF has additional binding partners including CHD8 , which is associated with DNA methylation [52] . Using ChIP analysis , we could not detect CHD8 on either Rasgrf1 allele ( data not shown ) , suggesting that at Rasgrf1 , other CTCF binding partners and functions might be more important , such as YY1 . Normal placement of DNA methylation on the paternal allele and H3K27me3 on the maternal allele both require the same tandemly repeated DNA sequence element , which we previously showed has DNA methylation programming activity ( [2] , [3] and YJP , HH and PDS unpublished ) . However , DNA methylation is more rigidly dependent on the repeated sequence than are the histone modifications . Whereas DNA methylation on the paternal core DMD was typically completely lost when the repeats were deleted , H3K27me3 and H3K9me3 on the maternal DMD were respectively reduced to levels only 1/2 and 1/6 of those seen when the repeats were present . Repeated sequences have been shown to have methylation programming activity in other systems [53] , [54] . Notably , at the DM1 locus in humans , a repetitive element is associated with heterochromatin accumulation [55] . Interestingly , like the maternal Rasgrf1 DMD and repeat sequences [4] , the DM1 repeat also is a CTCF-binding insulator . CTCF appears to restrict the boundary of heterochromatinization at DM1 , but it is not known if CTCF has a similar effect at Rasgrf1 . Sequences with appreciable similarity to the Rasgrf1 tandem repeats are not abundant in the mouse genome . However , the Rasgrf1 repeat unit has striking similarity to the B repeat sequences on Xist ( Figure S4 ) . Because Xist RNA regulates placement of H3K27me3 on the inactive X chromosome and at an autosomal transgenic site in cis [56] , [57] , it is possible there is mechanistic overlap between epigenetic regulation by Xist and the Rasgrf1 repeats . We do not know what functional motifs enable the methylation programmer at Rasgrf1 to control either DNA or H3 methylation . Its repeated nature may be sufficient [54] , possibly involving an RNA-dependent mechanism [58] . Other potentially important features include the CpG present in 36 of the 40 repeat units; GGGG tetramers that may facilitate the formation of G-quadruplex structures [59] , which in turn may alter the sensitivity of DNA to methyltransferase action [60]; or CTCF sites known to lie in the Rasgrf1 methylation programmer [4] . BORIS , the male germline paralog of CTCF [61] , may also be important for function of the Rasgrf1 methylation programmer . Figure 8 describes a model for the placement of DNA methylation and H3K27me3 in response to the Rasgrf1 methylation programmer , their antagonism , and the developmental timing of these events . However , it is unlikely that a universal rule dictates the regulation of DNA and H3K27 methylation at all loci within a species or among species . In human cell lines , some loci have been found at which DNA and H3K27 methylation occur simultaneously with one mark requiring the placement of the other [62] , whereas in Arabidopsis , DNA methylation does not seem to be closely associated with H3K27me3 [20] and in fact can be mutually exclusive [21] . Nonetheless , identifying the various rules that influence epigenetic programming of normal developmental states will provide insights for manipulating them for therapeutic benefit .
Mice used for DNA methylation analysis across the 12 kbp interval were F1 progeny of PWK and 129S4SvJae parents . Polymorphisms in these strains facilitated the assignment of a given clone from bisulfite PCR to one of the two parental alleles . Mice used to prepare MEFs for ChIP analysis across the 12 kbp interval were from strain 129S4SvJae backcrossed to C57BL/6 and included wild type animals , animals carrying a repeat deletion [2] and animals containing an engineered polymorphism at the DMD that did not disrupt imprinting [3] . All allele specific ChIP analyses were done using MEFs from mice carrying one of these mutations . Mice carrying the Rasgrf1 ICR transgene will be described in a separate report ( YJP , HH , PDS , in preparation ) . Previous reports describe the Suz12 mutation and preparation of homozygous ES cells and embryoid bodies [26] and the Yy1 mutation and preparation of trophoblast outgrowths [27] . MEFs from 13 . 5 day old F1 embryos of C57BL/6 and 129S4Jae parents were used for ChIP analysis as described in Text S1 . Modified histone-specific antibodies were from Millipore/Upstate ( H3K9me2 item 07-441 lot 29698 , H3K9me3 item 07-442 lot 24416 , H3K27me2 item 07-452 lot 24461 , H3K27me3 item 07-449 lot 24440 ) and Thomas Jenuwein , IMP , Austria ( H3K9me3 ) [15] . Specificity of antibody from Thomas Jenuwein's lab has been reported [15] . Validations of commercial antibody specificities are publicly available from the manufacturer ( see http://www . millipore . com for certificates of analysis for each catalog item and lot number ) . The DNA recovered after ChIP was used for Q-PCR with input chromatin and mock immunoprecipitations without antibody serving as controls . Q-PCR was performed in triplicate with SYBR green detection using primers listed in Table S1 . Ratios of bound to input signals are reported . Treatment of genomic DNA with bisulfite was performed as previously described [2] , with the added difference that we used 1 . 5 M betaine and 5% DMSO to enhance the yield in PCR of AT-rich , converted DNA . ExTaq HS DNA polymerase ( Takara , Japan ) was used for hotstart PCR . Primers used are provided in Table S1 and additional experimental details are in Text S1 . The bisulfite converted and amplified DNA was either cloned and sequenced or subjected to COBRA [28] using BstUI digestions . In this assay , cytosine methylation enables digestion , whereas absence of methylation prevents it . Assays for DNA methylation using HhaI digested DNAs were described [2] . | Methylation of DNA and histones exert profound and inherited effects on gene expression . These occur without changes to the underlying DNA sequence and are considered epigenetic effects . Disrupting epigenetic states can cause developmental abnormalities and cancer . Very little is known about how locations in the mammalian genome are chosen to receive these chemical modifications , or how their placement is regulated . We have identified a DNA sequence that acts as a methylation programmer at the Rasgrf1 locus in mice . It is required for methylation of nearby DNA sequences and can also influence the levels of local histone methylation . The methylation programmer has different effects on paternally and maternally derived chromosomes , directing DNA methylation on the paternal allele and histone H3 lysine 27 trimethylation on the maternal allele . These two methylation marks are not only mutually exclusive; they are also mutually antagonizing , whereby one blocks the placement of the other . Manipulations that cause aberrant changes in the levels of one of these marks had the opposite effect on the other mark . These observations identify novel mechanisms that specify epigenetic states in vivo and provide a framework for understanding how pathological epigenetic changes can arise , including those emerging at tumor suppressors during carcinogenesis . | [
"Abstract",
"Introduction",
"Results",
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"genetics",
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] | 2008 | Antagonism between DNA and H3K27 Methylation at the Imprinted Rasgrf1 Locus |
The O-acetylation of the essential cell wall polymer peptidoglycan occurs in most Gram-positive bacterial pathogens , including species of Staphylococcus , Streptococcus and Enterococcus . This modification to peptidoglycan protects these pathogens from the lytic action of the lysozymes of innate immunity systems and , as such , is recognized as a virulence factor . The key enzyme involved , peptidoglycan O-acetyltransferase A ( OatA ) represents a particular challenge to biochemical study since it is a membrane associated protein whose substrate is the insoluble peptidoglycan cell wall polymer . OatA is predicted to be bimodular , being comprised of an N-terminal integral membrane domain linked to a C-terminal extracytoplasmic domain . We present herein the first biochemical and kinetic characterization of the C-terminal catalytic domain of OatA from two important human pathogens , Staphylococcus aureus and Streptococcus pneumoniae . Using both pseudosubstrates and novel biosynthetically-prepared peptidoglycan polymers , we characterized distinct substrate specificities for the two enzymes . In addition , the high resolution crystal structure of the C-terminal domain reveals an SGNH/GDSL-like hydrolase fold with a catalytic triad of amino acids but with a non-canonical oxyanion hole structure . Site-specific replacements confirmed the identity of the catalytic and oxyanion hole residues . A model is presented for the O-acetylation of peptidoglycan whereby the translocation of acetyl groups from a cytoplasmic source across the cytoplasmic membrane is catalyzed by the N-terminal domain of OatA for their transfer to peptidoglycan by its C-terminal domain . This study on the structure-function relationship of OatA provides a molecular and mechanistic understanding of this bacterial resistance mechanism opening the prospect for novel chemotherapeutic exploration to enhance innate immunity protection against Gram-positive pathogens .
Multi-drug resistance amongst important human pathogens , such as methicillin-resistant Staphylococcus aureus ( MRSA ) , vancomycin-resistant Enterococcus ( VRE ) and drug-resistant Streptococcus pneumoniae , continues to challenge clinicians and threaten the lives of infected patients to the extent that the United Nations recently endorsed a “Global Action Plan on antimicrobial resistance” ( http://www . who . int/antimicrobial-resistance/publications/global-action-plan/en/ ) . With the pipeline of traditional antibiotics all but dried up , alternative strategies are now being considered [1] . One novel approach to address future antimicrobial therapy is to exploit a well-established antimicrobial target in a new way that works synergistically with the natural host defenses , while minimizing deleterious effects on the beneficial community of commensal bacteria . An example of this involves sensitizing the cell walls of bacterial pathogens to attack by either host immune systems or endogenous lysins ( autolysins ) through the inhibition of a specific metabolic target enzyme . The peptidoglycan ( PG ) sacculus is a key component of bacterial cell walls . PG encloses the cytoplasmic membrane to counter the turgor pressure of the cytoplasm thereby maintaining cell viability . Being both essential and unique to bacteria , PG is a prime target for the innate immune system , specifically through the production and release of lysozymes [2] . These enzymes hydrolyze the β- ( 1→4 ) linkage between the repeating N-acetylmuramoyl ( MurNAc ) and N-acetylglucosaminyl ( GlcNAc ) residues that form the glycan chains of PG ( Fig 1A ) thereby leading to rapid cell rupture and death . In the early stages of an infection , released PG fragments circulate in the host and serve as a critical activator of the immune system [3] . To defend against this host innate immune response , many pathogenic bacteria chemically modify their PG through O-acetylation . The O-acetylation of PG occurs at the C-6 hydroxyl group of MurNAc residues and thereby sterically inhibits the productive binding of lysozyme [4 , 5] in a concentration dependent manner ( reviewed in [6–9] ) . This PG modification exists in many Gram-positive and Gram-negative bacteria , but it appears to be particularly prevalent in pathogenic species . For example , only pathogenic species of Staphylococcus , including S . aureus , possess O-acetylated PG and each is highly resistant to lysozyme . On the other hand , non-pathogenic species lack this modification and they are lysozyme sensitive [10] . The extent of PG O-acetylation varies with species and strain , and typically ranges between 20% and 70% [6–9] . The age of a bacterial culture also appears to influence PG O-acetylation . For example , increases in O-acetylation of 10–40% were observed with cultures of Enterococcus faecalis entering stationary phase and a further 10–16% when cells become viable but non-culturable [11] . The increased susceptibility of PG with decreased levels of O-acetylation to host lysozyme has been demonstrated to correlate directly with the decrease in pathogenicity of , e . g . , S . aureus [10 , 12 , 13] , Streptococcus suis [14] , S . pneumoniae [15] , Streptococcus iniae [16] , E . faecalis [17 , 18] , Listeria monocytogenes [19–21] , Helicobacter pylori [22] , and Neisseria meningitidis [23] . With each of these pathogens , the enzyme directly responsible for PG O-acetylation and/or its regulator ( s ) was identified as a critical virulence factor . The enzyme catalyzing the O-acetylation of PG in Gram-positive bacteria was first identified in S . aureus over ten years ago as O-acetyltransferase ( Oat ) A [12] . Homologs of OatA from several other Gram-positive bacteria have since been characterized genetically and phenotypically , including those from: clinical isolates of S . pneumoniae [15 , 24] , Bacillus cereus [25] , E . faecalis [26] , Lactobacillus plantarum [27] and L . monocytogenes [20] . In addition to providing increased resistance to lysozyme [10 , 12–22] , OatA activity is known to attenuate resistance to ß-lactam antibiotics [15] , control endogenous autolytic activity [11 , 21 , 26 , 27] , and control cell septation [27] . Despite this recognition and its importance as a major virulence factor [10–23] , little is known about OatA at the molecular level . It is predicted to be bimodular , being comprised of an N-terminal integral membrane domain linked to a C-terminal extracytoplasmic domain [28] . Based on analogy to the two component PG O-acetylation system in Gram-negative bacteria , which involves an integral membrane acetyltransporter ( PatA ) and a cytoplasmic O-acetyltransferase ( PatB ) [6 , 8 , 29] , the surface-exposed C-terminal region of OatA is postulated to function as the O-acetyltransferase . There is minimal sequence similarity between the C-terminal domain of OatA and the well-characterized PatB [29–32] ( eg . 15 . 4% identity and 18 . 3% similarity between N . gonorrhoeae PatB and the C-terminal domain of S . aureus OatA ) . Moreover , no biochemical analysis of OatA has been reported . A lysine rich region in the C-terminal domain was postulated to contain the active site [10] but closer analysis of its predicted amino acid sequence suggests that it has the fold of SGNH/GDSL hydrolases with a signature catalytic triad of Asp , His and Ser residues [6 , 28] . However , to date the crystal structure of peptidoglycan O-acetyltransferase ( i . e . , PatB , OatA ) from any bacterium remains unknown .
To provide soluble forms of OatA homologs suitable for in vitro studies , the recombinant C-termini of the proteins from S . aureus ( SaOatAC; residues 435–603 ) and S . pneumoniae ( SpOatAC; residues 423–605 ) ( Fig 1B ) were produced and purified to apparent homogeneity , as judged by SDS PAGE ( S1 Fig ) . The amino acid sequences of these homologs share 28 . 5% identity and 54 . 1% similarity . We investigated their catalytic activity using our previously described qualitative assay for PG O-acetyltransferases [30 , 31] with pseudosubstrates p-nitrophenylacetate ( pNP-Ac ) , 4-methylumbelliferylacetate ( 4MU-Ac ) or acetyl-CoA as acetyl-donors , and chitotetraose ( GlcNAc4 ) as the acetyl acceptor . We used electrospray ionization-mass spectrometry ( ESI-MS ) analysis of reaction products to identify a single predominant O-acetylated chitotetraose product ion ( m/z = 873 . 35 [M+H]+ ) produced by both enzymes only when pNP-Ac or 4MU-Ac were used ( Fig 2 ) , suggesting that acetyl-CoA is not a suitable donor . The respective reaction products were analyzed further by MS/MS which showed that both enzymes modified the terminal non-reducing GlcNAc residue of chitotetraose ( S2 Fig ) . We observed a second O-acetylation by SpOatAC when using pNP-Ac as acetyl donor that occurred on one of the two internal GlcNAc residues which could be discerned by MS/MS . These data demonstrated that the extracytoplasmic C-terminal domains of OatA homologs function as O-acetyltransferases in vitro and that the activities are coupled to the turnover of the pseudosubstrates pNP-Ac or 4MU-Ac . In the absence of acceptor substrate , SpOatAC and SaOatAC exhibited weak hydrolase activity toward pNP-Ac and 4MU-Ac . We used this esterase activity to determine that the pH-activity optimum for both enzymes was 6 . 8 ( Fig 3A ) . Steady-state kinetic analyses provided similar Michaelis-Menten parameters for hydrolysis of pNP-Ac by each enzyme with SpOatAC being approximately 3-fold more efficient than SaOatAC , as reflected by kcat/KM values ( Fig 3B , 3C and 3E ) . However , as esterases the two enzymes were 252 and 45-fold less efficient , respectively , than authentic O-acetyl-PG esterase ( Ape ) from N . gonorrhoeae under similar conditions [33] . Accounting for the slower rates of hydrolysis in the absence of acceptors , we could determine the kinetics of O-acetyl transfer to various acceptors [31] ( S3 Fig ) . We used this assay to investigate the specificity of the enzymes for acceptor chain lengths . Initial experiments involved chito-oligosaccharides with degrees of polymerization ( DP ) between 2 and 6 as acceptors . With SpOatAC , its specific activity did not increase above the rate of hydrolysis when incubated in the presence of chito-oligosaccharides with a DP ≤ 3 . However , the inclusion of oligomers with a DP ≥ 4 significantly enhanced the rates of donor acetyl turnover . Confirmation that these GlcNAc oligomers served as acceptors was obtained by MS analysis ( S4 Fig ) . We attempted to determine the steady-state kinetics of the O-acetyltransferase activity with these chito-oligosaccharides but their limited solubility precluded our ability to provide saturating concentrations ( Fig 3D ) . Consequently , the kinetic parameters presented in Fig 3E were obtained by extrapolation of the Michaelis-Menten regression curves . Despite this limitation , the data suggested that SpOatAC has specificity for longer acceptor substrates as increased kcat/Km values were obtained with increasing acceptor DP . Furthermore , comparison of kcat values indicated that SpOatAC functions at least an order of magnitude faster as an O-acetyltrasferase than as an esterase . In contrast , reactions catalyzed by SaOatAC were not significantly influenced by any of the chito-oligosaccharide acceptors tested ( S3B Fig ) suggesting this homolog may have a higher specificity for more complex acceptor substrates . In an attempt to confirm that both SaOatAC and SpOatAC function as PG O-acetyltransferases , we tested their activity using our MS-based assay developed previously for the study of PatB [30 , 31] . This assay uses a pool of soluble muroglycans prepared by the limited mutanolysin digestion of purified PG as acceptor substrate . To our surprise , we could not detect any O-acetylated products in reaction mixtures following incubation of either OatAC with this heterogenous pool of muroglycans and either pNP-Ac or 4MU-Ac as acetyl donor . With the failure of this assay , we wondered if OatA has a more rigid specificity for muroglycans compared to PatB with respect to composition and/or DP . Unfortunately , it is technically challenging to prepare defined muroglycan substrates from natural sources of PG in sufficient quantity for study given the inherent heterogeneity of stem peptide composition , extent of cross-linking , and post-synthetic modifications . To circumvent this , we prepared a novel substrate in vitro that is a linear homopolymer of the natural precursor for PG biosynthesis , Lipid II . Recombinant penicillin-binding protein ( PBP ) 2a from S . pneumoniae was produced [34] and used to polymerize Lipid II under varying buffer conditions . The resulting linear homopolymers ( muroglycan-5P ) consisted of repeating units of GlcNAc-MurNAc-l-Ala-d-Glu-l-Lys-d-Ala-d-Ala ( GM-pentapeptide ) linked to an undecaprenyl pyrophosphate ( UndP ) through C1 of the reducing MurNAc residue ( S5 Fig ) . Muroglycan-5P remained uncrosslinked because the transpeptidase domain of S . pneumoniae PBP2a is only active on stem pentapeptides containing amidated d-Glu residues ( iso-d-Gln ) ; this amidation is conferred in vivo by Lipid II amidotransferase [34] . We found that the PBP2a-catalyzed polymerization of Lipid II could be controlled by detergent concentration ( S6 Fig ) . With 0 . 04% ( v/v ) Triton X-100 , a pool of muroglycans-5P enriched with DP 2–10 was generated . Whereas these muroglycans presented a suitable potential substrate for subsequent O-acetylation reactions , the presence of the residual UndP moiety at their reducing ends interfered with their MS analysis . Consequently , we digested samples with a muramidase ( mutanolysin ) prior to MS . We used muroglycan-5P to characterize the substrate specificity of the two OatAC homologs . MS analysis of a sample of muroglycan-5P ( DP 4–10 ) incubated with SaOatAC in the presence of pNP-Ac followed by mutanolysin digestion revealed a new prominent ion ( m/z = 1009 . 45 [M+H]+ ) 42 . 01 mass units larger than GM-pentapeptide ( m/z = 967 . 44 [M+H]+ ) which corresponds to an O-acetylated product ( Fig 4A ) . MS/MS analysis verified this O-acetylation and that it occurred only on MurNAc residues ( Fig 4B and 4C ) . The O-acetylated product was not observed in reactions with monomeric GM-pentapeptide that had been generated in situ by mutanolysin digestion prior to incubation with SaOatAC . Similarly , commercially available GM-dipeptide did not serve as an acceptor substrate for the enzyme . These data confirmed that SaOatAC functions as a PG O-acetyltransferase , and that it has specificity for the MurNAc residues within PG glycan chains . Given the lack of apparent activity toward the heterogeneous mix of sacculus-derived muroglycans ( as described above ) , we wondered if the substrate specificity of SaOatAC extended to the stem peptide of PG strands . To investigate this , samples of the muroglycan-5P were incubated with recombinant d , d-carboxypeptidase DacA ( PBP3 ) [35] to provide uniformly tailored muroglycans of GM-tetrapeptide repeats ( muroglycan-4P ) . Samples of these muroglycans-4P were then treated with l , d-carboxypeptidase DacB ( LdcB ) [35] to provide further trimmed muroglycans with GM-tripeptide repeats ( muroglycan-3P ) . ESI-MS confirmed the production of the respective muroglycan pools . Interestingly , neither muroglycan-4P nor muroglycan-3P served as effective acceptors for SaOatAC as very little product was observed with each ( Fig 4A ) . These results showed that this O-acetyltransferase has specificity for the pentapeptide stems on PG , a form of the muropeptide unit that would present in very low concentrations within mature PG . Parallel assays with SpOatAC revealed that it too only O-acetylates the MurNAc residues of muroglycans , but its substrate specificity with respect to stem peptide composition was distinctly different . In contrast to SaOatAC , SpOatAC was inactive against muroglycan-5P ( Fig 4A ) . Instead , it had a strong preference for muroglycan-4P and , like SaOatAC , was only weakly active on muroglycan-3P . Again , MS/MS analysis confirmed the specific O-acetylation of MurNAc residues ( Fig 4B and 4C ) . Taken together , these experiments demonstrated that the stem peptide composition of PG glycan chains has a significant effect on substrate recognition by the extracytoplasmic domains of OatA . To gain insight into the mechanism of action of OatAC , we undertook structural analysis of the enzyme using X-ray crystallographic techniques . Although , both SaOatAC and SpOatAC were subjected to crystallization trails , SaOatAC proved recalcitrant to crystallization . SpOatAC crystallized in both the native and SeMet derivative forms and crystals diffracted to 1 . 12 Å and 1 . 8 Å resolution , respectively ( S1 Table ) . We solved the structure using single-wavelength anomalous dispersion method and it was subsequently used as a search model for phasing the native high resolution diffraction data using molecular replacement method . The native enzyme was refined to Rwork/Rfree values of 15 . 0/16 . 8% ( S1 Table ) . The overall structure of SpOatAC adopts an atypical α/β hydrolase fold ( Fig 5A ) , where the core parallel β-sheet contains five strands ( β1 - β5 ) sandwiched between seven α-helices ( α1–α7 ) forming a shallow and solvent exposed putative active site pocket ( Fig 5B ) . A structural similarity search using the DALI server revealed that SpOatAC most closely resembles Bos taurus platelet-activating factor acetylhydrolase [36] ( PDB ID: 1BWQ; RMSD 2 . 4 Å over 158 residues ) and Escherichia coli thioesterase I/ protease I/ lysophospholipase L1 [37] ( PDB ID: 1IVN; RMSD 2 . 9 Å over 156 residues ) , two members of the SGNH/GDSL hydrolase superfamily ( cl01053 ) . Notable similarities were also seen with the SGNH/GDSL hydrolase Ape from N . meningitidis [38] ( PDB ID: 4K40; RMSD 2 . 9 Å over 155 residues ) and rhamnogalacturonan acetylesterase from Aspergillus aculeatus [39] ( PDB ID: 1DEO; RMSD 3 . 2 Å over 153 residues ) . Our identification of SpOatAC as a member of the SGNH/GDSL hydrolases is consistent with previous predictions regarding the structures of L . plantarum OatA [28] and N . gonorrhoeae PG O-acetyltransferase ( PatB ) [32] . Interestingly however , the DALI algorithm did not identify isoamyl acetate hydrolyzing esterase from Saccharomyces cerevisiae as a close homolog of SpOatAC; this other member of the SGNH/GDSL hydrolases was used by the algorithm to predict the structure of N . gonorrhoeae PatB [32] . That SpOatAC adopts a true SGNH hydrolase fold distinguishes it from the SGNH hydrolase-like structures of the alginate O-acetyltransferases of Pseudomonas aeruginosa ( PaAlgX ( PDB ID: ) ; identity: 11% , Cα RMSD: 3 . 6 Å over 79 residues ) and Pseudomonas putida ( PpAlgJ ( PDB ID: ) ; identity: 15% , RMSD: 3 . 1 Å over 92 residues ) , as well as Bacillus cereus secondary cell wall polysaccharide O-acetyltranferase ( BcPatB1 ( PDB ID: 5V8E ) ; identity: 11% , Cα RMSD: 3 . 6 Å over 79 residues ) . Although their folds are similar , topologically these latter enzymes are different from SpOatAC due to a circular permutation of their amino acid sequences , which characterizes them as part of the AlgX_N-like superfamily ( PaAlgX and PpAlgJ; cl16774 ) and the DHHW superfamily ( BcPatB1; cl25368 ) , respectively . On the whole , the true SGNH hydrolases ( esterase or transferase ) share low sequence similarity , but they are characterized by four consensus sequence Blocks ( I , II , III , V ) [40] ( Fig 6B ) . Almost all members of this family contain a conserved catalytic triad formed by a Ser nucleophile from Block I and conserved His and Asp residues from Block V . The homologous residues in SpOatAC are indeed aligned appropriately to serve as a catalytic triad ( Fig 5A ) . Ser438 is engaged in an H-bond network with His571 and Asp568 and the triad is positioned in the center of the putative active-site cleft of the enzyme ( Fig 5B ) . To verify their role as catalytic residues , we performed site-directed mutagenesis on the oatAC genes and kinetically characterized the recombinant variants . The S438A and H571A SpOatAC variants were devoid of detectable O-acetyltransferase activity while replacement of Asp568 with Asn resulted in minimal catalytic activity ( Table 1 ) . Our replacement of the equivalent residues in SaOatAC produced similar results . Unequivocal identification of Ser438 in SpOatAC as the catalytic nucleophile was made using the mechanism-based , irreversible inhibitor of Ser esterases methanesulfonyl fluoride ( MSF ) [41] . SpOatAC treated with this reagent lacked detectable catalytic activity and X-ray crystallographic analysis of a native crystal soaked with MSF revealed the formation of a covalent adduct to Ser438 ( described further below ) . A characteristic of the SGNH/GDSL hydrolases is the presence of an oxyanion hole comprised of the signature residues as H-bond donors: ( i ) the backbone NH of the Ser nucleophile; ( ii ) the backbone NH of Gly from consensus Block II , and ( iii ) the side chain amide of Asn from Block III ( Fig 6B ) . The residues of Block II form a type-II β-turn , which positions the backbone NH of the conserved Gly toward the active site so that it , together with the Ser and Asn residues , can serve its role in the oxyanion hole as an H-bond donor to stabilizes the oxyanion of the tetrahedral intermediate . The AlgX-like enzymes possess a similar Block II geometry , but lack the Asn in Block III that functions as the third H-bond donor ( Fig 6A and 6B ) . The oxyanion hole structure in SpOatAC is distinct from other SGNH hydrolases . Whereas SpOatAC possesses the Ser nucleophile and an Asn in Block III ( Asn491 in SpOatAC ) , the conserved Gly of Block II is replaced with a Ser ( Ser461 ) ( Fig 6B ) . Moreover , rather than forming a type-II β-turn , the residues of Block II in SpOatAC adopt a type-I β-turn resulting in 180° rotation of the peptide bond ( Fig 6A ) . This orients the backbone carbonyl oxygen of Val460 ( rather than backbone NH of Ser461 ) toward the active center where , together with the carbonyl oxygen of Val462 , it coordinates a water molecule ( w1 ) ( Fig 7A ) . This water serves as an H-bond acceptor for Nδ2 of Asn491and thereby stabilizes the resting conformation of this oxyanion hole residue . Another distinguishing feature of the oxyanion hole in SpOatAC is the positioning of its two component residues , Ser438 and Asn491 ( Fig 7A ) . The Nδ2 of Asn491 is positioned 3 . 4 Å from Ser438 Oδ , a distance significantly closer than the average 5 . 4 Å reported for the equivalent distance between the homologous residues in SGNH/GDSL hydrolases . We confirmed the importance of Asn491 in catalysis by generating an N491A variant of SpOatAC which lacked detectable transferase activity under the conditions tested ( Table 1 ) . Unexpectedly , however , the variant retained 45% activity as a hydrolase . The methylsulfonyl ( MeS ) adduct resulting from the inactivation of SpOatAC by MSF ( described above ) represents a transition-state analogue mimicking the attack of water on the acetyl-enzyme intermediate during hydrolysis . To confirm the identification of the catalytic nucleophile and gain further insight into the enzyme’s mechanism of action , we determined the structure of MSF-inactivated SpOatAC ( SpOatAC-MeS ) at 2 . 1 Å resolution ( S1 Table ) following modification of the native enzyme in cyrstallo with MSF . The MeS group is seen to form a covalent bond to the Oδ of Ser438 in a tetrahedral configuration ( Fig 7B ) and it is well defined in the electron density map ( Fig 7C , S7 Fig ) . The overall structures of SpOatAC and SpOatAC-MeS are very similar ( Cα RMSD: 0 . 327 Å over 178 residues ) , but several side chain displacements were observed in the active site on MeS binding . The most significant structural change involved the side chain of Asn491 ( Fig 7D ) . The presence of the MeS adduct opens the active site , shifting the Nδ2 of Asn491 2 Å from its initial position away from Ser438 and displacing the water molecule w1 ( Fig 7A , 7B and 7D ) . Other minor displacements occur in Ser438 , Ser461 , and His571 as a consequence of the steric effects imposed by the bound MeS . The methyl group of the MeS adduct appears to face the solvent adjacent to Val460 , and the sulfonyl O2 ( the structural mimic of an attacking water for hydrolytic activity; labeled O11 in the coordinate file ) forms a weak H-bond ( 3 . 3 Å ) to the imidazolium group of His571 while protruding into a hydrophobic pocket formed by Val490 and Val570 ( Fig 7B ) . Additionally , two H-bonds are made with the O1 of MeS ( the structural mimic of the carbonyl O of a bound acetyl group; labeled O12 in the coordinate file ) , one involving the backbone NH of Ser438 and the other with Nδ2 of Asn491 . These interactions are consistent with our earlier identification of Ser438 and Asn491 as comprising the oxyanion hole . Our alignment of Block II sequences of OatA homologs revealed the existence of an invariant Val/Ile residue at position five ( Val460 and Val475 of SpOatA and SaOatA , respectively ) ( S8 Fig ) that is not conserved in SGNH-GDSL esterase members . We probed the importance of Val at this position in SpOatAC by its site-specific replacement with the amino acids located in the same position in the esterases , platelet-activating factor acetyl hydrolase ( Gly ) and rhamnogalacturonan acetyl esterase ( Ala ) ( Fig 6B ) . The specific activity of both the V460G and V460A SpOatAC variants as esterases was slightly increased compared to the wild-type enzyme while a 10- and 5-fold reduction in transferase activity was observed , respectively ( Table 1 ) . Interestingly , replacement of Val460 with Ile , the only other residue found in this position in some OatA homologs , resulted in an increase in both activities , but the enhancement of O-acetyltransferase activity was significantly greater . Taken together , these data suggest that Val460 contributes to the effective binding of carbohydrate acceptor substrates .
One of the most common structural variations of PG produced by Gram-positive pathogens to protect them from lysis by innate immunity systems is the O-acetylation of MurNAc [6 , 7 , 42 , 43] . This modification to PG was first discovered almost 60 years ago [44] but the molecular details of the O-acetylation pathway remained unknown until now . In the current study , we show experimentally for the first time that the extracytoplasmic domains of OatA homologs from two important human pathogens function catalytically as O-acetyltransferases with specificity for both: i ) the C6 hydroxyl group of MurNAc residues within muroglycan chains , and ii ) the specific length of associated stem peptides . Additionally , our elucidation of the SpOatAC crystal structure has identified structural elements that are required for its catalytic mechanism . The likely natural source of the acetyl groups for PG O-acetylation , acetyl-CoA , does not serve as a donor substrate for OatAC . Given this , we postulate that the putative membrane-spanning , N-terminal OatA domain functions like PatA of Gram-negative bacteria [6 , 8 , 29] to translocate acetyl groups from a cytoplasmic source , presumably acetyl-CoA , across the membrane for their transfer to PG by OatAC ( Fig 8 ) . Whether the acetyl group is transferred directly from the N-terminal membrane domain to OatAC or via an exogenous carrier has yet to be determined . It is also not clear whether or not the two domains remain attached as a single bimodular protein following translation and insertion into the cytoplasmic membrane . Indeed , S . aureus OatA possesses a non-canonical type I signal peptidase cleavage site between the two domains , and the C-terminal domain alone has been detected in spent culture media [45] . Considering the kinetic and structural data presented above , we propose that OatAC employs a double-displacement mechanism of action involving a covalent acetyl-enzyme intermediate ( Fig 9 ) . As we have shown that the enzyme exists in both a resting and catalytically-active state , we suggest that binding of an acetyl donor molecule induces a conformational change involving the side chain of Asn491 to form the oxyanion hole which , together with the backbone amide of Ser438 , would serve to: ( i ) increase the electrophilicity of the carbonyl C to facilitate nucleophilic attack by the Ser438 hydroxyl group , and ( ii ) stabilize the negatively charged oxyanion of the tetrahedral transition state [46] . The nucleophilic attack on the carbonyl carbon of the acetyl donor by the Oδ of Ser438 is aided by abstraction of its proton by His571 and leads to a tetrahedral oxyanion , which is stabilized by the oxyanion hole residues Ser438 and Asn491 ( Figs 6 and 7 ) . The oxyanion collapses to the covalent acetyl-enzyme intermediate concomitant with the release of the donor product . A MurNAc residue of a PG glycan strand would then bind into the active site cleft and His571 again functions as a base to abstract the proton from the C6 hydroxyl group of the acceptor and render it nucleophilic . Attack by this C6 alkoxide on the carbonyl center of the acetyl-Ser438 leads to the formation of a second tetrahedral oxyanion , which then collapses to generate the O-acetyl MurNAc . Previous phylogenetic analysis of OatA had shown that homologs are distributed between three distinct clades [28] , where each cluster includes primarily proteins from a single bacterial order ( Lactobacillales and Bacillales ) . The exception is the genus Streptococcus ( belonging to the Lactobacillales ) for which the homologs of this group have branched into their own clade . Until now , only the two consensus motifs GDSV and Dx ( I/V ) H harboring the predicated catalytic triad residues had been identified in the C-terminal domain of OatA [28 , 47] . Our structural and biochemical characterization of SpOatAC demonstrated experimentally the functional significance of these conserved residues . More importantly , it enabled the identification of two additional motifs , the G ( T/V ) N motif containing Asn491 as an H-bond donor to the oxyanion hole , and the ( V/I ) ( G/S ) ( R/V ) motif as part of the type-I β-turn in the Block II-loop ( Fig 6B ) . While lacking the signature Gly of the oxyanion holes in SGNH/GDSL hydrolases , the retention of Asn in OatA signifies its closer evolutionary relationship to these enzymes compared to the PC-Esterases , a GDSL family of bimodular enzymes in eukaryotes that modify extracellular matrices; the PC-esterases lack both the Gly and Asn residues [48] . Replacement of Asn491 with Ala abolished transferase activity while reducing the specific activity of SpOatAC as an esterase toward pNP-Ac by only 58% ( Table 1 ) . Whereas this finding is consistent with our assignment of Asn491 as comprising the oxyanion hole for the stabilization of the transition state leading to formation of O-acetylated product , the level of residual esterase activity would suggest that Asn491 does not contribute significantly to the stabilization of the transition state for the first half of the reaction pathway involving the generation of the acetyl-enzyme . However , it should be recognized that enzyme-catalyzed hydrolysis of pNP-Ac proceeds through a transition state that has some tetrahedral character while maintaining partial carbonyl π bonding [49] , thus reducing the need for oxyanion hole stabilization . Also , it is possible that in addition to comprising the oxyanion hole , Asn491 contributes to the productive binding of acetyl-acceptor glycans . In this regard , examination of the surface topology of SpOatAC ( Fig 5B ) does not reveal a deep active site pocket/cleft . Moreover , unlike most carbohydrate-active enzymes , the shallow putative substrate-binding pocket is devoid of any aromatic residues . Despite lacking these common features , OatAC is active as a transferase on only glycans with a DP ≥4 ( Figs 2 and 3 ) suggesting that the enzyme possesses at least four carbohydrate-binding subsites . Presumably , these are arranged on its surface and serve to position specifically the C6 hydroxyl group of MurNAc residues for O-acetylation . Whereas OatAC has the capacity to function as an esterase in vitro , this hydrolytic activity of the extracytoplasmic domain would need to be minimized , if not precluded , in vivo to prevent the wasteful loss of acetyl groups ( as acetate ) to the external milieu . It is likely that a water-limiting environment is created by the juxtaposition of the domain with both the cytoplasmic membrane and the insoluble PG sacculus though this alone would not be sufficient to preclude water access . Jiang et al . [50] have observed that the type of β turn of the loop harboring an oxyanion residue distinguishes between hydrolytic and acyltransferase activities in some classical α/β hydrolases . Their observations invoke the participation of a bridging water that is H-bonded to the main-chain of a residue in the β-turn which either activates ( type-II ) or deactivates ( type-I ) the attacking water to promote hydrolase or transferase activity , respectively . However , our analysis of the SGNH/GDSL hydrolases and SpOatAC did not identify a bridging water molecule . Therefore , the consequences of the β-turn differences observed with a subset of the classical serine esterases/acyltransferases does not appear to apply to the SGNH/GDSL enzymes . More recently , Light et al . [51] have proposed that substrate binding to non-catalytic domains combined with a conformationally-stable active site promote transfer reactions , whereas conformational change at the active site is associated with hydrolysis . Their observations were made with glycosyl transferases , but it is possible that the same principles apply to esterases/transferases with homologous structures . With SpOatAC , we are unable to assess such binding contributions to its reaction pathway because the structure of the binding sub-sites and their associated interactions PG remains unknown . However , we did find through bioinformatic and protein engineering studies the importance of an invariant Val or Ile residue at the active site of the enzyme for transferase activity ( Val490 in SpOatAC ) . Presumably , either of these residues serve to stabilize acceptor substrates through hydrophobic interactions between their alkyl side-chains and the hydrophobic patches associated with carbohydrates . Also , examination of the MeS adduct ( a mimic of the carbonyl O of a bound acetyl group ) depicted in Fig 7 suggests the approach of an acceptor ligand ( e . g . , water or a carbohydrate ) to the carbonyl C of the bound acetyl group would have to be from a hydrophobic pocket formed by Val490 and Val570 . Thus , it is possible that the relative hydrophobicity of the reaction centre helps to restrict hydrolysis ( esterase activity ) and/or promote efficient transferase activity . As a maturation event , the O-acetylation of PG occurs extracytoplasmically on the existing PG sacculus [6 , 7 , 43] . Earlier biochemical studies involving pulse-chase experiments suggested the timing of the modification varies with species . Our kinetic characterization of OatAC from S . aureus and S . pneumoniae now provides a plausible explanation for this temporal difference at the molecular level . The final stages of PG biosynthesis involve the transglycosylation of Lipid II precursors into the growing glycan strand which is followed by the crosslinking of neighboring stem peptides . The latter occurs through a transpeptidation reaction whereby the crosslink is made with the concomitant loss of the terminal d-Ala from the donating stem pentapeptide , resulting in the formation of tetrapeptide stems . As SaOatAC has a high specificity for PG glycan chains possessing pentapeptide stems ( muroglycan-5P; Fig 3 ) , O-acetylation in this bacterium would have to immediately follow the transglycosylation reaction and precede transpeptidation . This is indeed consistent with the early observations of Snowden et al . [52] who suggested that O-acetylation must be very closely linked with the addition of PG units to the growing polymer . An analogous specificity would appear to exist in vancomycin-resistant E . faecailis where muropentapeptides terminating with d-Ala-d-Lac residues were found recently to be preferentially O-acetylated [53] . SpOatAC , on the other hand , has specificity for muroglycans with tetrapeptide stems ( Fig 3 ) and hence it would require the prior crosslinking and/or processing of nascent PG by a d , d-carboxypeptidase such as DacA before it could act . Further processing of stem peptides by a d , l-carboxpeptidase such as DacB to generate GM-tripeptide repeats would preclude continued O-acetylation . These unique specificities explain why , unlike PatB of Gram-negative bacteria [29 , 30] , OatAC was able to O-acetylate muroglycans derived from natural sacculi where the PG has undergone maturation . Thus , in addition to controlling the degree of crosslinking [54] , it would appear that the activity of carboxypeptidases such as DacA and DacB provides a means of control of PG O-acetylation at the substrate level . Another level of control of OatA activity imposed at the substrate level may concern its localization within a given species . The transglycosylation reactions for PG biosynthesis are catalyzed by the Class A PBPs [55] , and mono-functional transglycosylases [56–58] . The Class A PBPs are bifunctional possessing both transglycosylase and transpeptidase activities [55] . Consequently , OatA in S . aureus would need to be positioned in close proximity to , if not complexed with , one or both of its mono-functional transglycosylases so that it may act on the newly incorporated Lipid II precursors while they still possess their stem pentapeptides . Nothing is known about the organization of OatA and the monofunctional transglyosylases in S . aureus , but L . plantarum OatA was found to play a key role in the spatio-temporal control of cell elongation and septation . This function of OatA does not require its catalytic activity as an O-acetyltransferase [27] , suggesting that the protein helps to coordinate the PG biosynthetic complex of enzymes in PG metabolism . Hence , it is conceivable that S . aureus OatA may indeed complex with one or both of the monofunctional transglycosylases to permit PG O-acetylation . With S . pneumoniae , on the other hand , OatA would need to remain free and/or associated with its bi-functional PBPs for it to act on PG subunits with tetrapeptide stems following crosslinking reactions . This report has addressed several important aspects of PG O-acetylation in two human pathogens that have already overburdened healthcare systems worldwide . OatA is a key enzyme involved in bacterial resistance to the human innate immune response and it has been suggested to represent a useful target for pharmacological intervention [59] , which may apply especially to the treatment of MRSA and VRE . Our discovery that SaOatAC and SpOatAC have different substrate specificities will be an important consideration in the development of novel inhibitors that may serve as antivirulence agents for the sensitization of Gram-positive pathogens containing O-acetyl-PG to the lysozymes of innate immunity systems . In addition , this work will aid in the characterization of other carbohydrate O-acetyltransferases predicted to contain an SGNH hydrolase fold that perform important physiological and pathological roles in organisms from other kingdoms of life [60 , 61] .
The gene sequences encoding the extracytoplasmic domains of OatA from S . aureus and S . pneumoniae were identified based on topology and fold predictions using HHMTOP [62] and Phyre2 [63] , respectively . The gene encoding SaOatAC ( residues 435–603 ) was amplified by PCR using genomic DNA from S . aureus SA113 and the codon-optimized gene encoding SpOatAC ( residues 423–605; originally from S . pneumoniae R6 ) was synthesized and provided in a pUC57 ( pUC57-SpOatAC ) vector from Genscript ( Piscataway , NJ ) . For cloning , the PCR product encoding SaOatAC , pUC57-SpOatAC , and the expression vector pBAD-His A ( Invitrogen , Burlington , ON ) were digested with XhoI and EcoRI . Each gene was then ligated to pBAD-His A to produce pACPM31 ( SaOatAC ) and pDSAC81 ( SpOatAC ) . Both constructs contain an enterokinase-cleavable N-terminal His6 tag and are under the control of an arabinose inducible promoter . Site-specific replacements of amino acid residues for both constructs were performed by site-directed mutagenesis using the QuickChange Site-Directed Mutagenesis Kit ( Agilent Technologies Canada Inc . , Mississauga , ON ) with the appropriate primers listed in S2 Table . For the production of SaOatAC or SpOatAC , Escherichia coli BL21 ( DE23 ) was transformed with pACPM31 or pDSAC81 , respectively . Cells were grown in LB broth containing 100 μg·mL-1 ampicillin at 37 oC until an OD600 of 0 . 6 was reached , at which point arabinose was added to a final concentration of 0 . 2% ( w/v ) . The cultures continued to grow at 37 oC for an additional 4 h , after which the cells were harvested by centrifugation ( 5 , 000 × g , 4 oC , 15 min ) and frozen at—20 oC until needed . For the production of selenomethionine-labelled ( SeMet ) SpOatAC , pDSAC81 was transformed into E . coli B834 and grown in M9 minimal media supplemented with 40 mg selenomethionine as previously described [64] . The expression of SeMet-SpOatAC was carried out as described above for native protein . To purify SaOatAC , the cell pellets were resuspended in lysis buffer ( 50 mM sodium phosophate buffer , pH 7 . 8 , 500 mM NaCl , 20 mM imidazole , 20 μg·mL-1 DNase , 20 μg·mL-1 RNase , and 50 μg·mL-1 hen egg-white lysozyme ) and disrupted by sonication on ice . Unbroken cells were cleared from the lysate by centrifugation ( 15 , 000 x g , 4 oC , 15 min ) and the supernatant was incubated with cOmplete His-Tag purification resin ( Roche Diagnostics , Laval , QC ) pre-equilibrated with wash buffer ( 50 mM sodium phosphate pH 8 . 0 , 500 mM NaCl ) . After 1 h at 4 oC with nutation , the cell lysate containing SaOatAC-bound resin was loaded onto a gravity-flow column . The resin was washed with 100 mL wash buffer and then SaOatAC was eluted using wash buffer containing 250 mM imidazole . Following elution , SaOatAC was dialyzed against 25 mM sodium phosphate buffer 6 . 5 at ambient temperature for 1 h ( with one buffer change ) . The dialyzed protein was filtered using a syringe driven filter ( 0 . 22 μm; Milipore ) and loaded onto a Source 15S cation-exchange column ( GE Health Care Canada Inc . , Mississauga , ON ) pre-equilibrated with dialysis buffer using an NGC protein purification system ( Bio-Rad Laboratories ( Canada ) Ltd , Mississauga , ON ) . Protein elution was achieved with a linear gradient of 0−1 M NaCl at a flow-rate of 1 mL·min-1 . SpOatAC was purified similarly , however , in all cases the phosphate buffer was substituted for Tris-HCl buffer , dialysis was performed at pH 8 . 0 , and anion-exchange chromatography was conducted using a Source 15Q column ( GE Health Care ) at pH 8 . 0 . The production and purification of SaOatAC and SpOatAC possessing site-specific amino acid replacements were performed as described above , respectively , with the precaution of using fresh chromatography media to preclude the possibility of contamination with wild-type enzymes . The secondary structure of each purified protein was assessed by circular dichroism ( CD ) spectroscopy to ensure their correct folding . The genes encoding DacA ( covering residues 23–394 ) and DacB ( covering residues 56–238 ) lacking both their N-terminal trans-membrane and C-terminal membrane interaction helices were PCR amplified from S . pneumoniae R6 genomic DNA with the primers listed in S2 Table . Both PCR products were digested with NdeI and XhoI and ligated into pET-28a . The resulting constructs , pDSAC01 and pDSAC02 harboring dacA and dacB respectively , contained each gene in frame with an N-terminal His6 tag under the control of an IPTG inducible promoter . For the overproduction of DacA or DacB , the respective plasmids were transformed into E . coli BL21 pLysS and E . coli T7 Shuffle , respectively . The cells were grown in LB broth supplemented with 50 μg·mL-1 kanamycin until an OD600 of 0 . 6 was reached , at which point expression was induced with IPTG at a final concentration of 1 mM . After 4 h of additional growth , the cells were harvested by centrifugation ( 5000 × g , 15 min , 4 oC ) and the cell pellets were frozen at -20 oC until needed . For purification , the cells were lysed by sonication in lysis buffer ( 50 mM Tris-HCl pH 8 . 0 , 500 mM NaCl ) , the His6-tagged proteins were bound to cOmplete His-Tag purification resin , and eluted with lysis buffer containing 300 mM imidazole as described previously [31] . The purified proteins were dialyzed into 50 mM Tris-HCl pH 8 . 0 and kept at -20 oC until required . SpOatAC , SaOatAC , and their variants were diluted to 0 . 15 mg·mL-1 in 10 mM sodium phosphate buffer pH 7 . 0 . CD spectra ( 190 nm—260 nm , 1 nm increments ) of samples in a 0 . 1 cm quartz cuvette were measured in triplicate at 25 oC using a Jasco Model J-815 CD spectrometer ( Jasco Inc . , Easton , MD ) . To identify a suitable acetyl-donor for the OatAC homologs , 100 μL reaction mixtures containing enzyme ( 5 μM ) , 1 mM donor ( acetyl-CoA , pNP-Ac , or 4MU-Ac ) and 2 mM chitotetraose in 25 mM sodium phosphate buffer pH 6 . 5 were incubated at 37 oC for 1 h . Reactions were terminated by separating the substrates from the enzyme using porous graphitized carbon ( PGC ) solid-phase extraction ( SPE ) cartridges , previously charged with acetonitrile ( ACN ) and equilibrated with water . The PGC-SPE cartridges were washed with three volumes of water and both chitotetraose and O-acetylated products were eluted with 0 . 5 mL ACN/water ( 1:1 ) . ESI-MS analysis was performed by direct infusion using an Amazon SL ion-trap mass spectrometer ( Bruker Daltonics Ltd . , Milton , ON ) at a flow rate of 5 μL·min-1 with a spray voltage of 4 . 5 kV . The ion-trap was operated in positive ion mode and MS scans ranging from 200–2200 m/z . MS/MS scans were made on the major ions with a fragmentation amplitude of 1 . 0 . Mass spectra were analyzed using Bruker Compass tool ( Bruker ) . The pH optima for the SpOatAC- and SaOatAC-catalyzed hydrolysis of pNP-Ac were determined using the spectrophotometric assay for pNP release as described by Moynihan and Clarke [31] . Triplicate reaction mixtures ( 200 μL ) contained 5 μM enzyme and 1 mM pNP-Ac in 25 mM sodium borate-phosphate-citrate buffer with pH values ranging from 5 to 7 . 5 with 0 . 5 unit intervals . Hydrolysis was monitored at 410 nm over 15 min at 25 oC and enzymatic rates were determined by subtracting the rates of spontaneous pNP-Ac hydrolysis of control reactions lacking enzyme . The determination of steady-state Michaelis-Menten parameters for enzyme-catalyzed hydrolysis of pNP-Ac ( esterase activity ) were made using the spectrophotometric assay described above . Initial rates of 0 . 005–5 mM pNP-Ac hydrolysis in 50 mM sodium phosphate buffer pH 6 . 5 containing 5% ( v/v ) ethanol ( to maintain solubility of substrate ) were determined following the addition of 5 μM SpOatAC or 3 μM SaOatAC ( final concentration ) . The steady-state kinetics of acetyltransfer catalyzed by SpOatAC were determined also using the spectrophotometric assay for pNP release [38] . Enzyme ( 5 μM ) in 50 mM sodium phosphate buffer pH 6 . 5 was incubated at 25 oC with 2 mM pNP-Ac and varying concentrations of chito-oligosaccharides ( DP 3–6 ) in a total volume of 150 μL . Control reactions lacked the chito-oligosaccharide acceptors . The net rate of acetyltransfer was determined by subtracting the initial rates of pNP release in control reactions from reactions containing chitooligosaccharides . The Michaelis-Menten kinetic parameters were determined by non-linear regression using GraphPad Prism 4 ( GraphPad Software , Inc . , La Jolla , CA ) . Each of these experiments was performed with three different preparations of the enzymes . Enzyme ( 25 μM ) in 25 mM sodium phosphate buffer pH 6 . 5 was incubated with 5 mM MSF at 25 oC for 20 min . Samples were withdrawn and assayed for pNP-Ac hydrolytic activity as described above . Lys-containing Lipid II ( partially labeled with Dansyl chloride for facile detection ) was prepared enzymatically as previously described [33] . Linear muroglycans were generated by polymerizing Lipid II in 50 mM HEPES buffer pH 7 . 5 , 200 mM NaCl , 25 mM MgCl , 25% ( v/v ) DMSO , and varying concentrations of Triton X-100 using soluble S . pneumoniae PBP2a ( covering residues 78–731 ) lacking its N-terminal transmembrane helix . Following incubation at 30 ºC overnight , the reaction mixture was heat inactivated at 90 oC for 10 min and precipitated PBP2a was removed by centrifugation ( 10 , 000 × g , 5 min ) . The DP was determined by SDS PAGE analysis with fluorescence detection of the Dansyl label using 8 . 5% acrylamide gels [65] . Muroglycans with tetra- and tri-peptides were prepared by incubation of the original PBP2a product with recombinant d , d-carboxypepdiase DacA and l , d-carboxypeptidase from S . pnuemonae R6 . Samples ( 100 μL ) of the muroglycans ( 15 μg·mL-1 ) in 50 mM sodium phosphate buffer pH 6 . 5 were incubated at 37 oC overnight with DacA alone or with both DacA and DacB ( final concentration of each enzyme , 5 μM ) . Heat inactivation at 95 oC for 10 min was used again to quench further reaction and precipitated protein ( s ) was removed by centrifugation ( 10 , 000 × g , 5 min ) . Enzyme ( 10 μM ) in 50 mM sodium phosphate buffer pH 6 . 5 was incubated at 37 oC for 1 h with 0 . 5 mM pNP-Ac , and 10 μg·mL-1 muroglycans possessing either penta , tetra , or tripeptide stems . The enzymes were heat inactivated at 95 oC for 30 min and then removed by centrifugation ( 10 , 000 × g , 5 min ) . The PG oligomers were digested overnight at 37°C with 100 μg·mL-1 mutanolysin which was added directly to the reaction product pool . Digestion of the muroglycans to monomers ( GM-peptide ) was necessary for detection of the reaction products by ESI-MS . Following digestion , the reaction products were subjected to adsorption chromatography on PGC-SPE as described above , except the elution solvent contained 0 . 1% formic acid to facilitate the desorption of the charged muropeptides . Reaction products were then analyzed by ESI-MS . These experiments were repeated once with identical results . SpOatAC was concentrated to 42 mg·mL-1 using an Amicon Ultra-15 centrifugal filter ( 30 kDa MWCO; Millipore ( Canada ) Ltd . , Etobicoke , ON ) at 4 , 000 × g and 4 oC , followed by centrifugation ( 15 , 000 × g , 10 min , 4 oC ) to remove any insoluble material . The concentrated protein sample was used in the MCSG Crystallization Suite sparse matrix crystallization screens 1 to 4 ( Microlytic North America Inc . , Burlington , MA ) . Crystallization screening using the sitting drop vapor diffusion method was setup using a Gryphon robot ( Art Robbins Instruments , Sunnyvale , CA ) with 1 µL drops of protein and a protein to reservoir ratio of 1:1 . Large single diffraction quality crystals appeared after one week of incubation at 21 oC in 0 . 1 M HEPES:NaOH pH 7 . 5 , 1 . 2 M sodium citrate tribasic; and 2 . 4 M sodium malonate pH 7 . Crystal screening of selenomethionine ( SeMet ) labeled OatA was carried out as described above and large single crystals were grown in 2 . 4 M sodium malonate pH 7 . To produce SpOatAC in complex with MeS , crystals grown in 1 . 8 M NaH2PO4/K2HPO4 , pH 8; 0 . 1 M HEPES:NaOH pH 7 . 5 , 1 . 4 M sodium citrate tribasic were soaked in mother liquor containing 1 . 2 M sodium citrate tribasic and 250 mM MSF for 24 hours . Crystals were cryoprotected for 5–10 s in reservoir solution supplemented with 25% ( v/v ) ethylene glycol prior to vitrification in liquid nitrogen . Native and selenium single-wavelength anomalous diffraction ( Se-SAD ) data were collected on beam line X29 at the National Synchrotron Light Source ( Upton , NY ) ( S1 Table ) . The data were indexed and scaled using HKL2000 [66] . The Se-SAD data were used in conjunction with HKL2MAP [67] to locate four selenium sites , and density modified phases were calculated using SOLVE/RESOLVE [68] . The resulting electron density map was of good quality and enabled PHENIX AutoBuild [69] to build 100% of the protein . Manual model building of the remaining residues was completed in COOT [70] and alternated with refinement using PHENIX . REFINE [71] . The structures of the native and MeS proteins were determined by molecular replacement using the SeMet incorporated derivative and the native structure as the search model . The PHENIX AutoMR algorithm [71] was used with manual model building and refinement carried out as described previously . Translation/ Libration/Screw groups were used during refinement and determined automatically using the TLSMD web server [72 , 73] . All molecular models were generated using Pymol and structural superpositions were made using the cealign plug-in . Nucleotide sequencing of PCR products , as well as plasmids , was performed by the Genomics Facility of the Advanced Analysis Center ( University of Guelph ) . Protein concentrations were determined using the Pierce BCA protein assay kit ( Pierce Biotechnology , Rockford , IL ) with BSA serving as the standard . SDS-PAGE on 15% acrylamide gels was conducted by the method of Laemmli [74] with Coommassie Brilliant Blue staining and Western immunoblot analysis as previously described [29] . Data deposition: The crystallography , atomic coordinates , and structure factors have been deposited in the Protein Data Bank , www . pdb . org ( PDB ID code 5UFY ( SpOatAC ) ; 5UG1 ( SpOatACMeS ) . | Multi-drug resistance amongst important human pathogens , such as methicillin-resistant Staphylococcus aureus ( MRSA ) , vancomycin-resistant Enterococcus ( VRE ) and drug-resistant Streptococcus pneumoniae ( DRSP ) , continues to challenge clinicians and threaten the lives of infected patients . Of the several approaches being taken to address this serious issue is the development of antagonists that render the bacterial infection more susceptible to the defensive enzymes and proteins of our innate immunity systems . One such target is the enzyme O-acetyltransferase A ( OatA ) . This extracellular enzyme modifies the essential bacterial cell wall component peptidoglycan and thereby makes it resistant to the lytic action of lysozyme , our first line of defense against invading pathogens . In this study , we present the first biochemical and structural characterization of OatA . Using both the S . aureus and S . pneumoniae enzymes as model systems , we demonstrate that OatA has unique substrate specificities . We also show that the catalytic domain of OatA is a structural homolog of a well-studied superfamily of hydrolases . It uses a catalytic triad of Ser-His-Asp to transfer acetyl groups specifically to the C-6 hydroxyl group of muramoyl residues within peptidoglycan . This information on the structure and function relationship of OatA is important for the future development of effective inhibitors which may serve as antivirulence agents . | [
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... | 2017 | In vitro characterization of the antivirulence target of Gram-positive pathogens, peptidoglycan O-acetyltransferase A (OatA) |
Lyme disease spirochetes demonstrate strain- and species-specific differences in tissue tropism . For example , the three major Lyme disease spirochete species , Borrelia burgdorferi sensu stricto , B . garinii , and B . afzelii , are each most commonly associated with overlapping but distinct spectra of clinical manifestations . Borrelia burgdorferi sensu stricto , the most common Lyme spirochete in the U . S . , is closely associated with arthritis . The attachment of microbial pathogens to cells or to the extracellular matrix of target tissues may promote colonization and disease , and the Lyme disease spirochete encodes several surface proteins , including the decorin- and dermatan sulfate-binding adhesin DbpA , which vary among strains and have been postulated to contribute to strain-specific differences in tissue tropism . DbpA variants differ in their ability to bind to its host ligands and to cultured mammalian cells . To directly test whether variation in dbpA influences tissue tropism , we analyzed murine infection by isogenic B . burgdorferi strains that encode different dbpA alleles . Compared to dbpA alleles of B . afzelii strain VS461 or B . burgdorferi strain N40-D10/E9 , dbpA of B . garinii strain PBr conferred the greatest decorin- and dermatan sulfate-binding activity , promoted the greatest colonization at the inoculation site and heart , and caused the most severe carditis . The dbpA of strain N40-D10/E9 conferred the weakest decorin- and GAG-binding activity , but the most robust joint colonization and was the only dbpA allele capable of conferring significant joint disease . Thus , dbpA mediates colonization and disease by the Lyme disease spirochete in an allele-dependent manner and may contribute to the etiology of distinct clinical manifestations associated with different Lyme disease strains . This study provides important support for the long-postulated model that strain-specific variations of Borrelia surface proteins influence tissue tropism .
Lyme disease is distributed worldwide and is the most common arthropod-borne infectious disease in the United States [1]–[3] . The causative agent is the spirochete Borrelia burgdorferi sensu lato , which includes B . burgdorferi sensu stricto , B . garinii , and B . afzelii [4] [5] . Following the bite of an infected Ixodes tick , the Lyme disease spirochete produces a local infection , resulting in the characteristic skin lesion erythema migrans . In the absence of antibiotic treatment , spirochetes may disseminate to multiple organs , including joints , the central nervous system , and the heart , resulting in diverse manifestations such as arthritis , neurological abnormalities , and carditis [2] , [6]–[9] . Lyme disease spirochetes demonstrate strain- and species-specific differences in tissue tropism . For example , B . burgdorferi sensu stricto , most prevalent in the United States , B . garinii and B . afzelii , each more common in Europe [1] , [5] , are genetically distinct and are associated with different typical chronic manifestations: B . burgdorferi with arthritis , B . garinii with neuroborreliosis , and B . afzelii with the chronic skin lesion acrodermatitis [10] . In addition , the severity of human symptoms and the dissemination activities of different strains within a single Lyme disease species may also differ significantly [9] , [11] , [12] . Strain-to-strain variation in dissemination and disease manifestation has also been observed in animal studies [13] , [14] . The basis for differences in tissue tropism and/or disease severity is not well understood . Several documented or putative virulence factors encoded by Lyme disease spirochete vary in a strain-specific manner [3] , [15]–[17] . In some instances this variation is associated with differences in the postulated biological activity of the factor , e . g . binding of complement regulators by CspZ and other CRASPs ( complement regulator-acquiring surface proteins ) or binding of plasminogen by the outer surface protein OspC [16]–[19] . Moreover , in a set of three Lyme disease strains , invasiveness correlated with the ability of OspC to bind plasminogen [18] , [20] , giving rise to the hypothesis that allelic variation of B . burgdorferi surface proteins have the capacity to contribute to tissue tropism of different Lyme disease spirochete strains [9] , [12] , [18] , [21] . However , to date rigorous demonstration that isogenic strains harboring allelic variants of virulence genes indeed behave differently during animal infection has been lacking . Adhesion of bacterial pathogens to host cells or extracellular matrix ( ECM ) of target tissues , often mediated by outer surface protein adhesins , is thought to be an important early step in tissue colonization [22] . In fact , Borrelia sp . encode a plethora of adhesins that have been found to recognize different ECM components and/or to promote binding to diverse mammalian cell types [23]–[25] . Two related Borrelia adhesins , decorin binding proteins A and B ( DbpA and DbpB , respectively ) , encoded by a bicistronic operon [26] , bind to both decorin and to the glycosaminoglycan ( GAG ) dermatan sulfate [27] , [28] . Whereas the DbpB sequence is highly conserved in different strains of B . burgdorferi sensu lato , the DbpA sequence is highly polymorphic , with sequence similarities as low as 58% between variants [29] . Spirochetes disseminate less efficiently in decorin-deficient compared to wild type mice , suggesting an important function for decorin binding in spirochete tissue spread . [30] . B . burgdorferi lacking DbpA and DbpB in fact exhibited both reduced colonization and dissemination activity and a three- to four-log increase in ID50 , indicating that these adhesins play a significant role in infection [31]–[35] . Consistent with this role , dbpA and dbpB are expressed efficiently in culture conditions that may reflect the host environment , such as at mammalian body temperature or in the presence of atmospheric CO2 [36]–[38] . The ability of DbpA to bind to decorin and/or dermatan sulfate requires an intact C-terminus , and DbpA variants demonstrate differences in decorin- and/or dermatan sulfate-binding activities [21] , [39] . Given the abovementioned strain- and species-specific differences in tissue tropism among Lyme disease spirochetes , an attractive hypothesis is that the decorin and/or GAG-binding activities of DbpA ( and DbpB ) are critical for promoting colonization , and that allelic variation of dbpA might influence the tissue tropism of Lyme disease spirochetes . In the current study , we infected mice with various isogenic B . burgdorferi strains encoding DbpA variants , or a non-binding mutant . These studies indicate that decorin- and/or GAG-binding activity of DbpA is required for colonization functions . Importantly we also found that allelic variation of dbpA contributes to differences in tissue tropism .
We previously tested the ability of DbpA mutants or variants to mediate binding of a non-adhesive and non- infectious B . burgdorferi strain to decorin , dermatan sulfate or mammalian cells [39] . DbpAVS461ΔC11 , which lacks the 11 C-terminal residues of DbpAVS461 , was shown to be unable to promote spirochetal binding to decorin or dermatan sulfate . In addition , a set of variants that included DbpA from B . burgdorferi strains B31 ( DbpAB31 ) , 297 ( DbpA297 ) , N40-D10/E9 ( DbpAN40-D10/E9 ) , B356 ( DbpAB356 ) , B . afzelii VS461 ( DbpAVS461 ) , and B . garinii PBr ( DbpAPBr ) , showed variant-specific differences in the ability to promote bacterial adhesion to the two substrates . By using semi-quantitative ELISA , this study also analyzed the binding of recombinant versions of DbpA variants except DbpA297 and DbpAB356 , which display 90% and 99% similarities to DbpAB31 and DbpAN40-D10/E9 , respectively . To measure the decorin- and dermatan sulfate-binding affinities of DbpA variants more precisely , here we utilized quantitative ELISA and surface plasmon resonance ( SPR; Fig . S2A and Table 1 ) . The two independent methods for assessing binding gave results entirely consistent with each other and revealed dissociation constants indicating ( 1 ) robust decorin-binding by DbpAPBr ( KD = 0 . 06–0 . 09 µM ) ; ( 2 ) moderate decorin-binding by DbpAB31 , DbpA297 , and DbpAVS461 ( KD = 0 . 14–0 . 30 µM ) ; ( 3 ) less efficient decorin-binding by DbpAN40-D10/E9 and DbpAB356 ( KD = 0 . 71-0 . 95 µM ) . Interestingly , a BXBB motif ( residues 64 to 67 ) that has been proposed to form a positively charged pocket that binds to decorin and/or dermatan sulfate [40] , is not found in DbpAPBr ( Fig . S6 ) , suggesting that BXBB is not essential for decorin- or dermatan sulfate-binding . With the exception of DbpAVS461 , the calculated KD for dermatan sulfate binding of each DbpA variant was approximately two- to four-fold higher than its KD for decorin binding; DbpAVS461 bound to dermatan sulfate approximately six-fold less efficiently than to decorin ( Fig . S2 and Table 1 ) . Finally , recombinant protein DbpAVS461ΔC11 , which was found by far-UV CD analysis ( Fig . S1 ) to retain the secondary structure of wild-type DbpAVS461 , was unable to bind to decorin or dermatan sulfate . These findings were entirely consistent with previous results determined with less quantitative methods [39] , and likely reflect the fact that sequence lacking in DbpAVS461ΔC11 includes conserved K170 , a lysine residue previously shown to be critical for decorin-binding activity [41] ( Fig . S6 ) . DbpAPBr , DbpAVS461 , and DbpAN40-D10/E9 each represent one of the three binding profiles described above , as well as collectively encompass the three major genospecies of Lyme disease spirochetes , each of which has been associated with different human clinical manifestations . To focus on how variations in DbpA binding to decorin and dermatan sulfate may influence the infectious process and avoid potential functional redundancy associated with the production of another decorin- and dermatan sulfate-binding adhesin , we generated DbpA-producing strains that did not produce DbpB . We generated a set of plasmids that encode the bbe22 gene , which is required for spirochete survival in a mammalian host [42] , and the coding region of dbpAPBr , dbpAVS461 , or dbpAN40-D10/E9 , or dbpAVS461ΔC11 ( as a non-binding control ) under the control of the dbpBA promoter of B . burgdorferi strain B31 . The plasmids encoding different dbpA alleles were then individually introduced into a dbpBA deletion mutant of the highly transformable infectious strain B . burgdorferi ML23 , a derivative of B . burgdorferi B31 that lacks bbe22 and therefore cannot survive in the mouse in the absence of a complementing bbe22-encoding plasmid [43] . We verified by flow cytometry analysis that the DbpA variants produced in B . burgdorferi ML23ΔdbpBA were located on the surface of the recombinant spirochetes , and at levels indistinguishable from that of their DbpA-proficient parental strain ML23 ( Fig . S3 ) . We next investigated the distinct decorin- and dermatan sulfate-binding activities specifically conferred to infectious strain ML23 by the various dbpA alleles . We measured binding of radiolabeled ML23ΔdbpBA strains producing DbpA variants to microtiter wells coated with decorin or dermatan sulfate . Chondroitin-6-sulfate , included as a negative control , mediated binding of less than 5% of inoculum ( data not shown ) . Strain ML23 harboring the vector alone , a positive control that expresses both DbpA and DbpB , bound to decorin or dermatan sulfate with an efficiency of approximately 55% or 15% , respectively ( Fig . 1 ) . This level of binding was significantly greater than binding by strain ML23ΔdbpBA harboring vector alone , i . e . approximately 30% or 10% for binding to decorin or dermatan sulfate , respectively ( Fig . 1 ) . This “background” ( i . e . , DbpB- and DbpA-independent ) decorin- and dermatan sulfate-binding activity of strain ML23ΔdbpBA is considerably greater than that of the high-passage strain B . burgdorferi B314 ( i . e . , less than 2% for either substrate ) , suggesting that decorin- and dermatan sulfate-binding adhesins other than DbpA and DbpB are expressed by strain ML23ΔdbpBA . As expected , the production of both DbpA and DbpB in strain ML23ΔdbpBA ( Fig 1 , “pDbpBA” ) restored binding to the levels of strain ML23 . The production of DbpAVS461 , DbpAPBr , or DbpAN40-D10/E9 in strain ML23ΔdbpBA resulted in decorin- and dermatan sulfate-binding significantly greater than strain ML23ΔdbpBA harboring vector alone , indicating that these DbpA variants provide significant adhesive function to this strain ( Fig . 1 ) . DbpAVS461ΔC11 conferred no detectable increase in binding , indicating , as predicted , that the 11 C-terminal amino acids of DbpAVS461 are essential for binding to decorin and dermatan sulfate [39] . DbpAPBr promoted significantly greater spirochete binding to decorin and dermatan sulfate than did DbpAVS461 or DbpAN40-D10/E9 ( Fig . 1 ) . Thus , the degree of decorin- and dermatan sulfate-binding conferred to strain ML23ΔdbpBA by each DbpA variant was consistent with both the quantitative binding analysis of purified recombinant DbpA proteins described above ( Fig . S2 ) and with our previous study of these variants expressed in a non-adherent , non-infectious strain B314 [39] . The defect in decorin- and/or dermatan sulfate-binding by DbpAVS461ΔC11 provided an opportunity to determine if these activities of DbpA are essential to promote B . burgdorferi colonization . C3H/HeN mice were infected with ML23ΔdbpBA producing DbpAVS461 or DbpAVS461ΔC11 and the bacterial load at the inoculation site was assessed at 3 days post-infection . Strains ML23 and ML23ΔdbpBA/pDbpBA were included as positive controls and colonized the site efficiently ( ∼300 bacteria per 100 ng of DNA ) , 60-fold higher than that of ML23ΔdbpBA harboring vector alone ( Fig . 2 ) . ML23ΔdbpBA producing DbpAVS461 promoted significant colonization ( ∼30 bacteria per 100 ng DNA , or ∼six-fold more than ML23ΔdbpBA ) at the inoculation site . This finding indicated that production of DbpA alone could partially complement the defect of a B . burgdorferi ΔdbpBA mutant , consistent with previous studies [32] , [33] . In contrast , ML23ΔdbpBA producing DbpAVS461ΔC11 did not mediate colonization at a level any greater than ML23ΔdbpBA carrying the empty vector . To determine if DbpAVS461ΔC11 might promote colonization at a later time point , we also assessed infected mice at 28 days post-infection . The positive control strains B . burgdorferi ML23 and B . burgdorferi ML23ΔdbpBA/pDbpBA displayed efficient colonization at all sites tested ( Fig . 3 ) . In particular , colonization of the inoculation site , bladder and ear was 30-200-fold higher than that of ML23ΔdbpBA harboring vector alone . The production of DbpAVS461 by ML23ΔdbpBA producing DbpAVS461 did not promote colonization of the joints or heart at this time point but did promote colonization of the inoculation site , bladder , and ear at levels indistinguishable from the positive control strains . In contrast , ML23ΔdbpBA/pDbpAVS461ΔC11 did not mediate colonization at a level any greater than ML23ΔdbpBA carrying the empty vector at any of the sites tested . The bacterial load in a particular tissue may be in part a reflection of the rate of immune clearance . To determine if the colonization defect of ML23ΔdbpBA/pDbpAVS461ΔC11 might be due to the induction of a particularly robust immune response , at 28 days post-infection we measured B . burgdorferi-specific IgG or IgM in the sera of mice inoculated with this strain . No B . burgdorferi-specific antibodies were detected ( Fig . S4 ) , suggesting that ML23ΔdbpBA/pDbpAVS461ΔC11 is incapable of establishing a productive infection that triggers an adaptive immune response . In addition , the results suggest that the colonization defect of this strain was independent of an adaptive immune response . Consistent with this , a 28-day infection of the mice strain deficient for adaptive immune response ( SCID mice ) revealed that the production of DbpAVS461ΔC11 was unable to enhance the ability of ML23ΔdbpBA to colonize any of the tissues tested , in contrast to the production of DbpAVS461 ( Fig . 4 ) . Together , these results strongly suggest that the decorin- and/or dermatan sulfate-binding activity of DbpA is required for its ability to facilitate spirochetal colonization . To test whether variation in the decorin or dermatan sulfate binding capabilities by DbpA correlates with differences in colonization and/or disease , we chose to analyze the colonization promoting abilities of three DbpA variants that display distinct decorin- and dermatan sulfate-binding activities . C3H/HeN mice were infected with ML23ΔdbpBA producing DbpAPBr , DbpAN40-D10/E9 , or DbpAVS461 , and differences in colonization at the inoculation site , heart , joints , bladder and ear were assessed at 3 , 7 , 14 , 21 , or 28 days post-infection . Strains ML23 and ML23ΔdbpBA/pDbpBA were included as positive controls , and ML23ΔdbpBA harboring vector alone served as a negative control . As previously observed [31] , [34] , [44] , the kinetics of colonization by B . burgdorferi producing DbpA and DbpB varied with tissue: the bladder and joints were colonized by day 7 post-infection whereas the heart and ear were detectably colonized only at the 14 and 21-day time point , respectively ( Figs . 3 , 5 and Fig . S5; for comprehensive summary of bacterial loads at all times points , see Table S1 ) . ML23ΔdbpBA harboring vector alone was defective for colonization at all time points . Upon infection with ML23ΔdbpBA producing DbpAPBr , DbpAN40-D10/E9 , or DbpAVS461 , we found that at 21 days post-infection , each of the DbpA variants tested was capable of fully replacing the colonization function of the endogenous ( strain B31 ) DbpA and DbpB in the inoculation site , bladder , knee , and tibiotarsus ( Table S1 ) . On the other hand , in the ear or heart , production of these DbpA variants was associated with delayed colonization ( 28- vs . 14-day colonization in the ear; 21- vs . 14-day in the heart ) compared to these DbpA- and DbpB-proficient strains ( Figs . 3 , 5 and Fig . S5 ) , which is consistent with the findings reported previously [44] . Importantly , in several tissues , the different DbpA variants conferred significant differences in the efficiency or kinetics of colonization . At the inoculation site at three days post-infection , production of DbpAPBr , which displayed greater decorin- and dermatan sulfate-binding activity than DbpAVS461 or DbpAN40-D10/E9 , conferred approximately six- to nine-fold greater colonization ( P<0 . 05; Fig . 2 ) . The production of DbpAPBr was also associated with diminished late colonization of the inoculation site , because by 28 days post-infection , ML23ΔdbpBA producing DbpAPBr was present at this site at levels approximately 20- to 50-fold lower than ML23ΔdbpBA producing DbpAVS461 or DbpAN40-D10/E9 ( Fig . 3 ) . The production of the high affinity binding variant DbpAPBr also resulted in enhanced colonization of the heart at 21 and particularly 28 days post-infection compared to production of the other two DbpA variants ( Figs . 3 and 5 ) . At the later time point , ML23ΔdbpBA producing DbpAPBr was present at levels 15- to 50-fold higher than ML23ΔdbpBA producing DbpAVS461 or DbpAN40-D10/E9 ( P<0 . 05 ) , which were not present at levels significantly higher than the negative control strain ML23ΔdbpBA ( Fig . 3 ) . Interestingly , although as mentioned above , no dbpA allele-specific differences were observed in joint colonization at 21 days post-infection ( Table S1 ) , DbpAN40-D10/E9 , which binds to decorin and dermatan sulfate with the lowest affinity among the variants analyzed , promoted the greatest level of colonization of the tibiotarsus and knee at 28 days post-infection ( Fig . 3 ) . Whereas by this time ML23ΔdbpBA producing DbpAVS461 or DbpAPBr were no longer present in the knee or tibiotarsus at levels significantly greater than the DbpA- and DbpB-deficient ML23ΔdbpBA harboring vector alone , ML23ΔdbpBA producing DbpAN40-D10/E9 was present at levels 18 to 32-fold higher than strains producing either DbpAVS461 or DbpAPBr ( Fig . 3 ) ( P<0 . 04 ) . To test whether the distinct colonization levels in the inoculation site , heart , knee or tibiotarsus late in infection might be due to differences in the humoral immune response triggered by different DbpA variants , we quantitated serum IgG and IgM titers against each DbpA variant . We found no significant difference in anti-DbpA antibody production among animals infected with strains producing the different variants ( Fig . S4 ) . To determine if the ability to generate an adaptive immune response was required to elicit the differences in apparent tissue tropism among strains , we infected SCID mice with strains encoding each of the three alleles . Pilot experiments revealed that a dose of 103 bacteria , i . e . , ten-fold lower than that inoculated into wild type mice , was optimal for discerning colonization differences between strains ML23 and ML23ΔdbpBA ( data not shown; see Materials and Methods ) . We assessed tissue burden at 28 days post-infection and found that compared to ML23ΔdbpBA producing DbpAVS461 or DbpAN40-D10/E9 , an isogenic strain expressing DbpAPBr was present at approximately five- to ten-fold lower levels at the inoculation site ( P<0 . 02 ) and 15 to 87-fold higher levels in the heart ( P<0 . 02; Fig . 4 ) . ML23ΔdbpBA producing DbpAN40-D10/E9 colonized the knee and tibiotarsus six- to eight-fold more efficiently than ML23ΔdbpBA expressing DbpAPBr or DbpAVS461 ( P<0 . 04 ) . Thus , the strain-specific colonization pattern for the heart and joints were identical to those observed upon infection of immunocompetent mice . To determine whether the observed DbpA strain-specific differences in tissue tropism resulted in corresponding differences in disease severity , C3H/HeN mice infected with isogenic ML23ΔdbpBA derivatives producing DbpAVS461 , DbpAPBr or DbpAN40-D10/E9 were subjected to histopathological analysis . We evaluated carditis at the heart base at 28 days post-infection , at which time ML23ΔdbpBA producing DbpAPBr colonized the heart at levels six to nine-fold greater than the negative control strain ML23ΔdbpBA or strains producing DbpAVS461 or DbpAN40-D10/E9 ( Fig . 3 ) . When coded samples were scored blindly for carditis on a scale of 0 to 3 depending on the number and intensity of inflammatory foci at the heart base ( see Materials and Methods ) , the positive control strain ML23 induced robust ( grade 3 ) carditis ( Fig . 5B , left panel ) . Focal subendocardial mononuclear cell infiltrates were present upon infection by this strain ( thick arrow in Fig . 5A , top row ) , whereas strain ML23ΔdbpBA harboring vector alone or producing DbpAVS461 or DbpAN40-D10/E9 showed , at most , a very mild mononuclear cell infiltrate ( carditis score near grade 0; Fig . 5 , left panel ) , reflecting their relative levels of cardiac colonization at this time point ( Fig . 3 ) . Importantly , consistent with the persistent cardiac colonization by ML23ΔdbpBA producing DbpAPBr , the mice infected with this strain exhibited significant ( grade ∼2 ) carditis ( Fig . 5B , left panel ) . Focal interstitial subacute myocarditis ( thick arrow at Fig . 5A , top row ) and vasculitis ( thin arrow ) , involving mostly mononuclear cells was present . Histopathological analyses were also performed on the tibiotarsus joint at 28 days post-infection , a time point at which ML23ΔdbpBA producing DbpAN40-D10/E9 colonized the joints at levels 18- to 32-fold greater than isogenic strains producing DbpAVS461 or DbpAPBr or the negative control strain ML23ΔdbpBA ( Fig . 3 ) . When coded H&E-stained tibiotarsus joint samples were scored blindly for inflammatory infiltrates , severe ( grade 3 ) arthritis was triggered by the positive control strain ML23 ( Fig . 5B , right panel ) . Severe inflammation surrounding some tendons and of the synovial membrane was observed , with periostitis and some proliferation of new bone ( thick arrow at Fig . 5A , bottom row ) . In contrast , the negative control strain ML23ΔdbpBA carrying vector alone or producing DbpAPBr triggered no arthritis ( grade 0; Fig . 5A , bottom row and Fig . 5B , right panel ) . The strain producing DbpAVS461 appeared to induce mild ( grade ∼1; Fig . 5B , right ) arthritis evidenced by mild and focal inflammation ( thick arrow at Fig . 5A , bottom row ) . These findings are consistent with the low levels of joint colonization by those strains at this time point ( Fig . 3 ) . Importantly , reflecting the persistent joint colonization by ML23ΔdbpBA producing DbpAN40-D10/E9 , mice infected with this strain exhibited higher levels of arthritis ( grade ∼2; Fig . 5B right panel ) , with moderate mononuclear infiltrates commonly near connective tissue ( thick arrow at Fig . 5A , bottom row ) . We conclude that the higher levels of heart or joint colonization associated with the production of DbpAPBr or DbpAN40-D10/E9 , respectively , resulted in greater levels of pathology .
Although it has long been known that different genospecies or strains of Borrelia burgdorferi sensu lato cause infections with different clinical manifestations in humans and distinct pathogenicity and/or tissues tropism in animal infection models , the reasons for these differences have remained obscure [9]–[12] . An attractive hypothesis put forth has been is that variation in spirochetal factors that control spread to or survival in different tissues contribute to the disparate behavior during mammalian infection [9] , [12] , [18] , [21] . The ospC gene , which encodes a surface lipoprotein required for infection , is allelic variable , and a sampling of recombinant OspC variants from three invasive or noninvasive strains demonstrated a correlation between plasminogen binding and invasiveness in mice [18] . CRASP's ( complement regulator acquiring surface proteins ) variants , which promote serum resistance , differ in their ability to bind to the complement regulatory proteins factor H and factor H like protein ( FHL-1 ) [16] , [17] , [19] . Rigorous demonstration that allelic variation of genes encoding documented or putative virulence factors influences tissue tropism and/or disease manifestation requires experimental infection using isogenic strains , and has thus far been lacking . The dbpA gene , which encodes a Lyme disease spirochete adhesin required for full infectivity , is allelic variable , and DbpA variants differ in their ability to promote spirochetal attachment to decorin , dermatan sulfate , or mammalian cells [21] , [39] . DbpAVS461ΔC11 , a DbpA truncation that lacks 11 C-terminal amino acids was previously shown in semi-quantitative binding assays to be unable to bind dermatan sulfate or decorin [39] . We confirmed this finding by quantitative ELISA and SPR . The C-terminal 11 amino acids lacking in DbpAVS461ΔC11 are not generally well conserved among DbpA variants but do encompass the universally conserved residue K170 , which has been shown to be required for decorin/dermatan sulfate-binding [30] , [40] , [45] . To test whether the adhesive activity of DbpA is specifically required for colonization , mice were infected with a B . burgdorferi dbpBA deletion mutant that ectopically produced wild type DbpAVS461 or DbpAVS461ΔC11 . DbpAVS461ΔC11 was , in fact , also unable to facilitate colonization at the inoculation site , bladder , or ear , indicating that this binding activity of DbpA is likely required for tissue colonization . The requirement for DbpA adhesive activity for efficient mammalian colonization raised the possibility that the variability of ligand binding among DbpA variants found among Lyme disease spirochetes contributes to the observed strain-to-strain differences in tissue tropism and disease severity [21] , [29] , [39] . Thus , we quantitatively characterized the decorin- and dermatan sulfate-binding activities of three DbpA variants , i . e . DbpAPBr , DbpAVS461 and DbpAN40-D10/E9 , which together represent the three major Lyme disease spirochete genospecies , and generated a set of isogenic B . burgdorferi strains derived from a B . burgdorferi ΔdbpBA mutant that expressed each of these variants . These DbpA-producing strains exhibited the predicted differences in their ability to bind to decorin and dermatan sulfate , with DbpAPBr promoting the most efficient spirochetal binding to purified decorin and dermatan sulfate and DbpAN40-D10/E9 promoting the least . When mice were infected with these strains , the B . burgdorferi strain producing DbpAPBr promoted better early ( i . e . , three days post-infection ) colonization at the inoculation site . This result is consistent with reports that decorin is enriched in the skin [46] and that spirochetal overproduction of DbpA enhanced colonization of the inoculation site [47] . Importantly , the strain producing DbpAPBr infected the heart at levels one to two orders of magnitude greater than strains producing DbpAVS461 or DbpAN40-D10/E9 , and this more intense infection of the heart was associated with enhanced carditis . B . burgdorferi selectively colonizes decorin-rich heart microenvironments such as the tunica adventitia [35] , and upon infection , decorin-deficient mice harbor fewer B . burgdorferi in the heart than do littermate control mice [30] . We found that the relative tropism of the DbpAPBr-producing strain for skin and heart was also observed in SCID mice , indicating that the higher level of colonization of these sites by this strain is not accounted for by an adaptive immune response that might be generated more efficiently against one DbpA variant than another . Rather , the tissues that are more efficiently colonized by B . burgdorferi producing a variant of DbpA that binds tightly to decorin corresponds to what is currently understood about the relative enrichment of decorin in these tissues . Nevertheless , DbpA-mediated colonization is not a simple reflection of its ability to bind decorin because DbpAN40-D10/E9 , which displayed the weakest decorin and dermatan sulfate binding , promoted the most robust colonization of the joints late ( 28 days ) after inoculation . Upon scoring of coded histological samples , DbpAN40-D10/E9 was the only variant that promoted arthritis significantly more severe than the non-DbpA-producing control strain . Our in vitro assays indicate that compared to DbpAVS461 or DbpAPBr , DbpAN40-D10/E9 poorly recognizes human recombinant decorin and the ( commercially available porcine skin ) dermatan sulfate utilized in this study . However , it is possible that DbpAN40-D10/E9 binds to a host ligand present in the murine joint better than these other DbpA variants . Dermatan sulfate , like other GAGs , is heterogeneous with respect to epimerization and modification , raising the possibility that murine joint decorin may be well recognized by DbpAN40-D10/E9 . In addition , biglycan , which like the other class I proteoglycan decorin contains ten leucine-rich repeats and two dermatan sulfate GAGs , is present in the joint at higher levels than decorin and could be an additional ( well recognized ) ligand for DbpAN40-D10/E9 [48]–[50] . Finally , the tibiotarsus joint apparently presents B . burgdorferi with functionally distinct microenvironments , because B . burgdorferi colonizes both synovial and adjacent connective tissues in the joints of untreated SCID mice , but are cleared specifically from synovium by administration of anti-DbpA serum [51] . In our study , the tropism of DbpAN40-D10/E9 for joints was not a simple function of adaptive immunity because it was recapitulated in SCID mice , but it is possible that the different DbpA variants , by recognizing host ligands differently , promote distinct distributions of spirochetes among joint microenvironments . A technical challenge to experimental validation of this hypothesis is the relative paucity of spirochetes in the joints of infected animals . One interesting observation is that an allele of dbpA from a B . burgdorferi sensu stricto strain ( i . e . strain N40-D10/E9 ) promoted joint colonization and disease in the mouse , an apparent tropism that correlates with the common manifestation of Lyme arthritis upon infection by this genospecies of Lyme disease spirochete [10] . This is not to imply , however , that the production of a particular DbpA variant fully explains the tissue tropism of a given strain . Tissue tropism is undoubtedly multifactorial , so any approach that addresses the contribution of a single allelic variable gene , in this case dbpA , is inherently limited due to its concomitant inability to assess the role of other potential determinants . In addition , here we assessed strains that did not produce DbpB , which may have partially redundant function , and to what degree allelic variation of dbpA contributes to the etiology of distinct symptoms associated with different Lyme disease strains in otherwise wild-type strains will require further study . Nevertheless , the demonstration that dbpA influences colonization and disease by the Lyme disease spirochete in an allele-specific manner provides important support for the long-postulated model that allelic variation of a Borrelia surface protein influences tissue tropism .
All mouse experiments were performed in strict accordance with all provisions of the Animal Welfare Act , the Guide for the Care and Use of Laboratory Animals , and the PHS Policy on Humane Care and Use of Laboratory Animals . The protocol was approved by the Tufts University School of Medicine Institutional Animal Care and Use Committee ( IACUC ) , protocol docket number 2011–140 . All efforts were made to minimize animal suffering . The Borrelia and E . coli strains used in this study are described in Table S3 . Escherichia coli strains DH5α , BL21 and derivatives were grown in Luria-Bertani ( BD Bioscience , Franklin lakes , NJ ) broth or agar , supplemented with kanamycin ( 50 µg/ml ) or ampicillin ( 100 µg/ml ) where appropriate . All B . burgdorferi strains were grown in BSK-II completed medium supplemented with kanamycin ( 200 µg/ml ) or Gentamycin ( 50 µg/ml ) . To generate recombinant histidine-tagged DbpA proteins , the dbpA open reading frames lacking the putative signal sequences from B . burgdorferi strains B31 and N40-D10/E9 , B . garinii strain PBr , and B . afzelii strain VS461 were inserted into pET15b ( Novagen , Madison , WI ) as previously described [39] ( see Table S3 ) . In addition , dbpA open reading frames ( lacking the putative signal sequence ) from B . burgdorferi strain 297 ( encoding residues 30 to 187 ) , B356 ( encoding residues 33 to 194 ) , and an altered open reading frame encoding DbpAVS461ΔC11 ( residues 22 to 158 , lacking the 11 C-terminal amino acids , from B . afzelii strain VS461 ) , were amplified using the primers described in Table S3 . Amplified fragments were engineered to encode a BamHI site at the 5′ end and a stop codon followed by a SalI site at the 3′ end . PCR products were sequentially digested with BamHI and SalI and then inserted into the BamHI and SalI sites of pQE30 ( Qiagen , Valencia , CA ) . The resulting plasmids were transformed into E . coli strain M15 ( for dbpA297 , dbpAB356 , and dbpAVS461ΔC11 ) or BL21 ( for all other dbpA alleles ) and the plasmid inserts were sequenced ( Tufts core sequencing facility ) . The histidine-tagged DbpA variants were produced and purified by nickel affinity chromatography according to the manufacturer's instructions ( Qiagen , Valencia , CA ) . Antisera against DbpAN40-D10/E9 , DbpAPBr , or DbpAVS461 were generated by immunizing five-week-old BALB/C mice with each of the DbpA proteins as described previously [51] . Recombinant human decorin , a generous gift from David Mann ( MedImmune , Inc . ) , was purified from stably transfected Chinese hamster ovary cells ( ATCC CCL 61 ) as described previously [52] . CD analysis was performed on a Jasco 810 spectropolarimeter ( Jasco Analytical Instrument , Easton , MD ) under N2 . CD spectra were measured at RT ( 25°C ) in a 1 mm path length quartz cell . Spectra of DbpAVS461 ( 10 µM ) and DbpAVS461ΔC11 ( 10 µM ) were recorded in Tris buffer at 25°C , and three far-UV CD spectra were recorded from 190 to 250 nm for far-UV CD in 1 nm increments . The background spectrum of buffer without protein was subtracted from the protein spectra . CD spectra were initially analyzed by the software Spectra Manager Program . Analysis of spectra to extrapolate secondary structures was performed by Dichroweb ( http://dichroweb . cryst . bbk . ac . uk/html/home . shtml ) using the K2D and Selcon 3 analysis programs [53] . Quantitative ELISA for decorin and dermatan sulfate binding by DbpA proteins was performed similarly to that previously described [54] . One µg of decorin , dermatan sulfate , chondroitin 6 sulfate , or BSA was coated onto microtiter plate wells . One hundred microliters of increasing concentrations ( 0 . 03125 , 0 . 0625 , 0 . 125 , 0 . 25 , 0 . 5 , 1 , 2 µM ) of histidine-tagged RevA ( negative control ) or a DbpA variant , including DbpAB31 , DbpA297 , DbpAN40-D10/E9 , DbpAB356 , DbpAVS461 , DbpAPBr , or DbpAVS461ΔC11 , were then added to the wells . To detect the binding of histidine-tagged proteins , mouse anti-histidine tag ( Sigma-Aldrich , St . Louis , MO; 1∶200 ) and HRP-conjugated goat anti-mouse IgG ( Promega , Fitchburg , WI; 1∶1 , 000 ) were used as primary and secondary antibodies . The plates were washed three times with PBST ( 0 . 05% Tween20 in PBS buffer ) , and 100 µl of tetramethyl benzidine ( TMB ) solution ( Kirkegaard and Perry Laboratories , Gaithersburg , MD ) were added to each well and incubated for five minutes . The reaction was stopped by adding 100 µl of 0 . 5% hydro sulfuric acid to each well . Plates were read at 405 nm using a Synergy HT ELISA plate reader ( BioTek , Winooski , VT ) . To determine the dissociation constant ( KD ) , the data were fitted by the following equation using KaleidaGraph software ( Version 4 . 1 . 1 Abekbecj Software , Reading , PA ) . ( 1 ) Interactions of DbpA with decorin or dermatan sulfate were analyzed by a SPR technique using a Biacore 3000 ( GE Healthcare , Piscataway , NJ ) . Ten µg of biotinylated decorin or dermatan sulfate was conjugated to an SA chip ( GE Healthcare , Piscataway , NJ ) . A control flow cell was injected with PBS buffer without decorin or dermatan sulfate . For quantitative SPR experiments to determine decorin- or dermatan sulfate–binding , ten µl of increasing concentrations ( 0 , 15 . 625 , 31 . 25 , 62 . 5 , 125 , 250 , 500 nM ) of a DbpA variant , including DbpAB31 , DbpA297 , DbpAN40-D10/E9 , DbpAB356 , DbpAVS461 , DbpAPBr , or DbpAVS461ΔC11 , were injected into the control cell and flow cell immobilized with decorin or dermatan sulfate at 10 µL/min , 25°C . To obtain the kinetic parameters of the interaction , sensogram data were fitted by means of BIAevaluation software version 3 . 0 ( GE Healthcare , Piscataway , NJ ) , using the one step biomolecular association reaction model ( 1∶1 Langmuir model ) , resulting in optimum mathematical fit with the lowest Chi values . To generate the plasmids encoding dbpA alleles , genes dbpAN40-D10/E9 , dbpAVS461 , dbpAPBr , or dbpAVS461ΔC11 were first PCR amplified with the addition of a SalI site and a BamH1 site at the 5′ and 3′ ends , respectively , using the primers listed in Table S1 . Amplified DNA fragments were inserted into TA cloning vector pCR2 . 1-TOPO ( Invitrogen , Houston , TX; see Table S3 ) , to generate the plasmids pCR2 . 1- dbpAN40-D10/E9 , pCR2 . 1-dbpAVS461 , pCR2 . 1-dbpAPBr , and pCR2 . 1-dbpAVS461ΔC11 . The plasmids were then digested with SalI and BamHI to release the dbpA alleles , which were then inserted into the SalI and BamHI sites of pBBE22 ( see Table S3 ) . The promoter region of dbpBA from B . burgdorferi B31 , 289 bp upstream from the start codon of dbpB , was also PCR amplified , adding , SphI and SalI sites at the 5′ and 3′ ends , respectively , using primers pdbpBAfp and pdbpBArp ( Table S3 ) . Promoter fragments were then inserted into the SphI and SalI sites of pBBE22 to drive the expression of dbpAN40-D10/E9 , dbpAVS461 , dbpAPBr , and dbpAVS461ΔC11 . Electrocompetent B . burgdorferi ML23ΔdbpBA was transformed separately with 80 µg of each of the shuttle plasmids encoding dbpAN40-D10/E9 , dbpAVS461 , dbpAPBr , or dbpAVS461ΔC11 ( see Table S3 ) and cultured in BSK II medium at 33°C for 24 hours . Aliquots of the culture were mixed with 1 . 8% analytical grade agarose ( BioRad; Hercules , CA ) and plated on a solidified BSK II/agarose layer in sterilized 100×20 mm tissue culture dishes ( Corning Incorporated , Corning , NY ) . Plates were incubated at 33°C in 5% CO2 for two weeks . Kanamycin- and gentamycin-resistant colonies of dbpA-complemented B . burgdorferi were obtained and expanded at 33°C in liquid BSK II medium containing kanamycin and gentamycin , followed by genomic DNA preparation as previously described [55] . PCR was performed with primers ( Fig . S1 ) specific for kan ( encoding the kanamycin resistance gene ) , to verify its presence in the transformants . The plasmid profiles of the dbpBA deficient mutant complemented with dbpA alleles were examined as described previously [56] and found to be identical to those of this strain harboring the empty vector ( data not shown ) . To determine the production and the surface localization of DbpA variants and of OspC in B . burgdorferi , 1×108 B . burgdorferi cells were washed thrice with HBSC buffer containing DB ( 25 mM Hepes acid , 150 mM sodium chloride , 1 mM MnCl2 , 1 mM MgCl2 , 0 . 25 mM CaCl2 , 0 . 1% glucose , and 0 . 2% BSA , final concentration ) and then resuspended into 500 µL of the same buffer . A mixture of mouse antisera raised against DbpAB31 , DbpAN40-D10/E9 , DbpAVS461 , and DbpAPBr [39] and rabbit anti-OspC ( Rockland , Gilbertsville , PA ) was used as a primary antibody , and Alexa488-conjugated goat anti-mouse IgG ( Invitrogen; 1∶250× ) and Alexa 635-conjugated goat anti-rabbit IgG ( Invitrogen; 1∶250× ) were used as secondary antibodies . 300 µL of formalin ( 0 . 1% ) was then added for fixing . Surface production of DbpA and OspC was measured by flow cytometry using a Becton-Dickinson FACSCalibur ( BD Bioscience , Franklin Lakes , NJ ) . All flow cytometry experiments were performed within two days of collection of B . burgdorferi samples . Spirochetes in the suspension were distinguished on the basis of their distinct light scattering properties in a Becton Dickinson FACSCalibur flow cytometer equipped with a 15 mW , 488 nm air-cooled argon laser , a standard three-color filter arrangement , and CELLQuest Software ( BD Bioscience , Franklin Lakes , NJ ) . The mean fluorescence index ( MFI ) of each sample was obtained from FlowJo software ( Three star Inc , Ashland , OR ) representing the surface production of the indicated proteins . To compare the surface production of DbpA and OspC proteins in different strains , results in Fig . S3 are shown as relative production , the MFI normalized to that of B . burgdorferi strain ML23 . The results shown in Fig . S3 represent the mean of twelve independent determinations ± the standard deviation . Each standard deviation value was no more than 7 percent of its mean value . Binding of B . burgdorferi to purified decorin or dermatan sulfate was determined as previously described [39] . Briefly , spirochetes were radiolabeled with [35S] methionine , and 1×108 radiolabeled bacteria were added to break-apart microtiter plate wells previously incubated with 250 µg/mL decorin , dermatan sulfate or chondroitin 6 sulfate ( as a negative control ) . After 16 hours at 4°C , unbound bacteria were removed by washing with PBS containing 0 . 2% BSA . Plates were air-dried , and percent binding was determined by liquid scintillation counting . The percentage of bound bacteria was determined by radioactive counts in bound bacteria normalized to the counts in the inoculum . Four-week-old female C3H/HeN mice ( Charles River , Wilmington , MA ) were used for all experiments . Mice were infected by intradermal injection as previously described [31] with ∼104 B . burgdorferi ML23ΔdbpBA/vector , or derivatives expressing dbpAN40-D10/E9 , dbpAVS461 , dbpAPBr , or dbpAVS461ΔC11 . For the mice sacrificed at 3 days post-infection , the skin at the inoculation site was collected . For the mice sacrificed at 7 , 14 , 21 , or 28 days post-infection , skin at the inoculation site , the tibiotarsal joint , knee joint , bladder , heart , and ear were collected . For infections of mice defective in adaptive immunity , four-week-old C3H-SCID mice ( Jackson Lab , Bar Harbor , ME ) were infected as described above for C3H/HeN mice . In C3H-SCID mice , a dose of 103 resulted in a 30- to 236-fold difference in bacterial load of B . burgdorferi strain ML23 and ML23ΔdbpBA/vector , whereas a dose of 104 resulted in indistinguishable colonization by two strains . Hence to maximize the chances of revealing differences in colonization due to the production of the DbpA variants , the lower ( i . e . 103 ) dose was used in this study . All SCID mice were sacrificed on 28 days post-infection , and skin at the inoculation site , the tibiotarsal joint , knee joint , bladder , heart , and ear were collected . DNA was extracted from tissue using the DNeasy Blood & Tissue kit ( Qiagen ) . The quantity and quality of DNA for each tissue sample have been assessed by measuring the concentration of DNA and the ratio of the UV absorption at 280 to 260 . The amount of DNA used in this study was 100 ng for each sample , and the 280∶260 ratio was between 1 . 75 to 1 . 85 , indicating the lack of contaminating RNA or proteins . qPCR was then performed to quantitate bacterial load , using 100 ng of DNA per reaction . B . burgdorferi genomic equivalents were calculated using an CFX Connect Real-Time PCR detection system ( BioRad , Hercules , CA ) in conjunction with SYBR green PCR Mastermix ( BioRad ) , based on amplification of the B . burgdorferi recA gene using primers BBRecAfp and BBRecArp ( Table S2 ) , as described previously [57] . The number of recA copies was calculated by establishing a threshold cycle ( Ct ) standard curve of a known number of recA gene extracted from B . burgdorferi strain B31 , then comparing the Ct values of the experimental samples . To assure the low signals were not simply a function of the presence of PCR inhibitors in the DNA preparation , we subjected 5 samples from tibiotarsal joint , bladder , and heart of the mice infected by B . burgdorferi strain ML23/vector , ML23ΔdbpBA/vector ( i . e . the dbpBA mutant ) , or dbpBA mutant complemented with dbpAN40 , dbpAVS461 , dbpAPBr , or dbpAVS461ΔC11 to qPCR using mouse nidogen primers mNidfp and mNidrp ( Table S3 ) as an internal standard [58] . As predicted , we detected 107 copies of the nidogen gene from 100 ng of each DNA sample , ruling out the presence of PCR inhibitors in these samples . Nunc maxisorp flat-bottom 96-well plates were coated with 1 µg of recombinant DbpAB31 , DbpAN40-D10/E9 , DbpAPBr , or DbpAVS461 protein in 100 µl of coating buffer ( 0 . 05 M Na2CO3 , pH 9 . 0 ) overnight in 4°C . The next day , plates were washed three times with wash buffer ( 0 . 05% PBS Tween 20 ) and blocked for 1 hour in blocking buffer ( 0 . 05% PBS Tween 20 with 1% BSA ) . Plates were then washed three times , and incubated for 1 hour with serum ( diluted 1∶100 , 1∶300 and 1∶900 ) at room temperature . Then , after washing plates three times , a 1∶10 , 000 dilution of HRP-conjugated goat anti-mouse IgM or IgG antibodies ( Bethyl Lab , Montgomery , TX ) was added to each well for one hour at room temperature . Subsequently , plates were washed and 100 µl of SureBlue Reserve TMB 2-Component Microwell Peroxidase Substrate system ( Kirkegaard and Perry Laboratories ) were added to each well . Plates were then read at OD650 using a Synergy HT ELISA plate reader ( BioTek ) . For kinetic ELISA experiments , readings were taken every minute for 10 minutes . Vmax ( milli-optical density unit per minute ) based on the slope of the continuous readings were calculated using the Gen5 Software ( Version 2 . 00 . 18 , BioTek , Winooski , VT ) . Controls included three dilutions ( 1∶100 , 1∶300 and 1∶900 ) of purified IgG or IgM ( 125 µg/mL; Bethyl Lab ) coated on microtiter plates , and uninfected ( “naïve” ) serum run in parallel with sample sera . The product of Vmax × inverse serum dilution factor was largely independent of serum dilution factor . Arbitrary units of a given serum sample were chosen as the largest Vmax × inverse serum dilution factor product within the dilution range , and were expressed relative to the arbitrary units of control pooled sera , set to 100 ( Marty-Roix , R . and Maung , N . , unpublished data ) . Antibody units of sample sera were normalized by subtracting the antibody unit “background” of naïve mice , and expressed relative to the control wells coated with purified IgG and IgM . At least 10 tibiotarsus joints and 5 hearts were collected from each group of mice ( 5 animal/group ) infected with the different B . burgdorferei isolates . For histology , joints and hearts were fixed in 10% formalin and processed for Hematoxylin and Eosin staining . Sections were evaluated for signs of arthritis using histological parameters for B . burgdorferi-induced inflammation [51] , [59] , such as exudation of inflammatory cells into joints , altered thickness of tendons or ligament sheaths , and hypertrophy of the synovium . Signs of carditis [51] , [60] were evaluated based on cardiac inflammatory infiltrate , including transmural infiltration of neutrophils in the blood vessels and infiltration by macrophages into the surrounding connective tissue . Inflammation was scored as 0 ( no inflammation ) , 1 ( mild inflammation with less than two small foci of infiltration ) , 2 ( moderate inflammation with two or more foci of infiltration ) , or 3 ( severe inflammation with focal and diffuse infiltration covering a large area ) . Significant differences between samples were determined using the one-way ANOVA test following logarithmic transformation of the data . P-values were determined for each sample . | Lyme disease , the most common vector-borne disease in the United States , is caused by a bacterium , Borrelia burgdorferi . This bacterium infects the skin at the site of the tick bite and then can spread to other tissues , such as the heart , joints or nervous system , causing carditis , arthritis or neurologic disease . To colonize human tissues , the pathogen produces surface proteins that promote bacterial attachment to these sites . For example , DbpA binds to decorin , a component of human tissue . Different Lyme disease strains differ in the particular tissues they colonize and the disease they cause , but we do not understand why . Different strains also make distinct versions of DbpA that bind decorin differently , so variation of DbpA might contribute to strain-to-strain variation in clinical manifestations . To test this , we infected mice with Lyme disease strains that were identical except for the particular DbpA variant they produced . We found that the strains colonized different tissues and caused different diseases , such as arthritis or carditis . These results provide the first solid evidence that variation of an outer surface protein , in this case DbpA , influences what tissues are most affected during Lyme disease . | [
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... | 2014 | Strain-Specific Variation of the Decorin-Binding Adhesin DbpA Influences the Tissue Tropism of the Lyme Disease Spirochete |
Defining the complex dynamics of Zika virus ( ZIKV ) infection in pregnancy and during transmission between vertebrate hosts and mosquito vectors is critical for a thorough understanding of viral transmission , pathogenesis , immune evasion , and potential reservoir establishment . Within-host viral diversity in ZIKV infection is low , which makes it difficult to evaluate infection dynamics . To overcome this biological hurdle , we constructed a molecularly barcoded ZIKV . This virus stock consists of a “synthetic swarm” whose members are genetically identical except for a run of eight consecutive degenerate codons , which creates approximately 64 , 000 theoretical nucleotide combinations that all encode the same amino acids . Deep sequencing this region of the ZIKV genome enables counting of individual barcodes to quantify the number and relative proportions of viral lineages present within a host . Here we used these molecularly barcoded ZIKV variants to study the dynamics of ZIKV infection in pregnant and non-pregnant macaques as well as during mosquito infection/transmission . The barcoded virus had no discernible fitness defects in vivo , and the proportions of individual barcoded virus templates remained stable throughout the duration of acute plasma viremia . ZIKV RNA also was detected in maternal plasma from a pregnant animal infected with barcoded virus for 67 days . The complexity of the virus population declined precipitously 8 days following infection of the dam , consistent with the timing of typical resolution of ZIKV in non-pregnant macaques and remained low for the subsequent duration of viremia . Our approach showed that synthetic swarm viruses can be used to probe the composition of ZIKV populations over time in vivo to understand vertical transmission , persistent reservoirs , bottlenecks , and evolutionary dynamics .
Zika virus ( ZIKV; Flaviviridae , Flavivirus ) infection during pregnancy can cause congenital Zika syndrome ( CZS ) —a collection of neurological , visual , auditory , and developmental birth defects—in at least 5% of babies [1] . The frequency of vertical transmission is not known , although data suggest that it may be very common , especially if infection occurs during the first trimester [2] . For both pregnant and nonpregnant women , it was previously thought that ZIKV caused an acute self-limiting infection that was resolved in a matter of days . It is now clear that ZIKV can persist for months in other body tissues after it is no longer detectable in blood and in the absence of clinical symptoms [2–7] . During pregnancy , unusually prolonged maternal viremia has been noted , with viral RNA detected in maternal blood up to 107 days after symptom onset [8–11] . The source of virus responsible for prolonged viremia is not known , though it has been speculated that this residual plasma viral load could represent virus genome release from maternal tissues , the placenta , and/or the fetus . Recently , we established Indian-origin rhesus macaques ( Macaca mulatta ) as a relevant animal model to understand ZIKV infection during pregnancy , demonstrating that ZIKV can be detected in plasma , CSF , urine , and saliva . In nonpregnant animals viremia was essentially resolved by 10 days post infection [12 , 13] . In contrast , in pregnant monkeys infected in either the first or third trimester of pregnancy , viremia was prolonged , and was associated with decreased head growth velocity and consistent vertical transmission [2] . Strikingly , significant ocular pathology was noted in fetuses of dams infected with French Polynesian ZIKV during the first trimester [2] . We also showed that viral loads were prolonged in pregnant macaques despite robust maternal antibodies [2] . We therefore aimed to better understand the in vivo replication and evolutionary dynamics of ZIKV infection in this relevant animal model . To do this , we developed a novel “synthetic swarm” virus based on a pathogenic molecular ZIKV clone that allows for tracking and monitoring of individual viral lineages . The synthetic swarm consists of viruses that are engineered to be genetically identical except for a run of 8 consecutive degenerate nucleotides present in up to ~64 , 000 theoretical combinations that all encode the same amino acid sequence . This novel barcoded virus is replication competent in vitro and in vivo , and the number and relative proportion of each barcode can be characterized by deep sequencing to determine if the population composition changes among or within hosts . Here and in a companion manuscript by Weger-Lucarelli et al . , we demonstrate that this system will provide a useful tool to study the complexity of ZIKV populations within and among hosts; for example , this system can assess bottlenecks following various types of transmission and determine whether non-sterilizing prophylaxis and therapeutics impact the composition of the virus population . Moreover , data from molecularly barcoded viruses will help inform research of ZIKV infection during pregnancy by providing a better understanding of the kinetics of tissue reservoir establishment , maintenance , and reseeding .
Molecular barcoding has been a useful tool to study viruses including simian immunodeficiency virus , influenza virus , poliovirus , Venezuelan equine encephalitis virus , and West Nile virus , establishing conceptual precedent for our approach [14–20] . To generate barcoded ZIKV , we introduced a run of eight consecutive degenerate codons into a region of NS2A ( amino acids 144–151 ) that allows for every possible synonymous mutation to occur in the ZIKV infectious molecular clone ( ZIKV-IC ) derived from the Puerto Rican isolate ZIKV-PRVABC59 [21] . Following bacteria-free cloning and rolling circle amplification ( RCA ) , linearized and purified RCA reaction products were used for virus production via transfection of Vero cells . All produced virus was collected , pooled , and aliquoted into single-use aliquots , such that single aliquots contain a representative sampling of all genetic variants generated; this barcoded synthetic swarm virus was termed ZIKV-BC-1 . 0 . We used a multiplex-PCR approach to deep sequence the entire coding genome of the ZIKV-BC-1 . 0 stock , as well as the ZIKV-IC from which ZIKV-BC-1 . 0 was derived . For each stock , 1 x 106 viral RNA templates were used in each cDNA synthesis reaction ( Table 1 ) , and both stocks were sequenced in duplicate . We identified two nucleotide positions outside of the barcode region that encoded fixed differences between ZIKV-IC and ZIKV-BC-1 . 0 , when compared to the KU501215 reference that we used for mapping . The variant at site 1964 encodes a nonsynonymous change ( V to L ) in Envelope , and the variant at site 8488 encodes a synonymous substitution in NS5 . The variant at site 1964 was also present in our ZIKV-PRVABC59 stock ( see [22] ) , and Genbank contains records for two sequences that match this sequence ( accession numbers KX087101 and KX601168 ) and two that do not ( KU501215 and KX377337 ) . In addition , a single nucleotide position in NS5 ( site 9581 ) contained an 80/20 ratio of C-to-T nucleotide substitutions in ZIKV-BC-1 . 0 but was fixed as a C in ZIKV-IC . The C-to-T change is a synonymous mutation in a leucine codon . There were no other high-frequency variants that differentiate the two stocks outside of the barcode region in the remainder of the genome encoding the polyprotein open reading frame . We then characterized the diversity of barcode sequences present in the ZIKV-BC-1 . 0 stock prior to in vitro and in vivo studies . We used three separate approaches to define which barcodes to consider ‘authentic . ’ In the first approach ( Approach ‘A’ ) , we identified all the distinct non-WT barcodes that were detected in the ZIKV-IC and the ZIKV-BC-1 . 0 stocks in the region of NS2A encompassing the barcode . We then calculated the arithmetic mean ( 0 . 0018% ) plus 3 times the standard deviation ( 0 . 016% ) of the frequency of all the non-WT barcodes present in the two replicates of the ZIKV-IC stock , even if the frequency of a specific barcode in the ZIKV-IC stock was 0% . This threshold frequency was 0 . 049% . For the second approach ( Approach ‘B’ ) , we calculated the arithmetic mean ( 0 . 012% ) plus 3 times the standard deviation ( 0 . 040% ) of the frequency of all the non-WT barcodes present only in the ZIKV-IC stock . This threshold frequency was 0 . 13% . For the final method ( Approach ‘C’ ) , we identified the highest frequency of the most common non-WT barcode present in either replicate of the ZIKV-IC stock . This threshold frequency was 0 . 57% . As this third calculation was the most conservative , we used 0 . 57% to be the minimum threshold to consider a barcode in ZIKV-BC-1 . 0 as ‘authentic . ’ Using this value , we included 20 sequences in our list of authentic barcodes , and these were followed throughout the study . These barcodes were given independent labels ( e . g . Zika_BC01 , Zika_BC02 , etc . ) to simplify reporting . The wild type barcode sequence was also tracked , and it is labeled Zika_WT . All remaining sequences that were detected were labeled as ‘Other’ ( see S1–S3 Tables for barcodes identified using all three approaches ) . To ascertain whether input RNA template numbers influenced barcode composition , we sequenced a dilution series of viral RNA templates in triplicate ( Fig 1 and S4 and S5 Tables ) . When we used 10 , 000 or 2000 input vRNA templates , we detected all 20 barcodes . For 500 , 250 , 100 , and 50 input templates , the average number of enumerated barcodes was 17 . 3 ± 0 . 9 , 14 . 3 ± 1 . 2 , 12 . 7 ± 0 . 5 , and 6 . 7 ± 0 . 5 , respectively . These observations suggest that some barcodes are lost from the population when the number of input templates is reduced . We also examined diversity and similarity across sequencing replicates in this titration experiment using all the detected sequences , including the sequences labeled as ‘Other . ’ Not surprisingly , Simpson’s diversity increased when a greater number of input templates were used , plateauing at 500 input copies ( S1 Fig ) . When comparing similarity across replicates , the samples with 2 , 000 and 10 , 000 inputs had the highest Morisita-Horn similarity index ( S2 Fig ) . Unfortunately , it was not possible to obtain a large number of input templates at all timepoints from ZIKV-infected pregnant animals; therefore , the absence of a barcode in sequencing reads from a particular experiment could mean that either the barcode was not present at that timepoint or that it was present in the biological sample but not at a high enough concentration to be detected when sequencing from a small number of templates ( S3 Fig ) . Prior to use in nonhuman primates , viral infectivity and replication of ZIKV-BC-1 . 0 was assessed in vitro using Vero , LLC-MK2 , C6/36 , and Aag2 cells . Viral growth curves were similar between ZIKV-BC-1 . 0 , infectious clone-derived virus ( ZIKV-IC ) , and wild-type ZIKV-PRVABC59 ( ZIKV-PR ) ( S4 Fig and Weger-Lucarelli et al . , manuscript submitted ) . These results suggested that insertion of degenerate nucleotides in the barcode viral genome did not have a significant deleterious effect on either infectivity or replicative capacity in vitro , but we cannot exclude the possibility that different barcodes may have different effects with respect to each other . To confirm that ZIKV-BC-1 . 0 did not have any replication defects in vivo , we assessed its replication capacity in rhesus macaques . Three rhesus macaques were inoculated subcutaneously with 1 x 104 PFU of ZIKV-BC-1 . 0 . All three animals were productively infected with ZIKV-BC-1 . 0 , with detectable plasma viral loads one day post inoculation ( dpi ) ( Fig 2 ) . Plasma viral loads in all three animals peaked between two and four dpi and ranged from 2 . 34 x 103 to 9 . 77 x 104 vRNA copies/ml . Indeed , ZIKV-BC-1 . 0 displayed viral replication kinetics comparable to ZIKV-IC and ZIKV-PR ( Fig 2 ) , and replication kinetics were comparable to previous studies with other strains of ZIKV in nonpregnant rhesus macaques [12 , 13 , 23] . To compare overall replication kinetics , the data were log10-transformed and area under the curve ( AUC ) was calculated . One-way ANOVA then was conducted to compare AUC between groups and the data were not significantly different [F ( 2 , 6 ) = 0 . 887 , p = 0 . 460] ( S6 Table ) . We also infected a single pregnant macaque ( 776301 ) by subcutaneous inoculation of 1 x 104 PFU of ZIKV-BC-1 . 0 . This animal had been exposed to dengue virus serotype 3 ( DENV-3; strain Sleman/78 ) approximately one year prior to inoculation with ZIKV-BC-1 . 0 . To evaluate cross-reactive neutralizing antibody ( nAb ) responses elicited by prior exposure to DENV-3 in this animal , serum was obtained prior to inoculation with ZIKV-BC-1 . 0 . Neutralization curves with both DENV-3 and ZIKV revealed that DENV-3 immune sera did not cross-react with ZIKV , whereas DENV-3 was potently neutralized ( Fig 3A ) . The animal then was infected with ZIKV-BC-1 . 0 at 35 days of gestation ( mid-first trimester; rhesus term is 165 ± 10 days ) and had detectable plasma viral loads for 67 dpi ( Fig 3B ) ; consistent with replication kinetics of wildtype ZIKV in both pregnant macaques [2] and humans [8 , 9 , 24] . The animal also had four days of detectable vRNA in urine but no detectable vRNA ( Fig 3B ) in the amniotic fluid on 22 , 36 , 50 , or 120 dpi ( 57 , 71 , 85 , 155 days gestation , respectively ) . By 29 dpi neutralization curves of both viruses revealed a similar profile , indicating the production of a robust maternal nAb response to ZIKV ( Fig 3A ) coincident with prolonged plasma viral loads , similar to what has been shown previously in other ZIKV-infected pregnant macaques [2] . DENV-3 neutralization curves at 0 and 29 dpi were indistinguishable ( Fig 3A ) . The pregnancy progressed without adverse outcomes , and at 155 days of gestation , the fetus was surgically delivered , euthanized , and tissues collected . The fetus had no evidence of microcephaly or other abnormalities upon gross examination . Approximately 60 fetal and maternal tissues ( see S7 Table for a complete list ) were collected for histopathology and vRNA by QRT-PCR . No ZIKV RNA was detected in any samples collected from the fetus . This was surprising , as from seven neonatal macaques we have examined to date ( zika . labkey . com ) , this was the only animal found not to have detectable ZIKV RNA in tissues . Still , ZIKV RNA was detected at the maternal-fetal interface in a section of placental disc ( S7 Table ) . Fetal histology also revealed neutrophilic infiltration of the spleen ( Fig 4A ) , minimal to mild suppurative lymphadenitis of the inguinal lymph node ( Fig 4B ) , minimal multifocal lymphocytic deciduitis , mild multifocal placental infarction with suppurative villositis ( Fig 4C and 4D ) , but normal CNS anatomy , similar to changes noted in previous in utero ZIKV infections [2 , 25 , 26] . These data provide indirect evidence that vertical transmission did occur and demonstrate that ZIKV-BC-1 . 0 is fully functional in vivo with replication kinetics indistinguishable from other ZIKV strains . Thus , inclusion of the barcode did not detectably impair infectivity or replication in adult macaques . We deep sequenced the viruses replicating in the nonpregnant animals who were infected with ZIKV-BC-1 . 0 and ZIKV-IC ( Fig 5A and 5B , Tables 2 and S8 ) . In each group of three animals , we sequenced viruses at two time points from two animals , and then one time point from a third animal . In animals infected with ZIKV-IC , we found that >95% of sequences in the virus stock and all three animals were wild type across the 24 nucleotides that corresponded to where the barcode was located in ZIKV-BC-1 . 0 . We counted the number of authentic barcodes detected in the stock and the plasma of the nonpregnant animals infected with ZIKV-BC-1 . 0 . We detected a range of 8 to 20 authentic barcodes in these samples ( Fig 5C ) . We then compared the frequency distribution of the individual barcodes in the plasma of these three animals relative to that in the stock to assess whether there was any evidence for a bottleneck that influenced overall barcode distribution . This was accomplished using two independent statistical approaches . The first compared the frequency distributions by a stochastic equality test , which compares several random pairs of individual values taken from the two samples to test whether there is a significant tendency to get higher values in one over the other [27] . In all three animals , the frequency of each barcode at day two ( 514982 ) or at day three ( 715132 and 688387 ) was not significantly different from the frequency of each barcode in the stock: p-value based on 1000 bootstrap replications = 0 . 478 , 0 . 602 , and 0 . 114 , respectively . Likewise , the frequency of each barcode at day two ( 514982 ) or at day three ( 715132 ) was not significantly different from the frequency of each barcode in the stock when compared using the Kolmogorv-Smirnov test: p-value = 0 . 358 and 0 . 841 . However , this approach did detect a significant difference between the frequency of each barcode in 688387 at day three: p-value = 0 . 0021 , but we believe this to be an artifact of the animal’s viral load at this time point , because the frequency of each barcode at day five did not differ significantly from the frequency of each barcode in the stock , p-value = 0 . 358 . These data in conjunction with the results of the stochastic equality test therefore suggest that there was no evidence for changes in barcode frequency compared to input . We also examined the sequences outside the barcode region to determine if there were additional nucleotide differences present in the virus population as it replicated in animals . There were small fluctuations in some viral SNPs , but we detected no dramatic shifts in nucleotide frequencies among viruses replicating in vivo , except at site 9581 , which is synonymous . In the ZIKV-BC-1 . 0 stock , there was a mixture of T and C nucleotides ( 22% and 78% of sequences , respectively ) at this site . This position remained a mixture in the animals , but the ratios fluctuated . It dipped to a ratio of 10/90 in animal 688387 at day 5 to as high as 30/70 in animal 715132 at day 5 . Overall , there were no new mutations that were detected at greater than 10% frequency in both replicates in the virus populations during the first 5 days after infection in nonpregnant animals . Unfortunately , this site was too far from the barcode ( ~5000bp ) for us to obtain linkage on the same set of paired sequences , making it impossible to know whether this particular nucleotide change was carried on specific barcodes . We also deep sequenced the barcode in virus populations replicating in the one pregnant animal ( 776301 ) infected with ZIKV-BC-1 . 0 . Recognizing that the later time points from this animal had persistent , but low plasma viral loads , we modified our sequencing approach to prepare one tube of cDNA , and then split it into two independent PCR reactions that amplified small fragments ( 131bp and 178bp ) spanning the region containing the barcode ( Fig 6A , Tables 3 and S9 ) . We quantified the number of authentic barcodes we detected using the same parameters described in the previous section ( Fig 6B ) . At days 3 , 5 , and 7 , we detected all 20 barcodes . For the remainder of the infection , we detected 8 . 1 ± 2 . 3 barcodes . Likewise , barcode diversity , as measured by Simpson’s diversity index , also declined beginning at day 8 and remained low throughout the duration of infection ( Fig 6C ) . Interestingly , some barcodes , such as Zika_BC02 , were not detected at later time points , even though it had been present at ~15% during early infection . Other barcodes , such as Zika_BC07 , 08 , and 09 , became more common at later time points , even though they were only present at ~2–5% during early infection . Unfortunately , with such low virus input templates at the late time points , there were differences between replicates indicative of sampling uncertainty . With the exception of two samples ( day57_A and day60_B ) , however , greater than 85% of the sequences matched one of the 20 authentic barcodes . To begin to understand potential transmission bottlenecks within the vector and the impact they might have on ZIKV population diversity , Aedes aegypti vector competence for ZIKV-BC-1 . 0 was evaluated at days 7 , 13 , and 25 days post feeding ( PF ) from mosquitoes that were exposed to the pregnant macaque at 4 dpi . A single Ae . aegypti ( out of 90 tested ) was transmission-competent at day 25 PF ( Table 4 ) as measured by plaque assay . Infection efficiency indicates the proportion of mosquitoes with virus-positive bodies among the tested ones . Dissemination efficiency indicates the proportion of mosquitoes with virus-positive legs , and transmission efficiency indicates the proportion of mosquitoes with infectious saliva among the tested ones . All other mosquitoes screened using this methodology were ZIKV-negative . We also found low mosquito infection rates in a previous study exposing mosquitoes to ZIKV-infected rhesus macaques [22] . We deep sequenced virus ( viral template numbers added to cDNA synthesis reactions are listed in S10 Table ) from all three anatomic compartments from this mosquito ( body , leg , and saliva ) , and we only detected the presence of a single barcode: Zika_BC02 . The viral loads in the body , leg , and saliva were 2 . 57 x 108 , 4 . 73 x 107 , and 4 . 29 x 104 vRNA copies/ml , respectively . Zika_BC02 was present in the pregnant animal’s virus population at ~16% between days 3 and 5 after infection , representing the second most common barcode in the population ( Fig 7 , Tables 5 and S10 ) .
Mosquito-borne viruses like ZIKV typically exist in hosts as diverse mutant swarms . Defining the way in which stochastic forces within hosts shape these swarms is critical to understanding the evolutionary and adaptive potential of these pathogens and may reveal key insight into transmission , pathogenesis , immune evasion , and reservoir establishment . To date , no attempts have been made to enumerate and characterize individual viral lineages during ZIKV infection . Here , we characterized the dynamics of ZIKV infection in rhesus macaques . Specifically , using a synthetic swarm of molecularly barcoded ZIKV , we tracked the composition of the virus population over time in both pregnant and nonpregnant animals . Our results demonstrated that viral diversity fluctuated in both a spatial and temporal manner as host barriers or selective pressures were encountered and this likely contributed to narrowing of the barcode composition in macaques . For example , the proportions of individual barcoded virus templates remained stable during acute infection , but in the pregnant animal infected with ZIKV-BC-1 . 0 the complexity of the virus population declined precipitously 8 days following infection of the dam . This was coincident with the timing of typical resolution of ZIKV in non-pregnant macaques ( Figs 2 and 3 ) , and after this point the complexity of the virus population remained low for the subsequent duration of viremia ( Fig 6C ) . We speculate that the narrowing of the barcode composition in the pregnant animal was the result of establishment of an anatomic reservoir of ZIKV that is not accessible to maternal neutralizing antibodies , which is shed into maternal plasma at low , but detectable , levels . It also is possible that declining viral barcode diversity was an artifact of a declining viral population size and the consequent effects on sampling , without reservoir establishment . Unfortunately , the absence of ZIKV RNA in the fetus at term prevented us from comparing the barcode composition in the fetus to the barcodes in maternal plasma , so this experiment could not resolve questions related to the potential that the feto-placental unit acts as a tissue reservoir of ZIKV . There are several factors that could explain the apparent lack of ZIKV RNA in the fetus at term . One possibility is that ZIKV-BC-1 . 0 was impaired in its ability to traffic to the feto-placental unit due to introduction of the barcode sequence . However , we believe this scenario to be unlikely because the presence of ZIKV-induced pathology in both the fetus and placenta provide indirect evidence for vertical transmission ( Fig 4 ) . In addition , the inability to detect ZIKV RNA in affected tissues could be due to the focal nature of infection , assay sensitivity , and/or viral clearance by the time of necropsy . Indeed , resolution of maternal viral loads occurred 91 days prior to necropsy , and Hirsch et al . recently demonstrated that ZIKV infection of the placenta was highly focal and could only be determined by comprehensive biopsy of all placental perfusion domains [26] . Furthermore , although our previous studies suggest high rates of vertical transmission [2] , it is unlikely that vertical transmission occurs 100% of the time in humans or macaques . Finally , this animal had pre-existing DENV-3 immunity and it remains unclear what role this may play in subsequent ZIKV infection during pregnancy . Therefore , matching ZIKV barcodes in neonatal tissues with barcodes found in the mother will be important for better understanding vertical transmission . While the ZIKV-BC-1 . 0 reported here has limited complexity , we have recently developed a new synthetic swarm , ZIKV-BC-2 . 0 , which uses an optimized transfection strategy and has orders of magnitude more putative authentic barcodes . This new virus will be used in future studies in conjunction with deep sequencing techniques that enumerate individual templates with unique molecular identifiers [28] . We therefore expect that future studies of pregnant animals infected with barcoded ZIKV will help distinguish between these possibilities . In addition to better understanding vertical transmission , synthetic swarm viruses will be useful tools for future studies aimed at understanding persistent reservoirs , bottlenecks , and overall evolutionary dynamics . For example , by using synthetic swarm viruses it should be possible to estimate the effective size of ZIKV populations ( Ne ) which determines whether selection or genetic drift is the predominant force shaping their genetic structure and evolution [29 , 30] . Likewise , it should be possible to estimate the number of founder viruses that are required to initiate infection of the fetus during vertical transmission and/or the number of founder viruses required to initiate infection during mosquito-borne versus sexual transmission . Both the number of founder viruses and Ne have not been estimated for any step of the ZIKV infection and/or transmission cycle , but we postulate that a single or limited number of infectious particles likely contribute to the infection of the fetus during vertical transmission . Strong bottlenecks have been observed previously during vertical transmission in plant virus systems [30 , 31] and during mother-to-offspring transmission of HIV-1 [32 , 33] and bovine viral diarrhea virus [34] . In these studies , the vast majority of offspring harbored a single or few viral variants , which suggested a stringent population bottleneck associated with vertical transmission . Therefore , knowledge of Ne is of major interest for a better understanding of how virus population structure changes and/or regenerates as it encounters host barriers or selective pressures within and between hosts . Furthermore , barcoded ZIKV will be useful in studies that combine deep sequencing with experimental evolution to observe within host dynamics of ZIKV variants . Barcoded ZIKV is particularly appropriate for studying the effects of evolutionary forces , such as selection and genetic drift , on the emergence of new ZIKV variants that result from host adaptation or that may emerge in the face of new selective pressures: for example , biocontrol strategies , antiviral therapies , immune escape , vaccines , etc . The effects of these evolutionary forces on virus evolution historically have been challenging to address without the inclusion of neutral markers to estimate selection coefficients and Ne . Although we developed this system to better understand the dynamics of ZIKV infection in the vertebrate host , this approach can be applied to address other questions about ZIKV transmission . For example , ZIKV-BC-1 . 0 can be used to quantify the bottleneck forces during mosquito infection and transmission . As a result , we also attempted to characterize barcodes present in mosquitoes that fed on the ZIKV-BC-1 . 0-infected pregnant animal . Consistent with our previous experiments [22] , only a single Ae . aegypti became infected with ZIKV-BC-1 . 0 after feeding on ZIKV-BC-1 . 0-viremic macaques . This was likely the result of the low amount of infectious virus in macaque blood [35] . We only detected a single barcode during infection of mosquitoes . This is not entirely surprising because mosquitoes ingest small amounts of blood from infected hosts , which limits the size of the viral population founding infection in the vector . For example , it has been previously estimated that as few as 5–42 founder viruses initiate DENV infection of the mosquito midgut [36] . Also , during replication in mosquitoes , flaviviruses undergo population bottlenecks as they traverse physical barriers like the midgut and salivary glands [36 , 37] . We therefore expected barcode diversity to be low in infected mosquitoes and these data are perhaps indicative of a stringent midgut bottleneck in this individual that limited the variant pool in other anatomic compartments , but this requires further experimental confirmation . Consistent with what we show here , previous work has demonstrated considerable haplotype turnover for West Nile virus in Culex pipiens but not in Ae . aegypti , i . e . , haplotypes remained relatively stable as the virus trafficked from the midgut to the saliva [37] . Likewise , Weger-Lucarelli et al . , manuscript submitted most often detected only a single barcode in different Ae . aegypti populations that were exposed to ZIKV-BC-1 . 0 using an artificial membrane feeding system . In sum , our approach showed that synthetic swarm viruses can be used to probe the composition of viral populations over time in vivo to understand vertical transmission , persistent reservoirs , bottlenecks , and evolutionary dynamics .
This study was a proof of concept study designed to examine whether molecularly barcoded ZIKV could be used to elucidate the source of prolonged maternal viremia during pregnancy ( Fig 3 ) . Datasets used in this manuscript are publicly available at zika . labkey . com . This study was approved by the University of Wisconsin-Madison Institutional Animal Care and Use Committee ( Animal Care and Use Protocol Number G005401 ) . Five male and five female Indian-origin rhesus macaques utilized in this study were cared for by the staff at the Wisconsin National Primate Research Center ( WNPRC ) in accordance with the regulations , guidelines , and recommendations outlined in the Animal Welfare Act , the Guide for the Care and Use of Laboratory Animals , and the Weatherall report . In addition , all macaques utilized in the study were free of Macacine herpesvirus 1 , Simian Retrovirus Type D , Simian T-lymphotropic virus Type 1 , and Simian Immunodeficiency Virus . For all procedures , animals were anesthetized with an intramuscular dose of ketamine ( 10ml/kg ) . Blood samples were obtained using a vacutainer or needle and syringe from the femoral or saphenous vein . The pregnant animal ( 776301 ) had a previous history of experimental DENV-3 exposure , approximately one year prior to ZIKV infection . African Green Monkey kidney cells ( Vero; ATCC #CCL-81 ) were maintained in Dulbecco’s modified Eagle medium ( DMEM ) supplemented with 10% fetal bovine serum ( FBS; Hyclone , Logan , UT ) , 2 mM L-glutamine , 1 . 5 g/L sodium bicarbonate , 100 U/ml penicillin , 100 µg/ml of streptomycin , and incubated at 37°C in 5% CO2 . Aedes albopictus mosquito cells were ( C6/36; ATCC #CRL-1660 ) were maintained in DMEM supplemented with 10% fetal bovine serum ( FBS; Hyclone , Logan , UT ) , 2 mM L-glutamine , 1 . 5 g/L sodium bicarbonate , 100 U/ml penicillin , 100 µg/ml of streptomycin , and incubated at 28°C in 5% CO2 . ZIKV strain PRVABC59 ( ZIKV-PR; GenBank:KU501215 ) , originally isolated from a traveler to Puerto Rico with three rounds of amplification on Vero cells , was obtained from Brandy Russell ( CDC , Ft . Collins , CO ) . Virus stocks were prepared by inoculation onto a confluent monolayer of C6/36 mosquito cells with two rounds of amplification . A single harvest with a titer of 1 . 58 x 107 plaque forming units ( PFU ) per ml ( equivalent to 2 . 01 x 1010 vRNA copies per ml ) of Zika virus/H . sapiens-tc/PUR/2015/PRVABC59-v3c2 were used for challenges utilizing wild type virus . This virus also served as the backbone upon which the genetically-barcoded virus was generated . Genetically-barcoded ZIKV was constructed using the ZIKV reverse genetic platform developed by Weger-Lucarelli et al . [21] . The region for the barcode insertion was selected by searching for consecutive codons in which inserting a degenerate nucleotide in the third position would result in a synonymous change . The genetically-barcoded ZIKV clone then was constructed using a novel method called bacteria-free cloning ( BFC ) . First , the genome was amplified as two overlapping pieces from the two-part plasmid system of the reverse genetic platform ( see [21] ) . The CMV promoter was amplified from pcDNA3 . 1 ( Invitrogen ) . The barcode region was then introduced in the form of an overlapping PCR-amplified oligo ( IDT , Iowa , USA ) . All PCR amplifications were performed with Q5 DNA polymerase ( New England Biolabs , Ipswich , MA , USA ) . Amplified pieces were then gel purified ( Macherey-Nagel ) . The purified overlapping pieces were then assembled using the HiFi DNA assembly master mix ( New England Biolabs ) and incubated at 50°C for four hours . The Gibson assembly reaction then was treated with Exonuclease I ( specific for ssDNA ) , lambda exonuclease ( removes non-circular dsDNA ) and DpnI ( removes any original bacteria derived plasmid DNA ) at 37°C for 30 minutes followed by heat inactivation for 20 minutes at 80°C . Two microliters of this reaction then was used for rolling circle amplification ( RCA ) using the REPLI-g Mini kit ( Qiagen ) . RCA was performed following the manufacturer's specifications except that 2M trehalose was used in place of water in the reaction mixture because it has been previously shown that this modification reduces secondary amplification products [38] . Reactions were incubated at 30°C for four hours and then inactivated at 65°C for three minutes . Sequence was confirmed by Sanger sequencing . Virus was prepared in Vero cells transfected with the purified RCA reaction . Briefly , RCA reactions were digested with NruI at 37°C for one hour to linearize the product and remove the branched structure . Generation of an authentic 3’UTR was assured due to the presence of the hepatitis-delta ribozyme immediately following the viral genome [21] . The digested RCA reaction then was purified using a PCR purification kit ( Macherey-Nagel ) and eluted with molecular-grade water . Purified and digested RCAs were transfected into 80–90% confluent Vero cells using the Xfect transfection reagent ( Clontech ) following manufacturer’s specifications . Infectious virus was harvested when 50–75% cytopathic effects were observed ( 6 days post transfection ) . Viral supernatant then was clarified by centrifugation and supplemented to a final concentration of 20% fetal bovine serum and 10 mM HEPES prior to freezing and storage as single use aliquots . Titer was measured by plaque assay on Vero cells as described in a subsequent section . The ZIKV-PR stock , ZIKV-IC , and ZIKV-BC-1 . 0 were thawed , diluted in PBS to 1 x 104 PFU/ml , and loaded into a 3 ml syringe maintained on ice until inoculation . Each of nine nonpregnant Indian-origin rhesus macaques was anesthetized and inoculated subcutaneously over the cranial dorsum with 1 ml ZIKV-PR stock ( n = 3 ) , ZIKV-IC stock ( n = 3 ) , or ZIKV-BC-1 . 0 stock ( n = 3 ) containing 1 x 104 PFU . Likewise , the pregnant animal was anesthetized and inoculated via the same route with 1 ml barcoded virus stock containing 1 x 104 PFU . All animals were closely monitored by veterinary and animal care staff for adverse reactions and signs of disease . Nonpregnant animals were examined , and blood and urine were collected from each animal daily from 1 through 10 days , and 14 days post inoculation ( dpi ) . Sampling continued for the pregnant animal until the resolution of viremia . The Aedes aegypti black-eyed Liverpool ( LVP ) strain used in this study was obtained from Lyric Bartholomay ( University of Wisconsin-Madison , Madison , WI ) and maintained at the University of Wisconsin-Madison as previously described [39] . Ae . aegypti LVP are susceptible to ZIKV [40] . Infection , dissemination , and transmission rates were determined for individual mosquitoes and sample sizes were chosen using long established procedures [40–42] . Mosquitoes that fed to repletion on macaques were randomized and separated into cartons in groups of 40–50 and maintained as described in [22] . All samples were screened by plaque assay on Vero cells . Dissemination was indicated by virus-positive legs . Transmission was defined as release of infectious virus with salivary secretions , i . e . , the potential to infect another host , and was indicated by virus-positive salivary secretions . All ZIKV screens from mosquito tissue and titrations for virus quantification from virus stocks were completed by plaque assay on Vero cell cultures . Duplicate wells were infected with 0 . 1 ml aliquots from serial 10-fold dilutions in growth media and virus was adsorbed for one hour . Following incubation , the inoculum was removed , and monolayers were overlaid with 3 ml containing a 1:1 mixture of 1 . 2% oxoid agar and 2X DMEM ( Gibco , Carlsbad , CA ) with 10% ( vol/vol ) FBS and 2% ( vol/vol ) penicillin/streptomycin . Cells were incubated at 37 °C in 5% CO2 for four days for plaque development . Cell monolayers then were stained with 3 ml of overlay containing a 1:1 mixture of 1 . 2% oxoid agar and 2X DMEM with 2% ( vol/vol ) FBS , 2% ( vol/vol ) penicillin/streptomycin , and 0 . 33% neutral red ( Gibco ) . Cells were incubated overnight at 37 °C and plaques were counted . Macaque serum samples were screened for ZIKV and DENV neutralizing antibody utilizing a plaque reduction neutralization test ( PRNT ) on Vero cells as described in [43] against ZIKV-PR and DENV-3 . 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 50% and 90% of infection . 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 [2 , 13] . These samples were obtained at the gestational ages 57 , 71 , 85 , and 155 days . All fluids were free of any blood contamination . Plasma was isolated from EDTA-anticoagulated whole blood collected the same day by Ficoll density centrifugation at 1860 rcf for 30 minutes . Plasma was removed to a clean 15ml conical tube and centrifuged at 670 rcf for an additional 8 minutes to remove residual cells . Viral RNA was extracted from 300 µL plasma using the Viral Total Nucleic Acid Kit ( Promega , Madison , WI ) on a Maxwell 16 MDx instrument ( Promega , Madison , WI ) . Tissues were processed with RNAlater ( Invitrogen , Carlsbad , CA ) according to the manufacturer's 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 . 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 snap-cap 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 . RNA was then quantified using quantitative RT-PCR . If a tissue was negative by this method , a duplicate tissue sample was extracted using the Trizol Plus RNA Purification kit ( Invitrogen , Carlsbad , CA ) . Because this purification kit allows for more than twice the weight of tissue starting material , there is an increased likelihood of detecting vRNA in tissues with low viral loads . RNA then was re-quantified using the same quantitative RT-PCR assay . Viral load data from plasma are expressed as vRNA copies/ml . Viral load data from tissues are expressed as vRNA/mg tissue . At ~155 days gestation , the fetus was removed via surgical uterotomy and maternal tissues were biopsied during laparotomy . These were survival surgeries for the dams . The entire conceptus ( 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 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 S7 Table . 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 ( except neural tissues ) were fixed in 4% paraformaldehyde for 24 hours and transferred into 70% ethanol until alcohol processed and embedded in paraffin . Neural tissues were fixed in 10% neutral buffered formalin for 14 days 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 . 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 ZIKV-PR , vRNA from plasma and tissues was quantified by qRT-PCR using primers with a slight modification to those described by Lanciotti et al . to accommodate African lineage ZIKV sequences [44] . The modified primer sequences are: forward 5’-CGYTGCCCAACACAAGG-3’ , reverse 5’-CACYAAYGTTCTTTTGCABACAT-3’ , and probe 5’-6fam-AGCCTACCTTGAYAAGCARTCAGACACYCAA-BHQ1-3’ . The RT-PCR was performed using the SuperScript III Platinum One-Step Quantitative RT-PCR system ( Invitrogen , Carlsbad , CA ) on a LightCycler 480 instrument ( Roche Diagnostics , Indianapolis , IN ) . The primers and probe were used at final concentrations of 600 nm and 100 nm respectively , along with 150 ng random primers ( Promega , Madison , WI ) . Cycling conditions were as follows: 37°C for 15 min , 50°C for 30 min and 95°C for 2 min , followed by 50 cycles of 95°C for 15 sec and 60°C for 1 min . Viral RNA concentration was determined by interpolation onto an internal standard curve composed of seven 10-fold serial dilutions of a synthetic ZIKV RNA fragment based on a ZIKV strain derived from French Polynesia that shares >99% similarity at the nucleotide level to the Puerto Rican strain used in the infections described in this manuscript . Virus populations replicating in macaque plasma or mosquito tissues were sequenced in duplicate using a method adapted from Quick et . al . [45] . Viral RNA was isolated from mosquito tissues or plasma using the Maxwell 16 Total Viral Nucleic Acid Purification kit , according to manufacturer’s protocol . Viral RNA then was subjected to RT-PCR using the SuperScript IV Reverse Transcriptase enzyme ( Invitrogen , Carlsbad , CA ) . Theoretical input viral template numbers are shown in Tables 1–3 and 5 . For sequencing the entire ZIKV genome , the cDNA was split into two multi-plex PCR reactions using the PCR primers described in Quick et . al with the Q5 High-Fidelity DNA Polymerase enzyme ( New England Biolabs , Inc . , Ipswich , MA ) . For sequencing solely the barcode region , individual PCR reactions were performed that either used a primer pair generating a 131 bp amplicon ( 131F: 5’-TGGTTGGCAATACGAGCGATGGTT-3’; 131R: 5’-CCCCCGCAAGTAGCAAGGCCTG-3’ ) or a 178bp amplicon ( 178F: 5’-CCTTGGAAGGCGACCTGATGGTTCT-3’; 178R ( same as 131R ) : 5’-CCCCCGCAAGTAGCAAGGCCTG-3’ ) . Purified PCR products were tagged with the Illumina TruSeq Nano HT kit or the and sequenced with a 2 x 300 kit on an Illumina MiSeq . Full genome ZIKV sequences generated with the multiplex PCR approach were analyzed using a workflow we termed “Zequencer_2017” ( https://bitbucket . org/dholab/zikv_barcode_manuscript_scripts/src ) . Briefly , sequences were analyzed using a series of custom Python scripts . To characterize the entire ZIKV genome , up to 1000 reads spanning each of the 35 amplicons were extracted from the data set and then mapped to the Zika reference for PRVABC59 ( Genbank:KU501215 ) . Variant nucleotides were called using SNPeff [46] , using a 5% cutoff . Mapped reads and reference scaffolds were loaded into Geneious Pro ( Biomatters , Ltd . , Auckland , New Zealand ) for intrasample variant calling and differences between each sample and the KU501215 reference were determined . Sequence alignments of the stock viruses can be found in the sequence read archive: ZIKV-IC ( accession number: SRX3258286 ) ; ZIKV-BC-1 . 0 ( accession number: SRX3258287 ) . To characterize the barcodes and their frequencies , we developed a workflow called “ZIKV_barcode_analysis” ( https://bitbucket . org/dholab/zikv_barcode_manuscript_scripts/src ) that makes use of the bbmap suite of tools . Briefly , paired-end reads were merged and quality trimmed using bbmerge . Then , reads containing the barcode were extracted , using bbduk to select reads containing both 20 bp sequences upstream and downstream of the barcode region . These reads were mapped against the Zika reference ( GenBank:KU501215 ) with bbmap , and were then oriented and trimmed so that only the 24 bp barcode remained . Identical barcodes were identified and counted . Custom Python scripts were used to identify authentic barcodes and calculate their frequency in each sample . The diversities of the sequence populations were evaluated using the Simpson’s diversity index: Ds=1−∑i=1cni ( ni−1 ) n ( n−1 ) where ni is the number of copies of the ith unique sequence , c is the number of different unique sequences , and n is the total number of sequences in the sample . The similarities between pairs of samples were assessed using the Morisita-Horn similarity index: CMH= 2∑i=1cfigi∑i=1c ( fi2+gi2 ) where fi = n1i / N1 and gi = n2i / N2 , n1i and n2i are the number of copies of the ith unique sequence in samples 1 and 2 , and N1 and N2 are the total number of sequences in samples 1 and 2 , respectively . The summations in the numerator and the denominator are over the c unique sequences in both samples . The Simpson’s diversity and Morisita-Horn similarity indices account for both the number of unique sequences and their relative frequencies . These relative diversity and similarity indices range in value from 0 ( minimal diversity/similarity ) to 1 ( maximal diversity/similarity ) . The Simpson’s diversity index considers a more diverse population as one with a more even distribution of sequence frequencies and the Morisita-Horn similarity index considers populations to be more similar if the higher frequency sequences in both samples are common to both samples and have similar relative frequencies . Primary data that support the findings of this study are available at the Zika Open-Research Portal ( https://zika . labkey . com ) . Raw FASTQ sequencing data are available at the sequence read archive , accession number: SRP131908 . The authors declare that all other data supporting the findings of this study are available within the article and its supplementary information files . | Understanding the complex dynamics of Zika virus ( ZIKV ) infection during pregnancy and during transmission to and from vertebrate host and mosquito vector is critical for a thorough understanding of viral transmission , pathogenesis , immune evasion , and reservoir establishment . We sought to develop a virus model system for use in nonhuman primates and mosquitoes that allows for the genetic discrimination of molecularly cloned viruses . This “synthetic swarm” of viruses incorporates a molecular barcode that allows for tracking and monitoring individual viral lineages during infection . Here we infected rhesus macaques with this virus to study the dynamics of ZIKV infection in nonhuman primates as well as during mosquito infection/transmission . We found that the proportions of individual barcoded viruses remained relatively stable during acute infection in pregnant and nonpregnant animals . However , in a pregnant animal , the complexity of the virus population declined precipitously 8 days following infection , consistent with the timing of typical resolution of ZIKV in non-pregnant macaques and remained low for the subsequent duration of viremia . | [
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"primates",... | 2018 | Molecularly barcoded Zika virus libraries to probe in vivo evolutionary dynamics |
The complement system plays a key role in host defense against pneumococcal infection . Three different pathways , the classical , alternative and lectin pathways , mediate complement activation . While there is limited information available on the roles of the classical and the alternative activation pathways of complement in fighting streptococcal infection , little is known about the role of the lectin pathway , mainly due to the lack of appropriate experimental models of lectin pathway deficiency . We have recently established a mouse strain deficient of the lectin pathway effector enzyme mannan-binding lectin associated serine protease-2 ( MASP-2 ) and shown that this mouse strain is unable to form the lectin pathway specific C3 and C5 convertases . Here we report that MASP-2 deficient mice ( which can still activate complement via the classical pathway and the alternative pathway ) are highly susceptible to pneumococcal infection and fail to opsonize Streptococcus pneumoniae in the none-immune host . This defect in complement opsonisation severely compromises pathogen clearance in the lectin pathway deficient host . Using sera from mice and humans with defined complement deficiencies , we demonstrate that mouse ficolin A , human L-ficolin , and collectin 11 in both species , but not mannan-binding lectin ( MBL ) , are the pattern recognition molecules that drive lectin pathway activation on the surface of S . pneumoniae . We further show that pneumococcal opsonisation via the lectin pathway can proceed in the absence of C4 . This study corroborates the essential function of MASP-2 in the lectin pathway and highlights the importance of MBL-independent lectin pathway activation in the host defense against pneumococci .
Streptococcus pneumoniae infection is a major cause of pneumonia , otitis media , septicemia and meningitis [1] , [2] . Complement–driven opsonophagocytosis is a prominent feature of the host response to pneumococcal infections , [3] . Complement provides protection against invading microorganisms through both antibody-dependent and -independent mechanisms . It mediates many cellular and humoral interactions within the immune response , including chemotaxis , phagocytosis , cell adhesion , and B-cell differentiation . Three different pathways initiate the complement cascade , which are known as the classical , alternative and lectin pathways . In the classical pathway , the recognition subcomponent C1q binds to a variety of targets - most prominently immune complexes - to initiate the step-wise activation of associated serine proteases , C1r and C1s . Activated C1s cleaves C4 into C4a and C4b and then cleaves C4b-bound C2 to generate the C3 convertase , C4b2a , which converts the abundant plasma protein C3 into C3a and C3b; C3b is the major opsonin of the complement system . Accumulation of C3b in close proximity to the C4b2a complex leads to the formation of the C5 convertase , C4b2a ( C3b ) n , which initiates the terminal pathway of complement activation . In the alternative pathway , spontaneous low-level hydrolysis of C3 leads to deposition of C3b on cell surfaces , triggering complement activation on foreign cells . Host cells are protected by surface regulatory proteins that suppress complement activation . Like the alternative pathway , the lectin pathway may be activated in the absence of immune complexes . Activation is initiated by the binding of a multimolecular lectin pathway activation complex to pathogen-associated molecular patterns ( PAMPs ) , mainly carbohydrate structures present on microorganisms or aberrant glycocalyx patterns on apoptotic , necrotic , malignant or oxygen-deprived cells [4] , [5] . Rodents have at least four circulating lectin pathway recognition molecules , with differing , but overlapping , carbohydrate specificities; two mannan-binding lectins ( MBL-A and MBL-C ) , collectin-11 ( CL-11 ) and ficolin A ( Fcna ) [6] . A second murine ficolin , Fcnb , associated with monocyte and macrophage cell surfaces does not activate complement in mice , but may act as a lectin pathway recognition molecule in rats [7] . Humans have a single MBL ( the product of MBL2; MBL1 is a pseudogene ) , CL-11 ( collectin kidney 1 , CL-K1 ) and three ficolins , FCN1 ( M-ficolin ) , FCN2 ( L-ficolin ) and FCN3 ( H-ficolin ) [5] , [8] , [9] . These recognition molecules form complexes with three serine proteases , MASP-1 , -2 and -3 ( MBL-associated serine proteases 1 , 2 and 3 ) . The recognition molecules also interact with MAp19 and MAp44 ( alias MBL/ficolin-associated protein 1 ) , which are non-enzymatic , truncated alternative splice products of the MASP2 and MASP1/3 genes , respectively . Both truncated gene products lack the serine protease domain and may regulate lectin pathway activation by competing for the binding of MASPs to the carbohydrate recognition molecules [4] , [10]–[15] . Of the three MASPs , only MASP-2 is required and essential to form the lectin pathway C3 and C5 convertases ( C4b2a and C4b2a ( C3b ) n ) [6] , [10] , [16] , [17] . Like C1s , activated MASP-2 cleaves C4 and C4b-bound C2 , generating C4b2a , the classical and lectin pathway C3 convertase . Neither MASP-1 nor MASP-3 can cleave C4 and therefore cannot compensate for the absence of MASP-2 . Thus , formation of the lectin pathway C3 and C5 convertase complexes is impossible in absence of MASP-2 [6] . MASP-1 appears to facilitate lectin pathway activation by either direct cleavage of complex-bound MASP-2 or cleavage of C4b-bound C2 , but MASP-1 cannot drive lectin pathway activation in the absence of MASP-2 , as MASP-2 is required to initiate the formation of the lectin pathway convertases by the cleavage of C4 [6] , [18] , [19] . Interestingly , recent work demonstrated that MASP-1 ( and possibly MASP-3 ) play a key role in the maturation and initiation of the alternative activation pathway [20] , [21] . Infection studies using mice with targeted deficiencies in one or more complement components have provided evidence for the roles of the classical and alternative pathways in protection against S . pneumoniae . C1q deficient mice were found to be more susceptible to infection with S . pneumoniae than WT mice , indicating that the classical pathway has a protective role . The alternative pathway was also found to have a protective role against S . pneumoniae , but to a lesser extent than the classical pathway . Mice deficient in factor B had a significantly higher level of bacteria in lungs and in blood in comparison to their WT controls [22] . The contribution of the lectin activation pathway towards the defense against S . pneumoniae infection had not been assessed so far , mainly due to the lack of appropriate mouse models of total lectin pathway deficiency . Using MASP-2 deficient mice , completely devoid of the ability to form lectin pathway C3 and C5 convertases , this report demonstrates that lectin pathway activation provides a critical degree of protection against S . pneumoniae . We identified mouse ficolin A and CL-11 , but not MBL-A or MBL-C , to be the critical pattern recognition molecules that initiate complementactivation via the lectin pathway on the surface of this pathogen .
Complement deficient sera were used to determine which components contribute to C3b opsonisation of S . pneumoniae . C3b deposition was assayed by ELISA using formalin-fixed bacteria and by FACS analysis using live bacteria . MASP-2 deficiency leads to a total loss of C3b deposition ( fig . 1a–e ) . Using a simple end-point ELISA , C3b deposition appears to be unaffected by factor B deficiency ( fig . 1b ) . However , the conversion of C3 is slower in factor B deficient serum ( t1/2≈28 min ) than in WT serum ( t1/2≈8 min ) , indicating that the alternative pathway amplification loop contributes to the C3 turnover ( fig . 1c ) . Serum from MBL-null mice ( deficient in both MBL-A and MBL-C ) opsonised the bacteria as efficiently as WT serum , whereas ficolin A deficiency resulted in impaired C3b deposition . Ficolin B was not detectable in sera of WT and ficolin A deficient C57BL/6 mice ( data not shown ) . Serum deficient in MBL-A , MBL-C and ficolin A produced similar results to those seen using ficolin A deficient serum , suggesting that the remaining lectin pathway recognition component CL-11 may drive residual lectin pathway activation on S . pneumoniae ( fig . 1b ) . In addition to the recent publication by Hansen et al . ( 2010 ) [9] which demonstrated MASP-1 binding to CL-11 , we have shown that recombinant human CL-11 binds recombinant MASP-2 to form a lectin pathway activation complex under physiological conditions ( fig . S1 ) . Using C4 deficient mouse serum , the absolute amount of C3b deposited on S . pneumoniae was approximately half that observed using WT serum ( fig . 1b , c , e & f ) and the rate of conversion was lower ( T1/2≈30 min in C4 deficient serum; 8 min in WT serum; fig . 1c ) . C4 is an integral part of the classical and lectin pathway C3 convertase , C4b2a , suggesting that the residual C3b deposition seen in C4 deficient serum is a result of either alternative pathway activation [23] , [24] or the recently reported lectin pathway-specific C4-bypass [6] . Since ( i ) all experiments reported here were carried out at low serum concentrations ( 1 . 25% , fig . 1b; 2 . 5% , fig . 1c and; 5% , fig . 1e & f ) where the alternative activation pathway is dysfunctional , and ( ii ) the activation of C3 on the surface of S . pneumoniae is absent in MASP-2 deficient mice ( see fig . 1 ) , we conclude that the C3 deposition on S . pneumoniae in C4 deficient serum is mediated by the MASP-2 dependent C4-bypass activation route . Likewise , inhibition of MASP-2 activity with the anti-MASP-2 mAb AbD04211 abolished C3b deposition on S . pneumoniae incubated with C4 deficient serum , supporting the hypothesis that the MASP-2 dependent C4-bypass plays a significant role in the opsonisation of S . pneumoniae ( fig . 1f ) . Similar results were obtained using human serum from a donor with a complete deficiency of both C4 genes , C4A and C4B: C4 deficiency halved C3b deposition , although the EC50 value was unaffected ( ≈0 . 05% for all sera assayed; fig . 1g ) . Human MBL deficiency had no impact on the deposition of C3b on the surface of S . pneumoniae ( see fig . 1g ) . In contrast , analysis of 47 samples of normal human serum ( NHS ) revealed a significant correlation between serum L-ficolin concentration and the level of C3b deposition S . pneumoniae ( fig . 2f; p<0 . 0001; Fisher transformation of Pearson's correlation coefficient ) . The test group included 8 MBL deficient sera ( YO/YO or YO/XA genotypes , see [25] ) , none of which showed abnormally low C3b deposition , providing further evidence that that human MBL does not contribute to complement activation on S . pneumoniae . Antibodies directed against the larger C4 activation fragments , C4b and C4c , failed to detect any C4 deposition on the surface of S . pneumoniae exposed to normal human serum ( fig . 2a & c ) . However , when using an antibody directed against C4dg , the haemolytically inactive final degradation product of C4 , an abundant deposition of covalently bound C4dg was detected ( fig . 2b & d ) , supporting the hypothesis that S . pneumoniae sequester host complement control proteins to accelerate the degradation and inactivation of C4b [26] , [27] . A series of solid-phase binding experiments were performed to identify lectin pathway recognition molecules that bind to S . pneumoniae . Microtitre plates coated with S . pneumoniae D39 and control substrates were used to capture lectin pathway recognition molecules from WT mouse serum and NHS ( fig . 3 ) . As anticipated from the C3b deposition assays ( fig . 1b & g ) and previous reports [28] , MBL does not recognize the bacteria , whereas murine Fcna ( fig . 3b ) and CL-11 ( fig . 3c ) , and human L-ficolin and CL-11 ( alias CL-K1 ) ( fig . 3f ) do . Direct binding to the bacterial surface was confirmed using recombinant human CL-11 and mouse ficolin A ( data not shown ) . Nine other strains of S . pneumoniae representing three additional serotypes ( 18 , 6B and 3 ) were tested for binding of human and murine recognition molecules . With human serum the results were remarkably consistent: Of the 5 different lectin pathway specific carbohydrate recognition subcomponents , only L-ficolin and CL11 ( alias CL-K1 ) bound to the bacteria ( table S1 ) . Most of the strains showed little or no binding to murine MBL-C and none bound MBL-A . All of the strains tested bound murine CL-11 with similar affinities , and all strains tested bound Ficolin A . MBL-C and Ficolin A binding differed amongst strains of the same serotype , indicating that capsular polysaccharide is unlikely to be the main determinant of recognition by lectin pathway recognition subcomponents . The inability of MASP-2 deficient mouse serum to opsonise S . pneumoniae with C3b led to defective phagocytosis in vitro ( fig . 4 ) . S . pneumoniae D39 were opsonised with WT or MASP-2 deficient serum and mixed with freshly isolated human peripheral blood polymorphonuclear leukocytes ( PMN ) . Bacteria opsonised with WT serum were internalised ( fig . 4a & c ) , whereas bacteria opsonised with MASP-2 deficient serum were excluded from the PMN , indicative of defective uptake and phagocytosis ( fig . 4b ) . Samples taken from the mixture over a period of 2 hr were plated on blood agar and viable S . pneumoniae counted ( fig . 4d ) . Pneumococci mixed with WT serum are efficiently killed by PMN , while those opsonised with MASP-2 deficient serum survive as well as non-opsonised controls . In addition , 20% MASP-2 sufficient ( WT ) serum from non-immunized mice has no bacteriolytic activity on S . pneumoniae . This observation was confirmed using 50% WT mouse and human serum ( data not shown ) . We used MASP-2 and Fcna deficient mice to determine to what extent the lectin pathway contributes to host defense against S . pneumoniae in vivo . In contrast to MBL-null [29] and Fcna deficient mice [30] ( both of which having lectin pathway activation complexes formed with the remaining recognition molecules in their blood ) , MASP-2 deficient animals are unable to form the lectin pathway C3 and C5 convertases [6] . Ten-week old C57BL/6Masp2−/− mice and WT littermates were infected with S . pneumoniae D39 by intranasal inoculation and the course of the infection monitored for one week ( fig . 5 ) . 75% of the WT mice survived the infection , compared with only 20% of the MASP-2 deficient mice ( p = 0 . 0006 ) . During the first 12 hours after infection , the WT mice showed signs of an initial clinical response ( hunching ) , while the MASP-2−/− mice appeared unaffected . In both groups , the first animals reached the endpoint ( severe lethargy ) after 48 hours , and survival dropped further until 72 hrs after infection . All those animals alive after 72 hr survived ( see fig . 5a ) . In another series of experiments , animals were sacrificed 12 , 24 and 48 hr post infection to determine counts of viable S . pneumoniae in lung homogenate and blood . In MASP-2 deficient mice , CFUs in the lung ( fig . 5c ) and blood ( fig . 5e ) were significantly higher than in WT mice and rose progressively during the first 48 hr , at which point the experiment was stopped due to the high mortality in the MASP-2 deficient group . In WT mice that survived the first 72 hr , bacteria were progressively cleared from the both the lungs and blood . Similar results were obtained with C57BL/6Fcna−/− mice; 70% of the WT littermates survived , whereas 80% of the ficolin A deficient mice succumbed to the infection ( fig . 5b ) . Lung infection and bacteraemia are shown in fig . 5d and f . In contrast , intranasal infection of C57BL/6 MBL-null ( MBL-A and MBL-C double deficient ) mice resulted in neither significantly increased mortality nor compromised bacterial clearance mice compared to sex and age matched C57BL/6 WT controls ( fig . S2 ) . Quantitative RT-PCR analysis of cytokine and chemokine expression in lungs from infected animals showed that the onset of the inflammatory response was broadly similar in WT , ficolin A and MASP-2 deficient mice . After 12 hr , however , the pro-inflammatory TNFα response increased more rapidly in the lectin pathway deficient mice , and levels were significantly greater at 24 hr and 48 hr than in the WT mice . In MASP-2 deficient mice , the IL6 response was also elevated . The INFγ response was significantly greater in the ficolin A deficient mice . In the ficolin A and MASP-2 deficient mice , MIP-2 ( CLCX2 ) expression persists at 48 hr , indicating on-going macrophage activation at a time when the response is abating in the WT mice ( fig . S3 ) . MASP-2 deficiency can be simulated in WT mice using a mAb that specifically inhibits MASP-2 . A single i . p . dose of 0 . 6–1 . 0 mg/kg body weight leads to a loss of ≥90% of lectin pathway activity for up to 7 days [6] . WT mice treated with this mAb prior to infection with S . pneumoniae had significantly greater mortality and higher bacteraemia than untreated controls ( fig . 6 ) . Antibiotic treatment ( Ceftriaxone , 20 mg per kg body weight i . p . 12 h before infection and every 12 h thereafter ) resulted in complete protection against mortality in both Ab-treated and non-treated groups . These results suggest that increased susceptibility to S . pneumoniae in MASP-2 deficient mice is a direct result of the loss of MASP-2 driven lectin pathway activity , rather than an indirect result of MASP-2 deficiency on the development of the animal's immune response .
Complement-dependent opsonophagocytosis is a key feature of the host defense against S . pneumoniae . Thirty years ago , using a guinea pig model of pneumococcal bacteraemia , it was shown that the clearance of IgG and IgM opsonized pneumococci from the circulation is entirely dependent upon complement; animals deficient of C4 , or depleted of complement using cobra venom factor ( CVF ) , fail to clear the bacteria [31] . More recently , Brown and co-workers [22] used mice with engineered genetic deficiencies to demonstrate the importance of C1q , C4 and C3 in the defense against S . pneumoniae . Based on the observation that C1q deficient mice are as susceptible to infection as C4 deficient mice , the authors concluded that activation of the classical pathway is the predominant mechanism for complement-mediated opsonization and phagocytosis of S . pneumoniae and that the lectin pathway ( which according to the present text book view requires C4 to work ) plays a negligible role [22] . Here we analyzed experimental S . pneumoniae infection in the first available model of lectin pathway deficiency and reached the conclusion that the lectin pathway promotes innate resistance against pneumococcal infection in the non-immunized host . The results presented here show that MASP-2 deficient mice ( which can still activate complement via the classical and alternative pathways [6] ) are severely compromised in their ability to survive S . pneumoniae infection ( fig . 5 ) . Survival times and mortality rates were similar to those reported for C1q and C4 deficient mice , using the same strains of bacteria and mice , and the same dose and route of infection [22] . Neither the classical , nor the alternative activation pathway could compensate for the loss of lectin pathway mediated C3 opsonization of S . pneumoniae . In contrast , the absence of C1q had no effect on C3 opsonization of these bacteria in vitro ( fig . 1 ) implying that C1q may contribute to bacterial clearance in a process independent of direct C3b or iC3b deposition on the bacterial surface . Deficiency of factor B , a component of the alternative pathway C3 convertase led to a significantly slower C3 turnover ( fig . 1C ) , This is probably due to the loss of the alternative pathway amplification loop , a positive feedback mechanism that amplifies C3 activation via of all three pathways , which may account for the reported susceptibility of factor B deficient mice to S . pneumoniae infection ( Brown et al . , 2002 ) . As previously reported by others [26] , [32] , we were unable to detect any C4b or C4c on the surface of S . pneumoniae opsonized with normal human serum ( fig . 2 ) . However , the bacterial surface was abundantly decorated with C4dg , the final product of C4 decay . This finding strongly supports the hypothesis that S . pneumoniae avoids the accumulation of active C4b by sequestrating complement regulatory proteins from host serum to accelerate the breakdown of C4b , thus preventing the formation of the C3 convertase C4b2a on the pathogen , rather than by preventing C4 binding . Recent work suggests that the pneumococcal virulence factors PspA and PspC are responsible for recruiting factor H and C4-binding protein from host plasma , both of which accelerate the factor I-mediated breakdown of C4b to C4dg [26] , [27] . C3 deposition on pneumococci was impaired , but not completely blocked , by C4 deficiency in both mice ( fig . 1b–f ) and humans ( fig . 1g ) . In the mouse , C4 deficiency led to a significantly slower C3 turnover and in both species the absolute amount of C3 deposited on the bacteria was approximately half of that observed using WT serum . The residual C3 deposition in C4 deficient murine serum could be inhibited using a monoclonal antibody directed against MASP-2 ( fig . 1f ) , indicating that the MASP-2-dependent C4-bypass is active on S . pneumoniae [6] . Nevertheless , C4 deficient mice have an increased susceptibility to S . pneumoniae infection ( [22]; our unpublished data ) , indicating that the MASP-2-dependent C4-bypass only partially compensates for C4-dependent lectin pathway activation in this setting . The C4-bypass activation of the lectin pathway was shown to play a significant physiological role in ischemia-reperfusion injury; MASP-2 deficient mice are protected from reperfusion injury following myocardial ischemia , whereas C4 deficient mice are not [6] , [33] . We hypothesize that the rapid degradation of C4b on the bacterial surface seriously compromises the ability of the classical pathway to form a C3 convertase and thus opsonize S . pneumoniae with C3b , while the lectin pathway is still able to opsonize pneumococci with C3b via the C4-bypass , which provides a physiologically relevant degree of compensation for the impaired C4-dependent activation of C3 [6] . The loss of lectin pathway activity caused by MASP-2 deficiency or MASP-2 inhibition would remove a critical degree of C3 opsonization of S . pneumoniae in naive mice and hence explain the phenotype of compromised pneumococcal clearance in MASP-2 deficient or MASP-2 depleted mice . The rapid conversion of C4b to C4dg on the pathogen surface appears to be a feature of S . pneumoniae . This would explain why the absence of lectin pathway activity renders the host more susceptible to infections with this particular pathogen , whilst no increased predisposition to , or severity of , infection with other major pathogens , e . g . Pseudomonas aeruginosa and Neisseria meningitidis were observed in MASP-2 deficient mice ( [34]; our unpublished data ) . In murine serum , it is predominantly ficolin A and CL-11 that bind to S . pneumoniae ( fig . 3 and table S1 ) . The binding of both lectin pathway recognition molecules to the bacterial surface was confirmed using recombinant human CL-11 and recombinant murine ficolin A . Murine MBL-A does not bind to any of the S . pneumoniae strains studied here ( covering 4 serotypes ) , and MBL-C bound weakly or not at all ( table S1 ) . It was therefore not surprising that the presence or absence of both MBL-A and MBL-C in C57BL/6 mice had no impact on overall survival in our model of S . pneumoniae D39 infection . In contrast , following pneumococcal infection , C57BL/6Fcna−/− mice were severely compromised with a significantly higher degree of mortality and higher bacterial loads in blood and lung tissue than WT controls . This phenotype underlines our in vitro results and indicates that ficolin A ( but not MBL-A or MBL-C ) is a key recognition component of the lectin activation pathway in the innate host defense against pneumococcal infection . Interestingly , serum from mice deficient in all lectin pathway recognition components except CL-11 still deposits C3b on the surface of S . pneumoniae ( fig . 1b ) . Since mouse CL-11 binds strongly to the surface of S . pneumoniae ( see fig . 3c ) and since we show that CL-11 also forms complexes with the lectin pathway effector enzyme MASP-2 ( fig . S1 ) , we conclude that CL-11 acts synergistically with ficolin A as an initiator of lectin pathway activation following binding of specific PAMPs on the pneumococcal surface . The situation is similar in humans; only L-ficolin and CL-11 recognize S . pneumoniae ( fig . 3e & f ) . As previously reported by others [28] , we found no binding of MBL to any of the pneumococcal strains ( table S1 ) , and there was no indication that MBL deficiency leads to defective C3b deposition on the bacteria ( fig . 1g&h ) . As MBL deficiency is the most common hereditary complement deficiency in humans , affecting as many as 1 in 10 of the population [35] , there has been much interest in the possibility of an association between MBL deficiency and infectious disease . In the case of S . pneumoniae , the results of association studies have been largely negative or inconclusive , with two of the largest studies finding no association between the risk of community-acquired pneumonia and MBL deficiency [36] , [37] . Genetic variations of the L-ficolin gene are more subtle , with no complete functional deficiency in adults reported to date . Furthermore , there is no apparent association between polymorphisms in FCN2 that lead to low levels of L-ficolin and pneumococcal disease [38] , indicating that even low levels of L-ficolin and/or the presence of CL-11 are sufficient to mount a robust immune response against S . pneumoniae . We have previously shown that antibodies to MASP-2 can block lectin pathway driven inflammation and limit tissue loss in ischaemic pathologies [6] , suggesting therapeutic utility for anti MASP-2 antibody therapy . Our experiments show that such treatment may increase susceptibility to S . pneumoniae infection in naive mice . Pneumococcal vaccination history or immune status may need to be considered prior to initiating anti MASP-2 treatment in patients . Alternatively , since the increased susceptibility was completely reversed by concurrent treatment with ceftriaxone , MASP-2 antagonists should be safe to use with appropriate prophylactic antibiotic treatment . The results of this study call for a revision of the previously published conclusion by Brown et al . ( 2002 ) [22] that the lectin pathway of complement activation is not a major player in the host response to S . pneumoniae infection . This conclusion led the same research team to exclude any involvement of the lectin pathway in the clearance of pneumococci in subsequent publications . When studying the impact of human C2 deficiency on C3b opsonization and phagocytosis of S . pneumoniae [39] , no consideration was given to the fact that C2 deficient individuals are not only deficient of the classical activation pathway , but also of C3 and C5 convertases formed by the lectin pathway . The results presented here , however , strongly suggest that in none-immune sera , it is the loss of lectin pathway functional activity that accounts for the loss of C3b/iC3b opsonization of pneumococci . Finally , we describe clear evidence of lectin pathway activation in a physiological context in the absence of a discernable contribution by MBL . Thus , the prevailing view that MBL is the predominant initiator of lectin pathway activation may need to be revisited .
All animal experiments were authorized by the UK Home Office ( Animals Scientific Procedures Act 1986; Home Office project licence 80/2111 ) and approved the University of Leicester animal welfare committee . Every effort was made to minimize suffering and mice were humanely culled if they became lethargic during infection experiments . Unless otherwise stated , all reagents were obtained from Sigma-Aldrich . PSA , a polysaccharide produced by Aerococcus viridans that binds FCN3 was prepared as previously described [40] . AbD04211 , a recombinant mAb that potently inhibits mouse MASP-2 , has been described previously [6] . S . pneumoniae serotype 2 strain D39 was obtained from the National Collection of Type Cultures , London , United Kingdom ( NCTC 7466 ) . Bacteria were identified as pneumococci by Gram staining , catalase testing , alpha-hemolysis on blood agar plates , and determination of optochin sensitivity . Serotypes were confirmed by the Quellung reaction . To obtain pneumococci grown in vivo , bacteria were cultured and passaged through mice as described previously [41] and subsequently recovered and stored at −70°C . When required , suspensions were thawed at room temperature and bacteria were harvested by centrifugation before re-suspension in sterile PBS . Nine other clinical isolates of S . pneumoniae were kindly provided by Prof . Herminia de Lancastre , Instítuto de Tecnologia Química e Biológica , Oeiras , Portugal [42] . Mice deficient in MASP-2 and C4 have been described elsewhere [6] , [43] . Ficolin A deficient mice were generated by targeting Fcna using a conventional replacement vector , as described elsewhere [44] . MBL-null mice were purchased from MMRRC , Bar Harbor , Maine and crossed with Fcna−/− mice to produce a strain deficient in all three components . Complement deficient mouse strains were backcrossed with C57/BL6 mice for at least ten generations before use . Blood was collected from these animals and from WT C57/BL6 mice by cardiac puncture , serum prepared , aliquoted and stored at −80°C . C1q deficient and factor B deficient murine plasma was kindly provided by Dr . Marina Botto , Imperial College London . Human blood was obtained from healthy adult donors who had given written , informed consent , as required by the local ethics committee . L-ficolin concentration was determined as previously described [45] . Genomic DNA was prepared using a kit ( Promega ) and MBL2 A/O and X/Y genotypes were determined using fluorescent hybridization probes in a Roche LightCycler [46] . Serum from an individual with a complete deficiency of both C4 genes , C4A and C4B , has been described previously [47] . Nunc Maxisorb microtiter plates were coated with 100 µl of the following reagents: 10 µg/ml mannan ( a control for MBL binding ) , 10 µg/ml zymosan ( a control for CL-11 binding ) , 10 µg/ml N-acetylated BSA ( Promega; a control for ficolin A binding ) , 5 µg/ml of the FCN2-specific mAb GN4 , 10 µg/ml PSA , or formalin-fixed S . pneumoniae D39 ( OD550 nm = 0 . 6 ) in coating buffer ( 15 mM Na2CO3 , 35 mM NaHCO3 , pH 9 . 6 ) . Wells were blocked with 250 µl of 1% ( w/v ) BSA in TBS buffer ( 10 mM Tris-HCl , 140 mM NaCl , pH 7 . 4 ) , then washed three times with 250 µl of TBS with 0 . 05% Tween 20 and 5 mM CaCl2 ( wash buffer ) . Serial dilutions of serum in 100 µl of wash buffer were added and the plates incubated for 90 min at room temperature . Plates were washed as above and bound proteins detected using monoclonal rat anti-mouse MBL-A ( Hycult ) , rat anti-mouse MBL-C ( Hycult ) , rabbit anti-mouse ficolin-A , rabbit anti-human M-ficolin , rabbit anti-human L-ficolin , mouse anti-human H-ficolin , mouse anti-human CL-11 or rat anti-mouse CL-11 mAbs . Secondary antibodies were alkaline phosphatase-conjugates and bound antibody was detected using the colorimetric substrate p-nitrophenylphosphate ( pNPP ) . To measure C3 and C4 activation , Nunc MaxiSorb microtiter plates were coated with 100 µl of: 10 µg/ml mannan ( Promega ) , or formalin-fixed S . pneumoniae D39 ( OD550 nm = 0 . 6 ) in coating buffer . After overnight incubation , wells were blocked with 0 . 1% HSA in TBS then washed with wash buffer . Serum samples were diluted in BBS ( 4 mM barbital , 145 mM NaCl , 2 mM CaCl2 , 1 mM MgCl2 , pH 7 . 4 ) , added to the plates and incubated for 1 . 5 h at 37°C . The plates were washed again , and bound C3b or C4b was detected using rabbit anti-human C3c ( Dako ) or rat anti mouse C4 ( Hycult ) followed by alkaline phosphatase-conjugated goat anti-rabbit IgG or alkaline phosphatase-conjugated rabbit anti rat IgG followed by the colorimetric substrate pNPP . S . pneumoniae D39 were washed twice with TBS and re-suspended in BBS to a concentration of 106 cfu/ml . Two hundred µl of the bacterial suspension was mixed with 10 µl of NHS , WT mouse or complement deficient mouse serum and incubated for 1 h at 37°C . After opsonization , the bacteria were washed twice with wash buffer , re-suspended in wash buffer containing FITC conjugated rabbit anti-human C3c ( Dako ) , mouse anti-human C4dg ( Quidel ) or mouse anti-human C4c ( Santa Cruz ) and incubated for 1 h on ice . Where non-conjugated primary antibodies were used , the pneumococci were washed twice and incubated for a further hour with FITC conjugated anti-mouse IgG ( Dako ) . After two further washes , the bacteria were fixed using 1% w/v paraformaldehyde , and fluorescence intensity measured by FACS ( Becton Dickinson FACS Calibur ) . Polymorphonuclear leukocytes ( PMN ) were isolated from fresh human blood by discontinuous density gradient centrifugation using Histopaque-1119 and Histopaque-1077 , according to the manufacturer's instruction . Leukocytes were washed twice with Hank's balanced salt solution ( HBSS ) containing 1 . 2 mM Ca2+ and 1 . 2 mM Mg2+ , pH 7 . 4 ( Invitrogen ) and re-suspended in HBSS to a concentration of 107 cells/ml . Killing of pneumococci by PMN was estimated by measuring the decrease in viable bacteria over time . Pneumococci were opsonized by incubation with 20% v/v WT or complement deficient murine serum at 37°C for 30 min . 1×106 PMNs were mixed with 105 pre-opsonized or non-opsonized S . pneumoniae D39 in a final volume of 250 µl in HBSS and incubated at 37°C on a rotary mixer . Samples were taken at 0 , 30 , 60 , 120 and 240 min . To determine viable bacteria , samples were serially diluted in HBSS and plated onto blood agar plates . For histological staining , 25 µl samples of the PMN/pneumococci mix were attached to glass slides by centrifugation at 1500×g for 3 min in a Cytospin 2 ( Shanon ) . The slides were air dried for 15 min and stained using the RESTAIN Quick Diff . Kit ( REAGENA ) . The slides were washed with water , air-dried and then mounted in DPX resin and photographed by bright-field microscopy . For Transmission Electron Microscopy ( TEM ) , a PMN/pneumococci mix was centrifuged for 5 min at 250× g . Cells were washed twice with 500 µl of 0 . 1M PBS ( pH 7 . 2 ) and then fixed by re-suspension into 250 µl of 2 . 5% glutaraldehyde in 0 . 1 M PBS ( pH 7 . 2 ) . Fixed PMNs were then examined by TEM . To assess whether serum complement alone can reduce the number of recoverable S . pneumoniae D39 through complement-mediated lysis , bacteria were incubated for 240 min . in 20% and 50% WT human and mouse sera at 37°C on a rotary mixer , samples taken at 0 , 30 , 60 , 120 and 240 min and plated onto blood agar to determine viable bacteria . Ten to twelve week old female MASP-2 and Fcna deficient mice , and their WT littermates were used . Mice were lightly anaesthetized with 2 . 5% ( v/v ) fluothane ( AstraZeneca ) over oxygen ( 1 . 5 to 2 litre/min ) , and 50 µl PBS containing 1×106 cfu of S . pneumoniae D39 was then administered into the nostrils of the mice . The inoculum dose was confirmed by viable count after plating on blood agar . For survival experiments , mice were monitored for clinical signs and culled when they became severely lethargic . This time was recorded as the survival time . To determine bacterial tissue counts , groups of mice were deeply anaesthetized at pre-chosen time intervals and blood was collected by cardiac puncture . Immediately afterwards , the mice were culled by cervical dislocation . Lungs were removed separately into 10 ml of sterile PBS , weighed , and then homogenized in a Stomacher-Lab blender ( Seward Medical ) . Viable counts in lung homogenates and blood were determined by serial dilution in sterile PBS and plating onto agar plates supplemented with 5% ( v/v ) horse blood ( Oxoid ) and incubated for 18 h at 37°C in anaerobic conditions . | Streptococcus pneumoniae is a major human pathogen that causes pneumonia , septicemia and meningitis . The host defense against pneumococci is largely dependent on complement , a system of blood proteins which , when activated , attach to bacteria , targeting them for clearance by phagocytes . There are three routes of complement activation: The classical , lectin and alternative pathways . Limited information is available on the roles of the classical and alternative pathways in fighting pneumococci; the role of the lectin pathway has escaped the attention of previous research . This work demonstrates that the lectin pathway is critical in fighting pneumococcal infection . Of the five different lectin pathway recognition molecules in human serum , only L-ficolin and collectin 11 activate complement on pneumococci . Human mannose-binding lectin ( MBL ) , the best-known lectin pathway pattern recognition molecule , has no role whatsoever in fighting pneumococci . Similarly , in mouse serum , only ficolin A and collectin 11 drive complement activation on S . pneumoniae . Hence , MBL deficient mice are not compromised in pneumococcal infection , while ficolin A deficient mice and mice deficient of the key lectin pathway enzyme MBL-associated serine protease-2 ( MASP-2 ) are exquisitely susceptible to infection . This work explains why MBL deficiency , the most frequent hereditary immune deficiency , does not predispose to pneumococcal disease . | [
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] | [
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"... | 2012 | The Lectin Pathway of Complement Activation Is a Critical Component of the Innate Immune Response to Pneumococcal Infection |
The psychological impact of snakebite on its victims , especially possible late effects , has not been systematically studied . To assess delayed somatic symptoms , depressive disorder , post-traumatic stress disorder ( PTSD ) , and impairment in functioning , among snakebite victims . The study had qualitative and quantitative arms . In the quantitative arm , 88 persons who had systemic envenoming following snakebite from the North Central Province of Sri Lanka were randomly identified from an established research database and interviewed 12 to 48 months ( mean 30 ) after the incident . Persons with no history of snakebite , matched for age , sex , geograpical location and occupation , acted as controls . A modified version of the Beck Depression Inventory , Post-Traumatic Stress Symptom Scale , Hopkins Somatic Symptoms Checklist , Sheehan Disability Inventory and a structured questionnaire were administered . In the qualitative arm , focus group discussions among snakebite victims explored common somatic symptoms attributed to envenoming . Previous snakebite victims ( cases ) had more symptoms than controls as measured by the modified Beck Depression Scale ( mean 19 . 1 Vs 14 . 4; p<0 . 001 ) and Hopkins Symptoms Checklist ( 38 . 9 vs . 28 . 2; p<0 . 001 ) . 48 ( 54% ) cases met criteria for depressive disorder compared to 13 ( 15% ) controls . 19 ( 21 . 6% ) cases also met criteria for PTSD . 24 ( 27% ) claimed that the snakebite caused a negative change in their employment; nine ( 10 . 2% ) had stopped working and 15 ( 17% ) claimed residual physical disability . The themes identified in the qualitative arm included blindness , tooth decay , body aches , headaches , tiredness and weakness . Snakebite causes significant ongoing psychological morbidity , a complication not previously documented . The economic and social impacts of this problem need further investigation .
Snakebite is a significant health issue in the rural tropics . Globally , it has been estimated that at least 421 , 000 envenomings and 20 , 000 deaths occur due to snakebite each year each year , and that these numbers may even be as high as 1 . 8 million envenoming and 94 000 deaths [1] . The highest burden exists in South Asia , Southeast Asia , and sub-Saharan Africa . In Sri Lanka , about 40000 persons were treated for snake bite in government hospitals each year [2] . The actual number of bites is likely to exceed this number , as many of the victims seek traditional forms of treatment . Snakes are feared for their bite associated mortality and morbidity but only six of the 92 snake species in Sri Lanka are medically important . These are the Russell's viper , cobra , the two kraits ( common and Sri Lankan ) , saw scaled viper and hump nosed viper . The Russell's viper , cobra and kraits account for most of the morbidity and mortality . Most studies on snakebite only estimate the numbers of snakebites , acute complications and deaths[3] . There is very little data on the long term physical and psychological consequences experienced by victims of snakebite . This is unfortunate , as most snakebite victims are in the economically productive age group , and the economic impact of any disability is likely to be high . Snakebites are sudden and unexpected , and the element of surprise and the associated threat to life may cause extreme stress and anxiety in the victim . The long term psychological consequences of this , such as , post-traumatic stress disorder , generalized anxiety , avoidance of situations where they could be bitten again , health seeking behaviour and somatisation have not been previously studied . The objective of our study was to assess stress and anxiety: particularly symptoms of anxiety and depression , post-traumatic stress disorder , somatisation and impairment in functioning , at least 12 months following snakebite envenoming .
The Polonnnaruwa district of the North Central Province in Sri Lanka was selected for the study . This is in the dry zone with a predominantly rural agricultural population . The highest numbers of snakebite envenoming in Sri Lanka are reported from this region [3] . Mental health services in this area are poorly developed . The research team had access to an established database of snake bite victims from a previous study conducted in this area . There was a quantitative arm and qualitative arm to the study . In the quantitative arm 200 persons ( cases ) over 18 years of age , with a history of snakebite envenoming which had required treatment with antivenom at least 12 months previously , were randomly selected by the computer from among 296 eligible persons included in a database of 1500 snakebite victims from a previous study conducted in the area . Initial sample size calculation , based on 10% baseline anxiety and depression rate in the community and an expected doubling in the rate of depression and anxiety to 20% in snake bite victims ( at 80% power and 5% significance level ) , showed the need for 90 participants . Allowing for a more than 50% attrition rate , considering the time period since the bite and poor transport infrastructure in these rural areas , we planned to randomize 200 snakebite victims . Letters ( in Sinhala – the North Central Province is mainly inhabited by a Sinhala literate population ) were sent out to those selected inviting them to participate in the study . They were assessed by medical officers using a structured questionnaire on demographic characteristics , circumstances of the snake bite envenoming , hospital stay , perceived severity of the bite , and return to work and functioning . A physical examination was conducted to assess disability related to the snake bite . The following measures were administered to quantify psychological distress: a modified Sinhala version of the Beck depression inventory [4] , Post-traumatic Stress Symptom Scale – Self Report ( PSS-SR ) [5] , the Hopkins symptoms checklist – 25 ( HSCL-25 ) [6] , [7] and the Sheehan Disability Inventory [8] which have all been previously validated and used in Sri Lanka [9] . The psychological scales were administered by psychiatrists with knowledge and experience in administering these tools . Local hospital attendees matched for age , sex , geograpical location and occupation and without a history of snakebite were invited as controls . They were also administered the modified Sinhala version of the Beck depression inventory , a modified Hopkins somatic symptoms checklist and Sheehan Disability Inventory . In addition , focus group discussions were held with snakebite victims to explore perceived long term effects of the snakebite . A total of five focus group discussions were held until data saturation occurred . Each group consisted of 6–10 snake bite victims and was initiated by the same moderator who raised the question of possible long term health effects of the snake bite . The moderator did not participate in the discussion apart from clarifying unclear statements and facilitating the discussion . The group members discussed what they perceived to be effects on their health . The discussions were tape recorded and transcribed by independent evaluators . Informed written consent was obtained from all participants . Those identified to have severe psychological distress were referred to appropriate psychiatric services for further assessment and follow up . Ethical approval was obtained from the Ethics Committee of the Faculty of Medicine , University of Kelaniya , Sri Lanka . Analysis of quantitative data was done using SPSS version 16 . Comparisons between cases and controls were made using non-parametric tests . The Beck's modified depression scale scores were categorized into no depression ( 0–15 ) , mild depression ( 16–24 ) , moderate depression ( 25–32 ) and severe depression ( >32 ) in terms of accepted figures . The established clinically significant item-average cut-off score of ≥1 . 75 for each sub-scale was used for the Hopkins somatic symptoms checklist . The accepted cut off score ≥20 on the PSS-SR was taken as compatible with post traumatic stress disorder . Spearman correlations were used to compare the different symptoms scales and the factors within them . Chi squared test was used where appropriate for categorical variables . Qualitative data were thematically analyzed .
Of the 200 snake bite victims ( 167 males , 33 females ) to whom the letters of invitation were sent , 88 ( 74 males , 14 females ) responded and participated in the study . The mean age of the responders was 41 . 6 ( SD 13 . 7 ) years compared to 37 . 5 ( SD 12 . 7 ) ( P<0 . 013 ) in the non-responders . There was no statistically significant difference in , sex , occupational status , ethnicity , mean duration of hospital stay , treatment with antivenom or severity of reaction to antivenom between responders and non-responders ( Table 1 ) . The majority in both groups were unable to identify the offending snake . The mean depression score in the cases[19 . 1 ( SD 7 . 7 ) ] was significantly higher than that of controls [14 . 4 ( SD 2 . 5 ) ] [p<0 . 001; mean difference 4 . 74 ( 95%CI 3 . 02–6 . 46 ) ] ( Table 2 ) . In terms of these scores , 48 ( 54% ) cases and 13 ( 15% ) controls met criteria for depressive disorder . Similarly the Hopkins symptoms checklist score [38 . 9 ( SD 16 . 3 ) ] in cases was significantly higher than that of controls [28 . 1 ( SD 5 . 8 ) ] [p<0 . 001; mean difference 10 . 735 ( 95% CI 7 . 06–14 . 41 ) ] . The depression subscale scores in the Hopkins checklist showed that 20 ( 23% ) of cases and two ( 2 . 3% ) of controls were depressed . The correlation between the modified Beck depression score and the Hopkins anxiety score ( r = 0 . 728; p<0 . 001 ) and Hopkins depression score ( r = 0 . 856; p<0 . 001 ) were highly significant . On multiple regression analysis none of the variables , namely , age , sex , occupation , duration of hospitalization , ICU admission and adverse reactions to antivenom predicted depression . The mean post-traumatic symptom scale score among cases was 10 . 5 ( SD 12 . 7 ) . Nineteen cases ( 21 . 6% ) met criteria PTSD . The total PTSD score correlated strongly with the disability scores and the depression and anxiety scores ( Table 3 ) . PTSD was a significant predictor of depression on the modified Beck depression score [P = 0 . 004; Odds ratio 9 . 828 ( 95% CI 2 . 1–41 . 8 ) ] . The symptoms contributing most to the PTSD score were avoidance behavior ( r2 = 0 . 845 ) , hypervigilance ( r2 = 0 . 826 ) and physical changes related to hyperarousal ( r2 = 0 . 843 ) . However all the symptoms showed good correlation with the total PTSD score . The mean values of the PTSD measure were significantly higher in females ( 19 . 93 ) compared to males ( 8 . 72 ) [p<0 . 005 , mean difference 11 . 21] . On multiple regression analysis age , sex , occupation , duration of hospitalization , ICU admission and adverse reactions to antivenom did not predict PTSD . The Sheehan disability inventory showed a significant difference between cases and controls ( 13 . 66 vs 2 . 99; p<0 . 001; mean difference 10 . 74; 95% CI 1 . 25–13 . 25 ) . 17% of the cases claimed to have residual physical disability despite there being no external evidence on physical examination . A negative effect on their subsequent employment resulting in less skilled or fewer hours of work was claimed by 24 ( 27% ) of victims; nine ( 10% ) had stopped working after the incident . In comparison , during the preceding three years , ten ( 11 . 9% ) of the control group ( P = 0 . 007 ) had a change of job resulting in less skilled employment or fewer hours of work and three ( 3 . 5% ) ( P = 0 . 07 ) of the control group had stopped work due to various reasons . Various physical symptoms were attributed to the snake envenoming . Five main themes were identified - poor vision , tooth decay , body aches , headaches , weakness and tiredness of the body . Poor vision , body aches and tiredness were the most frequently occurring observations . “My vision has become poorer . It is as if there is a net in front of my eyes …… . ”; “My eye sight fluctuates since this event . One day I can see clearly but on some days my vision is poor . As I'm a teacher I find these problems affecting my work and it's very difficult to teach anymore … . ”; “I am having a thousand problems after the snake bit me . I have arm pain , stomach aches , eye pain , weakness of my legs , poor vision . I work in the fields but do so with great difficulty … . ” . Some interesting rare comments were bordering on overvalued or delusional ideas - “After getting bitten by the snake I feel a foul smell emanating from my sweat . I think this is the snake's venom leaving my body… . ” .
The high prevalence of psychological distress in the study population , including the control group , could at least partly be attributed to social disadvantages experienced by rural communities in developing countries . These were adults ( mean age of 41 years ) , with young families , living in poverty with a daily income of less than US$7 . 50 and often working under difficult conditions in farms and rice fields . The snake bite may be the adverse life event that tips the balance [17] , leading to psychological problems that persist long after the physical recovery . Associations between poverty and depression [10] and suicidal ideation [18] , and even risk of PTSD [19] , [20] have been previously documented . The additive effects of poverty and intimate partner violence in women with PTSD , depression and emotional difficulties have been discussed before [21] . Higher social support seems to predict lower PTSD severity at least for women with cumulative interpersonal trauma [22] . Following the tsunami that affected Sri Lanka in 2004 , PTSD and depression rates were 21% and 16% respectively , 20–21 months after the event [9] . In a study that looked at car crashes , as many as 23% of hospitalised passengers and 11% of hospitalised drivers were shown to have significant levels of stress 18 months after the incident [23] . Following war trauma in a civilian population in Sri Lanka , 27% reported PTSD , 25% major depression , 41% somatization and 26% anxiety disorders [24] , [25] . The unadjusted weighted prevalence rate reported among mass conflict victims for PTSD was 30 . 6% ( 95% CI , 26 . 3%–35 . 2% ) and for depression was 30 . 8% ( 95% CI , 26 . 3%–35 . 6% ) [26] . The PTSD prevalence in our snakebite victims is comparable to the rates seen after the tsunami and car crashes , but lower than that reported following war trauma in Sri Lanka . In contrast , depression symptom scores were higher in snakebite victims . This might be explained by sub-threshold depressive symptoms or somatization , not meeting criteria for serious depressive disorder . However , in our study , at least 16% of victims met criteria for moderate to severe depressive disorder , as opposed to 1% in the control group . The more conservative estimate in the Hopkins depression sub-scale of depressive disorder in 23% of snakebite victims may reflect the true prevalence although it appears to underestimate the morbidity , as the controls too have a lower than expected percentage with depressive symptoms . In psychological terms , a stressful event can be classified as a natural disaster . However , the event for the subject is individual and not collective akin to other natural disasters . The fear of death is very real and can lead to subsequent avoidance and phobic symptoms . Many people are terrified of snakes and the irrational fear called ophidiophobia persists despite most species being non-venomous . Beliefs and myths regarding snakes abound in many societies due to their characteristics such as speed and agility , the bifid tongue , unblinking lidless eyes , ability to renew their skin and inject venom . They have been objects of worship and awe as people attribute wisdom , cunning , power , fertility , sexuality and renewal of life to them , particularly in Africa and the Indian subcontinent [27] . In Sri Lanka too snakes are revered , and particularly the cobra is considered sacred . Stories of protection as well as vengeful attacks by snakes for past atrocities even in a previous birth , based on a belief of re-birth as animals , abound . These beliefs may colour the perceived long term effects of poor vision , weakness and fatigability brought out in the qualitative themes . In cognitive behavioural terms , the snakebite could be a critical incident , acting on existing psychological schemas , triggering negative automatic thoughts leading to anxiety and depression . In Sri Lanka , the incidence of snakebite is highest in the rural , agricultural areas . As most bites occur outdoors , any avoidance behaviour associated with underlying psychological morbidity [16] could result in avoidance of work in the fields or on farms resulting in loss of income . This is compounded by the fact that few psychiatric services are available in these rural areas , and primary care physicians may easily miss any psychological morbidity associated with snakebite . The attrition rate of more than 50% from the sample randomised is a significant limitation of this study . Those who participated in the study were older than the non responders , and we may therefore have ended up with a sample of older victims who were more maladjusted and had assumed a sick role after the envenoming . But even assuming a best case scenario with no morbidity among the non-responders the prevalence of depression would still be around 25% of the total population randomized , demonstrating a major burden of psychological ill health following snake bite . Probably due to our small sample we could also not find any predictors for depression and PTSD . Further exploration of the overall impact of snake bite in the rural tropics and the direct and indirect costs associated with the psychological sequelae and loss of employment is warranted [14] , [28] . | Snakebite envenoming is a neglected public health problem , especially in rural areas of tropical and sub-tropical countries . Little is known about the long term effects , and even less about the possible psychological effects , of snakebites and envenoming . We investigated the possible psychological impact of snakebite in 88 persons who had been envenomed 1 to 4 years ago in a rural agricultural area in Sri Lanka by using accepted measurements of psychological disability and group discussions among victims . 88 persons from the same areas who had not been bitten by a snake , but were of similar age , sex and occupation were also assessed in a similar manner . Compared to those who had not been bitten , snakebite victims had significantly more symptoms suggesting psychological disability , depression and post-traumatic stress . More than a fourth of those bitten claimed that the snakebite caused a negative change in their employment , and 10% had stopped working altogether . 17% claimed to have residual physical disability which they attributed to the bite , although no disability could be detected when they were examined . These findings indicate that snakebite results in ongoing psychological disability even 1 to 4 years after the episode , a complication that has not been previously reported . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
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] | 2011 | Delayed Psychological Morbidity Associated with Snakebite Envenoming |
Mammalian CST ( CTC1-STN1-TEN1 ) participates in multiple aspects of telomere replication and genome-wide recovery from replication stress . CST resembles Replication Protein A ( RPA ) in that it binds ssDNA and STN1 and TEN1 are structurally similar to RPA2 and RPA3 . Conservation between CTC1 and RPA1 is less apparent . Currently the mechanism underlying CST action is largely unknown . Here we address CST mechanism by using a DNA-binding mutant , ( STN1 OB-fold mutant , STN1-OBM ) to examine the relationship between DNA binding and CST function . In vivo , STN1-OBM affects resolution of endogenous replication stress and telomere duplex replication but telomeric C-strand fill-in and new origin firing after exogenous replication stress are unaffected . These selective effects indicate mechanistic differences in CST action during resolution of different replication problems . In vitro binding studies show that STN1 directly engages both short and long ssDNA oligonucleotides , however STN1-OBM preferentially destabilizes binding to short substrates . The finding that STN1-OBM affects binding to only certain substrates starts to explain the in vivo separation of function observed in STN1-OBM expressing cells . CST is expected to engage DNA substrates of varied length and structure as it acts to resolve different replication problems . Since STN1-OBM will alter CST binding to only some of these substrates , the mutant should affect resolution of only a subset of replication problems , as was observed in the STN1-OBM cells . The in vitro studies also provide insight into CST binding mechanism . Like RPA , CST likely contacts DNA via multiple OB folds . However , the importance of STN1 for binding short substrates indicates differences in the architecture of CST and RPA DNA-protein complexes . Based on our results , we propose a dynamic DNA binding model that provides a general mechanism for CST action at diverse forms of replication stress .
Although DNA replication must occur rapidly and with high fidelity , the replisome frequently encounters obstacles such as DNA damage or repetitive sequence that cause the replication fork to stall . Since stalled forks can lead to double strand breaks and genomic instability , multiple pathways exist to ensure their resolution [1 , 2] . Telomeres pose a particular challenge to the replication machinery due to their repetitive G-rich sequence and the inability of DNA polymerase to completely replicate the DNA 5’ terminus [3–5] . To ensure telomeres are duplicated efficiently , the replication process occurs in several distinct steps [3 , 6 , 7] and involves a number of ancillary proteins [8–11] . First , the repetitive dsDNA is duplicated by the replisome with assistance from various accessory factors . Next , the chromosome ends are processed by nucleases to form a single-stranded overhang on the 3’ G-rich strand ( termed the G-overhang ) . In telomerase positive cells , the G-overhang is then extended by telomerase . Finally , much of the elongated overhang is converted to duplex DNA by DNA polymerase alpha ( pol α ) in a process known as C-strand fill-in . This leaves a short G-overhang that is then bound by telomere proteins . CST is a protein complex that binds ssDNA and promotes telomere replication in a wide range of eukaryotes [12–16] . Budding yeast CST ( Cdc13-Stn1-Ten1 ) binds the G-overhang where it protects the telomere , recruits telomerase and mediates C-strand fill-in [17–20] . Mammalian CST ( CTC1-STN1-TEN1 ) is less important for telomere-end protection but it functions both in telomere duplex replication and C-strand fill-in [21–25] . It is also proposed to limit telomerase action , perhaps by competing for binding to the telomere protein TPP1 [26 , 27] . CST has additional genome-wide roles that are just starting to be appreciated [13 , 24 , 28–31] . In humans , CST facilitates recovery from various forms of replication stress throughout the genome . It promotes activation of dormant or late firing origins in response to replication fork stalling [24] and enhances viability when cells are treated with drugs that block replication fork progression [30] . Mutations in CTC1 cause the diseases Coats plus and dyskeratosis congenita [32–34] . The telomeric and non-telomeric roles of CST are likely to underlie the severity of these diseases . Although the mechanism of CST action is still unclear , multiple studies indicate a link to pol α . Mammalian CTC1 and STN1 were originally identified as Alpha Accessory Factor ( AAF ) , a factor that co-purified with pol α and enhanced its processivity and affinity for ssDNA templates [35 , 36] . CST and pol α have since been shown to interact in yeast , plants and mammals [20 , 21 , 37 , 38] . Xenopus CST stimulates DNA priming by pol α on ssDNA [39] while Candida CST enhances primase activity and primase to polymerase switching [40] . CST exhibits notable structural similarities to Replication Protein A ( RPA ) the eukaryotic ssDNA binding protein that directs the assembly of multi-protein complexes needed for DNA replication , recombination and repair ( Fig 1A ) [23] . RPA has three subunits ( RPA1 , RPA2 and RPA3 ) that together harbor six OB ( oligonucleotide-oligosaccharide binding ) folds ( Fig 1A ) [41 , 42] . Four of the OB folds participate in DNA binding . Because RPA has multiple DNA binding sites , individual OB folds can undergo rapid dissociation and re-association without causing the protein to fall off the DNA [43 , 44] . This dissociation and re-association of OB folds underlies RPA function as it makes binding dynamic and enables RPA to diffuse along DNA to melt DNA structure or load and unload proteins needed for replication , recombination or repair [45] . Like RPA , CST appears to harbor OB folds in all three subunits and X-ray crystallography indicates striking structural similarity between STN1-TEN1 and RPA2-RPA3 dimers [46–48] . The structural conservation encompasses the OB-fold and winged helix domains and the dimerization interface . The large subunits of RPA and CST appear less well conserved . Although RPA1 and Cdc13 from budding yeast each harbor 4 OB folds , Cdc13 needs only one OB fold for high affinity binding [42 , 49] . Moreover , Cdc13 dimerizes through its N-terminal OB fold to form a DNA pol α binding surface , whereas RPA1 does not self-associate [50] . In mammalian cells , Cdc13 is replaced by CTC1 but the two proteins share little sequence identity and the extent of structural or functional conservation is unclear [37] . Protein threading programs ( Phyr2 and HHpred ) predict 5–6 OB folds in human CTC1 with the three most C-terminal folds resembling those of RPA1 ( Fig 1A ) . In vitro studies have revealed an additional parallel between RPA and human CST as in each case high affinity DNA binding requires formation of the three protein complex [23 , 26 , 41 , 42] . The structural similarities between RPA and CST raise the possibility that dynamic DNA binding through multiple OB folds may also contribute to CST function . Since so little is known about CST mechanism of action and the relationship between DNA binding and CST function , we set out to analyze how reduced DNA binding affects CST activity at telomeres and elsewhere in the genome . We describe a STN1 OB fold mutant that preferentially affects in vitro binding to short DNA substrates . In vivo , the mutant can substitute for wild type STN1 in some aspects of CST function but other aspects are impaired . DNA binding studies indicate that , like RPA , CST appears to contact DNA via multiple OB folds and to have distinct modes of binding . However , we also provide evidence that the organization of OB-fold engagement by CST is quite different .
To generate the STN1 OB-fold mutant ( STN1-OBM ) we changed three residues ( W89A , R139L , Y141A ) that are conserved between STN1 and the OB fold of RPA2 and which either directly contact , or lie very close to DNA in RPA crystal structures ( Fig 1B ) [41 , 51] . The W89A and Y141A mutations were chosen because the equivalent mutations in mouse STN1/AAF-44 reduced DNA binding by ~60% in pull-down assays with biotin-labeled poly-dC [36] Co-immunoprecipitation and tandem affinity purification experiments verified that the STN1 mutant retained the ability to form a complex with CTC1 and TEN1 ( Fig 1C and 1D ) . In initial experiments , we co-expressed FLAG-tagged STN1 or STN1-OBM with HA-CTC1 in a previously characterized HeLa cell line over-expressing TEN1 [30] . When STN1-OBM was immunoprecipitated from whole cell lysate , both CTC1 and TEN1 co-purified ( Fig 1C ) . We also generated recombinant CST complexes containing wild type STN1 ( CST ( WT ) ) or STN1-OBM ( CST ( STN1-OBM ) ) by co-infecting insect cells with baculovirus encoding FLAG-tagged CTC1 , untagged TEN1 and His-tagged STN1 or STN1-OBM . Protein complexes were affinity purified on nickel resin followed by FLAG beads ( Fig 1D ) and again CTC1 and TEN1 co-purified with STN1-OBM . We next examined how STN1-OBM affects the ability of CST to bind a range of DNA substrates . As the affinity of CST for short versus long substrates seems to depend on DNA sequence [26] , we monitored binding of CST ( WT ) and CST ( STN1-OBM ) to telomeric and non-telomeric oligonucleotides of various lengths ( Fig 1E and 1F and Table 1 ) . When we used electrophoretic mobility shift assays ( EMSA ) to compare binding of CST ( WT ) and CST ( STN1-OBM ) to 48 nt substrates , the two complexes appeared to bind both non-telomeric ( NonTel-48 ) and telomeric G-strand ( TelG-48 ) DNA with similar affinity . However relative to CST ( WT ) , the CST ( STN1-OBM ) ) bound less efficiently to the 36 nt non-telomeric ( NonTel-36 ) and the 18 nt telomeric G-strand ( TelG-18 ) substrates . Neither complex bound equivalent concentrations of the 18 nt non-telomeric oligonucleotide ( NonTel-18 ) or dsDNA ( Fig 1E ) [23] . These results suggest that the STN1-OBM preferentially affects binding to short substrates . Note , we refer to TelG-18 as a short substrate because CST has very low affinity for DNA with fewer telomeric repeats , e . g . TelG-12 [26] . Our results also confirm that CST binds both telomeric and non-telomeric DNA but that telomeric DNA is preferred when substrate length is short [26] . To examine the in vivo effects of STN1 OB fold mutation , we generated HeLa cells that stably express FLAG-tagged STN1-OBM ( Fig 2A and S1A Fig ) by introducing an shRNA-resistant STN1-OBM cDNA into a previously characterized HeLa cell line expressing STN1 shRNA ( shSTN1 ) [24 , 25] . A cell line expressing FLAG-tagged shRNA-resistant wild type STN1 ( STN1-Res ) was previously made in the same manner [24] . In initial experiments , we asked if STN1-OBM could rescue the increase in anaphase bridges that occurs after STN1 depletion [24] . STN1-OBM cells and a series of control cells ( shSTN1 , STN1-Res and shNT , a non-target shRNA control ) were arrested in mitosis with nocadozole , released for 45–60 min , fixed and scored for the number of anaphase cells with DAPI-stained bridges ( Fig 2B ) . As previously described , depletion of STN1 caused an increase in bridges and this was rescued by expression of sh-resistant wild type STN1 [24] . In contrast , expression of sh-resistant STN1-OBM did not rescue bridge formation but instead further increased the fraction of anaphase cells with bridges . The reason for the higher level of bridges in the STN1-OBM cells relative to the shSTN1 cells is unclear but a possible cause is that STN1-OBM replaces residual endogenous STN1 in CST complexes . Overall , the inability of STN1-OBM to rescue the anaphase bridge phenotype indicates that STN1-OBM cannot substitute for wild type STN1 in some aspects of CST function . Anaphase bridges can have a number of causes including telomere-to-telomere fusion and the presence of unresolved replication intermediates either at telomeres or elsewhere in the genome [53 , 54] . Thus , to ask more specifically whether STN1-OBM affects the telomeric roles of CST , we looked for changes in telomere structure . Metaphase spreads from STN1-OBM and control cells were hybridized with telomere probe and examined for telomere loss , telomere fusions or other abnormal telomere signals . As previously reported , we did not observe an increase in telomere loss or telomere fusions in the shSTN1 and STN1-Res cells [24] ( S1B Fig ) . This was also true for the STN1-OBM cells ( S1B Fig ) , indicating that the anaphase bridges caused by STN1-OBM expression are unlikely to be caused by telomere fusions . However , relative to the STN1-Res control , the STN1-OBM cells showed a large increase in individual chromatids exhibiting Multiple Telomeric FISH Signals ( MTS ) ( Fig 3A ) . As expected , the shSTN1 cells also showed an increase in MTS but it was lower than in the STN1-OBM cells . Again this may reflect the displacement of residual endogenous STN1 with STN1-OBM in CST complexes . Past studies have shown that MTS arise after fork stalling during replication of the telomere duplex [8] and they occur after depletion of the various factors needed for telomere replication , including CST [8 , 25] . In particular , STN1 depletion slows replication through the telomere duplex and causes the appearance of MTS [25] . We therefore conclude that STN1-OBM is unable to rescue the deficiency in telomere duplex replication caused by STN1 depletion . We next asked if STN1-OBM affects telomere length or G-overhang structure . Genomic DNA was isolated from STN1-OBM or control cells and telomere restriction fragments were examined by Southern blotting or in-gel hybridization to monitor telomere length ( S1C Fig ) . This analysis revealed that telomeres of shSTN1 , STN1-Res and STN1-OBM cells were very similar in length , thus confirming our previous finding that telomere length in HeLa cells is largely unaffected by STN1 knockdown [25] and indicating that STN1-OBM has dominant negative effect . We then used an in-gel hybridization assay to ask if STN1-OBM affects G-overhang structure . Restriction digested DNA was separated briefly in agarose gels and hybridized with a probe to the telomeric G-strand under non-denaturing conditions ( Fig 3B ) . The DNA was then denatured and re-hybridized with the same probe . Quantification of the overhang signal relative to total telomeric DNA revealed the expected increase in overhang amount in the STN1-depleted cells ( Fig 3C ) . This increase has previously been shown to result from inefficient C-strand fill-in following telomerase extension [21 , 25] . Given that STN1-OBM affects binding to telomeric G-strand DNA in vitro ( Fig 1E ) and telomere duplex replication in vivo ( Fig 2 ) , we anticipated that the STN1-OBM cells would also have a deficiency in C-strand fill-in . However , to our surprise we found that STN1-OBM cells had normal length overhangs ( Fig 3C ) implying that the mutant STN1 was able to rescue C-strand fill-in . G-overhang length is determined by a number of activities that occur at specific stages in the cell cycle . Overhangs are elongated in S-phase as a result of G-strand synthesis by telomerase and C-strand resection by nuclease [6 , 7] . They are then returned to their original length in late S/G2 via C-strand fill-in by DNA pol α [25] . Given this balance between activities , it was possible that the normal length overhangs in the STN1-OBM cells result from decreased G-strand extension in S-phase in combination with decreased C-strand fill-in during late S/G2 . To investigate this possibility , we examined G-overhang length dynamics during the cell cycle . Cells were synchronized in G1/S with a double thymidine block , released into S-phase and harvested at intervals as they passed through mid S-phase , G2/M and back into G1 ( Fig 4A and S2A Fig ) . Following DNA isolation , relative overhang length was examined by in-gel hybridization as described above ( Fig 4B and 4C ) . Quantification of the overhang signal indicated that the STN1-Res cells showed the expected increase in overhang abundance as they transitioned from G1 ( 0 hr ) into mid S-phase ( 6 hrs ) [6 , 7 , 25] . The overhang signal then declined due to C-strand fill-in as the cells transitioned into G2 ( 8 hrs ) and G1 of the next cell cycle ( 10–12 hrs ) [25 , 55] . Interestingly , the pattern of overhang elongation and shortening in the STN1-OBM cells was indistinguishable from that seen with the control STN1-Res cells indicating that STN1-OBM does not affect overhang elongation or C-strand fill-in . In contrast , the shSTN1 cells exhibited the expected delay in overhang shortening in late S/G2 reflecting the deficiency in C-strand fill-in [25] . Thus although STN1-OBM affects telomere duplex replication , it does not appear to affect C-strand fill-in by DNA pol α . Several studies have shown that STN1 can interact with the shelterin protein TPP1 [26 , 56] , suggesting that this interaction might be important for recruiting CST or stabilizing CST binding at the telomere . Given that OB folds can mediate protein-protein interactions as well as DNA binding [42] , we considered the possibility that the in vivo effects of STN1-OBM expression might reflect decreased binding of CST to TPP1 . To test for a disruption in the TPP1-STN1 interaction , we transfected 293T cells with constructs encoding FLAG-tagged STN1 or STN1-OBM and HA-mCherry tagged TPP1 [57] and monitored co-immunoprecipitation of TPP1 with STN1 . When TPP1 was precipitated with antibody to HA , Western blot analysis showed that the STN1 and STN1-OBM co-precipitated with equivalent efficiency ( Fig 4D ) . We therefore conclude that STN1-OBM retains the ability to bind TPP1 . We also tested whether STN1-OBM disrupts binding to DNA pol α , the only other known CST binding partner [21 , 58] . 293T cells were transfected with constructs encoding TEN1 , FLAG or Myc-tagged CTC1 and FLAG-STN1 or FLAG-STN1-OBM , and CST was then precipitated from extracts with FLAG antibody . Western blot analysis of the immunoprecipitates showed that pol α co-precipitated with FLAG-STN1 only if both CTC1 and STN1 were overexpressed ( S2B Fig ) . However the level of pol α precipitation was similar with CST ( WT ) and CST ( STN1-OBM ) , indicating that STN1-OBM does not prevent CST from binding to pol α ( Fig 4E and S2B Fig ) . Our finding that C-strand fill-in is unaffected by STN1-OBM ( Figs 3B and 4C ) provides further support for a functional interaction between pol α and CST ( STN1-OBM ) , Since the above studies indicate that STN1-OBM has selective effects on CST function , we next examined whether the mutant affects the response to genome-wide replication fork stalling . In initial experiments , we asked if STN1-OBM could substitute for wild type STN1 to maintain cell viability after HU ( hydroxyurea ) treatment . STN1-OBM and control cells were treated with 2 mM HU for 0–24 hrs , allowed to recover for 24 hrs then cell viability was monitored by MTT assay ( Fig 5A ) . As observed previously , STN1 depletion increased sensitivity to HU [30] . However , wild type STN1 ( STN1-Res ) and STN1-OBM rescued this sensitivity to an equal extent , indicating the mutant was sufficient to allow CST function in recovery from prolonged fork stalling . To further explore the effect of STN1-OBM on recovery from fork stalling , we performed DNA fiber analysis to determine if the mutant can substitute for endogenous STN1 to promote origin firing after HU treatment . Cells were labeled with IdU ( iododeoxyuridine ) for 15 minutes , treated with HU for two hours then released into media containing CldU ( chlorodeoxyuridine ) for 60 min ( Fig 5B ) . The cells were then collected , lysed and the DNA fibers spread on silanized slides by hydrodynamic flow [59] . The fibers were stained with antibody to IdU and CldU then visualized by confocal microscopy to score the replication events ( Fig 5B–5D and S3 Fig ) . As observed previously , the HU-treated shSTN1 cells exhibited fewer green-only ( CldU-only ) tracks than the shNT and STN1-Res control cells [24 , 30] , indicating that STN1 depletion caused a decrease in new origin firing after HU release . In contrast , the HU-treated STN1-OBM cells exhibited a similar number of green-only tracks to the control cells . The frequency of other replication events was also similar ( S3 Fig ) . We therefore conclude that the STN1-OBM can substitute for wild type STN1 to promote new origin firing . Overall , our results indicate that STN1-OBM does not affect the capacity of CST to aid in the restart of replication following exogenous replication stress . This is in direct contrast to the inability of STN1-OBM to rescue the effects of endogenous stress as seen by the increase in anaphase bridges and MTS in unchallenged STN1-OBM cells . Our finding that STN-OBM affects only specific aspects of CST function is analogous to what has been observed for certain RPA OB-fold mutants , which support DNA replication but are defective for DNA repair [60 , 61] . These mutants cause only a small decrease in overall affinity of RPA for ssDNA and the deficit in repair is thought to result from a change in the dynamics of RPA binding through its multiple OB folds [45 , 61] . The structural similarities between CST and RPA suggest that CST function could also rely on dynamic binding using multiple OB folds . We therefore set out to explore the extent to which RPA binding can be used as a paradigm for understanding CST activity and the in vivo separation of function observed with STN1-OBM . As a first step , we revisited the effect of STN1-OBM on DNA binding by using filter binding assays to quantify the affinity of CST ( WT ) and CST ( STN1-OBM ) for telomeric and non-telomeric substrates of various lengths ( Fig 6A , 6C and S4 Fig ) . CST purified from insect cells was incubated with 32P-labeled DNA then the DNA-protein complexes were separated from free DNA by filtration through a sandwich of nitrocellulose and HyBond membrane . The bound versus free DNA was quantified and used to calculate the apparent dissociation constant ( Kd , app ) . Despite the different approach used to separate bound from free DNA in the filter binding and the original gel shift assay ( Fig 1E ) , the results of the two assays were qualitatively similar . The filter binding indicated that CST ( WT ) and CST ( STN1-OBM ) bound the 48 nt telomeric and non-telomeric substrates with a similar Kd , app while binding to TelG-18 was decreased for CST ( STN1-OBM ) relative to CST ( WT ) ( Fig 6A and 6C ) . Thus , the filter binding analysis again indicated that STN1-OBM preferentially affects binding to short DNA substrates . However the analysis also revealed that the overall decrease in Kd , app for CST ( STN1-OBM ) binding to TelG-18 was only 2–3 fold . When gel shift assays were used to examine CST ( STN1-OBM ) binding to the TelG-18 and NonTel-36 substrates a substantial amount of DNA was seen to migrate between the bands corresponding to free DNA and CST-bound DNA ( Fig 1E ) . This observation suggested that the DNA-protein complexes were dissociating and hence the decrease in Kd , app for CST ( STN1-OBM ) might reflect less stable binding . To test this possibility , we measured the rate of CST ( WT ) and CST ( STN1-OBM ) dissociation ( t½ ) from selected substrates . CST complexes were bound to 32P-labeled oligonucleotide , challenged with an excess of the corresponding cold oligonucleotide for various times and the remaining labeled DNA/protein complex was quantified by filter binding . This experiment revealed that CST ( STN1-OBM ) dissociated from the labeled TelG-18 and NonTel-36 1 . 6–2 . 6-fold faster than CST ( WT ) whereas dissociation from TelG-48 and NonTel-48 was essentially the same ( Fig 6B and 6C ) . We therefore conclude that the STN1-OB fold acts to stabilize CST binding to short ssDNA substrates . The 2–3 fold decrease in affinity of CST ( STN1-OBM ) for TelG-18 resembles the modest decrease in RPA affinity for ssDNA that has been observed after mutation of individual OB folds [60 , 62] . In the case of RPA , the small effect on overall binding affinity reflects the presence of multiple DNA binding domains within the complex such that disruption of one binding domain has a small effect on the macroscopic affinity constant . Thus , the observed decrease in CST ( STN1-OBM ) binding fits with the model that CST also engages DNA via multiple DNA binding domains . Given the six predicted OB folds in CTC1 , we anticipate that these multiple DNA binding domains correspond to the STN1 OB fold plus some or all of the OB folds in CTC1 . While CST appears to resemble RPA in terms of subunit composition and utilization of multiple OB folds for DNA binding , our finding that CST ( STN1-OBM ) destabilizes binding to short oligonucleotides suggested a significant difference in how the two complexes bind short DNA substrates ( Fig 6C ) . RPA binds DNA in a 5’ to 3’ direction with the OB-folds of RPA1 contacting DNA towards the 5’ end and providing the highest affinity binding sites [41 , 62] . As a result , OB-A and OB-B of RPA1 provide the only contacts to an 8 nt substrate . OB-A , -B and–C of RPA1 contact substrates of 12–23 nt but RPA2 ( the STN1 equivalent ) only contacts longer substrates of ~30 nt [41 , 42] . Consequently , mutations in RPA2 OB-D affect binding to long rather than short ssDNA [60 , 62] . Our finding that STN1-OBM destabilizes binding to short ( e . g . TelG-18 ) but not long ( TelG-48 & NonTel-48 ) substrates ( Fig 6C ) suggested that , unlike RPA2 , STN1 directly engages the DNA of short substrates to stabilize binding . To further explore this possibility , we used photo-crosslinking to explore the proximity of individual CST subunits to the 5’ or 3’ ends of 18 or 48 nt TelG oligonucleotides . CST ( WT ) and CST ( STN1-OBM ) were incubated with 32P-labeled TelG-18 or TelG-48 that had a photoactivatable 4-thiothymidine ( s4T ) at the third nucleotide from the 5’ or 3’ end ( Fig 7A and S5 Fig ) . The DNA-protein complexes were cross-linked by irradiation with UVA and then separated in a SDS-polyacrylamide gel . The gel was scanned by phosphorimager to determine whether CTC1 , STN1 or TEN1 had been cross-linked to the labeled DNA . Equivalent UV-irradiated samples separated in the same gel were used for Western blot analysis to determine the positions of uncross-linked CTC1 , STN1 and TEN1 . The low level of cross-linking precluded detection of the cross-linked DNA-protein complexes by Western blot . Additional reactions that had not been subject to cross-linking were analyzed by EMSA to monitor DNA binding . As shown in Fig 7B , the s4T residues did not significantly alter CST ( WT ) or CST ( STN1-OBM ) binding to either substrate . Analysis of the crosslinking products obtained with CST ( WT ) and 5’- or 3’-s4T TelG-18 revealed labeled bands that migrated at positions expected for CTC1 ( ≥130 kD ) and STN1 ( >43 kD ) ( Fig 7C ) indicating cross-linking to either substrate . However , cross-linking of STN1 relative to CTC1 was less efficient with the 5’-s4T TelG-18 , suggesting that STN1 was positioned closer to the DNA 3’ end . It was not possible to tell if TEN1 was cross-linked to either substrate because TEN1 migrated in the same region of the gel as the uncross-linked DNA . Thus , bands corresponding to TEN1-TelG-18 may be obscured by the heavy signal from the uncross-linked DNA . Overall , the results indicate that binding of CST to a short 18 nt substrate positions the DNA in close proximity to STN1 . Comparison of the cross-linking products obtained with the 3’ modified TelG-18 and CST ( WT ) or CST ( STN1-OBM ) revealed that cross-linking to STN1-OBM was reduced relative to wild type STN1 . This finding indicates that the contacts between STN1 and DNA are altered by STN1-OBM . Analysis of the products obtained with CST ( WT ) bound to TelG-48 revealed that only CTC1 was reproducibly cross-linked to the 5’-s4T substrate . In contrast , the 3’-s4T substrate crosslinked to all three CST subunits . CTC1 cross-linked more efficiently than STN1 or TEN1 and the level of TEN1 cross-linking was somewhat variable ( Fig 7D ) ( note: cross-linking of TEN1 to TelG-48 retards TEN1 migration enough for the band from the cross-linked product to become visible above the uncross-linked DNA ) . The cross-linking of STN1 and TEN1 to the 3’-s4T substrate but not the 5’-s4T substrate indicates that both subunits must be in close proximity to the DNA 3’ terminus but not the 5’ terminus . Examination of the photo-products obtained with of CST ( STN1-OBM ) bound to 3’-s4T TelG-48 revealed less cross-linking to STN1 and TEN1 relative to CST ( WT ) but CTC1 photoproducts were still formed , again indicating that STN1-OBM alters how STN1 contacts DNA . Taken together the above results demonstrate that CST ( WT ) binds long substrates with the DNA 3’ end positioned close to the CTC1-STN1-TEN1 interface while the 5’ end only contacts CTC1 . We therefore infer that , CST binds DNA in a similar orientation to RPA: i . e . with the large subunits of each complex contacting DNA near the 5’ end and the two smaller subunits positioned at the 3’ end . However , our data indicate that the identity of the binding sites used to engage short DNA substrates differs between CST and RPA . For CST , the binding sites lie close to the interface between CTC1 , STN1 and TEN1 , they engage DNA toward the 3’ end , and STN1 plays an important role in stabilizing the interaction . For RPA , the primary binding sites for short substrates are OB-A and OB-B of RPA1 and these engage DNA at the 5’ end . Thus , despite sharing some common structural features CST and RPA engage DNA quite differently . In addition to addressing the architecture of CST-DNA complexes , the in vitro cross-linking studies combine with the analysis of DNA binding affinity start to explain the in vivo separation of function observed with STN1-OBM cells . Our results show that the STN1 OB-fold mutation alters the interaction between STN1 and ssDNA and this translates into altered binding of CST to some but not all DNA substrates . In vivo , CST is likely to encounter DNA substrates of varied length and structure as the complex helps resolve a wide range of replication problems at telomeres and genome-wide . Thus , similar to what has been observed for RPA OB-fold mutants [60 , 61] , the altered DNA binding caused by STN1-OBM is likely to impair the ability of CST to bind and mediate the resolution of only a subset of replication intermediates .
Here we describe a series of in vivo and in vitro experiments that address the mechanism of CST action at telomeres and elsewhere in the genome . We show that a STN1-OB-fold mutant ( STN1-OBM ) which preferentially decreases affinity of CST for short ssDNA substrates is competent for some aspects of CST function but deficient in others . The effects of STN1-OBM do not align with the telomeric versus non-telomeric roles of CST , but instead separate out the different aspects of CST function both during telomere replication and in genome-wide replication rescue . At telomeres , STN1-OBM cells are competent for C-strand fill-in following telomerase action but they exhibit increased MTS which are indicative of deficiencies in the earlier process of telomere duplex replication . STN1-OBM cells are also competent to restart replication via new origin firing following exogenous genome-wide replication stress . However , STN1-OBM is not able to prevent the accumulation of anaphase bridges during mitosis . The latter finding indicates a deficiency in genome-wide resolution of endogenous replication stress because the anaphase bridges caused by CST depletion occur at both telomeric and non-telomeric loci [27 , 30] . Our findings underscore the importance of CST for multiple processes associated with telomere replication and genome-wide replication rescue . They also strongly suggest that different DNA binding transactions are needed for CST to resolve different forms of replication stress with a subset of these transactions being disrupted by STN1-OBM . While STN1-OBM did not inhibit interactions with TPP1 or pol α ( Fig 4 ) , it is possible that STN1-OBM disrupts CST interaction with as yet unidentified partner proteins . If this is the case , the interaction of STN1 with such proteins might provide an additional mechanism to target CST to its various sites of action within the genome . Our in vitro DNA binding studies using CST ( WT ) and CST ( STN1-OBM ) provide new insight into the mechanism of mammalian CST binding to ssDNA . Past studies provided conflicting information concerning the sequence specificity of CST binding [23 , 26] . We now confirm that human CST binds long ( 48 nt ) substrates with little sequence specificity , however sequence identity is important for binding to short ( 18 nt ) substrates as the telomeric G-strand substrate TelG-18 is bound with high affinity while binding to the non-telomeric substrate NonTel-18 is undetectable . We also provide evidence that human CST harbors multiple DNA binding domains . The STN1-OB fold comprises one of these domains and based on structure prediction , we suggest that OB folds in CTC1 comprise the others . Since CST only bound the 18 nt substrate that had the sequence of telomeric G-strand DNA ( Fig 1 ) , the domain ( s ) that bind short oligonucleotides ( i . e . the STN1 OB fold or an adjacent OB fold in CTC1 ) must provide important determinants for sequence-specific binding . Given that long substrates ( telomeric and non-telomeric ) are bound with higher affinity than short substrates and their binding is less affected by STN1-OBM , it seems likely that these substrates contact additional DNA-binding domains beyond those used to contact short substrates . The known structural similarity between STN1-TEN1 and RPA2-RPA3 , together with the likely presence of multiple OB folds in CTC1 , had previously suggested an RPA-like binding mechanism whereby mammalian CST contacts DNA via multiple OB folds . However , this was not a foregone conclusion because S . cerevisae CST binds DNA through one high affinity binding site in Cdc13 [49] . While our work supports the multiple OB fold binding mechanism for mammalian CST , it also reveals significant differences between CST and RPA in the contributions made by individual subunits during binding to ssDNA . For RPA , the only binding sites for short substrates correspond to the OB folds of RPA1 that bind proximal to the DNA 5’ end [41 , 42] . These OB folds also comprise the highest affinity binding sites . However , for CST , both CTC1 and STN1 contact short DNA substrates and STN1 , which binds near the DNA 3’ end , is necessary to stabilize binding . These findings imply that the high affinity binding sites in CST are contributed by STN1 and CTC1 and they interact with DNA towards the 3’ end . While this architecture differs from that of RPA , it is well suited for CST to bind a telomeric 3’ overhang . Despite the above differences between the two protein complexes , RPA can still be used as a model to help us understand the relationship between CST function and its mechanism of DNA binding . The ability of RPA to act as a hub that directs the sequential loading and unloading of partners such as Rad51 and Rad52 or SV40 T-antigen and pol α stems from the dynamic nature of RPA binding to ssDNA [41 , 44 , 63] . Because RPA utilizes 4 OB-folds to bind DNA , individual OB folds can undergo rapid microscopic dissociation and re-association from the DNA without causing the whole protein to dissociate [43 , 44] . Instead the rapid dissociation and re-association of individual OB folds is what enables RPA to diffuse along DNA to melt DNA structure or load and unload partner proteins [45] . Given that mammalian CST is likely to bind DNA via a similar number of OB-folds , it is possible that CST binding is also dynamic . If so , microscopic dissociation of individual OB folds from ssDNA could enable CST to engage or disengage interaction partners from the DNA ( Fig 7E ) . Like the CST complex from Candida glabrata , mammalian CST might also be able to resolve unwanted DNA structure such as G quadruplexes ( G4 ) [64] . The dynamic binding model for CST action is appealing because it can explain why CST is involved in multiple steps during telomere replication and in the resolution of diverse forms of replication stress . It can also explain many of the phenotypes of CST depletion . For example , during telomere replication , CST might aid in removal of G4 structure from the lagging strand during replication of the duplex DNA and it may engage pol α on the G-overhang to initiate C-strand fill-in following telomerase action . The role in G4 structure removal could explain why STN1 depletion leads to a slowing of telomere duplex replication with formation of MTS . Likewise , the role in pol α engagement could explain why C-strand fill-in is disrupted despite pol α remaining associated with the telomere [21 , 25] . The ability of CST to engage pol α to initiate DNA synthesis at dormant or late firing origins could also explain why STN1 depletion inhibits replication restart after genome-wide replication fork stalling . Moreover , resolution of DNA structure at G-rich or regions of repetitive sequence could underlie the role of CST in resolving endogenous replication stress at non telomeric loci [27 , 30 , 31] . While current models for CST function have focused on the regulation of DNA pol α , the large size of CTC1 suggests that CST will have many interaction partners . Thus , mammalian CST may well direct the actions of additional proteins involved in the resolution of replication stress . A broader understanding CST function will require the identification of these proteins and analysis of how CST modifies their ability to engage with stalled forks , replication origins or other replication intermediates . If having multiple DNA binding domains and a dynamic DNA binding mechanism is so important for CST function in mammals , one has to ask why S . cerevisiae Cdc13 uses only one OB fold to bind DNA [49] and S . pombe appears to lack a Cdc13/CTC1 subunit [65] . One possibility is that the multiple DNA binding domains necessary for dynamic binding are provided through dimerization or alternative subunit stoichiometries such as those found in S . cerevisiae and C . glabrata [50 , 64] . An alternative answer could lie in the division of labor between CST and RPA and how this has evolved between organisms . In S . pombe , RPA cooperates with the helicase Pif1 to help resolve G4 structures at lagging strand telomeres [66 , 67] and a simple Stn1/Ten1 complex appears sufficient to regulate telomerase to pol α switching for C-strand fill-in [65 , 68] . Thus , a full CST complex with dynamic DNA binding properties may be unnecessary for telomere maintenance . Perhaps a CST complex is also superfluous for genome-wide replication rescue because S . pombe RPA has adapted to function in these processes .
HeLa 1 . 2 . 11 STN1 knockdown ( clone shSTN1-7 ) , shSTN1 rescue ( STN1-Res ) , control non-target ( clone shNT-3 ) and TEN1 overexpressing cell lines were as described previously [24 , 25 , 30] . To create the STN1-OBM cells , the three amino acid mutations ( W89A , R139L and Y141A ) were introduced by PCR mediated mutagenesis into the shRNA-resistant FLAG-STN1 allele previously used to make the shSTN1-Res cells [24] . shSTN1 cells were transfected with retrovirus encoding shRNA-resistant FLAG-tagged STN1-OBM and the Thy1 . 1 marker . Cells expressing STN1-OBM were isolated by FACS based on Thy1 . 1 expression and were re-sorted periodically to maintain expression . | Mammalian CST ( CTC1/STN1/TEN1 ) is a three protein complex that aids in several steps during telomere replication and has genome-wide roles during recovery from replication fork stalling . Loss of CST leads to abnormalities in telomere structure , genomic instability and defects in chromosome segregation . Currently , we do not understand how CST acts to ensure the resolution of very diverse types of replication problem . We set out to address this question by studying a mutant form of CST that was predicted to alter DNA binding . The mutations are in the STN1 subunit . In vivo , the STN1 mutant ( STN1-OBM ) affects some aspects of CST function while others are normal . The effects of STN1-OBM do not align with the telomeric versus non-telomeric roles of CST but instead separate out different aspects of CST function at telomeres and genome-wide . In vitro binding studies indicate that STN1-OBM disrupts binding to only short DNA substrates . Since CST is likely to encounter DNA substrates of varied length and structure in vivo as it helps resolve different replication problems , this finding starts to explain why STN1-OBM affects only certain aspects of CST function . Our in vitro binding studies also shed light on how CST actually binds to DNA and they suggest a novel “dynamic binding model” that provides a mechanistic explanation for how CST helps resolve a diverse array of replication problems to preserve genome stability . | [
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"physica... | 2016 | STN1 OB Fold Mutation Alters DNA Binding and Affects Selective Aspects of CST Function |
The HIV envelope ( Env ) glycoprotein mediates membrane fusion through sequential interactions with CD4 and coreceptors , followed by the refolding of the transmembrane gp41 subunit into the stable 6-helix bundle ( 6HB ) conformation . Synthetic peptides derived from the gp41 C-terminal heptad repeat domain ( C-peptides ) potently inhibit fusion by binding to the gp41 pre-bundle intermediates and blocking their conversion into the 6HB . Our recent work revealed that HIV-1 enters cells by fusing with endosomes , but not with the plasma membrane . These studies also showed that , for the large part , gp41 pre-bundles progress toward 6HBs in endosomal compartments and are thus protected from external fusion inhibitors . Here , we examined the consequences of endocytic entry on the gp41 pre-bundle exposure and on the virus' sensitivity to C-peptides . The rates of CD4 and coreceptor binding , as well as the rate of productive receptor-mediated endocytosis , were measured by adding specific inhibitors of these steps at varied times of virus-cell incubation . Following the CD4 binding , CCR5-tropic viruses recruited a requisite number of coreceptors much faster than CXCR4-tropic viruses . The rate of subsequent uptake of ternary Env-CD4-coreceptor complexes did not correlate with the kinetics of coreceptor engagement . These measurements combined with kinetic analyses enabled the determination of the lifetime of pre-bundle intermediates on the cell surface . Overall , these lifetimes correlated with the inhibitory potency of C-peptides . On the other hand , the basal sensitivity to peptides varied considerably among diverse HIV-1 isolates and ranked similarly with their susceptibility to inactivation by soluble CD4 . We conclude that both the longevity of gp41 intermediates and the extent of irreversible conformational changes in Env upon CD4 binding determine the antiviral potency of C-peptides .
HIV Env-induced fusion between the viral and cellular membrane progresses through a series of steps that begin with binding of the gp120 subunit to CD4 . This step results in the formation of the gp120 bridging sheet which , along with the third hypervariable loop ( V3 loop ) , forms the coreceptor binding site ( reviewed in [1] ) . The recruitment of coreceptors , CCR5 or CXCR4 , by Env-CD4 complexes initiates gp41 refolding that progresses through a pre-bundle intermediate , in which the gp41 N- and C-terminal heptad repeat domains ( N-HR and C-HR , respectively ) are exposed [2]–[5] . The heptad repeat domains ultimately coalesce into the stable post-fusion conformation referred to as the 6-helix bundle ( 6HB ) . The 6HB is formed by an antiparallel association of the trimeric N-HR domain ( coiled coil ) with three peripheral C-HR domains ( reviewed in [6] ) . In a pre-bundle conformation , gp41 is susceptible to inhibition by synthetic peptides derived from its C-HR domain ( hereafter referred to as C-peptides ) . These peptides bind to the complementary N-HR region and block HIV fusion by preventing the formation of 6HBs [6]–[8] . The kinetics of HIV fusion and the progression of gp41 pre-bundles to the 6HB has been studied in a cell-cell fusion model [4] , [9]–[13] . Biochemical studies using a tagged C-peptide showed that , depending on the virus strain , the gp41 coiled coils can be exposed as early as upon CD4 binding [2] . Once formed , the pre-bundles are thought to persist for a couple of minutes prior to converting into the 6HB [14] . Using a real-time cell-cell fusion assay , we observed that small fusion pores collapsed soon after the addition of C-peptides [13] , indicating that the formation of 6HBs was not completed at this point . These findings show that Env remains vulnerable to inhibitors of 6HB formation and to antibodies targeting gp41 intermediates throughout the fusion reaction . Our recent work revealed important differences between cell-cell and virus-cell fusion models [15] . Whereas HIV-1 Env can mediate cell fusion by merging two plasma membranes , the virus itself fails to release its content at the cell surface . Instead , HIV-1 fuses with endosomes , presumably after undergoing CD4- and coreceptor-mediated endocytosis . Time-resolved single virus imaging showed that fusion with the plasma membrane was blocked at a stage downstream of lipid mixing and did not progress to productive entry . Importantly , endosomal fusion was markedly delayed relative to virus internalization , demonstrating that the surface exposure of gp41 intermediates is limited by the relatively quick virus clearance from the cell surface . Endocytic HIV-1 entry could thus attenuate the effects of neutralizing antibodies and C-peptides that target intermediate conformations of Env . Disparate HIV isolates are known to exhibit a broad range of sensitivities to C-peptides ( e . g . , [16] ) , but the mechanisms underlying this differential sensitivity are not well understood . Functional studies suggested a correlation between the potency of a 34-residue long peptide , C34 , and the propensity of Env to expose the gp41 coiled coil domains upon binding to a soluble CD4 ( sCD4 ) [2] , [17] , [18] . The efficacy of C-peptides is also modulated by their primary sequence and the sequence of complementary N-HR domains that determine the binding affinity [19] , [20] . However , the potency of C34 peptides derived from HIV-1 , HIV-2 and SIV isolates poorly correlated with their propensity to form stable 6HBs with the complementary N-HR domains [17] . Another determinant of the efficacy of C-peptides is thought to be the window of opportunity for their binding to gp41 intermediates . This notion is based on correlation between the kinetics of cell-cell fusion and the HIV-1 resistance to C-peptides [9] , [10] , [17] , [18] , [21] . These findings led to a hypothesis that the gp41 residence time in pre-bundle conformations determines the HIV-1 sensitivity to C-peptides [9] . Implicit for this model is the inverse relationship between the rate of fusion and the longevity of pre-bundles and the slow , rate-limiting binding of C-peptides to these intermediate conformations . The slow peptide binding would require prolonged exposure of the gp41 coiled coil and would thus limit its ability to block the quickly-progressing fusion . However , since the HIV-1 fusion proceeds through intermediate steps at which the gp41 coiled coils are not exposed , the overall kinetics of fusion may not reflect the window of opportunity for the peptide binding . Thus , in order to meaningfully examine the kinetic determinants of the HIV resistance to C-peptides , one needs to determine the actual residence time of gp41 in pre-bundle conformations on the cell surface . Endocytic entry of HIV-1 warrants careful examination of the relationship between the rates of the surface-accessible pre-fusion steps and the sensitivity to C-peptides . Here , we employed inhibitors of distinct steps of HIV-1 fusion to monitor the progression through CD4 and coreceptor binding steps followed by productive endocytosis that protected the virus from fusion inhibitors employed in this study . Using a simple kinetic model of HIV fusion , we determined the rates of HIV-1 progression through key pre-fusion intermediates and thus the residence times of Env in these intermediates . Our results imply that multiple factors contribute to the potency of C-peptides . An important kinetic factor is the lifetime of gp41 pre-bundles which is defined by the rate of engagement of a requisite number of receptors and coreceptors on one hand and the productive virus endocytosis on the other . We also found that viral determinants , such as the extent of conformational changes in Env in response to the CD4 binding , significantly modulate the susceptibility of HIV-1 to C-peptides . The ability to evaluate the HIV-1 residence time in intermediate states permits rationalization of the complex mechanisms that define the resistance to C-peptides and other inhibitors targeting intermediate conformations of Env .
In order to directly monitor HIV-1 fusion with target cells , we measured the cytosolic activity of the beta-lactamase-Vpr ( BlaM-Vpr ) chimera packaged into the viral core [22] . Pseudoviruses containing the reporter enzyme were bound to target cells in the cold , and their fusion was initiated by quickly raising the temperature to 37°C , as described in [15] . The BlaM activity originates exclusively from viral cores delivered into the cytosol through fusion , whereas cell-bound or internalized viruses do not contribute to the signal [22] . Due to the low number of fused viruses , an overnight incubation is required to accumulate detectable amounts of cleaved fluorogenic BlaM substrate loaded into the cytosol . In order to resolve the kinetics of HIV fusion that occurs within a few hours ( e . g . , [23] ) , high concentrations of fusion inhibitors were added at varied times of incubation at 37°C [15] . The acquisition of resistance to a membrane-impermeant inhibitor yields the kinetics of virus progression beyond the step targeted by that inhibitor . Alternatively , resistance to inhibitors targeting a late step of fusion can occur through virus internalization that protects it from external inhibitors and permits subsequent fusion with endosomes . The availability of inhibitors blocking distinct steps of HIV entry enabled monitoring the progression through sequential surface-accessible stages of fusion . The kinetics of CD4 binding were monitored by time-of-addition experiments using a small-molecule inhibitor BMS-806 [24] , [25] . Since the binding to CD4 renders HIV-1 resistant to this compound , escape from BMS-806 indicates the progression of fusion beyond the receptor-dependent steps ( Fig . 1B ) . The virtually complete inhibition of fusion by BMS-806 added at the beginning of incubation shows that cell-associated HIV-1 did not engage CD4 immediately following the virus pre-binding protocol ( 30 min at 4°C ) . The rates of CXCR4 or CCR5 binding were measured by adding small-molecule inhibitors AMD3100 and AD101 , respectively . The acquisition of resistance to C-peptides blocking the gp41 6HB formation has been traditionally interpreted as Env-mediated fusion [3] , [4] . However , since HIV-1 fuses with endosomes of HeLa-derived target cells [15] , escape from C-peptides must occur through virus uptake . The fact that HIV-1 escapes from coreceptor antagonists before escaping from C-peptides ( Fig . 1B ) implies that the fusion signal originates from viruses that engage both CD4 and coreceptors prior to undergoing endocytosis . Note that in HeLa-derived target cells the majority of viruses is internalized and degraded through CD4- and/or coreceptor-independent pathways [26] . It is unlikely that HIV-1 acquires resistance to these peptides by forming 6HBs prior to undergoing endocytosis because: ( i ) fusion with the plasma membrane does not progress beyond the lipid mixing stage [15]; and ( ii ) 6HB formation occurs only after opening of a fusion pore [13] . Here , we measured the rate of HIV-1 escape from C-peptides using a recombinant 52-residue peptide , C52L , derived from the gp41 C-HR domain [27] . In control experiments ( data not shown ) HIV-1 escape from the C52L peptide occurred at the same rate as escape from the better characterized 34-residue peptide , C34 . In this work , we will be concerned only with the pre-fusion steps occurring at the cell surface , which are key determinants of the sensitivity to C-peptides and antibodies targeting intermediate conformations of Env [9] , [10] , [18] , [28] , [29] . Once different HIV-1 isolates form ternary complexes with CD4 and coreceptors and undergo endocytosis , subsequent fusion events appear to occur with similar rates and efficiencies [15] . Thus , the fusion signal measured by the time-of-addition protocol should reflect the rate of cell surface-accessible steps of fusion . We sought to determine the residence time of HIV-1 in key intermediate states and thus to evaluate the lifetime of gp41 pre-bundles that are accessible on the cell surface to C-peptides and neutralizing antibodies . To this end , we considered a minimal kinetic model ( Fig . 1C ) that describes the virus association with the cell surface followed by CD4 binding , coreceptor ( CR ) binding , and , finally , by productive endocytosis . We operationally define the following intermediate states the virus adopts sequentially along its entry pathway: ( i ) the state ( V ) of the membrane-associated virus which is sensitive to all three types of fusion inhibitors; ( ii ) the state ( VCD4 ) resistant to an inhibitor blocking the HIV-CD4 binding , but sensitive to inhibitors of coreceptor binding and 6HB formation; ( iii ) the state VCD4CR resistant to inhibitors of receptor and coreceptor binding , but still sensitive to inhibitors of 6HB formation; and ( iv ) the state VE resistant to all three inhibitor types . The effective rate constants of transitions between the successive states V , VCD4 , VCD4CR and VE are denoted by k1 , k2 , and k3 . Our model can be readily modified to describe direct virus fusion with the plasma membrane by omitting the endosomal fusion step and treating VE as the fusion state . The model does not consider the reverse rates of CD4 and coreceptor binding reactions . Moreover , the model makes no assumptions about the stoichiometry of the receptor and coreceptor binding . If several Env glycoproteins are involved in HIV-1 entry , the virus must engage more than one pair of receptor and coreceptor molecules in order to undergo fusion . In that case , interactions with coreceptors at the virus-membrane contact may start before the recruitment of a requisite number of CD4 is completed . Then the VCD4 is a state where the receptor binding is finalized while the coreceptor recruitment is still incomplete , so that the transition to VCD4CR consists in the recruitment of the missing coreceptors . The model postulates that the viruses are subject to inactivation characterized by the inactivation rate constants . Whereas the general form of the model ( see Fig . S4 ) accounts for different inactivation rates at the sequential steps of the HIV-1 progression along the fusion pathway , it is currently impossible to experimentally determine the individual inactivation rates . Thus , in order to evaluate the effective rate constants of fusion , we used a simplified version of the model that assumes equal inactivation rate constants , ki , for all stages of the fusion reaction . We also assume that the HIV-1 inactivation is primarily due to a non-productive endocytosis which is the predominant pathway of HIV-1 uptake by HeLa-derived cells [15] , [26] . In other words , the total virus uptake is assumed to reflect the rate of virus inactivation . This non-productive pathway likely includes both CD4-independent and CD4-mediated virus uptake which , in the absence of coreceptor binding , does not lead to endosomal fusion . The differential equations describing the virus evolution through each of the states of the kinetic scheme ( Fig . 1A , C ) are given in Appendix S1 . The solution of these equations for the number of viruses VE entering through productive endocytosis ( leading to endosomal fusion ) as a function of time is given by:where Unlike the previously proposed models of Env-mediated fusion [23] , [30] , this model accounts for the effective lag before fusion . This lag is given by 1/ ( k1·k2·k3·Vtot ) , where Vtot is the total number of cell-bound fusion-competent viruses at time = 0 . Note that Vtot cancels out upon normalizing data to the final extent of fusion ( see also Fig . S1 ) , so that the kinetics of fusion do not depend on the multiplicity of infection ( MOI ) . Thus , normalization eliminates the need to determine and/or control the exact number of fusion-competent particles bound per cell . Our model describes a wide variety of cell-cell and virus-cell fusion data using four free parameters: k1 , k2 , k3 and ki . These effective rate constants can be defined through the measurements of the kinetics of CD4 binding ( escape from BMS-806 ) , coreceptor binding ( escape from AD101 or AMD3100 ) , the rate of productive endocytosis ( escape from C52L ) , and the rate of virus inactivation through non-productive endocytosis ( p24 uptake ) . The knowledge of the kinetics of virus inactivation is important because this process , along with the respective pre-fusion rate constants , determines the exit rates from V , VCD4 and VCD4CR . We thus obtained the ki by fitting a single exponential function to the HIV p24 uptake data ( Fig . 1B ) . A separate set of equations ( equations ( 10–12 ) of Appendix S1 ) was derived to describe the kinetics of virus escape from CD4 and coreceptor binding inhibitors and from C-peptides added at varied times of virus-cell incubation . Through fitting of the solutions of these equations to the respective data sets , we were able to determine the remaining three rate constants k1 , k2 and k3 for the surface-accessible steps of fusion ( see the legend to Fig . 2 for details and Table 1 ) . We first examined the progression of the primary R5-tropic JRFL isolate through the surface-accessible fusion intermediates . Pseudoviruses were produced and the incorporation and proteolytic processing of JRFL Env was assessed by Western blotting ( Fig . S2 ) . Viruses were pre-bound to target cells in the cold , and their uptake and fusion were initiated by shifting to 37°C . Inhibitors of CD4 or CCR5 binding were added at indicated times of incubation to obtain the kinetics of HIV-1 escape from these inhibitors . As discussed above , HIV-1 acquires resistance to the inhibitors of 6HB formation through receptor-mediated endocytosis as opposed to fusion at the cell surface . Productive endocytosis of this virus was thus measured by adding a high concentration of the recombinant C52L peptide at varied time points . In parallel experiments , the total virus uptake was measured by the intracellular accumulation of the HIV-1 p24 . These measurements allowed us to determine the fusion and inactivation rate constants for JRFL entry into different target cells . When HeLa-derived TZM-bl cells expressing high levels of CD4 and CCR5 [31] were used as targets , JRFL engaged a requisite number of CD4 and coreceptors with the virtually identical kinetics ( Fig . 2A ) . Thus , under these conditions , the effective rate of CCR5 binding was too fast to be resolved . We therefore sought to slow down the formation of ternary complexes by reducing the density of CCR5 on the cell surface or by diminishing its affinity to Env . A ∼20-fold reduction of the average number of CCR5 molecules per cell did not noticeably affect the rate of coreceptor engagement ( data not shown ) . However , the kinetics of CCR5 binding and the final extent of fusion were markedly diminished for JC . 10 cells [31] expressing a ∼100-fold lower number of CCR5 compared to TZM-bl cells ( Fig . 2B ) . We were thus able to kinetically resolve the CCR5 binding step and measure its effective rate constant , k2 ( Table 1 ) . Next , we examined the impact of the coreceptor binding affinity on the rate of the ternary complex formation . JRFL pseudoviruses were bound and fused with JYN . 2-15 cells [32] expressing high levels of wild-type CD4 and the Y14N CCR5 mutant similar to those present on TZM-bl cells . JRFL fusion with these cells was less efficient and was highly sensitive to inhibition by AD101 ( Table 2 ) , in agreement with the diminished affinity to gp120 caused by the loss of the critical Tyr14 residue at the CCR5 N-terminus . As expected , the Y14N mutation reduced the kinetics of virus escape from AD101 , whereas the rate of CD4 binding remained unchanged ( Fig . 2C and Table 1 ) . Together , these results demonstrate that the lifetime of Env-CD4 complexes on the cell surface can be manipulated by changing the density of coreceptors or their binding affinity to gp120 . Next , we compared the kinetics of surface-accessible steps of fusion induced by JRFL Env and by the laboratory adapted HXB2 Env . These glycoproteins differ in many aspects , including the coreceptor tropism and sensitivity to neutralizing antibodies and C-peptides [18] , [33] , [34] . HXB2 pseudoviruses engaged CD4 faster than JRFL ( Figs . 2A and 3A ) , in agreement with the enhanced receptor binding affinity associated with the HIV-1 adaptation to growth in culture [5] , [35] , [36] . By contrast , HXB2-CD4 complexes became protected from the coreceptor binding inhibitor at a much slower rate than JRFL . The different kinetics of coreceptor binding are consistent with the vastly different coreceptor binding affinities of laboratory adapted X4 and primary R5 Env glycoproteins [37]–[39] . The ∼10-fold higher CCR5 expression on TZM-bl cells compared to the CXCR4 expression [31] , [40] did not seem to be responsible for the more rapid CCR5 engagement , since the rate of this coreceptor binding was not noticeably affected by the 10-fold reduction in its expression level ( data not shown ) . Interestingly , HXB2-CD4-coreceptor complexes were internalized at a ∼3-fold faster rate compared to the ternary JRFL complexes ( k3 constant , Table 1 ) , whereas the rates of bulk endocytosis leading to virus degradation were close for these viruses ( Figs . 2A and 3A , crosses ) . As a result of the above compensatory variations in the rate constants of pre-fusion steps , the overall kinetics of JRFL and HXB2 escape from C52L were close . This result is in contrast with the faster kinetics of cell-cell fusion induced by JRFL compared to HXB2 Env [18] . We next assessed the effect of coreceptor binding affinity in the context of X4 Env . Toward this goal , we used a chimeric HXB2 Env in which the V3 loop was substituted with that of the R5-tropic BaL isolate [41] . This chimera , hereafter referred to as V3BaL , exclusively utilizes CCR5 for fusion and appears to bind CCR5 with high affinity [21] , [41] . This notion is consistent with our data showing that V3BaL fuses with target cells expressing the low-affinity CCR5 mutants ( Fig . S3A ) and with cells expressing low density of CCR5 ( data not shown ) . Moreover , V3BaL was even somewhat more resistant to AD101 than BaL and JRFL ( Table 2 ) . After verifying that HXB2 , V3BaL and BaL Env were proteolytically processed and incorporated into pseudoviruses at similar levels ( Fig . S2 ) , we compared the kinetics of fusion mediated by these glycoproteins . As expected , the rates of CD4 binding by V3BaL and HXB2 were indistinguishable ( Fig . 3A , B and Table 1 ) , whereas the V3BaL-CCR5 binding was ∼3-fold faster than HXB2-CXCR4 binding . This result is consistent with the high affinity of the chimera to CCR5 and with the higher expression of CCR5 on TZM-bl cells compared to endogenous expression of CXCR4 . In spite of the faster rate of ternary complex formation , the subsequent internalization of V3BaL-CD4-coreceptor complexes was ∼2-fold slower than that of HXB2 ( Table 1 ) . These opposite trends in the kinetics of the HXB2 and V3BaL pre-fusion steps resulted in similar overall rates of escape from C52L . To better understand the differences in the progression of HXB2 and V3BaL through surface-accessible steps of fusion , we examined the fusion of viruses pseudotyped with wild-type BaL Env . BaL exhibited markedly different kinetics of fusion compared to HXB2 and V3BaL ( Fig . 3 ) . First , BaL engaged CD4 ∼3-fold slower than JRFL and almost 9-fold slower than HXB2 ( Table 1 ) . By contrast , BaL escaped from AD101 and from C52L at rates that were indistinguishable from the rate of CD4 binding . The unusually quick BaL protection from C52L prompted us to examine whether this effect was due to the direct fusion with the plasma membrane as opposed to productive endocytosis demonstrated for JRFL and HXB2 viruses [15] . We therefore compared the rates of virus escape from C52L and from the temperature block applied at varied times of BaL incubation with TZM-bl cells ( see [15] and Fig . S3B ) . A marked delay between the BaL escape from the temperature block compared to its escape from the peptide inhibitor strongly implies that this virus also fuses with endosomes . Collectively , these data show that BaL engages CD4 slowly but then completes the CCR5 binding and enters endocytic compartments at an unusually high rate . Having determined the effective rate constants of progression through the CD4 and coreceptor binding steps for different Env glycoproteins and target cells ( Table 1 ) , we used the equations ( 6–8 ) of Appendix S1 to calculate the probability of finding the virus in VCD4 , VCD4CR and VE states as a function of time ( Fig . 4A–D ) . We then determined the time averages of HIV-1 in these states by integrating the equations ( 6 ) and ( 7 ) from time = 0 to the end of virus-cell incubation and dividing over this time interval ( the resulting equations ( 13 ) and ( 14 ) are given in Appendix S1 ) . The time averages of different HIV-1 in VCD4 and VCD4CR and the combined residence times in both states are shown in Fig . 4E . The gp41 pre-bundles are formed upon the Env binding to CD4 or both CD4 and coreceptors [2]–[4] and are cleared from the cell surface by endocytosis [15] . Thus , the ability to determine the time spent in VCD4 and VCD4CR states provided an opportunity to estimate the lifetimes of pre-bundles on the cell surface . The shortest apparent exposure of pre-bundle intermediates was observed for BaL , whereas the longest combined time in VCD4 and VCD4CR was observed upon JRFL fusion with cells expressing the low-affinity CCR5 mutant ( Fig . 4E ) . Since C-peptides target the gp41 coiled coils , we asked whether their inhibitory potency correlated with the lifetime of these intermediates on the cell surface . It has been proposed that the longevity of pre-bundles determines the HIV-1 sensitivity to C-peptides [9] . However , this notion was based on correlation between the peptide's potency and the overall kinetics of HIV Env-mediated cell-cell fusion and not on measurements of the actual lifetime of gp41 coiled coils in the context of virus entry . In order to rationalize the kinetic determinants of HIV-1 sensitivity to C-peptides , we sought to compare the time spent in pre-bundle intermediates with the inhibitory potency of these peptides . To determine the susceptibility of different HIV-1 Env to inhibition by C-peptides , we measured virus-cell fusion in the presence of the well-characterized C34 peptide [19] . JRFL exhibited the highest resistance to this peptide while BaL was somewhat more susceptible to inhibition ( Fig . 5A , Table 2 ) . By comparison , HXB2 and V3BaL were much more potently inhibited by C34 with the chimera being only marginally more resistant than the wild-type HXB2 . So , in the context of HXB2 Env and under our experimental conditions , the coreceptor tropism and the coreceptor binding affinity had a modest effect on the virus' resistance to C34 . Similar results were obtained with the C52L peptide ( data not shown ) . The 10-fold difference between the IC50 for JRFL and HXB2 by C34 is in stark contrast with the comparable rates of their escape from high doses of C-peptides due to productive endocytosis ( Figs . 2A and 3A ) . Plotting the IC50 values against the half-times of HIV-1 escape from C52L , as determined from the measurements shown in Figs . 2 and 3 , confirmed that the C34 potency did not correlate with the rate of virus protection from this inhibitor ( Fig . 6A ) . In contrast to these results , the kinetics of cell-cell fusion appears to inversely correlate with the potency of C-peptides [9] . These seemingly discrepant findings likely stem from the fact that HIV-1 escape from inhibitory peptides does not reflect virus-cell fusion , but rather corresponds to productive endocytosis . Another possibility is that the C34 peptide used in our experiments had different affinity to the gp41 N-HR domains of HIV-1 isolates examined in this work . The conventional C34 peptide is derived from the gp41 C-HR of the IIIB clone [17] , [19] , which is identical to the respective domains of HXB2 gp41 but not of JRFL gp41 ( Fig . 5D ) . Since the C34 sequence has been shown to affect its potency against HIV and SIV isolates [17] , we asked if the JRFL-derived C34 ( designated C34JRFL ) is a more potent inhibitor of fusion than the C34IIIB . Both C34IIIB and C34JRFL potently inhibited HXB2 fusion at comparable concentrations ( Fig . 5B ) . Even though JRFL was approximately 2-fold more sensitive to its own C34 than to C34IIIB , still higher doses of the former peptide were required to block JRFL fusion compared to HXB2 fusion . Thus , neither the kinetics of virus escape from C-peptides nor the sequences of C34 can fully account for the greater resistance of JRFL to this inhibitor . The above results highlight the importance of measuring the actual lifetime of gp41 pre-bundles ( Fig . 4 ) in order to better rationalize the kinetic factors controlling the HIV-1 resistance to C-peptides . We asked whether the time averages of VCD4 and VCD4CR states are predictive of the virus' sensitivity to C-peptides . When the potency of C34 was plotted against the time spent in VCD4 ( Fig . 6B ) , the points clearly fell into two groups – JRFL fusion with different target cells and HXB2/BaL/V3BaL fusion with TZM-bl cells . Within these two groups , the IC50 correlated well with the time average in VCD4 . Thus , in the context of JRFL Env or HXB2/BaL Env , the diminished rate of coreceptor engagement and thus the increased lifetime of early gp41 intermediates were associated with enhanced sensitivity to C34 . In contrast , we saw no apparent correlation between the lifetime of VCD4CR and the potency of this peptide ( Fig . 6C ) . This was surprising because the gp41 coiled coils should be better exposed to the peptide at VCD4CR compared to VCD4 [2] . Since the HXB2 ( and likely V3BaL ) coiled coils are exposed as early as upon CD4 binding [2]–[4] and should thus persist throughout the surface-accessible steps of fusion , a more meaningful parameter for characterizing the window of opportunity for the C34 binding is the total time spent in VCD4 and VCD4CR states . This parameter should also adequately describe the coiled coil exposure on JRFL and BaL gp41 . Even though the JRFL coiled coils are optimally exposed only after engaging both CD4 and CCR5 [2] , the total time in VCD4 and VCD4CR states is dominated by the latter intermediate ( Fig . 4C and E ) . We found that the combined residence time in these states inversely correlated with the IC50 for C34 ( Fig . 6D ) . As in the Fig . 6B , this correlation was more apparent when fusion of the V3 loop-swapped constructs ( BaL , HXB2 and V3BaL ) and JRFL fusion with different cells were considered separately . These data suggest that , in the context of the same Env backbone , the total time spent in VCD4 and VCD4CR is a good predictor of the C34's potency . The lifetime of the gp41 coiled coils did not fully account for the differences in the inhibitory potency of C34 . Indeed , the quick progression of BaL through the surface-accessible pre-fusion steps suggests that the gp41 coiled coils are very briefly exposed prior to entering into endosomal compartments . However , whereas BaL was much more resistant to C34 than HXB2 ( Table 2 ) , it was more susceptible to this inhibitor than JRFL , which spent much longer time in pre-bundle intermediates than BaL . Thus , virus strain-specific factors appear to contribute to the baseline sensitivity of HIV-1 to C-peptides . In addition , the modest effect of the HXB2 V3 loop substitution on the potency of C34 indicates that critical determinants of the virus' resistance reside outside the V3 loop . Envelope glycoproteins of laboratory adapted strains are generally less stable and tend to inactivate upon binding to CD4 [42]–[44] . It is thus possible that the degree to which different Env glycoproteins refold in response to the CD4 binding could determine the sensitivity to C-peptides [17] . Recent study implies that this inactivation occurs via CD4-induced conformational changes in Env and not due to the gp120 shedding [45] . This work also demonstrates the strain-dependent differences in the exposure of the gp41 coiled coils caused by sCD4 binding . To assess the extent of irreversible Env refolding in response to receptor binding , we measured to degree of virus inactivation after pre-treatment with sCD4 . Viruses were pre-incubated with varied concentrations of sCD4 , and the remaining fusion activity was determined after an additional 90 min-incubation with TZM-bl cells . These experiments revealed that JRFL was the most resistant to sCD4 , BaL showed an intermediate sensitivity , whereas V3BaL and HXB2 were both strongly inactivated under these conditions ( Fig . 5C ) . The similar effect of sCD4 on HXB2 and V3BaL viruses was as expected for Env glycoproteins sharing the same backbone . Notably , the extents of sCD4-induced inactivation and inhibition by C-peptides ranked similarly ( Fig . 5A and C ) . This result is consistent with the notion that the stability of Env-CD4 complexes determines the extent of exposure of the gp41 coiled coil . In other words , for the same time spent in a pre-bundle conformation , the sensitivity to C-peptides appears to depend on the extent of conformational changes in Env occurring in response to the receptor binding . This model is supported by the different efficacies of C34 against HXB2 fusing with TZM-bl and JRFL fusing with JC . 10 cells in spite of the similar lifetimes of gp41 pre-bundles ( Fig . 6D ) . Together , our results reveal a complex interplay between the Env stability ( viral determinants ) and the rate of progression through surface-accessible intermediates ( viral and cellular determinants ) in defining the HIV-1 resistance to C-peptides .
In the present work , we characterized the HIV-1 progression through surface-accessible steps of entry prior to virus uptake and fusion with endosomes . Through measuring the rates of escape from membrane-impermeant inhibitors blocking distinct pre-fusion steps , we were able to determine the residence times in intermediate states in which HIV-1 recruited a requisite number of CD4 or both CD4 and coreceptors . This analysis revealed the viral strain-dependent and target cell-dependent differences in the average times the HIV-1 spent in distinct intermediates on the cell surface . The knowledge of the HIV-1 progression through the pre-fusion steps permitted the rationalization of the inhibitory potency of C-peptides targeting the gp41 coiled coils . We found that , unlike the Env-mediated cell-cell fusion , the time-course of HIV-1 escape from inhibitors of 6HB formation poorly correlated with the resistance to C34 ( Fig . 6A ) . This could be due to the different rates of productive virus endocytosis that , in addition to the kinetics of CD4 and coreceptor engagement , control the time of exposure of the gp41 coiled coils on the cell surface . Quantitative analysis of the HIV-1 fusion kinetics revealed correlation between the total residence time in pre-bundle conformations and the potency of C34 . Interestingly , the lifetime of the VCD4 , but not of VCD4CR , was predictive of the virus' sensitivity to this inhibitor . This result was unexpected because the gp41 coiled coils should be better exposed to C-peptides at the latter state [2] . The previously proposed model [9] posits that the C-peptide binding to the complementary coiled coil domain is slow and thus occurs optimally upon prolonged exposure of these domains . However , our data suggest that the peptides can effectively bind to relatively short-lived gp41 intermediates ( Fig . 6B ) . The observation that C-peptides cause closure of nascent fusion pores shortly after their addition to fusing cells [13] also supports the notion that the peptide binding occurs on a shorter time scale than the average lifetime of a pre-bundle intermediate ( several minutes ) . We surmise that the quick peptide binding to the stably exposed coiled coils can account for the lack of correlation between the lifetime of ternary complexes and the potency of C34 ( Fig . 6C ) . On the other hand , the enhanced potency of C34 associated with the longer-lived VCD4 indicates that the coiled coil exposure at this point is not completed . Our findings are in agreement with the previous reports that multiple factors control the HIV-1 resistance to C-peptides [17] , [20] . First , the baseline sensitivity of diverse Env glycoproteins appears to be determined by their propensity to undergo irreversible conformational changes upon engaging CD4 . The exceptionally high resistance of JRFL to C-peptides in spite of the long time spent in CD4/coreceptor-bound state could be due in part to a restricted exposure of its coiled coils [2] . Second , the C-peptide's primary sequence , which affects their binding affinity to the gp41 coiled coil , appears to modulate their inhibitory potency . Third , our results show that kinetic factors determine the longevity of gp41 pre-bundles and thus control the potency of C-peptides . The window of opportunity for the C-peptide binding depends on cellular factors , such as the density of coreceptors and their affinity to Env , as well as on the rate of receptor-mediated virus endocytosis . We surmise that the faster rate of productive endocytosis in certain cell types may diminish the gp41 pre-bundle exposure and protect the virus from C-peptides and antibodies targeting Env intermediates . Clearly , a full quantitative description of HIV-1 fusion awaits the determination of the fusion stoichiometry , as well as the identification of intracellular steps and factors involved in virus entry . However , experimental strategies developed in this work provide a means to evaluate the kinetics of surface-accessible steps of HIV-1 fusion . Our data show that the rate of progression through pre-fusion steps is a critical determinant of the virus' susceptibility to C-peptides and likely to neutralizing antibodies targeting CD4-induced epitopes . Further studies involving a larger set of primary and laboratory adapted HIV strains are needed to substantiate the conclusions of this work and to define the viral and cellular determinants of resistance to peptide inhibitors .
HeLa-derived JC . 10 [31] , JYN . 2-15 , and JGR . H11 [32] cells were a gift from Dr . D . Kabat ( OHSU , OR ) . TZM-bl cells were obtained from NIH AIDS Research & Reference Reagent Program and grown in Dulbecco modified Eagle medium ( DMEM , Invitrogen , Carlsbad , CA ) supplemented with 10% fetal bovine serum ( FBS , HyClone Laboratories , Logan , UT ) and penicillin-streptomycin ( Invitrogen ) . 293T/17 cells ( ATCC , Manassas , VA ) were grown in DMEM/10% FBS , 0 . 5 mg/ml Geneticin ( Invitrogen ) , and penicillin-streptomycin . The pCAGGS plasmids encoding JRFL or HXB2 Env [46] were provided by Dr . J . Binley ( Torrey Pines Institute , CA ) . The pCAGGS plasmids encoding HXB2-BaL chimera Env in V3 loop , V3BaL , were constructed by replacing of Env coding sequence of pSV7D HXB BaL , a gift from Dr . R . Doms ( University of Pennsylvania ) . HIV-1 BaL . 01 [47] Env expression vector was obtained from NIH AIDS Research & Reference Reagent Program . The HIV-1 based packaging vector pR8ΔEnv lacking the env gene was from Dr . D . Trono ( University of Geneva , Switzerland ) . Soluble CD4 was purchased from Progenics ( Tarrytown , NY ) . The C52L recombinant peptide [27] was a gift from Dr . Min Lu ( Cornell University ) . BMS-806 [24] , [25] was synthesized by ChemPacific Corp . ( Baltimore , MD ) , AMD3100 [48] and pronase were purchased from Sigma ( St . Louis , MO ) , and AD101 [49] was a gift from Dr . J . Strizki ( Schering Plough , Kenilworth , NJ ) . The C34IIIB peptide was synthesized by Dr . L-X . Wang ( IHV , University of Maryland ) and the JRFL gp41-derived C34 peptide ( Ac-WMEWEREIDNYTSEIYTLIEESQNQQEKNEQELL-NH2 ) was kindly provided by Dr . W . Lu ( IHV , University of Maryland ) . The purity of these peptides was >98% , as determined by HPLC . Pseudoviruses containing the β-lactamase-Vpr ( BlaM-Vpr ) were produced as described in [15] . Briefly , 293T/17 cells on a 60 mm dish were transfected by Ca-phosphate protocol with 10 µg pR8ΔEnv , 5 µg pMM310 vector expressing BlaM-Vpr [50] , 4 µg pcRev [51] , and 15 µg pCAGGS encoding JRFL , HXB2 , or V3BaL Env , or pHIV1 BaL . 01 ( expressing BaL Env ) . The infectious titer was determined by a β-Gal assay in TZM-bl cells [52] . Measurements of HIV-1 fusion with target cells were carried out essentially as described previously [15] . Briefly , viruses bearing the BlaM-Vpr chimera were bound to TZM-bl cells by centrifugation at 2095×g , 4°C for 30 min . After washing off unbound viruses , cells were incubated at 37°C for 90–120 min . At indicated times of incubation , the fusion reaction was stopped by adding specific inhibitors of CD4 binding ( 10 µM of BMS-806 ) , coreceptor binding ( 5 µM of AMD3100 or 7 µM of AD101 ) , or inhibitors of 6-helix bundle formation ( 1 µM of C52L ) . The concentration of a given entry inhibitor used in these time-of-addition experiments exceeded the fully inhibitory concentration ( determined in separate experiments ) by at least 3-fold . Samples were then loaded with the BlaM substrate CCF2-AM ( GeneBLAzer in vivo detection kit , Invitrogen ) on ice and incubated at 20°C for 12 hr . The resulting fluorescence signals at 460 nm ( blue ) and 528 nm ( green ) were measured using the Synergy HT plate reader ( Bio-Tek Instr . , Germany ) . The dose-response dependence for HIV fusion in the presence of inhibitors was obtained by pre-binding viruses to cells , as above , and incubating at 37°C for 90 min with various concentrations of C34 prior loading cells with the BlaM substrate . Cells ( 3·104 cells/well in 96-well plates ) were grown overnight in regular medium . Virions were added to cells ( MOI 0 . 7 ) and centrifuged as described above . After washing to remove unbound viruses , cells were incubated at 37°C for varied times in the presence of 1 µM of C52L to prevent fusion . At defined time points , virus uptake was stopped and the external virus was stripped off by treatment with 2 mg/ml pronase on ice for 10 min . After washing with DMEM/10% serum , cells were lysed and the amount of p24 in cell lysate was determined using a p24 ELISA Kit ( PerkinElmer Life Sciences Inc , Boston , MA ) . Twenty µl aliquots of 10-fold concentrated viral preparations were pre-incubated for 30 min at 37°C with different concentrations of sCD4 . Following the incubation , the mixture was diluted 10-fold with the growth medium and added to TZM-bl cells ( final MOI = 0 . 8 in the absence of sCD4 ) . Virus binding to cells was augmented by centrifugation at 4°C , as described above . Cells were washed to remove unbound viruses , and fusion was initiated by shifting to 37°C for 90 min , after which time the process was stopped by reducing the temperature . The BlaM signal was normalized to that obtained for mock-treated viruses . | The human immunodeficiency virus ( HIV ) envelope glycoprotein ( Env ) mediates fusion between the viral and cell membranes . The fusion is initiated by Env-receptor interactions and is followed by coreceptor binding and refolding of the transmembrane gp41 subunit . The gp41 refolding proceeds through several distinct intermediates , culminating in the formation of a final helical bundle structure which is blocked by inhibitory peptides targeting the complementary domains of gp41 . We have recently shown that the exposure time of gp41 intermediates on the cell surface is limited by productive HIV endocytosis leading to fusion with endosomes . Here , we measured the rates of progression of different HIV isolates through distinct intermediate steps accessible to fusion inhibitors and correlated these rates with the inhibitory potency of peptides against these viruses . Whereas the potency of peptides was proportional to the lifetime of gp41 intermediates on the cell surface , the baseline sensitivity of the virus was also Env context-dependent . Higher concentrations of these inhibitors were required to block fusion induced by glycoproteins that were more resistant to inactivation by the soluble receptor . Collectively , these findings imply that both the kinetic factors and the stability of Env-receptor complexes control the HIV sensitivity to inhibitory peptides . | [
"Abstract",
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] | [
"virology/immunodeficiency",
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] | 2009 | Early Steps of HIV-1 Fusion Define the Sensitivity to Inhibitory Peptides That Block 6-Helix Bundle Formation |
The role of rodents in Leptospira epidemiology and transmission is well known worldwide . Rats are known to carry different pathogenic serovars of Leptospira spp . capable of causing disease in humans and animals . Wild rats ( Rattus spp . ) , especially the Norway/brown rat ( Rattus norvegicus ) and the black rat ( R . rattus ) , are the most important sources of Leptospira infection , as they are abundant in urban and peridomestic environments . In this study , we compiled and summarized available data in the literature on global prevalence of Leptospira exposure and infection in rats , as well as compared the global distribution of Leptospira spp . in rats with respect to prevalence , geographic location , method of detection , diversity of serogroups/serovars , and species of rat . We conducted a thorough literature search using PubMed without restrictions on publication date as well as Google Scholar to manually search for other relevant articles . Abstracts were included if they described data pertaining to Leptospira spp . in rats ( Rattus spp . ) from any geographic region around the world , including reviews . The data extracted from the articles selected included the author ( s ) , year of publication , geographic location , method ( s ) of detection used , species of rat ( s ) , sample size , prevalence of Leptospira spp . ( overall and within each rat species ) , and information on species , serogroups , and/or serovars of Leptospira spp . detected . A thorough search on PubMed retrieved 303 titles . After screening the articles for duplicates and inclusion/exclusion criteria , as well as manual inclusion of relevant articles , 145 articles were included in this review . Leptospira prevalence in rats varied considerably based on geographic location , with some reporting zero prevalence in countries such as Madagascar , Tanzania , and the Faroe Islands , and others reporting as high as >80% prevalence in studies done in Brazil , India , and the Philippines . The top five countries that were reported based on number of articles include India ( n = 13 ) , Malaysia ( n = 9 ) , Brazil ( n = 8 ) , Thailand ( n = 7 ) , and France ( n = 6 ) . Methods of detecting or isolating Leptospira spp . also varied among studies . Studies among different Rattus species reported a higher Leptospira prevalence in R . norvegicus . The serovar Icterohaemorrhagiae was the most prevalent serovar reported in Rattus spp . worldwide . Additionally , this literature review provided evidence for Leptospira infection in laboratory rodent colonies within controlled environments , implicating the zoonotic potential to laboratory animal caretakers . Reports on global distribution of Leptospira infection in rats varies widely , with considerably high prevalence reported in many countries . This literature review emphasizes the need for enhanced surveillance programs using standardized methods for assessing Leptospira exposure or infection in rats . This review also demonstrated several weaknesses to the current methods of reporting the prevalence of Leptospira spp . in rats worldwide . As such , this necessitates a call for standardized protocols for the testing and reporting of such studies , especially pertaining to the diagnostic methods used . A deeper understanding of the ecology and epidemiology of Leptospira spp . in rats in urban environments is warranted . It is also pertinent for rat control programs to be proposed in conjunction with increased efforts for public awareness and education regarding leptospirosis transmission and prevention .
Leptospirosis is a major zoonotic disease worldwide , having significant impact on both human and animal health [1 , 2] . It is known to be the most widespread zoonosis in the world [3] , affecting an estimated 1 . 03 million people and causing 58 , 900 deaths annually [4] . Leptospirosis can also cause major economic losses in livestock industries because of abortions and stillbirths in farm animals [2] . The disease is caused by pathogenic spirochete bacteria of the genus Leptospira , which consists of 22 known species ( pathogenic , intermediate , and saprophytic ) and is divided into more than 300 serovars [5] . Recently , 12 novel species of Leptospira have been isolated from tropical soils , suggesting a highly unexplored biodiversity in the genus [6] . Not only is leptospirosis a public health issue in developing countries , it has become an urban health problem in developed and industrialized countries , occurring in unsanitary environments in cities during periods of seasonal rainfall and flooding [7] . Leptospirosis is also associated with natural disasters , with large outbreaks occurring after hurricanes , typhoons , and floods in tropical regions [8] . A wide variety of mammals can act as reservoirs of Leptospira , harboring pathogenic Leptospira spp . in their renal tubules and then shedding them through urine , thus contaminating the environment [1] . Humans and other animals may be exposed to Leptospira spp . by direct or indirect contact with infected animals or through the contaminated environment such as soil or water [1 , 9] . Vertical transmission from mother to fetus or neonate through transplacental or transmammary transmission , respectively , as well as through sexual transmission within species , may also occur [2] . Wild rats ( Rattus spp . ) , especially the Norway/brown rat ( Rattus norvegicus ) and the black rat ( R . rattus ) , are abundant in urban and peridomestic environments and are the most important known sources of Leptospira infection [1 , 10] . Rats are chronic asymptomatic carriers of Leptospira spp . , maintaining the spirochetes in their proximal renal tubules [11 , 12] . They have also been reported to carry different pathogenic serovars of Leptospira spp . capable of causing disease in humans and other animals [13] . In this study , we focused on compiling and reviewing available data in the literature on global prevalence of Leptospira exposure and infection in rats , as well as comparing the global distribution of Leptospira spp . in rats with respect to prevalence , geographic location , methods of detection , diversity of serogroups/serovars , and species of rats .
To find studies describing Leptospira prevalence in rats worldwide , a thorough literature search was conducted using PubMed ( https://www . ncbi . nlm . nih . gov/pubmed ) with search terms including but not limited to “ ( ( Leptospira ) OR ( Leptospirosis ) ) AND ( Rats ) AND ( Prevalence ) , ” “ ( ( Leptospira ) OR ( Leptospirosis ) ) AND ( Rattus ) AND ( Prevalence ) , ” “ ( ( Leptospira ) OR ( Leptospirosis ) ) AND ( Rats ) AND ( Seroprevalence ) , ” “ ( ( Leptospira ) OR ( Leptospirosis ) ) AND ( Rattus ) AND ( Seroprevalence ) , ” “ ( ( Leptospira ) OR ( Leptospirosis ) ) AND ( Rodents ) AND ( Prevalence ) , ” and “ ( ( Leptospira ) OR ( Leptospirosis ) ) AND ( Rodents ) AND ( Seroprevalence ) , ” without restrictions on publication date . In addition , a search was performed using internet-based search engines such as Google and Google Scholar using similar search terms to manually search for other relevant articles . Titles and abstracts were initially screened against the inclusion criteria to determine their suitability to be included in this review . Abstracts were included if they described data pertaining to Leptospira spp . in rats ( Rattus spp . ) from any geographic region around the world , including reviews . Abstracts were excluded if they did not describe the prevalence of Leptospira spp . in rats or if they did not describe naturally occurring Leptospira infection in the rats . The full text documents were then assessed against specific inclusion criteria . Publications in languages other than English were excluded; however , such articles with an English abstract were included if they contained relevant data for extraction . We extracted data including the authors , year of publication , geographic location , and methods of detection used from the articles retrieved . We also extracted information on the species of rat ( s ) , sample size , and prevalence ( any kind including sero/molecular/culture/other prevalence ) of Leptospira spp . ( overall and within each rat species ) and information on species , serogroups , and/or serovars of Leptospira spp . detected if available . For cases in which mice or other rodents were also included in the study , we extracted only specific data regarding rats from the Rattus genus . We used a data extraction form to record the relevant data .
The database search retrieved 303 articles . Of these , 114 were rejected as duplicates , and 36 articles were excluded , as they did not have any information about Leptospira spp . in rats . Additionally , 29 articles that did not describe prevalence of Leptospira spp . in rats were excluded . Twelve publications in languages other than English were also excluded . However , six foreign language articles with an English abstract containing relevant data were included . Three articles describing prevalence of Leptospira spp . in laboratory rats , as well as four articles describing cases of human leptospirosis due to transmission from pet rats , were excluded for the purpose of this review; however , they will be discussed separately in this paper . In addition , 11 relevant articles were manually included through general internet-based searches , and a further 25 articles that reported Leptospira prevalence in different types of rodents or small mammals but had data on rats of the Rattus genus were included . In total , 145 articles published up until June 2018 were included in this literature review . Publication references are listed in S1 List . Including articles in foreign languages ( 157 total ) , five articles were published before 1950 , eight in 1951–1959 , six in 1960–1969 , five in 1970–1979 , eleven in 1980–1989 , seven in 1990–1999 , 32 in 2000–2009 , and 83 in 2010–2018 . Half of the number of articles in foreign languages ( 9/18 ) were published earlier in time , between 1949 and 1970 . The number of studies investigating Leptospira spp . in rats generally increased throughout the years and increased significantly in the last decade . The publications retrieved reported relevant data from a total of 62 geographical locations ( Fig 1; S1 Map ) . Data such as prevalence ranges and number of studies retrieved per geographic location are provided in Tables 1–8 , grouped according to geographical continents or regions . Detailed data on prevalence and serogroup/serovar information from each publication can be found in S1 Table . The top five countries that were reported based on number of articles include India ( n = 13 ) , Malaysia ( n = 9 ) , Brazil ( n = 8 ) , Thailand ( n = 7 ) , and France ( n = 6 ) . Prevalence of Leptospira spp . in rats varied considerably . For example , two studies in Australia reported a very low prevalence of 1 . 7% [16] and 2 . 9% [15] , and studies in China [31] and Ecuador [153] reported a similar prevalence of 3 . 0% . Several studies even reported zero prevalence of Leptospira spp . in rats , such as in Thailand [71] , Madagascar [86] , Tanzania [92] , and the Faroe Islands [98] . Conversely , other studies reported a prevalence of more than 70% , such as in Brazil [137–139 , 142 , 145] , Mexico [120] , Egypt [82] , Réunion [88] , and the Philippines [58] . The prevalence reported from the same country had significant variations as well . For example , in Hawaii , four studies reported a prevalence of 16 . 0% [22] , 24 . 4% [20] , 30 . 2% [21] , and 53 . 3% [19] . However , there were also instances in which independent studies from the same geographic location reported a similar prevalence , such as in Trinidad , with three studies which reported a prevalence of 16 . 5% [133] , 17 . 4% [131] , and 20 . 5% [19] . In Malaysia , of the seven articles retrieved , one reported a prevalence of 3 . 1% [51] , whereas the rest had a similar prevalence between 8% and 18% [50 , 53–57] . A wide variety of diagnostic methods used were reported ( Table 9 ) . The most common diagnostic methods used were microscopic agglutination test ( MAT ) , polymerase chain reaction ( PCR ) , and culture and isolation . The majority of the studies ( n = 90 ) used only one method of detection , either MAT , PCR , culture , or others . Within the methods of PCR and culture , studies used several types of tissues and body fluids for the detection of Leptospira spp . , with the most common being kidney and urine samples . Other samples utilized include blood , milk , liver , spleen , brain , lung , breast , and urinary bladder samples ( Table 10 ) . PCR target genes also varied , and the list of genes and the corresponding number of studies that used them can be found in Table 11 . S2 Table illustrates all relevant data pertaining to diagnostic methods used , including the reported prevalence of Leptospira spp . in rats based on each specific method of detection . A large number of serovars have been reported across all the studies retrieved , representing different geographic locations and continents . For each of those geographic locations , the serovars reported are listed in Tables 1–8 . Studies conducted in Asia reported the highest number of different serovars detected ( n = 30 ) , followed by studies conducted in South America ( n = 28 ) . A comparison of serogroups and serovars detected in all represented countries can be found in S3 Table . Interestingly , serovar Ballum has been reported in all represented countries in Oceania: Australia [16] , Fiji [17] , Hawaii [19–22] , New Caledonia [23] , and New Zealand [13 , 24 , 25] , with the exception of Wallis and Futuna [26] , which did not provide serovar information . In Asia , frequently reported serovars include Icterohaemorrhagiae ( reported in eight countries ) , Autumnalis , Javanica ( reported in six countries ) , Australis , Canicola , Pomona , and Pyrogenes ( reported in five countries ) . The most reported serovar in the Middle East was Icterohaemorrhagiae ( reported in four countries ) , whereas the most reported serovar in Africa was Canicola ( reported in three countries ) . In Europe , serovars Icterohaemorrhagiae and Sejroë were the most frequently reported serovars , detected in eight and three countries , respectively . Serovar Icterohaemorrhagiae was also the most frequently detected in North America , South America , and the Caribbean . Several serovars of the Icterohaemorrhagiae serogroup have been frequently reported in the Caribbean , including serovars Copenhageni , Icterohaemorrhagiae , and Mankarso . The most frequently reported serovar worldwide was Icterohaemorrhagiae , detected in 36 of 43 countries that provided serovar information . Among all rat species sampled in all studies , R . norvegicus and R . rattus were the two most frequently sampled species ( Tables 1–8 ) . Studies representing countries in Asia reported the most diverse species of rats sampled , with other species such as R . exulans and R . argentiventer in Cambodia , Malaysia , Thailand , Laos , and Vietnam; R . tanezumi in Cambodia , Laos , Thailand , and Vietnam; and R . losea in China , Cambodia , Laos , and Thailand ( Table 2 ) . Studies from Malaysia reported many other rat species that were not identified and sampled in other countries , such as R . diardii , R . bowersi , R . muelleri , R . rajah , R . sabanus , R . tiomanicus , and R . whiteheadi . Overall , 30 . 3% ( 4 , 829/15 , 917 ) of R . norvegicus , 17 . 8% ( 2 , 376/13 , 353 ) of R . rattus , 10 . 9% ( 344/3 , 143 ) of R . exulans , 19 . 3% ( 87/451 ) of R . argentiventer , 3 . 4% ( 15/435 ) of R . tanezumi , and 13 . 1% ( 18/137 ) of R . losea were reported to be positive for Leptospira spp . In general , R . norvegicus was largely found to have a higher prevalence than R . rattus within the same studies . However , the opposite was also reported—i . e . , the prevalence of Leptospira spp . in R . rattus was higher than R . norvegicus within the same studies . For example , on Réunion Island , one study reported a prevalence of 38 . 5% ( 214/562 ) in R . rattus , whereas R . norvegicus had a prevalence of 30 . 6% ( 52/170 ) [89] . The same was reported in New Zealand [13 , 25] , with R . rattus having higher prevalences ( 33 . 3%–34 . 4% ) than R . norvegicus ( 25 . 7%–25 . 9% ) . The prevalence of Leptospira spp . in the various rat species still varied greatly among all the studies . Detailed information about Leptospira prevalence in each rat species per study can be found in S4 Table . We also found three studies pertaining to natural Leptospira infection in laboratory albino rat ( R . norvegicus ) colonies . Overall , relatively high prevalences were reported and could be a good discussion point . The three articles reported prevalences of 67 . 0% [156] ( part 1 ) , 26 . 9% [156] ( part 2 ) , 90 . 0% [157] , and about 68 . 0% [158] . This demonstrated that Leptospira infection could even be endemic in laboratory colonies within controlled environments , most likely primarily caused by either carrier adult rats [156 , 158] or infection from wild rats [158] . Most of the infections were caused by serovar Icterohaemorrhagiae [156 , 158] , but other serovars were also reported , such as serovar Javanica [157] . In addition , four European articles reported cases of human leptospirosis associated with transmission from pet rats , which were not included in this review . Two articles published in 2008 reported one case in 2006 in the UK [159] and another case in Germany ( year not specified ) [160] . L . interrogans serogroup Icterohaemorrhagiae was identified in both cases . An article published in 2012 in the Czech language reported three human patients treated for leptospirosis from 2005 to 2010 in Czech Republic , with likelihood that they acquired the infection from their pet rats [161] . Another article published in 2017 identified six human leptospirosis cases from 2009 to 2016 in Belgium and France , for which pet rodents were the source of infection [162] . Of the six cases , three were identified to be caused by serogroup Icterohaemorrhagiae and one by serogroup Sejroë .
With rapid global urbanization and 68% of the world’s human population projected to be living in urban areas by the year 2050 ( 55% as of 2018 ) [163] , in addition to the increasing loss of natural habitats , it is anticipated that the majority of human–wildlife interactions would transpire in these areas . Wild rats seem to benefit from urbanization and thrive in urban and peridomestic environments , leading to frequent human exposure to these species [164] . R . norvegicus and R . rattus have become ubiquitous in urban environments and are significant sources of many zoonotic pathogens that can result in mortality and morbidity in humans and animals , and leptospirosis is one of those important rat-associated zoonoses . Because of knowledge gaps in the ecology of rats in urban environments , urban rat control is largely ineffective [165]; thus , it is critical to acquire a deeper understanding of the ecological and demographical drivers of zoonotic pathogen transmission in urban environments [164] . In addition , knowing the prevalence of a specific rat-associated zoonosis in a geographic region is essential in targeted pathogen screening in order to reduce underdiagnoses and misdiagnoses . In a broad perspective , significant information has been documented in almost every country included in this literature review . However , the results reveal findings consistent with the common knowledge that incidence of leptospirosis is higher in tropical or warm-climate countries compared with countries in temperate regions . Of the top five countries represented in terms of number of articles , four of them are in tropical regions: India , Malaysia , Brazil , and Thailand . However , more studies representing tropical countries were retrieved compared with those from temperate regions . Many of the studies conducted also reported prevalences based on small sample sizes , which might not be indicative of the true distribution of Leptospira spp . in those geographic locations . This could be because of the convenience sampling of rats in conjunction with other rodents or animals; nevertheless , data pertaining to the rat samples were extracted for this review . In addition , the actual number of rats and population density in the wild may vary considerably among all geographic locations , which might indirectly affect the differences in prevalence of Leptospira spp . Differences in rat species predominating in a certain region may also potentially contribute to the differences in prevalence , in which further research is necessary for evaluation . Several studies revealed zero prevalence of Leptospira spp . in the rats , which might be due to a number of possible reasons . For some of those studies , it could be simply due to the small sample size , with less than 50 rat samples obtained in studies in South Korea [61 , 63] , Thailand [71] , Mayotte [19] , Canada [116] , Austria [94] , and Hungary [94] . Another reason could be due to climatic conditions , which resulted in zero prevalence reported in a study in the Faroe Islands , to which they concluded that it could either be too cold for Leptospira transmission or too cold for the maintenance of adequate densities of rats [98] . An article from Madagascar reported a prevalence of 0% despite having a relatively decent sample size , and it concluded that Leptospira spp . was likely not present in Madagascar [86] . However , a more recent article reported a prevalence of 40 . 0% [85] , which could indicate a relatively recent change in geographical distribution of Leptospira spp . in Madagascar or that the methodology used in the earlier study was not optimal . A study done in Tanzania revealed zero prevalence in 384 rodents ( including 320 rats ) , which is a notable finding , considering the rodents were sampled in areas known to have a high incidence of human leptospirosis . This might indicate that peridomestic rodents are not a major source of human infection in that area [92] . Prevalences reported by studies from the same country also varied , which could be because of reasons such as differences in methodology or sampling from different parts of that country . As seen in the Results section , methods of detecting for Leptospira spp . varied greatly among all the studies retrieved , which may have certain implications on detection sensitivity . Some diagnostic methods such as PCR and other molecular methods detect Leptospira nucleic acids , whereas serological methods such as MAT detect anti-Leptospira antibodies , which only indicates exposure to the bacterium and not necessarily a current infection . Moreover , such serological techniques possess a risk of cross-reaction; thus , their results should be interpreted with caution . PCR protocols , in general , are used for detecting pathogenic Leptospira spp . , and isolation of infecting Leptospira strains followed by cumbersome serological methods are required for identifying the serovars , which is not pursued in many studies reported . In culture methods with the usage of dark-field microscopy for identification of spirochetes , there may be possibilities of human error or issues regarding ambiguity of results as well , with possible false positives or negatives . In addition , varied tissue samples were used among the publications retrieved , and some studies used only one type of tissue sample , whereas others used multiple types of samples , pooled or unpooled . There are also different sensitivities and specificities for each of the various diagnostic methods . All these factors could affect the detection of Leptospira spp . , which may have contributed to the varied prevalences observed . The diversity of serovars detected varied considerably among studies and geographic regions . This review revealed that studies conducted in Asia and South America detected the highest number of different serovars , which could have been influenced by several factors . Methodologies in general could influence this , with different methods of serovar characterization being used among the studies . In seroprevalence studies that used MAT , serovars not included in the diagnostic panel would not be detected and , thus , affect the study results . With Asia and South America being tropical regions , there could be plausible correlations with the large variety of serovars present . Factors to be considered are the higher incidence of Leptospira spp . in tropical regions and the relatively higher number of studies retrieved from Asia and South America , which could provide higher serovar diversity . Several possible correlations with regard to geographic distribution of infecting serovars could be observed . Serovar Ballum could be the main infecting serovar in rats in Oceania , with all studies that provided serovar information having identified the presence of serovar Ballum . Serovar Sejroë was reported in European countries more than countries from other regions . Interestingly , most of the studies conducted in the Caribbean concurrently identified several serovars of the Icterohaemorrhagiae serogroup ( serovars Copenhageni , Icterohaemorrhagiae , and Mankarso ) more frequently than studies in other geographic regions . Overall , serovar Icterohaemorrhagiae was the most frequently reported serovar , identified in almost all represented geographic locations . In countries that did not report serovar Icterohaemorrhagiae , certain methodological factors discussed earlier in this section could be the reason for the absence . For example , in Australia , despite retrieving three articles , only one provided serovar information . However , the extremely low prevalence ( 1 . 7% ) reported in that article meant that the true variety of serovars present may have been underestimated . Comparing the two most common rat species sampled , reported Leptospira prevalence was generally higher in R . norvegicus than R . rattus . This may suggest a possible correlation with the species of rats and susceptibility of Leptospira infection . However , many of the studies use morphological characteristics and general appearance to determine the exact rat species and , thus , may cause inaccurate reporting of results . For a number of studies , rat species were not determined and reported , which may have certain implications . As there are many other species of small mammals and rodents that resemble rats , they may not be of the genus Rattus and , therefore , are not considered “true” rats . The taxonomy of rats has also changed throughout the years , and rats that were once known to be under the Rattus genus may not be classified as one in the present day . Twleve species reported by studies have been identified to be potentially not of the Rattus genus or are subspecies of R . rattus ( S5 Table ) [166 , 167] . If such small mammals and rodents were misidentified as rats of the Rattus genus and reported in studies , this could be another reason for inaccurate reporting of results . In addition , some studies also combined the results of all rodents sampled , including mice and other rodents , and did not provide separate data and results for each type of animal . This caused inconsistencies in extraction of data from those articles . For future studies , inclusion of all information such as exact species of rats and the individual prevalence of each of those species will lower the inconsistency . Our review also identified relatively high prevalences of Leptospira spp . in laboratory rat colonies within controlled environments , indicating primary carrier status in laboratory rats or inadvertent transmission and spillover infection from wild rats . In addition to possible interference with biomedical research , one of the main implications of high Leptospira prevalence in laboratory rat colonies is the zoonotic potential to laboratory animal caretakers , as evidenced by Natrajaseenivasan and Ratnam [157] , who reported a very high seropositivity ( 91 . 0% ) in animal house workers . Several cases of human leptospirosis associated with transmission from pet rats demonstrate that wild rats are not the only sources of rodent-associated human infection . With the rising popularity of keeping rats as household pets , there may be concerns about pet rats being a potential source of human Leptospira infection , and exposure to infected pet rats could pose a significant public health risk .
This review summarizes the literature on global prevalence and distribution of Leptospira infection in rats . Prevalence of Leptospira spp . varies widely , with a considerably high prevalence reported in many countries involving multiple rat species . This review also demonstrated several weaknesses to the current methods of detecting and documenting Leptospira prevalence in rats worldwide . As such , this necessitates a call for standardized protocols for the detection and reporting of such studies , especially pertaining to the diagnostic methods used . In addition , appropriate quality control programs using standardized region-specific diagnostic panels , as well as improvements in techniques for serovar differentiation , could be proposed . A deeper understanding of the ecology and epidemiology of Leptospira spp . in rats in urban environments is warranted . It is also pertinent for rat control programs to be implemented in conjunction with increased efforts for public awareness and education regarding leptospirosis transmission and prevention . | The role of rodents in the transmission of many diseases , including leptospirosis , is widely known . Rats abundant in urban and peridomestic environments are the most important reservoirs and sources of Leptospira infection in humans and animals . Leptospirosis is a significant but neglected disease of humans and animals that is increasing in incidence in regions affected by natural disasters . This paper summarizes the global prevalence and distribution of Leptospira infection in rats and will add to the literature that supports research , education , and public awareness regarding leptospirosis transmission and prevention . | [
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"animal"... | 2019 | Leptospira infection in rats: A literature review of global prevalence and distribution |
Tumor cells develop different strategies to cope with changing microenvironmental conditions . A prominent example is the adaptive phenotypic switching between cell migration and proliferation . While it has been shown that the migration-proliferation plasticity influences tumor spread , it remains unclear how this particular phenotypic plasticity affects overall tumor growth , in particular initiation and persistence . To address this problem , we formulate and study a mathematical model of spatio-temporal tumor dynamics which incorporates the microenvironmental influence through a local cell density dependence . Our analysis reveals that two dynamic regimes can be distinguished . If cell motility is allowed to increase with local cell density , any tumor cell population will persist in time , irrespective of its initial size . On the contrary , if cell motility is assumed to decrease with respect to local cell density , any tumor population below a certain size threshold will eventually extinguish , a fact usually termed as Allee effect in ecology . These results suggest that strategies aimed at modulating migration are worth to be explored as alternatives to those mainly focused at keeping tumor proliferation under control .
Tumor cells possess a remarkable phenotypic plasticity that allows for adaptation to changing microenvironmental conditions [1 , 2] . Well-known examples are the epithelial-mesenchymal transition [3 , 4] and the shift from ATP generation through oxidative phosphorylation to an anaerobic , glycolytic metabolism , often referred to as the Warburg effect [5] . A further example is phenotypic plasticity with respect to cell proliferation and migration [6] , a phenomenon related to the “go-or-grow” mechanism . Such a migration-proliferation dichotomy has been observed for non-neoplastic cells [7 , 8] as well as in the course of tumor development [9–11] . The precise molecular mechanisms underlying this dichotomy remain poorly understood . It has been suggested that the switch between migrating and proliferative phenotypes is dependent on the cells’ microenvironment such as growth factor gradients [7] , properties of the extracellular matrix [12] or altered energy availability [13] . In this context , several mathematical models have shown that the migration-proliferation plasticity has a major impact on tumor spread [14–19] . There is a growing body of evidence which suggests that local cell density is correlated with gradients of nutrients , secreted factors , oxygen or toxic metabolites [20 , 21] . Hence , local cell density can be considered as a core factor for analyzing the dependence of the switch on the tumor microenvironment . However , while the consequences of density-dependent migration-proliferation plasticity on local tumor spread , as an essential feature of tumor invasion , have been explored already [14 , 18 , 19] , the potential effects of this type of plasticity on tumor initiation and persistence have not been investigated so far . In this work we point out some aspects of the phenotypic plasticity between migratory and proliferative phenotypes for tumor growth that have been unnoticed so far . To do this , we make use of a suitable mathematical model to be described below . We note in this context that mathematical models have proven successful for analyzing various aspects of tumor dynamics , see for example [22–24] . More precisely , we formulate and study a model that allows to derive the overall tumor cell population dynamics as an emergent property resulting from individual cell behavior . This is achieved by means of a cellular automaton model which extends model rules used in previous studies , where the impact of a migration-proliferation dichotomy has been investigated with a clear focus on tumor invasion [19 , 25 , 26] . Here , for the first time , the influence of a density-dependent migration-proliferation plasticity on tumor growth and persistence is studied . In our model , the switch between migratory and proliferative phenotypes is made explicitly dependent on the microenvironment , in particular on cell density . Analysis of our model reveals that two dynamically different regimes can be distinguished . If cell motility increases with local cell density , even a small initial tumor population will always grow . This regime can be associated to a biological situation where contact inhibition of cell migration ( CIM ) is downregulated . On the contrary , if cell motility decreases with local cell density , which is the case if CIM is present , tumor colonies which are small enough can be driven to extinction by the intrinsic cell population dynamics . We unveil that this behavior is a consequence of negative growth rates emerging at low densities , a phenomenon called Allee effect in ecology [27] . Accordingly , controlling tumor cell migration would have significant consequences not just for tumor dissemination , but also for overall tumor progression . In fact , our work predicts that tumors can potentially be driven to extinction if CIM is externally enhanced . However , loss of such type of inhibition will invariably lead to tumor persistence .
We develop a stochastic , spatio-temporal cell-based model to study the effects of density-dependent phenotypic plasticity . In this way we account for single cell behavior that depends on the local , spatial microenvironment and for microscopic fluctuations which reflect cellular and microenvironmental heterogeneity . To do that , a discrete model , namely a lattice-gas cellular automaton ( LGCA ) is defined . LGCA models are well-suited to model cell-cell interaction and cell migration [28–30] . The LGCA model is described on a discrete d-dimensional regular lattice ℒ with periodic boundary conditions . Each lattice node r is connected to its b nearest neighbors by unit vectors ci , i = 1 , … , b , called velocity channels . The total number of channels per node is defined by K ≥ b , where K − b is an arbitrary number of channels with zero velocity , called rest channels . Each channel can be occupied by at most one cell at a time . We consider a tumor population of two mutually exclusive cell phenotypes , moving ( m ) and resting ( r ) . Moving cells reside on the velocity channels , indexed by i = 1 , … , b , while resting cells are located within the rest channels , indexed by i = b + 1 , … , K , of the lattice . The total number of cells at time k and node r is given by n ( r , k ) = nm ( r , k ) + nr ( r , k ) , where nm and nr denote the moving and resting cell numbers , respectively . The parameter K is a local cell number bound . This constraint is imposed , since the maximal cell number in a given volume is limited in a biological tissue . Notice that K corresponds to a carrying capacity density and thereby accounts for cell crowding effects . The time evolution of our model is defined by the following rules: ( R1 ) cells of both phenotypes die with probability rd , ( R2 ) resting cells proliferate with probability rb unless the local carrying capacity is reached , i . e . all rest channels are occupied , ( R3 ) cells may change their phenotype from moving to resting ( respectively , from resting to moving ) with probability rs ( respectively , 1 − rs ) , ( R4 ) moving cells perform independent random walks . In the LGCA , rules ( R1 ) - ( R4 ) are realized by applying three operators: A cell reaction operator changes the local cell numbers nr , nm on each node according to ( R1 ) - ( R3 ) . A reorientation operator randomly shuffles the configuration within the velocity channels at each node . By applying a propagation operator , moving cells are shifted one lattice unit in directions determined by their velocities . Both reorientation and propagation steps define cell movement , ( R4 ) . At each discrete time point k , the composition of the three operators is applied independently at every node on the lattice to compute the configuration at time k + 1 , see Fig 1 ( a ) and 1 ( b ) and S1 Text . We hypothesize that the phenotypic switch between proliferative and migratory cell behavior depends on the local cell density . We regard local cell density as the result of tumor cell interactions with extracellular matrix components , chemical cues and other stromal cells . Therefore , we model all these effects by means of their impact on cell density . We do not aim to reproduce the switch process in all intracellular detail . Rather we coarse-grain the intracellular details into stochastic cell-based rules that allow for an analytically tractable model to provide a basic understanding of the underlying dynamics . Since it is not known how the phenotypic switch depends on cell density , we decide for the most simple form which is monotonous dependence . Then , two complementary types of plasticity can be distinguished: attraction towards or repulsion from highly populated areas . In the attraction case , cell motility decreases with local cell density , so that proliferation is favored in densely populated areas . In the repulsion case , cells tend to escape from highly populated regions , that is cell motility increases with local cell density , and proliferation is favored in sparsely populated areas . The switch probability rs ( ϱ ) ( respectively 1 − rs ( ϱ ) ) that a moving cell becomes resting ( or a resting cell becomes moving ) is modeled as a sigmoidal shaped function rs:[0 , 1] → ( 0 , 1 ) that depends on the cell density ϱ = n/K at the given node and two parameters κ ∈ ℝ and θ ∈ ( 0 , 1 ) , r s ( ϱ ) = 1 2 ( 1 + tanh ( κ ( ϱ - θ ) ) ) , ϱ ∈ [ 0 , 1 ] . ( 1 ) The absolute value of κ specifies the intensity of the switch’ density dependence while its sign determines whether the attraction case ( κ > 0 ) or the repulsion case ( κ < 0 ) holds . Parameter θ represents the critical cell density value at which switching probabilities from one phenotype into the other are equal . We remark that the functional form of the switching function has been proposed in a previous study [19] where , however , tumor invasion behavior has been studied . A plot of the switching probabilities Eq ( 1 ) is given in Fig 1 ( c ) and 1 ( d ) . We simulate the LGCA model on a two-dimensional square lattice ( d=2 , b=4 ) with 104 nodes . We explore the impact of the switch intensity κ and the switch position θ on the persistence of a growing tumor population . To this end , we investigate the total population growth rates in the ( κ , θ ) -parameter space and identify the parameter regimes for population survival and extinction . Proliferation and death probabilities are chosen such that 0 < rd ≪ rb ≪ 1 . The initial model condition reflects a biological situation where the tumor is small and spatially constrained . At the initial time a fixed number of moving and resting cells per node is placed in a predefined radius from the lattice center . In the simulations , the initial cell density is varied by changing the percentage of occupied nodes within this radius . The results do not depend on the fixed initial radius ( simulations not shown ) but on the initial cell density .
Fig 2 gives an overview of the observed cell population dynamics . In the repulsive case ( κ < 0 ) , the population always persists , regardless of the initial population density . In the attractive case ( κ > 0 ) , either survival or extinction may be observed , where the particular behavior is dependent on the specific values of κ and θ . Further , we investigate the survival of populations in the attractive case . For a wide range of different initial population densities , we record the frequency of extinction events . Sufficiently long simulation runs are performed to ensure that survival , when observed , is not a transient dynamical behavior ( see S1 and S2 Videos ) . The results depicted in Fig 3 ( a ) show that the smaller the initial population density the higher the probability of population extinction . Above a critical initial population density , the population always persists . Additionally , we record the population size distributions after a certain number of time steps for different initial cell densities , see Fig 3 ( b ) . One observes that low-density initial populations in the critical regime show bimodal stationary size distribution , indicating the possibility of either population extinction or persistence . The observed emergent population behavior can be understood intuitively by considering the feedback mechanisms on the cell scale , in particular the regulation of proliferative or migratory behavior , for the different types of phenotypic plasticity ( attractive or repulsive ) , see Fig 4 . In the repulsion case ( κ < 0 ) , increasing local cell density has a negative feedback on proliferation . In a sparsely populated environment , cells are predominantly resting . In this case , when cell replication takes place , the resulting increase in local cell density triggers the switch to a migratory phenotype . Migration of cells decreases local cell density which again triggers the switch towards the resting cell phenotype . As a consequence , proliferation and migration phases alternate , and the population always persists . In the attraction case ( κ > 0 ) , increasing local cell density has a positive feedback on proliferation . Accordingly , cell proliferation leads to increased cell density which implies further proliferation . On the other hand , migration of cells locally decreases cell density that leads to more migratory cells . If the portion of resting cells in sparse environment is large enough , cell replication dominates cell death . Thus , the positive feedback on proliferation might result in population growth . However , if cells in sparse environment almost exclusively migrate , they eventually die , and the result is population extinction . The feedback mechanisms described above are just an intuitive picture of the emergent population dynamics . To better understand the connection between individual cell scale and the population properties , we derive a mean-field description of our model . It facilitates to link the microscopic interactions at the cellular level to effects that take place at the macroscopic scale . In particular , it allows us to analytically investigate the existence of an extinction threshold . The LGCA model is composed of a birth-death process describing the single-node cell reactions and a cell-movement process which describes the exchange of cells between neighboring nodes . Therefore , we derive mean-field approximations for each process separately first and then combine the resulting descriptions into a partial differential equation ( PDE ) for the whole tumor growth process . We then show that the resulting PDE , which exhibits a nonlinear diffusion term , has a kinetic term which is of a bistable nature in a suitable parameter range . Bistability is characterized by the presence of two stable steady states; one corresponds to the situation where the tumor dies out and the other one where the tumor persists . Bistable dynamics is significantly different from monostable dynamics , where only one stable steady state exists which corresponds to the situation where the tumor always persists . It is important to stress that the bistable behavior , which is already observed in the LGCA model , is preserved after the mean-field approximation thereof , as shown by the form of the kinetic term appearing on the corresponding PDE to be derived below . If cell migration is neglected in the LGCA dynamics , the deterministic net changes occurring in the cell density of a given node between two consecutive times k and k+1 are determined by cell reactions only . Scaling time and transition rates such that the microscopic time k corresponds to the macroscopic time t = τk , τ ≪ 1 , one obtains two ordinary differential equations for the migratory and proliferative cell density , respectively . However , such a system is hard to analyze analytically because of non-linearities which arise from the phenotypic switching . In order to facilitate analytical treatment , like bifurcation analysis , we assume that the switch dynamics is much faster than cell number changes due to proliferation and death . Furthermore , we consider the system to be in equilibrium with respect to the switching dynamics . Hence , for low cell density , the fractions of resting and moving cells are given by rs ( ρ ) and 1 − rs ( ρ ) , respectively ( see S1 Text ) . The overall macroscopic growth term of the LGCA model can then be approximated by F ( ρ ) = R b r s ( ρ ) ρ ( 1 - ρ ) - R d ρ , ( 2 ) with ρ: = ρm + ρr , where ρm and ρr is the mean cell density of moving and resting cells , respectively , at a given position . The parameters Rb and Rd relate the models’ proliferation and death parameters , rb and rd , to the corresponding real time step length τ . If the average cell cycle time of a cell is given by Tb and the average life time of a cell by Td , then Rb = 1/Tb ≈ rb/τ and Rd = 1/Td ≈ rd/τ ( see S1 Text ) . Stability analysis of the macroscopic net growth term F ( ρ ) shows that the behavior depends mainly on the type of phenotypic plasticity , attractive ( κ > 0 ) or repulsive ( κ < 0 ) ( see S1 Text and S1 Fig ) . More precisely , one finds that there are essentially two regimes , a monostable one for κ < 0 and those values of κ > 0 for which rs ( ϱ ) rb > rd for small density values ϱ , and a bistable one for κ > 0 and r s ( ϱ ) r b < r d . ( 3 ) In the monostable regime , the cell density stabilizes at high density values where the exact location of the stable state is determined by the carrying capacity . In the bistable regime , additionally to the stable high-density state , the extinction state is stable . The critical region where κ > 0 and rs ( ϱ ) rb = rd for small density values ϱ is depicted in Fig 2 for ϱ = 0 . 25 . This is in good agreement with the simulation results . The stability of the extinction state in the bistable regime is due to the fact that the per capita growth rate F ( ρ ) /ρ is negative for small density values , see Fig 5 . Such negative density-dependence is termed Allee effect in the ecological literature and has been attributed strong impact on population persistence and invasion properties [31] . Here , the Allee effect emerges as a consequence of the phenotypic plasticity with respect to migratory and proliferative tumor phenotypes . The mean-field approximation for the LGCA cell movement process , detailed in S1 Text , is also derived under the assumption that the switch dynamics are much faster than cell proliferation and death dynamics . Since then , for low cell densities , a density-dependent portion rs ( ρ ) of cells is in the resting state , the diffusion coefficient turns out to be density-dependent . The LGCA migration process is isotropic with respect to the principal lattice directions . Along any direction , the diffusion equation for the mean-field cell migration in the macroscopic limit is given by ∂ t ρ = ∂ x ( D ( ρ ) ∂ x ρ ) , t ≥ 0 . ( 4 ) where the diffusion coefficient satisfies D ( ρ ) = D ( 1 - r s ( 0 ) 2 - r s ′ ( 0 ) ρ - 3 2 r s ′ ′ ( 0 ) ρ 2 ) , ρ ≪ 1 , ( 5 ) with D being the diffusive scaling constant that is related to the single cell motility . Combining the mean-field descriptions for the cell reaction and the cell migration processes , we obtain a single partial differential equation ( PDE ) , ∂ t ρ = ∂ x ( D ( ρ ) ∂ x ρ ) + F ( ρ ) , ( 6 ) where the macroscopic growth term is given in Eq ( 2 ) and the density-dependent diffusion coefficient is given in Eq ( 5 ) . Scalar reaction-diffusion equations such as Eq ( 6 ) are comparatively easier to analyze than the original LGCA model , particularly in the simplified case where the diffusion coefficient D ( ρ ) is constant and the kinetic term is either purely monostable or bistable . For instance , in any of these situations , the resulting equation admits a particular type of solutions , traveling waves , which have been used as a paradigm to describe tumor invasion [32] . As recalled in [33] , semilinear equations admit front travelling waves of the form u ( x , t ) = U ( x − ct ) = U ( z ) , where U ( z ) connects two steady states of the equation as z tends to ±∞ . In the bistable case , the wave speed is uniquely determined and can be positive or negative , depending on the precise form of F ( ρ ) . In contrast , in the monostable case , infinitely many ( only positive ) wave speeds are possible , all of which should satisfy an explicit lower bound [34 , 35] . Here , we are not interested in exploring the existence of traveling waves for the highly nonlinear Eq ( 6 ) , since such particular type of solutions cannot keep track of extinction phenomena as those stressed in this work . We rather wish to point out another important difference between the monostable and bistable cases , which has been thoroughly discussed in the case of linear diffusivity . Namely , in the monostable case , invasion cannot be stopped once it starts [36 , 37] , whereas solutions corresponding to sufficiently small initial populations may eventually become extinct in the bistable case [38] . This issue is , for nonlinear diffusion , an interesting target for further theoretical studies .
In this work , we studied the effect of plasticity between migratory and proliferative behavior on tumor growth by means of a cellular automaton model . The trigger for the phenotypic switch was assumed to depend on the microenvironment via the local cell density . We found that this migration-proliferation plasticity has dramatic consequences for tumor growth . Two parameter regions with respect to the migratory cell behavior can be distinguished where fundamentally different tumor growth dynamics at the tissue scale are observed . In one case , called repulsive regime here , the tumor cell population will inevitably grow . In the other case , called attractive regime , we identified conditions under which sufficiently small tumors die out and tumor growth is only observed if the tumor size is above a certain threshold . We revealed that the extinction behavior is a consequence of an emergent negative net cell growth rate at low cell densities , a phenomenon known as Allee effect in ecology . Comparing to previous studies [14 , 18 , 19] that investigate the effect of migration-proliferation plasticity with respect to the late phase of invasion and tumor spread , here we focus on an early phase of tumor growth and in particular initiation and persistence . Tektonidis et al . [19] have shown that glioma invasion data can be explained by assuming that the switching rates increase with increasing cell density while constant switching rates failed . However , it is not ruled out in this study that other parameter combinations , which might correspond to the attractive or repulsive case in our model , fit the data equally well . Finally , the authors in [19] refer to in vitro invasion data of a high-grade glioma cell line that according to our current results are likely to correspond to the repulsive case . The Allee effect seems to have been overlooked so far in the context of tumor growth and persistence . In our study , the Allee effect emerges from the specific regulation of the migration-proliferation plasticity at the cellular scale and has not been assumed a priori . Since the Allee effect has been shown in ecology to change optimal control decisions , costs of control and the estimation of the risk posed by potentially invasive species [31] , we expect it to be critical for tumor growth control as well . We point out that the Allee effect observed here is actually stochastic , displayed by the discrete cellular automaton model . This means that it is not an artifact arising from the mean-field approximation where stochastic effects are averaged out . In fact , our model actually accounts for stochastic fluctuations that may be particularly relevant for small to moderate size populations , a situation that may be relevant for tumor initiation . In our model , the microenvironmental influence on the phenotypic switch between moving and proliferative cell behaviors is incorporated through a local cell density dependence . This is a plausible assumption since further potential environmental influences such as nutrient and oxygen supply , molecular signal gradients or other cell-cell interactions are mediated through and correlate with the local cell density . Note that this reduction of the underlying complexity is not a drawback of the model but allows to reveal inherent organizational principles . We expect that important population features like persistence and extinction could still be observed if the dependence of plasticity on local density is resolved into a more precise dependence on particular cell-microenvironment interactions , a subject that we intend to address in the future . The stochasticity of our model incorporates heterogeneity of the microenvironment in its simplest form . Studying the implications of heterogeneity was not the focus of the current investigation as it would increase the model complexity and limit analytical investigations . However , ecological studies show that in many situations environmental heterogeneity has minor effects in growth dynamics where the Allee effect is present [39 , 40] . In the future , investigations are required to analyze the importance of heterogeneity for specific tumors . The Allee effect might have further implications for tumor spread . Here , we derived a mean-field description for the tumor cell density which is given by a reaction-diffusion equation with density-dependent diffusion coefficient and a potentially bistable reaction term . The behavior of solutions of fully nonlinear equations as Eq ( 6 ) is less known , although preliminary theoretical results [41] indicate a wealth of possible behaviors , including standing waves , oscillatory front and monotonic front solutions . It therefore seems that the Allee effect has a significant impact on population dispersal , which may be particularly relevant in the case of tumor dissemination . Recently , in some tumors , the existence of a migration-proliferation dichotomy has been questioned [42] . It has been shown that individual cells in human malignant melanoma and lung cancer cell lines exhibit either migratory or proliferative behavior , but on the population level , migration and proliferation occur simultaneously . Experimental limitations due to the used in vitro approaches do not lead to a conclusive picture yet . Our contribution with respect to this discussion consists of two points . First , we provide a theoretical model which might help to resolve the differences between observations at the cellular and the population level . Second , for tumors with an established migration-proliferation plasticity at the cellular level , we provide predictions on overall tumor growth . Our results might shed some light on the interpretation of recent experiments on tumor progression . For cell lines cultured from low-grade tumors , characterized by low cell density and well-differentiated tumor cells , it has been observed that they have low chances of persistence and low reproducibility in vivo and in vitro [6 , 12 , 43 , 44] . On the contrary , cell lines from high-grade tumors , which are characterized by increased cellular density and less differentiated cells , repeatedly persist . Until now , the underlying mechanisms that lead to such different behaviors are unclear . We conjecture that the behavior of low-grade tumors resembles the attractive regime in our model while high-grade tumors behave as in the repulsive model regime . We suggest that the emergence of an Allee effect in low-grade tumors explains the existence of subcritical populations with low persistence probabilities . In contrast , the high-grade tumor cells always persist . Thus , we propose that the progression to malignancy may result from altered adaption to the cellular microenvironment with respect to the regulation of cell migration and proliferation . Concretely , we conjecture the glioma progression from low-grade glioma tumors to high-grade secondary gliomas corresponds to the evolution of attractive to repulsive cell dynamics , i . e . change in the sign of parameter κ . The theoretical findings in our study might also provide suggestions for the design of new tumor therapies . Standard tumor therapy , such as chemo- and radiotherapy , are directed towards controlling cell proliferation . However , a recent study demonstrated that neoadjuvant chemotherapy selects for more migratory phenotypes at the expense of proliferative ones [45] . Our study shows that a possible therapeutic approach for malignant tumors is to combine conventional therapies with adjuvant treatments that restore sufficient contact inhibition of cell migration ( CIM ) . In our model , CIM relates to a situation where cell motility decreases with increasing local cell density ( attractive regime ) . In this case , if CIM is enforced , our model predicts that a sufficiently small tumor may die out due to the intrinsic cell population dynamics . On the contrary , if cell motility increases with local cell density ( repulsive regime ) , which corresponds to CIM downregulation , any tumor inevitably grows and recurrence cannot be prevented . It is well known that malignant tumor cells lose sensitivity to contact inhibition of migration [46 , 47] . Our study suggests that this is not only a bystander effect but might be a key determinant of tumor’s fate . Further investigations are required for the experimental validation of our hypothesis . | Controlling tumor growth remains a major medical challenge . Current clinical therapies focus on strategies to reduce tumor cell proliferation . However , during tumor progression , tumor cells may switch between proliferative and migratory behaviors , thereby allowing adaptation to microenvironmental changes that result in variations in local tumor cell density . We herein explore by means of a mathematical model the impact of migration-proliferation plasticity on tumor initiation and persistence . Our work suggests that small tumors can become extinct solely by their intrinsic cell population dynamics if cell motility decreases along with local cell density . In contrast , if cell motility increases with cell density , the tumor inevitably grows . Our model suggests that the regulation of cell migration plays a key role in tumor growth as a whole , making this feature a potential target for clinical studies . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | An Emerging Allee Effect Is Critical for Tumor Initiation and Persistence |
Schistosoma japonicum , which remains a major public health problem in the Philippines and mainland China , is the only schistosome species for which zoonotic transmission is considered important . While bovines are suspected as the main zoonotic reservoir in parts of China , the relative contributions of various non-human mammals to S . japonicum transmission in the Philippines remain to be determined . We examined the population genetics of S . japonicum in the Philippines in order to elucidate transmission patterns across host species and geographic areas . S . japonicum miracidia ( hatched from eggs within fecal samples ) from humans , dogs , pigs and rats , and cercariae shed from snail-intermediate hosts , were collected across two geographic areas of Samar Province . Individual isolates were then genotyped using seven multiplexed microsatellite loci . Wright's FST values and phylogenetic trees calculated for parasite populations suggest a high frequency of parasite gene-flow across definitive host species , particularly between dogs and humans . Parasite genetic differentiation between areas was not evident at the definitive host level , possibly suggesting frequent import and export of infections between villages , although there was some evidence of geographic structuring at the snail–intermediate host level . These results suggest very high levels of transmission across host species , and indicate that the role of dogs should be considered when planning control programs . Furthermore , a regional approach to treatment programs is recommended where human migration is extensive .
Infection by the Asian blood fluke Schistosoma japonicum remains an important public health burden in the Philippines , China and parts of Indonesia , despite continued efforts of ongoing control programs [1] . In the Philippines alone , it has been estimated that approximately 6 . 7 million people live in areas endemic for S . japonicum [2] . S . japonicum is unique among the species of schistosomes infecting humans , in that it can infect more than 40 other species of mammalian hosts and is the only species for which zoonotic transmission is considered important [3] . Recent studies by our group in Samar , the Philippines , found high prevalence and intensities of S . japonicum infection in dogs and rodents [4] , with intensities of infections in dogs at the village level found to be associated with the intensity of human infection [5] . Conversely , the same data used in a transmission dynamics model suggest that rats may play some role in human infection [6] . However , from such parasitological data alone it remains unclear which , if any , of these animals are most important as zoonotic reservoirs for human infection . Molecular tools are increasingly being applied to address questions concerning parasite epidemiology [7] , and the usefulness of molecular markers as tools for studying the transmission and host-specificity of parasites has been recently highlighted [8] . For example , molecular studies of Ascaris nematode populations in pigs ( A . suum ) and humans ( A . lumbricoides ) suggest there is significant genetic subdivision between the two parasite populations [9] , although some cross transmission may occur between pigs and humans in sympatric locations [10] , [11] . Unfortunately the number of similar molecular epidemiological studies on multi-host parasites such as S . japonicum is limited . Several researchers have called for a better understanding of schistosome genetic diversity and structure , and have recommended the use of microsatellite markers for such studies [12] , [13] , [14] . Microsatellite markers isolated and characterized for S . japonicum have shown significant polymorphism between isolates , making them highly useful for studying the population genetic structure of the parasite [15] . A recent study by Wang et al . [16] employed these markers to investigate population genetic structure in relation to definitive host species in the marshland region of Anhui province , China , and found that S . japonicum larval samples segregated into two main groups: isolates from humans , cattle and water buffalo clustered together , while isolates from dogs , cats , goats and pigs formed a second cluster . This suggested that human transmission in this region of China is more closely associated with bovines than with other domesticated animals . These markers have also revealed structuring of S . japonicum genotypes in China according to geographic region ( mountainous vs . lake/marshland areas ) and intermediate host morphology ( ribbed- vs . smooth-shelled Oncomelania hupensis snails ) , and also between China and the Philippines [17] . In the present study , we obtained S . japonicum larval isolates from four definitive host species and snail-intermediate hosts from two geographical areas within Samar Province of the Philippines . Genetic analysis of schistosome larvae sampled directly from naturally infected hosts ( miracidia hatched from eggs excreted by infected mammalian hosts , and cercariae shed from infected snail-intermediate hosts ) is now feasible , and eliminates the need to passage schistosomes through laboratory hosts [18] . This is particularly advantageous for molecular studies of S . japonicum , which shows strong bottlenecking of genotypes following passage through rodents [19] . In addition , the molecular techniques used in the aforementioned studies by Shrivastava et al . [17] and Wang et al . [16] have been further developed to allow multiple loci to be genotyped for each larval isolate , allowing for more robust genetic analyses [20] . Through application of these novel techniques , we present here the first population genetic study of S . japonicum in the Philippines , in which the main aims were to assess levels of parasite gene-flow , and thus also transmission , across different host species and geographic areas in the Philippines . A comparison is also made with previous findings in China , where the epidemiological setting for S . japonicum differs considerably from the Philippines in terms of the suspected animal reservoirs , snail hosts , topography , and seasonality of transmission . Implications in terms of potential differences in the evolution of S . japonicum between the two countries , and applications for current targeted control activities , are discussed .
The molecular analysis was a subcomponent of a larger epidemiological study called Schistosomiasis Transmission and Ecology in the Philippines ( STEP ) . The objective of the STEP study was to estimate the effect of man-made irrigation on human infection with schistosomiasis japonica in Samar province , region of the eastern Visayas , in the Philippines . One major specific aim was to estimate the role of infection in five animal species ( cats , dogs , pigs , rats and water buffaloes ) in human infection . The main study took place over 18 months in 50 villages ( known locally as ‘barangays’ ) , selected according to the number of hectares of farmland under water management and irrigation systems . Further details of the selection of villages can be found elsewhere [5] , [21] . During the statistical analysis of the data , the prevalence of infection in humans and animals was found to heavily cluster within three geographical areas in the province ( referred to as areas A , B and C ) [21] . Sampling for the molecular analysis was conducted from May to December 2005 across all three areas . However , in area C only a relatively small sample of isolates was obtained , which was unlikely to be representative of the genetic diversity within this region and was therefore excluded from the analysis . This paper therefore reports on samples collected across 24 villages in areas A and B . In area A , villages were scattered along narrow river valleys within an area of approximately 136 km2 , while in area B villages were situated among open foothills within an area of approximately 127 km2 [21] . Villages within each area were highly interconnected by watersheds . A map of the study region is shown in Figure 1 . Details on the selection , sampling , and measurement of infection status of human participants and animals for the STEP study can be found in [5] and [4] , respectively . Briefly , up to six humans from up to 35 randomly selected households in each village were asked to provide stool samples over three consecutive days which were subjected to Kato-Katz examination . Due to financial and logistical constraints on the molecular subcomponent of the STEP study , only a proportion of individuals testing positive in the parasitological surveys were retraced to obtain the molecular data presented here . To collect stools from non-human animals , dogs were tethered and cats and puppies were placed in cages ( supplied with food and water ) and allowed to defecate . Per rectal sampling was carried out on pigs and water buffaloes ( carabao ) . Stool samples were collected for two consecutive days in animals , with the same animals sampled on both days . In each village , 30 rat traps were set for three days , and fecal samples were collected from the floor of the cage . The Danish Bilharziasis Laboratory ( DBL ) sedimentation technique was used to determine the infection status of non-human animals [22] , [23] . Where possible , miracidia were hatched from infected fecal samples according to standard protocols [24] , [25] . In order to minimize contamination , miracidia were washed individually by sequential transfer to three successive Petri dishes containing autoclaved deionized water , and their DNA was stored on Whatman FTA cards according to protocols described elsewhere [18] , [19] . The number of hosts and miracidia isolates sampled across host species and geographic areas that were successfully genotyped are summarized in Table 1 , where it can be seen that the majority of isolates were obtained from humans and dogs ( 21 and 17 individuals , respectively ) . Isolates were also obtained from 4 rats and 3 pigs , whilst no miracidia were successfully hatched from cats or water buffaloes . Snail survey sites within villages were selected based on the types of aquatic environments most likely to support Oncomelania quadrasi [26] , which is the snail-intermediate host for S . japonicum in the Philippines [27] . Well-shaded areas along streams , springs or various canals ( drainage canals and others ) and swampy areas or grass land ( often currently unplanted rice fields ) were inspected for the presence of snail colonies . All collected O . quadrasi were transported to the laboratory and checked for shedding of cercariae using standard protocols [25] . Due to the low prevalence of infection among snails and time constraints in the field , all snails collected within each village were pooled together when examining for cercarial shedding , thus cercarial isolates could not be assigned to individual infected snails . However , to prevent any potential bias caused by sampling multiple clones arising from a single snail , the cercariae dataset was cleared of all clonal genotypes within each village prior to analyses ( see below ) . As with miracidia , cercariae were washed in autoclaved deionized water and stored on Whatman FTA cards [18] . The number of cercariae genotyped from each geographic area is shown in Table 1 . Of the 11 previously isolated and characterized S . japonicum microsatellite markers [15] , seven were used in this study , namely MPA , RRPS , TS2 , J5 , 2AAA , M5A and MF1 . The other four markers were excluded due to high frequency of null alleles or poor amplification in multiplex reaction conditions ( as distinct from the single locus reactions used in the previous studies [16] , [17] ) , despite considerable time taken to optimize reaction conditions during assay development . Primers were checked for interactions using Autodimer software [28] . The 5′ end of the forward primer for each locus was fluorescently labeled using either 6-FAM , VIC , PET or NED ( Applied Biosystems ) , using different colors for loci with overlapping size ranges . Larval ( miracidia and cercariae ) samples were removed from the Whatman FTA cards using a Harris Micropunch , and placed individually in 96-well dishes . Samples were washed in FTA Purification reagent and Tris-EDTA ( TE ) buffer according to standard protocol [18] , before adding to each well 25 µl of reagent mix , containing 0 . 01 µM of primers ( 0 . 005 µM for RRPS , M5A and J5 ) , 3 mM MgCl2 , ultra-pure high quality dNTP Mix and HotStarTaq DNA polymerase ( Qiagen Multiplex PCR kit , West Sussex , UK ) . Polymerase chain reaction ( PCR ) amplifications were performed on a PTC-200 Thermal Cycler ( MJ Research ) , using a stepdown PCR beginning with an initial hot-start activation at 95°C for 15 min , followed by 40 cycles of 30 sec at 94°C , 90 sec at annealing temperature ( 2 cycles at each temperature from 60°C to 56°C , then 20 cycles at 55°C ) , and 60 sec at 72°C , with a final extension at 60°C for 30 min . 2 µl of PCR product , along with LIZ-600 size standard ( Applied Biosystems ) was subjected to electrophoresis using an ABI Prism 3730 Genetic Analyzer ( carried out by Geneservice , Oxford , UK ) . Allele sizes were assigned using Genemapper version 4 . 0 ( Applied Biosystems ) . DNA from one of five S . japonicum adult worm isolates from China were genotyped on each PCR plate to check for consistency of marker amplification across PCR runs , and also consistency of allele calling across genotyping runs . Details on the origin and DNA extraction of these adult worm isolates can be found in [17] . Cercarial isolates from three villages ( Guanghui , Heping and Xingzhuang ) from a marshland region of Anhui Province , China , collected in March–April 2006 , were also genotyped as a control group . This was to confirm that the microsatellite markers could differentiate between isolates from quite separate and isolated regions , between which one would expect there to be little , if any , parasite gene-flow . The number of alleles , gene diversity ( unbiased expected heterozygosity ) , and polymorphism information content ( PIC ) values were calculated using PowerMarker version 3 . 25 [29] . Genetic diversity was also characterized by calculating allelic richness in FSTAT version 2 . 9 . 3 . 2 [30] , as this accounts for differences in sample sizes ( unlike number of alleles ) . Arlequin version 3 . 1 [31] was used to calculate observed heterozygosity and test for departures from Hardy-Weinberg equilibrium . The number of private alleles ( i . e . alleles only found in a single population ) were calculated using GDA version 1 . 1 [32] . To estimate parasite genetic structure among geographic areas and host species , Wright's hierarchical F-statistics [33] were calculated in Arlequin using an analysis of molecular variance ( AMOVA ) approach [31] , [34] . FST values were calculated to measure genetic differentiation among parasite populations grouped by area and host species , and can be defined as the correlation of alleles within these populations relative to that within the total parasite population . Inbreeding coefficients ( FIS values ) were also calculated , which measure the correlation of alleles within individual isolates relative to that within a defined parasite population . An important consideration when conducting population genetic analyses of parasite larval stages is that isolates sampled from a given individual host may be related by virtue of being siblings or clones . In the case of schistosomes , miracidia sampled from a definitive host may be siblings ( or indeed half siblings ) as a result of sexual reproduction between adult worms , while cercariae sampled from an infected snail are likely to be clones arising from asexual reproduction . FST values among populations could therefore be inflated if the correlation of alleles within parasite infrapopulations sampled from individual hosts is not adjusted for [8] ( where an infrapopulation is the population of parasites that inhabits a single individual host [35] ) . To minimize such potential effects when analyzing cercariae isolates , the cercariae dataset was cleared of clonal genotypes for each village , under the reasonable assumption that these would have arisen from the same snail . For miracidia , three-level hierarchical analyses were conducted such that isolates ( level 1 ) were grouped according to infrapopulations ( level 2 ) , which were then further grouped according to geographic area or host species ( level 3 ) . Using AMOVA , genetic variance is partitioned into each level of the hierarchy , thus all FST values calculated at level 3 , i . e . among parasite populations grouped by area and species , were adjusted for genetic variance components at the infrapopulation level . In order to test the potential importance of adjusting for genetic variation among parasite infrapopulations when estimating parasite genetic differentiation among groups of hosts , was also calculated using just two levels of hierarchy , in which isolates were simply grouped according to the host species from which they were sampled ( i . e . without any subdivision of isolates according to individual host ) . Ninety five percent confidence intervals ( 95% CI ) were calculated by bootstrapping over populations and subpopulations for each locus in Arlequin , thus it was possible to test whether FST values were significantly greater than zero ( which would indicate significant genetic differentiation ) at the P<0 . 05 level . Phylogenetic reconstruction was implemented using the neighbor-joining method in PowerMarker based on C . S . Chord genetic distance [36] , because it has been shown by analysis of simulations to generate the correct tree topology regardless of the microsatellite mutation model [37] . Reliability of tree topology was tested by generating 100 bootstrapped trees in PowerMarker . These trees were then analyzed in Phylip version 3 . 67 [38] using the Consense package to calculate bootstrapping values for each cluster . Bayesian clustering analysis was performed using STRUCTURE version 2 . 1 [39] , a model-based program which can infer population structure without using prior information on sample origin . Simulations in STRUCTURE were carried out using a burn-in of 5 000 and a run length of 50 000 , using a model in which allele frequencies were assumed to be correlated within populations . The software was run with the option of admixture , allowing for some mixed ancestry within individual isolates . This project was approved by the ethical boards of the Research Institute of Tropical Medicine ( RITM ) , Brown University and Imperial College London . Village leaders were asked for consent for their village to be included in the survey , and written informed consent was obtained from all human study participants and owners of sampled domesticated animals . Personal identifiers were removed from the dataset before analyses were undertaken . The animal protocol was reviewed and approved by the Brown University Institutional Animal Care and Use Committee , the DBL-Institute for Health Research and Development ( then called Danish Bilharziasis Laboratory ) and the RITM's animal protection committee adhering to the institution's guidelines for animal husbandry .
Bayesian clustering analysis using STRUCURE did not reveal any obvious clustering pattern of miracidia genotypes by geographic area within Samar ( see Supporting Information , Figure S1 ) . From hierarchical AMOVA , variation among areas was estimated to account for only 0 . 4% of the total genetic variation , and was estimated at 0 . 004 ( 95% CI from bootstrapping: −0 . 002 to 0 . 014 ) ( Figure 2 ) . Thus there was no evidence of significant genetic differentiation of parasite populations between the two areas at the definitive host level ( although there was some evidence for this at the intermediate host level , see below ) . Furthermore , the upper 95% CI of suggests that if parasite genetic differentiation does exist between the two areas , it is likely to be very small . Given the overall lack of evidence for genetic structuring of miracidia by geographic area , isolates were divided into populations according to definitive host species regardless of the site of sampling for analyses of genetic structure across host species . Hardy-Weinberg estimates revealed high levels of genetic polymorphism within larval isolates from the four definitive host species in all seven loci , confirming the suitability of these markers for population genetics studies of S . japonicum . There were significant losses of heterozygosity across the majority of loci in all definitive host species ( Table 2 ) . The greatest loss of heterozygosity was observed in rat isolates , as evident from the relatively high inbreeding coefficient ( FIS ) for this species ( Table 3 ) , perhaps suggesting greater inbreeding of parasites within this host species . Gene diversity indices were comparable across human , dog and rat isolates ( 0 . 57–0 . 62 ) , but slightly lower within pigs ( 0 . 45 ) . Similarly , allelic richness was lowest among pig isolates ( 3 . 3 ) compared with population isolates from other species ( 4 . 2–4 . 8 ) ( Table 3 ) . Of the 83 different alleles observed in miracidia , 54 ( 65 . 1% ) were shared across at least two host species , 18 ( 21 . 7% ) were universal across all host species , and notably , the most frequent alleles at each locus were found in all host species , suggesting substantial gene-flow between parasite populations of each species . Nevertheless , 29 alleles ( 34 . 9% ) were definitive host-specific , and the number of these private alleles varied at each locus and within host species , with the mean number of private alleles over all loci being highest in dogs ( 5 . 3 ) , followed by humans ( 4 . 0 ) , rats ( 2 . 9 ) and finally pigs ( 1 . 6 ) . However , the majority of these private alleles were very rare , with 20 out of the 29 ( 68 . 9% ) found at frequencies of less than 1% within their respective host species populations . Thus more private alleles may have been found in dogs and humans here simply because much higher numbers of miracidia were sampled from these species relative to rats and pigs . On the other hand , alleles 441 and 451 at locus MF1 , and allele 371 at locus TS2 , all of which were private to rat isolates , were observed at relatively high frequencies of 9 . 0% , 13 . 6% , and 7 . 7% respectively . STRUCTURE analysis revealed no discernable clustering of genotypes according to host species , nor were any obvious clusters relating to host species observed in neighbor-joining phenograms constructed at the individual host level ( data not shown ) . However , a phenogram at the host species level suggested that parasite genotypes sampled from dogs and humans may be more closely related to each other than with pig and rat isolates , with 100% of bootstrapped trees clustering human and dog population isolates together ( Figure 3 ) . From hierarchical AMOVA , the within-host individual variance component , estimated here at 92% , accounted for most of the genetic diversity of miracidia samples . The within-species among-individual host variance component was estimated at just over 7% , while variation among species was estimated to account for less than 1% of the total genetic variation ( Table 4 ) . Accordingly , ( adjusting for genetic variation among individual hosts ) was estimated to be very low at 0 . 007 , and not significant according to 95% confidence intervals estimated by bootstrapping ( −0 . 001 to 0 . 016 ) ( Figure 2 ) . Pairwise values were also calculated between parasite isolates from each host species using both two and three levels of hierarchy as described in the methods section . When using two levels of hierarchy , was very low ( 0 . 003 ) and not significant between dogs and humans ( Table 5 , above diagonal ) . All other pairwise from two-level analyses were significant , with the highest value observed between rats and pigs ( 0 . 09 ) , which supports the phenogram in Figure 3 , and might suggest moderate genetic differentiation between parasite populations of these species . However , when adjusting for the individual host level in three-level analysis , all pairwise values for pigs and rats were lower and not significantly greater than 0 ( Table 5 , below diagonal ) . Pairwise values for pigs and rats had wide confidence intervals in both two and three-level analyses , reflecting the relatively small sample sizes from these species . An analysis was also performed separately across human host individuals , although this did not reveal any obvious clustering of genotypes by host age , intensity of infection , occupation or sex . Genetic diversity and allelic richness indices were also comparable across these categories within humans ( data not shown ) . Contrary to clustering analyses of miracidia , a neighbor-joining phenogram of village population isolates of cercariae suggested at least some degree of geographical structuring . In Figure 4 , it can be seen that China cercarial population isolates clustered away from Philippines isolates in 100% of bootstrapped trees , while there also appeared to be some clustering of village isolates within the Philippines according to geographic area ( although it should be noted that many nodes of this tree were not strongly supported by bootstrap analysis ) . Villages 201 , 205 , and 217 from area A formed a cluster in 60% of bootstrapped trees , while villages 501 and 506 from area B were neighbors in 47% bootstrapped trees , within a cluster in which seven out of nine villages were from area B . Nevertheless , village 218 ( area A ) neighbored with village 507 ( area B ) with strong support from bootstrap analysis ( 82% ) , and villages 213 and 301 , also from different areas , were neighbors in 52% of bootstrapped trees . Genetic structure was therefore far from distinct between the two regions . From AMOVA , variation among areas was estimated to account for 7 . 8% of the total genetic variation observed in cercariae , and for cercariae was estimated at 0 . 08 ( 95% CI: 0 . 02–0 . 17 ) . This suggests significant and , according to Wright's criterion , moderate genetic differentiation among areas; substantially greater than that estimated at the definitive host level ( Figure 2 ) . Even when excluding villages from which we had not obtained any miracidia , greater genetic differentiation among areas was observed in cercariae relative to miracidia ( data not shown ) , suggesting that this was not simply a result of having obtained cercarial isolates from a wider range of villages . When comparing the number of alleles shared between cercarial isolates and definitive host isolates , dog and human isolates had the highest number ( averaged across loci ) of 6 . 3 and 5 . 6 respectively , followed by rats ( 4 . 1 ) and then pigs ( 3 . 4 ) . Accordingly , pairwise FST estimates between snail population isolates and each definitive host population were lower for dogs and humans relative to pigs and rats . It is worth noting , however , that these estimates were not significant when adjusting for variation among individuals within definitive host species and among villages within cercarial isolates ( Table 5 ) . Of the total 50 alleles found in cercarial isolates , four ( 8 . 0% ) were not found in any definitive host population isolates , although all of these alleles were at relatively low frequencies ( 0 . 5–2 . 0% ) within cercariae . Furthermore , four of these five “snail-specific” alleles were only present in cercarial isolates sampled from villages where no miracidia isolates were obtained .
To our knowledge this work represents the first study of the population genetic structure of S . japonicum across host species and geographic areas within the Philippines . The lack of genetic differentiation observed between parasite isolates from different definitive host species suggests high levels of parasite gene-flow between host species , and thus also a high frequency of S . japonicum transmission across species , particularly between dogs and humans . Dogs could thus potentially be a very important zoonotic reservoir of S . japonicum in the province of Samar , Philippines , in contrast to marshland regions of China where parasite genotypes from humans have been demonstrated to cluster with bovines and away from other domesticated animals such as dogs , cats , pigs and goats [16] . This molecular result is consistent with parasitological survey data from the same region of the Philippines , which found a mean prevalence across 50 villages of 14 . 9% among dogs , the highest detected across all domesticated animal species sampled , with prevalence reaching up to 86 . 3% in some villages . In comparison , the mean prevalence observed in cats , pigs and water buffalo was much lower at less than 2% , with only rats showing a higher mean prevalence ( 29 . 5% ) than dogs [4] . The intensity of infection in dogs was also the highest among domesticated animals [5] . Moreover , levels of infection among humans were observed to be significantly associated with the mean intensity of infection among dogs , with each unit increase in the village-level mean eggs per gram associated with a 4% increase in the prevalence of infection in humans [5] . Dogs are owned by a high proportion of households in rural Philippine communities and usually permitted to roam freely , often even entering or feeding in other household premises as they scavenge for food [40] , [41] . Such behavior might be expected to facilitate environmental contamination by S . japonicum-infected dogs in areas overlapping with human activity . Furthermore , census data from our study villages show a mean number of 104 . 9 dogs per village , which is almost three times that of water buffalo ( 36 . 2 ) and somewhat larger than the number of cats ( 90 . 4 ) [4] . Theoretical models of multi-host parasite evolution by Gandon [42] suggest that it may be adaptive to evolve higher transmission to host types that are more abundant , so it seems reasonable to hypothesize that S . japonicum in Samar may have evolved to exploit dogs as opposed to bovines as they offer greater transmission potential . Studies which aim to elucidate , for example , relationships between cercarial exposure and subsequent levels of infection in different host species could help elucidate whether this is the case . Despite the relatively low sample sizes obtained from rats and pigs , private alleles were observed in parasite isolates from each of these species , which , combined with the measures of genetic differentiation and a phenogram at the species level , suggests that there may be less gene-flow between parasite populations of these species and humans relative to that between dogs and humans . This is consistent with the observation that village-level infection intensities in these animals were not significantly associated with those in humans [5] . Nevertheless , the molecular results with regard to rats and pigs should be interpreted with some caution , as evident from the wide confidence intervals for FST values among parasite populations of these species , highlighting a need for future studies with increased sample sizes of these animals . It should also be noted that rats and pigs were sampled from just one area each , although the fact that there appears to be very little , if any , genetic differentiation between the two areas suggest that geographic confounding may not have been particularly important here . In a recent mathematical transmission dynamics model , the prevalence of infection in rats was suspected to contribute somewhat to prevalence of infection in humans [6] . Thus the role of rats in particular in zoonotic transmission of S . japonicum in Samar remains unclear . The fact that FST values between parasite isolates of different species lost significance when adjusting for individual host level provides empirical evidence for the importance of adjusting for individual host level when sampling larval stages of multi-host parasites , otherwise the relatedness of offspring from adult parasite infrapopulations within host individuals will inflate FST values among species [8] . Parasite isolates from pigs showed the lowest genetic diversity , not only in measures of expected heterozygosity , but also in terms of allelic richness which takes into account the size of the sample , suggesting this result may not simply have been due the relatively small number of isolates from this species . Pigs are often , but not always , penned or tethered , and thus might be exposed to a smaller , more localized parasite gene pool . An alternative , not mutually exclusive , explanation could be that the pig isolates represent longer term infections with subsequent reduced diversity , if pigs are exposed as free-roaming young piglets before being penned or tethered at adulthood . Furthermore , studies in China have shown pigs to be less susceptible to infection ( at least with the Chinese ‘strain’ of S . japonicum ) , with low rates of worm establishment compared to other mammalian hosts [4] , thus the reduced diversity could reflect bottlenecking of genotypes during the infection process in pigs . In terms of geographic structuring , it is interesting that greater and more significant genetic differentiation among areas was observed at the snail-intermediate host level relative to the definitive host level . One reason for this could be that definitive hosts , particularly humans , are more mobile and longer-lived , and thus have greater potential to acquire infections from various geographic areas . Snails on the other hand could be more localized , and are certainly shorter lived; thus snail colonies within a given geographic area may acquire infections from a smaller , more localized pool of infected definitive-host individuals . In light of this hypothesis , it would be interesting to see whether , under any increasing drug administration in the Philippines , parasite genotypes in definitive hosts ( particularly humans ) become more geographically clustered due to the fact that infections have not accumulated from such a range of geographic areas . Stronger geographic structuring of S . japonicum at the intermediate host level could also be due to differential compatibility of parasite genotypes with allopatric and sympatric snail genotypes . Previous studies suggest that strain-specificity for schistosomiasis tends to be stronger at the snail stage compared to the definitive host stage [43] , [44] , which may result in more selective uptake and/or output of parasite genotypes , and hence more structuring . A study by Hope and McManus [43] however , found no genetic variation between O . quadrasi snails from different regions of the Philippines . Indeed , this could explain why geographic structuring and diversity of S . japonicum in the Philippines appears to be far less distinct than observed in China [17] , where two different O . hupensis subspecies exist ( O . h . robertsoni in mountainous regions and O . h . hupensis in lake/marshland regions ) , and even populations within these subspecies show marked genetic variation [45] , [46] , [47] . It is worth noting , however , that these previous studies on the genetic diversity of Oncomelania populations are largely based on restriction fragment length polymorphism markers; thus future microsatellite studies of sympatric snail populations may be important to pursue in order to obtain molecular results more comparable with those on S . japonicum . Less distinctive geographic structuring of S . japonicum in Samar , relative to China , could also reflect frequent import and export of infections between geographic areas . Thus it may be inappropriate to assume that transmission cycles within villages are largely self-contained , raising important implications for control interventions , which may be more effective if implemented simultaneously across all villages and regions . Samar Province in the Philippines has a very wet climate throughout the year , which could facilitate substantial mixing of snail populations and year-round transmission across interconnected watersheds , in contrast to S . japonicum-endemic regions in China where the climate , and thus also transmission , is much more seasonal [48] , [49] . This phenomenon could also explain why genetic structuring of S . japonicum across definitive host species , which was not evident in the present Philippines study , has been observed in China , both in a study by Wang et al . [16] and in an ongoing study within our group , where more “boom and bust” snail population dynamics could force more sub-structuring in transmission . Indeed , one could even speculate that such factors have led to different evolutionary strategies of S . japonicum in the two countries , with the Philippines parasite having evolved a more generalist strategy , with genotypes displaying comparable transmission potentials across several definitive host species . In China , on the other hand , S . japonicum , while still displaying a generalist strategy in that it can infect a range of host species , may have achieved this by evolving into multiple specialist “strains” which show differential fitness depending on definitive and/or intermediate host types , perhaps resulting from and/or resulting in greater structuring of transmission according to host species and geographic area . To conclude , this study suggests there is frequent transmission of S . japonicum across different mammalian host species , and perhaps also across geographic areas , in Samar province of the Philippines , with dogs potentially playing a highly important role in zoonotic transmission . These findings raise important applied concerns for current chemotherapy-based control programs , which may be inefficient if humans are rapidly re-infected by animal host reservoirs . Indeed , unpublished data from the STEP study suggests that the risk of re-infection was approximately 11% over 12 months . In addition , the recent anti-schistosomal mass treatment campaign in Samar resulted in far lower participation than desired [50] . It may therefore be crucial for control efforts to include animals such as dogs , for example via chemotherapy and population control , if transmission control is to be achieved , although the feasibility of such measures is uncertain at this stage . Finally , in contrast to previous evidence suggestive of a potential “strain-complex” of S . japonicum in China relating to different definitive host species , this study did not reveal any host-related differentiation of S . japonicum in the Philippines , raising theoretical implications concerning the evolution of multi-host pathogens and how this may vary even within a single species of pathogen . | Schistosomiasis is a disease caused by parasitic worms known as schistosomes , which infect about 200 million people worldwide . In the Philippines , as in China , the species of schistosome ( Schistosoma japonicum ) which causes the disease infects not only humans , but also many other species of mammals . In China , bovines are thought to be particularly important for harboring and transmitting S . japonicum , whereas in the Philippines infections in bovines are relatively rare . However , dogs , rats and pigs are often infected with S . japonicum in the Philippines , although the extent to which infections in these animals may give rise to human infections is unclear . To help answer this question , we characterized the genetic variation of the parasite in Samar province of the Philippines , and found that S . japonicum samples from humans , dogs , rats and pigs were genetically very similar , with no significant genetic difference between samples from humans and dogs . This suggests that in the Philippines this parasite is frequently transmitted between different mammalian species , particularly between dogs and humans . Reducing levels of infections in dogs may therefore help to reduce infections in humans . The results also suggest high levels of transmission between geographic areas , thus regional co-ordination of treatment programs is recommended . | [
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"... | 2008 | Population Genetics of Schistosoma japonicum within the Philippines Suggest High Levels of Transmission between Humans and Dogs |
The malaria parasite Plasmodium falciparum has evolved an unusual genome structure . The majority of the genome is relatively stable , with mutation rates similar to most eukaryotic species . However , some regions are very unstable with high recombination rates , driving the generation of new immune evasion-associated var genes . The molecular factors controlling the inconsistent stability of this genome are not known . Here we studied the roles of the two putative RecQ helicases in P . falciparum , PfBLM and PfWRN . When PfWRN was knocked down , recombination rates increased four-fold , generating chromosomal abnormalities , a high rate of chimeric var genes and many microindels , particularly in known ‘fragile sites’ . This is the first identification of a gene involved in suppressing recombination and maintaining genome stability in Plasmodium . By contrast , no change in mutation rate appeared when the second RecQ helicase , PfBLM , was mutated . At the transcriptional level , however , both helicases evidently modulate the transcription of large cohorts of genes , with several hundred genes—including a large proportion of vars—showing deregulated expression in each RecQ mutant . Aberrant processing of stalled replication forks is a possible mechanism underlying elevated mutation rates and this was assessed by measuring DNA replication dynamics in the RecQ mutant lines . Replication forks moved slowly and stalled at elevated rates in both mutants , confirming that RecQ helicases are required for efficient DNA replication . Overall , this work identifies the Plasmodium RecQ helicases as major players in DNA replication , antigenic diversification and genome stability in the most lethal human malaria parasite , with important implications for genome evolution in this pathogen .
Protozoan Plasmodium parasites are the causative agents of human malaria , a disease responsible for widespread morbidity and almost half a million deaths each year [1] . Most malaria deaths are caused by the species P . falciparum , although four other Plasmodium species also infect humans . P . falciparum has one of the most highly A/T-biased genomes ever sequenced , at ~81% A/T [2] . This is maintained by a high mutational bias towards G/C to A/T transitions [3] and the resultant genome contains a preponderance of A/T repeat tracts [4] . These are prone to form structures such as hairpins and slipped-strand pairing , and they can expand and contract readily , producing a genome that is very prone to micro-indels [3] . Simple A/T repeats can also promote the duplication of whole genes via homologous recombination ( HR ) between repeats—a mechanism that favours genome evolution via gene duplication followed by functional diversification and/or selection [5 , 6] . This is specifically implicated in the evolution of drug resistance ( e . g . amplification of the multi-drug resistance gene PfMDR1 ) . As expected given the A/T bias , guanine-rich motifs are contrastingly very scarce . Only ~80 putative G-quadruplex ( G4 ) forming sequences ( non-double-helical structures that require four closely-spaced tracts of at least three guanines to form [7] ) are found outside the intrinsically guanine-rich telomeres in P . falciparum [8 , 9] . Both hairpins and G4s in DNA are implicated in stalling RNA and DNA polymerases , and in promoting recombination events via DNA breakage at stalled replication forks [10 , 11] . Plasmodium species repair DNA breaks primarily by homologous recombination because they lack a conventional non-homologous end joining pathway [12] . The Plasmodium genome is , however , haploid ( except for a brief diploid stage during sexual reproduction in the mosquito vector ) , so templates for HR are limited . The natural occurrence of HR during mitotic growth of haploid P . falciparum parasites in human erythrocytes has been quantified , showing that it occurs almost exclusively in subtelomeric regions and in chromosome-internal hypervariable regions . Both these regions contain genes from multi-gene families that encode variant surface antigens , such as var genes [13 , 14] . Var genes encode a virulence factor called P . falciparum Erythrocyte Membrane Protein 1 ( PfEMP1 ) that is expressed on the surface of parasite-infected erythrocytes [15–17] , and P . falciparum can maintain chronic infections via antigenic switching of this factor . Var recombination events usually generate new , functional chimeric genes [13 , 14]: in terms of genome evolution they are thus distinct from the gene duplications that can be selected under drug pressure . Var recombination appears to be selectively neutral in in vitro culture , but in vivo it could diversify the repertoire of antigens and enhance the parasite’s capacity for immune evasion . The var recombination breakpoints that occur during in vitro culture are spatially associated with potential helix-disrupting structures including hairpins [18] and G4s [9] , suggesting that HR is initiated when replication forks stall at such structures . In fact , the observation that sequences with the potential to form G4s are strongly clustered around var genes [9] suggests that such rare sequences may actually be maintained for this purpose , conferring an evolutionary advantage in var gene diversification . In model systems , non-canonical DNA structures including G4s are targeted by ‘RecQ’ helicases , which suppress the stalling of replication forks and hence recombination events [19] , as well as modulating transcription through non-canonical DNA structures [20] . We therefore investigated whether either recombination or transcription in the P . falciparum genome could be affected by the two putative RecQ helicases encoded by this parasite , PfWRN and PfBLM [8 , 9 , 21 , 22] . Characterisation of RecQ mutant lines revealed that these helicases have widespread and profound effects on genome recombination and diversification of the virulence gene repertoire , as well as on transcription of large cohorts of genes . We also measured DNA replication dynamics at a single-molecule level via DNA combing [23] , revealing that the RecQ helicases affect the speed at which replication forks move and the rate at which they stall , and thus providing a mechanistic explanation for the genome stability and transcriptional phenotypes . Overall , this work identifies the P . falciparum RecQ helicases as major players in DNA replication , antigenic diversification and genome stability in the most important human malaria parasite .
To investigate the roles of RecQ helicases in P . falciparum , the two genes that encode PfBLM and PfWRN were targeted for gene replacement via double homologous recombination . PfBLM was successfully knocked out , as shown by Southern blotting of the disrupted locus ( S1A Fig ) . The absence of a full-length transcript in the mutant line was confirmed by RT-PCR ( Fig 1A ) and RNA-Seq ( S1B Fig ) . In the case of PfWRN , gene knockout did not occur as predicted; the endogenous locus was disrupted ( S2A Fig ) but Southern blotting suggested that a two-plasmid concatamer had integrated into this locus via a single recombination event at the 5’ gene-targeting sequence: this was confirmed by whole-genome sequencing ( S2B Fig ) and RNA-Seq ( S2C Fig ) . The integration produced a promoter-less copy of the gene , truncated at the 5’ end , but the rest of the PfWRN transcript was still expressed at a low level ( <7% of wildtype , as detected by RT-PCR , Fig 1B ) , and this truncated transcript could potentially produce a protein with residual helicase function . This line , termed ‘PfWRN-k/d’ , therefore represents a >90% knockdown , at least at the RNA level , rather than a genuine knockout of PfWRN . Notably , several rounds of unsuccessful negative selection were conducted before this parasite line was obtained , perhaps because complete loss of the PfWRN helicase is lethal for blood-stage P . falciparum parasites . In keeping with this hypothesis , survival of the PfWRN-disruptant that was eventually obtained would require the thymidine kinase negative selection marker to be largely silenced ( as supported by RNA-Seq data in S2C Fig ) . Overall , this complex genetic event implies a strong selection pressure against complete functional inactivation of PfWRN . Both of the RecQ mutant lines showed slight growth defects and in the case of PfWRN-k/d the defect was significant in two independent assays ( Fig 1C and 1D ) . Parasites in both lines appeared morphologically normal and had normal cell cycle dynamics ( S3A Fig ) ; the growth defects may be partially attributable to slight reductions in the numbers of merozoites formed per schizont ( S3B and S3C Fig ) . These phenotypes corroborate results from the PlasmoGEM project , in which growth phenotypes were generated for genome-wide gene knockouts in the rodent malaria model species P . berghei [24] . Genetic modification in P . berghei is more efficient than in P . falciparum , allowing the creation of mutants in moderately deleterious genes , and mutants in both RecQ homologues were indeed successfully obtained in this screen ( S3D Fig ) . Deletion of the BLM homologue in P . berghei affected parasite growth only slightly ( average growth in 3 mice was 87% relative to wild-type: too marginal to be statistically significant with a 95% confidence interval of 0 . 7–1 . 05 ) , whereas deletion of the WRN homologue led to a significantly slow growth phenotype at an average of 71% relative to wild-type ( 95% C . I . 0 . 56–0 . 86 ) . To investigate whether disrupting the RecQ helicases could affect the rate or pattern of genomic mutations , ‘clone trees’ were constructed in both the mutant lines as well as in their wildtype parent . A clone tree can track the accumulation of mutations over long periods of in vitro growth , via repeated cloning and whole genome sequencing of successive generations of clones [13] ( Fig 2A ) . The total numbers of clones sequenced and their cumulative days in culture were: 27 clones and 1324 days for the parent 3D7 line; 36 clones and 1860 days for ΔPfBLM; 20 clones and 2183 days for PfWRN-k/d ( S4 Fig ) . Libraries were made without a PCR step to avoid any bias , yet the sequencing was deep enough to cover an average of 95% of the 3D7 reference genome with 10 or more reads ( S1 Spreadsheet , Sheet1 ) . We investigated the following events in all three clone trees: base pair substitutions ( BPS , the mutation origin of single nucleotide polymorphisms , SNP ) , micro-indels ( insertions or deletions , typically shorter than 15bp , found in microsatellite regions ) and structural variants ( deletions , duplications , inversions , all greater than 300bp , and translocations , which are recombinations between non-homologous chromosomes ) ( Fig 2B ) . BPS showed an excess of G:C to A:T substitutions ( S1 Spreadsheet , Sheet2 ) , as previously demonstrated [3] . The mean substitution rate was increased by 1 . 8 fold in PfWRN-k/d compared to 3D7 ( P = 0 . 040 by weighted t-test ) ; there was no difference in the ΔPfBLM line . As shown in previous studies , micro-indels were consistently detected within repetitive regions across the entire genome ( S1 Spreadsheet , Sheet3; S5 Fig ) . There was a significant 2 . 3 fold increase of micro-indels in the PfWRN-k/d line compared to 3D7 ( P < 0 . 007 by weighted t-test ) , while micro-indels were slightly decreased in the ΔPfBLM line . There was no difference in the chromosomal location or lengths of the micro-indels identified across all 3 lines ( S6 Fig ) . However , the proportion of micro-indels occurring in homorepeats ( [A]n or [T]n ) tripled in PfWRN-k/d ( P < 0 . 0006 , chi-square test ) ( S6G Fig ) . Therefore , the disruption of the WRN gene led to poor replication reliability in microsatellite regions , suggesting that PfWRN has a role in preventing DNA polymerase slippage , particularly in homorepeat regions . Structural Variants ( SVs ) were also drastically increased ( 4 . 2 fold ) in the PfWRN-k/d line compared to 3D7 ( P < 2 . 8E-08 by weighted t-test ) , with again no significant change in the ΔPfBLM line . The vast majority of SVs were restricted to hypervariable regions ( subtelomeric or internal ) which contain highly polymorphic genes such as var genes . As previously observed , in all three lines , the breakpoints occurred precisely within a short sequence ( median 15bp ) termed an ‘identity block’ with 100% identity between the two recombining var genes . Ectopic recombinations occurring within such genes create chimeric sequences . The recombination generally involves var domains of the same class and the breakpoint is located in a short region of higher homology , keeping the same gene architecture and keeping the sequence in frame [13] . However , in PfWRN-k/d we identified two examples of a group A var gene recombining with a group B gene , leading to abnormal , presumably non-functional , chimeras ( S1 Spreadsheet , Sheet4; S7 Fig ) . This had never been observed in any in vitro study of recombination dynamics [3 , 13] , and is predicted to be very rare in the wild [25] . Other abnormalities uniquely found in the PfWRN-k/d clone tree included: ( a ) a recombination , with two cross-over events , between a subtelomeric var and an internal var gene ( S8 Fig ) ; ( b ) an inversion of the mirror-image sequence of the invasion-related genes RH2a and RH2b ( S9 Fig ) ; ( c ) insertion/duplication hotspots within the liver stage antigen LSA1 gene and the gametocyte specific Pf11-1 gene ( S10 Fig ) . The latter gene is extremely repetitive and is known to be in a fragile region [26] , but in that gene alone we identified 8 unique mutations in 19 PfWRN-k/d subclones [S10B Fig] , versus none in any other clone tree published so far . In conclusion , the lack of a fully functional WRN helicase led to a large increase in the structural variant mutation rate , and also a wider range of chromosomal abnormalities . The data described in Fig 2 were further analysed by assessing the relationship between mutation events and putative DNA secondary structures , such as might be targeted by RecQ helicases . First , we calculated the average distance between mutation events and putative G-quadruplex forming sequences ( PQSs—the guanine rich motifs that have the potential to form G4s ) . We have previously reported that recombination events in wildtype parasites are highly associated with PQSs [9] , and this association held for recombination events leading to SVs in all three parasite lines analysed here ( Table 1 ) . Indeed , the median distance between a breakpoint and a PQS in wildtype 3D7 parasites was almost identical in our previous analysis and in this new dataset ( 16 . 4kb and 17 . 1kb ) . In the PfWRN-k/d line , however , the median PQS-to-breakpoint distance was 50% longer at 26 . 1kb . Unlike SVs , indels and SNPs were not spatially associated with PQSs , suggesting that G4s are not an initiating event for indel or SNP mutations . Micro-indels consistently occurred in regions with significantly high tandem repeats ( TR ) or regions of low sequence complexity ( LCR ) –as expected if they originate from polymerase stalling or stuttering at mispaired DNA—and this association was the same in the parent line and the RecQ mutants ( Table 2 ) . The breakpoints of SVs tended to occur in high-TR regions , suggesting that SVs can have the same mechanistic origin as micro-indels , i . e . impeded polymerase movement through repetitive DNA . However , this relationship was weaker for SVs than for micro-indels and reached significance only in the largest dataset ( SVs from PfWRN-k/d ) . SNPs , as expected , were largely unrelated to the TR/LCR environment ( and since all SNP datasets were very small , any bias in SNP occurrence in wildtype versus mutant parasites may not be meaningful ) . Overall , micro-indels were strongly associated with repeat-rich DNA; SVs were weakly associated with repeat-rich DNA and strongly associated with PQSs , and SNPs were not associated with such DNA at all . All the recombination events that generated SVs , including those so strikingly abundant in the PfWRN-k/d line , were associated with PQSs , and furthermore the PQS-to-breakpoint distance was specifically extended in the PfWRN-k/d line ( Table 1 ) , suggesting that DNA processing at or around G4s is altered in this mutant . The link between G4s and RecQ helicases was followed up by measuring two additional G4-related phenotypes in the RecQ mutant lines: sensitivity to G4-stabilising drugs and telomere maintenance . Drug sensitivity was measured because we have previously reported than G4-stabilizing drugs can affect the growth of wildtype parasites [27] , while telomeres were measured because the great majority of PQSs in the P . falciparum genome are found in the inherently G-rich telomere repeats [8] . G4s were stabilized using a matched pair of drugs , 5 , 10 , 15 , 20-tetra- ( N-methyl-4-pyridyl ) porphine ( TMPyP4 ) [28] and its structural analogue TMPyP2 , which has a markedly lower G4-binding affinity than TMPyP4 [29] . Wildtype 3D7 parasites are more sensitive to TMPyP4 than TMPyP2 , suggesting that disruption of G4 metabolism , rather than any off-target drug effect , can inhibit healthy parasite growth [27] . When these two drugs were tested on the RecQ mutant lines , both lines were more sensitive than their wildtype parent: ΔPfBLM showed significantly increased sensitivity to both drugs , while PfWRN-k/d showed a trend towards increased sensitivity ( S11A Fig ) . In both mutants the stronger G4-binding analogue , TMPyP4 , remained more toxic than TMPyP2 . To assess the effect of RecQ helicases on telomere maintenance , telomere restriction fragment length Southern blotting was used . Telomeres in several ΔPfBLM clones were slightly but consistently longer than those of the parent line ( S11B Fig ) , suggesting that telomere ‘set-point’ maintenance was subtly disrupted . Telomere lengths in PfWRN-k/d clones did not show any consistent change ( S11C Fig ) . Moving from the genomic to the transcriptomic level , RNA-Seq was conducted in both mutant lines to investigate whether the RecQ helicases might influence the ability of parasites to transcribe through non-canonical DNA structures ( S2 , S3 and S4 Spreadsheets ) . Both mutants showed major transcriptional changes , with several hundred genes throughout the genome being differentially expressed at statistically significant levels . An additional fold-change cutoff was applied and 1434 genes showed >1 . 5-fold change in at least one lifecycle stage ( Fig 3A ) , with 906 and 261 of these genes exhibiting >2-fold and >3-fold changes respectively ( S3 Spreadsheet ) . These genes occurred on all chromosomes and were not obviously clustered at subtelomeres or near to PQSs ( Fig 3B ) . Interestingly , deregulated expression was primarily seen in ring-stages , despite the fact that the peak of both PfBLM and PfWRN transcription in blood-stage parasites occurs in trophozoites . The sets of genes affected in the two mutant lines showed only limited overlap , either between stages ( Fig 3C ) or between the two mutants ( S12 Fig ) . Many different gene ontologies were represented ( S3 Spreadsheet ) and there was no obvious pattern in the GO terms associated with deregulated genes . We then assessed whether differentially-expressed genes were associated with particular genomic features that could form DNA secondary structures , using the same approach as for the recombination breakpoints . Genes deregulated in the ring stages of both mutants had markedly elevated TR and LCR content compared to all genes in the genome as a whole . This was particularly true of the gene sets upregulated rather than downregulated in rings , and did not apply to any of the gene sets identified in trophozoites or schizonts ( Fig 3D and 3E , S1 Table ) . Elevated TR/LCR content is not an intrinsic property of genes expressed primarily at rings ( S13 Fig ) . Therefore these data suggest that genes with a high TR/LCR content are specifically prone to deregulation in RecQ helicase mutants at the ring stage . Comparing deregulated genes with the positions of PQSs revealed a weak positive association in the ΔPfBLM line between PQSs and genes deregulated at all three lifecycle stages ( Fig 3F ) . In PfWRN-k/d , there was no association at all between PQSs and deregulated genes in ring stages , but in trophozoites and schizonts the small numbers of upregulated genes were specifically and strikingly associated with PQSs ( median gene-to-PQS distances of just 22kb in trophozoites and 11kb in schizonts ) . Var genes contain about half of all non-telomeric PQSs [8 , 9] and their recombination patterns are clearly affected in the RecQ mutant lines ( see Fig 2 ) . However , RNA-Seq is not the best assay to assess changes in var gene transcription because these genes naturally undergo stochastic transcriptional switching and therefore the mutant lines may not have the same transcriptional ‘starting point’ as their parent . Therefore , gene-specific RT-PCR was conducted across the var gene family in several recent clones of each RecQ mutant line alongside similarly-aged clones of the parental line . Changes were observed in both ΔPfBLM and PfWRN-k/d clones ( S14 and S15 Figs ) : in ΔPfBLM clones , var genes were expressed at significantly elevated overall levels ( S14A and S14B Fig ) and with a fixed pattern ( i . e . similar var genes expressed in every clone ( S14A and S14B Fig ) with the total variation being only 27% of that seen between clones of the parent line ( S15D Fig ) ) . In PfWRN-k/d clones , there was much less ‘fixing’ of the var genes expressed , with 74% of the wildtype level of variation ( S15D Fig ) . In both lines , however , var genes having a PQS within or upstream of the gene were disproportionately affected ( S14C Fig ) , with transcription being most strongly elevated when a PQS was on the antisense strand ( S14D Fig ) . The deregulated expression of var genes in RecQ mutant lines probably relates to their PQS motifs rather than to any other RecQ-targeted motifs such as hairpins , because var genes do not have an unusually high TR/LCR content compared with other ring-stage-expressed genes ( S13B and S13D Fig ) . Many of the phenotypes described above could be attributable to failure of RecQ-mutant parasites to resolve the stalling of RNA or DNA polymerases at secondary structures . To test this hypothesis we measured DNA replication dynamics in the mutant lines on a single-molecule level , using immunofluorescent labelling of nascent DNA replication on combed DNA molecules ( Fig 4A [23] ) . In both the RecQ mutant lines , in two independent experiments , replication forks moved more slowly than in the wildtype parent and replication origins fired closer together ( Fig 4B and 4C and S16A and S16B Fig ) . We previously showed that origin spacing positively correlates with fork speed across the course of S-phase [23] and this correlation was apparently maintained in the RecQ mutant lines ( S17 Fig ) . The knockdown of PfWRN had a significantly greater impact on replication fork velocity than PfBLM knockout ( Fig 4B , S16A Fig ) , and replication origins accordingly fired with the closest spacing in the PfWRN-k/d line . Together with the slowing of replication forks , the movement of bidirectional fork pairs on either side of replication bubbles became less symmetric in RecQ mutant lines ( Fig 4D , S16C Fig ) , and ‘unidirectional’ forks having no partner on the opposite side of a bubble became more frequent ( Fig 4E , S16D Fig ) . Unidirectional and asymmetric forks can both be taken as proxies for the amount of replication fork stalling: this was similar in both RecQ mutants , and significantly greater than in the wildtype parent . To test whether the phenotypes observed in Fig 4 might be related to polymerase stalling at unprocessed G4 motifs , we repeated the measurements of replication dynamics in all three parasite lines challenged with the G4-binding drugs TMPyP4 and TMPyP2 . In wildtype 3D7 parasites , replication dynamics were dramatically affected by these drugs , with a slowing of replication forks and a decrease in the spacing of origins , as well as increased measures of fork stalling ( Fig 5A–5D , S18A–S18D Fig ) . These changes were more severe in TMPyP4 , which is the stronger G4-binding drug , than in TMPyP2 . Interestingly , the slowing and stalling that had already been observed in RecQ mutant parasites when compared to wildtype 3D7 was not further exacerbated by G4-binding drugs ( Fig 5A–5D , S18A–S18D Fig ) .
We present here the first report on the biological roles of RecQ helicases in P . falciparum at the genomic and transcriptomic levels . We show that these helicases have far-reaching effects on genome stability and gene transcription , including particular effects on recombination and transcription of the important var family of virulence genes . At the genomic level , we observed a marked difference between the two mutant lines: knockout of PfBLM did not influence the mutation rate , while the knockdown of PfWRN created a highly elevated number of micro-indels and SVs , plus a plethora of unusual recombination patterns never observed in previous clone trees that were generated from wildtype parasite strains [3 , 13] . Because the growth rate of the PfWRN-k/d parasites is reduced , the true mutation rate could be even higher than the current estimation . Hypermutation at the level detected here is probably deleterious in the wild: no natural mutant in PfWRN appears in any sequenced strain and this helicase also appears to be more important for parasite survival in vitro than PfBLM , given our failure to obtain a complete PfWRN knockout . Indeed , the survival of our PfBLM knockout contradicts a previous report that PfBLM is essential: this was established by treating parasites with a dsRNA against PfBLM [30] , but no evidence was shown that the dsRNA actually affected the intended gene . To our knowledge this is the first discovery of a gene directly involved in genome stability in P . falciparum: a mild mutator phenotype has previously been linked to the mismatch repair factor PfMLH1 [13 , 31] , but this involved only an elevated SNP rate . By contrast , PfWRN appears to functionally suppress all types of mutations , including small indels , SNPs and in particular , large structural variants . Its role in suppressing structural variants and indels is probably particularly crucial for a genome in which repetitive sequences , and thus risks of DNA polymerase slippage , are common . An increased SNP rate was not necessarily expected , since PfWRN is reported to lack the proofreading exonuclease domain found in human WRN [22] , and importantly the SNP datasets were all very small , making changes in SNP rate only marginally significant . Nevertheless , it is possible that an unidentified , divergent exonuclease domain may exist in PfWRN , or that other defects causing an excess of single-stranded DNA could lead to an elevated SNP rate . Otherwise , the phenotypes seen here are consistent with RecQ functions in other organisms: for example , the yeast helicase Sgs1 is required to prevent indels and fragility in triplet repeat regions [32] , while metazoan RecQ homologues in species from humans to C . elegans are required to maintain chromosome integrity and suppress genome instability and aberrant recombination [33–35] . In P . falciparum , the result appears to be that a RecQ helicase has taken on a specific , and perhaps unique , role in modulating the evolution of a major virulence gene family ( albeit with the caveat that any recombination events between other , essential genes , must go unrecorded due to their lethality ) . Importantly , our clone tree plus whole genome sequencing approach successfully identified RecQ-associated mutations at a resolution never described in other model organisms so far . DNA features such as TRs , LCRs and G4s can all form secondary structures that impede the passage of polymerases , and many of the mutation events seen here correlate with such features: structural variants being particularly associated with PQSs , and to a lesser extent with TRs , while indels are strongly associated with TRs and LCRs . Mammalian RecQ homologs are known to act on stalled replication forks and recombination intermediates [36–38] and the two RecQ homologs in Plasmodium spp . presumably act similarly . Our evidence from DNA combing supports stalled replication forks as the mechanism underlying elevated rates of recombination in the PfWRN mutant , but it is curious that only this mutant showed severe genome instability , given that both mutants showed strong replication defects on DNA fibres . In fact , stalled forks may be processed via at least two different routes: a recombinogenic route in the absence of PfWRN and a less recombinogenic route in the absence of PfBLM ( Fig 6A ) . Indeed , the PfWRN mutant showed a specific change in the distance between recombination breakpoints and PQSs , suggesting that replication forks are processed differently when they encounter a G4 in this mutant , with longer lengths of DNA being unwound or resected before a recombination event can occur . This is commensurate with one of the reported roles of human WRN , suppressing resection of DNA breaks [39] . Additionally , the two RecQ helicases may preferentially target particular substrates , such as regressed replication forks , recombination intermediates , telomeric G4s or R-loops: such a ‘division of labour’ occurs amongst the five-member RecQ family in mammals [19] , and all these roles must presumably be condensed into a two-member family in Plasmodium . Recombinant protein fragments of both PfBLM and PfWRN have been shown to unwind partial-duplex DNA structures [21 , 40] but their affinity for other substrates has not been determined and the two helicases are certainly not functionally interchangeable . As expected , DNA replication was disrupted in wildtype parasites when they were treated with G4-binding drugs , showing that G4s are indeed replication-stalling structures . However , G4s are predicted to occur very rarely ( only ~1 per 300kb [9] ) , so every disrupted replication fork cannot be directly caused by a G4 . Instead , a few DNA breaks may induce a wider checkpoint response , slowing down all active forks in trans [41] . Alternatively , the TMPyP4/2 drugs may bind to DNA at other locations besides G4s: TMPyP4 is known to be a strong but not highly specific binder of Plasmodium G4s [42] . Finally , it is possible that the sequence-based prediction of PQSs severely underestimates the actual G4 density in the genome . However , the idea that replication stalling can induce a general checkpoint response in trans is further supported by the observation that in the RecQ mutants , existing disruption to replication dynamics was not further exacerbated by TMPyP4/2 , suggesting that it is already at its maximal level in these mutants owing to a constantly active checkpoint response . Almost nothing is currently known about cell cycle checkpoints in Plasmodium . In contrast to this possible in trans effect , the effects observed at the transcriptional level are more likely to occur in cis on a gene-by-gene basis ( Fig 6B ) . They are probably attributable to impeded RNA transcription when helicase activity is lacking at common DNA features such as hairpins , because the genes deregulated in ring-stage mutant parasites tended to have high levels of repetitive and low-complexity sequence ( TRs/LCRs ) , prone to form such secondary structures . In addition , specific changes were seen in var transcription and these may be primarily due to G4s , since var genes are enriched in PQSs but are not particularly rich in TRs/LCRs . Deregulated gene expression may be concentrated at the ring stage because other DNA processing proteins such as replicative helicases are not yet upregulated , making the RecQs at their least redundant in prereplicative parasites . Interestingly , a high TR/LCR content was linked primarily to up-regulation rather than down-regulation of transcripts , suggesting that the RecQ helicases normally slow down transcription when they process aberrant DNA structures , and that faster but potentially error-prone transcription can occur in their absence . Again , the effects of PfWRN and PfBLM mutations were largely non-overlapping , which is likewise seen in the transcriptomes of different RecQ mutants in mammalian cells [20] . Although many of the PfWRN and PfBLM mutant phenotypes showed little overlap , both helicases probably contribute to G4 processing at vars because both mutant lines showed altered transcription of PQS-containing vars in ring-stage parasites . Notably , not only was the PQSs-encoding subset of var genes disproportionately affected , but those vars with a PQS on the antisense strand were specifically upregulated . This may be because a persistent antisense G4 can keep the corresponding sense-strand free and thus accessible for transcription . Importantly , this could have a direct impact on the virulence of parasites in human hosts: if the expression or activity of RecQ helicases can vary during human infections , the expression and antigenic variation of the parasite’s primary virulence gene family could vary accordingly . Indeed , RecQ helicase expression can vary in vivo: it is higher in parasites from children than from pregnant women ( and still lower in cultured 3D7 ) [43] . Finally , we propose that in addition to the roles of PfBLM in modulating replication and transcription through DNA secondary structures , this helicase could have another role in telomere maintenance and in modulating subtelomeric chromatin structure ( Fig 6C ) . This is evidenced by the lengthening of telomeres and the upregulation of overall var gene expression ( regardless of PQS association ) in the ΔPfBLM mutant . Subtelomeric DNA that encodes var genes tends to be heterochromatinised [44] and relaxation of this state is expected to boost var expression , so PfBLM may have a specific effect in maintaining heterochromatin . This may well be linked to its effect upon telomere maintenance , because the heterochromatic state spreads inwards from the telomeres [45] and telomere repeats are intrinsically G4-rich , with incorrect processing of telomeric G4s deregulating telomerase activity [46–48] . The ΔPfBLM phenotype is intriguingly similar to that of a mutant in another chromatin-maintenance protein , the histone deacetylase PfSir2a [49–51] . Both mutants show telomere lengthening together with overexpression of a fixed set of var genes , suggesting that both enzymes affect the integrity of subtelomeric chromatin—possibly in direct collaboration . There is a precedent for this because the human sirtuin SIRT6 acts on telomeric chromatin and facilitates recruitment of human WRN to maintain telomere stability [52] . In P . falciparum the effect upon telomeres appears to be exerted primarily by PfBLM , but it is important to note that the two Plasmodium helicases are not necessarily functional homologs of their mammalian namesakes [21] . Taking our data as a whole , we have detected several overlapping but distinct roles for the P . falciparum RecQ helicases , as summarised in Fig 6 . We divide these into four overall categories: an effect on common DNA secondary structures throughout the genome; a second effect specific to G4-containing variant gene sequences , a third effect on chromatin structure and a fourth on telomere maintenance . Together these effects give rise to complex changes in both genome replication and transcription when the helicases are lacking . This study reveals the P . falciparum RecQ helicases as important modulators of virulence phenotypes and genome evolution in this major human pathogen .
The 3D7 strain of P . falciparum was obtained from the Malaria Research and Reference Reagent Resource Center ( MR4 ) . Parasites were cultured as previously described [53] , in gassed chambers at 1% O2 , 3% CO2 , and 96% N2 . Synchronised parasite cultures were obtained by treatment with 5% D-sorbitol [54] . For cloning by limiting dilution , parasites were diluted to a theoretical concentration of 0 . 1–2 . 0 parasites per well of a 96-well plate at 2% haematocrit . Parasites were fed with fresh 0 . 4% haematocrit medium on days 7 and 14 . Positive wells were identified microscopically between days 14 and 21 . To disrupt the PfBLM and PfWRN loci , gene targeting plasmids were constructed as previously described [55] and transfected into P . falciparum 3D7 . Further detail and primer sequences are given below . For DNA combing experiments , the mutant lines were additionally transfected with plasmids based on the same ‘pTK’ gene-targeting plasmid , and thus expressing thymidine kinase , with a second drug-selectable marker , Blasticidin S-deaminase , cloned in the place of the original dihydrofolate reductase marker . These lines were compared with parental 3D7 parasites that has also been transfected with a pTK plasmid and thus expressed thymidine kinase . 5’ and a 3’ segments of the PfBLM gene ( PF3D7_0918600 ) were amplified using the primer pairs PfBLM5’F/R and PfBLM3’F/R , respectively ( see Table 3 ) , and subcloned into the double-selectable gene-targeting pHHT-TK plasmid ( MRA-448 , MR4 ) [55] . A plasmid to target the PfWRN locus ( PF3D7_1429900 ) was similarly constructed using primer pairs PfWRN5’F/R and PfWRN3’F/R ( Table 3 ) . Transgenic parasites were generated by allowing synchronous late-stage parasite cultures to invade erythrocytes pre-loaded with 50–100 μg plasmid DNA as previously described [56] . Plasmid-carrying parasites were positively selected with 5 nM WR99210 . Double crossover knockout events were selected from transfected parasite populations by treatment with 20 μM ganciclovir . Genomic DNA was extracted from parasites using the QIAamp DNA Blood Mini Kit ( Qiagen ) and digested with restriction enzymes . Digested genomic DNA was resolved on a 1% agarose gel , transferred to GenScreen Plus ( PerkinElmer ) and hybridised with alkaline phosphatase-labelled probe ( AlkPhos Direct Labelling and Detection system , GE Healthcare ) . For confirmation of mutant lines , DNA was digested with SacII , EcoRI and HpaI ( ΔPfBLM ) or PmlI and SnaBI ( PfWRN-k/d ) . For telomere restriction fragment Southern blotting genomic DNA was digested with AluI , DdeI , MboII and RsaI and the membrane was probed with alkaline-phosphatase labelled probe specific for telomeres [57] . ImageJ software was used to quantify telomere length . Total RNA was extracted from parasites as previously described [58] . Extracted RNA was treated with DNaseI and cDNA was subsequently synthesised using the iScript cDNA Synthesis Kit ( BIO-RAD ) . cDNA was checked for genomic DNA contamination by PCR across the intron of the gene PF3D7_0424300 , as previously described [59] . Relative gene expression was determined by real-time PCR using a StepOnePlus Real-TIme PCR machine ( ThermoFisher Scientific ) and the SensiFAST SYBR Hi-ROX kit ( Bioline ) on synthesised cDNAs . Cycling conditions were 95°C for 3 minutes , 40 cycles of 95°C for 15 seconds , 54°C for 40 seconds , 60°C for 1 minute . All primers used are either cited elsewhere or listed herein . Realtime PCR for 3D7 var gene transcription was carried out as previously described [50] , using the same control genes: five housekeeping genes and also two ring-stage-specific genes . For this analysis , ring-stage RNA was taken from four separate recent clones of each line ( 4–5 weeks from cloning ) . Variation between the var gene expression patterns in different clones of 3D7 WT , ΔPfBLM and PfWRN-k/d was quantified as follows . The percentage contribution of each var gene to the total var RCN in each clone was calculated . Variation in this percentage was then calculated by making pairwise comparisons between all four clones ( A-D ) of each line , i . e . {|A-B|+|A-C|+|A-D|+|B-C|+|B-D|+|C-D|} . The sum of the ‘variation values’ for all var genes in the family was then calculated for each parasite line . Growth over one 48h growth cycle was measured by Malaria SYBR Green I-based fluorescence ( MSF ) assay , essentially as previously described [60] . Trophozoite-stage cultures of all parasite lines being tested were seeded in triplicate into 96-well plates at 1% parasitaemia , 4% haematocrit . The outer wells of each plate were filled with medium to prevent evaporation . Plates were incubated for 48h in a gassed chamber at 37°C . Following this , 100 μL of sample from each well was transferred to plate wells containing 100 μL MSF lysis buffer ( 20 mM Tris pH 7 . 5 , 5 mM EDTA , 0 . 008% saponin , 0 . 8% Triton X-100 ) supplemented with 0 . 2 μL mL-1 of SYBR Green I ( Sigma ) . After a 1h incubation in the dark at room temperature , SYBR Green I fluorescence was measured using the blue fluorescent module ( excitation 490 nm: emission 510–570 nm ) of a GloMax multidetection system ( Promega ) . Percentage parasite growth was calculated as follows: 100x[μ ( s ) —μ ( - ) /μ ( + ) —μ ( - ) ] where μ ( s ) , μ ( - ) and μ ( + ) are the means of the fluorescent readouts from sample wells ( μ ( s ) ) , control wells with 100μM chloroquine ( μ ( - ) , representing 0% growth ) , and control wells with wildtype 3D7 parasites ( μ ( + ) , 100% growth ) . Growth over two 48h cycles was measured by seeding parasites at 0 . 1% parasitaemia and then counting the parasitaemia via blood smear microscopy ( with a minimum of 100 parasites ) at 48h intervals . All growth assays were conducted in triplicate . Parasite DNA content was measured by two methods: merozoite-counting by microscopy , and flow cytometry . Flow cytometry was carried out on a Guava easyCyte system , using parasites isolated by Percoll and then held for 4h in the egress inhibitor E64 ( 10μM ) before staining with SYBR Green 1 , fixing with formaldehyde , and quantifying the fluorescence of 5000 parasites . Clone trees , DNA extraction and sequencing were performed as described in [13] . Briefly , cultures of 3D7 , ΔPfBLM and PfWRN-k/d were periodically cloned out by limiting dilution and one clone was arbitrarily picked at each stage for the next round of clonal dilution . At least 2μg of DNA per sample was used for PCR-free library generation at the Wellcome Trust Sanger Institute . 100bp paired-end reads were generated by Illumina sequencing , as previously described [61] . SNPs , micro-indels and structural variants were called as previously described [3 , 13] . Briefly , sequencing reads were mapped to the P . falciparum 3D7 genome with BWA . SAMtools mpileup detected SNPs , GATK UnifiedGenotyper detected micro-indels , DELLY2 detected structural variants ( translocations , inversions , duplications and deletions > 300bp ) . A downstream analysis using R scripts identified de novo mutations as genetic variants found in a “progeny” sample but not in its parent . All mutations were visualised with Savant [62] . 563 hits were manually inspected and 393 false hits were discarded ( the same false hits were often found in all subclones , hence the relatively large number ) ( S5A Fig ) . The False/True call was not biased towards any clone tree ( S5B Fig ) . Translocations ( or ectopic recombinations ) tend to occur in clusters , i . e . a translocation between two subtelomeres highly increases the chance of detecting further recombinations nearby . The short distance between two breakpoints ( sometimes < 100bp ) and the repetitive nature of subtelomeres makes it difficult to detect the exact number of recombinations . Therefore multiple recombinations between two subtelomeres within a sample were considered a single mutational event . All 85 clonal genomes are available on the ENA ( S1 Spreadsheet ) . Highly synchronous clonal cultures of 3D7 , ΔPfBLM and PfWRN-k/d were split into 3 separate dishes once invasion was complete ( confirmed by light microscopy ) and cultured under standard conditions . 3–5 μg total RNA was harvested from each of the 9 cultures , as previously described [58] , at the following time points of the subsequent developmental cycle: 14 . 5–16 . 5 , 24 . 5–26 . 5 and 38 . 5–40 . 5 h post invasion , giving 3 biological replicates of each line at ring , trophozoite and schizont stages . S19 Fig shows the strength of correlation between biological replicates . A Bioanalyzer Nano chip ( Agilent ) was used to QC and quantify total RNA . A modified RNA-seq protocol ( “DAFT-seq” , Chappell et al . , in preparation ) was used to account for the extreme AT-content of the P . falciparum transcriptome . Briefly , polyA+ RNA ( mRNA ) was selected using magnetic oligo-d ( T ) beads . Reverse transcription using Superscript III ( LifeTechnologies ) was primed using oligo d ( T ) primers , then second strand cDNA synthesis included dUTP . The resulting cDNA was fragmented using a Covaris AFA sonicator . A “with-bead” protocol was used for dA-tailing , end repair and adapter ligation ( NEB ) using “PCR-free” barcoded sequencing adaptors ( Bioo Scientific , similar to the method of Korarewa et al . [63] ) . After 2 rounds of SPRI clean-up the libraries were eluted in EB buffer and USER enzyme mix ( NEB ) was used to digest the second strand cDNA , generating directional libraries . The libraries were quantified by qPCR and sequenced on an Illumina HiSeq2000 . Sequence data have been submitted to the ENA database under accession number ERP021698 . TopHat2 [64] was used to map reads against the P . falciparum 3D7 reference genome . Read counts and fragments per kilobase of transcript per million mapped reads ( FPKM ) values were calculated for each gene using HT-seq count [65] and Cufflinks [66] , respectively . Differential expression was analysed using EdgeR [67] , using a threshold of 1 . 5-fold difference in expression from the wildtype 3D7 ( See S4 Spreadsheet ) . Data plots were created in R and Artemis [68] or Integrated Genome Browser ( IGB ) were used to visualise mapped reads . The proximity of all mutations found in the clone trees to PQSs ( which were located previously using the tool QGRS mapper ) was determined as previously described [9] . Median breakpoint-to-PQS distances were determined for each dataset , together with 95% confidence intervals ( C . I . ) . A significant difference was reported if a particular median fell outside the confidence interval for the control dataset , i . e . the median distance of random simulated breakpoints from PQSs , taken from our previous study [9] . The percentage content of tandem repeats and low-complexity regions ( TRs and LCRs ) in the 1kb surrounding each mutation was calculated after downloading the locations of these two features throughout the genome from PlasmoDB . org . PlasmoDB defines TRs as previously described [69] and LCRs according to the DUST algorithm ( for details see [70] ) . Overlapping regions of each type were amalgamated into single blocks to avoid double-counting them . The mean TR and LCR content of 1kb windows across the whole genome was calculated , as well as the mean TR and LCR content of coding genes ( i . e . the number of TR or LCR base-pairs that overlapped with each gene-coding region , divided by the total gene length to yield the percentage TR/LCR content of that gene ) . The mean TR/LCR content of the 1kb windows surrounding each set of mutations was then compared to the whole-genome average , and significant differences were assessed by 2-tailed t-test . To determine the proximity of differentially expressed ( DE ) genes to PQSs , a similar approach was taken as for the clone-tree data , using the algorithm detailed in Supplementary Methods . In brief , the distances from each end of a gene to all the PQSs that share its chromosome were calculated and the smallest distance was recorded . For each set of DE genes , their mean and median proximity to PQSs was then calculated . As a comparator , the PQS proximity of all genes in the genome was calculated . The statistical significance of differences between the proximity of DE gene sets and the proximity of all genes in the genome was assessed by comparing means via two-tailed t-tests . The mean TR/LCR content of each DE gene set was compared to that of all genes in the genome , as described above for 1kb windows around clone-tree mutations . Statistically significant differences were assessed by two-tailed t-tests . Agarose plugs for DNA molecular combing were prepared as previously described [23] . In brief , two modified nucleosides were used to label parasites: iodo-deoxyuridine ( IdU , Sigma ) and chloro-deoxyuridine ( CldU , Sigma ) . Parasites were sequentially labelled for 10 minutes with 25 μM IdU , then for 10 minutes with 200 μM CldU , added directly to the culture without intermediate washing . After labelling , the cultures were immediately placed on ice to stop DNA replication; parasites were removed from cells using saponin and embedded in agarose as previously described . The drugs 5 , 10 , 15 , 20-tetra- ( N-methyl-4-pyridyl ) porphine ( TMPyP4 ) and 5 , 10 , 15 , 20-tetra- ( N-methyl-2-pyridyl ) porphine ( TMPyP2 ) ( Frontier Scientific ) was added at 0 . 75μM as in previous work [27] , together with the first ( IdU ) label . Two independent labelling and combing experiments were performed , using wildtype , ΔPfBLM and PfWRN-k/d lines ( all three lines additionally expressing thymidine kinase ) , synchronised in parallel to a ~6hr window by double-sorbitol treatment as previously described [23] . Data from the second experiment are shown in S16 and S18 Figs; DNA replication parameters from both experiments are collated in S2 Table . Stage-matching was confirmed by counting the morphology of 50 parasites in each line by blood-smear microscopy ( S20 Fig ) . The three parasite lines were then harvested in parallel at the latest stage of the replicative period , measured in our previous work as ‘Stage 3’ ( predominantly schizonts and some late trophozoites ) . DNA molecular combing and immunofluorescent labelling of replication tracks was conducted exactly as previously described [23] . Antibodies were: anti-ssDNA antibody ( 1/100 dilution , Chemicon ) , mouse anti-BrdU antibody ( 1/20 dilution , clone B44 from Becton Dickinson ) , rat anti-BrdU antibody ( 1/20 dilution , clone BU1/75 ( ICR1 ) from Sera Lab ) , which recognize IdU and CldU respectively . Secondary antibodies were goat anti-rat antibody coupled to Alexa 488 ( 1/50 dilution , Molecular Probes ) , goat anti-mouse IgG1 coupled to Alexa 546 ( 1/50 dilution , Molecular Probes ) , and goat anti-mouse IgG2a coupled to Alexa 647 ( 1/100 dilution , Molecular Probes ) . Coverslips were mounted in Prolong Gold Antifade ( Molecular Probes ) before image acquisition via a fully motorized Leica DM6000 microscope equipped with a CoolSNAP HQ2 1 CCD camera and controlled by MetaMorph ( Roper Scientific ) . Statistical analyses of inter-origin distances and velocities of replication forks were performed using Prism 5 . 0 ( GraphPad ) . Data were analysed as previously described [23] . In brief , replication fork velocity was estimated on individual forks displaying an IdU track flanked by a CldU track; only intact forks were analysed , as ascertained by DNA counterstaining . Fork asymmetry was calculated as the ratio of the longer track over the shorter track in pairs of progressing divergent forks . A longer fork/shorter fork ratio >1 indicates asymmetry . Inter-origin distances were measured as the distance ( in kb , from the stretching factor of 2 kb/μm ) between the centres of two adjacent progressing forks located on the same DNA fibre . DNA replication parameters generally do not display a Gaussian distribution [71] so statistical comparisons were carried out using the nonparametric Mann–Whitney two-tailed tests . | Human malaria is caused by Plasmodium parasites , with most of the mortality ( almost half a million deaths each year ) being caused by one species , Plasmodium falciparum . This parasite has an unusual genome: it is exceptionally biased towards A and T nucleotides rather than G and C , and it contains specific areas rich in hypervariable virulence-associated genes which evolve very rapidly to produce new variants . This evolution is probably vital for the parasite to evade the human immune system and maintain chronic infections , but how it is controlled at a molecular level remains unknown . We have identified a helicase in the parasite with a huge influence on genome stability and the rate of genome evolution . It appears to function by unwinding various unusual DNA structures , and if this fails then the genome becomes unstable . In addition , the transcription of many genes whose DNA tends to form secondary structures is affected , and DNA replication is impeded . If this helicase was expressed variably in different parasite strains infecting humans , it could influence the parasites’ ability to grow and replicate efficiently , and also , crucially , its ability to evolve and thus evade the human immune system . | [
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"bi... | 2018 | RecQ helicases in the malaria parasite Plasmodium falciparum affect genome stability, gene expression patterns and DNA replication dynamics |
Chlamydiae are intracellular bacteria that commonly cause infections of the respiratory and genital tracts , which are major clinical problems . Infections are also linked to the aetiology of diseases such as asthma , emphysema and heart disease . The clinical management of infection is problematic and antibiotic resistance is emerging . Increased understanding of immune processes that are involved in both clearance and immunopathology of chlamydial infection is critical for the development of improved treatment strategies . Here , we show that IL-13 was produced in the lungs of mice rapidly after Chlamydia muridarum ( Cmu ) infection and promoted susceptibility to infection . Wild-type ( WT ) mice had increased disease severity , bacterial load and associated inflammation compared to IL-13 deficient ( −/− ) mice as early as 3 days post infection ( p . i . ) . Intratracheal instillation of IL-13 enhanced bacterial load in IL-13−/− mice . There were no differences in early IFN-g and IL-10 expression between WT and IL-13−/− mice and depletion of CD4+ T cells did not affect infection in IL-13−/− mice . Collectively , these data demonstrate a lack of CD4+ T cell involvement and a novel role for IL-13 in innate responses to infection . We also showed that IL-13 deficiency increased macrophage uptake of Cmu in vitro and in vivo . Moreover , the depletion of IL-13 during infection of lung epithelial cells in vitro decreased the percentage of infected cells and reduced bacterial growth . Our results suggest that enhanced IL-13 responses in the airways , such as that found in asthmatics , may promote susceptibility to chlamydial lung infection . Importantly the role of IL-13 in regulating infection was not limited to the lung as we showed that IL-13 also promoted susceptibility to Cmu genital tract infection . Collectively our findings demonstrate that innate IL-13 release promotes infection that results in enhanced inflammation and have broad implications for the treatment of chlamydial infections and IL-13-associated diseases .
Chlamydiae are Gram-negative , obligate intracellular bacteria that commonly cause respiratory and genital tract as well as ocular infections in humans . Globally , Chlamydophila pneumoniae has been estimated to account for 5% of cases of bronchitis and sinusitis , and up to 22% of cases of community-acquired pneumonia requiring hospitalisation [1] , [2] . Chlamydia trachomatis is the world's most common sexually transmitted bacterial infection with an estimated 92 million new cases reported annually [3] , and vertical transmission of C . trachomatis can initiate eye infections and pneumonia in new-borns [4] , [5] . Chlamydiae commonly cause asymptomatic infections and significantly , between 50–80% and 10–20% of adults have anti-C . pneumoniae and anti-C . trachomatis antibodies respectively , indicating the high prevalence of these infections within the community [1] , [6] , [7] , [8] . Furthermore , chlamydial infection has been linked with a number of chronic disease states including asthma [9] , chronic obstructive pulmonary disease ( COPD ) [10] , [11] , atherosclerotic cardiovascular disease [12] , and neurodegenerative disorders such as Alzheimer's disease [13] . Understanding the complex immunobiology of host-pathogen interactions and the delineation of the specific responses that drive clearance versus tissue damage are of paramount importance for the prevention and treatment of chlamydial infection and diseases . CD4+ T helper type 1 ( Th1 ) cells secreting IFN-γ play critical roles in the clearance of infection . The rate of clearance of Chlamydia from infected mouse lungs is directly proportional to increases in IFN-γ levels [14] , [15] , [16] , and the absence of this cytokine or its receptor drives infection into a persistent state [17] , [18] , [19] . IFN-γ enhances the ability of macrophages to clear chlamydial infections [20] , [21] and it is a powerful activator of indoleamine 2 , 3-dioxygenase ( IDO ) and inducible nitric oxide sythase ( iNOS ) , which prevent bacterial growth by limiting tryptophan availability and upregulating nitric oxide ( NO ) production , respectively [22] , [23] , [24] , [25] . Although Chlamydiae predominantly colonise epithelial cells , new evidence suggests that they can also infect smooth muscle cells , vascular endothelial cells and components of the immune system including macrophages and dendritic cells [26] , [27] . Importantly , infection of alveolar macrophages of both human and mouse origin has been demonstrated and is associated with enhanced production of anti-inflammatory cytokines [28] , [29] , [30] . Severe forms of tissue damage due to Chlamydia infections of the respiratory and genital tracts are generally caused by infections that elicit both cytopathic and delayed type hypersensitivity immunopathologic destruction of the epithelium [31] , [32] . In the case of C . pneumoniae and C . trachomatis this can lead to pneumonia and pelvic inflammatory disease and infertility , respectively . At the cell and molecular level immunopathology may consist of excessive infiltration of neutrophils , inflammatory monocytes , and the over-expression of the pro-inflammatory cytokines IL-1β and TNF-α [33] , [34] , [35] . Studies in animals have shown that a deficiency in the IFN-γ response , an overtly suppressive IL-10 response , or a delay in the development of a global T cell response during chlamydial infection can all lead to enhanced bacterial dissemination and disease sequelae [15] , [16] , [36] . Given these previous studies , it seems plausible that the development of anti-chlamydial Th2 immune responses could lead to increased disease susceptibility and immunopathology . In support of this concept , studies in our laboratory have shown that pulmonary infection with the natural mouse pathogen C . muridarum ( Cmu ) can lead to enhanced production of the Th2 cytokine IL-13 . Cmu infection early in life leads to increased production of IL-13 following allergen challenge in adult mice [37] , [38] . On a cellular level , Cmu infection of bone marrow-derived dendritic cells ( BMDC ) modulates the cytokine profile from both DCs and T cells to produce increased IL-13 in vitro [26] . Furthermore , urogenital Cmu infection in MyD88-deficient mice leads to a dominant Th2 response , skewed from the Th1/Th17 response of WT mice , which is associated with an ascending Cmu infection and severe pathology in the upper genital tract [39] . Allergic asthma is characterised by the infiltration of CD4+ Th type 2 ( Th2 ) cells , which produce a specific subset of cytokines ( e . g . IL-4 , IL-5 , IL-10 and IL-13 ) which have been linked to the pathogenesis of disease [40] . Clinical evidence directly links C . pneumoniae infection to asthma [41] , [42] , [43] , [44] . However , the mechanistic basis underlying this relationship remains poorly understood . Enhanced production of IL-13 in response to chlamydial infection may contribute to the induction and exacerbation of asthma [26] , [37] , [38] . IL-13 has been described as a susceptibility factor for infection with both Leishmania major and Crytococcus neoformans [45] , [46] . Both of these studies focus on the adaptive immune response to infection and attribute the ratio of Th2 cell derived IL-13 to Th1 cell IFN-γ as a key factor in determining the ability to mount a protective immune response and elimination of the pathogen . IL-13 is also produced by innate immune cells but the role of this cytokine in innate host defence against infection has received little attention . There is the potential that Chlamydia may induce innate and/or adaptive IL-13 responses to promote infection , which has significant implications for chlamydial respiratory and genital tract diseases , and associated conditions . In the present study we demonstrate that early production of IL-13 during the innate immune response plays a critical and previously unrecognised role in promoting Cmu infection of the respiratory and genital tract .
We first assessed the role of IL-13 in chlamydial respiratory infection . Adult WT and IL-13−/− mice were infected intranasally ( i . n . ) with Cmu and disease severity and bacterial numbers in the lungs were determined over time . Weight is an established indicator of disease severity , and substantial weight loss was observed in WT mice from 7 days after infection ( Figure 1A ) . At this stage of infection mice begin to display significant histopathological changes in the lung [37] . By contrast , IL-13−/− mice increased in body weight from day 7 p . i . ( Figure 1A ) . These differences in weight change between WT and IL-13−/− mice were significant from 9-20 days after infection ( Figure 1A ) . Differences in weight changes between WT and IL-13−/− mice also correlated with bacterial load in the lungs . WT mice had a significant increase in bacterial load from day 3 to day 15 p . i . ( Figure 1B ) . By contrast , IL-13−/− mice had significantly lower levels of Cmu at day 3 p . i . and throughout the course of infection ( Figure 1B ) . The administration of recombinant mouse ( rm ) IL-13 to the lungs of IL-13−/− mice prior to Cmu lung infection resulted in a significant increase in bacterial load at day 5 p . i . compared to untreated controls ( Figure 1C ) . Together , these data demonstrate that the early presence of IL-13 during the innate host defence response plays a central role in promoting susceptibility to Cmu lung infection . Furthermore IL-13 deficiency suppresses the development of clinical signs infection as a result of an enhanced ability to clear the bacteria . We then characterised the influence of IL-13 on inflammatory responses to Cmu infection . Pulmonary inflammation was assessed by enumerating leukocytes in the bronchoalveolar lavage fluid ( BALF ) of infected mice . Infection of WT mice led to a significant increase in the total number of leukocytes , neutrophils and macrophages present in the airways from as early as 5 days p . i . and significant increases in lymphocyte numbers were observed from 15 days p . i . ( Figure 2A–D ) . IL-13 deficiency resulted in a significant reduction in total leukocyte , neutrophil , macrophage and lymphocyte influx into the lungs compared to WT controls , with limited evidence of increases in cellular infiltrates compared to baseline levels . ( Figure 2A–D ) . Eosinophils were not detected in the airways of infected mice ( not shown ) . Differences in neutrophil influx between strains were detected at 5 days p . i . , whereas significant differences in macrophage and lymphocyte numbers were not apparent until the later stages of infection . An increased level of blood neutrophilia was also observed in infected WT compared to IL-13−/− mice ( data not shown ) . Therefore , IL-13 deficiency results in not only reduced bacterial load but decreases in associated inflammation . Next we assessed the temporal expression of IL-13 during chlamydial infection . Quantitative real-time PCR of lung tissue RNA was used to measure the expression of IL-13 in WT mice following i . n . infection and normalised to uninfected controls . Infection was accompanied by a 5-fold increase in IL-13 expression , which was observed as early as 24 hours p . i . compared to naïve controls ( Figure 3A ) . This increased level of IL-13 expression in the lungs of infected mice was maintained for at least 20 days p . i when compared to IL-13 expression in naïve tissue . These data represent the first report of pulmonary IL-13 expression during respiratory chlamydial infection . To explore the mechanisms by which IL-13 mediates the host response to Cmu lung infection , we determined whether IL-13 influences the expression of IFN-γ and IL-10 , factors known to play a central role in the immune response to chlamydial infection . Notably , the expression of IFN-γ and IL-10 were not different between naïve WT and IL-13−/− mice and the onset of IFN-γ and IL-10 production was not affected by the absence of IL-13 during the early stages of infection . Indeed , on days 3 and 5 p . i . there were no significant differences between the expression of IFN-γ in infected IL-13−/− mice compared to WT controls ( Figure 3B ) . On day 10 , IFN-γ production in WT mice was less than IL-13−/− mice , however , by day 15 the production of IFN-γ was greater in WT mice . Interestingly , differences in the levels of IL-10 expression were not observed until day 15 p . i . , where WT mice expressed more IL-10 compared to IL-13−/− mice ( Figure 3C ) . These results demonstrate that IL-13 directly or indirectly influences the expression of other cytokines that have been implicated in host defence against chlamydial infection . However , since these changes were not observed until the later stages of infection they do not explain the effect of IL-13 deficiency on bacterial numbers during the early onset of Cmu infection . This indicates that there are other mechanisms rather than changes in cytokine responses or in T cell phenotype that result in reduced infection in the absence of IL-13 . The limited studies that have investigated the role of IL-13 in pathogen infection have focused on this molecule as a cytokine that is produced by activated CD4+ Th2 cells . By contrast , our data suggest that IL-13 plays an important role as early as 3 days p . i . ( Figure 1B ) , and therefore is mediating innate rather than adaptive responses . To test this hypothesis we depleted CD4+ T cells using a specific monoclonal antibody ( mAb ) prior to and after i . n . infection of WT and IL-13−/− mice . FACS analysis confirmed that antibody treatment depleted CD4+ cell numbers in the lung to less than 5% of that in untreated WT mice ( 0 . 75 ± 0 . 11 Vs . 13 . 91 ± 1 . 26% viable cells , Figure S1 ) . WT mice treated with anti-CD4 mAb had increased chlamydial load in the lungs compared to untreated controls ( Figure 4 ) . Both untreated and treated WT mice displayed a significant drop in body weight 10 days post infection ( 93 . 17 ± 1 . 49 and 94 . 83 ± 1 . 78% of initial weight , p<0 . 01 , respectively ) , which became apparent earlier in the treated group ( data not shown ) . By contrast , CD4+ cell depletion did not significantly affect bacterial load ( Figure 4 ) or body weight in IL-13−/− mice ( 100 . 8 ± 0 . 70 and 100 . 57 ± 1 . 42% of initial weight in untreated and treated IL-13−/− mice respectively ) . Together , these observations suggest that the reduced susceptibility to chlamydial infection in the absence of IL-13 is not mediated by CD4+ T cells but is linked to the innate host defence response . IL-13 is known to affect macrophage function and impair phagocytosis . Phagocytosis of bacteria by macrophages plays an important role in the innate defence against pathogens , including Chlamydia . Therefore , the effect of IL-13 deficiency on Cmu uptake by macrophages was investigated . Equal numbers of bone marrow-derived ( BM ) macrophages from WT and IL-13−/− mice were cultured in the presence of equal titres of UV-inactivated , CFSE-labelled Cmu . Cells were then washed to remove any free Cmu and the percentage of BM macrophages ( F4/80+ cells ) that had taken up Cmu ( CFSE+ ) was determined using flow cytometry . The percentage of Cmu positive macrophages was significantly higher in cultures from IL-13−/− compared to WT mice ( 84 . 4 ± 2 . 3 Vs . 66 . 5 ± 1 . 1% , p<0 . 05 , Figure 5A ) . Notably these methods directly measure phagocytosis rate of a specific number of Cmu by a specific number of macrophages and are not affected by the differing amounts of Cmu present in the two strains . To confirm these data in vivo , the effects of IL-13 on the function of macrophages during Cmu lung infection was also investigated . Alveolar macrophages were isolated from the BALF of infected WT and IL-13−/− mice and the engulfment of Cmu was assessed by staining them using a Chlamydia-specific fluorescent labelling kit ( Figure 5B ) . Interestingly , only half as many BALF macrophages from WT mice stained positive for Cmu 3 days after infection compared to those from IL-13−/− mice ( Figure 5C ) . This is despite total BALF macrophage numbers being similar ( data not shown ) and Cmu numbers increased in the lungs of WT compared to IL-13−/− mice at this stage of infection ( Figure 1B ) . At 5 days after infection no strain-specific differences in the ability of macrophages to engulf Cmu were detected , however , this may be explained by the high numbers of Cmu observed in the lungs of WT mice at this stage of infection . Together , our findings show that in the absence of IL-13 , the uptake of Cmu by macrophages is enhanced . Thus , impaired phagocytosis of Cmu may represent an important mechanism by which chlamydial clearance is delayed in the presence of IL-13 . The absence of IL-13 had profound effects during the early stages of infection . Therefore , we hypothesised that , in addition to influencing macrophage phagocytosis , IL-13 may affect the susceptibility of airway epithelial cells to infection and intracellular proliferation of Cmu . To investigate this hypothesis we established an in vitro model of infection with LA4 cells , an immortalised murine lung epithelial cell line . Confluent monolayers of LA4 cells were infected with Cmu and cells were treated with anti-IL-13 ( αIL-13 ) mAb prior to and during infection . Infection was assessed by enumerating Cmu inclusion positive cells using fluorescent microscopy and by determining the levels of Cmu 16S RNA expression in cultures . 16S expression is an indicator of growth . Previous work in our laboratory has shown that Cmu infection of LA4 cells induces widespread cell lysis after 30 hours ( not shown ) . Therefore , the effects of IL-13 depletion on in vitro infection were assessed after 24 hours . Incubation for 24 hours still allows for the formation of large inclusions within infected cells and is appropriate for analysing of the effect of IL-13 depletion on cellular susceptibility to chlamydial infection . αIL-13 mAb treatment depleted IL-13 protein levels 24 hours after infection ( Figure 6A ) . Significantly , the depletion of IL-13 resulted in decreased susceptibility of LA4 cells to infection . αIL-13 treated LA4 cultures had lower percentages of Cmu inclusion positive cells 24 hours after infection compared to untreated controls ( Figure 6B ) . This observation was confirmed by quantitative real-time PCR analysis , demonstrating that IL-13 deficient cultures had lower copies of Cmu 16S than untreated cultures ( Figure 6C ) . These results indicate that IL-13 directly promotes infection of lung epithelial cells by Cmu . To determine if IL-13 also played a role in promoting infection at other mucosal surfaces we intravaginally infected mice with Cmu and assessed disease severity and bacterial numbers over time . The chlamydial genital tract infection model employed in this study[47] has minimal effects on mouse body weight thus we used a clinical scoring system to determine disease severity ( Table 1 ) . Intravaginally infected WT mice had significantly higher clinical scores and more bacteria in vaginal lavage fluid 15 days p . i . compared to infected IL-13−/− mice ( Figure 7 ) . These data suggest that the role of IL-13 in host responses to Chlamydia infection is not restricted to the lung and suggests that this cytokine may play a role in other Chlamydia associated diseases .
In this study we have shown for the first time that IL-13 responses to Cmu infection are important in establishing and promoting chlamydial infection , and inflammation and disease in the respiratory and genital tracts . These effects are associated with reduced macrophage phagocytosis and enhanced infection of airway epithelial cells . Chlamydial respiratory and genital tract infections and diseases are prevalent throughout the world and infections are associated with a number of other diseases , particularly asthma . Elucidating the mechanisms that determine susceptibility to infection and chlamydial clearance may identify new ways of treating these conditions . We have previously demonstrated that Cmu infection in vitro and in vivo induces IL-13 responses [26] , [38] and that transfer of Cmu infected murine bone marrow dendritic cells ( BMDCs ) into recipient mice subverts the in vivo immune response from a protective Th1 to a non-protective Th2 phenotype that may promote chronic infection [26] . In the present study we extend these studies and show that IL-13 promotes chlamydial infection and has an unexpected role in the immediate host defence responses to infection . Importantly , this association appears to be at the level of the innate rather than the adaptive immune response and is not predicated on alterations in T cells responses or the concomitant suppression of IFNγ responses . In our study IL-13 was increased 5-fold in the lung as early as 24 hours after infection . IL-13 is a potent cytokine and low levels in the airway enhances infection ( Figure 1C ) and induces profound changes in lung physiology [48] . WT mice displayed increased symptoms , Cmu load and airway inflammatory cell burden after infection compared to their IL-13−/− counterparts . Through their capacity to rapidly clear Cmu from the lungs IL-13−/− mice circumvent the development of sequelae associated with chronic infection , including the influx of inflammatory cells into the airway . The role of IL-13 in infection is typically attributed to its function as a Th2 cytokine , often acting as an immunological ‘switch’ by downregulating the Th1 response . Indeed IL-13 has been identified as a susceptibility factor for infection of mice by the protozoan parasite Leishmania major by suppressing the expression of IFNγ and IL-12 [45] . Moreover , over-expression of IL-13 in transgenic mice enhanced pulmonary infection of mice with C . neoformans , which was associated with increased Th2 cytokine production [46] . Interestingly , there was no inverse relationship detected between Th1 and Th2 cytokine production in this setting; however , increased fungal load correlated with attenuated Th17 cytokine production 60 days p . i . In our study the influence of IL-13 on chlamydial infection was evident as early as 3 days p . i . , again suggesting a novel role for this cytokine in the innate rather than acquired immune response to infection . The level of Cmu in the lungs of CD4-depleted , IL-13−/− mice was significantly lower than in both CD4-depleted , WT and untreated WT groups . Furthermore , there were no differences in IFN-g or IL-10 expression early in infection of WT and IL-13−/− mice . These results demonstrate that protection against infection in IL-13−/− mice is not dependent on CD4+ T-cell responses . These results confirm an important and central role for IL-13 in promoting infection during the early phases of the host defence response . Chlamydia is capable of infecting a range of cell types , including alveolar macrophages and epithelial cells [27] . Our study demonstrates for the first time that the presence of IL-13 reduces the ability of macrophages to engulf Cmu in vitro and during in vivo lung infection . This may account for the enhanced ability of mice to clear this pathogen from the respiratory tract in the absence of this cytokine . Investigations of the role of IL-13 in immune responses to infection have shown that this molecule can induce the development of macrophages , which have a documented impairment in the ability to engulf and destroy intracellular pathogens in vitro [49] , [50] and are associated with increased fungal burden in the lungs of mice during C . neoformans infection in vivo [46] . Interestingly , in vitro studies have also demonstrated that macrophage expression of the mannose receptor plays a pivotal role in determining susceptibility to chlamydial infection , although the significance of these findings in vivo have not yet been explored [51] . The capacity of IL-13 to modulate the innate immune response to infection in the present study may be underpinned by the development of macrophages with a reduced capacity to engulf and destroy Chlamydia in the lung . It is also possible that IL-13 may condition the respiratory epithelium so that it is more susceptible to infection , thus the action of IL-13 is on structural cells as well as non-lymphoid cells that play key roles in host defence pathways . Furthermore , the fact that IL-13 mediates susceptibility to genital tract infection highlights the potential widespread role of this molecule in promoting chlamydial infection and diseases . While CD4+ Th2 cells have typically been regarded as the principal source of IL-13 , there is now a growing body of evidence that non-lymphoid cells are important producers of this cytokine and contribute to its associated pathologies . Mast cells [52] , basophils [53] , macrophages [54] , bronchial mucosal cells [55] , airway epithelial cells [56] , dendritic cells [26] and natural killer T ( NKT ) cells [57] have all been demonstrated to generate IL-13 . In our study IL-13 is produced rapidly , with an increase in expression apparent within 1 day p . i . , which suggests that this cytokine is originating from non-lymphoid cells , with innate immune activity . Further studies are required to identify the key cell ( s ) that are the early cellular sources of IL-13 during Cmu infection . The effects of IL-13 in promoting enhanced Cmu infection demonstrated in the current study may provide a basis for the widely observed clinical and experimental link between chlamydial infection and asthma [9] , [38] , [58] , [59] , [60] . Allergic airway inflammation in mice inhibits pulmonary host defence against other respiratory pathogens such as Pseudomonas aeruginosa [61] and alveolar macrophages from children with poorly controlled asthma have an impaired ability to phagocytose FITC-conjugated Staphylococcus aureus [62] . Furthermore BALB/c mice , which are biased towards Th2 cytokine responses , are markedly more susceptible to chlamydial lung infection than the Th1-predisposed C57BL/6 strain [16] . Increases in pulmonary IL-13 in asthmatic patients may promote susceptibility and contribute to the prevalence of chlamydial infection in these patient populations . Our in vitro evidence that IL-13 increases the susceptibility of airway epithelial cells to infection with Cmu also supports this concept . In summary , our study reveals for the first time that production of IL-13 during the innate host defence phase plays a central role in establishing and promoting Cmu respiratory and genital tract infections . This role appears to be independent of CD4+ T cell-mediated adaptive immune responses and may be a result of the reduced ability of macrophages to engulf Cmu and an increased susceptibility of pulmonary epithelial cells to infection . This study enhances our understanding of the pathogenesis of chlamydial infection and identifies IL-13 as new potential target to attenuate infection , inflammation and pathology associated with Chlamydia .
This study was carried out in strict accordance with the recommendations set out in the Australian code of practice for the care and use of animals for scientific purposes issued by the National Health and Medical Research Council ( Australia ) . All protocols were approved by the University of Newcastle Animal Care and Ethics Committee and all efforts were made to minimise suffering . Adult ( 6–8 weeks old ) WT BALB/c mice and IL-13−/− mice on a BALB/c background were supplied by the animal breeding facilities of the Australian National University or the University of Newcastle . Mice were housed under specific pathogen free conditions . Adult mice were infected i . n . with 100 ifu of Cmu ( ATCC VR-123; in 30 µl of sucrose phosphate glutamate buffer [SPG] ) [37] , [38] , [60] , [63] . Mice were monitored over a 20 day period and rate of weight gain/loss was used as a measure of clinical condition . At selected time points , mice were sacrificed by sodium pentobarbital overdose ( Abbott Australasia , Kurnell , Australia ) for analysis . IL-13−/− mice were intratracheally administered rmIL-13 ( 10 ng , 30 µl of PBS , R&D Systems , Gymea , NSW ) or PBS 6 hours prior to infection and sacrificed 5 days later for analysis . Adult mice were subcutaneously injected with 2 mg medroxyprogesterone acetate ( Troy Laboratories , Smithfield , Australia ) to synchronise their estrous cycles . Seven days later mice were infected intravaginally with 5×104 ifu Cmu ( in 20 µl SPG ) [47] . Mice were monitored over a 15 day period and their clinical score determined according to specific signs of disease ( Table 1 ) . At selected time points , mice were sacrificed by sodium pentobarbital overdose for analysis . Whole lungs from mice infected i . n . with Cmu were removed and stored at −80°C . Vaginal lavage was performed on intravaginally infected mice by flushing the vaginal vault with 2×60 µl Hanks buffered salt solution ( HBSS; Trace Scientific , Noble Park , NSW ) . DNA extractions were performed and Cmu numbers ( IFU ) determined in whole lungs or vaginal lavage by real-time quantitative PCR and comparison with known standards as previously described [37] , [38] , [60] , [63] . BALF was obtained by cannulation of the trachea and flushing the airways with 2× 1 ml HBSS [37] . BALF cytospins were stained with May-Grunwald-Giemsa and leukocytes enumerated by morphological criteria ( ≈300 cells by light microscopy [40X] ) [37] . All samples were coded and counts performed in a blinded fashion . Cytokine expression was evaluated by real-time PCR [38] , [60] . Total RNA was extracted from all samples using TRIZOL according to the manufacturer's instructions ( Invitrogen , Mount Waverley , VIC ) . Reverse transcription of RNA ( 1000 ng ) was performed using Superscript III and random hexamer primers ( Invitrogen ) . Relative abundance of genes was determined compared to the reference gene hypoxanthine-guanine phosphoribosyltransferase using a Prism7000 Sequence Detection System ( Applied Biosystems , Scoresby , VIC ) . Primers used were; IFN-γ , Fwd 5′- TCT TGA AAG ACA ATC AGG CCA TCA , Rev 3′- , GAA TCA GCA GCG ACT CCT TTT CC , IL-10 , Fwd 5′- CAT TTG AAT TCC CTG GGT GAG AAG , Rev 3′- , GCC TTG TAG ACA CCT TGG TCT TGG , IL-13 Fwd 5′- AGC TGA GCA ACA TCA CAC AAG ACC , Rev 3′- , TGG GCT ACT TCG ATT TTG GTA TCG , 16S of Cmu , Fwd 5′- GCG GCA GAA ATG TCG TTT T , Rev 3′- , CGC TCG TTG CGG GAC TTA and hypoxanthine-guanine phosphoribosyltransferase , Fwd 5′- AGG CCA GAC TTT GTT GGA TTT GAA , Rev 5′- CAA CTT GCG CTC ATC TTA GGC TTT . Mice were treated intraperitoneally with 300 µg αCD4 ( clone GK1 . 5 ) on days -3 , -1 , 2 and 5 of Cmu lung infection . The effect of T-cell depletion on bacterial recovery was assessed in whole lungs on day 10 . Depletion of CD4+ T-cells was confirmed on day 10 by flow cytometry ( Figure S1 ) . Femurs and tibias of WT and IL-13−/− mice were collected and bone marrow flushed out with complete RPMI ( RPMI 1640 , 5×10−5 M 2-mercaptoethanol , 10% heat-inactivated FCS , 2 mM L-glutamine , 20 mM HEPES , 100 µg/ml penicillin and 100 µg/ml streptomycin ) . Red blood cells were lysed and cells washed through a 70 µm nylon cell strainer . The cells were plated out at 1×105 cells/ml in 10 mls complete RPMI supplemented with 15 ng/ml rmGM-CSF ( Gift from Walter and Eliza Hall Institute [WEHI] , Melbourne ) and incubated at 37°C 5% CO2 . On day 3 , another 5 ml medium containing 15 ng/ml rmGM-CSF was added . On day 7 , supernatants were removed and non-adherent and semi-adherent cells were removed by washing in cold PBS . Adherent cells were recovered by gentle cell scraping and washed using cold PBS supplemented with 2 mM EDTA . These cells were shown to be >90% macrophages by flow cytometry . BM macrophages were plated out ( 2×105 cells/ml , 96 well plate ) and inoculated with CFSE-labelled , UV-inactivated Cmu ( MOI 5 ) and incubated overnight . ( 37°C , 5% CO2 ) in complete RPMI . Cultures were washed with complete RPMI to remove all free Cmu and the percentage of BM macrophages ( F4/80+ cells ) that stained positive for Cmu ( CFSE+F4/80+ cells ) was determined by flow cytometry . BALF was collected from mice on days 3 and 5 following respiratory tract infection . BALF cells were incubated on sterile 10 mm round glass coverslips in a 48 well culture plate for 1 h ( 37°C , 5% CO2 ) in complete RPMI to allow adhesion of macrophages . Coverslips were removed and adhered cells stained using the Chlamydia Cel LPS kit ( CelLabs , Brookvale , NSW ) according to the manufacturers instructions . The percentage of macrophages that stained positive for the presence of Chlamydia was determined in each sample ( ≈300 macrophages assessed by fluorescent microscopy [40X] ) . All samples were coded and counts performed in a blinded fashion . LA4 cells ( 3×105 ) were plated out on sterile 10 mm glass coverslips in a 48 well culture plate and incubated in Iscove's modified Eagle media ( 500 µl , 10% fetal calf serum ) for 24 h in the presence of either 100 µg αIL-13 mAb ( R&D Systems ) or PBS ( untreated control ) . Confluent cell monolayers were then infected with Cmu ( MOI 5 ) , treated again with αIL-13 mAb or PBS and cultured for a further 24 h . Supernatants were collected and IL-13 ELISA performed according to the manufacturer's instructions ( R&D Systems ) . For staining of chlamydial inclusions , coverslips were removed and cells stained with the Chlamydia Cel LPS kit . The percentage of Cmu inclusion positive cells was determined for each treatment ( average of >10 fields determined at 40× magnification using a fluorescent microscope ) . To determine 16S Cmu RNA expression RNA was prepared and assayed by real-time PCR as described above . Results are presented as mean±SEM . Statistical significance of whole data sets was initially confirmed using one-way ANOVA . The Wilcoxon Rank-sum test was used for non-parametric tests ( Mann-Whitney test for two independent samples ) . P<0 . 05 was considered statistically significant . | Chlamydial infections are a common cause of respiratory , genital tract and eye diseases , and infections are clinically associated with the aetiology of asthma , emphysema , heart disease and Alzheimer's . However , it is not known what immune factors regulate enhanced susceptibility to infection and immunopathology . In this study we have investigated the role of the immune factor , interleukin-13 ( IL-13 ) , in C . muridarum infections in mice . IL-13 is produced rapidly after respiratory infection in normal mice . However , mice deficient in IL-13 have reduced clinical symptoms and numbers of C . muridarum in their lungs after infection . The immune cells of mice deficient in IL-13 phagocytose more C . muridarum and their lung cells have less infection . The role of IL-13 is not restricted to the lung as IL-13-deficient mice have significantly lower levels of bacterial replication and more mild disease during genital tract infection . Our results suggest that IL-13 responses enhance chlamydial infections and that this factor may be a new therapeutic target for the treatment of disease . | [
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... | 2011 | Interleukin-13 Promotes Susceptibility to Chlamydial Infection of the Respiratory and Genital Tracts |
Mammalian sleep varies widely , ranging from frequent napping in rodents to consolidated blocks in primates and unihemispheric sleep in cetaceans . In humans , rats , mice and cats , sleep patterns are orchestrated by homeostatic and circadian drives to the sleep–wake switch , but it is not known whether this system is ubiquitous among mammals . Here , changes of just two parameters in a recent quantitative model of this switch are shown to reproduce typical sleep patterns for 17 species across 7 orders . Furthermore , the parameter variations are found to be consistent with the assumptions that homeostatic production and clearance scale as brain volume and surface area , respectively . Modeling an additional inhibitory connection between sleep-active neuronal populations on opposite sides of the brain generates unihemispheric sleep , providing a testable hypothetical mechanism for this poorly understood phenomenon . Neuromodulation of this connection alone is shown to account for the ability of fur seals to transition between bihemispheric sleep on land and unihemispheric sleep in water . Determining what aspects of mammalian sleep patterns can be explained within a single framework , and are thus universal , is essential to understanding the evolution and function of mammalian sleep . This is the first demonstration of a single model reproducing sleep patterns for multiple different species . These wide-ranging findings suggest that the core physiological mechanisms controlling sleep are common to many mammalian orders , with slight evolutionary modifications accounting for interspecies differences .
The diversity of mammalian sleep poses a great challenge to those studying the nature and function of sleep . Typical daily sleep durations range from 3 h in horses to 19 h in bats [1] , [2] , which has led to recent speculation that sleep has no universal function beyond timing environmental interactions , with its character defined purely by ecological adaptations on a species-by-species basis [3] . Consolidated ( monophasic ) sleep , has only been reported in primates [2] , whereas the vast majority of mammals sleep polyphasically , with sleep fragmented into a series of daily episodes , ranging in average length from just 6 min in rats to 2 h in elephants [1] . Some aquatic mammals ( such as dolphins and seals ) engage in unihemispheric sleep , whereby they sleep with only one brain hemisphere at a time [4]–[6] . This behavior appears to serve several functions , including improved environmental surveillance and sensory processing , and respiratory maintenance [7] , although the physiological mechanism is unknown [8] , [9] . Determining which aspects of mammalian sleep patterns can be explained within a single framework therefore has important implications in terms of both the evolution and function of sleep . As we show here , although mammalian sleep is remarkably diverse in expression , it is very likely universal in origin . Recent advances in neurophysiology have revealed the basic mechanisms that control the mammalian sleep cycle [10] , [11] . Monoaminergic ( MA ) brainstem nuclei diffusely project to the cerebrum , promoting wake when they are active [12] . Mutually inhibitory connections between the MA and the sleep-active ventrolateral preoptic area of the hypothalamus ( VLPO ) result in each group reinforcing its own activity by inhibiting the other and thereby indirectly disinhibiting itself . This forms the basis of the sleep-wake switch , with active MA and suppressed VLPO in wake , and vice versa in sleep [10] . State transitions are effected by circadian and homeostatic drives , which are afferent to the VLPO [13] . The approximately 24 h periodic circadian drive is entrained by light , and projects from the suprachiasmatic nucleus ( SCN ) to the VLPO via the dorsomedial hypothalamus ( DMH ) [14] . The homeostatic drive is a drive to sleep that increases during wake due to accumulation of somnogens , accounting for the observed sleep rebound following sleep deprivation [15] . During sleep , somnogen clearance exceeds production and the homeostatic drive decreases . The exact physiological pathway has yet to be fully elaborated , but some important somnogenic factors have been identified , including adenosine ( a metabolic by-product of ATP hydrolysis ) [16] and immunomodulatory cytokines [17] . The present work uses a model that does not depend on the precise identity of the somnogen ( or somnogens ) , but may help to elucidate its characteristics . Whether the above system can account for the wide variety of mammalian sleep patterns is unknown . Is the sleep-wake switch a universal physiological structure among mammals ? Or are the qualitative differences in sleep-wake patterns between species such as rats and dolphins due to fundamentally different mechanisms ? To answer these questions we apply a recent quantitative physiologically-based model [18] , [19]; this approach allows the underlying physiological structure to be related to the observed dynamics . As shown in Fig . 1 , the model includes the MA and VLPO groups , circadian and homeostatic drives to the VLPO , and cholinergic and orexinergic input to the MA ( for mathematical details , see Methods ) . The model is based on physiological and behavioral studies of a small number of species , including rats , mice , cats , and humans , and has been calibrated previously to reproduce normal human sleep and recovery from sleep deprivation [18] , [19] . But as we will show , the model is also capable of reproducing the typical sleeping patterns for a wide range of mammalian species , including both terrestrial and aquatic mammals .
With nominal parameter values ( given in Methods ) , the model has previously been shown to reproduce normal human sleep patterns , with approximately 8 h of consolidated sleep , and relatively rapid ( approximately 10 min ) transitions between wake and sleep [18] , as shown in Fig . 1 . We found that by varying just two of the model parameters , the model could be made to reproduce the bihemispheric sleep patterns of a wide variety of mammals , including many in which the neuronal circuitry controlling sleep rhythms has not been examined . These parameters were: ( i ) the homeostatic time constant , determining the rate of somnogen accumulation and clearance , and ( ii ) the mean drive to the VLPO , provided by the SCN , DMH and other neuronal populations . The homeostatic time constant was found previously to be approximately 45 h for humans , based on the rate of recovery from total sleep deprivation [19] , but we found here that reducing it below 16 h resulted in polyphasic sleep , as seen in most other mammals . This is because a shorter time constant causes somnogens to accumulate more quickly during wake , and dissipate more quickly during sleep , resulting in more rapid cycling between wake and sleep . Increasing the mean inhibitory drive to the VLPO was found to decrease daily sleep duration with little effect on the other dynamics . Fitting the model to experimental data for 17 species in which both average daily sleep duration and average sleep episode length have been reliably reported yielded the map in Fig . 2 , showing which regions of parameter space correspond to the typical sleep patterns of each species . ( Note that at least some quantitative sleep data is available for over 60 species , but these two measures have not both been reliably reported in most cases . ) This map enables classification of mammals based on sleep patterns , and can be further populated in future when more data becomes available . The regions corresponding to the human , rhesus monkey , and slow loris lie in the monophasic zone , but with different mean VLPO drives . In each case , the lower bound for the homeostatic time constant was determined by the boundary of the monophasic zone . For humans , the upper bound of 72 h was previously determined using sleep deprivation experiments [19] . In the absence of experiments detailing recovery from total sleep deprivation in non-human primates , we used the same upper bound for both the rhesus monkey and the slow loris; more data is required to rigorously constrain the homeostatic time constant for these species . Animals that sleep relatively little , such as the elephant , were inferred to have high values of mean drive to VLPO , while animals that sleep a lot , such as the opossum and armadillo , were inferred to have low values of mean drive to VLPO . Those that cycle rapidly between wake and sleep , such as rodents , were inferred to have short homeostatic time constants ( around 10 min to 1 h ) , while those with fewer sleep episodes per day , such as the jaguar and elephant were inferred to have longer time constants ( around 5 h to 10 h ) , thus lying closer to the boundary between polyphasic and monophasic sleep . The extreme cases of no wake and no sleep may correspond to brainstem lesions , such as those documented clinically [31] , and possibly other states of reduced arousal ( e . g . , hibernation , torpor , coma ) , although we did not pursue them here . Using parameter values from the appropriate regions in Fig . 2 , we generated sample time series for various species . Comparisons to experimental data for the human , elephant and opossum are shown in Fig . 3 . In each case , the model reproduced the salient features of the sleep/wake pattern . For the opossum , the circadian signal was shifted in phase by 12 h to reproduce the nocturnal distribution . This is justified by physiological evidence suggesting that temporal niche is determined by how SCN output is modulated by the DMH relay system [11] . Plotting the homeostatic time constants inferred for each species versus body mass in Fig . 4 revealed a positive correlation . Fitting a power-law relationship yielded an exponent of 0 . 29±0 . 10 for non-primates . Additional data are required to accurately constrain homeostatic time constants in non-human primates , but using the human-derived upper bound of 72 h yielded an exponent of 0 . 01±0 . 26 for primates , and 0 . 28±0 . 12 for all species . Power-law relationships are ubiquitous in biology , although their quantification remains controversial . For mammals it has been found that brain mass scales as approximately , where is total body mass , and metabolic power per unit volume scales as for brain tissue [33] . Without knowing the precise mechanism by which the homeostatic drive is regulated , we nonetheless tested general assumptions that are equally applicable to a wide range of candidate mechanisms . We assumed that somnogen production is proportional to the total power output of the brain ( as would plausibly be the case for adenosine ) , meaning production per unit volume would scale as , with different production rates in wake and sleep . Furthermore , we made the generic assumption that somnogen clearance rate is proportional to working surface area , where this surface area may be glial , vascular , or otherwise , depending on the exact physiological pathway . The total clearance rate then scaled as , where , depending on the geometry: corresponds to surface area scaling as the square of the brain's linear dimension ( i . e . , as for simple solids ) , and to scaling as its cube ( e . g . , as for solids with highly convoluted or fractal surfaces ) . By assuming clearance rate was also proportional to somnogen concentration , the homeostatic time constant was found to be proportional to ( see Methods for a full derivation ) . For , this yielded a power law exponent of 0 . 23 , consistent with that found for non-primates . The smaller exponent found for primates was consistent to within uncertainties with that found for non-primates; more primate data are required to determine whether is closer to 1 in primates , or whether both groups follow the same scaling law but with different normalization constants . We next turned to modeling unihemispheric sleep by extending the above model to permit distinct dynamics for the two halves of the brain . As shown in Fig . 1 , this was achieved by coupling together two identical versions of the original model , each representing one hemisphere . This division in the model was justified by the fact that all nuclei in the VLPO and MA groups are bilaterally paired [12] , [34] , with the exception of the dorsal raphé nucleus , which lies on the brainstem midline [12] . Separate homeostatic drives were included for each brain hemisphere , based on experimental evidence for localized homeostatic effects in humans , rats and dolphins [35]–[38] . Aquatic mammals that have been observed to sleep unihemispherically spend little or no time in bihemispheric sleep while in water [8] ( although fur seals switch to exclusively bihemispheric sleep when on land [39] ) . Hence , we postulated the existence of a mutually inhibitory connection between the two VLPO groups in aquatic mammals to prevent both activating at once ( just as the mutually inhibitory VLPO-MA connection prevents both those groups activating simultaneously ) , thereby preventing bihemispheric sleep . This connection is presumably absent or very weak in other mammals . For VLPO-VLPO connection strengths weaker than a threshold value sleep was purely bihemispheric , and above this value at least some unihemispheric sleep episodes occurred . For connection strengths stronger than a higher threshold the model exhibited purely unihemispheric sleep , typical of cetaceans . Differing homeostatic pressures between the two hemispheres drove alternating episodes of left and right unihemispheric sleep , with episode length controlled by homeostatic time constant , in a way similar to polyphasic bihemispheric sleep as described above . In Fig . 5 , increasing the VLPO-VLPO connection strength was shown to cause a transition from polyphasic bihemispheric sleep to unihemispheric sleep , as for fur seals moving from land to water [6] , [39] . Since no other parameter changes were required , we hypothesized that fur seals achieve this readjustment by dynamically neuromodulating the VLPO-VLPO connection strength in response to environmental stimuli . The required strengthening by a factor of somewhat more than 2 . 4 is reasonable given the magnitudes of typical neuromodulator effects .
We have provided the first demonstration that the neuronal circuitry found in a small number of species in the laboratory , including rats , mice and cats , can account for the sleep patterns of a wide range of mammals . Furthermore , this was achieved by varying only two model parameters , with all others taking fixed values determined previously . The implications of this are far-reaching: universality of this fundamental physiological structure across diverse orders would suggest that its evolution predates mammals . This is consistent with findings that show the monoaminergic system is phylogenetically pre-mammalian [40] , and that simple organisms such as the zebrafish share homologous neuronal and genetic control of sleep and wake [41] , [42] . Our results also demonstrate the inherent functional flexibility of the sleep-wake switch , which plausibly accounts for its evolutionary success in the face of diverse evolutionary pressures on the sleep-wake cycle . Physiological commonality is also of immense importance when using animals in pharmaceutical development , and for inferring the consequences for humans of animal sleep experiments and genetics . Our findings suggest that the rate of cycling between wake and sleep is largely determined by the homeostatic time constant , which is inferred to have a positive correlation with body mass . Deviations from this relationship are likely due to selective pressures such as predation , food availability , and latitude . Consistent with this , a previous study found a scaling law of exponent 0 . 20±0 . 03 between the characteristic timescale of sleep episode durations ( which followed an exponential distribution ) and body mass [43] . Mean drive to the VLPO determined sleep duration , and no clear correlation was found between this parameter and body size . Experimental evidence suggests that sleep duration is dictated by interplay between physiological and ecological pressures [44] . The primary advantage conferred by using a physiologically-based model to analyze and interpret data is the ability to relate such behavioral measures to physiology , giving new insights into how interspecies differences in sleep patterns arise . Due to the relative paucity of appropriate data , in this study we made use of all data we could find . This meant combining results of behavioral studies with EEG studies , despite the fact that these methods likely produce slightly different estimates of sleep duration and sleep bout length . While this should not affect our main conclusions , it could fractionally shift the zones in Fig . 2 . We thus emphasize the importance of experimentalists continuing to study a wide variety of mammalian species , and encourage them to report metrics such as sleep bout length , total daily sleep duration , and transition frequencies . While the exact physiological mechanism underlying the homeostatic sleep drive is unknown , some pieces of the puzzle have been identified . Growing evidence points to the role of adenosine accumulation at specific brain sites in promoting sleep . In the rat , basal forebrain adenosine concentration has been found to gradually rise and fall during wake and sleep , respectively , with heightened levels following sleep deprivation [16] . Artificial infusion of adenosine reduces vigilance [45] , and the wake-promoting effects of caffeine ( which is a competitive antagonist of adenosine ) provide additional indirect evidence for adenosine's role in homeostatic sleep regulation . However , the pathway by which adenosine induces sleep is not altogether clear . Adenosine inhibits wake-promoting cholinergic neurons in the basal forebrain , and disinhibits the VLPO via another basal forebrain population [13] , [46] , yet adenosine agonists continue to promote sleep even after cholinergic neurons are lesioned [47] . Immune signaling molecules such as interleukin-1 ( IL-1 ) and tumor necrosis factor ( TNF ) have also been linked to homeostatic sleep regulation [17] . Levels of TNF and IL-1 alternate with the sleep/wake cycle , and their exogenous administration induces sleepiness [48] . Furthermore , increased cytokine production during bacterial infection increases sleep duration [48] , unless the IL-1 system is antagonized [49] . However , the pathway by which cytokines regulate sleep has yet to be fully elaborated . More critically , no physiological process has been demonstrated to account for the homeostatic drive's timescale , which can be up to a week in the case of chronic sleep deprivation in humans [50] . Adenosine's half life in the blood is only seconds [51] , suggesting that clearance and production may be rate-limited further upstream . In this paper , we assumed that somnogen production and clearance rates are proportional to brain volume and surface area , respectively . The utility of this approach is that it does not require precise knowledge of the physiology underlying the homeostatic drive , because these assumptions are equally valid for a wide range of candidate mechanisms . Using them , we were able to relate scaling laws for metabolism and brain mass to the observed interspecies differences in sleep patterns . Additional data is required to ascertain whether primates follow a different scaling law from non-primates , and if so whether this is due to greater cortical folding , cortical thickness , and neuronal density than most other mammals [52] , which could feasibly account for geometrical differences in vascular surface area for instance . Furthermore , additional data is required to determine whether the positive correlation between body mass and homeostatic time constant conforms to a power law . In a similar vein , a theoretical study by Savage and West [53] was able to predict an observed power law relationship between body mass and the ratio of sleep to wake duration , based on the assumption that sleep's primary function is brain maintenance and repair , but the present derivation is the first from a dynamical sleep model . While sleep/wake patterns are controlled at a fundamental level by systems in the brainstem and hypothalamus , it is worth remembering that sleep is a multi-scale phenomenon , regulated at many levels . For example , synaptic homeostasis may contribute to the local regulation of slow wave activity in the cortex during sleep , and could even play a role in generating the homeostatic drive to the sleep-wake switch [54] , [55] . The proposed interhemispheric inhibitory connection in unihemispheric sleepers awaits experimental testing . To date , VLPO afferents have only been studied in animals that sleep bihemispherically , with the great majority of these being ipsilateral [34] . It remains to be seen whether aquatic mammals have a stronger contralateral connection . A question that naturally arises is whether an analogous connection might also be present to some degree in animals that sleep bihemispherically , and whether unihemispheric sleep could be induced by decoupling the hemispheres by other means . Acallosal humans have decreased EEG coherence between hemispheres during sleep , but do not display unihemispheric sleep [56] , suggesting that hemispheric synchrony is achieved subcortically . Consistent with this , bisection of the brainstem in cats has been shown to result in all four behavioral states: bihemispheric wake , bihemispheric sleep , and unihemispheric sleep in each hemisphere [57] . This suggests that in bihemispheric sleepers , contralateral excitatory connections between wake-promoting brainstem nuclei and/or the VLPO nuclei may be important to maintaining synchrony . However , bisection of the brainstem in monkeys did not induce unihemispheric sleep [58] . The existence of several other commissures between the hemispheres , including the corpus callosum , may help to explain these results , with one able to compensate for the lack of another in some species . Animals that sleep unihemispherically appear to have evolved multiple physiological changes in parallel to enable this mode of sleep , including a narrow or absent corpus callosum in dolphins and birds , respectively , to reduce interhemispheric coupling [59] . In future , our model could be applied to the sleep of species from other classes , including unihemispheric sleep in reptiles and birds [8] . Furthermore , we could consider explicitly modeling the DMH pathway to explore how temporal niche ( diurnal vs . nocturnal vs . crepuscular ) is determined . Extending the model to differentiate between REM and NREM sleep could provide additional insights . Using such approaches in parallel with physiological investigations could then help to elucidate the evolutionary development of the sleep-wake switch and its specializations .
We begin by reviewing the sleep-wake switch model developed previously; for more details see references [18] and [19] . The model includes the MA and VLPO neuronal populations , and the parameters of the model have been rigorously calibrated by comparison to physiological and experimental data for normal human sleep and recovery from sleep deprivation [18] , [19] . Nominal human parameter values are given in Table 1 . Each neuronal population has a mean cell-body potential relative to resting and a mean firing rate , where for MA and VLPO , respectively , with ( 1 ) where is the maximum possible firing rate , is the mean firing threshold relative to resting , and is its standard deviation . Neuronal dynamics are represented by ( 2 ) ( 3 ) where the weight the input to population j from k , is the decay time for the neuromodulator expressed by group j . The orexinergic/cholinergic input to the MA group is held at a constant average level to smooth out ultradian REM/NREM dynamics [18] . The drive to the VLPO , ( 4 ) includes homeostatic and circadian components , where and are constants determining the strengths of the homeostatic and circadian drives , respectively . The parameter is positive , so that the homeostatic drive promotes sleep; this is consistent with disinhibition of the VLPO by basal forebrain adenosine [13] . The parameter is negative , consistent with the fact that SCN activity promotes wake in diurnal animals [60] . Differences in temporal niche appear to be due in part to an inversion of this signal [60] , but as noted in the Discussion , we do not attempt to model this here . The circadian drive is here assumed to be well entrained and so is approximated by a sinusoid with 24 h period , ( 5 ) where h−1 , is the mean drive to the VLPO , and is the initial phase . The homeostatic sleep drive is represented by somnogen concentration , with its dynamics governed by ( 6 ) where is the homeostatic time constant , and is a constant which determines the rate of homeostatic production . Previously , has been considered a model for adenosine concentration in the basal forebrain [18] , but this general form is equally applicable to many other candidate somnogens . As shown in earlier work [18] , during normal functioning of the model , is high ( ∼5 s−1 ) in wake , is low ( ∼0 s−1 ) and is increasing , while is low in sleep , is high and is decreasing . For the purposes of comparing to data , we define the model to be in wake if s−1 , based on comparison with experimental data for MA firing rates [61] . The model differentiates wake vs . sleep states , and we make no attempt to reproduce different sleep intensities or intra-sleep architectures between species . The parameters and are varied to reproduce mammalian sleep patterns using total daily sleep duration and average sleep episode length as metrics to calibrate against . They have previously been estimated to take the values and h for humans . These parameters were selected as best able to account for differences in both total daily sleep duration and sleep bout length based on preliminary investigations and previous sensitivity analysis [18] . Data for calibration were derived from an extensive search of the literature to find studies that reported ranges for both metrics , yielding the 17 species used here . Parameter ranges that satisfied these metrics were plotted as the regions shown in Fig . 2 . All of the available data were used , with one exception: additional data for non-human primates that sleep monophasically were omitted since we are unable to derive an upper bound for the homeostatic time constant without obtaining data detailing the dynamics of recovery from total sleep deprivation for these species . Those included in the study ( the slow loris and the rhesus monkey ) are shown for illustrative purposes using the human-derived upper bound of 72 h . To produce Fig . 3 , we add noise terms with to the right hand sides of Eqs ( 2 ) and ( 3 ) , respectively , so as to make the sleep patterns less regular . The noise is taken from a normal distribution of mean 0 and standard deviation 1 , and mV h1/2/ ( ΔT ) 1/2 , where ΔT is the size of the time step used in the numerical integration . Values of parameters are taken from within the appropriate regions in Fig . 2 . For the human , we use , h; for the elephant , we use , h; for the opossum we use , h . For modeling unihemispheric sleep , the above model , defined by Eqs . ( 1 ) – ( 6 ) is used identically to model the dynamics of each half of the brain , with the following modification to the VLPO differential equation: ( 7 ) where is the firing rate of the VLPO population in the other half of the brain , and represents the strength of the contralateral inhibitory connection . Mammalian brain mass has been found to follow an approximate scaling law ( 8 ) where is body mass [33] . Furthermore , the power output of the brain follows , ( 9 ) If the total rate of somnogen production in the brain is assumed to be proportional to the total power output of the brain , then the rate of somnogen production per unit volume , denoted by , is ( 10 ) We assume that the total clearance rate is proportional to the working surface area , which may be glial , vascular , or otherwise . The working surface area will thus scale as the brain's mass , , where depending on the brain's geometry . Therefore , the rate of somnogen clearance per unit volume , denoted by , is ( 11 ) Now , if is produced at a rate where is a factor that depends on the state of arousal ( i . e . , production is expected to be higher in wake than in sleep ) , and is cleared at a rate , where is constant , then ( 12 ) which can be rewritten as ( 13 ) where the homeostatic time constant is , and . For , this yields and , justifying the approximation of holding constant while varying throughout this study . | The field of sleep physiology has made huge strides in recent years , uncovering the neurological structures which are critical to sleep regulation . However , given the small number of species studied in such detail in the laboratory , it remains to be seen how universal these mechanisms are across the whole mammalian order . Mammalian sleep is extremely diverse , and the unihemispheric sleep of dolphins is nothing like the rapidly cycling sleep of rodents , or the single daily block of humans . Here , we use a mathematical model to demonstrate that the established sleep physiology can indeed account for the sleep of a wide range of mammals . Furthermore , the model gives insight into why the sleep patterns of different species are so distinct: smaller animals burn energy more rapidly , resulting in more rapid sleep–wake cycling . We also show that mammals that sleep unihemispherically may have a single additional neuronal pathway which prevents sleep-promoting neurons on opposite sides of the hypothalamus from activating simultaneously . These findings suggest that the basic physiology controlling sleep evolved before mammals , and illustrate the functional flexibility of this simple system . | [
"Abstract",
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"Results",
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"Methods"
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] | 2010 | Mammalian Sleep Dynamics: How Diverse Features Arise from a Common Physiological Framework |
Alternative polyadenylation ( APA ) can for example occur when a protein-coding gene has several polyadenylation ( polyA ) signals in its last exon , resulting in messenger RNAs ( mRNAs ) with different 3′ untranslated region ( UTR ) lengths . Different 3′UTR lengths can give different microRNA ( miRNA ) regulation such that shortened transcripts have increased expression . The APA process is part of human cells' natural regulatory processes , but APA also seems to play an important role in many human diseases . Although altered APA in disease can have many causes , we reasoned that mutations in DNA elements that are important for the polyA process , such as the polyA signal and the downstream GU-rich region , can be one important mechanism . To test this hypothesis , we identified single nucleotide polymorphisms ( SNPs ) that can create or disrupt APA signals ( APA-SNPs ) . By using a data-integrative approach , we show that APA-SNPs can affect 3′UTR length , miRNA regulation , and mRNA expression—both between homozygote individuals and within heterozygote individuals . Furthermore , we show that a significant fraction of the alleles that cause APA are strongly and positively linked with alleles found by genome-wide studies to be associated with disease . Our results confirm that APA-SNPs can give altered gene regulation and that APA alleles that give shortened transcripts and increased gene expression can be important hereditary causes for disease .
In protein-coding genes , the polyadenylation process consists of cleaving the end of the 3′ untranslated region ( UTR ) of precursor messenger RNA ( pre-mRNA ) and adding a polyadenylation ( polyA ) tail . Alternative polyadenylation ( APA ) can occur when several polyadenylation ( polyA ) signals lie in the last exon of a protein-coding gene . Many APA signals are evolutionary conserved [1] , and Expressed Sequence Tag ( EST ) data suggest that 54% of human genes have alternative polyadenylation signals [1] . The polyA signals themselves are hexamer DNA sequences that usually lie 10 to 30 nucleotides upstream from the cleavage site [2] , but a GU-rich region 20 to 40 nucleotides downstream of the cleavage site is also important for the polyA-process [2] . One functional consequence of APA is transcripts with different 3′UTR lengths and different microRNA ( miRNA ) regulation [3] , [4] . Shortened transcripts tend to have increased expression compared with longer transcripts , and the same expression increase can be achieved by deleting miRNA target sites in non-shortened transcripts [5] . Data on APA can be used as an efficient biomarker for distinguishing between cancer subtypes and for prognosis [6] , and seems to play an important role in gene deregulation and in many human diseases [7] . One such mechanism for deregulation is mutations in the polyA signal or GU-rich downstream region [7] . A single nucleotide polymorphism ( SNP ) in the GU-rich region downstream of an alternative polyA signal in the FGG gene has for example been shown to affect the usage of this polyA site , and has been associated with increased risk for deep-venous thrombosis [8] . Similarly , a mutation in the 3′UTR of the CCND1 gene has been shown to create an alternative polyA signal and is associated with increased oncogenic risk in mantle cell lymphoma [9] . Hypothesizing that mutations in DNA elements such as the polyA signal can be an important cause of altered APA , we investigated to what extent SNPs can create or disrupt APA signals ( APA-SNPs ) . Specifically , we tested whether APA-SNPs can give shorter 3′UTRs , increased gene expression through loss of miRNA regulation ( Fig . 1 ) , and be associated with disease . Our hypothesis focuses on shorter 3′UTRs rather than longer ones , because the loss of functional miRNA sites in the 3′UTR is more likely than the gain of new sites downstream of the gene . First , by analysing EST data , we found that SNPs can create polyA motifs and affect 3′UTR length . Second , differential allelic expression from RNA-seq data , as well as mRNA and miRNA microarray expression data revealed an association between alternative polyA site strength ( signal and GU-content ) , loss of miRNA target sites , and transcript expression . Third , based on these analyses we also identified significant APA-SNPs . Fourth , we mapped the identified SNPs to disease-associated SNPs and found that APA alleles were significantly correlated with disease-risk alleles . Together , these results suggest that APA-SNPs can be a significant causative mechanism in disease ( Fig . S1 ) .
The distribution of SNPs within 3′UTRs is fairly uniform [10] ( Fig . S2A ) . The main exceptions are microRNA target sites and the start and end of the 3′UTR , which have decreased SNP diversity that is consistent with these regions containing functional elements under selective pressure [10] . Indeed , when specifically investigating the region around the transcription end site , we found that the position containing the polyA signal has a markedly decreased SNP density ( Fig . S2B , C ) , indicating that SNPs arising there could have a high functional impact . To analyse SNPs in alternative polyadenylation signals , we first identified a set of SNPs that potentially create new APA signals in 3′UTRs . Specifically , we searched for any Hapmap SNP [11] that could create or disrupt one of the 13 known polyA signal hexamers [1] in any coding gene's 3′UTRs ( see Methods ) . We found 1954 SNPs , including 755 SNPs that are mono-allelic in the CEU population from Hapmap [11] ( see Datasets ) . We kept only the APA-SNPs that change from no signal to one signal in the locus , by discarding loci with several signals in the 40 nucleotides around the SNP , discarding SNPs that change one signal into another , and discarding mono-allelic SNPs . After filtering , 412 SNPs that can create or delete potential polyadenylation signals remained . We will from now refer to them as our candidate SNPs . To investigate whether SNPs can create functional alternative polyA sites , we analysed the EST-based polyA sites from the PolyA_Db database [12] , [13] . In the PolyA_Db database , there are several polyA sites which do not have any noticeable polyA signal ( according to the reference genome ) in the 40 , 80 , and 100 nucleotides upstream from the reported cleavage site position ( Table S1 ) . In those regions , we used different SNP data to look for SNPs that could create a polyA signal with the non-reference allele . When considering regions of 100 nucleotides and SNPs from NCBI dbSNP Build 130 [14] , we could identify polyA signals with the alternative allele for more than of the missing signals . Some of the remaining sites can probably be explained by SNPs further upstream , and some other by exon splicing , by alterations in ESTs that are not registered in dbSNP , or as false positive sites . Since EST-based annotated polyA sites can be affected by SNPs , we wanted to test whether alleles in polyA sites could be associated with EST ending positions . Specifically , we first took the intersection between the polyA signals from our 412 candidate SNPs , and the polyA sites from PolyA_Db database [12] , [13] . We identified 18 intersecting polyA sites that have a polyA signal for either the reference or the non-reference allele . These sites corresponded to 18 SNPs in 18 genes . Five SNPs were discarded because they lie within the 20 last nucleotides of the reference 3′UTR . The following 13 genes remained: ABCC4 , AKAP13 , FANCD2 , KY , MIER1 , OSTM1 , PNN , RASGRP3 , RHOJ , SELS , SHMT1 , SLBP , and SLC11A2 . Second , for each of these genes , we identified and imputed ( see Methods ) alleles at the SNPs in the EST sequences when possible , and tested if the proportion of alleles with polyA signal ( APA alleles ) was different for EST sequences ending within the interval nucleotides around the polyA site , compared to EST sequences ending further downstream ( see Methods ) . The two genes MIER1 ( SNP rs17497828 ) and PNN ( SNP rs532 ) were significant ( Fig . 2 , Table 1 ) . After correcting for multiple testing ( Benjamini & Hochberg correction ) , the genes remained significant when including alleles imputed based on haplotype ( Table 1 ) . For MIER1 , 12 of the 16 EST sequences ending near the annotated APA site had the APA allele ( including 2 with a clear polyA tail ) , whereas 3 had the non-APA allele ( none of them had a clear polyA tail ) . Similarly , for PNN , all of the 34 EST sequences ending near the annotated APA site had the APA allele ( including 10 with a clear polyA tail ) . Together , these results suggest that SNPs can create functional APA sites and thereby affect 3′UTR length . EST data can be used to identify alleles and transcript ending positions ( Fig . 1 ) , but EST data seldom have sufficient resolution to quantify transcript expression levels . In contrast , RNA-seq data can both be used to genotype SNPs [15] and to analyse transcript length and expression patterns . The main challenge with RNA-seq data compared with ESTs , however , is the shorter sequence reads , which makes it challenging to distinguish between homozygotes , heterozygotes with strong expression differences between its alleles ( allelic imbalance ) , sequencing errors , and alignment errors . To explore whether RNA-seq data could reveal whether APA-SNPs affect transcript expression , we therefore developed and validated an RNA-seq-based genotyping approach ( see Supporting Text S2 ) . We then used this approach to show that APA-SNPs can affect transcript expression and that this effect is associated with loss of miRNA regulation . Specifically , we first show that homozygous APA-SNPs have significantly shorter 3′UTRs than have heterozygous or homozygous wildtype SNPs . Second , we show an association between allelic imbalance of heterozygous APA-SNPs and the two following important features of polyA sites: signal strength and GU level downstream of the cleavage site . Third , we show that the loss of miRNA target sites can be the missing link in this association . Fourth , we use allelic imbalance to detect potentially functional APA-SNPs . Fifth , we show that APA-SNPs at strong sites ( strong APA signal and high GU level ) that have a strong predicted effect on miRNA regulation , have higher allelic imbalance and higher transcript expression than have other APA-SNPs . To confirm the results from the RNA-seq-based allelic imbalance analyses , we turned to gene expression data from the well characterised Hapmap population . We looked at human gene expression profiling of EBV-transformed lymphoblastoid cell lines from 270 unrelated Hapmap individuals [17] , and genotypes of the same individuals , from the Hapmap database [11] . Specifically , we first investigated whether genotypes of SNPs in strong polyA sites that affect miRNA targeting in general are associated with increased gene expression . Second , we investigated whether individual APA-SNP genotypes correlate significantly with gene expression . Since SNPs can alter polyadenylation and affect miRNA target sites and gene expression , we wondered whether they can also play an important role in human diseases . We therefore tested if any of our APA-SNPs were linked to trait-associated SNPs from the NHGRI GWAS catalogue [20] , [21] , which consists of SNP-trait associations from published genome-wide association studies ( GWAS ) ( accessed Apr . 18 , 2011 ) . Specifically , we mapped our 412 APA-SNPs to the 4304 GWAS SNPs , by using the mapping method described in Thomas et al . [22] . The mapping was based on linkage disequilibrium ( LD ) data from the Hapmap database ( CEU population release 27 ) . We identified 135 APA-SNP/GWAS-SNP pairs ( consisting of 84 unique APA-SNPs and 123 unique GWAS SNPs ) that had available haplotype data in Hapmap and one known and unique risk allele in the GWAS catalogue . For each APA-SNP/GWAS-SNP pair , we computed the correlation between the APA allele and risk allele as the LD value [23] , where , , and are respectively the APA allele frequency of the APA-SNP , the risk allele frequency of the GWAS SNP , and the “APA allele risk allele” haplotype frequency in the CEU Hapmap population . For each of the 84 unique APA-SNPs , we computed as the mean of when an APA-SNP was linked to several GWAS SNPs , and similarly as the mean of . We hypothesised that if APA-SNPs play a role in diseases , then APA alleles would be positively ( ) and strongly ( high ) correlated with risk alleles , particularly for the significant APA-SNPs that we identified in the previous sections , as they are more likely to be functional , and particularly those that are linked to GWAS-SNPs from CEU-population-related studies , since the values are based on CEU haplotypes . Among the 84 APA-SNPs , 60 were paired to GWAS-SNPs that are trait-associated in CEU-related populations . Nine of those SNPs were identified in the previous sections as significant APA-SNPs , and those nine SNPs had a significantly high number of positive ( more positive correlations between APA and risk alleles than expected ) and a significantly high number of greater than 0 . 2 ( higher number of correlations between APA and risk alleles than expected ) ( Table 2 ) . In contrast , for computed from CEU haplotypes but for GWAS-SNPs that are trait-associated in non-CEU-related populations , binomial test p-values were not significant , suggesting that GWAS and haplotype data should be matched according to population , to detect potential disease-related APA-SNPs . Those results show that a significantly high proportion of our candidate SNPs is in LD with trait-associated SNPs and their APA alleles are positively correlated with risk alleles of trait SNPs . This suggests that those APA-SNPs can potentially be the cause of their corresponding disease-association signals measured and registered in the GWAS catalogue .
Our analyses confirmed the hypothesis ( presented in Fig . 1 ) that SNPs can create functional alternative polyadenylation signals and thereby affect miRNA-based gene regulation and give increased gene expression . Both EST and RNA-seq analyses supported our hypothesis , despite some limitations . Additionally , the microarray analysis could further confirm these results and strengthen our hypothesis . Given the results from these three analyses , we estimate the proportion of functional APA-SNPs to be ( ) . The EST analysis supports our hypothesis but has some limitations . Specifically , we analysed EST data for 13 genes and found that 2 of them had an APA-SNP that could create polyA motifs and affect 3′UTR length . However , the EST analysis does not take into account the presence of a polyA tail in the EST sequence . Moreover , the ESTs came from a mix of tissues , which could also affect the results . Segregating ESTs based on tissue origin or filtering on sequences with clear tails in the “short” group , reduces sample size and affects statistical power . However , when combining sequences from our two significant genes , all of the 12 EST sequences ending at the alternative cleavage site and that have a polyA tail , had the APA allele . This number is significant ( binomial test p-value of , where the expected proportion of the APA allele is the combination of weighted allele frequencies of APA alleles for the 2 SNPs ) , and tells that the shortened transcripts arose from functional APA signals from the APA alleles . Similarly , RNA-seq data from the Burge Lab , matched to miRNA expression data showed association between alternative polyA site strength ( signal and GU-content ) , loss of miRNA target sites , allelic imbalance , and transcript expression . The Burge dataset was generated by using cDNA fragmentation , which gives a good coverage of 3′UTRs [24] . An increased allelic imbalance towards the APA allele could come from the loss of miRNA target sites , but also from the fragmentation method . This is because cDNA fragmentation gives a good coverage at the end of the transcript , and , in case of alternative polyadenylation , the transcript is shorter for the APA allele , which results in a high coverage at the SNP locus . In contrast , a longer transcript with the non-APA allele could have a higher coverage downstream , but a lower coverage at the SNP locus . Bias from cDNA fragmentation would therefore give an increased allelic ratio towards the APA allele simply because of transcript length differences . Consequently , we cannot exclude that some of the overall RNA-seq trends can be attributed to cDNA fragmentation bias . The independent microarray data strongly support the EST and RNA-seq results , however . Specifically , the mRNA and miRNA microarray expression data showed association between alternative polyA site strength ( signal and GU-content ) , loss of miRNA target sites , and transcript expression . This microarray analysis had the advantage of directly using genotype data from Hapmap , instead of genotyping SNPs through mapped RNA-seq reads . Furthermore , the microarray analysis focused on transcript expression differences between individuals and therefore required data from a unique cell type , whereas the RNA-seq analysis focused on allelic expression differences within a sample and could therefore involve different cell types . As expected , the microarray analysis showed similar results as the RNA-seq analysis , suggesting that the increased allelic ratios from RNA-seq data did not come from a potential bias due to the cDNA fragmentation method , but from the loss of functional miRNA target sites . One clear disadvantage of using the RNA-seq data for genotyping and allelic-imbalance-based detection , was false positive homozygotes . We could detect potentially functional candidate SNPs by testing for allelic imbalance , which takes into account the number of reads and their quality , while testing for unusual allele proportion patterns . The difficulty was to find extreme allelic imbalance , as we could miss extreme imbalance by classifying a locus as homozygote because of too few reads ( ) corresponding to the alternative allele . This was a conscious trade-off , however , since we wanted to maximise true positive heterozygotes and avoid false positives ( i . e . predicted heterozygotes that were in fact homozygous ) . RNA-seq data enabled us to genotype SNPs in expressed genes and compute allelic imbalance . Genotype classification could be checked with known genotypes from the Heap dataset and with mono-allelic SNPs . However the Heap dataset could not be used in the allelic imbalance analysis , because the library was generated by using RNA fragmentation , which gives a good coverage for the coding regions [24] , but not for the UTRs . Since we were interested in SNPs in 3′UTRs , and particularly at the end of potentially alternative transcripts , RNA fragmentation would affect allelic imbalance . The whole analysis is limited to SNPs that can make the reference 3′UTR shorter , lose miRNA sites and upregulate genes , because the loss of functional miRNA sites within the 3′UTR is more likely than the gain of new ones downstream of the annotated 3′UTR . However , it could be interesting to consider the hypothesis where SNPs in the signals at the end of the reference transcript could make 3′UTR longer having more miRNA target sites further downstream , and down-regulate the gene . Alternative polyadenylation alleles play a role in 3′UTR shortening , gene deregulation , and increased disease risk ( Fig . 1 ) . Our analyses confirm that APA is an important factor for miRNA-mediated gene regulation [4] . EST data suggest that SNPs can create polyA motifs and affect 3′UTR length , and allelic imbalance from RNA-seq data coupled to miRNA expression data suggest an association between alternative polyA site strength ( signal and GU-content ) , loss of miRNA target sites , allelic imbalance and transcript expression . Similarly , mRNA microarray expression data and matched genotypes of the same individuals , coupled with miRNA expression data could confirm association between alternative polyA site strength ( signal and GU-content ) , loss of miRNA target sites , genotype and transcript expression . Each of our analyses could also be used to detect potentially functional APA-SNPs . The detected APA-SNPs could further be linked to GWAS-SNP markers and a significant part of these APA-SNPs had their APA allele positively correlated with disease-risk alleles . We propose that these APA SNPs are potential disease-causative variants .
We used SNP data from the CEU population ( CEPH - Utah residents with ancestry from northern and western Europe ) from the human haplotype map project ( HapMap database [11] ) , release 22 for haplotype data , and release 27 for the genotype , allele , frequency , and linkage disequilibrium data . We used the human genome assembly version 18 ( hg18 ) [25] , RefSeq gene annotations ( hg18 version ) , and EST sequences from the UCSC Genome browser [26] . We used human APA sites from PolyA_Db [12] , [13] . We used disease-associated SNPs from the NHGRI GWAS catalogue [20] , [21] . RNA-seq data came from Heap et al . [15] and from the Burge Lab [27] . Human miRNA profiles came from Landgraf et al . [16] ( their Table S5 ) and from Wang et al . [18] . MicroRNA data came from the MirBase database release 16 [28] . Thirteen polyA signal motifs are known in human genes: AAUAAA , AUUAAA , UAUAAA , AGUAAA , AAGAAA , AAUAUA , AAUACA , CAUAAA , GAUAAA , AAUGAA , UUUAAA , ACUAAA , and AAUAGA [1] ( ordered by strength ranks ) . We detected SNPs in potential APA signals , by a motif search that looks if any CEU Hapmap SNP in the 3′UTR of any coding gene would create/disrupt one of those 13 motifs . For a given SNP , the motif search looks for a given motif in an mRNA sub-sequence consisting of the SNP and its flanking sequences ( 6 nucleotides up/downstream ) , for each allele . We downloaded the 28 . 857 APA sites ( human ) from PolyA_Db [12] , [13] from the UCSC track ( hg18 ) [26] . We downloaded knownToLocusLink . txt and knownToRefSeq . txt from UCSC ( hg18 ) [26] to convert entrez gene ID to RefSeq gene ID . We took the intersection between our APA signals and polyA sites from PolyA_Db , by taking all the sites from PolyA_Db that lie up to 40 bp downstream of our signals . For each of the 13 candidate genes , we downloaded the EST sequences ( Expressed sequence tag ) from UCSC ( hg18 , tables ‘all_mrna’ and ‘all_est’ ) [26] that lie within their 3′UTR region . We also downloaded their alignment to their reference mRNA sequence from UCSC [26] , and the list of EST that support the considered polyA site from PolyA_Db2 [13] . We used sequence alignment to identify the allele and haplotype of each sequence , when possible . Otherwise , the APA-SNP allele was imputed , by using haplotypes from the CEU Hapmap population [11] ( see Dataset ) . We tested the proportion of APA alleles that support the candidate APA site , versus longer transcripts , by using a 2×2 contingency table . If the 4 expected values were greater than 5: we used the 2×2 , and Fisher's exact test otherwise . Given a 3′UTR region of a gene of interest , we took all the phased SNPs from Hapmap [11] in that region , as well as their haplotypes in the CEU population [11] . For each of those SNPs , we identified the allele in the EST sequence when possible , to identify the EST haplotype . We discarded EST haplotypes that had zero identified allele . For each remaining EST haplotype , we selected haplotypes from Hapmap that fit the identified alleles in the EST haplotype . The APA-SNP could be imputed if there was only one unique allele at that SNP in all the selected haplotypes from Hapmap . We downloaded RNA-seq data from human primary cells from 4 individuals [15] ( Short read archive accession number: SRA008367 ) , reads in FASTQ format , length of 45 bp . We downloaded Burge lab RNA-seq [27] ( Short read archive: SRA002355 , and Gene expression omnibus: GSE12946 ) : Human tissue samples ( brain , liver , heart , skeletal muscle , colon , adipose , testes , lymph node , breast , MAQC , 6 Cerebellum ) , immortalised and cancer cell lines ( BT474 , HME , MCF-7 , MD435 , T47D , MAQC UHR ) , reads in FASTQ format , length of 36 bp . MAQC is a mixture of brain cell types from several donors , MAQC UHR is a mixture of several cancer cell lines , and MD435 is thought to be contaminated by the M14 melanoma cell line . Therefore those 3 cell lines were discarded from the allelic imbalance analysis . We mapped RNA-seq reads using the RMAP software [29] , with option ‘-Q’ for position weight matrix matching , based on quality score . Alignment was stored in BED files . We used the default options: 2 mismatches allowed in the 32 first nucleotides , 10 mismatches allowed in the whole read . Ambiguous reads were discarded . Paired-End reads were mapped as Single-End reads . We mapped those reads to 3′UTR 50 bp: the reference sequence is all 3′UTR DNA sequences ( from the human genome assembly HG18 [25] ) from all coding genes ( excluding Y chromosome because of overlap with X ) , including introns , extended of 50 nucleotides up- and downstream . Overlapping sequences were merged ( 19012 regions ) . We mapped reads to a second version of the reference sequence , where reference alleles of APA-SNPs were replaced by non-reference alleles . We counted base calls based on base quality probability score and sequence alignment score: We discarded reads mapped with an alignment score , and reads that had a quality score accuracy at the SNP . Quality score probability of accuracy at a SNP was computed as follows: , where is the ASCII character of one base call in a read in FASTQ file format [30] . We computed the mapping score as , where is the alignment score given by RMAP . We counted alleles as for each allele ( for all the FASTQ files of each individual ) . We discarded alleles that do not fit Hapmap bi-allelic SNPs . If there was only one allele left , we classified the SNP as homozygous . If there were two alleles left , with both proportions greater than 0 . 15 , we classified the SNP as heterozygous . If there were two alleles but one had its proportion lower than 0 . 15 , we classified the SNP as homozygous with the allele having the biggest proportion . We mapped reads from the Burge dataset using the alignment software Bowtie [31] version 0 . 12 . 7 with default options . Bowtie generated alignments in the SAM format [32] . The transcript assembly software Cufflinks version 1 . 3 . 0 [33] was then used with the SAM files to generate a list of expressed exons for each run ( default options ) . Those exons were then mapped back to annotated RefSeq genes . Exons that mapped to several different genes were discarded; the corresponding genes they overlapped were also discarded . For a given gene and a given run , the 3′ end of the exon that mapped the most downstream on the gene was used as an estimate of the gene's 3′ end . Finally , the distance between the estimate and the annotated transcript end was computed for each gene and each run . This distance is negative when the transcript is shorter than the annotation and had a logarithmic distribution for negative s . Few transcripts were longer than the annotated transcription end site , resulting in positive values . To handle these few positive values , we put a threshold at 30 , so that all were truncated to 29 . We then converted the s to the logarithm scale by using the following formula: . Log Allelic Ratio for each heterozygous SNP is defined as , where counts of alleles are computed in a similar way as in the genotyping section ( by taking base quality and alignment score into account ) . is positive when the transcripts with APA alleles are up-regulated compared to non-APA allele . However , to avoid that a mapping bias towards reference alleles affects allelic ratios , we used a corrected allelic imbalance in our analyses , by combining allelic ratios computed from reads mapped to the reference genome with reference alleles , and allelic ratios computed from reads mapped to the same genome but with non-reference alleles at candidate SNPs . We defined it as the mean of the two log-ratios: where is the allelic ratio , and are the counts of APA alleles mapped to respectively the genome with reference alleles , and the one with non-reference alleles . Similarly and are the counts of non-APA alleles . We took all the known coding genes from the UCSC RefSeq gene database ( hg18 ) [26] . To define the precise region of GU-analysis , for each gene , we computed the GU proportion in a 5-nucleotide long window sliding from the polyA signal downstream in a 70-nucleotide long region . Those curves represent the variation of GU proportion in the region for each gene . We then took the mean of all the curves , which showed that the increased GU region was from the window to the window ( Fig . S4 ) . We therefore defined the GU level as the mean of the GU-proportions in the 5-nucleotide windows , from the to the downstream of the polyA signal . We downloaded human gene expression profiling of EBV-transformed lymphoblastoid cell lines from 270 unrelated Hapmap individuals [17] ( Gene expression omnibus: GSE6536 , data normalised across populations ) , and genotypes for the same individuals , from the Hapmap database release 27 . We mapped probe IDs to RefSeq genes using the BioConductor package for R [35] , [36] ( R version 2 . 10 . 1 , AnnotationDbi package version 1 . 8 . 2 [37] and the annotation file illuminaHumanv1 . db version 1 . 4 . 0 ) . One candidate SNP could have one or several RefSeq gene IDs , which could be mapped to one or several probe IDs . Among those probe IDs , we selected the one with maximum variance across all the individuals in the dataset , and assigned it to the given SNP in the 3′UTR . Genotype was encoded as 0 , 1 , and 2 for non-APA homozygotes , heterozygotes , and APA homozygotes , respectively . We computed bootstraps of median differences: Given two groups with different sizes , we resampled with replacement in each group with their actual original size . We took the median in each resampling and computed the difference . We repeated this procedure 1000 times to create a median difference distribution , which was then used to compute the 95% confidence interval ( CI ) . We mapped APA-SNPs to GWAS SNPs , using the mapping method described in Thomas et al . [22] . The mapping was based on linkage disequilibrium ( LD ) data from the Hapmap database ( CEU population release 27 ) . The mapping parameter was the threshold ( see Thomas et al . [22] ) , to identify all neighbouring APA-SNP/GWAS-SNP pairs . | Variants in DNA that affect gene expression—so-called regulatory variants—are thought to play important roles in common complex diseases , such as cancer . In contrast to variants in protein-coding regions , regulatory variants do not affect protein sequence and function . Instead , regulatory variants affect the amount of protein produced . The 3′ untranslated region ( UTR ) is one gene region that is critically important for gene regulation; cancers for example , often express genes with shortened 3′UTRs that , compared with full-length 3′UTRs , have higher and more stable expression levels . We have investigated one kind of regulatory variant that can affect the 3′UTR length and thereby cause disease . We identified several such variants in different genes and found that these variants affected the genes' expression . Some of these variants were also strongly linked with known markers for disease , suggesting that these regulatory variants are important hereditary causes for disease . | [
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"g... | 2012 | Single Nucleotide Polymorphisms Can Create Alternative Polyadenylation Signals and Affect Gene Expression through Loss of MicroRNA-Regulation |
Peroxisome proliferator activated receptor gamma 2 ( PPARg2 ) is the nutritionally regulated isoform of PPARg . Ablation of PPARg2 in the ob/ob background , PPARg2−/− Lepob/Lepob ( POKO mouse ) , resulted in decreased fat mass , severe insulin resistance , β-cell failure , and dyslipidaemia . Our results indicate that the PPARg2 isoform plays an important role , mediating adipose tissue expansion in response to positive energy balance . Lipidomic analyses suggest that PPARg2 plays an important antilipotoxic role when induced ectopically in liver and muscle by facilitating deposition of fat as relatively harmless triacylglycerol species and thus preventing accumulation of reactive lipid species . Our data also indicate that PPARg2 may be required for the β-cell hypertrophic adaptive response to insulin resistance . In summary , the PPARg2 isoform prevents lipotoxicity by ( a ) promoting adipose tissue expansion , ( b ) increasing the lipid-buffering capacity of peripheral organs , and ( c ) facilitating the adaptive proliferative response of β-cells to insulin resistance .
An adipocentric view of the Metabolic Syndrome ( MS ) considers obesity as the major factor leading to insulin resistance in peripheral metabolic tissues . However , the link between obesity and insulin resistance is complex , as indicated by the fact that some extremely obese people are glucose tolerant , while others with a mild degree of obesity develop severe insulin resistance and diabetes . This suggests that the absolute amount of fat stored may not be the most important factor determining the relationship between obesity and insulin resistance . Recent work showing the complexity of the molecular mechanisms controlling adipogenesis [1 , 2] suggests that adipose tissue expandability may be an important factor linking obesity , insulin resistance , and associated comorbidities . There are two mechanisms that have been proposed to explain how expansion of the adipose tissue stores affects insulin sensitivity . One mechanism suggests that increased adiposity induces a chronic inflammatory state characterized by increased cytokine production by adipocytes and/or from macrophages infiltrating adipose tissue . Cytokines produced by these adipocytes or macrophages may directly antagonise insulin signalling [3 , 4] . A second nonexclusive hypothesis is lipotoxicity . The lipotoxic hypothesis states that if the amount of fuel entering a tissue exceeds its oxidative or storage capacity , toxic metabolites that inhibit insulin action are formed [5–8] . Of particular relevance to this article , lipid metabolites , such as ceramides and diacylglycerol ( DAG ) or reactive oxygen species generated from hyperactive oxidative pathways , have been shown to inhibit insulin signalling and to induce apoptosis [9–11] . The nuclear receptor peroxisome proliferator activated receptor gamma ( PPARg ) is critically required for adipogenesis and insulin sensitivity [12–15] . There are two PPARg isoforms , PPARg1 and PPARg2 . PPARg1 is expressed in many tissues and cell types , including white and brown adipose tissue , skeletal muscle , liver , pancreatic β-cells , macrophages , colon , bone , and placenta [16] . Under physiological conditions , expression of PPARg2 , the other splice variant , is restricted to white and brown adipose tissue [16 , 17] . In adipose tissue PPARg is the key regulator of adipogenesis . PPARg2 is the more adipogenic PPARg isoform in vitro , it is also the isoform regulated transcriptionally by nutrition [17–20] . Although under physiological conditions expression of PPARg2 is limited to adipose tissues , we have shown that PPARg2 is ectopically induced in liver and skeletal muscle in response to overnutrition or genetic obesity [2 , 18] . De novo expression of PPARg2 in liver and muscle in obesity suggests that PPARg2 may have a role in insulin resistance and lipotoxicity in these tissues . Little in vivo research into the metabolic roles for the specific isoforms of PPARg has been carried out , with the studies so far focusing almost exclusively on adipose tissue [2 , 13 , 21 , 22] . PPARg ( both isoforms ) deletions have been generated in most major metabolic tissues . Liver-specific deletion of both PPARg isoforms caused an impairment in insulin sensitivity , particularly when challenged by different genetic backgrounds ( lipoatrophic or leptin-deficiency ) [23 , 24] . The effect of ablating both PPARg isoforms in muscle produced controversial results , with two groups reporting different effects on insulin sensitivity [25 , 26] . The role of PPARg in pancreatic β-cells is unclear , primarily due to its low expression under physiological conditions [27–29] and secondly because ablation of both PPARg isoforms in β-cells did not result in a metabolic phenotype . However PPARg may play a role in β-cell hyperplasia in response to insulin resistance , an idea supported by the fact that mice that lack PPARg in β-cells do not expand their β-cells mass in response to a high-fat diet [30] . More recently , it has been shown that heterozygous PPARg-deficient mice develop impaired insulin secretion , which is associated with increased islet triacylglycerol ( TAG ) content [31] . Here we investigate the physiological relevance of PPARg2 under conditions of positive energy balance by ablating PPARg2 in ob/ob mice . We use a new approach that integrates traditional physiological phenotyping with advanced lipidomic technology and transcriptomics . Our results indicate that in the context of positive energy balance , the absence of PPARg2 results in a major metabolic failure . Furthermore , we provide evidence that control of adipose tissue expansion by PPARg2 may be an important variable linking positive energy balance to its metabolic complications including insulin resistance , β-cell failure , and dyslipidaemia . Similarly , our lipidomic results indicate that induction of PPARg2 in nonadipose tissues should be considered as a physiological adaptation that prevents the toxic effects produced by excess nutrients . This antilipotoxic effect of PPARg2 is achieved by increasing the lipid-buffering capacity of peripheral organs and facilitating β-cell hyperplasia in response to insulin resistance .
PPARg2−/− Lepob/Lepob mice with genetic ablation of the PPARg2 isoform on the obese hyperphagic ob/ob background ( POKO ) were generated . Matings of PPARg2+/− Lepob/Lep+ mice followed the expected Mendelian distribution ( Fisher's test = 0 . 074 and 0 . 135 for males and females , respectively ) . PPARg1 gene expression in white adipose tissue ( WAT ) from five-week-old POKO mice was similar to PPARg2 KO mice and was not significantly different from wild-type ( WT ) mice ( Figure S1 ) . Figure 1A shows growth curves for male and female mice of four genotypes ( WT , PPARg2 KO , ob/ob , and POKO mice ) over a 12-week period . At birth , the body weight of male and female POKO mice was indistinguishable from other genotypes ( unpublished data ) . The ob/ob mice quickly became heavier than their WT littermates , with significantly elevated body weight by four and six weeks of age in female and male mice , respectively . However , the POKO mice did not become obese , and their body weight remained close to WT and PPARg2 KO body weights mice during the 12-week study . POKO mice were as hyperphagic ( Figure 1B ) as the ob/ob mice but drank far more water compared with ob/ob littermates ( 81 . 85 ± 15 . 14 versus 9 . 05 ± 2 . 32 ml/70 h , p < 0 . 01 , female POKO versus ob/ob , n = 4 at 20 wk ) ( Figure S2A ) . Dual-energy X-ray absorptiometry analysis at 20 wk ( Figure 1C ) confirmed that female POKO mice had slightly increased fat content ( 4% ) compared to WT and PPARg2 KO mice , but significantly reduced fat mass compared to the 40% increase observed in ob/ob mice . At the age of 20 wk , POKO and ob/ob mice had a trend to a decreased total locomotor activity during dark and light cycles compared with the WT and PPARg2 KO mice over the 72-h period . However POKO had similar total locomotor activity compared with ob/ob mice ( Figure S2B ) . At six weeks of age , female POKO mice consumed a similar amount of oxygen as ob/ob mice ( vO2 = 25 . 06 ± 0 . 89 versus 23 . 10 ± 0 . 99 ml/kg bodyweight 0 . 75/min , p = 0 . 07 POKO versus ob/ob , n = 6–8 ) showing a lower respiratory exchange ratio ( 0 . 916 ± 0 . 011 versus 0 . 952 ± 0 . 007 , p = 0 . 01 , female POKO versus ob/ob ) in the fed state , but similar respiratory exchange ratio in the fasted state ( 0 . 73 ± 0 . 014 versus 0 . 75 ± 0 . 018 , p-value = 0 . 59 POKO versus ob/ob mice ) . Water intake was already significantly increased in POKO compared to ob/ob mice ( 13 . 59 ± 1 . 88 versus 8 . 15 ± 0 . 89 ml/d , p-value < 0 . 05 , POKO versus ob/ob ) . Furthermore , levels of glucose in urine were higher in POKO mice compared with ob/ob mice ( 403 . 4 ± 49 . 2 versus 34 . 13 ± 13 . 5 mMol/l , POKO versus ob/ob mice , p-value = 0 . 001 ) , showing an energy loss of 15 . 43 ± 3 . 06 kJ/d through urine compared with 0 . 70 ± 0 . 19 kJ/d in ob/ob mice . At this age , POKO mice showed similar locomotor activity compared with the ob/ob mice during the day , but increased locomotor activity during the night ( Figure S2C ) . Histomorphometric analysis of adipose tissue from 16-wk-old male mice revealed that POKO mice had fewer small adipocytes than the ob/ob mice ( Figure 1D and 1E ) . This analysis of adipocyte size suggests that ablation of PPARg2 in the ob/ob background impairs the potential for adipocyte recruitment . As expected the reduced adipose tissue expandability of the POKO mouse was associated with severe insulin resistance . Surprisingly insulin resistance developed very early in life with elevated insulin levels and blood glucose compared to ob/ob mice ( Table 1 ) . We investigated whether peripheral insulin resistance and/or a severe defect in insulin secretion may cause hyperglycaemia in the POKO mouse . No differences in plasma glucose levels were detected three to five days after birth amongst the four genotypes for both genders ( unpublished data ) . At weaning ( three weeks of age ) total body weight was indistinguishable amongst the four genotypes , and blood glucose levels were similar in males and females ( Figure 2A ) . However , by the age of four weeks , coincident with the change to a chow diet , male and female POKO mice developed severe hyperglycaemia compared to the other genotypes . Insulin plasma levels in the POKO mice at four weeks of age were increased compared to ob/ob mice ( Table 1 ) . Insulin resistance in POKO mice was confirmed by an insulin tolerance test ( ITT ) in four-week-old male and female mice ( Figure 2B ) . Furthermore insulin resistance in adipose tissue was demonstrated by the extremely low levels of glucose transporter4 ( GLUT4 ) protein in POKO adipose tissue when compared with GLUT4 levels in adipose tissue from ob/ob mice ( Figure S3 ) . Of note , insulin resistance in the POKO mice was associated with hypertriglyceridaemia as early as four-weeks of age ( Table 1 ) . Given the early insulin resistance and hyperinsulinaemia in the young POKO mice , we expected to see increased insulin levels in mature POKO mice . At 16 weeks , male POKO mice exhibited severe hyperglycaemia in the fasted and fed states compared to littermate controls . Male POKO mice had inappropriately low levels of insulin ( Table 2 ) . A similar , but milder phenotype was also observed in POKO female mice ( unpublished data ) . Of note , adult ob/ob mice compensated for their insulin resistance with increased insulin levels ( Table 2 ) . POKO mice also had hypertriglyceridaemia when compared to WT , ob/ob , or PPARg2 KO mice . The inappropriately low insulin levels in the adult POKO mice suggested a defect in β-cells . Insulin resistance in ob/ob mice was compensated for by increasing pancreatic insulin secretion , islet number , and size ( Figure 3A ) . However , despite being more insulin resistant than ob/ob mice , POKO mice did not increase their β-cell mass , resulting in lower plasma insulin levels than the ob/ob controls . Morphometric analysis of pancreatic sections from 16-week-old male mice confirmed that the islet-to-pancreas volume ratios were similar in the POKO , WT , and PPARg2 KO mice ( 0 . 023 ± 0 . 005 , 0 . 013 ± 0 . 006 , and 0 . 016 ± 0 . 005 , respectively ) and markedly increased in ob/ob mice ( 0 . 077 ± 0 . 017 , p < 0 . 01 ob/ob versus POKO ) . Additionally , POKO mice had significantly decreased islet number and size ( average area of islets POKO = 18 . 40 ± 2 mm2 ) compared to ob/ob mice ( ob/ob = 61 . 59 ± 8 mm2 ) . Insulin staining demonstrated that islets from POKO mice contained fewer insulin-positive cells than islets from ob/ob mice ( Figure 3A ) . The normal cellular organization of the islet , abundant β-cells ( insulin staining ) in the centre of the islet and a rim of α-cells at the periphery ( glucagon staining ) , was retained in the insulin resistant ob/ob mice but was disrupted in the islets of POKO mice ( Figure 3A ) . Islets from POKO mice had decreased number of insulin positive β-cells when compared to islets from ob/ob mice and a scattered pattern of α-cells , which are morphological changes associated with islet remodelling in the context of β-cell failure . Gene expression analysis of islets from 16-week-old mice revealed decreased expression of pancreatic duodenal homeobox-1 , insulin receptor substrate 2 , Glut2 , and insulin in islets from POKO mice when compared with those from WT or ob/ob ( Figure S4 ) . The changes seen in the β-cells of POKO mice were not the result of an inherent failure of the β-cell to develop properly as indicated by histological studies of neonatal pancreas ( day 3 to day 5 ) ( unpublished data ) and four-week-old pancreas ( Figure 2C ) , showing no morphological differences in the size , number , or insulin staining of islets from POKO mice when compared to ob/ob controls . We measured glucose-stimulated insulin secretion in 16-week-old female POKO mice and their ob/ob littermates . Islets isolated from POKO mice were 30% smaller than those from ob/ob mice . Moreover , whereas normal islets were pure white with a smooth surface , islets from POKO mice were gray; their surface was irregular and required less time for collagenase digestion ( only ten minutes instead of 30 minutes ) , suggesting that they were also more fragile . Insulin content in islets from ob/ob mice was more than 30-fold greater than in those from POKO mice ( Figure 3B ) . Insulin secretion from the islets of POKO mice was strikingly impaired compared to those of ob/ob mice , even when expressed relative to insulin content ( Figure 3C ) . This was observed under basal ( 1 mM glucose ) and stimulated ( 16 mM glucose , 16 mM glucose + tolbutamide ) release . As expected , the POKO mice had increased hepatic fat deposition compared to WT and PPARg2 KO mice ( Table S1 ) , but surprisingly the POKO mouse had much milder hepatosteatosis than the ob/ob mouse ( Figure 3D ) , suggesting that ectopic expression of the PPARg2 isoform in the liver of ob/ob mice ( see below ) , might contribute to the deposition of TAGs in the liver . To investigate lipotoxicity as a potential pathogenic mechanism we used liquid chromatography/mass spectrometry ( LC/MS ) [32] to compare a broad spectrum of cellular lipids in the adipose tissue , pancreatic islets , liver , and skeletal muscle between the POKO mouse and controls ( Protocol S1 ) . Given the lipotoxic profiles identified in the POKO mouse , we hypothesised changes in the expression of metabolic genes directly related to PPARg2 ablation and also compensatory changes in genes associated with cellular stress ( Table S4 ) .
The link between obesity , insulin resistance , and diabetes while epidemiologically very clear is still not properly understood at a mechanistic level . An emerging concept is that the absolute amount of fat stored may be less important than the remaining storage capacity of the adipose tissue . Here we show that the PPARg2 isoform may be an important factor controlling obesity-induced comorbidities through two mechanisms: ( a ) by regulating nutritionally induced adipose tissue expandability and ( b ) when de novo expressed in nonadipose tissues , by allowing the storage of energy in the form of relatively harmless TAG species . Previously we described the metabolic phenotype of the adult PPARg2 KO mouse [2] , characterised by mild insulin resistance observed only in males . Given the greater adipogenic potency of PPARg2 compared with PPARg1 in vitro , we expected PPARg2 KO mice to have many more severe defects in adipose tissue than we observed , and therefore insulin sensitivity . As PPARg2 is the PPARg isoform regulated in response to nutrition and obesity [17–20] , we hypothesised that PPARg2 would only become essential for adipose tissue function in the face of positive energy balance . The metabolic challenge we opted for was PPARg2 ablation in the obese ( ob/ob ) background ( PPARg2−/− Lepob/Lepob , POKO mouse ) . The POKO mouse had severely decreased body-fat mass due to impaired adipose tissue expandability . Despite eating as much as an ob/ob mouse and expending a similar amount of energy , the POKO mouse was unable to store fat efficiently in its adipose tissue . This mismatch between increased energy availability and lack of adipose tissue expandability lead to a global metabolic failure characterised by severe insulin resistance , β-cell failure , and dyslipidaemia . The observation of reduced fat mass and increased insulin resistance in the POKO mouse compared to the ob/ob mouse strongly supports two of our hypotheses . First , we hypothesised that PPARg2 is required to recruit new adipocytes in overnutrition , but it is not required to make adipocytes during development . This is reflected by similar expression of aP2 , a late marker of adipocyte differentiation , in POKO and ob/ob mice . The absence of small adipocytes was markedly different to other forms of lipodystrophy [38 , 39] . Additionally , and again in contrast with other lipodystrophic models that have markedly less adipose tissue than WT controls [38–40] , the POKO mice had a percentage body fat that was similar ( only 4% more ) to WT and PPARg2 KO mice , as opposed to ob/ob mice , which had 40% fat as a proportion of body mass . This suggests that the remaining PPARg1 isoform is sufficient to support development of adipose tissue and fat deposition requirements of a lean mouse model . However , under conditions of positive energy balance , adipose tissue expandability mainly relies on the PPARg2 isoform . This idea is also suggested by the studies in heterozygous mice harbouring the murine equivalent of the human mutation ( P465L ) in PPARg on an ob/ob background [41] . These mice were able to accumulate fat and become obese even though showing a body mass 14% lower than ob/ob controls . In humans there is also evidence for a role for PPARg2 . We have observed that metabolically healthy , nondiabetic , morbidly obese individuals have elevated levels of PPARg2 in their adipose tissue when compared to lean individuals [19] . Our second hypothesis , that the mismatch between energy availability and adipose tissue expandability is more important than fat mass itself as a predictor of insulin resistance , is also supported by our data . In fact the ob/ob mouse is much more obese than the POKO mouse but is much less insulin resistant . Furthermore , the POKO mice were already more insulin resistant than the ob/ob mice by the age of four weeks , with very low levels of GLUT4 in adipose tissue , before large differences in body weight developed , suggesting that the bioenergetic mismatch rather than the total amount of fat stored is important for the development of insulin resistance . Although we hypothesised that the POKO mice would become insulin resistant , the degree of hyperglycaemia in these animals was in excess of what we expected . We found that the normal adaptive response of β-cells to insulin resistance did not occur in the POKO mice as indicated by the pathological changes observed by histology and the lack of β-cell hypertrophy . Although it has been shown that genetic background can affect the ability of ob/ob mice to undergo β-cell hypertrophy [42 , 43] , we found that the ob/ob controls on our mixed 129Sv × C57BL/6J background underwent adaptive β-cell hyperplasia and hypertrophy , suggesting that the lack of PPARg2 was responsible for the failure of the POKO β-cells to adapt to insulin resistance . Interestingly the mass of pancreatic islets in POKO mice remained similar to the noninsulin resistant WT and PPARg2 KO mice . Furthermore , these defects in POKO β-cells did not appear to be the result of a developmental defect , as new born and four-week-old mice had morphologically normal islets . The severe β-cell phenotype of the POKO mouse contrasts with the absence of hyperglycaemia observed in the pancreatic β-cell specific PPARg KO mouse [30] . However it should be kept in mind that in the β-cell specific PPARg KO mouse , the expression of PPARg and the lipid storage capacity of other tissues , most importantly adipose tissue , were not affected , and that insulin sensitivity was only mildly affected by high fat feeding in these mice when compared to the severe insulin resistance observed in POKO mice . Therefore the challenge to the pancreatic β-cells in this model was milder than in POKO mice . This is a clear example of how tissue-specific genetic manipulations are not always the best approach to understand the physiology of an organ in the context of the global energy homeostasis . The potential importance of the de novo expression of PPARg2 isoform in β-cells is also supported by the observation that humans harbouring the Pro12Ala mutation in PPARg2 , a mutation that is located in the g2 isoform and makes PPARg2 less active , has only been associated with insulin deficiency and disease severity in obese individuals with type 2 diabetes [44] . The liver of the POKO mouse also displayed an unusual phenotype . We expected the POKO mice to have worse hepatosteatosis with increased triglyceride deposition in liver compared to ob/ob mice , because the POKO mice could not store fat in adipose tissue . However POKO mice had less hepatosteatosis than ob/ob mice suggesting that the PPARg2 isoform may directly contribute to facilitate triglyceride deposition in the liver . A common mechanistic link for the phenotypes observed in the POKO liver and β-cell was not immediately obvious . To try to determine the role of PPARg2 in these locations we performed lipidomic and gene expression analyses of the adipose tissue , pancreatic islet , liver , and skeletal muscle of the POKO mouse . The lipid pattern of adipose tissue from POKO mice was characterised by decreased TAGs and increased DAGs in parallel with decreased gene expression of DGAT2 , hormone-sensitive lipase , and adipose triglyceride lipase . This decrease in TAGs in the POKO adipose tissue was associated with increased levels of reactive lipid species and a gene expression profile suggestive of increased oxidative stress [45–49] . Although it has been described that oxidative stress and insulin resistance may be related to infiltration of adipose tissue by macrophages , resulting in a chronic state of inflammation [50–52] , we did not observe increased macrophage infiltration in the adipose tissue of POKO mice compared to that of ob/ob mice . Lipidomic analysis of POKO derived islets also showed decreased levels of triacyl and DAGs and increased levels of ceramides , suggesting that PPARg2 may contribute to increasing the lipid-buffering capacity of β-cells by promoting formation of TAGs and thus preventing lipotoxic insults . Liver and skeletal muscle lipidomics also showed reduced TAG and increased formation of reactive lipid species such as ceramides and lysophosphatidylcholines in POKO mice compared to ob/ob mice . This lipid profile was associated with impaired expression of pathways controlling de novo lipogenesis , transport of fatty acids , and beta oxidation in the POKO mice compared with the ob/ob mice . Of interest , Ppargc1a and other gluconeogenic genes were induced in the liver of POKO mice compared to that of ob/ob mice , suggesting a potential mechanism contributing to marked hyperglycaemia in POKO mice [53 , 54] . Overall , our lipidomic studies identify a remarkably similar pattern of changes in lipid species in the four tissues studied . The reduced adipose tissue mass and hepatosteatosis in the POKO mouse compared to the ob/ob mouse is explained by reduced levels of mature TAG in the POKO mouse . Similarly , ablation of PPARg2 resulted in accumulation of reactive lipid species implicated in causing insulin resistance , not only in adipose tissue , but also in other organs involved in whole-organism glucose metabolism . These results indicate that expression of PPARg2 in the pancreas , liver , and muscle of the ob/ob mouse may be performing a protective role , by increasing the capacity of these organs to buffer toxic lipid species by allowing accumulation of relatively harmless TAGs . The importance of this peripheral antilipotoxic role of PPARg2 becomes more evident if we consider that POKO and ob/ob mice are under the same degree of positive energy balance as determined by similar food intake , locomotor activity , and energy expenditure , that both models lack leptin , and that the only difference between ob/ob and POKO mice is the presence or absence of PPARg2 . Given the decreased adipose tissue expandability of the POKO mice compared to ob/ob , it was anticipated that , as in the liver , muscle , or β-cells of lipodistrophic mice , the POKO mouse would accumulate more fat than the ob/ob . However , our results clearly indicate that mice lacking PPARg2 , despite massive nutrient availability , are unable to deposit TAG in peripheral tissues and instead accumulate reactive lipid species in these organs . Therefore the pathologies of the liver and β-cell observed in the POKO mouse may be a result of a common lipotoxic insult facilitated by the absence of PPARg2 ( Figure 6 ) . In summary , in this study we provide new insights into the physiological relevance of the PPARg2 isoform and identify adipose tissue expandability as an important determinant of metabolic complications . Ablation of PPARg2 decreases adipose tissue expandability , but its pathophysiological effects only become relevant in the context of a mismatch between energy availability and adipose tissue expansion . We show that PPARg2 also plays protective role when expressed de novo in peripheral organs by increasing their capacity to buffer toxic lipids . Ablation of PPARg2 under conditions of positive energy balance determined by absence of leptin produced early development of severe insulin resistance , β-cell failure , diabetes , and hyperlipidaemia . Extrapolation of this model to humans may suggest that normal to overweight individuals with positive energy balance and inappropriately severe manifestations of the MS may have a defect in PPARg2 and/or alternative mechanisms that control adipose tissue expandability .
Mice heterozygous for a disruption in exon B1 of PPARg2 on a 129Sv background ( PPARg2+/− ) [2] were crossed with heterozygous ob/ob ( Lepob/Lep+ ) mice on a C57Bl/6 background to obtain mice heterozygous for both the PPARg2 ablation and the leptin point mutation ( PPARg2+/− Lepob/Lep+ ) . These mice were crossed to obtain the four experimental genotypes: WT ( PPARg2+/+ Lep+/Lep+ ) , PPARg2 KO ( PPARg2−/− Lep +/Lep+ ) , ob/ob ( PPARg2+/+ Lepob/Lepob ) , and POKO ( PPARg2−/− Lepob/Lepob ) . Genotyping for deletion of PPARg2 and the point mutation in the ob gene was performed by PCR using standard protocols [2 , 55] . Animals were housed at a density of four animals per cage in a temperature-controlled room ( 20–22 °C ) with 12-h light/dark cycles . Food and water were available ad libitum unless noted . All animal protocols used in this study were approved by the UK Home Office and the University of Cambridge . Mice of the four experimental genotypes were placed at weaning ( three weeks of age ) on a normal chow diet ( 10% of calories derived from fat; D12450B , Research Diets , http://www . researchdiets . com ) . Enzymatic assay kits were used for determination of plasma FFAs ( Roche , http://www . roche . com ) and TAGs ( Sigma-Aldrich , http://www . sigmaaldrich . com ) . Elisa kits were used for measurements of leptin ( R & D Systems , http://www . rndsystems . com ) , insulin ( DRG Diagnostics International Limited , http://www . drg-international . com ) , and adiponectin ( B-Bridge International , http://www . b-bridge . com ) according to manufacturers' instructions . Dual-energy X-ray absorptiometry ( DEXA , Lunar Corporation , http://www . lunarcorp . com ) was used to measure body composition; glucose in blood and in urine and food intake were monitored in the four experimental genotypes as previously shown [2] . Oxygen was measured using an eight-chamber open-circuit oxygen-monitoring system attached to and sampled from the chambers of a Comprehensive Laboratory Animal Monitoring System ( CLAMS; Columbus Instruments , http://www . colinst . com ) . Water consumed was also measured using CLAMS . Mice were housed individually in specially built Plexiglass cages maintained at 22 °C under an alternating 12:12-h light-dark cycle ( light period 08:00–20:00 ) . Sample air was sequentially passed through oxygen ( O2 ) and carbon dioxide ( CO2 ) sensors ( Columbus Instruments ) for determination of O2 and CO2 content . Mice were acclimatized to monitoring cages for 72 h before data collection . Mice were weighed before each trial . Ambulatory activity of individually housed mice was evaluated using an eight-cage rack OPTO-M3 Sensor system ( Columbus Instruments ) . Cumulative ambulatory activity counts were recorded every 5 min throughout the light and dark cycles . Energy lost in urine was calculated accordingly as previously shown before [56] using the following calculations: Energy lost in urine kJ/day = ( glucose in urine [mMol/l]/1 , 000 ) × molecular weight glucose × ( water intake [ml/day]/1 , 000 ) × E densitycarb; E densitycarb = energy density related to oxidations within the body for carbohydrates as glucose = 15 . 76 kJ/g . Total RNA was isolated from islets and tissues samples according to the manufacturer's instructions ( RNAeasy kit , Qiagen , http://www . qiagen . com ) and STAT60 ( Tel-Test , http://www . isotexdiagnostics . com/tel-test . html ) . Real-time quantitative PCR was performed using a TaqMan 7900 ( Applied Biosystems , http://www . appliedbiosystems . com ) according to standard protocols . The tissue samples ( 40 μg ) were subjected to SDS-PAGE on 8% polyacrylamide gels . Proteins were then electrophoretically transferred to polyvinylidene difluoride filters . After transferring , the filters were blocked with 5% nonfat dry milk in TBS-Tween 20 followed by incubation with primary GLUT4 and extracellular signal-regulated kinase 1/2 ( ERK1/2 ) antibodies ( Promega , http://www . promega . com ) overnight . The bands were quantified by scanning densitometry . Tissue samples for morphological and immunohistochemcal analysis were prepared according to published protocols [2] . Morphometric analyses of adipose tissue and pancreas sections were acquired using a digital camera and microscope ( Olympus BX41 , http://www . olympus . com ) , and cell areas were measured using AnalySIS software ( Soft Imaging System , http://www . soft-imaging . net ) . For adipose tissue , two fields from each section were analysed to obtain the mean cell-area per animal ( n = 5 per genotype ) . The Computer Assisted Stereology Toolbox ( CAST ) 2 . 0 system from Olympus was used to perform all measurements in the pancreas according to published protocols [57] . The pancreas was injected via the bile duct with cold Hank's solution containing 0 . 4% ( w/v ) liberase ( Roche ) . The pancreas was removed , digested for 15–30 min , and islets collected by handpicking . Isolated islets were cultured overnight in h-cell medium ( SBMI 06 , hcell technology , http://www . hcell . com ) at 37 °C in 5% CO2 in air . Islets were used the day after isolation for insulin secretion studies or RNA extraction . Insulin secretion from isolated islets ( five islets/well ) was measured during 1-hr static incubations in Krebs—Ringer Buffer containing either 1 mM glucose , 16 . 7 mM glucose , or 16 . 7 mM glucose plus 200 μM tolbutamide in DMSO . The supernatants were assayed for insulin . Insulin content was extracted using 95:5 ethanol/acetic acid . Insulin was measured using a Mouse Insulin ELISA kit ( Mercodia , http://www . mercodia . com ) . Islets were isolated from three mice of each genotype for these experiments . Thus , the data are the mean of three separate experiments , in which data were collected for each test solution from six samples each of five islets . For each sample , insulin release was normalised to insulin content . ITTs on four-week-old mice were performed as previously published [58] . For WAT and muscle , the tissue sample ( 50 mg ) was homogenized with 0 . 15 M sodium chloride ( 300 μl ) , and the lipids were extracted with 2 ml of chloroform: methanol ( 2:1 ) and used for LC/MS as previously described [2] . For liver and islets , an aliquot ( 20 μl for liver or 10 μl for islets ) of an internal standard mixture ( 11 reference compounds at concentration level 8–10 μg/ml ) , 50 μl of 0 . 15 M sodium chloride ( for liver ) , and chloroform:methanol ( 2:1 ) ( 200 μl for liver or 90 μl for islets ) was added to the tissue sample ( 20–30 mg ) . The sample was homogenized , vortexed ( 2 min for liver or 15 s for islets ) , let to stand ( 1 h for liver , 20 min for islets ) , and centrifuged at 10 , 000 RPM for 3 min . From the separated lower phase , an aliquot was mixed with 10 μl of a labelled standard mixture ( three stable isotope-labelled reference compounds at concentration level 9–11 μg/ml ) , and 0 . 5–1 . 0 μl injection was used for LC/MS analysis . Total lipid extracts were analysed on a Waters Q-Tof Premier mass spectrometer ( http://www . waters . com ) combined with an Acquity Ultra Performance LC ( UPLC ) . The column , which was kept at 50 °C , was an Acquity UPLC BEH C18 10 × 50 mm with 1 . 7 μm particles . The binary solvent system ( flow rate 0 . 200 ml/min ) included A , water ( 1% 1 M NH4Ac , 0 . 1% HCOOH ) , and B , LC/MS grade ( Rathburn , http://www . rathburn . co . uk ) acetonitrile/isopropanol ( 5:2 , 1% 1 M NH4Ac , 0 . 1% HCOOH ) . The gradient started from 65% A/35% B , reached 100% B in 6 min , and remained there for the next 7 min . The total run time per sample , including a 5 min re-equilibration step , was 18 min . The temperature of the sample organizer was set at 10 °C . Mass spectrometry was carried out on Q-Tof Premier ( Waters ) run in ESI+ mode . The data were collected over the mass range of m/z 300–1 , 200 with scan duration of 0 . 2 s . The source temperature was set at 120 °C , and nitrogen was used as desolvation gas ( 800 l/h ) at 250 °C . The voltages of the sampling cone and capillary were 39 V and 3 . 2 kV , respectively . Reserpine ( 50 μg/l ) was used as the lock spray reference compound ( 5 μl/min; 10 s-scan frequency ) . Data processing was performed using the MZmine software [59] . Identification was performed based on an internal reference database of lipid species , or alternatively utilizing the tandem mass spectrometry . The statistical analyses were performed using Matlab ( Mathworks , http://www . mathworks . com ) and the Matlab library PLS Toolbox ( Eigenvector Research , http://www . eigenvector . com ) . Tandem mass spectrometry was used for the identification of selected lipid species . MS/MS runs were performed by using ESI+ mode , collision energy ramp from 15–30 V , and mass range starting from m/z 150 . The other conditions were as shown in the Protocol S1 . Results were expressed as mean ± standard error of mean . Statistical analysis was performed using a two-tailed unpaired t-test between appropriate pairs of groups , and significance declared if p-values were less than 0 . 05 . | It is known that obesity is linked to type 2 diabetes , however how obesity causes insulin resistance and diabetes is not well understood . Some extremely obese people are not diabetic , while other less obese people develop severe insulin resistance and diabetes . We believe diabetes occurs when adipose tissue becomes “full , ” and fat overflows into other organs such as liver , pancreas , and muscle , causing insulin resistance and diabetes . Peroxisome proliferator activated receptor gamma ( PPARg ) is essential for the development of adipose tissue and control of insulin sensitivity . PPARg2 is the isoform of PPARg regulated by nutrition . Here we investigate the role of PPARg2 under conditions of excess nutrients by removing the PPARg2 isoform in genetically obese mice , the POKO mouse . We report that removing PPARg2 decreases adipose tissue's capacity to expand and prevents the mouse from making as much fat as a normal obese mouse , despite eating similarly . Our studies suggest that PPARg plays an important antitoxic role when it is induced in liver , muscle , and beta cells by facilitating deposition of fat as relatively harmless lipids and thus prevents accumulation of toxic lipid species . We also show that PPARg2 may be involved in the adaptive response of beta cells to insulin resistance . | [
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] | 2007 | PPAR gamma 2 Prevents Lipotoxicity by Controlling Adipose Tissue Expandability and Peripheral Lipid Metabolism |
Genes that have experienced accelerated evolutionary rates on the human lineage during recent evolution are candidates for involvement in human-specific adaptations . To determine the forces that cause increased evolutionary rates in certain genes , we analyzed alignments of 10 , 238 human genes to their orthologues in chimpanzee and macaque . Using a likelihood ratio test , we identified protein-coding sequences with an accelerated rate of base substitutions along the human lineage . Exons evolving at a fast rate in humans have a significant tendency to contain clusters of AT-to-GC ( weak-to-strong ) biased substitutions . This pattern is also observed in noncoding sequence flanking rapidly evolving exons . Accelerated exons occur in regions with elevated male recombination rates and exhibit an excess of nonsynonymous substitutions relative to the genomic average . We next analyzed genes with significantly elevated ratios of nonsynonymous to synonymous rates of base substitution ( dN/dS ) along the human lineage , and those with an excess of amino acid replacement substitutions relative to human polymorphism . These genes also show evidence of clusters of weak-to-strong biased substitutions . These findings indicate that a recombination-associated process , such as biased gene conversion ( BGC ) , is driving fixation of GC alleles in the human genome . This process can lead to accelerated evolution in coding sequences and excess amino acid replacement substitutions , thereby generating significant results for tests of positive selection .
Whole-genome comparisons have revealed hundreds of noncoding elements that are extremely conserved across mammals but show evidence for accelerated evolution along the human lineage [1–4] . One possible explanation for these human-accelerated regions ( HARs ) is the action of positive selection in the human lineage . However , HARs tend to have biased patterns of nucleotide substitution , dominated by AT → GC changes—referred to here as “weak-to-strong” ( W→S ) as they result in a replacement of a “weak” A:T bond with a “strong” G:C bond . This pattern is strongly discordant with the genomic average , where S→W substitutions predominate . Positive selection is not expected to generate such biased patterns of base substitution . Interestingly , HARs also have a propensity to occur in regions with high recombination rates . These biased substitution patterns could potentially be explained by variation in the pattern of mutation , localized selection for increased GC content , or by biased gene conversion ( BGC ) , which is a recombination-associated molecular drive that favors fixation of W→S mutations [5 , 6] and has population dynamics similar to natural selection [7] . There is now strong evidence for an association between recombination and patterns of nucleotide substitutions in the human genome , suggesting that an excess of W→S base substitutions occur in regions of high recombination [8] . The evidence can be summarized as follows: first , patterns of substitution in human–primate genomic alignments correlate with human recombination rates [8–10] . Second , parts of mammalian and avian genomes subject to very high recombination rates , such as duplicated gene families [11–13] and the X-linked pseudoautosomal region [14] , are both extremely GC-rich and have GC-biased substitution patterns . Third , GC content correlates with recombination in a wide range of eukaryotes [15–17] . Fourth , experiments on primate cell lines and yeast indicate a bias in repair mechanisms , which leads to mismatches being preferentially repaired to GC bases [15 , 18 , 19] . Fifth , GC-biased clustered substitutions have been observed close to human recombination hotspots and near telomeres [20] , and these regions also tend to be more GC-rich [21] . Several studies have also reported a correlation between sequence divergence and recombination rate [22–24] . It is therefore possible that recombination could directly influence patterns of substitution , although it is unknown whether mutations generated by recombination are W→S biased . The fact that the proportion of W→S mutations leading to human single-nucleotide polymorphisms ( SNPs ) is discordant with the proportion leading to nucleotide substitutions on the human lineage [25] strongly suggests a bias in fixation rather than mutation processes . Further support comes from observations that W→S and S→W changes segregate at different frequencies on average in human populations , particularly in regions with elevated recombination rates [6 , 25 , 26] ( but see [27] ) . The distribution of recombination events is highly variable along vertebrate chromosomes . Recombination is mainly restricted to short ( <1 kb ) hotspots [28] , which are extremely short-lived over evolutionary time [29] . Clusters of W→S biased substitutions have been observed on a similar scale , and it is proposed that these are the result of biased fixation of GC alleles in recombination hotspots [20] . Recombination hotspots therefore could be responsible for localized lineage-specific bursts of W→S biased substitutions , which could contribute to human-accelerated evolution in conserved noncoding elements . Biased substitution patterns could also potentially result from selection on GC content . Mammalian genomes exhibit variation in GC content on the scale of hundreds of kilobases , commonly referred to as the isochore structure [30 , 31] . A potential explanation for this variation is that some regions experience selection in favor of increased GC content due to increased thermal stability [30] . In addition to this , experimental evidence indicates that GC-rich genes may be expressed with greater efficiency than GC-poor genes [32] , which could lead to selection in favor of increased GC content in expressed sequences . Selection is more efficient on regions of high recombination due to a reduction in Hill-Robertson interference [33] , which could lead to increased fixation of W→S mutations in these regions due to selection . Some protein coding sequences also show patterns of evolution that are consistent with high levels of recombination-associated fixation of W→S mutations . For example , the Fxy gene is found on the X-specific portion of the X chromosome in human , rat , and short-tailed mouse ( Mus spretus ) . However , in the house mouse ( M . musculus ) , this gene has been translocated so that only its 5′ portion now resides in the X-specific region , whereas its 3′ portion overlaps the pseudoautosomal region ( PAR ) , which is subject to very high levels of recombination [14] . This translocation resulted in a massive increase in substitution rate in the PAR portion of the gene , including substitutions that cause amino acid replacements . Since the common ancestor of M . spretus and M . musculus , the M . spretus lineage has accumulated one replacement substitution in the 3′ portion and one replacement substitution in the 5′ portion . In contrast , the M . musculus lineage has accumulated no substitutions in the 5′ portion , but 28 replacement substitutions in the PAR-overlapping 3′ portion [5] . Furthermore , all 28 substitutions are W→S . Substitution patterns in the HARs and the Fxy gene may indicate that recombination-associated biased fixation of W→S mutations can compete with purifying selection , leading to the accumulation of weakly deleterious variants [5] . It is possible that this effect could affect common tests for positive selection in coding sequences , although the predicted impact of W→S fixation bias on these tests has not been demonstrated . For example , a gene under the influence of W→S fixation bias on a particular lineage could potentially acquire an increased ratio of nonsynonymous to synonymous rates of base substitution ( dN/dS ) . This could lead to a significant acceleration in dN/dS , which is commonly assumed to indicate positive selection [34] . Similarly , fixation of weakly deleterious variants could potentially lead to an excess of amino acid replacement substitutions compared with polymorphism . This could generate significant results for the McDonald-Kreitman [35] test of neutrality , which could also lead to false inference of positive selection on protein sequence . We examined the possibility that biased fixation of W→S mutations could affect the evolution of human protein-coding regions across the genome by analyzing patterns of evolution in a genome-wide set of human-chimpanzee-macaque 1:1:1 orthologous genes [36] . We first identified individual protein-coding exons with evidence for accelerated rates of nucleotide substitution in the human lineage using a likelihood ratio test ( LRT ) . We then characterized patterns of nucleotide substitution in these loci . We also tested whether fast-evolving genes are associated with recombination hotspots or regions of elevated recombination . Our findings are consistent with the hypothesis that a recombination-associated process has generated an increased rate of nucleotide substitutions on the human lineage within particular genes since the split with chimpanzee . Interestingly , these genes also have increased numbers of amino acid replacement substitutions . This observation motivated us to theoretically and empirically examine the relationship between W→S fixation bias and rates of nonsynonymous base substitution . Our results suggest that W→S fixation bias can generate significant results for tests designed to detect directional selection , including LRTs for accelerated dN/dS [34] and McDonald-Kreitman tests [35] , potentially leading to false inference of positive selection .
In total , 83 exons ( in 82 genes ) show evidence for acceleration in the human lineage with an expected false discovery rate ( FDR ) less than 5% . Henceforth , we refer to these 83 human-accelerated coding sequences as “accelerated exons . ” The mean length of the accelerated exons is 516 . 6 bp , which is higher than the mean length of exons in the entire dataset ( 167 . 6 bp ) . On average , the accelerated exons contain 7 . 73 substitutions on the human lineage , compared to a mean of 0 . 43 substitutions in the entire dataset . This suggests that the majority of exons are too short for an acceleration in evolutionary rate to be detectable by this method , given the evolutionary distance between human and chimpanzee . Genes containing the accelerated exons have a mean of 13 . 3 human substitutions , compared with an average of 3 . 58 in all genes . Furthermore , there is a tendency for substitutions in these genes to be clustered: 11 . 0% of genes containing accelerated exons have a significantly nonuniform clustering of substitutions into the most diverged exon ( p < 0 . 05 ) , compared to less than 1 . 1% of all genes ( see Methods ) . We estimated the pattern of substitution on the human and chimpanzee lineages by comparing the extant sequences with the maximum likelihood ( ML ) reconstructed ancestor using a codon model of substitution where the dN/dS on the human branch was able to vary from the rest of the tree . The 83 accelerated exons demonstrate a bias for weak to strong ( W→S ) substitutions , with 326 W→S and 248 S→W base substitutions ( W→S bias = 0 . 57; see Methods ) . This substitution pattern is significantly incongruent with the genome as a whole , where W→S bias = 0 . 39 ( Fisher's exact test ( FET ) p < 2 . 2 × 10−16; bootstrap p < 0 . 001 ) . This bias strongly affects the most accelerated exons and drops to close to the genomic average for exons with less evidence of acceleration ( Figure 1A ) . Strikingly , the top 20 accelerated exons ( Table 1 ) have 154 W→S compared to only 62 S→W substitutions ( W→S bias = 0 . 71 , FET p < 2 . 2 × 10−16; bootstrap p < 0 . 001 ) . The positions of each nucleotide substitution on the human lineage in the genes containing the top 20 accelerated exons are shown in Figure 2 . The excess of W→S substitutions can be clearly seen , and there is an obvious tendency for clusters of W→S substitutions to occur in single exons in particular genes . We used the ML reconstructed human-chimpanzee ancestral sequences to infer the ancestral GC content of each exon . The accelerated exons have an average ancestral GC content of 0 . 53 , whereas the top 20 accelerated exons have an average GC content of 0 . 54 . In comparison , average ancestral GC content in all of the coding sequences in the dataset is 0 . 50 . The elevated GC content of accelerated exons is observed at all three codon positions ( unpublished data ) . Differences in GC content therefore cannot explain the differences in base substitution patterns between accelerated and nonaccelerated genes . If base substitution probabilities were constant across genomic regions , genes with higher GC content would be expected to have lower W→S substitution rates , when the opposite is actually observed . Our test for differences in the substitution patterns is therefore conservative . The most accelerated exons also have a bias toward a greater number of nonsynonymous substitutions compared with the genomic average . The proportion of nonsynonymous substitutions in the top 20 accelerated exons is 0 . 60 ( 146 nonsynonymous versus 96 synonymous ) , which is significantly higher than the proportion of 0 . 38 observed in the entire dataset ( FET p < 3 . 0 × 10−11; bootstrap p < 0 . 001 ) . This bias is most extreme for the most accelerated exons ( Figure 1B ) . Nonsynonymous substitutions also have a tendency to exhibit a stronger W→S bias , particularly in the accelerated exons . The W→S bias of accelerated exons is 0 . 63 for nonsynonymous sites and 0 . 51 for synonymous sites ( FET p = 0 . 004 ) . In the top 20 accelerated exons , W→S bias is 0 . 75 for nonsynonymous sites and 0 . 66 for synonymous sites ( FET p = 0 . 129 ) . In the entire dataset , W→S bias is 0 . 41 for nonsynonymous sites and 0 . 37 for synonymous sites ( FET p = 2 × 10−9 ) . To determine whether the W→S substitution bias is confined to protein-coding regions , we analyzed the pattern of base substitution in noncoding regions within 100 bp flanking both sides of each accelerated exon . Around the top 20 accelerated exons , there are 60 W→S but only 11 S→W base substitutions ( W→S bias = 0 . 85 ) . This is significantly different from the flanking regions surrounding all exons in the dataset ( W→S bias = 0 . 46; FET p < 3 . 2 × 10−11; bootstrap p < 0 . 001 ) . The W→S bias in flanking sequences is strongest for the most accelerated exons ( Figure 1C ) . Average ancestral GC content in the regions flanking the top 20 accelerated exons is 0 . 48 , which is higher than the average of 0 . 44 in the entire dataset . This suggests that differences in GC content could not be responsible for the differences in patterns of base substitution . We analyzed patterns of substitution in progressively larger windows of noncoding sequence surrounding each exon to determine the scale at which the W→S bias in substitution patterns exists ( Figure 3 ) . We found that there is a marked decrease in W→S bias with increasing distance from the accelerated exon . The W→S bias in 10 kb of noncoding sequence on both sides of the 20 most accelerated exons approaches the genomic average . These results suggest that the process generating the W→S bias in substitution patterns in accelerated exons acts on a regional level , rather than specifically on coding sequences . Furthermore , strongly W→S biased substitution patterns seem to be restricted to a scale of less than a few kilobases . We investigated the recombination rates of the regions where accelerated exons reside . We find that the most accelerated exons tend to be found in regions with elevated male recombination rates . In the top 20 accelerated exons , the average male recombination rate is 2 . 65 , which is significantly higher than the average of all exons in the dataset ( 0 . 92; bootstrap p < 0 . 001 ) . By contrast , female recombination rate in the top 20 accelerated exons is 1 . 62 , which is not significantly higher than the genomic average of 1 . 69 ( bootstrap p = 0 . 45 ) . Male recombination rate is therefore highly elevated in the most accelerated exons , whereas female recombination rate remains relatively constant ( Figure 4A ) . Accelerated exons show a slight tendency to occur near human recombination hotspots ( Figure 4B ) . In the top 20 accelerated exons , average distance to a hotspot is 50 . 0 kb , compared to 54 . 8 kb in the entire dataset , although this difference is not significant ( bootstrap p = 0 . 16 ) . There is a highly significant tendency for accelerated exons to be found close to telomeres , where recombination rates are elevated in males [17] . Seven out of the top 20 accelerated exons are found in the last chromosome band . This proportion ( 0 . 35 ) is significantly higher than 0 . 075 observed in the entire dataset ( bootstrap p < 0 . 001 ) . We identified genes where one exon had greater divergence on the human lineage than the rest of the coding sequence , termed “relative divergence” ( see Methods ) . Relative divergence was not calculated for exons with less than four substitutions to avoid bias from very short sequences . The 20 genes showing the highest relative divergence have most diverged exons with a significant excess of W→S substitutions compared with the entire dataset ( FET p = 0 . 00013; Table 2 ) . The spatial distribution of substitutions in the genes containing the top 20 most relatively diverged exons is presented in Figure S1 . This pattern is also observed in the flanking regions of highly relatively diverged exons compared with the entire dataset ( FET p = 2 . 3 × 10−9 ) . Thus , when genes contain clusters of nucleotide substitutions in single exons , these substitutions tend to exhibit a W→S biased pattern . The observation that the patterns extend into flanking introns and intergenic sequence suggests that these patterns do not result from selection on protein coding sequence and that a regional bias in mutation or fixation of mutations is a more likely explanation . To distinguish between biases in patterns of mutation and fixation , we compared W→S bias in nucleotide substitutions with human SNPs from the HapMap project . Patterns of substitutions in accelerated exons are significantly more W→S biased than human SNPs ( Table 3 ) . These differences are highly significant for the top 20 accelerated exons ( FET p = 0 . 0015 ) and for all 83 accelerated exons ( FET p = 0 . 00063 ) . These results suggest that either the W→S bias substitution patterns in these exons result from a mutation bias that is no longer active in the human population , or that the patterns result from a bias towards fixation of W→S mutations . We performed an additional LRT to identify individual exons with significantly elevated dN/dS ratios on the human lineage . On average , we inferred 0 . 17 nonsynonymous and 0 . 26 synonymous substitutions per exon since the human-chimpanzee split , which suggests that estimates of dN/dS are unreliable for most exons . We therefore restricted our analysis to exons with more than four substitutions inferred on the human lineage . Only 887 exons out of the entire dataset ( n = 84 , 784 ) passed this criterion ( 1 . 0% ) . As shown in Table 4 , exons with evidence for accelerated dN/dS in humans tend to have more W→S biased patterns of nucleotide substitution . At the p < 0 . 01 ( ** ) level , this is significant by FET ( p = 0 . 015 ) but not bootstrap ( p = 0 . 104 ) . At the p < 0 . 05 ( * ) level , neither of the tests are significant ( FET p = 0 . 104; bootstrap p = 0 . 130 ) . Exons with accelerated dN/dS on the human lineage therefore appear to be associated with W→S biased patterns of nucleotide substitution , although in the majority of exons , not enough substitutions have occurred to perform this test . The 83 accelerated exons have a significantly higher number of substitutions than average on the chimpanzee lineage . There is a base substitution in 0 . 0043 of sites on the chimpanzee lineage in the top 20 accelerated exons , compared to 0 . 0011 in all exons on the chimpanzee lineage ( FET p < 2 . 2 × 10−16; bootstrap p = 0 . 001 ) . This is an interesting observation , given that the LRT is designed to identify acceleration specifically on the human branch . Accelerated exons show similar , although less pronounced , patterns of W→S biased substitutions in the chimpanzee lineage . The top 20 accelerated exons are inferred to have a W→S bias of 0 . 50 , compared with 0 . 39 averaged across all exons . However , these values are not significantly different by FET ( p = 0 . 053 ) or bootstrap ( p = 0 . 31 ) . The top 20 accelerated exons also have a greater-than-average proportion of nonsynonymous substitutions in the chimpanzee lineage , with 54 nonsynonymous and 30 synonymous substitutions , a bias of 0 . 64 toward nonsynonymous substitutions , compared with 0 . 42 in the entire dataset ( FET p < 5 . 35 × 10−5; bootstrap p = 0 . 002 ) . There is also a similar W→S bias in the noncoding regions flanking accelerated exons in the chimpanzee genome , with 18 W→S and 11 S→W substitutions ( W→S bias = 0 . 62 ) compared with a W→S bias of 0 . 46 in all of the flanking sequences ( FET p = 0 . 093; bootstrap p = 0 . 146 ) . These results are consistent with previous studies suggesting that regional patterns of base substitution are correlated between human and chimpanzee [10 , 20 , 38] . We next examined the relationship between rates of protein evolution and W→S substitution bias on the whole-gene level . We identified genes with significant evidence for accelerated nonsynonymous substitution rates on the human lineage using branch models of codon substitution and a LRT . We refer to these as “genes with accelerated dN/dS” . Based on significance of rejection of a model with single dN/dS ratio ( codeml model 0 ) by a model where the human lineage had a separate dN/dS ( codeml model 2; see Methods ) , we defined three different levels of significance: p < 0 . 001 ( ***; 20 genes ) , p < 0 . 01 ( **; 112 genes ) and p < 0 . 05 ( *; 485 genes ) . Table 5 shows the pattern of nucleotide substitution in genes at each level of significance . The distribution of these substitutions in the top 20 genes is presented in Figure S2 . LRT statistics for all genes in our dataset are presented in Table S2 . Comparison of the substitution patterns in genes with accelerated dN/dS to the entire dataset reveals a trend towards W→S biased substitution patterns , although this is not significant . However , when we restrict the analysis to the exon in each gene with the largest number of human substitutions per base , the substitution pattern in dN/dS category *** exhibits a much higher W→S bias ( 0 . 68 ) than the average W→S bias for most diverged exons ( 0 . 39 ) in the entire dataset . This difference is highly statistically significant ( FET p = 7 . 1 × 10−6; bootstrap p = 0 . 0065 ) . The W→S bias in the most diverged exons of genes in dN/dS category ** is less extreme ( 0 . 47 ) , but still significantly different from the entire dataset ( FET p = 0 . 012; bootstrap p = 0 . 044 ) . In dN/dS category * , the average W→S bias is lower ( 0 . 41 ) , and not significantly different from the entire dataset . In addition to being the region with the most W→S biased substitution pattern , the most diverged exon in each gene also tends to have a larger proportion of nonsynonymous substitutions ( Table 5 ) . We noticed that the gene KIF26B , kinesin family member 26B , contributes disproportionately to the number of substitutions in the genes in dN/dS category *** . KIF26B is located in the last band of the q arm of human chromosome 1 . Its most diverged exon ( exon 1 ) contains 17 substitutions , which are all W→S . The most diverged exons in the remaining 19 genes in dN/dS category *** contain an average of just 2 . 6 substitutions . These exons have an average W→S bias of 0 . 55 , compared with 0 . 68 when KIF26B is included , whereas the W→S bias among the most diverged exons is 0 . 39 . The W→S bias in these 19 exons ( with KIF26B excluded ) is still significantly higher than average ( FET p = 0 . 035; bootstrap p = 0 . 019 ) . However , the evolution of KIF26B is particularly striking . It is the only gene that both contains one of the top 20 accelerated exons and has highly significant acceleration in dN/dS ( *** ) . It also has a strongly W→S biased substitution pattern . We examined patterns of base substitution in 100 bp of noncoding sequence flanking each side of all exons in the genes with accelerated dN/dS ( Table 6 ) . There is no evidence that noncoding sequence nearby genes with accelerated dN/dS at any of the levels of significance have W→S biased substitution patterns compared with genomic averages . This is the case when we analyze all the exons in genes with accelerated dN/dS and when we analyze only the most diverged exon in each of these genes ( tested by FET and bootstrap , unpublished data ) . We examined whether genes with accelerated dN/dS tend to be associated with regions of elevated recombination using a bootstrap test ( Table 7 ) . There is no significant tendency for accelerated genes at any of the p-value cutoffs to occur close to telomeres , or in regions of elevated male , female , or sex-averaged recombination . However , there is a highly significant ( p < 10−4 ) tendency for genes in dN/dS significance category *** ( p < 0 . 001 ) to be closer to recombination hotspots . This tendency is also significant for genes in dN/dS category ** ( p = 0 . 032 ) but not for those in dN/dS category * . We examined patterns of nucleotide substitution in genes with evidence for an excess of amino acid replacement substitutions on the human lineage compared to human polymorphisms . These genes were identified using a modified version of the McDonald-Kreitman ( MK ) test [35] presented by Bustamante et al . [39] . A total of 3 , 878 genes in this dataset overlapped with the human-chimpanzee-macaque orthologues . Out of these , 20 show evidence for an excess of replacement amino substitutions at the p < 0 . 01 ( ** ) level and 124 are significant at the p < 0 . 05 ( * ) level ( Table 8 ) . The proportion of W→S nucleotide substitutions is clearly elevated in these genes , and this is most pronounced in the most diverged exon of each gene . For the genes with the strongest excess of amino-acid substitutions ( ** ) , this increase is not significant for substitutions across the entire gene ( FET p = 0 . 055; bootstrap p = 0 . 11 ) , but is highly significant for substitutions in the most diverged exon ( FET p = 0 . 0012; bootstrap p = 0 . 008 ) . For all genes with evidence for an excess of amino-acid substitutions ( * ) , the W→S bias is significant for substitutions across the entire gene ( FET p = 0 . 025; bootstrap p = 0 . 0446 ) , but not for substitutions in the most diverged exon ( FET p = 0 . 055; bootstrap p = 0 . 07 ) . MK tests based on HapMap SNP data ( http://www . hapmap . org/ ) for all genes in our dataset show similar patterns ( unpublished data ) but are subject to ascertainment bias and do not accurately reflect the true underlying SNP density . In summary , there is a clear association between excess amino acid replacement substitutions and W→S biased substitution patterns . Table 9 shows the recombination rates of genes identified by the MK test . The genes with the strongest excess of nonsynonymous substitutions ( ** ) are situated significantly closer to recombination hotspots ( bootstrap p = 0 . 026 ) than the rest of the genes . For all significant genes , the mean distance to a hotspot is higher than average , although this is not significant ( p = 0 . 765 ) . There are no significant differences between the average or sex-specific recombination rates in genes with significant MK test values . Figure 5 indicates the overlap between the main sets of fast-evolving genes we have identified . Fourteen genes with accelerated dN/dS on the human lineage at the p < 0 . 05 level also contain accelerated exons . This is significantly higher than the 3 . 9 genes expected purely by chance ( binomial test p = 3 . 0 × 10−5 ) , although it is not surprising that genes with evidence for acceleration in the relative rate of nonsynonymous substitutions also show evidence for acceleration in evolutionary rates overall . Eleven of the genes with accelerated dN/dS also show evidence for an excess of amino acid substitutions using the MK test [39] at the p < 0 . 05 level , which is larger than the 5 . 9 expected , but not significant ( p = 0 . 051 ) . Five of the genes with significant MK tests also contain accelerated exons , which is larger than the 2 . 0 expected , but not significant ( p = 0 . 054 ) . The three different tests therefore have a tendency to identify some of the same genes , but in general they appear to target genes with different evolutionary histories . Out of the 82 genes containing accelerated exons , the gene ontology ( GO ) category “myosin complex” is enriched ( p = 0 . 0011 ) due to the presence of five myosin complex protein coding genes ( MYOM1 , MYO18B , MYO3B , MYH10 , and MYH3 ) . The genes containing the top 20 accelerated exons contain three olfactory receptors ( OR3A3 , OR3A2 , and OR4K17 ) , which generates a significant enrichment for “neurological system process” ( p = 0 . 039 ) . The GO category “multicellular organismal process” is strongly enriched in all of the genes containing accelerated exons ( p = 5 . 09 × 10−5 ) , as well as those containing the top 20 accelerated exons ( p = 0 . 039 ) . We tested the genes with accelerated dN/dS for enrichment of particular GO categories . There is no evidence for enrichment for any GO category at the p < 0 . 1 level for any of the accelerated dN/dS significance levels . We also tested for enrichment of GO categories within genes with significant MK tests at the p < 0 . 05 level ( 190 genes ) . There was a significant enrichment for “calcium ion binding” among genes with evidence of recent positive selection ( 21 genes , p = 0 . 027 ) . Another cause of apparent W→S substitutions could be misinference of ancestral bases . This is particularly problematic at CpG sites , where multiple CpG mutations on different lineages ( always S→W ) could give a false inference of the reverse ( W→S ) substitution due to homoplasy . In order to quantify this , we performed BLAST searches against three additional closely related primate genomes ( gorilla , orangutan , and baboon ) for the genes containing the top 20 accelerated exons , and the genes with strongest evidence ( p < 0 . 001 , *** ) for accelerated dN/dS . All of the bases in both of these datasets were alignable to at least one of the three primates . We were able to align 95% of bases to at least two of the species and 84% of bases to all three species . We compared the human-chimpanzee ancestral bases , inferred from the human-chimpanzee-macaque alignments by ML , to the orthologous bases in the additional primate genomes . We did not identify a single case where the ML inferred ancestral base of a human-specific substitution was incongruent with the orthologous base in the most closely related primate species . This indicates the effect of ancestral misinference is negligible in the human-accelerated sequences . Our empirical results suggest that genes with elevated rates of nucleotide substitution have been affected by a fixation bias in favor of W→S mutations . Such a bias could be caused by BGC or directional selection on GC content . We also observe W→S biased substitution patterns in genes with ( a ) accelerated dN/dS ratios on the human lineage , and ( b ) elevated numbers of nonsynonymous changes in substitution versus polymorphism data in MK tables . This suggests that a W→S fixation bias could potentially generate an increased rate of nonsynonymous compared with synonymous substitutions . To investigate this issue , we used a theoretical model of the interaction between a W→S fixation bias and purifying selection in an ideal Wright-Fisher population with parameter values determined empirically from the exon dataset . We assume that a W→S fixation bias can be modeled using a selection coefficient , as demonstrated by Nagylaki [7] . We estimated the pattern of mutation in genes with different ancestral GC contents by analyzing substitutions in 4-fold degenerate ( 4d ) sites . We used these to estimate the relative number of mutations expected in each mutational class , given the ancestral sequences . We then calculated the probability of fixation of each mutation , based on the selective coefficient and effective population size ( Ne; assumed to be 10 , 000 ) . The selective coefficients were determined by combining a bias ( f ) that favors fixation of all W→S mutations and loss of all S→W mutations with a distribution of negative fitness effects on nonsynonymous mutations ( c ) derived by Eyre-Walker et el . [40] . We calculated the predicted substitution rate in each mutational class from the product of mutation and fixation probabilities . As expected , increasing the fixation bias ( f ) in favor of W→S mutations results in a W→S bias in the pattern of substitution ( Figure 6A ) . This effect is most pronounced for GC-poor genes , whose substitution patterns have a higher degree of W→S mutational bias in the absence of a W→S fixation bias . A significant effect of f on the W→S bias can be observed once f > 1/4Ne ( 2 . 5 × 10−5 ) , which is the approximate selection coefficient required for a new mutation under selection to have a higher probability of fixation than a neutral mutation . For values of f > 10−4 , the W→S bias approaches 1 . Perhaps more surprisingly , at values of f > 10−4 , W→S fixation bias is also predicted to increase the dN/dS ratio ( Figure 6B ) . Hence , when f is high it appears to override the effects of negative selection , leading to an increased proportion of nonsynonymous fixations . Interestingly , the effect of f is much more pronounced on GC-rich genes , and can potentially lead to dN/dS > 1 ( typically assumed to indicate positive selection ) . This phenomenon can be explained by an observation that W→S mutations in GC-rich genes have a greater probability of occurring in nonsynonymous sites . In GC-poor genes ( ancestral GC = 0 . 3–0 . 4 ) , we predict 47% of new W→S mutations to be nonsynonymous , whereas in GC-rich genes ( ancestral GC = 0 . 6–0 . 7 ) , we predict this proportion to be 66% . This difference is likely due to synonymous sites in GC-rich genes already being saturated with W→S substitutions . The effect of a W→S fixation bias is predicted to have a similar effect on genes under different levels of selective constraint ( Figure S3 ) .
Homologous recombination events between a pair of chromosomes that are heterozygous at a particular locus can lead to the formation of a heteroduplex DNA molecule during meiosis . The BGC hypothesis proposes that when the heteroduplex contains a weak/strong ( AT/GC ) mismatch , this is preferentially repaired to the strong allele [6] . This implies that weak/strong heterozygotes transmit more GC than AT alleles to the next generation , particularly at loci in regions of high recombination . Theoretical modeling has shown that this leads to biased fixation of W→S substitutions , with dynamics similar to natural selection [7] , consistent with the patterns of evolution we observe in accelerated exons . An alternative hypothesis is that directional selection for increased GC content has been operating on accelerated exons and their flanking regions . Clusters of highly expressed genes have been found to occur in regions of elevated GC content [41 , 42] , and it is therefore possible that GC content has a direct effect on gene expression [43] . Hence , another explanation for our findings is that selection for increased gene expression has driven a local increase in GC content in the accelerated exons . mRNA structure and isochore GC content [30] are other possible sources of selective pressure . Without deeper understanding of the role of GC content in gene expression and chromosome evolution , it is difficult to hypothesize why selection on GC content would affect single exons and their flanking sequences rather than chromosomal domains or spliced transcripts . Across the entire genome , clusters of human and chimpanzee nucleotide substitutions have a significant tendency to be W→S biased and to occur in regions of elevated recombination [20] . Such clusters are also observed in conserved noncoding elements with evidence for acceleration in humans ( HARs ) [1 , 5] . Here we have shown that protein-coding sequences are also subject to this unusual phenomenon . Exons with elevated substitution rates in humans exhibit a striking excess of W→S biased substitutions compared with all exons in the dataset . These substitutions also show a strong tendency to be clustered in single exons , rather than the entire gene . Similar W→S biased patterns can be observed in surrounding noncoding sequence , decaying sharply to background levels with increasing distance from the accelerated exon , so that W→S bias in 10 kb on each side of a accelerated exons approaches the genome average . The observation that W→S biased substitution patterns extend into surrounding noncoding sequence strongly suggests that natural selection acting at the protein level could not be responsible for the biased fixation of GC alleles . However , it appears that clusters of W→S substitutions in accelerated exons are extremely localized to within a few kilobases around the exon . We also observe that when genes have evidence for clustering of base substitutions in a single exon , these substitutions exhibit a strong W→S bias . Furthermore , there is a strong discordance between levels of W→S bias in polymorphism compared with divergence , indicative of a bias towards fixation of W→S mutations . All of these observations are consistent with the action of BGC or localized selection in favor of increased GC content driving the evolution of the human-accelerated coding sequences we have identified . It should be noted that not all accelerated exons have W→S biased substitution patterns . In particular , adenylate cyclase-associated protein 1 ( CAP1 ) on human chromosome 1p34 contains a cluster of seven substitutions that are all S→W in exon 7 . Six of these substitutions are nonsynonymous . None of the substitutions appear to be the result of CpG hypermutability . Furthermore , there is no evidence of a local increase in base substitution rate in the noncoding regions flanking exon 7; there are no substitutions on the human lineage within 100 bp of noncoding sequence on each side of this exon . It is possible that human-specific positive selection has contributed to acceleration in evolutionary rate in this exon . However , the biased pattern of base substitution suggests a bias in the pattern of mutation or fixation has also contributed , although the cause of this bias is unclear . Our method for analyzing accelerated evolutionary rates in single exons could potentially be a promising approach for identifying genes involved in human-specific adaptations . Accelerated exons show a highly significant tendency to occur in regions of the human genome with elevated male recombination , consistent with the results of Dreszer et al . [20] . A correlation between the proportion of W→S substitutions and male recombination rate in humans is also observed in studies using human-chimpanzee-macaque comparisons across the genome [10] , and in patterns of evolution in Alu repeats [9] . In addition , we find a significant enrichment of accelerated exons close to telomeres , similar to what has been observed for clusters of base substitutions in general and for HARs . Furthermore , like HARs [1 , 2] , accelerated exons tend to be closer to recombination hotspots . Most recombination in humans is restricted to short ( <1 kb ) hotspots where recombination rates are >10× the genomic average [28] . If BGC were able to generate nucleotide substitutions , we would expect them to be concentrated in these regions . Selection in favor of increased GC content would also be expected to be more efficient in these regions , due to a reduction in Hill-Robertson interference [33] . Recombination hotspots are believed to arise rapidly and become rapidly extinguished , potentially because of the “hotspot conversion paradox” [44] . Hotspot turnover is suggested by differences in the location of hotspots between human and chimpanzee [45 , 46] , effects of certain allelic variants on recombination rate in known hotspots [47 , 48] , and theoretical modeling [49] . In contrast , large-scale recombination rates are correlated between humans and chimpanzees [46] . Assuming that a strong W→S fixation bias is associated with recombination hotspots , then localized clusters of W→S substitutions would be expected to occur in bursts , mirroring the rapid turnover of recombination hotspots . Due to their ephemeral nature , it is extremely difficult to measure the impact of hotspots in a particular genomic region since the human-chimpanzee ancestor . The two measures we used are large-scale recombination rates estimated from pedigree data [17] and a map of human recombination hotspots generated by analyzing patterns of linkage disequilibrium in the HapMap dataset . Estimates of the regional recombination rate and distance from the nearest hotspot of a particular genomic location are only rough indicators of the average density of recombination hotspots in that region since the human-chimpanzee split . Another problem is that we only have measures of when recombination events are resolved as crossovers and cannot directly measure the frequency or length of gene conversion events . Hence , although the clusters of substitutions we observe in accelerated exons are consistent with the action of an intense W→S fixation bias in recombination hotspots , we cannot reconstruct or implicate the locations of specific ancient hotspots . We also observe W→S biased substitution patterns in the chimpanzee lineage for exons that are accelerated in humans , although the degree of bias is weaker . This suggests that high rates of recombination could also affect these exons in the chimpanzee lineage . Analysis of nucleotide substitutions across the entire human and chimpanzee genomes show similar patterns [10] . These findings are consistent with conservation of the average density of hotspots between human and chimpanzee , which could affect patterns of substitution in both lineages . It should be noted that we do not expect W→S fixation bias due to selection or BGC to be specific to the human lineage , and we would generally expect different exons to be accelerated on the chimpanzee lineage . It is unclear why male recombination shows a stronger correlation with clusters of W→S biased substitutions ( and with the pattern of W→S biased substitution across the genome ) than does female recombination . This difference is not predicted by a model of selection on GC content modulated by Hill-Robertson effects on the efficacy of selection . It is possible that there is a stronger correspondence between the rate of crossovers and gene conversion in males than in females , which would cause the strength of BGC to correlate more strongly with male recombination . The site frequency spectrum should be altered in regions where a W→S fixation bias is occurring , due to an increase in frequency of GC alleles . Several studies have demonstrated that GC alleles segregate at elevated frequencies across the genome in human populations , and that this effect is stronger near recombination hotspots [21 , 26 , 50] . However , it has been suggested that these findings may have been influenced by a systematic error in inferring the ancestral state of SNPs [27] . An alternative theory for how recombination could generate W→S substitutions is by a direct mutagenic effect [23 , 51] . However , neither ancestral misinference nor a mutagenic effect of recombination can explain why the excess of GC alleles at elevated frequency increases in the vicinity of recombination hotspots [10] . In particular , the allele frequency distribution at a recently arisen recombination hotspot should be skewed towards low frequency GC alleles if recombination generated W→S mutations , which is the opposite of what is observed . A recent model of the effect of BGC on the pattern of base substitution [10] is a good fit to observed patterns across the human genome , suggesting that BGC—rather than a direct effect of recombination—can account for the patterns of molecular evolution observed in the human-accelerated coding regions we have identified . It is also possible that a reduction in Hill-Robertson interference in regions of high recombination could result in clusters of W→S biased substitutions due to selection . However , it is currently unclear whether this process would result in the observed variation in W→S bias and substitution rate over short physical distances . An important finding of this study is that biased fixation of W→S mutations can drive replacement amino acid substitutions . In addition to W→S biased substitution patterns , accelerated exons exhibit an excess of nonsynonymous to synonymous changes compared with the genomic average . This is consistent with previous suggestions that BGC may compete with purifying selection , resulting in the fixation of deleterious mutations [5] . This process may have occurred in noncoding HARs , which are generally extremely highly conserved between mammalian species other than humans , and probably play important functional roles ( e . g . , in regulation of gene expression ) . An increase in mutation rate is not expected to increase the proportion of nonsynonymous to synonymous changes , as it would be expected to remove the same proportion of nonsynonymous changes in regions of high or low mutation rates . Natural selection on amino acid sequence is also not expected to generate the W→S biased substitution patterns we observe in accelerated exons , which extend into noncoding flanking sequence . Using theoretical modeling , we have shown that W→S fixation bias is predicted to increase the dN/dS ratio under realistic assumptions regarding the strength of bias and distribution of negative fitness effects on nonsynonymous mutations . This effect is observable with a fixation bias corresponding to a selective coefficient >10−4 ( assuming Ne = 10 , 000 ) . An important simplifying assumption made by our model is that the W→S fixation bias can be modeled in an identical way to positive selection [7] . In reality there is likely to be a complex interaction between the two processes . In particular , the effects of selection may extend to distant linked sites , whereas the effects of BGC are likely to be confined to short conversion tracts . Further work is necessary to fully understand this interaction . Our model uses the method of Li [52] to predict the dN/dS ratio , whereas we used a codon-based ML method [53] to estimate this ratio from our alignments . Although the two methods may give slightly different estimates of dN and dS under certain scenarios , we do not expect this discrepancy to influence our prediction that a W→S fixation bias increases the dN/dS ratio . One assumption of codon models of substitution is that codon frequencies are at equilibrium , which is unlikely to be true at loci where a fixation bias is operating . However , the choice of model is not likely to lead to misinference of ancestral bases at short genetic distances , such as between human and chimpanzee . The strength of BGC depends on the rate of formation of heteroduplex DNA , the size of the hetoroduplex tracts , and the strength of the repair bias , all of which are difficult to estimate empirically . By comparing a large number of studies in yeast , Birdsell [15] has estimated a that GC/AT mismatches are repaired to GC with a bias of about 1 . 5 . Recombination rates of >50 cM/Mb are predicted to be common in localized ( 1–2 kb ) hotspots in the human genome [28] , and even higher rates have been observed in individual hotspots [54] . We cannot predict how often a particular site in a recombination hotspot will be involved in biased repair from these figures . However , it does not seem unrealistic that fixation biases >10−4 could occur at particular sites due to BGC if they are regularly included in recombination events in hotspots . We observed enrichment of certain GO categories in genes containing accelerated exons . Olfactory receptor proteins were overrepresented in the top 20 accelerated exons , and the genes containing the 83 accelerated exons were enriched for myosin complex genes . It is notable that these genes belong to superfamilies with many paralogs . In addition to allelic gene conversion events between homologues , gene conversion also occurs between duplicated paralogous genes . Previous studies have suggested that gene conversion between paralogs generates W→S biased patterns of base substitution in gene families [11 , 12] . Hence it is possible that extremely high levels of BGC between paralogs has contributed to the accelerated evolution and biased patterns of substitution we observe . Gene conversion is likely to occur more frequently between physically linked gene duplicates [11] . It is interesting to note that two of the fast-evolving olfactory receptors , OL3A3 and OL3A2 , lie within 200 kb of each other on the last band of chromosome 17p , close to a number of other olfactory receptors . Although none of the myosin complex genes containing accelerated exons occur on the same chromosome , MYH3 lies within a cluster of myosin family genes spanning 300 kb on chromosome 17p13 . Olfactory receptors are part of the largest supergene family in mammals . Several of these genes are believed to be under positive selection in humans , although disproportionately large numbers have become pseudogenes in humans compared with chimpanzee [55] . It is possible that excess fixations caused by BGC in human olfactory receptors are tolerated because purifying selection is relaxed in these genes in humans , and in some cases this has resulted in pseudogenization . However , it is also possible that previous reports of an enrichment of olfactory receptors amongst genes with accelerated dN/dS on the human lineage [56] could be influenced by BGC . Because our dataset is constructed from 1:1:1 orthologues , we cannot observe the effects of gene conversion between recent duplicates . However , BGC between closely related paralogs could potentially have a major influence on their evolution . One gene , kinesin family member 26B ( KIF26B ) , shows a particularly striking pattern of evolution on the human lineage . The most accelerated exon of this gene is exon 1 , which is 718 bp long and has 17 substitutions on the human lineage . All of these substitutions are W→S and nonsynonymous . The remaining three exons lie > 9 kb away from the first and have just two substitutions ( one W→S and one S→W ) within 500 bp . This gene is also the only one with a highly significantly accelerated dN/dS ( *** ) that also contains one of the top 20 accelerated exons . The molecular evolution of KIF26B in primates strongly parallels the Fxy gene in rodents . The 3′ portion of Fxy has been translocated into the highly recombining pseudoautosomal region ( PAR ) in M . musculus , whereas in the closely related M . spretus the entire gene is nonrecombining . This translocation coincides with a massive increase in the substitution rate in the 3' end of Fxy; M . musculus has 28 nonsynonymous substitutions , all of which are W→S , compared with only one nonsynonymous substitution in M . spretus [14] . The human substitutions at KIF26B are also almost exclusively nonsynonymous ( 18 out of 19 ) and the ML inferred dN/dS ratio for the human branch is 1 . 75 . This extreme substitution pattern may indicate the involvement of both positive selection and BGC . However , KIF26B has an extremely high GC content ( 0 . 72 ) , and our theoretical modelling suggests that a W→S fixation bias can potentially result in dN/dS > 1 in such GC-rich genes in the absence of positive selection . This is because synonymous sites are more saturated with W→S substitutions in GC-rich genes so that W→S mutations have a greater probability of occurring in nonsynonymous sites , which could also explain why the W→S bias is greater in nonsynonymous sites in accelerated exons . It is possible that positive selection can promote compensatory amino acid replacement substitutions after deleterious mutations become fixed due to BGC , but these substitutions would not all be expected to be W→S , as observed at the KIF26B locus . We identified genes with evidence for increased rates of dN/dS on the human lineage using an LRT . We find that the most diverged exons in these genes have significantly W→S biased substitution patterns . This pattern is not seen in the most diverged exons of genes overall , indicating that W→S fixation bias may affect the evolution of the genes with the strongest evidence for accelerated rates of amino acid substitutions in humans . The strongest signal for W→S bias occurs in the exons with the largest proportion of amino acid replacement substitutions . These observations suggest that a W→S fixation bias could contribute to elevated levels of dN/dS and possibly lead to false inference of positive selection at the protein level . Genes with accelerated dN/dS differ from accelerated exons in several ways . First , we do not observe significantly W→S biased substitution patterns in the noncoding regions associated with genes with accelerated dN/dS . Nonetheless , the significantly elevated GC content of these regions suggests that they may have experienced W→S biased substitution patterns previously . Second , compared to accelerated exons , genes with accelerated dN/dS show a weaker association between substitution rates and local recombination rates . These genes are significantly enriched close to human recombination hotspots , but they are not enriched in regions of elevated recombination ( measured from the DECODE recombination map [17] ) or in distal chromosome regions . These findings suggest that while the signature of recombination-associated W→S fixation bias is observable within genes with elevated dN/dS in humans , they have been affected to a lesser extent than the accelerated exons . Alternatively , W→S biased substitution patterns in genes with accelerated dN/dS may result from different evolutionary processes . For example , one factor that could contribute to the relationship between recombination hotspots and dN/dS is the higher efficiency of natural selection in regions of high recombination , due to a reduction in the strength of Hill-Robertson interference [33] . We also observed an increase in W→S bias in genes with an excess of amino acid replacement substitutions relative to human polymorphism identified using the modified MK test [35] of Bustamante et al . [39] . The largest W→S bias occurs in genes with the most significant values of the test . W→S bias is particularly marked in the most diverged exon of each gene . These genes are also significantly enriched close to human recombination hotspots , although their average recombination rates are not significantly different from the genomic average . This pattern is consistent with a W→S fixation bias driving additional weakly deleterious amino acid substitutions , mainly restricted to single exons . Our observations are consistent with the past existence of transient recombination hotspots in these regions , which are , in general , no longer actively driving fixation of GC alleles in the human population . However , as we do not observe a strong correlation between present day recombination rates and significant MK test results , it is possible that the W→S fixation bias is unrelated to recombination in these genes . Overlap between genes identified by the two tests of positive selection is not significantly higher than expected by chance , which is indicative that they identify genes with different evolutionary histories . The dN/dS LRT identifies genes with increased dN/dS ratios on the human lineage . These genes would not necessarily exhibit a significant excess of amino acid substitutions relative to polymorphism , unless they were under the influence of strong positive selection , or experienced recent shifts in their mode of evolution . In contrast , the MK test compares patterns of divergence and polymorphism , but does not detect whether the rate of protein evolution has changed on the human lineage . The accelerated exons do not all show a strong excess of nonsynonymous changes , which explains the limited overlap between them and genes identified by tests of selection . It is notable that all three tests identify coding sequences with W→S biased patterns of substitution . The effect of W→S fixation bias at a particular locus is likely to depend on a variety of factors , including the time scale and intensity of a W→S drive and the locus-specific interaction with natural selection . All of these factors are predicted to vary between loci , likely due to stochastic variation in the strength and location of recombination hotspots over time . It is therefore not surprising that signals of a W→S fixation bias can be found using a variety of tests for increased evolutionary rates . Importantly , our results suggest that a W→S fixation bias , rather than positive selection on protein function , could be responsible for generating significant tests for selection in some genes , which cause us to urge care in the interpretation of these tests . We have presented evidence that protein-coding sequences with accelerated rates of evolution in humans have significantly biased patterns of nucleotide substitutions . These results are consistent with a strong effect of W→S fixation bias on the evolution of the most rapidly evolving coding exons in our genome . This process may have led to the increased fixation of replacement amino acid changes on the human lineage , and may bias tests of positive selection .
We analyzed a dataset of 10 , 376 alignments of 1:1:1 human-chimpanzee-macaque orthologous genes presented in the rhesus macaque genome paper [36] and available from http://compgen . bscb . cornell . edu/orthologs/ . The alignments consisted of a filtered dataset of orthologous genes derived from known human protein coding genes identified from the RefSeq [57] , Vega [58] , and UCSC known gene [59] annotations . Genes with poor syntenic relationships , incomplete alignments , frame-shift indels , changes in exon-intron structure , and evidence for recent duplications had all been excluded from the dataset [36] . Annotation files for all of the genes were downloaded from Biomart ( http://www . ensembl . org/biomart/martview/ ) and UCSC ( http://genome . ucsc . edu/ ) . These were used to identify the exon boundaries in all of the alignments and their location in the hg18 human genome sequence assembly . A small number of genes ( <1% ) were excluded due to poorly matching gene annotation data . We finally excluded alignments with ten or more bases in runs of mismatches of three or more between any of the sequences , resulting in a dataset of 10 , 238 genes . Human recombination rates , based on the DECODE map [17] were obtained from the UCSC table browser ( http://genome . ucsc . edu/cgi-bin/hgTables ) . Positions of human recombination hotspots as inferred from coalescent analysis of large-scale SNP genotyping data were downloaded from the HapMap website ( http://www . hapmap . org/downloads/ ) . All analyses were based upon the hg18 human genome assembly , aligned to the chimpanzee ( panTro2 ) and the macaque genome ( rheMac2 ) . The liftover tool , available from the UCSC website , was used to convert human annotation to the hg18 assembly where needed ( http://hgdownload . cse . ucsc . edu/downloads . html ) . We also constructed alignments of the noncoding sequence flanking each exon in the coding dataset . To do this , we first obtained pairwise chained and netted blastz alignments of the hg18 versus panTro2 assemblies and the hg18 versus rheMac2 assemblies from the UCSC website ( http://hgdownload . cse . ucsc . edu/downloads . html ) . These were converted into a human-chimpanzee-macaque alignment for each human chromosome using tools from the multiz package [60] . Finally , we masked all exons and extracted flanking sequence on both sides of each exon using the gene annotation files . We used the phast package [61] to analyze the rate of nucleotide substitution individually for each exon sequence alignment , implementing the general time-reversible ( REV ) model . We compared a model with relative branch lengths ( i . e . , relative substitution rates ) equal to those from a genome-wide model to a model where the human branch is longer ( i . e . , has an accelerated substitution rate ) . We used an LRT to identify exons with statistically significant substitution rate acceleration on the human branch [1] . We used the codeml program of PAML [62] with F3x4 codon frequencies and the Goldman and Yang [53] model of codon substitution to infer the pattern of synonymous and nonsynonymous nucleotide substitutions at each gene on the human and chimpanzee branches of the tree under two models usingML . We first used the one-ratio model , where the dN/dS ratio was fixed along all lineages of the tree . We compared this with the two-ratio model , were dN/dS was allowed to vary along the human lineage . Sequences with accelerated dN/dS on the human branch were identified with an LRT . We repeated this analysis on the whole-gene alignments and on individual exon alignments . For the single exon analysis , codons that overlapped between two consecutive exons were removed from the alignments . We compared the ML reconstructed human-chimpanzee ancestral sequence from the two-ratio model with the human sequence to determine the pattern of substitutions along the human lineage . Substitutions were divided into four different classes: strong-to-strong ( S→S ) , strong-to-weak ( S→W ) , weak-to-strong ( W→S ) , and weak-to-weak ( W→W ) . “Weak” designates A or T base pairs , which are bound by only two hydrogen bonds . “Strong” designates C or G base pairs , which are bound by three hydrogen bonds . We defined the W→S bias of a genomic region as follows: W→S bias = nW→S / ( nW→S + nS→W ) , where nW→S and nS→W are the number of W→S and S→W substitutions , respectively . Substitutions were also classified as nonsynonymous or synonymous . Multiple substitutions in the same codon were taken into account using the same criteria as single substitutions . These were inferred by ML to account for only 0 . 9% of substitutions . Substitutions in noncoding alignments surrounding each exon , and the GC content of the ancestral sequences , were inferred using parsimony . Human-specific substitutions were identified and assigned to the four different categories above by determining the ancestral state of each site using the macaque sequence . We analyzed whether there was a tendency for nucleotide substitutions to cluster using a statistic that captures the relative substitution rate in the most diverged exon of a gene compared to the overall substitution rate in the gene: where indexes the exon , si is the number of single base substitutions in exon i , and li is the length of exon i ( in bases ) . Genes with large values of T have an exon that has a higher substitution rate than expected given the overall rate of substitutions across exons in the gene . For each gene , we conducted a simulation to assess the statistical significance of the observed value of T . Fixing the exon boundaries at the observed positions , we uniformly placed the observed number of substitutions at random sites across the gene and calculated the value of T . Repeating this substitution assignment 1 , 000 times provides a null distribution for the statistic T , under the assumption that the substitution process is uniform . An empirical p-value can be calculated as the proportion of the 1 , 000 null T values that exceed the observed T value . We estimated the total number of substitutions of each type for every gene , dividing substitutions into individual exons . We also calculated the GC content of each exon , the distance to the nearest recombination hotspot , the recombination rate , and whether each gene is in the last chromosome band . We ranked each exon according to its degree of acceleration in evolutionary rate on the human lineage , taking all substitutions into account , using the LRT statistic with the REV model of nucleotide substitution . Significance was estimated by simulating 10 , 000 datasets from the null model and calculating the LRT statistic for each exon . The p-value for each exon was estimated as the number of simulated LRTs that exceed the observed value . These p-values were adjusted for multiple testing using the FDR controlling method of Benjamini & Hochberg [37] . We also classified genes according to evidence of a significantly different dN/dS along the human lineage . We divided genes into three levels of significance based on comparing the LRT statistic to the chi-square distribution: p < 0 . 001 ( *** ) , p < 0 . 01 ( ** ) , and p < 0 . 05 ( * ) . We ranked exons according to their level of “relative divergence , ” using the statistic T defined above . Significant differences in the patterns of nucleotide substitution in the most accelerated exons and genes in all categories were identified using FET and by bootstrapping each exon with 10 , 000 replicates . The FET assumes that each substitution is an independent data point , whereas the bootstrap test considers each exon independently thereby accounting for correlation between substitutions within an exon . We identified human SNPs within our alignments using data from the HapMap project . We obtained the position and alleles of >15 million SNPs on the hg18 human genome build using the HapMart tool available at http://hapmart . hapmap . org/BioMart/martview . We then determined the ancestral allele of each SNP that overlapped one of our alignments by comparison with the chimpanzee base at that position . To minimize errors due to ancestral misinference , only biallelic SNPs where one allele matched both the chimpanzee and macaque sequence were included in the analysis . We identified genes in our dataset with evidence for an excess of amino acid replacement substitutions relative to human polymorphism based on the genome scan of Bustamante et al . [39] . This analysis estimated the selection coefficient from MK contingency tables [35] of polymorphism and divergence at synonymous and nonsynonymous sites . The posterior probability of the selection coefficient was used to estimate the probability that a gene is under positive selection ( has an excess of amino acid replacement substitutions ) . Only genes that appeared in our dataset and in the dataset of Bustamante et al . [39] were included in the analysis . We compared patterns of nucleotide substitutions between genes with evidence for positive selection with the entire dataset using FET and bootstrapping each gene with 10 , 000 replicates . The FET assumes that each substitution is an independent data point , whereas the bootstrap test considers each gene independently . We tested whether genes containing exons with significantly accelerated rates of base substitution , genes with significantly accelerated dN/dS ratios , and genes with significant MK tests were enriched for particular GO categories . We performed these analyses using GOstat [63] , available at the website http://gostat . wehi . edu . au/ . To detect potential incidences of ancestral misidentification in our dataset , we performed BLAST searches of the most accelerated genes and exons in our alignments against the NCBI trace archives from three other primate sequences: gorilla ( Gorilla gorilla ) , orangutan ( Pongo pygmaeus abelii ) , and baboon ( Papio hamadryas ) . These sequences were aligned to the existing alignments and used to identify human-chimpanzee mismatches where the ML inferred ancestral base was incongruent with the orthologous base in the additional species . In cases where bases were not in concordance between the three additional species , the base from the species most closely related to human and chimpanzee was compared with the inferred ancestral base . Nagylaki [7] demonstrated that BGC can be modeled using a selection coefficient . We therefore assume that BGC and a W→S fixation bias due to selection can be modeled in the same way . We modeled the effect of a W→S fixation bias by applying the inferred neutral mutation rate , a realistic distribution of negative fitness effects on nonsynonymous sites , and a range of values of a selection coefficient that favors fixation of W→S mutations and loss of S→W mutations , to the inferred ancestral sequences . We first estimated the pattern of neutral mutation on the human lineage using the inferred pattern of substitution at fourfold degenerate sites from our codeml analysis with the two-ratio model ( see above ) . The mutation pattern was estimated separately within four categories of ancestral GC content ( 0 . 3–0 . 4 , 0 . 4–0 . 5 , 0 . 5–0 . 6 , 0 . 6–0 . 7 ) . The relative probability of every possible mutation at each base in each GC content category was calculated as follows for each of the 12 possible single base mutations . The A→C mutation is shown as an example: where nX is the number of sites in category X and X is a mutational type ( e . g . , nAC is the number of sites with A→C mutations ) . We next concatenated the ancestral sequences of all genes in each GC content category . For each concatenated sequence , we calculated the expected relative rate of synonymous and nonsynonymous mutations in each of the following mutational classes ( W→S , S→W , W→W , S→S ) by adapting the method of Li [52] as follows . First , the number of nondegenerate ( L0 ) , 2-fold degenerate ( L2 ) , and 4-fold degenerate sites ( L4 ) in the ancestral sequence were counted . A site is nondegenerate if all possible mutations at that site are nonsynonymous , 2-fold degenerate if one of the possible mutations is synonymous , and 4-fold degenerate if all possible changes are synonymous . The one possible case of a 3-fold degenerate site is treated as 2-fold degenerate . Each possible mutation at every site in the ancestral sequence was then classified as a transition or a transversion . The relative numbers of expected transitional ( Si ) and transversional ( Vi ) mutations ( i = 0 , 2 , 4 ) at each type of site in the entire sequence were then calculated separately for W→S , S→W , W→W , and S→S mutations as the sum of the relative probability of each possible transition and transversion at each site . Finally , we calculated the expected relative rate of synonymous and nonsynonymous mutations separately for each of the four mutational classes ( uWS ( syn ) , uSW ( syn ) , uWW ( syn ) , uSS ( syn ) , uWS ( nonsyn ) , uSW ( nonsyn ) , uWW ( nonsyn ) , uSS ( nonsyn ) ) , using the values of Si , Vi , and Li to estimate dN and dS according to Li [52]: We simulated the selective coefficient ( s ) for each of the eight classes of mutation based on the combined effects of a W→S fixation bias ( f ) and selective constraint ( c ) . The values of s for synonymous changes are: sWS ( syn ) = f , sSW ( syn ) = –f , sWW ( syn ) = 0 , and sSS ( syn ) = 0 . The W→S fixation bias alters the probability of fixation of W→S and S→W mutations , but W→W and S→S mutations are assumed to evolve completely neutrally . The values of s for nonsynonymous changes are: sWS ( nonsyn ) = f – c , sSW ( nonsyn ) = – f – c , sWW ( nonsyn ) = –c and sSS ( nonsyn ) = –c . Selective constraint on a nonsynonymous mutations depends on a distribution of negative fitness effects , which is commonly modeled using a gamma distribution . We therefore sampled c from a descretized gamma distribution with shape parameter 0 . 23 and mean 0 . 0425 , assuming an effective population size ( Ne ) of 10 , 000 . This distribution was inferred by Eyre-Walker et al . [40] to be a good fit to the distribution of fitness effects of SNPs segregating in the human population , and is in good concordance with other studies ( e . g . , [64] ) . We considered a range of values of f between 10−10 and 1 . We calculated the probability of fixation separately for mutations in each of the 8 classes using the following equation derived by Kimura [65]: where N is the population size of an ideal Wright-Fisher population , which we assume to be 10 , 000 . The predicted relative substitution rates ( K ) at each mutational class were then calculated by multiplying their probability of fixation , P , by their relative mutation rates , u . We calculated K for each value of f ( between 10−10 and 1 ) , separately for each ancestral GC content category . We used these rates to calculate dS , dN , and W→S bias by summing across the different mutational categories . | Regions of the human genome that appear to evolve rapidly may have been under strong positive selection and could contain the genetic changes responsible for the uniqueness of our species . However , neutral ( nonadaptive ) evolutionary processes can give rise to signals that can be mistaken as signs of selection . In this article , we identify coding sequences that have undergone accelerated rates of change in humans , affecting the divergence of the proteins they encode . By analyzing patterns of molecular evolution in these genes and their distribution in the genome , we show that many protein-coding changes in the fastest-changing genes are not a result of selection operating on the genes , but instead result from biased fixation of AT-to-GC mutations . Our findings are consistent with a model of recombination-driven biased gene conversion . This leads to the provocative hypothesis that many of the genetic changes leading to human-specific characters may have been prompted by fixation of deleterious mutations . | [
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] | 2009 | Hotspots of Biased Nucleotide Substitutions in Human Genes |
Development in the central nervous system is highly dependent on the regulation of the switch from progenitor cell proliferation to differentiation , but the molecular and cellular events controlling this process remain poorly understood . Here , we report that ablation of Crb1 and Crb2 genes results in severe impairment of retinal function , abnormal lamination and thickening of the retina mimicking human Leber congenital amaurosis due to loss of CRB1 function . We show that the levels of CRB1 and CRB2 proteins are crucial for mouse retinal development , as they restrain the proliferation of retinal progenitor cells . The lack of these apical proteins results in altered cell cycle progression and increased number of mitotic cells leading to an increased number of late-born cell types such as rod photoreceptors , bipolar and Müller glia cells in postmitotic retinas . Loss of CRB1 and CRB2 in the retina results in dysregulation of target genes for the Notch1 and YAP/Hippo signaling pathways and increased levels of P120-catenin . Loss of CRB1 and CRB2 result in altered progenitor cell cycle distribution with a decrease in number of late progenitors in G1 and an increase in S and G2/M phase . These findings suggest that CRB1 and CRB2 suppress late progenitor pool expansion by regulating multiple proliferative signaling pathways .
During vertebrate retina development , one type of glial cell and six types of neurons are formed by the orderly generation of post-mitotic cells from a common pool of retinal progenitor cells [1] , [2] . In this temporally fine-tuned process , ganglion cells are generated first , followed by horizontal cells , cone photoreceptors and early born amacrine cells , rod photoreceptors and late born amacrine cells , and finally bipolar cells and Müller glial cells [2] . Retinal progenitor cells are elongated and polarized cells that extend along the apicobasal axis and connect to adjoining cells by adherens junctions via their apical processes . The proliferation of the progenitors is carefully regulated through a combination of intrinsic and extrinsic signals followed by a complete cessation of cell division around 10 days after birth in mice [3] . Many extrinsic soluble or membrane-bound factors directly promote proliferation activity such as Notch , sonic Hedgehog and Wnt signalling pathways [4] . In addition , intrinsic regulatory genes and transcription factors such as Chx10 regulate the cell cycle machinery [5] . Recent work suggests that cell adhesion and cell polarity complex proteins play a critical role in the maintenance of the proliferation of the progenitor cells [6] . The polarity proteins that form the Crumbs complex reside at the subapical region adjacent to the adherens junctions between retinal progenitor cells in the developing retina or between photoreceptors and Müller glial cells in mature retinas . The Crumbs protein was first identified in Drosophila as a key developmental regulator of apical-basal polarity [7] . In mammals , the Crumbs homologue family is composed of three genes , CRB1 , CRB2 and CRB3 . CRB proteins have a large extracellular domain ( which is lacking in CRB3 ) composed of epidermal growth factor and laminin-globular domains , a single transmembrane domain , and an intracellular domain containing FERM and PDZ protein-binding motifs [8] . Through this PDZ motif CRB proteins interact with PALS1 , which binds to MUPP1 or PATJ , thus forming the Crumbs complex [8] . Recently , it has been shown that the CRB-interacting partner PALS1 has a role in regulating the proliferation of neural progenitors . Deletion of PALS1 in the developing cortex caused premature exit of progenitors from the cell cycle and massive cell death leading to absence of the cortical structures [9] . Studies suggest a common function of CRB proteins and their partners in regulating growth factor signalling pathways , which orchestrate cell proliferation and cell fate decisions . It has been suggested that Drosophila Crumbs and human CRB2 inhibit Notch1 cleavage and signalling by binding to the presenilin complex , inhibiting γ-secretase activity [10] , [11] . Zebrafish CRB extracellular domains can directly bind to the extracellular domain of Notch1 and inhibit its activation [12] . The Crumbs complex can negatively modulate the mammalian Target of Rapamycin Complex 1 ( mTORC1 ) pathway via the direct interaction between PATJ and the tumour suppressor gene TSC2 and depletion of PALS1 protein results in loss of mTORC1 activity in the murine developing cortex [9] , [13] . The Hippo pathway is a key regulator of organ size and tumorigenesis in humans and flies [6] , [14] . Drosophila Crumbs has been shown to control the Hippo pathway by direct interaction of its FERM domain [15] , [16] . Furthermore , PALS1 and PATJ can interact with the effectors of the Hippo pathway Yes-associated Protein ( YAP ) and transcriptional co-activator with PDZ-binding motif ( TAZ ) proteins and thus promote their inhibition and retention in the cytoplasm [17] . Mutations in the human CRB1 gene cause autosomal-recessive progressive retinitis pigmentosa and Leber congenital amaurosis ( LCA ) [18] . LCA is one of the most severe forms of retinal dystrophy leading to blindness around birth due to defects in the development or maturation of the retina [19] . CRB1-LCA retinas are remarkably thick and lack the distinct layers like immature retinas suggesting a developmental defect [20] . The functional roles of CRB proteins during mammalian development remain poorly understood . Both CRB1 and CRB2 are expressed from embryonic day ( E ) 12 . 5 onwards in the developing murine retina at the subapical region adjacent to adherens junctions in retinal progenitor cells [21]–[23] suggesting a role of the CRB proteins during the development of the retina . Crb1 knockout , Crb1C249W/− knockin and the naturally occurring Crb1rd8/rd8 mutant mice show mild retinal disorganization in adulthood , limited to the inferior quadrant [24]–[27] . Crb2 conditional knockout ( cKO ) retinas show progressive abnormal lamination of newborn rod photoreceptors and disruption of adherens junctions in postnatal developing retina [22] . Here , we study the effects of loss of CRB1 and CRB2 and their potential overlapping functions during early retinal development . Loss of both CRB1 and CRB2 results in absence of a separate photoreceptor layer , misplaced cell types throughout the retina and loss of retinal function mimicking the phenotype observed in human LCA patients . Our data suggests that the pool of late progenitor cells during retinal development is suppressed by CRB1 and CRB2 through the regulation of mitogenic signaling pathways .
We crossed Crb1 KO mice with conditionally floxed Crb2 mice [22] , [24] . The mice were bred with Chx10Cre transgenic mice , which express Cre recombinase fused to GFP throughout the developing retina starting at E11 . 5 [28] . We showed previously that efficient recombination of the floxed Crb2 alleles occurred around E12 . 5 [22] . In this study , double homozygote Crb1−/−Crb2F/FChx10CreTg/+ conditional knockout retinas ( Crb1Crb2 cKO ) were compared to littermate Crb1−/−Crb2F/F and Crb1−/−Crb2F/+Chx10CreTg/+ retinas . Crb1+/−Crb2F/FChx10CreTg/+ ( Crb1+/−Crb2 cKO ) retinas were compared to littermate double heterozygote Crb1−/+Crb2F/+Chx10CreTg/+ ( Crb1+/−Crb2F/+ cKO ) retinas . We verified the loss of CRB1 and CRB2 proteins in the Crb1Crb2 cKO at E15 . 5 and P14 ( Figures S4D and S3D ) . In vivo functional and structural analysis were performed on 1 to 6 month ( M ) old Crb1Crb2 cKO , Crb1+/−Crb2 cKO and control mice , using electroretinography , spectral domain optical coherence tomography and scanning laser ophthalmoscopy . Already at 1M , Crb1+/−Crb2 cKO and Crb1Crb2 cKO mice showed more pronounced reduction in amplitudes of electroretinogram responses than Crb2 cKO mice ( Figures 1A and S1A ) . Both scotopic and photopic responses were affected , which indicate alterations of both rod and cone system components . At 3 and 6M ( Figures 1B and S1B–C ) , electroretinogram responses were below detection level , although Crb1+/−Crb2 cKO responses were more variable ( Figures 1B and S1B ) . In vivo imaging analysis revealed changes in Crb1+/−Crb2 cKO retinas in fundus appearance as well as in retinal layer morphology in contrast to Crb1+/−Crb2F/+ cKO control retinas ( Figure S2 ) . With native scanning laser ophthalmoscopy , many spots and patchy areas were visible throughout the retina , corresponding to pseudo-rosettes in the photoreceptor layer and in histological sections ( Figures S2B and 2A–B ) . Already at 1M , spectral domain optical coherence tomography revealed an aberrant layering in Crb1Crb2 cKO retinas ( Figure 3E–F ) . The retina consisted of a single inner plexiform layer , an abnormal thick ganglion cell layer and a second broad nuclear layer ( Figure 2A–B ) . All retinal cell types appeared to be generated , but a separate photoreceptor nuclear layer , inner and outer segment layer and outer plexiform layer were not formed . Two types of rosettes in the broad nuclear layer could be identified and were primarily formed of photoreceptors or ganglion cells and inner nuclear layer cells ( Figure 2A–B black arrowheads and asterisks , respectively ) . Using electron microscopy and immunohistochemistry , we found ectopically localized photoreceptor outer segments , delocalized basal bodies of cilia , adherens junctions and ribbon synapses in the Crb1Crb2 cKO at 1M ( Figures 2E–F and S3A , C ) . The retina thickness in the Crb1Crb2 cKO was significantly increased compared to control retinas at P10 ( 276 . 1±13 . 2 µm vs 199 . 7±5 . 4 µm , respectively ) and P14 ( 247 . 8±6 . 9 µm vs 211±7 . 7 µm , respectively; Figure 2G ) . Both Crb1Crb2 cKO and Crb1+/−Crb2 cKO retinas degenerate rapidly after 1M , which was associated with retinal vasculature defects leading to the thinning of the retinas in 3–6M retinas ( Figures 2C–D , S2 and 3 ) . Quantification of cleaved caspase 3 positive cells showed an increase in the number of apoptotic cells in Crb1Crb2 cKO retinas at P10 , P14 and 3M ( Figure 2H ) . Cleaved caspase 3 positive cells at P10 and P14 were identified as rod photoreceptor cells and at 3M mainly as bipolar cells ( Figure S3E–F ) . As CRB1 and CRB2 are expressed in the retinal progenitor cells from E12 . 5 onwards at the subapical region adjacent to adherens junctions [21]–[22] and due to the severe disorganization of these retinas in adult , we analyzed control , Crb1+/−Crb2 cKO and Crb1Crb2 cKO mice from E11 . 5 to P5 . Whereas no visible defects were observed at E11 . 5 and E12 . 5 , perturbations at the outer limiting membrane and cellular mislocalizations near the retinal pigment epithelium were visible at E13 . 5 in Crb1Crb2 cKO retinas ( Figure 4A , black arrowhead ) . Between E15 . 5 and E17 . 5 in Crb1Crb2 cKO , the adherens junctions were gradually lost and the nuclei of the retinal progenitors showed abnormal orientation , whereas in control retinas , progenitors were arranged radially along the apical-basal axis ( Figures 4B–C and S4B ) . Electron microscopic analyses showed loss of adherens junctions in the neural retina and ectopic nuclei close to the retinal pigment epithelium ( Figures 4F–G and S4E–F ) . During retinogenesis , the photoreceptor layer and the outer plexiform layer formed at P5 . However , in the Crb1Crb2 cKO , this process never ensued , as no distinct photoreceptor layer was formed ( Figure 4E ) . In Crb1+/−Crb2 cKO , perturbations at the outer limiting membrane started at the periphery of the retina at E15 . 5 ( Figure 4B , black arrowhead ) . It progressively extended to the centre of the retinas where rosettes also formed ( Figure 4C–E ) . In late developmental stages , in addition to photoreceptor rosettes , ganglion cell nuclei and inner nuclear layer cells were found in the outer nuclear layer and some photoreceptor nuclei were found in the ganglion cell layer ( Figure 2A ) . These retinas display intermediate phenotypes between the Crb2 cKO [22] and Crb1Crb2 cKO . Due to the severe disorganisation of the retinas , we further investigated whether all retinal cell types formed in the absence of CRB1 and CRB2 . Using specific markers for the different cell types , we found that all the different cell types formed and there were no indications for hybrid retinal cell types ( Figure S5 and data not shown ) . Several of the retinal cell types appeared to localize ectopically . To further analyze this , we compared the localization of the cell nuclei in the top and bottom parts of the broad nuclear layer in Crb1Crb2 cKO mice to the outer and inner nuclear layer in control retinas ( Figures 5A–F and S5A–F ) . The localization of the earliest born cell types , ganglion cells ( marked by Brn3b ) , cone photoreceptors ( Cone arrestin ) , horizontal cells ( Calbindin ) and the earliest born amacrine cells ( ChAT ) was less affected than the late born cell types , rod photoreceptors ( Rhodopsin ) , Müller cells ( Sox9 and glutamine synthetase ) and bipolar cells ( PKCα or Cre-GFP under the Chx10 promoter ) . In Crb1+/−Crb2 cKO retinas , rods , cones and bipolar cells localized ectopically in the ganglion cell layer ( Figure S5G–H ) , and amacrine and ganglion cells surrounded by bipolar cells formed pseudo-rosettes in the photoreceptor layer ( Figure S5I–J ) . These results suggest that all cell types are generated in retinas that lack CRB1 and CRB2 but their normal migration/localization is affected . To test whether retinal cell types formed in normal numbers , we counted the different cell types at P14 ( Figure 5G ) . The number of early born cells was unchanged whereas the number of late born cells was increased compared to control retinas: GABAergic amacrine cells ( 19 . 4±1 . 6 versus 14 . 8±0 . 6 cells/100 µm ) , late born GlyT1 positive amacrine ( 38 . 9±2 . 8 versus 20 . 9±1 . 4 cells/100 µm ) , Chx10+ bipolar cells ( 77 . 2±5 . 0 versus 46 . 7±2 . 8 cells/100 µm ) and Sox9+ Müller cells ( 44 . 3±1 . 8 versus 18 . 8±0 . 6 cells/100 µm ) . At P14 , the number of rod photoreceptors was not significantly increased due to ongoing apoptosis ( Figures 3H and S3E ) . We found at P10 an increase in number of rods ( 695±44 in Crb1Crb2 cKO and 412±17 cells/100 µm in control; Figure 5H ) . This finding suggests that CRB1 and CRB2 may play a role in regulating the proliferation of the retinal progenitors . In the Crb1Crb2 cKO retinas , the increased number of late born cells might be due to overproliferation of progenitors or reduced apoptosis . Therefore , in control , Crb1+/−Crb2 cKO and Crb1Crb2 cKO retinas from E13 . 5 to P5 animals , we analysed the number of phospho-Histone H3 ( pH3 ) positive cells and cleaved caspase 3 positive cells , which are markers for mitotic cells and apoptotic cells respectively ( Figures 6A–B and S6C–D ) . From E15 . 5 onwards , the number of M-phase cells was significantly increased in Crb1Crb2 cKO retinas , and the number of apoptotic cells was increased at E13 . 5 and E17 . 5 onwards . These data showed an increase in both mitosis and apoptosis in retinas lacking CRB1 and CRB2 . Furthermore , cells in M-phase are normally located at the apical region in control retinas . However , in E17 . 5 Crb1Crb2 cKO retinas , where the apical region was almost completely lost , the cells in M-phase localized randomly throughout the entire thickness of the retina ( Figure S6C–D ) . To test whether precursor cells formed in normal numbers , we counted at E17 . 5 early and late-born precursor cells . The number of Islet1+ early-born precursor cells ( ganglion and amacrine cells ) is unchanged in contrast to an increased number of Otx2+ late-born precursor cells ( photoreceptors and bipolar cells; 139 . 3±5 cells/100 µm in Crb1Crb2 cKO retinas versus 110 . 9±4 . 1 cells/100 µm in control; Figure 6D ) . At E17 . 5 , in Crb1+/−Crb2 cKO retinas , the number of mitotic and apoptotic cells was increased like in Crb1Crb2 cKO retinas ( Figure S6A–B ) . However , at P5 an increased number of mitotic cells and a decreased number of apoptotic cells were observed like in Crb2 cKO [22] , indicating that the Crb1+/−Crb2 cKO showed intermediate features between Crb2 and Crb1Crb2 cKO . We further investigated , at E17 . 5 , which phases of the cell cycle were affected using a combination of 30 min pulse labelling with BrdU for the S-phase , phospho-Histone H3 ( pH3 ) for the M-phase and Ki67 labelling , a marker for M , G2 , S and late G1 phases of the cell cycle ( Figures 6C , S6C and S6E ) . This showed that in Crb1Crb2 cKO retinas the number of pH3+ ( 6 . 1±0 . 2 in control versus 8 . 4±0 . 4 cells/100 µm in cKO retinas ) , BrdU+ ( 185 . 9±12 . 1 in control versus 238 . 8±17 . 5 cells/100 µm in cKO retinas ) and Ki67+ cells ( 329±8 . 3 in control versus 384 . 5±15 cells/100 µm in cKO retinas ) were increased . In mice , the proportion of dividing cells decreases dramatically at the centre of the retinas from P5 onwards , whereas the progenitors at the periphery of the retina still proliferate . Ultimately , mitosis is finished at the centre at P6 and at the periphery at P10 [3] . Surprisingly , in Crb1Crb2 cKO retinas the number of cells in M-phase ( pH3+ ) was higher compared to the controls ( Figure 6A ) . We further investigated this phenomenon using the Ki67 marker to analyse the proliferating cells in all phases of the cell cycle ( Figure S6D , F ) and found that the total number of cells was increased by a factor of two both in the centre and at the periphery at P5 ( Figure S6H ) . In contrast to the control , some Ki67 positive cells were still present at the periphery of the retina at P10 in Crb1Crb2 cKO retinas ( data not shown ) . These results suggest that active proliferating cells in Crb1Crb2 cKO retinas may reside longer than those in control retinas . We performed flow cytometry analysis based on the DNA content and KI67 labelling at E17 . 5 , P1 and P5 to study the proportion of cells at G1 , S and G2/M phases of the cell cycle or which already exited the cell cycle in G0 ( Figures 6E , G , H and S6G ) . At E17 . 5 , the proportion of cells in G1 was reduced whereas the proportion of cells in S and G2/M was increased and G0 unchanged . At P1 and P5 , the proportion of cells in Crb1Crb2 cKO returned to control proportion . In addition , levels of cyclin D1 , cyclin E and c-myc transcripts ( Figure 7A ) were changed suggesting also an aberrant regulation of the cell cycle in Crb1Crb2 cKO retinas at E17 . 5 . We examined how the cell cycle exit was affected in the mutants by injecting BrdU at E16 . 5 and analysing 24 hours later ( Figures 6F and S6F ) [29]–[30] . The proportion of cells which exit the cell cycle ( BrdU+KI67− ) in the total population of BrdU labelled cells was significantly decreased in Crb1Crb2 cKO retinas ( 12 . 3±0 . 7% ) compared to control ( 16 . 3±1 . 3% ) . However , the number of BrdU+KI67− cells per 100 µm is not significantly different ( 40 . 2±2 . 9 ) compared to control ( 35 . 3±1 . 8 ) . In summary , our data suggest that the increased population of late progenitor cells and late born cells is due to dysregulation of the cell cycle at E17 . 5 . We investigated which proliferative signalling pathway ( s ) might be involved in the overproliferation of the murine progenitors in Crb1Crb2 cKO retinas at E17 . 5 and in early postnatal days . The phospho-S6 ribosomal protein ( pS6RB ) , a downstream target of mTOR signalling , localised in the post-mitotic cells in the retina and the number of the pS6RB positive cells or pS6RB protein levels at E17 . 5 and P1 were unchanged in Crb1Crb2 cKO retinas , suggesting that mTOR signalling is not affected in the retina upon removal of CRB1 and CRB2 ( Figure S7D and data not shown ) . No differences were observed in the primary downstream targets Gli1 and Ptch1 of sonic hedgehog signalling ( Figure 7A ) . The downregulation of Smoothened and Gli2 might be due to a secondary effect of the loss of CRB proteins . The sonic hedgehog signalling seemed to not be directly involved in the increased number of progenitors . In E17 . 5 and P1 retinas , whereas no difference in the amount of cleaved active intracellular form of Notch1 protein was detected , the transcript levels of Notch1 and its primary downstream targets Hey1 and Heyl were reduced in Crb1Crb2 cKO compared to control ( Figures 7 and S7 ) . The Notch1 signalling might be affected following loss of CRB1 and CRB2 . The role of Wnt-β-catenin canonical signalling in retinal proliferation remains controversial . In E17 . 5 control retinas , P120-catenin and β-catenin localized mainly in the adherens junctions at the subapical region whereas in the Crb1Crb2 cKO the adherens junctions were disrupted and the catenins are membrane-associated ( Figure S7A–B , white arrowheads ) . At E17 . 5 , levels of P120-catenin proteins were increased in Crb1Crb2 cKO retinas , in contrast to β-catenin , whereas transcript levels were unchanged ( Figures 7 and S7E–F ) . Furthermore , we showed that the zinc finger protein Kaiso was expressed in E17 . 5 and P1 developing retinas , but that its protein levels were not affected in Crb1Crb2 cKO mice ( Figures 7 and S7E ) . The presence of Kaiso in the retina and the increased levels of P120-catenin proteins are of interest as the inhibition of Kaiso on Wnt signalling is blocked through its interaction with P120-catenin ( Figure 7E ) [31] , [32] . Only recently , YAP , the downstream effector of the Hippo pathway , has been reported to promote the proliferation of the murine progenitors in postnatal retinas , followed by downregulation around P5 during neuronal differentiation [33] . In control mice , YAP protein was detected in progenitor nuclei , overlapping with Chx10Cre-GFP localization ( Figure S7C ) . YAP localized also at the apical region where the adherens junctions and the CRB complex were located . In the Crb1Crb2 cKO retinas , YAP localized at the remaining subapical region and only in the cytoplasm of the progenitors ( Figure S7C ) . Phosphorylation of YAP causes its retention in the cytoplasm and binding to the adherens junctions , thus inactivating the protein [14] . Both YAP and phospho-YAP ( pYAP ) protein levels and the transcripts of the direct downstream targets genes CTGF and Cyr61 were reduced in Crb1Crb2 cKO retinas at E17 . 5 and P1 ( Figure 7B , D ) . The YAP signalling is affected by the loss of CRB1 and CRB2 .
One key element in the construction of the retina during development is the tight control of the proliferation and differentiation of the retinal progenitor cells by a combination of extrinsic and intrinsic influences [2] . In this study , we analyzed the effect of ablation of CRB1 and CRB2 in the murine retina and showed that levels of CRB protein control the lamination and proliferation of the progenitors . Complete loss of CRB1 and CRB2 proteins in the mouse retina mimics human LCA due to mutations in the CRB1 gene . The adherens junctions play a critical role in the migration of post-mitotic cells from the apical surface to their final destination [34] . Ganglion , bipolar and photoreceptor cells extend basal processes that guide nucleus translocation to their final destination . Bipolar and ganglion cells relinquish their apical attachment when translocation is complete whereas photoreceptors maintain adherens junctions with Müller glial cells . Amacrine and horizontal cells by contrast display active cellular migration without apical attachment by sensing their local environment [34] . Disruption of the apical adherens junctions/subapical region in Crb1+/−Crb2 cKO retinas at E15 . 5 leads to ectopic localization of some photoreceptor and bipolar cells in the ganglion cell layer and vice versa , ganglion , amacrine and bipolar cells in the outer nuclear layer . In Crb1Crb2 cKO mice , where the disruption occurs two days earlier , the lack of apico-basal axis leads to distribution of all the cell types in two nuclear layers and lack of a separate photoreceptor layer . Photoreceptor , ganglion and bipolar cells may undergo misguided migration due to the lack of apical attachment . The localization of the earliest born cells remains less affected , probably due to completion of migration prior to adherens junction disruption . Apart from the role in orchestration of migration , we suggest a direct role of CRB proteins in regulation of proliferation of retinal progenitors . Crb1 KO retinas do not show an obvious developmental phenotype [24] , and Crb2 cKO retinas show an increase in the number of progenitors only at P3 [22] . However , the Crb1Crb2 cKO showed increased number of mitotic cells from E15 . 5 to P10 and Crb1+/−Crb2 cKO retinas at E17 . 5 and P5 . Thus , the uncontrolled proliferation of progenitors is proportional to the lack of CRB1 and CRB2 proteins . A study on CRB-interacting protein PALS1 has shown that the CRB complex might be involved in the control of progenitor proliferation in the developing mouse cortex [9] . However , in mouse retinas , conditional knockout or knockdown of Pals1 does not lead to increased proliferation of retinal progenitor cells [35] , [36] . The role of CRB protein on the proliferation of the progenitors may be independent of PALS1 and involve other partners . Ablation of CRB1 and CRB2 proteins leads to an increased number of proliferating cells and abnormalities in the cell cycle . Hence , CRB proteins restrain the proliferation acting on the cell cycle machinery . Additionally , the lack of the apical CRB1 and CRB2 had an effect on the cell cycle exit potentially directing the decision to re-enter the cell cycle and explaining the increased number of progenitors . The reduced number of cells withdrawing the cell cycle may explain why retinal progenitor cells in Crb1Crb2 cKO retinas undergo several more cell cycles compared to control retinas , leading to an increase in number of late-born cell types and significant thickening of the retina . Here , we report that CRB1 and CRB2 act on the proliferation of the retinal progenitor cells through dysregulation of the proliferative signalling pathways such as Notch1 and YAP/Hippo . In addition , we report the presence of Kaiso in the retina and increased level of P120-catenin at E17 . 5 . We hypothesize that the lack of CRB1 and CRB2 leads to disruption of the adherens junction complex and release of available β- and P120-catenins in the cytoplasm and nuclei of progenitors . P120-catenin may retain Kaiso in the cytoplasm leading to the loss of inhibition of the Wnt target genes . Overexpression of P120-catenin and Kaiso has been linked to aberrant mitosis in cancer cells [37] , [38] . Lack of CRB proteins affects the YAP/Hippo pathway . Despite its direct role on proliferation , YAP promotes cell survival by inhibiting apoptotic pathways [14] . The decrease in YAP signalling at E17 . 5 and P1 in Crb1Crb2 cKO might explain the increase in apoptosis observed . Mutations in the CRB1 gene cause progressive autosomal-recessive retinitis pigmentosa and LCA . CRB1-LCA retinas are remarkably thick and lack distinct layers as detected by optical coherence tomography [20] . Mice lacking CRB1 function show limited and mild retinal disorganization in the inferior quadrant [24]–[27] . Prominent differences were found between the severe loss of retinal function in humans and the mild phenotype in mice [39] . In contrast , Crb2 cKO mice display a severe phenotype with progressive loss of photoreceptors and retinal activity mimicking CRB1-related retinitis pigmentosa [22] . Many genes involved in retinal dystrophies have been reported to show difference in temporal and spatial expression patterns and in their localization inside the retina [40] , [41] . Furthermore , compensation by other members of the same protein family occurs frequently in mice and humans such as the tumor suppressor genes during retinal development [42] . Further investigations on CRB1 and CRB2 would be needed to completely understand the difference between mice and humans . From Crb2 cKO , Crb1+/−Crb2 cKO and Crb1Crb2 cKO retina studies , the severity of the retinal disease is inversely proportional to the amount of CRB1 and CRB2 proteins which seemed to be critical for the development of the retina . As no genotype-phenotype correlation in CRB1 retinal dystrophies has been identified [43] , additional down-regulation of CRB2 function in human CRB1-mutant retinas might range from CRB1-retinitis pigmentosa to CRB1-LCA . Several polymorphisms in highly conserved residues have been identified in the CRB2 gene but not directly linked to retinal dystrophies [44] . Further investigations on possible mutations in CRB complex member genes in CRB1-LCA versus CRB1-RP patients might address the question of the genotype-phenotype correlation . Here , we report that Crb1Crb2 retinas display a thicker retina due to excessive proliferation of late-born retinal progenitor cells and also immature layering . Moreover , Crb1Crb2 and Crb1+/−Crb2 cKO animals show severe loss of retinal function . Crb1Crb2 and Crb1+/−Crb2 cKO retinas exhibit the characteristics of human CRB1-LCA retinopathies , and are therefore mouse LCA models for the development of therapeutic drugs .
Animal care and use of mice was in accordance with protocols approved by the Animal Care and Use Committee of the Royal Netherlands Academy of Arts and Sciences ( KNAW ) . All mice used were maintained on a 50% C57BL/6JOlaHsd and 50% 129/Ola genetic background . Animals were maintained on a 12 h dark/dim light cycle and supplied with food and water ad libitum . Crb1 KO mice [24] and Crb2F/FChx10CreTg/+ clone P1E9 ( Crb2 cKO ) generated previously [22] were crossed to generate Crb1+/−Crb2F/FChx10CreTg/+ ( Crb1+/−Crb2 cKO ) and Crb1−/−Crb2F/FChx10CreTg/+ ( Crb1Crb2 cKO ) . Crb1Crb2 cKO retinas were compared to littermate Crb1−/−Crb2F/F and Crb1−/−Crb2F/+Chx10CreTg/+ retinas and Crb1+/−Crb2 cKO to littermate Crb1+/−Crb2F/+ cKO . Chromosomal DNA isolation and genotyping were performed as previously described [22] . Scanning laser ophthalmoscopy ( SLO ) , spectral domain optical coherence tomography ( SD-OCT ) and electroretinography ( ERG ) measurements were performed at 1 , 3 , 6 and 12 month in 4 to 6 animals of each genotype . Electroretinograms were recorded binocularly as described previously [45] . Single-flash responses were obtained under scotopic ( dark-adapted overnight ) and photopic ( light-adapted with a background illumination of 30 cd/m2 starting 10 minutes before recording ) conditions . Single white-flash stimuli ranged from −4 to 1 . 5 log cd s/m2 under scotopic and from −2 to 1 . 5 log cd s/m2 under photopic conditions . Ten responses were averaged with inter-stimulus intervals of 5 s ( for −4 to −0 . 5 log cd s/m2 ) or 17 s ( for 0 to 1 . 5 log cd s/m2 ) . Retinal morphology of the anesthetized animals was visualized via SLO imaging with a HRA 1 and HRA 2 ( Heidelberg Engineering , Heidelberg , Germany ) according to previously described procedures ( Text S1 ) [46] . SD-OCT imaging was performed with a commercially available Spectralis HRA+OCT device from Heidelberg Engineering . This equipment features a broadband superluminescent diode at λ = 870 nm as low coherent light source ( Text S1 ) [47] . Eyes were collected from embryonic day E11 . 5 to 12M ( n = 3–5/age/group ) and were fixed at room temperature with 4% paraformaldehyde in PBS . Eyes were dehydrated in ethanol and embedded in Technovit 7100 ( Kulzer , Wehrheim , Germany ) and sectioned ( 3 µm ) . Slides were dried , counterstained with 0 . 5% toluidine blue and mounted under coverslips using Entellan ( Merk , Darmstadt , Germany ) . The thickness of the retina in Crb1Crb2 cKO mice from P8 to 12M was measured from the outer limiting membrane to the inner limiting membrane ( from top to bottom of Crb1Crb2 cKO retinas ) at exactly 1 mm apart from the optic nerve and the average of the ventral and dorsal measurement was compared to the dorsal measurement of control mice . E17 . 5 and 1M old mice were perfused with 4% paraformaldehyde , 2% glutaraldehyde in 0 . 1 M cacodylate buffer pH 7 . 4 . After the retinas were dissected free , they were post-fixed in 1% osmium tetroxide . Tissues were thoroughly rinsed and stained with 2% uranyl acetate in 70% ethanol . Samples were then dehydrated in a graded series of ethanol and embedded in epon 812 ( Polysciences ) . Ultrathin sections were examined with a Zeiss 912 electron microscope . Positive cells ( Table S1 ) from 20–30 representative sections of the whole retina from 3–5 different control or experimental animals were manually counted and corrected by the length of each section ( measured using ImageJ software fiji-win32 ) . Retina sections of E13 . 5 to P5 were stained with cleaved Caspase 3 ( cCasp3; marker for apoptotic cells ) and phospho-Histone H3 ( pH3; marker for M-phase mitotic cells ) antibodies . To examine the proportion of progenitors in S-phase , pregnant females were injected with BrdU ( 50 µg/g body weight ) at E17 . 5 and embryos were collected 30 min after BrdU injection . To examine the number of progenitors which exit the cell cycle , pregnant females were injected with BrdU at E16 . 5 and embryos were collected 24 h later . The number of BrdU+Ki67− cells represents the number of cells which have exited the cell cycle . The number of retinal cells at P14 was counted on 20–30 representative pictures of retinas stained with specific antibodies for each cell type . Cones , rods , horizontal , Müller and ganglion cells were counted using cone arrestin , rhodopsin , calbindin , Sox9/glutamine synthetase and Brn3B antibodies , respectively . Bipolar cells were counted using PKCα staining and Cre-GFP expression ( GFP is fused to the Cre in Chx10Cre mouse line ) . Subsets of amacrine cell types were stained using choline acetyltransferase ( ChAT ) , GABA , and GlyT1 antibodies . These experiments were performed similarly to [29] . Retinas from at least 4 controls and Crb1Crb2 cKO were isolated and mechanically dissociated with colagenase/DNAse I ( 370 U ) at 37°C . Cells were fixed with 4% paraformaldehyde in PBS for 5 minutes followed by fixation in ethanol 70% one hour at 4°C . Cells were labelled with KI67 antibody diluted 1/50 in PBS-0 . 5% Tween-20-BSA 0 . 1% ( PBS-TB ) overnight at 4°C followed by goat anti-mouse-Alexa 488 antibody diluted 1/500 in PBS-TB . DNA content was labelled with PBS-TB containing 100 µg/ml RNase A 30 minutes at 37°C followed by 100 µg/ml propidium iodide 30 minutes . Cells analysis was performed using the flow cytometer BD LSR Fortessa . See more details about the analysis in Text S1 . The E17 . 5 and P1 retinas from at least 3 Crb1Crb2 cKO or control littermate mice were isolated , homogenized and incubated on ice in 20 µL of lysis buffer ( 10% glycerol , 150 mM NaCl , 1 mM EGTA , 0 . 5% Triton x-100 , 1 mM PMSF , 1 . 5 mM MgCl2 , 10 µg/µL aprotin , 50 mM Hepes pH 7 . 4 and protease inhibitor cocktail ) . Retina extracts from 3 independent control and Crb1Crb2 cKO animals were fractionated by SDS-PAGE electrophoresis , using 4–12% precast gels ( NuPage Novex Bis-Tris Mini Gels , Invitrogen ) . After transfer to nitrocellulose membrane and blocking in 5% BSA in T-TBS buffer ( Tris-HCL 50 mM pH7 . 5 , 200 mM NaCl , 0 . 05% Tween-20 ) , the primary antibodies ( table S1 ) were diluted 1/1000 in T-TBS-5% BSA and incubated overnight at 4°C . After washing , they were incubated with the appropriate secondary antibodies ( conjugated to DyLight Dye-800 , Li-COR Odyssey or to cyanine 5 ) diluted 1/5000 in T-TBS buffer . After washing , the blots were then scanned using LI-COR Odyssey IR Imager . Densitometry of bands was performed in ImageJ . The densitometry for each band was subtracted to the background and normalized with GAPDH densitometry from the same sample . RNA was isolated from 3–6 control and Crb1Crb2 cKO retinas using TRIZOL reagent ( Gibco life technologies ) , according to the manufacturer manual , and after the final precipitation dissolved in RNase-free water . After genomic DNA degradation with RNase-free DNase I ( New England Biolabs ) , 1 µg of total RNA was reverse transcribed into first-strand cDNA with Superscript III Plus RNase H-Reverse Transcriptase ( Invitrogen ) and 50 ng random hexamer primers , during 50 min at 50°C in a total volume of 20 µl . To the resulting cDNA sample , 14 µl of 10 mM Tris , 1 mM EDTA was added . From all samples , a 1∶20 dilution was made and used for qPCR analysis . For this analysis , primer pairs were designed with a melting temperature of 60–62°C , giving rise to an amplicon of 80–110 bp . Real-time qPCR was based on the real-time monitoring of SYBR Green I dye fluorescence on a ABI Prism 7300 Sequence Detection System ( Applied Biosystems , Nieuwekerk a/d IJssel , The Netherlands ) . The PCR conditions were as follows: 12 . 5 µL SYBR Green PCR 2× mastermix ( Applied Biosystems ) , 20 pmol of primers , and 2 µl of the diluted cDNA ( ca 3 ng total RNA input ) . An initial step of 50°C for 2 min was used for AmpErase incubation followed by 15 min at 95°C to inactivate AmpErase and to activate the AmpliTaq . Cycling conditions were as follows: melting step at 95°C for 1 min , annealing at 58°C for 1 min and elongation at 72°C , for 40 cycles . At the end of the PCR run , a dissociation curve was determined by ramping the temperature of the sample from 60 to 95°C while continuously collecting fluorescence data . Non template controls were included for each primer pair to check for any significant levels of contaminants . Values were normalized by the mean of the 3 reference genes hypoxanthine-guanine phosphoribosyltransferase , elongation factor 1-a and ribosomal protein S27a . Normality of the distribution was tested by Kolmogorov-Smirnov test . Statistical significance was calculated by using t-test of 3–5 independent retinas ( 20 sections ) /genotype/age . Values are expressed as mean ± s . e . m . Values of *P<0 . 05 , **P<0 . 01 , ***P<0 . 001 were considered to be statistically significant . Calculations and graphs were generated using GraphPad Prism 5 . | Mutations in the human CRB1 gene lead to one of the most severe forms of retinal dystrophies , called Leber congenital amaurosis . Here , we report that ablation of CRB1 and the second family member CRB2 are crucial for proper retinal development . These mice display severe impairment of retinal function , abnormal lamination and thickening of the retina mimicking human Leber congenital amaurosis due to loss of CRB1 function . The thickening of the retina is due to increased cell proliferation during late retinal development leading to an increased number of late-born retinal cells . We describe in these CRB1 Leber congenital amaurosis mouse models the molecular and cellular events involving CRB proteins during the development of the retina . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2013 | Targeted Ablation of Crb1 and Crb2 in Retinal Progenitor Cells Mimics Leber Congenital Amaurosis |
Eukaryotic gene expression requires the coordinated action of transcription factors , chromatin remodelling complexes and RNA polymerase . The conserved nuclear protein Akirin plays a central role in immune gene expression in insects and mammals , linking the SWI/SNF chromatin-remodelling complex with the transcription factor NFκB . Although nematodes lack NFκB , Akirin is also indispensable for the expression of defence genes in the epidermis of Caenorhabditis elegans following natural fungal infection . Through a combination of reverse genetics and biochemistry , we discovered that in C . elegans Akirin has conserved its role of bridging chromatin-remodellers and transcription factors , but that the identity of its functional partners is different since it forms a physical complex with NuRD proteins and the POU-class transcription factor CEH-18 . In addition to providing a substantial step forward in our understanding of innate immune gene regulation in C . elegans , our results give insight into the molecular evolution of lineage-specific signalling pathways .
A fundamental part of innate immune responses is the regulated expression of defence genes . In both vertebrates and many invertebrates , including Drosophila , two of the key regulators controlling innate immunity are the Rel-homology domain ( RHD ) protein NF-κB and its protein partner IκB [1] . Across many species , NF-κB functions in concert with members of the conserved Akirin family ( InterPro: IPR024132 ) to govern the expression of defence genes [2] . More specifically , in vertebrates , Akirin2 bridges NF-κB and the SWI/SNF chromatin-remodelling complex , by interacting with IκB-ζ and the BRG1-Associated Factor 60 ( BAF60 ) proteins , downstream of Toll-like receptor ( TLR ) signalling [3 , 4] . In insects , an equivalent complex ( including Relish and the Brahma-associated proteins BAP55 and BAP60 in Drosophila ) governs antimicrobial peptide ( AMP ) gene expression upon infection by Gram-negative bacteria [4–6] . Infection of Caenorhabditis elegans by its natural pathogen Drechmeria coniospora [7] provokes an increase of AMP expression , but in the absence NF-κB and independently of the single TLR gene tol-1 [8 , 9] . It was therefore surprising that akir-1 , the sole nematode Akirin orthologue was identified in a genome-wide RNAi screen for genes involved in the regulation of nlp-29 [10 , 11] , an AMP gene that has been extensively used as a read-out of the epidermal innate immune response ( e . g . [12–16] ) . These previous studies have revealed surprising molecular innovation in the pathways that regulate AMP gene expression . To give one example , in other animal species , STAT-like transcription factors function in concert with Janus kinases ( JAKs ) . But in C . elegans , although there are no JAKs [17] , the 2 STAT-like proteins , STA-1 and STA-2 , function in antiviral [18] and antifungal immunity [19] , respectively . In the latter case , STA-2’s function appears to be modulated by a nematode-specific member of the SLC6 family , SNF-12 , acting downstream of the GPCR DCAR-1 and a p38 MAPK pathway to regulate nlp-29 expression [20] . Here , we undertook a focused study of akir-1 , to understand how AMP gene expression is governed and also to gain insight into the evolution of lineage-specific signalling pathways . We have been able to identify Akirin’s functional partners in C . elegans and thus reveal an unexpected molecular swap at the core of innate immune gene expression .
We previously conducted a semi-automated genome-wide RNAi screen [10] for genes that control the expression of the AMP reporter gene nlp-29p::gfp , following infection of C . elegans with D . coniospora [11] . In the screen , sta-1 was used as a negative control since its inactivation has no observable effect on nlp-29 reporter gene expression [19 , 20] . The candidates identified as positive regulators are collectively referred to as Nipi genes , for No Induction of Peptide expression after Infection . While akir-1 ( RNAi ) caused a robust reduction in the induction of nlp-29p::gfp expression after infection ( Fig 1A ) , it did not significantly affect the size of treated worms , nor the expression of the control col-12p::DsRed reporter transgene ( S1A Fig ) , identifying it as Nipi gene and suggesting that it could have a specific function in innate immunity . When we used an available deletion allele , akir-1 ( gk528 ) , which is predicted to be a molecular null , we recapitulated the effect on nlp-29p::gfp expression ( S1B Fig ) . This analysis was , however , hampered by the mutants’ pleiotropic phenotypes [21] , including a developmental delay and very marked decrease in the expression of the control reporter transgene ( S1C Fig ) . To avoid these confounding effects , and since RNAi of akir-1 gave robust and reproducible results , we used akir-1 ( RNAi ) for our subsequent analyses . The induction of nlp-29p::gfp expression upon D . coniospora infection is correlated to the infectious burden , which in turn reflects the propensity of spores to bind the worm cuticle [11 , 22] . There was no reduction in spore adhesion following akir-1 ( RNAi ) ( S1D Fig ) . Many genes required for the induction of nlp-29p::gfp expression after infection , including the GPCR gene dcar-1 [20] and the STAT transcription factor-like gene sta-2 [19] , are also required for the transcriptional response of C . elegans to physical injury . We found that akir-1 ( RNAi ) also abrogated reporter transgene expression upon wounding ( Fig 1A ) . One trigger for the epidermal innate immune response is the increase in the tyrosine metabolite HPLA that accompanies infection with D . coniospora . HPLA acts via DCAR-1 to activate a p38 MAPK signalling cascade [20] . This GPCR can also be activated by the HPLA tautomer DHCA [23] , a non-physiological ligand , which we use routinely as it is somewhat more potent and less toxic for worms than HPLA [20] . The induction of nlp-29p::gfp expression upon exposure to DHCA was greatly reduced upon akir-1 ( RNAi ) , to a degree that was comparable to dcar-1 ( RNAi ) ( Fig 1A ) . Together , these results suggest that akir-1 is required for the activation of the epidermal innate immune response , downstream of DCAR-1 . In contrast to the induction of nlp-29p::gfp provoked by infection , wounding or DHCA , the induction of nlp-29p::gfp observed after 6 hours exposure to moderate osmotic stress is DCAR-1 and p38 MAPK PMK-1-independent [20 , 24] . We found that akir-1 ( RNAi ) , like dcar-1 ( RNAi ) , did not affect the induction of reporter gene expression upon osmotic stress ( Fig 1A ) . Unlike dcar-1 ( RNAi ) , but similar to sta-2 ( RNAi ) [13 , 25] , akir-1 ( RNAi ) abolished the strong expression of nlp-29p::gfp seen in worms expressing a constitutively active form of the Gα protein GPA-12 ( GPA-12* ) ( Fig 1B ) . Together , these results support the specific role for akir-1 in innate immune signalling , placing it downstream of , or in parallel to , gpa-12 . To evaluate when and where akir-1 was expressed , we generated strains carrying a transcriptional reporter gene ( akir-1p::gfp ) . Consistent with previous studies [26] , expression of GFP was observed from the late embryo stage onwards , peaking at the late L4 stage . Expression was most evident in the lateral epithelial seam cells , the major epidermal syncytium , hyp7 , as well as in multiple head and tail neurons ( Fig 2A ) . The different components of the p38 MAPK pathway , including dcar-1 , gpa-12 and sta-2 , act in a cell autonomous fashion in the epidermis [13 , 19 , 20] . To determine whether this was also the case for akir-1 , we knocked down its expression in the epidermis , using the previously characterized strain IG1502 [11 , 20] . This greatly decreased nlp-29p::gfp expression upon infection , and also , as judged by qRT-PCR substantially reduced the induction of all the genes of the nlp-29 locus , while not affecting their constitutive expression ( Figs 2B , 2C & S2A and S2B ) . Although low levels of RNAi silencing in non-epidermal tissues have been reported for the strain JM43 [27] from which IG1502 was derived , overall our results suggest that akir-1 acts in a cell autonomous manner in the epidermis to modulate AMP gene expression upon infection . To test the functional relevance of these observations , we assayed the effect of akir-1 ( RNAi ) on the resistance of C . elegans to D . coniospora infection . Compared to the negative control , sta-1 ( RNAi ) , knocking down akir-1 principally in the epidermis ( with strain IG1502 ) was associated with a significant reduction in survival ( Fig 3 ) . Interpretation of this result is complicated by the fact that the same RNAi treatment also caused a significant decrease in longevity on non-pathogenic E . coli ( S2C Fig ) , so the reduced resistance to D . coniospora infection is not likely to result solely from the observed diminution in AMP gene expression . AKIR-1 is a member of the Akirin family . While invertebrates generally have just one Akirin protein , vertebrates can have up to 8 [28] . In mice and humans there are 2 paralogues [29] . AKIR-1 is much more similar to murine Akirin2 than Akirin1 ( 32 . 8% vs 10 . 9% overall sequence identity by BLASTP ) . While Akirin1 has been proposed to be involved in muscle regeneration and cell chemotaxis [30] , as mentioned above , Akirin2 has a conserved function controlling innate immune gene expression through its interaction with BAF60/BAP60 and more generally the SWI/SNF chromatin-remodelling complex [2 , 3 , 5] . We therefore used RNAi to knock down the expression of components of the nematode SWI/SNF chromatin-remodelling complexes , but also of the Nucleosome Remodelling and histone Deacetylase ( NuRD ) and MEC complexes , as well as related genes [31] . With the exception of swsn-1 , which caused pleiotropic development defects and affected expression of the control col-12p::DsRed reporter transgene , consistent with our previous results [11] , none of the other SWI/SNF genes appeared to be required for nlp-29p::gfp expression ( S3A and S3B Fig ) . On the other hand , knocking down 6 genes dcp-66 , hda-1 , let-418 , lin-40 , lin-53 , and mep-1 , largely , and specifically , blocked the expression of nlp-29p::gfp upon D . coniospora infection ( Figs 4A , S3C and S3D ) . Of note , the 3 RNAi clones that gave the most robust Nipi phenotype , those targeting hda-1/HDAC , lin-40/MTA and dcp-66/p66 , had been identified in the previous genome-wide screen [11] . These 3 genes encode core subunits of the two canonical chromatin-remodelling ( NuRD ) complexes in C . elegans . The two complexes also share LIN-53/RbAp , but differ in their Mi-2 orthologs , having either LET-418 or CHD-3 . LET-418 but not CHD-3 , can interact with the Krüppel-like protein MEP-1 in a distinct complex , the MEC complex [31 , 32] . Our results suggest that both the LET-418-containing NuRD complex and the MEC complex are involved in defence gene expression . The 6 RNAi clones also strongly abrogated the elevated expression of nlp-29p::gfp normally seen in worms expressing GPA-12* , in clear contrast to chd-3 ( RNAi ) ( Fig 4B ) . RNAi with the same 6 clones also blocked the induction of reporter gene expression in the strain IG1502 ( S4A Fig ) . Under these conditions , ( i . e . RNAi principally in the epidermis ) , the induction of expression of 5 endogenous nlp AMP genes normally provoked by D . coniospora infection was also severely compromised ( S4B Fig ) . In contrast , there was no evidence for a role for HDA-2 , RBA-1 or EGL-27 ( Fig 4A ) , the respective homologues of the core subunits HDA-1 , LIN-53 and LIN-40 , that do not form part of either of the 2 biochemically characterized NuRD complexes in C . elegans [31] . Together these results suggest that both the LET-418 containing NuRD complex and the MEC complex act cell autonomously in the epidermis , downstream of ( or in parallel to ) gpa-12 , to control nlp AMP gene expression upon D . coniospora infection . Further , they suggest that in contrast to what has been described in flies and mammals , AMP gene expression is not dependent upon the SWI/SNF complex in C . elegans and raised the possibility that AKIR-1 might function together with the NuRD and MEC chromatin remodelling complexes . To address this possibility , we took an unbiased biochemical approach to identify the in vivo protein partners of AKIR-1 . From a mixed-stage population of worms carrying a functional akir-1p::AKIR-1::gfp construct ( S5 Fig ) , we pulled down AKIR-1::GFP by immunoprecipitation from whole worm extracts and subjected the purified proteins to mass spectrometry analysis ( Fig 5A ) . Remarkably , all of the proteins that make up the NuRD and MEC complexes were found , i . e . LIN-40 , LIN-53 , LET-418 , HDA-1 , MEP-1 and DCP-66 . The first 3 , together with 6 other known or putative DNA-binding or transcription-related proteins [33] , including CEH-18 , were among the 53 high confidence protein partners ( Fig 5B and 5C ) . Significantly , 9 of these 53 candidates ( p = 2 . 7x10-7 ) , again including LIN-40 and CEH-18 , had been identified in our previous RNAi screen for regulators of nlp-29p::gfp [11] . In the complete list of close to 1400 protein partners , there were a further 111 hits ( S1 Table ) , so overall , fully 35% of the known candidate regulators of AMP gene expression ( Nipi genes ) were recovered through this independent biochemical approach when one includes the lower confidence candidates . When we compared the list of 53 high confidence candidate AKIR-1 binding proteins with the 190 proteins identified as potential interactors of the nematode BAP60 homologue SWSN-2 . 2 [34] , we found only 3 common proteins , none of which have been characterized as being specific regulators of nlp-29p::gfp expression ( i . e . found as Nipi genes [11]; S2 Table ) . Using a less stringent list of 190 potential AKIR-1 binding proteins extended the overlap to 11 common partners , with just 2 corresponding to Nipi genes ( arp-1 and dlst-1 that encode an actin-related protein , and a predicted dihydrolipoyllysine succinyltransferase , respectively ) . The 11 common proteins did , however , also include SWSN-1 and SWSN-4 ( S2 Table ) . This suggests that in some contexts , but not during its regulation of AMP gene expression , AKIR-1 might interact with the SWI/SNF complex . This functional dichotomy was further reinforced by examining the genes differentially regulated following knockdown of both swsn-2 . 2 and its paralogue ham-3 [34] . There were only a very small number ( 33/1521 ) of genes characterized as up-regulated by D . coniospora infection and among them , there were none encoding AMPs ( S2 Table ) . Together these results support the idea that there is a specific AKIR-1-containing protein complex involving the NuRD and MEC chromatin remodellers , required for AMP gene regulation . We therefore focused on the interaction between AKIR-1 and these chromatin-remodelling factors . We used available antibodies to validate the NuRD and MEC complex proteins LET-418 and HDA-1 as AKIR-1-interactors . Both could be detected together with AKIR-1::GFP , in samples from infected and control worms , derived from the strain used for mass spectrometric analysis , and importantly also from a strain of worms carrying a single copy akir-1::gfp insertion in the wild-type background ( Fig 6A ) . In the latter strain , AKIR-1::GFP exhibited an predominantly nuclear localization , including in the epidermis ( S6 Fig ) . There was a clear reduction in the quantity of LET-418 that was pulled down with AKIR-1::GFP from the samples of infected worms compared to non-infected worms . The same tendency was observed for HDA-1 . These results strongly support the existence of a physical complex between AKIR-1 and the NuRD and MEC complexes in uninfected worms that changes following infection . Seeking to confirm the potential physical interaction between AKIR-1 and CEH-18 , we made use of a strain expressing both AKIR-1::GFP and a doubly-tagged version of CEH-18 ( CEH-18::GFP::3xFLAG; [35] ) . As the AKIR-1::GFP construct is a single-copy insert its expression is expected to be close to that of the endogenous protein; it was not detectable in the total protein extract . When we analysed the complex that was pulled-down together with CEH-18 , however , we were readily able to detect AKIR-1::GFP ( Fig 6B ) , lending further support to the proposed AKIR-1/NuRD/CEH-18 complex . As mentioned above , we previously reported a role for ceh-18 in the regulation of nlp-29p::gfp [11]; the results for 6 independent experiments assaying the effect of ceh-18 ( RNAi ) on reporter gene expression following D . coniospora infection are available at http://bioinformatics . lif . univ-mrs . fr/RNAiScreen ( clone sjj_ZC64 . 3 ) . We were able to confirm this effect using a ceh-18 mutant strain ( IG1714 ) carrying the frIs7 reporter gene: expression was abrogated upon infection compared to the wild-type ( Fig 7A ) . We also demonstrated by qRT-PCR that ceh-18 was required for the increased expression of several nlp genes after infection ( Fig 7B ) . In common with sta-2 ( RNAi ) , knocking down ceh-18 by RNAi did not reduce the induction of nlp-29p::gfp provoked by osmotic stress , but did strongly abrogate the elevated reporter gene expression normally seen in worms expressing GPA-12* . RNAi against ceh-18 also significantly reduced the induction of reporter gene expression in the IG1502 strain ( Fig 7A ) . This is the same pattern of phenotypes as seen with akir-1 ( RNAi ) ( Figs 1A , 1B and 2B ) . The non-redundant function of CEH-18 resembles that of its binding partner , AKIR-1 , supporting the hypothesis that they act together in a common complex . When we assayed the effect of ceh-18 ( RNAi ) on the resistance of C . elegans to D . coniospora infection , we observed a significant reduction in survival of IG1502 that was more pronounced than that seen upon akir-1 ( RNAi ) or sta-2 ( RNAi ) ( Fig 7C ) . Unlike akir-1 ( RNAi ) that reduces worm longevity ( S2C Fig ) , ceh-18 ( RNAi ) extends lifespan [36] . These results therefore support a specific role for ceh-18 in innate defence against D . coniospora infection , potentially via a regulation of immune gene expression . We then addressed the question of whether AKIR-1 ( and by extension CEH-18 ) has the potential to interact with DNA , by chromatin immunoprecipitation ( ChIP ) , using the strain of worms carrying a single copy akir-1::gfp insertion . We first tested the specificity of the ChIP by assaying the occupancy of AKIR-1::GFP on the promoter of act-1 , an actin-encoding gene that is used as a control for qRT-PCR since its expression is unaffected by D . coniospora infection [37] . We detected a low and constant occupancy of the act-1 promoter using samples from uninfected or infected populations of worms ( Fig 8A ) . We take this to reflect non-specific binding . We then assayed the capacity of AKIR-1::GFP to associate with DNA fragments corresponding to the promoters of 3 AMP genes , or to their 3’ UTRs . For all 3 AMP genes assayed , binding to the 3’ UTRs appeared to be non-specific . On the other hand , we observed markedly higher binding to the promoter regions relative to the 3’ UTRs . The 3 genes , nlp-29 , nlp-31 and nlp-34 are strongly induced by D . coniospora infection [24] . There was a >10-fold higher occupancy of AKIR-1::GFP on DNA in the samples from non-infected worms relative to the infected ones ( Fig 8A ) . Taken together , our results support a model , discussed further below , in which AKIR-1 plays 2 indissociable roles . First , in association with the NuRD and MEC complexes , it binds to the promoters of defence genes and potentially recruits transcription factors including CEH-18 . Our results suggest that this does not influence the STA-2-independent basal expression of nlp genes . Secondly , AKIR-1 and its protein partners negatively regulate the STA-2-dependent transcription of defence genes , with this repression being relieved upon their removal from their binding sites following infection ( Fig 8B ) . This could explain why loss of AKIR-1 ( or CEH-18 ) function is associated with an incapacity to express AMP genes upon infection .
We are interested in the mechanisms involved in the regulated expression of nlp-29 , a representative of one class of AMP genes in C . elegans [24 , 38 , 39] . In common with many other AMP genes , the level of nlp-29 mRNA rapidly increases following either physical injury or infection with the nematophagous fungus D . coniospora . In both cases , the integrity of the cuticle and underlying epidermis is compromised . Although we have advanced in our understanding of how this triggers the innate immune response , and how the associated signal transduction pathway is organized , the details of the transcriptional regulation remain to be fully elucidated . We previously identified ELT-3 , an epidermis specific GATA factor as being partially required , in a generic fashion , for nlp-29 expression [24] . The STAT-like transcription factor STA-2 plays a more specific role . It is largely dispensable for the constitutive expression of nlp-29 , but is required for its induction upon wounding and infection [13 , 19] . In this work , we have made a considerable step forward by characterizing the key role of AKIR-1 and identifying its protein partners , including the NuRD and MEC complex chromatin remodelling proteins and the transcription factor CEH-18 . All these factors are required for AMP gene expression after fungal infection of the nematode epidermis . CEH-18 is a member of the POU subgroup of the Hox class of homeodomain transcription factors . These are regulators of cellular proliferation , differentiation and migration across species . In C . elegans , ceh-18 has primarily been characterized for its negative regulatory role in a somatic gonadal sheath cell-dependent pathway that governs oocyte meiotic arrest [40] . It has not been implicated in innate immunity previously . Among POU transcription factor genes in Drosophila , Dfr/Vvl , Pdm1/nub and Pdm2/miti were identified in a screen for transcriptional regulators that bind the NF-κB-family transcription factor Dif; they are important for the control of AMP gene expression [41–43] . The corresponding proteins were not , however , identified as physical interactors of Akirin in Drosophila [5] . Thus if POU transcription factors do have a conserved role in regulating AMP gene expression , their precise function must have evolved , especially as nematodes lack Rel-family transcription factors [9] . Another transcription factor , LIN-40 , a GATA protein , NuRD complex component and one of two C . elegans homologs of human metastasis-associated protein MTA1 , was the top hit among AKIR-1’s binding partners . Recent genome-wide ChIP-seq data from the “model organism encyclopedia of regulatory networks” project ( via www . encodeproject . org ) , revealed the presence of LIN-40 at the nlp-29 promoter ( binding site peak , V: 3984375 ) in DNA from uninfected young adult worms . This independent line of evidence supports the presence of a NuRD/AKIR-1 complex within this AMP gene cluster in the absence of infection . Consistent with our current understanding of its mechanism of action , we did not find STA-2 among the AKIR-1-interacting proteins . In the simplest model , a complex of AKIR-1 , CEH-18 and the NuRD/MEC chromatin remodelling proteins is recruited to the nlp locus and opens it , but represses gene expression . Upon infection , the chromatin structure allows activated STA-2 access to the AMP gene promoters , and removal of the repressive NuRD/AKIR-1/CEH-18 complex permits gene expression . It is noteworthy that 3 of the 53 high-confidence AKIR-1 interactors are implicated in ubiquitin-mediated protein turn-over , and that in preliminary tests , in vitro ubiqutination activity could be detected within the purified AKIR-1 protein complex specifically after infection , not before . Chromatin remodelling at the promoters of immune genes can prime them for enhanced activation [44] . Many AMP genes in C . elegans , as in other species , are arranged in genomic clusters [24] . AKIR-1-dependent modification of chromatin structure offers the possibility of coordinating a rapid increase in the expression of neighbouring AMP genes , potentially important when faced with a fast-growing pathogen like D . coniospora . Akirin functions together with the SWI/SNF complex in other species . Although we excluded a role for the C . elegans SWI/SNF complex in nlp-29 expression , we did identify some SWI/SNF complex proteins , including SWSN-1 , -3 , -4 and -6 , among the potential AKIR-1 binding partners . These were found through an unbiased whole-organism approach; it is likely that we sampled separate complexes from different tissues . Indeed AKIR-1 is known to be expressed widely and also to have essential functions in development; it is necessary for synaptonemal complex ( SC ) disassembly during meiosis [21] . These different candidates therefore merit investigation in the context of AKIR-1’s other functions . It would also clearly be of interest to attempt to recover AKIR-1 interactors specifically from the epidermis , but this is a technical feat beyond the current study . SC disassembly involves a conserved RAS/ERK ( Extracellular signal-regulated kinase ) MAPK cascade . Interestingly , the same pathway is required for the response of C . elegans to infection by the Gram-positive bacterium Microbacterium nematophilum [45] . Within the rectal epithelium , it cooperates with a Gαq signalling pathway to trigger changes in cell morphology . At the same time , in motor neurons , Gαq functions independently of RAS signalling to influence nematode behaviour in the presence of M . nematophilum [46] . Following infection , it also acts in the pharynx to regulate , non-cell autonomously , defence gene expression in the intestine [47] . These instances illustrate how the physiological response to infection is a mélange of interconnected signal transduction cascades . Further studies will be required to establish whether akir-1 is required for any or all of these processes . Across species , MAPKs act as regulators of chromatin structure . In yeast , the p38-related MAPK Hog1 physically interacts with the RSC chromatin-remodelling complex . This association is increased upon osmotic stress and is thought to direct the complex to bind osmo-responsive genes , changing nucleosome structure , increasing RNA polymerase II binding and causing a burst of transcription [48] . In vertebrates , the SWI/SNF subunit BAF60 can be phosphorylated by p38 MAPK , also targeting it to specific loci [49] . It is not yet clear whether PMK-1 directly phosphorylates AKIR-1 or NuRD/MEC complex proteins; it was not found as a physical interactor of AKIR-1 . The p38 MAPK PMK-3 on the other hand was . RNAi of pmk-3 does not inhibit nlp-29 expression [11] . Notably , pmk-3 does participate in adult axon regeneration , in a p38 pathway that while sharing some elements with the epidermal innate immune pathway [50] is clearly distinct . Our results therefore raise the possibility that AKIR-1 plays a role in axon regeneration , in association with PMK-3 . We established that the SWI/SNF complex does not play a major part in modulating AMP gene expression in the epidermis . Rather the NuRD and MEC complexes , in a physical complex with AKIR-1 and CEH-18 play an essential role . One possible cause of this evolutionary re-wiring of a regulatory circuit could be the loss of NF-κB from nematodes , which has also led to a restructuring of the TLR pathway [51] . The precise evolutionary trajectories that led to these changes can only be the subject of speculation , but these lineage-specific adaptations likely reflect the extreme selective pressure that is exerted by pathogens . This plasticity is even more remarkable when one considers the essential developmental processes that many of these factors are involved in , limiting the degree of change that can be tolerated . In conclusion , as well as substantially advancing our understanding of immune defences in C . elegans , our results illustrate how an organism can evolve novel molecular mechanisms to fight infection while conserving an overall regulatory logic .
All strains were maintained on nematode growth media ( NGM ) and fed with E . coli strain OP50 [52] . The wild-type reference strain is N2 Bristol . Strains carrying akir-1 ( gk528 ) , ceh-18 ( mg57 ) , rde-1 ( ne300 ) and the transgene [ceh-18::TY1::GFP::3xFLAG] ( OP533 ) were obtained from the Caenorhabditis Genetics Center ( CGC ) . Double mutants and strains containing multiple independent transgenes were generated by conventional crossing . The strains IG274 ( containing frIs7[nlp-29p::gfp , col-12p::DsRed] IV ) and IG1389 ( containing frIs7 and frIs30[col-19p::GPA-12* , unc-53pB::gfp] I ) have been described elsewhere [13 , 38] . We recently validated the use of strains carrying col-19p::GPA-12* as a model for the inductive part of the epidermal innate immune response [53] . Full genotypes of the transgenic strains are given below . The akir-1p::AKIR-1::gfp construct contains 1 . 6 kb of genomic sequence upstream of the start codon of E01A2 . 6 and was obtained by PCR fusion [54] using primers JEP2091 , JEP2092; JEP2108 , JEP568 , JEP569 and JEP570 and using genomic DNA and the vector pPD95 . 75 as templates . Microinjections were first performed using 20 ng/μl of the construct and the coinjection marker myo-2p::mCherry at a concentration of 80 ng/μl into N2 animals . Although transgenic strains were readily obtained , the observed fluorescence declined rapidly across successive generations ( OZ unpublished observations ) . Since mutants in the Argonaute gene rde-1 do not exhibit transcriptional silencing of transgenes in the soma [55] , we then performed the same microinjection but used rde-1 ( ne300 ) animals . From three independent transgenic lines generated , one was subsequently integrated using X rays and outcrossed three times with rde-1 ( ne300 ) generating IG1550 rde-1 ( ne300 ) V; frIs32[akir-1p::AKIR-1::gfp; myo-2p::mCherry] . This strain maintained transgene expression constantly across multiple generations . All additional strains carrying the frIs32[akir-1p::AKIR-1::gfp; myo-2p::mCherry] transgene were obtained by conventional crosses . The akir-1p::gfp construct was generated by PCR fusions using primers: JEP2091 , JEP2092 , JEP2095 , JEP2096 , JEP569 and JEP570 using genomic DNA , and the vector pPD95 . 75 as templates . Microinjections were performed using 20 ng/μl of the construct of interest and the co-injection marker pNP135 ( unc-53pB1::DsRed ) at a concentration of 80 ng/μl in WT animals . Three independent lines were obtained and IG1485 was retained for further study . The single copy strain IG1654 carrying AKIR-1::GFP ( wt; frSi12[pNP157 ( akir-1p::AKIR-1::GFP ) ] II ) was obtained by CRISPR in N2 worms at the location of the ttTi5605 Mos1 insertion [56] and subsequent excision of the self-excising cassette ( SEC ) [57] . pNP157 was made by Gibson cloning from a vector containing the SEC and recombination arms for ttTi5605 ( pAP087 , kindly provided by Ari Pani ) flanking akir-1p::AKIR-1::GFP , amplified from the strain IG1550 , and the 3’UTR of akir-1 , amplified from the wild type strain . The full locus akir-1p::AKIR-1::GFP::3’UTR_akir-1 was confirmed by sequencing ( primers available upon request ) . Microinjections were performed using pNP157 ( akir-1p::AKIR-1::GFP ) at 10ng/μl , pDD122 ( sgRNA ttTi5605 ) at 40 ng/μl ( kindly provided by Ari Pani ) , pCFJ90 ( myo-2p::mCherry ) at 2 . 5ng/μl , pCFJ104 myo-3p::mCherry at 5ng/μl and #46168 ( eft-3p::CAS9-SV40_NLS::tbb-2 3'UTR; Addgene ) at 30 ng/μl . Roller worms that did not display red fluorescence were selected then heat shocked to remove the SEC by FloxP as described [57] . IG274 wt; frIs7[nlp-29p::gfp , col-12p::DsRed] IV [24] IG1389 wt; frIs7 IV; frIs30[col-19p::GPA-12* , pNP21 ( unc-53pB::gfp ) ] I [13] IG1485 wt; frEx547[akir-1p::gfp; unc-53p::DsRed] IG1502 rde-1 ( ne219 ) V; Is[wrt-2p::RDE-1; myo-2p::mCherry]; frIs7 IV [20] IG1550 rde-1 ( ne300 ) V; frIs32[akir-1p::AKIR-1::gfp; myo-2p::mCherry] IG1555 wt; frIs32[akir-1p::AKIR-1::gfp; myo-2p::mCherry] IG1575 akir-1 ( gk528 ) I; rde-1 ( ne300 ) V; frIs32[akir-1p::AKIR-1::gfp; myo-2p::mCherry] IG1577 akir-1 ( gk528 ) I; frIs32[akir-1p::AKIR-1::gfp; myo-2p::mCherry] IG1654 wt; frSi12[pNP157 ( akir-1p::AKIR-1::GFP ) ] II IG1665 wt; frSi12[pNP157 ( akir-1p::AKIR-1::GFP ) ] II; wgIs533[CEH-18::TY1::GFP::3xFLAG + unc-119 ( + ) ] IG1714 ceh-18 ( mg57 ) X; frIs7[nlp-29p::gfp , col-12p::DsRed] IV The sequences of the primers used are: JEP568: agcttgcatgcctgcaggtcgact , JEP569: aagggcccgtacggccgactagtagg , JEP570: ggaaacagttatgtttggtatattggg , JEP2091: gatgaacaccgatagagagcaactg JEP2092: gctctcgcggaaatgacgaat JEP2095: agtgaaaagttcttctcctttactcattttacttctgaaagaaataatttgtggtta JEP2096: atgagtaaaggagaagaacttttcact JEP2108: agtcgacctgcaggcatgcaagctggagaggtacgaataggaatagtcat RNAi clones were from the Ahringer [58] and the Vidal [59] RNAi libraries . Insert sequences were verified and target genes confirmed using Clone Mapper [60] before use . To limit RNAi principally to the epidermis , we used the strain IG1502 rde-1 ( ne219 ) ;Is[wrt-2p::RDE-1; myo-2p::mCherry];frIs7[nlp-29p::gfp , col-12p::DsRed] [20] . Worms were transferred onto RNAi plates at the L1 stage . Infections , epidermal wounding and osmotic stress or dihydrocaffeic acid ( DHCA ) treatments were performed as previously described [10 , 11 , 20 , 25] . For the experiments reported in Figs 3 and S2C , 50–70 worms at the L1 stage were cultured on the appropriate RNAi bacterial clone at 25°C , and then ( for Fig 3 ) infected at the young adult stage for 1h with D . coniospora and transferred to fresh RNAi plates and cultured at 15°C ( to accentuate differences in survival [61] ) , or transferred directly to fresh RNAi plates and cultured at 20°C ( for S2C Fig ) . In both cases , the surviving worms were counted every day as described elsewhere [62] . For the experiments reported in Fig 7 , worms at the L1 stage were cultured on the appropriate RNAi bacterial clone at 25°C for 32 hours and then infected with D . coniospora overnight . Groups of 20–30 worms were then transferred to wells in 12-well plates ( 3 wells per condition ) , and images of each well collected automatically at regular intervals ( roughly every 20 minutes ) using a custom system that will be described elsewhere . The images were then examined , and worms scored as dead when they no longer showed sign of any movement between images . Statistical analyses used one-sided log rank test within Prism ( Graphpad software ) . Expression of nlp-29p::gfp reporter was quantified with the COPAS Biosort ( Union Biometrica ) . Generally , a minimum of 80 synchronized worms were analyzed for size ( TOF ) , extinction ( EXT ) , green ( GFP ) and red ( dsRed ) fluorescence . The ratio Green/TOF was then calculated to normalize the fluorescence . When only mean values for ratios are presented , the values for the different samples within a single experiment are normalized so that the control worms ( WT ) had a ratio of 1 . As discussed more extensively elsewhere [38] , standard deviations are not an appropriate parameter and are not shown on figures with the Biosort . The results shown are representative of at least 3 independent experiments . RNA preparation and quantitative RT-PCR were done as described [24] . Results were normalized to those of act-1 and were analyzed by the cycling threshold method . Control and experimental conditions were tested in the same ‘run’ . Each sample was normalized to its own act-1 control to take into account age-specific changes in gene expression . Primers used for qRT-PCR are for: act-1: JEP538 ccatcatgaagtgcgacattg JEP539 catggttgatggggcaagag; dcar-1: JEP2030 cctacgctatttggtgcattggct JEP2031 tgcaccgaatcaccagaaacag; nlp-27: JEP965 cggtggaatgccatatggtg JEP966 atcgaatttactttccccatcc; nlp-28: JEP967 tatggaagaggttatggtgg JEP968 gctaatttgtctactttcccc; nlp-29: JEP952 tatggaagaggatatggaggatatg JEP848 tccatgtatttactttccccatcc; nlp-30: JEP948 tatggaagaggatatggtggatac JEP949 ctactttccccatccgtatcc; nlp-31: JEP950 ggtggatatggaagaggttatggag JEP953 gtctatgcttttactttcccc; nlp-34: JEP969 atatggataccgcccgtacg JEP970 ctattttccccatccgtatcc; Affinity co-purification assays were performed as previously described [63] with minor modifications . From 3 independent mixed stage cultures of control rde-1 ( ne300 ) or rde-1 ( ne300 ) ; akir-1 ( gk528 ) worms carrying akir-1p::AKIR-1::gfp , samples were harvested , yielding about 4 g of flash-frozen pellets of C . elegans . In parallel , samples were also prepared from equivalent cultures that had been infected with D . coniospora for 16 h at 25°C . Frozen samples were defrosted in a presence of lysis buffer ( 0 . 1% Nonidet P-40 Substitute , 50 mM Tris/HCl , pH 7 . 4 , 100 mM KCl , 1 mM MgCl2 , 1 mM EGTA pH 8 . 0 , 10% glycerol , protease inhibitor cocktail ( Roche ) , 1 mM DTT ) and sonicated on Diagenode ( cycle: 0 . 5 s , amplitude: 40–45% , 10 sessions , interval between sessions: 30 s ) . After sonication , Nonidet P-40 Substitute was added up to 1% and the lysates were incubated with head over tail rotation at 4°C for 30 min , followed by centrifugation at 20 , 000° g for 20 min at 4°C . Cleared lysate was then collected and split into either the anti-GFP agarose beads or the blocked control beads ( 40–50 μl , NanoTrap , Chromotek ) ( Fig 5A ) . After head over tail rotation at 4°C for 60–90 min , the beads were washed once with lysis buffer containing 0 . 1% Nonidet P-40 Substitute , followed by two washings in each of the buffers I ( 25 mM Tris-HCl , pH 7 . 4 , 300 mM NaCl , 1 mM MgCl2 ) then buffer II ( 1 mM Tris-HCl , pH 7 . 4 , 150 mM NaCl , 1 mM MgCl2 ) . Proteins were eluted twice by orbital shaking in 100 μl of 6 M urea followed by ethanol precipitation . Precipitated proteins were resolubilized in 6 M urea/2 M thiourea buffer ( 10 mM HEPES , pH 8 . 0 ) . Reduction and alkylation of proteins were then performed at room temperature , followed by digestion in solution sequentially using lysyl endopeptidase ( Lys-C , Wako ) for 3 h and trypsin ( Promega ) overnight as previously described [64] . Peptides were purified by solid phase extraction in C18 StageTips [65] . Mixed stage worms ( IG1665 ) carrying AKIR-1::GFP and CEH-18::GFP::FLAG were harvested on ice and lysed in lysis buffer ( 0 . 5% Nonidet P-40 Substitute , 50 mM Tris/HCl , pH 7 . 4 , 100 mM KCl , 1 mM MgCl2 , 1 mM EGTA , 10% glycerol , protease and phosphatase inhibitor cocktail ( Roche ) , 1 mM DTT ) , subjected to three cycles of freeze and thaw and sonicated on Diagenode ( cycle: 0 . 5 s , amplitude: high , 5 min , interval between sessions: 30 s ) . Lysates were cleared by centrifugation . 200 μg of total protein was used for each immunoprecipitation: with anti-Flag ( M2 clone , Sigma ) , and anti-HA as the unrelated control antibody ( clone HA . 11 ) . Co-immunobound proteins were precipitated using Dynabeads Protein G matrix ( ThermoFisher ) and eluted in SDS buffer ( 1% SDS in TE , 150 mM NaCl ) . Immunoprecipitates were then resolved on a gel and subjected to Western blot analysis as described below . Peptides were separated in an in-house packed analytical column ( inner diameter: 75 μm; ReproSil-Pur C18-AQ 3-μm resin , Dr . Maisch GmbH ) by online nanoflow reversed phase chromatography through an 8–50% gradient of acetonitrile with 0 . 1% formic acid ( 120 min ) . The eluted peptides were sprayed directly by electrospray ionization into a Q Exactive Plus Orbitrap mass spectrometer ( Thermo Scientific ) . Mass spectrometry measurement was carried out in data-dependent acquisition mode using a top10 sensitive method with one full scan ( resolution: 70 , 000 , target value: 3 × 106 ) followed by 10 fragmentation scans via higher energy collision dissociation ( HCD; resolution: 35 , 000 , target value: 5 × 105 , maximum injection time: 120 ms , isolation window: 4 . 0 m/z ) . Precursor ions of unassigned or +1 charge state were rejected for fragmentation scans . Dynamic exclusion time was set to 30 s . Raw data files were processed by MaxQuant software package ( version 1 . 5 . 5 . 0 ) [66] using Andromeda search engine [67] . Spectral data were searched against a target-decoy database consisting of the forward and reverse sequences of WormPep release WS254 ( 28 , 071 entries ) , UniProt E . coli K-12 proteome release 2016_02 ( 4 , 314 entries ) and a list of 245 common contaminants . Trypsin/P specificity was selected . Carbamidomethylation of cysteine was chosen as fixed modification . Oxidation of methionine and acetylation of the protein N-terminus were set as variable modifications . A maximum of 2 missed cleavages were allowed . The minimum peptide length was set to be 7 amino acids . At least one unique peptide was required for each protein group . False discovery rate ( FDR ) was set to 1% for both peptide and protein identifications . Protein quantification was performed using the LFQ label-free quantification algorithm [68] . Minimum LFQ ratio count was set to one . Both the unique and razor peptides were used for protein quantification . The “match between runs” option was used for transferring identifications between measurement runs allowing a maximal retention time window of 0 . 7 min . All raw mass spectrometry data have been deposited in the PRIDE repository with the dataset identifier PXD008074 . Statistical data analysis was performed using R statistical software . Only proteins quantified in at least two out of the three GFP pull-down replicates ( or two out of two GFP pull-downs for the experiment using infected worms ) were included in the analysis . LFQ intensities were log2-transformed . Imputation for missing values was performed for each pull-down replicate in Perseus [69] software ( version 1 . 5 . 5 . 0 ) using a normal distribution to simulate low intensity values below the noise level ( width = 0 . 3; shift = 1 . 8 ) . The LFQ abundance ratio was then calculated for each protein between the GFP pull-downs and the controls . Significance of the enrichment was measured by an independent-sample Student's t test assuming equal variances . Specific interaction partners were then determined in a volcano plot where a combined threshold ( hyperbolic curve ) was set based on a modified t-statistic ( t ( SAM , significance analysis of microarrays ) ; s0 = 1 . 5 , t0 = 0 . 9 ∼ 1 . 5 ) [70 , 71] . Proteins cross-reactive to the anti-GFP antibody were identified by a pull-down experiment using the non-transgenic rde-1 strain and were filtered out from the AKIR-1 protein interactor dataset . Samples for western blot analysis were either prepared as per the co-precipitation protocol with the final elution performed in 50 μl 200 mM glycine pH 2 . 6 and immediately neutralisation by addition of 0 . 2 M Tris pH 10 . 4 , or as per the immunoprecipitation protocol . Samples were then resolved on a 4–12% BisTris Gel ( Invitrogen ) and subjected to transfer to a membrane . Primary antibodies used in that study were as follow: anti-GFP ( clone 11E5 , Invitrogen , dilution 1:2000 ) , anti-HDA-1 ( Santa Cruz , dilution 1:2000 ) , anti-LET-418 ( kind gifts of F . Muller and C . Wicky , used at 1:500 ) , anti-FLAG ( M2 , Sigma , dilution 1:2000 ) and anti-actin ( Abcam , dilution 1:1500 ) . The membrane was then incubated with horseradish peroxidase-conjugated secondary antibodies ( 1:10 , 000 ) at room temperature for 1 h , followed by brief incubation with substrates for enhanced chemiluminescence ( Pierce ECL Plus ) . For extract preparations , N2 worms were grown on rich NGM seeded with HT115 bacteria , and young adult populations of worms were used to prepare about 3–4 gr of flash frozen worm popcorn . Worms were then fixed first with 1 . 5 mM EGS ( ethylene glycol bis ) for 20 min and then in 1 . 1% formaldehyde , with protease and phosphatase inhibitors , at room temperature with shaking , for 20 min . The fixing reaction was quenched by addition of glycine to a final concentration of 125 mM . Worms were then washed once with 10 ml FA buffer ( 50 mM HEPES/KOH ( pH 7 . 5 ) , 1 mM EDTA , 1% Triton X-100 , 0 . 1% sodium deoxycholate , 150 mM NaCl ) with protease inhibitors ( Pierce ) , resuspended in FA buffer containing 0 . 1% sarkosyl and protease and phosphatase inhibitors , then dounce-homogenized on ice . Well-resuspended mixtures were then sonicated to shear chromatin ( size rage 300–800 bp ) using 12 cycles ( 30’ on , 30’ off ) in a Bioruptor-Pico ( Diagenode ) . Cellular debris was removed by centrifugation at 17 , 000 g for 15 min at 4°C . Immunoprecipitation reactions contained approximately 3 mg of total protein , with 1% sarkosyl . Before addition of the antibody ( NanoTrap-GFP , Chromotek ) , 5% of the material was taken as input . Immunocomplexes were collected and washed with 1 ml of the following buffers: FA buffer , two washes , 5 min each; FA buffer with 1 M NaCl , 5 min; FA with 500 mM NaCl , 10 min; TEL buffer ( 0 . 25 M LiCl , 1% NP-40 , 1% sodium deoxycholate , 1 mM EDTA , 10 mM Tris-HCl , pH 8 . 0 ) , 10 min , and TE ( pH 8 . 0 ) , two washes , 5 min each . Complexes were eluted in 1% SDS in TE with 250 mM NaCl at 65°C for 30 min . Samples and inputs were treated with Proteinase K for 1 h , and cross-links were reversed at 65°C overnight . DNA was purified with Qiagen PCR purification columns . Locus-specific ChIP qPCR reactions ( SYBR Premix ExTaq II , TaKara ) were done for each immunoprecipitation using specific elution ( ChIP ) , negative control elution ( nonspecific ) and input samples , following a 50-fold dilution . Ct values were used to calculate the fold difference in DNA concentration between ChIP and nonspecific samples , normalized to the input . p_act-1A: JEP2537 gggcgggtcaaacagaaa , JEP2538 atgcgccgcccttttatt p_act-1B JEP2522 tgcaagtgcagcgagaaa , JEP2528 aacacgttcgtcgcgttg p_nlp-29: JEP2521 gaaaaagaaacagagtctcgtgatg , JEP2527 tttctgattattaccacgtttttcg p_nlp-31: JEP2529 cccagttcttcgtgtcaccac , JEP2530 gccgggcaaaatcacaaa p_nlp-34: JEP2535 gacgtacctagacgtagaccatacacc , JEP2536 gtgacgtaattcgcaacatgg 3’UTR_nlp-29: JEP2544 ggggaagaaaataatttacatgagc , JEP2545 gcaagcgcaaaaatgttaaaaa 3’UTR_nlp-31: JEP2531 gcttttaataatatgacatgaccgaaa , JEP2532 gaaatttgacattcatcaaaatgct 3’UTR_nlp-34: JEP2539 ccgtacggatacggaggata , JEP2540 tttaaagtatattcgtcagcagcag Confocal images were captured using an inverted confocal spinning disk microscope ( Yokogawa , Visitron Systems GmbH ) associated with a 512 x 512 pixels EM-CCD camera ( Hamamatsu ) . Worms were immobilized in 0 . 01% levamisole and visualized through a CFI Plan Fluor Nikon 40X oil , 1 . 3 NA objective and 1 . 5X lens , using a 488 nm laser . Z-stacks were acquired with a step size of 0 . 3 μm . | When animals are infected , as part of their innate immune response , they switch on defence genes that encode proteins that help fight pathogens . We use the nematode Caenorhabditis elegans to understand the steps in this process . When infected , C . elegans can turn on clusters of antimicrobial peptide genes . We have discovered that the coordinated expression of these genes requires a particular chromatin remodelling complex ( proteins that open up compact DNA ) , working in conjunction with a protein called Akirin . Akirin plays a central role in immune gene expression in insects and mammals , but we found that although it has conserved its role of bridging chromatin-remodellers and transcription factors needed for gene expression , the identity of its functional partners is different . Our findings represent a major advance in our understanding of innate immune gene regulation in C . elegans , and give insight into how biological mechanisms can evolve . | [
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"mo... | 2018 | Evolutionary plasticity in the innate immune function of Akirin |
Understanding the binding mode of agonists to adrenergic receptors is crucial to enabling improved rational design of new therapeutic agents . However , so far the high conformational flexibility of G protein-coupled receptors has been an obstacle to obtaining structural information on agonist binding at atomic resolution . In this study , we report microsecond classical molecular dynamics simulations of β1 and β2 adrenergic receptors bound to the full agonist isoprenaline and in their unliganded form . These simulations show a novel agonist binding mode that differs from the one found for antagonists in the crystal structures and from the docking poses reported by in silico docking studies performed on rigid receptors . Internal water molecules contribute to the stabilization of novel interactions between ligand and receptor , both at the interface of helices V and VI with the catechol group of isoprenaline as well as at the interface of helices III and VII with the ethanolamine moiety of the ligand . Despite the fact that the characteristic N-C-C-OH motif is identical in the co-crystallized ligands and in the full agonist isoprenaline , the interaction network between this group and the anchor site formed by Asp ( 3 . 32 ) and Asn ( 7 . 39 ) is substantially different between agonists and inverse agonists/antagonists due to two water molecules that enter the cavity and contribute to the stabilization of a novel network of interactions . These new binding poses , together with observed conformational changes in the extracellular loops , suggest possible determinants of receptor specificity .
Beta adrenergic receptors are a class of transmembrane receptors responsible for binding catecholamines , such as the endogenous hormone adrenaline or the neurotransmitter noradrenaline . They belong to the G-protein-coupled receptors ( GPCRs ) family and are crucially involved in heart muscle contraction ( β1 ) , smooth muscle relaxation ( β2 ) and lipolysis enhancement ( β3 ) . As a consequence , their signaling pathways are central for cardiac function regulation and relaxation of vascular and bronchial tone . The development of a large number of compounds able to modulate the activity of such receptors has been a major goal for the pharmaceutical industry to improve the clinical treatment of various diseases including hypertension , heart failure , asthma and preterm labor [1] . Since distinction between β adrenergic receptors can be based upon their relative affinities for the endogenous catecholamine agonists adrenaline and noradrenaline , determination of the differences that are responsible for their characteristic role upon agonist activation is crucial for the development of selective β-blockers [2] . The pharmacological characteristics of adrenergic receptors and their relative affinities and efficacies have been studied exhaustively , leading to the identification of a large number of clinically relevant agonists and antagonists . However , only recently determination of the crystal structures of β2 and β1 adrenergic receptors bound to inverse agonists/antagonists has provided a view of the binding mode of ligands inside the orthosteric binding pocket with atomic resolution [3] , [4] . In particular , these crystal structures have confirmed that the crystallized ligands are engaged in specific interactions with a set of amino acid side chains in helices III , V , VI and VII that extensive mutation analyses already suggested as preferred interaction partners for catecholamines [5] , [6] , [7] , [8] , [9] , [10] . In addition , the X-ray data suggested a functional role for the second extracellular loop ( ECL2 ) , based on its structure and close proximity with the bound ligand . An atomistic description of the binding mode of agonists , on the other hand , is still lacking , and structure determination of adrenergic receptors in complex with agonists has so far been proven elusive . To address this pharmacologically crucial issue , structure-based drug design using the antagonist-bound β2AR structure as a template have been recently reported [11] , [12] , [13] , [14] , [15] , [16] . These studies have primarily focused on the ability to identify partial/full agonists with docking based in silico screening methods , focusing on the molecular description of the strong agonist-specific [6] , [10] polar interaction network between the catechol functional group and an anchor site formed by three serines in helix V , and the possible displacement of this helix to ease agonist binding [13] , [16] . However , it is widely acknowledged [10] , [17] , [18] , [19] that agonist binding is an intrinsically dynamical event that occurs via kinetically distinguishable conformational intermediates [20] , and indeed recent in silico screening of approximately 1 million of commercially available “lead-like” molecules has confirmed an apparent bias toward inverse agonists among the docking hits [14] . On the other hand , it is known that agonist efficacy can be modulated by a number of allosteric factors , including G protein binding [21] , GDP and GTP concentration [21] , pH [22] and oligomerization state [23] . In particular , recent NMR studies on rhodopsin [24] and on β2AR [25] have revealed that the conformation of the extracellular surface of these receptors changes upon activation and that , in β2AR , drugs exhibiting different efficacies towards G-protein activation can stabilize distinct conformations of the extracellular loops , thus demonstrating a conformational coupling between this region and the orthosteric binding site . These findings are of special interest in view of the fact that the binding sites are very similar amongst β adrenergic receptors , whereas the extracellular loops are remarkably diverse and are therefore a possible target for the discovery of subtype-selective drugs . To further elucidate agonist binding in the family of β adrenergic receptors , taking into account inherent receptor flexibility and explicit solvation known to be crucial for GPCR function [26] , [27] , [28] , [29] , we have carried out submicrosecond MD simulations of β1 and β2 adrenergic receptors bound to the potent agonist isoprenaline as well as in their apoforms . In order to properly analyze the agonist-induced local conformational changes in the two receptors , we also compare these simulations with previously reported MD simulations of β1 and β2 adrenergic receptors bound to the antagonist cyanopindol and the to the inverse agonist carazolol [30] . Anticipating our results , our simulations suggest that internal water molecules , that are usually left out in rigid docking experiments , play a major role in stabilizing agonist-receptor interactions , participating in two complex hydrogen bond networks between the agonist and the receptor . One of them involves the catechol moiety of the agonist while the other its ethanolamine part , and both differ from the inverse agonist interactions reported in the recently solved crystal structures of β adrenergic receptors [3] , [4] . In addition , the specific behavior of the extracellular loops helps rationalize the allosteric activity of this region and provides meaningful insights into drug-receptor specificity .
All simulations are based on the crystal structure of human β2 Adrenergic Receptor ( Protein Data Bank code: 2RH1 ) [3] , and on chain B of the crystal structure of partially mutated ( β1AR-m23 ) turkey β1 Adrenergic Receptor ( Protein Data Bank code: 2VT4 ) [4] . Missing amino acids ( including the third extracellular loop and the C and N termini ) and ionizable side chains have been modeled according to Ref . [30] . In β1AR , residues S68 , V90 , A227 , L282 , A327 , M338 are mutated back to R68 , M90 , Y227 , A282 , F327 and F338 . The explicit membrane environment is formed by 1-stearoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine ( SOPE ) lipids , and the systems are immersed in a box of SPC water [31] . Sodium and chloride ions were added to the aqueous phase to obtain an overall neutral system at physiological ion concentration . The systems consist of approximately 100 . 000 atoms in a box of size 100 cubic Å . The all-atom AMBER/parm99SB [32] force field was used and all bound ligands ( S-carazolol , S-cyanopindolol and R-isoprenaline ) carry a net positive charge of +1e ( see Figure 1 ) . The atomic charges for these ligands were derived by RESP [32] , [33] , [34] fitting using HF/6-31G* optimized structures and electrostatic potentials obtained using the Gaussian03 package [35] . The forcefield parameters for the ligands are reported in Supplementary Information ( Dataset S1 , S2 and S3 ) . All data collections and equilibration runs were done using GROMACS 4 [36] . Electrostatic interactions were calculated with the Ewald particle mesh method [37] , with a real space cutoff of 12 Å . Bonds involving hydrogen atoms were constrained using the LINCS [38] algorithm and the time integration step was set to 2 fs . The systems were coupled to a Nosé-Hoover thermostat [39] , [40] and to an isotropic Parrinello-Rahman barostat [41] at a temperature of 310K and a pressure of 1 atm . Simulations of the apoforms and isoprenaline-bound β2AR and β1AR were started from the equilibrated carazolol-bound and cyanopindolol-bound structures taken from Ref . [30] after removal of the bound ligand or replacement of the bound carazolol with isoprenaline using a superposition of the N-C-C-OH motif shared by many adrenergic receptor agonists and antagonists . The systems were then slowly heated up to 310 K in 1040 ps without restraints . Data analysis was performed on the following systems ( between parenthesis the length of the corresponding MD runs in the case of a deprotonated Asp ( 2 . 50 ) and of a protonated Asp ( 2 . 50 ) ) for a cumulated length of 6 . 5 µs: carazolol-bound β2AR ( 820 ns; 600 ns ) , isoprenaline-bound β2AR ( 830 ns; 500 ns ) , unliganded β2AR ( 800 ns; 450 ns ) ; cyanopindolol-bound β1AR ( 820 ns; 600 ns ) , isoprenaline-bound β1AR ( 500 ns; 500 ns ) , unliganded β1AR ( 500 ns ) . Unless stated otherwise , the analyses described in the text refer to the simulations with deprotonated Asp ( 2 . 50 ) . All data analysis were done using GROMACS [36] utilities and all molecular images were made with Visual Molecular Dynamics ( VMD ) [42] . Hydrogen bonds are defined by a heavy atom distance cutoff of 3 Å and an angle cutoff of 20 degrees .
Comparison of the chemical similarities of β adrenergic receptor ligands suggests that while some interactions might be common for agonists and antagonists , others can be expected to be specific for agonists only . In particular , while most β adrenergic agonists and antagonists ( including the co-crystallized cyanopindolol and carazolol ) present a positively charged amine or ethanolamine groups , the presence of the polar catechol group is strongly agonist specific . At the same time , it is known that while antagonist binding to β adrenergic receptors is largely entropy driven , with only a small enthalpy component , the binding of agonists is associated with a large decrease in enthalpy [43] . These considerations suggest formation of a large structured hydrogen bond network , probably located in close proximity to Ser ( 5 . 42 ) [10] , Ser ( 5 . 43 ) [6] and Ser ( 5 . 47 ) [6] in helix V , as possible key component of agonist binding . The crystal structures of the antagonist/inverse agonist bound forms have indeed confirmed these considerations , showing that the carbazole heterocycle of carazolol and the indole moiety of cyanopindolol interact with the receptor mainly via hydrophobic interactions and a lone hydrogen bond with Ser ( 5 . 42 ) , while Asp ( 3 . 32 ) and Asn ( 7 . 39 ) form a complementary H-bond network with the ethanolamine group of the ligands . To understand the binding mode of agonists inside the binding pocket of adrenergic receptors as well as the conformational changes induced in the receptor by the presence of different ligand effectors , we performed MD simulations ranging between 500 ns–830 ns of β1 and β2 adrenergic receptors in their apoforms , and bound to the full agonist isoprenaline . The simulations were started from receptor structures bound to the co-crystallized antagonist cyanopindolol and the inverse agonist carazolol previously equilibrated in an explicit membrane environment ( see Methods and ref . [44] ) . Root mean square deviation ( RMSD ) analysis of the backbone atoms of all alpha helices as well as of the ligand binding site , defined as all residues within 5 Å from the bound ligand in the crystal structures , suggests that the simulations are equilibrated within approximately one hundred nanoseconds ( see Figure 2 ) . Very little global structural rearrangements with respect to the crystal structures , in line with previously reported MD simulations of the same systems in their apo [45] and antagonists-bound [44] forms , are observed . At the same time , the apoforms of the receptors need a longer equilibration time , especially in the case of β1AR , where equilibration is reached only after approximately 200 ns . This difference is related to the extent of internal solvation-induced rearrangements that take place in the apoform , in contrast to the case of the ligand bound receptors where a set of hydrophobic residues contributes to ligand stabilization inside the binding pocket with only few internal water molecules playing a crucial role . Interestingly , the ligand binding site remains very close to the original conformation both in MD simulations of the isoprenaline-bound forms and in the unliganded systems , suggesting that only local rearrangements take place . The most significant of these local changes are due to conformational transitions of crucial residue Phe193 in the second extracellular loop ( ECL2 ) which cause the fluctuations of the active site RMSD in the isoprenaline-bound β2AR simulations ( green line in the right panel of Figure 2 ) and their functional significance will be discussed in more detail below . The crystal structures of β adrenergic receptors have revealed that the structure of the extracellular loops in these receptors able to bind diffusible ligands is remarkably different from rhodopsin where the N-terminus and ECL2 form a structured cap over the covalently bound retinal to prevent ligand hydrolysis . In order to allow ligand access to the binding pocket , ECL2 and ECL3 in adrenergic receptors are mainly composed of polar and charged residues and , unlike in rhodopsin , they do not prevent ligand access , even though rearrangements of ECL2 are expected during ligand entry and exit [50] . Recent NMR studies on rhodopsin [24] and on β2AR [25] have revealed that the conformation of the extracellular surface changes upon activation and that , in β2AR , drugs exhibiting different efficacies towards G-protein activation can stabilize distinct conformations of the extracellular loops . All these findings demonstrate a conformational coupling between this region and the orthosteric binding site . In particular , it has been suggested that the extracellular Lys305-Asp192 salt bridge in β2AR ( Figure S3 , Supplementary Information ) is weakened in the active state and that inverse agonists may function in part by stabilizing bulky hydrophobic interactions with Phe193 in ECL2 that block the motion of helix VI . These findings are of special interest because although the ECL2 and ECL3 backbone conformations are very similar in β1 and β2 adrenergic receptors , only 55% of their residues are identical , in contrast to the 94% sequence identity of the binding pockets . Interestingly , while in the simulations of β2AR bound to carazolol and isoprenaline the backbone structure of ECL2 and its relative distance to TM7 remain approximately identical to the crystal structure , in the simulation of unliganded β2AR ECL2 approaches the binding pocket ( see Figure 5 ) . Notably , even if the salt bridge between Lys305 and Asp192 remains stable in all simulations ( Figure S3 , Supplementary Information ) , the conformation of Phe193 is substantially different in the three simulations ( see Figure 5 ) : it remains close to the crystal structure conformation in the carazolol-bound simulations ( trans conformation ) , it partially displaces towards helix III and VII in apo-β2AR and it adopts g ( + ) and g ( − ) conformations interacting with the hydrophobic tail of the ligand in the isoprenaline-bound simulation ( Figure S4 , Supplementary Information ) . As a consequence of the displacement of Phe193 in the isoprenaline-bound case , the side chain of Thr195 changes orientation and its hydroxyl group points towards helix III eventually hydrogen bonding Phe193 backbone oxygen . In β1AR , on the other hand , the salt bridge between Lys305 and Asp192 is absent , because lysine is replaced by the aspartic acid Asp322 . However , the high degree of structural similarity of the backbone conformations of loops ECL2 and ECL3 in the two receptors suggests that the role of these charged residues ( lysine and aspartic acid in β2AR and two aspartic acids in β1AR ) is not directly related to loop stabilization . At the same time , the behavior of ECL2 is similar to the one observed in β2 receptor: ECL2 remains close to the crystal structure conformation in the isoprenaline-bound simulation , while it approaches the binding pocket in unliganded β1AR . At the same time , Phe201 in β1AR ( which is equivalent to Phe193 in β2AR ) is also approaching helix III in the isoprenaline-bound simulation but without changing side chain rotameric conformation . Remarkably , while in the simulations of β2AR the overall structure of ECL3 remains very close to the crystal structure independently of the nature of the bound ligand , the behaviour of this loop is substantially different in the simulations of β1AR . In fact , in the cyanopindolol-bound simulation of β1AR , ECL3 is displaced from the binding site and Phe315 points towards the extracellular side moving away from the ligand interaction region . On the other hand , due to the additional interactions that are formed between the catechol moiety of isoprenaline and Asn ( 6 . 55 ) , in the agonist-bound simulations ECL3 approaches the binding site , with Phe315 playing a prominent role in the hydrophobic stabilization of the binding site ( see Figure 6 ) . Since ECL3 is linking helices VI and VII , this event could be a precursor of an inward motion of the extracellular moiety of helix VI towards helix III to favor the interaction between Asn ( 6 . 55 ) and the β hydroxyl group of the agonist that is supposed to be a later intermediate along the activation pathway [8] .
Even though a clear understanding of the binding mode of agonists to β adrenergic receptors would constitute a major step for the development of selective drugs , no structural information on agonist binding at atomic resolution is available yet and the only resolved crystal structures have been obtained in complex with inverse agonists or antagonists . As a consequence , the only available information on possible agonist docking poses can be inferred from rigid or semi-flexible docking protocols that use the inactive receptor as a template and suffer from well-known intrinsic limitations [12] . Even if the current capabilities of force-field based MD simulations do not allow to reach all intermediates along the activation pathway of adrenergic receptors , that are in the milliseconds time scale [46] , they are able to follow the early local structural rearrangements that take place in the binding pocket due to the effect of agonist binding . Moreover , despite the limited statistic arising from the fact that only one replica per system was run , they allow determining the newly formed pattern of interactions between the bound ligand and the receptor taking correctly into account protein flexibility , allosteric modulation and internal solvation . The microsecond MD simulations presented here show the formation of a complex hydrogen bond network between the catechol moiety of isoprenaline and a set of residues in helices V and VI , thus providing a possible explanation of the finding that agonist binding is associated with a large change in enthalpy , while antagonist binding is mainly entropy driven [43] . At the same time , they rationalize the role of Ser ( 5 . 43 ) [6] and Ser ( 5 . 47 ) [6] in agonist binding , while only Ser ( 5 . 42 ) [10] is involved in antagonist binding . Interestingly , despite being in close proximity to the bound ligand , Ser ( 5 . 43 ) does not interact directly with the drug , but stabilizes another crucial residue , Asn ( 6 . 55 ) , through the formation of a stable hydrogen bond that restrains Asn ( 6 . 55 ) conformation enabling a direct interaction between the NH2 moiety of the residue and one of the two hydroxyls of the catechol group of isoprenaline . While it is acknowledged that Asn ( 6 . 55 ) is involved in agonist binding through the formation of an hydrogen bond with the β alcohol of the agonist in a late conformational stage , the simulations suggest that Asn ( 6 . 55 ) can also play a major role in agonist recognition in the early steps of the binding event . In addition , the simulations do not support a large movement of helix V during agonist binding that was suggested based on the marked improvement in the calculated binding affinities for agonist compounds using a semi-flexible docking approach [13] . In contrast , it turns out that only very limited helix V movement is sufficient to achieve a very stable network of interactions that is a direct consequence of the presence of internal water molecules that help bridging the gap between the agonist and helix V . In an analogous way , the presence of few internal water molecules plays a major role in the stabilization of the interaction between helices III and VII and the ethanolamine group of isoprenaline . Despite the structural and chemical similarity displayed by most agonists and antagonists , the binding mode of isoprenaline to Asp ( 3 . 32 ) and Asn ( 7 . 39 ) is remarkably different with respect to the antagonist binding mode suggested by the crystal structures , due to the presence of the internal water molecules . Interestingly , this decreased stability of the interaction between Asn ( 7 . 39 ) and the ethanolamine group of agonists was already reported by MD simulations of an endogenous agonist , adrenaline , where the newly formed interactions appeared to be dynamically less stable [51] . In addition , recent NMR studies on β2AR [25] have revealed a direct coupling between the extracellular loops and the ability of the receptor to activate its cognate G-protein , showing that different conformations of the extracellular loops can be stabilized upon binding of ligands with different activities . In particular , it has been suggested that the extracellular Lys305-Asp192 salt bridge in β2AR is weakened in the active state and that inverse agonists may function in part by stabilizing bulky hydrophobic interactions with Phe193 in ECL2 that block the motion of helix VI . Even though in our simulations we cannot observe any substantial change in the Lys305-Asp192 salt bridge , probably due to the fact that the time scales we are investigating are not sufficient to allow for a complete relaxation of the receptor to the active state , already in the submicrosecond time scale it is possible to notice a different behavior of Phe193 depending on the type of ligand that is bound to the receptor . The pronounced stability that Phe193 displays in the antagonist bound simulations ( due to the presence of strong hydrophobic interactions ) is lost in the unliganded and in the isoprenaline-bound simulations , and the conformational transitions of Phe193 side-chain allow for a closer interaction between this residue and the Lys305-Asp192 salt bridge , constituting a mean to potentially alter the strength of this salt bridge . In conclusion , the reported microsecond MD simulations of agonist bound β adrenergic receptors propose a detailed and dynamical description of agonist-receptor interactions , where hydrogen bonding and internal water molecules play a crucial role . In addition , the specific behavior of the extracellular loops in the different systems can help rationalize the allosteric activity of such loops and provide possible clues into drug-receptor specificity . | G-protein coupled receptors are the largest family of membrane proteins in the human genome and they constitute the largest class of drug targets . Amongst them , beta adrenergic receptors are involved in the regulation of muscular and vascular tone and are thus molecular targets for the treatment of various diseases including hypertension , heart failure and asthma . The function of these receptors is regulated via the binding of endogenous or exogenous ligands that can either lead to activation ( agonists ) or inactivation ( inverse agonists/antagonists ) . However , structure determination of these receptors has been very elusive , and the few atomic resolution structures that are available so far have only been obtained in the presence of inverse agonists or antagonists . In order to study the binding mode of agonists inside the binding pocket , we employ all-atom molecular dynamics . This facilitates the study of the details of the interaction between agonist and receptor in full atomistic detail . We find that agonists binding to beta adrenergic receptors require the formation of a highly structured hydrogen bond network that is further stabilized by the presence of internal water molecules . The observed local rearrangements also help provide insights into the molecular origin of the differences between agonist and inverse agonist binding . | [
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"bi... | 2011 | Predicting Novel Binding Modes of Agonists to β Adrenergic Receptors Using All-Atom Molecular Dynamics Simulations |
Large-scale insertional mutagenesis screens can be powerful genome-wide tools if they are streamlined with efficient downstream analysis , which is a serious bottleneck in complex biological systems . A major impediment to the success of next-generation sequencing ( NGS ) -based screens for virulence factors is that the genetic material of pathogens is often underrepresented within the eukaryotic host , making detection extremely challenging . We therefore established insertion Pool-Sequencing ( iPool-Seq ) on maize infected with the biotrophic fungus U . maydis . iPool-Seq features tagmentation , unique molecular barcodes , and affinity purification of pathogen insertion mutant DNA from in vivo-infected tissues . In a proof of concept using iPool-Seq , we identified 28 virulence factors , including 23 that were previously uncharacterized , from an initial pool of 195 candidate effector mutants . Because of its sensitivity and quantitative nature , iPool-Seq can be applied to any insertional mutagenesis library and is especially suitable for genetically complex setups like pooled infections of eukaryotic hosts .
Virulence factors are key for successful infections by pathogens . Their identification is of major interest because of the necessity to develop effective counter strategies . For instance , fungal virulence factors are typically identified by mutating single loci in fungi , followed by individual fungal mutant infections of host tissue and subsequent assessment of pathogen fitness [1–4] . Individual infection assays are not ideal for the genetic screening of a large number of pathogen mutants because they are laborious , cost-intensive , and—most importantly—assessment of infections is often subjective and qualitative rather than quantitative . An attractive alternative is infection with a pool of pathogen mutants allowing direct assessment of individual pathogen fitness in the same host tissue . However , using a pooled pathogen infection creates the challenge of identifying pathogens with reduced virulence within a complex mixture of genetic material extracted from infected host tissue . Mutant collections can be efficiently generated using insertional mutagenesis . Insertional mutagenesis employs gene cassettes that commonly comprise a selectable marker under the control of a strong constitutive promoter . The detection of genome–cassette junctions can serve as a molecular identifier for each insertion mutant . During screening , insertional mutants before selection in the host are defined as the genetic input , whereas surviving insertional mutants after selection comprise the genetic output . Insertional mutagenesis can be achieved randomly through transposon insertion [5–8] or Agrobacterium tumefaciens-mediated transformation [3 , 9] , or specifically through site-specific insertion by homologous recombination [10 , 11] . Over the last decade , several approaches were established that use massive parallel sequencing for the detection of inserted gene cassettes . These approaches were successfully used to track mutants from the small genomes of prokaryotic pathogens and allowed the identification of bacterial genes involved in virulence or host colonization after pooled infections [12–16] . However , only a few attempts were reported that identified virulence factors using pools of eukaryotic pathogens [17] . The main factors limiting the successful insertional mutagenesis of eukaryotic pathogens by pooled infections in complex host-pathogen systems are variable infection rates of individually mutated pathogens , the size ratio of host/pathogen genomes , the inability to sufficiently detect inserted gene cassettes from pathogenic material , and biases that arise through PCR-based amplification steps . To enable successful and quantitative insertion mutant screen-based identification of virulence factors in complex biological systems , we developed insertion Pool-Sequencing ( iPool-Seq ) . We determined the sensitivity and efficiency of iPool-Seq using an insertion mutant collection of 195 predicted virulence factors encoded by the maize pathogen U . maydis . The haploid U . maydis genome consists of approximately 20 . 5 megabases [18 , 19] , whereas the diploid genome of maize is 2 . 3 gigabases large [20] . This represents a 100-fold genome size difference , which is beside the proportion between fungal and host plant genome abundance as a limiting factor , making the robust detection of U . maydis sequence information in infected maize tissue necessary . The iPool-Seq workflow consists of Tn5 Transposase-mediated tagmentation of complex genomic DNA ( gDNA ) allowing efficient library preparation from low-input material [21 , 22] . This is followed by the efficient enrichment of extremely rare insertion cassettes from fungal genomes using biotin-streptavidin affinity purification of PCR products . Amplification biases are monitored through incorporated unique molecular identifiers ( UMIs ) . Insertional mutant fitness within host tissues is directly measured through quantification of UMI counts present in infected output material compared to UMI counts from the input library . iPool-Seq on U . maydis infections of maize confirmed the identity of 5 known fungal virulence factors that were included as positive controls in the screen . Importantly , 23 previously unreported virulence factors encoded by U . maydis were uncovered . Three of these factors were confirmed to be novel virulence factors of U . maydis after testing by individual infection . The combination of pooled insertion mutant infections and iPool-Seq technology represents a straightforward and cost-effective approach to map insertion mutants in complex host–pathogen systems with the potential to generate genome-wide virulence maps of relevant crop pathogens and beyond .
We employed the smut fungus U . maydis as a model to establish iPool-Seq . We generated a Golden Gate cloning-compatible plasmid , which allows for recombination of multiple fragments in a single reaction [23] . To this end , we combined a hygromycin resistance cassette that is flanked by unique primer binding sites ( UPSs ) with the chromosomal up- and downstream regions ( 1 , 000 bp ) of 195 predicted U . maydis effector genes ( Fig 1A; S1 Table ) . Plasmids were linearized and transformed into U . maydis SG200 protoplasts for deletion of the putative virulence factors by homologous recombination ( Fig 1B ) . For each of the insertion mutant constructs , we isolated 3 independent transformants and analyzed deletion events using PCR primers directed against the effector genes sequences . Absence of PCR products indicated successful deletions ( Fig 1C ) . For each successful deletion , 3 independent transformant replicates were verified and stored separately , allowing for individual propagation to avoid growth competition prior to pooled infections . We performed 2 independent infections with pools containing the entire collection of 195 insertional mutants and established the iPool-Seq library preparation protocol ( S2 Fig ) . For later comparison of mutant material abundance within the collection , iPool-Seq libraries were prepared from gDNA representing the mutant pool before infection ( the input ) and from infected tissues containing both maize and U . maydis genomes ( the output , Fig 2A ) . To minimize the number of library preparation steps and conserve material , we replaced mechanical shearing of gDNA ( requiring DNA-end repair , tailing , and adapter ligation steps ) with Tn5-mediated tagmentation ( Fig 2B ) [21] . Although this approach yields a wider size range of DNA fragments , simultaneous DNA fragmentation and adapter ligation makes Tn5-mediated tagmentation preferable to DNA shearing approaches . We produced recombinant Tn5 transposase and adapted the published protocol to large gDNA inputs ( S3 Fig ) [21] . Furthermore , customized adapters for Tn5-mediated tagmentation were designed containing 12 bp unique molecular identifiers ( UMIs ) followed by a sequencing primer binding site ( SBS; Fig 2B; S2 Table ) , which enables sequencing of UMIs using a custom-made first strand sequencing primer . Fragmented gDNA from pooled fungal infections of maize are not only highly diverse but fungal DNA content will certainly be underrepresented , making it necessary to efficiently enrich for insertion cassette junctions with genomic regions . To enrich for such junctions , the tagmentation-derived DNA fragments were amplified using specific adapter primers and biotinylated primers that bind to unique sequences at the distal ends of deletion cassettes ( Fig 2B; S2 Table ) . Consequently , both genomic junctions of individual insertion cassettes were amplified , yielding biotinylated PCR products from all insertional mutants . Biotinylated PCR products were isolated using streptavidin-based affinity purification ( Fig 2C ) and Illumina-compatible adapters were introduced via nested PCR ( S2 Table ) . Sequencing was performed on an Illumina MiSeq platform . In conclusion , we designed iPool-Seq to benefit from tagmentation , specific amplification , and streptavidin purification for efficient enrichment of ultra-rare genome deletion cassette junctions out of a highly diverse gDNA mixture . We infected maize in two independent experiments with three biological replicates of a pool of 195 verified insertional U . maydis mutants ( S1 Table ) , resulting in six input and output libraries . The libraries were prepared as described above and sequenced on an Illumina MiSeq platform with paired-end ( PE ) sequencing . After read validation and read mapping , 87 . 7% ± 1 . 7% and 85 . 3% ± 1 . 6% of the obtained sequencing reads ( input versus output , respectively ) were mapped to U . maydis insertional mutation loci ( Fig 3A; S1 Supporting methods ) . To remove reads produced by PCR bias and which would affect quantitative evaluation of input and output reads , we collapsed all reads with highly similar UMIs to a single UMI count after sequencing . Based on the observed distribution of reads per UMI and comparison to a model prediction , we then set a library-specific read count threshold , removed UMIs with fewer reads than the threshold as likely PCR and sequencing artifacts , and corrected the number of remaining UMIs for the estimated loss of real UMIs ( Fig 3B , S1 Supporting methods ) . After this UMI analysis , we retained 79 . 9% ± 3 . 6% and 76 . 0% ± 2 . 2% of initial reads from input and output for downstream analyses , respectively ( Fig 3A ) . The sequencing results indicated that three-fourths of all iPool-Seq reads were informational for insertion mutant abundance . Moreover , iPool-Seq generated similar amounts of valid reads from input- and output-derived gDNAs , indicating that yield performance was not diminished using gDNA derived from two organisms . Since each inserted mutagenesis cassette has two junctions with neighbouring genomic regions , an unbiased library preparation should produce similar read numbers for up- and downstream junctions . We observed high correlation values ( R ) for all insertion mutants for the input and output samples , indicating that iPool-Seq is not suffering from considerable PCR biases during exponential amplification of DNA fragments containing mutagenesis cassette–genome junctions ( Fig 3C ) . To identify U . maydis virulence factors , we analyzed input and output reads for significantly depleted sequences from the pool of 195 insertion mutants . First , the read output of all insertional mutants was normalized to the corresponding input reads . Second , we defined an internal reference set of U . maydis mutant strains that do not have virulence phenotypes [18 , 24] and whose output and input reads showed a neutral and linear relationship ( Fig 4A , neutral; Fig 4B; S3 Table ) . Our collection contains additional mutants that were previously reported to be neutral . In these communications , neutral mutants formed symptoms with the same severity as the progenitor strain SG200 . However , these observations did not provide any distinct information about quantitative growth defects of these mutants . Therefore , we constrained the neutral reference set to five mutants that displayed a reproducible neutral behavior in the iPool-Seq data ( S1 Supporting methods ) . We then calculated , for each mutant , the level of depletion from the output sample compared to the input and determined significance through normalization to the internal reference set . This resulted in the identification of a substantial proportion of sequences that were significantly depleted from the output libraries ( Fig 4B , red circles; S1 Data ) . We analyzed this depleted sequence set for known virulence factors and identified Pep1 , Pit2 , and Stp1 ( UMAG_01987 , UMAG_01375 , and UMAG_02475 ) [25–27] as known essential virulence factors of U . maydis ( Fig 4A , lost virulence ) . In addition , we found the previously described virulence factors ApB73 ( UMAG_02011 ) [28] and Fer1 ( UMAG_00105 ) [29] among the less depleted and reduced candidate sequences ( Fig 4A , reduced ) . Two other mutants ( UMAG_06223 and UMAG_02239 ) , for which minor defects in disease symptom induction had been reported previously , were not significantly depleted in the iPool-seq results and one mutant ( UMAG_12313 ) previously reported to be unaffected in virulence showed a weak but significant reduction in our iPool-seq approach ( S4 Table ) [24] . In summary , iPool-Seq results largely overlap with previously reported symptom scoring data for characterized virulence factors ( S4 Table ) . It is also sensitive , as not only apathogenic but also reduced virulence factor mutants were identified . Importantly , analysis of the depleted sequence set yielded 23 fungal mutants that are potential novel virulence factors of U . maydis ( Fig 4C; S4 Table ) . In contrast to the identification of depleted mutant sequences , we did not identify sequences that were reproducibly enriched in all biological replicates , indicating that none of the fungal mutants tested conferred enhanced virulence to U . maydis on the tested host accession Early Golden Bantam ( EGB; Fig 4C ) . We next modeled the performance of iPool-Seq on a high-throughput mutant library of U . maydis ( S9 Fig , S1 Supporting methods ) . To this end , we used the following parameters: 1 ) 20 , 000 insertion mutants were chosen cover the approximately 20-MB genome of U . maydis with approximately 1 , 000 bp average distance of insertion sites . 2 ) During maize colonization , approximately 1 , 500 of the approximately 6 , 900 U . maydis genes are transcriptionally up-regulated—and we showed that about 14% of all mutants from our library contributed to virulence ( Fig 4C; S4 Table ) [18 , 30] . Based on these observations , we extrapolate that approximately 3% of all U . maydis genes are likely to be involved in virulence . 3 ) We showed with iPool-Seq that known reduced virulence factors of U . maydis had a mean logarithmic fold change of −1 . 53 and known essential virulence factors of −2 . 75 in comparison to the neutral reference set , respectively ( Fig 4A ) . Due to a lack of data , the model does not take into account the number of unsuccessful infection events on the host plant but assumes 100% infection rate for each individual of a neutral mutant strain . The model resulted in 40 ( for essential virulence factors ) and , respectively , 100 ( for weak virulence factors ) detected individuals necessary for each mutant in the input samples to identify virulence factors with 99% sensitivity . Based on observed average of approximately 10 reads per UMI ( Fig 3B ) and due to the insertion flank sequencing efficiency of at least 75% ( Fig 3A ) , the required sequencing depth would be 26 Mio reads ( 20 , 000·100·10·1 , 33 = 26 , 600 , 000 ) per library . This suggests that the iPool-Seq technology can be used for large scale mutant screens in U . maydis and similar systems . To validate the 23 potential virulence factors identified by iPool-Seq , we chose three top candidates and tested their effects on virulence using individual infection assays . We observed a severe loss of U . maydis virulence upon infection of plants with fungi carrying these mutations . Whereas the wild-type progenitor strain SG200 produced galls on infected maize , all three mutant strains failed to form galls , indicating that they are essential for fungal virulence ( Fig 5A ) . This effect was specifically due to virulence , as growth assays under stress-inducing conditions showed no difference between these mutant strains and SG2000 ( Fig 5B ) . Using confocal microscopy on infected plants , we observed that mutant strains were severely impaired in colonizing maize leaf tissues ( Fig 5C ) . Our combined results show that iPool-Seq facilitates the identification of essential factors for U . maydis virulence . Furthermore , the streamlined library preparation of iPool-Seq should make the method widely applicable for identifying unknown virulence factors in complex biological systems , such as in vivo infected tissues .
Pooled mutant screens have proven to be very powerful tools to uncover individual genes affecting particular phenotypes in a time- and cost-effective fashion . Positive selection screens usually lead to limited numbers of individual surviving cells that are easily identifiable by a combination of restriction enzyme digests , inverse PCR , and sequencing . Negative selection screens rely on the survival of most analyzed cells , making it necessary to devise methodology that allows comparing the presence/absence of genetic information before and after selection . To tackle the later challenge , several insertional mutagenesis approaches have been developed [31] . Although successful in bacterial systems for the elucidation of virulence factors [5 , 13 , 32] , such insertion mutant approaches were not widely used in eukaryotic systems , mainly because of unresolved technical issues such as low sensitivity and system-intrinsic limitations ( for example , genome ploidy , lifestyle of the investigated model system ) . Here , we introduce iPool-Seq as a versatile and highly sensitive method for the analysis of insertion mutant pools before and after selection , enabling both negative and positive mutant selection screens in complex eukaryotic systems including the analysis of host–pathogen interactions . We used iPool-Seq to examine virulence factors from a defined set of mutants of the crop fungus U . maydis , both confirming known factors and identifying novel ones . From the predicted mutant collection we used , most mutants were not significantly depleted from the output reads , indicating no function in virulence for the underlying genes . However , the role of some factors could be difficult to decipher , for example , because their action could be covered by functional redundancy of other virulence factors . Although we infected insertion mutants in dense pools , depleted insertional mutants appeared not to be affected by in trans complementation , by using the secreted factors of neighbouring fungal cells for example . Nevertheless , it cannot be excluded that , for certain gene products , in trans complementation could occur and mask the virulence defect of the respective mutant in a pooled infection setup . In conclusion , negative depletion screens have limitations to decipher redundancy and potential in trans complementation of virulence factors . In addition , we did not identify significantly enriched mutants in the iPool-Seq analysis of the mutant collection . A significant enrichment of output reads would indicate the loss of a negative regulator of virulence . A possible reason that we did not find enrichment could be our choice of the maize accession , EGB , which is highly susceptible to the U . maydis strain SG200 . Microscopy of U . maydis strain SG200 infecting maize tissue implies that many cells fail to penetrate the host [28] . In very complex insertion mutant libraries , this large individual failure rate could lead to the loss of mutants that lack any real defect in virulence . Therefore , for genome-wide virulence maps of U . maydis and similar biotrophic pathogens , the size of the insertion mutant pool must be individually adapted to the infection rate of the respective pathogen . To overcome this problem , genome-wide screens might need to be performed in subpools , as it has been done in a previous study with the fungal pathogen Cryptococcus neoformans [11] . iPool-Seq uses insertion cassette–specific primers to amplify the genomic insertion junctions from a mutant pool [17] . Additionally , iPool-Seq enriches for PCR products by using biotin/streptavidin interaction , an approach that has previously been used in bacterial transposon integration site identification methods such as high-throughput insertion tracking by deep sequencing ( HITS ) [5] . Importantly , UMIs in the adapter primer allow in silico elimination of PCR biases . The unique barcode identifiers additionally overcome cluster position identification problems during Illumina sequencing that would otherwise occur when the first bases from the insertion flank would otherwise be identical for all mutant loci . Dark cycle sequencing , as used in Quantitative insertion-site sequencing ( QIseq ) for example , is therefore unnecessary [17] . iPool-Seq was established using a defined insertion mutant collection of U . maydis . However , the technology can be adapted to any insertion mutant collection , such as transposon or A . tumefaciens-derived T-DNA libraries [33 , 34] . The modeling of the iPool-Seq sensitivity indicates that iPool-Seq meets all premises to work for high-throughput . Therefore , iPool-Seq promises to be a versatile technology for reanalysis of existing knock-in , activation-tagging , or transposon-insertion libraries , dramatically reducing labor costs for selection screens when compared to classical scoring approaches . Additionally , the relatively low costs of iPool-Seq for broad screens could also foster research in less funded emerging model systems . Due to the strong enrichment of insertion gene cassettes , the sequencing depth and costs of iPool-Seq are low . Thus , this technology will enable researchers to test diverse new selection criteria to efficiently build genotype–phenotype relationships . This will help to fill the knowledge gap that is currently still hampering research as exemplified for the well annotated U . maydis genome with 6 , 786 protein-encoding genes , of which 41 . 5% are in the category unknown [35] . Moreover , even if genes are annotated , their involvement in various biological processes might , simply , not yet be known . From the candidate virulence factors that we identified with iPool-Seq , we chose 3 for verification and confirmed their virulence defect by classical scoring of disease symptoms . However , the assessment of disease symptoms is indirect , and discrepancies between the two methods might occur for other novel virulence factors . We speculate that the U . maydis genome encodes virulence factors whose mutants show reduced proliferation but still cause full disease symptoms based on qualitative measures . In line with this , the iPool-Seq data did not show significant depletions for two mutants that were previously reported with mild defects in symptom induction [24] . In contrast to these disease ratings , iPool-Seq has the potential to identify virulence factors that do not have an obvious effect on symptom formation on a genome-wide level . In summary , we have demonstrated the functional genomic technology iPool-Seq by identifying both known and novel virulence factors from pooled infection assays of a biotrophic fungus within a complex host background . iPool-Seq is therefore a sensitive in vivo tool for researchers to help fill the genotype–phenotype gap in the post-genomic era .
For all DNA manipulation we used Escherichia coli Mach1 ( Thermo Fisher Scientific ) . The vector backbone for the generation of the mutant collection is based on pGBKT7 ( Clontech Laboratories ) . We replaced kanamycin resistance with a spectinomycin resistance cassette and removed internal SapI , BsaI , BsmBI , and BbsI restriction sites by direct mutagenesis from a derivative of the original vector , respectively [36] . The hygromycin resistance marker originates from vector pHwtFRT [37]; and SapI , BsaI , BsmBI , and BbsI restriction sites were removed by site-directed mutagenesis . Moreover , we elongated the hygromycin cassette with a UPS on the 5′- and 3′-end ( 5′-TCGCCACAGGATACCACAGGACATCTGGGATATC and 3′-GCCACTCACGCCACAGGATACCACAGGACATCTGGGATATC; UPS is underlined ) . In detail , for each mutant locus we amplified 1 , 000 bp up- and downstream borders from U . maydis gDNA with standard molecular cloning procedures [38] and combined them with the modified hygromycin-selectable marker cassette flanked with UPS ( Fig 2; S2 Table ) and the plasmid backbone . Depending on the occurrence of internal restriction sites , we used either SapI , BsaI , BsmBI , or BbsI restriction sites ( ordered by priority of choice ) for Golden Gate cloning [23] . Constructs were verified by Sanger sequencing and subsequently transformed into the haploid solopathogenic strain SG200 of U . maydis as previously described [18 , 39 , 40] . Transformants were verified by direct PCR: single mutants were grown in YepsLight ( 0 . 4% yeast extract , 0 . 4% peptone and 2% sucrose ) liquid medium at 28°C with shaking at 200 rpm in 48-well plates overnight . The next day , 100 μL overnight culture was pelleted and resuspended in 20 μL 0 . 02 M NaOH . 1 μL was then utilized for a direct PCR reaction with a primer pair directed against the replaced gene . As a positive control , a primer pair binding to another mutant locus was used . Subsequently , we isolated gDNA from at least 4 PCR positive strains and repeated the direct PCR using 1 μL of 1:10 diluted gDNA as a template . All primer pairs used for the verification of deletion strains produced PCR products from a gDNA template from the progenitor strain SG200 . Three independently verified U . maydis insertional mutants were preserved at −80°C in PD liquid supplemented with 50% glycerol . For each mutant collection pool replicate we infected at least 100 plants of maize variety EGB ( Olds Seeds , Madison , WI , USA ) . Seedlings were grown under a 14-hour/10-hour light/dark cycle at 28°C/20°C in plant growth chambers and infected 7 days after potting . U . maydis mutant strains were grown individually on selective PD plates supplemented with 200 μg/mL hygromycin for 2–3 days at 28°C . Subsequently , for each mutant strain , 1 mL YepsLight ( 0 . 4% yeast extract , 0 . 4% peptone and 2% sucrose ) liquid preculture was inoculated in 48-well plates and grown at 28°C overnight with shaking at 200 rpm . For main cultures , precultures were diluted 1:2 , 000 in 3 mL YepsLight in test tubes and grown at 28°C with shaking at 200 rpm overnight . After 14–16 hours , the main cultures of all mutants were adjusted to an OD600 of 3 and mixed in equal amounts . The mutant pool was pelleted at 2 , 000 x g for 10 minutes and resuspended in sterile water . 250 μL of the mutant pool was infected in each maize seedling with a syringe . After 7 days , infected areas from the second and third leaves were harvested , ground to a fine powder in liquid nitrogen , and preserved at −80°C until iPool-Seq library preparation . For output gDNA extraction , 0 . 75–1 g of infected plant powder was supplemented with 2 mLLysis buffer ( 10 mM Tris , pH 8; 100 mM NaCl; 1 mM EDTA; 2% Triton X 100 [v/v]; 1% SDS [w/v] ) , 2 . 5 mL TE-buffer equilibrated phenol , chloroform , and isoamyl alcohol ( 25:24:1 , pH 7 . 5–8 , Carl Roth ) and 100 μL sterile glass beads ( 450–600 μM , B . Braun ) in a 7-mL Precellys tube . The material was processed for 20 seconds at 4 , 500 rpm with a Precellys evolution bead mill ( Bertin ) . The debris was pelleted at 17 , 000 x g for 15 minutes , and 2 mL supernatant was added to 2 . 2 mL Isopropanol . The precipitated gDNA was washed with 1 mL 80% EtOH and eluted in 150 μL or 200 μL TE supplemented with RNAse A ( 20 μg/mL , Thermo Fisher Scientific ) . For input gDNA extraction , gDNA was extracted from 2 mL of insertional mutant pool as previously described [41] . gDNA concentrations were determined with PicoGreen ( Thermo Fisher Scientific ) . Tn5 fragmentation of a total of 10 μg gDNA for output and 1 μg gDNA for the input was adapted from [20] , and performed as follows [21]: We combined 1 μg gDNA per 20 μL reaction with Tn5 transposase ( 150 ng/μL f . c . ) preloaded with 25-μM adapters in 1x TAPS buffer ( 50 mM TAPS-NaOH , 25 mM MgCl2 , 50% v/v DMF , pH 8 . 5 at 25°C ) and incubated the reaction mix in a thermocycler at 55°C for 10 minutes . We purified each reaction mix with a 1:1 ratio of Agencourt AMPure XP beads ( Beckman Coulter ) according to the manufacturer’s protocol and performed PCR with Phusion polymerase ( New England Biolabs ) using an adapter specific forward primer and a biotinylated insertion specific primer from 250 ng fragmented gDNA ( denaturation for 15 seconds at 95°C , annealing for 15 seconds at 65°C , elongation for 30 seconds at 72°C; repeated for 15 cycles; 1 minute final elongation ) . We pooled all PCRs of the same sample and purified 1/5 with Agencourt AMPure XP beads ( ratio 1:1; Beckman Coulter ) . The PCR amplicons eluted from each sample were split into 4 PCR reactions and amplified with nested primers to add Illumina compatible P5 and P7 ends ( 15 cycles , with 65°C annealing temperature and 30 seconds elongation at 72°C ) . The final PCR products were purified with Agencourt AMPure XP beads in a 1:1 ratio . The average fragment size was measured on a fragment analyzer ( Advanced Analytical Technologies , Inc . ) and library quality was controlled with qPCR . Illumina Sequencing was performed on a MiSeq platform with 75 PE conditions . We used a custom designed forward sequencing primer and the standard Illumina primers for reverse and index sequencing ( S2 Table ) . We confirmed the results of iPool-Seq for 3 candidate genes with individual infection assays , microscopy , and in vitro growth assays . The infection assay was performed as previously described [18] . In summary , for each insertional mutant , 3 replicates of U . maydis were grown overnight in YepsLight liquid medium ( 0 . 4% yeast extract , 0 . 4% peptone and 2% sucrose ) with 200 rpm agitation to an OD600 of 0 . 6–1 and adjusted to an OD600 of 1 in sterile water . We syringe-infected 7-day-old maize seedlings of the variety EGB with approximately 250 μL fungal suspension per plant . Symptoms were scored 7 days post infection ( dpi ) according to the published protocol [18] . Fungal leaf colonization was assessed 7 dpi via microscopy . Fungal hyphae were stained with WGA-AF488 ( Thermo Fisher Scientific ) and plant cell walls with propidium iodide ( Sigma-Aldrich ) as previously described [28] . Confocal microscopy was performed with the following settings: We utilized an LSM780 Axio Observer confocal laser scanning microscope with an LD LCI Plan-Apochromat 25x/0 . 8 Imm Corr DIC M27 objective ( Zeiss , Jena , Germany ) . WGA-AF488 was excited at 488 nm and detected at 500–540 nm; propidium iodide was excited at 561 nm and detected at 580–660 nm . For each sequenced library , adapter read-throughs were removed from the raw Illumina reads , UMIs were extracted and stored separately , and the reads ( lacking UMIs ) were mapped to the U . maydis reference genome [18] using NextGenMap [42] . The reads mapping to each flank ( 5' and 3' ) of each insertional mutant were grouped by UMI , and highly similar UMIs were merged to correct for sequencing errors [43] . UMIs with fewer reads than the error-correction threshold were removed as likely artifacts , and the number of surviving ( and thus likely true ) UMIs for each gene and flank were counted . To correct for biases caused by different detection losses ( i . e . , # undetected genomes/# total genomes ) between mutants and flanks , the mutant- and flank-specific losses were estimated from the observed mutant- and flank-specific distributions of reads per UMI ( S1 Supporting methods ) using the TRUmiCount algorithm ( see S1 Supporting methods for details ) [44] . To discern stochastic fluctuations from knockout phenotypes , the number of true UMIs detected in the output pool for neutral insertional mutants were assumed to follow a negative binomial distribution with mean μm=λ·nmin·1-lmout/1-lmin and ( inverse ) overdispersion parameter rm=nmin/1+d·nmin . Briefly , a neutral mutant m’s expected UMI count in the output pool thus depends on ( 1 ) the number nmin of detected UMIs in the input pool , ( 2 ) the estimated losses lmout and lmin for the output and input pool , and ( 3 ) a mutant-independent normalization factor λ to account for differences in total genome count between input and output samples . The sources of overdispersion of the output counts are ( 4 ) the ( Poissonian ) sampling uncertainty of the input pool counts nmin , and ( 5 ) random fluctuations of fungus proliferation accounted for by the mutant-independent parameter d . For each output pool , parameters λ and d were estimated ( see S1 Supporting methods for details ) by fitting the model to a reference set of presumed neutral mutants ( S3 Table ) , 2 one-sided p-values for the significance of depletion ( respectively , enrichment ) compared to the reference set were computed for each insertional mutant and transformed to q-values to control for the false discovery rate ( FDR ) [45] . Undetected insertional mutants ( i . e . , with zero UMIs ) in input pools were excluded from the analysis of the corresponding output pools . Undetected insertional mutants in output pools were not assigned p- or q-values . To quantify the change in virulence of an insertional mutant , its abundance in the output was first normalized to its abundance in the input ( thus assuming independent fates of the individuals in the input ) . Then , the log2-fold change between its normalized output abundance and the normalized output abundance of the internal reference set was computed ( see S1 Supporting methods for details ) . Further details on the modeling can be found in S1 Supporting methods . | Insertion mutant screens are widely used to identify genotype–phenotype relationships . In negative selection screens , a major limitation is the efficient identification of mutants that are lost or retained after selection . To identify these mutants , the two genomic sequences flanking the insertion cassette must be found . However , pinpointing these insertion flanks within a genome is like looking for a needle in a haystack; a problem that becomes even worse when several organisms form a biotrophic interaction . To overcome this hurdle , we developed insertion Pool-Sequencing ( iPool-Seq ) . With iPool-Seq , we were able to efficiently amplify and enrich insertion flanks from complex genomic DNA samples . This technique allows for the quantification of relative insertion mutant abundance before and after selection by next-generation sequencing ( NGS ) . We demonstrate the power of iPool-Seq with a negative selection screen by infecting maize with 195 candidate effector mutants of the fungal pathogen Ustilago maydis . We identified 28 virulence factors , of which 23 have not been previously described . iPool-Seq is extremely sensitive , cost- and time-efficient , and promises to be a powerful tool for identifying target genes in large selection screens . | [
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"mode... | 2018 | In vivo insertion pool sequencing identifies virulence factors in a complex fungal–host interaction |
Glossina fuscipes fuscipes is the major vector of human African trypanosomiasis , commonly referred to as sleeping sickness , in Uganda . In western and eastern Africa , the disease has distinct clinical manifestations and is caused by two different parasites: Trypanosoma brucei rhodesiense and T . b . gambiense . Uganda is exceptional in that it harbors both parasites , which are separated by a narrow 160-km belt . This separation is puzzling considering there are no restrictions on the movement of people and animals across this region . We investigated whether genetic heterogeneity of G . f . fuscipes vector populations can provide an explanation for this disjunct distribution of the Trypanosoma parasites . Therefore , we examined genetic structuring of G . f . fuscipes populations across Uganda using newly developed microsatellite markers , as well as mtDNA . Our data show that G . f . fuscipes populations are highly structured , with two clearly defined clusters that are separated by Lake Kyoga , located in central Uganda . Interestingly , we did not find a correlation between genetic heterogeneity and the type of Trypanosoma parasite transmitted . The lack of a correlation between genetic structuring of G . f . fuscipes populations and the distribution of T . b . gambiense and T . b . rhodesiense indicates that it is unlikely that genetic heterogeneity of G . f . fuscipes populations explains the disjunct distribution of the parasites . These results have important epidemiological implications , suggesting that a fusion of the two disease distributions is unlikely to be prevented by an incompatibility between vector populations and parasite .
Tsetse ( Diptera: Glossinidae ) are the sole vectors of pathogenic trypanosomes in tropical Africa , where they cause Human African trypanosomiasis ( HAT ) , or sleeping sickness . HAT is a zoonosis caused by the flagellated protozoa Trypanosoma brucei rhodesiense in East and Southern Africa and by T . b . gambiense in West and Central Africa , with the two diseases separated geographically more or less along the line of the Great Rift Valley [1] . The pathologies of the parasite subspecies are markedly different . Disease resulting from T . b . rhodesiense has a rapid onset leading to a fatal condition within the first 6 months of infection , while infection with T . b . gambiense produces a chronic condition with long symptom-free periods , which may last several years [2] . It is estimated by the World Health Organization ( WHO ) that there are still around 100 , 000 cases of HAT , with 60 million people at risk in 37 countries covering about 40% of Africa [3] , [4] . In addition to the human disease-causing parasites , the related species T . b . brucei , T . congolense and T . vivax are responsible for a fatal disease ( nagana ) in cattle , domestic pigs , and other farm animals . Nagana has restricted agricultural development and nutrient availability and has had a profound economic effect on the continent [5] , [6] , with an estimated annual economic loss of $4 . 5 billion US in livestock alone [7] . The only country with known foci of infection with both parasites is Uganda , with T . b . gambiense present in the north-west and T . b . rhodesiense found in the south ( Figure 1 ) [8] . Despite unrestricted movement of cattle and people , T . b . gambiense and T . b . rhodesiense have maintained a disjunct distribution . However , T . b . rhodesiense has recently spread westward into districts previously uninfected , so that only a 160 km belt remains between the two parasites ( Figure 1 ) [9]–[12] . Given the differences in disease pathologies and treatment of the two parasites , combined with the difficulty of timely diagnosis , the coalescence of the distribution of the chronic and acute forms of the disease will pose a critical problem for its control and treatment . The tsetse flies that are vectors of HAT belong to the genus Glossina . This genus is subdivided into three subgenera; morsitans , fusca , and palpalis , consisting of 33 currently recognized species and subspecies [13] . Although all species of tsetse are potential vectors , the major human disease vectors are members of the palpalis and morsitans complex [14] , which constitute riverine + forest and savannah flies , respectively . The fusca group is found in forest habitat and contains species that rarely feed on people . While control of savannah species can be sufficiently realized through traditional trapping technologies [15] , these are less effective for reducing riverine fly populations . In Uganda , where tsetse flies are estimated to infest approximately 2/3 of the total land area [16] , three major Glossina species are present: G . fuscipes , G . pallidipes , and G . brevipalpis [17] , belonging to the palpalis , morsitans and fusca subgenera respectively . As a result of human expansion and habitat reduction , G . pallidipes and G . brevipalpis populations were greatly reduced by the early 1980's , while G . fuscipes population densities have increased steadily [18] , [19] . G . fuscipes has a wide geographic distribution in sub-Saharan Africa and is comprised of three allopatric subspecies; G . f . fuscipes , G . f . martinii , and G . f . quanzensis . Of these , G . f . fuscipes has the broadest distribution . It is the only subspecies found in Uganda , located at the eastern margin of its range , which extends further east only along the shores of Lake Victoria in Western Kenya . The range of G . f . fuscipes extends westward across the central part of the African continent , and includes southern Sudan , Chad , the Central African Republic , the Democratic Republic of Congo ( DRC ) , and Angola . Isolated populations are also present in southwestern Ethiopia and southern Sudan [20] . G . pallidipes and G . brevipalpis , the two other Ugandan tsetse species , are at low densities and have ranges that include the country's drier forest patches . In contrast , G . f . fuscipes , a riverine species , has poor waterproofing abilities and low water reserves . Therefore , the majority of G . pallidipes and G . brevipalpis habitat is unsuitable for G . f . fuscipes . Instead , G . f . fuscipes is confined to hydrophytic habitats , such as forested patches along rivers and lacustrine environments [21] . G . f . fuscipes habitat extends throughout much of Uganda , including the narrow belt separating the two diseases , whereas this area is unsuitable to G . pallidipes and G . brevipalpis . Importantly , the latter two species feed mostly on wild animals , whereas G . f . fuscipes feeds on the wild and domestic animals that serve as reservoirs for the parasites , as well as humans [22]–[24] . This opportunistic feeding behavior , coupled with a high population density , causes G . f . fuscipes to be the most important human disease vector species in Uganda [11] , [25] . Population genetic data on a variety of tsetse species , including savannah ( G . morsitans , G . pallidipes , G . swynnertoni ) , forest ( G . palpalis palpalis ) , and riverine flies ( G . palpalis gambiensis ) indicate relatively high levels of genetic structuring [13] , [26]–[29] . This finding may not be unexpected given the patchy distribution of tsetse populations , even though tsetse have the ability to disperse hundreds of meters daily [30] , [31] . Although all studied tsetse show relatively high levels of genetic structuring , indicating low levels of gene flow , in comparison to other tsetse , G . swynnertoni , a savannah species from the highland of Tanzania , as well as G . p . gambiensis , a riverine species from West Africa , show the highest levels of gene flow . While estimates of gene flow among G . swynnertoni populations might be inflated because of a recent genetic expansion [26] , those between G . p . gambiensis populations are likely to be more accurate and reflect linear dispersal along water bodies bordering its patchy forest habitat [32]–[36] . The high level of genetic structuring observed in various tsetse species suggests that genetic heterogeneity in G . f . fuscipes populations could be responsible for the disjunct distributions of T . b . rhodensiense and T . b . gambianse in Uganda . That is , G . f . fuscipes could consist of genetically distinct populations , with the two Trypanosoma subspecies adapted to the specific genotypes found in their respective host populations . Therefore , we used nuclear ( microsatellite ) and mitochondrial DNA ( mtDNA ) data to analyze levels and patterns of genetic differentiation between G . f . fuscipes populations throughout Uganda , including populations from both the T . b . rhodesiense and T . b . gambiense diseases belts . These data are not only relevant with respect to the disjunct distribution of the two Trypanosoma subspecies , but through a comparison with the structure of other tsetse populations also provide insight into factors responsible for governing tsetse distribution and migration . These findings will contribute to the development and planning of tsetse intervention and disease control strategies .
G . f . fuscipes specimens were collected from nine locations in Uganda and one location in southern Sudan between March 2004 and August 2005 . Five of the Ugandan populations , i . e . Kamuli , Tororo , Lumino , Busia , and Iganga , are located south of Lake Kyoga; and four locations; i . e . Moyo , Soroti , Lira and Apac are located north of the lake ( Figure 1 ) . Moyo and Tambura are from the T . b . gambiense disease belt , whereas all other populations are from the T . b . rhodesiense disease belt . Samples were collected using non-impregnated biconical traps using standard procedures [37] . Either legs or abdomens were used for DNA extraction . See Table 1 for sample sizes . Extraction of genomic DNA was performed following [38] , or using the Easy DNA Kit ( Invitrogen ) . Primers to amplify five microsatellite loci were developed based on clones of a microsatellite enriched library . The library was in E . coli ( strain DH5 alpha ) transformed with recombinant plasmid pUC 19 . This library was constructed by the Genetic Identification Services , California , USA , using total genomic DNA extracted from the thoracic muscle of teneral flies from a G . f . fuscipes colony maintained at the International Atomic Energy Agency ( IAEA ) in Seibersdorf , Austria . The colony was established in Seibersdorf in 1986 and originated from flies collected in the Central African Republic . Primers for these loci were as follows: B03For 5′ GGAGGCTATGCTGATGAATG 3′ , B03Rev 5′ TGATGCGAAAAAGAGAAACAG 3′ , D05For 5′ TTTCCTTCCAGACGAACTG 3′ , D05Rev 5′ CTTGGTATGGTCGTACATGG 3′ , B05For 5′ CGCGCTTAGCTAGGAAACTC 3′ , B05Rev 5′ AACGATTTGCTGTCCTCGAT 3′ , D101For 5′ TGCCTTTACACTGCATACTACC 3′ , D101Rev 5′ AAAAAGAGGAGCAATGATGTG 3′ , D12For 5′ GTTGATGGTCACACAACATAAG 3′ , D12Rev 5′ TCAATGAGGAAAACTGAACTG 3′ . Polymerase Chain Reaction ( PCR ) amplifications were performed using fluorescently labeled forward primers in 20 µl reactions containing 1 µl template DNA , 2 µl 10X PCR buffer , 1 mM of MgCl2 , 0 . 5 µM dNTP's , 1 µM of each primer , and 1 unit of AmpliTaq Gold ( Applied Biosystems ) . PCR reactions were performed using the following program: 10 min of denaturation at 94 °C , followed by 35 cycles of 30 sec at 94 °C , 30 sec at 55 °C , and 30 sec at 72 °C . All reactions were followed by a final extension step of 20 min at 72 °C . PCR products were diluted 1/10 and run on an ABI 3730 automated sequencer . Genotype scoring was performed using Genemapper version 3 . 7 ( Applied Biosystems ) . PCR amplification of 349 bp of the mtDNA COII gene and 433 bp of the CytB gene using universal invertebrate primer pairs mtD13/mtD15 and mtD26/mtD28 respectively [39] was also achieved . PCRs were performed in 25 µl containing 1 µl of template DNA , 2 . 5 µl 10X PCR buffer , 0 . 8 mM dNTP , 2 mM MgCl2 , 0 . 4 µM of each primer , 1 µl of BSA and 1 unit of AmpliTaq Gold ( Applied Biosystems ) . Thermal cycler conditions consisted of an initial 10 min denaturation step at 94 °C , followed by 35 cycles of 1 min at 94 °C , 1 min at 48 °C , and 1 min at 72 °C . Reactions were terminated with a final extension time of 5 min at 72 °C . PCR products were purified with the Qiaquick PCR Purification Kit ( Qiagen ) and sequenced on an ABI 3730 automated sequencer ( Applied Biosystems ) following standard manufacturer protocols . Sequencing was performed in both the forward and reverse directions to minimize error . Average heterozygosity and allelic richness for the microsatellite loci were calculated using FSTAT [40] . The program Microchecker [41] was used to determine if null alleles were present in our data set . Tests of Hardy-Weinberg and linkage disequilibrium ( 10 , 000 permutations ) were performed using Arlequin version 3 . 1 [42] . Arlequin was also used to perform a locus-by-locus AMOVA of the microsatellite data set in which populations north and south of Lake Kyoga were grouped ( 10 , 000 permutations ) . Additionally , an AMOVA was performed in which the Moyo population , which transmits T . b . gambiense , was considered a single group and the other three northern populations , Apac , Lira and Soroti , which transmit T . b . rhodesiense , were clustered . Fst values between populations were calculated using the ENA method implemented in FreeNA [43] , which corrects for the presence of null alleles . Because this software only implements bootstrapping over loci to determine significance of Fst values , these were also calculated using Arlequin ( 10 , 000 permutations ) . Fst values calculated with FreeNA were used to construct a neighbor-joining tree in PAUP version 4 . 0b10 [44] , and to perform a Mantel test to determine if genetic and geographic distances between populations are correlated using Isolation By Distance Web Service version 3 . 14 ( 10 , 000 randomizations ) [45] . We used the program Structure [46] to determine the most likely number of clusters ( k ) within our dataset . These analyses were run for 350 , 000 generations with a burn-in of 100 , 000 . Seven runs were performed for k = 1 to 8 . This analysis was also performed including only the northern four populations to determine if populations transmitting different Trypanosoma parasites are differentiated . Sequence data from COII and CytB were edited with Sequencher 4 . 2 . 2 . ( Gene Codes Corporation ) and the data from the two genes were combined for all subsequent analyses . Alignments were performed with Clustal W [47] . MtDNA diversity indices , including the number of haplotypes ( H ) , haplotypic diversity ( h ) , and nucleotide diversity ( π ) , were estimated for each population using DnaSP v . 4 . 10 . 9 [48] . An AMOVA , in which populations north and south of Lake Kyoga were grouped , was performed following Excoffier et al . [49] using Arlequin version 3 . 1 [42] . For this analysis the Tambura ( Sudan ) population was excluded , but an additional AMOVA was performed in which this population was included as a third group . Additionally , the four northern populations were divided into two clusters , separating Moyo from Apac , Lira and Soroti , and the analysis was repeated . Arlequin was also used to calculate pairwise Fst values for the mtDNA data set following Excoffier et al . [42] . These Fst values were used to perform a Mantel test for Isolation-by-Distance using Isolation by Distance Web Service version 3 . 14 ( 10 , 000 randomizations ) [45] . A haplotype network was constructed using TCS version 1 . 18 . mac software package [50] . The 95% parsimony criterion was used for connecting haplotypes , and all instances of alternative connections were resolved using predictions from coalescent theory as described in Posada and Crandall [51] . To detect departure from selective neutrality and demographic equilibrium , a Fs test [52] and R2 test [53] were performed . If neutrality can be assumed and there is no genetic hitchhiking , these are the most powerful available tests to detect historical demographic expansions [53] , [54] . DNAsp v . 4 . 10 . 9 provides p-values based on a coalescent simulation algorithm ( 10 , 000 simulations were run ) . A significant p-value may be caused by violation of any of the assumptions in the null hypotheses; neutrality , constant population size , panmixia , or no recombination . Significant negative departures of these tests are caused by an excess of new mutations resulting from evolutionary forces such as selective sweeps or population expansion . Processes that maintain an excess of old mutations result in positive departures [55] . The mtDNA sequence data have been submitted to Genbank under accession nos EU559605-EU559621 ( COII ) and EU562262-EU562281 ( CytB ) .
Eight Ugandan G . f . fuscipes populations from the two disease belts were analyzed using five microsatellite loci . One population , Moyo , transmits T . b . gambiense , whereas the other seven populations transmit T . b . rhodesiense . Heterozygosity varied greatly between loci and between populations , with Kamuli fixed for a single allele at locus D12 , and a heterozygosity of 0 . 80 for locus D05 in Apac ( Table S1 ) . Heterozygosity averaged over all populations was 0 . 60 , 0 . 54 , 0 . 35 , 0 . 41 and 0 . 23 for loci D05 , B05 , D101 , B03 and D12 , respectively . The number of observed alleles was 11 , 5 , 6 , 13 and 6 , respectively . Allelic richness , the number of observed alleles per population corrected for sample size , ranged from 1 to 6 . 2 ( Table S2 ) . Out of 80 tests for linkage disequilibrium , three were significant after Bonferroni correction . Two of these tests were between locus B05 and D101 ( Lira and Iganga ) , and these two loci also showed significant linkage disequilibrium in Tororo and Soroti before Bonferroni correction . This could indicate that these two loci may be linked and are not fully independent markers . However , in two other populations these two loci were completely unlinked ( p = 1 ) . Out of 40 tests of Hardy-Weinberg disequilibrium , only locus D05 in the Tororo population showed a significant excess of homozygotes after Bonferroni corrections . That is , we found no evidence for subdivision within populations . An analysis using Microchecker detected the possible presence of null alleles in 13 out of 40 tests . Because this can bias estimates of genetic differentiation , Fst values were calculated using the ENA algorithm [43] , which corrects for null alleles , resulting in relatively unbiased Fst estimates ( Table 2 ) . Fst values were also calculated without correcting for null alleles ( Table 2 ) to determine if their presence created a substantial bias . Although , there are some differences between the corrected and uncorrected estimates of genetic differentiation , none were substantial , and no consistent bias was observed . The FreeNA software implements a significance test based on bootstrapping over loci , resulting in a very weak test . Our use of relatively few loci further reduced the test's power . No significant differentiation was observed between populations based on these tests . However , the much more powerful permutation tests implemented in Arlequin using the uncorrected data set detected highly significant differentiation in most pair-wise comparisons between populations . Importantly , genetic differentiation between populations from opposite sides of the Lake was always larger than between populations from the same side , and the few non-significant pairwise Fst values are between populations from the same side of Lake Kyoga . This pattern is also clear from the neighbor-joining tree constructed using these Fst values ( Figure 2 ) , which visualizes the genetic differentiation between populations . The populations from opposite sides of Lake Kyoga , henceforth referred to as northern vs . southern populations , cluster relatively close together , with a larger genetic differentiation between the two groups . A population clustering analysis using the program Structure clearly indicated that populations north and south of Lake Kyoga indeed belong to two separate clusters . For k = 1 the LR score = −2860 . 6 , whereas the LR score = −2324 . 9 for k = 2 , stabilizing between −2316 . 9 to −2371 . 5 for k = 3 to 8 . Therefore , the Structure analyses did not detect any additional substructure within the northern or southern groupings . In Figure 3 , the probability of each individual belonging to one of the two clusters is presented . In all , 93 . 5% of northern individuals and 93 . 7% of southern individuals were assigned to their respective group . This clustering of G . fuscipes populations is also clear from an AMOVA based on the microsatellite data ( Table 3 ) . Between group differences account for 26 . 9% of the variation , whereas differences within groups explain only 5 . 9% . We also performed a separate clustering analysis including only the northern populations . This was done to examine whether any further sub-structuring was present within this group , in which populations differ in the Trypanosoma parasite species they transmit . This analysis did not detect any additional sub-structuring within the northern group ( results not presented ) . A Mantel test of isolation-by-distance based on Slatkin's linearized Fst values [56] showed no significant correlation between genetic differentiation and geographic distance ( p = 0 . 10 ) ( see Figure S1 ) . A total of 782 bp from the CytB and COII genes were obtained for 202 G . f . fuscipes individuals belonging to nine populations . Two of these , Moyo and Tambura transmit T . b . gambiense , whereas the other seven populations transmit T . b . rhodesiense . We observed a total of 37 different haplotypes and haplotypic diversity within populations ranged from 0 . 552 to 0 . 830 , with an overall haplotypic diversity of 0 . 931 ( Table S2 ) . Nucleotide diversity ( π ) within populations ranged from 0 . 0016 to 0 . 0116 , with an overall nucleotide diversity of 0 . 0130 ( Table S2 ) . The TCS haplotype network shows a clear distinction between populations from the north and south of Lake Kyoga ( Figure 4 ) . No haplotypes are shared between these two groups and haplotypes from both groups of populations are separated by a minimum of 10 substitutions . One group of northern haplotypes could not be connected to the main network using the 95% parsimony criterion , however , if this criterion was relaxed to 90% these haplotypes connected to the northern group with a minimum of 13 substitutions . Alternative connections were removed following Posada and Crandall [51] . In one instance , the choice between two alternative connections within the northern group was dubious , but this did not affect the topology of the network with respect to the grouping of northern and southern populations . Although most Sudan haplotypes cluster with northern Uganda samples , as expected based on geography , one Sudanese haplotype surprisingly falls within the southern group . Fst values based on the mtDNA data set between almost all populations were highly significant ( Table 4 ) . Within the southern group Fst values ranged between 0 . 010 and 0 . 504 . Within the northern group , Fst values ranged between 0 . 131 and 0 . 600 , and between the northern and southern group Fst values ranged from 0 . 642 to 0 . 911 . An AMOVA grouping northern and southern populations also clearly indicated this large differentiation between the northern and southern groups ( Table 3 ) . Differences between the two groups accounted for 71 . 74 % of the observed variation , whereas difference between populations within groups accounted only 8 . 30% of the variation . Including the Sudan population ( Tambura ) as a third group did not change these results markedly ( Table 3 ) . In contrast to the microsatellite data set , a significant correlation between the geographic distance and linearized Fst values between populations was found for the mtDNA data set ( p = 0 . 020 ) ( see Figure S1 ) . No departure from selective neutrality and demographic equilibrium ( Table 1 ) was detected for any population using the Fs and R2 tests .
Both the microsatellite and mtDNA data analyses revealed high levels of differentiation between the studied G . f . fuscipes populations . Almost all pair-wise comparisons of Fst values were significant ( Table 2 and 4 ) , indicating some restriction in gene flow between populations . However , the most striking result , which is indicated by both the mtDNA and microsatellite data , is the strong differentiation between the populations north and south of Lake Kyoga . Interestingly , this north-south structuring of G . f . fuscipes populations does not coincide with the distribution of T . b . rhodesiense and T . b . gambiense ( Figure 1 ) . Our analyses indicate that the Moyo ( microsatellite and mtDNA ) and Tambura ( mtDNA only ) populations lying in the T . b . gambiense belt are no more differentiated from the northern populations ( Apac , Lira , and Soroti ) lying in the T . b . rhodesiense belt , as those are from each other . That is , although populations within the northern and southern clusters are in most cases significantly differentiated , we found no evidence of genetic differentiation between tsetse transmitting T . b . gambiense vs . T . b . rhodesiense , other than would be expected based on their geographic separation . Our analyses indicated that the microsatellite data set included null alleles . This could have affected the data analysis and have lead to an overestimation of genetic differentiation . However , a comparison of Fst values using a method that does not take into account the presence of null alleles vs . the ENA method , indicates that no substantial bias was introduced . Additionally , the number of microsatellite loci included in the study was rather small , and heterozygosity was low at locus D12 . Therefore , the power of the microsatellite analysis was low , and finer scale patterns of population structuring probably could not be detected in this study . However , the fact that even with this low power we observe highly significant clustering of populations north and south of Lake Kyoga , combined with the observation that the mtDNA data set shows exactly the same pattern , clearly indicates that G . f . fuscipes in Uganda is subdivided into at least two distinct clusters with very limited gene flow between them . The forces that maintain the separation of these lineages seem to have been in place for some time since 10 fixed substitutions are present between northern and southern Ugandan populations . The levels of genetic variation observed for both the mtDNA and the microsatellite markers between G . f . fuscipes populations are comparable to those for other Glossina species and subspecies . Populations of savannah species , such as G . morsitans and G . pallidipes , tend to be substantially structured . This is consistent with the patchy distribution of most tsetse populations [27] , [29] , [35] , [57]–[60] , but at odds with results from ecological work that suggest a rate of population expansion of about 7 km/year [31] , [61] , [62] . This high degree of genetic structuring , despite a high dispersal capacity , is thought to be due to dramatic reductions in tsetse population sizes in recent times . This was caused by the rinderpest epidemic in the late 1890s , which killed over 90% of livestock , followed by additional epidemic episodes in the early part of the 20th century , as well as more recent HAT control measures [58] , [59] , [63] , [64] . Since the early 20th century , after episodes of the rinderpest epidemics ceased , tsetse populations have rebounded , and are expanding from highly scattered relict populations . Population recovery has also been assisted by reduced control efforts due to unstable political and economic conditions . In contrast to the strong genetic structuring found in savannah and forest tsetse species , the riverine species G . p . gambiensis in West Africa has low levels of genetic differentiation between populations [32] , [33] , [35] , [36] . This species lives in humid savannah and can easily disperse through the forests along riverbanks . Such linear dispersal through suitable habitat was also observed for G . palpalis , for which mark-release-recapture studies indicate that it can disperse up to 21 km in 5 days along gallery forests [32] , [65] , but only 8 km along rivers with bare banks [66] . However , gene flow among G . gambiensis populations seems to occur not only within single river systems , but also among populations distributed in the different river basins of Mali [67] . This species seems to be expanding or contracting its populations in a pattern that follows the seasonal fluctuations of water level and temperature , resulting in seasonal fusions of the populations . While G . p . gambiensis flies experience high levels of gene flow , suggesting that an isolation-by-distance ( IBD ) model may best explain their population structure , for a few savannah species the correlation between genetic differentiation and geographic distance was weak , suggesting that an island model , rather than IBD , may best describe the population structure of these tsetse species [29] , [59] . In our study we found a significant correlation between genetic and geographic distance when we analyzed all Uganda populations using the mtDNA data set ( Figure S1 ) . However , this does not necessarily imply that an IBD model best describes the causal factors associated with the spatial distributions of these populations . The observed IBD pattern is most likely an artifact of the genetic structure caused by Lake Kyoga . That is , the average geographic distance between populations on the two sides of the lake is larger than the average geographic distance between populations on the same side . If more populations were available , a more appropriate test would be to include only populations from either the northern or southern cluster . This issue will be explored in more detail when denser geographic sampling becomes available . While Lake Kyoga is the main factor in the genetic structuring of Ugandan G . f . fuscipes populations , the limited gene flow between populations within the northern and southern group suggests that the patchy distribution of G . f . fuscipes populations likewise plays a role in shaping the population structure of these vectors . In this regard , the riverine G . f . fuscipes is more similar to the savannah species G . morsitans and G . pallidipes , than it is to the other riverine species G . p . gambiensis . This observation is also supported by Krafsur et al [68] , who concluded that the dispersal tendencies of G . f . fuscipes are either overestimated , or thwarted by unapparent environmental circumstances in the habitats interspersing the populations included in their study . Consequently , forces of genetic drift in East African G . f . fuscipes are much stronger than gene flow . It is worth noting that the presence of 10 fixed differences in the mtDNA , with the exception of a single Sudanese haplotype , implies an ( almost ) complete absence of gene flow between the northern and southern populations . However , for the microsatellite makers , even though substantial differences in allele frequencies were observed between northern and southern populations , and each locus carried at least some alleles that were unique to either the north or south , no fixed differences were found . This discrepancy between the mtDNA and microsatellites could indicate a difference in dispersal between males and females . If dispersal is limited to males , fixed differences could accumulate in the maternally inherited mtDNA , whereas even a low number of migrating males would prevent the accumulation of fixed differences in the nuclear microsatellites . However , the lack of fixed differences in the microsatellite markers may also reflect a bias in the loci studied , as variability was one of the criteria for selecting the loci used for this study . Alternatively , the fast , step-wise mode of evolution of microsatellites with its tendency to create homoplasies could explain the lack of fixed microsatellite differences between the north and south . Within the nine Ugandan populations , both microsatellite and mtDNA data suggest that genetic diversity is relatively high with no evidence of genetic sub-structuring ( Table S1 , S2 ) . Given that levels of genetic diversity are directly related to effective population size , this suggests that G . f . fuscipes population sizes in Uganda may be substantial . Although there is evidence of sub-structuring within single populations for some forest populations of G . p . palpalis in western Africa [34] , results from other tsetse species suggest that single locations tend to have genetically homogeneous populations [27] , [57] . A recent report on mtDNA variation in three G . f . fuscipes populations from the border region between Uganda and Kenya also indicates that single locations have genetically homogeneous G . f . fuscipes populations [68] . The population genetic parameters ( H , h , theta ) we report for G . f . fuscipes populations based on the mtDNA diversity ( Table 1 , Table S2 ) are comparable to those reported by Krafsur et al . [68] . Our estimates of both mtDNA and microsatellite variation ( Table S1 ) are similar , although at the high end , to those reported for savannah or riverine tsetse species ( see Table 5 ) . However , genetic diversity estimates for southern Africa populations of both savannah and forest tsetse species tend to be substantially lower [26] , [27] , [29] , [58] . This is thought to be the result of a dramatic reduction in tsetse population sizes due to the rinderpest epidemic of the late 1890s . This epidemic affected the southern regions of the African continent more severely than others [63] , [64] . The level of genetic variation observed in our study indicates that G . f . fuscipes in Uganda , like other tsetse from central and western Africa , does not appear to have been severely affected by this event . Furthermore , we found no evidence for bottlenecks or recent population expansions in Ugandan G . f . fuscipes populations . This is in congruence with data collected by Krafsur et al [68] . Various tsetse populations have been shown to carry infections of the endosymbiont Wolbachia [69] , [70] . This symbiont , which has infected a wide-range of invertebrate hosts , can cause a variety of reproductive abnormalities , one of which is termed cytoplasmic incompatibility ( CI ) and results in death early in embryogenesis . In an incompatible cross , the sperm enters the egg but does not successfully contribute its genetic material to the potential zygote , and in most species none or very few eggs hatch . Different strains of Wolbachia have been shown to generate such incompatibility . Preliminary studies of G . f . fuscipes in Uganda indicate the presence of Wolbachia infections ( Aksoy , unpublished data ) . These infections also have the propensity to influence population structure . Future studies on the identification of the Wolbachia strains present in the Northern and Southern G . f . fuscipes populations can provide additional information on the genetic differentiation between them . Knowledge on the population structure of tsetse can provide specific guidance on the design of the most effective and economic vector control efforts , as well as on the sustainability of the control efforts . For example , the trapping systems are most effective if the genetic data shows the presence of highly structured populations in the target areas , indicating a minimal risk of re-invasion . Information on genetic differentiation also provides guidance to ongoing control projects as to where the most vulnerable populations reside , and where special effort needs to be given to incorporate physical barriers to prevent reinvasions . For example , our data indicate that tsetse control on either side of Lake Kyoga , is not likely to be affected by migration across or around the lake . These results also have at least two important epidemiological implications . First , from the vector point of view there is no genome-wide genetic discontinuity at putatively neutral loci across G . f . fuscipes populations that can explain the existence of an historical break in the Trypanosoma distributions . This separation remains puzzling given unrestricted movement of animals and people across this region . Second , and of more immediate concern , given the narrow and progressively reducing corridor that separates the two diseases , our results imply that a fusion of the T . b . rhodesiense and T . b . gambiense ranges , currently less than 120 km apart , is unlikely to be prevented by genetic incompatibilities between vector and parasites . Our data suggest that the genetic structuring found among G . f . fuscipes Ugandan populations is more likely to reflect past geological and/or biogeographic events , and is not correlated with the subspecies of Trypanosoma parasite they transmit . | The two types of sleeping sickness in West and East Africa are markedly distinct , require different treatments , and are caused by different parasites . The only country where both parasites are present is Uganda , where they are separated by a narrow 160 km disease-free belt . Because there is no restriction on the movement of humans and animals between the two disease zones , this separation is puzzling . We asked whether this disjunct distribution can be explained by variation within the tsetse fly that is largely responsible for transmitting both diseases in Uganda , Glossina fuscipes fuscipes . We therefore examined whether this tsetse subspecies is genetically uniform across Uganda . Our results indicate that G . f . fusicipes is not genetically different between the two disease zones , but there are clear genetic differences between northern and southern populations , which are separated by Lake Kyoga . Therefore , it is unlikely that variation in the tsetse fly determines the distribution of the two parasites . This implies that the two diseases may fuse in the near future , which would greatly complicate diagnosis and treatment of sleeping sickness in any potential area of overlap . | [
"Abstract",
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] | 2008 | High Levels of Genetic Differentiation between Ugandan Glossina fuscipes fuscipes Populations Separated by Lake Kyoga |
Borrelia burgdorferi , the spirochetal agent of Lyme disease , is a vector-borne pathogen that cycles between a mammalian host and tick vector . This complex life cycle requires that the spirochete modulate its gene expression program to facilitate growth and maintenance in these diverse milieus . B . burgdorferi contains an operon that is predicted to encode proteins that would mediate the uptake and conversion of glycerol to dihydroxyacetone phosphate . Previous studies indicated that expression of the operon is elevated at 23°C and is repressed in the presence of the alternative sigma factor RpoS , suggesting that glycerol utilization may play an important role during the tick phase . This possibility was further explored in the current study by expression analysis and mutagenesis of glpD , a gene predicted to encode glycerol 3-phosphate dehydrogenase . Transcript levels for glpD were significantly lower in mouse joints relative to their levels in ticks . Expression of GlpD protein was repressed in an RpoS-dependent manner during growth of spirochetes within dialysis membrane chambers implanted in rat peritoneal cavities . In medium supplemented with glycerol as the principal carbohydrate , wild-type B . burgdorferi grew to a significantly higher cell density than glpD mutant spirochetes during growth in vitro at 25°C . glpD mutant spirochetes were fully infectious in mice by either needle or tick inoculation . In contrast , glpD mutants grew to significantly lower densities than wild-type B . burgdorferi in nymphal ticks and displayed a replication defect in feeding nymphs . The findings suggest that B . burgdorferi undergoes a switch in carbohydrate utilization during the mammal to tick transition . Further , the results demonstrate that the ability to utilize glycerol as a carbohydrate source for glycolysis during the tick phase of the infectious cycle is critical for maximal B . burgdorferi fitness .
Borrelia burgdorferi is the spirochetal agent of Lyme disease , the most frequently reported vector-borne disease in the United States [1] . In the Northeastern United States , B . burgdorferi is transmitted between mammalian hosts by the bite of the black legged deer tick , Ixodes scapularis , with the white-footed mouse ( Peromyscus leucopus ) serving as the primary reservoir host [2] , [3] . The transmission cycle is as intricate as the life of the tick itself . B . burgdorferi are acquired by uninfected larvae feeding on an infected small mammal [4] . This is essential for the continued maintenance of B . burgdorferi in nature , since there is no transovarial transmission in Ixodes spp . [5] , [6] . The bacteria remain in the midgut of engorged larval ticks through the molt . The infected nymph will take a blood meal on a mammal , at which point B . burgdorferi multiply and begin their migration from the tick midgut to the salivary glands from which they are transmitted to a mammalian host [7]–[9] , thereby completing the enzootic cycle . B . burgdorferi must adjust its gene expression program in response to the different physiological cues encountered during the natural enzootic cycle . In bacteria , regulation of gene expression in response to environmental cues is often mediated by two-component systems ( TCS ) and/or alternative sigma factors [10] , [11] . The B . burgdorferi genome encodes only two alternative sigma factors and two TCS [12] , [13] . Thus , B . burgdorferi must orchestrate its complex expression programs with a limited repertoire of known transcriptional regulators . Studies by Norgard and co-workers demonstrated a link between one TCS , Hk2-Rrp2 , and the alternative sigma factors RpoN and RpoS [14] , [15] . The expression of several virulence genes , including ospC , dbpA and bbk32 , are dependent on RpoS [14] , [16] , [17] . RpoS is also essential for repression of genes whose expression is required during the tick phase , but not in the mammalian host [17] , [18] . BB0647 ( BosR , Fur ) has also been shown to play a role in RpoN-dependent expression of rpoS [19]–[21] . Less is currently known regarding the second TCS , consisting of Hk1 and Rrp1 , but recent studies have begun to elucidate the processes that are regulated by this TCS [22]–[24] . In particular , Rrp1 has been shown to be responsible for production of bis- ( 3′-5′ ) -cyclic dimeric guanosine monophosphate ( c-di-GMP ) and mutagenesis of Rrp1 results in alteration of expression for a substantial number of genes , including those involved in uptake and dissimilation of glycerol [22] , [23] , [25] . Different carbohydrates are selectively available to B . burgdorferi during its enzootic cycle . Glucose is the primary carbohydrate constituent in mammalian blood [26] , [27] and B . burgdorferi can use glucose to support growth [28] . Ticks rely on a high concentration of carbohydrates and other nutrients available in the blood meal for molting and successful oogenesis [29] , [30] . During feeding , ticks create a peritrophic matrix above the epithelial cell layer , which serves both as a compartment to trap the blood meal and as a barrier to prevent invasion by microorganisms that accompany the blood meal . However , the peritrophic matrix is permeable to hexose sugars [29] , [31] . Once hexoses permeate across the matrix , they are sequestered by midgut epithelial cells during larval feeding [29] , [31] . Consequently , nutrients present in the blood meal are rapidly depleted during larval feeding and are likely non-existent in an unfed nymphal midgut . Therefore , spirochetes resident in the midgut must identify and utilize alternative carbohydrates until the unfed nymph takes its next blood meal . Glycerol , a diffusible carbohydrate , is a readily available nutrient in the tick . Glycerol is produced by Ixodes spp . and serves as a colligative antifreeze for tick survival during the winter [32]–[34] . B . burgdorferi encodes a putative glycerol utilization operon consisting of three genes . glpF ( bb0240 ) encodes a putative transmembrane facilitator protein that mediates the entry of free glycerol into the cell . glpK ( bb0241 ) encodes a putative kinase that would produce glycerol 3-phosphate ( G3P ) which would be the substrate for glycerol 3-phosphate dehydrogenase ( G3PDH ) , an enzyme putatively encoded by the third gene in the operon , bb0243 . The resulting product , dihydroxyacetone phosphate , can enter glycolysis through the action of triose phosphate isomerase and ultimately result in the net production of one ATP molecule per original glycerol molecule [12] , [28] . Alternatively , G3P may be converted to phosphatidic acid through the action of two enzymes , BB0327 ( G3P acyltransferase ) and BB0037 ( Lysophosphatidic acid acyltransferase ) ; this pathway is required for phospholipid biosynthesis and production of new cell membrane [12] ( Figure 1 ) . Three lines of evidence suggest that glycerol utilization may be important during the vector phase of the enzootic cycle . Ojaimi et al . reported that all genes of the glycerol utilization operon are more highly expressed during in vitro growth in BSK-II medium at 23°C as compared to growth at 35°C [35] . Caimano et al . demonstrated that repression of glp operon expression is dependent on RpoS within the mammalian host [17] . Moreover , constitutive expression of the glp operon partially restores the ability of Rrp1-deficient B . burgdorferi to survive within feeding ticks [23] . In order to elucidate the role of glycerol uptake and utilization by B . burgdorferi during its natural life cycle and the regulatory events that govern glp operon expression , the gene predicted to encode G3PDH ( bb0243 ) was disrupted and the effects of mutagenesis were evaluated in vitro and during infection of ticks or mice . The results demonstrate that the ability to utilize glycerol as a carbohydrate for use in the glycolytic pathway during the tick phase of the infectious cycle is critical for maximal B . burgdorferi fitness .
The B . burgdorferi G3PDH genomic sequence has been annotated to putatively encode the anaerobic form of the enzyme based on its similarity to the anaerobic G3PDH ortholog of Haemophilus influenzae strain Rd ( glpA ) [12] . Other organisms containing an anaerobic GlpA ( such as E . coli ) contain two additional subunits as part of the functional G3PDH enzyme; GlpB , a subunit involved in FMN binding [36] and GlpC , a small membrane anchoring subunit [37] . Together , the individual protein molecules form a functional GlpABC heterotrimer [36] . Whole genome sequencing of B . burgdorferi failed to reveal putative genes with homology to any known glpB or glpC orthologs [12] . Further , BLASTP analysis revealed no orthologs in B . burgdorferi with similarity to either E . coli strain K12 or H . influenzae strain Rd GlpB or GlpC . The tertiary structure of B . burgdorferi G3PDH was predicted using the SWISS-MODEL server [38]–[40] by comparison to E . coli K12 aerobic GlpD and anaerobic GlpA , as well as H . influenzae strain Rd anaerobic GlpA . B . burgdorferi G3PDH autoaligned with E . coli aerobic GlpD ( PDB 2QCU ) , but not with E . coli GlpA [41] ( Figure 2 ) . E . coli anaerobic GlpA and H . influenzae GlpA auto-aligned to the anaerobic GlpA of Bacillus halodurans ( PDB 3DA1 ) [42] ( Figure 2 ) . The modeling predicts that B . burgdorferi G3PDH and E . coli aerobic GlpD share similar tertiary structures . Yeh et al . have described 14 amino acid residues that participate in the E . coli GlpD active site based on a 1 . 75 Å structural model [41] . B . burgdorferi G3PDH contains conserved residues at 12/14 positions , in contrast to the E . coli and H . influenzae GlpA proteins ( 9/14 ) . Taken together , the bioinformatic analyses suggest that B . burgdorferi G3PDH has greater similarity to aerobic forms of the enzyme . We propose that annotation of bb0243 should be changed to indicate that it putatively encodes an aerobic GlpD and B . burgdorferi G3PDH is referred to as GlpD in the remainder of this report . The physical linkage of bb0240 , bb0241 , and bb0243 in the B . burgdorferi chromosome suggests that these genes comprise an operon [35] . RT-PCR analysis using RNA extracted from B . burgdorferi strain B31-A3 revealed that these genes are transcribed as a single operon ( Figure 3 ) . Ojaimi et al . reported that the B . burgdorferi glycerol operon is more highly transcribed at 23°C relative to transcript levels in cells grown at 35°C [35] . In order to explore if this increased transcript level is reflected in protein , strain B31-A3 whole cell lysate was tested to determine the protein expression levels at these two temperatures . Immunoblot analysis revealed that when B . burgdorferi strain B31-A3 was grown at 25°C , 7-fold more GlpD was generated compared to the level in cells grown at 37°C ( Figure 4 ) . To explore the possibility that expression may be differentially regulated in vivo , glp transcript levels were measured in infected ticks or mouse joints by real time RT-PCR; transcription of ospA and ospC was monitored as a control . Expression of the latter genes followed the expected pattern; ospA was expressed exclusively in ticks and ospC transcript was detected only in feeding nymphs and mouse joints ( Figure 5 ) . glpD expression was substantially higher during all tick stages ( fed larvae , 3 . 68±2 . 72 copies/10 copies of flaB; unfed nymphs , 5 . 31±4 . 42; fed nymphs , 4 . 97±0 . 74 ) than in mouse joints ( 1 . 45±1 . 98 copies/10 copies of flaB ) . A similar expression pattern was observed for glpF , the first gene in the operon ( fed larvae , 4 . 42±1 . 07 copies/10 copies of flaB; unfed nymphs , 1 . 48±0 . 61; fed nymphs , 3 . 70±1 . 89; mouse joint , 0 . 13±0 . 23 ) ( Figure 5 ) . Caimano et al . showed that transcription of glp operon genes is subject to RpoS-dependent repression [17] . This was confirmed at the protein level for GlpD as shown in Figure 6 . Wild-type or RpoS mutant cells were grown in vitro at either 23°C or 37°C or in dialysis membrane chambers ( DMCs ) implanted in rat peritoneal cavities . Induction of OspC expression and repression of OspA expression in DMCs confirmed that B . burgdorferi attained the host-adapted state and abrogation of these changes in expression in the RpoS mutant showed that these alterations were dependent on RpoS , as expected . GlpD expression was virtually abolished in wild-type B . burgdorferi grown in DMC and this effect was not observed in the RpoS mutant cells ( figure 6 ) . To study the role of glycerol utilization in B . burgdorferi , glpD , the distal ORF in the glycerol operon was inactivated in strain B31-A3 by disruption with a flgB-aadA cassette inserted at residue K149 ( Figure 7 ) . Three mutants , two with the flgB-aadA cassette in the same orientation as the operon ( CP176 , CP177 ) and one with the insert in the opposite orientation ( CP257 ) , were isolated ( Figure 8A ) . Southern blot analysis confirmed a disruption in glpD and showed that recombination occurred by a double crossover event in all three mutants ( Figure 8B ) . Western blot analysis revealed that GlpD was absent in the mutants ( Figure 9 ) . Analysis of plasmid content of the wild type by PCR revealed that it lacked lp5 and cp9 and contained all other B31 linear plasmids , including those essential for murine infectivity . GlpD mutants had the same plasmid profile as the parental strain ( data not shown ) . Repeated attempts to isolate a complemented mutant strain were unsuccessful . Most experiments described below were carried out with all three isolated glpD mutants . Mutants CP176 and CP177 were isolated from one transformation and CP257 was obtained independently , thereby mitigating the concern that the observed mutant phenotypes were the result of a second site mutation . To begin to characterize the role of GlpD in B . burgdorferi physiology , growth of glpD mutants was compared to that of wild-type B31-A3 in BSK-II , an undefined , enriched medium that contains glucose as the principal carbohydrate source [43] . No differences in final cell density were detected between wild-type and glpD mutants at either 25°C ( 1 . 3×109 and 1 . 1×109 , respectively ) or 37°C ( 1 . 4×109 and 1 . 3×109 , respectively ) . In addition , no difference in growth characteristics was observed ( data not shown ) . Previous studies have shown that N-acetyl glucosamine ( GlcNAc ) is required for growth of B . burgdorferi in vitro [44]–[46] . There were no differences in growth characteristics between B31-A3 and CP176 grown in a modified BSK-II medium that did not contain glucose but had GlcNAc as the carbohydrate source ( BSK-lite [28] ) ( Figure 10A ) . In contrast to growth in BSK-II with GlcNAc only or medium supplemented with glucose ( data not shown ) , there was a significant difference in growth between wild type and glpD mutants when glycerol was supplied as the principal carbohydrate source . B31-A3 reached a significantly higher cell density in BSK-glycerol medium compared to CP176 when grown at 25°C ( 6 . 4×108 and 1 . 1×108 , respectively; P<0 . 001 ) ( Figure 10B ) . Interestingly , this effect was observed only at 25°C; when cultivated at 37°C , the growth characteristics of wild type and CP176 were indistinguishable . Indeed , B31-A3 cultures achieved significantly higher cell densities at 25°C as compared to 37°C in BSK-glycerol medium ( 6 . 4×108 and 9 . 1×107 , respectively; P<0 . 001 ) . These experiments were repeated with the other two independent glpD mutants ( CP177 , CP257 ) with essentially identical results ( data not shown ) . These findings suggest that B . burgdorferi can utilize glycerol to support enhanced growth at the lower temperature . This observation would be consistent with the elevated expression of GlpD at 25°C ( Figure 4 ) . In order to determine whether the absence of GlpD affects the pathogenic properties of B . burgdorferi , C3H/HeJ mice were needle inoculated with 1×104 cells of either wild type or glpD mutant . All mice in both the wild type and glpD mutant groups were infected and were seropositive by four weeks post-inoculation ( Table 1 ) . Unfed larvae were allowed to feed to repletion on these infected mice to allow spirochete acquisition by ticks . Infected fed larvae that molted to nymphs were fed to repletion on naïve C3H/HeJ mice . Viable spirochetes were recovered from all mice that were fed on by either wild type- or glpD mutant-infected ticks and seroconverted by 4 weeks post-feeding ( Table 1 ) . These results demonstrate that GlpD is not required for murine infection by B . burgdorferi . Further , GlpD-deficient spirochetes were acquired by larvae fed on infected mice , persisted through the molt and were transmitted to naïve mice by infected nymphs . The enhanced growth of B . burgdorferi at lower ambient temperature in vitro when glycerol is the principal carbohydrate source , elevated expression of GlpD at the lower temperature and its RpoS-dependent repression in DMCs suggested that glycerol may be an important nutrient for B . burgdorferi during the tick phase of its life cycle . Therefore , the effect of glpD disruption was explored more extensively in infected ticks . Naïve , unfed larvae were placed on mice infected with either B31-A3 or CP176 , allowed to feed until repletion and molt to the nymphal stage . Spirochete loads in infected ticks were measured by qPCR ( Table 2 ) . Larvae infected with either B31-A3 or CP176 had similar spirochete loads ( approximately 700 spirochetes/larvae ) . Spirochete numbers in wild type-infected ticks increased slightly after larval molting to nymphs but decreased in nymphs infected with any of the glpD mutant strains . This resulted in a significant five-fold decrease in CP176 density in unfed nymphs compared to the wild-type ( Table 2 ) . Further , in independent experiments , CP177 and CP257 had an identical phenotype to that observed for CP176 , i . e . spirochete densities were significantly lower after molting as compared to spirochete loads in B31-A3-infected ticks ( data not shown ) . Infected nymphs were fed on naïve mice and spirochete loads were measured in the resulting fed nymphs . As expected , spirochete numbers increased substantially during nymphal feeding in both wild type- and CP176-infected nymphs , although the spirochete burdens in the glpD-infected engorged nymphs were significantly lower than in nymphs infected with the parental strain ( P< . 02 ) ( Table 2 ) . These results suggest a role for glycerol utilization by B . burgdorferi as an important factor for spirochete maintenance during transtadial transition . As previously described , wild type- and glpD mutant-infected nymphs are equally capable of transmitting B . burgdorferi to , and causing infection in , mice ( Table 1 ) . However , those studies were conducted by allowing nymphs to feed to repletion . A feeding nymph will attach and feed on a host for 72 hours or longer [47] . During this time , replicating B . burgdorferi surround midgut epithelial cells , penetrate the midgut basement membrane , and enter the hemocoel and salivary glands from which they are ultimately transmitted to the mammal [8] , [9] . Therefore , replication is a critical step in spirochete transmission from the vector to the mammalian host . Since the density of glpD mutant spirochetes decreases as a result of molting and was five-fold lower than in wild type-infected unfed nymphs , we reasoned that nymphs harboring glpD mutant spirochetes would require a longer feeding period before transmission to the host due to its delayed exit from the tick midgut . To explore this possibility , B31-A3- and CP176-infected nymphs were placed on naïve mice , allowed to begin feeding , but forcibly removed at different time points post-attachment . Mice were then monitored for evidence of infection . In a pilot experiment , nymphs were fed on naïve mice for 65 hours; 2/2 mice fed on by B31-A3-infected nymphs became infected , whereas 0/3 mice fed on by CP176-infected nymphs acquired infection . Based on this pilot study , B31-A3- or CP176-infected unfed nymphs were placed on the outer ear of naïve C3H/HeJ mice and allowed to feed for either 24 , 48 , 55 , 62 or 72 hours or collected at drop off ( >72 hours ) . Ticks were removed at each time point and spirochete load was determined by qPCR . Results presented in Figure 11 demonstrate that CP176 experienced a lag in replication and achieved significantly lower spirochete loads at times beyond 48 hours of feeding ( P<0 . 001 ) . At these points , spirochete loads per tick were 3 . 5–5 fold lower in CP176-infected ticks than in those infected with B31-A3 ( e . g . , at 55 hours of feeding spirochete loads were 42 , 633 and 8 , 581 for B31-A3 and CP176-infected nymphs , respectively ) ( Figure 11 ) . Mice were also monitored for infection . Results demonstrate that mice fed on by wild type-infected nymphs were infected by 62 hours of feeding . In contrast , CP176-infected nymphs produced infection in mice only after at least 72 hours of feeding ( Table 3 ) . These data suggest that wild type-infected nymphs are more readily able to infect naïve mice due to a more rapid increase in spirochete density induced on commencement of tick feeding . Further , disruption of glycerol utilization results in reduced fitness of the spirochete during the tick phase and spirochetes that are unable to utilize glycerol are at a disadvantage for transmission to a mammalian host . Chitobiose is a di-GlcNAc molecule that is a component of the peritrophic matrix and tick chitin [45] , [46] , [48] , [49] . The B . burgdorferi genome contains open reading frames that encode gene products that can mediate chitobiose transport and metabolism [12] , [46] , [48] , [49] . These include the three subunits of a chitobiose transporter ( BBB04-BBB06 ) , a putative chitobiase ( BB0002 ) and NagA and NagB ( BB0151 and BB0152 ) . In combination , the actions of these gene products would result in production of glucose 6-phosphate that could enter the glycolytic pathway ( Figure 1 ) . Both chitobiose and chitin can support B . burgdorferi growth in vitro [45] , [46] , [48] , [49] . Therefore , the transcript levels for chbC ( bbb04 ) , which encodes subunit C of the chitobiose transporter , were also measured to determine whether chitobiose utilization by B . burgdorferi may be important during the tick phase of the enzootic cycle . Substantially higher expression of chbC occurred during the various tick stages ( fed larvae , 5 . 10±7 . 00 copies/10 copies of flaB; unfed nymphs , 4 . 42±2 . 33; fed nymphs , 2 . 87±0 . 36 ) as compared to expression in mouse joints ( 0 . 59±0 . 71 copies/10 copies of flaB ) ( figure 5 ) .
On acquisition by feeding larvae from an infected mammal , B . burgdorferi must initially adapt to the new host ( i . e . tick ) environment . The spirochete must then survive the tick molting process and endure a substantial period in a nutrient-poor milieu ( unfed nymph ) . This is not a period of metabolic dormancy since several studies , including our own , demonstrate that B . burgdorferi gene expression is modulated in different tick developmental stages and that expression of some genes is higher in unfed nymphs than in fed nymphs [17] , [50] , [51] . During the subsequent nymphal blood meal , B . burgdorferi enter a rapid replication phase , experiencing a significant increase in density within a 48 hr period [8] , [9] and must prepare for transmission back to a mammal . How does B . burgdorferi generate the energy required to withstand this harsh environment ? Glycerol and its metabolites play important roles in cellular biochemistry [52] and glycerol is a readily available carbohydrate in Ixodes ticks [32]–[34] . Most bacteria have the ability to acquire glycerol from the surrounding milieu or to re-utilize it from its own metabolites [52] , [53] . G3P is a crucial intermediate for energy metabolism ( via its conversion to dihydoxyacetone phosphate and entry into the glycolytic pathway ) and for phospholipid biosynthesis ( via its conversion to phosphatidic acid [Figure 1] ) . The B . burgdorferi genome putatively encodes all the enzymes required for both processes [12] , [54] . The possibility that glycerol uptake and utilization may play an important role during the tick phase of the enzootic cycle was suggested by previous studies showing that genes comprising the glp operon had elevated expression during growth in vitro at 23°C and were subject to RpoS-dependent repression within the mammalian host [17] , [35] . A number of findings from the current study confirm that this is the case . First , in medium supplemented with glycerol as the principal carbohydrate source , wild-type B . burgdorferi grew to a significantly higher cell density compared to a glpD mutant during growth at 25°C ( Figure 10B ) . This difference was not observed during growth at 37°C or when glucose was employed as the principal carbohydrate source . Second , transcript levels for glpF and glpD were significantly lower in mouse joints relative to their levels in ticks ( Figure 5 ) . Third , GlpD protein was not produced during growth in DMCs and its repression was dependent on the presence of RpoS ( Figure 6 ) . Finally , the glpD mutant was fully infectious in mice when introduced by either needle or tick inoculation ( Table 1 ) , but had a replication defect in ticks ( Table 3 and Figure 11 ) . Absence of GlpD results in reduced spirochete fitness in the tick . This defect is manifested at two distinct points during this phase of the enzootic cycle . Spirochete loads are reduced five-fold after the larval molt in the mutant relative to the wild type . Spirochete loads were measured in larvae that had fed to repletion and in unfed nymphs two weeks after the molt . Therefore , it is not clear whether the reduction in B . burgdorferi density occurred during the molt or during the initial period in the unfed nymph . We favor the latter possibility . At the onset of nymphal feeding , the glpD mutants display a lag prior to beginning replication; as a result , they replicate more slowly than wild-type spirochetes and fail to achieve the same final spirochete densities ( Figure 11 ) . As a consequence , there is delayed transmission of glpD mutant spirochetes to mice during feeding . Whereas ticks infected with wild-type B . burgdorferi caused infection by 62 hours of feeding , those infected with mutant spirochetes required at least 72 hours of feeding before productive transmission occurred . Dunham-Ems et al . have demonstrated that B . burgdorferi migration from the midgut to the salivary glands for transmission to a mammal proceeds in two phases . In the initial step , replicating spirochetes form non-motile networks that advance toward the basolateral surface of the gut epithelium . The non-motile spirochetes then transition to motile organisms that penetrate the basement membrane into the hemocoel and migrate to the salivary gland [9] . This model of B . burgdorferi dissemination provides an explanation for the delayed transmission phenotype of the glpD mutant . As dissemination of B . burgdorferi in the tick during the first phase of feeding does not depend on motility , but instead is replication driven , the reduced replication rate of the mutant would result in delayed dissemination to the hemocoel . As a result , the mutant would require additional time for successful tick to mammal transmission . Spirochete loads of wild type and glpD mutant were identical in fed larvae whereas those of the mutant were reduced approximately five-fold after the larval molt; the reduced level of mutant persisted throughout the subsequent stages of the tick cycle ( Table 2 ) . In a very recent study , He et al . showed that a glpF polar deletion mutant , which does not express any of the glp operon genes , had a phenotype both in vitro and in vivo very similar to that described here for a glpD mutant ( i . e . the mutant failed to reach the same cell density as the wild type when cultured in medium with glycerol as the principal carbohydrate and had reduced spirochete loads in infected nymphs ) [23] . Interestingly , the reduction in mutant spirochete levels in nymphs was much more severe ( >2 logs ) in their study than was observed here for the glpD mutant . Presumably , this difference is due to the fact that the glpD mutant will only have an effect on glycerol utilization for glycolysis , whereas the glp operon mutant will also affect phospholipid biosynthesis ( Figure 1 ) . Thus , study of the glpD mutant is important in allowing evaluation of the contribution of glycerol utilization for energy metabolism without any confounding from effects on other metabolic pathways . Why isn't the glpD mutation lethal rather than being simply growth inhibitory ? Clearly , there must be an alternative carbohydrate source that can be metabolized via glycolysis to produce the required ATP . We propose that this alternative energy source is chitobiose . Tilly et al . reported that chbC transcript is elevated at 23°C relative to 34°C [45] and we have found that chbC expression is significantly higher in ticks than in mouse joints ( Figure 5 ) . Taken together , these data suggest that chitobiose utilization by B . burgdorferi is important during the tick phase of the cycle . Chitobiose would be available to the spirochete during tick feeding , when it is shed from the forming peritrophic matrix , as well as during molting when the tick cuticle is being re-modeled for growth [31] , [49] . It has been suggested that chitobiose utilization would be essential for B . burgdorferi during the tick phase of the enzootic cycle for spirochete glycolysis and cell wall synthesis . However , chbC mutants , which cannot take up exogenous chitobiose or utilize chitin to support growth , successfully complete the mouse-tick-mouse infectious cycle [48] . It is possible that glycerol availability may be partially responsible for rescue of the chbC mutant . This would suggest that B . burgdorferi maintains spirochete fitness in the nutrient deplete environment of the tick midgut by utilizing either glycerol and/or chitobiose as glycolytic precursors . It would be of interest to determine whether a glpD-chbC double mutant would be capable of completing the natural infectious cycle . As described earlier , signals that lead to phosphorylation of Rrp2 result in activation of RpoN which , in turn , initiates transcription of rpoS [14] , [15] . RpoS is expressed only in feeding nymphs and mammals and therefore , is thought to be responsible for the regulon that is required for mammalian infection [17] , [55] . This is consistent with the fact that Rrp2 , RpoN and RpoS mutants cannot establish infection in mice [16] , [56] , [57] . The RpoS regulon includes genes that are absolutely dependent on RpoS for their transcription ( e . g . ospC ) , as well as genes subject to RpoS-dependent repression [17] , [18] . The glp operon is in the latter category . Several recent studies have begun to reveal the role of the Hk1/Rrp1 TCS in B . burgdorferi [22]–[24] . Lack of Hk1 and Rrp1 has no effect on infectivity in mice . However , Hk1 and Rrp1 mutants are killed within the tick midgut during feeding [23] , [24] . Hk1 and Rrp1 appear to be expressed during all stages of the B . burgdorferi life cycle [22] , [24] , but the important consideration is whether Rrp1 is phosphorylated leading to the production of c-di-GMP . Interestingly , Caimano et al . have recently shown that Hk1 mutants are killed during the larval and nymphal blood meals , indicating that c-di-GMP is required during both tick feeding stages [24] . It is reasonable to conclude that the Rrp2/RpoN/RpoS pathway governs the expression of B . burgdorferi genes required in the mammalian host , whereas Hk1/Rrp1 controls a subset of borrelial gene products that is critical for survival in the tick vector . A number of genes that are induced by Rrp1 ( i . e . c-di-GMP ) are subject to RpoS-dependent repression; these include the glp operon genes and bba74 [22] , [23] . The current study demonstrates that glp operon expression is modulated by nutrient availability . Several reports have established that this operon is regulated in a reciprocal manner by RpoS and Rrp1 [17] , [22] , [23] . The glp genes are the first borrelial gene products linked to spirochete metabolism whose expression is subject to regulation by both B . burgdorferi TCSs . As such , these genes represent a valuable paradigm for elucidating the interplay between these two regulatory pathways . A model that integrates both carbohydrate availability and presence/absence of transcriptional regulators is presented in Figure 12 . It is presumed that early in larval feeding RpoS is still present , but must be degraded in order to allow for expression of tick phase genes; the precise timing of RpoS disappearance is not currently known . Glucose should be available at this stage in quantities sufficient to support B . burgdorferi growth . Later in the blood meal hexose sugars and other serum constituents crossing the peritrophic matrix are sequestered by tick midgut epithelial cells . This creates a nutrient-poor environment in which B . burgdorferi must rely on glycerol and rapidly depleting chitobiose to support glycolysis . The turnover of RpoS during larval feeding would result in the de-repression of glycerol pathway enzymes and presence of c-di-GMP will activate their expression , ensuring that spirochetes can rapidly switch from a glucose-based to a glycerol-based metabolism . Once spirochete infection is established in the midgut and the larva molts to an unfed nymph , B . burgdorferi remains a metabolically active spirochete that must rely on glycolysis for maintenance of cellular integrity . Glycerol is presumed to be the primary carbohydrate at this stage and absence of RpoS would allow expression of the glp operon . Early in nymphal feeding while blood constituents are scarce , B . burgdorferi must actively replicate and migrate through the epithelial midgut lumen to begin its migration to the salivary glands . At this point glycerol would be a primary energy source for support of cellular replication , as chitobiose will not be available until the eventual breakdown of the peritrophic matrix . Inability to utilize glycerol , as in the glpD mutant , would result in delayed and reduced spirochete replication that could impact transmission of B . burgdorferi to the mammalian host . Presence of c-di-GMP would result in sustained expression of glp operon genes . As RpoS levels increase during the nymphal blood meal , presence of c-di-GMP will counteract the repressive effects of RpoS on glp gene expression , ensuring that glycerol utilization can continue until the spirochetes are transmitted to a mammalian host . The model presented in Figure 12 accounts for carbohydrate source availability and presence of regulatory molecules throughout the tick-mouse enzootic cycle and highlights the interdependence of these two parameters . Concentrations of glucose and glycerol in mouse plasma are approximately 150 and 2 . 8 mg/100 mL , respectively [58] . Glycerol is abundantly present during all tick stages . On this basis , the model assumes that B . burgdorferi utilizes glucose as the preferred nutrient source when it is available in the mammal or at certain stages during the tick blood meal , but switches to utilizing glycerol , especially in the unfed nymph when glucose is not present . This may represent the B . burgdorferi version of carbon catabolite repression ( CCR ) , which is defined as a regulatory mechanism by which the expression and enzymatic activities of enzymes involved in the use of secondary carbohydrates are reduced in the presence of sufficient levels of the preferred carbohydrate [59] . The mechanisms underlying CCR in most bacteria involve a glucose-specific phosphotranferase subunit ( EIIA ) that can be reversibly phosphorylated based on the phosphoenolpyruvate to pyruvate ratios . B . burgdorferi encodes a putative EIIA subunit ( BB0559 ) , but does not appear to contain other major components that modulate CCR in other bacteria [12] . It is reasonable to assume that B . burgdorferi possesses sensing mechanisms that monitor the relative levels of glucose and glycerol in the environment . It is tempting to speculate that modulation of Hk1 kinase activity is one outcome of the fluctuating nutrient ratios . When the glycerol/glucose ratio increases Hk1 would phosphorylate Rrp1 leading to the production of c-di-GMP . The specific molecular signal that is recognized by Hk1 is not currently known . Likewise , the precise timing of the transcriptional activation/repression of RpoS and the possible reciprocal modulation of c-di-GMP levels is not known . Studies designed to elucidate the molecular events underlying the proposed model are warranted .
All animal experimentation was conducted in strict accordance with the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocols were approved by the Institutional Animal Care and Use Committee of New York Medical College ( Approval number 31-1-0310H ) . B . burgdorferi strains B31-A3 [60] , 297 ( c162 ) and a strain 297-based RpoS mutant ( c174 ) [17] were employed in this study . Spirochetes were grown in modified Barbour-Stoenner-Kelley-II medium [43] , [61] supplemented with 6% heat inactivated rabbit serum ( Sigma , St . Louis , MO ) ( BSK-II ) . BSK-lite medium was based on the formulation of Barbour [43] with modifications as previously described [28] . B . burgdorferi were grown to late log phase ( 5–10×107 cells/ml ) in BSK-II medium at 25°C . For BSK-lite experiments , spirochetes were diluted 100 fold in BSK-lite medium to remove BSK-II medium constituents . 5×104 spirochetes in 40 ml of BSK-lite medium with a specific carbohydrate ( either glucose or glycerol ) were aliquoted into eight 5 ml tubes . Four tubes of each sample were placed at either 25°C or 37°C and observed for up to 60 days . Individual tubes were counted daily for cultures grown at 37°C and every two days for those incubated at 25°C . Spirochete density was enumerated by dark field microscopy as previously described [62] . Student's two-tailed , unpaired t-tests were performed on data collected during exponential phase and stationary phases of cell growth . Significance was defined as a P<0 . 01 . Cultivation of c162 and c174 in DMCs was carried out as described [63] . The strategy for disruption of B . burgdorferi is presented in figure 7 . A 2519 bp region of B . burgdorferi chromosomal DNA containing bb0243 was amplified by PCR using primers bb0243F/R ( Table 4 ) ligated into the pGEM-T vector ( Promega , Madison , WI ) , transformed into E . coli DH5α and cells containing recombinant plasmids were selected by blue-white screening . Selected transformants were purified to single colonies and plasmids were confirmed to contain bb0243 by DNA sequence analysis ( Davis Sequencing , Davis , CA ) . The pGEM-T-bb0243 construct was digested with DraII ( corresponding to position 248 , 983 in the B . burgdorferi chromosome ) . A DNA fragment containing flgB-aadA ( a spectinomycin/streptomycin resistance cassette driven by the B . burgdorferi flgB promoter ) was amplified from vector pKFSS1 as previously described [64] and inserted into the DraII site within PGEM-T-bb0243 by blunt-end ligation . The construct was transformed into E . coli DH5α and selected by growth on LB agar plates supplemented with 100 µg/ml of spectinomycin . Transformants harboring plasmids containing bb0243 disrupted by the flgB-aadA cassette were isolated , purified to single colonies and plasmid inserts were confirmed by PCR and DNA sequence analysis . flgB-aadA cassette orientation was determined by restriction enzyme digestion . A plasmid construct designated pCP100 had the flgB-aadA cassette in the same orientation as bb0243 and a plasmid construct designated pCP200 had the flgB-aadA cassette in the reverse orientation . The ampicillin resistance cassette ( bla ) located in pGEM-T was disrupted in both constructs as previously described [65] yielding a plasmid designated pCP101 from pCP100 and pCP201 from pCP200 . Spectinomycin-resistant , ampicillin-sensitive colonies of each construct were selected by growth on LB agar containing either 100 µg/ml ampicillin or 100 µg/ml spectinomycin . pCP101 and pCP201 were isolated and transformed into B . burgdorferi B31-A3 competent cells by electroporation as described [66] . Transformants were screened by growth in a 96 well plate in the presence of streptomycin ( 100 µg/ml ) . Selected transformants were cloned by limiting dilution in BSK-II medium containing streptomycin ( 100 µg/ml ) . The glpD disruption in selected transformants was confirmed by Southern blot and Western blot analyses ( Figures 8 and 9 ) . Plasmid content for selected mutants was determined as previously described [67] to ensure that all plasmids essential for murine infectivity were present . Southern blot analysis and generation of a digoxygenin-labeled bb0243 probe were performed as previously described [67] with the following modifications . A 196 base pair fragment of bb0243 was generated from strain B31-A3 by PCR using primers 243probeF/R ( Table 4 ) . B . burgdorferi DNA was fragmented by incubation with 4 . 5 units of BamHI in 1× buffer B ( Fermentas , Glen Burnie , MD ) or EcoRI in buffer EcoRI ( Fermentas ) overnight at 37°C . C3H/HeJ mice ( Jackson Laboratories , Bar Harbor , ME ) were infected with either wild-type or glpD mutant B . burgdorferi by needle inoculation as previously described [68] , [69] . Once infection was established as determined by culture of ear biopsy , mice were anesthetized with ketamine and 100–300 naïve , unfed larvae were placed in and around the ear canal . Mice were placed individually into cages with approximately 1 cm water at the bottom . A metal grid of the same length and width as the cage , and standing 1 . 5 cm high , was placed in the cage . Larvae were allowed to feed until repletion . Following drop off , larvae were collected , rinsed in water , pooled into groups of 30 in 5 ml tubes with a porous cover and maintained in a desiccator at 21°C , >95% relative humidity with a 16 hour∶8 hour light: dark cycle . Larvae molted to unfed nymphs in approximately 5–6 weeks . At four weeks post molt , three unfed nymphs were placed on three-week old uninfected C3H/HeJ mice ( Jackson ) and allowed to feed until repletion . Fed nymphs were collected as described above . For interrupted feeding experiments , 3 unfed nymphs were allowed to feed on naïve C3H/HeJ mice for 24 , 48 , 55 , 62 , and 72 hours or to repletion . Ticks were carefully removed from mice by forceps at the indicated time point . Ticks were processed for DNA isolation as described below . Mice were tested for infection as previously described [68] , [69] . DNA isolation from 5×108 B . burgdorferi was performed using the Puregene DNA isolation kit as per manufacturer's instructions ( Qiagen , Valencia CA ) . DNA pellets were resuspended in 30 µl of nuclease free water . DNA concentration was measured by spectrophotometric analysis at 260 nm . DNA was isolated from pools of 10 fed larvae . DNA was obtained from unfed nymphs that were processed either individually , in groups of 5 or in groups of 10 . DNA was isolated from individually processed fed nymphs . Ticks were surface sterilized by washing successively with 800 µl of sterile H2O , 0 . 5% sodium hypochlorite , 3% hydrogen peroxide ( Sigma ) , 70% ethanol ( Fischer Scientific , Pittsburgh , PA ) and sterile H2O each for 1 minute . DNA extraction was performed as adapted from the Qiagen DNeasy blood and tissue kit as described by Beati et al . [70] with the following modifications . Ticks were homogenized with an 18 . 5 gauge needle . Samples were lysed with 220 µl animal lysis buffer and 0 . 45 mg recombinant proteinase K ( Roche , Mannheim , Germany ) per reaction overnight in a 56°C incubator . Following all wash steps , mixtures were centrifuged at 10 , 000 rpm . DNA was eluted twice with 25 µl of PCR-grade H2O pre-warmed to 72°C . qPCR reaction mixtures ( 25 µl total volume ) contained 2 µl of sample DNA , 3 µl of nuclease free water , 20 pmol each of primers FL-571F/FL-677R , 5 pmol of flaB- specific Taqman probe ( flaBFAM ) ( table 4 ) , and 12 . 5 µl Taqman PCR mastermix ( Roche ) . DNA copy number was determined on an ABI prism 7900HT thermocycler with an amplification profile of 50°C for 2 minutes , 95°C for 10 minutes , followed by 40 cycles of 95°C for 15 seconds and 60°C for 1 minute . Samples were run in duplicate and each plate contained two samples lacking DNA as negative controls . Ct values were obtained using the SDS2 . 1 software program ( Applied Biosystems , Carlsbad , CA ) . To assess spirochete density per sample , standard curves were generated for flaB , a constitutively expressed gene , in log increments ( 10–104 ) . Copy numbers were compared by a two-tailed , unpaired t-test for each condition ( fed larvae , unfed nymph , fed nymph ) , where significance was defined as P≤0 . 05 . Ticks infected with B . burgdorferi were processed in pools of 50 for fed larvae , 100 for unfed nymphs and 35 for fed nymphs . Ticks were homogenized in 1 ml TRIzol reagent ( Invitrogen , Carlsbad , CA ) for 5 minutes . For in vitro experiments , 50 ml of cell culture ( approximately 2 . 5×109 cells ) was centrifuged at 12 , 000 rpm for 10 minutes and 1 ml TRIzol was added to the cell pellet . RNA was recovered as per manufacturer's instructions ( Invitrogen ) . The RNA pellet was resuspended in 30 µl nuclease-free water and DNase treated twice with the Ambion DNA free kit per manufacturer's instructions ( Ambion , Austin , TX ) . Mammalian hind limb joints were surgically removed from euthanized C3H/HeJ mice , snap frozen in liquid nitrogen and pulverized with mortar and pestle . The powdered tissue was transferred to a glass homogenizer and homogenized with 0 . 5 ml denaturation solution and the supernatant containing total RNA was isolated from samples as per manufacturer's instructions ( ToTALLY RNA , Ambion ) . RNA was rehydrated in 30 µl of nuclease free water and DNase treated as described above . Mouse RNA was removed by MICROBEnrich as per manufacturer's instructions ( Ambion ) . The recovered RNA pellet was resuspended in 15 µl of sodium citrate buffer ( Ambion ) and 15 µl of nuclease free water . cDNA was generated from RNA samples by addition of 2 µg of purified RNA to a mixture containing 4 µl of 5× reverse transcriptase buffer ( Promega ) , 0 . 02 mM dNTPs ( Roche ) , 0 . 5 µg random hexamer ( Promega ) , 2 units of RNase inhibitor ( Ambion ) , 5 units of AMV reverse transcriptase enzyme ( Promega ) and nuclease free water in 20 µl total volume . The reaction mixture was incubated at 42°C for 2 hours . Reverse transcriptase enzyme was heat inactivated at 95°C for 5 minutes and cDNA was stored at −20°C until further use . For generation of standard curves , specific gene fragments for bb0240 , bb0243 and bbb04 were amplified by PCR using primers pairs bb0240qRTPCRF/bb0240qRTPCRR , bb0243qRTPCRF/bb0243qRTPCRR , bbb04qRT-PCRF/bbb04qRT-PCRR , ospA-288F/ospA-369R and ospC-B31FTq/ospC-B31RTq , respectively ( table 4 ) . PCR reaction mixtures contained 100 ng of B31-A3 DNA , 0 . 25 µl Taq polymerase ( Roche ) , 0 . 5 µl dNTPs ( Roche ) , and 1× Taq polymerase buffer ( Roche ) in a total volume of 25 µl . Amplification conditions were 95°C for 5 minutes , followed by 36 cycles of 95°C for 30 seconds , 55°C for 30 seconds and 72°C for 30 seconds and a final incubation at 72°C for 10 minutes . Production of the expected product was confirmed by gel electrophoresis and the PCR products were ligated into the TOPO 2 . 1 cloning vector , the vector was transformed into E . coli Mach1 cells and recombinant clones were selected as per manufacturer's instructions ( Invitrogen ) . Clonal isolates were grown in 10 ml of LB broth supplemented with 100 µg/ml ampicillin and the plasmids were extracted as described above . PCR confirmed the presence of the desired gene fragments . Plasmid concentration was determined by spectrophotometric analysis at 260 nm , followed by mathematical computation of copy number ( http://www . uri . edu/research/gsc/resources/cndna . html ) . Transcript levels for bb0240 ( glpF ) , bb0243 ( glpD ) , bbb04 ( chbC ) , ospA , ospC and flaB were determined by performing qRT-PCR as previously described [65] using the primer pairs listed in table 4 on an ABI Prism 7900HT thermocycler followed by analysis using the SDS2 . 1 software program ( Applied Biosystems ) . For each experimental run , standard curves for these genes were generated using known quantities ( 10–104 in log increments ) of gene specific plasmids for calculation of absolute copy number . One-way analysis of variance was performed on qRT-PCR results . To determine significance , a Kruskal-Wallis multiple comparison Z-value test ( Dunn's test ) was performed , where significance was defined as P≤0 . 05 . bb0243 was amplified using primers NdeI243F/XhoI243R ( Table 4 ) , cloned into the TOPO 2 . 1 vector , transformed into E . coli Top10 cells and recombinant clones were selected per manufacturer's instructions ( Invitrogen ) . The bb0243 insert was excised from the TOPO 2 . 1 plasmid by double digestion with NdeI and XhoI ( Fermentas ) and the insert was purified after separation by gel electrophoresis using the Wizard SV genomic gel purification kit according to manufacturer's instructions ( Promega ) . pET-15b ( Novagen , Gibbstown , NJ ) was digested with NdeI and XhoI and the gel-purified bb0243 insert was ligated with the NdeI/XhoI-cut pET-15b at a 2∶1 ratio with 10 units of T4 ligase ( New England Biolabs , Ipswich , MA ) . The recombinant plasmid was transformed into E . coli DH5α and clones were selected on LB agar plates containing 100 µg/ml ampicillin . Recombinant pET-15b carrying bb0243 was transformed into E . coli BL21-DE3 and grown on LB agar plates containing 100 µg/ml ampicillin . A clone containing bb0243 was selected and subjected to DNA sequencing . This sequence contained two single nucleotide changes relative to the reported sequence in strain B31-MI [12] . Nucleotide 107 had a T to C change that would result in a predicted amino acid change of I359T and nucleotide 591 had an A to T substitution that would result in an amino acid change of E197D . The selected clone was grown at 37°C in 250 ml Luria broth containing 100 µg/ml ampicillin and 1 mM IPTG with agitation for 4 hours . Cells were recovered by centrifugation at 8000 RPM for 10 minutes and rGlpD was isolated from the cells using Ni-NTA His Bind Resin ( Novagen ) according to the manufacturer's instructions . Fractions containing rGlpD , as determined by SDS-PAGE , were pooled and loaded into an Amicon Ultra 50 kDa molecular weight cut off spin column ( Millipore , Billerica , MA ) . The protein sample was centrifuged at 7500× g for approximately 8 minutes to a volume of 800 µl . The protein solution was dialyzed against 2 liters of 1× PBS , 6 M urea ( pH 7 . 4 ) with stirring overnight at 4°C . Identity of the protein as B . burgdorferi rGlpD was confirmed by LC-MS/MS analysis ( Keck Biotechnology Resource Laboratory , New Haven , CT ) . The yield of purified rGlpD was 1 . 3 mg . 100 µg of purified rGlpD in 1×PBS , 6 M urea ( pH 7 . 4 ) was inoculated along with Freund's adjuvant into two Sprague-Dawley rats by Harlan Laboratories ( Madison , WI ) . The rats received a boost at day 28 and day 56 post-inoculation and were sacrificed and bled on day 70 post inoculation . GlpD antiserum was tested by ELISA and confirmed to be specific for GlpD by immunoblot analysis . B . burgdorferi cells grown in vitro or in DMCs were lysed with Bugbuster HT ( Novagen ) and 1 µg/ml of lysozyme ( Sigma ) according to manufacturer's instructions . 2 µg of whole cell lysate was subjected to 12 . 5% SDS-PAGE and separated proteins were visualized by silver staining as described [71] . For immunoblotting , separated proteins were transferred to PVDF membrane . Membranes were exposed to protein-specific primary rat antiserum ( GlpD , 1∶400 dilution; FlaB , 1∶2500 dilution ) followed by alkaline phosphatase-linked anti-rat secondary antibody ( 1∶500 ) ( KPL , Gaithersburg , MD ) . The membrane was washed three times for 10 minutes with 1× TBS/0 . 05% Tween 20 and developed with BCIP/NBT phosphatase substrate ( KPL ) until band development ( approximately 2–4 minutes ) . To determine seroconversion in mouse infection studies , mouse serum was added to 1× TBS with 0 . 5% dry milk at 1∶200 dilution and incubated with whole B . burgdorferi lysate Marblot strips ( MarDX , Jamestown , NY ) for 1 hour at room temperature . The remaining procedure is as described above , with anti-mouse secondary antibody ( 1∶5000 dilution ) . | Borrelia burgdorferi is the vector-borne pathogen that causes Lyme disease . It has a complex life cycle that involves growth in a tick vector and a mammalian host — two diverse environments that present B . burgdorferi with alternative carbohydrate sources for support of growth . Previous studies suggested that glycerol may be an important nutrient in the tick vector . Here we show that genes predicted to be involved in glycerol metabolism have significantly elevated expression during all tick stages . Repression of expression in the mammalian host is dependent on the alternative sigma factor , RpoS . A mutant that cannot convert glycerol into dihydroxyacetone phosphate to support glycolysis was able to infect mice . In contrast , the mutant was present at significantly lower levels in nymphal ticks , its replication was delayed during nymphal feeding and longer feeding times were required for transmission from nymph to mouse . The results demonstrate that the ability to utilize glycerol as a carbohydrate source for glycolysis during the tick phase of the infectious cycle is critical for maximal B . burgdorferi fitness . | [
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"pat... | 2011 | Borrelia burgdorferi Requires Glycerol for Maximum Fitness During The Tick Phase of the Enzootic Cycle |
In spite of decades-long studies , the mechanism of morphogenesis of plus-stranded RNA viruses belonging to the genus Enterovirus of Picornaviridae , including poliovirus ( PV ) , is not understood . Numerous attempts to identify an RNA encapsidation signal have failed . Genetic studies , however , have implicated a role of the non-structural protein 2CATPase in the formation of poliovirus particles . Here we report a novel mechanism in which protein-protein interaction is sufficient to explain the specificity in PV encapsidation . Making use of a novel “reporter virus” , we show that a quasi-infectious chimera consisting of the capsid precursor of C-cluster coxsackie virus 20 ( C-CAV20 ) and the nonstructural proteins of the closely related PV translated and replicated its genome with wild type kinetics , whereas encapsidation was blocked . On blind passages , encapsidation of the chimera was rescued by a single mutation either in capsid protein VP3 of CAV20 or in 2CATPase of PV . Whereas each of the single-mutation variants expressed severe proliferation phenotypes , engineering both mutations into the chimera yielded a virus encapsidating with wild type kinetics . Biochemical analyses provided strong evidence for a direct interaction between 2CATPase and VP3 of PV and CAV20 . Chimeras of other C-CAVs ( CAV20/CAV21 or CAV18/CAV20 ) were blocked in encapsidation ( no virus after blind passages ) but could be rescued if the capsid and 2CATPase coding regions originated from the same virus . Our novel mechanism explains the specificity of encapsidation without apparent involvement of an RNA signal by considering that ( i ) genome replication is known to be stringently linked to translation , ( ii ) morphogenesis is known to be stringently linked to genome replication , ( iii ) newly synthesized 2CATPase is an essential component of the replication complex , and ( iv ) 2CATPase has specific affinity to capsid protein ( s ) . These conditions lead to morphogenesis at the site where newly synthesized genomes emerge from the replication complex .
Morphogenesis is a crucial step at the end of the virus' life cycle that provides newly synthesized genomes with a protective shell to survive in the extracellular environment yet assures attachment to and penetration into subsequent host cells . Morphogenesis of viral genomes must be specific because encapsidation of non-progeny nucleic acid is wasteful for the virus , for which reason elaborate mechanisms have evolved to discriminate against nucleic acids other than its own genome . Here we describe our studies of the morphogenesis of a group of single , plus-stranded RNA viruses that belong to the genus Enterovirus of Picornaviridae , a family of viruses containing a large number of human and animal pathogens . Poliovirus ( PV ) , the prototype enterovirus , has been extensively studied for a century and although much is known about its virion structure , uptake into host cell , genome structure and macromolecular events of replication , the mechanism of particle assembly is only poorly understood [1] . The key requirement of morphogenesis , namely the specific selection of viral genomes , has also remained obscure . We have discovered a novel mechanism for enteroviruses in which the specificity of encapsidation is facilitated by protein-protein interaction . It should be noted that this mechanism is different from the one used by some other RNA viruses such as hepatitis B virus and alphaviruses [2] , [3] . The specificity of encapsidation with these viruses is dependent on an RNA encapsidation signal and RNA/protein interactions . Enteroviruses synthesize only one protein , the polyprotein , which is cleaved by two virus-encoded proteinases , 2Apro and 3Cpro/3CDpro , into intermediates expressing specific functions ( e . g . 3CDpro ) and into mature proteins ( Figure 1A ) . After its release from the polyprotein by 2Apro , the precursor of the structural proteins ( P1 ) interacts with cellular chaperone Hsp90 [4] , a requirement for its subsequent processing by 3CDpro into capsid proteins VP0 , VP3 and VP1 ( Fig . 1A ) [5] . These cleavage products will spontaneously form a 5S protomer ( VP0 , VP3 , VP1 ) that can oligomerize to the 14S pentamer ( VP0 , VP3 , VP1 ) 5; twelve pentamers , subsequently , assemble into a 75S empty capsid [ ( VP0 , VP3 , VP1 ) 5]12 , also called procapsid [6] , [7] . It is not known at what stage progeny genomes interact with the capsid precursors . They may be inserted into the procapsid or , alternatively , pentamers may condense around RNA emerging from the replication complex . Either process will yield provirions {[ ( VP0 , VP3 , VP1 ) 5]12RNA} [8] , [9] , [10] that mature to virions when VP0 is cleaved to VP4 and VP2 by a mechanism possibly involving an RNA-dependent autocatalytic process [6] , [7] . The encapsidation process in PV morphogenesis is highly restricted to newly synthesized plus strand progeny RNA [11] , [12] . Under normal conditions of replication in HeLa cells , cellular RNAs , PV mRNA lacking VPg or viral VPg-linked minus strand RNA are excluded from mature viral particles [6] . Numerous studies aimed at determining the specificity of encapsidation by searching for an RNA packaging signal have been unsuccessful . The very long 5′NTR of PV can be replaced with that of the distantly related coxsackie B3 virus ( CVB3 ) [13] or CVB4 [14] yielding virions containing chimeric genomes that proliferate with PV wild type ( wt ) kinetics . Similarly , the cloverleaf of PV can be changed to that of HRV2 [15] , or the PV IRES has been exchanged with IRESes from other picornaviruses [16] , [17] , [18] and even with that of HCV [19] without yielding impaired encapsidation phenotypes . The 3′NTR of PV , in turn , has been exchanged with that of HRV14 , a single stem-loop structure with no apparent similarity in structure and sequence to that of PV . This chimera too proliferated with wt kinetics [20] . This makes it highly unlikely that the 5′- and 3′-NTRs of poliovirus contain packaging determinants . The genomic sequence encoding the capsid P1 precursor cannot harbor an encapsidation signal since the entire P1 encoding region can be deleted [21] or replaced by foreign genes [14] , [22] , [23] . Such PV replicons , all of which can replicate , can be efficiently encapsidated with PV capsid proteins in trans . Recent experiments from this laboratory , employing a “scrambled” sequence [24] of the P2 coding region ( scramble of synonymous codons ) have eliminated this region too from carrying an encapsidation signal ( Song , Mueller , Ward , Skiena , Futcher , Paul and Wimmer , manuscript in preparation ) . Finally , genetic modification of the PV VPg coding sequence [25] , [26] or engineering PVs carrying VPg sequences of other picornaviruses [25] , [27] , [28] have also eliminated the VPg coding sequence as providing an encapsidation signal . VPg , however , may still play a role in encapsidation ( see below ) . Currently it seems unlikely that poliovirus or other enteroviruses ( including the rhinoviruses that have recently been classified as enteroviruses ) harbor an RNA signal that would instruct the capsid components to bind to and enclose the viral genome in a specific manner . Only one member of the extended family of Picornaviridae , Aichi virus ( Kobuvirus genus ) , was reported to contain a 5′-terminal RNA stem loop with a role in particle assembly [29] . Among the nonstructural proteins of PV , 2CATPase and 3CDpro , have been reported to be involved in packaging although no mechanism ( s ) is known . Studies with an in vitro translation/RNA replication system , which produces viable viruses [11] , have suggested that 3CDpro functions at a late step in the assembly process just before or during the maturation cleavage of VP0 to VP2 and VP4 [30] . Protein 2CATPase of PV has been implicated in virion capsid formation through genetic analysis of a cold-sensitive mutant [31] or by determining escape mutants from drug ( hydantoin ) inhibition [32] . The multifunctional 329 amino acids-long 2CATPase is the most complex and least understood nonstructural proteins of enteroviruses . The functions of this protein that are highly conserved among picornaviruses , include , in addition to encapsidation , host cell membrane rearrangements [33] , [34] , genome replication [35] , [36] and even uncoating of viral particles [37] . Based on sequence analyses the protein has been classified as a member of the superfamily III helicases , which contain 3 conserved motifs ( A–C ) , including two classical ATP binding motifs ( A and B ) ( Fig . 1B ) [38] . Purified 2CATPase possesses ATPase activity [39] , [40] , which is inhibited by guanidine HCl ( GnHCl ) [41] , a known potent inhibitor of PV RNA replication [18] . In vitro the protein forms homo-oligomeric structures required for ATPase activity [42] . The N-terminal part of the protein contains a RNA binding domain and an amphipathic helix , which is involved in membrane binding and oligomerization [36] , [42] , [43] . Another amphipathic helix , a RNA binding domain and a cysteine rich domain that binds zinc are located near the C-terminus [44] , [45] . In infected cells 2CATPase appears to be associated with viral RNA in the replication complexes on the surface of membranous vesicles [46] . Available evidence suggests that genome replication is a precondition of PV encapsidation [11] , [12] . Electron-microscopic studies , which showed that RNA replication complexes co-localize with capsid precursors on membranous vesicles during infection [47] , supported these observations . Nugent et al . [12] hypothesized that encapsidation specificity may be determined by the spatial arrangement of replication complexes with the capsid precursors . This intriguing hypothesis lacked an essential component: what brings the capsid precursors into the vicinity of the replication complexes since PV replicons lacking the P1 domain altogether can be efficiently encapsidated in trans ? Human enteroviruses have been divided into several clusters based on genotype relationships [48] . PV types 1–3 , and eleven C-cluster coxsackie A virus serotypes share the C-cluster , also referred to as C-cluster human enteroviruses ( C-HEVs ) . Their difference in affinity to cellular receptors , PVs using CD155 [49] , [50] while C-CAVs using ICAM-1 [51] , accounts for significant capsid dissimilarities between the member viruses of this species [52] , [53] . In contrast , the differences between the non-structural proteins of PV vs C-CAVs are less pronounced . We have used the similarities and dissimilarities between PV and C-CAVs to separate RNA replication from encapsidation by constructing chimeric viruses in which capsid precursor P1 and/or 2CATPase have been exchanged . All of the chimeric viruses studied here replicated their genomes with wt kinetics in tissue culture cells but were blocked in encapsidation , a phenotype that we examined by genetic analyses . We present genetic evidence suggesting a specific interaction between 2CATPase and VP3 , which is essential for genome encapsidation . The genetic evidence of the 2CATPase-VP3 interaction was further substantiated by biochemical assays . We propose that the primary determinant of encapsidation specificity in the enterovirus life cycle is protein-protein interaction .
HeLa H1 cells were maintained in DMEM ( Life Technology ) , supplemented with 10% FCS , 100 units of penicillin , and 100 mg of streptomycin per milliliter . The prototype strain of C-CAVs , CAV20 , CAV21 ( Kuykendall ) and CAV18 , propagated in HeLa H1 cells , were obtained from the American Type Culture Collection . Polioviruses ( PVM ) were derived from cDNA pT7PVM [54] by transfection . Parental plasmids of PV: pT7PVM contain a full-length infectious cDNA of PVM . Parental plasmids of C-CAVs: pT7CAV20 contains a full-length infectious cDNA of CAV20 [48] . pGEM-CAV21 and pT7CAV18 , which contain a full length infectious cDNA of CAV21 and CAV18 ( Kuykendall ) , respectively , were constructed by Elizabeth Rieder . Chimeric genomes: Parental plasmids of PVs and C-CAVs were used as the backbone for cloning as described below . All plasmids contain the T7 promoter in front of the 5′ end of the full length genomic cDNA for in vitro RNA transcription by T7 RNA polymerase [54] . Parental plasmid cDNAs of CAV20 , CAV21 and CAV18 were used as the backbone for cloning . Using a three-step overlapping PCR , chimeras between CAV20 and CAV21 ( or CAV18 ) were generated by precise swapping of the genetic segment encoding the P1 region of the polyprotein [48] . The oligonucleotides and the templates for PCR are summarized in Supplementary Table 2 in Text S1 . The overlapping PCR fragment and the vectors were digested with the same pair of restriction enzymes and ligated to produce the cDNA clone of the chimeric genome . The vectors and the restriction sites for construction of the chimeric genomes are listed in Supplementary Table 3 in Text S1 . The DNA sequence of the final constructs was verified by sequencing analysis using BigDye Kit and ABI Prism DNA sequencer ( model 310 ) . Replacement of the original 2CATPase coding region in each of the chimeric genome with that of the same origin as the capsid coding region follows the same strategy described above ( Supplementary Table 2 & 4 in Text S1 ) . Construction of the chimeric C20PP genome was described before [48] . For construction of the C20PP derivatives , listed in Supplementary Table 3 in Text S1 and Figure 4 , a two-step overlapping PCR similar to the one described above was performed using C20PP as the template with the mutation ( s ) introduced into the internal primers ( Supplementary Table 3 & 4 in Text S1 ) . To test the RNA replication efficiency of chimeric viruses , we used novel reporter viruses , which contain the Renilla luciferase gene fused to the N-terminal of the P1 coding region of the chimeric genomes . The same strategy ( three-step overlapping PCR ) , described above , was used to introduce the Renilla luciferase gene into the N-terminal of P1 the coding region of the chimeric genomes ( Supplementary Table 3 & 4 in Text S1 ) . The luciferase protein is post-translationally cleaved from the remainder of the polyprotein by 3CDpro at a recombinant 3CDpro cleavage site . Parental plasmid cDNAs pT7PVM , pT7CAV20 , pGEM-CAV21 , pT7CAV18 and the chimeric constructs were linearized at a unique restriction sites downstream the poly ( A ) tract ( Supplementary Table 5 in Text S1 ) and used as templates for in vitro RNA synthesis using T7 RNA polymerase . RNA transcripts were transfected into HeLa H1 cell monolayers by the DEAE-Dextran method as described before [54] . Following transfection , virus was harvested from the transfected cells when 90–95% of the cells displayed cytopathic effect ( CPE ) . Lysates of transfected cells from the chimeric genomes showing no CPE were inoculated into 35-mm-diameter HeLa H1 cell monolayers for 6–8 subsequent serial passages . The plaque phenotypes and virus titers ( PFU/ml ) of the parental and chimeric viruses were determined in triplicate by plaque assay [11] using 0 . 6% tragacanth gum . The identity of the chimeric viruses was confirmed by RT-PCR/sequencing analysis . In vitro RNA translations were performed with HeLa cell S10 cytoplasmic extracts at 34 degree Celsius as described previously [11] . HeLa H1 cell monolayers ( 5×106 ) were infected with viruses that were purified from plaque assay . At 7-hr post infection , total cytoplasmic RNA was extracted with 1 ml Trizol reagent ( Invitrogen ) and amplified into DNA using Titan one tube RT-PCR system ( Roche ) . The RT-PCR products were sequenced using the Bigdye Terminator Sequencing Kit ( ABI , Applied Biosystems ) . Dishes ( 35-mm diameter ) of monolayered HeLa H1 cells were transfected with 5 µg of replicon RNAs and were incubated at 37 degree Celsius in standard tissue culture medium in the presence and absence of 2 mM GnHCl . Luciferase activities were determined in lysates of cells harvested 16 hrs after transfection . Cell lysates ( 10 µl ) was mixed with 20 µl of luciferase assay reagent ( Promega; luciferase assay system catalog no . E2810 ) and Renilla luciferase activity was measured in an Optocomp I luminometer ( MGM Instruments , Inc . ) . Cell lysates from transfections were used to re-infect HeLa H1 cells in the presence and absence of 2 mM GnHCl and luciferase activities were determined in lysates of cells harvested 8 hrs after infection . Luciferase activity ratio ( −GnHCL/+GnHCl ) represents: luciferase activity without GnHCl divided by luciferase activity with GnHCl in either transfection or infection . A PCR fragment containing full length PV VP3 was amplified and cloned into the pET21b vector ( Novagen ) with the restriction enzymes Sac I and Xho I . GST-tagged 2CATPase and His-tagged VP3 recombinant proteins were expressed in E . coli . The GST-2CATPase proteins were expressed from pGEX-2C vector and purified by glutathione sepharose column ( GE Healthcare ) as described before [41] . The His-VP3 proteins were purified by nickel column chromatography ( QIAGEN ) . Briefly , 5 µg GST-2CATPase ( or 2 µg GST as a control ) were incubated with glutathione sepharose beads at 4°C for 3 hr in buffer containing 50 mM Tris-HCl pH7 . 5 , 140 mM NaCl , 0 . 1% TritonX-100 with protease inhibitor cocktail tablets ( Roche ) . The protein bound GSH beads were washed with PBS 3 times and then 5 µg His-VP3 was added . After 1 hr incubation at 4 degree Celsium , the glutathione beads were washed 3 times and were boiled in 1x SDS sample buffer for 5 min . The samples were analyzed by SDS-polyacrylamide gel ( 12 . 5% acrylamide ) electrophoresis and followed by western blot analysis using antibodies against PV VP3 ( polyclonal , kindly contributed by Dr . Delpeyroux , Pasteur Institute , France ) . Plasmids used for in vitro translation of CAV20 structural protein VP3 ( wt ) , VP3 ( E180G ) and CAV20 non-structural protein 2CATPase ( wt ) , PV non-structural proteins 2CATPase ( wt ) and 2CATPase ( N252S ) were generated with A2 plasmid [55] and PCR fragments encoding wt and mutant proteins of VP3 and 2CATPase according to methods described previously [55] . 2 µg of each VP3 and 2C RNA transcripts generated in vitro by T7 RNA polymerase were co-translated in HeLa extract and labeled by 35S-labeled methionine . Using anti-PV 2C polyclonal antibody , Co-IP assay was performed with co-translated 35S labeled 2CATPase and VP3 proteins following standard protocols using protein A/G plus-agarose ( Santa Cruz Biotechnology ) and [56] . The radioactive signals from input proteins and Co-IP reaction products were quantified by a PhosphorImager ( Molecular Dynamics , Storm 860 ) by measuring the amount of 35S incorporated into product . Interactions between 2CATPase and VP3 were represented by percentages of the levels observed in the Co-IP reaction with CAV 2CATPase and CAV VP3 after normalizing the amount of input 2CATPase and VP3 . Numbers given for the extents of interactions represented the average of three independent experiments .
The lack of evidence for an RNA packaging signal in enterovirus proliferation has prompted us to study the specificity of encapsidation by searching for possible protein-protein interactions needed for this process . Previous studies have shown that chimeric constructs of the PV polyprotein with exchanges of varying coding regions of closely related picornaviruses can be utilized to analyze determinants of viral macromolecular interactions and replication [57] , [58] , [59] , [60] , [61] , [62] . PV and C-CAVs share a high degree of amino acid identity in their nonstructural proteins but are not closely related in their capsid sequences probably because they evolved to use different cellular receptors [48] . In a chimera with the capsid of one C-HEV and the nonstructural proteins of another C-HEV , this difference may produce specific morphogenesis phenotypes due to incompatibility or poor interaction between capsid and nonstructural proteins . In our previous work , we have already observed that the replacement of the PV type 1 Mahoney ( PVM ) capsid with that of its closest relative , CAV20 , resulted in a quasi-infectious virus , C20PP ( Figure 2A ) [48] . In C20PP , the first letter refers to the origin of the P1 region , the 2nd and 3rd letters refer to the origins of the P2 and P3 regions , respectively . The quasi-infectious phenotype means that a step in the life cycle of C20PP is so severely debilitated that only escape variants can be recovered from transfections with RNA transcripts [48] . The molecular basis of the defective phenotype of C20PP was not elucidated but could be proteolytic processing of the capsid precursor , genome replication or encapsidation . The observed quasi-infectious phenotype of C20PP made it possible to subject this chimera to a genetic analysis that may reveal a defect in encapsidation . We first provided evidence that the quasi-infectious phenotype of C20PP was not due to abnormal translation or protein processing resulting from poor compatibility between the heterologous capsid and the 3CDpro polypeptide in C20PP . Translation of RNA transcripts of wt and chimeric constructs in a HeLa cell-free extract [11] showed normal translation and protein processing patterns ( Figure 2B ) . The search for the block of C20PP proliferation led us to develop a novel reporter virus in which the PV open reading frame ( ORF ) of the Renilla Luciferase ( R-Luc ) protein was fused to the N-terminus of the viral polyprotein . In the course of the infection the R-Luc is cleaved off from the viral polyprotein at an engineered 3CDpro proteinase cleavage site . Due to the small size of the inserted R-Luc gene this virus was stable for 1 passage after transfection and , thus , suitable for our experiments . This construct is similar to a previously described recombinant coxsackie B3 virus that stably expressed eGFP in tissue culture [63] . The advantage of using our reporter virus over conventional reporter replicons , in which the P1-coding sequence is replaced by the luciferase gene , is that it can distinguish between a defect in replication and encapsidation . A reporter viral genome ( with the R-Luc sequence ) that is unable to encapsidate itself will exhibit normal RNA replication levels as evidenced by a wt-like Renilla luciferase signal after RNA transfection . However , it would not generate infectious progeny and , consequently , passage to fresh cells will fail , leading to the loss of the luciferase signal . We have made such reporter viruses from both the parental wt CAV20 and the chimeric C20PP ( Figure 2C ) . RNA transcripts were transfected into HeLa H1 cells both in the absence and presence of 2 mM GnHCl , a potent inhibitor of PV [18] and CAV20 RNA replication [18] , [48] . Luciferase activity was determined at 16-hr post transfection either in the presence of GnHCl ( +GnHCl ) throughout the incubation period that allows us to measure the translation of the transfecting RNA , or in the absence of GnHCl ( −GnHCl ) when the luciferase signal is increased because of RNA synthesis . The ratio of the luciferase signals –GnHCl/+GnHCl indicates the extent of genome replication . As shown in Figure 2D there was a 100 fold increase of the luciferase signal at −GnHCl compared to +GnHCl with both wt R-Luc-CAV20 and R-Luc-C20PP viruses , an observation indicating robust RNA synthesis under these conditions . Lysates of transfected cells were then inoculated to fresh HeLa H1 cells as 1st passage either in the presence or absence of GnHCl . Eight hours post infection the luciferase activity was measured ( Figure 2D ) . The high level of luciferase activity obtained after the first passage of the R-Luc-CAV20 virus indicated the formation of virions that had encapsidated the wt genome in the course of transfection . In contrast , no luciferase signal could be detected after passage of the lysate harboring the R-Luc-C20PP chimera ( Figure 2D ) . We conclude that the genome of the C20PP chimera , although competent in RNA replication , cannot form infectious progeny , e . g . it is defective in genome encapsidation . The reason for the defect in encapsidation , however , remains elusive . As mentioned above , the C20PP chimera is quasi-infectious . Variants that escaped the block in encapsidation were found only after three blind passages following transfection . This indicated the emergence of mutation ( s ) . To identify the rescuing mutation ( s ) , we plaque purified two viruses that had emerged after three passages from two independent transfections with C20PP transcripts . RT-PCR and sequence analyses of the viral genomes revealed two independent single mutations that mapped to the coding region of either VP3 ( E180G ) or 2CATPase ( N252S ) . By separately engineering these two mutations back into the cDNA of C20PP we obtained two viable viruses C20PP-VP3E180G and C20PP-2CN252S ( Figure 3A ) . Their titers after transfection were as low as those observed with isolates after three passage of C20PP ( Figure 2A ) and 1000 fold lower than that observed with wt CAV20 . Moreover , C20PP-VP3E180G and C20PP-2CN252S expressed a small plaque phenotype compared to that of wt CAV20 ( Figures 2A and 3A ) . The phenotypes of C20PP-VP3E180G and C20PP-2CN252S did not change after further passages , e . g . all attempts to isolate variants with improved proliferation phenotypes failed ( data not shown ) . This prompted us to engineer both the VP3E180G and 2CN252S mutations into C20PP ( C20PP-DM ) . Variant C20PP-DM expressed phenotypes ( virus titer and plaque size ) almost the same as that of wt CAV20 ( compare Figures 2A and 3A ) . Currently , we cannot explain why in our experiments the C20PP-DM-like variant did not evolve during passaging of C20PP . To confirm the rescue of the encapsidation defect of C20PP by the mutations in VP3 and 2CATPase , we constructed reporter viruses R-Luc-C20PP-VP3E180G , R-Luc-C20PP-2CN252S and R-Luc-C20PP-DM ( Figure 3B ) . All three produced strong luciferase signals after transfection of their genomic RNAs into HeLa H1 cells , as expected ( Figure 3C ) . After a passage into fresh HeLa H1 cells , the luciferase activity was highly impaired with C20PP but was found to be partially rescued if the virions carried the single 2CN252S or VP3E180G mutation or fully rescued by the double mutation ( Figure 3C ) . Thus , although a single mutation can partially rescue the proliferation phenotype of C20PP , the double mutation 2CN252S/VP3E180G in the genome of the chimera is capable of producing a proliferation phenotype similar to that of wt CAV20 . This observation , confirms the previous genetic data by Vance et al . [32] that the coding region of 2CATPase is linked to encapsidation . More importantly , the cooperative activity of VP3 with 2CATPase suggests that capsid protein VP3 functions through a direct interaction with 2CATPase in encapsidation . As indicated before , the coding sequence of 2CATPase , however , can be eliminated as carrying an encapsidation signal . The cre , the only known essential RNA structure in coding sequence of 2CATPase , are highly homologous in sequence between PV and CAV20 . Moreover , scrambling of the P2 RNA sequence has no influence on PV proliferation if the essential cre is transplanted to the 5′NTR ( Song , Mueller , Ward , Skiena , Futcher , Paul , and Wimmer , manuscript in preparation ) . It is , thus , likely that VP3 and 2CATPase or their precursors cooperate by protein-protein interaction , a novel mechanism for specific genome encapsidation of enteroviruses . It should be noted that the mutation in 2CATPase , which rescues in part the encapsidation of C20PP-2CN252S , is an N/S change in PV 2CATPase at position 252 ( Figure 4A ) . Amino acid sequence alignment demonstrated that CAV20 has a Gly at this position ( Figure 4A ) , an observation indicating that a CAV-20 like , uncharged residue might be favorable at this position . Thus , since C20PP-2CN252S expressed a severe encapsidation phenotype , it was of interest to determine whether a C20PP-2CN252G mutant would yield a chimera equal or superior in encapsidation to C20PP-2CN252S . Similar to C20PP-2CN252S , the N252G mutation in the PV 2CATPase only partially rescued the encapsidation phenotype of C20PP ( Figure 4B ) . The observed N/S mutation in a naturally selected escape mutant can be explained by the reasoning that the CAV20-like N/G change in codon N252 would have required two nucleotide changes ( AAT/GGT ) while the N/S mutation entails only a single nucleotide change ( AAT/AGT ) . Overall , the CAV20 like single amino acid change at 252 of PV 2CATPase was favorable but not sufficient to fully rescue the VP3-related function of the PV 2CATPase protein in encapsidation . Based on this observation , we reasoned that the replacement of the entire 2CATPase coding region in C20PP with its CAV20 counterpart should yield a chimera whose protein/protein interaction required for encapsidation would be sufficient and , thus , yield a virus with proliferation phenotypes similar to that of wt CAV20 . Therefore , we generated a chimera designated as C20P ( C202C ) P that showed CPE after transfection with a virus titer comparable to that of wt CAV20 ( compare Figures 2A and 4B ) . These results provide further support for the hypothesis that the 2CATPase protein is a partner required for encapsidation . It should be noted that the chimera C20P ( C202C ) P had a growth phenotype more similar to that of the wt CAV20 virus than the chimera C20PP-2CN252S ( compare Figures 2A and 4B ) , an observation indicating that sequences besides residue 252 in 2CATPase are also important for function during viral encapsidation . The observation that CAV20 VP3 needs its own 2CATPase to fully rescue the defect in encapsidation suggests that the cooperation or interaction between 2CATPase and capsid might be specific and generally true for C-HEVs . To test this hypothesis we extended our analyses to CAV18 and CAV21 , two viruses that are phylogenetically related to CAV20 and PV [48] . Chimeras C20C21C21 and C18C20C20 ( Figure 5A ) displayed non-viable phenotypes as judged by the lack of virus in plaque assays even after 8 blind passages on fresh HeLa H1 monolayers ( Figure 5A ) . In order to test whether the lethal phenotypes of the two chimeric viruses were due to the same encapsidation defect as that of C20PP , we constructed reporter viruses of CAV18 and of the chimeras C20C21C21 and C18C20C20 ( Figure 5B ) just as that of CAV20 ( Figure 2C ) . After transfection of RNA transcripts into HeLa H1 cells , R-Luc activity at 16-hr post transfection showed that the parental and chimeric viruses replicated their genomes with nearly wt efficiency ( Figure 5C ) . However , after the first passage on fresh HeLa H1 cells only wt CAV20 and wt CAV18 reporter viruses yielded normal luciferase signals ( Figure 5C ) . The chimeric genomes R-Luc-C20C21C21 and R-Luc-C18C20C20 could not produce an infection , a result demonstrating an encapsidation defect . To test whether the lethal proliferation phenotypes of the two chimeras ( C20C21C21 and C18C20C20 ) are related to an incompatibility between the capsid and the 2CATPase proteins derived from different parental viruses , we constructed new chimeras [C20C21 ( C202C ) C21 , C18C20 ( C182C ) C20] in which the capsid and 2CATPase proteins were derived from the same origin ( Figure 6A ) . The resulting chimeras all showed CPE after transfection ( Figure 6B ) and the virus titers were comparable to that of the parental viruses ( data not shown ) . The finding that the lethal growth phenotypes of the chimeras were fully rescued when the capsid and 2CATPase were derived from the same origin serves as further support of our hypothesis that 2CATPase and capsid proteins communicate with each other during the process of encapsidation . So far , we have not been able to determine , by continued passage , the necessary amino acid changes in the 2CATPase protein of CAV20 and CAV21 to allow encapsidation of the C20C21C21 and C18C20C20 chimeras . This observation might be explained by the fact that there are many amino acid differences either between CAV20 and CAV21 or between CAV20 and CAV18 flanking residue 252 of the 2CATPase protein ( Figure 6C ) . This may make it difficult for the two chimeras ( C20C21C21 and C18C20C20 ) to generate escape mutants simply by natural selection during passages . The genetic evidence described above strongly suggested a direct interaction between the capsid proteins and 2CATPase , which is required for encapsidation . To confirm this interaction , we carried out a GST-pull down assay with purified PV proteins GST-2CATPase and His-VP3 ( Figure 7A , lane 2 ) . The same assay was performed with purified GST protein as a control ( Figure 7A , lane 1 ) . Our results clearly showed that PV GST-2CATPase interacts directly with the PV His-tagged VP3 protein . To provide further proof that direct interaction between VP3 and 2CATPas is required for the encapsidation process , co-immunoprecipitation ( Co-IP ) assays were performed with VP3 and 2CATPase proteins in three different combinations: CAV20 VP3 & CAV20 2CATPase , CAV20 VP3 & PV 2CATPase , CAV20 VP3 ( E180G ) & PV 2CATPase ( N252S ) , which correspond to those observed in wt CAV20 , nonviable chimera C20PP , and rescued C20PP-DM , respectively . In vitro transcribed RNA transcripts of 2C and VP3 coding sequences in different combinations were co-translated in HeLa cell extracts ( Figure 7B , lanes 4–6 ) [11] , [55] . Using PV 2C polyclonal antibody , which recognizes PV 2CATPase and CAV20 2CATPase with the same efficiency ( data not shown ) [56] , CAV20 VP3 was co-immunoprecipitated readily by CAV20 2CATPase ( 100% , Figure 7B , lane 1 ) but only weakly by PV 2CATPase ( 32% , Figure 7B , lane 2 ) . The extent of interaction between 2CATPase and VP3 was quantified using a PhosphorImager and is expressed as percentage of the level observed in the CAV20 2CATPase and CAV20 VP3 Co-IP reaction . These results indicated a strong , direct interaction between 2CATPase and VP3 of the same origin ( CAV20 ) but not between PV 2CATPase and CAV20 VP3 , a combination that yielded the nonviable C20PP chimera . In contrast , the interaction between PV 2CATPase ( N252S ) and CAV20 VP3 ( E180G ) proteins was restored ( 78% , Figure 7B , lane 3 ) when the two mutations were incorporated into PV 2CATPase and CAV20 VP3 , respectively , This observation , which correlates with the rescue of the nonviable phenotype of C20PP by the two mutations , strongly support the notion that sufficient protein-protein interaction between 2CATPase and VP3 is essential for the encapsidation process . The same Co-IP assays were also performed with α-actin antibody and empty resin as controls to ensure that the interactions were not due to non-specific binding of the proteins to the antibody or to the resin ( data not shown ) . It should be noted that there was an extra protein band shown below the band of 2CATPase in each of the input lanes ( Figure 7B , lane 4–6 , indicated by asterisk ) , which was possibly generated from the internal initiation or premature termination of the translation of RNA transcripts of 2C coding sequences . Apparently these incomplete translation products could not be recognized by the 2C antibody since protein bands disappeared after Co-IP ( Figure 7B , lane 1–3 ) . These results confirm the specificity of the Co-IP assay in which the detection of the VP3 protein was due to its co-immunoprecipatation with the 2CATPase protein , recognized by anti-2CATPase antibody . The data support our hypothesis that 2CATPase is required for viral encapsidation through a direct interaction with capsid protein VP3 and also confirm that 2CATPase interacts with VP3 through protein–protein rather than RNA-protein interaction . Given that 2CATPase and capsid proteins are colocalized on the surface of membranous vesicles in the RNA replication complex [46] , [47] , it is likely that 2CATPase interacts with VP3 either in the form of the mature protein or in the context of one of the VP3-containing capsid precursors ( 5S , 14S , 75S and 150S ) .
The mechanism of picornavirus genome encapsidation has been a conundrum for many years . In previous studies on poliovirus morphogenesis , mostly trans encapsidation experiments were performed to determine the specificity of PV morphogenesis . In trans encapsidation experiments , the capsid proteins are offered from a different molecular entity to the parental genome either by coinfecting picornaviruses [14] , by the vaccinia system [22] , [23] or by expression from co-transfected cDNAs [64] . However , differences in the experimental design also affect the outcome of the experiments . Jia et al . , [64] have reported trans-encapsidation of PV replicons into capsids of coxsackie B3 , human rhinovirus 14 , and coxsackie B24 viruses . These data , however , are in contrast to those of Porter et al . , [23] and Barclay et al . , [14] , who failed to trans encapsidate the reporter PV replicon by super-infecting with CAV21 . In the current study , we have used a novel system to study encapsidation of closely related enteroviruses , the C-cluster enteroviruses ( C-HEVs ) . They consist of two classes of virus serotypes: PV and C-CAVs . We have made use of differences between these viruses to investigate the effect of capsid exchanges on C-HEV morphogenesis . By studying a variety of C-HEV chimeric viruses in which the capsid P1 precursors were exchanged , we now present direct evidence for the involvement of 2CATPase in enterovirus morphogenesis via direct interaction with capsid protein VP3 . Different from trans encapsidation assays , in which the capsid proteins are offered from a different molecular entity to the parental genome , our experiments were designed to measure cis encapsidation of genomes , in which the capsid is provided ( generated ) by the chimeric genome itself . It appears that in these chimeras the non-structural proteins are more discriminatory to capsid proteins because they are required to proteolytically process the heterologous capsid precursor . In addition , the quality and quantity of the heterologous capsid proteins produced might not be ideal for the chimeric genome . As we have shown here , favorable conditions for encapsidation are rarely met in the chimera , even if the viruses are as closely related as PV and CAV20 . In a previous study on genetic recombination between PV and C-CAVs , we observed that capsid chimera C20PP initially could not grow [48] , an observation indicating that it harbors defect ( s ) debilitating the viral replication life cycle . Translation in HeLa cell extracts showed , however , that both translation and proteolytic processing of the CAV20 capsid precursor in C20PP was unimpaired . This is not surprising since the 3CDpro proteins of poliovirus and CAV20 are closely related in amino acid sequence [48] and because the 3CDpro cleavage sites within the P1 precursor of PVM and CAV20/21 are well conserved ( Supplementary Table 1 in Text S1 ) . These two facts reduce the likelihood of a processing defect of the foreign capsid precursor prior to packaging . In contrast , a chimera consisting of the PV capsid and the coxsackie virus B3 ( CBV3 ) nonstructural domains was not only dead but it also revealed a processing defect of the PV capsid precursor [65] . CBV3 is an enterovirus belonging to the B-cluster , and its genetic kinship with PV is much more distant than that between PV and CAV20 . Thus , CBV3 3CDpro proteinase was apparently unable to properly cleave the PV capsid precursor . Similar results were obtained with a chimera of PV in which the 3C-coding region was derived from HRV14 . The foreign proteinase was not capable of recognizing the PV-specific processing sites within the capsid precursor [57] . The robust RNA replication phenotype of C20PP demonstrated here with the use of a new reporter virus construct suggested to us that this chimera might be quasi-infectious with respect to encapsidation . This was proven to be correct since viable viruses were found upon blind passages of C20PP but they harbored mutations . The virus isolates from two independent transfections contained a mutation either in 2CATPase ( N252S ) or in VP3 ( E180G ) . Either of these single mutations was able to partially rescue the defective encapsidation and growth phenotype of C20PP . Introducing both mutations together into the C20PP genome fully rescued packaging and resulted in normal production of progeny virus . It is noteworthy that we never found both mutations in a single isolate even after eight passages . Perhaps the mutations conferred to the variants too little of an advantage to be selected under the conditions of the experiments . As discussed earlier , an involvement of essential RNA sequences in the 2CATPase and VP3 coding sequences during the process of encapsidation can be excluded . A direct interaction between the 2CATPase and VP3 proteins , suggested by the genetic experiments , was confirmed by biochemical assays using either purified or in vitro translated PV and CAV20 proteins . It should be noted that 2CATPase also functions in the viral life cycle in the form of its precursor 2BCATPase . A requirement of an interaction between 2BCATPase and VP3 for packaging is , however , unlikely since 2B is less homologous between PV and CAV20 in sequence than 2CATPase and the exchange of the mature 2CATPase protein alone is sufficient for full rescue . We are currently investigating whether the interaction between 2CATPase and VP3 involves the mature VP3 polypeptide or one of the capsid intermediates during viral assembly and/or maturation . The encapsidation defect of C20PP could also be rescued by replacing the entire 2CATPase coding sequence of PV with that of CAV20 . Additional experiments indicated that the lethal growth phenotypes of other CAV/CAV capsid chimeras could also be reversed by replacing their 2CATPase coding sequence with that of the capsid donor virus . It is noteworthy that these observations are not contradictory to the scenario of another chimera previously described . PC20C20 , which , in contrast to C20PP , possesses a chimeric genome encoding PV capsid and CAV20 nonstructural protein sequences , grows as well as wt PV [48] . We have previously proposed that the evolutionary direction is from C-CAV to PV within C-HEVs resulting in a receptor switch from ICAM-1 to CD155 during the speciation [48] . If so , the newly emerged PV capsid may still be compatible with 2CATPase of the C-CAV ancestors and achieve sufficient interaction required for encapsidation . Our data also clarify some unanswered questions about previous trans encapsidation experiments using poliovirus replicons containing a reporter gene in the capsid-coding region [14] , [23] . Those studies showed that CAV21 was not able to encapsidate a PV replicon even though co-infection of cells with CAV21 resulted in high levels of replication of both CAV21 and the PV replicon . The most likely reason for those results is that the CAV21 capsid , similar to CAV20 capsid , fails to properly interact with PV 2CATPase . From their studies with hydantoin , Vance et al . , have suggested that 2CATPase might have a role in encapsidation by an association of the progeny RNA with the capsid [32] . In other experiments with the same drug , however , Oh et al . , [66] have recently proposed that hydantoin inhibits the release of the progeny RNA from the replication complex prior to encapsidation . Whether the interaction between 2CATPase and VP3 , as we have observed in our studies , is required during or just before the union of the RNA with capsid proteins remains to be determined . An intriguing phenomenon of poliovirus encapsidation is that only newly replicated RNA molecules are incorporated into virions [11] , [12] , an observation reported also for some other RNA viruses such as flock house virus [67] , [68] , [69] , and brome mosaic virus [70] . Coupling encapsidation specifically with replication offers an efficient mechanism of discriminating against cellular RNAs or viral mRNA . Since genome replication is coupled with translation [71] , [72] the link to encapsidation “can impose a form of late proofreading” for the progeny virus [12] . In Figure 8 , we present a model of morphogenesis that is based , admittedly , on much speculation . We currently propose that in the context of the membrane-associated replication complex 2CATPase will directly interact with a 14S pentamer via VP3 . The pentamer will then bind the newly emerging , VPg-linked genomic RNA [9] while the assembly of the virion proceeds in close contact with the membranous environment . This model offers a new mechanism for the specificity of enterovirus encapsidation: it is dependent on protein/protein interactions at the site of the active replication complex . It is likely that our model will be applicable to most , if not all , picornaviruses as well as to other families of plus strand RNA viruses . For example , the requirement for an interaction between a capsid protein and nonstructural proteins for encapsidation has also been observed for members of the Flaviviridae . Murray et al . , reported that several assembly-deficient core mutants of HCV genotype 2a ( Hepacivirus genus ) could be rescued by compensatory mutations in p7 or NS2 [73] . In addition , it was shown that HCV core and NS5A colocalize on the surface of lipid droplets , a process required for particle assembly [74] . Furthermore , recent reports indicate the importance of nonstructural proteins in the maturation of Kunjin virus and Yellow fever virus ( Flavivirus genus ) [75] , [76] and of bovine diarrhea virus ( Pestivirus genus ) [77] . We have noted before that Aichi virus , a member of the Kobuvirus genus in the Picornaviridae , requires a 5′-terminal RNA element for encapsidation [29] . This signal by itself , however , is not sufficient to confer encapsidation specificity since it can be replaced by a similar stem loop from hepatitis A virus , a member of the genus Hepatovirus of Picornaviridae , and the resulting chimera expresses a severe proliferation phenotype [27] . On the other hand different genera of Picornaviridae may have evolved different strategies of encapsidation . This is not entirely unlikely considering the fundamentally different strategies that different genera of Flaviviridae are using to control genome translation ( cap-dependent vs . IRES-dependent initiation of translation [78] . Our model does not explain , however , how VPg-linked minus-stranded poliovirus RNA is discriminated against in encapsidation . Previous studies have reported that several picornaviral 2CATPase proteins bind specifically to the 3′-end of minus strand RNA in vitro [79] , [80] . However , the importance of this interaction , if any , for encapsidation is unlikely . Normally , plus strands are produced in great excess over minus strands [81] , a phenomenon thought to lead to the depletion of free minus strands by forming the replicative form ( RF ) or replication intermediates ( RI ) [18] . If the balance between the plus and the minus strands is disturbed , free minus strands may emerge from the replication complex and they may then be encapsidated . Indeed , encapsidation of both plus and minus strand genomic RNAs was observed in non-cytopathogenic CBV3 that were isolated from persistently infected murine hearts and cardiac myocyte cultures [82] . It is possible that the non-cytopathogenic CBV3 produces minus stranded RNA in excess such that it will emerge from replication complexes where capsid precursors are waiting to encapsidate them . Whether the “cap” of a positively charged VPg on both plus or minus strands plays a role in this process remains to be seen . | Enteroviruses are single , plus-stranded RNA viruses that contain a large number of closely related pathogens . Human enteroviruses cause altogether >3 billion human infections per year , inflicting diseases ranging from benign ( common cold ) to very serious ( poliomyelitis ) . Enterovirus replication has been studied for decades yet the mechanism of genome selection during encapsidation , a key step open for chemotherapeutic intervention , remains unknown . Attempts to identify a genomic “packaging signal” , instructing the genome to engage with capsid proteins in morphogenesis , have failed . We have used the similarities and dissimilarities of two closely related subspecies of enteroviruses , poliovirus and coxsackie A viruses ( CAVs ) , and constructed chimeras in which the capsid coding region was interchanged . A chimera , with the CAV capsid domain and the poliovirus two non-structural domains of the polyprotein , synthesized its genome with wt kinetics yet was blocked in morphogenesis . Genetic and biochemical studies of chimeras led to the discovery that the non-structural protein 2CATPase ( essential part of the replication complex ) and capsid protein VP3 must directly interact for morphogenesis to proceed . This has led us to propose a novel mechanism by which the specificity of enterovirus morphogenesis is governed by protein-protein rather than RNA-protein interaction at the site of genome synthesis . | [
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] | 2010 | Direct Interaction between Two Viral Proteins, the Nonstructural Protein 2CATPase and the Capsid Protein VP3, Is Required for Enterovirus Morphogenesis |
Epigenetic research has been focused on cell-type-specific regulation; less is known about common features of epigenetic programming shared by diverse cell types within an organism . Here , we report a modified method for chromatin immunoprecipitation and deep sequencing ( ChIP–Seq ) and its use to construct a high-resolution map of the Drosophila melanogaster key histone marks , heterochromatin protein 1a ( HP1a ) and RNA polymerase II ( polII ) . These factors are mapped at 50-bp resolution genome-wide and at 5-bp resolution for regulatory sequences of genes , which reveals fundamental features of chromatin modification landscape shared by major adult Drosophila cell types: the enrichment of both heterochromatic and euchromatic marks in transposons and repetitive sequences , the accumulation of HP1a at transcription start sites with stalled polII , the signatures of histone code and polII level/position around the transcriptional start sites that predict both the mRNA level and functionality of genes , and the enrichment of elongating polII within exons at splicing junctions . These features , likely conserved among diverse epigenomes , reveal general strategies for chromatin modifications .
Epigenetics refers to the regulation of gene expression that is heritable to daughter cells without alteration of genetic information [1] . Epigenetic regulation is commonly achieved via DNA methylation , covalent modification of histones , and association/dissociation of chromatin factors [2] . Chromatin modifications of many genes in a genome in a specific fashion leads to epigenetic programming of the genome . It has been assumed that chromatin modifications occur in a cell-type-specific fashion in order to specify and maintain diverse cell fates [3] . This presumed central feature of chromatin modifications has been the subject of intensive investigation and has been supported by abundant evidence . However , of equal importance , there must also be common patterns of chromatin modifications that exist in all types of cells , which would reflect general features of the epigenome that are shared by diverse cell types within an organism or even among distant species . It is important to understand such general features of chromatin modifications , and substantial effort has been devoted to this area of study . There is strong evidence supporting the existence of general features of chromatin modifications that are shared by all types of cells . Perhaps the strongest evidence is the presence of constitutive heterochromatin in centromeres and telomeres — a feature not only present in all types of nucleated cells within an organism but also well conserved during evolution [4] . Centromeric heterochromatin is essential for chromosome condensation and segregation during mitosis; whereas telomeric heterochromatin may be related to telomere function and telomeric silencing of transcription . Beyond these two examples , relatively little is known about the general features of chromatin modifications in the bulk of the genome , especially in the euchromatic genome . To explore these general features systematically , we combined high-resolution chromatin immunoprecipitation and high-throughput sequencing ( ChIP-Seq ) to map the distribution patterns of a panel of histone modifications , Heterochromatin Protein 1a ( HP1a ) , and RNA polymerase II ( RNA polII ) in Drosophila melanogaster . This allowed us to construct a high resolution whole-genome map of Drosophila with these key chromatin modifications and the transcriptional activity mapped at 50 base-pair resolution . Our mapping data are consistent with recent major mapping efforts in Drosophila cell lines and major developmental stages [5] , [6] , [7] , [8] . Moreover , our map , derived from all cell types in the adult Drosophila weighted by their natural abundance , reveals striking features of the chromatin modifications with important functional implications .
To gain high resolution whole-genome maps of the Drosophila chromatin modification , we isolated nuclei from whole adult flies for ChIP-Seq . In order to achieve an unbiased representation of both euchromatin and heterochromatin in the following ChIP , we modified the standard ChIP-Seq method by first treating nuclei with limited amount of micrococcal nuclease ( MNase ) and then separating chromatin into euchromatic and heterochromatic fractions ( Figure 1A ) . Chromatin in heterochromatin fractions was further fragmented by sonication into a size range comparable to the euchromatic chromatin ( Figure S1A ) . Chromatin from euchromatic and heterochromatic fractions were subjected to immunoprecipitation of post-translationally modified histone 3: histone 3 trimethylated at Lysine 4 ( H3K4me3 ) and acetylated at lysine 9 ( H3K9ac ) as euchromatic marks , whereas histone 3 trimethylated at Lysine 9 ( H3K9me3 ) and trimethylated at Lysine 27 ( H3K27me3 ) as heterochromatic marks . To minimize biases introduced by partial MNase digestion and nucleosome positioning , we preformed the immunoprecipitation of total histone 3 ( H3 ) as a control for normalization . In addition , crosslinked chromatin was used for immunoprecipitation of HP1a , a heterochromatic protein , as well as RNA polII that indicates transcription activity ( Figure 1A ) . For these two epigenetic marks , a mock ChIP was conducted as a control for normalization . The high specificity of HP1a antibody used in this study was confirmed by Western blotting ( Figure S1B ) . All precipitated DNA was sequenced by Illumina Genome Analyzer 1G , which achieved 7 . 9-fold coverage of the Drosophila genome in total ( Table S1 ) . The relative abundance of epigenetic marks across the entire genome was quantified as detailed in Materials and Methods and Figure S1 . So far , most published bioinformatic analyses of ChIP-Seq are based exclusively on unique-mapping ( i . e . deriving from single genomic location ) Illumina reads , which have unambiguous genomic origins [9] . However , we find that ∼24 . 5% of Illumina reads from the mock ChIP sample are multiple-mapping reads with more than one matching site within the genome ( Table S1 ) . BLAST analyses indicate that these multiple-mapping reads represent repetitive , low complex , and transposon-derived sequences , frequently found in heterochromatic regions of the Drosophila genome ( data not shown ) . The fact that some heterochromatic marks are mostly enriched in repetitive sequences and that these repetitive sequences function in heterochromatic silencing demands the inclusion of these multiple-mapping reads in the ChIP-Seq analyses . To this end , we employed two different calculations in the score generation step of ChIP-Seq analyses: a unique-mapping only method , which calculates the ChIP-Seq scores purely based on unique-mapping reads [ChIP-Seq ( U ) ]; and a method combining both unique-mapping and multiple-mapping reads [ChIP-Seq ( U+M ) ] ( Figure S1 ) . In the latter method , a multiple-mapping tag contributes equally to all matching genomic sites with score matrices weighted by the reciprocal of the number of genomic matching sites . Although this method cannot discriminate multiple matching sites for a single Illumina read , we reasoned that many multiple-mapping reads and unique-mapping reads together will generate individual scores for similar transposon/repetitive sequences in the genome . A similar approach was recently employed to interrogate H3K9me3 distribution pattern within repetitive genomic regions in human CD4+ T lymphocytes [10] . To validate our ChIP-Seq analyses , we first compared our ChIP-Seq results of HP1a distribution patterns with the published results of HP1a Chromatin IP combined with the genome tiling array experiment ( ChIP-Chip ) in Drosophila S2 cells [11] and DNA adenine methyltransferase identification combined with the genome tiling array experiment ( DamID-Chip ) in adult whole flies [12] . Our ChIP-Seq ( U ) results faithfully reproduce HP1a localizations from the ChIP-Chip assay with a Pearson Product-Moment correlation coefficient as high as 0 . 83 ( Figure 1B ) . We find that both ChIP-Seq ( U ) and ChIP-Seq ( U+M ) results feature eminent resolutions and can largely replicate previous observations of HP1a distributions in a gene-rich region ( Figure 1C ) . Strikingly , our ChIP-Seq ( U+M ) scores successfully recapitulate previous findings of the DamID-Chip assay showing that HP1a is specifically associated with a Doc retrotransposon , but not with an adjacent copia retrotransposon ( Figure 1D ) . Overall , our ChIP-Seq ( U+M ) results largely repeat the HP1a distribution patterns from DamID-Chip assay ( Pearson correlation coefficient = 0 . 77 , Figure S2 ) . Again , our ChIP-Seq ( U+M ) data on HP1a features much higher resolution ( 50 bp ) as compared to the DamID-Chip method . Using the above-described method , we conducted the whole-genome mapping of H3K4me3 , H3K9me3 , H3K27me3 , H3K9ac , HP1a , and RNA polII in euchromatic arms ( chrX , chr2L , chr2R , chr3L , chr3R and chr4; hereafter called euchromatic genome ) as well as other sequenced internal scaffolds and unmapped regions ( XHet , 2LHet , 2RHet , 3LHet , 3RHet , YHet , U and Uextra; hereafter called heterochromatic genome ) . To gain an overview of the distributions of chromatin modifications , we compared their ChIP-Seq ( U+M ) scores over different genomic features ( CDS , 5′UTR , 3′UTR , intron , transposon/repetitive sequence , and intergenic region ) within the euchromatic genome and all sequenced genome ( Figure 2A ) . This comparison reveals distinct distribution patterns of chromatin modifications in the genome related to specific types of genomic sequences . We find RNA polII and H3K9ac are highly enriched in protein-coding genes , with 69 . 3% of RNA polII scores and 62 . 3% of H3K9ac scores located within CDS , 5′UTR , 3′UTR and intron regions ( Figure 2A ) . This is consistent with the notion that these two chromatin modifications are associated with actively transcribing genes [13] . Within genes , RNA polII and H3K9ac show distinct distribution patterns with respect to subgenic regions: RNA polII is preferentially present in CDS and 5′UTR regions whereas H3K9ac is relatively enriched in introns . In contrast to these euchromatic marks , 85 . 9% of HP1a scores and 78 . 7% of H3K9me3 scores are situated in transposons and repeats within all sequenced genome ( Figure 2A ) , which largely reflect the natural abundance of these two marks on polytene chromosomes [14] . Interestingly , we find transposons and repeats include 59 . 3% and 73 . 3% of H3K4me3 scores within euchromatic and all sequenced genome , respectively ( Figure 2A ) . This is consistent with previous reports that both euchromatic ( H3K4me3 ) and heterochromatic ( H3K9me3 ) marks are present within heterochromatin [15] , [16] . To explore the chromatin modification of transposons , we calculated the total ChIP-Seq ( U+M ) scores of chromatin modifications on all transposons in the genome . We find that heterochromatic marks H3K9me3 , H3K27me3 and HP1a are abundant within transposons ( Figure 2B ) . In contrast , transposons are mostly devoid of transcription activity marks , H3K9ac and RNA polII . These results are consistent with the notion that most transposons in the Drosophila genome are transcriptionally silenced whereas a small portion of transposons remain transcriptionally active [17] . To investigate epigenetic marks co-localized in transposons , we performed pair-wise Pearson correlation analyses for chromatin modification densities in transposons classified into 185 classes ( Figure 2C ) . The significant positive correlation between H3K9me3 density and H3K27me3 density indicates these two chromatin modifications are co-localized on transposons ( P . c . = 0 . 9 , p = 8 . 746×10−68 ) . We find H3K9me3 is also co-occcurring with HP1a within transposons ( P . c . = 0 . 336 , p = 3 . 01×10−6 ) , which suggests HP1a is recruited here by this mark . In addition , correlated RNA polII and H3K9ac densities ( P . c . = 0 . 444 , p = 2 . 42×10−10 ) implicates some transposons , like G6 and Burdock , are transcriptionally active in the Drosophila genome ( Figure 2C , 2D ) . To further investigate the enrichment patterns of chromatin modifications within protein-coding genes , we sorted ∼2 . 4 million 50-bp windows within euchromatic genomes into 100 percentiles based on their ChIP-Seq ( U ) scores and calculated the percentages of genomic features for every percentile individually ( Figure 3A–3E , Figure 4A ) . The relative abundance of a chromatin modification over a genomic feature was determined by comparing the percentages to the natural representation of the genomic feature within the euchromatic genome ( Figure 3A–3E , Figure 4A ) . Furthermore , we determined the distribution of these chromatin modifications relative to the transcriptional start sites ( TSSs ) , the mid points of gene bodies , and the transcription end sites ( TxEnds ) of protein coding genes with regard to their transcriptional levels ( Figure 3F–3J , Figure 4B ) . 6 , 756 genes with known gene expression levels were classified into 10 groups according to their relative expression levels in whole fly samples interrogated by microarray experiments ( GSE5382 , GSE7763 ) , with each group representing a 10% increment of expression levels . Within protein coding genes , the top 10% of H3K4me3- and H3K9ac-dense sequences are highly represented in 5′UTRs and CDSs ( Figure 3A and 3B ) . Specifically , both H3K4me3 and H3K9ac are highly enriched in the 5′ ends of high- and medium-expressing genes ( +50 bp∼+750 bp for H3K4me3 and +50 bp∼+1 kb for H3K9ac ) , but sharply declined around TSSs ( −50 bp∼+50 bp ) and severely under-represented in proximal promoter regions ( −600 bp∼TSS ) ( Figure 3F and 3G ) . Such a dynamic pattern is not observed in low-expressing and silent genes . H3K9ac differs from H3K4me3 in two additional features within protein coding genes . First , moderately to highly H3K9ac-dense sequences ( 70th∼90th percentiles ) are also enriched in intronic sequences but devoid from intergenic regions . This is consistent with the notion that H3K9ac specifically associates with transcriptional activity and can spread over the whole gene body [18] . Second , H3K9ac is enriched in 3′ends of genes ( −1 kb regions upstream of TxEnds ) of medium- and high-expressing genes , in contrast to the slight enhancement of H3K4me3 at the TxEnds ( Figure 3F and 3G ) . The H3K9me3 mark is the binding target of HP1a , and is generally regarded as an epigenetic silencing mark [19] , [20] . Within protein coding genes , extremely H3K9me3-dense ( top 2% ) sequences are located in intergenic and intronic regions ( Figure 3C ) . Intriguingly , in actively transcribed genes , H3K9me3 is highly enriched in the promoter region ( −1 kb∼−100 bp ) but generally depleted in the 5′ ends of genes ( Figure 3H ) . This pattern is opposite to that of H3K4me3 and H3K9ac , and echoes recent observations that H3K9me3 is associated with promoters of active genes in mammalian genomes [21] , [22] . Similarly , H3K27me3 , the binding target for Polycomb repressive complex 1 ( PRC1 ) , is enriched in discrete intergenic regions ( Figure S3A , Table S2 ) , but under-represented in CDS , 3′UTR and intronic regions ( Figure 3D ) . Most of H3K27me3-enriched regions are located within cytological bands that were previously identified as cytobands bound by Polycomb proteins on polytene chromosomes and S2 cells ( Figure S3A ) [5] , [8] , [23] , [24] , [25] . Moreover , of 167 predicted PRE/TREs [25] , 89 are enriched for the H3K27me3 marks , which validates these PRE/TRE as constitutive binding sites for PRC1 in adult flies . For example , the three most prominent H3K27me3-enriched regions on chromosome arm 3R are the Antennapedia complex ( ANT-C ) , Bithorax complex ( BX-C ) , and a 200-kb region between mod ( mdg4 ) and InR , which contains multiple predicted PRE/TREs ( Figure S3B ) . At boarders of ANT-C and BX-C , as well as in active genes CG7922 and CG7956 , H3K27me3 is dramatically reduced to background levels . On average , genomic regions surrounding the 167 predicted PRE/TREs are significantly enriched for H3K27me3 marks comparing to randomly selected intergenic regions within the euchromatic genome ( Figure S3C ) . Expectedly , the density of H3K27me3 in the promoter , 5′ ends , bodies , and 3′ ends of protein coding genes are negatively correlated to mRNA levels ( Figure 3I ) . H3K27me3 is generally absent from medium- and high-expressing genes , but is enriched in the promoters and 5′ ends ( −1 kb∼+1 kb ) of silent and extremely low-expressing genes . This pattern resembles the distribution of H3K27me3 in the human genome [26] and reflects its function in long-term gene silencing [24] , [27] . Notably , for low expressing genes , H3K27me3 is enriched in the promoter regions ( −1 kb∼−250 bp ) and 5′ ends ( +200 bp∼+1 kb ) , but is absent around the TSSs . This observation appears to be consistent with recent findings that H3K27me3 and H3K4me3 are co-localized at a group of ‘bivalent’ promoters poised for transcription [28] . Consistent with the fact that RNA polII is the central player of transcription , the top 20% of polII-dense sequences are conspicuously over-represented within 5′UTRs and intergenic regions , yet moderately polII-dense sequences ( within 40∼80% ) are also enriched in CDS ( Figure 3E ) . Moreover , the level of RNA polII is strictly correlated to the RNA expression level ( Figure 3J ) . Particularly , polII concentrates around TSSs , forming a sharp peak within a narrow region immediately downstream of TSSs ( 0 bp∼+100 bp , Figure 3J ) . Significant RNA polII signals are also present within gene bodies and at the 3′ ends of expressing genes . Although HP1a is predominantly associated with transposons and repeats , about 23% of HP1a ChIP-Seq ( U+M ) scores are present in genic/intergenic regions . Within these regions , HP1a is particularly enriched in the 5′UTR regions and coding sequences ( Figure 4A ) . Within a transcriptional unit , HP1a is highly concentrated around the TSS with only low levels of HP1a spreading over the gene body ( Figure 4B ) . Strikingly , the levels of HP1a concentration at the TSSs are strictly correlated to the mRNA levels of its residing genes , confirming previous reports ( see Discussion ) . Particularly , the sharp peaks of HP1a immediately surrounding TSSs ( 0 bp∼+100 bp ) mimic the polII enrichment within the same regions . These prominent similarities strongly suggest HP1a functions together with RNA polII in transcription ( see Discussion ) . The high levels of agreement between our whole-fly-derived HP1a scores and ChIP-Chip scores generated from embryonic S2 cells indicate HP1a localizations are generally stable during development . Thus , we recruited a published microarray dataset , which contains gene expression data for both wild type third instar larva with and without HP1a-knockdown [29] . 12 , 521 interrogated genes were sorted and grouped into 100 percentiles based on their folds of changes in gene expression ( hereafter called fold of change percentiles; Figure 4C ) . To better understand genes regulated by HP1a , we calculated 11 additional features for genes in all percentiles ( Figure 4C ) . Interestingly , genes highly repressed in HP1a RNAi knockdown larva ( 1st∼3rd fold of change percentiles , green dots ) are overly high-expressing genes in wild type larva , which are generally short in length and away from centromeres . By contrast , genes highly activated by HP1a knockdown ( 97th∼100th fold of change percentiles , red dots ) are generally devoid of any recognizable feature . We find a distinct third class of genes , representing moderately activated genes in HP1a knockdown ( 80th∼97th fold of change percentiles , yellow dots ) . This class predominantly contains high-expressing , large genes , characterized by their large numbers of sparsely located exons . Notably , these genes also tend to localize within gene-rich regions . However , none of the above gene classes is correlated to transposon/repeat densities either upstream , downstream or within the gene bodies . The above analyses implicate that HP1a concentrated at TSSs may have a direct function in regulating the expression of its target genes . To understand this function , we asked whether HP1a is specifically enriched at TSSs of its target genes . The HP1a density surrounding TSSs of 10 gene classes grouped by 10% increments of fold of change percentiles was investigated ( Figure 4D ) . We find HP1a is enriched at TSSs of genes that are either highly repressed ( 1∼10% percentile ) or highly activated ( 90∼100% percentile ) in HP1a knockdown , indicating HP1a has direct functions of both activation and silencing on its target genes . Intriguingly , the highest levels of HP1a enrichment at TSSs are found among the third class genes that are moderately activated by HP1a RNAi , suggesting this gene class represents a distinct HP1a-mediated regulome . We further calculated averaged levels of histone modifications over TSS regions ( +/−500 bp ) for all percentiles but failed to identify any correlation ( Figure 4E–4F ) . This suggests that HP1a-mediated gene expression regulation is globally independent of other examined chromatin modifications . Recent studies have revealed that RNA polII is poised or stalled at the TSS regions of about 10% genes in the Drosophila genome [30] , [31] . It has been proposed that these poised/stalled polII allow rapid responses of gene activation to environmental stimuli and developmental cues . To gain a detailed view of RNA polII dynamics and gene expression , we adopted a previously established strategy [31] and categorized TSSs of genes into three classes: those with elongating polII ( 785 TSSs ) , stalled polII ( 685 TSSs ) or no polII ( 695 TSSs; Figure 5A ) . Notably , stalled polII is detected in the TSS of Hsp70 gene ( CG18743 ) , which is the first defined gene with stalled polII [32] . We find that the presence of elongating polII at the TSSs corresponds to genes within the top 50% expression levels whereas absence of polII at TSSs represents genes within the lowest 40% expression levels ( Figure 5B , upper and lower panels ) . Interestingly , genes with stalled polII at their TSSs exhibit a broader range of expression levels ( Figure 5B , middle panel ) . To infer the precise positions of RNA polII at different types of TSSs , we calculated the frequency of polII-immunocoprecipitated reads matched to the sense and the antisense strands of genes and binned these reads into 5-bp windows ( Figure 5C ) . A similar approach has been previously employed to position nucleosomes surrounding TSS regions [33] . By this method , we pinpoint stalled polII into a narrow region , centered at the +35 bp position ( Figure 5C , middle panel ) . This location is identical to previous permanganate footprinting results , which localized open transcription bubbles within this region [31] . In contrast , for genes with elongating polII , only 30∼40% of polII resides around the TSS , however , it resides at the +45 bp position ( Figure 5C , upper panel ) . The Kolmogorov-Smirnov test confirms that both of the 5′ ends distribution and the 3′ ends distribution of polII-immunocoprecipitated reads between stalled polII group and elongating polII group are statistically significant ( 5′ end: p = 2 . 3×10−3; 3′ end: p = 1 . 7×10−4 ) . This 10-bp difference of RNA polII position may reflect distinct pausing stages during the transition from transcription initiation to fully engaged elongation . It may be used as a signature to predict the transcriptional activity of a gene . To understand the relationship between RNA polII stalling and epigenetic regulation , we analyzed the distribution of chromatin modifications within 2-kb regions around different classes of TSSs ( Figure 5D ) . Interestingly , polII-stalled TSSs are associated with a strong peak of HP1a but not other chromatin modifications ( Figure 5D , middle panel ) . This echoes our finding that HP1a-mediated gene expression regulation is independent of other interrogated chromatin modifications and suggests that HP1a is not recruited here by H3K9me3 , but possibly rather by interaction with RNA polII . Distinct to this profile , genes with elongating RNA polII show very low levels of HP1a at TSSs but high levels of H3K4me3 and H3K9ac downstream of TSSs ( Figure 5D , upper panel ) . To further explore the overall effect of chromatin modification on gene expression , we clustered 7 , 826 Drosophila genes with known expression levels based on similarities of their epigenetic profiles around TSSs ( Figure 6A ) . Interestingly , hierarchical clustering reveals six prominent gene clusters , each of which displays a characteristic gene expression profile and epigenetic signature around TSSs . Cluster ( a ) represents high-expressing genes with only high levels of RNA polII but no other epigenetic marks . Gene ontology analysis indicates this cluster is enriched for genes involved in transcription regulation , alternative splicing and development ( Table S3 ) . Cluster ( b ) contains low-expressing/silent genes with medium levels of RNA polII and H3K27me3 but high levels of HP1a . Cluster ( c ) and ( d ) consist of high-expressing genes with high levels of RNA polII , and high levels and medium levels of H3K9ac , respectively . These clusters are enriched for housekeeping genes , related to ribosome functions . Cluster ( e ) represents low-expressing/silent genes with H3K4me3 , H3K27me3 and H3K9ac present at TSSs . This cluster is enriched for genes involved in G-protein coupled receptors . Cluster ( f ) contains medium-expressing genes with medium levels of RNA polII and high levels of H3K9ac . This cluster is enriched for oxidoreductases encoding genes . The above data reveal strong correlations between histone codes surrounding TSSs and expression of genes with distinct types of biological functions in a whole organism context . To further understand this correlation , we employed a four-layer artificial neural network ( ANN ) [34] to predict gene expression levels by quantitative values of chromatin modifications around TSSs . With 50% of data allocated as a training set , we achieved 86 . 7% accuracy in the prediction of quantitative gene expression levels , which strongly suggests a causal relationship between TSS-located histone codes and gene expression ( Figure 6B ) . Furthermore , we extracted weights for an individual “neuron” within the input layer after training , and identified H3K9ac downstream of TSSs and H3K27me3 surrounding TSSs as the two most critical factors determining the accuracy of target gene expression prediction ( Figure 6B ) . To further narrow down the critical regions of these chromatin modifications in determining gene expression , we fed a neural network with averaged densities of chromatin modifications in nineteen 50-bp windows around TSSs ( −450 bp∼+450 bp ) . With overall 87 . 9% accuracy , we find the presence of RNA polII and H3K9ac downstream of TSSs ( 0∼450 bp ) are remarkable positive predictors of gene expression ( Figure 6C ) . In addition , H3K4me3 and H3K27me3 around TSSs ( −100 bp∼+100 bp ) are also pivotal to gene expression prediction , which echoes the opposing functions of Trithorax group proteins ( TrxG ) and Polycomb group proteins ( PcG ) in regulating gene expression . In searching for chromatin modifications at exon-intron and intron-exon junctions , we discovered that RNA polII is unevenly distributed at splicing junctions . Specifically , RNA polII is concentrated within exons with a prominent peak centered at −90 bp upstream of exon-intron junctions ( Figure 7A ) . By contrast , RNA polII scores drastically drop to the background levels once the transcription machinery goes into introns . At intron-exon junctions , RNA polII is devoid from the region centered at −30 bp upstream of the junctions but accumulated on the exon sides ( Figure 7B ) . This distribution profile of RNA polII mimics the nucleosome densities surrounding the exon-intron and intron-exon junctions in Drosophila [35] , implicating an influence of chromatin structure on polII elongation . Our results support the hypothesis that nucleosomes enriched in exons function as ‘speed bumps’ at splicing junctions to slow the rate of RNA polII elongation in favor of RNA splicing [35] . To gain further insight on the uneven distribution of polII at splicing sites , we calculated the numbers of exons and splicing variants for genes manifesting the polII slowing in exons ( 254 genes in total ) and compared to those of remaining genes . As expected , those genes with polII slowing in exons have 2 . 07 annotated splicing variants on average , which are significantly more than other Drosophila genes ( Figure 7C and 7D ) .
Transposons occupy approximately one third of the Drosophila genome [36] . In the everlasting competition with these parasitic DNA , flies have evolved defensive mechanisms to regulate transposition of transposons . Recent discoveries indicate that transposon mobilization is controlled at two levels: transcriptional silencing by heterochromatin formation and post-transcriptional silencing via small RNA-based transposon RNA degradation . Our finding that heterochromatic marks H3K9me3 and HP1a are enriched in transposons indicates that a general scheme of transposon silencing in Drosophila is packaging the transposon-rich sequences into heterochromatin . Within heterochromatin , methyltransferase SU ( VAR ) 3–9 sets the H3K9me3 mark , which recruits HP1a to initiate the heterochromatin formation [19] , [20] , [37] . In line with this view , we observed significant correlation between H3K9me3- and HP1a-levels in transposons . The most striking correlation is between H3K9me3 and H3K27me3 , which suggests the possible co-localization of these two silencing marks in transposons . The co-localization of H3K9me3 and H3K27me3 has been observed in the chromocenter core regions on Drosophila polytene chromosomes [38] . Since no known enzyme can methylate H3 to trimethylation states for both Lysine 9 and Lysine 27 , it would be interesting to investigate in the future whether SU ( VAR ) 3–9 and E ( Z ) function synergistically to silence transposons by heterochromatin formation . Recently , RNA-based transposon silencing mechanisms have been uncovered . In Drosophila , posttranscriptional silencing pathways mediated by endo-siRNAs and piRNAs are involved in transposon silencing in the soma and germline , respectively [39] . A common scheme in these pathways is that transcription from transposon-rich regions is employed by host cells to generate defensive small RNAs , which in turn are utilized to degrade transposon transcripts . The presence of transposon-derived small RNAs dictates that transcriptional activity must exist in transposon sequences . In support of this idea , we find euchromatic mark H3K4me3 is indeed prevalent in some but not all transposons . This observation also echoes our previous finding that a transposon-rich region in the subtelomere of the right arm of chromosome 3 ( 3R-TAS ) contains both heterochromatic ( H3K9me2 , H3K9me3 and HP1a ) and euchromatic ( H3K4me2 , H3K4me3 and H3K9ac ) marks [16] . Interestingly , this well-defined heterochromatin region is transcriptionally competent , giving rise to a panel of piRNAs and permissive to transcriptional activities from a reporter gene inserted in this region . Therefore , it is conceivable that many transposons and repetitive sequences with similar epigenetic states are also transcriptionally active , albeit at low levels . Our analysis of protein-coding genes reveals three salient features of chromatin modifications , which reflect distinct histone codes , in all transcriptionally active genes . First , their transcribed regions are all enriched with H3K9ac . This is consistent with the notion that H3K9ac specifically associates with transcriptional activity and can spread over the whole gene body . Second , the TSSs and TxEnds of active genes are further enriched with H3K4me3 ( Figure 3F ) , which is consistent with the enrichment of H3K4me3 around TSSs of transcriptionally active genes in mammalian genomes . In addition , the drastic enrichment of H3K4me3 and H3K9ac in the 5′ transcribed region ( 5′TR ) and the sharp decrease at TSSs to become severely under-represented in promoter regions ( Figure 3F and 3G ) is also observed for H3K4me3 in the human genome . In contrast to H3K4me3 and H3K9ac , H3K9me3 shows the opposite pattern in the promoter-5′TR; whereas H3K27me3 is underrepresented in both promoter and 5′TR of active genes ( Figure 3H and 3I ) . These striking patterns of histone code around the TSS collectively represent an epigenetic signature for all actively transcribed genes . The robustness of this signature corresponds nicely to the transcriptional activity of a gene . It indicates that , in active genes , the promoter region is highly enriched in HP1a , the 5′TR is highly euchromatic , and the Polycomb repressive complex 1 is absent from both promoter and 5′TR of active genes . Third , RNA polII is over-represented in both promoter and 5′TR of active genes . Moreover , the extent of the over-representation strictly corresponds to the transcriptional activity of the gene . Fourth , stalled and elongating RNA polymerase II are positioned at +35 bp and +45 bp , respectively ( Figure 5C ) , as discussed in detail in the next section . Lastly , different active genes with different biochemical functions have distinct signatures of histone code at their TSS region . This finding , based on clustering 7 , 826 Drosophila genes according to similarities of their epigenetic profiles around TSSs , indicate the possibility that genes of similar functions are transcriptionally co-regulated by the same histone code set . This type of transcriptional regulation would be conceptually similar to the trans-operon fashion of translational regulation , where many mRNAs sharing common 3′UTR elements are regulated by a common translational repressor [40] . Although it has been assumed that transcription initiation is the rate-limiting step in gene expression regulation , recent genome-wide mapping of RNA polII have revealed polII stalling as a critical control mechanism of gene expression during development [30] , [31] , [41] . In humans and fruitflies , RNA polII initiates on most genes but pauses immediately downstream of TSSs before it enters into productive elongation to generate full-length mRNAs . The permanganate footprinting has mapped the transcription bubbles between +30 bp to +80 bp on a small set of polII-stalled genes in Drosophila [30] , [31] . Similarly , RNA-Seq of nuclear capped short RNAs has implicated that polII stalls within a region ranging from +25 bp to +60 bp downstream of TSSs [42] . In this study , we directly map RNA polII around TSSs by ChIP-Seq in an unprecedented 5-bp resolution , which unambiguously pinpoints the stalled polII in a 50 bp region , centered at +35 bp downstream of 685 TSSs . The fact that our ChIP-Seq sample is from whole flies indicates that polII stalling around +35 bp is a general mechanism ubiquitously present in most , if not all , cells . In addition , we also found a lower but evident level of polII stalled around +45 bp on actively transcribing genes . Intriguingly , the different positions of stalled polII and elongating polII echo the different positions of +1 nucleosome at the 5′ ends of genes . In mammals , active genes ( mostly with elongating polII ) have the 5′ ends of the +1 nucleosome predominantly peaked at +40 bp , which is in contrast to the +10 bp positioning of +1 nucleosome in the inactive promoters ( including promoters with stalled polII ) [33] . In Drosophila , the predominant arrangement of the 5′ ends of the +1 nucleosome at +62 bp might allow the free access to the TSS by RNA polII at the initiation stage whereas also pose potential blockage downstream of TSS after initiation [43] . Thus , this 10 bp difference of RNA polII may reflect the influence of +1 nucleosome on stalled and elongating polII . It would be interesting to understand the positioning of +1 nucleosomes for polII-stalled genes and polII-elongating genes in the future . Alternatively , this difference of polII position suggests that RNA polII stalling may process in multiple steps . In addition to its well-known role in heterochromatin formation in transposon-rich regions , HP1a has been reported to positively regulate the expression of protein coding genes [44] , [45] , [46] , [47] . This euchromatic function of HP1a is supported by both genome-wide mapping of HP1a binding sites [11] , [12] , [48] and gene expression analysis of HP1a mutants [29] , [49] . By ChIP-Chip assays , HP1a is revealed to bind to the whole transcription unit , particularly exons , of its target genes [11] , [48] . However , it remains controversial whether HP1a is associated with promoters in general [11] , [48] . Our high-resolution mapping of HP1a by ChIP-Seq reveals the prevalence of HP1a binding to both promoters and transcription units of many protein-coding genes throughout the genome . In addition , the striking positive correlation between the accumulation of HP1a and the expression levels of its target genes strongly suggests a direct role of HP1a in transcriptional regulation . Such a correlation was previously observed for HP1a target genes on 4th chromosomes and led to a “buffering” hypothesis , wherein HP1a and Painting of Fourth ( POF ) represent counteracting repressing and stimulating factors to achieve a stable expression of their common target genes [11] . Given the specific localization of POF , the function of HP1a in gene expression regulation on other autosomes remains elusive . Instead , our high-resolution map of chromatin modifications at 5-bp resolution , reveals an amazing similarity between HP1a localization and that of RNA polII on protein coding genes . Although we cannot exclude the possibility that HP1a and RNA polII locate separately in the same set of genes but in different cells , the almost identical spatial and quantitative distributions of HP1a and RNA polII strongly suggests that these two factors actually are co-localized . In support of this view , HP1a has been recently demonstrated to bind to mRNAs and interacts with RNA polII in Drosophila [46] . Our data further indicate that HP1a may co-localize with stalled polII on chromatin immediately downstream of TSSs , implicating a regulatory function of HP1a in controlling RNA polII elongation . This is consistent with our observation that HP1a is preferentially concentrated at TSSs of its regulated genes . We hypothesize that HP1a may function to stabilize RNA polII in its permissive state , waiting for external signals . In the absence of HP1a , un-stabilized polII will either terminate the transcription or prematurely transit to the elongating step . This hypothesis can potentially explain the profound opposing effects of HP1a on its activated and repressed genes , wherein a comparable amount of HP1a is observed around TSSs . Perhaps , the most unexpected finding in our study is that RNA polymerase II is concentrated on the exon sides of exon-intron and intron-exon junctions . This enrichment clearly indicates that elongating polII moves at a reduced rate within exons . These data provide strong direct evidence to a proposed kinetic model , which suggests that a reduced transcriptional elongation rate may facilitate the recognition of splice sites by the transcription-coupled splicing machinery [50] . This model is further supported by recent studies , which clearly demonstrated nucleosomes and trimethyl Histone 3 at Lysine 36 ( H3K36me3 ) are preferentially enriched in exons comparing to introns [35] , [51] , [52] , [53] , [54] . This kinetic model further predicts that genes with multiple exons and/or alternative splicing events should preferentially demand polII slowing at their splicing junctions . Indeed , we found genes manifesting RNA polII slowing at exon-intron junctions have significant more RNA splicing variants than other genes . Taken together , our findings , along with a series of recent discoveries , support that the positioning of modified histones and nucleosomes marks the exons to slow down RNA polII elongation . This slowing down of RNA polII may facilitate the recruitment of splicing machinery to recognize cis-acting regulatory elements on emerging nascent RNA [35] . Notably , we cannot exclude the possibility that the depletion of RNA polII centered at −30 bp of intron-exon junctions is due to the polypyrimidine tract localized at this region . Such polypyrimidine tracts , predominant with thymidine ( T ) repeat and thus lack of uniqueness , may cause bias during micrococcal nuclease digestion and during mapping of sequencing tags to the genome . Further investigations based on different techniques may shed light on the precise polII processivity at intron-exon junctions .
Approximately 5 ml of newly eclosed flies ( w1118 ) were collected , frozen in liquid nitrogen , and pulverized to a fine powder using a mortar and pestle . The fine powder was resuspended in 5 ml of Buffer A+ [60 mM KCl , 15 mM NaCl , 13 mM EDTA pH 8 . 0 , 0 . 1 mM EGTA , 15 mM HEPES pH 7 . 4 , 0 . 5 mM DTT , 0 . 5% NP-40 , 1× Protease Inhibitor Cocktail ( 1xPI , Roche ) ] and sequentially disrupted with ∼10 strokes in a 7 ml homogenizer ( Dounce ) and ∼20 strokes in a 15 ml homogenizer ( Wheaton ) . The homogenate was then filtered through two layers of Miracloth , loaded onto 2 ml of Buffer AS ( 60 mM KCl , 15 mM NaCl , 1 mM EDTA pH 8 . 0 , 0 . 1 mM EGTA , 15 mM HEPES pH 7 . 4 , 0 . 3 M sucrose ) and centrifuged at 3 , 500 rpm for 12 minutes at 4°C ( Beckman Coulter Optima L-100 XP Ultracentrifuge ) . The cytosolic layer was removed and the nuclei pellet were resuspended in 5 ml of Buffer A ( 60 mM KCl , 15 mM NaCl , 1 mM EDTA pH 8 . 0 , 0 . 1 mM EGTA , 15 mM HEPES pH 7 . 4 , 0 . 5 mM DTT , 1 mM PMSF , 5 mM Sodium Butyrate , 1xPI ) . The nuclei solution was transferred to a 7 ml homogenizer ( Wheaton ) and disrupted with ∼10 strokes of the “loose” pestle . The solution was again loaded onto 2 ml Buffer AS and centrifuged at 3 , 500 rpm for 10 minutes at 4°C . The crude nuclei were aliquoted into 2 ml siliconized eppendorf tubes and stored at −80°C until ∼5×109 nuclei were collected . The nuclei samples were thawed on ice and pooled . The volume was adjusted with Buffer AC ( 60 mM KCl , 15 mM NaCl , 0 . 1 mM EGTA , 15 mM HEPES pH 7 . 4 , 0 . 5 mM DTT , 1 mM PMSF , 5 mM CaCl2 , 5 mM Sodium Butyrate , 1xPI ) so that the final ratio of nuclei to Buffer AC equals 8∶3 . Pilot experiments determined that 0 . 1 U micrococcal nuclease ( MNase , USB Corp . ) will digest 120 µg chromatin DNA and produce mono- , di- , and poly-nucleosomes in a 5 minute reaction . DNA concentrations of the nuclei solution was determined by A260 absorbance readings after alkali lysis . 0 . 1 U MNase was added into nuclei based on DNA concentration and incubated at 37°C for 5 minutes . 10 µl 0 . 5 M EDTA ( pH 8 . 0 ) was added to stop the digestion . The nuclei pellets were resuspended in 500 µl Buffer AG ( 60 mM KCl , 15 mM NaCl , 10 mM EDTA pH 8 . 0 , 0 . 1 mM EGTA , 15 mM HEPES pH 7 . 4 , 0 . 5 mM DTT , 5% Glycerol , 5 mM Sodium Butyrate , 1xPI ) , centrifuged at 5 , 000 rpm . Supernatant containing mono- and di-nucleosomal fraction was separated from the pellets ( poly-nucleosomal fraction ) . This extraction was repeated 3 times in total . The pellets after the last extraction were resuspended in 500 µl Buffer AG and pooled together . The polynucleosomal fraction was sonicated ∼30 times of 20 seconds pulses at 30% output ( Branson Sonifer 450 with a microtip ) . The mono- , di-nucleosomal fraction and the sonicated poly-nucleosomal fraction were pre-cleared with Protein A Sepharose beads ( Millipore ) for 1 hour with constant agitation . The fractions were then aliquoted into 15 ml siliconized tubes . The histone antibodies were then added to each tube: 50 µg anti-trimethyl-H3K9 ( Upstate ) , 25 µg anti-trimethyl-H3K27 ( Upstate ) , 50 µg anti-acetyl-H3K9 ( Upstate ) , 50 µg anti-trimethyl-H3K4 ( Upstate ) , 25 µg anti-Histone H3 ( Upstate ) . Chromatin was incubated with antibodies overnight at 4°C with rotation . The ChIP beads were equilibrated overnight with tRNA in Buffer AG ( 200 µg tRNA/250 µl beads ) and washed with Buffer AG for 3 times to remove any excess tRNA . The tRNA-coated beads ( 5 µl dry beads per1 µg antibody ) were added to each sample and incubated for 2 hours at 4°C with rotation . The beads were washed sequentially with Wash Buffer 1 ( 60 mM KCl , 15 mM NaCl , 10 mM EDTA pH 8 . 0 , 0 . 1 mM EGTA , 15 mM HEPES pH 7 . 4 , 0 . 5 mM DTT ) , Wash Buffer 2 ( 60 mM KCl , 55 mM NaCl , 10 mM EDTA pH 8 . 0 , 0 . 1 mM EGTA , 15 mM HEPES pH 7 . 4 , 0 . 5 mM DTT ) , and Wash Buffer 3 ( 60 mM KCl , 105 mM NaCl , 10 mM EDTA pH 8 . 0 , 0 . 1 mM EGTA , 15 mM HEPES pH 7 . 4 , 0 . 5 mM DTT ) . After washing , beads were incubated in 1 ml Elution Buffer ( 50 mM TrisHCl pH 9 . 0 , 20 mM EDTA , 1% SDS ) at room temperature for 1 hour . The supernatants were phenol/chloroform extracted in PhaseLocking gel and ethanol precipitated . The precipitated DNA pellets were submitted for Illumina library construction and sequencing . Formaldehyde was added to a final concentration of 0 . 1% to the nuclei and incubated at room temperature for 15 minutes . To quench the crosslinking , 2 . 5 M glycine was added to the nuclei to a final concentration of 0 . 125 M . Quenching was performed at room temperature for 10 minutes with constant agitation . Pellet nuclei were combined and resuspended into 20 ml ChIP Buffer ( 75 mM NaCl , 50 mM HEPES pH 7 . 4 , 1 mM EDTA , 1 mM DTT , 5 mM MgCl2 , 1XPI , 10% Glycerol ) in a 50 ml siliconized tube . The nuclei were sonicated on ice for ∼30 second intervals at 30% output for 2 hours . 250 µl Protein A Sepharose beads were used for every 5×108 nuclei . The beads were washed with ChIP Buffer and then equilibrated with tRNA ( 200 µg/250 µl beads ) in ChIP Buffer + 1% BSA for overnight at 4°C . The beads were then washed with ChIP buffer for 3 times to remove any excess tRNA . Antibodies were added and incubated with beads overnight at 4°C: 250 µl crude anti-HP1a antisera ( Covance ) , 160 µg anti-RNA Polymerase II ( clone CTD4H8 , Millipore ) , 200 µg mouse IgG1 ( for mock ChIP , Abcam ) . The beads were then washed with ChIP buffer to remove any excess antibody . Chromatin samples were incubated with antibody-bound beads overnight at 4°C . The beads were washed for 5 minutes for each washing buffer: 1 . RIPA 150 ( 50 mM HEPES pH 7 . 4 , 150 mM NaCl , 2 mM EDTA pH 8 . 0 , 1% Triton X-100 , 0 . 1% SDS ) , 2 . RIPA 500 ( 50 mM HEPES pH 7 . 4 , 500 mM NaCl , 2 mM EDTA , 1% Triton X-100 , 0 . 1% SDS ) , 3 . LiCl Buffer ( 50 mM HEPES pH 7 . 4 , 0 . 25 M LiCl , 1 mM EDTA , 1% NP-40 ) , 4 . TE Buffer . The beads were then eluted at room temperature in 500 µl Elution Buffer for 30 minutes . The supernatant was transferred to another tube and the elution was repeated with another 500 µl Elution Buffer . 8 µl Proteinase K ( 20 mg/ml ) was added to the 1 ml combined elute samples and incubated at 37°C for 30 minutes . The ChIP samples were then reversed crosslinked by incubating at 65°C for 4 hours , phenol/chloroform extracted in PhaseLocking gels , and ethanol precipitated . The ChIP DNA pellets were dissolved in TE . Adapters are ligated to the ends of the ChIP DNA and PCR amplified before sequencing on Illumina GA . Sequenced 35 nt reads ( with <5 ambiguous bases ) and corresponding quality tracks were collected from the Bustard module of Illumina Analysis Pipeline and transformed into FASTQ format . A PERL-coded Illumina ChIP-Seq analysis pipeline was developed to streamline the tag mapping and downstream data collection and statistic analyses . Input reads were iteratively mapped to the Drosophila melanogaster genome ( BDGP R5 ) by a third-party SOAP program with increasing allowance of mismatches ( up to 5 bases ) and indels ( up to 4 bases ) , until the majority ( >60% ) of input reads were mapped to the reference genome . Both unique-mapping tags ( mapped to only one genomic locus ) and multiple-mapping tags ( mapped to more than one genomic loci ) were retained and only the best genomic matching site ( s ) were reported . Numbers of tags ( mapped Illumina reads ) for each ChIP-Seq library are listed in Table S1 . Because Illumina only sequences the first 35 nucleotides from the 5′ ends of DNA fragments , we applied a previously published tag extension approach ( XSET ) to score the genome . Briefly , a scoring matrix , reflecting the probabilities of the length of precipitated DNA fragments , was determined by the intensities of the input DNA on an agarose gel ( Figure S1B ) . These probability scores were employed to indicate the relative possibilities of associations of epigenetic marks/regulators with target genomic regions . Scores of ChIP-Seq tags were allocated into 50 bp bins across the entire genome ( including euchromatic arms , sequenced internal scaffolds and unmapped regions ) . For each tag , the genomic location of the 5′ end determines the first bin . The probability scores were given to the first bin and the downstream 9 bins ( Figure S1C ) . In order to generate comparable scores for different ChIP datasets , raw scores were transformed via three normalizations ( Figure S1D–S1G ) . First , accumulated raw scores from all tags were normalized as to 10 million tags were sequenced ( Figure S1D ) . To subtract scores of control datasets from epigenetic mark datasets ( hereafter called experimental datasets ) , we further normalized scores based on non-specific noise levels in all ChIP-Seq datasets ( Figure S1E ) . To this end , normalized scores ( per 10 million tags ) were plotted against corresponding bin numbers for each experimental dataset and the control dataset ( as exemplified by RNA polII ChIP-Seq vs . mock ChIP-Seq in Figure S1F ) . A critical value , beyond which the corresponding bin numbers in an experimental dataset are always more than those in the control dataset , was determined for each experimental/control dataset pair ( Figure S1F ) . A normalizer was further determined for each experimental/control dataset pair in a way that the correlation coefficient between these two datasets for values lower than the critical value are maximized when the scores of the experimental dataset are multiplied by this normalizer . We found this normalizer can be estimated by the ratio between X ( representing the peak value of the control dataset ) and Y ( representing the peak value of the experimental datasets ) for most datasets examined ( Figure S1F ) . We calculated adjusted scores for all bins in experimental datasets with signals from control datasets subtracted ( Figure S1G ) . For an adjusted score , we estimated the FDR as the ratio of the number of bins that the control dataset indicated should occur by chance , to the number observed in experimental dataset . For each experimental dataset , we chose a threshold of adjusted scores as the smallest adjusted scores that was equivalent to FDR<0 . 001 . Only adjusted scores above this threshold were reported to indicate the relative abundance of epigenetic marks across the genome . For each ChIP-Seq dataset , the final adjusted ChIP-Seq scores were recorded into files in wiggle track format ( WIG ) and browser extensible format ( BED ) for viewing the data in Integrated Genome Browser ( Affymetrix ) and the UCSC Genome Browser . HP1a ChIP-Chip datasets were collected from Gene Expression Omnibus ( GEO ) database ( GSM205826 , GSM205827 and GSM205828 ) . HP1a DamID-Chip datasets were collected from GEO database ( GSM151831 , GSM151832 and GSM151833 ) . Genome coordinates from both datasets were changed to the Drosophila melanogaster genome ( BDGP R5 ) by UCSC liftover tools . To correlate ChIP-Chip with ChIP-Seq , the genomic regions interrogated by Nimblgene tiling array ( GPL5404 ) were divided into 1-kb windows sorted based on their ChIP-Chip scores for HP1a . Windows were grouped into 100 percentiles and the corresponding averaged ChIP-Seq ( U ) scores were calculated . Pearson Product-Moment correlation was performed between ChIP-Chip scores and ChIP-Seq ( U ) scores for these 100 percentiles . To correlate DamID-Chip with ChIP-Seq , the genomic regions interrogated by Nimblgene tiling array ( GPL2678 ) were divided into 1-kb windows sorted based on their DamID-Chip scores for HP1a . Windows were grouped into 100 percentiles and the corresponding averaged ChIP-Seq ( U+M ) scores were calculated . Pearson Product-Moment correlation was performed between ChIP-Chip scores and ChIP-Seq ( U+M ) scores for these 100 percentiles . Gene expression information of adult whole flies was obtained from Gene Expression Omnibus ( GSE5382: GSM106918 , GSM122994 , GSM123002 , GSM123003 , GSM123007 and GSE7763: GSM188112 , GSM188113 , GSM188114 , GSM188115 ) . In total , 12 , 523 genes were interrogated by Affymetrix Drosophila GeneChip 2 . 0 microarray assays in both datasets . Of these , 6 , 756 genes show consistent relative expression levels ( denied by SAM analyses ) between samples and between datasets . These 6 , 756 genes were sorted based on the averaged expression values from microarray replicates , and were further classified either into 10 gene expression groups or 100 gene expression percentiles by ranks in the expression profile . Gene expression information of wild type and HP1a RNAi third instar larva was downloaded from GEO ( GSM67069 , GSM67070 , GSM67067 , GSM67068 , GSM67073 , GSM67071 and GSM67072 ) . In total , 12 , 521 genes were interrogated by Affymetrix Drosophila Genome 2 . 0 Array . These genes were sorted and grouped into 100 percentiles based on the ratios of their expression in HP1a RNAi samples versus wild type samples . Gene expression of males and females were calculated separately . The correlation analyses shown in Figure 4C were performed using gene expression data from females . Although HP1a was shown to have male-specific effects on lethality and gene expression regulation , the analyses using gene expression data from males revealed essentially the same trends as those of females ( data not shown ) . Genomic coordinates of TSS , TxEnd , Exon-Intron junctions , Intron-Exon junctions were collected from Drosophila melanogaster annotation database R5 . 5 ( ftp://ftp . flybase . net/releases ) . Genes in different expressive groups were aligned at the same direction at the transcription start sites ( TSSs ) , at the mid points of gene bodies and the transcription end points ( TxEnds ) , respectively . To avoid noises from nearby transposon/repetitive sequences , ChIP-Seq ( U ) scores were employed in this analysis . Sliding windows of 5 bp were applied in the calculation . For each 5-bp window , scores of all genes within a gene expression group were averaged after trimming off outliers ( 10% of the total gene number ) in both ends . If a gene has more than one annotated TSSs or TxEnds , averaged scores of all TSS and TxEnd were included in the gene expression group that the gene belongs to . To classify genes into groups with elongating RNA polII , stalled RNA polII and no polII , RNA polII stalling index was calculated in the same way as previously published [31] , [33] . To avoid the noises from nearby transposon/repetitive sequences , ChIP-Seq ( U ) scores were used in this analysis . The polII scores of promoters were calculated as the average RNA polII ChIP-Seq scores within TSS-surrounding regions ( −500 bp∼+500 bp ) . The polII scores of gene bodies were calculated as the average RNA polII scores within gene bodies downstream of TSSs ( +750 bp∼+2500 bp ) . If the promoter region or gene body region of two genes were overlapping with each other , scores from overlapped regions were not included in the calculation . A stalling index was then defined as the ratio of the promoter polII score over the gene body score . Genes with elongating polII were defined as those with promoter scores at least 5 and with stalling index less than 3 . Genes with stalled polII were defined as those with promoter scores at least 5 and with stalling index greater than 10 . Genes without polII were defined as genes with both promoter score and body score less than 1 . To infer the precise positions of RNA polII at TSSs , Illumina reads from polII ChIP-Seq were mapped to the TSS surrounding regions ( −1 kb∼+1 kb ) and separated based on their relative orientation to genes . The number of Illumina reads in each 5-bp windows surrounding TSSs were normalized to the corresponding read numbers from the mock ChIP-Seq . A positive value for normalized read number indicates RNA polII is enriched whereas a negative value indicates RNA polII is depleted . Similar analysis was performed to investigate RNA polII pausing at exon-intron and intron-exon junctions . Dynamic neural network with an input layer ( 10 neurons in analysis shown in Figure 6B , or 114 neurons in analysis shown in Figure 6C ) , two hidden layers ( 2 neurons by 3 neurons ) and an output layer ( quantitative gene expression estimation ) were constructed and trained by 50% of random selected input data . To infer the relative important of each input variables , 10 runs of independent training/estimation were performed ( Figure 6B ) . Relative importance was calculated from neuron weights and averaged . Flybase IDs of a gene set were analyzed by a web-based Functional Annotation Tool of Database for Annotation , Visualization and Integrated Discovery ( DAVID , http://david . abcc . ncifcrf . gov/ ) . | Just as a genome sequence map is indispensible to genetic studies , an epigenome map is crucial for epigenetic research . This is especially true for a sophisticated genetic model such as Drosophila melanogaster , where the wealth of information on genetics and developmental biology awaits systematic epigenetic interpretation on a whole-genome scale . In this manuscript , we report a high-resolution map of key chromatin modifications in the Drosophila genome constructed by the ChIP–Seq approach . This map is derived from all cell types in the adult Drosophila weighted by their natural abundance . It contains key histone marks , HP1a and RNA polymerase II , mapped at 50-bp resolution throughout the genome and at 5-bp resolution for regulatory sequences of genes . It reveals striking features of chromatin modification and transcriptional regulation shared by major adult Drosophila cell types . We anticipate that this map and the salient chromatin modification landscapes revealed by this map should have broad utility to the fields of epigenetics , developmental biology , and stem cell biology . | [
"Abstract",
"Introduction",
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"Methods"
] | [
"biology"
] | 2011 | A High-Resolution Whole-Genome Map of Key Chromatin Modifications in the Adult Drosophila melanogaster |
In a study of household contacts ( HHC ) , households were categorized into High ( HT ) and Low ( LT ) transmission groups based on the proportion of HHC with a positive tuberculin skin test . The Mycobacterium tuberculosis ( Mtb ) strains from HT and LT index cases of the households were designated Mtb-HT and Mtb-LT , respectively . We found that C3HeB/FeJ mice infected with Mtb-LT strains exhibited significantly higher bacterial burden compared to Mtb-HT strains and also developed diffused inflammatory lung pathology . In stark contrast , a significant number of mice infected with Mtb-HT strains developed caseating granulomas , a lesion type with high potential to cavitate . None of the Mtb-HT infected animals developed diffused inflammatory lung pathology . A link was observed between increased in vitro replication of Mtb-LT strains and their ability to induce significantly high lipid droplet formation in macrophages . These results support that distinct early interactions of Mtb-HT and Mtb-LT strains with macrophages and subsequent differential trajectories in pathological disease may be the mechanism underlying their transmission potential .
Mtb is one of the most successful pathogens known; yet mechanisms underlying variability in transmission remain poorly understood . Pioneering work from Riley and colleagues [1] using TST conversion in guinea pigs that were exposed to air from a TB ward as a measure of infectiousness , found significant variability in infectiousness among untreated patients with drug susceptible Mtb . Despite having comparable sputum positivity , only 8 of the 61 patients in the TB ward were found to transmit infection [1] . Using a similar model of air sampling analysis in test animals , a great degree of variability in infectiousness was also reported for HIV-infected patients with drug susceptible and resistant TB [2–4] . Subsequent studies demonstrated that some patients transmit their infection to large numbers of contacts whereas other patients transmit rarely or not at all ( even after controlling for factors such as extent of disease in the index case and length of exposure ) [5–10] . Variability in transmission could result from differences in the variability of infectious aerosols produced during coughing by patients with pulmonary tuberculosis [11] . Mycobacterium tuberculosis Complex ( MTBC ) comprises of six human adapted lineages and a recently discovered lineage 7 [12] . Whole genome sequence data show that the lineages differ in their content of SNPs , small insertion and deletions , large genomic deletions , large duplications and insertion sequences [12] . Several studies have addressed whether Mtb genotypic diversity is associated with diversity in clinical outcome [reviewed in [12 , 13]] . Overall , lineage 2 was found to be highly associated with virulence and transmission in different ethnic populations [14–20] . However , other studies did not find a higher fitness for Beijing strains of lineage 2 [21–23] . For example , in a cohort study of patients with TB and their HHC in The Gambia where M . africanum is endemic , there was no difference in transmission between M . africanum and Mtb or between the MTBC lineages [24] . In another population-based study in Montreal , Canada , four Mtb lineages were identified- Euro-American ( lineage 4 ) , Beijing ( lineage 2 ) , Indo-Oceanic ( lineage 1 ) and East African-Indian ( EAI-lineage 3 ) [25] . In contrast to previous studies , higher transmissibility of the Beijing lineage was not observed in this study . However , the EAI lineage was associated with lower rates of TB transmission , as measured by positive TST among close contacts of pulmonary TB cases [25] . The Beijing genotype consists of a number of sub-lineages and so the discrepant findings could be due to the prevalence of different sub-lineages in the different study populations , as suggested previously [12] . For example , in a study conducted in Western Cape , South Africa , significantly higher transmission was found to be linked to recently evolved sub-lineages of the Beijing strain family than to other sub-lineages , indicating that strains within individual lineages have acquired distinct transmissibility traits [17] . Similarly , a study from China also concluded that transmissibility was dissimilar among the Beijing sub-lineages [26] . Consistent with the idea that there is heterogeneity within a lineage , studies in an animal model of transmission reported that Beijing genotype strains exhibited various degrees of virulence phenotype and transmissibility [26] . It has been suggested that the heterogeneic immune response and virulence of the Beijing strains may be due to their differential engagement of the innate Toll-like receptors ( TLR ) [27] . The high transmissibility and prevalence of some sub-lineages belonging to the Beijing phenotype raises the question of whether the type of immune response elicited by some strains in the lineage gives them a selective advantage over other genotypes . In this regard , strains within the highly prevalent “modern” Beijing genotype have been linked to low inflammatory cytokine responses [28–30] and faster growth rate in vitro [31 , 32] compared to strains within the “ancient” Beijing genotype . By selecting representative strains from the Modern ( lineage 2 , lineage 3 and lineage 4 ) and ancient lineages ( lineage 1 , lineage 5 and lineage 6 ) , Portevin et al . [30] extended the analysis of macrophage cytokine responses to all the major phylogenetic lineages . They found that overall , strains from the modern lineages induced lower levels of pro-inflammatory cytokines when compared with strains representing ancient lineages . Furthermore , two strains , HN878 ( lineage 2 ) , a member of the Beijing family that caused several outbreaks of TB in Texas [33 , 34] and Mtb strain CH ( lineage 3 ) that caused a large outbreak of TB in Leicester , UK [35] also exhibited a low inflammatory phenotype . In contrast , CDC1551 ( lineage 4 ) that also caused a large number of TB infections in a small rural community in Tennessee [36] , induced a robust inflammatory response and was less virulent in mice [37] . The finding with CDC1551 , together with several studies showing lack of association of “modern” lineages with disease presentation [38–41] or transmission [21–24] , indicates an incomplete understanding of bacterial factors that favor transmission success . Many factors , including source infectiousness [42] , cough aerosols [43] and nature and proximity of contact [44] affect transmission . To address pivotal questions pertaining to transmissibility of different Mtb strains , we conducted a study that included 731 household contacts ( HHC ) of 124 infectious TB patients , and found marked heterogeneity in Mtb transmission within households [42] . Index cases ( with pulmonary TB disease ) and their respective households were categorized into high ( HT ) and low ( LT ) transmission groups based on the proportion of HHC with a positive tuberculin skin test . The Mtb strains from HT and LT index cases of the households were designated Mtb-HT and Mtb-LT , respectively . The goal of this study was to explore the role of Mtb strain in the observed differences in transmission and the mechanistic basis by which the epidemiologically characterized Mtb-HT and Mtb-LT strains , though belonging to lineage 4 , have diversified in their transmission profile . The C3HeB/FeJ mouse model was employed to examine the role of Mtb strain in the dichotomous transmission outcomes of the HT and LT households . Although there are disparities in susceptibility to infection and disease manifestations that exist between humans and animals , experimental models such as C3HeB/FeJ mice that present with lung pathology more typical of human TB disease [45–49] are useful for hypothesis-driven research aimed at understanding TB immunopathogenesis . Using the C3HeB/FeJ mouse model , we found that Mtb-HT and Mtb-LT strains induced distinct growth pattern and pathological disease that fit their transmission phenotype . We also found increased lipid biogenesis in Mtb-LT infection of macrophages compared to Mtb-HT infection suggesting that this difference in host response may be a factor in the divergence in infection outcome between the two groups of animals .
As previously reported , the HHC study only included crowded ( ≥3 HHC ) dwellings with an intense ( ≥3 weeks of cough ) and homogeneous ( sputum AFB ≥2 ) infectious exposure , and classification of households as “high” or “low” transmission was based on TST positivity of contacts at the end of enrollment [42] . Briefly , the percentage of contacts from a given household that had a TST≥ 10mm of induration either at baseline or by 8–12 weeks was used to determine the transmission category of the household . If there were ≥70% TST positivity in HHCs , the active TB disease patient or “index case” was considered “High Transmission” ( HT ) and if there was ≤40% contacts that were TST positive , the index case was considered “Low Transmission” ( LT ) [42] . 293 TB patients were screened and 124 index cases were enrolled . The Mtb strain isolated from HT index case was designated Mtb-HT and from LT index case was designated Mtb-LT . From the panel of HT and LT strains , three strains from each group were randomly picked , blinded to any patient or household contact details . Based on subsequent examination of the index case and household characteristics , it is reasonable to assume that the six randomly selected strains are representative of the larger groups of HT and LT strains . All of the HT and LT strains belong to lineage 4 . The index case and household characteristics of the six strains are described in Table 1 . Total TST positivity was 100% for the HT index cases and 14–40% for the LT cases ( Table 1 ) . All of the six isolates were collected from the Vitória Metropolitan area . Vitória , Brazil is the capital city of Espírito Santo , a state with a TB incidence rate of 38/100 , 000 and very low HIV prevalence in TB cases ( <2% ) and the general population ( <1% ) . While migration into this region is limited , there is a high level of inter-municipality mobility amongst inhabitants . We previously showed that there was no relationship between the HT and LT transmission phenotypes and the presence of RFLP/spoligotyping clusters in the community [50] . As shown in Table 1 , the six strains were unique isolates or belonged to different clusters . Based on RFLP , Mtb-HT1 and Mtb-LT1 are different even though they both fall within the LAM9 sub-lineage . This sub-lineage is the most common spoligotyping sub-lineage in Brazil . Based on radiographic appearance , HT1 and HT3 index cases had far advanced lung disease and HT2 , LT1 , LT2 and LT3 index cases had moderately advanced lung disease . Chest X-rays of the TB patients showed that HT1 , HT2 and HT3 index cases had cavitations , whereas only patient LT1 presented with cavitary disease ( Table 1 ) . For in vitro assays , seven additional strains isolated from HT and LT index cases were tested ( S1 Table ) . In separate infections , previously grown stocks of the six Mtb clinical strains described in Table 1 were used to infect C3HeB/FeJ mice . Bacterial burden was monitored at different time-points following aerosol infection of the mice ( Fig 1 ) . We observed that despite similar inoculum size , lung bacterial burden in mice infected with two of the three Mtb-LT strains , Mtb-LT1 and Mtb-LT2 , were significantly higher than all three HT strains at all time points sampled ( Fig 1 ) . Mtb-LT3 produced higher bacterial growth at week 2 post infection but was not significantly different from Mtb-HT strains at later time points ( Fig 1 ) . These changes in bacterial growth were also reflected in extra-pulmonary dissemination to the spleen and liver ( S1 Fig ) . A repeat experiment with Mtb-HT1 and Mtb-LT1 also showed that CFU in the lungs , mediastinal lymph nodes and spleen at 12 weeks of infection was significantly higher in Mtb-LT1 infected mice compared with Mtb-HT1 infected mice ( S2 Fig ) . To delineate whether host genotype contributed to the differences between Mtb-HT and Mtb-LT strains , we also infected inbred C57BL/6 and BALB/c mice with Mtb-HT1 and Mtb-LT1 strains . In both genotypes of mice , we observed that compared to Mtb-HT1 , Mtb-LT1 infected C57BL/6 and BALB/c mice showed significantly higher CFU in the lungs ( S3A Fig ) . Next , we evaluated the composition of the cellular infiltrates to the lungs of 4 week-infected C3HeB/FeJ mice . We observed that all three strains of Mtb-LT infected C3HeB/FeJ mice had significantly higher number of total viable cells in the lungs as compared to the mice infected with the three Mtb-HT strains ( Fig 2A ) . Further analysis of the cellular composition of the recruited cells showed that , compared to Mtb-HT1 , all three Mtb-LT infected mice had significantly increased numbers of CD8+ T cells and CD11b+CD11c+ recruited macrophages while B220+ B-cells , CD11bhiLy6G+ neutrophils were increased in Mtb-LT1 and Mtb-LT2 infections . CD4+ T cells and CD11b-CD11c+ alveolar macrophages were significantly enhanced only in Mtb-LT1 infection ( Fig 2B ) . There was no significant increase in any cellular subsets in Mtb-HT2 and Mtb-HT3 infections compared to Mtb-HT1 ( Fig 2B ) . The increase in neutrophil numbers in Mtb-LT1 infection was confirmed in immunohistochemical staining of lung sections . A large number of Ly6G+ neutrophils were observed in the granulomatous lesions of four week Mtb-LT1 infected mice compared to Mtb-HT1 infected mice that had sparse neutrophils in the granuloma ( Fig 2C ) . Consistent with increased cellular recruitment , evaluation of lung homogenates showed an overall increase in TNF , IL-1β , IL-6 , IL-17 and KC ( CXCL1 ) in Mtb-LT infected mice at four weeks following infection compared with Mtb-HT infected mice ( S4 Fig ) . These data indicate that Mtb-LT strains induce an overall strong inflammatory response , admittedly , though , this could be an indirect effect as a result of the increased bacterial burden in these mice . H&E staining of paraffin-embedded lung sections revealed that there were striking differences in the types of granulomatous lung lesions that were formed between animals infected with Mtb-HT and Mtb-LT strains . Although early on , there were no clear differences in lung pathology between the Mtb-HT and Mtb-LT infected mice ( Fig 3A and 3B , top panel ) , at four weeks post-infection Mtb-HT infected mice had well-defined , circumscribed lesions in otherwise normal parenchyma . In contrast , diffuse granulomatous inflammation was observed in Mtb-LT infected animals ( Fig 3A and 3B , middle panel ) . This is consistent with the enhanced cytokine and chemokine induction , and neutrophil accumulation in Mtb-LT infected mice . During the chronic stages of infection ( weeks 8–12 ) , well-formed granulomas in the lungs of Mtb-HT infected mice were seen to expand , whereas Mtb-LT infected mice showed widespread tissue destruction ( Fig 3A and 3B , bottom panel ) . At the latest time point , caseating granulomas in the HT-infected mice were well-defined , circumscribed lesions surrounded by a thin layer of fibroblasts and collagen , in otherwise normal parenchyma ( Fig 4A ) . Many of these lesions were in close proximity to intact airways ( Fig 4C ) , spilling bacterial and necrotic debris into the airway lumen . Surrounding the necrotic center were acid fast organisms ( Fig 4D ) and collagen-rich cell debris ( Fig 4B and 4E ) enriched with foamy macrophages within a collar of fibroblasts ( Fig 4B ) . Many of the granulomas in Mtb-HT infected mice appeared as small aggregates of cells ( Fig 5A ) , dominated by lymphocytes ( Fig 5B ) , minimal inflammation ( Fig 5C ) and containing few intracellular bacteria ( Fig 5D ) . In contrast to the discrete granulomas observed in mice infected with Mtb-HT strains , there was diffuse lung pathology in mice infected with the Mtb-LT strains ( Fig 6A ) . Bacteria-laden macrophages expanded to fill alveolar spaces , with no evidence of containment of the inflammatory process . In addition , multiple small lymphoid aggregates were present throughout the lung as well as foci of acute neutrophilic inflammation ( Fig 6B ) . Besides the widespread destruction of lung parenchyma , fluid and inflammatory cells were present in remaining airways ( Fig 6C ) . Of note , throughout the course of infection , we observed 20% ( 6 of 30 mice ) and 12% ( 3 of 25 mice ) mortality in Mtb-LT1 and Mtb-LT2 , respectively . This can be attributed to the replacement of alveolar surfaces by the rapidly progressing inflammatory process seen in these animals . Although there were far more bacilli present in the lungs of Mtb-LT infected mice , AFB staining demonstrated that these were primarily intracellular ( Fig 6D ) . In addition , within the granulomatous lesion of Mtb-LT infected animals we found foamy macrophages and lipid clefts similar to those found in atheromatous plaques in patient with hypercholesterolemia ( S5 Fig ) . These solid lipid crystals , dissolved by the solvents used in tissue processing to leave clefts , are a source of inflammation as well as mechanical injury [51] . To further confirm that the differences in the pattern of disease pathology is not confounded by examining a single lobe for histopathology , we performed another infection with Mtb-HT3 ( n = 4 ) and Mtb-LT3 ( n = 4 ) and analyzed multiple lung lobes from 12 week-infected animals . In line with earlier experiments , all of the Mtb-HT3 infected animals developed discrete granulomas and 2 of the 4 showed caseating granulomas ( S6A Fig ) in one lobe while 100% of Mtb-LT3 infected mice exhibited diffused inflammatory pathology that was present in all lung lobes ( S6B Fig ) . Together , these data confirm that Mtb-HT and Mtb-LT infected mice develop strikingly different pathological disease . Combined histological evaluations of 12 and 16 week-infected lungs revealed that only a proportion of Mtb-HT infected animals developed caseating granulomas ( Table 2 ) . The rest of the mice exhibited discrete granulomas with the potential to progress to caseous necrotic granulomas . Of significance , none of the Mtb-HT infected animals at either 12 or 16 week of infection exhibited diffused inflammation . In contrast , all of the Mtb-LT1 and Mtb-LT2 infected animals developed diffused inflammation with no evidence of caseating or discrete granulomas in any of the mice . Notably , despite having lung bacterial numbers similar to Mtb-HT infected mice , 8 of 9 mice of the Mtb-LT3 infected animals developed diffused inflammation and none of these infected mice had caseating granulomas ( Table 2 ) . If we consider the two pathological outcomes , caseating granulomas and diffused inflammation between Mtb-HT1-3 and Mtb-LT1-3 as a primary endpoint , a two-sided Fisher’s exact test yields a p value of p<0 . 0001 . This suggests that the 3 Mtb-HT and 3 Mtb-LT strains have significantly different pathological outcomes . In parallel , we also evaluated the lung pathological response in C57BL/6 and BALB/c animals that were infected with Mtb-HT1 and Mtb-LT1 strains . Quantification of granulomatous inflammation in both mouse genotypes established that at 12-weeks post infection , animals infected with Mtb-LT1 strain had significantly higher lung area involvement as compared with Mtb-HT1 infected animals ( S3B Fig ) . Between the genotypes , BALB/c mice infected with Mtb-LT1 had significantly more lung area involvement at this time point ( S3B Fig ) . Central to the intracellular growth of Mtb is its ability to induce foamy macrophage by triggering the accumulation of lipid droplets , which are composed of triglycerides and cholesteryl esters [52 , 53] . Lipid droplets thus provide a nutrient source to intracellular Mtb and promote successful replication of the pathogen in the host [54 , 55] . We argued that the difference in the growth of Mtb-LT and Mtb-HT in vivo in mice is due to their differential ability to induce lipid droplet formation . MH-S cells , a mouse lung alveolar macrophage cell line , were infected individually in vitro at an MOI of 10 with the 3 Mtb-HT and 3 Mtb-LT strains studied so far and with an additional 7 each of Mtb-HT and Mtb-LT strains . Based on flow cytometric analysis , cells infected with Mtb-LT strains had a strong signal for the LipidTOX dye ( a reagent that stains neutral lipid droplets ) and overall significantly high MFI as compared to cells infected with Mtb-HT strains ( Fig 7A ) . Representative images from confocal microscopy supported the flow cytometry observations ( Fig 7B ) . These data suggest that induction of lipid droplets may be differentially regulated by Mtb-HT and Mtb-LT strains . Mepenzolate bromide ( MPN ) was shown previously to reduce lipid droplet formation in Mtb-infected macrophages by targeting the anti-lipolytic G protein-coupled receptor GPR109A which resulted in enhanced TAG turnover [52] . Consistent with lipid droplets serving as a nutrient source for Mtb , growth of Mtb in vitro in macrophages was reduced in the presence of MPN [52] . Therefore , to determine if there was a link between lipid droplet formation and increased Mtb-LT growth , bone marrow macrophages were infected with the three Mtb-HT and 3 Mtb-LT strains , with or without MPN , and intracellular bacterial growth was determined at day 7 following infection . Firstly , we found that the intracellular growth of Mtb-LT strains was significantly higher than Mtb-HT strains . Furthermore , MPN treatment selectively decreased intracellular bacterial growth of only Mtb-LT strains ( Fig 7B ) . However , bacterial growth in liquid culture of all three Mtb-HT and Mtb-LT1 and Mtb-LT2 strains was significantly inhibited by MPN . Mtb-LT3 had a slow growth rate in vitro and addition of MPN did not further reduce growth . ( S7A Fig ) . Although , the target of MPN in Mtb remains unclear , nonetheless , these data indicate that in vitro growth characteristics of Mtb-HT and Mtb-LT strains are not predictive of its intracellular growth pattern in macrophages , the latter we propose being more relevant to in vivo infections and further that lipid droplet formation is a factor in the enhanced intracellular growth of the Mtb-LT strains . Signaling via GPR109A activates inflammatory [56] and anti-inflammatory pathways [57] . We , therefore , tested whether the level of TNF was altered in MPN-treated macrophages and found no significant difference in the production of the cytokine between macrophages with or without MPN treatment ( S7B Fig ) . Overall , these data indicate that Mtb-LT strains induce significantly higher lipid droplets to promote their intracellular growth .
In this study , Mtb clinical strains were carefully characterized on the basis of epidemiological data into high and low transmission groups and studied to gain insight into the pathogenic mechanisms leading to their transmission phenotype . The experimental results demonstrate that Mtb-HT and Mtb-LT strains exhibit differential bacterial growth and lung pathology in genotypically similar hosts . Our results also demonstrate early modulation of lipid biogenesis by Mtb-LT strains which could be the likely mechanism dictating the differential outcome of infection between Mtb-HT and Mtb-LT-infected animals . Data arising from this study also advance the C3HeB/FeJ mouse model as a tractable system to identify bacterial determinants that interact with the host immune response to cause the type of pathological disease that enables different extent of bacterial transmission . Previous studies have shown that C3HeB/FeJ mice infected with Mtb Erdman or H37Rv develop caseating granulomas and exhibit granulocytic tuberculous pneumonia referred to as Type I and Type II lesions , respectively [48] . Interestingly though , the same Mtb strain induced both lesion types . The novel observation in this study is that the granulomas evolved to caseation characterized by fibrous encapsulation with central liquefaction necrosis similar to Type 1 lesions only in Mtb-HT infected animals . Although , caseating granulomas did not develop in all of the Mtb-HT infected mice , nonetheless , none of them presented with diffused inflammatory pathology . In contrast , all of the Mtb-LT-infected mice rapidly developed diffused inflammatory pathology , but none presented with caseating granulomas . The bacterial burden in mice infected with Mtb-LT3 , although similar to Mtb-HT at later time points of infection , was nonetheless significantly higher than the three Mtb-HT strains at week 2 of infection . Of note , the Mtb-LT3 exhibited a pathological response that was very similar to the two other Mtb-LT strains . This suggests that the early events leading to differences in bacterial growth in Mtb-HT and Mtb-LT-infected animals may dictate the divergence in pathological response . The genetic differences in Mtb-HT and Mtb-LT strain and the ensuing specific interactions with the host may be driving the development of predominantly one or the other lesion types in the infected hosts . Consistent with this idea , a recent study in guinea pigs also found that strains that do not transmit disease caused more inflammatory pathology compared to high transmission strains [58] . The difference in bacterial replication and inflammation between the Mtb-HT and Mtb-LT strains in the C3HeB/FeJ mice was also recapitulated in two other mouse genotypes , indicating that bacterial factors likely contribute to the differential pathological outcome of Mtb-HT and Mtb-LT infections . A comparative genomics study of a panel of 19 clinically and epidemiologically characterized isolates of Mtb found that those with greater genome deletions caused significantly less pulmonary cavitation suggesting that pathogenicity is linked to bacterial factors [59] . That bacterial genotype contributes to the transmission phenotype of the host is also indicated by the finding that a large sequence polymorphism in a gene encoding molybdopterin oxyreductase was associated with clustering [60] and an Mtb strain associated with a large outbreak in the UK harbored an insertion in an intergeneic region Rv2815-2816c [61] . Whole genome sequencing and evolutionary convergence analysis of 100 strains either least or most likely to be transmitted revealed that five Mtb genes were shared by the transmissible strains . Importantly , the Mtb strains with mutations variably affected monocyte and lymphocyte cytokine production and neutrophil generation of reactive oxygen species [62] . Together , these findings indicate that differences in bacterial factors could regulate the extent of TB transmission occurring in a host . However , future studies should determine if host genetics synergize with bacterial factors to enhance transmission . Diversity Outbred ( DO ) [63 , 64] and Collaborative Cross ( CC ) mice are highly heterogeneous populations that provide a tractable experimental system to model the genetic diversity of the human outbred population . The outcome of Mtb infection in DO [65] and CC [66] mice was highly varied , ranging from resistance to high susceptibility , and was associated with a diverse range of pathological responses . Of note , the susceptible mice exhibited necrotizing tuberculous pneumonia , similar to the pathological response of C3HeB/FeJ mice infected with Mtb-LT . In the DO and CC mice , the same strain induced different pathological responses whereas in our study strain variation contributed to the different pathological disease outcome . An integrated approach that combines Mtb-HT and Mtb-LT infections in heterogenous DO and CC mice will provide a powerful means to investigate whether transmissibility is the combinatorial effect of host and strain genetic diversity . Mtb-HT and Mtb-LT strains induce distinct immunopathological responses in the susceptible host and thereby create an environmental context that we posit is differentially permissive to transmission between the susceptible host and an exposed individual . The finding that there are higher levels of Mtb-LT organisms in granulocytic pneumonitis in mice , if directly relevant to humans would not necessarily equate to their greater abundance in infectious aerosols . Rather , it is bacterial replication in area of caseation necrosis in granulomas that is associated with cavity formation and also perhaps differential survival in aerosols that lead to increased transmission . The C3HeB/FeJ mice are disease susceptible , however , a limitation of the model is that not all Mtb-HT infected animals developed caseating necrotic granulomas , and furthermore , none of the mice developed cavitary disease , a key pathological feature of human TB . A reason for why the Mtb-HT infected mice did not develop cavitary disease may be because mice lack a functional ortholog of human MMP1 that causes matrix destruction in TB [67] . However , pulmonary cavitation in C3HeB/FeJ mice was detected after aerosol infection with Mtb by serial computed tomography ( CT ) imaging [68] . Together , these findings suggest that further refinement of the model such as crossing MMP-1 transgenic mice with C3HeB/FeJ or the B6 . C3H-sst1 mice [69] may provide a superior mouse model to study TB pathogenesis and transmission . The formation of lipid-filled foamy macrophages is a hallmark of Mtb infection [53] . In mycobacteria infected cells , lipid droplets are found in close apposition to the phagosome [70] . Lipid droplet and phagosome interaction leads to engulfment of mycobacteria into the lipid droplet , providing the microbe unrestricted access to host lipids [70 , 71] . Accumulation of triacylglycerol-rich lipid bodies has been shown to aid mycobacterial survival and host neutral lipids can further be stored within the bacilli as intracytoplasmic lipid inclusions , thus acting as an energy source and enhancing bacterial growth in granulomatous lesions [54 , 55] . Thus lipid droplets play a prominent role in sustaining successful Mtb survival and replication in the host . What bacterial factors from Mtb-LT strains activate the GPR109A to induce the rapid accumulation of lipid droplets in macrophages awaits clarification , nonetheless , the findings from this study show that Mtb-LT exploits this host signaling pathway to its advantage . A recent study argues that lipid droplet formation is not a bacterially driven process during infection with the laboratory derived Mtb Erdman , but instead is dependent on IFNγ , and is not a source of host lipids for the pathogen [72] . Our findings that Mtb-HT induce significantly less lipid droplets and that their intracellular growth is not affected by MPN , suggests that , like Mtb Erdman , lipid droplets may not be a source of lipids for Mtb-HT . However , lipid droplet formation by Mtb-LT and their decreased growth in the presence of MPN indicates that lipid droplets specifically contribute to the enhanced intracellular growth of Mtb-LT strains . The data we present show that Mtb-LT strains engage the GPR109A pathway that is known to suppress TAG turnover to enhance lipid droplet accumulation . However , Mtb can also induce host cell lipid synthesis [73] and use triacylglycerol to accumulate lipid droplets [74] . Future investigations should explore these possibilities . Additionally , whether other factors , such as ability to survive aerosol stress also contributes to the overall transmissibility of an Mtb strain needs further inquiry . From the standpoint of bacterial dynamics , how Mtb-LT strains survive and propogate in the community remains an interesting question . In fact , the low fitness for transmissibility of Mtb-LT strains may portend a future decline in prevalence in the community unless the strains show increased propensity to progress to disease . It is possible as well that Mtb-LT transmission is enhanced in hosts with co-morbidities , such as HIV infection , diabetes or malnutrition and in them rapid transmission to disease maintains the strains in the community . The overall findings from this study are that Mtb-HT and Mtb-LT strains belonging to the same lineage differ in their interaction with the host immune system leading to different trajectories in bacterial growth and in the development of disease pathology . The divergence in disease pathology is likely the underlying cause of differences in infectiousness of the source case . However , since the current findings are based on a small sample size , larger confirmatory studies are required for broader inference that individual strains have biological properties that induce different pathological response that affects their transmission potential . Bearing in mind this limitation , the planned next stage of this work is to define an in vitro immune phenotype correlating with the in vivo growth and pathology to provide a high throughput screening method for validation of the current findings in a large panel of Mtb-HT and Mtb-LT strains . Furthermore , findings from ongoing studies of whole genome sequencing and metabo-lipidomic profiling of a large panel of HT and LT strains will uncover key genes and bacterial factors responsible for the dichotomy in pathogenesis . In the future , this can be translated into transmission interventions that target the bacteria .
The household contact study from which the Mtb strains were derived was approved by the Comite de Ética em Pesquisa do Hospital Universitário Cassiano Antonio de Morais , and the Institutional Review Boards of Rutgers University Biomedical Health Sciences-Newark ( RBHS ) ( formerly UMDNJ ) and Boston University School of Medicine . Written informed consent and assent in Portuguese were obtained from all study participants as per the consent procedure approved by IRBs from all participating institutions . All animal experiments described in this study conform to the Rutgers University Biomedical Health Sciences-Newark ( RBHS ) and Institutional Animal Care and Use Committee ( IACUC ) Guidelines as well as NIH and USDA policies on the care and use of animals in research and teaching . Efforts were taken to ensure minimal animal pain and suffering and when applicable , approved anesthesia methods were employed for the same . Clinical strains of Mtb were first grown on Lowenstein Jensen ( LJ ) growth media . Bacterial colonies picked from LJ slants were cultured in 7H9 media until mid-log phase . Cultures were then centrifuged at 400 RPM for 5 minutes , causing clumps to settle down in the bacterial pellet . The culture supernatant was collected , mixed with a final concentration of 20% glycerol , and was stored in 1 mL aliquots at -80°C . The stock titer was determined by plating 10-fold serial dilutions on Middlebrook 7H11 selective medium ( Difco by BD , Franklin Lakes , NJ ) and by counting the bacterial colonies 15–20 days later . The bacteria were passaged in vitro only twice to minimize any phenotypic/genotypic changes that might occur in the growing cultures . 6–8 weeks old female C57BL/6J , BALB/c and C3HeB/FeJ mice were purchased from the Jackson Laboratory ( Bar Harbor , ME , USA ) . Bacterial stocks were generated as described above . Mice were exposed for 40 minutes to nebulized bacteria at a density optimized to deliver a standard low dose of around 50–120 CFU ( unless otherwise indicated ) using Glass-Col Full Body Inhalation Exposure . For all infections , the actual infection dose was determined by plating total lung homogenates from a minimum of 3 mice on Middlebrook 7H11 plates at 24 hours after aerosol exposure . Lungs , spleens , mediastinal lymph nodes and livers were harvested and homogenized at indicated time points post-infection . Total CFU per organ was determined by plating 10-fold serial dilutions on Middlebrook 7H11 plates , which were counted after 28–35 days of incubation at 37°C . Post-mortem , lungs of Mtb-infected mice were perfused with sterile PBS and fixed in 4% paraformaldehyde for seven days , followed by paraffin embedding . For histopathological analysis , 5- to 7-μm sections were cut and stained using a standard H&E protocol . Leica SCN400 F whole-slide scanner ( Experimental Pathology Research Lab , NYU Langone Health ) was used for scanning histological sections and images were analyzed using Aperio ImageScope . Stereoscopic images were obtained using Act-1 software from Nikon . For quantitation of granulomatous inflammation in the lung section , Image-Pro Discovery Software was used to create a grid overlay onto each photomicrographs of H&E stained lung section and numbers of points hitting areas of granulomatous infiltration were counted . Masson’s trichrome staining [75] was carried out by NJMS Histology core . For visualization of acid-fast bacilli ( AFB ) , tissue sections were stained using the Ziehl-Neelsen method . For immunohistochemical detection of Ly6G+ cells , tissue samples were de-paraffinized with xylene and rehydrated with ethanol gradations and water . The samples were subjected to heat-induced antigen retrieval by microwave warming using 10 mM citrate buffer ( pH 6 . 0 ) . Endogenous peroxidase activity was blocked using 0 . 3% hydrogen peroxide and then subsequently blocked with 1× PowerBlock ( BioGenex ) . PBS containing 0 . 05% Tween-20 was used to wash tissues in between steps . For each sample , serial sections were incubated with the primary anti-mouse Ly6G antibody ( clone 1A8; Biolegend ) at a 1∶250 dilution or with isotype control ( Rat IgG2a , κ; BioLegend ) at the same concentration . Sections were subsequently incubated with biotinylated secondary antibody ( 1∶100 Vector Laboratories ) . Streptavidin horseradish peroxidase ( BioGenex ) was used to label the secondary antibody for immunodetection by DAB chromogen ( BioGenex ) . After counterstaining with Mayer’s hematoxylin ( BioGenex ) , the samples were dehydrated with ethanol gradations , dipped in xylene , and mounted using Cytoseal-60 ( ThermoFisher ) . Histopathological evaluations were performed with blinding to the identity of the strain . Single-cell lung suspensions were prepared and cell viability was determined using Trypan-blue exclusion method . For surface staining , approximately 1 million cells were washed and resuspended in FACS buffer ( PBS + 2% fetal calf serum ( FCS ) and 0 . 09% sodium azide ) containing a cocktail with the appropriate concentrations of specific fluorochrome-conjugated monoclonal antibodies . Isotype controls were included for each . Cells were first incubated with LIVE/DEAD Fixable Aqua Dead Cell stain . Directly conjugated fluorochrome labeled antibodies were used for the following cell-surface markers: anti-mouse CD4-V450 ( clone RM4-5; BD Horizon ) , anti-mouse CD8-AF488 ( clone 53–6 . 7; BD Pharmingen ) , anti-mouse B220-PECF594 ( clone RA3-6B2; BD Pharmingen ) , anti-mouse CD11b-PE ( clone M1/70; BD Pharmingen ) , anti-mouse Ly6G-PECy7 ( clone 1A8; BD Pharmingen ) , anti-mouse CD11c-AF700 ( clone HL3; BD Pharmingen ) and anti-mouse Ly6C-PerCPCy5 . 5 ( clone HK1 . 4; eBiosciences ) . Following surface staining , samples were fixed in 4% paraformaldehyde for 30 minutes and then acquired on a LSRII flow cytometer ( BD Biosciences ) . Analysis was performed using FlowJo software ( Tree Star , Inc . ) . Gating was based on fluorescence minus one ( FMO ) controls . For detection of lipid bodies , infected cells were fixed with Cytofix/Cytoperm solution ( BD ) for 20 minutes . Then , cells were washed twice with Perm/Wash buffer ( BD ) and cells were then resuspended in PBS solution of HCS LipidTOX Deep Red Neutral Lipid stain ( ThermoFisher Scientific ) . Following this incubation step , cells were washed twice with PBS and resuspended in PBS for flow cytometric analysis . Adherent MH-S cells were grown on coverslips ( Fisherbrand ) placed in 6-well plates ( Corning ) . Following Mtb infection , cells were fixed in 4% formaldehyde , washed and then stained with PBS solution of HCS LipidTOX Deep Red Neutral Lipid stain ( ThermoFisher Scientific ) , followed by 300 nM DAPI nuclear stain solution ( ThermoFisher Scientific ) . Coverslips were then washed three times with PBS and then mounted on Super frost/Plus microscope slides using Molecular Probes Slowfade Light antifade medium . Nikon A1RS confocal microscope was used to acquire images and quantification of signal intensity was performed using ImageJ software and Nikon imaging software , Nikon Elements 4 . 5 . BMDMs were prepared as described previously [76] . On day 7 , BMDMs were plated in 96 well plate ( Corning ) at a cell density of 0 . 08 x 106 cells/well in 200μL of D10 media [antibiotic free DMEM media ( Mediatech , Inc . ) containing 10% defined FBS ( HyClone Laboratories , Logan , UT ) ] and supplemented with 2% conditioned medium from L-cells . Cells were infected in replicates of 5 with 3 MOI of three Mtb-HT and three Mtb-LT strains for 4 hours . Wells were then washed 4 times with PBS + 1% BCS and cells were untreated or treated with 100nM of MPN . Infected cells were maintained in D-10 media supplemented with 2% conditioned medium from L-cells . At day 7 , post-infection cells were washed with serum-containing PBS and then lysed with sterile water . Total CFU was determined by plating 10-fold serial dilutions on Middlebrook 7H11 plates , which were counted after 21 days of incubation at 37 °C . 48-hour culture supernatants were harvested for measuring TNF levels . Lung lysates from Mtb infected mice were treated with 2X protease inhibitor ( ThermoFisher Scientific ) at the time of collection and supernatants from infected BMDMs were sterilized using 0 . 22μm . Ultrafree-MC centrifugal filter ( EMD Millipore ) . ELISA Ready-Set-Go kit was used or IL-17 ( eBioscience ) . For all ELISA , colorimetric analyses were used to calculate protein concentration levels ( Molecular Devices , Softmax Pro ) . For TNF , IL-1β , IL-6 and KC , a multi-analyte detection system that incorporates electro-chemiluminescence based readout was used ( MesoScale Discovery , Rockville , MD , USA ) . Pre-coated 10-spot MULTI-SPOT plates with capture antibodies were purchased ( catalog # K15048D ) . The assays are based on the principle of electrochemiluminescence ( ECL ) sandwich ELISA . The calculations to establish calibration curves and determine analyte concentrations were carried out using the MSD DISCOVERY WORKBENCH analysis software .
All statistical analyses were performed using Graph Pad Prism software . For analysis of two groups , the unpaired t-test was used . For greater than two groups , One- or Two- way ANOVA with Bonferroni’s correction was used . In all cases , p value <0 . 05 was considered to be statistically significant . | Mycobacterium tuberculosis ( Mtb ) , the bacteria that causes tuberculosis ( TB ) , is spread through the air from infected patients to their close contacts . In a household contact ( HHC ) study of patients with TB , we found that in some households a larger proportion of contacts were infected with Mtb compared to other households . We categorized the households into High ( HT ) and Low ( LT ) transmission groups . The Mtb strains obtained from the TB patients of the HT and LT households were designated Mtb-HT and Mtb-LT , respectively . In this study , we investigated in a mouse model of TB , the mechanistic basis for the variability in transmission of Mtb from infected patients to their close contacts . We found that C3HeB/FeJ mice infected with Mtb-LT strains developed diffused inflammatory lesions characteristic of granulocytic tuberculous pneumonia . In stark contrast , a significant number of mice infected with Mtb-HT strains developed caseating granulomas , a lesion type with high potential to cavitate . In conclusion , we report that the segregation of Mtb strains into high and low transmission phenotype is mechanistically linked to their ability to induce distinct pulmonary pathology . | [
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"symptoms... | 2019 | Transmission phenotype of Mycobacterium tuberculosis strains is mechanistically linked to induction of distinct pulmonary pathology |
As one of the leading causes of visual impairment and blindness , myopia poses a significant public health burden in Asia . The primary determinant of myopia is an elongated ocular axial length ( AL ) . Here we report a meta-analysis of three genome-wide association studies on AL conducted in 1 , 860 Chinese adults , 929 Chinese children , and 2 , 155 Malay adults . We identified a genetic locus on chromosome 1q41 harboring the zinc-finger 11B pseudogene ZC3H11B showing genome-wide significant association with AL variation ( rs4373767 , β = −0 . 16 mm per minor allele , Pmeta = 2 . 69×10−10 ) . The minor C allele of rs4373767 was also observed to significantly associate with decreased susceptibility to high myopia ( per-allele odds ratio ( OR ) = 0 . 75 , 95% CI: 0 . 68–0 . 84 , Pmeta = 4 . 38×10−7 ) in 1 , 118 highly myopic cases and 5 , 433 controls . ZC3H11B and two neighboring genes SLC30A10 and LYPLAL1 were expressed in the human neural retina , retinal pigment epithelium , and sclera . In an experimental myopia mouse model , we observed significant alterations to gene and protein expression in the retina and sclera of the unilateral induced myopic eyes for the murine genes ZC3H11A , SLC30A10 , and LYPLAL1 . This supports the likely role of genetic variants at chromosome 1q41 in influencing AL variation and high myopia .
Myopia increases the risk of visual morbidity and poses a considerable public health and economic burden globally , especially in Asia , where the prevalence is significantly higher than other parts of the world [1] . Human myopia primarily results from an abnormal increase in ocular axial length ( AL ) , the distance between the anterior and posterior poles of the eye globe , whereas the role of corneal curvature and lens thickness is minimal [2] . A 1 millimeter ( mm ) increase in AL is equivalent to a myopic shift of −2 . 00 to −3 . 00 diopters ( D ) with no corresponding changes in the optical power of the cornea and lens . High myopia , often defined as ocular spherical equivalent ( SE ) refraction below −6 . 00 D , is associated with an abnormally long AL , and this affects between 1% to 10% of the general population [3] . The degenerative changes in the retina and the choroid due to the excessive elongation of the globe are not prevented by optical correction and this subsequently increases the risk of visual morbidity through myopic maculopathy , choroidal neovascularization , retinal detachment and macular holes [4] . The active remodeling of the sclera , mediated by the signaling cascade initiated in the retina under visual input , has also been found to be critical in determining axial growth , and thus the refractive state of the eye [5] . Environmental factors such as the extent of near work , level of educational attainment and amount of outdoor activities have been documented to affect myopia development [6] . Evidence from family and twin studies has also supported a substantial genetic component in spherical refractive error and AL [7]–[9] . The heritability of the quantitative trait AL has been estimated to be as high as 94% comparable to that for SE ( for a review , see [10] ) . Although linkage scans on pedigrees ( myopia loci MYP1 to MYP18; see http://www . omim . org ) and genome-wide association studies ( GWAS ) [11]–[16] have implicated several regions in the human genome as being significant for refractive error and myopia , no myopia genes have been consistently identified within or across different population groups . This scenario reflects the complexity in the disease architecture of myopia pathogenesis . Genetic factors influencing AL and refraction appear to be at least partly shared , given previous literature from twin studies illustrating that at least half of the covariance between AL and refraction are due to common genetic factors [18] . The measurement of AL is more precise and less prone to errors compared to cycloplegic or non-cycloplegic assessments of refraction . As AL is an endophenotype for spherical refractive error , identifying genes that are responsible for AL variation provides insight into myopia predisposition and development . Presently there are only two genome-wide linkage studies performed in European descent populations that suggest the presence of AL quantitative trait loci ( QTLs ) on chromosomes 2p24 [19] and 5q ( at 98 centimorgans ) along with two classical myopia loci ( MYP3 at 12q21 and MYP9 at 4q12 ) [20] , and there are no reports of any genes that are indisputably confirmed to be associated with AL . We thus performed a meta-analysis of three genome-wide surveys of AL in a total of 4 , 944 individuals in Asian populations comprising ( i ) Chinese adults from the Singapore Chinese Eye Study ( SCES ) ; ( ii ) Chinese children from the Singapore cohort Study of the Risk factors for Myopia ( SCORM ) ; and ( iii ) Malay adults from the Singapore Malay Eye Study ( SiMES ) . SNPs that have been identified from this meta-analysis to be significantly associated with AL were further assessed for association with high myopia in an additional two independent case-control studies from Japan . We also examined the expression patterns of the candidate genes located in the vicinity of the identified SNPs in human ocular tissues and in the eyes of myopic mice .
A genome-wide meta-analysis of three GWAS on AL was performed in the post quality control samples from SCES ( n = 1 , 860 ) , SCORM ( n = 929 ) and SiMES ( n = 2 , 155 ) . Principal component analysis ( PCA ) of these samples with reference to the HapMap Phase 2 individuals showed that the two Chinese cohorts ( SCES and SCORM ) are indistinguishable with respect to samples of Han Chinese descent , and the differentiation from samples of Japanese descent is evident only on the fourth principal component ( Figure S1 ) . The SiMES Malays are genetically similar to the Chinese-descent samples relative to individuals with European or African ancestries . The distributions of AL measurements in the three cohorts were approximately Gaussian and the baseline characteristics are summarized in Table 1 . The mean AL were 23 . 98 mm ( SD = 1 . 39 mm ) , 24 . 10 mm ( SD = 1 . 18 mm ) and 23 . 57 mm ( SD = 1 . 04 mm ) for SCES , SCORM and SiMES respectively . Moderate to high correlations between AL and SE were observed ( SCES/SCORM/SiMES; Pearson correlation coefficient r = −0 . 75 , −0 . 76 and −0 . 62 respectively ) . The meta-analysis was performed on 456 , 634 SNPs present in all three studies , and the quantile-quantile ( QQ ) plots of the P-values showed only modest inflation of the test statistics in SCES and in the meta-analysis ( genomic control inflation factor: λmeta = 1 . 03; λSCES = 1 . 05; λSCORM = 1 . 00; λSiMES = 1 . 00 , Figure S2 ) . A cluster of four SNPs on chromosome 1q41 ( rs4373767 , rs10779363 , rs7544369 and rs4428898 ) attained genome-wide significance on meta-analysis for AL , adjusting for age , gender , height and education level ( Figure 1 ) . Analyses conducted without adjustment for height or education level yielded the same pattern of results . The most significant SNP rs4373767 ( Pmeta = 2 . 69×10−10 ) explained 0 . 98% of AL variance in SCES , 0 . 86% in SCORM and 0 . 73% in SiMES , and each copy of the minor allele ( cytosine ) decreased AL by 0 . 16 mm on average ( Table 2 ) . These top associated SNPs at chromosome 1q41 remained significant after adjustment for genomic control ( Pmeta≤1 . 85×10−8 ) . Table 2 also lists three genetic loci at chromosome 2p13 . 1 ( SEMA4F ) , 2p21 ( SPTBN1 ) and 5q11 . 1 ( PARP8 ) exhibiting suggestive evidence of association with AL that were seen in at least one SNP with P-values<1×10−5 . To assess whether these four SNPs at chromosome 1q41 have any role in high myopia predisposition , we performed association testing of these SNPs with high myopia in two independent case-control studies from Japan consisting of 987 high myopes and 1 , 744 controls . High myopes were defined as individuals with SE≤−9 . 00 D or AL≥28 mm ( see Materials and Methods ) . All four SNPs exhibited consistent evidence of association ( P<0 . 05 ) in both Japanese studies , suggesting a potential role of these SNPs for high myopia ( Table 3 ) . We further dichotomized the quantitative refraction from our three population-based studies ( SCORM , SCES , and SIMES ) to define samples as high myopes and controls according to similar criteria from the Japanese datasets . High myopes in SCES and SiMES were younger and more highly educated than controls ( Table S1 ) . While the case-control associations of these 4 SNPs with high myopia did not achieve statistical significance in SCES and SiMES , this is likely a consequence of the small sample sizes since the direction and magnitude of the odds ratios were highly similar across all cohorts . The meta-analysis of 1 , 118 high myopia cases and 5 , 433 controls from all the five cohorts yielded strong evidence of association with high myopia at these SNPs ( Pmeta between 1 . 45×10−6 to 7 . 86×10−8 , Table 3 ) , with no evidence of inter-study heterogeneity ( P≥0 . 75 for heterogeneity ) . The minor allele cytosine at rs4373767 lowered the odds of high myopia by 25% with respect to the thymidine allele ( ORmeta = 0 . 75 , 95% CI: 0 . 68–0 . 84 , Pmeta = 4 . 38×10−7 ) . The stringent definition of high myopia ( SE≤−9 . 00D ) used here only considered between 1 . 0% to 2 . 4% of our samples as cases , and relaxing this criterion to the commonly adopted threshold of SE≤−6 . 00D identified more myopia cases and increased the statistical support of all four SNPs ( Pmeta between 1 . 47×10−7 to 9 . 13×10−9 , Table S2 ) . This associated interval spans approximately 70 kb in the extended linkage disequilibrium ( LD ) block within an intergenic region on chromosome 1q41 ( pairwise r2>0 . 5 with the most significant SNP rs4373767 , Figure 2A ) . Zinc finger family CCCH-type 11B pseudogene ZC3H11B ( RefSeq NG_007367 . 2 ) is embedded between the associated top SNPs rs4373767 and rs10779363 ( Figure 2B ) . The most significant SNP rs4373767 is located 223 kb downstream from SLC30A10 ( RefSeq NM_018713 . 2 ) , which is a member of solute carrier family 30 , and 354 kb downstream of LYPLAL1 ( RefSeq NM_138794 . 3 ) , encoding a lysophospholipase-like protein . The mRNA expression levels of ZC3H11B , SLC30A10 and LYPLAL1 were surveyed in 24-week human fetal and adult tissues using reverse-transcriptase polymerase chain reaction ( RT-PCR ) . Whilst ZC3H11B and LYPLAL1 were found to be expressed across all the tissues including brain , placenta , neural retina , retina pigment epithelium ( RPE ) and sclera , the expression of ZC3H11B was more abundant compared to LYPLAL1 ( Figure 3 ) . SLC30A10 was expressed in all tissues but the adult sclera , analogous to observations made in other zinc transporters [21] . Gene expressions for ZC3H11A , SLC30A10 and LYPLAL1 from the tissues of myopic ( with SE<−5 . 0 D ) and fellow non-occluded eyes of the experimental mice were compared with age-matched control tissues ( Figure 4 ) . The mRNA levels of ZC3H11A , a gene that is conserved with respect to ZC3H11B in human , were significantly down-regulated in myopic eyes compared to naive controls ( retina/RPE/sclera , Fold change = −2 . 88 , −3 . 24 and −2 . 07; P = 2 . 60×10−5 , 2 . 62×10−6 and 1 . 08×10−4 , respectively ) . At the neighboring gene SLC30A10 , there was a similarly significant reduction in the expression of mRNA in the retina tissue of myopic eyes in contrast to independent controls ( retina/RPE , Fold change = −2 . 02 , −2 . 69; P = 2 . 00×10−4 , 2 . 00×10−4 , respectively ) , with elevated expression in the sclera ( Fold change = 4 . 58; P = 4 . 02×10−4 ) . Another neighboring gene LYPLAL1 exhibited up-regulation of transcription levels in retina tissue but was down-regulated in the sclera ( retina/RPE/sclera , Fold change = 2 . 71 , 3 . 45 and −2 . 36; P = 1 . 50×10−4 , 1 . 50×10−4 and 1 . 54×10−4 , respectively ) . Immunohistochemical results confirmed the localization of ZC3H11A , SLC30A10 and LYPLAL1 proteins in the neural retina , RPE and sclera ( Figure 5 ) . For ZC3H11A , positive immunostaining intensity was reduced significantly in the myopic tissues of experimental mice compared to the non-myopic independent controls ( Figure 5A ) . This is consistent with the differential expression patterns at the transcription level . For SLC30A10 and LYPLAL1 , there were also similarly noticeable changes in the expression of proteins to that of their mRNA levels ( Figure 5B and 5C ) .
We report that the chromosome 1q41 locus ( most significant SNP rs4373767 ) is associated with AL in a meta-analysis of three GWAS performed in the study cohorts consisting of Chinese adults , Chinese children , and Malay adults . The discovery of chromosome 1q41 as a locus for high myopia in our data is further supported by validation in two independent Japanese cohorts , and the observed genetic effects are highly consistent across all five studies . The pseudogene ZC3H11B and two nearby genes SLC30A10 and LYPLAL1 were found to be expressed in the human retina and sclera . The potential roles in regulating myopia at three candidate genes were further implicated by the concordant changes in the pattern of transcription and protein expression in the mouse model . The ZC3H11B pseudogene belongs to the CCCH-type zinc finger family , whereas such type of zinc finger protein has been shown as a RNA-binding motif to facilitate the mRNA processing at transcription [22] . Emerging evidence suggests that pseudogenes , resembling known genes but not producing proteins , play a significant role in pathological conditions by competing for binding sites to regulate the transcription of its protein-coding counterpart [23]–[25] . Although the function of the ZC3H11B in humans is presently unknown , the implicated role of the murine gene ZC3H11A ( conserved gene of ZC3H11B in mouse ) in myopia development is in keeping with previous findings that several zinc finger proteins are involved in myopia [26] , [27] . Given their role as transcription factors [28] , zinc finger protein ZENK has been proposed to function as a messenger in modulating the visual signaling cascade in the chicken retina , where the expression of the ZENK was suppressed by the condition of minus defocus ( induced myopic eye growth ) and enhanced by positive defocus ( induced hyperopic eye growth ) [29]–[31] . Similarly , it has been reported that ZENK knockout mice had elongated AL and a myopic shift in refraction [27] . Moreover , early growth response gene type1 EGR-1 ( the human homologue of ZENK ) has been shown to activate transforming growth factor beta 1 gene TGFB1 by binding its promoter [32] , [33] , a gene that is implicated to be associated with myopia [34] , [35] . Another zinc protein finger protein 644 isoform ZNF644 has recently been identified to be responsible for high myopia using whole genome exome sequencing in a Han Chinese family [26] , whereas its influence on “myopia genes” remains to be elucidated . In light of this , the observation that ZC3H11B is abundantly expressed in retina and sclera , together with the significant down-regulation of the coding counterpart ZC3H11A in myopic mice eyes , suggests it may promote or inhibit the transcription of ocular growth genes vital in myopia development . One of the two neighboring genes SLC30A10 is an efflux transporter that reduces cytoplasmic zinc concentrations [36] . The SLC30 zinc transporters are expressed abundantly in human RPE cells , and the retina has been observed to possess the highest concentration of zinc in the human body [21] . Zinc deficiency in the intracellular retina has thus been implicated in the pathogenesis of age-related macular degeneration ( AMD ) [37] , [38] , and in RPE-photoreceptor complex deficits , which can affect visual signal transduction from retina to sclera and lead to visual impairment [39] . LYPLAL1 functions as a triglyceride lipase and this gene has been shown to be up-regulated in subcutaneous adipose tissue in obese individuals [40]–[42] . While the relationship between LYPLAL1 and myopia is unknown , elevated saturated-fat intake has been proposed to influence myopia development through the retinoid receptor pathway [43]–[45] . Interestingly , the SNPs pinpointing chromosome 1q41 in our study are 1 Mb away from the transforming growth factor beta 2 gene ( TGFβ2 ) which has been implicated in the down-regulation of mRNA levels in myopia progression of an induced tree shrew myopia model [46] . None of these nearby genes , however , are within the LD block containing our identified SNPs . Chromosome 1q41 is a previously reported locus for refraction from a linkage analysis of 486 pedigrees in the Beaver Dam Eye Study , US [47] . Using microsatellite markers , Klein et al identified novel regions of linkage to SE on chromosome 1q41 , whereas the peak spanned a broad region near Marker D1S2141 ( multipoint P<1 . 9×10−4 ) . This result however was not replicated in a subsequent genome-wide linkage scan for SE with denser SNP markers , partially due to varying information of linkage conveyed by SNPs versus microsatellites [48] . The identified variants at chromosome 1q41 in our study were noted to exhibit weaker , albeit still significant , association with SE in SCES and SCORM ( rs4373767 , SCES/SCORM: P = 3 . 54×10−3 , 3 . 49×10−2 , respectively; Table S3 ) , but not in SiMES ( 3 . 51×10−1 ) , which is consistent with the lower correlation of AL and SE seen in the SiMES data , partially from increasing lens opalescence in the Malay population [49] , [50] . Our data have shown that genetic variants on chromosome 1q41 influence the physiological attribute of AL and are also associated with high myopia . Elongation of AL is the major underlying structural determinant of high myopia , mostly accompanied with prolate eyeballs and thinning of the sclera , macula and retina [4] . Thus , high myopia is also defined as AL of >26 mm in some studies [13] , [51] . It is possible that genes involved in a quantitative trait ( refraction or underlying AL ) also play a role in the extreme forms of the trait ( high myopia ) [52] . Two recent GWAS performed in general Caucasians population have identified genetic variants for quantitative refraction at chromosome 15q14 [11] and 15q25 [12] , of which the locus on 15q14 was subsequently confirmed to be associated with high myopia in the Japanese [53] . Our GWAS results herein highlight AL QTLs relevant for high myopia predisposition , which advances our understanding of the genetic etiology of myopia at different levels of severity . The meta-analysis of three GWAS in our discovery suggests that the quantitative trait locus at chromosome 1q41 accounts for variation in AL in both school children and adults , regardless of age differences . Notably , the early-onset of myopia in childhood may continuously progress toward high myopia in later life , while adult-onset of myopia is usually in the low or moderate form [54] , [55] . The significant association on chromosome 1q41 for high myopia in adults and children thus also implicates this locus identified for AL is likely to be associated with early-onset myopia . The prevalence of myopia among Asian population is considerably higher than in Caucasians [1] . Although distinct genetic mechanisms governing myopia may exist for populations with different genetic backgrounds , we believe there are polymorphisms involved in refractive variation that are shared across populations . However , the allele frequencies of these identified SNPs vary across populations . For instance , the minor C allele of rs4373767 was a major allele in the HapMap Africans and Europeans with frequency of 0 . 92 and 0 . 62 respectively . Four distinct linkage disequilibrium ( LD ) blocks existed in 50 kb region encapsulating our top SNPs in the HapMap Africans , whereas high LD was observed for the Chinese , Malays and Japanese populations . Such heterogeneity may confer different statistical power and confound the transferability of the same variants across populations [56] , [57] . In addition , we note that the variability in refraction attributed to AL may vary in different ethnic groups . For example , AL has been reported to account for a larger proportion of the variation in refraction in East-Asian children compared to their Caucasian counterparts [58] , therefore the increased power of refraction may reflect more variation in factors other than pure elongation of AL in certain ethnic groups . In conclusion , our findings suggest that common variants at chromosome 1q41 are associated with AL and high myopia in a pediatric and an adult cohort , the latter incorporating Chinese , Malay and Japanese populations . Further evaluation of causal variants and underlying pathway mechanisms may contribute to early identification of children at highest risk of developing myopia , and eventually lead to appropriate interventions to retard the progression of myopia .
All the studies used a similar protocol for ocular phenotype measurements . For subjects in SCES and SiMES , AL for both eyes were measured using optical laser interferometry ( IOLMaster V3 . 01 , Carl Zeiss; Meditec AG Jena , Germany ) [59] , [61] . Children in the SCORM study underwent AL measurements using the A-scan ultrasound biometry machine ( Echoscan US-800; Nidek Co , Tokyo , Japan ) [17] . For subjects in the Japan dataset 1 , applanation A-scan ultrasongraphy ( UD-6000 , Tomey , Nagoya , Japan ) or partial coherence interferometry ( IOLMaster , Carl Zeiss Meditec , Dublin , CA ) were used to measure AL . AL was assessed using a portable A-scan Biometer/pachymeter ( AL-2000 , Tomey , Negoya , Japan ) for the participants in the Japan dataset 2 . Non-cycloplegic refraction in SCES and SiMES as well as cycloplegic refraction in SCORM ( three drops of 1% cyclopentolate at 5 minutes apart ) were measured by autorefractor ( Canon RK-5 , Tokyo , Japan ) [66] . For subjects in the Japan dataset 2 , refraction was measured using auto-refraction ARK-730A ( NIDEK ) , ARK-700A ( NIDEK ) and KR-8100P ( TOPCON ) . SE was calculated as the sphere power plus half of the cylinder power for each eye . To perform the genetic association of high myopia in SCES and SiMES , we used the definition adopted by the Japan case-control studies and defined high myopia cases as subjects having SE≤−9 . 0 D in at least one eye , and non high-myopia controls as samples with SE≥−3 . 0 D in both eyes . For children from SCORM aged 10 to 12 years , cases were defined as SE≤−6 . 0 D for at least one eye , while controls were defined as SE≥−1 . 0 D for both eyes; this is approximately equivalent to the projected SE of −9 . 0 and −3 . 0 respectively at university age based on the estimated annual progression rate in SE of −0 . 6 D for Chinese myopic children and −0 . 3 D in the controls [67] . Given the small sample sizes of high myopia cases identified in our population-based cohorts , in the supplementary analysis , we further applied the commonly adopted criteria of SE≤−6 . 0 D in either eye as cases . Controls were defined as SE≥−1 . 0 D in both eyes . For SCORM children , we retained the same criteria in both analyses . The detailed definitions of cases and controls are described in Table S4 . Age , gender , height and level of education were obtained from all Singapore participants who underwent ophthalmologic examination . Education was measured on an ordinal scale from no formal education to the highest educational level . For participants in SCORM , the education of the child was defined by the level of educational attainment of the father , as a marker of socioeconomic status . All studies followed the principle of the Declaration of Helsinki . Study procedures and protocols were approved by the Institutional Review Board of each local institution involved in the study . In all cohorts , participants provided written , informed consent at the recruitment into the studies . Informed written consent was obtained from adult participants , and from the parents of the SCORM children . Animal study approval was obtained from the SingHealth IACUC ( AAALAC accredited ) . All procedures performed in this study complied with the Association of Research in Vision and Ophthalmology ( ARVO ) Statement for the Use of Animals in Ophthalmology and Vision Research . For SCES , a total of 1 , 952 venous blood-derived samples were genotyped using Illumina Human 610 Quad Beadchips ( Illumina Inc . , San Diego , US ) according to the manufacturer's protocols . Samples which failed genotyping or with low call rate ( <95% , n = 11 ) , with excessive heterozygosity ( defined as sample heterozygosity exceeding 3 standard deviations from the mean sample heterogzygosity; n = 3 ) , with gender discrepancies ( n = 2 ) were excluded , as were cryptically related samples identified by the identity-by-state ( IBS ) ( n = 41 ) and population structure in the principal components analyses ( PCA ) ( n = 6 ) . The criteria to define cryptically related samples and outliers with population structure in the discovery cohorts are described in the following paragraph . After the removal of the samples , SNP QC was then applied on a total of 579 , 999 autosomal SNPs for the 1 , 889 post-QC samples . SNPs were excluded based on ( i ) high rates of missingness ( >5% ) ( n = 26 , 437 ) ; ( ii ) monomorphism or minor allele frequency ( MAF ) <1% ( n = 59 , 633 ) ; or ( iii ) genotype frequencies deviating from Hardy-Weinberg Equilibrium ( HWE ) defined as HWE P-value<10−6 ( n = 1 , 821 ) . This yielded 492 , 108 autosomal SNPs . Those individuals with missing data on phenotypes were further removed ( n = 29 ) . Finally , 492 , 108 SNPs in 1 , 860 samples were available for analyses . For SCORM , 1 , 116 DNA samples ( 1 , 037 from buccal swab and 79 from saliva ) were genotyped on the Illumina HumanHap 550 Beadchips and 550 Duo Beadarrays . A total of 108 samples were excluded , comprising ( i ) 70 samples with call rates below 98%; ( ii ) 6 with poor genotyping quality; ( iii ) 11 samples identified from sib-ships; ( iv ) 18 with inconsistent gender information; and ( v ) 3 due to population structure . This left a total of 1 , 008 samples for further SNP QC . Based on 514 , 849 autosomal SNPs , we excluded 32 , 669 markers if they had missing genotype calls >5% , MAF<1% , or significantly deviated from HWE ( P<10−6 ) [14] . A final set of 929 samples with 482 , 180 post-QC SNPs and completed AL measurement were included in analyses . For SiMES , 3 , 072 DNA samples were genotyped using the Illumina Human 610 Quad Beadchips . The detailed QC procedures were provided elsewhere [68] . In brief , we omitted a total of 530 individuals due to: ( i ) subpopulation structure ( n = 170 ) ; ( ii ) cryptic relatedness ( n = 279 ) ; ( iii ) excessive heterozygosity or high missingness rate >5% ( n = 37 ) ; and ( iv ) gender discrepancy ( n = 44 ) . After the removal of the samples , SNP QC was then applied on a total of 579 , 999 autosomal SNPs for the 2 , 542 post-QC samples . SNPs were excluded based on: ( i ) high rates of missingness ( >5% ) ( n = 26 , 343 ) ; ( ii ) monomorphism or MAF<1% ( n = 34 , 891 ) ; or ( iii ) genotype frequencies deviating from HWE ( P<10−6 ) ( n = 3 , 645 ) . This yielded 515 , 120 SNPs after the same SNP QC criteria . Individuals without valid measurements for AL were further removed ( n = 387 ) . After the above filtering criteria , 515 , 120 SNPs in 2 , 155 samples were available for association analyses . In our discovery cohorts , IBS was estimated with the genome-wide SNP data using PLINK software to assess the degree of recent shared ancestry for a pair of individuals [69] . For a pair of putatively-related samples defined as an identity by descent ( IBD ) value greater than 0 . 185 [70] , we removed one individual from each pair of monzygotic twins/duplicates , parent-offspring or full-siblings etc . Population structure was ascertained using PCA with the EIGENSTRAT program and genetic outliers were defined as individuals whose ancestry was at least 6 standard deviations from the mean on one of the top ten inferred axes of variation [71] . For SiMES Malays , we also excluded the samples falling in the main clusters of PCA plots of the Chinese and Indians ethnic groups , as described in the previous study [68] . In SiMES , we noticed some degree of admixture in genetic ancestry of Malays and thus adjusted for ancestry along the top five axes of variation , as the spread of principal component scores was greater for the top five eigenvectors in the bivariate plots of PCA ( Figure S3 ) , The top ten principal components explained a small percentage of the global genetic variability of 1 . 3% while top five explained 1 . 0% , suggesting , all together , they had minimal effects on our association analyses . High myopia cases in the Japan dataset 1 were genotyped using Illumina Human-Hap550 and 660 chips [13] , while controls in the Japan dataset 1 were genotyped on Illumina Human-Hap610 chips . Subjects in the Japan dataset 2 were genotyped on the Affymetrix GeneChip Human Mapping 500 K Array Set ( Affymetrix Inc . , Santa Clara , US ) . For SNPs not available on the Affymetric chips ( rs43737678 , rs10779363 and rs7544369 ) , genotyping was performed with TaqMan 5′ exonuclease assays using primers supplied by Applied Biosystems ( Foster City , US ) . The probe fluorescence signal was detected using the TaqMan Assay for Real-Time PCR ( 7500 Fast Real-Time PCR System , Applied Biosystems ) . Experimental myopia was induced in B6 wild-type ( WT ) mice ( n = 36 ) by applying a −15 . 00 D spectacle lens on the right eye ( experimental eye ) for 6 weeks since post-natal day 10 . The left eyes were uncovered and served as contra-lateral fellow eyes . Age matched naive mice eyes were used as independent control eyes ( n = 36 ) . Each eye was refracted weekly using the automated infrared photorefractor as described previously [72] . AL was measured by AC- Master , Optic low coherence interferometry ( Carl-Zeiss ) , in-vivo at 2 , 4 and 6 weeks after the induction of myopia [73] . The minus-lens-induced eyes after six weeks were significantly associated with increased AL and myopic shift in refraction of <−5 . 00 D as compared to independent control eyes ( n = 36 , P = 3 . 00×10−6 for AL , and 2 . 05×10−4 for refraction ) . Eye tissues were collected at 6 weeks post myopia induction for further analyses . Total RNA was isolated from pooled cryogenically ground mouse neural retina ( retina ) , retinal pigment epithelium ( RPE ) and sclera for three batches using TRIzol Reagent ( Invitrogen , Carlsbad , CA ) with each batch ( n = 6 ) comprising the myopic eye , fellow eye and control eye . RNA concentration and quality were assessed by the absorbance at 260 nm and the ratio of absorbance ratio at 260 and 280 nm respectively , using Nanodrop ND-1000 Spectrophotometer ( Nanodrop Technologies , Wilmington , DE ) . RNA was purified using the RNeasy Mini kit ( Qiagen , GmbH ) . 500 ng of purifed RNA was reverse-transcribed into cDNA using random primers and reagents from iScriptTM select cDNA synthesis kit ( Bio-rad Laboratories , Hercules , CA ) . The pseudogene ZC3H11B ( zinc finger CCCH type containing 11B ) is not characterized in the mouse genome , therefore we examined a similar gene ZC3H11A ( zinc finger CCCH type containing 11A ) in mice . ZC3H11A in mice and ZC3H11B in humans are highly conserved with 79% nucleotide similarity by BLAST alignment analysis ( http://blast . ncbi . nlm . nih . gov ) . We used quantitative Real-Time PCR ( qRT-PCR ) to validate the gene expression . qRT-PCR primers ( Table S5 ) were designed using ProbeFinder 2 . 45 ( Roche Applied Science , Indianapolis , IN ) and this was performed using a Lightcycler 480 Probe Master ( Roche Applied Science , Indianapolis , IN ) . The reaction was run in a Lightcycler 480 for 45 cycles under the following conditions: 95°C for 10 s , 56°C for 10 s and 72°C for 30 s . Gene expressions in the retina , RPE and sclera after six weeks of myopic eyes and the fellow eyes were compared to the control eyes . Glyceraldehyde 3-phosphate dehydrogenase ( GAPDH ) was used as an endogenous internal control . Whole mouse eyes ( 6 weeks minus lens treated myopic , contra-lateral fellow and independent control eyes , n = 6 per type ) were embedded in frozen tissue matrix compound at −20°C for 1 hour . Prepared tissue blocks were sectioned with a cryostat at 6 microns thicknesses and collected on clean polysine™ glass slides . Slides with the sections were air dried at room temperature ( RT ) for 1 hour and fixed with 4% para-formaldehyde for 10 min . After washing 3X with 1x PBS for 5 minutes , 4% bovine serum albumin ( BSA ) diluted with 1x PBS was added as a blocking buffer . The slides were then covered and incubated for 1 hour at RT in a humid chamber . After rinsing with 1x PBS , a specific primary antibody raised in rabbit against ZC3H11A , SLC30A10 and raised in goat against LYPLAL1 ( Abcam , Cambridge , UK ) diluted ( 1∶200 ) with 4% BSA was added and incubated further at 4°C in a humid chamber overnight . After washing 3X with 1x PBS for 10 min , fluorescein-labeled goat anti-rabbit secondary antibody ( 1∶800 , Invitrogen-Molecular Probes , Eugene , OR ) and fluorescein-labeled rabbit anti-goat secondary antibody ( 1∶800 , Santa Cruz Biotechnology , Inc . CA , USA ) was applied respectively and incubated for 90 min at RT . After washing and air-drying , slides were mounted with antifade medium containing DAPI ( 4 , 6-diamidino-2-phenylindole; Vectashield , Vector Laboratories , Burlingame , CA ) to visualize the cell nuclei . Sections incubated with 4% BSA and omitted primary antibody were used as a negative control . A fluorescence microscope ( Axioplan 2; Carl Zeiss Meditec GmbH , Oberkochen , Germany ) was used to examine the slides and capture images . Experiments were repeated in duplicates from three different samples . GAPDH , ZC3H11B , SLC30A10 , and LYLPLAL1 were run using 10 ul reactions with Qiagen's PCR products consisting of 1 . 26 ul H2O , 1 . 0 ul 10X buffer , 1 . 0 ul dNTPs , 0 . 3 ul MgCl , 2 . 0 ul Q- Solution , 0 . 06 ul taq polymerase , 1 . 0 ul forward primer , 1 . 0 ul reverse primer and 1 . 5 . 0 ul cDNA . The reactions were run on a Eppendorf Mastercycler Pro S thermocycler with touchdown PCR ramping down 1°C per cycle from 72°C to 55°C followed by 50 cycles of 94°C for 0:30 , 55°C for 0:30 and 72°C for 0:30 with a final elongation of 7:00 at 72°C . All primer sets were designed using Primer3 [74] . The gel electrophoresis was run on a 2% agarose gel at 70 volts for 35 minutes . The primers were run on a custom tissue panel including Clontech's Human MTC Panel I , Fetal MTC Panel I and an ocular tissue panel . The adult ocular samples were obtained from normal eyes of an 82-year-old Caucasian female from the North Carolina Eye Bank , Winston-Salem , North Carolina , USA . The fetal ocular samples were from 24-week fetal eyes obtained by Advanced Bioscience Resources Inc . , Alameda , California , USA . All adult ocular samples were stored in Qiagen's RNAlater within 6 . 5 hours of collection and shipped on ice overnight to the lab . Fetal eyes were preserved in RNAlater within minutes of harvesting and shipped over night on ice . Whole globes were dissected on the arrival day . Isolated tissues were snap-frozen and stored at −80°C until RNA extraction . RNA was extracted from each tissue sample independently using the Ambion mirVana total RNA extraction kit . The tissue samples were homogenized in Ambion lysis buffer using an Omni Bead Ruptor Tissue Homogenizer per protocol . Reverse transcription reactions were performed with Invitrogen SuperScript III First-Strand Synthesis kit . The primary analysis was performed on the AL quantitative trait . As a strong correlation exists in AL measurements from both eyes ( r>0 . 9 ) , we used the mean AL across both eyes in the GWAS analysis , as was recommended in a review [75] . Linear regression was used to interrogate the association of each SNP with AL after adjusting for age , gender , height and level of education , under the assumption of an additive genetic effect where the genotypes of each SNP are coded numerically as 0 , 1 and 2 for the number of minor alleles carried . In addition , for SiMES , the top five principal components of genetic ancestry from the EIGENSTRAT PCA were also included as covariates to account for the effects of population substructure as described in genotype QC section [60] . Association tests between each genetic marker and phenotype were carried out using PLINK software [69] ( version 1 . 07 ) . Analyses were also repeated without adjustment for education level or height for the purpose of comparison . In the discovery phase , we conducted a meta-analysis of GWAS results from 3 cohorts for AL using a weighted-inverse variance approach by fixed-effect modeling in METAL ( http://www . sph . umich . edu/csg/abecasis/metal ) . In the secondary analyses , SNPs that have been identified from the primary analyses were tested for association with high myopia onset ( as a binary trait ) and SE ( as a quantitative trait ) . For Singapore cohorts , the association analyses adjusted for the same covariates as the primary analyses within a linear regression and logistic regression framework respectively . For Japan case-control datasets , only age and gender were included as covariates in the model for high myopia , as the other covariates were not available . The regional association plots were constructed by SNAP ( http://www . broadinstitute . org/mpg/snap ) . Haploview 4 . 1 ( http://www . broad . mit . edu/mpg/haploview ) was used to visualize the LD of the genomic regions . Genotyping quality of all reported SNPs has been visually evaluated by the intensity clusterplots . The coordinates reported in this paper are on NCB136 ( hg18 ) . For functional studies in the myopic mouse model , gene expression of all three identified genes in control and experimental groups was quantified using the 2−ΔΔCt method [76] . The standard student's t-test was performed to determine the significance of the relative fold change of mRNA between the myopic eyes of the experimental mice with the independent age-matched controls . | Myopic individuals exhibit an increase in ocular axial length ( AL ) . As a highly heritable ocular biometry of refractive error , identification of quantitative trait loci influencing AL variation would be valuable in informing the biological etiology of myopia . We have determined that a genetic locus on chromosome 1q41 containing zinc-finger pseudogene ZC3H11B is associated with AL and high myopia through a meta-analysis of three genome-wide association scans on AL in Chinese and Malays , with validation for high myopia association in two additional Japanese cohorts . In addition , variations in the expression of murine gene ZC3H11A and two neighboring genes SLC30A10 and LYPLAL1 in the retina and sclera in a myopic mouse model implicate the role of these genes in myopia onset . To our knowledge , this is the first genome-wide survey of single nucleotide polymorphism ( SNP ) variation of AL in Asians . Our results suggest that genetic variants at chromosome 1q41 have potential roles in both common and high myopia . | [
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] | 2012 | Genetic Variants on Chromosome 1q41 Influence Ocular Axial Length and High Myopia |
CTCF is an essential , ubiquitously expressed DNA-binding protein responsible for insulator function , nuclear architecture , and transcriptional control within vertebrates . The gene CTCF was proposed to have duplicated in early mammals , giving rise to a paralogue called “brother of regulator of imprinted sites” ( BORIS or CTCFL ) with DNA binding capabilities similar to CTCF , but testis-specific expression in humans and mice . CTCF and BORIS have opposite regulatory effects on human cancer-testis genes , the anti-apoptotic BAG1 gene , the insulin-like growth factor 2/H19 imprint control region ( IGF2/H19 ICR ) , and show mutually exclusive expression in humans and mice , suggesting that they are antagonistic epigenetic regulators . We discovered orthologues of BORIS in at least two reptilian species and found traces of its sequence in the chicken genome , implying that the duplication giving rise to BORIS occurred much earlier than previously thought . We analysed the expression of CTCF and BORIS in a range of amniotes by conventional and quantitative PCR . BORIS , as well as CTCF , was found widely expressed in monotremes ( platypus ) and reptiles ( bearded dragon ) , suggesting redundancy or cooperation between these genes in a common amniote ancestor . However , we discovered that BORIS expression was gonad-specific in marsupials ( tammar wallaby ) and eutherians ( cattle ) , implying that a functional change occurred in BORIS during the early evolution of therian mammals . Since therians show imprinting of IGF2 but other vertebrate taxa do not , we speculate that CTCF and BORIS evolved specialised functions along with the evolution of imprinting at this and other loci , coinciding with the restriction of BORIS expression to the germline and potential antagonism with CTCF .
CCCTC-binding factor ( CTCF ) is a ubiquitously expressed protein that binds to more than 20 , 000 sites within the human genome [1]–[3] . The distribution of these binding sites , along with experimental data from several well-characterised loci ( reviewed [4] ) indicates that CTCF acts as an insulator protein genome-wide , defining boundaries for gene clusters or segregating alternative promoters . This can affect gene expression , for instance at the well-studied chicken ß–globin locus , where CTCF binding to the FII insulator leads to transcriptional silencing by blocking the effects of a nearby enhancer [5] . CTCF is also required for inter-chromosomal interactions such as pairing of the X chromosomes during initiation of X chromosome inactivation [6] and even co-localisation of non-homologous chromosomes [7] . It is now considered that CTCF contributes more broadly to the establishment of nuclear compartments where transcription is enhanced or repressed [8] , [9] , rather than functioning only to insulate neighbouring regions of the genome from each other . Given these diverse and significant roles , it is not surprising that CTCF is essential for life ( reviewed [9] ) . Furthermore , point mutation and loss of heterozygosity of CTCF is associated with human cancer , identifying CTCF as an important candidate tumour-suppressor gene [10] . The CTCF protein , and the nucleotide sequence that encodes it , can conceptually be divided into three separate domains ( Figure 1A ) . The central ( ZF ) domain contains ten Cys2His2 zinc-fingers ( ZFs ) , and one Cys2HisCys ZF , combinations of which are used to bind various DNA sequences [11] . Flanking the ZF domain are the N- and C-terminal domains , which interact with other DNA-binding proteins , histones and histone modifying proteins , and the large subunit of polymerase II ( reviewed [8] ) . In all three of its domains , CTCF shows extraordinary conservation throughout vertebrates [11]–[14] , and even non-vertebrates [15] , reflecting the considerable functional constraint CTCF must face due to its multiple essential roles and many interacting partners . In humans and mice , a paralogue of CTCF has been identified known as CTCF-like ( CTCFL ) , or as it was originally named ( and how we will refer to it hereafter ) , Brother Of Regulator of Imprinted Sites ( BORIS ) [16] . Human and mouse BORIS posses a suite of ZFs with binding capability , sequence and underlying gene structure that is extremely similar to CTCF ( Figure 1A ) . However , the N- and C-terminal domains of human and mouse BORIS show almost no similarity to CTCF , implying that although they can bind the same DNA , they are likely to act differently at these sites . One example of how CTCF and BORIS may function differently comes from their effects on the regulation of genomic imprinting , which is responsible for parent-of-origin specific , mono-allelic gene expression in about 100 mammalian genes [17] . The most extensively studied imprinted gene , insulin-like growth factor 2 ( IGF2 ) , is expressed exclusively from the paternally-derived chromosome in eutherian ( ‘placental’ ) mammals [18]–[21] and marsupial mammals [22] , [23] . Located downstream of IGF2 is the untranslated RNA H19 , which is expressed solely from the maternally derived chromosome [24] , [25] . Biallelic expression of IGF2 was discovered in the egg-laying monotreme mammals [26] , birds [22] , [27] and fish [28] , implying that imprinting of this region evolved at the same time as viviparity , 180-210MYA [29] . In mice , imprinted expression of Igf2/H19 depends on the imprint control region ( ICR ) , an insulator element located between these two genes . The ICR is methylated during spermatogenesis , specifically marking the paternally-derived chromosome [30] . CTCF binds to the ICR , but only on the unmethylated , maternally-derived chromosome . When bound to the maternally-derived ICR , CTCF performs many functions including protecting the ICR from methylation [31]–[33] , blocking Igf2 access to a downstream enhancer ( resulting in Igf2 silencing in cis [34] , [35] ) , and simultaneously activating H19 expression [33] . CTCF is thought to orchestrate these events through the formation of maternal-specific chromosomal loops [36] and the establishment of local chromatin modifications [37] . Thus , CTCF acts somatically to ‘interpret’ the differential methylation mark of the ICR acquired during gametogenesis , resulting in imprinted expression of Igf2/H19 . In contrast , BORIS appears to be essential for the establishment of differential methylation at the IGF2/H19 ICR [38] . In mouse testes , BORIS is bound to the Igf2/H19 ICR during the time when the ICR becomes methylated . Methylation is accomplished by members of the de novo methyltransferase 3 family , of which DNMT3L is essential to this process [39] , [40] and DNMT3A/3B are partially redundant [41] . Transgenes containing the mouse ICR were methylated in Xenopus oocytes only when co-injected with BORIS , DNMT3L , one of DNMT3A/3B and a histone modifier called protein arginine methyltransferase 7 ( PRMT7 ) [38] . Thus , BORIS and CTCF both bind to the ICR through their common ZF domain , yet appear to act differently at this site . BORIS establishes differential methylation of the ICR and later CTCF interprets this mark , resulting in imprinted expression of Igf2/H19 . Significantly , in humans and mice CTCF and BORIS show mutually exclusive expression; BORIS is transcribed only in certain parts of the developing and adult testes , whereas CTCF is expressed in all other regions tested [16] , [38] . The only reported instances of BORIS expression outside of the testes is in various types of cancers [42]–[47] . This mutually exclusive expression pattern could be explained in part by the recent discovery that CTCF actually binds to the promoter of BORIS and negatively regulates its expression [44] . BORIS is associated with a large group of potentially oncogenic “cancer-testis” ( CT ) genes , which also show testis-specific , or gonad-specific , expression in healthy individuals , but are highly expressed in cancers [48] . CTCF binds to the promoter of many CT-genes in healthy somatic tissue where these genes are silenced [42] , [43] , [49] , [50] . However , this repression is disrupted by conditional expression of BORIS , which replaces CTCF binding at the promoter and subsequently causes local demethylation and gene activation [42] , [43] , [49] . Similarly , CTCF-binding has a repressive effect on the promoter of the anti-apoptotic gene BAG1 , whereas BORIS performs oppositely , altering histone methylation and upregulating BAG1 expression [51] . The discovery that CTCF and BORIS have opposite effects on transcription of BAG1 , some CT-genes , and on the epigenetic status of the IGF2/H19 ICR , has lead to the ( albeit controversial [47] ) hypothesis that CTCF and BORIS are antagonistic regulators of the common loci to which they bind , and that inappropriate interactions between them is cancer promoting [16] , [52] . Comparisons between the genomes of mammals and other vertebrates are powerful tools in understanding how human genes and their products are regulated , what their function is and how and why they evolved [53] , [54] . Indeed , much of CTCF function has been characterised in chicken , including its capacity as an insulator protein [5] and recent studies have revealed the extreme conservation of CTCF sequence and function in amphibians [13] , fish [14] and even invertertebrates such as Drosophila [15] . Despite this , CTCF has not been characterised in non-eutherian mammals or reptiles and whether BORIS exists outside humans and mice is not even known . From reported failures to find BORIS sequence in chicken and fish [14] , [16] it has been proposed that BORIS arose recently from duplication of CTCF in an early mammal [16] . However , here we report that BORIS orthologues are present in all major mammalian groups and at least two reptilian species , proving that BORIS evolution occurred much earlier than has been recognised . We examined the expression pattern of CTCF and BORIS in the three major mammalian clades and a reptile , discovering that although CTCF is ubiquitously expressed in all species , BORIS became progressively specialised to testis throughout amniote evolution . We consider these new data with respect to current theories regarding CTCF and BORIS as antagonistic epigenetic regulators and their roles in governing genomic imprinting at the IGF2/H19 locus .
Homologues of CTCF and BORIS were amplified from a range of amniotes by reverse-transcriptase PCR ( RT-PCR ) and rapid amplification of cDNA ends , using primers designed from sequenced genomic data or evolutionarily conserved regions ( Table S1 ) . Full-length or near full-length protein coding cDNA sequences were retrieved in this way from our model eutherian , marsupial , monotreme and reptilian species; domestic cattle ( Bos taurus ) , tammar wallaby ( Macropus eugenii ) , duck-billed platypus ( Ornithorhynchus anatinus ) and central bearded dragon ( Pogona vitticeps ) respectively ( accession numbers EU527852-EU527858 ) . Similarity searches , using these sequences and other annotated CTCF and BORIS sequences as queries , were conducted in a variety of databases hosted at NCBI ( http://www . ncbi . nlm . nih . gov ) and Ensembl ( http://www . ensembl . org ) . This approach identified a further 37 homologues of these genes in vertebrates ( Table S2 ) . From the largest region of common overlap between these homologues , a neighbour joining tree was constructed , revealing two distinct clusters of sequence ( Figure 2 ) . One of these clusters contained previously annotated copies of CTCF from human ( NM_006565 ) , mouse ( NM_007794 ) , rat ( NM_031824 ) , cattle ( NM_001075748 ) , chicken ( NM_205332 ) and zebrafish ( NM_001001844 ) . The other cluster contained annotated BORIS sequence from human ( NM_080618 ) and mouse ( NM_001081387 ) . The branch separating these two clusters was supported by a 100% bootstrap value . This unambiguously defined which sequences were CTCF orthologues and which were BORIS orthologues . In line with previous studies , we detected CTCF orthologues in all major vertebrate groups [12]–[14] . Included in this cluster were closely related duplicate CTCF sequences ( designated CTCF1 and CTCF2 ) from stickleback and medaka . The BORIS cluster included , as well as orthologues from many eutherian species , clear orthologues in two marsupials ( Gray short-tailed opossum , Monodelphis domestica , and wallaby ) , a monotreme ( platypus ) and two reptiles ( bearded dragon and green anole , Anolis carolinensis ) . No orthologues of BORIS could be detected using nucleotide BLAST , or translated BLAST searches in genomes of any avian ( chicken , Gallus gallus; and zebra finch , Taeniopygia guttata ) , amphibian ( Western-clawed frog , Xenopus tropicalis ) , teleost fish ( puffer fish , Takifugu rubripes and Tetraodon nigroviridis; zebrafish , Danio rerio; stickleback , Gasterosteus aculeatus; and medaka Oryzias latipes ) or primitive vertebrate ( sea lamprey , Petromyzon marinus ) . Although BLAST searches failed to identify any sequence orthologous to BORIS in bird , amphibian and fish genomes , it remained possible that BORIS is present in these genomes but is too diverged to detect using standard alignment methods . This seemed particularly likely for chicken , as birds are a sister taxon to the reptiles , in which we discovered BORIS orthologues . Applying a strategy previously used in the search for divergent genes [55] , we sought orthologues of markers on either side of human BORIS . We located such sequences in multiple species , and searched the dividing spaces for BORIS-like sequence . We found that genes flanking BORIS in humans were part of a single large block of genes ( TMEPAI-BMP7 ) clustered together in the same orientation in all tetrapods ( data not shown ) . Genes from this block were either not clustered together , or were not present in sea lamprey and teleost fish genomes . We aligned the regions containing genes immediately adjacent to BORIS ( PCK1 and RBM38 ) between human , mouse , dog , opossum , platypus , chicken , green anole and frog ( Figure 3 ) . As before , we could detect no BORIS orthologues in frog , but found some similarity between the first zinc finger of BORIS and a 108-bp region of the chicken PCK1-RBM38 intergenic sequence . When this sequence was used a query for reciprocal BLAST against the entire human genome , the best alignments were to the first zinc finger of CTCF and BORIS , indicating that these sequences were homologous . We could uncover no evidence for this sequence being part of an active gene other than finding that it overlaps with an Ensembl ab-initio gene prediction ( GENSCAN00000030237 ) . We therefore conclude that the sequence is a degraded relic of BORIS . We aligned predicted CTCF and BORIS proteins and found that , like previously annotated versions of these proteins , all possessed eleven ZFs , ten of which belong to the Cys2His2 class , and one which belongs to the Cys2HisCys class ( Figure S1 ) . As previously reported for human , mouse , chicken , zebrafish and frog [12]–[14] , [16] , we found that all vertebrate CTCF orthologues are extremely highly conserved throughout their entire length . From pairwise alignments over the entire length of its sequence , we found 92% average identity between human CTCF and other selected vertebrate CTCF sequences ( Table 1 ) . In comparison , similarity of BORIS orthologues , to each other and to CTCF , was largely restricted to the region encoding the ZFs . When human BORIS was compared to other BORIS sequences the average identity was 80 . 4% within the ZF domain , but less than 35% similar in the other two regions . Moreover , comparisons of human BORIS with CTCF sequences produced an average identity of 74 . 1% within the ZF domain , but less than 15% conservation within the other regions . CTCF genomic sequence from human , mouse , zebrafish and frog were all reported to have ten protein-encoding exons when they were first characterised [13] , [14] , [16] . In contrast , chicken CTCF was reported by Klenova et al . [12] to only have seven protein coding exons , four of which contained all eleven zinc fingers . We analysed the gene structure of CTCF in all species from which there was full genomic sequence and found that all sequences , including chicken CTCF , contained ten exons in total , with seven ZF exons ( Figure 1B ) . BORIS orthologues were also found to have a very similar structure , especially within the ZF domain where intron-exon boundaries were identical . One of the most remarkable characteristics of CTCF and BORIS is that in humans and mice they show apparently mutually exclusive expression . BORIS is transcribed only in specific parts of the testis , while CTCF is expressed in all tissues except those expressing BORIS [16] , [38] . This expression pattern underpins the hypothesis that BORIS is the key regulator establishing the male germline imprint of IGF2 , that it acts antagonistically to CTCF and defines its inclusion within the cancer-testis group of genes . To determine if this expression pattern is conserved more widely in vertebrates , we examined the transcription of CTCF and BORIS in cattle , wallaby , platypus and bearded dragon . Initially , we performed 35 cycles of RT-PCR on a series of tissues using CTCF/BORIS primers anchored within at least one of the ZFs and a surrounding non-zinc finger region ( Table S1 ) . CTCF transcripts were detected in this way for all tissues and animals tested ( Figure 4A ) . BORIS transcripts were detected only in the gonads of cattle and wallaby; strongly in testes , and weakly in ovarian samples . In contrast , BORIS was amplified from a much wider set of somatic and reproductive tissues in platypus ( brain , heart , liver , kidney and testis ) ; and bearded dragon ( brain , lung , liver , kidney , spleen , testis and ovary ) . To minimise the possibility we were observing tissue specific splice variants , we repeated our RT-PCR experiments using primers from different regions of BORIS ( Table S1 ) , and found similar results ( data not shown ) . Despite these discoveries , due to the nature of conventional ‘end-point observed’ RT-PCR our initial experiments were semi-quantitative at best . Thus , we were unsure if the expression we were observing was at a level which was biologically relevant . A recent publication using the quantitative real-time PCR technique found that although BORIS expression is considered to be restricted to the testis and some tumours , BORIS transcripts could be detected in other tissues up to 0 . 3% of the level of BORIS in the testis [47] . The authors concluded from this that expression of BORIS less than 0 . 3% of the level in testis was not biologically relevant . We performed real-time PCR amplifications of CTCF and BORIS on all our available tissues in triplicate and comparatively quantified their respective levels using the Corbett Research Rotorgene system , with SYBR Green as the fluorescent DNA-binding dye . Differences in template concentration within a species were taken into consideration by normalising our results to the housekeeping gene glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) . In agreement with our initial RT-PCR experiments , amplification of CTCF occurred in all tissues and species reproducibly , but with up to 50-fold variation between tissues ( Figure S2 ) not unlike that seen previously in developing zebrafish and frog [13] , [14] . Like previous experiments , we found that BORIS amplifications by real-time PCR were predominantly from the testis , with consistently high expression between 10% and 100% of the level of GAPDH ( Figure S2 ) . As expected , BORIS amplification was also detected on multiple occasions outside of the testis , particularly within platypus and bearded dragon , and at levels well within the expected limitations of our assay ( see methods ) . When we applied the 0 . 3% cut-off defined by Kholmanskikh et al . , [47] to our results , we found that as in humans , levels of BORIS in somatic tissues were below this threshold in cattle and wallaby ( <0 . 2% of testis expression ) , while ovarian BORIS levels were just on ( cattle ) or above ( wallaby ) this threshold ( Figure 4B ) . Expression of BORIS outside of the testis in platypus and bearded dragon was much higher . BORIS transcripts in the liver and kidney of platypus was within 6–10% of that found in platypus testis ( Figure 4B ) , and was at a level comparable to CTCF expression found in these tissues ( Figure S2 ) . Likewise , levels of BORIS transcripts in bearded dragon brain , kidney and ovary were 2–5% of the level of BORIS in testis . BORIS transcripts were detected in other five other somatic tissues of platypus ( brain , heart and spleen ) and bearded dragon ( lung and spleen ) at levels just on or above the 0 . 3% threshold .
Previous studies established that CTCF is a highly conserved and ubiquitous gene in humans and mice , as well as other vertebrates including birds , fish and amphibians [12]–[14] . Our studies on cattle , wallaby , platypus and dragon lizard confirm the expectation that CTCF is highly conserved in all vertebrate groups , and is expressed to varying degrees in all tissues of eutherian , marsupial and monotreme mammals , as well as reptiles ( Figures 4A and S2 ) . In contrast to the well-studied CTCF gene , much less is known about the evolutionary history and function of BORIS . BORIS sequence was previously determined only in humans and mice [16] , and no orthologue was detected in chicken . This gave rise to the speculation that BORIS duplicated from CTCF only recently in the mammal lineage . In addition , chicken CTCF was reported to have a gene structure significantly different from that of mammal CTCF and BORIS . Chicken was therefore considered to represent the ancestral gene structure , and an alteration of CTCF gene structure was proposed to have occurred in the mammalian ancestor , followed by a duplication to give rise to BORIS . We found that chicken CTCF was not , after all , different in structure from mammal CTCF as was previously reported [12] , [16] ( Figure 1B ) . The chicken genome project had not been undertaken when chicken CTCF was initially sequenced , so sequence coverage from this early study may not have been sufficient to build a reliable assembly of the region . Alternatively , the CTCF clone that was sequenced may have been a cDNA and genomic DNA chimaera . Unexpectedly , we found orthologues of BORIS in at least two reptilian species ( bearded dragon and green anole ) . This means that the duplication of CTCF which gave rise to BORIS must have occurred prior to the divergence of sauropsids ( birds and reptiles ) and mammals 210–310 million years ago ( Figure 5 ) . In agreement with Loukinov et al . [16] we could find no full orthologue of BORIS within the chicken genome . However , by analysing the intergenic region between markers flanking the expected site of BORIS in chicken , we did discover a small 108-bp segment of DNA homologous to the first zinc finger of BORIS ( Figure 3 ) . Although this region of DNA may be part of another functional gene , we consider that it is unlikely to be functionally related to other BORIS orthologues , given that no other regions showed conservation , even the usually well-conserved zinc fingers . We conclude that either BORIS succumbed to pseudogenisation in birds some time after they diverged from reptiles , or underwent a rapid functional change leaving behind only small traces of its evolutionary past . In an extension of previous studies [16] , we found extremely high conservation between vertebrate CTCF orthologues , but observed that BORIS homologues were similar to each other , and to CTCF , only within the ZF domains ( Table 1 ) . These observations support the prediction of Loukinov et al . that any major differences between CTCF and BORIS function are probably attributable to the N- and C-terminal domains , given these are the most divergent . In fact , the N- and C-terminal domains of CTCF and BORIS contained only small pockets of sequence that were obviously alignable ( Figure S1 ) . Interestingly , two of these conserved regions overlapped the start and end of these proteins , implying that the duplication that gave rise to BORIS must have involved the entire CTCF sequence . The ZF domain of CTCF orthologues we examined showed an almost perfect ( 99 . 5% average ) identity with human CTCF . In comparison , the average conservation between the ZF domain of human BORIS and other BORIS orthologues was much lower ( 80 . 4% ) . This suggests that BORIS experienced a decrease in functional constraint relative to CTCF , initially because it was a duplicate , and presently because it only binds a subset of the sites bound by CTCF . Alternatively , BORIS may bind some sequences not recognised by CTCF [38] . In support of this , we found that although all of the amino acids thought to perform protein-DNA interactions [56] were 100% conserved for vertebrate CTCF , many were not conserved in some , or all BORIS orthologues ( Figure S1 ) . It would be interesting to investigate this further by mapping BORIS binding sites in the genome relative to the published CTCF binding sites [2] , [3] . Our RT-PCR experiments showed two main patterns of BORIS expression ( Figure 4 ) . In the marsupial and the eutherian ( wallaby and cattle respectively ) we found predominantly testis-specific expression with some ovarian expression , whereas in the reptile ( bearded dragon ) and the monotreme ( platypus ) we detected expression of BORIS in multiple somatic tissues as well as the gonads . When these experiments were repeated using quantitative real-time PCR , we discovered that after 45 cycles of PCR , some BORIS transcripts could be detected outside of the germline in cattle and wallaby . However , we found that these levels of BORIS were extremely low , approaching the limits of detection and falling under a previously defined threshold for meaningful expression of BORIS [47] . Thus , we expect that BORIS function in cattle and wallaby is absent from somatic tissues , just as is predicted in humans and mice . More experiments will be required to determine if the ovarian expression of BORIS in cattle and particularly wallaby is functionally significant . The highest levels of BORIS expression outside of the testis were found in platypus and bearded dragon . The most striking examples of these came from the liver and kidney of platypus and the brain , kidney and ovary of bearded dragon , which were at levels 2-10% of BORIS expression in the testis ( Figure 4B ) . In two cases ( platypus liver and kidney ) this level of expression was close to the level of CTCF expression within the same tissues ( Figure S2 ) . These results strongly suggest that BORIS in platypus and bearded dragon functions outside of the testes , including in the ovary and multiple somatic tissues . This finding is of significance because it indicates that BORIS had wide expression in an ancestral amniote , similar to that of CTCF , the gene from which it arose by duplication . The question then arises , why was the CTCF duplicate ( or “proto-BORIS” ) initially retained and why did it succumb to evolutionary change ? The high degree of CTCF conservation throughout vertebrates implies that it is a gene under extreme functional constraint . Accordingly , perhaps it is not surprising that a CTCF duplicate in a new genomic environment would be retained and undergo sub-functionalisation , alleviating some mutational load upon CTCF . Subfunctionalisation may also explain why duplicate copies of CTCF have been retained in the genomes of medaka and stickleback ( Figure 2 ) , following whole-genome duplication of early teleost fish [57] . Although we observed CTCF and BORIS expression alongside each other in some tissues of monotremes and reptiles , these genes are apparently not co-expressed in humans and mice and may even be antagonistic . CTCF and BORIS bind competitively to common sites and display opposing effects on the epigenetic status of the Igf2/H19 ICR and transcription of BAG1 and the CT-genes [16] , [42] , [43] , [49] , [52] . Thus , at some stage during the evolution of therian mammals , CTCF and BORIS evolved mutually exclusive expression and potential antagonism . As our studies were performed on whole tissues , we could not resolve whether CTCF and BORIS show mutually exclusive expression amongst the many discrete cell-types in testis and ovary in wallaby and cattle , so we cannot pinpoint when mutually exclusive expression arose in therian mammals after their divergence from the monotremes . To date , the only non-pathological function proposed for BORIS is the establishment of paternal-specific methylation at the Igf2/H19 ICR in mice [16] , [38] . If found to be true for mice , it seems likely that this function is conserved in humans , since they also possess a paternally methylated CTCF-dependent insulator ( the ICR ) [34] , [35] and testis-specific BORIS expression which is exclusive of CTCF [16] . Moreover , differential methylation of CTCF/BORIS binding sites upstream of a maternally-expressed H19 orthologue has been discovered in sheep and wallaby [58]-[60] , suggesting that the mouse model of Igf2/H19 imprinted regulation and BORIS function may be conserved throughout all therians . Yet , BORIS is not expected to have this function in reptiles and monotremes , or the amniotic ancestor from which BORIS first arose , as IGF2 imprinting evolved after the divergence of monotremes from therian mammals . Our finding that BORIS expression is gonad-specific in wallaby and cattle , both of which possess imprinting of IGF2 [21] , [23] , implies that restriction of BORIS expression to the germline correlates with the evolution of genomic imprinting at IGF2/H19 and other loci ( reviewed [61] ) . In support of this , the evolution of another essential regulator of the Igf2/H19 ICR is also strongly correlated with the evolution of imprinting . Orthologues of the de novo methyltransferase family member DNMT3L are present in eutherians and marsupials ( which posses imprinting ) , but apparently not in chicken , fish [62] or platypus ( T . H . , unpublished data ) which are thought to lack imprinting . We propose that a duplication of CTCF occurred in a common ancestor of all amniotes , probably some time after their divergence from amphibians 350-310MYA ( Figure 5 ) . We predict that originally this ‘proto-BORIS’ functioned alongside CTCF , perhaps subfunctionalising to take on tissue-specific roles from the highly conserved and functionally constrained CTCF protein . When genomic imprinting arose in early therian mammals 210-180MYA , BORIS was recruited to perform imprint establishment in germ cells , and CTCF imprint interpretation at IGF2/H19 and potentially other imprinted genes . We speculate that this specialisation marked the start of antagonism between BORIS and CTCF , through the development of opposing epigenetic effects at the common loci to which they bound . The result of this was restriction of BORIS expression to the gonads of early therian mammals , and later restriction to the testes in the ancestor of humans and mice . The divergent nature and proposed clash of function between CTCF and BORIS has often been described as ‘sibling-rivalry’ [16] , [52] . Our results show that this rivalry did not always exist , and ironically may have evolved in response to the evolution of genomic imprinting , which is in turn thought to have evolved from other conflicts in the family [63] .
Adult cattle tissue was sourced from commercial abattoirs processing farmed animals from New South Wales , Australia . Tissue from adult wallaby and platypus were sourced from a captive breeding colony of wallabies and a platypus tissue collection , both held at the Research School of Biological Sciences , Australian National University , Canberra , Australia . Juvenile central bearded dragon tissues samples were sourced from a captive breeding colony held at the University of Canberra , Australia . All tissue ( excluding testes samples ) was from females , except for platypus tissue which was male . The captivity and sacrifice of all animals was approved by the Australian National University ( wallaby and platypus ) and University of Canberra ( bearded dragon ) Animal Experimentation Ethics Committees ( AEECP R . CG . 08 . 03 , R . CG . 02 . 00 and CEAE 04/04 respectively ) . Sourcing of cattle tissue was exempt from AEEC approval , as these animals were not sacrificed primarily for research purposes ( Simon Bain , ANU AEEC ) . Genomic DNA extraction was performed on liver tissue samples following the standard protocol for mammalian tissue [64] . Total RNA was extracted using the GenElute Mammalian Total RNA Miniprep Kit ( Sigma-Aldrich ) according to the manufacturer's instructions . Eluted RNA was treated by DNAse digestion , using the DNA-free Dnase kit ( Ambion ) as recommended by the manufacturer . All samples were checked for quality and purity on a 1 . 2% denaturing formaldehyde agarose gel [64] . RNA was tested for genomic DNA contamination by PCR prior to first strand synthesis of cDNA . Approximately 800 ng of purified RNA was used to create cDNA using the SuperScript III Reverse Transcriptase system ( Invitrogen ) according to manufacturer's instructions . All first strand synthesis reactions were undertaken using random hexamer primers except for Rapid Amplification of cDNA Ends ( RACE ) experiments , where the GeneRacer Oligo dT primer ( Invitrogen ) was used . Conventional PCR amplifications were performed in a 50 µL reaction , including either 1 µL of undiluted cDNA or 200 ng of genomic DNA as a template , 0 . 2 µM of each primer ( Table S1 ) and the following reagents from Invitrogen; 1X PCR Buffer , 0 . 8 mM dNTP mixture ( 0 . 2 mM each ) , 1 . 5 mM MgCl2 and 0 . 2 µL of Platinum Taq DNA Polymerase . Cycling conditions used were as follows; 94°C , 2 min; 34× ( 94°C , 30 sec; 61°C , 30 sec; 72°C , 1 min ) ; 72°C , 10 min . When amplifications over 1000 bp were performed , extension times were increased by 1 min/kb . Nested PCR amplifications for 3′ RACE were also undertaken using this protocol , except with reduced cycle numbers , modified primer concentration and increased annealing temperatures as stipulated in the GeneRacer kit ( Invitrogen ) protocol . For initial gene expression studies 5 µL of CTCF and BORIS amplified products were combined together with 6 µL of loading buffer ( 30% glycerol , with light Bromophenol blue staining ) and subjected to electrophoresis for 40min at 7 . 6 V/cm on a 1% agarose gel with TAE buffer and SYBR Safe DNA gel stain ( Invitrogen ) . Gels photographs were illuminated with blue light and exposed using the Gel Logic 100 Imaging System ( Kodak ) . Other than cropping , no alterations to these images were performed . Full length CTCF and BORIS cDNAs were amplified from liver and testes samples respectively and cloned using the TOPO TA Cloning Kit . Recombinant plasmid DNA was purified using the Wizard Plus SV Miniprep System and then combined with relevant primers ( Table S1 ) for sequencing at the Australian Genome Research Facility . Real-time PCR was performed in 20 µL reactions using the QuantiTect SYBR Green PCR Kit ( Qiagen ) according to manufacturer's instructions . Amplifications were performed and detected with a Rotorgene 3000 cycler ( Corbett Research ) using the following cycling conditions; 95°C , 15 min; 45× ( 94°C , 30 sec; 58°C , 30 sec; 72°C , 20 sec ) ; 72°C , 10 min . All experimental amplifications were performed in triplicate and averaged over two or three concordant results which varied by Ct values of less than 0 . 7 . Levels of CTCF and BORIS relative to GAPDH in each tissue and species were calculated using the comparative quantitation software supplied by Rotorgene . All products were checked for specificity by melt-curve analysis and electrophoresis . Primers used in this analysis were designed for each species from similar intron-spanning regions of CTCF , BORIS and GAPDH ( Table S1 ) . These primers were selected for high amplification efficiency ( >1 . 65 ) and low primer-dimer . A 10-fold serial dilution of testis cDNA was undertaken to determine the amplification range and performance of BORIS primers at low template concentrations , because BORIS ( unlike CTCF and GAPDH ) is known to have low or undetectable expression in many tissues [16] , [47] . We found that BORIS transcripts could be detected reliably down to the 10−3 dilution . Primers for the positive control gene GAPDH ( Table S1 ) were designed from sequence deposited on NCBI for cattle ( NM_001034034 . 1 ) , platypus ( EH003224 ) and wallaby ( EF654515 and trace archive data ) . For bearded dragon , GAPDH primers were designed from sequence we determined ourselves by PCR amplification and sequencing ( EU784660 ) . Homology searches were performed using BLASTn and tBLASTn [65] against the non-redundant , expressed sequence tag and trace archive databases at the NCBI website ( http://www . ncbi . nlm . nih . gov ) or release 46 of the Ensembl website ( http://www . ensembl . org ) . For species in which gene prediction was not available , or was unrealistic , we performed our own gene predictions using Genomescan [66] and local alignment . A multiple alignment of the resulting set of predicted and experimentally determined cDNA sequence ( Table S2 ) was produced using ClustalW2 with default parameters ( http://www . ebi . ac . uk/Tools/clustalw2 ) . Phylogenetic analysis was performed on aligned cDNA sequences by the neighbour-joining method with uncorrected distance measure , using the phylogenetic program PAUP* version 4 . 0 b 10 [67] . 1 , 000 replications were performed for bootstrap analysis . Protein coding predictions of these cDNA sequences were also made and aligned using ClustalW2 . This alignment was then used to calculate pairwise identity between selected orthologues using MacVector v9 . 5 . 2 . The conserved block of genes orthologous to the region surrounding human BORIS was identified in amniote species by BLAST with the criteria of unique reciprocal best-hits back to the query sequence in the human genome . Genomic sequence from these orthologous blocks was extracted from Ensembl and aligned using the LAGAN algorithm [68] available on the mVISTA website with default parameters ( http://genome . lbl . gov/vista/mvista/submit . shtml ) . | Epigenetic mechanisms heritably change gene expression without altering DNA sequence . Currently , little is known about the evolution of epigenetic traits , and the genes that control them . CTCF is an essential epigenetic regulator that is expressed widely in the tissues of vertebrates and modifies the transcription of genes by altering their location within the nucleus . CTCF duplicated at some time during vertebrate evolution , giving rise to a similar gene called BORIS with expression that is limited to parts of the testes of humans and mice , but whose function is largely unknown . BORIS may contribute to the regulation of genomic imprinting , a form of epigenetic control specific to live-bearing mammals . We discovered BORIS in all mammal groups and reptiles , implying that its genesis from CTCF occurred much earlier than previously thought , preceding genomic imprinting by over 100 million years . CTCF and BORIS have not previously been found expressed together except in tumours , leading to the hypothesis that CTCF and BORIS have conflicting functions that cause cancer when allowed to overlap . We found that CTCF and BORIS are expressed alongside each other in multiple somatic and reproductive tissues of a reptile ( bearded dragon ) and an egg-laying mammal ( platypus ) , but that BORIS is restricted to the gonads of live-bearing mammals ( cattle and wallaby ) . This indicates that BORIS specialised during mammalian evolution , in concert with the evolution of genomic imprinting . | [
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] | 2008 | The Evolution of Epigenetic Regulators CTCF and BORIS/CTCFL in Amniotes |
Knowledge of infectious disease burden is necessary to appropriately allocate resources for prevention and control . In Latin America , rabies is among the most important zoonoses for human health and agriculture , but the burden of disease attributed to its main reservoir , the common vampire bat ( Desmodus rotundus ) , remains uncertain . We used questionnaires to quantify under-reporting of livestock deaths across 40 agricultural communities with differing access to health resources and epidemiological histories of vampire bat rabies ( VBR ) in the regions of Apurimac , Ayacucho and Cusco in southern Peru . Farmers who believed VBR was absent from their communities were one third as likely to report livestock deaths from disease as those who believed VBR was present , and under-reporting increased with distance from reporting offices . Using generalized mixed-effect models that captured spatial autocorrelation in reporting , we project 4 . 6 ( 95% CI: 4 . 4–8 . 2 ) rabies cases per reported case and identify geographic areas with potentially greater VBR burden than indicated by official reports . Spatially-corrected models estimate 505–724 cattle deaths from VBR in our study area during 2014 ( 421–444 deaths/100 , 000 cattle ) , costing US$121 , 797–171 , 992 . Cost benefit analysis favoured vaccinating all cattle over the current practice of partial vaccination or halting vaccination all together . Our study represents the first estimate of the burden of VBR in Latin America to incorporate data on reporting rates . We confirm the long-suspected cost of VBR to small-scale farmers and show that vaccinating livestock is a cost-effective solution to mitigate the burden of VBR . More generally , results highlight that ignoring geographic variation in access to health resources can bias estimates of disease burden and risk .
Knowledge of the number of cases and associated economic losses from infectious diseases ( “disease burden” ) is crucial to allocate resources for prevention and control appropriately . Estimating disease burden is a priority for the control of neglected zoonoses [1] but is challenging , particularly in low- and middle-income countries ( LMICs ) where passive surveillance systems face chronic but typically unquantified under-reporting of cases . This can create large discrepancies between the officially reported and the actual disease burden [2] . Community-based studies ( CBS ) can complement passive surveillance systems by asking communities directly about disease events [3–5] . CBS are routinely used to quantify a range of parameters needed to estimate disease burden , including under-reporting and the costs of outbreaks . CBS can also improve estimates of parameters crucial for disease prevention and control , such as vaccination uptake [6 , 7] . Associations between reporting and vaccination and more widely measured variables such as socio-economic status are commonly used to extrapolate disease burden and vaccine uptake across larger geographic areas [8] . In Latin America , rabies is considered among the most important zoonoses for human and animal health [9] . The common vampire bat ( Desmodus rotundus ) is the principle reservoir throughout the region . Main activities for prevention and control include culling bats using poison and vaccination of humans and livestock [10] . The burden of vampire bat-transmitted rabies ( VBR ) on human lives and livelihoods is largely anecdotal [11 , 12] . Livestock losses across Latin America were estimated as roughly US$100 million annually in the 1960s and US$50 million annually in the 1990s [11] , including US$15 million in Brazil alone [13 , 14] . However , to our knowledge these estimates were based on assumed rates of under-reporting and rabies prevalence , making quantitative valuation of the benefits of interventions difficult . These uncertainties contribute to neglect that ultimately increases the burden of the disease [15–17] . In Peru , geographic expansions of VBR have raised serious concerns for agriculture and public health [15 , 18] . Like most Latin American countries , Peru maintains passive surveillance for rabies and other infectious diseases of livestock that rely on community reporting of suspected outbreaks . However , neither the average rate of under-reporting nor the extent of variation in under-reporting across communities is known . One important source of variation in disease reporting and in preventative behaviours such as vaccination is the degree of access to health resources [19 , 20] . This is particularly important in LMICs such as Peru , where poor transport and accessibility in rural areas limits the use of health resources [21 , 22] . Although geographic isolation is widely acknowledged as an important factor influencing reporting and vaccination uptake [19 , 20 , 23–25] , it is not typically incorporated in studies estimating disease burden . Independently of spatial effects , reporting and prevention practices may increase with socio-economic status [20 , 26] because those with higher incomes are better able to access health resources and to pay for vaccines . Reporting and vaccination may also increase with perceptions of heightened disease risk [27 , 28] , greater trust in the health authorities [19 , 29] and better knowledge of veterinary services [25] . Finally , environmental features underlying risk may be important . For example in vampire bat rabies , elevation may influence both the presence of vampire bats and reporting practices [30] . The purpose of this study was to estimate under-reporting rates using surveys and use these rates to project the actual number of VBR cases from reports to the official passive surveillance system . We focused on a region in the southern Peruvian Andes where VBR remains poorly controlled [15] . Specifically , by linking questionnaires on infectious diseases of livestock in 40 communities with passive surveillance data on 11 years of VBR outbreaks , we ( i ) quantify under-reporting and vaccination rates for VBR; ( ii ) identify predictors of the observed spatiotemporal variation in disease reporting and vaccination; ( iii ) estimate the burden of VBR accounting for this spatial variation in reporting; ( iv ) visualize how reporting biases may alter perceptions of geographic hot spots of rabies burden that might affect control decisions and ( v ) compare the costs and benefits of alternative vaccination scenarios relative to current vaccination coverage .
All participants were read a consent form ( including study objectives , risks and benefits for participants , confidentiality and that participation was voluntary ) and received clarification if requested before signing . Participants also received a leaflet explaining the project , a copy of their written consent and contact information to request study results , and a pair of cattle identification tags as reimbursement for their time after the interview . The study was approved by the Ethics Committee of the College of Veterinary Science , University of Glasgow . Questionnaires were conducted during 2015 in the regions of Apurimac , Ayacucho and Cusco , which account for almost 70% of reported rabies cases in Peru and have been affected by VBR for at least three decades [10 , 15 , 18 , 30] . Altogether , these regions have a human population of approximately 2 . 5 million [31] and a cattle population of approximately 1 . 1 million heads in around 185 , 000 farms according to the 2012 Agricultural Census of Peru ( CENAGRO IV ) . Communities were chosen using a stratified random sampling procedure . First , we divided districts with ( N = 280 ) and without ( N = 120 ) a confirmed report of VBR to the National Service of Animal Health ( SENASA , Fig 1 ) . From each set of districts , we selected communities that were accessible by public transport and that were located between 0 and 100km from a SENASA office . From each community , we obtained a list of households that kept livestock from the local community leaders or farmers’ representatives and randomly selected 10 households for inclusion . Questionnaires included 53 questions covering disease knowledge , reporting practices , prevention practices , knowledge of vampire bats , as well as information about socio-economic status . Interviews lasted around 1 hour and were performed in Quechua or Spanish by E . P . and J . B . Questionnaires were first validated on a small number of farmers ( N = 10 ) to test the clarity of questions and farmers’ comprehension , and revised where necessary . Community leaders were informed of our study objectives . Data used in this study are available in S1 Table . We analysed ( i ) the factors associated with general disease reporting ( the death of a sick cow regardless of clinical signs ) and ( ii ) the factors associated with vaccinating cattle against VBR ( a rabies-specific preventative action ) . We included the following factors which were calculated from questionnaires ( S2 Table ) : perception of risk ( i . e . , farmer believes the disease has been present in local livestock ) for six diseases that currently or historically affected livestock in the area ( mainly VBR but also Clostridiosis by Clostridium chauvoei , brucellosis , swine vesicular disease , bovine tuberculosis and foot-and-mouth disease ( FMD ) ) , household socio-economic status ( SES ) , the participant’s gender , age , knowledge of the role of SENASA and confidence in whether SENASA would investigate a reported livestock death , and the number of animals present . An additional factor , the distance from each farm to the closest SENASA reporting office ( also the main supplier of vaccines ) was calculated using a modification of the least-cost path distance described in Benavides et al . [15] . Specifically , we used the road map of the area and applied a conductance of 1 to all roads , while assuming that paths outside of roads were twice ( and up to five times ) as costly to follow . Results were unchanged at higher levels of resistance for non-road travel . We described differences in the SES of farmers using a Principal Components Analysis ( PCA ) that included 13 variables related to SES [32] ( see S2 Table for a list of variables ) . The first two principal components accounted for 20% and 12% of the total variation respectively and were used as indicators of SES in later analyses . The binary nature of our response variables ( i . e . report or not and vaccinate or not ) and the possibility of community-level differences in reporting that were not captured by our explanatory variables required using generalized linear mixed models with binomial errors ( i . e . logistic regression ) . Furthermore , since surveys were spread across a large geographic area , our analysis needed to account for potential spatial autocorrelation , which occurs when values of variables sampled at close locations are more similar than those sampled far from each other [33] . Thus , following Dormann et al . [33] , analyses used generalized quasi-likelihood linear mixed models ( glmmPQL ) to include both spatial autocorrelation and the identity of the community as random effects . All models were built using the glmmPQL function of the MASS package in R 3 . 2 . 1 [34–35] . The significance of spatial autocorrelation for the raw data and the residuals of each model were tested using the Moran’s I test [36] in the ape package of R [37] . We used the method of Gibbons et al . [24] to estimate under-reporting of VBR cases in livestock and to calculate the multiplication factor ( MF ) , defined as the multiplier needed to obtain an estimate of the actual number of VBR outbreaks from the number of reported outbreaks . We calculated the MF by multiplying the probabilities of four events that occur between the detection of a suspected outbreak and its entry into the national surveillance system ( Fig 2 ) . These four steps comprised the probability that a farmer reports a VBR outbreak ( p1 , estimated from questionnaires ) , the probability that SENASA attends a reported outbreak ( p2 , estimated from questionnaires ) , the probability that a sample was taken during the visit ( p3 , estimated from SENASA surveillance records ) and the sensitivity of the fluorescent antibody test ( FAT ) for diagnosing VBR ( p4 ) . Although the FAT has high sensitivity ( 99% ) under ideal laboratory conditions [38] , sensitivity is lower in degraded samples that are transported from remote areas , resulting in false-negatives [39–41] , and large variability has been observed in the performance of this test across laboratories of Latin America [42] . In our analysis , we assigned a constant probability to p4 for completeness of the framework ( p4 = 0 . 99 ) , but explored variation due to false negatives by calculating the MF separately for both laboratory-confirmed and for all suspected rabies outbreaks regardless of FAT results . We estimated two different MFs that used either the average level of under-reporting across the area ( MFuncorrected ) or spatially explicit under-reporting rates that were corrected by the effect of geographic isolation from the nearest reporting office ( MFcorrected ) . The spatially explicit under-reporting rate was estimated from the glmmPQL model , where reporting probability was explained only by distance from the outbreak location to the office . The inverse of this probability was used to derive the ‘actual’ number of outbreaks . We assumed that no VBR outbreaks occurred in districts without a reported outbreak since 2003 ( the year the surveillance system was implemented ) . Rabies absence from these putatively rabies-free areas was supported by statements from farmers that they had not observed clinical signs matching rabies in their animals ( N = 0 out of 120 ) . We checked the consistency of our modelled burden estimates with a third approach that calculated the number of VBR outbreaks in livestock using farmers’ observations of clinical signs of rabies in their animals , rather than official surveillance data and claims of reporting tendencies from questionnaires . Specifically , we calculated this estimate ( V ) of cattle outbreaks from VBR as: V=N×B×U×S Eq 1 where N is the total number of farms in districts with suspected outbreaks estimated from the 2012 National Census , B is the proportion of farms experiencing bat bites , U is the proportion of unvaccinated farms estimated from our surveys and S is the proportion of farmers from our survey that had observed specific clinical signs of rabies in their cattle during 2014 . This estimate assumed that all cattle in a farm reporting vaccination are vaccinated . To correct this estimate by district-level differences , we estimated district specific parameters for each variable in Eq 1 from our surveys . For districts reporting outbreaks in 2014 , but where no surveys were conducted ( 27/42 districts ) , we assigned the average estimate at the province- ( 23/27 ) or regional-level ( 4/27 ) for each variable . The number of cattle deaths was calculated by multiplying the estimated number of outbreaks from each of these three methods ( MFuncorrected , MFcorrected , V ) by the average number of cattle deaths per outbreak . The economic burden of VBR was then estimated by multiplying the actual number of cattle deaths by the average market value of a cow inferred from our surveys . Values of cows of different ages ( adult , female and juveniles ) were recorded in Peruvian New Soles ( PNS ) and converted to US$ using the average exchange rate of 2014 from the Central Bank Reserve of Peru ( 1US$ = 2 . 84 PNS ) . Uncertainty in the estimation of each probability used to calculate the MFs and in the overall economic burden of VBR was modelled by resampling each probability from a binomial distribution with variance determined by the sample size of the data . The spatially-corrected under-reporting coefficient was resampled from a normal distribution determined by the model , while market prices and the number of cases per outbreak were sampled from their observed distributions . The uncertainty was assessed using 50 , 000 Monte Carlo simulations . The current cost of VBR to farmers includes both the expenses of vaccination and losses from livestock mortality . We compared relative costs of current practices ( i . e . , partial livestock vaccination and rabies mortality ) to two alternative scenarios: vaccinating 100% of at-risk cattle ( which would virtually eliminate VBR outbreaks ) and forgoing vaccination entirely ( which would presumably increase VBR outbreaks , but eliminate costs of vaccination ) . We used the cattle population reported in the 2012 census and the direct costs of vaccination per head of cattle to estimate cost scenarios . We assumed that under 100% coverage no livestock deaths would occur due to rabies , whereas under no vaccination , livestock deaths due to rabies would occur according to rates calculated in Eq 1 , with U = 1 . We used the estimated number of cattle deaths due to VBR from MFcorrected and the estimated number of unvaccinated cattle in the area to estimate a VBR incidence of unvaccinated cattle . Assuming a linear relationship between VBR incidence in our study area and cattle vaccination coverage , we then estimated the potential losses due to VBR mortality if no cattle were vaccinated as the total cattle population multiplied by the rabies incidence . We assume that cattle must be vaccinated annually for protection against VBR , as this is the current practice in Peru .
We interviewed 400 farmers between May and October 2015 in 40 communities ( 10 farmers per community ) in 31 districts of 12 provinces in the Regions of Apurimac , Ayacucho and Cusco ( Fig 1 ) . The average number of cattle per farm was 10 . 6 ( SD: 11 . 7 , range: 1–151 ) . On average , 38% of farmers stated they would report the death of a cow suspected to be caused by an infectious disease to SENASA . However , reporting varied from 0 to 100% across communities , with a lower tendency to report in districts that had not reported VBR from 2003 until the time of the study ( 6% vs 51% in districts with confirmed cases , Fig 1C ) . Reporting was spatially autocorrelated ( Moran’s I test , p < 0 . 001 ) up to ca . 50 km , meaning farms located less than 50 km from each other had similar reporting patterns . Reporting declined with greater distances from reporting offices ( Odds Ratio ( OR ) = 0 . 94 , p < 0 . 01 , Table 1 , Fig 3 ) . Reporting rates were more than twenty times lower in the Cusco region , where VBR arrived most recently , compared to Apurimac , which has a long history with rabies [15] . General perception of the risk of three diseases ( VBR , Clostridiosis and FMD ) increased the probability of reporting a dead cow by at least 80% , with the effect of VBR risk perception almost double the effect of risk perception of Clostridiosis or FMD ( Table 1 ) . Farms with larger herds were slightly less likely to report . Reporting was unrelated to farm elevation , two SES variables , respondent age or gender , knowing a veterinarian , or confidence in SENASA responding to a reported outbreak . Across the study area , 59% of farmers reported vaccinating their cattle against rabies . As with reporting , vaccination rates varied from 0–100% across communities ( Fig 1D ) , and vaccination was spatially autocorrelated up to ca . 50km . Vaccination was generally performed by SENASA ( 78% of farmers that vaccinated ) , but 16% of farmers reported using a private or municipality veterinarian , and 5% of farmers vaccinated their animals themselves after purchasing vaccines from SENASA or private veterinarians . The vast majority ( 98% ) of farmers paid the full cost of the vaccine and delivery ( US$1 . 2 [SD: 0 . 3 , range: 0 . 8–2 . 1] ) from personal funds and 98% of those who vaccinated stated that they vaccinated all of their cows . Vaccination costs varied according to the price established by private veterinarians and the costs of the delivery and administration of vaccines . The main factor associated with vaccination was whether the farm was located in a district where a VBR case had been confirmed by SENASA prior to our surveys . Vaccination rates were 83% in farms located in districts with confirmed cases and 2% in farms located in districts without confirmed cases ( Fig 1D ) . Thus , we tested factors associated with vaccination using a glmmPQL that included only data from farms in districts with confirmed outbreaks ( N = 280 ) . Vaccination against VBR was 13 times higher by respondents who also vaccinated against Clostridiosis , 3 times higher in farmers who stated they were aware of SENASA as an authority on animal health , and 7 times higher in farmers who lived in the Cusco region ( Table 2 ) . Vaccination slightly decreased at higher elevations ( OR = 0 . 9960 , p < 0 . 01 ) . Neither distance to the SENASA office , the perceived risk of rabies in the community , socio-economic factors , perceived vaccine efficacy nor knowing a veterinarian were associated with vaccination ( Table 2 ) . Re-running the model replacing rabies risk perception by the last year that farmers perceived rabies in their community ( modelled as a factor ) showed that vaccination continued for the first 3 years after outbreaks , but decreased when rabies was perceived to be absent for 4 or more years ( OR = 0 . 09 , p = 0 . 02 ) . Given that disease reporting by farmers was influenced by the local presence of VBR , we calculated the MF using only data from districts with at least one laboratory-confirmed VBR outbreak , which we assumed to reflect the actual presence of rabies in that district . This led to the exclusion of a single district ( Chalhuanca ) that had suspected , but no laboratory confirmed rabies cases . Without accounting for the effect of spatial isolation on reporting , we estimated an average MFuncorrected of 3 . 1 ( 95% CI: 2 . 7–3 . 7 ) outbreaks for each reported outbreak ( Fig 2 ) . Incorporating the effect of distance to the office on reporting ( OR = 0 . 970 , p = 0 . 04 , Fig 3 ) increased the MFcorrected to 4 . 6 ( 95% CI: 4 . 4–8 . 2 ) . We also explored how this spatial correction of under-reporting affected the perceived distribution of outbreaks across the region either for the overall burden of VBR from 2003–2014 ( assuming the effect of distance to office is constant across years ) , or for 2014 alone ( Fig 4 ) . This analysis highlighted districts in Ayacucho and Cusco that appeared to have relatively few outbreaks according to national surveillance records , but likely suffered a disproportionate number of outbreaks after adjusting for spatial effects on under-reporting . In contrast , districts near reporting offices in Apurimac had fewer outbreaks than implied by the raw data ( Fig 4C and 4F ) . In 2014 , 157 suspected outbreaks of VBR in cattle , associated with 169 deaths , were reported to SENASA in the regions of Ayacucho , Apurimac and Cusco , with 104 outbreaks ( 113 cases ) laboratory-confirmed . The mean number of cattle deaths per outbreak was 1 . 06 ( SD = 0 . 28 , range 1–3 ) , and the average price of cattle estimated from our surveys was mean ± SD: US$241 ± 134 . For a total cattle population of 160 , 939 and 120 , 011 animals in districts with suspected and confirmed cases , this represents an official reported incidence of 105 suspected and 94 confirmed VBR deaths per 100 , 000 cattle . Across methods used to account for under-reporting , the estimated true number of VBR outbreaks during this period ranged from 341 ( 284 deaths/100 , 000 cattle ) to 714 ( 444 deaths/100 , 000 cattle ) , representing economic losses of UD$81 , 524–171 , 992 ( Table 3 ) . At the national level in 2014 , there were 254 suspected outbreaks , with 166 confirmed by FAT and 1 . 2 cases per outbreak ( SD: 0 . 74 , range: 1–10 ) . Assuming a similar national MFuncorrected to that estimated from our CBS , economic losses were estimated to UD$148 , 841–206 , 840 ( Table 4 ) . Assuming the same level of under-reporting from 2003 to 2014 , the economic burden of rabies had an average loss of US$150 , 876 ( suspected cases ) and US$ 93 , 554 ( confirmed cases ) per year . Vaccinating all cattle to eliminate the burden of VBR in districts with suspected cases would have cost US$194 , 496 in 2014 , an average cost of US$12 per farmer . The vaccination coverage according to our surveys implies that farmers actually spent ~US$161 , 403 on cattle vaccination in 2014 . Thus , the total cost of VBR ( vaccination and MFcorrected rabies mortality ) in 2014 was US$333 , 395 . In the hypothetical scenario in which no cattle were vaccinated , our models project that 4 , 196 cattle would die of VBR annually ( 2 , 607 deaths/100 , 000 cattle ) , equivalent to an economic cost of US$1 , 010 , 560 . Therefore , the current vaccination rate prevents approximately 3482 cattle deaths , a saving of ca . US$838 , 601 . Under these assumptions , the benefit-cost ratio of vaccinating all cattle instead of no vaccination would be 5 . 2 , and 1 . 71 compared to the current situation .
We identified factors associated with livestock disease reporting and vaccination against VBR , which we used to estimate the burden of VBR in southern Peru . After accounting for under-reporting , cattle VBR mortality was more than 4 times higher than the cost implied by official reports . At current vaccination levels , farmers in our study area spend approximately US$161 , 000 annually and still experience livestock losses due to VBR on the order of 444 deaths per 100 , 000 cattle . Together , animal mortality and vaccination costs exceed US$300 , 000 per year , representing a major loss for impoverished farming communities that rely on livestock for subsistence . Encouragingly however , our results suggest enhancing vaccination programs could dramatically diminish these financial losses . Our estimates of economic costs of VBR cattle mortality in southern Peru in 2014 ranged from US$81 , 524 to US$171 , 992 , depending on the method and on whether only laboratory confirmed or all suspected cases were considered . Given the lower sensitivity of the FAT test on degraded samples [40] and the significant reduction in reporting from farms located far from SENASA offices , we expect the true burden to be closer to our upper estimate . Costs towards this upper estimate were also supported by our independent calculation based on farmers’ personal observations of clinical signs of rabies in their animals ( Table 3 ) . The average monthly income in Ayacucho , Apurimac and Cusco for 2014 was US$243 , and Ayacucho and Apurimac are among the poorest regions of the country [31] . Thus , the loss of a single cow from VBR ( ~US$241 ) is equivalent to approximately one month of income . Our surveys show that 61% of farmers used income from selling cows for household maintenance , and 30% for childhood education . Therefore these losses , while outwardly modest , may reinforce poverty among small-scale farmers in the Andean region that rely on livestock for subsistence , and consider livestock as ‘saving accounts’ [1 , 43] . At the national level , cattle deaths from VBR costed US$148 , 742–206 , 840 during 2014 . However , given the wide variation in reporting tendencies that we observed in our study region , similar studies in other areas are needed to further refine the total burden of VBR in Peru . For example , reporting could decrease more sharply with distance in areas where transportation is more limited , such as the Amazonian regions . Furthermore , regional differences in reporting and vaccination could occur independently of distance to the nearest reporting office , as we observed for Cusco . Nonetheless , our estimate can be used as a starting point when prioritizing efforts for disease control . For example , the national VBR burden is much lower than the economic losses estimated in Peru for parasites in llamas ( ~US$1 . 5 million [44] ) but equivalent to the burden of Echinococcis ( ~US$196 , 000 only for direct losses [45] ) . It is important to acknowledge additional costs of VBR that we were unable to include . First , we did not directly quantify the losses associated with dairy production , which was practiced by 60% of farmers in our study . However , we expect that the price of a cow will account for part of this cost . Second , although almost 90% of reported VBR outbreaks in Peruvian livestock involve cattle [15] , even greater under-reporting of less valued livestock species ( e . g . , goats , pigs ) is likely [46] . Third , the average number of deaths per outbreak was reported in the surveillance system as the number of dead or sick animals during the SENASA visit , but additional animals that died after the visit would not have been included in our estimates . We also excluded data from districts with no official reports of rabies , which would make our estimates overly conservative if rabies were actually present . However , questionnaires confirmed the absence of animals with clinical signs of rabies in putative rabies-free districts ( compared to 14% in endemic districts ) , and our previous epidemiological analyses of travelling waves of VBR implied that these areas are truly rabies-free [15] . Thus , while we expect the bias introduced by this assumption is minimal , delayed reporting in newly infected might still occur which would increase the estimated number of outbreaks to higher than reported here [47] . Finally , data were unavailable to estimate the financial costs of sampling and diagnostic testing of suspected rabies cases . All together , these factors are likely to increase the net cost of VBR beyond the estimates presented in this study . We also demonstrated a statistical framework to incorporate spatial heterogeneity in reporting practices into estimates of disease burden . Although we corrected the estimated burden by using only distance to reporting offices , in principle our approach can be generalized to include other factors affecting reporting or diagnostic sensitivity when these are available . In our dataset , correcting for spatially heterogeneous under-reporting revealed geographic areas that had a disproportionately higher burden of VBR than implied by official records ( Fig 4 ) . This finding highlights the possibility that resources for prevention and control will be directed to areas that have high reporting , but not necessarily the highest burden , which could amplify disparities in VBR burden . Moreover , given that VBR persists in bats through spatial dynamics , neglected high burden/low reporting areas could create hotspots of transmission that facilitate long term viral persistence [48] . Our results support the findings from previous studies that livestock vaccination is the most effective intervention to reduce the burden of VBR [11 , 17] . In our study , vaccination coverage against VBR was high ( 83% ) in districts with confirmed outbreaks , but almost non-existent ( i . e . 2% of farmers ) in neighbouring , putatively rabies-free districts [15] . This shows that vaccination occurs reactively to VBR outbreaks and provides a mechanism ( lower vaccination rates and reduced herd immunity ) by which outbreaks in newly invaded areas might be larger than in historically endemic areas . Within VBR endemic areas , distance to the reporting office was not correlated with vaccination , suggesting that the presence of VBR outweighs logistical challenges to acquire vaccines . Given the high cost of this vaccine to farmers ( around US$1 . 2 per dose ) , it was surprising that socio-economic factors were unrelated to vaccination , suggesting that the perceived risk of rabies is more important than affordability in driving vaccination uptake for VBR . We estimated that the current vaccination coverage of 83% prevented the death of around 3842 cattle in 2014 , which saved farmers ~US$800 , 000 . These savings should be treated with caution since farmers may have over-stated vaccination rates and independent confirmation ( e . g . , vaccination certificates ) were unavailable . Moreover , our estimate assumes a linear relationship between vaccination coverage and VBR incidence , which while intuitive , has not been empirically demonstrated , and reactive vaccination in response to outbreaks may further complicate this relationship . Nonetheless , our results imply that vaccinating all cattle would be 1 . 7 times more beneficial than the current vaccination coverage , and 5 times more beneficial than not vaccinating cattle due to the expected increase in livestock mortality . The latter ratio is similar to the benefit-cost ratio of 6 estimated in Mexico [17] . Therefore , our results suggest that further investments in cattle vaccination , perhaps through government subsidies , would be economically beneficial to mitigate the burden of VBR . However , vaccinating the remaining cattle population could be more challenging and costly than achieving the current coverage , especially if the remaining cattle population is owned by farmers that are reluctant to vaccinate because they do not perceive VBR as a threat . To our knowledge , our study is the first estimate of the burden of VBR in Latin America to incorporate estimated under-reporting rates or spatial heterogeneity in reporting and disease occurrence . This estimate , at least four times higher than official reports , is essential in planning and implementing cost-effective measures to prevent and control the disease , which mainly affects low-income , small-scale farmers . Our results further suggest that increasing the risk perception of communities that are far from reporting offices could both increase reporting and reduce cattle losses by encouraging preventative vaccination in high risk areas . This could be achieved by developing awareness campaigns using relatively inexpensive tools like community radios . More broadly , this work highlights how variation in disease reporting can influence estimates of disease burden , which will be important to consider when extrapolating burden estimates from community-based studies across larger spatial scales . | The number of cases and monetary cost of a disease guides how resources for prevention and control are allocated . In Latin America , rabies transmitted by vampire bats is one of the most recognized zoonoses affecting humans and livestock , but its burden on lives and livelihoods has been difficult to calculate because the percentage of outbreaks that are not reported to surveillance systems is unknown . Here , using surveys to calculate farmers’ tendencies to report livestock deaths , we estimate that over 500 cattle died of rabies in southern Peru in 2014 , a loss of approximately US$170 , 000 or over 700 months of local income . Our results also show that the perceived risk of rabies strongly affected reporting of cattle mortality and vaccination coverage , suggesting that campaigns to increase awareness could reduce the burden of rabies . | [
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... | 2017 | Quantifying the burden of vampire bat rabies in Peruvian livestock |
The oligodendrocyte density is greater and myelin sheaths are thicker in the adult male mouse brain when compared with females . Here , we show that these sex differences emerge during the first 10 postnatal days , precisely at a stage when a late wave of oligodendrocyte progenitor cells arises and starts differentiating . Androgen levels , analyzed by gas chromatography/tandem-mass spectrometry , were higher in males than in females during this period . Treating male pups with flutamide , an androgen receptor ( AR ) antagonist , or female pups with 5α-dihydrotestosterone ( 5α-DHT ) , revealed the importance of postnatal androgens in masculinizing myelin and their persistent effect into adulthood . A key role of the brain AR in establishing the sexual phenotype of myelin was demonstrated by its conditional deletion . Our results uncover a new persistent effect of postnatal AR signaling , with implications for neurodevelopmental disorders and sex differences in multiple sclerosis .
The incidence and clinical course of many neurological disorders differ between sexes , and elucidating the underlying biological basis has become a high priority challenge [1 , 2] . The potential impact of sex differences in brain structure has long been neglected . They were indeed believed to be restricted to specific brain regions , in particular those involved in reproductive functions [3] . This concept has changed with recent neuroimaging studies uncovering sex differences in neuronal connectivity across the entire brain [4 , 5] . Moreover , structural sex differences in the human brain are shaped by fetal testosterone [6] . Rodent models have provided valuable insights into mechanisms leading to sex differences in brain structure and function . They can be reversible and only caused by the temporary actions of sex-specific hormones [7] . Alternatively , sex dimorphism in brain may be persistent and result from developmental processes , including the masculinizing actions of testicular testosterone during sensitive perinatal and postnatal periods , and the shaping of neuronal circuits by sex chromosome-linked genes , epigenetic factors and the hormonal environment [8–11] . In mice and rats , neural circuits are sensitive to the persistent differentiating ( organizational ) effects of gonadal steroids around birth and during a postnatal period which may extent to 4 weeks [3 , 12] . During the perinatal period , the male brain is exposed to the masculinizing effects of a transient surge of testicular testosterone , driven by kisspeptin and gonadotropin released by hypothalamic neurons [13] . In both rats and mice , the aromatization of testosterone to estradiol plays an important role in masculinization of the brain [14–16] . However , disrupting androgen receptor ( AR ) signaling also interferes with the process of hormone-dependent sexual differentiation of the brain [17 , 18] . The respective roles of estrogen receptor ( ER ) and AR signaling are not completely understood . In mice , AR are sparse in the brain at the time of the neonatal testosterone surge , and their expression only increases by postnatal day 4 ( P4 ) [17 , 19] . For this reason , it can be presumed that estrogens play a major role in the organizational effects of neonatal testosterone , when brain ER and aromatase are highly expressed , and that the role of AR signaling may become more important during postnatal brain development [17] . However , aromatase knockout male mice , developmentally deprived of their brain estrogens , show normal coital behavior following adult hormone treatment [20] . It is likely that respective organizational functions of androgens and estrogens are dependent on brain functions and differ between species . Intriguingly , a sexual dimorphism affecting the density of oligodendrocytes , the myelin forming glial cells of the central nervous system ( CNS ) , and the structure of myelin has been reported in adult mice and rats [21] . The density of oligodendrocytes was found to be 20–40% greater in adult males compared with females in the corpus callosum and other white matter tracts of the CNS . Moreover , the expression of myelin basic protein ( MBP ) and proteolipid protein ( PLP ) , two myelin-specific proteins , was significantly greater in males . Interestingly , the sexual dimorphism of oligodendrocytes and myelin was sensitive to long-term castration , over 3 months . Indeed , the density of oligodendrocytes was decreased and became comparable to the one observed in females , pointing to a possible role of testicular secretions [21] . However , a persistent organizational effect of neonatal androgens on myelin appeared highly unlikely , as oligodendrocyte progenitors arise in the rodent cerebral cortex and corpus callosum and begin to differentiate into myelinating oligodendrocytes between the first and second postnatal week [22] . Herein , we report the unexpected observation that myelin is in fact sexually differentiated in mice by postnatal androgens and AR signaling . We establish that sex differences in myelin are already present at postnatal day 10 ( P10 ) using a transgenic mouse line selectively expressing the enhanced green fluorescent protein ( EGFP ) in the oligodendroglial cell lineage [23] . Furthermore , using gas chromatography coupled to tandem mass spectrometry ( GC-MS/MS ) [24 , 25] , we report that brain levels of testosterone and 5α-DHT , both endogenous agonist ligands of the AR , are significantly higher in males when compared with females between postnatal days P0 and P10 , We also show persistent effects of postnatal androgens on the density of oligodendrocytes and the structure of the myelin sheaths by postnatal pharmacological treatments . Finally , we demonstrate a key role of brain AR in the structural phenotype of myelin by specifically deleting the receptor in neural cells of the CNS . The role of AR in determining the structure of myelin was further strengthened in genetic male mice with the testicular feminization mutation ( Tfm ) , which lack functional AR . These findings provide new insights into the sexual differentiation of the brain , moving persistent sex differences from neurons to myelin and uncovering new long-lasting effects of postnatal AR signaling .
To study the developmental origin and hormonal determinants of the sexual dimorphism of oligodendrocytes and myelin , we used a transgenic mouse line expressing the enhanced green fluorescent protein ( EGFP ) driven by the PLP promoter ( PLP-EGFP mouse ) . In this mouse , EGFP is selectively expressed in cells of the oligodendroglial lineage throughout the brain ( Fig 1A ) [23] . As expected , the density of fluorescent oligodendroglial cells was about 20% higher in the corpus callosum of adult male mice when compared with females ( Fig 1B ) . As the sexual dimorphism of oligodendrocytes and myelin has been previously demonstrated only in adult rodents [21] , we investigated whether it originates early during postnatal brain development . We observed a 17% higher density of cells expressing the transcription factor Olig2 ( oligodendroglial lineage marker ) in PLP-EGFP male mice when compared with females as early as postnatal day 5 ( P5 , Fig 1C and 1D ) . However , the density of EGFP+ and EGFP+/Olig2+ oligodendroglial cells did not significantly differ between sexes . At this early stage , Olig2 is still expressed in progenitors of both astrocytes and oligodendrocytes [26 , 27] . Only 20% of the Olig2+ glial progenitors were also EGFP+ , which would be expressed in the maturing cells of thus belonging to the oligodendroglial lineage . On the other hand , all EGFP+ cells expressed Olig2 , confirming the restricted expression of the fluorescent marker [28] . Between P5 and P10 , there was an increase in the density of Olig2+ , EGFP+ and EGFP+/Olig2+ cells in the corpus callosum of both sexes . At P10 , the density of all these markers was 20% higher in males when compared with females ( Fig 1E–1H ) . Likewise , the number of cells labelled with the CC1 antibody directed against adenomatous polyposis coli , an accepted marker of differentiated oligodendrocytes [29] , and of Olig2+/CC1+ co-expressing oligodendrocytes was higher in males than in females at P10 ( Fig 1I–1K ) . Thus , the density of oligodendroglial cells becomes sexually dimorphic between P5 and P10 in the mouse corpus callosum . Moreover , the number of EGFP+ cells in the transgenic mice closely approximates the number of CC1+ cells in wild type mice ( Fig 1H–1K ) . The higher density of oligodendroglial cells at P10 might suggest an early sexual dimorphism of myelin . Sagittal brain sections from P10 male and female mouse brains were immunostained by using an antibody against MBP , a major component and established marker of CNS myelin [30] . Although myelin was still sparse at P10 , there was nearly 35% more MBP-staining in corpus callosum of males when compared with females ( Fig 2A–2C ) . Consistent with the immunohistochemistry results , qRT-PCR analysis showed about 30% higher levels of MBP transcripts in the male brain when compared with females ( Fig 2D ) . Analysis by electron microscopy showed that only a small percentage of corpus callosum axons were myelinated at P10 ( < 5% ) , but that there were more than twice as many myelinated fibers in males than in females . In contrast , the total number of axons did not differ between sexes ( Fig 2E–2H ) . Thus , the density of oligodendrocytes , MBP expression and the number of myelinated axons already differ at P10 between sexes . To assess whether the observed sex difference in the density of oligodendrocytes and the extent of myelination at P10 may be dependent on the postnatal hormonal environment , we first analyzed brain steroid levels between P0 and P10 by GC-MS/MS . Levels of testosterone were higher in the male than in the female brain between P0 and P10 ( Fig 3A ) . Their analysis by two-way ANOVA showed a significant effect of sex ( F ( 1 , 74 ) = 15 . 51 , p < 0 . 0001 ) and age ( F ( 2 , 74 ) = 4 . 7 , p = 0 . 012 ) . The significant increase in testosterone at P10 in the male brain correlated to a marked drop of its immediate metabolite 5α-DHT ( Fig 3B ) . At P0 and P5 , brain levels of the more potent androgen 5α-DHT were higher in males , as compared to females ( F ( 1 , 75 ) = 3 . 72 , p = 0 . 05 ) . The combined levels of testosterone and 5α-DHT , both ligands of AR , were significantly higher in the male than in the female brain at P0 , P5 and P10 ( Fig 3C ) . Analyzing their combined levels by two-way ANOVA showed a significant effect of sex ( F ( 1 , 77 ) = 10 . 6 , p = 0 . 002 ) . A more extensive profiling of brain steroids at P10 revealed that only levels of testosterone ( p<0 . 001 ) and estradiol ( p<0 . 05 ) were higher in males than in females , whereas the levels of 13 other steroids , including progesterone , were similar in both sexes ( Table 1 ) . The absence of sex differences in progesterone levels is interesting , as this neurosteroid also stimulates myelination during postnatal development [31 , 32] . Higher brain levels of testosterone and 5α-DHT in males were concomitantly associated by significantly higher brain levels of AR mRNA , as determined by qRT-PCR ( Fig 3D ) . To investigate a link between AR signaling , the density of oligodendrocytes and the extent of myelination in corpus callosum at P10 , male PLP-EGFP pups were subcutaneously injected every two days between P0 and P10 with 1 mg/kg of the selective AR antagonist flutamide . Blocking AR caused a 30% decrease in the density of EGFP+ oligodendroglial cells in the male corpus callosum at P10 , which became similar to females ( Fig 4A ) . Conversely , injecting female PLP-EGFP pups between P0 and P10 every two days with 1 mg/kg of testosterone or 5α-DHT , which is not aromatized into estrogens , increased the density of oligodendroglial cells in their corpus callosum to male-like levels ( Fig 4B ) . To determine whether treatment with flutamide during the first 10 postnatal days also affected the organization of myelin , we measured at P10 the length of myelinated axon segments at the junction between the genu of the corpus callosum and the striatum , where they can be easily observed and quantified . Myelin segments were significantly longer in males when compared with females , but treatment of male pups with flutamide completely abolished this sex difference ( Fig 4C and 4D ) . Systemic treatment with flutamide or 5α-DHT affects AR signaling in the entire body . To assess the role of cerebral AR in the development of postnatal sex differences in corpus callosum myelin , we deleted AR in neural cells using the Cre/Lox system . A mouse line carrying a floxed exon 1 of the AR gene , located on chromosome X , was used . In this line , Cre recombination results in the excision of the transcription start site and deletion of the N-terminal domain of AR [33] . Female ARLox mice were crossed with male mice expressing the Cre recombinase under the control of the promoter and the CNS-specific enhancer of rat nestin [34] . This NesCre mouse line is characterized by a very efficient and selective Cre-mediated recombination [35 , 36] . In the resulting male ARNesCre mice , AR expression was deleted in CNS neurons , astrocytes and oligodendrocytes , but not in microglial cells . ARLox males were used as controls . The specific knockout of AR expression in the brain of ARNesCre males was verified by qPCR analysis ( Fig 5A ) . AR mRNA expression was not affected in muscle and testis . The genetic deletion of AR in CNS neurons and macroglial cells resulted in markedly reduced MBP expression in the brain at P10 . Levels of MBP mRNA transcripts and protein isoforms were decreased by almost 40% and 70% , respectively ( Fig 5B–5D ) . Immunofluorescence analysis of the corpus callosum at P10 showed a significant reduction in MBP staining density , as well as in the number of Olig2+ cells and mature oligodendrocytes ( CC1+ and CC1+/Olig2+ cells ) in ARNesCre males when compared with ARLox males ( Fig 5E–5I ) . Both pharmacological and genetic inhibition of AR thus showed that postnatal androgens , via their receptor , are involved in the sexual dimorphism that affects the density of oligodendrocytes and the extent of myelination at P10 . To assess whether exposure to androgens during the first ten postnatal days has a long-lasting impact on the sexual phenotype of corpus callosum myelin , we first used organotypic cultures of cerebellar slices prepared from P10 male and female PLP-EGFP pups [37] . At this stage , the myelination of axons only starts in cerebellum [31 , 38] . Importantly , the cerebellar tissue was exposed prior to culture to higher levels of endogenous testosterone and 5α-DHT in males when compared with females . The cerebellar slices were then cultured for 2 weeks to allow axons to become fully myelinated . Although the culture medium contained 25% horse serum , levels of androgens in the culture medium were below the limit of detection by GC-MS/MS ( 1 pg/ml for testosterone and 2 pg/ml for 5α-DHT , see Table 1 ) . Therefore , myelination proceeded to completion in an androgen-deprived medium . Consistent with a masculinizing effect of androgens on the process of myelination prior to P10 , the density of EGFP+ oligodendroglial cells in the cerebellar lobules was 36% higher in slices prepared from male pups than in those prepared from female pups ( Fig 6A and 6B ) . Furthermore , MBP staining density was about 30% higher in the male slices ( Fig 6A and 6C ) . These observations are consistent with a persistent effect of the postnatal androgen environment on myelin . To determine whether postnatal androgen-dependent sex differences in myelin persist into adulthood , we treated again male PLP-EGFP pups with flutamide and female pups with 5α-DHT between P0 and P10 ( 1 mg/kg every two days ) . We then counted oligodendrocyte cells in their corpus callosum at the age of 3 months . As for P10 , postnatal treatment with flutamide decreased the density of oligodendroglial cells in the adult male corpus callosum by 30% ( Fig 6D ) . Conversely , treating female PLP-EGFP pups between P0 and P10 every two days with 5α-DHT increased the density of oligodendroglial cells in the adult corpus callosum by about 20% ( Fig 6E ) . Thus , in spite of the constantly very low levels of endogenous androgens in females , their exposure to exogenous 5α-DHT during the first 10 postnatal days was sufficient to induce a male-like density of oligodendrocytes in their corpus callosum . Both in vitro and in vivo experiments thus documented persistent influences of postnatal androgens on myelin . Conditional deletion of AR in the brain had a major impact on the density of oligodendroglial cells and the extent of myelination in the male corpus callosum at P10 . Moreover , postnatal androgens exerted long-lasting masculinizing effects on myelin , extending into adulthood . Adult ARNesCre male mice were thus expected to exhibit a female-like phenotype of myelin with a reduced density of oligodendroglial cells and decreased MBP immunostaining . Indeed , immunohistochemical analysis of the corpus callosum by fluorescence microscopy revealed that at the age of 3 months , the densities of Olig2+ oligodendroglial cells , CC1+ mature oligodendrocytes and Olig2/CC1 co-expressing oligodendrocytes were reduced by 20 to 30% in ARNesCre male mice when compared with ARLox controls , thus becoming similar to females ( Fig 7A and 7C–7E ) . On the other hand , MBP immunostaining was decreased by 20% in corpus callosum of ARNesCre males ( Fig 7A and 7B ) . Analysis by electron microscopy showed that the percentage of myelinated axons in corpus callosum was decreased in ARNesCre males by 15% when compared to control ARLox males , but was similar to ARLox females ( Fig 7F ) . However , the total number of callosal axons was not affected by AR deletion in the brain . The mean g-ratio of myelinated callosal axons was significantly higher in ARNesCre males than in controls and similar in ARNesCre males and in ARLox females ( Fig 7G ) . The thickness of the axons is approximately 0 . 89 +/- 0 . 07 μm in ARNesCre and 0 . 90 +/- 0 . 08 μm in ARLox whereas that of the whole fiber is approximately 1 , 09 +/- 0 , 06 μm in ARNesCre and 1 . 21 +/- 0 . 10 μm in ARLox males . This suggests that myelin sheaths are thinner in males after AR deletion , becoming comparable to females . Each myelinated axon segment between two nodes of Ranvier , named internode , is formed by a single oligodendrocyte process . Importantly , oligodendrocytes can myelinate several internodes . Thus , an increase in the density of oligodendroglial cells may result in a decreased number of internodes formed per oligodendrocyte , or alternatively in shorter internodes [39] . The latter is what we observed by measuring internodal distances between two paranodal regions in cerebral cortex , where extended parts of myelinated axons can be observed in a same plane . The length of internodes of myelinated axons was measured after triple immunolabeling of contactin-associated protein ( Caspr ) , a glycoprotein present in the paranodal region , of MBP and of neurofilaments ( NF200 ) ( Fig 7H ) . Internodal distances in the cortex of ARLox males were about 40% shorter than in ARNesCre males , and they were comparable to normal females ( Fig 7I ) . Thus , ARNesCre males exhibited a female-like phenotype of myelin , characterized by thinner myelin sheaths and longer internodes . The conditional deletion of AR in the brain demonstrated its importance in the masculinization of myelin . To corroborate this finding , myelin was also examined in adult male mice carrying the naturally occurring AR testicular feminization mutation ( ARTfm ) . In these mice , a frame shift mutation in exon 1 of the AR gene results in a nonfunctional receptor in the entire body [40 , 41] . The reduction in the densities of Olig2+ oligodendroglial cells , CC1+ oligodendrocytes and Olig2/CC1 co-expressing oligodendrocytes in the corpus callosum of 3 months ARTfm males was even more marked than for ARNesCre males , reaching 40 to 50% when compared with wild-type ( Fig 8A–8C ) . Consistently , the amount of MBP analyzed by Western blot ( Fig 8D and 8E ) and MBP immunostaining in corpus callosum ( Fig 8F–8H ) were significantly lower in these ARTfm males when compared with wild-types . Particularly marked was the reduction in myelinated axons within the corpus callosum of ARTfm males and the thinner myelin sheaths observed by electron microscopy ( Fig 8I–8O ) . The thinner myelin in ARTfm males was reflected by a significant increase in the mean g-ratio ( Fig 8O ) . However , the density of callosal axons did not differ between wild types and ARTfm males ( Fig 8M ) . Taken together , the myelin phenotype of ARTfm mice resembled the one of ARNesCre mice , but differences with the controls appeared to be more marked .
Analyses by GC-MS/MS revealed that between P0 and P10 , at the time when the process of myelination begins and sex differences in myelin emerge , brain levels of testosterone and 5α-DHT are significantly higher in males than in females . This is after the masculinizing surge of testosterone , which takes place around birth in males and only lasts for a few hours [13 , 44 , 45] . Interestingly , an earlier biochemical work in rats already reported higher levels of ligand-occupied nuclear AR in male pups when compared with females during the postnatal period [46] . This sex difference in AR ligand availability is consistent with a masculinizing action of postnatal androgens during developmental myelination . A second important observation was that brain levels of 5α-DHT are markedly higher in males at P0 and P5 , but drop to low female-like levels at P10 . This developmental period corresponds to the transient expression in the brain of the type 2 isoform of the 5α-reductase , which has a higher affinity for testosterone than the type 1 isoform and is normally expressed in peripheral androgen-target tissues such as the prostate [47] . Although both testosterone and 5α-DHT act through a single receptor , 5α-DHT is a more potent agonist ligand of AR . The conversion of testosterone to 5α-DHT thus amplifies the androgenic signal [48] . Moreover , in contrast to testosterone , 5α-DHT cannot be converted to estrogens and its formation thus selects the AR signaling pathway . The transient elevation in brain levels of 5α-DHT in males is likely to play a role in the masculinization of myelin . Indeed , the density of EGFP+ oligodendroglial cells in corpus callosum and the length of myelinated processes below the genu were reduced in the P10 male brain by the AR antagonist flutamide , which also inhibits expression of the 5α-reductase type 2 [47 , 49] . Conversely , giving 5α-DHT to female pups between P0 and P10 resulted in a male-like density of oligodendroglial cells at P10 . These two observations also provided a first line of evidence for a key role of AR signaling in the sexual differentiation of myelin . Consistently , AR mRNA expression was higher in the postnatal male brain when compared with females . We provide evidence for a key role of the brain AR in the masculinization of myelin by using ARNesCre mice with selective excision of AR in neural cells of the CNS . Under the control of the nestin promoter , the Cre recombinase is expressed in neural precursor cells as early as embryonic day 10 [34] . Cre-dependent excision of the floxed exon 1 of the AR gene resulted in complete AR invalidation in the brain . This genetic tool allowed us also to avoid the confounding effects of systemic hormonal changes caused by injections of flutamide or 5α-DHT . At P10 , both mRNA and protein levels of MBP were markedly reduced in the brain of ARNesCre males when compared with control ARLox males . Within the corpus callosum , MBP immunostaining , the densities of Olig2+ cells and of mature oligodendrocytes expressing CC1 or coexpressing CC1 and Olig2 , were also significantly reduced in ARNesCre males . These observations demonstrate that sex differences in myelin observed at P10 are dependent on the presence of a functional AR in the male brain . We then addressed the important question of a hormonal imprinting of developmental myelination by early postnatal androgens . We first used organotypic cultures of cerebellar slices prepared from P10 male and female PLP-EGFP mice . Remarkably , although cerebellar slices were cultured during 2 weeks in the absence of detectable levels of androgens , the myelin formed in vitro differed between sexes , with a higher density of EGFP+ oligodendroglial cells and of MBP+ staining density in males . This observation was consistent with a persistent effect of the postnatal androgen environment on myelin prior to culture . We then demonstrated that postnatal androgen-dependent sex differences in myelin persist into adulthood . Treatment of male pups with flutamide between P0 and P10 reduced the density of EGFP+ cells in the adult corpus callosum to female-like levels . Conversely , treatment of female pups with 5α-DHT between P0 and P10 significantly increased the density of callosal EGFP+ cells in adults . It is important to emphasize that females treated during their first 10 postnatal days with 5α-DHT were no longer exposed to significant levels of androgens afterwards . Thus , postnatal androgens have persistent effects on myelin , independent on the later hormone environment . Because of the persistent and AR-dependent effects of postnatal androgens on myelin , a reduced density of oligodendrocytes and MBP expression could be expected in the corpus callosum of adult mice lacking functional AR . This was indeed observed when comparing 3 months old ARNesCre males with ARLox males . Moreover , analysis of corpus callosum axons at the electron microscopic level revealed a reduction in the percentage of myelinated axons and in the thickness of the myelin sheaths , reflected by an increased g-ratio in ARLox males . Oligodendrocytes myelinate multiple internodes on different axons . Thus , when their number is reduced , a single oligodendrocyte can be expected to myelinate more axonal segments or to form longer segments of myelin ( internodes ) . In cerebral cortex , where internodes can be measured accurately , their mean length was significantly increased in ARNesCre males when compared with ARLox males . Adjusting internode length has been identified as a means of regulating conduction velocity [50] . However , the underlying determinants remain poorly understood . Thus , variations in internode length have been proposed to result from neuronal signals during development or to reflect neuron-independent intrinsic properties of oligodendrocytes [51] . A recent study has shown that in organotypic cultures of cerebral cortex slices , a reduced number of oligodendroglial cells resulted in longer internodes [52] . Our results uncover a novel role of neural AR signaling in determining internode length . Longer internodes in ARNesCre males and in females , when compared with control ARLox males , should result in faster conduction velocities . However , ARLox males have thicker myelin sheaths , which reduce capacitance along internodes , thus allowing a faster propagation of action potentials . We do not know whether the thicker myelin sheaths compensate for the shorter internodes in males , nor how the sex-specific characteristics of myelin affect information processing in the brain . The analysis of conduction velocities and compound action potentials of fast conducting myelinated axons in mouse corpus callosum has so far not allowed identifying significant differences between males and females [53] . However , these measures reflect mean responses of large numbers of electrically stimulated nerve fibers . Thus , further studies are necessary to shed more light on this matter . The myelin phenotype in the corpus callosum of ARTfm males , with a nonfunctional AR in all tissues , strongly resembled the one observed in ARNesCre males , including a lower density of oligodendroglial cells , a decreased MBP expression , a smaller percentage of myelinated axons and thinner myelin sheaths with higher g-ratio values . Although in ARTfm mice , the absence of functional AR in all tissues is accompanied by endocrine abnormalities , this model has been widely used to probe the role of AR in shaping brain and behavior in rodents [54] . Most important , related mutations of the AR gene in humans , also known as complete androgen insensitivity syndrome ( CAIS ) , suggest that functional AR are required to masculinize the human brain [55] . Indeed , a recent study using diffusion tensor imaging has shown that individuals with CAIS show female-typical characteristic of white matter microstructure [56] . Although influences of postnatal androgens on myelin are long lasting , they may not be entirely irreversible . In the adult brain , myelin indeed shows structural plasticity and myelin remodeling has been proposed to participate in cognitive processes [57 , 58] . Although the majority of oligodendrocytes are generated during the first postnatal weeks in mice , Oligodendrocyte Progenitors ( OP ) remain present in the adult brain , where they continue to differentiate into oligodendrocytes and form new myelin sheaths [59 , 60] . The slow remodeling of myelin , which takes place throughout life and involves adult OP , could also be affected by the presence or absence of androgens . Thus , long-term castration of adult male mice resulted after 3 months in a more female-like phenotype of myelin characterized by fewer oligodendrocytes [61] . The role of androgens indeed goes beyond the sexual differentiation of myelin during development , as both testosterone and AR also play a key role in the regeneration of adult myelin . We have recently shown that testosterone stimulates the formation of new myelin in a mouse model of severe and chronic demyelination . In this study , we also identified the neural AR as a key target for the remyelinating actions of testosterone [36] . Of note , after severe cuprizone-induced demyelination of the corpus callosum , testosterone treatment stimulated the formation of new myelin with a male-like phenotype in both sexes [36] . Moreover , our recent study shows that after the acute demyelination of axons in the ventral white matter of the spinal cord , testosterone and a functional AR in the CNS are required for the spontaneous regeneration of myelin by oligodendrocytes [62] . Despite a greater susceptibility to multiple sclerosis ( MS ) , women have a better prognosis with respect to disability progression than men [63] [64] [65] . Sex-related differences in experimental autoimmune encephalomyelitis ( EAE ) , an accepted model of MS , are in line with these clinical observations [66] . As an explanation to this disparity , other than distinct immune mechanisms in both sexes , hormone-dependent mechanisms of neuronal resilience have been proposed [67] . The organization of the myelin sheaths may indeed impact their integrity and vulnerability to immune attacks [68 , 69] . Thus , the long-term developmental effects of androgens on myelin assembly , observed in the present work , may contribute to sex differences in the maintenance and regeneration of the myelin sheaths and their vulnerability to immune attacks . Therefore , the present observations in addition to our previous results , uncovering the efficacy of androgens as remyelinating agents [36 , 62] , provide a new conceptual framework for myelination and remyelination processes , with potential implications for demyelinating diseases such as multiple sclerosis .
All procedures were performed according to the European Communities Council Directive ( 86/806/EEC ) for the care and use of laboratory animals . All mice except the ARTfm ( testicular feminization mutation , see below ) were bred in our animal facility under a 12 hours dark/light cycle with food and water ad libitum . All mice were healthy with no obvious behavioral phenotypes , and none of the experimental mice was immune compromised . Mouse lines used in this study are the following: newborn ( P0 ) , 5 days old ( P5 ) or 10 days old ( P10 ) C57Bl/6 wild type mice and mice expressing the enhanced green fluorescent protein under the control of the proteolipid protein gene promoter PLP-EGFP [23] at P5 , P10 and adulthood . Mice of either sex were used and were randomly allocated to experimental groups . ARTfm male mice , which carry a naturally inactivating mutation of the AR , were obtained from the French Atomic Energy Commission [41] . We also generated mice lacking the androgen receptor in neural cells , using the Cre/Lox system . A mouse line carrying a floxed exon 1 of the AR gene , located on chromosome X , was provided by CIE-CERBM of IGBMC ( Pr . Pierre Chambon ) [70] . In this line , Cre recombination results in the excision of the transcription start site and deletion of the N-terminal domain of AR [33] . Female ARLox mice were crossed with male mice expressing the Cre recombinase under the control of the promoter and the CNS-specific enhancer of rat nestin [34] . In experiments involving these mice , ARLox male littermates were used as controls to maintain the same genetic background . In case of steroid injections , testosterone ( T ) , 5α-dihydrotestosterone ( 5α-DHT ) or flutamide were dissolved in sesame oil at an optimal concentration of 1 mg/ml . PLP-EGFP pups were subcutaneously injected with 20 μl of these solutions every 2 days from P0 till P10 whereas control animals were injected with sesame oil . Mice were sacrificed at P10 or at 3 months of age . Mice used for immunofluorescence studies were intracardially perfused with 4% paraformaldehyde ( PFA ) in phosphate buffer . Brains were dissected and post-fixed in the same solution for at least two days . 50μm thick sagittal slices were cut using a vibratome ( Leica ) . Slice cultures were done as described earlier [32 , 36] . Briefly , after decapitation , brains of P10 PLP-EGFP pups were dissected out into cold Gey's balanced salt solution containing 5 mg/ml glucose ( GBSS-Glu ) and meninges were removed . Cerebellar parasagittal slices ( 350 μm thick ) were cut on a MacIlwain tissue chopper and transferred onto membranes of 30 mm Millipore culture inserts with 0 . 4 μm pore size . Slices were maintained in culture in six-well plates containing 1 ml of culture medium at 35°C in a 5% CO2 atmosphere . The medium was composed of 50% basal medium with Earle's salts , 25% Hanks' balanced salts solution , 25% horse serum , L-glutamine ( 1 mM ) and 5 mg/ml glucose . The medium was changed every 2 days . Fourteen days later , cultures were fixed for one hour with 4% PFA for later immunostaining . Free-floating sections and cultured slices were processed identically for immunostaining . Slices were blocked with 0 . 1 M lysine solution in a PBS-GT buffer ( PBS buffer supplemented with gelatin and 0 . 25% Triton 100X ) for one hour and then incubated over night at 4°C with primary antibodies . Slices were then washed before being incubated with the corresponding secondary antibodies for two hours at room temperature . Processed slices were permanently mounted and pictures were taken using a Zeiss confocal microscope . For each cerebellar slice culture , three different cerebellar lobules were photographed . In brain sections , splenium , center and genu of corpus callosum were photographed . For each animal , images were analyzed using ImageJ software ( NIH ) to count oligodendrocyte cell numbers or to quantify the staining density ( area % ) in the case of MBP staining . For statistical analysis , we used the mean value of the three images per animal . The following primary antibodies were used: anti-Olig2 ( rabbit polyclonal; mouse monoclonal ) , anti-MBP ( rabbit polyclonal; mouse monoclonal; rat monoclonal ) , anti-Adenomatous Polyposis Coli ( CC1 ) ( mouse monoclonal ) , anti-Calbindin D-28K ( rabbit polyclonal ) , anti-Caspr ( rabbit polyclonal ) , anti-Neurofilament 200 ( NF200 ) ( rabbit polyclonal ) . The following secondary antibodies were used: anti-mouse Alexa488 conjugated , anti-mouse Alexa633 conjugated anti-rabbit Alexa633 conjugated , anti-rabbit Cy3 conjugated , anti-rat Cy3 conjugated . A list of antibodies used can be found in the antibodies section of the key resources and identifiers ( see below ) . Mice were perfused with phosphate buffer containing 2% PFA and 2% glutaraldehyde ( Fluka ) . Tissues were dissected and immersed in the same fixative solution at 4°C overnight , washed in phosphate buffer , postfixed in 2% osmium tetroxide , dehydrated in graded ethanol series , and embedded in epoxy resin . Semithin sections of corpus callosum ( genu ) were cut with a glass knife at ( 0 . 5–1 μm ) and stained with methylene blue/azur II . Blocks were cut with 60-nm-thickness , and were stained with 3% uranyl acetate and 0 . 5% lead citrate . Ultrastructural analyses were performed in a JEOL jem-1011 electron microscope , equipped with a Gatan digital camera . Image acquisition was performed at the Cochin Imaging Facility . The g ratio , the ratio between the axon diameter and fiber diameter ( axon diameter + myelin sheath ) was measured using ImageJ software . To evaluate axon number , myelination density and g-ratio , at least 100 axonal cross sections were evaluated for each animal at higher magnification , x15000 micrographs ( n ≥ 3 animals per group ) . At least four animals per group were sacrificed by decapitation . Brains were dissected out and the two hemispheres were separated and snap frozen using dry ice for further processing . For qPCR analysis , RNA extraction from the left hemisphere was done using RNeasy Mini kit ( Cat . No . 217004 , Qiagen , France ) according the manufactures' instructions on the left hemisphere . For mRNA quantitation , Reverse Transcription ( RT ) was performed using High Capacity cDNA Reverse Transcription Kit ( Part No 4368814 , Applied Biosystems , UK ) , according to manufacturer’s instructions . Quantitative real-time PCR ( qPCR ) was performed using Power SYBR-Green Master Mix ( ref 4367659 , Applied Biosystems , UK ) on an Applied 7300 Real-Time PCR system . Primers used were: MBP ( forward , 5'-GTACAAGGACTCACACACGAGAACTAC-3'; reverse , 5’-TTGAAGAAATGGACTACTGGGTTTT -3’ ) , AR ( forward , 5'-GACATGCGTTTGGACAGTACCA-3'; reverse , 5’-TCCACAGATCAGGCAGGTCTT-3’ ) , GAPDH ( forward , 5'-GTCGGTGTGAACGGATTTGG-3'; reverse , 5’-GACTCCACGACATACTCAGC-3’ ) , CyclophilinA ( cycloA ) ( forward , 5'-GTCAACCCCACCGTGTTCTT-3'; reverse , 5’-CTGCTGTCTTTGGGACCTTGT-3’ ) . Tissue from the right hemisphere was homogenized in cold RIPA buffer plus protease inhibitor cocktail ( Roche ) . Total protein concentration was measured using the BCA method ( Pierce , Thermoscientific ) . Proteins ( 10 μg ) were separated using a 12% polyacrylamide gel , followed by blotting onto a PVDF transfer membrane . Blots were incubated with rabbit antibody anti-myelin basic protein ( MBP , 1:2000 , AB980 , Millipore ) and with mouse antibody anti-β-actin ( A5441 , 1:5000 , Sigma ) and HRP-conjugated secondary antibodies ( A2304 and A0545 , 1:10000 , Sigma ) . Densitometry quantification was done using ImageJ software ( NIH ) . Animals were sacrificed by decapitation . Individual brains ( 60–100 mg ) from P0 , P5 and P10 male and female mice ( at least n = 7 mice ) were dissected out and the cerebella separated , weighted and stored at -20°C for further processing . Steroid levels were determined by GC-MS/MS . Extraction was performed by adding 10 volumes of methanol and internal standards were introduced for steroid quantification . Samples were purified and fractionated by solid-phase extraction with the recycling procedure . The unconjugated steroid-containing fraction was filtered and further purified and fractionated by HPLC ( Thermoscientific , USA ) . All the fractions were derivatized and analyzed by GC-MS/MS with an AI 1310 autosampler ( Thermo Fisher Scientific , USA ) . The Trace 1310 gas chromatograph is coupled with a TSQ 8000 mass spectrometer ( Thermo Fisher Scientific , USA ) . The mass spectrometer was used in tandem mode using Argon as collision gas . Injection was performed in the splitless mode at 250°C and the temperature of the gas chromatograph oven was initially maintained at 50°C for 1 min and ramped between 50 to 200°C at 20°C/min , then ramped to 300°C at 10°C/min and finally ramped to 350°C at 30°C/min . The helium carrier gas flow was maintained constant at 1 ml/min during the analysis . The transfer line and ionization chamber temperatures were 330°C and 200°C , respectively . Electron impact ionization was used for mass spectrometry with ionization energy of 70 eV . Identification of steroids was supported by their retention time and according to two or three transitions . Quantification was performed according to the more abundant transition for the calibration solutions and for the biological extracts . The analytical protocol has been validated for all steroids by using a pool of male rat brain . The precision was in the 95–105% range , the limits of quantification of 0 . 002 ng/g and the interassay variation of 5–10% . | Sex differences in brain structure are of great scientific and medical interest because the incidence and progress of many neurological and psychiatric disorders differ between males and females . They affect neural networks and also the myelin sheaths that insulate and protect axons and thus allow the rapid conduction of electrical impulses . In the central nervous system , myelin is formed by a particular type of cells named oligodendrocytes . In the male mouse brain , the density of oligodendrocytes is greater and myelin sheaths are thicker when compared with females . We show that these sex differences in myelin result from the long-lasting actions of androgens in males during their first 10 postnatal days . Importantly , the postnatal masculinizing effects of androgens involve brain androgen receptors as shown by the use of pharmacological and genetic tools . These findings are important for understanding sex-related differences in the susceptibility and progression of demyelinating diseases such as multiple sclerosis . They also reveal a so far unknown role of androgen receptor signaling in sexual differentiation of the brain . | [
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"method... | 2017 | Long-lasting masculinizing effects of postnatal androgens on myelin governed by the brain androgen receptor |
Colonization of the human nose by Staphylococcus aureus in one-third of the population represents a major risk factor for invasive infections . The basis for adaptation of S . aureus to this specific habitat and reasons for the human predisposition to become colonized have remained largely unknown . Human nasal secretions were analyzed by metabolomics and found to contain potential nutrients in rather low amounts . No significant differences were found between S . aureus carriers and non-carriers , indicating that carriage is not associated with individual differences in nutrient supply . A synthetic nasal medium ( SNM3 ) was composed based on the metabolomics data that permits consistent growth of S . aureus isolates . Key genes were expressed in SNM3 in a similar way as in the human nose , indicating that SNM3 represents a suitable surrogate environment for in vitro simulation studies . While the majority of S . aureus strains grew well in SNM3 , most of the tested coagulase-negative staphylococci ( CoNS ) had major problems to multiply in SNM3 supporting the notion that CoNS are less well adapted to the nose and colonize preferentially the human skin . Global gene expression analysis revealed that , during growth in SNM3 , S . aureus depends heavily on de novo synthesis of methionine . Accordingly , the methionine-biosynthesis enzyme cysteine-γ-synthase ( MetI ) was indispensable for growth in SNM3 , and the MetI inhibitor DL-propargylglycine inhibited S . aureus growth in SNM3 but not in the presence of methionine . Of note , metI was strongly up-regulated by S . aureus in human noses , and metI mutants were strongly abrogated in their capacity to colonize the noses of cotton rats . These findings indicate that the methionine biosynthetic pathway may include promising antimicrobial targets that have previously remained unrecognized . Hence , exploring the environmental conditions facultative pathogens are exposed to during colonization can be useful for understanding niche adaptation and identifying targets for new antimicrobial strategies .
Staphylococcus aureus is a major cause of human invasive infections ranging from superficial skin and soft tissue infections to severe disseminated diseases such as sepsis and endocarditis [1] . S . aureus is also a human commensal and part of the microbiota in healthy individuals , which facilitates its access to sterile tissues via open wounds and catheter entry sites . S . aureus can be isolated from various human body surfaces such as the pharynx , axillae and perineum but its main ecological niche and reservoir is known for long to be the human nose [2]–[4] . In contrast , coagulase-negative staphylococci ( CoNS ) , such as Staphylococcus epidermidis , have a much lower virulence potential and use different areas of the skin as their major habitats [5] . The basis of staphylococcal host and niche-specificity has remained unknown . Analysis of nasal carriage over long time periods has identified three types of S . aureus carriers [6] . About 20% of the human population can be regarded as non-carriers , who are never or only in very rare instances colonized with low bacterial numbers . In contrast , intermittent carriers show alternating periods of non-carrier status and colonisation by various S . aureus strains . The number of bacteria per isolation can be highly variable . The third group of roughly 20% persistent carriers is characterised by the presence of S . aureus in nearly all nasal swabs , usually at high bacterial numbers and with one specific strain per person over time . Recently , it has been suggested to distinguish only between carriers and non-carriers because of similar S . aureus nasal elimination kinetics and anti-staphylococcal antibody profiles in intermittent- and non-carriers [7] . Recent studies have shown that being an S . aureus carrier bears a higher risk of invasive S . aureus infections , predominantly by the carriers' own strain [8] , but a lower risk of infection-associated mortality compared to being a non-carrier [9] . The reasons for the underlying predisposition , which may involve individual differences in epithelial ligands for bacterial adhesins , local host defense , or availability of nutrients in the nose , have remained unclear . While some polymorphisms in immunity-related genes are weakly associated with the carrier status , the human predisposition appears to have multifactorial reasons [10] . On the bacterial side several factors required for nasal colonization have been identified . Wall teichoic acid ( WTA ) polymers at the staphylococcal surface [11] , [12] and cell-wall anchored proteins , such as ClfB [13] , [14] and IsdA [15] , have been found to be required for nasal colonization and adhesion to nasal epithelial cells . While the epithelial receptor for WTA is still unknown , ClfB and IsdA bind to cytokeratin 10 and loricrin , major components of human squamous epithelial cells , and IsdA also binds to the matrix protein involucrin [15] , [16] . Recently , up-regulation of WTA-biosynthetic genes tagO and tarK and of clfB and isdA during nasal colonisation has been shown in nasal swab samples from human volunteers [17] and in the cotton rat model of S . aureus nasal colonisation [18] , underscoring the importance of these factors in nasal colonization . S . aureus encounters iron-limiting conditions in the nose because isdA expression is strictly dependent on iron limitation [19] , and haemoglobin has recently been shown to promote S . aureus nasal colonization [20] . The human body can be regarded as a chemostat , where the nutrients required for bacterial growth are replenished over time and allow growth of bacteria within human microenvironments [21] . While several S . aureus nasal adhesion factors have been studied in the past , nothing is known about the growth conditions in nasal fluid such as the availability of carbon and nitrogen sources and the metabolic activities of S . aureus in its nasal habitat . Knowledge of metabolite availabilities and utilisation patterns could direct the identification of important metabolic enzymes that are essential during infection or colonization by S . aureus and could serve as targets for new antibiotics . Along this line enzymes from the folic acid biosynthetic pathway or the isoleucyl-tRNA synthetase are valuable targets for widely used anti-staphylococcal antibiotics such as cotrimoxazole or mupirocin , respectively . Mupirocin is frequently used to eliminate S . aureus from the noses of high-risk patients [22] , but the increasing resistance to mupirocin [23] and almost all antibiotics used to prevent or treat staphylococcal infections puts urgency to the development of new antimicrobial compounds . For this purpose the most critical and ‘drugable’ metabolic pathways of S . aureus need to be identified . In this study we elucidated the abundance of potential nutrients for S . aureus in the human nose by metabolomics analysis of nasal secretions . We found a high diversity but low concentrations of metabolites and no significant differences in the composition of secretions from S . aureus carriers and non-carriers . A synthetic nasal medium ( SNM3 ) was composed based on the metabolomics data . S . aureus growth in SNM3 led to similar gene expression patterns as during in vivo colonization . While S . aureus isolates grew steadily in SNM3 , CoNS did not , indicating that S . aureus is particularly well adapted to life in the human nose . Analysis of global gene expression in SNM3 revealed that the methionine-biosynthetic pathway may be a critical target for new anti-colonization drugs . In support of this notion an inhibitor of methionine biosynthesis had antimicrobial activity against S . aureus in SNM3 but not in complex media . The inhibitor's staphylococcal target gene was strongly up-regulated during human nasal colonization , and deletion of the target gene led to reduced colonisation ability of the respective mutant in the cotton rat colonisation model . Thus , deciphering the in vivo metabolism of pathogens represents a valuable strategy for defining new antimicrobial targets .
The abundance of potential nutrients in nasal secretions has never been described . In order to explore the metabolic lifestyle of S . aureus during nasal colonization , the amounts of small organic compounds in secretions from eight volunteers who were not carriers of S . aureus , were analyzed by metabolomics ( Fig . 1A , Table 1 ) . Similar amounts of amino acids and organic acids were found in the micromolar range in the eight samples . Urea was by far the most abundant organic substance at concentrations of 2 . 5–7 . 5 mM . Glucose exhibited the highest concentrations among carbohydrates with large variation between 35 µM and ca . 1 mM , while only very low amounts of other mono- or disaccharides were detected . Most of the proteinogenic amino acids and ornithine were present at average concentrations between 50 and 150 µM , while tryptophan and cysteine were detected only at very low concentrations around 10 µM . Some amino acids were not found ( methionine , glutamine , tyrosine , isoleucine , asparagine , and aspartate ) . Whereas the carboxylic acids fumarate , malate and citrate were detected at about 5–25 µM , pyruvate and succinate were usually present at much higher concentrations ( Table 1 ) . No lactate and only trace amounts of several other substances , including fatty acids , cholesterol and pyrimidines , were found ( Fig . 1B ) . To confirm the observed results and to investigate potential differences between S . aureus carriers and non-carriers , the metabolite composition in nasal secretions from six S . aureus non-carriers were compared with those from seven S . aureus carriers . The metabolite patterns of carriers exhibited a similar degree of variation as in non-carriers but no significant difference between the two groups of donors for any of the detected compounds ( Fig . 1C ) . Thus , the human S . aureus carrier status is not associated with a notable difference in nasal nutrient supply , and the metabolic activities of S . aureus do not seem to have a major impact on the overall metabolite concentrations in the nose . The average nutrient concentrations found in human nasal secretions were used to compose a synthetic medium for simulating S . aureus growth in the nose ( Table 1 ) . Amino acids and glucose were added to SNM at the upper limit of the detected concentration ranges found in the samples but not at higher amounts than twice the mean concentration values . The amounts of inorganic ions in nasal secretions have previously been described [24] , and these values served as a basis for the salt content of SNM . The synthetic medium was buffered with 10 mM phosphate buffer ( pH 7 . 2 ) , which corresponds to the previously described nasal phosphate content [25] . The concentrations of essential cofactors such as vitamins and trace elements in nasal secretions were below detection limits . Since earlier studies had shown that S . aureus requires minimal amounts of these compounds [26] , highly diluted standard vitamin and trace element solutions were included in SNM . Moreover , because recent gene expression data have shown that S . aureus encounters iron-limited conditions in the human nose [17] , iron was omitted from the trace element solution , and SNM was supplemented with 200 µM of the iron-complexing agent 2 , 2′-bipyridin , which has been shown to confer iron limitation in S . aureus [27] . The concentrations of inorganic salts , 2 , 2′-bipyridine , trace elements , and cofactors in SNM are listed in Table 2 . The community-associated methicillin-resistant S . aureus ( CA-MRSA ) clinical isolate USA300 LAC and the laboratory strain Newman were used to evaluate if S . aureus is able to grow in SMN . Despite the very low amount of 238 mg amino acids per liter , both strains showed reproducible but moderate growth in SNM . This is in agreement with the rather low bacterial numbers found in swabs from the human nose [28] . In contrast , much higher bacterial densities have been found in microbiomes which are in contact with ingested food e . g . in the human mouth or gut [29] , [30] . When we increased the concentration of amino acids , organic acids and glucose in SNM , the maximal bacterial densities also increased until they reached a plateau at approximately 20-fold nutrient concentration for S . aureus USA300 ( Fig . 2A ) . Because epithelial secretions are continuously produced and removed , nutrient concentrations should remain more or less constant at the surface of nasal tissues , while they are continuously decreasing in a test tube culture . In agreement with this notion S . aureus Newman reached 2 . 4-fold higher bacterial numbers when grown in SNM in a continuous flow system compared to static SNM ( Supplementary Figure S1 ) . Because several of the subsequent experiments involved growth on SNM agar plates or in multiple parallel cultures , which could not be performed in a continuous flow system , we used SNM with threefold increased amino acid , organic acid and glucose concentration ( SNM3 ) in subsequent experiments . In order to validate the capacity of SNM3 to simulate living conditions for staphylococci in the human nose , 87 different staphylococcal strains from the anterior nares of 37 human volunteers were isolated , and growth of the corresponding 18 S . aureus , 57 S . epidermidis , and 12 other CoNS strains ( Staphylococcus capitis , Staphylococcus lugdunensis , Staphylococcus warneri , Staphylococcus hominis ) in SNM3 was compared . All S . aureus grew in SNM3 liquid cultures without long lag-phases and reached their highest densities after about 12 . 5 hours ( Fig . 2B ) . When serial dilutions of the same strains were spotted on SNM3 agar , which should correspond better to the sessile lifestyle on the nasal epithelial surface than liquid SNM3 , identical CFUs as on complex medium agar ( basic medium , BM ) were found for all S . aureus except for two strains ( Fig . 3A ) . This indicates that SNM3 offers efficient growth conditions for the vast majority of nasal S . aureus strains . In contrast , most of the S . epidermidis and other CoNS grew in liquid SNM3 only after long lag-phases and often with much longer generation times compared to S . aureus ( Fig . 2B ) . Moreover , only a very small percentage of cells ( one to ten out of a million viable cells ) of the S . epidermidis and other CoNS strains were able to form colonies on SNM3 agar ( Fig . 3A ) . This property appeared to be a stable trait because sub-cultivation of such outgrowing clones resulted in much higher numbers of colonies on SNM3 compared to the parental clones ( data not shown ) . Hence , most S . aureus appear to be metabolically well adapted to life in the human nose , whereas the vast majority of CoNS exhibited arrested growth with only a small minority of cells starting multiplication on SNM3 agar . These differences reflect recent findings that the nose of permanent S . aureus carriers usually contains substantially lower numbers of CoNS than S . aureus [7] , [31] . To investigate if S . aureus is simply better adapted to dilute nutrient concentrations than CoNS , a selection of strains , whose ability to form colonies on SNM3 was in the median range , was tested for colony formation on SNM agar with three , five , ten , and twenty-fold concentrated nutrients . As shown in Figure 3B , concentrating nutrients in SNM agar plates ten to twenty-fold improved the outgrowth of most of the tested S . epidermidis and some other CoNS strains , but only some strains reached similar growth capacities as S . aureus , while most formed colonies at several magnitudes lower numbers than S . aureus even at the highest nutrient concentrations . Thus , CoNS appear to be much less capable of adapting to diluted nutrient concentrations than S . aureus and exhibit enormous intra-species variation in their capacities to grow on SNM3 agar , even when nutrient concentrations were strongly increased . Two recent studies have described if and how efficiently critical S . aureus genes are transcribed during nasal colonization of humans or cotton rats [17] , [18] . In order to evaluate if growth in SNM3 leads to similar transcriptional profiles as found during in vivo colonization , we compared marker gene expression of S . aureus USA300 actively growing in SNM3 or BM by quantitative RT-PCR ( qRT-PCR ) ( Fig . 4 ) . Bacteria grown to stationary phase in BM ( BM-stat ) were also included because this growth condition has recently been used to assess intranasal expression of relevant S . aureus marker genes [17] , [18] . The global virulence regulator RNAIII , which responds to the concentration of a secreted agr autoinducer peptide ( quorum sensing ) , and the agr-controlled psmß have been shown to be only moderately expressed in the nose [17] , [18] , and artificial induction of the RNAIII transcript reduces the nasal colonization capacity of S . aureus in the cotton rat model [20] . These previous findings corresponded to the low expression of RNAIII and psmß in BM and SNM3 compared to expression in BM stat . Also , the keratin-binding adhesin gene clfB was expressed in SNM3 at a similar level as in growing BM cultures , corresponding to the expression profile found recently in human noses [17] . Moreover , expression of the iron-regulated isdA and the lytic transglycosylase gene sceD , found to be up-regulated in the nose compared to BM or BM-stat cultures [17] , [18] , was also enhanced in SNM3 . Taken together , these data indicate that the composition of SNM3 provides suitable conditions for in vitro simulation of S . aureus growth and gene expression in the nasal habitat . SNM3-grown S . aureus cultures enabled us to monitor global gene expression under conditions reflecting nasal colonization and to compare these with expression profiles from previous studies , which have usually used S . aureus grown in complex media . RNA from S . aureus USA300 , actively growing either in SNM3 or BM , was hybridized to Affymetrix microarrays and analyzed with respect to basic cellular and metabolic pathways ( data deposited under GEO Series accession number GSE43712 ) . Multivariate data analysis was used to show differences or similarities between the transcriptomic data . Principal component analysis ( PCA ) confirmed that the three biological replicates performed for each of the two conditions led to very reproducible results , with substantial differences in SNM3 or BM-derived transcription profiles and a PCA mapping value of 77 . 7% ( Fig . 5A ) . Expression of 521 signals corresponding to 341 genes differed more than two-fold upon growth in SNM3 vs . BM with p-values below 0 . 05 ( Fig . 5B ) . Thus , complex media represent a very artificial situation for S . aureus that differs profoundly from colonization-related conditions . A total of about 12 . 6% of the genes categorized in the “Clusters of Orthologous Groups of proteins” ( COG ) database [32] as being involved in “cellular processes and signalling” ( Fig . 5B ) showed more than two-fold expression differences between the two growth conditions , with 22 genes being up- and only six down-regulated . Most pronounced in this group was the two- to threefold higher expression of various capsule biosynthesis genes ( functional category M ) in SNM3 compared to BM ( Supplementary Fig . S2 ) . This finding is in agreement with the crucial role of the capsule in S . aureus nasal colonization recently shown in a rodent model [33] . The up-regulated signals also included the genes for the iron-regulated IsdC surface protein and the osmoprotectant system OpuCC and OpuD . In the group of genes categorized for “information storage and processing” 10 . 6% of the genes were differentially expressed , 13 genes were up- and 20 down-regulated including various transcriptional regulators . As expected , most of the major differences were found among genes governing the central “metabolism” ( 26 . 6% of all genes assigned to this group ) , in which 54% of all genes from the functional group E ( “amino acid transport and metabolism” ) differed more than twofold in expression between the chosen growth conditions . Here , 79 genes were up- and only three down-regulated in SNM3 compared to BM ( Supplementary Fig . S2 ) . Significant up-regulation of amino acid biosynthesis genes was observed for glutamate , histidine , lysine , valine , leucine , isoleucine and methionine in SNM3 compared to BM . Remarkably , all of these amino acids , except for methionine and isoleucine , are integral components of SNM3 . Whereas isoleucine can easily be generated from threonine , methionine has to be synthesized from aspartate , which was also not detectable in nasal secretions and therefore was not included in SNM3 . Via O-acetyl-L-homoserine , aspartate reacts in a transsulfuration reaction with cysteine to form L-cystathionine and L-homocysteine ( Fig . 6 ) . The genes for cystathionine-γ-synthase ( metI , SAUSA300_0360 ) and cystathionine-β-lyase ( metC , SAUSA300_0359 ) , whose gene products are responsible for these enzymatic reactions , were 26- to 32-fold up-regulated and exhibited the strongest up-regulation of all genes in SNM3 . Among the methionine-biosynthetic genes those for MetE ( 5-methyltetrahydropteroyltriglutamate-homocysteine S-methyl-transferase ) and its homologue MetF SAUSA300_0358 ( bifunctional homocysteine S-methyltransferase ) , responsible for the conversion of L-homocysteine to L-methionine , were 13 to 14-fold up-regulated . The strong up-regulation of two L-methionine ABC-transport systems ( SAUSA300_0435-0437 and SAUSA300_0796-0798 ) underscored the importance of methionine supply during growth in SNM3 . In addition to the biosynthetic operons of the above mentioned amino acids , many ABC-type dipeptide/oligopeptide ( opp genes ) as well as metal ion transporters ( especially for iron-siderophores ) , were strongly up-regulated in SNM3 ( Supplementary Fig . S2 , functional category P ) . The presence of iron-limiting conditions in SNM3 was reflected by distinct up-regulation of the operon for biosynthesis of staphyloferrin B ( also called staphylobactin , sbnABCDEFGHI; SAUSA300_0118 to SAUSA300_0126 ) , a potent siderophore facilitating the extraction of iron from human transferrin [34] . The ferric uptake regulator ( Fur ) controls the expression of iron-regulated genes via binding to a consensus sequence in the promoter regions in staphylococci [35] . Besides the sbn operon additional Fur-regulated genes and operons , as listed at the RegPrecise regulon site ( http://regprecise . lbl . gov/RegPrecise/regulon . jsp ? regulon_id=6608 ) , exhibited slightly to moderately altered expression in SNM3 compared to BM . These included the isd genes ( iron-regulated surface determinant system; also called sir; staphylococcal iron-regulated proteins ) and those for the ferritin storage protein , the TatAC system and the ferrichrome ABC-transporter SstABCD ( supplementary Figure S3 ) . To evaluate the validity of the microarray results , gene expression of selected S . aureus USA300 genes , which were strongly up-regulated in SNM3 , was reinvestigated by qRT-PCR . Besides metI ( methionine biosynthesis; SAUSA300_0360 ) and the methionine transporter gene metN ( SAUSA300_0435 ) , expression was analyzed for hisC ( histidine biosynthesis; SAUSA300_2610 ) , aspartate kinase ( SAUSA300_1225 ) , oligopeptide transporter oppB ( SAUSA300_0201 ) and staphyloferrin B biosynthesis gene sbnC ( SAUSA300_0120 ) . As shown in Figure 7 , all of the investigated genes exhibited significant up-regulation in SNM3 compared to BM , thereby confirming the microarray data . The strong expression of methionine-biosynthetic genes prompted us to investigate if the absence of methionine is significantly limiting the growth of S . aureus USA300 in SNM3 . However , the step-wise increase of methionine in SNM3 had no effect on colony formation on SNM3 agar ( Fig . 3C ) and only a marginal impact on S . aureus growth in liquid SNM3 ( data not shown ) . Hence , methionine limitation does not compromise S . aureus growth , probably as a result of efficient ways to synthesize methionine . We also investigated if methionine limitation might be a reason for the inefficient outgrowth of CoNS on SNM3 agar . For this purpose , we analyzed colony formation of various nasal CoNS isolates and the laboratory strain S . epidermidis 1457 on SNM3 agar with increasing methionine concentrations ( Fig . 3C ) . However , even high methionine amounts of 100 µM increased colony formation of S . epidermidis and CoNS strains only slightly , and only a small minority of strains benefitted strongly from the addition of methionine . This finding suggests that the inability of CoNS to thrive on SNM3 agar is probably the result of complex differences in the metabolic or regulatory properties of S . aureus and CoNS . In order to analyze the importance of the capacity of S . aureus to synthesize methionine , the gene of the methionine-biosynthetic enzyme MetI was inactivated in S . aureus Newman . The resulting mutants showed no growth defects in complex medium . However , they were completely unable to grow in SNM3 , while addition of methionine restored growth of the mutants , thereby demonstrating a crucial role of MetI under colonization-related conditions ( Supplementary Fig . S4 ) . Antimicrobial targets for new decolonization drugs are urgently needed because of increasingly emerging mupirocin resistant S . aureus [23] . The synthetic compound DL-propargylglycine has been shown to inhibit the bacterial cytathionine-γ-synthase MetI leading to a block of methionine biosynthesis [36] . We hypothesized that it may have antimicrobial activity against S . aureus under conditions where MetI plays a crucial role . DL-propargylglycine hardly affected growth of S . aureus USA300 in BM ( minimal inhibitory concentration , MIC>10 mg/ml ) , whereas it inhibited growth of all tested S . aureus strains in SNM3 ( Table 3 ) . These data suggest that MetI inhibitors might in fact be useful to limit the growth of S . aureus in vivo . Supplementation of SNM3 with methionine abrogated the antimicrobial activity of DL-propargylglycine ( MIC>10 mg/ml ) confirming that DL-propargylglycine inhibits S . aureus growth by blocking an indispensable step of methionine biosynthesis . In order to analyze if the critical genes found to be up-regulated by S . aureus USA300 in SNM3 vs . BM exhibit similar expression profiles during nasal colonization , their transcription was measured> by qRT-PCR in nasal swabs from six documented S . aureus carriers . Their corresponding nasal S . aureus strains were subsequently grown in SNM3 and BM for RNA isolation , and all samples were analyzed by qRT-PCR ( Fig . 8 ) . For some samples expression of certain genes was not detectable , possibly as a result of sequence variation at primer binding sites or low RNA concentrations . The expression patterns in SNM3 and in vivo were overall very similar , and none of the analyzed genes exhibited significant differences in vivo and in SNM3 compared to BM . Gene expression in the six nasal isolates was generally more variable in vivo than in SNM3 , suggesting that some parameters of the nasal living conditions may vary to a certain extent between donors . In most of the samples isdA , sceD , and oppB expression analysis confirmed up-regulation in vivo and in SNM3 compared to BM . While all strains that yielded detectable qRT-PCR signals for aspartate kinase and hisC were consistently up-regulated in SNM3 compared to BM , this was only found in some of the in vivo samples . This variability indicates that in vivo expression of these genes depends on the individual host . Expression of sbnC was high in SNM3 and in vivo compared to complex medium , confirming that iron-limiting conditions were indeed present under both conditions . Notably , expression of metI was strongly up-regulated in SNM3 compared to BM in all six strains ( median about 100-fold , Fig . 8 ) , and the in vivo metI expression was nearly the same as in SNM3 . Cotton rats have been shown to be a suitable model for S . aureus nasal colonization [11] , [37] . When S . aureus Newman and the isogenic ΔmetI mutant were used to inoculate the noses of cotton rats , a strongly reduced colonization capacity of the mutant was observed compared to the parental strain ( Figure 9 ) . Thus , MetI has a critical role during nasal colonization , and the methionine-biosynthetic pathway may include previously unrecognized targets for new antimicrobial strategies .
The metabolomics analysis of nasal secretions reveals that the human nose represents an environment with rather limited nutrient availability . The concentrations of glucose and amino acids are substantially lower in nasal secretions compared to human plasma of healthy individuals ( glucose about 0 . 04–1 mM vs . 4–8 mM; amino acids about 0 . 65–2 . 2 mM vs . 2 . 6 to 4 . 3 mM , respectively ) [38] . The sputum covering lung epithelia of cystic fibrosis ( CF ) patients , which are frequently infected by S . aureus [39] , [40] , contains similar concentrations of glucose and even higher concentrations of free amino acids than plasma ( 1 . 3 to 4 . 5 mM and 4 . 7 to 24 . 7 mM , respectively [41] . These differences in nutrient availability suggest that S . aureus requires different metabolic activities during colonization of the human nose or infection of sterile tissues . It is interesting to note that lactate , an abundant compound on skin with concentrations around 2 . 5 mM [42] and a product of S . aureus energy metabolism [43] , was undetectable in nasal secretions . Accordingly , metabolites in the nasal habitat differ from those on skin , and S . aureus metabolism does not seem to affect much the nasal metabolome . Our data indicate that the concentration of many nutrients in nasal secretions varies between donors , but none of the differences could be associated with the S . aureus carrier status . Thus , factors other than nutrient supply , such as differences in epithelial immunity or ligands for S . aureus adhesins , may be responsible for the predisposition to the S . aureus carriage status . Various chemically defined media have been developed over the past decades with the purpose to achieve maximal growth and high capsule or protein expression in S . aureus [44]–[47] . In contrast , our aim was to simulate the in vivo situation in the human nose , to use a representative synthetic nasal medium for comparing colonization capacities of different staphylococcal strains and to elucidate colonization-related bacterial metabolic processes . Expression profiles of representative S . aureus genes upon growth in the artificial nasal medium SNM3 corresponded well to those found in the human nose indicating that SNM3 provides suitable conditions for simulating S . aureus growth during nasal colonization . Of note , global transcriptomes of bacteria from SNM3 and complex media differed extensively indicating that complex media can hardly reflect in vivo-related gene expression . In accord with this finding , transcriptome data of S . aureus grown in human blood and serum have also yielded major differences compared to previously described expression profiles from complex-media grown bacteria [48] , [49] . Thus , SNM3 will allow to investigate bacterial metabolic processes during nasal colonization in detail and to monitor S . aureus competition with other resident bacteria under in vivo-like conditions . Nevertheless , results obtained with SNM3 in genome-wide in vitro experiments should be validated in in vivo models . In accordance with the limited nasal nutrient supply , the human nasal microbiome has been shown to be much less complex [31] , [50] than those of the upper or lower digestive tract , where bacteria are in regular contact with ingested food [30] , [51] . Hence , bacteria in the human nose can be expected to compete fiercely for available nutrients and depend on mechanisms allowing them to thrive even with very low amounts of nutrients . In line with this notion all tested nasal S . aureus isolates grew well in SNM3 , and almost all viable cells formed colonies on SNM3 agar . S . aureus is obviously adapted to growth in moist environments with very dilute nutrients , while human skin is usually dry except for atopic dermatitis patients , whose skin structure and permeability is severely perturbed [52] . In contrast , CoNS colonize healthy skin as their major habitat [53] , which is in accordance with our finding that most of the tested CoNS isolates had major problems to form colonies on SNM3 agar and grew in liquid SNM3 only after long lag phases . It has remained unclear if CoNS use the human nose as a preferred or only as a transient habitat . While permanent S . aureus carriers are usually colonized by one specific single clone , multiple S . epidermidis strains can be found per nose and the pattern of strains is highly variable over time [54] . Our results indicate that CoNS are usually much less adapted to growth in nasal secretions than S . aureus . In line with our data a recent study has found a negative association between the colonisation with S . aureus and the abundance of S . epidermidis . It has been speculated that these bacterial species compete with each other during colonization of the nares [31] . Our data supports the notion that most S . aureus strains can overgrow CoNS because of better metabolic adaptation . In addition to differences in the abilities to utilize dilute nutrients , competition between S . aureus and CoNS may also involve different capacities to produce bacteriocins such as lantibiotics [55] , [56] , to induce and resist host antimicrobial peptides such as defensins [57] , which have been detected in nasal secretions [58] , and to produce factors that compromise the ability of other staphylococci to adhere to epithelial surfaces such as the S . epidermidis Esp protease [59] . Metabolomics analyses have been proposed to facilitate the identification of new antimicrobial targets and have recently helped to define the staphylococcal pyruvate dehydrogenase as a target for a new class of organobismuth antimicrobials [60] . We demonstrate here that a combined metabolomics and transcriptomics approach can lead to the identification of targets that are specifically important during in vivo-like conditions . Gene expression analysis of S . aureus grown in SNM3 , or from in vivo samples , revealed that various amino acid biosynthesis operons are up-regulated during colonization . This implies a general importance of several anabolic pathways under such conditions . Since SNM3 does not contain isoleucine , it can be assumed that the global transcription repressor CodY plays an important role for the up-regulation of a number of genes under the conditions used for microarray experiments , especially those for isoleucine biosynthesis [61] , [62] . It has recently been shown that CodY also influences S . aureus metICFE-mdh expression , which is essentially regulated by a T-box riboswitch that recognizes uncharged initiator tRNAfMet [63] . Despite the obvious influence of CodY on the gene expression pattern no clear signs of stringent response , like down-regulation of ribosomal protein rpsL , could be detected [64] . The absence of methionine in nasal secretions and SNM3 was reflected by the strong up-regulation of S . aureus methionine import and , most conspicuously , methionine biosynthesis genes in SNM3 and in the noses of human volunteers . In a similar approach , metabolomics analysis of sputum from CF patients has recently allowed to develop a synthetic sputum medium , leading to the unexpected finding that Pseudomonas aeruginosa depends on L-alanine as carbon source during CF lung infections . Furthermore , the high concentrations of aromatic amino acids in CF-sputum and the corresponding synthetic medium have been implicated in high-level production of pyocyanin [41] , [65] . This cytotoxic respiratory inhibitor is important in competition of P . aeruginosa with S . aureus in the CF lung , since the latter is strongly inhibited because of its pyocyanin-sensitive cytochrome bd oxidase [66] . The methionine biosynthetic enzymes fulfil important criteria for antimicrobial drug targets , because they are absent from human cells that need to take up methionine from exogenous sources . However , such enzymes have hardly been regarded as antimicrobial targets before , because their importance has probably been missed when growing bacteria in complex media in antimicrobial screening programs . Nevertheless , this pathway has recently been proposed as a potential staphylococcal “Achilles heel” [63] . In our study the synthetic compound DL-propargylglycine , described as an inhibitor of cystathionine-γ-synthase ( MetI ) , which is unique to microorganisms and plants [36] , [67] was used . The activity of DL-propargylglycine against S . aureus and the inability of metI mutants to grow in SNM3 underscore the potential use of MetI or other methionine-biosynthetic enzymes as targets for new nasal decolonisation drugs . These drugs could be alternatives to eradicate e . g . mupirocin-resistant S . aureus . In agreement with this notion , the S . aureus metI gene was strongly upregulated in human noses , and the metI mutant was compromised in nasal colonization of cotton rats . However , DL-propargylglycin itself does not seem to be suitable as a drug , because it also inhibits the human cystathionine-γ-lyase . This enzyme converts exogenous methionine to cysteine via the transsulfuration pathway [68] , [69] , leading to reduced production of the gaseous messenger molecule hydrogen sulfide with various eminent consequences [70] . While the rather low activity against S . aureus and the severe impact on mammalian metabolism precluded the use of DL-propargylglycine in animal models , derivatives or new compounds with higher selectivity and activity against bacterial MetI or other methionine-biosynthetic enzymes may become promising lead substances for the development of new antimicrobial drugs . Notably , all these enzymes were significantly up-regulated in SNM3 ( Fig . 6 ) .
The nasal secretion study and sample collection procedures were approved by the clinical ethics committee of the University of Tuebingen ( No . 109/2009 BO2 ) and informed written consent was obtained from all volunteers . Secretion samples and nasal swabs were taken exclusively from healthy adults . The staphylococcal laboratory strains used in this study are S . aureus USA300 LAC [71] , S . aureus Newman [72] , and S . epidermidis 1457 [73] . Beside these characterised strains a set of 87 staphylococcal isolates from nasal swabs from 37 healthy volunteers were used . The collection of nasal isolates includes 18 S . aureus , 57 S . epidermidis , six S . capitis , three S . lugdunensis , two S . warneri and one S . hominis strain . Identification was accomplished according to an established scheme [74] by sequencing of a variable ca . 931-bp PCR fragment of the glyceraldehyde-3-phosphate dehydrogenase gene ( gap ) , amplified with primer pair gap-F and gap-R ( Table S1 ) . Ambiguities were clarified by additional sequencing of a variable part of the dnaJ gene , amplified with primer pair dnaJ-F and dnaJ-R ( Table S1 ) . BM ( 1% tryptone , 0 . 5% yeast extract , 0 . 5% NaCl , 0 . 1% glucose and 0 . 1% K2HPO4 , pH 7 . 2 ) was used as standard complex medium . The composition of the chemically defined medium SNM , corresponding to nasal secretions , is listed in Tables 1 and 2 . The content of inorganic ions in human nasal secretions listed in Table 1 has been published earlier [24] , [25] and the described buffer , salt and co-factor concentrations were included in SNM as listed in Table 2 . In contrast to the published data calcium was omitted from the medium , because it led to precipitates . Trace elements and cofactors were added from 1000-fold concentrated stock solutions . The iron-complexing agent 2 , 2′-bipyridine ( Merck , Darmstadt , Germany ) was added at a final concentration of 200 µM . SNM3 contained the same concentrations of inorganic salts , urea , trace elements , and cofactors as SNM while amino acids , organic acids , and glucose as listed in Table 1 were threefold concentrated . BM and SNM agar plates contained 1 . 5% agar . For growth curves bacteria from overnight cultures grown in BM were centrifuged , washed with PBS , and diluted in SNM3 to an initial OD600 nm of 0 . 02 in microtiter plates ( MTP ) and grown in a TECAN Infinite 200 PRO reader ( Tecan Group Ltd . , Switzerland ) with shaking ( 180 rpm ) at 37°C with continuous measurement of optical densities . For MIC determination 24-well MTP plates , essentially inoculated as described above , were grown for 48 hours at 37°C and 160 rpm . For the calculation of growth , inoculation density was subtracted from final optical density and the MICs , defined as the concentration of DL-propargylglycine ( Sigma-Aldrich , Taufkirchen , Germany ) at which 75% growth inhibition occurred , were calculated . For monitoring bacterial growth in three to 20-fold SNM cultures 12-ml medium in 100-ml buffled Erlenmeyer flasks were inoculated with an SNM3 over-night culture to an initial OD578 nm of 0 . 02 and incubated with vigorous shaking at 160 rpm at 37°C , until the final OD578 nm was determined after 90 h growth . For RNA isolation all media were inoculated with SNM3 overnight cultures , grown at 37°C with vigorous shaking at 160 rpm in 250-ml buffled Erlenmeyer flasks . For continuous cultures sterile fresh medium was added from a reservoir to the growing culture with a peristaltic pump . A second pump was used to remove consumed medium , including bacteria , from the culture . 100 ml SNM in 500-ml glass bottles ( Schott ) were inoculated to an OD578 nnm of 0 . 02 and incubated with shaking at 140 rpm at 37°C with a sterile filter in the bottle lid to allow aeration . About 4 ml fresh medium were added and simultaneously removed from the culture per hour resulting in exchange of the complete culture volume within approximately 24 hours . Non-continuous batch cultures were performed in the same way , except that continuous medium exchange was omitted . Nasal secretions were taken with the help of slight vacuum suction with suction catheters ( model 14 Ch , Bicakcilar Healthcare Products , Turkey ) mounted on sputum collection traps ( P . J . Dahlhausen & Co . GmbH , Germany ) . After short centrifugation the samples were immediately frozen at −80°C . Metabolites from frozen nasal secretions were extracted with methanol/chloroform/water 4/4/2 . 85 after addition of internal standards ( ribitol and norvaline ) , samples were vortexed twice for 10 s and then centrifuged ( 4°C , 10 min , 13000 rpm ) . Supernatants were transferred to new glass vials and dried by lyophilisation . Dry samples were derivatized for GC-MS analyses and measured according to a previously described method [75] . Briefly , metabolites were identified by matching retention time and identification ion of pure chemical standards , measured under the same conditions . Ratios of peak areas to the respective internal standard ( ribitol ) were used for absolute and relative quantification . Calibration curves of pure substances were measured over a wide range of concentrations under the same conditions and were used for the calculation of the total , micromolar metabolite concentration . Because arginine is unstable when derivatized for GC-MS , its content was determined by HPLC using ortho-phthaldehyde ( OPA ) pre-column derivatization . OPA was diluted to a final concentration of 1 mg/ml with 1 M sodium-borate-buffer , pH 9 . 0 . Nasal secretion samples were sonicated for 20 s in a sonication water bath to reduce viscosity and diluted 1∶1 with distilled water . Subsequently , each sample ( 6 µl ) was mixed with 1 . 5 µl OPA for 90 s and immediately injected and separated on an Agilent 1200 series HPLC-system using a Grom-SIL OPA-3 ( 5 µm ) , 4 . 0×150 mm column ( Grace Davison , Lokeren , Belgium ) . A linear gradient from 100% buffer A ( 25 mM sodium-phosphate buffer , 0 . 7% tetrahydrofuran , pH 7 . 2 ) to 100% buffer B ( 50% buffer A , 35% methanol , 15% acetonitrile ) in 24 min was run at a flow rate of 1 . 1 ml/min . Arginine was detected at 450 nm and quantified against a standard calibration curve with arginine concentrations of 10 µM , 100 µM , 1 mM , and 10 mM . Data were analyzed by Agilent ChemStation software . Relative abundance is given in cases were no dilution series of pure standard compounds was measured . Data analysis was performed within the GC-MS software Chemstation ( Vers . E . 02 . 00 Service Pack 2 , Agilent ) . Statistical analysis was accomplished with Aabel 3 . 0 . 4 ( Gigawiz ) and SIMCA P+ 12 . 0 . 1 , for principal component analysis ( PCA ) , and for partial least square ( PLS ) analysis log-transformed peak areas with UV scaling were used . For qRT-PCR 40-ml cultures were inoculated to an optical density of 0 . 02 at 578 nm ( ca . 2×107 CFU/ml ) and grown for three hours . RNA was isolated by a modified protocol of Bhagwat et al . adapted to large culture volumes [76] . Briefly , cells were immediately killed and RNA was stabilized by the addition of 1/9 vol . of an ice-cold 9∶1 ethanol∶phenol solution ( equilibrated with Tris/EDTA-buffer ( TE ) ; Applichem , Darmstadt , Germany ) . After 5 min on ice cells were harvested ( 20 min , 4500×g , 4°C ) , resuspended in 1 ml TRIZOL solution ( Invitrogen - Life Technologies Corporation , Darmstadt , Germany ) , and lysed with 0 . 5 ml zirconia-silica beads ( Karl Roth GmbH , Karlsruhe , Germany; 0 . 1 mm-diameter ) in a high-speed benchtop homogenizer ( FastPrep-24 , MP Biomedicals , Germany ) . Subsequently , RNA was isolated as described in the instructions provided by the manufacturer of the RNA isolation kit ( ExpressArt RNAready , AmpTec GmbH , Germany ) . In order to get rid of potential RT-PCR inhibitors , a first washing step with 0 . 5 ml ‘Inhibitor removal buffer’ was applied ( High Pure PCR Template Preparation Kit , Roche Applied Science ) . DNA was removed by on-column DNAse treatment according to the ExpressArt RNAready protocol . RNA for microarrays was isolated from 100-ml cultures , inoculated to an OD578 nm of 0 . 005 and grown until OD578 nm of 0 . 02 . RNA was stabilized as described above by ethanol∶phenol addition . After centrifugation , the cell pellet was washed with 2 ml ice-cold ethanol∶acetone ( 1∶1 ) to remove phenol traces . A second washing and stabilisation step was applied by resuspending the cells in 2 ml RNAprotect bacteria reagent ( QIAGEN GmbH , Germany ) ∶TE-buffer ( 2∶1 ) . After centrifugation cells were lysed in 100 µl TE buffer containing 10 µl lysostaphin ( 2 mg/ml , Genmedics GmbH , Germany ) by incubation for 3 min at room temperature . After the addition of 350 µl RLT buffer ( RNeasy Kit , QIAGEN GmbH , Germany ) cells were lysed with 0 . 2 ml zirconia-silica beads as described above and RNA was purified with the RNeasy Kit according to the manufacturer's instructions . RNA for qRT-PCR from nasal swabs was isolated essentially as described above for in vitro cultures . The cotton swabs ( MSP Schmeiser , Horb , Germany ) were soaked in sterile PBS and used to carefully wipe the anterior nares of volunteers and afterwards directly resuspended in 1 ml TRIZOL . For confirming the carrier status additional swabs were taken , resuspended in PBS , and serial dilutions were plated on BM agar . The presence of S . aureus was confirmed with the Slidex Staph Plus latex agglutination test ( bioMérieux Deutschland GmbH , Nürtingen , Germany ) according to the manufacturer's instructions . Since some of the volunteers had quite low numbers of S . aureus in their nose ( <1 . 000 S . aureus/swab ) , the isolated RNA amounts were sometimes not sufficient for qRT-PCR . In such cases RNA was amplified once with the ‘Bacterial Nano mRNA amplification Kit’ ( AmpTec GmbH , Hamburg , Germany ) as described by the manufacturer . Relative quantification of various transcripts was performed as described previously [18] . Briefly , isolated RNA from cultures and nasal swabs was transcribed into complementary DNA using SuperScriptIII Reverse Transcriptase ( Invitrogen ) and 200 ng of random hexamer primers ( Fermentas , St . Leon-Rot , Germany ) . For relative quantification standards were generated by PCR with the primers listed in Table S1 with S . aureus USA300 genomic DNA as template . All agarose gel-purified PCR products were used in 10-fold serial dilutions . For the genes metN and sbnC PauI ( Fermentas ) -digested and purified chromosomal DNA of S . aureus USA300 was used as standard . Complementary DNA was diluted 1∶10 and quantitative real-time PCR ( qRT-PCR ) was performed with primers listed in Supplementary Table S1 , using the LightCycler instrument ( LightCycler 480 , Roche ) in combination with SYBR Green I ( QuantiFast SYBR Green PCR Kit , QIAGEN ) . Master mixes were prepared according to the manufacturer's instructions . Relative gene expression level was calculated by the method of Pfaffl with PCR efficiency correction [77] . 5 µg of RNA from three biological replicates per condition were applied to GeneChip microarrays ( Affymetrix ) and processed according to the manufacturer's protocol . The biological replicates yielded highly reproducible expression profiles . The GeneChip S . aureus genome array was provided by MFTServices ( www . mftservices . de ) , a Core Lab provider authorized by Affymetrix Inc . ( Santa Clara , CA ) . GeneChip hybridization , washing , staining , and scanning were performed as described by the manufacturer . The images were processed with Expression Console ( Affymetrix ) . The raw data from the array scans were normalized by median-centering genes for each array , followed by log transformation . Expressed genes were identified using Affymetrix GeneChip Operating Software ( GCOS , Ver . 1 . 1 ) . To identify genes that are differentially expressed in treated samples compared to controls , the Partek software version 6 . 6 was used . To select the differentially expressed genes , we used threshold values of ≥2 . 0- and ≤−2 . 0-fold change between the conditions . The false discovery rate ( FDR ) significance level with Benjamini-Hochberg was <5% . The data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus [78] and are accessible through GEO Series accession number GSE43712 ( http://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE43712 ) . For the construction of a markerless mutant of S . aureus Newman , the flanking regions of metI were amplified with primer pairs cgsF1 up/cgsF1 down or cgsF2 up/cgsF2 down . After digestion of PCR product F1 with EcoRI/BglII and of PCR product F2 with BglII/NheI the two fragments were ligated into the previously described vector pBASE6 [64] , digested with EcoRI and NheI and used to transform E . coli DC10B [79] . The resulting plasmid pBASE6-ΔmetI was isolated and directly transferred to S . aureus Newman , where the homologous recombination process resulted in metI mutants , which were confirmed by PCR analysis . For the colonisation of cotton rats spontaneous streptomycin-resistant mutants of S . aureus Newman wild type and ΔmetI were selected on BM agar plates with 500 µg/ml streptomycin . The cotton rat model was used as described earlier [11] . Cotton rats were anesthetized and instilled intranasally with 10 µl of 1×108 colony-forming units ( CFU ) of S . aureus . Six days after bacterial instillation the animals were euthanized and noses were removed surgically . The noses were vortexed in 1 ml of PBS containing 0 . 5% Tween for 30 s . Samples were plated on appropriate agar plates ( B-medium , sheep blood containing 250 µg/ml streptomycin and HiCrome Aureus Agar ( Fluka ) ) and the bacterial CFU was determined . All animals received drinking water with 2 . 5 mg/ml streptomycin continuously , starting three days prior to the experiment to reduce the natural nasal flora . All animal experiments were conducted in accordance with German laws after approval ( protocol T1/10 ) by the local authorities ( Regierungspraesidium Tuebingen ) . | Many severe bacterial infections are caused by endogenous pathogens colonizing human body surfaces . Eradication of notorious pathogens such as Staphylococcus aureus from risk patients has become an important preventive strategy . However , efficient decolonization agents are rare , and the living conditions of colonizing pathogens have hardly been studied . Using a combined metabolomics and transcriptomics approach , we explored the metabolism of S . aureus during colonization of its preferred niche , the human nose . Based on nasal metabolite profiles , a synthetic nasal medium ( SNM3 ) was composed , enabling steady growth of S . aureus but not of staphylococcal species preferentially colonizing the human skin . Marker gene expression was similar in SNM3 and the human nose , and genome-wide expression analysis revealed that amino acid biosynthesis , in particular that of methionine , is critical for S . aureus during colonization . An inhibitor of methionine biosynthesis had anti-staphylococcal activity in SNM3 but not in complex media , and transcription of the S . aureus target enzyme was strongly up-regulated in human noses . Furthermore , mutants defective in methionine biosynthesis exhibited strongly compromised nasal colonisation capacities in a cotton rat model . Altogether , our results indicate that the elucidation of in vivo metabolism of pathogens may lead to the identification of new antimicrobial targets and compounds . | [
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"physiol... | 2014 | Nutrient Limitation Governs Staphylococcus aureus Metabolism and Niche Adaptation in the Human Nose |
As a result of poor economic opportunities and an increasing shortage of affordable housing , much of the spatial growth in many of the world's fastest-growing cities is a result of the expansion of informal settlements where residents live without security of tenure and with limited access to basic infrastructure . Although inadequate water and sanitation facilities , crowding and other poor living conditions can have a significant impact on the spread of infectious diseases , analyses relating these diseases to ongoing global urbanization , especially at the neighborhood and household level in informal settlements , have been infrequent . To begin to address this deficiency , we analyzed urban environmental data and the burden of cholera in Dar es Salaam , Tanzania . Cholera incidence was examined in relation to the percentage of a ward's residents who were informal , the percentage of a ward's informal residents without an improved water source , the percentage of a ward's informal residents without improved sanitation , distance to the nearest cholera treatment facility , population density , median asset index score in informal areas , and presence or absence of major roads . We found that cholera incidence was most closely associated with informal housing , population density , and the income level of informal residents . Using data available in this study , our model would suggest nearly a one percent increase in cholera incidence for every percentage point increase in informal residents , approximately a two percent increase in cholera incidence for every increase in population density of 1000 people per km2 in Dar es Salaam in 2006 , and close to a fifty percent decrease in cholera incidence in wards where informal residents had minimally improved income levels , as measured by ownership of a radio or CD player on average , in comparison to wards where informal residents did not own any items about which they were asked . In this study , the range of access to improved sanitation and improved water sources was quite narrow at the ward level , limiting our ability to discern relationships between these variables and cholera incidence . Analysis at the individual household level for these variables would be of interest . Our results suggest that ongoing global urbanization coupled with urban poverty will be associated with increased risks for certain infectious diseases , such as cholera , underscoring the need for improved infrastructure and planning as the world's urban population continues to expand .
In 2008 , for the first time in human history , more than half of the world's population was living in urban areas , and this proportion is expected to increase . Much of the future growth in urban areas is expected to take place in developing countries , with Africa and Asia predicted to have nearly seven out of every ten urban inhabitants in the world by 2030 [1] . Unfortunately , due in part to limited economic opportunities and an increasing shortage of affordable housing , the majority of urban growth in many of the developing world's fastest growing cities is a result of the expansion of informal settlements , often referred to as slums [2] . UN-HABITAT defines slums as urban areas where households lack one or more of the following conditions: access to an improved drinking water source , access to improved sanitation facilities , sufficient living area , durable housing in a non-hazardous location , and security of tenure [2] . As one might expect , these conditions can have severe consequences for human health and are of particular concern when considering their potential impact on the spread and burden of infectious diseases [3] , [4] . For example , tuberculosis , influenza , meningitis , typhus , plague , typhoid and cholera are among many infectious diseases historically associated with conditions now common in urban informal settlements . In spite of this , few modern data are available assessing the current association of infectious diseases with ongoing global urbanization , especially at the neighborhood and household level in informal settlements [5] , [6] . To begin to address this , we therefore analyzed urban environmental data and the burden of cholera in Dar es Salaam , Tanzania , a rapidly expanding African city . Dar es Salaam , Tanzania's largest city , covers an area of approximately 1800 km2 situated alongside the Indian Ocean . The city is comprised of three municipalities – Kinondoni , Ilala , and Temeke – which are divided into 73 wards ( Figure 1 ) . The city grew from a population of 76 , 000 in 1950 to a population of 3 . 31 million in 2008 [7] . With a current estimated growth rate of 4 . 3% per year [8] , Dar es Salaam contains 29% of the country's urban population , though this percentage is expected to nearly double by 2010 [7] . Most of the city's growth has occurred along the coastline and along four main arterial roads [9] ( Figure 2 ) . Despite increasing efforts on the part of municipal and city governments to address informal settlement expansion , the speed of the city's growth and the inability to invest adequately in housing and infrastructure have led to the growth of existing settlements and to the development of new ones . As a result , Dar es Salaam now has one of the highest proportions of informal-settlement households in East Africa , with 65% of households living in informal areas [7] . Investigating the relationship between cholera incidence and the size of and conditions in informal settlements may help to shed light on some of the health consequences of settlement expansion . Vibrio cholerae is a water- and food-borne Gram-negative bacterium and the cause of cholera , a severe , dehydrating diarrhea in humans . V . cholerae is unique among the diarrheal pathogens because of its ability to cause global pandemics . The disease has a short incubation period of 18 hours to five days [10] , and can thus spread rapidly through a population . Cholera may cause explosive outbreaks in crowded conditions , such as occurred in Goma in 1994 [11] and in Zimbabwe in 2009 [12] . In addition to causing epidemic disease , cholera is also endemic in many areas of the world , especially sub-Saharan Africa and South Asia . If untreated , mortality rates due to cholera can be as high as 50% [13] , though nearly all deaths can be avoided if replacement fluids are promptly administered . Antibiotics may also be used to shorten the recovery period for severe cases [14] . Strains of V . cholerae can be differentiated serologically by the O side chain of the lipopolysaccharide ( LPS ) component of the outer membrane , and the strains that produce epidemic cholera belong to serogroup O1 or O139 . V . cholerae O1 itself is classified into two biotypes , classical and El Tor , which differ clinically and biochemically . V . cholerae O1 biotype El Tor is responsible for the current seventh pandemic of cholera , and is the current cause of cholera in Dar es Salaam [15] . Although reporting may be incomplete , cholera is one of the few diseases that require reporting to the WHO under the International Health Regulations . Though a cholera epidemic was first reported in East Africa in 1836 , no cases were reported across Africa between 1870 and 1970 [16] , when cholera returned to the continent as part of the seventh cholera pandemic , which started in Asia in 1961 [10] . Cholera cases associated with this most recent pandemic were reported for the first time in Tanzania in 1974 , and have been reported each year since 1977 . The first major outbreak in Tanzania occurred in 1992 , although the largest country-wide epidemic occurred in 1997 , with more than 40 , 000 cases reported . This epidemic was reported to have started in Dar es Salaam [15] . Of all regions in Tanzania , Dar es Salaam has had the most cholera cases since 2002 . In an outbreak in 2006 , Dar es Salaam was the most affected region , accounting for 63% of the total cases ( 14 , 297 ) and 40% of the total deaths ( 254 ) [15] . Cholera is most commonly caused by ingestion of water or food contaminated with fecal matter , and due to this mode of transmission , risk factors for cholera include lack of safe drinking water , poor sanitation , high population density , crowding , and lack of previous exposure , all of which are often common features in urban slum areas [17] , [18] . In a number of countries , cholera incidence has been shown to be highest in highly urbanized areas [19]–[21] . We , therefore , chose to focus our analysis on the associations between cholera incidence and the nature of informal settlements in Dar es Salaam .
In order to gain a sense of the general pattern in cholera cases in Dar es Salaam and to identify a time period that might be particularly useful for analysis , weekly suspected cholera case reports from 2006 through June 2008 were gathered from the City Health Officer and analyzed over time and by municipality . Suspected cases included all those patients assessed at one of the city's three cholera camps ( described in detail below ) whose symptoms were deemed to meet the WHO case definition for cholera in endemic areas: “a patient older than 5 years who develops severe dehydration from acute watery diarrhea ( usually with vomiting ) ; or any patient above the age of 2 years with acute watery diarrhea in areas where there is an outbreak of cholera” [13] . Suspected cases of cholera among children younger than 2 years of age were also included in analyses if confirmatory laboratory results were available . However , though ages of suspected cholera cases were available in Kinondoni , they were not available for the other two municipalities , and it was not possible to link suspected cases to confirmatory laboratory results for these areas . Based on data from Kinondoni , it was estimated that less than 2% of the sample was comprised of children under the age of 2 years . Daily reports of suspected cases were collected from the District Medical Officer in each municipality , including information on the ward of residence , month and year . Where possible , information on the age and gender of suspected cases was also collected . Rectal swab results from those suspected cholera patients who were tested were also obtained from Amana Hospital in Ilala , from Temeke Hospital in Temeke , and from Mwananyamala Hospital in Kinondoni from 2006 through June 2008 in order to confirm the presence of V . cholerae O1 during months when suspected cases were being reported . Rectal swabs were collected at the discretion of the attending health provider as part of routine diagnostic assessments and were not collected for research purposes . Cholera incidence was calculated by ward for each year , using the available cholera count data and population projections for each ward based on the 2002 Census [22] . In comparison to the year 2006 , in which 8 , 753 cases of cholera were reported in Dar es Salaam , only 395 cases were reported in 2007 and only 216 cases had been reported by the end of June in 2008 . Due to the high volume of cholera cases in 2006 , we focused our analysis on this year alone . Though the number of cases by municipality was available for all months in 2006 , the location of cases by ward for the months of June through September was unable to be retrieved . However , 89 . 2% of the year's cases occurred in other months , including the months with the highest number of cases . Therefore , our analysis focused on these eight months . In addition , by using data from the Unplanned Land Property Register Project , analysis was limited to the 45 of the city's 73 wards included in the project; included areas were predicted to contain 84% of the city's population ( Figures 1 and 2 ) . Because the relationship between cholera incidence and predictors was nonlinear , cholera incidence was transformed into a natural logarithmic scale . All potential cholera cases were sent to one of three cholera camps located in the city for further assessment and , if needed , treatment . These camps were located at Buguruni Health Center in Ilala , Mburahati Dispensary in Kinondoni , and at Temeke Hospital between Azimio and Tandika wards in Temeke . The geographic coordinates for these camps were obtained from the Tanzania Service Availability Mapping 2005–2006 [23] . In order to calculate population density and distance to the nearest cholera camp , all data were mapped in ArcMap 9 . 2 [24] , utilizing a map file of wards in Dar es Salaam obtained from the International Livestock Research Institute [25] . Since we were not able to acquire individual addresses of suspected cholera cases , the distance to the closest cholera clinic was calculated , utilizing the center of the ward as the spatial reference . In addition , the area of each ward was calculated in square kilometers , and population density estimated based on the 2006 population estimates by ward . A shapefile of roads in Tanzania was acquired from the Food and Agriculture Organization's Multipurpose Africover Database [26] , and the presence or absence of a major road in each ward was recorded as a categorical variable . Between 2004 and 2007 , the Ministry of Lands and Human Settlements Development conducted a survey in informal settlements located in 45 wards as part of the Dar es Salaam Unplanned Land Property Register Project . The data were collected for administrative purposes . Data on 225 , 911 informal plots were gathered , mostly collected in 2005 . Questionnaires were distributed to owners or close relatives , or , in the case of residences occupied by tenants only , tenants were questioned and the homeowner was notified in order to verify the information provided . Information was collected about plot use ( residential , commercial , industrial , agricultural , other ) , the type and quantity of occupants , road access , source of water supply , type of sanitation , electricity , phone , building materials , length of time the occupants had lived in the area , ownership of household items and livestock , household income and type of employment , and garbage collection , among other characteristics . Of 207 , 085 plots whose use was known , 98 . 2% contained residences . Of 203 , 289 residential plots , 186 , 631 were occupied at the time of the survey , 23 . 9% of which were in Ilala , 37 . 4% of which were in Kinondoni , and 38 . 8% of which were in Temeke . Only records for occupied residential plots were included for analysis . Among these records , 97 . 5% ( 181 , 896 records ) contained complete information about a water source , while 61 . 4% ( 114 , 593 records ) contained complete information about sanitation . The number of informal residents in each ward was calculated by aggregating the number of occupants in each residential plot at the ward level . The percentage of informal residents in each ward was then calculated based on the 2006 population estimates . For three wards , estimates of the percent of the population that is informal were greater than 100 . This is likely a result of rapid urban expansion that was underestimated by the population estimates . As a result , for these three wards , the maximum informal percentage obtained from other wards , which was 95 . 8% , was used . The percentage of informal residents in each ward was used as a proxy for the percent of residents in each area that would likely be living in areas with poorer environmental conditions . Access to improved drinking water and access to improved sanitation were assessed based on guidelines from the WHO Joint Monitoring Program for Water Supply and Sanitation [27] . Thus , improved water sources included household connections , a neighbor's on-plot connection , and community pumps . Deep wells were also considered improved sources while shallow wells were not . The survey did not ask specifically about whether wells were protected , but due to the fact that shallow wells have a higher potential for contamination , particularly if they are uncovered , shallow wells were considered unimproved sources . Only sanitation facilities connected to the sewer system or to a septic tank were considered improved , as the type of pit latrine was not specified . Due to the lack of a reliable measure of income among informal residents , an asset index was constructed in order to serve as a proxy for long-term economic status and to provide a more sensitive means of differentiating between poor households [28] . Following the example of Filmer and Pritchett [29] , principle components analysis was used to generate weights for an index based on 22 asset indicators , including household ownership of consumer goods ( air conditioner , bicycle , car , computer , DVD player , fan , furniture , iron , motorcycle , radio or CD player , refrigerator , sewing machine , stove , TV or video player , tools , truck ) and household ownership of animals or livestock ( goat or sheep , chicken , cow , pig , dog or cat , other animals ) . Only the first principal component was used , which explained 16 . 9% of the variance . The index was designed so that a score of zero would indicate possession of no assets , while the score would increase with the possession of increasing numbers of assets . Data analysis was conducted using only de-identified data , which were analyzed at the ward level . As a way to assess whether environmental conditions in informal settlements had an effect on the city's pattern of cholera incidence , correlations were first calculated between the natural log of cholera incidence in 2006 and the percentage of a ward's residents who were informal , the percentage of a ward's informal residents without an improved water source , the percentage of a ward's informal residents without improved sanitation , distance to the nearest cholera camp , population density , median asset index score in informal areas , and presence or absence of a major road . Including as predictors only those variables significantly correlated at the 95% confidence level with the natural log of cholera incidence , data on the number of cholera cases per ward in 2006 were used to estimate cholera incidence rate ratios associated with the percentage of a ward's residents who were informal , population density , the percentage of a ward's informal residents without improved sanitation , and median asset index score in informal areas . Since we sought to model the number of cholera cases , and considering that overdispersion was observed ( i . e . the variance in the number of cholera cases exceeded the mean ) , a negative bionomial regression model was used for analysis , with the logarithm of a ward's population size included as an offset variable .
In 2006 , 8 , 753 cases of cholera were reported in Dar es Salaam , of which 42 . 8% were in Ilala , 32 . 5% in Kinondoni , and 24 . 7% in Temeke . The outbreak displayed two peaks – one in April and one in October ( Figure 3 ) . In any given month , V . cholerae O1 was identified by culture from rectal swabs taken from suspected cases in at least a third of those tested . The median incidence of cholera per 10 , 000 people in Dar es Salaam in 2006 was 15 . 8 , with 25% percent of wards reporting an incidence of 7 . 8 cases or fewer per 10 , 000 people , and 25% of the wards reporting an incidence of 36 . 6 cases or higher per 10 , 000 people . The maximum incidence reported was 99 . 6 , while one ward reported no cases ( Figure 4 ) . Since the Unplanned Land Property Register Project was restricted to 45 wards , further analysis was restricted to this area . These wards contain the majority of urban areas in Dar es Salaam , and account for 84% of the city's population . For the 45 wards analyzed , the percentage of informal residents without access to improved drinking water ranged from 37 . 8% to 90 . 0% , with a mean of 71 . 8% . The percentage of informal residents lacking improved sanitation ranged from 71 . 7% to 97 . 3% , with a mean of 92 . 4% . The average percentage of informal residents per ward was 60 . 1 , ranging from 5 . 4 to 95 . 8 . The mean population density for these wards was 14 , 874 people per km2 , ranging from a low of 334 people per km2 to a high of 48 , 257 people per km2 . Distance to the nearest cholera clinic ranged from 0 . 4 km to 17 . 4 km , with a mean of 3 . 8 km . The median asset index score overall ranged from 0 in 26 wards to 0 . 7 in one ward . Among occupied residential households , 56 . 3% did not report ownership of any of the items about which they were asked ( Table 1 ) . Major roads crossed 27 of the 45 wards analyzed . Of all the variables considered ( Figure 5 ) , median asset index score was the most highly correlated with the natural log of cholera incidence ( r = −0 . 53 , p<0 . 001 ) . The percentage of a ward's informal residents without access to improved sanitation , the percentage of informal residents in a ward and population density had moderate and positive effects on cholera incidence ( r = 0 . 49 , p<0 . 001 , r = 0 . 42 , p = 0 . 004 and r = 0 . 35 , p = 0 . 02 , respectively ) . In comparison , major road presence , distance to the nearest cholera clinic , and percentage of informal residents without access to improved water sources were not found to be significantly correlated with cholera incidence . Results of the negative binomial regression model indicated that when all four predictors were included , the effects of percent of informal residents , population density , and median asset index score on cholera incidence were found to be significant , while the effect of percentage of informal residents without access to improved sanitation was not found to be significant ( Table 2 ) . Although additional data would strengthen any potential explanatory model , our analysis of available data and interpretation of coefficients of the negative binomial model suggested nearly a one percent increase in cholera incidence for every percentage point increase in informal residents , and approximately a two percent increase in cholera incidence for every increase in population density by 1 , 000 people per km2 in Dar es Salaam in 2006 . At the same time , the model suggested nearly a fifty percent lower cholera incidence in a ward with a median asset index score of 0 . 32 , which is equivalent to informal residents owning a radio or CD player , compared to a ward where the median asset index score was zero .
Through an analysis of the spatial patterns of cholera in Dar es Salaam , we found in this study that the extent of informal occupancy , population density , and income level had significant effects on cholera incidence in the city in 2006 . Interestingly , in our analysis , we did not find an association between cholera incidence and access to improved water sources or improved sanitation at the ward level , despite the fact that cholera is transmitted fecal-orally . This may be due to the fact that , as shown in Figure 5 , the range of access to improved sanitation and improved water sources was quite narrow at the ward level in Dar es Salaam in 2006 , limiting our ability to discern relationships between these variables and cholera incidence . Analysis at the individual household level for these variables would be of interest . Poverty has , however , been closely linked to inadequate water and sanitation in the past [30] , and our detection of an association between median asset index score and cholera incidence may reflect in part the level of access to improved water and sanitation in this study . Underscoring the relationship between cholera and extreme poverty , our study suggests that relatively minor increases in income can correlate with a marked decrease in the risk of cholera . Our observed association of cholera incidence with population density and the extent of informal settlement may also reflect in part the increased risk of acquiring V . cholerae recently passed by another human in a densely populated urban slum area , compared to the risk of acquiring V . cholerae from ecological reservoirs not recently contaminated by humans . V . cholerae can exist in environmental water sources independent from humans , especially in association with zooplankton and phytoplankton , and these organisms may serve as an important reservoir for infection [10] , [31] . However , the passage of V . cholerae through a human intestine leads to a transient hyperinfectious bacterial state that can persist for up to 24 hours in environmental reservoirs , and such hyperinfectiousness may contribute significantly to human-to-human transmission [32]–[36] . Individuals in densely populated urban slums characterized by poor sanitary conditions may be at particular risk of ingesting such hyperinfectious V . cholerae , of therefore becoming involved in explosive outbreaks and epidemics , and of contributing to ongoing human-to-human transmission . Interestingly , recent data suggest that V . cholerae loses a significant degree of its hyperinfectiousness within hours of passage from a human intestine , suggesting that even in densely populated urban slums , relatively minor modifications in water usage patterns ( such as securely storing water for perhaps as short as a day prior to ingestion to allow V . cholerae to revert to its non-hyperinfectious state ) could possibly have significant impact on the burden of cholera in a slum area [37] . By suggesting that variations in the economic and physical conditions between and within informal settlements may translate into variations in disease patterns , this study validates previous findings that statistical analysis at the city level may mask important intra-urban differences . For example , infant and child mortality rates among Nairobi's slum populations were found to be three to four times higher than the city's average , and higher even than the average for rural areas in Kenya [38] . In Accra , Ghana , the relative risk of infectious and parasitic diseases was also found to be twice as high in areas of the city with the worst social and physical environmental conditions compared to the burden in the best areas [39] . Furthermore , this study adds to the growing body of research demonstrating that even within and between informal settlement areas , relatively small variations in social and physical conditions can result in markedly different rates of infection [18] , [40] , [41] . This pattern resembles the conditions resulting from rapid growth of European cities in the eighteenth and nineteenth centuries , which often led to a poorer health environment in urban areas [42] . However , the rate at which urban growth has been and is occurring in developing countries is unprecedented , and the resources available to address the myriad issues coupled with this growth are often extremely limited [4] , [43] . Although urban-associated infectious disease burden will predominantly be borne by the poorest in many of the world's fastest growing cities , the increased movement of people within and between population centers and countries will also facilitate the spread of these diseases between poor urban centers and other areas and populations [3] . Again , using cholera as an example , between 2006 and 2007 , more than 82 , 000 cases of cholera and 3 , 000 deaths were reported in Angola , the worst outbreak ever reported in that country [44] . The epidemic was reported to have started in one of the poorest and most overcrowded informal settlements in the capital city of Luanda and , over the course of the epidemic , spread to 16 of the country's 18 provinces [45] . Our study has a number of limitations . We analyzed cholera data collected during an epidemic , and patterns of endemic disease and factors involved in its transmission during endemic periods might be different than those we assessed . However , our use of data during the selected period allowed us to analyze a sufficient cholera case burden in the context of our measured environmental parameters . We used extant data sets reporting cholera burden that themselves were largely based on a syndromic classification system using WHO criteria . It is possible that cases classified as cholera where not caused by V . cholerae infection , and that other actual cases of cholera were not captured in the municipal reporting system; however , all cases included in this analysis met WHO criteria , microbiologic data were highly supportive when performed , and reporting criteria did not change during the period of data collection . In addition , though the negative binomial model used in this analysis accounted for high variability in the number of cholera cases , it did not account for any spatial structure that might have been present in the data . Given that our model tended to underestimate the number of cholera cases in the center of the city while overestimating the number of cases farther from the center , a spatial model might have provided additional insight , but was not able to be used given the small number of wards for which data were available . By using an extant data set , we were also limited by incomplete survey information; however , we felt that the ability to analyze an urban environmental survey undertaken immediately prior to an urban cholera epidemic provided a unique opportunity for analysis and , at least in part , mitigated this limitation . Similarly , while we may have obtained a more robust understanding of the risk of cholera had we analyzed data at the household or individual level ( as opposed to the ward level ) , such data were not available . Such an analysis may have shown that access to specific water sources or certain types of sanitary conditions or behaviors may affect the risk for cholera within a household . For instance , in a randomized control trial in low-income squatter settlements with poor water and sanitation in urban Pakistan , children in households encouraged to wash their hands with soap had a 53% lower incidence of diarrhea than in control households [46] . It should also be mentioned that we made the assumption in this analysis that people who became ill with cholera did so due to conditions in their area of residence , while it may also be the case that where people work and the types of activities they engage in away from home may have an effect on their risk of diarrheal illness . For example , consumption of food prepared away from the home is increasing in many developing countries , and was found in Nairobi to be associated with the distance one worked from the home . Preparation of these foods often involves questionable hygienic practices , which may increase the risk of diarrheal disease for those who consume them [47] . However , during an outbreak such as the one in 2006 in Dar es Salaam , the home environment may well play an important role in the spread of the disease . In order to determine whether the relationship between environmental conditions and cholera in Dar es Salaam is unique or indicative of a more general relationship between environmental conditions and the risk for infectious disease , it would also be useful to compare the pattern of cholera incidence with patterns of other diseases across the city to see whether the nature and spatial pattern of risks are similar . For instance , one might predict that the risk for other enteric diseases such as shigellosis might similarly correlate with population density and sanitation , while tuberculosis and influenza might correlate with crowding , and vector-borne diseases such as arboviral infections and malaria might correlate more with water sources , vector biting habits , and human behavior . Equally important , as the municipalities have taken important steps in recent years to address conditions in informal areas , evaluating the impact of these efforts on the incidence of disease should be a crucial part of determining their effectiveness . For instance , in at least one example of informal settlement upgrading , improvements in health have already been noted . Specifically , the upgrading of an informal settlement in Hanna Nassif ward in Dar es Salaam from 1994 to 1998 , which focused on the installation of water vending kiosks , the management of solid waste collectors , and construction of improved access roads and storm water drainage channels , led to a 39% reported decline in waterborne diseases from the start to the finish of the project [48] . In every developing region of the world excluding North Africa , slum growth is expected to closely match the rate of city growth [2] . In sub-Saharan Africa , 59 cities are expected to exceed one million inhabitants by 2015 , with 43% of urban inhabitants living below the poverty line [7] . Our analysis suggests that the ongoing growth of many of the world's cities and expansion of informal settlements will be associated with increased risks to human health , including cholera and possibly other infectious diseases , and underscores the importance of urban planning , resource allocation , and infrastructure placement and management as the rapidly progressive trend of global urbanization proceeds . | In 2008 , for the first time in human history , more than half of the world's population was living in urban areas , and this proportion is expected to increase . As a result of poor economic opportunities and an increasing shortage of affordable housing , much of the spatial growth in many of the world's fastest growing cities is a result of the expansion of informal settlements where residents live without security of tenure and with limited access to basic infrastructure . Although inadequate water and sanitation facilities , crowding , and other poor living conditions can have a significant impact on the spread of infectious diseases , analyses relating these diseases to ongoing global urbanization , especially at the neighborhood and household level in informal settlements , have been infrequent . To begin to address this deficiency , we analyzed urban environmental data and the burden of cholera in Dar es Salaam , Tanzania . We found that cholera incidence was most closely associated with informal housing , population density , and the income level of informal residents . Our analysis suggests that the current growth of many cities in developing countries and expansion of informal settlements will be associated with increased risks to human health , including cholera and other infectious diseases , and underscores the importance of urban planning , resource allocation , and infrastructure placement and management , as the rapidly progressive trend of global urbanization proceeds . | [
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] | 2010 | Informal Urban Settlements and Cholera Risk in Dar es Salaam, Tanzania |
Despite environmental , social and ecological dependencies , emergence of zoonotic viruses in human populations is clearly also affected by genetic factors which determine cross-species transmission potential . RNA viruses pose an interesting case study given their mutation rates are orders of magnitude higher than any other pathogen – as reflected by the recent emergence of SARS and Influenza for example . Here , we show how feature selection techniques can be used to reliably classify viral sequences by host species , and to identify the crucial minority of host-specific sites in pathogen genomic data . The variability in alleles at those sites can be translated into prediction probabilities that a particular pathogen isolate is adapted to a given host . We illustrate the power of these methods by: 1 ) identifying the sites explaining SARS coronavirus differences between human , bat and palm civet samples; 2 ) showing how cross species jumps of rabies virus among bat populations can be readily identified; and 3 ) de novo identification of likely functional influenza host discriminant markers .
Emerging infectious diseases ( EIDs ) continue to represent a significant public health threat , as illustrated by the 2009 H1N1 influenza pandemic and the 2003 severe acute respiratory syndrome ( SARS ) epidemic . Of particular concern are the 60%+ of EIDs of zoonotic origin [1] , [2] . In addition to influenza and SARS [3] , notable examples include hantaviruses [4] , Nipah and Hendra viruses [5] and HIV [6] . While predicting the emergence of new pathogens is likely to remain an unachievable goal for the immediate future , an emphasis of current research has been to try to identify ecological , behavioural and biological predictors of cross-species transmission and consequent disease emergence [2] , [7] , [8] , [9] , [10] . The wealth of pathogen sequence data becoming available makes identification of pathogen genomic markers of emergence one of the more promising approaches [11] , particularly for RNA viruses given their high mutation rate and resulting high diversity at the population level [12] . The identification of genetic markers predicting cross-species disease emergence faces many of the same challenges as genotype-to-phenotype mapping in other spheres , such as human genome-wide association studies of risk factors for chronic diseases [13] . Principle among these are relatively small sample sizes coupled with a very large number of potential explanatory variables ( single nucleotide substitutions and their interactions ) [14] , [15] . However , the much higher frequency of polymorphisms in RNA viruses and their fast population-level evolution offers unique challenges and opportunities . While most viral variants generated in a specific host are selectively neutral in that host , upon crossing the species barrier they are under strong selective pressure . We expect selection to shape the relative frequencies of viral variants found in donor and recipient species . Specific hosts impose specific evolutionary landscapes on viruses which will translate into signature genetic sequences . We therefore expect comparisons of allele frequencies between sequences of the same pathogen isolated from different hosts to reveal a large subset of alleles which are conserved between host species and a smaller subset of host specific alleles . This comparison can be performed by statistical techniques able to discriminate phenotype ( host ) relevant variables ( alleles ) . Here we apply feature selection methods which identify a subset of variable sites which can be used to build a robust phenotype classifier [16] . We focus on one algorithm for classification - the random forest algorithm ( RFA ) - that offers excellent performance in classification tasks , providing direct measures of variable importance and classification error [17] .
Our goals are two-fold . First , we investigate how well feature-selection algorithms such as RFA can reliably classify RNA viruses according to their host species reservoir , thereby giving insight into pathogen evolution , and the frequency of cross-species transition events . Identification of functional polymorphisms is not critical in meeting this goal , though clearly is desirable . Second , we evaluate how well RFA can identify sets of sites that are functionally relevant to the phenotype of interest ( in this case host species ) , in the context of dense RNA virus genomes and their high degree of linkage . We first analyse polymerase gene sequences of RNA viruses to identify the genetic signatures predicting host species . As an example , Figure 1a represents the diversity of Flavivirus polymerase amino acid sequences ( Table S2 ) . Here we use principal component analysis ( PCA ) solely to visualise the variation between samples , not as a classification tool . Figure 1b illustrates how feature selection identifies amino acid positions which robustly classify samples by host species , resulting in clustering of samples which infect the same reservoir . The clustering of samples seen in the PCA plot is similar to that seen in the maximum likelihood tree ( Figure 1c ) , supporting the use of PCA as a useful tool for generating low-dimensional representations of genetic variation . Second , we examine the potential of RFA applied as a phenotypic classifier to give insight into cross-species disease emergence . In this case , analysis of sequences of viruses which have fully adapted to particular host species – as in the Flavivirus example – is insufficient to distinguish between the subset of mutations required to allow cross-species emergence and later non-essential mutations which further increase viral fitness in a new species . We therefore need to examine data collected from zoonotic outbreaks . The 2003 SARS epidemic is a good example of a zoonosis which rapidly developed a high level of transmissibility in humans [3] , [18] , [19] . The pathogen was rapidly identified [3] and the origin of the virus was initially traced back to palm civets [19] , before bats were identified as the natural reservoirs of SARS-like coronaviruses [20] . We applied the RFA to nucleotide sequences of the spike protein of SARS-like coronaviruses ( Table S3 ) , recovered from human patients and palm civets from the 2003 and 2004 epidemics and bat sequences available in the Genbank database . Figure 2a illustrates the extent to which bat sequences differ from the human and palm civet sequences recovered in China in 2002–2004 , and also highlights the similarity of palm civet and human sequences [19] . Analysis of the variation in the selected host-discriminant viral alleles ( highlighted in Figure 3 ) reveals interesting relationships between host reservoirs ( Figure 2b ) . Firstly , there is noticeable genetic variation in the samples from human SARS patients collected in the early and mid-stages of the 2003 epidemic , compatible with adaptation of the virus to a new host species . The late 2003 samples were less variable , suggesting selective pressures may by then have stabilized [21] . Secondly , human patient samples from a small outbreak in January 2004 are more closely related to palm civet 2004 samples than to any human sample from the previous year , indicating that the 2004 outbreak represented an independent cross species transition [22] . The palm civet samples from 2003 were collected a few months after the human epidemic ended so there might have been an accumulation of mutations responsible for the substantial distance between palm civet 2003 samples and human 2003 samples . However , the close proximity between the bat samples and the first samples from the human 2003 epidemic suggests that the transition from palm civet to human occurred quite rapidly after the transition from bat to palm civet . With respect to our second goal – identifying functional relevant sites – it is notable that 12 of the 15 positions identified by feature selection coded for non-synonymous substitutions ( Table S4 ) , most of which are mapped onto the surface of the spike protein . It should be noted that of the 15 positions identified in the current study , 13 overlap with those found in [23] . The functional relevance of the two unique positions ( 239 and 311 ) found here and that of the 13 unique positions identified in [23] is not clear . When running the RFA for amino acid sequences of the same viruses , we obtain a subset of 12 significant amino acid positions that are coded for by the exact same non-synonymous substitutions highlighted by the RFA conducted on the nucleotide sequences . High mutation rates in RNA viruses facilitate the overcoming of host specific barriers [24] particularly in ecological settings where hosts display high contact rates [8] , [22] . However , cross-species transfer seems to be favoured between closely related host species [9] , [25] , [26] , [27] , suggesting that the fitness landscape of host adaptation is shaped by host phylogeny . Streicker and colleagues [26] defined lineages of rabies virus associated to particular bat taxa , identifying 43 cross species transmission events involving 15 bat species . Here we reanalyse the complete nucleoprotein sequences available for five of those bat species ( Table S5 ) . PCA applied to these sequences ( Figure 4a ) shows how viruses collected from 3 of the bats species ( L . borealis , L . seminolus , L . cinereus ) are extremely similar , with a substantially divergent lineage infecting E . fuscus bats and an isolated small cluster of viruses seen in T . brasiliensis . Applying RFA to predict host species to these sequences allows discrimination of L . cinereus specific traits ( Figure 4b ) , but does not significantly separate the L . borealis and L . seminolus clusters . This suggests that transmission of rabies virus between these two bat species is much more frequent than between any other pair of species examined . The advantage of RFA compared with phylogenetic methods is that it allows a probability of “belonging” to each host bat species to be estimated for each virus sample . Thus we can examine whether a virus isolated in one species is in fact native to a different host species . Figure 4b highlights the 8 outlier sequences ( T1–T8 ) in this dataset – viruses which are closer to rabies viruses native to a different species from that in which they were isolated . For these 8 viruses , Figure 4c gives the RFA classification probabilities of these viruses to the 5 different host species considered . In six cases , the cross-species transitions thus identified agree with those identified in [26] . Five of these 8 transitions occurred between L . borealis and L . seminolus . This , and the relatively poor ability of RFA to choose between these species in classifying viruses ( Table S6 ) , suggests that phylogenetic closeness between host species ( Figure S4 ) facilitates cross-species transmission . To address our second goal of investigating the functional relevance of identified discriminant features , we applied RFA to a collection of influenza A samples from distinct host species focusing on two viral segments that have been suggested to be major determinants of host range and virulence [28] . First , as a critical validation of the RFA , we analysed H1N1 hemagglutinin ( HA ) amino acid sequences collected in human ( pre and post 2009 pandemic ) and swine hosts , since multiple sources of empirical evidence for the functional relevance of specific amino acids in that gene are available [29] , [30] , [31] . Second , we analysed the PB2 Influenza A gene , since it is highly conserved across subtypes and its evolution has been hypothesised to reflect host specific adaptation [32] . The HA analysis serves not only as an assessment of the functional relevance of the positions being highlighted as host specific by RFA , but also as a benchmark of the method by direct comparison with a recently published study [33] which made use of an alternative feature-selection algorithm ( Adaboost ) . We compare algorithm performance on three levels: prediction ability , percentage of selected amino acids in functionally relevant positions , and overlap of selected amino acids . We use full HA segment amino acid sequences and analyse the proportion of selected amino acids that fall in the Receptor Binding Domain ( RBD ) , and in known antigenic sites . Table 1 summarises our findings by comparison with the Adaboost results [33] . There is substantial overlap with the sets of relevant positions between the two methods , although RFA seems to consistently identify a larger proportion of amino acids in HA's receptor binding domain ( RBD ) , particularly those that are also known antigenic sites , with a greater predictive ability . Even if one were to aggregate the Adaboost results ( Adaboost can only undertake binary classification , so two comparisons were needed to explore host-specific determinants for 3 virus groups ) , that algorithm identifies 47 significant positions , 20 ( 42 . 5% ) of which belong to the RBD , 7 ( 35% ) in known antigenic sites . A multi-class RFA is able to identify a significant larger subset of amino acids in known antigen sites ( 12 in the RBD plus 2 others ) , the functional relevance of which can be explored in future experimental studies . Table S7 lists all the positions selected as significant , while Figure 5 portrays allelic diversity across the HA samples analysed and gives clear intuition into why the identified sites were selected by RFA . We should note the absence of the 190 and 225 mutations ( hallmark mutations of human-adapted H1N1 HA ) from the subset of significant residues determined by RFA . Although these mutations confer optimal contact with the sialic acid receptors [29] , we find that 190D is highly conserved throughout our sequences , contrasting with the 190E amino acid found in avian samples . Residue 225 is picked as one of the 100 most informative sites for host discrimination by the RFA . All the virus groups examined contain samples with the 225D allele , while the 225G allele ( the consensus in avian viruses ) is present in some seasonal human and swine samples . Had we included avian samples in the analysis , the 225 positions would certainly be classified as highly host discriminant . Here , we identify other mutations which have empirically been found to influence contact with the α2–6 glycans , either by providing additional anchoring sites for the sialic acid ( position 145 ) ; by forming a network interacting with Asp190 ( 186 , 187 and 189 ) ; or by modulating the stability of those contacts ( 219 and 227 ) [34] , [35] . Identified positions 155 and 131 are also thought to play a relevant role in binding to sialic acid receptors [34] , [36] . Feature selection performed on the PB2 segment highlights subtype transcending functionally relevant amino acids from sequences of 7 influenza subtypes ( H1N1 , H1N2 , H2N2 , H3N2 , H5N1 , H3N8 , H7N7 ) , collected in 5 different hosts ( humans , birds , pigs , dogs , and horses ) , as detailed in Table S8 . Overall , we identified a subset of 23 host discriminant positions ( Table S9 ) , out of which only 7 fall outside known functional domains [37] , [38] . Our results are substantially congruent ( overlap of 7 identified positions out of 12 ) with those of a phylogenetic study aimed at identifying amino acid sites with strong support for different selection constraints in human and avian viruses [39] , even though our analysis is not limited to differences between these two hosts . A closer look at the identified sites in the most extensively studied functional domains ( the 627 and NLS domains ) reveals that all lie on the surface of the protein ( Figure 6 ) , with mutations at positions 588 , 591 , 627 , and 702 being responsible for the most drastic conformational changes . Analysis of the physiochemical properties of the selected amino acids reveals side chain charge reversals in positions 591 and 627 ( Table S9 ) . The insertion of a lysine in an otherwise avian adapted H5N1 virus ( which is unable to infect humans ) has been shown to promote host adaptation [40] , [41] and increase virulence [42] , [43] . Conversely , mutation in amino acid 591 can reduce the selective pressure for mutations at amino acid 627 , serving as an alternate human adaptive strategy [44] . This possible interaction is emphasised by the juxtaposition of residues 591 and 627 , as observed in Figure 6 . Of the remaining selected amino acids , some refer to mutations that can alter domain structure , three of which are human discriminating ( 661 , 674 , and 702 ) . Interestingly , only one of the selected sites ( 292 ) differentiates canine viruses from equine viruses . The paired mean distance between groups ( measured in terms of the number of differences observed in the full gene sequences ) is smallest for the canine and equine viruses ( Table S10 ) . These host species turn out to be the ones with the most recent common ancestor [45] , [46] , lending additional support to the hypothesis that host phylogeny shapes evolution of viruses by affecting cross-species mutational barriers . However , influenza H1N1 viruses found in human hosts are more similar ( on average ) to avian viruses than to viruses found in other mammalian hosts . Bird viruses are also the least divergent comparison group from swine viruses , perhaps reflecting the avian origin of all influenza viruses , and that , for influenza , transmission between birds and some mammalian hosts ( human and swine in this case ) is more frequent than expected by their phylogenetic relationships , probably due to persistent exposure in domestic settings .
In recent years , genome-wide association studies ( GWAS ) have become an increasingly popular tool to identify genetic determinants of non-infectious human diseases [47] . However , statistically rigorous genotype-to-phenotype mapping for pathogens has been much less common . The methods used for human GWAS are particularly ill-suited to feature selection in RNA viruses , due to the short genome length , very high substitution rate and diversity , and the high degree of genetic linkage [48] , [49] . Human GWAS tend to concentrate on common variants to explain the observed phenotypes [15] , [49] , [50] by looking at individual SNPs , thus having severe limitations in the presence of epistasis [15] , [48] , [50] , [51]; our work demonstrates that non-parametric machine-learning based methods – such as RFA – are more appropriate in the context of RNA viruses , by identifying sets of substitutions associated with a particular phenotypic class , rather than solely evaluating the significance of individual polymorphisms [48] , [51] . The incorporation of interactions among predictor variables in RFA makes it possible to identify possible epistatic effects , as highlighted in Figure 3 , with substitutions being determinant for host discrimination when found together with other substitutions at other sites , but being fairly unimportant by themselves . While RFA and other related discriminative methods arise from a different theoretical paradigm from likelihood-based statistical models , their predictive performance can be readily assessed via bootstrapping and other resampling methods . Our work demonstrates that machine-learning based feature selection methods are a powerful tool for de novo discovery of likely functional host discriminating markers , whilst providing a measure of the relative importance of those markers to host specificity . More generally , we highlight the potential of RFA for gaining important biological insights on cross-species transitions of RNA viruses . . First , we find that even relatively distantly related viruses within viral families – that might be geographically isolated and transmitted by different routes – share highly conserved genetic signatures of host specificity . Second , we see that the fitness landscapes of host adaptation are shaped by host phylogeny , with evolutionary barriers generally being lower between closely related host species , though not always ( influenza A viruses transfer between birds and some mammalian hosts being a counter-example ) . Third , our analysis of influenza A often selects sites with empirically proven functional relevance [34] , [36] , [41] , [44] to host specificity – in the case of HA , playing critical roles in cell receptor binding; for PB2 , being exposed on the protein surface ( Figure 6 ) and thus potentially interacting with host importin molecules to gain access to the nucleus [52] or with the nucleoprotein in the ribonucleoprotein complex [53] , [54] . Overall , genotype to phenotype mapping using host reservoir as the discriminant phenotype can reveal evolutionary trajectories of RNA viruses in rapid expansion and under great evolutionary pressure ( capturing the effects of diversification and expansion in a new host , as well as the contraction of diversity following host adaptation ) , while establishing the genetic signatures imposed by specific hosts which permit cross-species transmission events to be identified . Although discriminant analysis approaches are typically marred by biases related to sampling efforts and founder effects [55] , RFA enables the circumvention of some of these biases through cross-validation , sampling with replacement and attribution of weights to unequally sampled groups ( see Text S1 for more details ) . Even though some residual sources of bias are impossible to eliminate , these rigorous methods ( which are computationally efficient and thus applicable to large numbers of sequences ) are potentially useful for assessing the risk of viral emergence , and represent a powerful additional tool alongside phylogenetic analysis for analysing the phenotypic evolution of RNA viruses .
Feature selection methods try to find the subset of relevant features for building robust learning models that can accurately inform a classification algorithm [16] . We focussed on the random forest algorithm ( RFA ) , since it offers excellent performance in classification tasks [17] , and provides direct measures of variable importance and classification error . Each tree in a random forest is trained on a bootstrap sample of the data , and at each split a random subset of the variables is chosen from all the available variables ( in this case , a subset of positions in the sequence for each split ) . Final classification of each sample results from aggregating the votes of all trees in the forest . The importance measure of each variable is obtained as the loss of accuracy of classification caused by the random permutation of attribute values for that variable . RFA identifies which variables give the most discriminating information regarding the independent categorical variable of interest ( host reservoir in this case ) . We used the varSelRF package in R to run the random forest algorithm [56] . The information within a given sequence alignment was numerically recoded into an allele frequency matrix , using the adegenet R package [57] ( see Text S1 for more details ) . Starting from a multiple sequence alignment , all conserved sites are discarded , and a presence/absence matrix of all other alleles is assembled . Since we are dealing with RNA viruses , this matrix is actually equivalent to a presence/absence matrix of amino acid/nucleotide types in polymorphic sites ( Table S1 ) . Outside of phylogenetic analysis , direct comparison of genetic sequences is challenging , due to the high dimensionality of the datasets , typically consisting of dozens of sequences containing thousands of nucleotides . However , the relationship between a set of viral sequences can be represented through dimensional reduction techniques such as principal component analysis ( PCA ) [58] . Here we use PCA simply as a tool to graphically represent the variance in our datasets and to highlight the relationships between the viral samples collected in different host species , similar to past studies [59] . Selecting the two dominant principal components ( which in our study always explained more than 40% of the variance ) allows for a straightforward interpretation of differences between any set of sequences through a two dimensional plot , with the scores for the two principal components serving as the coordinates . We can then assess how well feature selection clusters RNA viruses by phenotype class ( here host reservoir ) by applying PCA to both the original dataset and to the dataset consisting exclusively of sites selected by feature selection . RFA prediction errors and variable importance are estimated from the samples which are left out of the training set at each split of the tree –the ‘out-of-bag’ samples . This makes RFA highly robust to over-fitting . Although RFA is unlikely to over-fit , we carried out cross-validation of the algorithm by performing multiple bootstrap runs of the feature selection procedure . Each bootstrap run is a new realisation of the complete feature selection procedure , thus removing selection bias concerns on the importance of the most significant variables . More details on the methods employed throughout can be found in Text S1 . | Moving away from genome scan methods used for human GWAS ( ultimately inappropriate for the short highly polymorphic genomes of RNA viruses ) , our work shows the power and potential of multi-class machine learning algorithms in inferring the functional genetic changes associated with phenotypic change ( e . g . crossing a species barrier ) . We show that even distantly related viruses within a viral family share highly conserved genetic signatures of host specificity; reinforce how fitness landscapes of host adaptation are shaped by host phylogeny; and highlight the evolutionary trajectories of RNA viruses in rapid expansion and under great evolutionary pressure . We do so by ( for each dataset ) unveiling a set of phenotype characteristic mutations which are shown to be functionally relevant , thus providing new insights into phenotypic relationships between RNA viruses . These methods also provide a solid statistical framework with which the degree of host adaptation can be inferred , thus serving as a valuable tool for studying host transition events with particular relevance for emerging infectious diseases . These methods can then serve as rigorous tools of emergence potential assessment , specifically in scenarios where rapid host classification of newly emerging viruses can be more important than identifying putative functional sites . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2013 | Feature Selection Methods for Identifying Genetic Determinants of Host Species in RNA Viruses |
Epithelial cells are a major port of entry for many viruses , but the molecular networks which protect barrier surfaces against viral infections are incompletely understood . Viral infections induce simultaneous production of type I ( IFN-α/β ) and type III ( IFN-λ ) interferons . All nucleated cells are believed to respond to IFN-α/β , whereas IFN-λ responses are largely confined to epithelial cells . We observed that intestinal epithelial cells , unlike hematopoietic cells of this organ , express only very low levels of functional IFN-α/β receptors . Accordingly , after oral infection of IFN-α/β receptor-deficient mice , human reovirus type 3 specifically infected cells in the lamina propria but , strikingly , did not productively replicate in gut epithelial cells . By contrast , reovirus replicated almost exclusively in gut epithelial cells of IFN-λ receptor-deficient mice , suggesting that the gut mucosa is equipped with a compartmentalized IFN system in which epithelial cells mainly respond to IFN-λ that they produce after viral infection , whereas other cells of the gut mostly rely on IFN-α/β for antiviral defense . In suckling mice with IFN-λ receptor deficiency , reovirus replicated in the gut epithelium and additionally infected epithelial cells lining the bile ducts , indicating that infants may use IFN-λ for the control of virus infections in various epithelia-rich tissues . Thus , IFN-λ should be regarded as an autonomous virus defense system of the gut mucosa and other epithelial barriers that may have evolved to avoid unnecessarily frequent triggering of the IFN-α/β system which would induce exacerbated inflammation .
The intestine has to maintain tolerance to the symbiotic gastrointestinal microflora , while mounting an effective immune response when challenged with opportunistic bacteria or enteric viruses . Thus , the intestinal mucosa , composed of the lining epithelium and underlying lamina propria cells , forms the first line of defense against pathogenic microorganisms entering the body via the oral route . The type I interferon family ( IFN-α/β ) represents a key element of the innate antiviral defense [1–5] . In humans the type I IFN family encompasses 13 IFN-α , a single IFN-β and a few minor IFN subtypes ( IFN-κ/ε/ω ) that all bind to a single heterodimeric cell surface complex known as IFN-α/β receptor [6] . IFN-α/β receptor engagement activates the Jak-STAT signaling pathway and induces the expression of several hundred IFN-stimulated genes ( ISGs ) , many of which exhibit direct antiviral activity [7–10] . In 2003 , the type III IFN family ( IFN-λ ) , encompassing 3 similar IFN-λ molecules , was discovered [11 , 12] . It quickly became clear that the induction and mechanism of action of IFN-λ and type I IFN are very similar [13–16] , although IFN-λ uses a distinct receptor for signaling . These observations raised the question why two seemingly redundant antiviral systems may have evolved . The major difference between the IFN-α/β and the IFN-λ systems is that IFN-λ receptor expression is confined mostly to the mucosal epithelium , whereas the IFN-α/β receptor seemingly is ubiquitously expressed [13] . Accordingly , IFN-α/β receptor-deficient mice show enhanced susceptibility to a large panel of different viruses [2 , 4] . On the contrary , mice lacking functional IFN-λ receptors control systemic viral infections quite well and are only slightly more susceptible to respiratory viruses than wild-type mice [14 , 16] . Interestingly , mice deficient in both IFN-α/β and IFN-λ are extremely susceptible to various respiratory viruses , demonstrating redundancy of the two IFN systems in the lung that is rich in epithelial cells [14] . The importance of the type I IFN system for controlling enteric viral infections varies greatly depending on the challenge virus . For example , IFN-α/β plays an important role in restricting virus-induced disease after oral inoculation of mice with poliovirus or human reoviruses , but it is of moderate importance in restricting rotavirus that exhibits a high tropism for gut epithelial cells [17–23] . We recently demonstrated that the IFN-λ system is essential for efficient control of rotavirus replication in intestinal epithelial cells [23] . This finding was surprising , considering the fact that receptors for IFN-α/β are believed to be expressed on all nucleated cells and raised the question of why the IFN-α/β system was unable to compensate for IFN-λ deficiency in this case . We demonstrate here that intestinal epithelial cells express only low levels of the two chains of the IFN-α/β receptor complex , have a low density of IFN-α/β receptors on the surface and , accordingly , respond only very poorly to stimulation with type I IFN . Interestingly , besides responding strongly to IFN-λ , intestinal epithelial cells also readily produced IFN-λ but not IFN-α or IFN-β in response to viral triggers , suggesting that IFN-λ functions as an autonomous antiviral defense mechanism in the gut epithelium that requires no assistance by type I IFN . Virus challenge experiments of mice lacking functional receptors for either IFN-α/β or IFN-λ confirmed the concept of a compartmentalized intestinal mucosal IFN system and highlighted the exceptionally dominant role of IFN-λ in antiviral protection of intestinal epithelial cells and bile ducts .
To address the question why the gut epithelium is poorly protected by type I IFN against infection with rotavirus [23] , we measured IFN receptor gene expression in isolated intestinal epithelial cell ( IEC ) and lamina propria lymphocyte ( LPL ) fractions of adult wild-type mice by quantitative reverse transcription PCR ( RT-qPCR ) . We analyzed the purity of isolated cell fractions by measuring the expression of marker genes of epithelial cells ( Cdh1 encoding E-cadherin ) and leukocytes ( Ptprc encoding CD45 ) ( S1A and S2 Figs ) , as well as by flow cytometry using antibodies against CD45 and the epithelial marker EpCAM ( S1B Fig ) . As expected , Ifnlr1 and Il10r2 , coding for the two chains of the IFN-λ receptor complex , were highly expressed in IECs but not in LPLs ( Figs 1A and S2 ) . Both components of the type I IFN receptor complex , Ifnar1 and Ifnar2 , were highly expressed in LPL that are well known to readily respond to type I IFN . By contrast , in IECs , we observed only low expression of Ifnar1 and Ifnar2 ( Figs 1A and S2 ) . Flow cytometric analysis revealed that the IEC fractions contained about 5% CD45+ cells ( S1B Fig ) . Thus , we used fluorescence-activated cell sorting to purify epithelial ( EpCAM+CD45- ) cells from crude IEC and LPL fractions ( S1B Fig ) . RT-qPCR analysis revealed strongly decreased expression of Ifnar1 and Ifnar2 in purified epithelial cells when compared to leukocytes ( EpCAM-CD45+ ) ( S1C Fig ) . To determine if low expression of Ifnar1 and Ifnar2 in IECs would result in low levels of IFN-α receptor on the cell surface , we used an IFNAR1-specific antibody for immunostaining experiments . FACS analysis confirmed the presence of easily detectable levels of IFNAR1 on LPLs from wild-type but not Ifnar1-/- mice ( Fig 1B ) . Importantly , under these experimental conditions , the staining of IECs from wild-type mice was not more intense than the staining of IECs from Ifnar1-/- mice ( Fig 1B ) , demonstrating that cell surface expression of the type I IFN receptor on IECs is intrinsically low . These data offer a simple explanation for why type I IFN is anti-virally ineffective in intestinal epithelial cells . Mononuclear phagocytes from germ-free mice do not readily mount type I IFN responses after TLR triggering or virus-mediated immune stimulation [24–26] , suggesting that commensal bacteria-derived signals induce baseline IFN signaling that calibrates the activation threshold of various cell types and determines whether the host can mount a timely inflammatory response upon encountering a pathogen . We hypothesized that if IECs predominantly responded to IFN-λ , IECs of Ifnar1-/- , but not Ifnlr1-/- , mice should exhibit low steady state IFN responses . To evaluate this hypothesis , we measured the expression of two representative ISGs , Isg15 and Oasl2 , in IEC and LPL fractions isolated from intestinal tissue of wild-type , Ifnar1-/- and Ifnlr1-/- mice ( Fig 1C ) . Indeed , baseline expression of ISGs was low in IECs of Ifnlr1-/- but not Ifnar1-/- mice . As expected , the reverse pattern of ISG expression was observed in LPLs , though the effect was less pronounced . To comparatively analyze the roles of type I IFN and IFN-λ in inducing ISG expression in the intestinal mucosa , we treated mice subcutaneously with a high dose of recombinant IFN and stained tissues for IFN-induced Mx1 protein that accumulates in the nuclei of IFN-responsive cells . IFN receptor knockout mice were used to exclude background staining of Mx1 induced by endogenous IFN . Injection of IFN-λ into Ifnar1-/- mice led to a strong accumulation of Mx1 in the nuclei of E-cadherin-positive IECs of the gastrointestinal tract in its entire length ( Figs 1D and S1D ) . In stark contrast , IFN-α injection into Ifnlr1-/- mice resulted in strong accumulation of Mx1 in the nuclei of lamina propria cells but not IECs ( Figs 1D and S1D ) . Combined treatment with IFN-α and IFN-λ of Ifnar1-/-Ifnlr1-/- double knockout control mice did not result in detectable levels of Mx1 in the nuclei of either IECs or the cells of the lamina propria region ( S1E Fig ) . Type I IFN and IFN-λ have a redundant role in defense of the lung and upper respiratory epithelium against epitheliotropic respiratory viruses [14 , 27] . As a positive control for in vivo IFN treatment , we extracted tissues of the respiratory tract . Interestingly , a different picture emerged when tissue samples from the respiratory tract and the gut of the same animals were analyzed for the presence of Mx1 . Similar to the gut mucosa , IFN-λ induced Mx1 exclusively in epithelial cells of respiratory tissues ( S1F Fig ) . In IFN-α-treated animals , however , a broad range of cell types from the lung and trachea , including the E-cadherin-positive epithelial cells , showed prominent nuclear Mx1 staining ( S1F Fig ) , indicating striking differences in type I IFN responsiveness in cells from the gut and the respiratory tract . No Mx1 staining was observed in tissue from the respiratory tract after combined treatment with IFN-α and IFN-λ of Ifnar1-/-Ifnlr1-/- double knockout control mice ( S1G Fig ) . These results suggest that unlike epithelial cells of the lungs and the trachea , epithelial cells of the intestine rely almost exclusively on IFN-λ for antiviral defense . Lymphocytes are crucial producers of type I IFN in the intestinal mucosa [17 , 28] . However , the IFN-λ-producing cell types in the gut have not been identified . Data shown in Fig 1C suggested constitutive production of baseline levels of IFNs in the gut . To identify the IFN-producing cells at steady state , we monitored type I IFN and IFN-λ gene expression by RT-qPCR in isolated IEC and LPL fractions from naïve adult wild-type mice . Substantial baseline expression of type I IFN genes was only observed in the LPL but not in the IEC fraction ( Fig 2A ) . By contrast , baseline expression of IFN-λ genes was observed in the IEC fraction only ( Fig 2A ) . Analysis of purified cells indicated that the IFN-λ-producing cells in the epithelial fraction express the CD45 marker ( S3 Fig ) . Therefore , the IFN-λ-producing cells in the gut mucosa at steady state are of hematopoietic origin . Dendritic cells are the major producers of IFN after virus infection or stimulation with the synthetic double-stranded RNA analogue poly I:C [29 , 30] . Indeed , intraperitoneal injection of poly I:C into wild-type mice triggered rapid expression of type I and type III IFN genes in cells of the LPL fraction . By contrast , the Ifnl2/3 but not type I IFN genes were induced in cells of the IEC fraction under these conditions ( Fig 2B ) . Interestingly , the cells strongly expressing IFN-λ in response to poly I:C in the epithelial fraction were not leukocytes but mainly EpCAM+ epithelial cells ( Fig 2C ) . Collectively , these experiments identified IECs and a fraction of mucosal CD45+ immune cells as important sources of IFN-λ . In earlier studies we used rotavirus to assess the role of IFN-λ in the gastrointestinal tract [23] . Due to the high tropism of rotaviruses for IECs , IFN-mediated antiviral effects in other cell types cannot be assessed with rotavirus . To determine why the IFN system is compartmentalized in the intestinal mucosa , we employed reovirus as a model [17 , 31–33] . Mammalian reoviruses have a wide cell tropism and exhibit a low degree of species specificity . After infection by the oral route , type I IFN signaling is of crucial importance for restricting systemic reovirus dissemination . By contrast , in IFN-competent hosts , reovirus-induced disease is mostly mild [17 , 34 , 35] . Indeed , intra-gastric inoculation of adult Ifnar1-/- mice with the human reovirus type 3 Dearing strain led to severe neurological symptoms such as hind limb paralysis , and all Ifnar1-/- animals had to be sacrificed by day 4 post-infection . By contrast , no symptoms were observed after infection of adult Ifnlr1-/- and wild-type mice ( S4A Fig ) . Accordingly , reovirus replication in the terminal small intestinal tissue at day 4 post-infection was significantly higher in Ifnar1-/- mice compared to Ifnlr1-/- or wild-type animals ( Figs 3A and S4B ) . For efficient spread via the fecal-oral route , enteric viruses must be released from infected tissues to the gut lumen and excreted in feces . In Fig 1 we demonstrated that IFN-λ , but not type I IFN , induces a strong antiviral response in the epithelial barrier that separates the gut lumen from sterile host tissues . To examine the role of type I and type III IFNs in virus excretion , we quantified reovirus shedding in feces on day 4 post-infection . We observed high titers of infectious virus in feces of adult Ifnar1-/- and Ifnlr1-/- but not wild-type mice ( Fig 3B ) . Considering the largely different virus titers in the intestinal tissue ( Fig 3A ) , Ifnar1-/- mice excreted relatively small amounts of virus when compared to Ifnlr1-/- mice . Animals lacking both IFN receptors ( Ifnar1-/-Ifnlr1-/- ) had comparable virus titers in the tissue to Ifnar1-/- mice , whereas virus shedding in feces was even higher than from Ifnlr1-/- mice ( S4C Fig ) . Together , these results suggested that excreted virus may originate from different cell types in Ifnar1-/- and Ifnlr1-/- mice . Immunohistochemical staining of tissue samples from the small intestine confirmed this view . Reovirus antigen was almost exclusively found in IECs of Ifnlr1-/- mice at day 4 post-infection ( Fig 3C , right panel ) , whereas reovirus was restricted to lamina propria cells in Ifnar1-/- mice ( Fig 3C , middle panel ) . Reovirus specifically adheres to M cells and initially replicates in cells of the Peyer’s patch ( PP ) mucosa [36] . Accordingly , we detected reovirus antigen in cells of the PP of all three mouse strains ( Fig 3D ) . In infected Ifnar1-/- mice the PPs were enlarged , and massive changes in the structure of the follicle-associated epithelium was observed ( Fig 3D , middle panel ) as previously described for reovirus type 1 [17] . In infected Ifnlr1-/- mice no such changes of the PP structure were noted . Interestingly , reovirus antigen in Ifnlr1-/- was detected in the follicle-associated epithelium as well as in the underlying tissue ( Fig 3D , right panel ) . In contrast , reovirus staining in wild-type animals was restricted to few PP cells located under the epithelium ( Fig 3D , left panel ) . These data indicate that reovirus produced by IECs of Ifnlr1-/- mice may more easily reach the feces than virus produced by cells in the tissue below , a mechanism accounting for the observed enhanced virus shedding in feces in Ifnlr1-/- mice . Severe viral gastroenteritis is a major problem of newborns and small children . Similarly , suckling mice are far more susceptible to rota- and reovirus-induced disease than adult animals [37–40] . We therefore asked whether the compartmentalized IFN response pattern , unique for the intestinal mucosa , might have more pronounced consequences for young animals . Two-days-old wild-type , Ifnlr1-/- and Ifnar1-/- animals were orally infected with reovirus , and viral titers in small intestine and colon were analyzed on day 4 post-infection . Contrary to the situation in adult mice , reovirus grew extremely well in the gut tissue of suckling Ifnlr1-/- mice , and virus titers in the small intestine ( Fig 4A ) and colon ( S5A Fig ) of such animals were significantly higher than in Ifnar1-/- mice . Immunohistochemistry revealed heavy infection of IECs in the terminal small intestine ( Fig 4B ) and colon ( S5B Fig ) of Ifnlr1-/- mice , whereas the virus was largely localized to the lamina propria region of the small intestine ( Fig 4B ) in Ifnar1-/- mice . Quantification of virus-infected cells demonstrated a striking differential cell tropism of reovirus to epithelial and non-epithelial cells in the small intestine depending on whether the receptors for IFN-α or IFN-λ were defective ( S5C Fig ) . Low levels of infectious reovirus were measured in intestinal tissue of wild-type mice ( Fig 4A ) , but no viral antigen was detected by immunostaining ( Fig 4B ) . Under these experimental conditions , Ifnar1-/- mice developed neurological symptoms and succumbed to reovirus infection within 5–7 days ( Fig 4C ) . Ifnlr1-/- mice displayed no early neurological symptoms . However , on day 9 post-infection they started to develop symptoms typical for oily hair syndrome [40] accompanied by arrest of weight gain . By day 13 , all reovirus-infected Ifnlr1-/- animals had died or had to be sacrificed due to severe disease ( Fig 4C ) . The majority of reovirus-infected wild-type pups showed normal weight gain until day 11 , when some animals started to develop neurological symptoms followed by a sudden weight loss and death over the next few days ( Fig 4C ) . After oral infection of suckling mice , reovirus type 3 may spread to the intrahepatic biliary epithelium ( cholangiocytes ) and to the brain , causing either liver disease or lethal encephalitis [40–43] . To determine whether the oily hair syndrome , observed in infected Ifnlr1-/- mice , was due to preferential replication of reovirus in biliary epithelial cells , we stained the liver and extrahepatic biliary tubules for virus antigen at day 4 post-infection . In these animals , large amount of reovirus antigen was indeed detected in extra- and intrahepatic cytokeratin-positive biliary epithelial cells , but seemingly not in any other cell type ( Fig 4D and 4E ) . By contrast , reovirus-positive cells were present throughout the liver and detected adjacent to epithelial cells of the extrahepatic bile ducts of Ifnar1-/- mice , whereas the epithelium was largely virus free ( Fig 4D and 4E ) . No virus antigen-positive cells were present in either the liver or the bile ducts of wild-type mice ( Fig 4D and 4E ) . Analysis of tissues from Ifnlr1-/- mice that succumbed to the disease revealed destruction of the biliary epithelium , accumulation of virus antigen and blockade of the bile ducts ( Fig 4F ) . H&E staining of the liver tissue on day 4 post-infection revealed inflammatory cells in all reovirus-infected animals with infiltrates localized predominantly around intrahepatic bile ducts in Ifnlr1-/- mice ( S5D Fig ) . Taken together , these infection studies demonstrated a clear functional separation of the type I IFN and the IFN-λ system in antiviral defense of the gastrointestinal mucosa . They further revealed that reovirus can specifically target cholangiocytes of Ifnlr1-/- mice which prominently express functional IFN-λ receptors [44] . To characterize the mucosal IFN system in more detail , we analyzed reovirus replication in intestinal tissue of suckling mice at day 1 and day 4 post-infection . On day 1 , high level reovirus was detected in both wild-type and mutant mice by titration and RT-qPCR . Virus was largely cleared in wild-type mice by day 4 , but was still present in guts of Ifnar1-/- and Ifnlr1-/- mice ( Figs 5A and S6A ) . RT-qPCR analysis of RNA isolated from the whole intestinal tissue revealed strong expression of the IFN-regulated genes Isg15 and Oasl2 in wild-type and Ifnar1-/- mice on day 1 ( Fig 5B ) . By contrast , Ifnlr1-/- mice failed to mount a proper IFN response on day 1 and showed a strongly attenuated response on day 4 post-infection ( Fig 5B ) . A similar picture emerged when isolated IEC fractions rather than whole tissues were analyzed ( S6B Fig ) , indicating that the protective response in the gut is predominantly mediated by IFN-λ , which is produced quickly after virus infection . To visualize the virus-induced IFN response in the intestinal mucosa in time and space , we immunostained tissue sections from infected suckling mice for reovirus antigen and Mx1 at 1 and 4 days post-infection . At day 1 , a large number of virus-positive IECs were detectable in the terminal part of the small intestine of wild-type , Ifnar1-/- and Ifnlr1-/- mice ( Fig 5D ) . High levels of nuclear Mx1 were detectable in the majority of IECs in tissue samples from wild-type and Ifnar1-/- animals already at day 1 post-infection . In contrast , no Mx1 signals were detected in tissue from Ifnlr1-/- mice at this time point ( Fig 5D , right panels ) , confirming that early responses are due to IFN-λ in the epithelium . At the early time post-infection , lamina propria cells that readily respond to exogenous type I IFN ( see Fig 1 ) did not contain detectable levels of Mx1 in wild-type or Ifnlr1-/- , suggesting that type I IFN production was low . By day 4 post-infection , wild-type animals had largely cleared the virus , whereas the intestinal tissue of Ifnar1-/- and Ifnlr1-/- mice was still heavily positive for reovirus antigen . Interestingly , on day 4 post-infection the vast majority of infected cells in Ifnar1-/- mice were located in the lamina propria region and not the epithelium as on day 1 , whereas virus antigen remained associated with IECs in Ifnlr1-/- mice ( Fig 5D , right panels ) . Virus clearance from IECs of wild-type and Ifnar1-/- mice by day 4 correlated with a strong IFN-λ-induced antiviral state , visualized by strong epithelial Mx1 staining . In Ifnlr1-/- mice , however , only a small fraction of villi were positive for Mx1 at this late time point , indicating that IFN-λ-independent antiviral responses were induced in only a small fraction of IECs by day 4 ( Fig 5D ) . These data , together with RT-qPCR analysis of ISG expression ( Fig 5B ) , demonstrate that during enteric virus infection type I IFN cannot compensate for the loss of IFN-λ , leading to prolonged replication of the virus in epithelial cells . Minimal Mx1 expression was detected in cells of the lamina propria region . Nevertheless , these cells remained protected from reovirus in wild-type and Ifnlr1-/- mice , suggesting that type I IFN production during reovirus infection was low but protective ( Fig 5D ) . Type I IFN that restricts systemic reovirus spread and protects mice against lethal infection is produced by dendritic cells [17] . IFN-λ production in virus-infected gut has to date not been analyzed . Earlier observations suggested that cells derived from the gut epithelium are potent producers of IFN-λ ( see Fig 2 ) . We therefore directly measured the expression of IFN genes by RT-qPCR in IEC fractions isolated from mock- and reovirus-infected mice . Ifnl2/3 but not type I IFN genes were significantly induced in cells from wild-type mice on day 1 post infection ( Fig 5C ) . In IEC preparations from Ifnlr1-/- mice that are highly susceptible to reovirus infection , induction of the Ifnl2/3 genes was nearly 100-fold higher than in infected wild-type mice , whereas type I IFN genes were not expressed at enhanced rates at this early time point ( Fig 5C ) . Our data demonstrates that IFN-λ produced by cells of the gut epithelium drives the early antiviral response that largely clears the virus from epithelial cells by day 4 . Type I IFN appears to play no major role at this early stage of the reovirus infection . It rather prevents systemic virus spread .
The major conclusion from the experiments described here is that the intestinal mucosa possesses a highly compartmentalized IFN system that acts in concert to restrict enteric virus replication , and that the gut epithelium represents a unique cell compartment in the organism that does not strongly rely on IFN-α/β for antiviral defense but rather uses IFN-λ . We found that IFN-α/β was unable to induce the expression of antiviral genes in the intestinal epithelium and failed to protect these cells from infection with an enteric virus due to low expression of the IFN-α/β receptor complex . In contrast , IFN-λ induced robust antiviral protection in IECs . IFN-λ but not IFN-α/β genes were expressed at low but detectable levels in the gut mucosa of uninfected animals , and the gut epithelium produced high amounts of IFN-λ but not IFN-α/β in response to treatment of mice with an IFN-inducing chemical or after reovirus infection . Thus , the intestinal epithelium and the lamina propria are two compartments of the gut that not only preferentially produce but also preferentially respond to different types of IFN . Mice lacking a functional IFN-α/β receptor show high susceptibility to a large number of viruses , including some attenuated virus strains which fail to induce disease in wild-type animals [2 , 4 , 14] . Interestingly , however , rotaviruses that preferentially infect the intestinal epithelium , are only moderately restricted by signaling through the type I IFN receptor [18 , 21 , 23] , a finding that can easily be explained by the observation described in this report that IECs express the IFN-α/β receptor at only very low level . Likewise , norovirus replication in the gut is restricted by IFN-λ , whereas type I IFN controls norovirus replication in extra-intestinal sites [45] . Recent experimental evidence indicates a role of IFN-λ in virus control at various epithelial surfaces others than the gut [15 , 44] . However , it appears as if the contribution of IFN-λ at these other sites , including the lung , is mostly inferior to that of type I IFN . The reovirus data presented here explain our earlier observations with murine rotavirus which had pointed toward a non-redundant role of IFN-λ in epithelial cells of the intestinal tract [23] . Because reovirus can vigorously replicate in the epithelium of IFN-λ receptor-deficient mice , it has easy access to the gut lumen and is excreted in feces at high levels . The comparatively low fecal shedding of reovirus observed in IFN-α/β receptor-deficient mice might be explained by a barrier function of the largely virus-free epithelial layer that physically separates virus-producing lamina propria cells from the gut lumen . We previously reported a significant role for IFN-λ in fecal shedding of rotavirus by adult mice [23] . We further reported that the respiratory SARS-CoV can be detected in feces of mice lacking both IFN receptor systems , but not in mice that only lack receptors for IFN-α/β [14] . Consistently , the Stat1 and Ifnlr1 but not the Ifnar1 genes were recently shown to limit fecal norovirus shedding in mice [45] . Collectively , these results point to a substantial importance of IFN-λ in restricting virus excretion . We assume that other cytokines such as IFN-γ might also contribute , but this was not investigated here . Since the fecal-oral route is the major mode for transmission of enteric human viruses , such as poliovirus , norovirus , rotavirus , hepatitis E and A viruses , it is tempting to speculate that IFN-λ helps limiting excretion of these important human pathogens . Plasmacytoid dendritic cells are very potent producers of biologically active IFN-α/β and IFN-λ [17 , 46 , 47] , but most other cell types are also able to express IFN genes upon virus infection . Several recent studies suggested that cells of epithelial origin , such as the respiratory epithelium , keratinocytes and hepatocytes are potent producers of IFN-λ in virus-infected hosts [48–55] . We found that both IECs and hematopoietic cells in the epithelium strongly expressed IFN-λ but not IFN-α/β genes quickly after stimulation with poly ( I:C ) and in response to reovirus infection . Thus , the mucosal epithelium has evolved mechanisms to specifically produce IFN-λ . As similar signaling pathways are believed to control the expression of IFN-α/β and IFN-λ genes [56] , this observation is surprising and suggests that the induction of genes encoding IFN-α and IFN-β is specifically blocked in IECs by an unknown mechanism . In polarized intestinal epithelial cells peroxisome-bound MAVS may preferentially trigger expression of IFN-λ genes [57] , offering a potential explanation for our observations . Orally administered reovirus has a broad tissue tropism in IFN-α/β receptor-deficient mice , infecting hepatocytes , myocardiocytes and many other cells , eventually causing a fatal disease [17 , 34] . We found that suckling mice lacking functional receptors for IFN-λ showed a milder disease than IFN-α/β receptor-deficient mice , although virus titers in the gastrointestinal tract of the IFN-λ receptor-deficient animals were substantially higher . This can probably be explained by the fact that severe damage of the gut epithelium has no immediate lethal consequences . Interestingly , reovirus-infected suckling mice deficient in functional receptors for IFN-λ showed symptoms resembling biliary atresia [58] , which included oily fur syndrome and liver inflammation . Biliary atresia is a rare disease affecting one in 10 , 000 infants with etiology and pathology largely unknown . Infection with various viruses , including reovirus type 3 , has been proposed to be associated with the disease in children [59 , 60] . Infection of mice with certain strains of rota- and reoviruses can reproduce most features of the human disease [61 , 62] . We detected virus antigen in cholangiocytes of our IFN-λ receptor-deficient but not wild-type or IFN-α/β-deficient mice that were infected with reovirus at early age , strongly suggesting that IFN-λ plays a decisive role in defending the biliary tract against viruses . This conclusion is consistent with our recent finding that mouse cholangiocytes are readily responding to exogenous IFN-λ [44] . Based on the results of our mouse model system , it is conceivable that children with biliary atresia may have genetic defect in their IFN-λ system . Considering the fact that most cell types in the body are protected by IFN-α/β , our finding that type I IFN plays a negligible role in the gut epithelium is intriguing . In this context it is important to note that IFN-α/β is a double-edged sword . Besides inducing and regulating innate and acquired immunity against pathogens and tumors , IFN-α/β can also induce excessive inflammation ( reviewed in [63] ) [64] . Chronic virus infections , such as HIV or LCMV , can lead to lymphocyte dysfunction due to prolonged IFN signaling [20 , 65] or refractoriness to IFN stimulation in hepatocytes in the case of HCV [66] . Therefore , it is tempting to speculate that the gut epithelium , which is in constant contact with commensal bacteria , has lost the ability to produce and respond to IFN-α/β due to its potential negative effects .
All mice used in the study were bred locally in our facility and handled in accordance with guidelines of the Federation for Laboratory Animal Science Associations ( www . felasa . eu/recommendations ) and the national animal welfare body ( Gesellschaft für Versuchstierkunde; www . gv-solas . de/index . html ) . Animal experiments were performed in compliance with the German animal protection law ( TierSchG ) and approved by the local animal welfare committee of the University of Freiburg ( permit G-12/93 ) . The mouse strains used have been described earlier [16] . Briefly , B6 . A2G-Mx1 wild-type mice carry intact Mx1 alleles ( wild-type ) , B6 . A2G-Mx1-Ifnar1-/- mice lack functional IFN-α/β receptors ( Ifnar1-/- ) , B6 . A2G-Mx1-Ifnlr1-/- mice lack functional IFN-λ receptors ( Ifnlr1-/- ) , and B6 . A2G-Mx1-Ifnar1-/—Ifnlr1-/- double-knockout mice ( Ifnar1-/-Ifnlr1-/- ) lack functional receptors for both IFN-α/β and IFN-λ . Newborn mice weighing 1 . 5 to 2 g or young adult mice ( 6–8 weeks of age ) were used for experiments . Reovirus type 3 Dearing strain was propagated on mouse fibroblast cell line L929 maintained in DMEM medium supplemented with 10% FCS . Newborn mice were orally inoculated with 5 μl of cell culture supernatant containing 5x106 pfu of virus . Adult mice were intra-gastrically inoculated with 100 μl of virus ( corresponding to 108 pfu ) using a 22G gastric gavage needle . Viral titers from feces and tissue homogenates were determined by plaque assay on L929 cells . Briefly , tissue was homogenized in 800 μl of PBS and feces in 500 μl of PBS using the FastPrep apparatus ( MP Biomedicals ) . The homogenates were treated with chloroform ( 10% final concentration ) , centrifuged briefly and serial dilutions of the aqueous supernatants were incubated on L929 cells at room temperature . After 1 h , the inoculum was removed and cells were covered with 1 . 5% AVICEL in 1x DMEM medium containing 0 . 1% BSA . After four days medium was removed , cells were fixed with 4% paraformaldehyde and plaques were visualized with 0 . 5% crystal violet . One μg of hybrid human IFN-αB/D [67] or mouse IFN-λ2 ( IL-28A; PeproTech ) were subcutaneously injected in 100 μl of PBS . 100 μg of poly I:C was injected intraperitoneally in 200 μl of PBS . Tissue was fixed in 4% paraformaldehyde at 4°C for 24 h and embedded in paraffin . Antigen retrieval on deparaffinized 5-μm tissue sections on glass slides was performed in 0 . 01 M sodium citrate buffer at 121°C for 10 min . Tissue was permeabilized in 0 . 05% Triton-X100 and blocked with 10% normal donkey serum ( Jackson ImmunoResearch ) for 1 h at room temperature . Sections were incubated overnight at 4°C with rabbit-anti-reovirus T3D antiserum ( a generous gift from T . Dermody , Vanderbilt University ) , mouse-anti-Mx1 monoclonal antibody M149 [68] , rabbit anti-Mx1 polyclonal antiserum ( AP5 ) [40] or mouse monoclonal anti-pan cytokeratin ( Sigma ) , followed by the appropriate AF555- , AF488- , Cy3- , or Cy5-conjugated secondary antibody ( Molecular Probes , Jackson ImmunoResearch ) . E-cadherin was stained with AF647-conjugated monoclonal mouse anti-E-cadherin antibody ( BD Bioscience Pharmingen ) . Slides were mounted in DAPI-containing Vectashield ( Vector Laboratories ) . Tissue sections were stained for reovirus antigen and , simultaneously , E-cadherin to identify epithelial cells . The numbers of reovirus-positive cells expressing or lacking the E-cadherin were assessed by evaluating virus antigen-reactive cells in 3 visual fields of gut sections derived from at least 3 individual Ifnar1-/- and Ifnlr1-/- mice . Isolation of intestinal epithelial cells and lamina propria leukocytes was performed as described previously [69] . Briefly , the whole small intestine was harvested , cut open longitudinally and washed briefly in PBS . Dissociation of epithelial cells was performed by incubation at 37°C in HBSS containing 5 mM EDTA and 10 mM Hepes on a shaker for 20 min . The remaining tissue was cut into pieces of approximately 1 mm2 before enzymatic digestion with 5 U/ml dispase ( BD ) , 0 . 5 mg/ml collagenase D ( Roche ) and 0 . 5 mg/ml DNaseA ( Sigma-Aldrich ) . Lymphocyte enrichment was performed by Percoll ( Sigma-Aldrich ) gradient centrifugation . The purity of isolated IEC and LPL fractions was confirmed by analyzing expression of epithelial ( Cdh1-encoding E-cadherin ) and leukocyte ( Ptprc-encoding CD45 ) marker genes . Single-cell suspensions of lamina propria lymphocytes were analyzed using a FACS Canto II flow cytometer and the FACS Diva software ( BD Biosciences ) . For data analysis , FlowJo V9 . 2 software ( TreeStar ) was used . To analyze cell surface expression of the IFN α/β receptor 1 chain , PE-labeled monoclonal antibody MAR1-5A3 ( eBioscience ) was used . For sorting of intestinal epithelial cells and lymphocytes , the small intestines were cut into pieces of 1 mm2 and subjected to enzymatic digestion as described above . After blocking of Fc receptors with CD16/CD32 antibodies , single-cell suspensions were incubated with fluorescent conjugated antibodies against CD45 and EpCAM . After washing , cells were incubated with 4' , 6-diamidino-2-phenylindole ( DAPI ) for exclusion of dead cells and sorted using a BD FACSAria III cell sorter ( BD Biosciences ) . RNA was isolated with Trizol reagent ( Invitrogen ) according to manufacturer’s instructions . One μg of RNA was reverse-transcribed using QuantiTect Reverse Transcription Kit ( Qiagen ) . Real-time PCR was performed using the QuantiTect SYBR Green PCR Kit ( Qiagen ) or TaqMan Universal Master Mix with gene specific probes ( Applied Biosystems ) and run on an ABIPrism 7900 sequence detector ( Applied Biosystems ) . Samples were normalized to the expression of Hprt . The following mouse specific TaqMan assays were used: Hprt: Mm00446968_m1 , Ifnl2/3: Mm04204156_gH , Ifna5: Mm00833976_s1 ( Life Technologies ) . The following primers were used for SYBR Green based assays: Ifnb: forward , 5’- TCAGAATGAGTGGTGGTTGC -3’ , reverse , 5’- GACCTTTCAAATGCAGTAGATTC -3’ , Isg15: forward , 5’- GAGCTAGAGCCTGCAGCAAT -3’ , reverse , 5’- TTCTGGGCAATCTGCTTCTT -3; Oasl2: forward , 5’- GGATGCCTGGGAGAGAATCG -3’ , reverse , 5’- TCGCCTGCTCTTCGAAACTG -3’; Ifnlr1: forward 5’- GGAACTGAAGTACCAGGTGGA -3’ , reverse 5’- GCCATAGGGAGTGTCAGGAA -3’; Il10rb: forward , 5’- TCTCTTCCACAGCACCTGAA -3’ , reverse , 5’- GAACACCTCGCCCTCCTC -3’; Ifnar1: forward , 5’- CATGTGTGCTTCCCACCACT -3’ , reverse , 5’- TGGAATAGTTGCCCGAGTCC -3’; Ifnar2: forward , 5’- GACCTTCGGATAGCTGGTGG -3’ , reverse , 5’- CTCATGATGTAGCCGTCCCC -3’; Ptprc: forward , 5’-GAACTAAAACACATCTGGGAAAAATTA-3’ , reverse , 5’-GCTTTCATGGTTGTTTTCACC-3’; Cdh1: forward , 5’-CAGGTCTCCTCATGGCTTTGC-3’ , reverse , 5’-CTTCCGAAAAGAAGGCTGTCC-3’ . Testing for statistical significance was performed on log-transformed viral titers by Student’s unpaired t-test or One-way ANOVA and Bonferroni multiple comparison test using Prism 4 software ( GraphPad Software ) . | Virus-induced interferon consists of two distinct families of molecules , IFN-α/β and IFN-λ . IFN-α/β family members are key antiviral molecules that confer protection against a large number of viruses infecting a wide variety of cell types . By contrast , IFN-λ responses are largely confined to epithelial cells due to highly restricted expression of the cognate receptor . Interestingly , virus resistance of the gut epithelium is not dependent on IFN-α/β but rather relies on IFN-λ , questioning the prevailing view that receptors for IFN-α/β are expressed ubiquitously . Here we demonstrate that the IFN-α/β system is unable to compensate for IFN-λ deficiency during infections with epitheliotropic viruses because intestinal epithelial cells do not express functional receptors for IFN-α/β . We further demonstrate that virus-infected intestinal epithelial cells are potent producers of IFN-λ , indicating that the gut mucosa possesses a compartmentalized IFN system in which epithelial cells predominantly respond to IFN-λ , whereas other cells of the gut mainly rely on IFN-α/β for antiviral defense . We suggest that IFN-λ may have evolved as an autonomous virus defense system of the gut mucosa to avoid unnecessarily frequent triggering of the IFN-α/β system which , due to its potent activity on immune cells , would induce exacerbated inflammation . | [
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] | [] | 2015 | Leukocyte-Derived IFN-α/β and Epithelial IFN-λ Constitute a Compartmentalized Mucosal Defense System that Restricts Enteric Virus Infections |
The objective of this paper is to report evaluated observations from survey records captured through a cross-sectional observational study regarding canine populations and dog owners in rabies enzootic KwaZulu-Natal province , South Africa . Our aim was to evaluate respondent knowledge of canine rabies and response to dog bite incidents towards improved rabies control . Six communities consisting of three land use types were randomly sampled from September 2009 to January 2011 , using a cluster design . A total of 1992 household records were analyzed using descriptive statistics and regression modeling to evaluate source of rabies knowledge , experiences with dog bites , and factors affecting treatment received within respective households that occurred within the 365 day period prior to the surveys . 86% of the population surveyed had heard of rabies . Non-dog owners were 1 . 6 times more likely to have heard of rabies than dog owners; however , fear of rabies was not a reason for not owning a dog . Government veterinary services were reported most frequently as respondent source of rabies knowledge . Nearly 13% of households had a member bitten by a dog within the year prior to the surveys with 82% of the victims visiting a clinic as a response to the bite . 35% of these clinic visitors received at least one rabies vaccination . Regression modeling determined that the only response variable that significantly reflected the likelihood of a patient receiving rabies vaccination or not was the term for the area surveyed . Overall the survey showed that most respondents have heard of dog associated rabies and seek medical assistance at a clinic in response to a dog bite regardless of offending dog identification . An in-depth study involving factors associated within area clinics may highlight the area dependency for patients receiving rabies post exposure prophylaxis shown by this model .
Rabies kills tens of thousands of people in developing countries each year , and it is estimated that almost half of global rabies incidences occur in Africa [1]–[2] . However , one major factor compounding the problems of rabies is a high probability of disease underreporting . Studies in Tanzania , for example , indicated that there are ten cases for every one officially reported [1] . Once clinical signs of encephalitis become apparent , human rabies is virtually untreatable [3] . Although there has been at least one bona fide case of survival using intensive care treatment , much remains to be understood about factors determining the outcome of such treatment procedures while the required facilities and cost of procedure put such interventions outside the reach of those countries where dog and human rabies is most prevalent [4] . Reliance on proper wound management , and timely post exposure prophylaxis ( PEP ) [appropriate administration of vaccine and immunoglobulin] , is crucial to the prevention of human rabies in exposed persons . From the above perspective , rabies deaths in Africa are linked to ignorance and poverty . People from rural areas and young children , lacking knowledge of rabies and thus the requirement and urgency of PEP , are most frequently affected [5] . In just one example , from a relatively progressive African state , viz . South Africa , it was shown that half of the laboratory confirmed cases from 2008 did not seek any medical intervention after dog bite exposure [6] . Although rabies PEP is free of charge for bite victims in South Africa , the full post exposure treatment with vaccine and immunoglobulin G costs the South African health system more than USD $152 per individual [7] . KwaZulu-Natal ( KZN ) , one of nine provinces , is located on the east coast of South Africa ( Figure 1 ) with an area of 94 , 361 km2 and a human population last estimated at 10 , 819 , 130 with a growth rate of 1 . 2% for all races of people [8] . KZN contains just over 21% of the total human population for South Africa despite the province being only 7 . 7% of the country's land mass . Over 84% of the population is black African , mostly of Zulu cultural origin [8] . It is thought that canine rabies spread to KZN from adjacent Mozambique during the 1960's . Although the disease was then eradicated through the use of mass vaccination campaigns and dog control , rabies was reintroduced in the mid 1970's and has been enzootic to KZN ever since [9] . Historically , most of the human rabies cases in South Africa over past decades have been from KZN . Many dogs in South Africa are not immunized against rabies despite laws mandating vaccination , and KZN is no exception . High dog population turnover , lax enforcement of government regulations and interruptions in vaccination campaigns are all likely factors that contribute to low rabies immunization coverage . In this regard , rabies does not generally appear to enjoy appropriate public health priority in African countries . Poor reporting and poor surveillance , resulting in an apparent lack of political commitment to rabies control , seems to be common practice . In this study it was our objective to better quantify issues such as the above , for the particular region of KZN . Here we analyze the responses to dog bites in an area that has been dog rabies-enzootic for decades , and where control has been attempted for an equal period of time . A better understanding of the societies and practices involved , including knowledge and awareness , would be crucial in improving a disease situation that has been ongoing for the past 40 years . As part of a comprehensive rabies control program , we have queried a representative sample of several population segments of the KZN province about rabies knowledge , interest in enforcement of animal control laws and in community based surveillance .
From September 2009 through January 2011 , household surveys were conducted in six different communities across KZN province , covering three land use types: rural , urban and peri-urban ( Figure 1 ) . Distribution of the 1992 households completing the surveys was 52% rural , 33% urban and 15% peri-urban . Rabies was enzootic in all areas , with the exception of the peri-urban community of Wembezi . Affluent urban and suburban areas where people keep dogs in confined spaces most likely have lower rabies risk due to fewer affective contacts between animals and easier access to veterinary services and were therefore excluded [10] . Poorer urban townships and rural villages most frequently represent the areas from where canine rabies is reported ( KZNDAERD unpublished data ) . The study areas were selected with the assistance of the KZN Department of Agriculture and Environmental Affairs and Rural Development ( KZNDAERD ) , Veterinary Services division . Simple random sampling and systematic surveys are difficult in developing countries due to logistical and sometimes adverse cultural reasons [11] . Random sampling using a cluster or ‘area’ design was used because homesteads in rural areas are not numbered and informal housing settlements within townships frequently are arranged haphazardly [12] . Based upon World Health Organization guidelines [13] the questionnaires were composed of two parts; a household survey for collecting demographics and community opinions , and an individual dog survey for descriptive statistics of the owned dog population . Though the primary objective of the surveys was to gain provincial dog demographics , respondents were asked exploratory questions regarding their knowledge of rabies , histories of dog bites and response to those incidents in consideration of possible future studies . Respondents were also queried about their interest in animal-law enforcement , animal ownership regulations and community based surveillance . The surveys were translated into isiZulu and then back translated to English before being piloted in a township with similar human demographics and a history of canine rabies . The survey tool was refined prior to use in this study and the final questionnaires were well received by both the surveyors and the target population with no further improvements or modifications required . KZNDAERD Animal Health Technicians and students , Department of Health workers , Environmental Health workers and SPCA employees were trained to perform the surveys . Surveyors were instructed to introduce themselves to household respondents and explain the purpose of the questionnaire prior to asking their permission to carry out the survey . Surveyors wore name tags which had ‘Rabies Surveillance Team’ printed in large block letters with a bright red border and the Departmental insignia as an identification aid . Prior permission to conduct the surveys had been sought from municipal counselors . All interviews were conducted between the hours of 9 am and 3 pm . The data from each area was entered into a Microsoft Excel spreadsheet and then imported into SAS version 9 . 3 ( SAS Institute , Inc . , Cary , North Carolina , USA ) . Descriptive statistics were generated , and cross tabulations calculating Pearson's Chi Square ( χ2 ) were performed in tests of association . A logistic regression model was built using SAS to predict outcomes of human dog bite victims receiving rabies PEP [14] . The study was approved by the University of Pretoria , Veterinary Faculty Research Committee at Onderstepoort campus . An application for the non-experimental use of animals was approved by the Animal Use and Care Committee from the University of Pretoria . Interviewed subjects were provided informed consent orally in their native language as was stated in the research proposal approved by the Research Committee . The purpose of the survey interview was explained to each participant by the interviewer , who could either accept or decline to participate in the survey . If the respondent declined to be interviewed it was marked at the top of the survey form , whereas those who agreed to be interviewed had a third party witness to this verbal agreement , and the interview was continued .
A total of 1992 households consisting of 13 , 756 people ( range 1–34 , median = 6 ) completed the surveys within the three targeted community types . Surveys were answered by a person defined as head of the household in 68% ( 1361/1992 ) of the cases across the province ( range 63–76% ) . The sex of the respondent was not recorded . Of the remaining cases , 11 comprised interviews with children under the age of fourteen years of age in the presence of an older relative who consented to the child answering questions . Another 183 children over the age of fourteen years were interviewed at homes where adults were not present . In 435 surveys , an adult other than the head of the household responded to interview questions . In 2 cases the category of the respondent was missing . Eighty-six percent of the population ( 1716/1992 ) surveyed across the province had heard of the disease called rabies ( Figure 2 ) . No attempt was made to evaluate the individual's depth of rabies knowledge . Some respondents stated that they did not truly know the source of rabies or how to prevent it . However , it was clear that some respondents knew that vaccination of dogs was important to the safety of people in the community based upon their remarks . There was no significant relationship found between area surveyed and respondent knowledge of rabies ( χ2 = 10 . 864 , df = 5 , p = 0 . 541 ) . When surveyed areas were grouped by land use , 81% of the peri-urban society had some knowledge of rabies , whereas 87% of rural and 88% of urban citizens had knowledge of rabies . Surprisingly , non-dog owners were 1 . 6 times more likely to have heard of rabies compared with dog owners . No respondents stated that fear of rabies infection was a reason for not owning a dog . Persons who responded that they did have some knowledge of rabies were further queried as to the source of their knowledge . Government Veterinary Services Animal Health Technicians have the role of visiting schools and educating children about rabies . Among other resources , they utilize a government prepared video entitled “If I Only Knew” and various informative pamphlets discussing rabies . We found that schools and school children accounted for 19% of the population's knowledge source across the province . However , there was not a significant relationship between the presence of school children and knowledge of rabies in individual households ( χ2 = 0 . 027 , df = 1 , p = 0 . 868 ) . Less than two percent of the surveyed population indicated that they have acquired rabies knowledge from the local health clinic . Since one objective of our research was to understand where citizens were able to receive valuable information about rabies , any viable source was noted and utilized as an element of feedback for the development of future programs employed by the government departments responsible for human and animal health . Public print and broadcast media were cited highest among non-dog owners as their source of rabies knowledge , whereas government sponsored campaigns were most frequently cited from dog owners ( Figure 3 ) . 12 . 7% ( 95% CI 11 . 3–14 . 2 ) of the 1992 households in the areas surveyed reported that at least one member of the household had been bitten by a dog in the past year . Age of bite victim was not recorded . The lowest incident rate was in Esikhawini ( urban ) and the highest incidence occurred in Wembezi ( peri-urban ) . Across KZN , significantly more people who did not own dogs had been bitten by a dog than those who did own a dog ( χ2 = 9 . 477 , df = 1 , p = 0 . 002 ) . Among victims who were dog owners the number of dogs owned did not make a difference in dog bite incidence . Although 33% ( 667/1992 ) of households reported feeding of dogs that they did not own ( on their property ) , there was not a significant relationship between being bitten by a dog and feeding other dogs on the property ( χ2 = 3 . 424 , df = 1 , p = 0 . 064 ) . As a follow up question , households with recent dog bite victims were asked if they knew the aberrant dog involved in the incident ( Figure 4 ) . Identification of the offending dog was missing in 10% ( 26/253 ) of recorded cases . In 71% of records where the dog was identified , the neighbor's dog had bitten the victim . Only 12% of victims had been bitten by their own dog and 17% of victims had been bitten by a dog with which they were unfamiliar . Unknown dogs were referred to as strange dogs rather than stray dogs , as the animal could be owned but unrestricted . Historically there have been concerns about people in rural areas visiting traditional healers rather than attending a clinic after a dog bite event . Sudarshan et al [15] showed that 60% of dog bite victims in India who succumbed to rabies had sought some kind of indigenous treatment following the incident , receiving either magico-religious practices or some kind of herbal therapy . After a recent emerging rabies epidemic in the Limpopo province of South Africa ( 2005–2006 ) , it was established that 20% of the fatal human rabies case patients saw a traditional healer prior to attending hospital [16] . In this survey in KZN , less than 2% ( 4/253 ) of dog bite victims , all of whom were from rural areas , reported resultant visits to a traditional healer . With regard to the washing of bite wounds as a first response to incident , only 8% of victims mentioned washing the wound . We found that 56% ( 1115/1992 ) of domiciles visited in our surveys had either a pit latrine or no toilet facilities , indicative of a lack of running water at the household level . In some rural areas a public tap was available some distance from the house . In other rural areas , people made use of rivers or streams for daily water . In the six areas surveyed , over 80% ( 207/253 ) of victims visited a clinic as a response to dog bite incident except in the rural area of St . Chad's ( Figure 5 ) . This area alleged the highest rate of rabies knowledge ( 88% ) ( Figure 2 ) , but had the least number of visits to the clinic ( 54% ) as a response to bite incidence . St . Chad's has both a community health center and close access to neighboring community clinics and hospitals . Detailed questions that would uncover the decisions made by bite victims , actions taken and reasons for those actions were not asked . Those households with victims who had visited a clinic in response to a dog bite were asked what injections they had received ( Table 1 , Figure 6 ) . Twenty-four percent ( 50/207 ) of clinic visitors reported receiving no injections . Thirty-four percent ( 70/207 ) of respondents did not know the extent of treatment received , as it was either not explained to them , they could not remember or they did not attend the clinic with the victim . Thirty-five percent ( 73/207 ) of persons visiting the clinic received rabies vaccine , 5% received tetanus only and 1 . 4% received both rabies and a tetanus vaccine . Those victims who said they received rabies vaccine were not asked if they returned to the clinic to complete the World Health Organization recommended ( Essen schedule in the case of South Africa ) four injection series or if they received immunoglobulin in the case of category III bites [17] . Severity and location of bite wounds was not queried of respondents . An effort was made to determine if there was an association between those clinics where patients had received rabies vaccine and the area surveyed , whether the victim owned dogs , respondent knowledge of rabies and identification of offending dog . Fifty-two responses ( 20% ) were deleted from the model due to missing values for either the response or explanatory variables . In the final logistic regression model only the area surveyed significantly contributed to human rabies vaccination outcome ( Table 2 ) . The model appeared to fit the data ( Somer's D = 0 . 395 ) . The urban township of Esikhawini was the area with the most dog bite victims receiving rabies vaccine , while victims in urban Umlazi Township received the least ( Table 3 ) . Respondents were queried if they were interested in learning more about illnesses that could be shared between people and animals . Ninety-four percent of the population surveyed across the province ( 1865/1992 ) said they would be interested in gaining information about zoonotic disease potential in their community . The urban area of Umlazi , where only 88% of the respondents answered agreeably , stood out as the only area where there are a significant number of respondents who were disinterested in zoonoses ( χ2 = 30 . 581 , df = 10 , p = 0 . 001 ) . Respondents were asked if they would , as witnesses , be interested in reporting ill dogs , strange behavior or dog bite incidents occurring in their communities . The majority of respondents across all communities were interested in reporting such sightings; however , the peri-urban and urban communities had significantly less interest than the rural areas in community based reporting ( χ2 = 22 . 120 , df = 5 , p = 0 . 000 ) ( Figure 7 ) . Respondents answering in the affirmative were further queried as to whom in the community they would want to report these incidents . Nearly 40% identified government veterinary services when considering reporting sick dogs and possible rabies cases ( Figure 8 ) . Other parties mentioned were the local clinic , a teacher , the dog's owner , or SPCA . However , community members regularly stated that despite their desire to report , they had no contact information for either veterinary services or the SPCA . Other than dogs , 2 potential rabies maintenance hosts present in KZN are mongooses and jackals . Bat eared foxes , which maintain rabies in the western provinces of South Africa [18] , are rarely seen in KZN . Questioning respondents about sightings in their community served as a screening tool for the possibility of further studies concerning wildlife and the spread of rabies in KZN . Overall , less than 22% of the respondents across the province encountered either of these wildlife species in their communities ( Figure 9 ) . The rural tribal authority area outside of Pongola has dense flora and is located on the Swaziland border which could explain why there were so many more jackal sightings in this rural area versus any other . Despite South Africa possessing laws requiring vaccination and licensure of dogs , these regulations are rarely enforced . Respondents were asked if they desire law enforcement regarding removal of stray or unsupervised dogs ( Figure 10 ) . There was a significant difference in area type and desire for animal control law enforcement , with the least concern reported from the rural areas ( p = 0 . 0001 ) . Surveys respondents were asked if they desired laws that would limit the number of dogs that one household could own ( Figure 11 ) . The number of dogs owned by the dog owning households surveyed was similar between the rural and peri-urban households with an average of 2 . 47 dogs per dog owning household ( range 2 . 16–2 . 64 ) . Urban dog owning households had fewer dogs with the average being 1 . 66 ( range 1 . 64–1 . 68 ) . Some households in rural areas were recorded as owning up to 19 dogs . There was a significant difference between rural areas and the urban/peri-urban areas in desire for limitations on the number of dogs one household could own ( p = 0 . 0001 ) .
The results from this survey indicate that 86% of persons in high risk canine rabies areas of KwaZulu-Natal have at least heard of the disease even if they are unaware of the details surrounding transmission and consequences of exposure . The long history of enzootic canine rabies in the province and the continuous efforts put forth by the KZNDAERD- Government Veterinary Services appear to contribute the most ( 33% ) to this public awareness . Although 100% would be ideal , an 86% knowledge rate is better than was reported from other studies . In dog rabies enzootic Zimbabwe , for example , 74% of pet owners interviewed in Harare animal clinics were aware that rabies was transmitted to people by dogs [19] . Zimbabwean respondents also reported gaining information about other zoonotic diseases from their veterinarian . Respondents in KZN do not have local veterinary clinics as a resource from which to gain this knowledge . In the current study , the peri-urban working community of Wembezi had the lowest rate of rabies knowledge at 81% . This is interesting in that it is also the only community identified as being free of canine rabies for greater than 10 years per surveillance records from KZNDAERD . Thirty-nine percent of households in Wembezi owns at least one dog and has an estimated dog population of 2 , 916 ( Hergert unpublished data ) . Calculated dog density figures for Wembezi are similar to the urban areas surveyed in this study , where a slightly higher level of rabies knowledge was recorded . Non-dog owners were 1 . 6 times more likely to have heard of rabies versus dog owners . People who do not own dogs are gaining information about rabies from media sources , which had a value of almost 30% from respondents in all areas . This is similar to findings in the developed world – e . g . in Texas , USA 43% of non-pet owners reported learning about zoonotic diseases from the media or newspaper [20] . Media sources for rabies information may actually be viewed by both the dog owning and non-dog owning public; however , dog owners may be more likely to respond that their source of rabies knowledge was from government vaccination campaigns , as they would be attending these events . Therefore , a certain amount of bias may weigh towards government campaigns as a source for dog owners due to their familiarity . Understanding why more non-dog owners report knowing about rabies versus dog owners is unclear from this survey and would require further study . South African Government Veterinary Services has the task of informing people about rabies through vaccination campaigns and schools . When these two reported sources of knowledge are combined it is evident that Veterinary Services is responsible for 52% of the information gained by both the dog and non-dog owning public . However , there was not a significant relationship between household knowledge of rabies and knowledge source originating from schools . Veterinary Services of KZN might take into consideration when planning educational campaigns in their communities , that schools are not heavily targeted . Eighty-two percent of interviewed households contained school aged children; therefore , schools appear to be a viable outlet for the dissemination of rabies information . Human health clinics were reported as a knowledge source in less than 2% of responses . This result may support the findings from Francophone countries of Africa where medical authorities and health practitioners are reported to be under educated in the perils of rabies [5] . In Texas , USA , the family doctor was reported as the source of zoonotic disease information in only 6% of both pet and non-pet owning households [20] . Doctors were also indicated well below veterinarians and the media as a source of disease information in Zimbabwe [19] . Detailed examination into what transpires in KwaZulu-Natal clinics for dog bite case patients should be explored in the face of a One Health environment . Twelve percent of the households in the areas surveyed had someone bitten by a dog in the last year . Other animal bite victims in African countries have been identified through retrospective studies starting at the clinic or hospital level using a trace back system in order to locate and interview the victims in depth [21]–[22] . This type of retrospective study should be conducted in KwaZulu-Natal in order to gain further descriptive information of the dog bite incidence . The neighbor's dog was identified as the offending canine in 71% of bite cases in this survey . Only 12% of the people had been bitten by their own dog . However , 17% of victims had been bitten by a dog with which they were unfamiliar . These dogs were identified as strange rather than strays or feral dogs , as they could not be differentiated from owned free roaming dogs . Eighty-three percent of dogs in this study were identified as being fully or partially unrestricted , being allowed to wander at will . Over 96% of the human rabies cases in India from 1992 to 2002 resulted from a dog bite , with 75 . 2% resulting from stray dogs and 11 . 1% from pets [15] . In response to the dog bites more than 80% of people went to the clinic in all areas except for rural St . Chad's where only 54% of bite victims reported clinic visits . St . Chad's residents reported a high awareness of rabies ( 88% ) , which could be explained by the rabies epidemic experienced in the area a few months prior to the survey . This area has a community clinic , as well as other nearby clinics and hospitals reachable by taxi . Without in depth queries , the reason why more persons did not visit a clinic remains unknown . Despite concerns about delayed treatment after dog bites , less than 2% of victims in this study visited a traditional healer and all of those cases were from rural areas . Herbal therapy and magico-religious practices were sought by rabies bite victims in India in 60% of fatal cases [15] . Respondents in KZN may be more informed about rabies than persons in other developing countries . One survey respondent said that the reason he did not go to the clinic after being bitten by his neighbor's dog was because the neighbor could prove to him that his dog had been previously vaccinated against rabies . Therefore , the victim felt he was safe to treat the wound at home . The investigation , follow through and cognition shown by this respondent is not something that should be expected from most bite victims . Dog bite victims in this study tended to visit the clinic regardless of their familiarity with the dog that bit them . Of those victims that did attend a clinic 22–75% received at least one rabies vaccine . The lower end of this spectrum is similar to what was seen in India where only 21% of rabies victims had received at least one rabies vaccine [15] . The area with the lowest rabies vaccination treatments was urban Umlazi Township and the highest was urban Esikhawini Township . In the regression model predicting what factors had an important impact on the victim receiving a rabies vaccine , only the area surveyed was found to be significant ( p = 0 . 0001 ) . Health facilities in South Africa where rabies vaccine and immunoglobulin ( RIG ) are available are listed with telephone contact numbers in the national rabies guideline [23] . However , a nationwide telephonic survey , which included 50% of the facilities identified for KwaZulu-Natal , was conducted in order to confirm the availability of these products . Only 68% of all the sites surveyed across the country were contactable by telephone . Forty-one percent had both vaccine and RIG , 32% had only vaccine , 5% had only RIG and 21% had neither vaccine nor RIG available [24] . Considering the results of this telephonic survey it is quite conceivable that administration of rabies vaccine is area dependent across the country . The juxtaposition of Esikhawini Township to the Port of Richard's Bay could explain why this area , which had the lowest recorded number of dog bite cases , had the highest amount of rabies vaccine administered . The Richard's Bay area may have more rabies vaccine dispensed that are related to aspects about the constituents the medical community serves , or because the medical staff could be indiscriminately dispensing supplies regardless of exposure risk . In Francophone African countries accurate rabies data is scarce [5] . This may be true in other African countries as has been previously eluded from Tanzania [1] . This survey showed a large respondent willingness to participate in community based surveillance at the village level . Community based surveillance activities should be considered in countries which lack central political will or local municipal finances . However , it has been stated that passive systems in developing countries are ineffective; therefore , an economic community based active surveillance system is recommended [25] . Unfortunately , community based systems have been shown to fail , particularly when there is a discrepancy in the interpretation of needs between the community and the donor organization [26] . Therefore , the methodology to be employed would have to be developed from a grassroots level rather than at a higher administrative level , which would take a commitment not previously demonstrated from this rank of society . Persons living in communities at high risk for canine rabies are interested in animal control laws and regulations . However , there is an indication of concern in the rural areas that these laws would also limit the number of livestock owned . This result may be due to rural areas owning more livestock . An indirect association between the limitations on number of dogs allowed with restrictions on livestock ownership may be behind these results . In rural Texas , USA , a survey regarding cattle ownership conducted from Texas A&M University indicated that ranchers were reluctant to comply with trace back ear-tagging measures , as the procedure would identify to officials how many cattle were owned by each producer at any point in time ( Dominguez unpublished data ) . Responsiveness and dedication to upholding animal control laws in this cultural environment by obliged parties will have to be instilled in a generation of officers committed to uplifting the community . Crucially , since this simple intervention may be particularly effective in preventing infection , only 21 of the 253 people in our survey bitten by a dog washed their bite wound as a response to treatment . It has been established that washing the bite wound for 15 minutes with soap and water can help reduce the incidence of disease by eliminating or inactivating the virus [5] . As only 44% of households were reported as having indoor plumbing ( indicated by flush toilets ) lack of available fresh water may explain the low percentage of wound washing as a response to post-bite treatment .
This study shows that greater than 86% of the population has at least heard of the disease called rabies , but the response to dog bites indicates that both the general public and health sectors of the population do not understand the possible consequences related to dog bites in rabies enzootic environments . Availability of vaccine is an important factor in determining if bite victims receive rabies vaccine during clinic visits in KwaZulu-Natal and other parts of Africa; however , factors within the clinic setting such as staff knowledge need to be considered as well . Consideration of the offending dog in the bite incident has not been shown to play a role in victim response to dog bites . Therefore , the wasting of PEP could be as a big a problem as people at risk not receiving necessary vaccine . Our results also indicate that schools and rabies education of schoolchildren can be much improved . Not only are children most at risk of rabies exposure , but schools may present appropriate structures for dissemination of this kind of information and should be utilized to a greater extent . Questions in this survey regarding response to dog bites could have been more detailed . An example would be to include the age of the bite victim as a variable . Regardless , these results lend credence to the statement that an in-depth study regarding the treatment people are receiving and the public knowledge of rabies needs to be conducted . | Canine rabies has been enzootic to KwaZulu-Natal province , South Africa since the mid-1970's . Vaccination requirements for domestic species and animal control laws enforced in industrialized countries frequently eliminate the need for rabies post exposure prophylaxis ( PEP ) when an animal bite occurs . Rabies deaths in Africa are frequently linked to poverty and ignorance resulting in a lack of urgency for PEP in an environment where less than 70% of the domestic dog population is vaccinated against the disease . The results presented here are part of a larger canine ecology study conducted in KwaZulu-Natal from September 2009 through January 2011 . The six surveyed areas consisted of three land use types: three rural villages , two urban townships and one peri-urban township . The findings show that although a large portion of the population has awareness of rabies , there is a lack of understanding in the response to dog bites . Regression modeling of data suggests that there is an effect of area upon the result of a bite victim receiving PEP as part of treatment . Detailed retrospective study of dog bite incidence and an introspective study of clinics and treatment centers within the province may help explain the results found in this study . | [
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] | 2013 | Dog Bite Histories and Response to Incidents in Canine Rabies-Enzootic KwaZulu-Natal, South Africa |
Antimicrobial peptides play an important role in host defense against microbial pathogens . Their high cationic charge and strong amphipathic structure allow them to bind to the anionic microbial cell membrane and disrupt the membrane bilayer by forming pores or channels . In contrast to the classical pore-forming peptides , studies on histatin-5 ( Hst-5 ) have suggested that the peptide is transported into the cytoplasm of Candida albicans in a non-lytic manner , and cytoplasmic Hst-5 exerts its candicidal activities on various intracellular targets , consistent with its weak amphipathic structure . To understand how Hst-5 is internalized , we investigated the localization of FITC-conjugated Hst-5 . We find that Hst-5 is internalized into the vacuole through receptor-mediated endocytosis at low extracellular Hst-5 concentrations , whereas under higher physiological concentrations , Hst-5 is translocated into the cytoplasm through a mechanism that requires a high cationic charge on Hst-5 . At intermediate concentrations , two cell populations with distinct Hst-5 localizations were observed . By cell sorting , we show that cells with vacuolar localization of Hst-5 survived , while none of the cells with cytoplasmic Hst-5 formed colonies . Surprisingly , extracellular Hst-5 , upon cell surface binding , induces a perturbation on the cell surface , as visualized by an immediate and rapid internalization of Hst-5 and propidium iodide or rhodamine B into the cytoplasm from the site using time-lapse microscopy , and a concurrent rapid expansion of the vacuole . Thus , the formation of a spatially restricted site in the plasma membrane causes the initial injury to C . albicans and offers a mechanism for its internalization into the cytoplasm . Our study suggests that , unlike classical channel-forming antimicrobial peptides , action of Hst-5 requires an energized membrane and causes localized disruptions on the plasma membrane of the yeast . This mechanism of cell membrane disruption may provide species-specific killing with minimal damage to microflora and the host and may be used by many other antimicrobial peptides .
Oral candidiasis is most commonly associated with individuals infected with the human immunodeficiency virus ( HIV ) , and it is also seen in infants , patients with diabetes mellitus , and those receiving broad-spectrum antibiotics . However , oral candidiasis is relatively uncommon in the general population , despite the fact that Candida albicans can be recovered in the alimentary canal of healthy individuals in over 50% of cases [1] . Antimicrobial peptides , including histatins , play an important role in the innate defense against oral Candida infections . Histatins are a family of low-molecular weight histidine-rich cationic peptides that are found specifically in human salivary secretions [2] . Histatin-5 ( Hst-5 ) , a 24-residue peptide is the most potent member of the family with respect to fungicidal activity against C . albicans . It kills C . albicans in vitro at physiological concentrations ( 15–30 µM ) [3] , [4] . Structural studies of Hst-5 have shown that it takes on a random coil structure in aqueous solvents and adopts a largely α-helical conformation in non-aqueous solutions [5] , [6] . Many antimicrobial cationic peptides form either α-helical or β-sheet structures that exhibit a strong amphipathic nature . After the initial electrostatic attraction to an anionic microbial surface , these cationic amphipathic peptides can spontaneously insert into cell membranes and form pores/channels , causing lysis of the cell membrane [7] , [8] . However , unlike the classical pore-forming peptides , Hst-5 is predicted to lack sufficient amphipathic character to insert spontaneously into microbial membranes [3] , [6] . Consistent with this prediction , Hst-5 has little lytic effect in a liposome model system [9] . The activity of Hst-5 against C . albicans is believed to be initiated through cell wall binding , followed by translocation and intracellular targeting . Hst-5 has been shown to localize to the cytoplasm of C . albicans cells , where it associates with the energized mitochondria and inhibits respiration [10] , [11] . Cytoplasmic Hst-5 also affects cell membrane functions . Hst-5 induces a sizeable noncytolytic efflux of ATP and potassium and magnesium ions into the extracellular milieu , causing a loss in cell volume and ionic imbalance to the yeast cell [12]–[15] . On the other hand , Hst-5 has also been reported to cause slow depolarization of the cytoplasmic and mitochondrial membranes , indicating a lytic activity towards the membranes [16] . Cells treated with Hst-5 also have elevated cell permeability to the small cationic dye propidium iodide ( PI ) as shown by FACS analysis [10] . Internalization of Hst-5 by C . albicans cells is tightly linked to killing and is dependent on cellular metabolism [16]–[18] . Oxygen depletion or inhibition of respiration by sodium azide blocks the translocation of Hst-5 into the cell by rigidifying the cell membrane [10] , [17] . The initial binding of Hst-5 to the C . albicans cell surface is thought to be initiated by specific binding to Ssa1/2 , a heat shock protein present on the cell surface of the yeast [19] , [20] . Cells without Ssa2 show an impaired Hst-5 uptake [20] . However , how Hst-5 is internalized is not known . The initial cell surface binding by Hst-5 does not lead to cellular lysis as seen with other antimicrobial peptides [12] . Most polar macromolecules are excluded from the interior of cells due to the impermeability of the plasma membrane . The typical mechanism of entry of extracellular components into yeast cells is dependent on either fluid-phase or receptor-mediated endocytosis [21]–[23] . Recently , cationic cell-penetrating peptides , such as HIV Tat and polyarginine , have been shown to translocate directly from the extracellular surface into the cytoplasm without the need for endocytic vesicles in both yeast and mammalian cells [24] , [25] . This novel internalization requires cationic charge and an electrostatic interaction with cell the surface . This study aimed to determine how Hst-5 is translocated into the cytoplasm of C . albicans . To date , the mode of internalization of Hst-5 is not defined , though it has been suggested that internalization of the antifungal peptide is initiated through a non-lytic manner by an unidentified translocase [26] . Here we report that the internalization event is actually a non-classical lytic event . We visualized an immediate and rapid internalization of Hst-5 and fluorochromatic dyes into the cytoplasm from a spatially restricted site on the plasma membrane , and a concurrent rapid expansion of the vacuole . Cell death is completely correlated with the appearance of cytoplasmic Hst-5 . Our study provides the first direct evidence for a breach in the plasma membrane as the initial damage by extracelluar Hst-5 on C . albicans and a mechanism of its internalization into the cytoplasm .
Hst-5 at physiological concentration ( 10–30 µM ) has been found distributed throughout the cytoplasm of C . albicans cells [27] , [28] . However , by using FITC-conjugated Hst-5 at 10 µM or 20 µM , we observed two populations of cells with distinct Hst-5 localization ( Figure 1A ) . In some cells , Hst-5 was localized strictly to the vacuole , but not in the cytoplasm; in other cells , Hst-5 was localized throughout the cytoplasm . The internalization of the FITC-conjugated Hst-5 produced varying fluorescent intensity in both the vacuolar- and cytoplasmic-associated cells . It seemed that more cells showed vacuolar localization at 10 µM than at 20 µM Hst-5 , and the reverse was seen for cells with cytoplasmic localization at these concentrations . To examine a possible effect of Hst-5 concentration on its cellular localization , we examined cells in 5 µM and 50 µM Hst-5 . Strikingly , cells exposed to 5 µM Hst-5 showed mostly vacuolar localization and cells in 50 µM showed largely cytoplasmic localization with little vacuolar fluorescence ( Figure 1A ) . Therefore , with increasing Hst-5 concentrations , we observed a shift in cell population from vacuolar to cytoplasmic localization . Because the fluorescent intensity of cells with cytoplasmic Hst-5 was much higher than that of cells with vacuolar Hst-5 , we were able to quantify the percentage of cells in each population by flow cytometry ( Figure 1B and 1C ) . Cells with vacuolar Hst-5 are in the peak with low intensity on the left , and cells with cytoplamic Hst-5 are in the high intensity peak on the right . Moreover , with increasing Hst-5 concentrations , more cells are shifted from the low intensity peak to the high intensity peak in flow cytometry ( Figure 1B and 1C ) . Since the majority of cells with cytoplasmic Hst-5 still had enlarged intact vacuoles that excluded Hst-5 , the concentration dependent localization of Hst-5 is likely through two distinct pathways of internalization . The vacuolar uptake of Hst-5 could be through either receptor-mediated or fluid-phase endocytosis . To determine which is responsible for vacuolar Hst-5 uptake , mutants that block receptor-mediated , but not fluid-phase , transport to the vacuole were used . Monoubiquitination of transmembrane receptors at their cytoplasmic domains is required for the sorting of these integral membrane proteins into the luminal vesicles of multivesicular bodies ( MVBs ) . ESCRT ( endosomal sorting complex ) complexes are essential for the sorting event . Receptors that normally internalize and traffic into MVBs and subsequently degrade in the vacuole are instead accumulated on the membrane of MVBs in the mutants of VPS36 or SNF7 , components in the ESCRT complexes [23] , [29]–[31] . After incubating C . albicans wild-type , vps36 , and snf7 mutant cells in 10 µM Hst-5 and 10 µM FM4-64 , a lipophilic membrane dye , for 30 minutes at 30°C , Hst-5 was found to accumulate on the surface of , but excluded from the lumen of vacuole-like membrane structures in vps36 and snf7 mutant cells ( Figure 2A ) . It should be noted that FM4-64 increased the necessary threshold concentration of Hst-5 in order to observe vacuolar or cytoplasmic-associated Hst-5 localization . These results indicate that Hst-5 is internalized to the vacuole by a receptor-mediated endocytic pathway . Next , we evaluated the effect of blocking the initial internalization step of endocytosis on Hst-5 uptake . The actin cytoskeleton and type I myosins are critical for the initial invagination event at the cell surface [21] , [32] . Mutation of the type I myosin gene ( MYO5 ) in C . albicans is also deficient in endocytosis , as the uptake of FM4-64 is impeded at the plasma membrane [33] . When myo5 mutant cells were incubated with 10 µM Hst-5 and 10 µM FM4-64 for 10 minutes at 30°C , both FM4-64 and Hst-5 were found on the plasma membrane , but not in the vacuole in the majority of the cell population ( Figure 2B ) . This observation is consistent with the reported defect of myo5 cells in endocytosis . Surprisingly , a moderate proportion of the population , 19 . 01% , had Hst-5 localized within the cytoplasm . Similarly , in cells treated with latrunculin A ( LatA ) or cytochalasin A ( CytoA ) , which prevents actin polymerization , Hst-5 at 5 µM was observed in the cytoplasm in a majority of the cells , especially CytoA-treated cells , but was not observed in the vacuole or on the plasma membrane ( Figure 2C ) . Therefore , cells without functional actin cytoskeleton greatly decreased the threshold necessary to induce cytoplasmic Hst-5 translocation . The cationic charge of antimicrobial peptides is critical for the initial electrostatic attraction of the peptides to negatively charged cell membranes , and there is a strong correlation between peptide cationicity and antimicrobial activity [34] . For Hst-5 , cationic charge is also important for its candicidal activity . A single lysine substitution for a histidine or amidation of the C-terminus of Hst-5 analogs increases the candidacidal activity of the peptide by almost two-fold [35] , [36] . Whereas , replacement of lysine-13 with glutamic acid and arginine 22 with glycine , a variant of Hst-5 ( m68 ) reported by Tsai et al . , caused a significant reduction in its killing ability [37] . The amino acid substitutions in m68 reduce the cationic charge at pH 7 . 0 from 6 . 6 in Hst-5 to 3 . 6 . To determine whether the cationic charge of Hst-5 affects how the antimicrobial peptide is internalized into the fungal cell , we observed the localization of a FITC-conjugated m68 in C . albicans . When cells were exposed to concentrations of 5 , 10 , 20 , 50 , and 200 µM FITC-m68 at 30°C for 30 minutes , cytoplasmic m68 was not observed at 5 , 10 , and 20 µM ( data not shown ) and was only seen in a small portion of the cell population at 50 and 200 µM m68 ( Figure 3A ) . In contrast to Hst-5 at these concentrations , FITC-m68 was localized to the vacuole in the majority of cells ( Figure 3A ) . The result suggests that a robust cationic charge is necessary for cytoplasmic localization of Hst-5 . Since Hst-5 sequence is 29% histidine , which has a pI at around physiological pH , the peptide is expected to have different charges at pHs 4 . 5 , 7 . 0 , and 9 . 0 , which are within the resting pH range of the oral cavity [38] . By incubating C . albicans with 20 µM Hst-5 in varying pHs , we could examine the effect of cationic charge on the peptides cellular localization . In cells exposed to Hst-5 at pH 9 . 0 , giving the peptide a charge of +3 . 6 , the majority of the cells showed either cell surface or vacuolar localization , while no cytoplasmic localization was observed . Conversely , when the cells were incubated with Hst-5 at pH 4 . 5 , which induces a positive net charge of 12 . 9 , a preponderance of cells had Hst-5 localized within the cytoplasm and only a small population had the antimicrobial peptide bound to the cell surface ( Figure 3B ) . This is consistent with the previous observation that a strong cationic charge is important for the cytoplasmic localization of Hst-5 . However , extreme pHs may have effects on cell physiology that potentially could influence the uptake of Hst-5 . Indeed , endocytosis has been shown to be impaired at a low pH [39] , which may account for why vacuolar Hst-5 was not observed at pH 4 . 5 . Therefore , Hst-5 uptake pathway is likely affected by both the pH-dependent cationic charge of Hst-5 and pH effects on cell physiology . Nonetheless , we have shown through both amino acid substitution and the ionization of histidine using the pH range of the oral cavity that a strong cationic charge determines the mode of uptake for Hst-5 . Hst-5 at 10 µM kills with around 50% efficiency in a population of 106 cells/ml . Since this concentration gives a mixed population of cells with either vacuolar or cytoplasmic Hst-5 , we were interested in determining whether cells with different Hst-5 localizations had different fates . We have observed that cells with cytoplasmic Hst-5 have higher fluorescence intensity than cells with vacuolar Hst-5 , and the difference in fluorescence intensity is sufficient to allow us to separate cells into two populations with different Hst-5 localizations ( Figure 1 ) . After incubating C . albicans cells in 10 µM Hst-5 at 30°C for 30 minutes , cell sorting was carried out to give us two distinct populations of Hst-5 localized cells ( Figure 4A ) , which were confirmed by fluorescence microscopy . Approximately two hundred cells from each population were aliquotted onto plates to determine colony-forming units . Cells from a no-peptide control and cells with vacuolar Hst-5 showed 100% survival . Conversely , none of the cytoplasmic-localized cells produced colonies ( Figure 4A ) . These results provide irrefutable evidence that cytoplasmic Hst-5 is linked to killing , whereas vacuolar Hst-5 is non-cytotoxic to the cells and is maintained in the vacuole . Previous research has shown that the yeasts C . glabrata and S . cerevisiae show a marked resistance to Hst-5 [40]–[42] . We wanted to determine if their insensitivity to the antimicrobial peptide was due to the lack of cytoplasmic translocation of Hst-5 . The yeasts C . albicans , C . glabrata , and S . cerevisiae were exposed to 50 µM of Hst-5 for 30 minutes and examined using fluorescent microscopy with a fixed exposure time ( 9 ms ) . Interestingly , in C . glabrata cells , Hst-5 was predominantly localized to the vacuole , whereas in S . cerevisiae , the peptide was found bound to the cell surface ( Figure 4B ) . Thus , the resistance of C . glabrata and S . cerevisiae to Hst-5 may be due to the lack of cytoplasmic translocation of the antifungal peptide . To determine if the lack of Hst-5 uptake was due to a difference in cell surface binding , we exposed Hst-5 to the yeasts in the presence of sodium azide , which has been shown to prevent the internalization of Hst-5 [17] . Hst-5 uniformly bound to the cell surface of C . albicans and S . cerevisiae ( Figure 4B ) . Therefore , the lack of cytoplasmic translocation of Hst-5 in S . cerevisiae was not due to the lack of cell surface binding . The uniform Hst-5 localization was not observed in C . glabrata . Instead , punctate regions were detected , which may correspond to ligand-receptor interactions and receptor-mediated endocytosis . Our data suggest that the resistance of C . glabrata and S . cerevisiae to Hst-5 is dependent on its ability to hinder the mechanism of cytoplasmic translocation . Our previous experiments indicated that the cytoplasmic localization of Hst-5 was achieved in as little as 10 minutes after cells were exposed to the peptide . To further evaluate the internalization event , we used time-lapse confocal microscopy to visualize the process of Hst-5 uptake . 50 µM FITC-Hst-5 was added to C . albicans cells in a thin glass-bottom dish . Image acquisition started prior to the addition of the peptide , and frames were recorded every 9 seconds for a total of 7 minutes and 30 seconds . Hst-5 bound uniformly to the cell surface of the yeast almost immediately after addition of the peptide . Surprisingly , shortly afterwards , a green punctuate site was observed mostly on or near the plasma membrane in many cells ( Figure 5A ) . Only one restricted region of concentrated Hst-5 was seen for each cell . Hst-5 rapidly spread throughout the cytoplasm by diffusion , resulting in a uniform accumulation of Hst-5 in the yeast cell ( Figure 5A and Video S1 ) . Concurrent with the internalization of Hst-5 , we observed a rapid expansion of the vacuole with a parallel loss in cell volume in less than sixty seconds ( Video S2 ) . Eventually , at about 10 minutes , the vacuole collapsed in some cells ( Video S2 ) . The disruption in cellular membrane compartments is in agreement with the published electron microscope images of Hst-5 treated cells [43] . The observation of Hst-5 concentrated in a spatially constricted region is intriguing . One possible explanation is that Hst-5 caused a break on the plasma membrane and the peptide entered into the cytoplasm through the damaged site . If so , the site should also allow the entrance of other molecules . It is known that Hst-5 treatment of cells causes internalization of the cationic molecule propidium iodide ( PI ) . Therefore , we asked whether PI enters cells from the same site as the antifungal peptide . Interestingly , PI was found localized as a single small dot either at or right under the cell surface that also colocalized with Hst-5 ( Figure 5A ) . PI rapidly spread throughout the cytoplasm as was seen with FITC-Hst-5 ( Figure 5A and Video S3 ) . The co-localization of PI and Hst-5 at the same spatially restricted site suggests the existence of a breach of the cell surface by Hst-5 . No internalization of PI was observed in the absence of Hst-5 ( data not shown ) . Whereas , PI localized to a spatially restricted site on the cell surface when cells were treated with unconjugated Hst-5 , confirming that FITC-Hst-5 and native Hst-5 have the same property in membrane perturbation ( Figure S1 ) . Among cells in several time-lapse experiments , we never observed a cell with more than one site of PI internalization . This was further supported by the acquisition of a three-dimensional image of the initial uptake of PI into the cytoplasm shortly after C . albicans was treated with FITC-Hst-5 ( Video S4 ) . Due to the rapid uptake of the fluorochrome , wide-field microscopy and constrained iterative deconvolution were used in place of confocal microscopy . The initial Hst-5 uptake site on the cell surface could not be observed in this image due to the high fluorescein signal on cell surface . Even myo5 mutant cells , which have a lowered Hst-5 concentration threshold for cytoplasmic translocation , had solitary breaches on their cell surface ( data not shown ) . To further validate the findings that translocation of Hst-5 into the cytoplasm is mediated by the formation of a spatially restricted site on the cell surface of the yeast , C . albicans was treated with 50 µM FITC-Hst-5 in the presence of 5 µg/ml of rhodamine B ( RB ) . The fluorchrome RB is useful indicator of membrane integrity and viability and is advantageous in this particular assay since it does not bind mitochondria or DNA [44] , [45] . As observed with PI , the uncharged fluorochrome RB was internalized from a single regional area that colocalized with FITC-Hst5 ( Figure 5B ) . Taken together the data indicates that Hst-5 induces a spatially localized breach on the cell surface of the C . albicans , leading to a disruption in its membrane integrity and a loss in viability . Having shown that Hst-5 causes spatially restricted sites on the cell surface , we wanted to determine whether the site correlated with known cell surface markers . To evaluate whether the breach site was in regions where daughter cells had budded off , C . albicans cells were treated first with calcofluor white , and then with PI and biotin-conjugated Hst-5 . The site of PI uptake did not correlate with bud scars ( Figure 6A ) . This is consistent with the previous finding that Hst-5 is capable of killing spheroplasts of C . albicans [46] . We then examined whether there was any correlation between the site of the breach and cell polarity , which is linked to the active sites of secretion and endocytosis . Sterol and sphingolipid-rich raft domains are also concentrated at the site of active growth [47] . We performed time-lapse experiments with 50 µM biotin-Hst-5 and 5 µg/ml PI with C . albicans cells carrying GFP-tagged Spa2p , a component of the polarisome that controls cell polarity [48] . To facilitate analysis , hyphal cells with highly polarized growth were used . Spa2p was found to be localized to sites of polarized growth , such as the small bud , the bud neck , and the hyphal tip . However , the site of PI uptake did not correlate with the cellular localization of GFP-Spa2p ( Figure 6B ) . Therefore , the spatially restricted site on the cell surface does not correlate with either of the two tested cell surface landmarks and is either a random manifestation on the cell surface or the uptake of the peptide is dependent on an unknown cellular marker found in association with either the cell wall and/or the plasma membrane of C . albicans .
The general mode of action of most α-helical cationic antimicrobial peptides is initiated by their net positive charge that attracts them to an anionic microbial surface . Following this electrostatic binding , the α-helical peptide is inserted into the plasma membrane , resulting in the release of cellular contents and/or lysis of the cell . Previous Hst-5 research has indicated that the mode of Hst-5 killing does not behave in this classical manner . Rather it has been suggested that Hst-5 binds the heat shock protein 70 ( Ssa1/2 ) located on the cell wall and is subsequently transported across to the cytoplasm in a nonlytic manner [12] , [20] , [49] . Intracellular targeting by cytoplasmic Hst-5 to the mitochondria and the plasma membrane leads to cell death [6] , [10] , [49] , [50] . Here we show for the first time that the uptake of Hst-5 is actually a dichotomous event . Under low physiological concentrations the peptide is internalized to the vacuole via receptor-mediated endocytosis . Whereas under moderate to high physiological conditions , uptake of Hst-5 to the cytoplasm is initiated by a direct translocation through a spatially restricted site on the plasma membrane , causing the initial fungicidal activity to the yeast by damage to the cell membrane . Uptake of Hst-5 is both a dynamic and stochastic process within the Candida population at low to moderate concentrations . The rapid uptake of Hst-5 into the cytoplasm and its subsequent killing of C . albicans most likely prevents the slower process of receptor-mediated endocytosis from happening in the same cells . On the other hand , when Hst-5 is below the critical concentration necessary to induce cytoplasmic translocation , the endocytic removal of Hst-5 from the cell surface likely lowers the build-up of Hst-5 on the cell surface , and therefore impedes the candidacidal activity of the antimicrobial peptide . These two opposing internalization pathways give rise to two cell populations with distinct Hst-5 localizations and outcomes . Net cationic charge of Hst-5 plays a greater role than just the initial binding affinity to the surface of C . albicans . A single lysine substitution for a histidine or amidation of the C-terminus of Hst-5 analogs increases the candidacidal activity of the peptide by almost two-fold [35] , [36] . Whereas , reduction of the net positive charge of Hst-5 by either amino acid substitution or an increase in pH markedly reduced the cytoplasmic translocation of the antimicrobial peptide without affecting binding to the cell surface . In support of this idea Dathe et al . showed that increasing the charge of a magainin 2 analog from +3 to +5 increased its antibacterial activity [51] . It has been postulated that mechanism of translocation of cationic peptides is based on the strong trans-negative membrane potential common to many pathogenic organisms . It is thought that the electrochemical gradient helps orient the cationic peptide to the membrane so that it may gain entrance to the polar membrane core and/or translocate across the exoplasmic to the cytoplasmic membrane leaflet [34] . The permeabilization of cellular membranes by magainin and platelet microbicidal proteins ( PMPs ) has been shown to require acidic phospholipids and a large membrane potential [52] , [53] . Furthermore , while not affecting the initial binding event of Hst-5 , C . albicans cells treated with uncouplers of the electrochemical gradient , such as carbonylcyanide-m-chlorophenylhydrazone , dinitrophenol , and sodium azide , as well as petite respiration-deficient mutants have increased resistance to Hst-5 [12] , [18] . The membrane potential of S . cerevisiae has been measured at −71 mV , a value closer to that of mammalian cells ( −90 to −110 mV ) , whereas C . albicans membrane potential is −120 mV , a value more in line with bacterial pathogens ( −130 to −150 mV ) [34] , [54] , [55] . The trans-negative electrochemical gradient may potentially act as an underlying mechanism providing Hst-5 resistance to S . cerevisiae and Hst-5 susceptibility to C . albicans . This mechanism could provide species-specific targeting of the peptide while preserving nonpathogenic microbial communities and host tissue . One of the most intriguing aspects of this study was the demonstration that the primary event in the inevitable killing of C . albicans was due to the concentration dependent formation of a single disruption site on the plasma membrane , visualized by the rapid influx of the fluorochromes PI and RB and Hst-5 through the disruption on the cell surface of C . albicans . The existence of a breach on the plasma membrane is also evident from the rapid expansion of the vacuole and the loss of cell volume . In S . cerevisiae , the vacuole expands when cells are shifted to a hyposmotic condition [56] . The rapid expansion of the vacuole in Hst-5 treated cells could be a response to the loss of ions and other small solutes from the cytoplasm . The disruption site is likely responsible for the rapid efflux of ATP and K+ that are linked to the killing of C . albicans . The size of the holes should be small , as only proteins smaller than 4 kDa were found to be released into the culture [28] . To our knowledge only one other antimicrobial peptide , the amphibian skin peptide dermaseptin s3 , has been observed to induce a single breach site on the surface of a microorganism [57] . The dependence of Hst-5 internalization on the membrane potential may provide an explanation for a single rupture per cell , as once there is one site of perturbation , the membrane potential is lost , and therefore , prevents a second rupture . The dependence on the existence of the membrane potential may explain why Hst-5 had little lytic effect on vesicles in vitro [9] . Moreover , Hst-5 is capable of targeting and disrupting the electrochemical gradient of isolated mammalian mitochondria , as well as the mitochondria of C . albicans and Leishmania species [6] , [58] , [59] . The site of the rupture seems to be random , as it does not correlate to regions where daughter cells bud off or to the region of polarized growth . The randomness of the solitary disruption site further indicates that Hst-5 may act on the plasma membrane directly , but not through a particular cellular landmark . However , at this time we cannot definitively exclude the possibility that the formation of the Hst-5 spatially restricted site is due to its greater affinity to an unknown cellular marker on the surface of C . albicans rather than the strong electrochemical gradient of the plasma membrane . Nonetheless , two additional lines of evidence suggest that the Hst-5 interaction with the plasma membrane initiates a mode of action that weakens the stability of membrane bilayer . First , our research indicates that the deletion of the class I myosin and the depolymerization of F-actin by CytoA and LatA markedly reduces the threshold necessary for the cytoplasmic translocation of Hst-5 . The cortical actin cytoskeleton is important for the stability of the plasma membrane under hyperosmotic conditions , as S . cerevisiae act1 mutants and C . albicans myo5 mutants are extremely sensitive to salt stress [33] , [60] . Furthermore , the high-osmolarity glycerol pathway ( Hog1p ) , involved in adaptation to osmotic and oxidative stress [61]–[63] , is required to prevent severe growth defects in the C . albicans myo5 mutants [60] . Second , Hst-5 is shown to activate the Hog1 pathway in C . albicans [15] . In S . cerevisiae , the Hog1 pathway is activated by a reduction of turgor pressure in response to hyperosmotic stress that induces water efflux or by treatment with nystatin , a membrane-permeabilizing antifungal drug that causes leakage of low molecular weight cytosolic components [64] . Moreover , Hst-5 shows strong synergistic killing of C . albicans when combined with amphotericin B [65] , [66] . The synthetic interaction between Hst-5 and amphotericin B and the fact that both activate the Hog1 pathway suggests that Hst-5 and polyene macrolides ( eg . amphotericin B and nystatin ) have overlapping functions . In summary , Hst-5 is not a classical channel forming cationic peptide . However , we do show in this report that Hst-5 induces perturbation at a spatially restricted site on the plasma membrane . Unlike classical channel forming antimicrobial peptides , this action requires an energized membrane and causes disruption at one region of the plasma membrane . This mechanism of cell membrane disruption may provide species-specific killing with minimal damage to microflora and the host , and may be used by many other weakly amphipathic antimicrobial peptides .
The following fungal strains were used in this study: C . albicans SC5314 ( wild-type clinical isolate ) ; C . albicans vps36 ( BWP17 Cavps36Δ::UAU1/Cavps36Δ::URA3 ) and C . albicans snf7 ( BWP17 Casnf7Δ::UAU1/Casnf7Δ::URA3 ) ( gifts from A . Mitchell , [67] ) ; C . albicans COU46 ( CAI4 Camyo5::hisG/Camyo5::hisG ) ( gift from M . Whiteway , [68] ) ; C . albicans SPA2-GFP ( BWP17 SPA2/SPA2-GFP-URA3 ) ; C . glabrata BG2 ( gift from B . Cormack , wild-type clinical isolate , [69] ) ; and S . cerevisiae BY4741 ( MATa , leu2Δ0 , met15Δ0 , and ura3Δ0 ) . All of the yeast strains were maintained on YPD plates [1% ( w/v ) yeast extract , 2% ( w/v ) peptone , and 2% ( w/v ) glucose] . Prior to Hst-5 localization assays , the cells were grown overnight at 30°C in 5 ml YPD broth . A 1/50 dilution of the overnight culture was suspended in fresh 5 ml YPD and grown for an additional 4 hours at 30°C to obtain a mid-log phase culture at which time the optical density was determined ( OD595 of 1 . 0 = 3×107 cells/ml ) using a Beckman Coulter DU 800 spectrophotometer to obtain a cell population of 106 cells/ml . Unconjugated Hst-5 and FITC- and biotin-labeled Hst-5 ( DSHAKRHHGYKRKFHEKHHSHRGY ) and FITC-labeled Hst-5 m68 ( DSHAKRHHGYKREFHEKHHSHGGY ) were synthesized and purified by Genemed Synthesis , Inc . ( San Francisco , CA ) . The identity and purity of the peptides were confirmed by mass spectrometry . Both FITC-Hst-5 and biotin-Hst-5 have been shown to have similar levels of candicidal activity when compared against unlabeled Hst-5 [10] , [13] , [49] . The intracellular localization of FITC-Hst-5 ( 5 , 10 , 20 , and 50 µM ) and FITC-m68 ( 5 , 10 , 20 , 50 , and 200 µM ) was investigated either alone or in a double-labeling experiment using FM4-64 ( Molecular Probes , Inc . Eugene , OR ) . Yeast cells in 50 µl ( ∼106 cells/ml ) were incubated for 30 minutes at 30°C with 10 µM FITC-Hst-5 and 10 µM FM4-64; the cells were then washed twice with 10 mM NaN3 and 10 mM NaF in 20 mM PBS buffer , and analyzed immediately by wide-field fluorescence microscopy . To depolarize F-actin , cells were treated with either 5 µM cytochalasin A or 50 µM latrunculin A ( Sigma , St . Louis , MO ) for 1 hour at room temperature . The control cells ( wild-type and myo5 ) were treated with the equivalent volume of the DMSO solvent ( 0 . 5% ) . The cells were then exposed to 5 µM of FITC-Hst-5 for 30 minutes at 30°C . The cells were then washed twice with buffer containing NaN3 and NaF and analyzed by wide-field fluorescence microscopy and flow cytometry . For live cell imaging , 300 µl of a 100 µg/ml solution of concanavalin A ( MP Biomedicals , LLC . Solon , Ohio ) was coated onto a sterile 0 . 17 mm glass bottom dish ( WillCo Wells BV , Amsterdam , Denmark ) . The wells were incubated for 1 hour at room temperature and then washed three times with water . A 300 µl buffer suspension of ∼2×106 C . albicans cells were aliquoted onto the well and incubated at room temperature . After settling and binding for 15 minutes unbound cells were washed away [70] . Buffer containing 50 µM of either unconjugated Hst-5 or FITC-Hst-5 and 5 µg/ml PI or RB was added to the cells and uptake of fluorescence was followed by time-lapse confocal microscopy . To determine the position of site specific breach by Hst-5 in relation to known cellular markers , cells were either observed using 2 µg/ml calcofluor white ( Sigma , St . Louis , MO ) and 5 µg/ml PI in PBS buffer or the C . albicans Spa2-GFP strain was grown in the presence of PI and 2% fetal calf serum in water . Buffer containing 50 µM biotin-Hst-5 was added to the cells and uptake of PI was followed by time-lapse wide-field fluorescence microscopy at room temperature and 37°C , respectively . Wide-field fluorescence images were obtained on either Zeiss Axioplan 2 or the inverted Zeiss Axio Observer . Z1 Microscope ( Carl Zeiss MicroImaging , Inc . Thornwood , NY ) fluorescent system , equipped with the AttoArc HBO 100 and the X-Cite series 120 mercury lamps , respectively . Images were taken using a 100× NA 1 . 4 objective . Both fluorescence microscopes were equipped with GFP , RFP , and DAPI filter sets . Data sets were obtained as 10–20 optical sections per wavelength spaced 0 . 2 µm apart along the Z-axis . Out of focus information was removed using a constrained iterative deconvolution algorithm . During the experiment cells were kept at either a constant 30° or 37°C using the TempModule S system on the microscope . Processing was done on a PC using the software packages Axiovision 3 . 1 and 4 . 6 . 3 , as well as Photoshop ( Adobe Systems Inc . , Mountain View , CA ) . Confocal laser scanning microscopy was performed on an inverted LSM510 laser scanning microscope ( Carl Zeiss , Göttingen , Germany ) using a Plan-Apo 100×/1 . 4 NA lens . For the simultaneous detection of fluorescein-labeled peptides and the fluorochromes PI or RB , the 488-nm line of the argon ion laser and the light of a 543-nm helium neon laser were directed over an HFT UV/488/543/633 beam splitter , and the fluorescence was detected using an NFT 545 beam splitter in combination with a BP 500–550 band pass filter for fluorescein detection and an BP 565–615 band pass filter for PI and RB detection . The distribution of FITC-labeled Hst-5 over the cell population was investigated by using a dual laser fluorescence-activated cell sorter ( BD FACSCalibur System , Becton Dickinson , San Jose , CA ) . The results were analyzed with the software package CellQuest Pro ( version 5 . 1 . 1 ) provided by Beckton Dickinson . C . albicans cells were incubated for 30 minutes with 10 µM of FITC-Hst-5 at 30°C . The cells were then washed twice with 20 mM PBS buffer and under went flow cytometric cell sorting using the DAKO Cytomation MoFlo Flow Cytometer ( DAKO , Glostrup , Denmark ) . The results were analyzed on a PC using the software package Summit ( version 4 . 0 ) provided by DAKO . The cells were sorted by gating the two peaks of the histogram representing vacuolar and cytoplasmic localization of Hst-5 . Cellular localization of Hst-5 was confirmed with fluorescence microscopy . The sorted cells were then plated onto YPD plates and incubated overnight at 30°C ( data as a mean±1SD of triplicate cultures ) . Determination of charge for Hst-5 and m68 were done using PROTEIN CALCULATOR v3 . 3 ( www . scripps . edu/∼cdputnam/protcalc2 . html ) . The pKa values for the individual amino acids are from Stryer Biochemistry , 3rd edition . The software was designed by Chris Putnam at the Scripps Research Institute cdputnam@scripps . edu . | In most healthy individuals , the yeast Candida albicans is found within the oral cavity as part of the normal microflora . Though under immunocompromising conditions , this benign microbe can become an opportunistic pathogen causing oral candidiasis ( i . e . thrush ) . Although antifungal drugs are typically efficacious , the paucity of drugs and their increasing usage has led to rising drug resistance . Thus , researchers have begun to look at alternative therapeutics , such as the candidacidal salivary peptide histatin-5 . To date , little is known about the initial binding and subsequent internalization that facilitates Hst-5's killing activity . Thus , our study attempted to determine how Hst-5 is internalized into C . albicans . It was thought that Hst-5 is transported into the cytoplasm without disruption of the plasma membrane . However , our study finds that Hst-5 , under physiological concentrations , disrupts the plasma membrane and is rapidly translocated into the cytoplasm , leading to cell death . Interestingly , the internalization of Hst-5 is initiated from a single spatially restricted site on the plasma membrane rather than multiple breaches on the cell surface . This novel mechanism of membrane disruption provides new insights into how Hst-5 and other antimicrobial peptides may be acting on pathogenic microorganisms . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"microbiology/medical",
"microbiology",
"microbiology/innate",
"immunity"
] | 2008 | The Antimicrobial Peptide Histatin-5 Causes a Spatially Restricted Disruption on the Candida albicans Surface, Allowing Rapid Entry of the Peptide into the Cytoplasm |
Successful reproduction is critical to pass genes to the next generation . Seminal proteins contribute to important reproductive processes that lead to fertilization in species ranging from insects to mammals . In Drosophila , the male's accessory gland is a source of seminal fluid proteins that affect the reproductive output of males and females by altering female post-mating behavior and physiology . Protein classes found in the seminal fluid of Drosophila are similar to those of other organisms , including mammals . By using RNA interference ( RNAi ) to knock down levels of individual accessory gland proteins ( Acps ) , we investigated the role of 25 Acps in mediating three post-mating female responses: egg production , receptivity to remating and storage of sperm . We detected roles for five Acps in these post-mating responses . CG33943 is required for full stimulation of egg production on the first day after mating . Four other Acps ( CG1652 , CG1656 , CG17575 , and CG9997 ) appear to modulate the long-term response , which is the maintenance of post-mating behavior and physiological changes . The long-term post-mating response requires presence of sperm in storage and , until now , had been known to require only a single Acp . Here , we discovered several novel Acps together are required which together are required for sustained egg production , reduction in receptivity to remating of the mated female and for promotion of stored sperm release from the seminal receptacle . Our results also show that members of conserved protein classes found in seminal plasma from insects to mammals are essential for important reproductive processes .
Molecules in seminal fluid induce physiological changes in females , thereby affecting the reproductive capacity of both sexes ( [1–6]; for reviews see [7–9] ) . In some animals , the absence or different levels of certain individual seminal proteins can lead to sterility ( e . g . , [10 , 11] ) . In others , including Drosophila , the absence of a particular seminal fluid protein can impair fertility and/or interfere with certain post-mating effects [12–15] . Drosophila , with its stereotyped mating behavior , excellent genetics , and characterized set of seminal fluid proteins , allows comprehensive tests for seminal fluid protein function . In Drosophila , proteins synthesized and secreted by accessory glands of the male reproductive tract form part of the seminal fluid and are transferred to the female during mating [16–20] . These accessory gland proteins ( Acps ) induce striking physiological as well as behavioral changes in mated females ( reviewed in [7–9] ) . These post-mating changes include increased egg laying ( due to increased oogenesis [21] and increased ovulation [22] ) , the induction of genes encoding antimicrobial proteins [23–25] , and decreased female receptivity to remating [3 , 26] . In addition , Acps are essential for causing morphological changes in the mated female reproductive tract [27] and for normal sperm storage and utilization in females [5 , 28] , and they are hypothesized to play important roles in sperm competition [29–32] . Acps also form part of the mating plug [20 , 33] . Further , Acps have been implicated in reducing the life span [34 , 35] and influencing the feeding behavior [36] of the mated female . The post-mating responses of increased egg production and reduction in receptivity to remating occur in two phases: a short-term and long-term response [3 , 5 , 37–39] . The short-term response occurs during the first 24 h after mating , with the induction of elevated egg production and reduction in receptivity largely dependent on Acps and not sperm . One Acp , ovulin ( Acp26Aa ) , affects only short-term egg production by regulating ovulation for the first 24 h [13 , 22] . After 24 h , maintenance of post-mating physiological and behavioral changes requires the presence of stored sperm in the female ( the long-term response; also called sperm effect [37 , 38] ) . One Acp , the sex peptide ( SP , Acp70A ) , is known to be critical for the long-term mating response: females mated to SP null males fail to elevate egg production and remain highly receptive to remating [12 , 14] . A mechanism suggested for the SP-mediated long-term response is the binding of SP to sperm [40] . Subsequently , the C-terminal portion of the SP is released from the tail of sperm stored within the female . It is proposed that this released C-terminal SP is involved in eliciting the long-term response [25] . In Drosophila melanogaster , 112 predicted Acps ( including SP and ovulin ) have been identified so far by analyses of RNA , expressed sequence tags ( EST ) , and recent proteomic and microarray analyses ( see [9] for references and discussion ) . These molecules are predicted to belong to protein classes that include peptides and prohormones , lectins , lipases , proteases , protease inhibitors , cysteine rich secretory proteins ( CRISPs ) , and defensin-like proteins [41] . Interestingly , similar protein classes are found in the seminal fluids of mammals [42–44] , crickets [45 , 46] , medflies [47] , and honeybees [48] . Because Drosophila seminal fluid proteins are members of conserved families that are found in the seminal fluid of animals ranging from insects to mammals , Drosophila can potentially serve as a model system with which to dissect seminal fluid protein function genetically . However , biological functions of only a few Acps are known to date . These include three peptides and prohormones ( ovulin , SP , and CG10433 [12–14 , 22 , 26 , 35 , 36 , 39 , 49–51] ) , three predicted or known Acp protease inhibitors ( Acp62F [52]; CG8137 , and CG9334 , [51] ) , two predicted Acp proteases ( CG11864 , [53]; CG6168 , [51] ) , and the glycoprotein Acp36DE [15 , 54 , 55] . To obtain a more comprehensive picture of the Acps that mediate post-mating changes and to understand how these changes are triggered mechanistically , it is essential to identify the functions of other Acps . Here , we used RNA interference ( RNAi ) to systematically investigate the roles of Acps in inducing changes in egg laying , fertility , receptivity , and sperm storage . We focused on Acps within five predicted biochemical protein classes , members of which are known or suggested to be critical for several reproductive processes in Drosophila and/or mammals . We analyzed the functions of 25 Acp peptides/prohormones , lectins , CRISPs , proteases , and protease inhibitors; these comprise ∼50% of the stringently defined Acps [56] . We chose peptides/prohormones given the important roles of SP ( peptide ) and ovulin ( prohormone-like Acp ) in Drosophila reproduction ( reviewed in [40 , 57] ) . Acps in the lectin , CRISP , protease , and protease inhibitor classes were included because of the conservation of these biochemical protein classes in the seminal fluids across various organisms , the important reproductive functions of some members of these classes in higher vertebrates including mammals ( reviewed in [58] ) , and our previous finding of the importance of proteolysis regulators in Drosophila seminal protein processing [53] . We identified five Acps ( a new member of the peptide class , member ( s ) of the lectin class , one CRISP , and one predicted protease ) that affect egg production and fertility . Four of these Acps are also needed for persistence of the reduction of the mated female's receptivity to remating and for modulating the release of sperm from storage . Our findings on this latter group of four Acps indicate that multiple Acps are required for long-term post-mating responses to come into effect in mated females .
We used the w1118 strain of D . melanogaster to generate transgenic lines and tubulin-GAL4/TM3 , Sb flies [59] to generate knockdown ( RNAi ) or control males . Assays were done by crossing these knockdown or control males to females of the Canton-S strain of D . melanogaster . All flies were maintained on yeast-glucose medium at room temperature ( 22 ±1 °C ) and a 12:12 light dark cycle . We initially focused our analysis on 26 Acps in five predicted protein functional classes ( Table 1 ) . Lines for the majority of Acps tested here were made following the method in Ravi Ram et al . [53]; generation of lines for the remaining Acps was reported in that paper , where those lines were tested for effects on ovulin processing . Briefly , using the Gateway system ( Invitrogen ) , we moved each Acp into a modified form of the sympUAST vector [60] , altered to accept Gateway inserts ( sympUAST-GW , [53] ) . Transgenic fly lines carrying different sympUAST-Acp ( UAS-Acp-UAS ) constructs and subsequent experimental or knockdown males ( tubulin-GAL4;UAS-Acp-UAS ) as well as control males ( TM3 , Sb;UAS-Acp-UAS ) were generated . Protein samples for western blotting were prepared by dissecting accessory glands from eight RNAi or control males and homogenizing them in the 40 μl 2× SDS sample buffer ( as described in [20] ) ; protein equivalent to the amount in one male was loaded into each gel lane . For all ten Acps for which sufficiently clean antibodies are available ( Table 1 ) , we used western blotting to detect the level of knockdown as in Ravi Ram et al . [20 , 53] For Acps for which no antibodies were available ( Table 1 ) , we used reverse transcription PCR ( RT-PCR ) to confirm knockdown at the transcript level , as in Chapman et al . [12] and Ravi Ram et al . [53] . To check the specificity of gene targeting , the gene sequences used to generate dsRNA were subjected to the dsCheck software ( http://dsCheck . RNAi . jp/; [61] ) . We also BLASTed the coding sequences of those Acps for which we detected phenotypes upon RNAi against the predicted genes data base ( D . melanogaster genome release 5 . 1 ) using the BLASTn algorithm on the FlyBase BLAST server ( http://flybase . net/blast/ ) . To further confirm the specificity of the knockdowns and to analyze whether knockdown of any Acp affected the transfer of non-targeted seminal proteins to the mated female , we probed the proteins extracted from accessory glands of knockdown males , and from reproductive tracts of their mates , with other available Acp antibodies ( for example , against CG14560 , Acp26Aa , Acp36DE , Acp29AB , CG8137 , CG6289 , Acp53Ea , or CG9334 as in Ravi Ram et al . [20] ) . For 21 Acps , we observed no effects in males except for the knockdown of targeted Acp . For two pairs of gene duplicates ( CG1652 and CG1656; CG8137 and CG9334 ) , we observed no effects in males except for the knockdown of the targeted Acp and its duplicate ( see below and [53] ) . However , for one Acp , CG9024 , we observed that its knockdown affected the transfer of multiple Acps to the female ( see Results/Discussion section for details ) . Therefore , of the 26 Acps with RNAi lines , we excluded CG9024 from further functional analysis and carried out the following functional assays using only the remaining 25 Acp knockdowns . Egg laying response ( fecundity ) of mates of knockdown or control males was quantified as described in Kalb et al . [3] and Herndon and Wolfner [13] . Fertility ( number of progeny produced ) and hatchability ( by comparing the number of eggs laid to the number of progeny ) assays were done as in Ravi Ram et al . [53] . The assays were calibrated using ovulin null and control males [13] and then used to assess RNAi males and their matched controls . For the initial screening , we carried out these assays twice each on one knockdown line per Acp construct for 25 Acps . Each time , 15–20 females mated to either control or experimental males were measured for egg laying and fertility . The differences in fecundity , fertility , or hatchability between the females mated to control or experimental males were statistically analyzed by Mann-Whitney U test using the JMP5 . 1 statistical program ( SAS Institute , Cary , NC , USA ) . For Acp knockdown lines that showed a phenotype , we repeated the assay on a minimum of 2–3 independent lines per Acp construct to control for the insertion/line effect . In all cases , TM3 , Sb;UAS-Acp-UAS male siblings of the experimental flies were used as controls . Experimental males of one line also acted as controls for other lines to rule out any possible effects due to the ubiquitous presence of GAL4 protein in the fly . A Bonferroni correction for multiple tests was performed for fecundity and fertility assays . The receptivity response to remating for all 25 Acps tested was measured as in Kalb et al . [3] and Ravi Ram et al . [53] at 24 h ASM ( after the start of mating ) to test for short-term response . The assay was calibrated with SP null and control males [14] and subsequently assessed using RNAi males and their matched controls . For the Acp lines that showed a longer-term phenotype , receptivity to remating was also measured at 4 d ASM . A minimum of 15–20 females at 24 h ASM or at 4 d ASM were analyzed for control and experimental groups . Fisher's exact tests were used to determine significance and a Bonferroni correction was subsequently performed for multiple tests . Sperm counts were performed as in Neubaum and Wolfner [15] at 2 h ASM , 4 d ASM , and 10 d ASM . Each slide was counted twice to assess the counting precision which was >92 . 5% , and sample identity was coded to avoid bias . A minimum of 15–25 replicates were counted for each time point per treatment and data were analyzed using two tailed Student's t-test and subsequently a Bonferroni correction was applied for multiple tests .
We analyzed multiple independent RNAi lines for all 26 Acps . For all ten Acps for which sufficiently specific affinity purified antibodies are available to use on western blots , the levels of the targeted Acp detected on such blots was knocked down to ≤ 2 . 5% of control levels , although not to zero ( here and [53]; see Figure 1 western blots panel for examples ) . For Acps with no available antibodies , we used RT-PCR and we observed no/little amplification of mRNAs from the RNAi targeted genes in knockdowns relative to control males ( here and [53]; see Figure 1 PCR amplification panel for examples ) . Using the dsCheck program to check the specificity of gene targeting , we did not detect any potential off-targets for any targeted Acp except for the two pairs of gene duplicates mentioned in Materials and Methods ( CG1652 and CG1656 is one pair; CG8137 and CG9334 is the other ) . In each pair , one member is the off-target of the other . These cases of off-targeting between gene duplicates are not surprising: CG1652 and CG1656 are about 75% identical [41 , 56] , and CG8137 and CG9334 are about 85% identical [41 , 53 , 56] at the DNA level . Indeed , when we probed protein samples from accessory glands of CG1656 RNAi males with affinity-purified anti-CG1656 , we observed that the levels of CG1656 were knocked down to ≤ 2 . 5% of the control males ( Figure 1 , western blots panel , see CG1656 RNAi ) but in CG1652 RNAi males , the levels of CG1656 were knocked down only to ∼5%–10% relative to control males ( Figure 1 , western blots panel , see CG1656 in CG1652 RNAi ) . Using RT-PCR we observed that CG1652 transcript levels were knocked down not only in CG1652 but also in CG1656 knockdown males ( Figure 1 , PCR amplification panel ) . In a separate study , we found that RNAi for the other pair of gene duplicates , CG8137 and CG9334 , also reciprocally knocked down each other [53] . We did not see inappropriate knockdown of any other Acps . For the Acps with common phenotypes , even in the BLAST search , with the exception of the members of gene duplicate pairs noted above , we did not detect any overlap in the genes pulled out of the BLASTn search ( with sequence similarity of <30% ) , suggesting that the observed phenotypes are not due to any common off-target ( s ) . Further tests on specificity of targeting using western blots showed that all knockdown males tested synthesized normal amounts of non-targeted Acps ( see Figure S1 for examples ) . For 25 of the targeted Acps , all knockdown males transferred all tested Acps to their mates in normal amounts ( See Figure S1 for examples ) . However , although CG9024 ( Acp26Ab ) knockdown males made normal amounts of all tested Acps except CG9024 ( Figure S1; see CG9024 under accessory gland panel ) , they transfer reduced amounts of all Acps tested ( Figure S1; see CG9024 under mated female reproductive tract panel ) . We observed this with both independent lines of CG9024 knockdown males tested ( Figure S1 ) . Because we used tubulin-GAL4 to drive the expression of UAS-9024-UAS , at present we do not know whether the reduced transfer is the consequence of CG9024 knockdown in accessory glands alone . Because of its reduced Acp transfer , we did not include CG9024 RNAi in assays of effects on females . Therefore , the results reported in this paper are for the remaining 25 Acp knockdowns . Mating triggers females to undergo both physiological and behavioral changes ( examples reviewed in [7 , 9 , 58 , 62] ) . In D . melanogaster , these post-mating changes reflect the combined effects of sperm and proteins including Acps in the seminal fluid ( [63 , 64]; for review see [57] ) . To determine the role of Acps in modulating the physiological and behavioral changes of the mated female , we analyzed the effects of individual knockdown of 25 Acps ( see above ) on egg laying , fertility , hatchability , receptivity , and storage of sperm in mated females . To identify new Acps necessary to stimulate these post-mating responses , we counted the number of eggs laid ( fecundity ) , and the number of progeny produced ( fertility ) , by females mated to Acp knockdown or control males . Drosophila females show post-mating responses of elevated levels of egg laying and reduced receptivity in two phases: a short-term response for one day is largely dependent on Acps , and a long-term response persisting for about 1–2 weeks requires both sperm and Acps [37 , 38] . Therefore , we analyzed fecundity/fertility data at 24 h ASM to identify Acps affecting the short-term response and total fecundity and fertility counts over a period of 10 days to identify Acps involved in the long-term response . Males depleted for CG33943 , CG1652/CG1656 ( gene duplicates ) , CG17575 , or CG9997 did not stimulate full egg laying in their mates ( Figures 2 and 3 ) . Mates of the remaining 20 knockdown males did not significantly differ from controls in the overall number of eggs laid ( p > 0 . 5; Bonferroni correction at the 5% level is 0 . 002; Figure 2 ) . Sperm in storage is a major factor in the long-term persistence of post-mating responses [37 , 38] . Since mates of CG1652/CG1656 , CG17575 , or CG9997 knockdown males were defective in the long-term post-mating response , we tested whether these knockdowns affected sperm storage . D . melanogaster females store sperm in the single seminal receptacle ( containing about 65%–80% of the stored sperm ) and the paired spermathecae [15 , 28 , 65 , 66] . Acps are required for normal sperm storage and utilization in the mated female [5 , 15 , 28] . We counted the number of sperm in the sperm storage organs of females mated to CG1652/CG1656 , CG17575 , or CG9997 knockdown males along with their controls at several times post-mating . Mates of any of these Acp knockdown or control males did not differ significantly in the number of sperm in storage at 2 h ASM ( p > 0 . 2; Bonferroni correction at the 5% level is 0 . 01; Figure 4 , seminal receptacle panel ) . At 4 d ASM , there was no significant difference in the number of sperm stored in the seminal receptacle of females mated to CG1652/CG1656 , CG17575 , or CG33943 knockdown males compared to their controls ( p > 0 . 2; Bonferroni correction at the 5% level is 0 . 01; Figure 4 , seminal receptacle panel ) . However , at 4 d ASM , females mated to CG9997 knockdown males had significantly more sperm stored in the seminal receptacle when compared to their controls ( p < 0 . 002; Bonferroni correction at the 5% level is 0 . 01; Figure 4 , seminal receptacle panel ) . Interestingly by 10 d ASM , females mated to CG1652/CG1656 or CG17575 knockdown males , as well as mates of CG9997 knockdown males , had significantly more sperm stored in their seminal receptacle compared to their controls ( p < 0 . 0001; Bonferroni correction at the 5% level is 0 . 01; Figure 4 seminal receptacle panel ) . These results suggest that sperm from CG1652/CG1656 , CG17575 , or CG9997 knockdown males can get into storage as efficiently as sperm from their control males but that sperm from knockdown males are not released from the seminal receptacle as efficiently as sperm of control males . These results also suggest that like their effect on long-term egg production and receptivity , CG1652/CG1656 , CG17575 , or CG9997 affect the long-term release of sperm from storage . We observed no significant difference in the number of sperm stored in the spermathecae of females mated to any of these knockdowns or control males ( p > 0 . 2; Bonferroni correction at the 5% level is 0 . 01; Figure 4 , spermathecae panel ) at all three time points . The egg hatchability of mates of CG1652/CG1656 , CG17575 , or CG9997 knockdown males was unaffected ( above and unpublished data ) , suggesting that the sperm from these RNAi males in storage are of normal viability and have normal capacity to fertilize eggs . Despite the presence of viable sperm in females mated to males knocked down for CG1652/CG1656 , CG17575 , or CG9997 , these females were deficient in sustaining long-term egg production and were receptive to remating . This is similar to findings previously reported for another Acp , SP [12 , 14] . Chapman et al . [12] and Liu and Kubli [14] proposed that the sperm effect is in fact an effect of SP , but one that is manifest only in the presence of sperm . In the present study , though knockdown males of each of the four Acps ( CG1652/CG1656 , CG9997 , or CG17575 ) transferred normal levels of SP ( unpublished data ) to the mated females , those females still failed to exhibit the long-term post-mating responses . These results suggest that manifestation of long-term post-mating responses requires multiple Acps ( CG17575 , CG1652/CG1656 , and CG9997 as well as SP [39] ) and that this occurs only in the presence of sperm . The four Acps identified here may either act in concert with each other and/or SP or may act in independent pathways to promote long-term mating response . Storage and management of sperm within females is a multistep process ( reviewed in [67] ) involving progression of transferred sperm through the female reproductive tract towards the storage organs , entry of sperm into the storage organs , maintenance of viable sperm in storage , and release of sperm from storage for fertilization . One Acp , Acp36DE , is essential for the entry of sperm into storage [15 , 54] . However , the role of Acps in the release or utilization of stored sperm is poorly understood . The present study has provided candidate Acps for future studies to understand the role of Acps in sperm management . Females mated to CG1652/CG1656 , CG17575 , or CG9997 knockdown males had significantly more sperm in the seminal receptacle at later time points , suggesting a requirement of these Acp ( s ) for the release of sperm from storage . However , the observation that the release of sperm only from the seminal receptacle , but not from the spermathecae , is affected in mates of these RNAi males is intriguing . At present not much is known about the pattern of utilization of sperm from these storage organs in Drosophila except that spermathecae have been suggested to serve as long-term storage organ [65] . However , it is interesting to note that CG1652/CG1656 , CG17575 , and CG9997 affect both sperm release and egg laying . It is not clear whether and how these latter two phenotypes are linked . Release of sperm from storage is independent of presence of eggs in the long-term [68] , although presence of eggs affects some transitions in the sperm storage process . It is not known whether egg laying rate is affected by the rate of sperm release . Consideration of tissue targets of these Acps may be informative . Targets of CG1652 , CG1656 , CG9997 , and CG17575 have been identified ( [20] , Ravi Ram and Wolfner , unpublished data ) . All four are detected in the uterus immediately after mating where they can presumably interact with each other , with other Acps , and with sperm . CG1652 , CG1656 , and CG9997 are subsequently detected in sperm storage organs , consistent with a role in affecting these tissues and/or the sperm stored within them . Further studies of the interactions between these Acps ( and SP ) , if any , and of their specific localization may provide an insight into mechanisms of controlling sperm release from storage , and its interaction with egg laying . The Acps for which we have identified roles in sperm release fall into three different protein classes . CG1652 and CG1656 are predicted C-type lectins , CG17575 is a predicted CRISP , and CG9997 is a predicted serine protease [41] . These protein classes are found in seminal fluids across wide range of taxa ( Drosophila , [9 , 41]; mammals [42–44]; crickets , [45 , 46]; medflies , [47]; honeybees , [48]; see [9 , 58] for reviews ) . In vertebrates , including mammals , lectin-like spermadhesins ( reviewed in [69–71] ) , CRISPS [72–74] , and proteases ( [75 , 76] and reviewed in [77] ) in the seminal fluid are suggested to play important roles in reproductive processes such as sperm function and mediating gamete fusion . In the present study , we showed that member ( s ) of these families in Drosophila seminal fluids are important for sustained post-mating responses . A separate study demonstrated that a predicted astacin-like Acp protease plays an important role in proteolysis of seminal fluid molecules [53] . Therefore , members of the conserved protein classes in the seminal fluid are critical for successful reproduction in Drosophila as well as in vertebrates . It will be interesting in future studies to determine if the similar protein classes are involved in analogous mechanisms across different organisms . To conclude , we have found that Drosophila seminal protein CG33943 plays an essential role in short-term induction of egg laying . We also found that seminal proteins CG1652/CG1656 , CG9997 , and CG17575 are essential for sustained egg laying , reduced receptivity of the mated female , and for the release of sperm from storage , indicating that the maintenance of female post-mating responses for a long term requires multiple Acps contributed by the male . The observations from the present study , along with those of previous studies , show that some Acps act only to mediate short-term responses while others are required for long-term post-mating responses . Lack of any significant phenotype for the remaining 20 Acp knockdowns does not mean that they lack reproductive function , but instead could be due to ( a ) their functions in processes that we did not assay , such as regulation of sperm competition [32] , cost of mating ( longevity , [34 , 35] ) , female post-mating feeding behavior [36] , or in inducing female immune response [25 , 51] , ( b ) remaining residual levels of the targeted Acp , since RNAi knocks down Acp levels but does not completely remove them; residual levels might be sufficient to mediate post-mating changes or might have caused changes smaller than our level of detection , ( c ) redundancy in Acp function . Redundancy has already been observed for some Acps' function: although both ovulin [13] and SP [12 , 14] are essential to increase egg laying post-mating , removal of either one does not completely abolish the increase in egg laying . Further , there is a redundancy in tissue targeting of Acps: more than one Acp targets to any given tissue in the mated female reproductive tract [20] . Further studies involving the knockdown of these different Acps in multiple combinations may help in the identification of their functions . Finally , our results suggest that members of conserved protein classes in the seminal fluid are critical for optimal reproductive output and therefore that Drosophila's suite of seminal proteins can serve as a potential model for understanding the roles of these conserved protein classes in the seminal fluid . | In sexually reproducing organisms , sperm enter the female in combination with seminal proteins that are critical for fertility . These proteins can activate sperm or enhance sperm storage within the female , and can improve the chance that sperm will fertilize eggs . Understanding the action of seminal proteins has potential utility in insect pest control and in the diagnosis of certain human infertilities . However , the precise function of very few seminal proteins is known . To address this , we knocked down the levels of 25 seminal proteins individually in male fruit flies , and tested the males' abilities to modulate egg production , sperm storage/release , or behavior of their mates . We found five seminal proteins that are necessary to elevate offspring production in mated females . Four of these proteins are needed for efficient release of sperm from storage to fertilize eggs , a function that had not been previously assigned to any seminal protein . All four are in biochemical classes that are conserved in seminal fluid from insects to humans , suggesting they may play similar sperm-related roles in other animals . In addition to assigning functions to particular seminal proteins , our results suggest that fruit flies can serve as a model with which to dissect the functions of conserved protein classes in seminal fluid . | [
"Abstract",
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] | 2007 | Sustained Post-Mating Response in Drosophila melanogaster Requires Multiple Seminal Fluid Proteins |
Categorization is an important cognitive process . However , the correct categorization of a stimulus is often challenging because categories can have overlapping boundaries . Whereas perceptual categorization has been extensively studied in vision , the analogous phenomenon in audition has yet to be systematically explored . Here , we test whether and how human subjects learn to use category distributions and prior probabilities , as well as whether subjects employ an optimal decision strategy when making auditory-category decisions . We asked subjects to classify the frequency of a tone burst into one of two overlapping , uniform categories according to the perceived tone frequency . We systematically varied the prior probability of presenting a tone burst with a frequency originating from one versus the other category . Most subjects learned these changes in prior probabilities early in testing and used this information to influence categorization . We also measured each subject's frequency-discrimination thresholds ( i . e . , their sensory uncertainty levels ) . We tested each subject's average behavior against variations of a Bayesian model that either led to optimal or sub-optimal decision behavior ( i . e . probability matching ) . In both predicting and fitting each subject's average behavior , we found that probability matching provided a better account of human decision behavior . The model fits confirmed that subjects were able to learn category prior probabilities and approximate forms of the category distributions . Finally , we systematically explored the potential ways that additional noise sources could influence categorization behavior . We found that an optimal decision strategy can produce probability-matching behavior if it utilized non-stationary category distributions and prior probabilities formed over a short stimulus history . Our work extends previous findings into the auditory domain and reformulates the issue of categorization in a manner that can help to interpret the results of previous research within a generative framework .
Categorization is a natural and adaptive process that allows the brain to organize the typically high-dimensional and continuous sensory information into robust hierarchical and discrete representations . These discrete representations , or categories , are a means to mentally manipulate , reason about , and respond to objects in our environment [1] , [2] . For instance , in auditory perception , humans and other animals can ignore the natural acoustic variability that exists between different utterances of the same vocalization in order to differentiate one type of vocalization ( e . g . , a howl ) from a second type ( e . g . , a bark ) . In other situations , listeners can use this variability to identify one caller ( e . g . , Lassie ) from another ( e . g . , Benji ) . The perceptual ease with which we can categorize sound belies the complex computations underlying this ability . One reason categorization is complex is that a sensory property may be ambiguous with respect to the stimulus' category membership . For example , because both dogs and wolves can produce howls , the acoustic structure of the howl by itself may not provide enough information to the listener for proper identification of the caller . In such cases , and in the absence of other sensory information , the listener needs to rely on other sources of information to correctly categorize a sound and identify whether the howl came from a dog or a wolf . This information can be prior knowledge such as knowing that the probability of encountering a wolf is low . Since prior information is subjective , it is of fundamental interest to understand the degree to which an observer acquires this information and then uses it to perform categorical judgments . The utility of prior information in visual categorization has been well studied [1] , [3]–[10] . In comparison , our understanding of how prior information informs categorical judgments in audition is relatively limited and has only more recently become an active area of research [11]–[15] . More importantly , auditory categorization has not been tested or modeled in situations in which the auditory stimulus is ambiguous with regard to its category membership . Understanding auditory-categorization behavior is important for differentiating between modality-specific versus modality-general computational strategies , which can provide insights into the underlying neural computations . In particular , categorization can be understood as the result of a probabilistic inference process in which the observer combines sensory and prior information according to their relative levels of uncertainty ( noise ) [16] . Bayesian statistics is a useful mathematical framework to formulate generative models for such categorical inference processes . However , it requires a precise quantification of the different levels of uncertainty in order to provide behavioral predictions that allow for unique model interpretations . For example , different decision strategies can lead to very similar model predictions if the sensory noise levels are allowed to be free parameters . The purpose of this study was two-fold: ( 1 ) to test whether human subjects can learn and use category-prior information when making auditory categorical judgments and ( 2 ) to carefully constrain and validate a generative Bayesian model of auditory categorization against experimental data . To this end , we developed a novel auditory categorization task that required subjects to categorize the frequency of a tone burst into one of two overlapping categories ( or ) . We systematically varied the prior probability of choosing a frequency from category or in different blocks of the experiment . Furthermore , we determined each subject's sensory uncertainty by measuring individual frequency-discrimination thresholds . Based on these uncertainty measurements , we formulated a Bayesian model to individually quantify how well each subject learned the categorical priors ( i . e . , the category distributions and prior probabilities ) and to test whether subject's employed an optimal decision strategy . We found that most subjects appropriately learned the different category prior probabilities , yet showed some variability and uncertainty in the shape of the learned category distributions . Furthermore , given the measured sensory uncertainty during the experiment , subjects' overall behavior was more consistent with probability matching rather than an optimal decision strategy for category choice . Further analyses indicated that overall probability-matching behavior could emerge if , trial-by-trial , subjects employed an optimal decision strategy and assumed non-stationary categorical priors .
All subjects participated in a purely voluntary manner , after providing informed written consent , under the protocols approved by the Institutional Review Board of the University of Pennsylvania . Six subjects ( two female ) participated in two tasks: ( 1 ) a discrimination task that estimated each subject's frequency-discrimination thresholds and ( 2 ) an auditory-categorization task that tested how each subject used category-prior information . Both tasks were conducted in a darkened anechoic chamber ( 2 m×1 . 5 m , Industrial Acoustics Company , Inc . ) , which housed a chair for the subject , a gamepad , a table mounted with an LCD computer screen ( P190S , Dell , Inc . ) , a speaker ( MSP7 , Yamaha , Inc . ) , and a chin rest . The speaker was positioned ∼0 . 1 m below a subject's ears when his/her head was placed on the chin rest . The gamepad registered the subject's responses during each task . Both the discrimination and categorization tasks were designed and implemented in MATLAB ( version R2010b ) with the Tower-of-Psych and Snow-Dots packages ( freely available resources [17] , [18] ) . For both tasks , the stimuli were 750-ms tone bursts ( 10-ms ramp; frequency range: 500–5550 Hz ) . The tone frequencies were distributed uniformly in units . Stimuli were synthesized with an RX6 Multifunction Processor ( Tucker-Davis Technologies , Inc . ) with a sampling rate of 25 kHz and were presented at 65 ( ± 3 ) dB SPL . Each subject participated in a two-interval , two-alternative forced choice frequency-discrimination task . This task measured each subject's frequency-discrimination threshold at eight different “standard” frequencies , which were distributed between 500–5550 Hz: 794 , 1260 , 2297 , 2639 , 3031 , 3482 , 4462 , and 4976 Hz . A trial began with a visual “GO” cue on the computer screen , followed by the presentation of the first tone burst . After a 1000-ms delay , the second tone burst was presented . Following offset of this second tone burst , the subject had 2000 ms to report which tone burst had the higher frequency . Subjects only received feedback ( in the form of a yellow circle on the computer screen ) when a response was not made within the allotted response window . In each trial , one tone burst was one of the standard frequencies , whereas the other “comparison” tone burst had a different frequency . We used a 2-up-1-down adaptive staircase procedure [19] to adjust the frequency of the comparison tone across trials . On a trial-by-trial basis , the order of the standard and comparison tone bursts was randomized , as well as the choice of the standard tone burst . Each subject participated in 2–4 experimental sessions . Each session consisted of two blocks of trials; each block contained 30 or 40 trials per standard tone frequency ( 320 or 480 total trials ) . The data for each subject were collapsed across sessions and only trials in which a response was made within the allotted response window were included in subsequent analyses . We computed a psychometric function representing the probability that the subject reported the comparison tone ( ) as higher than the standard tone ( ) . Since the values of varied across subject and session , values were binned into five equidistant bins ( in units ) for each and subject . Each subject's psychometric functions ( i . e . , one function for each standard tone frequency ) were fit with a cumulative Gaussian with free parameters and using a maximum-likelihood fitting procedure to the raw data . We assumed that a subject's discrimination process was the result of a comparison between the frequencies of the standard and comparison tone bursts . We also assumed that the subject's sensory measurements of the comparison and standard tone bursts followed Gaussian distributions , each with the same standard deviation , , that we defined as the frequency-discrimination threshold of that standard tone frequency [20]–[22] . Consequently , was calculated directly from the derived from the cumulative Gaussian fit: . We then computed each subject's frequency-discrimination threshold as the average of the values measured at each of the eight standard tone frequencies ( in units ) . We used this average value for the predictions of our Bayesian model ( see Bayesian model ) . Each subject then participated in a two-alternative , forced-choice categorization task . The subject reported whether the frequency of a tone burst was a member of one of two different frequency categories ( or ) . The frequency range between 550–5550 Hz was divided into two equal ( in units ) , but overlapping , piecewise-uniform category distributions ( Figure 1a ) . Category contained frequency values between 500 to 2488 Hz . Category contained frequency values between 1115 to 5550 Hz . These two categories were designed so that category comprised the lower two-thirds of the frequency range , whereas category comprised the upper two-thirds of the frequency range ( again in units ) . As a consequence of this design , one part of each category's distribution was exclusive to that category ( i . e . , the extreme thirds of the entire frequency range ) , whereas the other part was shared with the other category ( i . e . , the middle third of the range ) . Our critical experimental manipulation was to vary the category prior probabilities , , where was either category or category . We varied the prior probabilities , on a block-by-block basis , by appropriately selecting the proportion of trials originating from a particular category . We tested the influence of three different category prior probabilities ( Figure 1b ) . In two of the manipulations , it was more likely that the frequency of a tone burst originated from one category than the other . In the third manipulation , it was equally likely that the frequency of a tone burst originated from either category . Before the first session , the category prior probabilities were explained to each subject . A trial began with a brief 1500-ms countdown , followed by a visual ‘GO’ cue indicating the imminent presentation of a tone burst . After tone-burst offset , the subject had 1000 ms to report a choice . Subjects received visual feedback on every trial: a green circle for correct responses , a red circle for incorrect responses , and a yellow circle for no response within the allotted 1000-ms response window . In separate blocks of trials , the prior probability for category was one of three values: = 0 . 25 , 0 . 5 , or 0 . 75 . On a trial-by-trial basis , we randomly selected the category according to its prior probability . Once a category was selected , we randomly selected a frequency from that category . As noted above , because the category distributions were piecewise uniform , any stimulus within the category was equally likely: for all frequencies within the category distribution ( or ) and outside of the distribution . The value of , where , is defined by the width of the category distributions . Each subject participated in 3–5 sessions of the categorization task; each session included one block of each of the three category prior probabilities . In total , each subject completed between 600–1000 trials for each category prior probability . For each subject , we computed the psychometric function ( where represents the subject's category choice ) for each of the three category prior probabilities across all sessions . Tone frequencies were binned into nine equidistant bins that spanned the entire frequency range: three frequency bins in each of the two unambiguous frequency regions and three bins in the ambiguous frequency region . We fit each psychometric function with a cumulative Gaussian using a maximum-likelihood procedure and identified the frequency at which a subject was equally likely to choose or : that is , the point of subjective equality ( PSE ) . We also fit cumulative Gaussians to each subject's categorization performance separately for each session to test for any potential learning effects throughout the course of the experiment . We developed a Bayesian model that tested three key aspects of each subject's categorization behavior . First , we tested whether subjects used the category-prior information for their categorical decisions . Second , we tested the degree to which subjects were able to learn category distributions . Finally , we tested the degree to which subjects employed an optimal decision strategy given the characteristics of the categorization experiment . Categorization can be considered an inference process over the generative graphical model shown in Figure 2a . The true category of a stimulus is governed probabilistically according to the prior probability ( Figure 2b , top panel ) . The category distribution , , indicates the probability that a stimulus from a category has a certain tone frequency . We assumed that each tone with frequency generated a sensory signal according to the probability density , which characterized the sensory uncertainty and noise in the auditory pathway . We assumed to be Gaussian with a mean centered on the true tone frequency and a standard deviation that reflected the level of sensory uncertainty ( Figure 2b , bottom panel ) . We measured for each subject as his or her frequency-discrimination threshold ( see Discrimination task and analysis ) . We assumed that subjects performed Bayesian inference over this generative model when solving the categorization task: given the sensory evidence , subjects computed the posterior probability . In this equation , is the likelihood that the measured frequency belonged to a particular category or . The likelihood was calculated by marginalizing over the tone frequency as . We assumed that subjects either ( 1 ) learned the experiment's stimulus distributions ( “objective priors”; Figure 2b , middle-left ) or ( 2 ) only learned an approximation of these distributions ( “subjective priors” ) . For the latter case , we parameterized using two piecewise-uniform distributions , each convolved with a Gaussian ( Figure 2b , middle-right ) . The subjective category distributions can be thought of as noisy estimates of the objective distributions . Each subjective distribution had its own mean ( and ) but had the same distribution width ( ) and the same Gaussian standard deviation ( ) . Finally , similar to the category distributions , the values of the category prior probability were assumed either to be ( 1 ) the experimental prior probabilities ( objective priors ) or ( 2 ) the free parameters , , and , representing each category prior probability ( subjective priors ) . Based upon the posterior , we tested whether subjects employed an optimal decision strategy to make a category choice ( either or ) . This strategy is a maximum a posteriori ( MAP ) strategy , in which subjects chose the most probable category given . In other words: . Thus , the subjects chose if , and chose otherwise . We also tested whether subjects' decisions reflected probability matching ( MATCH ) as a general index of sub-optimal categorization behavior [23]–[25] . Probability matching is equivalent to a decision strategy that results in subjects choosing a category probabilistically according to the posterior probability . In other words , . Finally , to directly compare and fit the model's predictions to each subject's behavioral data , we computed the psychometric function as a function of the true frequency as . Assuming objective priors , we used the Bayesian model to quantitatively predict each subject's categorization performance . We assumed the likelihood function was a Gaussian distribution with a standard deviation , which was measured and fixed separately for each subject ( ; see Discrimination task and analysis ) . Under these assumptions , the model has no free parameters . Therefore , we could predict each subject's psychometric function for each category prior probability and for both optimal ( MAP ) and sub-optimal ( MATCH ) categorization . We calculated the quality of the MAP and MATCH predictions by computing their respective log-likelihood values across all conditions . We rescaled these log-likelihood values relative to the predictions of two reference models: ( 1 ) an empirical model , which represents how well the observed data explains itself ( i . e . , a binomial model that employs the empirical choice probabilities ) , and ( 2 ) a random-guessing model [26] . Assuming that subjects only learned noisy estimates of the categorical priors ( i . e . , subjective priors ) , we also computed maximum-likelihood fits of the model for both MAP and MATCH behavior to each subject's categorization performance . The sensory uncertainty was again fixed for each subject based on the results of the discrimination experiment . Thus , the model fit with the subjective priors had seven free parameters , namely , , , , , , and ( see Figure 2b and previous section ) . We tested the goodness of fits by again comparing the normalized total log likelihoods for both MAP and MATCH . Finally , to assess the full potential of either type of decision behavior to explain each subject's categorization performance , we computed maximum-likelihood fits of the model using subjective priors , this time including as an additional free parameter ( for a total of eight free parameters ) . Once again , we tested the goodness of fits by comparing the normalized total log likelihoods .
We measured each subject's frequency-discrimination threshold to determine individual sensory uncertainty . The frequency-discrimination experiment required subjects to indicate the interval that contained the higher-frequency tone burst . For each subject , we calculated discrimination thresholds for each standard frequency , which is summarized in Figure 3a . As expected [27]–[30] , we found that the thresholds were approximately constant across the tested frequency range . Consequently , for each subject , we computed the mean of the thresholds ( ) across the eight standard frequencies ( Figure 3b ) . We used as the measure of each subject's sensory uncertainty in our Bayesian model . Because the subjects were initially unaware of the categorical priors , subjects had to learn both the category distributions and the category prior probabilities to make informed category decisions . To test whether subjects learned this information , we first compared each subject's psychometric functions ( i . e . , ) across the three different values of the category prior probability . We fit these psychometric functions with a cumulative Gaussian and extracted the point of subjective equality ( PSE ) for each curve . The psychometric functions and Gaussian fits for an example subject ( S3 ) are depicted in Figure 4a . Two main points can be taken from this figure . First , as the tone frequency increased , the probability that the subject chose decreased . Second , as increased , the psychometric functions shifted toward higher tone frequencies . However , the slopes of the psychometric functions remained consistent across category prior probability . These effects were comparable across individual subjects , with all but subject S2 exhibiting clear effects of the different category prior probabilities . These findings are summarized in Figure 4b and 4c . These effects of the different category prior probabilities were evident as early as the first session . Generally , additional experience with the categorical priors had little differential effect on PSE and slope ( Figure 5 ) . Thus , for subsequent analyses we grouped each subject's data across sessions . Our Bayesian model makes distinct predictions for subjects' psychometric performance ( Figure 6 ) . In the lowest and highest thirds of the frequency range , choice behavior is independent of category prior probability and identical for MATCH and MAP . This independence occurs because these frequency ranges are exclusive to categories and , respectively . The effects of are only present in the middle third of the frequency range , where the category distributions overlap . Under the objective-priors assumption , probability matching ( Figure 6a , left ) yields psychometric functions that exhibit a characteristic plateau . Increasing causes vertical shifts in these plateaus . In contrast , the MAP decision strategy ( Figure 6a , right ) yields smooth , sigmoidal psychometric functions . Moreover , increasing causes lateral shifts of the psychometric function . For both behaviors , governs the steepness of the transition in choice behavior from choosing to choosing . Under the subjective-priors assumption , the predicted characteristics of the psychometric functions change distinctly for MAP and MATCH ( Figure 6b ) . With MATCH , the psychometric functions become smoother overall with increasing values of ( Figure 6b , left column ) . However , the vertical shifts with increasing are still evident . The predictions for the MAP decision strategy are similar to those under the objective-priors assumption ( compare Figures 6a and 6b , right column ) . Contrary to what is seen in the predictions for MATCH behavior , here does not affect the slopes but , instead , affects the relative lateral shifts of the psychometric functions . We compared the predictions of the Bayesian observer with each subject's behavior assuming the objective priors ( see METHODS ) . In general , the model predictions for both types of decision behavior did not accurately reflect subjects' behavior ( Figure 7 ) . MATCH behavior predicted step-like psychometric functions ( see Figure 6 ) that were reflected only in some subjects' performance ( e . g . S4 ) . The predictions of the model with the MAP decision strategy were even less accurate: this decision strategy predicted slopes of the psychometric functions that were substantially and consistently steeper than those observed in each subject . We quantified the quality of the two model predictions by calculating the total likelihood of the models given each subject's behavior . MATCH was significantly more predictive of each subject's performance , as exemplified by the likelihoods for each type of decision behavior across subjects ( Figure 8 ) . In fact , the MAP strategy was significantly worse than a random guess for all subjects , whereas MATCH was better than random guessing for half of the subjects ( i . e . , S1 , S4 , and S5 ) . Because the objective category distributions did not fully predict the subjects' performances , we used subjective categorical priors and fit the Bayesian model ( see Figure 2 and METHODS ) . However , as before , we fixed to reflect each subject's measured frequency-discrimination threshold . Fits assuming MATCH behavior almost perfectly accounted for the data , with an accuracy that approached empirical performance ( Figures 9 and 10 ) . However , the fits under the MAP strategy were still poor: the MAP strategy failed to account for the slopes of the psychometric functions ( Figure 9 ) . Except for subject S1 , the MAP strategy yielded fits that were significantly worse than random guessing . In fact , the MAP-strategy fits to the data did not provide any better account of the data than its predictions based on the objective priors ( compare Figures 8 and 10 ) . Finally , we were interested in reconstructing the subjective category distributions for the subjects and comparing them to the objective distributions; because the MAP decision strategy provided a poor description of subjects' performances , we focused only on the fits assuming MATCH behavior . The reconstructed category distributions tended to more closely resemble Gaussian distributions rather than boxes ( Figure 11 ) . Both the modeled category means and category widths either were close to or overlapping with the actual means and widths of the objective distributions ( Figure 12a–c ) . However , the category edges were much less defined as compared to the edges of the objective distributions , exemplified by large values ( Figure 12d ) . Overall , the fitted category prior probabilities , , and for individual subjects were remarkably similar to the actual values 0 . 25 , 0 . 5 , and 0 . 75 , respectively ( Figure 12e–g ) . The previous model analyses revealed that probability matching ( MATCH ) is much better than the optimal ( MAP ) strategy in both predicting each subject's categorization behavior as well as explaining behavior after fitting the model with subjective priors . However , this comparison assumes that we have accurately measured each subject's sensory uncertainty . It is possible that , with additional sources of sensory uncertainty ( e . g . , memory noise [31] , [32] ) , the MAP strategy could be equally as descriptive as MATCH behavior . Indeed , under certain noise conditions , MAP and MATCH behaviors are equivalent [33] . To address this possibility , we performed an additional analysis in which all of the parameters were fit , including ( for a total of eight free parameters ) . When we included as a free parameter , both strategies accurately reflected individual subject's categorization behavior ( fits not shown ) . However , we found that , without exception , MATCH behavior was still a better explanation of each subject's performance ( Figure 13a ) . Moreover , in order for the MAP strategy to achieve this improvement in explanatory power , the sensory noise had to be 10–100 times larger than the measured values for each subject . In comparison , the fitted levels of obtained from the MATCH fits were quite close to the individually measured discrimination thresholds for each subject ( Figure 13b ) . Up to now , the model formulations assumed that subjects' estimates of the categorical priors were constant . However , this may not be true . Thus , we were interested in determining how trial-by-trial noise on the categorical priors may affect categorization performance . In particular , we wanted to test whether this additional noise could cause performance under an optimal decision strategy ( MAP ) to appear sub-optimal ( MATCH ) . We conducted a series of simulations in which we added noise to both the means of the category distributions and the prior probabilities ( Figure 14a ) . Increasing category-distribution noise ( ) led to decreases in the slope of the psychometric function ( Figure 14b ) . Note , even though the net effect of this noise is similar to having constant Gaussian-shaped distributions ( Figure 14b , inset ) , the predicted categorization performance is different from the MAP predictions with constant Gaussian-shaped distributions ( see Figure 6 ) . In the latter case , there is no effect on the slopes of the psychometric function . Increasing prior-probability noise ( ) exhibited qualitatively different effects on performance as a function of ( Figure 14c ) . First , under asymmetric prior-probability conditions ( i . e . , = 0 . 25 or 0 . 75 ) , sufficiently small levels of ( e . g . , below ∼0 . 08 ) did not substantially influence the psychometric function ( Figure 14c , left and right panels ) . However , larger levels of caused the function to exhibit plateaus . Moreover , depending on the level of , we could observe over- , under- , or true probability matching; compare the bright and dark red traces in the left and right panels of Figure 14c . Interestingly , when the prior probabilities were symmetric ( i . e . , = 0 . 5 ) , any level of led to psychometric functions with a characteristic plateau . One potential interpretation of this noise is that subjects' categorical priors are non-stationary . Specifically , we hypothesized that subjects estimated the categorical priors only over recent trial history . To investigate this hypothesis , we computed running estimates of over different bin lengths of consecutive trials and compared the variability in these estimates with the levels of that yielded step-like psychometric functions . We found that the variability in over relatively short bin lengths ( i . e . , generally <16 trials ) was generally consistent with these levels ( Figure 15 ) .
We found that subjects learned the categorization task to varying degrees . All but one subject could use the category-prior information to solve the task . Subjects learned general characteristics of the category distributions ( i . e . , high versus low frequencies ) and the category prior probabilities as early as the first session . This is consistent with previous work showing that the largest effects of category learning occur early in training and then are fine-tuned with further experience [34] , [35] . Our finding that subjects learned the category prior probabilities is consistent with previous visual categorization tasks [5] , [8] , [9] , [36]–[38] . However , the systematic evaluation of prior probabilities and category learning in this study is novel for audition . One goal of this study was to test whether subjects employed an optimal decision strategy to perform auditory categorization under categorical ambiguity . In order to do this , we developed a single generative Bayesian model that allowed us to both predict and fit each subject's psychometric curve for all tested conditions under instances of either optimal or sub-optimal categorization behavior . A critical component of this approach was that we separately estimated each subject's perceptual noise by measuring frequency-discrimination thresholds . One finding of our model predictions was that subjects' performances were not accurately predicted assuming the objective priors ( i . e . , box-shaped distributions ) . This suggests that subjects were limited in their ability to learn the objective priors . Indeed , our model fits were consistent with the hypothesis that subjects learned smooth approximations of the box-shaped distributions . This finding may not be surprising: previous work has demonstrated that subjects often assume approximate versions of experimental distributions when learning new behavioral tasks [39]–[42] . It is possible that the large degree of uniform overlap between the categories contributed to subjects' difficulties in estimating the category distributions . However , other evidence suggests that subjects can , to an extent , learn category distributions that are non-Gaussian [41] , [43] , [44] . Therefore , with extensive training , subjects might have been able to learn the objective priors . Another important finding was that subjects' performances were more consistent with probability matching . This was the case after both predicting and fitting performance with our Bayesian model . Because this type of behavior reflects sub-optimal categorization , we conducted further analyses to investigate whether subjects actually implemented an optimal decision strategy but performed sub-optimally due to additional uncertainties [33] , [45] , [46] . Additional memory noise was unlikely to account for this possibility for two reasons . First , when sensory noise was a free parameter and could account for additional memory noise , probability matching still outperformed the optimal decision strategy . Second , the fitted values of the sensory noise for the optimal strategy were 10–100 times larger than our measured estimates ( Figure 13 ) . This difference between the measured and fitted values seems unreasonable given previous work on the effects of memory noise on frequency discrimination [31] , [32] . We also simulated the effects of additional noise on the category distributions and prior probabilities . The results of the simulations suggested that a combination of category-distribution and prior-probability noise could lead to psychometric functions that mimic probability-matching behavior ( i . e . , shallow psychometric functions with a plateau ) , even though the decision strategy was optimal ( see Figure 14 ) . Categorical-prior noise could reflect true uncertainty or subjects' tendencies to search for patterns in sequences of random events [23] , [25] , [47] , [48] . One interpretation is that our subjects assumed that the categorical priors changed over time ( i . e . , they were non-stationary ) . Under this assumption , our analyses suggested that subjects' estimates of the categorical priors were reflections of the short-term stimulus history ( see Figure 15 ) . Future work is necessary to determine more quantitatively whether subjects whose performance is most sensitive to the local trial history are more likely to exhibit psychometric functions that mimic probability-matching behavior and how this effect changes after extensive training . Together , our results suggest that the prevalence of probability matching in perceptual tasks might reflect model assumptions of stationarity that are not correct [7] , [49]–[52] . In other words , the interpretation of subjects' categorical behavior should not focus on sub-optimal versus optimal decision strategies but , rather , should focus on the degree to which subjects assume the environment is stationary and which factors can impact these assumptions . For example , changes in cost-reward structures may not change subjects' decision strategy , but may influence their view of environmental stationarity [7] , [8] , [37] , [50] . | Categorization is an important cognitive process that allows us to simplify , extract meaning from , and respond to objects in the sensory environment . However , categorization is complicated because an object can belong to multiple categories . Thus , to inform our categorical judgments , we must make use of prior information . Given the importance of categorization , we hypothesized that humans utilize optimal strategies for making categorical judgments that allow us to minimize categorization errors . We found , though , that whereas subjects used prior information ( i . e . , category prior probability ) , they were sub-optimal in their categorization behavior . This seems to be common in other perceptual and cognitive tasks as well . We then explored the bases for this sub-optimal behavior and found that it can be consistent with an optimal strategy if we assume that subjects have trial-by-trial noise in components of the judgment process . This work extends previous similar findings into the field of auditory categorization and provides a means to reinterpret previous results . | [
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] | 2014 | Characterizing the Impact of Category Uncertainty on Human Auditory Categorization Behavior |
Ribosomal protein L3 is an evolutionarily conserved protein that participates in the assembly of early pre-60S particles . We report that the rpl3[W255C] allele , which affects the affinity and function of translation elongation factors , impairs cytoplasmic maturation of 20S pre-rRNA . This was not seen for other mutations in or depletion of L3 or other 60S ribosomal proteins . Surprisingly , pre-40S particles containing 20S pre-rRNA form translation-competent 80S ribosomes , and translation inhibition partially suppresses 20S pre-rRNA accumulation . The GTP-dependent translation initiation factor Fun12 ( yeast eIF5B ) shows similar in vivo binding to ribosomal particles from wild-type and rpl3[W255C] cells . However , the GTPase activity of eIF5B failed to stimulate processing of 20S pre-rRNA when assayed with ribosomal particles purified from rpl3[W255C] cells . We conclude that L3 plays an important role in the function of eIF5B in stimulating 3′ end processing of 18S rRNA in the context of 80S ribosomes that have not yet engaged in translation . These findings indicate that the correct conformation of the GTPase activation region is assessed in a quality control step during maturation of cytoplasmic pre-ribosomal particles .
Ribosomes are very intricate ribonucleoprotein particles that catalyse protein synthesis . In all organisms , ribosomes are composed of two ribosomal subunits ( r-subunits ) , the large one ( 60S , LSU ) being about twice the size of the small one ( 40S , SSU ) [1] , [2] . In eukaryotes , synthesis of ribosomes is a multicomponent , multistep process that is highly compartmentalised ( for reviews , see [3]–[5] ) . Most ribosome maturation reactions take place in the nucleolus , but later steps occur in the nucleoplasm and cytoplasm [6]–[8] . Although evolutionary conserved throughout eukaryotes , ribosome biogenesis has been best studied in the yeast Saccharomyces cerevisiae . In the yeast nucleolus , the mature 18S , 5 . 8S and 25S rRNAs are transcribed as a single large precursor rRNA ( pre-rRNA ) that undergoes both co-transcriptional and post-transcriptional processing [9] . Concomitant with processing , the pre-RNAs undergo RNA modification and folding , association with trans-acting factors , and assembly with 5S rRNA and most ribosomal proteins ( r-proteins ) to form pre-ribosomal particles . The yeast pre-rRNA processing pathway is well-characterised [10] ( see Figure S1 ) . Among the pre-rRNA processing reactions , cleavage at site A2 is special since it separates the intermediates on the LSU and SSU synthesis pathway , which apparently follow independent nuclear maturation . Correct nuclear maturation of pre-ribosomal particles leads to the recruitment of export factors and acquisition of export competence . Incorrectly assembled pre-ribosomal particles are strongly retained in the nucle ( ol ) us and are targeted to degradation ( for examples , see [11] , [12] and references therein ) . Cytoplasmic pre-ribosomal particles undergo final maturation before becoming translationally active [8] , [13] . Cytoplasmic maturation of pre-60S particles involves pre-rRNA processing of the 6S pre-rRNA to mature 5 . 8S rRNA [6] and the dissociation and recycling of several export and assembly factors by an ordered series of linked ATPase- and GTPase-dependent steps [8] , [14] . Among these factors are Tif6 and Nmd3 , which are proposed to impede joining of pre-60S with mature 40S r-subunits [15] , [16]; thus , they should be removed before mature 60S r-subunits enter translation . Concomitant with this , the assembly of several r-proteins occurs , amongst them P0 ( also P0 in the new proposed nomenclature of r-proteins [17] ) , L10 ( L16 ) , L24 ( L24e ) and L40 ( L40e ) . During cytoplasmic maturation of pre-40S particles , Dim1 dimethylates two consecutive , conserved adenines at the 3′ end of the 18S rRNA [18] , followed by Nob1-dependent cleavage of the 20S pre-rRNA at site D to produce the mature 18S rRNA 3′ end [7] , [19] . Late-acting factors associated with the cytoplasmic pre-40S particles may prevent premature association with translation initiation factors , mRNA , initiator tRNA , and mature 60S r-subunits [20] . Only a few 40S r-proteins are thought to stably assemble in the cytoplasm , and these are likely to include S3 ( S3 ) , S10 ( S10e ) and S26 ( S26e ) [21] . We are interested in understanding the contribution of specific 60S r-proteins to ribosome biogenesis . L3 is an evolutionarily conserved protein that contains two tightly packed globular domains bound on the solvent side of the LSU , close to the binding region for GTP-dependent translation factors . Moreover , L3 contains two extensions that enter deep into the central core of the LSU and are very close to the peptidyl transferase center ( PTC ) ( Figure S2 ) [2] , [17] . Dinman and coworkers have extensively studied the role of yeast L3 in ribosome function and revealed that it modulates translation elongation by coordinating both the accommodation of charged tRNAs and the binding of elongation factor 2 ( eEF2 ) ( e . g . [22] , [23] ) . We have previously undertaken the analysis of L3 in yeast ribosome synthesis . Our results indicate that L3 has an essential role in the formation of early pre-60S r-particles [24] . To further study the role of L3 in ribosome synthesis , we have analysed the phenotypic effects of a collection of viable rpl3 point mutants . Herein , we show that , unexpectedly , the rpl3[W255C] mutation leads to the accumulation of translation-competent cytoplasmic pre-40S r-particles containing the 20S pre-rRNA . These in vivo results unequivocally demonstrate the requirement of the 60S r-subunit for efficient 20S pre-rRNA processing . Two recent studies have revealed that 20S pre-rRNA cleavage to mature 18S rRNA might require the association of pre-40S r-particles with the yeast translation initiation factor eIF5B/Fun12 and the 60S r-subunit to form an 80S-like complex [25] , [26] . In agreement with these reports , our results demonstrate that despite the fact that in vivo yeast eIF5B associates with similar efficiency to wild-type and L3[W255C] containing ribosomes , its GTPase activity is unable to stimulate processing of 20S pre-rRNA in rpl3[W255C] cells . Taking into account that the L3[W255C] mutant protein alters the structure of the 60S r-subunits [27] and the in vitro affinity of ribosomes for the elongation factors eEF1 and eEF2 [23] , we postulate that the correct conformation of the binding site of ribosome-dependent GTPases is used as a quality control step to ensure proper maturation of cytoplasmic pre-ribosomal particles .
To define better the role of L3 in the normal accumulation of 60S r-subunits , we studied the phenotypes of selected rpl3 point mutations ( Figure S2A ) . The rpl3[K30E] and rpl3[Q371H] mutations were found to be synthetically lethal with mutants of genes encoding components of the Dpb6-containing subcomplex [28] , [29] . The rpl3[W255C] , rpl3[P257T] , rpl3[I282T] and rpl3[W255C , P257T] mutations have been reported to affect different translation properties [22] , [23] , [30] . All these mutant proteins support growth as the sole source of L3 , although not at wild-type levels , and are recessive ( Figure S3 , and data not shown ) . We next examined the polysome profiles of the different mutants grown at 23°C relative to an isogenic wild-type strain . As shown in Figure 1 , the rpl3[K30E] , rpl3[Q371H] and rpl3[P257T] mutants clearly displayed profiles consistent with a deficit of 60S r-subunits . Notably is the appearance of polysome halfmers ( indicated with arrows in Figure 1 ) , which reflect formation of 43S pre-initiation complexes that are not bound by 60S r-subunits . Moreover , the rpl3[I282T] mutant apparently has a mild translation initiation defect . Unexpectedly , both the single rpl3[W255C] and the double rpl3[W255C , P257T] mutants displayed a clear deficit in free 40S relative to 60S r-subunits . This finding was not previously reported for the original mak8-1 mutant , which consists of the double rpl3 mutation W255C P257T [31] . Northern analyses were used to determine whether the polysome profiles obtained for the rpl3[W255C] and the rpl3[W255C , P257T] mutants correlated with defects in pre-rRNA processing or rRNA accumulation . Comparison of total RNA isolated from the rpl3 mutants and the isogenic wild-type strain revealed only slight differences in the levels of most pre-rRNAs in rpl3 mutants ( Figure 2 ) . The exception was a dramatic accumulation of 20S pre-rRNA in the rpl3[W255C] and rpl3[W255C , P257T] mutants , accompanied by modest reductions in mature 18S rRNA accumulation . These phenotypes were similar to those observed in the previously characterised rps14A[R136A] mutant , which served as a positive control for 20S pre-rRNA accumulation [32] . We conclude that , unexpectedly for a specific mutation in a 60S r-subunit protein , the mutation rpl3[W255C] leads to a 40S r-subunit biogenesis deficit due to a defect in 20S pre-rRNA processing . Processing of the 20S pre-rRNA occurs in the cytoplasm [7] , so a defect in 20S pre-rRNA processing might result from either reduced export of pre-40S particles or impaired cleavage of cytoplasmic 20S pre-rRNA . To assess pre-40S export , we analysed the subcellular localisation of the 40S r-subunit reporter S2-eGFP in wild-type and rpl3[W255C] cells . As shown in Figure 3A and Figure S4 , both S2-eGFP and the 60S r-subunit reporter L25-eGFP were almost exclusively cytoplasmic in both wild-type and rpl3[W255C] cells . We also visualised the 20S pre-rRNA and its precursors by FISH using a probe complementary to the 5′ region of ITS1 . In the wild-type strain , the FISH signal was predominantly nucleolar with a faint cytoplasmic signal ( Figure 3B ) . This was expected , since the 20S pre-rRNA is rapidly converted to mature 18S rRNA following export of pre-40S particles to the cytoplasm . However , in the rpl3[W255C] mutant , the signal was substantially stronger and predominantly cytoplasmic , indicating that the unprocessed 20S pre-rRNA accumulated in the cytoplasm of rpl3[W255C] cells . The 20S pre-rRNA is dimethylated at the 3′ end of 18S rRNA by Dim1 following export and prior to cleavage [33] . Primer-extension is blocked by the presence of the dimethylation , which was clearly present in 20S pre-rRNA of rpl3[W255C] cells ( Figure 3C ) , confirming that the block in maturation occurs following export . We conclude that the 20S pre-rRNA is exported from the nucleus but fails to be efficiently processed in the cytoplasm in rpl3[W255C] cells . Identical results were obtained in analyses of rpl3[W255C] yeast strains derived from W303 or BY4741 , showing our findings to be independent of genetic background and any secondary mutation ( s ) ( data not shown ) . We previously reported that pre-40S r-particles containing the 20S pre-rRNA could be efficiently incorporated into translating ribosomes in ubi3Δub mutant cells [34] . In contrast , pre-40S r-particles are not found in polysomes in wild-type cells or in most mutants that accumulate cytoplasmic 20S pre-rRNA [25] , [32] , [35] , [36] . Interestingly , pre-40S r-particles can engage with mRNAs and 60S subunits but are unable to efficiently elongate in cells depleted of Rio1 or Nob1 , or expressing S14A[R136A] [25] , [36] , [37] . To assess whether the pre-40S r-particles accumulated in rpl3[W255C] cells engage in translation , the distribution of the 20S pre-rRNA in polysome gradients was determined by northern blotting and compared to the wild type and cells expressing L3[Q371H] or S14A[R136A] ( Figure 4 ) . In wild-type and rpl3[Q371H] mutant cells , 20S pre-rRNA co-migrated with the 40S r-subunit peak . In rps14A[R136A] cells , the 20S pre-rRNA accumulated in the 80S peak , whereas the rpl3[W255C] mutant showed 20S pre-rRNA in complexes of high molecular weight that co-sedimented with polysomes . To confirm that the slowly sedimenting 20S pre-rRNA containing particles were not simply aggregates , cell extracts were prepared under polysome run-off conditions ( omission of cycloheximide ) either in standard buffer or in a buffer lacking MgCl2 ( which causes dissociation of 80S couples into 40S and 60S r-subunits ) . In the absence of cycloheximide , the 20S pre-rRNA was shifted from the high molecular weight fractions to the 80S fractions in the presence of MgCl2 or to 40S fractions in the absence of MgCl2 ( Figure S5 ) . Moreover , quantification of the 20S/18S and 20S/25S ratios showed similar values for each polysomal fraction in Figure 4 , indicating that the accumulated , 20S pre-rRNA containing pre-40S r-particles are competent for both translation initiation and elongation ( data not shown ) . We conclude that the presence of L3[W255C] in the 60S r-subunits leads to the accumulation of pre-40S particles that assemble into 80S ribosomes and are competent for translation elongation . We assessed whether translation influences the accumulation of pre-40S r-particles in the rpl3[W255C] mutant ( Figure 5 ) . Protein synthesis was inhibited by treatment of wild-type and rpl3[W255C] strains with 0 . 8 µg/ml cycloheximide ( the lowest concentration that arrested growth ) . As shown in Figure 5A , cycloheximide treatment for 6 h did not significantly affect steady-state levels of mature 25S and 18S rRNA in the wild-type or the rpl3[W255C] strain and resulted in only a minor accumulation of 35S pre-rRNA in wild-type cells . Cycloheximide also had little effect on 20S pre-rRNA levels in the wild-type strain , whereas a 2-fold reduction was already observed 1 h after cycloheximide addition to rpl3[W255C] cells . To discard any indirect effect of the cycloheximide treatment , we blocked translation initiation by using a cdc33–42 mutant , in which Cdc33/eIF4E is defective in recognition of the cap structure of mRNAs during translation initiation [38] . As shown in Figure 5B , in the cdc33–42 rpl3[W255C] double mutant , the 20S pre-rRNA levels again decreased about 3-fold in comparison to those from an isogenic rpl3[W255C] single mutant , while the 20S pre-rRNA levels in the cdc33–42 single mutant were similar to those of the wild type strain . The fraction of ribosomes engaged in translation is much lower in slow-growing than in fast-growing cells [39] . Consistently , when wild-type and rpl3[W255C] cells were cultivated in different media , we found a clear correlation between the measured doubling times and the levels of accumulation of 20S pre-rRNA in the rpl3[W255C] strain ( Figure 5C and Table S4 ) . Thus , fast-growing cells accumulated about 4-fold more 20S pre-rRNA than slow-growing cells . These data indicate that 20S pre-rRNA accumulation in rpl3[W255C] cells is promoted by active translation , suggesting that 20S pre-rRNA processing and/or decay is prevented in pre-40S r-particles engaged in translation . Fun12 ( the yeast homologue of eIF5B ) is a GTPase required for binding of initiator tRNA and r-subunit joining during translation initiation [40] . In addition , Fun12/eIF5B is required for efficient 20S pre-rRNA processing [26] , [41] , which requires binding of Fun12/eIF5B to pre-40S r-particles and mature 60S r-subunits [25] , [26] . To assess binding of Fun12 to 60S r-subunits containing L3[W255C] , we expressed a fully functional genomically integrated Fun12-TAP construct [42] in wild-type and rpl3[W255C] cells and performed immunoprecipitation experiments with IgG-Sepharose . As shown in Figure 6A , western blot analysis indicated that Fun12-TAP co-precipitates Nob1 and r-proteins from both r-subunits to the same extent in both strains . Furthermore , Northern hybridisation showed that Fun12-TAP co-precipitated similar levels of 20S pre-rRNA and mature 25S rRNAs relative to the levels of their respective inputs in cells of both strains ( Figure 6B ) . As previously reported [26] , Fun12 also co-precipitated nuclear 35S , 32S and 27S pre-rRNAs . The significance of this is unclear , but more efficient association with these species was observed in wild-type compared to rpl3[W255C] cells . Since Fun12/eIF5B co-precipitates several pre-rRNAs , we studied the association of TAP-tagged Fun12/eIF5B with pre-ribosomal particles by sucrose gradient analysis . As shown in Figure S6A , Fun12-TAP is enriched in the low-molecular-mass fractions , in free 40S r-subunits , 80S and polysomes . In agreement with our previous results , the sedimentation pattern of Fun12-TAP was similar in cell extracts of wild-type and rpl3[W255C] cells . Likewise , analysis of the sedimentation pattern of fully functional N-terminal PTH-tagged Nob1 in sucrose gradients showed that PTH-Nob1 is enriched in the low-molecular-mass region and free 40S r-subunit fractions of the gradient with a weaker peak around 80S to 90S in wild-type cells . This sedimentation pattern was also similar for wild-type and rpl3[W255C] cells ( Figure S6B ) . We conclude that the binding of Fun12/eIF5B and Nob1 to 80S-like r-particles is not significantly altered in rpl3[W255C] cells . In vitro cleavage of 20S pre-rRNA by the endonuclease Nob1 is stimulated by addition of ATP or GTP , and Fun12/eIF5B was identified as the relevant GTPase [26] . We used this assay to determine whether L3 directly contributes to 20S pre-rRNA cleavage . To this end , we purified pre-ribosomal particles from cells expressing L3 or L3[W255C] via N-terminally PTH-tagged Nob1 , which co-purifies both free pre-40S r-particles and pre-40S-60S complexes [26] . The stimulation of 20S pre-rRNA processing upon addition of ATP or GTP was assessed by primer extension ( Figure 7 ) . As controls , pre-ribosomes were also purified from cells expressing L3[K30E] and rsa3Δ cells; both mutations reduce 60S r-subunit accumulation to a similar extent , but do not lead to 20S pre-rRNA accumulation ( [29] , and Figure 2 ) . Nob1 , like other PIN-domain nucleases , requires Mn2+ for efficient in vitro cleavage ( see ref . [19] and references therein ) . During the incubations required for purification of the pre-ribosomes , cleavage is inhibited by the use of buffers containing only Mg2+ . Cleavage is then activated at time 0 by addition of Mn2+ plus the relevant nucleotide . However , Nob1 inhibition in the absence of added Mn2+ is not complete , so the 0 min time point contains some level of pre-rRNA that has been cleaved at site D [26] . Thus , in our assays , the efficiency of cleavage was quantified relative to the signal at time 0 . Moreover , the amount of 20S pre-rRNA that is recovered and available for cleavage is not the same for different mutants . In particular , the in vivo 20S pre-rRNA processing defect shown by rpl3[W255C] strains results in substantially higher recovery , as shown by the stronger primer extension stop at the 18S rRNA dimethylation sites at A1781/1782 and the increased signal at site D at time 0 . Since only a small fraction of the total 20S pre-rRNA is cleaved , even under optimal conditions , the primer extension stop at A1781/1782 was used as a control for input to normalize between the different time points for each strain . Comparison of primer extension stops at site D and at A1781/1782 in the 0 min samples , indicated that the fraction of the 20S pre-rRNA that was cleaved during pre-ribosome purification was similar in each sample ( Figure S7 ) . As shown in Figures 7A and 7B , addition of Mn2+ plus ATP to pre-ribosomes purified from the wild-type cells increased the level of cleaved 20S pre-rRNA about 3 . 5-fold after 30 min incubation . Cleavage of 20S pre-rRNA in the presence of ATP was mildly reduced when r-particles were purified from rpl3[K30E] , rpl3[W255C] or rsa3Δ cells ( only 2 . 5-fold stimulation at 30 min ) probably reflecting the deficit in 60S r-subunit levels . In contrast , when cleavage was activated by addition of Mn2+ plus GTP , the level of 20S pre-rRNA cleaved at site D was elevated around 2 . 5 fold in pre-ribosomes purified from the wild-type , rpl3[K30E] , or rsa3Δ strains , whereas substantially less cleavage was observed for pre-ribosomes recovered form rpl3[W255C] cells ( less than 1 . 5-fold stimulation at 30 min ) ( Figures 7C and 7D ) . We conclude that impairment of 20S pre-rRNA processing in rpl3[W255C] cells is , at least , partially due to the inability of the GTP-dependent activity of Fun12/eIF5B to stimulate the Nob1 cleavage activity at site D . Since L3[W255C] protein is a component of 60S r-subunits , these data demonstrate that 20S pre-rRNA processing could occur in particles formed by pre-40S and pre-60S or mature 60S r-subunits . To test for functional interactions between L3 and Nob1 , we combined the rpl3[W255C] mutation with the NOB1-TAP allele , which expresses Nob1 fused at its C-terminus with a TAP-tag . This nob1 allele also leads to a mild 20S pre-rRNA accumulation , in contrast to the PTH-NOB1 construct , which behaves like the wild type protein ( [26] , and data not shown ) . As shown in Figure 8 , the NOB1-TAP allele specifically exacerbated the growth defect of the rpl3[W255C] mutant at both 23°C or 30°C . Taken together with the results of the previous section , these data strongly suggest that the conformational changes of 60S r-subunits caused by the W255C mutation in L3 negatively affect the functionality of the D-site endonuclease Nob1 .
Multiple steps in the translation cycle are mediated by ribosome-associated GTPases , including eIF5B/Fun12 ( r-subunit joining ) , eEF1 and eEF2 ( translation elongation ) , eEF3 ( translation termination ) and even Hbs1 ( release of stalled ribosomes and NGD ) ( reviewed in [43] ) . Each of these associates with a common binding site in the 60S r-subunit , which is referred to as the GTPase-associated center . Recent reports have proposed that final maturation of cytoplasmic pre-40S r-particles is stimulated by association with Fun12 and mature 60S r-subunits [25] , [26] . Here , we demonstrate a functional link between formation of the correct structure in the GTPase-associated center region of 60S r-subunits and the stimulation of 20S pre-rRNA cleavage . L3 has been described as the “gatekeeper to the A-site” [23] and the L3[W255C] protein alters the structure of the 60S r-subunits [27] and the binding in vitro of elongation factors [23] . These results strongly suggest that the correct conformation of the domain forming the binding site for the ribosome-dependent GTPases is a prerequisite for final 40S r-subunit maturation . This model is outlined in Figure 9 . Examination of the L3 structure within the 60S r-subunit ( see Figure S2B ) reveals that W255 is located at the tip of the internal “finger” that extends through the A-site to the PTC . Indeed , this residue makes the closest approach of any amino acid to the PTC site . Residue P257 induces a bend in the finger that helps position W255 [17] , [22] , [23] , [27] . Biochemical and molecular analyses show that L3 functions in binding of aminoacylated tRNAs and eEF2 . Moreover , mutations in L3 affect peptidyl-transferase activity , antibiotic sensitivity and translation of RNA derived from the “killer” dsRNA virus ( see [22] , [23] and references therein ) . The rpl3[W255C] allele was found to be functionally important as this mutation conferred resistance to anisomycin , decreased peptidyltransfer rate and increased programmed −1 r-frameshifting ( −1 PRF ) , leading to loss of the killer virus . All these phenotypes appear to result from increased affinity of ribosomes containing L3[W255C] for the eEF1-GTP-aminoacylated tRNA ternary complex and decreased affinity for eEF2 [22] , [23] . In the 80S ribosome structure , the W255 residue is about 12 nm away from the 3′ end of the 18S rRNA , making it unlikely to directly contact the 20S pre-rRNA processing machinery ( see Figure S2B ) . It also appears unlikely that the reduced 20S cleavage in rpl3[W255C] strains is an indirect effect of reduced translation of ( a ) 20S pre-rRNA processing factor ( s ) , since other rpl3 alleles ( e . g . rpl3[P257T] and rpl3[I282T] ) also result in strong anisomycin resistance , peptidyl-transferase inhibition and stimulation of −1 PRF [30] but do not impair 20S pre-rRNA processing or turnover ( Figures 1 and 2 ) . Therefore , the observed 20S pre-rRNA processing impairment in rpl3[W255C] cells is likely caused by the loss of proper interaction and/or function of a distinct trans-acting factor that stimulates the activity of the D-site endonuclease Nob1 . In line with such a scenario , we observed that only the rpl3[W255C] mutation exacerbates the mild slow-growth phenotype of a NOB1-TAP allele , which expresses a C-terminally TAP-tagged Nob1 protein ( Figure 8 ) . The observation that ribosomes containing L3[W255C] show alterations in the affinity and function of elongation factors eEF1 and eEF2 [22] , [23] , suggested that functional interactions with Fun12/eIF5B might also be impaired . The structural homology between the eIF5B G-domains of Fun12/eIF5B , eEF1 and eEF2 strongly indicates that these proteins interact similarly with the ribosome ( [44] , reviewed in [43] , [45] ) . The GTPase activity of Fun12 promotes r-subunit joining [40] , [46] and stimulates in vitro Nob1-dependent 20S pre-rRNA cleavage in purified pre-40S r-particles in conjunction with mature 60S r-subunits [26] . Stimulation of 20S pre-rRNA cleavage by GTP is lost in pre-40S r-particles that were associated with 60S particles containing L3[W255C] ( Figures 7C and 7D ) . Since Fun12 is responsible for GTP-mediated stimulation of 20S pre-rRNA cleavage in vitro [26] , we conclude that Fun12 function ( i . e . its GTP-hydrolysis dependent conformational change ) is practically impaired in ribosomes containing L3[W255C] . This does not appear to be due to strongly reduced binding of Fun12 to 80S particles , since Fun12-TAP co-precipitated in vivo particles containing 20S pre-rRNA and 25S rRNA with similar efficiencies from wild-type and rpl3[W255C] cells ( Figure 6 ) . Fun12-TAP also co-precipitated 35S , 32S and 27S pre-rRNA species , and maturation of both 35S and 27S pre-rRNAs is delayed in a fun12Δ strain [26] , [41] . The rpl3[W255C] allele did not clearly alter 35S or 27S pre-rRNA processing ( see Figure 2 ) , but strongly reduced association of these pre-rRNA species with Fun12-TAP ( Figure 6 ) . The significance of the association of Fun12 with nuclear and nucleolar pre-ribosomes remains to be determined . In vitro , cleavage of 20S pre-rRNA in purified pre-40S r-particles is also activated by an ATP-binding factor that remains to be identified [26] . The stimulation of 20S pre-rRNA processing by ATP is reduced , to slightly different extents , for r-particles purified from rpl3[K30E] , rsa3Δ or rpl3[W255C] cells ( Figures 7A and 7B ) . This indicates that the factor responsible for ATP-stimulated cleavage is also dependent on 60S r-subunits , but with a specificity that is different from Fun12 . Analysis of the presence of 20S pre-rRNA in polysome fractions clearly indicated that pre-40S particles accumulated in rpl3[W255C] cells are competent for elongation ( Figures 4 and S4 ) . This was unexpected , since late-acting pre-40S synthesis factors are expected to block association with translation factors , 60S r-subunits and the mRNA [20] , [47] . This indicates that the block induced by L3[W255C] allows these factors to dissociate from the late pre-40S r-particles . Supporting this model , Nob1 , which should impair binding of translation initiation factors , was not detected in polysomal fractions of either wild-type or rpl3[W255C] cells ( [25] , Figure S6B ) . Consistent with this , pre-40S r-particles that are engaged in translation were unable to undergo 20S pre-rRNA processing . The accumulation of 20S pre-rRNA in rpl3[W255C] cells was partially suppressed by reduced translation ( Figure 5 ) , suggesting that the loss of Nob1 , and therefore loss of cleavage competence , from pre-40S particles might be stimulated by translation . In Dictyostelium discoideum immature r-particles efficiently enter polysomes and require active translation for final maturation [48] . In contrast , yeast 80S complexes formed during 40S r-subunit maturation are unable to initiate translation [25] and 20S pre-rRNA maturation is opposed by the engagement of the pre-ribosomal particles in protein synthesis . During late maturation of pre-60S r-particles , release of the nucleolar shuttling factor Tif6 is dependent on the GTPase Efl1/Ria1 , which is also homologous to eEF2 [49] , [50] and apparently binds to the same sites as eEF2 in 60S r-subunits [51] . Tif6 prevents the association between 40S and 60S r-subunits [15] , [52] , [53] but mutations that trap Tif6 on cytoplasmic pre-60S r-particles , including the recently described P-site loop mutations of L10 [54] , do not lead to 20S pre-rRNA accumulation [50] , [55]–[59] ( see also Figure S8 ) . These results imply that 20S pre-rRNA processing is not exclusively performed in 80S-like particles or that Tif6 does not fully prevent association of pre-ribosomal subunits . Characterization of the L10 P-site loop mutants led to the conclusion that cytoplasmic maturation of pre-60S r-subunits also involves verification of the correct structure in the binding site of ribosome-stimulated GTPases ( [54] , reviewed in [60] ) . Our results unequivocally indicate that cytoplasmic maturation of pre-40S to translation competent 40S r-subunits also relies on the proper conformation of this binding site within pre-60S r-particles via Fun12 . The common binding site for the ribosome-dependent GTPases is a key structural feature for most steps in translation . Together the data indicate that the correct structure in this domain is required for the final maturation steps for both r-subunits prior to their entry into the translating pool .
All yeast strains used in this study are listed in Table S1 , plasmids in Table S2 and oligonucleotides in Table S3 . Unless otherwise indicated , experiments were conducted in the W303 [61] or BY4741 [62] genetic backgrounds . Strain CDK35-4A [63] was crossed to JDY318 [YCplac111-rpl3-W255C] , the resulting diploid was sporulated , tetrads dissected and the progeny examined . JDY945 is a segregant of the resulting diploid , which contains the cdc33::TRP1 and rpl3::HIS3MX6 alleles and harbours the YCplac33-cdc33–42 and the YCplac111-rpl3[W255C] plasmid . Strain JDY318 [YCplac111-rpl3-W255C] was crossed to DY121 , the resulting diploid was sporulated , tetrads dissected and the progeny examined . JDY1025 is a segregant of the resulting diploid , which contains the FUN12-TAP::TRP1 and rpl3::HIS3MX6 alleles and harbours the YCplac111-rpl3-W255C plasmid . Strain DY121 was a generous gift from R . H . Singer [42] . Growth and handling of yeast and standard media were done following established procedures [64] . Plasmids YCplac111-RPL3 , YCplac111-rpl3-Q371H ( also known as YCplac111-rpl3-101 ) , YCplac111-rpl3-K30E ( also known as YCplac111-rpl3-102 ) , YCplac22-RPL3 , YCplac22- rpl3-Q371H and YCplac22- rpl3-K30E have been previously described [29] . To generate YCplac111-rpl3-W25C and YCplac22-rpl3-W255C , site directed mutagenesis was performed on wild-type RPL3 cloned into YCplac111or YCplac22 , respectively [65] . All inserts were fully sequenced . Plasmid YCplac22-rps14A-R136A was generated by a similar strategy . Plasmids pRS316-RPL25-eGFP , pRS316-RPS2-eGFP and pRS314-DsRed-NOP1 ( generous gift from J . Bassler and E . Hurt ) have been previously described [66]–[68] . Plasmid pRS415-PTH-NOB1 has also been previously described [26] . Other plasmids used in this study are described in Table S2 . Cell extracts for polysome and r-subunit analyses were prepared and analysed as previously described [69] using an ISCO UA-6 system equipped to continuously monitor A254 . When needed , fractions of 0 . 5 ml were collected from the gradients; protein and RNA were extracted from the different fractions as exactly described [70] , and analysed as described below by northern or western blot analyses . RNA extraction , northern hybridisation and primer extension analyses were carried out according to standard procedures [71] , [72] . In all experiments , RNA was extracted from samples corresponding to 10 OD600 units of exponentially grown cells . Equal amounts of total RNA ( 5 µg ) were loaded on gels or used for primer extension reactions [72] . For primer extensions , Superscript III ( Invitrogen ) was used . The sequences of oligonucleotides used for northern hybridisation and primer extension analyses are listed in Table S3 . Phosphorimager analysis was performed with a FLA-5100 imaging system ( Fujifilm ) . To test pre-40S export , the wild-type strain and the rpl3[W255C] mutant were transformed with pRS316 plasmids harbouring the L25-eGFP [66] or S2-eGFP [67] reporters ( gifts from J . Bassler ) and inspected by fluorescence microscopy as previously described [12] , [73] . To examine the localization of the 20S pre-rRNA , fluorescence in situ hybridisation ( FISH ) was carried out as previously described [34] , [74] , using a Cy3-labelled ITS1-specific probe ( see Table S3 ) . The 20S pre-rRNA in vitro cleavage assays were performed with pre-ribosomal particles purified via N-terminally PTH-tagged Nob1 as previously described [26] . Briefly , pre-ribosomal particles were immunoprecipitated using immunoglobulin G ( IgG ) -Sepharose beads . Nucleotides were added to a final concentration of 1 mM . Reactions were incubated at 20°C for 0 , 2 , 5 , 10 and 30 min; after these incubation times , RNA was extracted as previously described [75] and analysed by primer extension , as described above , using oligonucleotide ITS1RT . Extracts from wild-type or rpl3[W255C] cells expressing TAP-tagged Fun12 were immunoprecipitated using IgG-Sepharose beads as previously described [75] . RNA was recovered from the beads and total cell extracts with phenol-chloroform exactly as previously described [75] and analysed by Northern blotting as described above . | Recent progress has provided us with detailed knowledge of the structure and function of eukaryotic ribosomes . However , our understanding of the intricate processes of pre-ribosome assembly and the transition to translation-competent ribosomal subunits remains incomplete . The early and intermediate steps of ribosome assembly occur successively in the nucleolus and nucleoplasm . The pre-ribosomal subunits are then exported to the cytoplasm where final maturation steps , notably including D site cleavage of the 20S pre-rRNA to mature 18S rRNA , confer subunit joining and translation competence . Recent evidence indicates that pre-40S subunits are subject to a quality control step involving the GTP-dependent translation initiation factor eIF5B/Fun12 , in the context of 80S-like ribosomes . Here , we demonstrate the involvement of 60S subunits in promoting 20S pre-rRNA cleavage . In particular , we show that a specific point mutation in the 60S subunit ribosomal protein L3 ( rpl3[W255C] ) leads to the accumulation of pre-40S particles that contain the 20S pre-rRNA but are translation-competent . Notably , this mutation prevents the stimulation of the GTPase activity of eIF5B/Fun12 , which is also required for site D cleavage . We conclude that L3 plays an important role in regulating the function of eIF5B/Fun12 during 3′ end processing of 18S rRNA at site D , in the context of 80S ribosomes that have not yet engaged in translation . | [
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] | 2014 | Final Pre-40S Maturation Depends on the Functional Integrity of the 60S Subunit Ribosomal Protein L3 |
Chronic lung infections in cystic fibrosis ( CF ) patients are composed of complex microbial communities that incite persistent inflammation and airway damage . Despite the high density of bacteria that colonize the lower airways , nutrient sources that sustain bacterial growth in vivo , and how those nutrients are derived , are not well characterized . In this study , we examined the possibility that mucins serve as an important carbon reservoir for the CF lung microbiota . While Pseudomonas aeruginosa was unable to efficiently utilize mucins in isolation , we found that anaerobic , mucin-fermenting bacteria could stimulate the robust growth of CF pathogens when provided intact mucins as a sole carbon source . 16S rRNA sequencing and enrichment culturing of sputum also identified that mucin-degrading anaerobes are ubiquitous in the airways of CF patients . The collective fermentative metabolism of these mucin-degrading communities in vitro generated amino acids and short chain fatty acids ( propionate and acetate ) during growth on mucin , and the same metabolites were also found in abundance within expectorated sputum . The significance of these findings was supported by in vivo P . aeruginosa gene expression , which revealed a heightened expression of genes required for the catabolism of propionate . Given that propionate is exclusively derived from bacterial fermentation , these data provide evidence for an important role of mucin fermenting bacteria in the carbon flux of the lower airways . More specifically , microorganisms typically defined as commensals may contribute to airway disease by degrading mucins , in turn providing nutrients for pathogens otherwise unable to efficiently obtain carbon in the lung .
Mutations in the gene encoding the cystic fibrosis transmembrane conductance regulator ( CFTR ) protein cause an imbalance of ion transport that leads to mucus hyperviscosity and impaired mucociliary clearance [1] . Within the airways , prolonged residence time of mucus provides a stagnant nidus for chronic bacterial infections–the predominant cause of mortality in CF patients [2] . Traditionally , culture-based studies have focused on a small number of taxa associated with CF lung disease ( e . g . Pseudomonas aeruginosa , Staphylococcus aureus ) , however , culture-independent surveys of the CF lung microbiome have revealed a far more complex bacterial community than previously appreciated [3–5] . While the temporal dynamics of these communities and their association with disease states have been studied in detail , the in vivo host environment , and microbial metabolism therein , is relatively understudied . For example , the means by which CF pathogens obtain sufficient energy for growth is not known . Bacterial numbers within the CF lung can reach 108−109 cells gm-1 of sputum [6] , which are comparable to densities found within the distal colon [7] . However , unlike the gut where dietary sources provide a constant influx of nutrients , carbon within the airways must be predominately host-derived . The respiratory tract contains a number of host compounds that can be used by microbes as nutrient sources , including immunoglobulins , cytokines , defensins and lactoferrin [8 , 9] , yet these are unlikely to be present at concentrations to support the dense microbiota of the CF airways [10–13] . Additionally , studies of CF sputum from adult patients have shown an abundance of small molecules that can support the growth of pathogens in vitro , including sugars , fatty acids , phospholipids , and amino acids [14–17] . However , the mechanism by which these compounds reach high abundance in airway mucus remains poorly defined . The accumulation of mucus secretions in the CF airways represents an abundant nutrient source . The major macromolecular constituents of mucus , mucins , are a large reservoir of both carbon and nitrogen , and have been measured at concentrations of up to 10 g L-1 in sputum [18] . Mucins are high molecular weight ( 2–20 x 105 Da ) glycoproteins composed of an amino acid backbone with O-linked oligosaccharide side chains that form 50–90% of the molecular mass [19] . Carboxyl and sulfate groups decorate their terminal sugars conferring a net negative charge , while terminal cysteine-rich domains form disulfide bonds with neighboring polymers , forming a highly cross-linked gel-like structure that is resistant to rapid bacterial degradation [20] . Despite their recalcitrance , mucins are a main nutrient source for niche-specific microbiota of the gut and oral cavity . For example , oral streptococci produce a variety of glycolytic and proteolytic enzymes that liberate bioavailable carbohydrates from salivary glycoproteins [21] . Few single species are known that can completely degrade mucins when grown in monoculture [22] , though specific consortia of oral bacteria have been shown to co-operatively degrade both the polysaccharide and peptide structures of salivary mucins [21 , 23] . In turn , these primary degraders are thought to modify the nutritional landscape of the oral cavity and stimulate the growth of secondary colonizers [24] . Similar interactions between commensal gut microbiota and the mucosal layer of the large intestine are well known [25] . By contrast , very little is known about the degradation of airway mucins by opportunistic pathogens and their role as a nutrient source in vivo [26] . Here , we investigated the role of mucins in the carbon flux of the CF airways and characterized their potential to stimulate pathogen growth . Our results demonstrate that P . aeruginosa uses mucins inefficiently in monoculture . This lack of growth raised the question: can other members of the CF microbiota degrade mucins and alter the nutritional reservoir available for pathogens ? We subsequently found that co-culture of pathogens with an anaerobic bacterial consortium composed of taxa commonly found in the lower airways [3 , 5 , 27 , 28] can facilitate robust pathogen growth using mucins as a sole carbon source . We also confirmed that fermentation-derived metabolites are abundant within expectorated CF patient sputum , consistent with previous studies [14 , 29] . Finally , we found that genes required for the catabolism of mucin fermentation byproducts are highly expressed by P . aeruginosa in vivo . Taken together , these data support a central ecological role for commensal anaerobes in the nutritional dynamics of the lower airways and the progression of CF lung disease .
We first wanted to determine if mucins alone could sustain the growth of P . aeruginosa . To do so , we assayed strain PA14 for growth in a defined minimal medium containing intact mucins from porcine gastric mucin ( PGM ) as the sole carbon source ( Fig 1A ) . PGM was first dialyzed and filtered to remove impurities and small metabolites that could potentially support growth ( see Methods ) . Interestingly , 15g L-1 of purified mucins ( sugar equivalent of ~65mM glucose assuming 80% sugar by weight ) only resulted in a moderate OD600 gain of 0 . 1 after 24 h . By contrast , PA14 grew to 0 . 65 OD on glucose ( 13mM ) alone , which underscores the inability of PA14 to efficiently break down and utilize PGM . Recognizing that PGM and human respiratory mucins ( MUC5AC and MUC5B ) are structurally diverse [30] , we also assayed Pseudomonas growth in a minimal medium containing purified MUC5B as the sole carbon source ( S1 Fig ) . PA14 reached a two-fold lower density when utilizing MUC5B relative to PGM , suggesting that P . aeruginosa PA14 cannot efficiently utilize complex mucin glycoproteins , including the most abundant mucin of the lower airway . Given that PA14 was isolated from a burn wound , we then reasoned that P . aeruginosa clinical isolates derived from a mucin-rich sputum environment would have enhanced ability to degrade and utilize mucins as a growth substrate . To test this , clinical isolates derived from CF patients at various stages of disease were grown in minimal mucin medium . Growth yield was assayed long past the onset of stationary phase ( 48h ) to account for slow growth phenotypes . Under these conditions , each isolate achieved a moderate density on PGM , comparable to PA14 ( final OD600 between 0 . 06 and 0 . 19 ) ( Fig 1B ) . Growth on mucin was also compared to growth with glucose alone , in addition to growth with a complete amino acid supplement to account for auxotrophy , a common trait among CF lung isolates [31] . Indeed , isolates JMF2 , JMF3 , and JMF5 grew poorly on glucose , suggesting auxotrophies that were corrected by the supplement . The ability of these isolates to grow on glucose supplemented with amino acids to a greater extent than the more nutrient-dense mucin medium suggests that the lack of robust growth on PGM was not due to slow-growth phenotypes . Rather , the fact that each isolate grew when sufficient carbon was made available to them demonstrates that P . aeruginosa has a general inability to efficiently utilize complex mucin glycoproteins in monoculture . The inefficiency of P . aeruginosa to use mucins as a growth substrate motivated us to consider recent culture-dependent and culture-independent studies of CF microbiota for insights into the carbon flux of the airways . Notably , obligately anaerobic taxa have gained recent attention for their abundance in expectorated sputum , bronchoalveolar lavage fluid and explanted lungs [5 , 27 , 28 , 32–34] . A role for these organisms in CF disease has not yet been established; however , some have been characterized for their ability to degrade and ferment salivary mucins in the oral cavity [21 , 23 , 35] . Based on these observations , we hypothesized that oral anaerobes , once aspirated into the lower airways , could alter the nutrient pool by degrading respiratory mucins . More specifically , we predicted that the degradation and fermentation of mucin glycoproteins would liberate sugars , amino acids and short chain fatty acids ( SCFAs ) , all of which are abundant components of CF sputum that are readily utilizable by P . aeruginosa [36] . To test whether fermentative bacteria are able to generate metabolites from mucin that could simultaneously stimulate CF pathogen growth , a saliva-derived bacterial community was first enriched on PGM ( S2 Fig ) . This enrichment culture was then used to inoculate an anaerobic minimal mucin medium supplemented with 1 . 0% agar to mimic a high-viscosity sputum gel [37] ( Fig 2A ) . Once the lower agar phase containing the mucin-enriched bacterial community had solidified , PA14 was suspended in buffered 0 . 7% agar medium without mucin ( i . e . no carbon source ) and was placed in the upper portion of the tube . This experimental setup a ) establishes an oxygen gradient allowing anaerobes to grow , and b ) restricts the movement of microbes but allows metabolites to freely diffuse . Under these conditions , P . aeruginosa would be expected to achieve a higher cell density if provided with diffusible growth substrates from the lower phase . Co-culture growth was monitored over a 72h period . After 24h , turbidity was noticeable in the lower phase and a diffusible blue-green pigment ( pyocyanin ) characteristic of P . aeruginosa growth was observed throughout the co-culture tube ( Fig 2B ) . By contrast , no observable pigment was produced in the absence of oral anaerobes . Colony counts of the upper phase revealed that P . aeruginosa reached its maximum density after 48h of co-culture ( Fig 2C ) , and achieved an order of magnitude ( 10X ) increase ( p = 0 . 007 ) in cell density relative to the tubes in which oral anaerobes were omitted . These data demonstrate that while PA14 can achieve a moderate density using PGM as a sole growth substrate ( consistent with Fig 1A ) , its growth and production of a known virulence factor is significantly enhanced via mucin breakdown and cross-feeding by oral-associated anaerobes . We then tested the growth of several P . aeruginosa clinical isolates in addition to the CF-associated pathogens Achromobacter xylosoxidans , Burkholderia cenocepecia , Stenotrophomonas maltophilia and Staphylococcus aureus using the agar co-culture model ( Fig 2D and 2E ) . For each bacterium , a notable increase in growth over the inoculum was observed in the presence of mucin fermenters after 48h . With the exception of JMF3 , the final cell density was significantly higher for each co-culture relative to monoculture tubes in which anaerobes were omitted . Collectively , these data support the hypothesis that oral-derived microbiota can serve as primary mucin degrading organisms , in turn liberating metabolites that stimulate the growth of P . aeruginosa and other CF lung pathogens . To determine if there exists a fraction of the CF lung microbiota that has the ability to degrade and ferment mucin glycoproteins , we then performed mucin enrichment experiments on expectorated sputum from 14 stable , non-exacerbating CF patients . To do so , a small fraction of sputum was used to inoculate an anaerobic culture medium supplemented with PGM as the sole carbon and nitrogen source . Following anaerobic growth , genomic DNA was isolated from the initial sputum sample and the corresponding enrichment culture followed by bacterial 16S rRNA gene sequencing to identify enriched taxa . If taxa from sputum become enriched in a medium with mucin as the sole carbon source , it would demonstrate the presence of mucin-degradation capacity in the lower airway environment . As expected , sputum microbiota ( prior to enrichment ) was highly variable between patients ( Fig 3A ) , and Pseudomonas made up the highest percentage of sequence reads with a per-patient average of 31 . 3% across the cohort ( Fig 3B ) . Notably , taxa previously characterized for their mucin-degrading activity ( Prevotella , Veillonella , Streptococcus and Fusobacterium ) also made up 35 . 1% of the population ( 11 . 4% , 9 . 7% , 9 . 9% and 4 . 1% of normalized sequence reads , respectively ) . Post-enrichment , sputum-derived communities were predominated by fermentative organisms commonly associated with both the oral cavity and lower airways ( Fig 3A and 3B ) . On average , enrichment communities were composed of 66% of taxa known to have salivary mucin degradation ability ( 27 . 4% Prevotella , 19 . 2% Veillonella , 10 . 7% Streptococcus , 8 . 4% Fusobacterium ) with all other genera present at 4% or below ( Fig 3B ) . Lachnoanaerobaculum and Prevotella were significantly enriched while Neisseria , Staphylococcus , and Pseudomonas were selected against ( p<0 . 05 ) . The relative abundance of mucin-fermenting taxa in the initial sputum samples and their ability to grow on mucin in vitro suggests a suitable niche space exists in the CF lung for mucin-fermenting anaerobes . We then tested representative isolates of the four most abundant mucin-enriched species for their ability to cross-feed P . aeruginosa PA14 ( Fig 3C ) . Using the co-culture model , mucin degradation by P . melaninogenica and V . parvula alone did not stimulate an increase in P . aeruginosa growth relative to anaerobe-free controls . By contrast , F . nucleatum and S . parasanguis both supported a significant increase in PA14 growth; however , final PA14 cell density achieved in the presence of any individual mucin-fermenter was significantly less ( p<0 . 0001 ) than when all four mucin-degraders ( P . m . , V . p . , F . n . and S . p . ) were added at an equal density . Notably , the PA14 cell density achieved with this defined , four-species anaerobic consortium was comparable to growth achieved using the undefined enrichment culture ( S2 Fig ) used in Fig 2 . These data demonstrate that while P . aeruginosa growth can be stimulated by select sputum-enriched anaerobes individually , the collective activity of a mucin-degrading consortium associated with the lower airways results in a significantly higher growth yield . To study the cross-feeding ability of mucin fermenting bacteria in further detail , we then characterized the metabolites that were generated during sputum enrichment . Fermentative anaerobes are known to produce mixed acid metabolites so we quantified a number of organic acids via high performance liquid chromatography ( acetate , butyrate , citrate , formate , isobutyrate , isovalerate , ketobutyrate , ketoisovalerate , lactate , 2-methylbutyrate , propionate , succinate and valerate ) , and quantified amino acid production using gas chromatography . Enrichment cultures generated detectable levels of only three short-chain fatty acids ( SCFAs ) measured: high amounts of acetate ( 30 . 2 +/- 9 . 7 mM ) and propionate ( 15 . 4 +/- 3 . 8 mM ) were found in each sample , while only one enrichment sample containing an abundance of Streptococcus sp . ( #7025 , see Fig 3A ) produced a detectable concentration of lactate ( 7 . 8 mM ) ( Fig 4A ) . No other SCFAs assayed were detectable in the mucin-enrichment supernatants . Not surprisingly , free amino acids were also present in each sample ( 1 . 37 +/- 1 . 32 mM total ) ( Fig 4B ) , most likely due to their liberation from the mucin polypeptide backbone . The abundance of amino acids correlates well with previous studies of sputum composition where they were found to be present in appreciable quantities [15] . Altogether , these data demonstrate that acetate , propionate , and amino acids are the major byproducts of mucin fermentation by sputum-derived anaerobes in vitro , suggesting that they may be carbon sources that are bioavailable to pathogens in vivo . To assess the contributions of propionate and acetate to P . aeruginosa growth in our in vitro cross-feeding model , we generated mutants lacking the genes encoding AcsA ( acetyl-coA synthetase ) and PrpB ( methylisocitrate lyase ) that are required for the catabolism of acetate and propionate , respectively . We also generated a double mutant ( ΔprpBΔacsA ) that was defective in both pathways . Each mutant grew normally on glucose , yet demonstrated a predictable growth limitation when its cognate substrate was provided as the sole carbon source ( S3 Fig ) . Mutants were then tested for their ability to grow in the agar co-culture model with the oral-derived anaerobic consortium ( S2 Fig ) provided as the mucin-degrading inoculum . ΔacsA , ΔprpB , and ΔacsAprpB demonstrated significant growth defects relative to PA14 ( p<0 . 05 ) when grown in co-culture with mucin fermenters ( Fig 5 ) . These data demonstrate that P . aeruginosa growth is partially dependent on acetate and propionate catabolism in a model bacterial community characteristic of the CF lower airways . Finally , to provide evidence of fermentative activity in vivo , we used two complementary techniques to study bacterial metabolism within expectorated sputum: mass spectrometry and quantitative reverse transcription PCR ( qRTPCR ) . First , using gas chromatography mass spectrometry ( GC-MS ) , acetate and propionate were quantified in paired saliva/sputum samples collected from 7 stable CF patients . Given the presence of fermenting taxa and SCFA previously identified in saliva [38] , an oral rinse was first performed prior to sample collection to reduce the residual metabolite background from the mouth ( see Methods ) . SCFAs were found at millimolar concentrations ( 5 . 9 +/- 1 . 8 mM and 48 . 2 +/- 47 . 2 μM , for acetate and propionate , respectively ) in all sputum samples . Despite our washing effort , the saliva sample also contained detectable levels of both acetate and propionate . Acetate concentrations were significantly higher in sputum relative to saliva ( 5 . 9 versus 2 . 4 mM , p = 0 . 004 ) ( Fig 6A ) . Propionate , on the other hand , showed no significant difference ( p = 0 . 89 ) between sample pairs ( Fig 6B ) . Thus , we cannot rule out propionate contamination from the oral cavity . However , given that the propionate concentration in saliva was not diluted compared to sputum , it is reasonable to approximate that sputum contains a comparable concentration of propionate to the saliva samples . Our results are supported by recent reports of acetate and propionate in CF bronchoalveolar lavage fluid [14 , 29] . The ratio of propionate to acetate ( 1:100 ) in our samples was unexpected given the much higher ratio ( 1:2 ) generated during in vitro mucin fermentation . This disparity may suggest that propionate is either produced at low levels in vivo , or that propionate , over acetate , is preferentially consumed by CF microbiota in a cross-feeding relationship . As a complement to our GC-MS measurements , we then used qRTPCR to assess whether Pseudomonas senses and responds to acetate and/or propionate within the airways . As a proxy of the use of these mucin-derived metabolites by P . aeruginosa , we targeted the expression of both acsA and prpD in sputum relative to their expression levels under controlled laboratory conditions . In vitro , acsA and prpD were differentially expressed by both PA14 and JMF5 in the presence of acetate ( 4 . 0-fold higher , p = 0 . 01 ) and propionate ( 10 . 8-fold , p<0 . 001 ) , respectively , relative to growth on glucose alone ( Fig 7 ) . When compared to in vitro cultures , analysis of sputum revealed that prpD ( 5 . 4-fold , p = 0 . 005 ) but not acsA ( no change , p = 0 . 73 ) was highly expressed . Expression of prpD was highly variable , however this was not unexpected given the variable nature of patient samples . These qRTPCR data are consistent with the active catabolism of propionate by Pseudomonas in vivo , and may account for the disparity seen in propionate:acetate ratios between sputum and mucin enrichment cultures . If SCFAs were simultaneously produced and consumed by the airway bacterial community , we would expect the concentration of these metabolites to remain low , and genes required for their catabolism to be highly expressed . Though we cannot rule out the possibility of low rates of propionate production in vivo , the expression of prpD by Pseudomonas within sputum is a reliable biomarker of the presence of mixed-acid fermentation byproducts . It is noteworthy that acetate catabolism via AcsA is important to PA14 yields during cross-feeding in vitro , yet the qRTPCR data suggest that acsA is minimally expressed in vivo . This discrepancy may be due to strain-specific differences in PA14 compared to clinical isolates , or may be influenced by unknown environmental cues in vivo . Collectively , data presented here demonstrate the presence of fermentation metabolites and evidence consistent with their catabolism in the airways of CF patients . These results , coupled with previous reports of SCFA in bronchoalveolar lavage fluid [14 , 29] and degraded mucins in CF sputum [18 , 39] , provide compelling evidence that anaerobic organisms can contribute to CF lung disease by degrading mucins and consequently providing utilizable substrates for opportunistic airway pathogens .
In this study , we investigated the nutritional role of mucins in the growth of P . aeruginosa in the CF airways . While Pseudomonas was found to inefficiently utilize mucins as a carbon source on their own , we determined that mucin fermentation by oral anaerobes can stimulate the growth ( 10X ) of P . aeruginosa and other opportunistic CF pathogens . Moreover , we revealed that in vitro mucin fermentation generated high concentrations of SCFAs and amino acids , which were also abundant and bioavailable for P . aeruginosa within patient sputum . Together , these results suggest that the high levels of utilizable metabolites present in sputum reported previously [14 , 15 , 29] may be derived from bacterial mucin degradation . In this context , fermentative anaerobes aspirated from the oral cavity that become established in the lower airways may play a central role in the progression of CF lung disease . Expectorated sputum and many of its specific constituents–lipids [15 , 17] , amino acids [16] , and modified sugars [40] , for example–are known to support bacterial growth in vitro and have been studied in detail . Yet , how the majority of these compounds are made available within the CF airways has not been defined . Mucins represent an abundant source of both amino acids and sugars , and play a key role in shaping the microbial community structure of the gastrointestinal tract . However , the process of mucin degradation , and its potential contribution to airway disease has not been addressed in detail . Previous studies have shown that mucins can support the carbon demands of P . aeruginosa in vitro [41 , 42]; however , these studies included autoclaved preparations of commercial porcine gastric mucin ( PGM ) that contain low molecular mass compounds that are readily utilized . In fact , when PGM preparations were filtered and dialyzed in our study ( leaving only large , intact glycoproteins ) appreciable growth of P . aeruginosa isolates was not observed . The near ubiquitous presence of mucin-fermenting anaerobes in sputum [5 , 27 , 28 , this study] , coupled with numerous studies demonstrating that the respiratory mucins MUC5B and MUC5AC are degraded in CF patients compared to healthy controls [18 , 39] supports the idea that bacterial mucin degradation is commonplace within the CF airways . Streptococcus sp . , for example , which were consistently abundant in mucin-enriched sputum cultures , have been extensively characterized for their ability to degrade salivary mucins [21] . By doing so , oral streptococci modify the nutritional landscape of the oral cavity and stimulate the growth of secondary colonizers [24] . Here we demonstrate that by degrading mucins , commensal anaerobes can also stimulate the growth of opportunistic pathogens found within the respiratory tract , supporting an ecological role for mucin-fermenting anaerobes in the development of CF airway infections . In vitro , degradation of glycan sugars and the polypeptide backbone of mucin by sputum-derived anaerobes generated an abundance of SCFAs and amino acids . Consistent with recent studies [14 , 29] , SCFAs were also found in CF patient sputum . Because SCFAs serve as a reliable biomarker of fermentative metabolism [43] , the universal presence of SCFAs across our patient cohort provides strong supporting evidence for the existence of fermentation within the CF airways . Specifically , our data demonstrate that the fermentation of mucins generates the same metabolites that have been shown to support growth of Pseudomonas in sputum [15] . Moreover , the expression of prpD in sputum suggests that P . aeruginosa is both sensing and utilizing propionate in vivo; however , the significance of propionate catabolism in disease is not known . While propionate can support growth of P . aeruginosa , it is also a potent microbial inhibitor [44] . As such , we do not yet know if the in vivo degradation of propionate helps to satisfy the carbon requirements of P . aeruginosa or whether it is being selectively degraded for detoxification purposes . Altogether , our data point to a compelling model for the role of oral anaerobes in the development of CF lung disease ( Fig 8 ) . In this model , opportunistic pathogens that cannot degrade mucins ( e . g . P . aeruginosa , S . aureus ) do not become established in the lower airways until mucin-fermenting bacteria have colonized . In healthy subjects , anaerobes that are routinely aspirated into the lower airways encounter functional host defenses and are effectively cleared . In CF , however , impaired mucociliary clearance and defective immunological responses [2] increase the likelihood of oral anaerobe colonization ( Fig 8A and 8B ) . Their increased residence time allows anaerobes to degrade respiratory mucins and condition the lung environment into a niche that is suitable for pathogens to thrive ( Fig 8C ) . Several lines of clinical evidence exist in support of our proposed model: ( i ) pediatric patients often have asymptomatic primary colonization by oral anaerobes [45 , 46] prior to the establishment of chronic P . aeruginosa infections , ( ii ) routine administration of broad-spectrum antibiotics in the absence of respiratory infection symptoms is an effective therapy to delay the onset of colonization by P . aeruginosa and reduce the frequency of acute exacerbations [47 , 48] , and ( iii ) the in vitro antibiotic susceptibility of lung pathogens does not always correlate with clinical outcomes [49] . In the latter instance , we propose that antibiotics do not solely target the pathogen , but rather disrupt the complex metabolic interactions that supply them with substrates for growth and stimulate their pathogenicity . While this work suggests a role for mucin fermenters in the progression to pathogen colonization , it also raises a number of questions . Most importantly , it does not address the role of oral anaerobes or bacterial nutrient acquisition in late stages of CF disease ( Fig 8D ) . In chronic airway infections , bacterial diversity often declines and lung microbiota becomes predominated by P . aeruginosa [50 , 51] . Therefore , it is probable that P . aeruginosa does not rely upon mucin fermentation in late stages , but rather contributions from the host inflammatory response . It is known that chronic airway infections can lead to a ‘leaky’ lung epithelium that allows bulk plasma , with an abundance of bioavailable metabolites , to reach the epithelial surface [52] . Additionally , persistent P . aeruginosa infections incite a neutrophil-dominant inflammatory response that is associated with increased concentrations of nutrients and proteases in the airway milieu . Human neutrophil elastase , for example , is capable of cleaving mucins glycoproteins into free amino acids , and has been implicated in the progression of lung disease [39] . Given these other potential nutritional sources , it is probable that P . aeruginosa uses multiple carbon sources in vivo as infections progress , and we suspect that pathogens may become independent from mucin fermenters in late stages of CF lung disease . This study underscores the importance of identifying the underlying microbial ecological dynamics that give rise to CF lung disease progression . In particular , our data warrant further studies of targeted therapies towards fermentative organisms and their metabolisms that may contribute to the establishment and progression of chronic airway disease . In a broader context , the presence of oral anaerobes in other , mucus-rich disease environments where both oral anaerobes and P . aeruginosa are major players–chronic obstructive pulmonary disease , sinusitis , and ventilator-associated pneumonias–suggests that mucin fermentation and metabolic cross-feeding may be a more widespread phenomenon . We are currently investigating this interspecies dynamic in a range of infectious contexts .
Bacterial strains and primers are shown in S1 Table . P . aeruginosa PA14 and Staphylococcus aureus MN8 were obtained from D . K . Newman ( California Institute of Technology ) . S . parasanguis ATCC 15912 was obtained from M . C . Herzberg ( University of Minnesota ) . F . nucleatum subsp . nucleatum ATCC 25586 , P . melaninogenica ATCC 25845 , and V . parvula ATCC 10790 were obtained from Microbiologics ( St . Cloud , MN ) . Clinical strains of P . aeruginosa , B . cenocepecia , S . maltophilia , and A . xylosoxidans [53] were isolated from patients enrolled in this study . Aerobes were routinely cultured in Luria Bertani medium or a minimal mucin medium containing 60mM KH2PO4 ( pH 7 . 4 ) , 90mM NaCl , 1mM MgSO4 , 15 g L-1 porcine gastric mucin ( PGM; Sigma ) , and a trace minerals mix described elsewhere [54] . During preparation , PGM was first autoclaved , dialyzed using a 13 kDa molecular weight cutoff membrane , clarified by centrifugation , followed by passage through a 0 . 45 μm Millipore syringe filter to sterilize and isolate soluble intact glycoproteins . MUC5B was used in place of PGM where specified , though was used sparingly due to its purification difficulty [55] . Glucose ( 13mM ) , NH4Cl ( 60mM ) , acetate ( 20mM ) and propionate ( 20mM ) were supplemented where specified . MEM essential and non-essential amino acid mixes ( Sigma ) were added at a final concentration of 0 . 5X the manufacturer suggested concentration . S . parasanguis , F . nucleatum , P . melaninogenica , and V . parvula were cultured in Brain-Heart Infusion media supplemented with hemin ( 0 . 25 g L-1 ) , vitamin K ( 0 . 025 g L-1 ) and laked sheep’s blood ( 5% vol/vol ) ( BHI-HKB ) . Growth was monitored in 96-well plates ( Corning ) in 250 μL volumes using a BioTek Synergy H1 plate reader . For enrichment growth , approximately 100 μL of sputum was then used to inoculate minimal mucin medium under anoxia ( 95% N2 , 5% CO2 ) and the remainder was frozen at -80°C . Following 48h of incubation at 37°C , 100 μL of culture was used to inoculate a second anaerobic culture tube and allowed to grow for 48h at 37°C . Genomic DNA was isolated from both the initial sputum sample and enrichment cultures , and bacterial community composition was determined using 16S rRNA gene sequencing . Forty-eight adult participants with CF were recruited at the University of Minnesota Adult CF Center . Inclusion criteria were a positive diagnosis of CF and ability to expectorate sputum . For enrichment cultures , sputum was expectorated following an oral rinse into 50mL conical tubes , placed on ice , and processed within three hours . Sputum used for qRTPCR analysis was placed in RNALater ( Sigma ) immediately following expectoration , and stored at -80°C . For metabolite analysis ( n = 7 ) , subjects first performed an oral rinse , followed by paired saliva and sputum collection and immediate storage at -80°C . To obtain clinical isolates , sputum aliquots were cultured on Pseudomonas Isolation Agar ( Oxoid ) for 72 hours at 37°C . Colonies were screened using PCR , sequenced to confirm identity , and stored in 15% glycerol at -80°C . Sputum and enrichment cultures were thawed to room temperature , and 500 μL of each sample was used for genomic DNA extraction using the PowerSoil DNA isolation kit ( MoBio , Carlsbad , CA ) . Purified DNA was submitted to the University of Minnesota Genomics Center ( UMGC ) for 16S library preparation using a two-step PCR protocol described previously [56] . A defined mock community was also submitted for sequencing , as were water and reagent controls that did not pass quality control step due to 16S rRNA gene content below detection thresholds . Raw sequence reads were obtained from UMGC and analyzed using a QIIME [57] pipeline developed by the UMGC . The average number of reads per sample after filtering and taxonomic assignment was 2 . 2 x 105 , with the minimum and maximum reads per sample of 5 . 6 x 103 and 5 . 1 x 105 , respectively . Read pairs were stitched together and 16S amplicon primers were removed using PandaSeq ( version 2 . 7 ) [58] . Fastq files were merged and sequence IDs converted to QIIME format using a custom perl script . Chimeric sequences were detected using the QIIME ( version 1 . 8 . 0 ) script identify_chimeric_seq . py function , using the usearch61 method . Open reference OTU picking was performed using the pick_open_reference_otus . py script , using the usearch61 method and the Greengenes 13_8 16S rRNA reference database [59] clustered at 97% similarity . MetaStats was used to detect differentially abundant features of the mucin-enriched bacterial community [60] . Mucin fermentation cultures ( diluted 1/100 ) were used to inoculate 2 mL of mucin ( 15g L-1 ) minimal medium in molten 1 . 0% agar at 50°C in a glass culture tube under anoxic conditions ( Fig 2A ) . Mucin fermentation cultures contained one of the following: ( 1 ) individual anaerobic species ( V . parvula , F . nucleatum , P . melaninogenica , or S . parasanguis ) grown from single colony picks , grown overnight in anaerobic BHI-HKB broth and washed twice with PBS; ( 2 ) a defined four-species anaerobic consortium ( V . parvula , F . nucleatum , P . melaninogenica , and S . parasanguis together ) prepared as described above; or ( 3 ) a saliva-derived mucin-fermenting bacterial community ( S2 Fig ) revived from glycerol freezer stocks and passaged twice in mucin minimal medium . Upon solidification of the mucin-fermenting fraction , an additional 1 mL of molten minimal medium agar ( without mucin ) was inoculated with a 1/1000 dilution of an overnight culture of P . aeruginosa ( or other strains where specified ) . Inoculum sizes are shown in S2 Table . Samples were then poured over the mucin fermenting community fraction and allowed to solidify . Tubes without mucin-fermenters were used as negative controls . After solidification , co-cultures were placed at 37°C for 48 h or other specified time points . Agar plugs were then removed from the upper phase and homogenized by pipetting in 10 mL of phosphate buffered saline . Colony forming units per tube were determined by serial dilution and plating on LB agar . Unmarked deletions were generated for the genes prpB ( PA14_53940 ) and acsA ( PA14_52800 ) in the PA14 wild-type background . Flanking regions ( ~1kb in length ) containing the first and last codons of for acsA and prpB were generated using primers listed in S1 Table . The flanking regions and the deletion vector pSMV8 [61] ( linearized by digestion with XhoI and SpeI ) were assembled by Gibson assembly [62] . The resulting plasmid was transformed into E . coli WM3064 [61] and mobilized into PA14 by conjugation . Single recombinants were selected on LB agar containing 50 μg mL-1 gentamicin . Double recombinants were selected for on LB agar containing 6% sucrose . Potential prpB and acsA mutants , or prpBacsA double mutants were identified by PCR , and markerless deletions were confirmed by sequencing . Targeted quantification of short-chain fatty acids was performed via high performance liquid chromatography ( HPLC ) . The system consisted of a Shimadzu SCL-10A system controller , LC-10AT liquid chromatograph , SIL-10AF autoinjector , SPD-10A UV-Vis detector , and CTO-10A column oven . Separation of compounds was performed with an Aminex HPX-87H guard column and an HPX-87H cation-exchange column ( Bio-Rad [Hercules , CA] ) . The mobile phase consisted of 0 . 05 N H2SO4 , set at a flow rate of 0 . 5 mL min-1 . The column was maintained at 50°C and the injection volume was 50 μL . Amino acid and metabolite ( acetate and propionate ) quantification from enrichment supernatants were performed by Millis Scientific , Inc . ( Baltimore , MD ) using liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry ( GC-MS ) . Samples for amino acid quantification were spiked with 1 μL of uniformly labeled amino acids ( Cambridge Isotope Labs ) and derivatized using AccQ-Tag reagent ( Waters Corp . ) for 10 min at 50°C . A Waters Micromass Quatro LC-MS interfaced with a Waters Atlantis dC18 ( 3 μm 2 . 1x100 mm ) column was used . Reverse-phase LC was used for separation ( mobile phases A:10mM ammonium formate in 0 . 5% formic acid , B:methanol ) with a constant flow rate ( 0 . 2 mL min-1 ) and a column temperature of 40°C . Electrospray ionization was used to generate ions in the positive mode and multiple reaction monitoring was used to quantify amino acids . Samples ( ~100 μL ) for acetate and propionate quantification were first diluted ( 150 μL water ) , spiked with internal standards ( 10 μL of 1000ppm acetate [13C2] and 1000 ppm propionate [13C1] ) and acidified using 2 μL of 12N HCl . After equilibration at 60°C for 2h , carboxen/ polydimethylsiloxane solid phase microextraction ( SPME ) fiber was used to adsorb the headspace at 60°C for 30min . Acids were then desorbed into the gas chromatograph inlet for 2 min . A 30 m x 0 . 32 mm ID DB-624 column attached to a Thermo Electron Trace gas chromatograph with helium carrier gas ( 2 . 0 mL min-1 ) was used for separation of analytes . A Waters Micromass Quatro GC mass spectrometer was used for detection and quantification of target ions . Significance between sputum and saliva samples were determined by paired Student’s t-test . To quantify P . aeruginosa gene expression in vivo , sputum ( n = 17 ) was expectorated into RNAlater and immediately frozen to preserve the gene expression profile . Frozen sputum was thawed in TriZol ( Life Technologies ) , homogenized using ceramic beads and purified according to the manufacturer’s protocol . RNA was concentrated using the Clean & Concentrator kit ( Zymo ) and de-salted using Turbo DNA-free ( Life Technologies ) . Bacterial RNA was enriched ( only in sputum samples ) using the MicrobEnrich kit ( Life Technologies ) , and purity was confirmed using Qubit ( LifeTechnologies ) spectrophotometry . qRTPCR was performed as previously described [63] . Briefly , DNA was reverse transcribed from 1 μg of total RNA using the iScript cDNA synthesis kit ( BioRad ) . cDNA was then used a template for quantitative PCR on an iQ5 thermocycler ( BioRad ) using iTaq Universal SYBR Green Super Mix ( BioRad ) . Triplicate measurements were made on each sputum sample . For control cultures , P . aeruginosa was grown in 4-morpholinepropanesulfonic acid ( MOPS ) minimal medium to an OD600 of~0 . 6 supplemented with glucose ( 12mM ) , acetate ( 20mM ) , propionate ( 20mM ) , or acetate + propionate ( 20mM each ) where specified . After growth , cells were harvested by centrifugation , frozen at -80°C , and RNA was extracted as described above . Primer pairs are listed in S1 Table . For all primer sets , the following cycling parameters were used: 94°C for 3 min followed by 40 cycles of 94°C for 60s , 55°C for 45s , and 72°C for 60s . Primer efficiencies were tested for clpX ( 91 . 6% ) , acsA ( 91 . 6% ) and prpD ( 96 . 8% ) . Relative RNA values were calculated from the Ct values reported and the experimental primer efficiencies , and were normalized to the expression of clpX . clpX was compared to oprI values to ensure constitutive expression levels . Significance between treatments was determined by two-tailed unpaired Student’s t-test . 16S rRNA gene sequences generated as part of this study were deposited as fastq files in NCBI GenBank under BioProject accession number SRP067035 . These studies were approved by the Institutional Review Board at the University of Minnesota ( UMN IRB nos . 1401M47262 and 1404M49426 ) . All subjects ( adults ) provided informed written consent prior to sample collection . | Persistent CF lung infections are composed of hundreds of microbial taxa whose interactions contribute to respiratory failure . Despite their importance , the complex interplay between the lung microbiota and host environment is poorly understood . For example , the nutrients that sustain bacterial growth in vivo , and how those nutrients are derived , are not well characterized . We reveal that a subset of CF microbiota is capable of fermenting mucins for carbon and energy which , in-turn , can support the carbon demands of other respiratory pathogens in co-culture . Moreover , we show that metabolites consistent with mucin fermentation are abundant within airway secretions , highlighting a potential key role for fermentative metabolisms in CF lung disease . A thorough understanding of pathogen ecology in the CF airway and the nutritional dynamics that sustain their growth will have important implications for the design of new therapeutic strategies and the management of disease progression . | [
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... | 2016 | Evidence and Role for Bacterial Mucin Degradation in Cystic Fibrosis Airway Disease |
The diversity of life is one of the most striking aspects of our planet; hence knowing how many species inhabit Earth is among the most fundamental questions in science . Yet the answer to this question remains enigmatic , as efforts to sample the world's biodiversity to date have been limited and thus have precluded direct quantification of global species richness , and because indirect estimates rely on assumptions that have proven highly controversial . Here we show that the higher taxonomic classification of species ( i . e . , the assignment of species to phylum , class , order , family , and genus ) follows a consistent and predictable pattern from which the total number of species in a taxonomic group can be estimated . This approach was validated against well-known taxa , and when applied to all domains of life , it predicts ∼8 . 7 million ( ±1 . 3 million SE ) eukaryotic species globally , of which ∼2 . 2 million ( ±0 . 18 million SE ) are marine . In spite of 250 years of taxonomic classification and over 1 . 2 million species already catalogued in a central database , our results suggest that some 86% of existing species on Earth and 91% of species in the ocean still await description . Renewed interest in further exploration and taxonomy is required if this significant gap in our knowledge of life on Earth is to be closed .
Robert May [1] recently noted that if aliens visited our planet , one of their first questions would be , “How many distinct life forms—species—does your planet have ? ” He also pointed out that we would be “embarrassed” by the uncertainty in our answer . This narrative illustrates the fundamental nature of knowing how many species there are on Earth , and our limited progress with this research topic thus far [1]–[4] . Unfortunately , limited sampling of the world's biodiversity to date has prevented a direct quantification of the number of species on Earth , while indirect estimates remain uncertain due to the use of controversial approaches ( see detailed review of available methods , estimates , and limitations in Table 1 ) . Globally , our best approximation to the total number of species is based on the opinion of taxonomic experts , whose estimates range between 3 and 100 million species [1]; although these estimations likely represent the outer bounds of the total number of species , expert-opinion approaches have been questioned due to their limited empirical basis [5] and subjectivity [5]–[6] ( Table 1 ) . Other studies have used macroecological patterns and biodiversity ratios in novel ways to improve estimates of the total number of species ( Table 1 ) , but several of the underlying assumptions in these approaches have been the topic of sometimes heated controversy ( [3]–[17] , Table 1 ) ; moreover their overall predictions concern only specific groups , such as insects [9] , [18]–[19] , deep sea invertebrates [13] , large organisms [6]–[7] , [10] , animals [7] , fungi [20] , or plants [21] . With the exception of a few extensively studied taxa ( e . g . , birds [22] , fishes [23] ) , we are still remarkably uncertain as to how many species exist , highlighting a significant gap in our basic knowledge of life on Earth . Here we present a quantitative method to estimate the global number of species in all domains of life . We report that the number of higher taxa , which is much more completely known than the total number of species [24] , is strongly correlated to taxonomic rank [25] and that such a pattern allows the extrapolation of the global number of species for any kingdom of life ( Figures 1 and 2 ) . Higher taxonomy data have been previously used to quantify species richness within specific areas by relating the number of species to the number of genera or families at well-sampled locations , and then using the resulting regression model to estimate the number of species at other locations for which the number of families or genera are better known than species richness ( reviewed by Gaston & Williams [24] ) . This method , however , relies on extrapolation of patterns from relatively small areas to estimate the number of species in other locations ( i . e . , alpha diversity ) . Matching the spatial scale of this method to quantify the Earth's total number of species would require knowing the richness of replicated planets; not an option as far as we know , although May's aliens may disagree . Here we analyze higher taxonomic data using a different approach by assessing patterns across all taxonomic levels of major taxonomic groups . The existence of predictable patterns in the higher taxonomic classification of species allows prediction of the total number of species within taxonomic groups and may help to better constrain our estimates of global species richness .
We recognize a number of factors that can influence the interpretation and robustness of the estimates derived from the method described here . These are analyzed below .
Knowing the total number of species has been a question of great interest motivated in part by our collective curiosity about the diversity of life on Earth and in part by the need to provide a reference point for current and future losses of biodiversity . Unfortunately , incomplete sampling of the world's biodiversity combined with a lack of robust extrapolation approaches has yielded highly uncertain and controversial estimates of how many species there are on Earth . In this paper , we describe a new approach whose validation against existing inventories and explicit statistical nature adds greater robustness to the estimation of the number of species of given taxa . In general , the approach was reasonably robust to various caveats , and we hope that future improvements in data quality will further diminish problems with synonyms and incompleteness of data , and lead to even better ( and likely higher ) estimates of global species richness . Our current estimate of ∼8 . 7 million species narrows the range of 3 to 100 million species suggested by taxonomic experts [1] and it suggests that after 250 years of taxonomic classification only a small fraction of species on Earth ( ∼14% ) and in the ocean ( ∼9% ) have been indexed in a central database ( Table 2 ) . Closing this knowledge gap may still take a lot longer . Considering current rates of description of eukaryote species in the last 20 years ( i . e . , 6 , 200 species per year; ±811 SD; Figure 3F–3J ) , the average number of new species described per taxonomist's career ( i . e . , 24 . 8 species , [30] ) and the estimated average cost to describe animal species ( i . e . , US$48 , 500 per species [30] ) and assuming that these values remain constant and are general among taxonomic groups , describing Earth's remaining species may take as long as 1 , 200 years and would require 303 , 000 taxonomists at an approximated cost of US$364 billion . With extinction rates now exceeding natural background rates by a factor of 100 to 1 , 000 [31] , our results also suggest that this slow advance in the description of species will lead to species becoming extinct before we know they even existed . High rates of biodiversity loss provide an urgent incentive to increase our knowledge of Earth's remaining species . Previous studies have indicated that current catalogues of species are biased towards conspicuous species with large geographical ranges , body sizes , and abundances [4] , [32] . This suggests that the bulk of species that remain to be discovered are likely to be small-ranged and perhaps concentrated in hotspots and less explored areas such as the deep sea and soil; although their small body-size and cryptic nature suggest that many could be found literally in our own “backyards” ( after Hawksworth and Rossman [33] ) . Though remarkable efforts and progress have been made , a further closing of this knowledge gap will require a renewed interest in exploration and taxonomy by both researchers and funding agencies , and a continuing effort to catalogue existing biodiversity data in publicly available databases .
Calculations of the number of species on Earth were based on the classification of currently valid species from the Catalogue of Life ( www . sp2000 . org , [34] ) and the estimations for species in the ocean were based on The World's Register of Marine Species ( www . marinespecies . org , [35] ) . The latter database is largely contained within the former . These databases were screened for inconsistencies in the higher taxonomy including homonyms and the classification of taxa into multiple clades ( e . g . , ensuring that all diatom taxa were assigned to “Chromista” and not to “plants” ) . The Earth's prokaryotes were analyzed independently using the most recent classification available in the List of Prokaryotic Names with Standing in Nomenclature database ( http://www . bacterio . cict . fr ) . Additional information on the year of description of taxa was obtained from the Global Names Index database ( http://www . globalnames . org ) . We only used data to 2006 to prevent artificial flattening of accumulation curves due to recent discoveries and descriptions not yet being entered into databases . To account for higher taxa yet to be discovered , we used the following approach . First , for each taxonomic rank from phylum to genus , we fitted six asymptotic parametric regression models ( i . e . , negative exponential , asymptotic , Michaelis-Menten , rational , Chapman-Richards , and modified Weibull [23] ) to the temporal accumulation curve of higher taxa ( Figure 1A–1E ) and used multimodel averaging based on the small-sample size corrected version of Akaike's Information Criteria ( AICc ) to predict the asymptotic number of taxa ( dotted horizontal line in Figure 1A–1E ) [23] . Ideally data should be modeled using only the decelerating part of the accumulation curve [22]–[23] , however , frequently there was no obvious breakpoint at which accumulation curves switched from an increasing to a decelerating rate of discovery ( Figure 1A–1E ) . Therefore , we fitted models to data starting at all possible years from 1758 onwards ( data before 1758 were added as an intercept to prevent a spike due to Linnaeus ) and selected the model predictions if at least 10 years of data were available and if five of the six asymptotic models converged to the subset data . Then , the estimated multimodel asymptotes and standard errors for each selected year were used to estimate a consensus asymptote and its standard error . In this approach , the multimodel asymptotes for all cut-off years selected and their standard errors are weighted proportionally to their standard error , thus ensuring that the uncertainty both within and among predictions were incorporated [36] . To estimate the number of species in a taxonomic group from its higher taxonomy , we used Least Squares Regression models to relate the consensus asymptotic number of higher taxa against their numerical rank , and then used the resulting regression model to extrapolate to the species level ( Figure 1G ) . Since data are not strictly independent across hierarchically organized taxa , we also used models based on Generalized Least Squares assuming autocorrelated regression errors . Both types of models were run with and without the inverse of the consensus estimate variances as weights to account for differences in certainty in the asymptotic number of higher taxa . We evaluated the fit of exponential , power , and hyperexponential functions to the data and obtained a prediction of the number of species by multimodel averaging based on AICc of the best type of function . The hyperexponential function was chosen for kingdoms whereas the exponential function for the smaller groups was used in the validation analysis ( see comparison of fits in Figure S4 ) . We contacted 4 , 771 taxonomy experts with electronic mail addresses as listed in the World Taxonomist Database ( www . eti . uva . nl/tools/wtd . php ) ; 1 , 833 were faulty e-mails , hence about 2 , 938 experts received our request , of which 548 responded to our survey ( response rate of 18 . 7% ) . Respondents were asked to identify their taxon of expertise , and to comment on what percentage of currently valid names could be synonyms at taxonomic levels from species to kingdom . We also polled taxonomists about whether the taxonomic effort ( measured as numbers of professional taxonomists ) in their area of expertise in recent times was increasing , decreasing , or stable . | Knowing the number of species on Earth is one of the most basic yet elusive questions in science . Unfortunately , obtaining an accurate number is constrained by the fact that most species remain to be described and because indirect attempts to answer this question have been highly controversial . Here , we document that the taxonomic classification of species into higher taxonomic groups ( from genera to phyla ) follows a consistent pattern from which the total number of species in any taxonomic group can be predicted . Assessment of this pattern for all kingdoms of life on Earth predicts ∼8 . 7 million ( ±1 . 3 million SE ) species globally , of which ∼2 . 2 million ( ±0 . 18 million SE ) are marine . Our results suggest that some 86% of the species on Earth , and 91% in the ocean , still await description . Closing this knowledge gap will require a renewed interest in exploration and taxonomy , and a continuing effort to catalogue existing biodiversity data in publicly available databases . | [
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] | 2011 | How Many Species Are There on Earth and in the Ocean? |
The chromosome 9p21 ( Chr9p21 ) locus of coronary artery disease has been identified in the first surge of genome-wide association and is the strongest genetic factor of atherosclerosis known today . Chr9p21 encodes the long non-coding RNA ( ncRNA ) antisense non-coding RNA in the INK4 locus ( ANRIL ) . ANRIL expression is associated with the Chr9p21 genotype and correlated with atherosclerosis severity . Here , we report on the molecular mechanisms through which ANRIL regulates target-genes in trans , leading to increased cell proliferation , increased cell adhesion and decreased apoptosis , which are all essential mechanisms of atherogenesis . Importantly , trans-regulation was dependent on Alu motifs , which marked the promoters of ANRIL target genes and were mirrored in ANRIL RNA transcripts . ANRIL bound Polycomb group proteins that were highly enriched in the proximity of Alu motifs across the genome and were recruited to promoters of target genes upon ANRIL over-expression . The functional relevance of Alu motifs in ANRIL was confirmed by deletion and mutagenesis , reversing trans-regulation and atherogenic cell functions . ANRIL-regulated networks were confirmed in 2280 individuals with and without coronary artery disease and functionally validated in primary cells from patients carrying the Chr9p21 risk allele . Our study provides a molecular mechanism for pro-atherogenic effects of ANRIL at Chr9p21 and suggests a novel role for Alu elements in epigenetic gene regulation by long ncRNAs .
The chromosome 9p21 ( Chr9p21 ) locus is the strongest genetic risk factor of atherosclerosis known today , yet , the responsible mechanisms still remain unclear . Chr9p21 lacks associations with common cardiovascular risk factors , such as lipids and hypertension , indicating that the locus exerts its effect through an alternative mechanism [1]–[4] . The risk region spans ∼50 kb of DNA sequence and does not encode protein-coding genes but the long non-coding RNA ( ncRNA ) antisense non-coding RNA in the INK4 locus ( ANRIL; Figure 1A ) [5] , [6] . CDKN2BAS or CDKN2B-AS1 are used as synonyms for ANRIL . The closest neighbouring genes are the cyclin-dependent kinase inhibitors CDKN2A and CDKN2B , which are located ∼100 kb proximal of the Chr9p21 atherosclerosis risk region . While these genes are expressed in atherosclerotic lesions [7] , the majority of studies in humans speak against a cis-regulation of CDKN2A and CDKN2B by Chr9p21 ( reviewed by [8] ) . Studies in mice revealed no effect on atherosclerosis development [9] , [10] . In contrast , a clear association of ANRIL with the Chr9p21 genotype has been established in several studies , even though the direction of effects is still a matter of dispute [5] , [6] , [8] , [11]–[13] . Moreover , a correlation of ANRIL expression with atherosclerosis severity has been described [2] , [8] . Based on these clinical and experimental data , ANRIL must be considered as a prime functional candidate for modifying atherosclerosis susceptibility at the Chr9p21 locus . ANRIL belongs to the family of long ncRNAs , which are arbitrarily defined and distinguished from short ncRNA , such as microRNA , by their length of >200 bp [14]–[16] . Long ncRNAs have been implicated in diverse functions in gene regulation , such as chromosome dosage-compensation , imprinting , epigenetic regulation , cell cycle control , nuclear and cytoplasmic trafficking , transcription , translation , splicing and cell differentiation [15] , [17]–[19] . These effects are mediated by RNA-RNA , RNA-DNA or RNA-protein interactions [17]–[19] . Previous mechanistic work on ANRIL in prostate tissue and cell lines has focused on its role in cis-suppression of CDKN2A and CDKN2B [3] , [20] . Using RNAi against ANRIL , these studies showed impaired recruitment of chromobox homolog 7 ( CBX7 ) , a member of Polycomb repressive complex 1 ( PRC1 ) [3] , and of suppressor of zeste 12 ( SUZ12 ) , a member of PRC2 [20] , to the Chr9p21 region . PRCs are multiprotein complexes , responsible for initiating and maintaining epigenetic chromatin modifications and thereby controlling gene expression [21] . Yap et al found that knock-down of ANRIL decreased trimethylation of lysine 27 residues in histone 3 ( H3K27me3 ) and was associated with increased CDKN2A expression , while CDKN2B remained unchanged [3] . In contrast , Kotake et al showed that shRNA-mediated ANRIL knock-down disrupted SUZ12 binding to the Chr9p21 locus and led to increased CDKN2B expression whereas CDKN2A remained unaffected [20] . While results of ANRIL knock-down are conflicting with regard to expression of CDKN2A and CDKN2B , both studies demonstrated a significant reduction of cell proliferation [3] , [20] , a key mechanism in atherogenesis [22] . In these studies , however , potential effects of ANRIL knock-down on trans-regulation were not investigated . Sato et al transiently over-expressed one specific ANRIL transcript in HeLa cells and found effects on expression levels of various genes in trans [23] . Even though the molecular mechanisms were not investigated in that work , this finding was of interest because trans-regulation of target genes has been proposed as a key mechanism for biological effects of other long non-coding RNA such as HOTAIR [24]–[26] . It is believed that these long ncRNAs mediate their effects through targeting epigenetic modifier proteins to specific sites in the genome [17] , [19] , [27] . Taken together , the previously available data suggested that ANRIL might influence gene expression by modulating chromatin modification and thereby affect cardiovascular risk . The aim of the present study was to investigate the role of ANRIL in gene regulation and cellular functions related to atherogenesis on a mechanistic level . To this end , we performed genome-wide expression analyses in cell lines over-expressing distinct ANRIL transcripts that were associated with Chr9p21 . We studied the molecular mechanisms of ANRIL-mediated gene regulation by investigating ANRIL binding to epigenetic effector proteins and their distribution across the genome . Using bioinformatics studies , we identified a regulatory motif characteristic for ANRIL-regulated genes . Finally , the functional relevance of the motif was confirmed by deletion and mutagenesis and results were validated in primary human cells from patients with and without the Chr9p21 atherosclerosis risk allele .
Using rapid amplification of cDNA ends ( RACE ) and subsequent PCR experiments , we identified four major groups of ANRIL transcripts in human peripheral blood mononuclear cells ( PBMC ) and the monocytic cell line MonoMac ( Figure S1 , Figure 1C ) . Consensus transcripts designated ANRIL1-4 , comprising the most frequently occurring exon-combinations and most strongly expressed in MonoMac cells ( Figure S1E ) , are shown in Figure 2A . Association of these transcripts with Chr9p21 was confirmed in PBMC ( n = 2280 ) and whole blood ( n = 960 ) of patients with and without coronary artery disease ( CAD ) in the Leipzig LIFE Heart Study [28] and in endarterectomy specimens ( n = 193 ) ( Figures 1D and 1E ) . The Chr9p21 risk allele was associated with increased ANRIL expression ( Figure 1E ) and different isoforms were positively correlated with each other ( Figure S2 ) . Using an assay detecting a common exon-exon boundary present in the majority of ANRIL isoforms ( Ex1-5 ) , we found a 26% overall increase of ANRIL expression per CAD-risk allele ( P = 2 . 04×10−33 ) in PBMC of the Leipzig LIFE Heart Study . Strongest isoform specific effects were found for ANRIL2 ( 5% increase per risk allele; P = 0 . 002 ) and ANRIL4 ( 8% increase per risk allele; P = 3 . 02×10−6 ) ( Figure 1E ) . To investigate the functional role of distinct ANRIL transcripts , we generated stably over-expressing cells lines ( Figure 2B , Figure S3 ) . ANRIL over-expression led to significant changes of gene expression in trans as determined by genome-wide mRNA expression analysis ( Figure 2C ) . 219 transcripts were down- and 708 transcripts were up-regulated in ANRIL1-4 cell lines with average fold-changes smaller than 0 . 5 and greater than 2 compared to vector control , respectively ( Table S1 and Table S2 ) . These genes were distributed across the genome and there was no evidence for regulation of CDKN2A/B in the Chr9p21 region ( Figure S4 ) . Gene set enrichment analysis predicted an effect of ANRIL over-expression on movement/adhesion , growth/proliferation and cell death/apoptosis ( Table 1 ) , which are central mechanisms of atherogenesis [22] . We therefore aimed to experimentally validate these predictions in ANRIL over-expressing cell lines . Studies confirmed that ANRIL led to increased cell adhesion with strongest effects observed for cell lines over-expressing ANRIL4 ( Figures 2D–2F ) . Over-expression of ANRIL further promoted cell growth and metabolic activity ( Figures 2G–2I ) . Apoptosis , as determined by flow cytometric analysis of AnnexinV-positive cells ( Figure 2J ) , caspase-3 activity ( Figure 2K ) and caspase-3 immunohistochemical staining ( Figure 2L ) was attenuated . Greatest biological effects were consistently found in cell lines over-expressing isoforms ANRIL2 and 4 , the same isoforms , which also revealed the strongest associations with the Chr9p21 risk genotype ( Figure 1E ) . Moreover , we demonstrated a dose-dependent effect on these mechanisms in independently established cell lines over-expressing these isoforms ( Figure S5 ) . Effects on cell adhesion , proliferation and apoptosis could be reversed by RNAi-mediated knock-down of ANRIL as shown in ANRIL2 and ANRIL4 cell lines ( Figures 2M–2O , Figure S6 ) , further supporting a pivotal role of ANRIL in these pro-atherogenic cellular functions . To systematically identify ANRIL-associated epigenetic effector proteins , we next screened ANRIL binding to Polycomb group ( PcG ) proteins ( AEBP2 , BMI1 , CBX7 , EED , EZH2 , JARID2 , MEL18 , PHF1 , PHF19 , RBAP46 , RING1B , RYBP , SUZ12 , YY1 ) and CoREST/REST ( CoREST , REST , LSD1 ) using RNA immunoprecipitation ( RIP ) in nuclear extracts from ANRIL2 and 4 cells ( Figures 3A–3B ) . ANRIL did not bind to CoREST/REST repressor proteins but bound to PRC1 proteins CBX7and RING1B and to PRC2 proteins EED , JARID2 , RBAP46 , and SUZ12 . ANRIL also bound to PRC-associated proteins RYBP and YY1 which have been shown to induce gene expression [29] , [30] . To investigate genome-wide distribution of Polycomb complexes , we chose CBX7 [3] and SUZ12 [20] as representative PcG proteins and performed chromatin immunoprecipitation followed by high-throughput sequencing ( ChIP-seq ) in ANRIL2 cells . Analysis of PcG distribution patterns in ANRIL-target gene promoters revealed reduced SUZ12 and CBX7 occupancy compared to not-regulated genes , following a wave-shaped binding pattern ( Figure 3C and Figure S7 ) . Reduced SUZ12 and CBX7 binding , as well as identical occupancy pattern , was replicated in publicly available data from BGO3 cells ( Figure 3D ) . Over-expression of ANRIL increased SUZ12 and CBX7 binding to promoters of up-regulated genes ( Figures 3E–3F ) , concordant with a recently described role of PRCs in regulation of active genes [31] . In further support , RNAi against CBX7 and SUZ12 largely reversed expression patterns not only of ANRIL-repressed , but also induced genes in ANRIL2 cells ( Figure 3G ) . Whereas ANRIL binding to CBX7 and SUZ12 has previously been demonstrated in the context of cis-repression [3] , [20] , our experiments now extent the role of these proteins to ANRIL-mediated trans-regulation of gene networks pivotal in atherogenesis . To address , which additional factors might be relevant for ANRIL-mediated trans-regulation , we performed bioinformatic analyses of promoter regions of ANRIL up- and down-regulated target genes . To this end , we used the MEME algorithm searching for differences in motif abundance and identified two partially overlapping DNA motifs ( Figure 4A ) . Combined analysis of all trans-regulated genes validated the core motif CACGCCTGTAATCCCAGCACTTTGG ( Figure 4A ) . The identified motif is an Alu-DEIN element [32] , [33] with approximately 60 . 000 copies per human genome [34] . Since MEME does not provide information whether a motif is enriched or depleted , we quantitatively tested motif occurrence and found a significant depletion in up- and down-regulated genes compared to genes not regulated by ANRIL over-expression ( 4 vs . 6 occurrences per 5 kb promoter , respectively , P<10−15; Figure 4B ) . These data were consistent with decreased PcG occupancy in target-gene promoters ( Figures 3C–3D ) . Notably , strong enrichment of PcG binding was found ∼150 bp downstream of the Alu motif compared to random DNA control ( Figure 4C ) . This finding was replicated in the independent dataset for SUZ12 in BGO3 cells ( Figure 4D ) suggesting Alu element-dependent binding of PcG proteins as a general mechanism . Due to the repetitive nature of the investigated Alu motif , the significant spatial coherence between the motif and PcG occupancy was not detected when analyses were masked for repetitive elements ( Figure 4E ) . Importantly , the same Alu motif which was found in the DNA promoter sequence of ANRIL-regulated genes was also present in ANRIL transcripts ( Figure S8 ) . Here , it was predicted to form a stem-loop structure in ANRIL RNA ( Figure 4F ) suggesting RNA-chromatin interactions as a potential effector mechanism [16] . Using RIP , we show that ANRIL co-immunoprecipitates with H3 and trimethylated lysine 27 of histone 3 ( H3K27me3 ) ( Figure 4G ) . These results speak further in favor of ANRIL-chromatin interaction at genomic sites where PRC-mediated epigenetic histone methylation takes place . To validate the functional relevance of Alu sequences implemented in ANRIL transcripts , we generated stably over-expressing cell lines devoid of exons containing these sequences ( Figure 5A , Figure S9 ) . Over-expression of mutant isoforms ANRIL2a-c and ANRIL4a , b reversed expression changes of representative transcripts that were otherwise induced ( TSC22D3; Figure 2C and Figure 5B ) or suppressed ( COL3A1; Figure 2C and Figure 5C ) in ANRIL2 and 4 cells . Increased cell adhesion in ANRIL2 and 4 was abolished in cell lines lacking the Alu motif ( Figure 5D ) . Consistent with this finding , ANRIL2a-c and ANRIL4a , b cell lines showed increased apoptosis and proliferated more slowly compared to ANRIL2 and 4 ( Figures 5E–5F ) . To exclude that depletion of whole exons led to significant changes in ANRIL secondary structure and thus impaired ANRIL function , we next generated cell lines stably over-expressing ANRIL isoforms with single-base mutations of 25% , 33% , and 100% of nucleotides in the identified Alu motif ( Figure 5G , Figure S9 ) . Over-expression of these ANRIL isoforms confirmed the important role of the Alu motif by reversing expression changes of ANRIL trans-regulated genes ( TSC22D3 , Figure 2C and Figure 5H; COL3A1 , Figure 2C and Figure 5I ) compared to ANRIL2 cells . Moreover , ANRIL-mediated effects on adhesion , apoptosis and proliferation were attenuated ( Figures 5J–5L ) , further supporting the functional relevance of ANRIL Alu motifs in pro-atherogenic cellular functions . To investigate whether findings from cell culture studies could be translated into the human situation , we investigated genome-wide transcript expression in PBMC from 2280 subjects of the Leipzig LIFE Heart Study and associated gene expression with the Chr9p21 haplotype and ANRIL expression . While no transcripts were significantly associated with Chr9p21 on a genome-wide level , gene set enrichment analyses of genes correlated with ANRIL expression ( n = 5066; P value≤0 . 01 ) and associated at a nominal significance level with Chr9p21 ( n = 1698; P-value≤0 . 05 ) revealed comparable pathways to those identified in ANRIL over-expressing cell lines ( Table 2 ) . We next investigated adhesion and apoptosis in PBMC from patients , which were either homozygous for the protective or the CAD-risk allele at Chr9p21 ( Figures 6A–6B ) . Consistent with our earlier cell culture studies , the risk allele , which was associated with increased expression of linear ANRIL transcripts ( Figure 1 ) , led to increased adhesion ( P = 0 . 001; Figure 6A ) and decreased apoptosis ( P = 0 . 001; Figure 6B ) compared to PBMCs from carriers of the protective allele .
Here we show that the same ANRIL isoforms , which were up-regulated in patients carrying the Chr9p21 atherosclerosis risk haplotype , modulate gene networks in trans leading to pro-atherogenic cellular properties . At the molecular level , we provide strong evidence for an Alu sequence ( Figure 4A ) as the key regulatory element responsible for ANRIL-mediated trans-regulation ( Figure 6C ) . This Alu motif was not only expressed in ANRIL RNA transcripts but also marked promoters of target-genes and was associated with epigenetic effector protein binding . Depletion and mutagenesis of the motif reversed trans-regulation and normalized cellular functions . More generally , the proposed mechanism of ANRIL in atherogenesis highlights a novel role of Alu elements in epigenetic trans-regulation of gene networks , which might be relevant for other long ncRNAs as well . To the best of our knowledge , this is the first study investigating the role of distinct ANRIL isoforms in several key mechanisms of atherogenesis using stable over-expression and knock-down approaches ( Figure 1 and Figure 2 ) . All investigated ANRIL isoforms had more or less pronounced effects on cellular functions ( Figure 2 , Table S3 ) , but strongest effects were consistently found in cell lines over-expressing ANRIL isoforms which were up-regulated in patients carrying the Chr9p21 risk allele ( Figure 1 ) . These effects were also dose-dependent ( Figure S5 ) . Importantly , results from cell culture studies were validated in primary cells from patients with and without the Chr9p21 risk haplotype ( Figure 6 ) . So far , mechanistic work on ANRIL has focused on cell proliferation using RNAi approaches [3] , [20] , [35] , [36] . In these studies down-regulation of ANRIL led to decreased proliferation in different cell culture models , which is well in line with our observation of increased proliferation in stable ANRIL over-expressing cell lines ( Figure 2 ) . Network analyses of trans-regulated genes in the present study indicated that in addition to proliferation , cell adhesion and apoptosis were also affected in ANRIL cell lines . These predictions were functionally validated revealing that ANRIL over-expression led to increased adhesion and decreased apoptosis . Again , effects were greatest for those isoforms showing the strongest associations with the Chr9p21 risk genotype and could be reversed by RNAi against ANRIL ( Figure 2 ) . Moreover , the direction of atherogenic cell functions ( increased cell adhesion , increased proliferation and decreased apoptosis ) nicely fits with evidence for a potential pro-atherogenic role of ANRIL from patient studies [6] , [22] . Taken together , our data provide a plausible mechanism for pro-atherogenic functions of Chr9p21-associated ANRIL transcripts . In previous studies , it has been shown that long ncRNA may affect gene expression of target genes [24]–[26] , [37]–[39] . Among the best studied examples is the long ncRNA HOTAIR , which is transcribed from the HOXC cluster and was shown to repress genes in the HOXD cluster in trans [25] , [26] . A potential role of ANRIL in trans-regulation has previously been postulated by Sato et al , investigating genome-wide mRNA expression in HeLa cells upon transient over-expression of a single ANRIL isoform [23] . In the current work , we used a model of stable over-expressing cell lines and found evidence for trans-regulation of distinct gene networks that overlapped between different ANRIL isoforms ( Table 1 ) . To translate these finding to patients with coronary artery disease , we performed pathway analysis of genes that were correlated with ANRIL expression and associated with the Chr9p21 risk genotype in 2280 participants of the Leipzig LIFE Heart Study . While no transcript was associated with Chr9p21 at a genome-wide level of significance , we found almost identical pathways in patients with high ANRIL expression and high genetic risk at Chr9p21 as in stable ANRIL over-expressing cell lines ( Table 2 ) . The lack of significant associations of gene expression with Chr9p21 has also been observed by Zeller et al [40] and might be explained by the rather subtle modulation of ANRIL by Chr9p21 with slighter effects on trans-regulation as opposed to stronger over-expression in the investigated cell culture models . Nevertheless , permanently elevated ANRIL levels might activate the observed gene networks leading to subtle changes of cellular functions ( Figure 6 ) and thereby increasing cardiovascular risk over time . On the mechanistic level , it has been postulated that long ncRNA may serve as a scaffold , guiding effector-proteins to chromatin [24]–[26] , [37]–[39] . Indeed , previous work has demonstrated ANRIL binding to CBX7 [3] and SUZ12 [20] , which are proteins contained in PRC1 and PRC2 , respectively . Both previous papers focused on ANRIL-mediated cis-repression of CDKN2A and CDKN2B using RNAi but did not investigate potential trans-regulatory effects [3] , [20] . In the current work , we found no effect of ANRIL over-expression on expression of CDKN2A and CDKN2B ( Figure S4 ) . Thus , the spatial coherence of ANRIL transcription with adjacent protein-coding genes might be relevant for cis-suppression . This is the first study systematically investigating ANRIL binding to 17 different proteins contained in chromatin modifying complexes PRC1 , PRC2 and CoREST/Rest ( Figure 3 ) . We demonstrated binding to predominantly inhibitory ( CBX7 , RING1B , EED , JARID2 , RBAP46 , SUZ12 ) [41] and potentially activating factors ( RYBP , YY1 ) [29] , [30] . CBX7 and SUZ12 were selected as representative proteins for PRC1 and 2 , respectively , and were followed up in genome-wide ChIP-seq experiments ( Figure 3 and Figure 4 ) . Notably , ANRIL over-expression was accompanied with changes of CBX7 and SUZ12 distribution in ANRIL target-gene promoters ( Figure 3 ) . The role of PRCs in ANRIL-mediated gene regulation was further proven by RNAi against CBX7 and SUZ12 which reversed trans-regulation of down- and also of up-regulated target genes in ANRIL cells ( Figure 3G ) . Induction of gene expression through PcG proteins might seem at odds with the current understanding of PRC-mediated gene silencing . However , binding of PcG proteins in active genes has been described in earlier studies [31] . Moreover , Morey et al demonstrated reduced gene repression in distinct PRC1 compexes containing RYBP , which was shown to associate with ANRIL ( Figure 3 ) [42] . Alternatively , ANRIL-bound activating factors RYBP and YY1 may directly activate gene expression [29] , [30] or ANRIL might bind other activating epigenetic effector proteins [43] . Taken together , we demonstrate a central role of PRC1 and PRC2 but not CoREST/Rest in ANRIL-mediated repression and induction of genes but additional work is clearly warranted to unravel the complex nature of these trans-regulatory mechanisms . A key limitation in the current understanding of long ncRNA function , in particular with regard to their trans-regulatory effects , is the lack of knowledge about specific regulatory sequences or structural motifs . These sequences might be responsible for targeting long ncRNA to distinct regulatory sites in the genome . Here , we provide first evidence for an important role of Alu motifs in this process , which mark the promoters of ANRIL trans-regulated genes ( Figure 4 ) . Additionally , genome-wide ChIP-seq analysis revealed binding of ANRIL-associated PcG effector proteins in close proximity to the Alu motif . Importantly , the same Alu motif was included in ANRIL ncRNA transcripts and predicted to be located in a central stem-loop like structure ( Figure 4F ) . Additional evidence for ANRIL binding to chromatin comes from its association with histone H3 and H3K27me3 ( Figure 4G ) . In previous work , Alu-like , CG- and GA-rich sequences were proposed as potential RNA-DNA interaction sites associated with RNA:DNA:DNA triplex formation [44] , [45] . Paradoxically , Alu occurrence was significantly depleted in ANRIL-regulated genes , suggesting that a certain spatial patterning or additional co-factors in promoter regions rather than motif abundance alone might be relevant ( Figure 4 , Figure 6C ) . Functional relevance of the motif was proven by depletion and mutagenesis in ANRIL RNA , which reversed trans-regulation and pro-atherogenic cellular properties ( Figure 5 ) . Thus , our data suggest that ANRIL may bind to chromatin through interaction via its Alu motif , thereby guiding PRC proteins to ANRIL-regulated genes ( Figure 6C ) . Despite long consideration as “genomic junk” , Alu elements are coming into the focus of intense research . Alu enrichment occurred over the course of evolution [46] and integration at genomic sites was associated with maturation and gain-of-function of ncRNAs [47] . Alu elements as well as distal ANRIL exons are not conserved in the orthologous chromosomal region on mouse chromosome 4 , which might be an explanation for the lack of effect on atherosclerosis when deleting that region [48] . Recent work by Jeck et al has also demonstrated preferred inclusion of Alu motifs in non-coding RNA lariats which are commonly thought to represent inactive forms of ncRNAs [49] . Whether implementation of Alu motifs in ncRNA lariats leads to silencing of the effector sequences or not remains to be determined . In summary , our work extends the function of Alu motifs to regulatory components of ncRNAs with a central role in ncRNA-mediated epigenetic trans-regulation . Furthermore , it implies a pivotal role for Alu elements in genetically determined vascular disease and describes a plausible molecular mechanism for pro-atherogenic ANRIL function at Chr9p21 .
The Leipzig LIFE Heart Study has been approved by the Ethics Committee of the Medical Faculty of the University Leipzig ( Reg . No 276-2005 ) and was described previously [28] . RNA from peripheral blood mononuclear cells ( PBMC; n = 2280 ) and whole blood ( n = 960 ) from the same patients of this study was isolated as described [6] . Human endarteryectomy specimens ( n = 193 ) were collected in an independent cohort of patients undergoing vascular surgery and the utilization of human vascular tissues was approved by the Ethics Committee of the Medical Faculty Carl Gustav Carus of the Technical University Dresden ( EK316122008 ) [7] . Genotyping of single nucleotide polymorphisms rs10757274 , rs2383206 , rs2383297 , and rs10757278 in 2280 probands of the Leipzig LIFE Heart Study and in vascular tissue was performed as described [6] , [7] . Initial screening of human cell lines MonoMac , THP1 , U937 , HEK293 , HepG2 , CaCo2 , and Hutu80 for Chr9p21 gene expression ( MTAP , CDKN2A , CDKN2B , ANRIL , qRT-PCR assays were described in [6] ) revealed that MonoMac and HEK293 cells expressed all Chr9p21 transcripts ( data not shown ) . This suggested that these genes might be functionally relevant in these cells whereas all other investigated cell lines were lacking expression of at least one of the Chr9p21 transcripts . HEK293 cells ( DMSZ , ACC305 ) were cultured in DMEM ( Life Technologies ) containing 10% fetal calf serum ( FCS , Biochrom ) , 1% penicillin/streptomycin ( P/S , Life Technologies ) . MonoMac cells ( DSMZ , ACC124 ) were cultured in RPMI 1640 ( Biochrom ) containing 10% FCS , 1% P/S , 1% MEM ( Life Technologies ) , and 1% OPI ( Sigma ) . Cryopreserved PBMC ( n = 32 ) were thawed , cultured in RPMI 1640 ( Biochrom ) containing 10% FCS , 1% P/S and functional assays were performed within 48 hours . ANRIL isoforms were cloned in the bicistronic pBI-CMV2 ( Clontech ) or pTRACER-SV40 ( Life Technologies ) vectors allowing parallel expression of a green fluorescent protein ( GFP ) and ANRIL transcripts . Using Lipofectamine 2000 ( Life Technologies ) , HEK293 cells were either co-transfected with ANRIL-pBI-CMV2 vectors/empty vector control and neomycin-encoding vector or transfected with ANRIL-pTRACER vectors/empty vector control encoding a GFP-Zeocin resistance gene . Transfected cells were selected with geneticindisulfate ( G418 , Roth ) or Zeocin ( Life Technologies ) . After 2 weeks , stably transfected cells were selected by flow cytometry and over-expression of ANRIL was validated by quantitative RT-PCR . On average , 2–4 cell lines were generated per ANRIL isoform and vector control , respectively . Cell adhesion assays were performed in 96-well plates coated with collagen ( Roche ) , Matrigel ( BD ) or PBS . Cells were allowed to adhere for 40 min , quadruplicate measurements/cell line were performed . Numbers of adherent cells were determined using CellTiter-Blue/CellTiter-Glo ( Promega ) in relation to standard curves of the respective cell line . PBMC adhesion assays were performed accordingly . Quadruplicate measurements/subject were performed . Cellular proliferation was either determined by counting absolute cell numbers ( trypan blue staining ) or viability assays ( CellTiter-Blue/CellTiter-Glo , Promega ) . Glucose in the cell culture supernatants was determined using standard chemistry ( Roche ) . Apoptosis was determined using flow-cytometric detection of AnnexinV positive cells ( GFP-Certified Apoptosis/Necrosis Detection Kit , ENZO ) , caspase-3 activity ( Caspase-3/CPP32 Fluorometric Assay Kit , BioVision; CaspaseGlo 3/7 , Promega ) and caspase-3 staining . siRNA knock-down of ANRIL ( n272158 , Life Technologies ) , CBX7 ( s23926 , Life Technologies ) , SUZ12 ( s23967 , Life Technologies ) was performed using Lipofectamine 2000 ( Life Technologies ) . Knock-down efficiency was determined by quantitative RT-PCR and Western blotting . 10 µg RNA from human PBMC and from MonoMac cells were reverse transcribed using the ExactSTART Eukaryotic mRNA 5′- & 3′-RACE Kit ( Epicentre Biotechnologies ) according to the manufacturer's instructions . RACE PCR reactions were prepared using Advantage 2 Polymerase Mix ( Clontech ) and subcloned ( pCR2 . 1-TOPO Vector , Life Technologies ) . Primers used for RACE experiments are listed in Table S4 . Amplification of full-length isoforms was performed using primers listed in Table S5 ( schematic in Figure S1 ) . Sequencing of PCR products was performed with an automated DNA sequencer ( Applied Biosystems ) . Quantitative RT-PCRs and analysis of data were performed as described [6] . Primers and probes for ANRIL isoforms ( n = 5 ) , TSC22D3 , COL3A1 , and U1 are given in Table S6 . RNA from cell lines ANRIL1-4 and vector control cell line , siRNA-treated ANRIL2 cells , and RNA from PBMC ( n = 2280 ) was labeled and hybridized to Illumina HumanHT-12 v4 BeadChips . Arrays were scanned with an Illumina iScan microarray scanner . Bead level data preprocessing was done in Illumina GenomeStudio . Antibodies against AEBP2 ( 11232-2-AP , Proteintech ) , BMI1 ( 05-637 , Millipore ) , CBX7 ( ab21873 , Abcam ) , EED ( 03-196 , Millipore ) , EZH2 ( ACC-3147 , Cell Signaling ) , JARID2 ( NB100-2214 , Novus Biologicals ) , MEL18 ( ab5267 , Abcam ) , PHF1 ( sc-101107 , Santa Cruz ) , PHF19 ( 11895-1-AP , Proteintech ) , RBAP46 ( MA1-23277 , Thermo Scientific ) , RING1B ( NBP1-49966 , Novus Biologicals ) , RYBP ( NBP1-97742 , Novus Biologicals ) , SUZ12 ( ab12073 , Abcam ) , YY1 ( NBP1-46218 , Novus Biologicals ) , LSD1 ( 39186 , Active Motif ) , REST ( 07-579 , Millipore ) , CoREST ( 07-455 , Millipore ) , H3 ( ab1791 , Abcam ) , H3K27me3 ( ab6002 , Abcam ) , rabbit control IgG ( kch-504-250 , Diagenode ) , mouse control IgG ( kch-819-015 , Diagenode ) , and goat control IgG ( sc-2346 , Santa Cruz ) were used . The immunoprecipitation reaction followed with some modifications previously described protocols [50] , [51]: 2×107 ANRIL2 , ANRIL4 and vector control cells were treated with 0 . 1% formaldehyde for 10 min at 23°C . Nuclear extracts were preincubated with non-immune IgG and tRNA ( 100 µg/ml ) for 1 h and primary antibodies and control IgG reacted overnight at 4°C . The immunoprecipitates were washed 3× with low-salt , 3× with high-salt and 1× Li-salt buffers . The retrieved RNA was quantitated , reverse transcribed using random hexamer primers , and analyzed by qRT-PCR with ANRIL-specific primers ( Ex1-5 assay , Table S6 ) . U1-specific primers were used as negative control ( Table S6 ) . 2–5×107 ANRIL2 and vector control cells were fixed with 1% formaldehyde for 10 min at 23°C . Cross-linking reaction was stopped by adding glycine to a final concentration of 0 . 125 M for 5 min followed by three washes with ice-cold PBS . Cells were harvested , suspended in 50 mM Hepes-KOH , pH 7 . 5 , 100 mM NaCl , 1 mM EDTA , pH 8 . 0 , 0 . 5 mM EGTA , pH 8 . 0 and incubated for 10 min at 4°C . Cells were washed with 10 mM Tris-HCl , pH 8 . 0 , 200 mM NaCl , 1 mM EDTA , pH 8 . 0 , 0 . 5 mM EGTA , pH 8 . 0 for 10 min , pelleted by centrifugation and the nuclei lysed in 10 mM Tris-HCl , pH 8 . 0 , 200 mM NaCl , 1 mM EDTA , pH 8 . 0 , 0 . 5 mM EGTA pH 8 . 0 , 0 . 1% Na-Deoxycholate , 0 . 5% N-lauroylsarcosine for 10 min at 4°C . Samples were sonicated with Diagenode Bioruptor UCD-300TO ( High level , 8×5 cycles 30 sec on/30 sec off , 4°C ) , centrifuged at 15 , 000× g for 10 min at 4°C and the supernatant was shock-frozen in liquid nitrogen and stored at −80°C . Nuclear extracts were preadsorbed with non-immune IgG for 1 h and treated with SUZ12 , CBX7 , and control IgG antibodies overnight at 4°C . Precipitates were processed with the HighCell#ChIP kit ( Diagenode ) and Illumina DNA sequencing libraries were generated using the ChIP-seq Sample Preparation Kit ( IP-102-1001 , Illumina ) . Purity and quantity was measured on an Agilent Technologies 2100 Bioanalyzer . Sequencing was performed with the Illumina Genome Analyzer II platform . ChIP-seq data are deposited in the Sequence Read Archive ( SRA ) under accession number SRA052089 . 1 . BGO3 ( GSM602674 ) data are publicly available at ( http://www . ncbi . nlm . nih . gov/geo ) . | Chromosome 9p21 is the strongest genetic factor for coronary artery disease and encodes the long non-coding RNA ( ncRNA ) ANRIL . Here , we show that increased ANRIL expression mediates atherosclerosis risk through trans-regulation of gene networks leading to pro-atherogenic cellular properties , such as increased proliferation and adhesion . ANRIL may act as a scaffold , guiding effector-proteins to chromatin . These functions depend on an Alu motif present in ANRIL RNA and mirrored several thousand-fold in the genome . Alu elements are a family of primate-specific short interspersed repeat elements ( SINEs ) and have been linked with genetic disease . Current models propose that either exonisation of Alu elements or changes of cis-regulation of adjacent genes are the underlying disease mechanisms . Our work extends the function of Alu transposons to regulatory components of long ncRNAs with a central role in epigenetic trans-regulation . Furthermore , it implies a pivotal role for Alu elements in genetically determined vascular disease and describes a plausible molecular mechanism for a pro-atherogenic function of ANRIL at chromosome 9p21 . | [
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"n... | 2013 | Alu Elements in ANRIL Non-Coding RNA at Chromosome 9p21 Modulate Atherogenic Cell Functions through Trans-Regulation of Gene Networks |
In principle it appears advantageous for single neurons to perform non-linear operations . Indeed it has been reported that some neurons show signatures of such operations in their electrophysiological response . A particular case in point is the Lobula Giant Movement Detector ( LGMD ) neuron of the locust , which is reported to locally perform a functional multiplication . Given the wide ramifications of this suggestion with respect to our understanding of neuronal computations , it is essential that this interpretation of the LGMD as a local multiplication unit is thoroughly tested . Here we evaluate an alternative model that tests the hypothesis that the non-linear responses of the LGMD neuron emerge from the interactions of many neurons in the opto-motor processing structure of the locust . We show , by exposing our model to standard LGMD stimulation protocols , that the properties of the LGMD that were seen as a hallmark of local non-linear operations can be explained as emerging from the dynamics of the pre-synaptic network . Moreover , we demonstrate that these properties strongly depend on the details of the synaptic projections from the medulla to the LGMD . From these observations we deduce a number of testable predictions . To assess the real-time properties of our model we applied it to a high-speed robot . These robot results show that our model of the locust opto-motor system is able to reliably stabilize the movement trajectory of the robot and can robustly support collision avoidance . In addition , these behavioural experiments suggest that the emergent non-linear responses of the LGMD neuron enhance the system's collision detection acuity . We show how all reported properties of this neuron are consistently reproduced by this alternative model , and how they emerge from the overall opto-motor processing structure of the locust . Hence , our results propose an alternative view on neuronal computation that emphasizes the network properties as opposed to the local transformations that can be performed by single neurons .
Since the introduction of the neuron doctrine about 100 years ago , a central question has become what local operations the primitive elements of nervous systems can perform . So far , the only operation that has clear experimental support is the threshold operation that converts the depolarization of the membrane into action potentials . However , also other local non-linear operations such as multiplications and divisions have been proposed . For instance , the Elementary Motion Detector ( EMD ) , a well-established model of motion detection in the fly visual system that relies on multiplication in order to explain the neural responses of the Horizontal and Vertical System ( HS , VS ) visual interneurons [1] . In addition , it has been proposed that attentional modulation can result in a multiplicative gain of neuronal response to sensory stimuli [2] . Another example is the divisive inhibition that is assumed to underlie some of the non-linear adaptation properties of cortical neurons [3] , [4] , while several other studies have investigated how neuronal noise or dendritic saturation could contribute to divisive gain control [5] , [6] . Moreover , theoretical studies on neocortical pyramidal cells have suggested that multiplicative dendritic integration could account for non-linear sensory processing enhancing stimulus classification [7] , [8] . Despite the above examples , its computational attractiveness and the fact that some data can be satisfactorily described in non-linear terms , it remains unclear how the biophysics of single neurons could implement these operations . One particular case in point is the Lobula Giant Movement Detector ( LGMD ) visual interneuron of the locust . Recently it has been shown that the responses of this visual interneuron can be explained in terms of a local product of two high-level features of visual stimuli , their angular size and angular speed by means of a non-linear transfer function of the neuron [9] , [10] . If correct , this is the most explicit case reported in the experimental literature that supports the notion of local non-linear neuronal operations and it will have important consequences for our understanding of the computations that the nervous system can perform , as it significantly increases the computational power we can ascribe to single neurons . Hence , given the implications of this finding , it is important to investigate whether the non-linear relationship between the responses of the LGMD neuron and the visual stimuli it is exposed to can be understood in alternative terms , yet consistent with our current knowledge of the system . Here we investigated the alternative hypothesis that the non-linear responses of the LGMD can be explained in terms of an emergent non-linear operation that results from the integration of distributed computations performed by the neurons of the processing architecture as a whole as opposed to being a multiplication operation that is local to a single unit , i . e . the LGMD . The LGMD neuron is a wide-field neuron that is known to respond preferentially to looming stimuli [11] , [12] . Initially , it was first thought to be an on-off neuron due to its integration of neuronal responses generated in the afferent medulla layer that correlate with the onset and offset of local visual features [13]–[15] . More recently the relationship between properties of looming stimuli and the firing rate of the LGMD have been extensively documented , including the non-linear relationship between firing rate and time to collision ( TTC ) , the constant relation between peak firing rate and angular size , the independence of the peak firing rate of the stimulus speed , shape and texture , and the linear relationship between the TTC of the LGMD peak firing rate and the apparent looming stimulus' speed [9] , [16]–[18] . The LGMD has been the target of a number of theoretical studies that either investigated its collision detection capabilities [19]–[22] , or its putative non-linear integration properties [9] , [16]–[18] . The first model was published in the late 90's [22] . Rind et al . have shown that the integration of on- and off-channels by a LGMD model can account for aspects of its looming sensitivity and subsequently this model has been applied to collision avoidance by roving robots [22]–[26] . Recently , it has been shown that all of the known response properties of the LGMD can be accounted for in terms of the multiplication of the angular velocity ( θ′ ) with the angular size ( θ ) of a looming stimulus [9] , where θ and log ( θ′ ) are directly conveyed to the LGMD via separate inhibitory and excitatory pathways ( Figure 1 ) . The membrane potential ( Vm ) deflection is subsequently assumed to be proportional to this multiplication that is subsequently expressed in a firing rate , f−l , via an exponential mapping: ( 1 ) where , ( 2 ) and θthreshold is an animal and species dependent parameter that specifies the approaching object's angular size at which the LGMD firing rate is maximal [27] . Hence , by performing an exponential on the summed inputs an effective multiplication occurs . This model indeed provides for an excellent fit of the LGMD responses to looming stimuli , and as such constitutes a useful benchmark for any model of the LGMD [10] . Nevertheless , this local multiplicative model makes a number of strong assumptions and overlooks the role of the neurons pre-synaptic to the LGMD . More concretely: how does the fan-in to the LGMD delineate an “object” of which θ′ and θ can be assessed , given that an “object” has been defined , how are log ( θ′ ) and θ computed , how is this high-level information represented by the massive fan-in to the LGMD , and how are the parameters related to the approaching stimulus ( θ′ and θ ) extracted and conveyed to the LGMD in the early visual system of the locust ? Moreover , this proposal assumes that the excitatory and inhibitory inputs to the LGMD respond to high level information about the visual stimulus ( θ′ and θ ) and that the role of the LGMD is to compute a functional multiplication on those . By definition , the functional multiplication attributed to the LGMD heavily depends on having the two above mentioned features reliably computed and delivered to distinct pathways . However , in mathematical terms , there is not a unique combination of input signals to the LGMD that could give rise to the above described firing rate pattern ( eq . 1 ) , and thus , no reason to exclude this possibility . Indeed , our model suggests that this is the case ( Figure 1 , layers C–D right panel ) . Would the LGMD in that case still perform a functional multiplication or just a non-linear mapping of its inputs ? In fact , the putative multiplicative properties of the LGMD have already been a matter of debate [28]–[30] . In this study we approach the above mentioned points from a system and architectural point of view . We evaluate the alternative hypothesis that the non-linear relationship between the responses of the LGMD neuron and the stimuli the organism is exposed to result from the interaction of many neurons in the sensory processing architecture , i . e . it is an emergent non-linearity that is read-out by the LGMD . In particular , we will assess the contribution of each processing layer in the visual processing hierarchy of the locust , how and what information is conveyed to the LGMD , and the resulting integration at the LGMD level . The empirical validation of this alternative hypothesis , however , is currently unpractical since it requires simultaneous in-vivo measurements from large numbers of neurons under well-controlled behavioural conditions . Hence , to assess the validity of our alternative “emergent non-linearity” hypothesis we resort to a computational approach and use a computational model that is consistent with the anatomy and physiology of the locust visual processing hierarchy , including the ommatidia , medulla , lobula , LGMD and the Descending Contra-lateral Movement Detector ( DCMD ) . Using this model we show that all properties of the LGMD neuron that can be described in terms of a local non-linear operation can be explained as emerging from the structure of the network as a whole . Above all , we show that the inputs to the LGMD are directly driven by the stimulus dynamics rather than resulting from a process of segmentation or computation of the speed of the approaching objects . Despite the differences with Gabbiani's et al . model , the model proposed here displays identical responses to its biological counterpart on all standard stimulation protocols reported in the literature . We demonstrate that the emergent non-linear operations are strongly dependent on the details of the synaptic organization of the locust's visual system . In addition , we apply our model to a high-speed mobile vehicle and show that it reliably stabilizes the movement trajectory and robustly avoids collisions . Hence , our model not only suggests that the functional non-linear response properties of the LGMD emerge out of the network as a whole but also shows robust and realistic real-world properties .
The structure of our model consists of four layers that capture the most relevant processes involved in the pathway to the LGMD , and both the output of the LGMD and the population responses for each layer are considered ( Figure 1 ) . We model the photoreceptor layer with Linear Threshold ( LT ) units that are driven by a CCD camera with automatic gain control ( see Experimental Procedures ) ( Figure 1A ) . The lamina is modelled with a centre/surround connectivity that produces an edge enhancement [31] ( Figure 1B ) . Subsequently , neurons in the medulla layer produce onset and offset sensitive responses [13]–[15] ( Figure 1C ) . The connectivity between the medulla and the lobula layer transduces the excitatory input to the LGMD ( Figure 1D ) . Post-synaptic inhibition onto the LGMD is modelled through the integration of the activity of the onset and offset sensitive neurons in the medulla where the summed activity inhibits the excitatory projections onto the LGMD from the second chiasma . The LGMD is modelled as an Integrate and Fire ( I&F ) neuron that integrates the above mentioned excitatory and inhibitory inputs from the medulla and produces spikes ( Figure 1E ) . All neurons in our model are standard leaky I&F or leaky LT neurons [32] , [33] ( see Experimental Procedures for model details and dynamic equations ) . In the context of this study , we present an exhaustive analysis of the responses of our model to a set of standard LGMD stimulation protocols that allow us to validate our model with respect to the biological system . Additionally , the contribution of each neural layer of the model to the LGMD responses' properties is assessed experimentally ( Figure 1A–E ) as well as analytically , and its real-world properties are evaluated using a fast moving robot . In our first experiment we evaluate the model by using a looming stimulus consisting of a solid square with 10 to 21 repetitions performed per each l/|v| pair ( where l stands for the half length of the object and v for its linear velocity ) ( see the Experimental Procedures for further details ) . This ratio determines the time course of the angular size ( θ ) of the looming stimulus in an independent fashion from the actual stimulus properties ( eq . 3 ) . This experiment replicates the protocol used in [17] . Our model of the LGMD displays the typical response of this neuron to an approaching stimulus ( Figure 2A ) ; as the angular size of the retinal projection of the stimulus increases , the firing rate increases , peaks and decays before the collision occurs . This response closely resembles that of the biological data with the multiplicative model ( r = 0 . 98 ) ( Figure 2A , middle panel ) . We observe that the fit of the peak firing rate and the TTC versus the l/|v| ratio is consistent with that observed in the biological system , and is well captured by the multiplicative model that was derived from LGMD recordings ( eq . 1 ) ( Figure 2B ) . The response of the LGMD neuron has been shown to peak when the angular size of the projection of the looming stimuli onto the retina of the insect reaches a specific size , known as the angular threshold [9] , [10] , [16] , [17] , [34] , [35] . Moreover , the time at which the response of the LGMD peaks , that is , when the stimulus reaches the angular threshold , depends linearly on the l/|v| ratio . This reflects a robust detection of the angular threshold over a wide range of l/|v| ratios since the time at which the response of the LGMD peaks is proportional to l/|v| . The linear relationship between TTC of the peak firing rate and the l/|v| ratio is a known property of the LGMD [17] , [18] ( eq . 2 ) , that is reliably replicated by our model ( r>0 . 99 ) ( Figure 2C ) . We propose a specific connectivity for the LGMD pre-synaptic fan-in such that the projections from the medulla to the lobula integrate oriented contrast boundaries ( see Experimental Procedures ) . These projections are retinotopic and integrate the activity of a set of on-off neurons of the medulla that surround its location at distances δx and δy ( surround excitation ) . Consequently , δx and δy define the width and height of the region within which the boundaries of a looming stimulus have to fall in order to achieve maximal excitation , what defines the angular threshold . To further test this aspect of the model , we performed a control experiment in which we varied δx and δy to define a surround receptive field of 25 , 29 and 36 degrees of the camera's field of view . The predicted behaviour of our model is that the changes in δx and δy would affect the angle of the peak firing rate , and therefore the TTC . Indeed , we obtained a change of the slope of the linear regression between the frequency peak and the l/|v| ratio which correlates with the changes in δx and δy; the bigger δx and δy , and hence the angular threshold . The later the LGMD response firing rate reaches its maximum and the flatter the slope is ( Figure 2C ) . In conclusion , our model is consistent with the known properties of the LGMD [9] , [16] , [17] and shows that the response peak is defined by the topology of the projections from the medulla to the LGMD . It was shown that the responses of the LGMD are largely independent of the shape of the stimulus and its texture [17] . In a series of experiments , we assessed whether our model shows similar invariant properties ( Figure 3 ) . To do so , consistent with previous experiments [17] , we used four different shapes . For all stimuli tested , and over the whole range of l/|v| ratios ( from 5ms to 50ms ) , the model's responses show the same linear relationship with the TTC as reported for the biological system , with a correlation coefficient between the model's responses and the regression lines of r>0 . 99 ( Figure 3C ) . The response invariance to the approach angle of looming stimuli is biologically highly relevant in a system that can serve to detect potential predators , as is the LGMD . This reported property of the LGMD was investigated in the last set of experiments . The invariance was assessed by using the same experimental protocol as previously employed , but now aligning the camera at different angular orientations with respect to the projection screen as was reported in [17] . In the following we refer to 0% of the visual field when there is a complete alignment of the camera orientation and screen , and to 100% when the centre of the screen is at the edge of the camera's visual field ( Figure 4B , insertion ) . We found that our LGMD model shows a robust response invariant to the approach angle up to an angle that represents approximately 75% of the visual field ( Figure 4 ) . A one-way ANOVA analysis of the distribution of the model responses revealed that a significant difference in the mean number of spikes only occurs at an angle exceeding 75% of the total visual field of the camera ( approximately 30° ) ( p<0 . 05 ) , i . e . when the stimulus was partially lying outside of the visual field of the camera . Although the fields of view of the locust eye and our camera are not equivalent , yet we have designed it to have a similar angular resolution of 2 . 33° per pixel [36] . Additionally , the fraction of field of view where the response is invariant is comparable to the one of the biological system [16] ( Figure 4A ) . Subsequently , we investigated the linear relationship of the TTC of our LGMD model over a wide range of l/|v| ratios and approach angles . Our results show that the invariance of the response properties can be seen as well in the TTC domain ( Figure 4B ) . Here , the correlation coefficients of the data and its linear regression are above 0 . 9 for both a perfect alignment between the camera and the screen and in case of a misalignment of 75% of the visual field . Thus , even though the activity of the neural model is significantly reduced due to the loss of stimulation by the looming stimulus at a very shallow approach angle ( Figure 4A ) , the intrinsic linear dependence of the TTC with respect to the l/|v| of the LGMD is preserved ( Figure 4B ) . In order to understand better and to be more specific about the nature of the inputs to the LGMD , we propose the use of additional stimulation protocols that can be applied to the locust using currently available experimental technologies . For instance , in the multiplicative model , the firing rate of the LGMD is defined by the product of the angular speed ( θ′ ) and a value related to the object's angular size ( θ ) ( eq . 1 ) . If those two variables were indeed the input to the LGMD , it would imply that for an object that is approaching at a constant angular speed the LGMD should display a completely different time response . In fact , since the angular approaching speed of the stimulus ( θ′ ) would be constant , the predicted output by the multiplicative model would be an exponentially decreasing firing rate . Hence , we explicitly evaluate the different responses between our model for each neural layer and the multiplicative one by using objects that show a uniform increase in size ( Figure 5 , layers A–E left panel ) . We observe that , whereas the multiplicative model displays the expected exponential decreasing response , our emergent non-linearity model still displays a peak at the preferred angular size . This stimulation protocol was previously used by Hatsopoulos et al . showing a response profile consisting of a fast increase of the firing rate , a peak and subsequently followed by a slower decrease of the activity [18] . Although some of the data could eventually be approximated by an exponential function , a more quantitative analysis of the LGMD responses is required in order to find the relationship between stimuli and rising , peak and decay properties of the responses of the LGMD under this protocol . Additionally , we see that the predicted excitatory input to the LGMD with our model differs from the constant factor predicted by the multiplicative fit ( Figure 5 , layer D left panel ) . Thus , a further examination of the LGMD responses under this protocol is essential to unveil what the real input to the LGMD is , and therefore to understand whether it computes a product of the object's angular size ( θ ) and angular speed ( θ′ ) or responds to a different processing as suggested by our results . Next , we analyze the activity of each layer of our model to identify the relationship between receding stimuli and the intensity of the LGMD response ( Figure 5 , layers A–E right panel ) . The responses are consistent with a number of experiments of stimulus selectivity of the LGMD that showed a preference for looming stimuli and its diminished response to receding ones [11] , [12] , [35] . Two hypothetical peaks in the TTC curve to receding stimulus are predicted depending on the weighting of the post-synaptic inhibition ( Figure 5 , right panel ) . We show that the specific amplitude-time course of this response depends on the gain of the inhibitory projections onto the LGMD . So far we have shown that we can account for all known aspects of the responses of the LGMD neuron to looming stimuli with a model that relies on the transformations performed in the complete pathway from the photoreceptors to the LGMD as opposed to a local multiplication . We now want to assess the behavioural validity of our model by applying it to a high-speed impeller driven based robot called “Strider” . Given its structure , the Strider is highly sensitive to inertia and friction forces , yet it delivers high-speeds . For the robot to be sensitive to shallow approach angles , its camera was equipped with a wide angle lens ( 190 deg . field of view ) . Although the aim of the robot is to have dynamics comparable to that of a flying insect , our robot has longer reaction times due to its increased mass , i . e . it operates at a higher Reynolds number than a flying insect . We therefore use a course stabilization system to guarantee that the robot is able to follow straight trajectories . This course stabilization system is based on the fly's Elementary Motion Detectors ( EMD ) and uses directional motion information from the visual input to correct for drifts , and has been previously deployed on flying vehicles [37] . The real-world behavioural task of the robot is to drive forward on a straight course until an imminent collision is detected . The modelled LGMD neuron will detect this upcoming collision and induce a collision avoidance reaction that consists of two phases: first deceleration of the robot , and then change of heading direction . To deal with the inertia of the robot , the braking manoeuvre is realized by driving the impellers backwards at full speed for one second . The change in heading direction is achieved by a turn-in-place manoeuvre of 1 . 25s duration . The LGMD model reports the detection of an imminent collision when its firing rate exceeds a specific threshold , and will trigger avoidance actions until its firing rate decreases below the above mentioned threshold value . The following analysis is based on 16 experiments in a confined environment of 3 . 5 by 4 . 5 meters that lasted approximately 3 minutes each , where both course stabilization and collision avoidance systems were active . Additionally , we performed 5 control experiments where the LGMD neuron model was active but the course stabilization system was disabled . The experimental results confirm the necessity of a course stabilization system: when the robot is solely controlled by the LGMD model it displayed an erratic behaviour dominated by multiple loops in either one direction or the other ( Figure 6A , right panel ) . When the LGMD model is combined with the EMD-based course stabilization system , the robot exhibited longer periods of translation exploring a larger area , and had a less variable heading direction ( Figure 6A , polar plots ) . The nearly uniform distribution of the variation of the heading direction during the control experiments ( Figure 6A , right panel polar histogram ) is the result of the continuous changes that result from the complex dynamics of the Strider robot . When both the LGMD model and the course stabilization system were combined , this distribution was significantly different and reduced to a few preferred heading directions ( Figure 6A , left panel polar histogram ) ( p<0 . 01 , Kolmogorov-Smirnov ) . To further demonstrate the effect of the course stabilization system in the control of the behaviour of the robot , a linear segmental fitting of the behavioural traces , consisting of finding a sequence of linear segments that keep the Mean Square Error ( MSE ) of the fit below a threshold value , was performed ( Figure 6A ) . This measure allows quantifying the straightness of the trajectory . That is , the longer the segments are on average , the straighter the overall trajectories are ( Figure 6D ) . In order to assess the dependency of the fit upon the threshold value , different threshold values were tested . All tested values yielded comparable results . Although it is not the objective of this study to evaluate our course stabilization model , these data serve to illustrate the complex dynamics of the Strider robot . A statistical analysis of the segment length distribution ( two-sample Kolmogorov-Smirnov ) showed that in case of the combined system , the distributions of the linear segments were significantly different ( p<0 . 01 ) . Longer segments and a higher variance were obtained for the combined system ( Figure 6D ) ; concluding that the stabilization system contributes significantly to the straightness of the trajectory . Therefore , the course stabilization system we included is an essential component in order to deal with the dynamics of the Strider , and allows us to perform and evaluate the collision avoidance task with a high-speed robot . To evaluate the performance of the LGMD component of the robot system , all collision detections were classified into three groups: correctly detected , false negatives ( missed ) , and false positives . These data have to be read in the context of this fast moving robot , that on average detects a collision 0 . 5m away from a wall while moving at a mean speed of 1 . 2m/s . Hence , if the robot does not dramatically change its speed at the moment of detection , it collides in less than half a second . Collisions detected 20–100cm away from the walls were considered as correct , while all collisions detected closer than 20cm from the wall were considered to be detected too late , and thus missed ( false negative ) . Conversely , collisions detected farther than 100cm from the walls , were considered false positives ( Figure 6A , grey dashed region ) . In total , 87 . 8% of the detections were correct , 4 . 9% were false positives and 7 . 3% were missed ( Figure 6B ) . The distribution of the number of detections vs . the distance to the wall at the time of detection peaked at 0 . 5m , and decreased exponentially further away from the wall ( Figure 6C ) . Thus , the behaviour of the robot directly results from the non-linear nature of the response of the LGMD model ( Figure 2 ) . Since the responses of the DCMD neuron feed directly into the thoracic motor ganglia of the locust that control the wing muscles , this seems to suggest that the amplitude-time course of the LGMD defines a particular collision avoidance strategy that minimizes the number of false positives as the distance to objects increases . In conclusion , these behavioural experiments suggest that the exponential transfer function of the LGMD neuron [9] is more related to its role in the regulation of behaviour rather than to the computation of object approach per se .
The question whether neurons can perform non-linear operations is of great relevance to answer what computations neuronal systems can be expected to perform . It has been argued , on the basis of the physiology of the LGMD neuron , that these neurons can perform a multiplication of high-level features of visual stimuli in order to detect pending collisions [9] , [10] , [16]–[18] . Gabbiani et al . proposed a model that provides for an excellent fit of the LGMD responses to looming stimuli , and as such constitutes a useful benchmark for any model of the LGMD . Using a biologically constrained model of the locust visual system , we have demonstrated that an alternative interpretation can not be excluded . In this alternative view , the local non-linear transfer function of the LGMD neuron can be accounted for in terms of the physiological and anatomical properties of its afferent visual processing hierarchy . We tested our model using simulated analogues of the locust experiments reported in the literature and assessed the real-world validity of our model using a high-speed robot . We showed that our model is able to account for all reported properties of the LGMD neuron without assuming any non-linearities other than thresholding that is intrinsic to standard leaky I&F and leaky LT neural models [32] , [33] ( see Materials and Methods ) . Consistent with our model , recent findings support the existence of a retinotopic mapping of the LGMD pre-synaptic network and suggest that a topographic map would be used to magnify the dendritic sampling of the acute zone [38] . Our model proposes an alternative view that suggests that a non-linear transfer function between stimulus and response can emerge out of the interaction of many distributed neuronal operations and their specific mapping through synaptic topologies . Moreover , our simulations show that the computation of angular speed and angular size pre-synaptic to the LGMD is not necessary to explain its properties . It has been reported that the LGMD shows an exponential relationship between the membrane potential and the firing frequency [9] , [17] . Such properties are standard to integrate and fire neurons and can be explained in terms of their sigmoid transfer function [39] . As such , we believe that the LGMD has a similar transfer function and we have included it in our model . Additionally , our experiments reveal that this non-linear transfer function does not play a significant computational role in the detection of a collision , but rather that it shapes the LGMD response with respect to the behaviour requirements of collision avoidance , as demonstrated with our robot experiments . In our analysis we have presented a plausible model of how motion selective responses can arise from the interaction between on-set and off-set sensitive neurons . The idea of having selective motion detection via delayed on-off interactions has been previously used to model visual motion-selective neurons in the mammalian neocortex [40] . The analysis of our “emergent non-linearity” hypothesis shows that the non-linear responses of the LGMD are caused mainly by the particular connectivity through the second chiasma and the parameters of the neurons in the network . It is the contribution of the restricted and local non-linearities in the medulla and structures pre-synaptic to the LGMD that give rise to the non-linear responses of our model . This mechanism is akin to the way a multilayer perceptron can approximate any continuous function with an arbitrary accuracy based on a distributed set of non-linearities [41]–[43] . Nonetheless , ours is not the first connectionist model proposed to explain the responses of the LGMD neuron to visual stimuli . In fact , Rind and Bramwell proposed a model that accounts for the looming sensitivity and selectivity when stimulated with approaching , translating or receding objects over a decade ago [44] . Consistent with ours , Rind and Bramwell's model is a feed-forward model with transient detectors ( on and off-set sensitive neurons ) and a feed-forward inhibition that brings the LGMD activity back to baseline . Moreover , Rind and Bramwell's model has been successfully applied to mobile robots [23]–[25] , [45] . Although the model has been shown to provide a similar functionality to that of its biological counterpart , there are a number of aspects of LGMD computation that it does not account for since this model was proposed before many of the properties of the LGMD were unveiled . Thus , it does not address aspects such as the emergence of the angular threshold or the non-linear responses of the biological LGMD with respect to the specific properties of the visual stimulus ( angular size and angular velocity ) . Our model goes a step beyond Rind's model , making clear anatomical predictions on how the specific properties of the LGMD arise and showing that a non-linear interaction in the form of a multiplication between stimulus' angular size and velocity is not required to account for the known properties of the LGMD neuron . In our predictions , we test new stimulation protocols that would help us to better understand the functional aspects of the LGMD encoding of visual stimuli . We have considered other possible , and probably simpler , explanations of the responses of the LGMD such as the idea that all the non-linear behaviours of this neuron could be driven directly by the input dynamics ( see Text S1 for further details ) . Interestingly , as proposed by Rind and Simmons [11] , the second derivative of the size of the looming stimulus displays a very similar time course to the actual LGMD responses . However , the second derivative model is unable to explain the invariance of the LGMD response since can not guarantee that the peak firing rate does always occur at the same angular size of the object ( Figure S1 ) . Although this stimulus dynamics based explanation cannot account for all the known LGMD properties , it does provide an alternative approach to explaining the LGMD response dynamics . To understand to what extent a direct linear mapping between input and output would suffice to explain the LGMD responses , a multivariate Least Squares linear regression method was used to fit our model's responses to a sequence of raw input images of an approaching object ( Figure S1 ) . This linear input-output mapping is indeed able to reproduce the responses of our LGMD model , as well as of its biological counterpart . Yet , as a linear mapping is not able to capture directional motion information , it fails to predict our model's responses when it was tested against receding stimuli . These two observations strongly suggest that the standard stimulation protocol used to study the LGMD neuron is under-constraint , and yields results that are insufficient to fully understand the input-output transformations it performs . In fact , what is needed are new stimulation protocols that independently manipulate both angular size and speed under different conditions – as in the linearly increasing object case – to demonstrate that the LGMD does compute the product of angular speed and size . Though some steps have been undertaken to investigate new stimulation protocols such as multiple simultaneously approaching objects , they do not capture all functional aspects of LGMD encoding of visual stimuli [31] , [32] , [41] , [42] . Some of the stimulation protocols that we propose have recently been used in the context of the behavioral responses of the Locust to approaching predator like objects . In particular , the behavioral responses to looming and uniformly increasing angular size stimuli were studied when triggering an escape response [46] . In this study it was found that a hindleg flexion reaction ( cocking ) always occurred with a fixed delay after the stimulus reached a fixed angular size , independent of speed and type of approach of the stimulus . Moreover , the timing of this behavioral reaction changes in a linear fashion with the l/|v| ratio , as does the peak of the firing rate in the LGMD ( Figure 2C , Figure 3 ) . Nonetheless , there seems to be a discrepancy between these findings and the ones reported by [47] , where this relationship was not found . If correct , the findings of Santer et al . would be consistent with the fact that the LGMD fires maximally when the stimulus reaches the angular threshold and thus with our predictions ( see Results section ) . However , according to Gabbiani's model [18] , the LGMD would not show a peak in its firing rate for uniformly expanding objects ( Figure 5 ) . Interestingly , sectioning the contralateral nerve cord ( the stimulated DCMD ) did not prevent cocking from occurring , but it just increased its variability [46] . Thus , there seem to be other parallel mechanisms that also contribute to this visually mediated behavioral response . These results seem to suggest that the role of the LGMD in this context is more related to timing of the escape action rather than the selection or execution of it . Although there are valuable data on different stimulation protocols , there remains the need for a more detailed quantification if we want to pinpoint the underlying principle that gives rise to the non-linear responses of the LGMD . Specifically , to assess how the different parameters of different stimulation protocols ( angular size and angular velocity ) do affect the shape of the responses of the LGMD ( the timing of the peak firing rate , the slope of the rising and declining phases , etc ) . We have used our model to make functional , structural and testable predictions of the response of the LGMD . These predictions can help to explain the sub-linear behaviour found by Krapp and Gabbiani [48] when mapping the LGMD sensitivity to local motion stimuli , as well as aid in explaining the functional role of the post-synaptic inhibition . Recently , picrotoxin , a chloride channel blocker , was used to investigate the functional contribution of the feed-forward inhibition to the LGMD [35] . The main conclusion of that study was that the feed-forward inhibition contributes actively to the termination of the LGMD response to looming objects . This post-synaptic inhibition increases in an approximately exponential manner as the stimulus expands , and it is followed by a fast decay . These results are consistent and match the behaviour observed in our model . Yet , recent research has shown that other mechanisms can not be disregarded , such as spike frequency adaptation or synaptic plasticity , which can further contribute to the sharpening of the looming selectivity of the LGMD neuron [34] , [39] . Finally , we implemented the LGMD model in the context of a behavioural robot experiment that demonstrates the reliability of the system to detect imminent collisions on a high-speed and inertial robot system . It has been shown that high frequency spikes of the LGMD are involved in triggering escape manoeuvres to lateral looming predators [50] . The responses of the LGMD have been shown to be correlated with cocking behavior [46] , and to be sufficient to trigger gliding behavior [50] . Contrary to gliding , cocking is not necessarily triggered by the LGMD responses in isolation [46] . In fact , gliding has been shown to be triggered when the spikes of the DCMD summate significantly in the MN84 neuron , the second tergosternal flight motor neuron [50] . In this case the timing of the gliding responses is not directly related to the angular size of the visual stimulus , as in the case of cocking , but to high frequency activity ( >150Hz ) produced by the LGMD neuron . The difference between relying on the angular size of the approaching object or on high frequency activity from the LGMD supports the notion that gliding is triggered as a “last resort” when the other existing mechanisms to evade a thread fail [51] , [52] . In the case of our high-speed robot experiments we have used a very similar approach to what occurs in gliding . That is , the robot only triggers an avoidance reaction when the responses of the LGMD summate over a threshold in a motor neuron responsible for the avoidance reactions ( see Robot Experiments section ) . Furthermore , our experiments show that the exponential transfer function of the LGMD could play an important role in minimizing the probability of false positive detection at long distances from obstacles without compromising the performance of the system . We thus propose that the exponential Vm to firing rate mapping of the LGMD may more be related to its role in the regulation of behaviour than to its putative computational role in input processing .
The rate of expansion of an approaching object of half length l with velocity v was reproduced by a simulated looming stimulus . Any object approaching at a constant speed shows a typical slow angular speed that rapidly increases as it gets closer to the camera . The angular size of this approaching object can be described as a function of l and v , where l is the half-size of the object length and v its linear velocity . ( 3 ) Consistent with previous studies ( Gabbiani et al . , 2002; Gabbiani et al . , 1999; Gabbiani et al . , 2001 ) , looming stimuli with l/|v| ratios that range from 5 to 50ms , with a 5ms step size , were used , with 10 to 21 repetitions for each stimulation condition . Using these stimuli we have assessed the relationship between the responses of the model LGMD and stimulus properties , including the relationship between the TTC and the l/|v| ratio and the invariance of the angular threshold of the LGMD response over the whole range of l/|v| ratios used . In these experiments the stimuli are presented as a solid shape ( square ) and the centre of the screen is aligned with the centre of the camera in both azimuth and elevation . Subsequently , we performed a set of measurements in order to establish the dependence of the LGMD response on the shape and texture of the stimulus using stimuli reported in the literature: a solid square , a solid circle , a square with a checkerboard pattern and a square with a pattern consisting of concentric squares [17] . Finally , we investigated the invariance of the responses of the LGMD model to the approach angle considering presentation angles of stimuli corresponding to 0% , 33% , 55% , and 75% of the visual field of the camera , where 0% represents the alignment of the camera with the screen , and at 100% the looming stimulus lies outside of the visual field of the CCD camera . A high-end CCD camera ( EVI-D31 , Sony Corp . , Japan ) placed 10cm in front of the screen was used as input to our model . The camera was positioned such that its image covered the complete display , resulting in a visual field size of 74 . 65°H×56 . 25°V . To present the looming stimuli , a LCD screen with a resolution of 800×600 pixels was used . The spatial resolution of the screen ( 0 . 019cm per pixel ) corresponds to an angular resolution of 0 . 0933° per pixel . The highest luminance ( LHigh ) value reported by our video acquisition system ( mean of value for the RGB color channels ) was defined as 255 and the lowest as 0 ( LLow ) on a 0 to 255 scale . The stimuli were generated with an ideal luminance contrast of infinity , where CR = 1 indicates no contrast . The acquisition rate of the camera was 25Hz ( PAL ) and the refresh-rate of the LCD monitor was set to 60Hz . For the purpose of the simulations presented here , the system was not required to run in real-time . Thus , we simulated a processing power of 100 images per second for our model . For the acquisition , we approximated a uniformly distributed compound eye of 32×24 ommatidia/photoreceptors . This is obtained by sub-sampling the image that is acquired from the camera , making the step size increase of the looming stimulus negligible . The resulting angular resolution corresponds to 2 . 33° per pixel , a good match to the real photoreceptor acceptance angle of the locust which is close to 1 . 5° in light conditions and 2 . 5° when dark adapted [36] . We evaluated the behavioural implications of our model using a ball caster based robot platform called “Strider” , specifically designed to have low frictional forces with the surface and that uses a propulsion system that allows it to deliver high-speeds , with the advantage of a low deployment and maintenance effort ( Figure 7 , left panel ) . The Strider is about 16cm long and it is equipped with three passive wheels ( ball casters ) ( Euro Unit 15mm , AlwayseEngineering Ltd , United Kingdom ) , and propelled by two ducted fans ( GW/EDF-50 , Grand Wing Servo-tech Co . , Ltd . , Taiwan ) . The base platform on which the wheels are mounted connects to the upper part via a servo ( Microservo FS 500 MG , Robbe Modellsport GmbH & Co , Germany ) , allowing the robot to turn in place , a task difficult to achieve with ducted fans alone . The lift-strength of one ducted fans is 30g , allowing the robot to move at a maximum speed of about 3m/s which corresponds to 19 body lengths per second . Similarly , the locust displays a free flight speed of about 4m/s [53] . Two separate lithium-polymer batteries ( t-technik , Germany ) are used as independent power-supplies for controller-board and sensors , and motors respectively . The total weight of the robot is 280g . A Bluetooth® link is used to send control signals to the motors of the robot and to read sensor states from the robot . The robot carries a wireless camera ( 1 . 2GHz Mini Wireless Camera Kit , ZTV Technology Co . , Ltd , China ) with a 190° wide-angle lens . The robot experiments were performed in a 3×4m arena ( Figure 7 , right panel ) . The walls of the arena ( 0 . 5m high ) were covered with random textures consisting of vertical and horizontal stripes to provide the robot with visual cues . The behavioural data was acquired in real-time with a custom-built general purpose video tracking system called “AnTS” developed by the authors . The AnTS tracking system receives its input from a B/W CCIR camera ( CSB-465C , Pacific Corporation , Japan ) with a wide-angle lens fixed on a 2 . 2m high tripod . To obtain an undistorted planar view of the arena , correction algorithms for perspective and wide-angle lens distortions were built into the AnTS tracking software . As a compromise between sampling frequency and spatial accuracy , a QVGA image resolution ( 320×240 pixels ) was used; this resulted in a spatial resolution of 1 . 56cm for the 3×4m arena and an update frequency of 35Hz . The behavioural data recorded with AnTS was acquired synchronously with the states of the model of the locust visual system ( see below ) . Two standard neuron types are used in these simulation experiments: Leaky Integrate & Fire ( I&F ) and leaky Linear Threshold ( LT ) neurons [32] , [33] . Both neuron models are equivalent to a circuit built from a capacitor C and a resistor R connected in parallel to ground on one end and driven by current on the other end [39]: ( 4 ) For a constant input current the voltage is defined by: ( 5 ) The voltage at the membrane of both neural models will increase asymptotically to . While the voltage is below the firing threshold ( ) the neuron remains silent , and once is reached the neuron's output is equal to the membrane potential in the case of LT , or it produces an action potential ( spike ) and resets the membrane voltage to zero in the case of the I&F . The charging time constant of the membrane potential is defined as . Our model captures the basic processes found in the locust visual system and can be divided into three sequential processing steps ( Figure 1 ) . First , the centre-excitation/surround-inhibition connectivity among the signals received from the photoreceptors in the lamina layer that provides an edge enhancement [31] . Second , the interaction of neurons in the medulla layer yields onset and offset sensitive responses [13]–[15] . Third , the lobula layer provides a specific connectivity that contributes to the transformation of the onset/offset signals into the response of the LGMD . Our model is structured exclusively with leaky Integrate and Fire ( I&F ) and leaky Linear Threshold ( LT ) neurons ( see Experimental Procedures for the dynamic equations ) and implements the three layers described above . An edge enhancement on the input image is achieved via a centre-excitation/surround-inhibition connectivity from the photoreceptors to the lamina layer , modelled as LT neurons . Our model implements onset and offset responses of the medulla by combining the activity of one excitatory and one inhibitory neuron with the same visual sensitivities from the lamina onto a common third neuron , where the inhibition is time delayed relative to the excitation in case of onset detection , and time advanced relative to the excitation in case of offset detection ( Figure 8 ) . When we assume that a transition of activity in the receptive fields of the on and off neurons is a moving edge , there exists a unique arrangement of on and off cells with a combined response that is maximal whenever the moving edge is being displaced in a specific direction , i . e . neighbouring cells placed along the movement axis , where a first offset sensitive cell and a second onset sensitive cell synapse onto a common neuron . The post-synaptic neuron is maximally excited only when both pre-synaptic cells are active at the same time , i . e . when an offset and an onset stimulus coincide . Hence , the only situation that can provoke this kind of response is a moving edge passing out of the off cell's receptive field , generating an offset event , to the receptive field of the on cell , generating an onset response . Therefore , as outlined above , a pair-wise combination of on and off transient detectors can encode for directionally selective motion pre-synaptic to the LGMD . This neuronal processing structure is consistent with our knowledge of the pre-synaptic structure of the LGMD since the 1970s [13]–[15] . One of the most important and most studied properties of the LGMD is related to the angular threshold ( θthreshold ) , which is defined as the angular size of a looming object for which the LGMD produces the maximal firing rate . It has been shown that there is a constant relationship between the peak firing rate of the response of this neuron and the angular size of the looming stimulus , independent of the approach speed and angle , object shape , texture and contrast [9] , [16] , [17] . To account for the angular threshold properties ( θthreshold ) we propose a specific connectivity between the on-off cell ensembles onto the LGMD , referred to as the LGMD pre-synaptic fan ( Figure 9 ) . It is central to our hypothesis that the projections from the medulla to the lobula are such that the excitation on the target cells is maximal when the collection of detected oriented contrast boundaries reach a specific size . The LT neurons connecting the medulla with the LGMD through the second chiasma collect the activity of a set of surrounding on-off neurons in the medulla with a particular directional selectivity at distances δx and δy ( Figure 9 ) . These LT neurons have lateral interactions with the neighbouring cells via a lateral excitation that spreads and smoothes their activity over the pre-synaptic excitatory fan of the LGMD ( Figure 9A ) . The δx and δy define the width and height of the connectivity where the expanding boundaries of a looming stimulus lie to maximally excite that post-synaptic neuron . This connectivity pattern is applied to each of the neurons that mediate the excitatory pathway to the LGMD across the second chiasma and receive input from the onset/offset sensitive cells . These neurons will concentrate a spot of high activity for looming stimuli approaching the angular threshold size whereas a sparse distribution of activity will occur for other stimuli ( receding , translating , etc ) ( Figure 9B ) . It is now possible to define the exact values of δx and δy that make the LGMD maximally excited for a given object angular size and excited below maximum otherwise . The accuracy with which we can define the angular threshold is given by the resolution of our model , being ±2 • acceptance angle of one pixel ( approximately ±5° ) . In our implementation of the model , only four type of ensembles of on and off neurons with different directional sensitivities were used ( Figure 9A ) . By means of a thresholding mechanism , the LT neurons that cross the second chiasma respond only when a number of the surrounding ( δx and δy ) pre-synaptic motion sensitive ensembles detect expanding moving edges . Hence , by looking at the neural activity of this layer of neurons it is possible to extract the position of the looming stimulus in the visual field ( Figure 9B ) . Subsequently , the spatial integration by the LGMD pre-synaptic fan of those responses discards the position information , and in this way introduces the important property of response invariance to object position and approach angle . The structure of the feed-forward network up to this point supports the consistency and invariance of the angular threshold ( θthreshold ) , i . e . the independency of the approach angle , position inside the visual field , object shape and looming speed . In the last processing stage , the LGMD receives a post-synaptic inhibition from the activity of the on-off neurons in the medulla ( Figure 8 ) . The role of this inhibition is to bring the LGMD neuron's activity back to baseline after the looming object reaches the angular threshold size . For the data analysis , a Gaussian smoothing filter with a window size of 20ms was applied to our raw data , consistent with previous LGMD studies [9] . The membrane potential of the LGMD was computed in the simulation while the used Vm/F transfer function of the LGMD neuron is consistent with the one reported in the literature [16] , [17] . A one-way ANOVA analysis was used to evaluate significant differences between the data sets obtained during the experiments . The simulations were performed on a 2GHz Pentium4 personal computer ( Intel , Santa Clara , USA ) under the Linux operating system . The neural simulation software iqr , an open source simulation software ( iqr . souceforge . net ) , was chosen for the implementation and evaluation of the neural model , including the robot experiments [54] . All creation of visual stimuli was performed using openCV ( the Open Source Computer Vision library , Intel , Palo Alto , USA ) while the analysis was performed using Matlab ( Mathworks , Natick , Massachusetts , USA ) . | The tiny brains of insects of about 1mm3 smoothly control a flying platform while avoiding obstacles , regulating its distance to objects and search for objects of interest . This is largely achieved through a complex hierarchical processing of signals from the multitude of ommatidia in their eye to a set of highly specialized neurons that are optimized to respond to specific properties of the visual world . One of these neurons , the Lobula Giant Movement Detector ( LGMD ) of the locust , has been recently shown to perform a functional multiplication of its synaptic inputs . If true , that would make the LGMD neuron a unique and highly sophisticated neuron that raises questions about the non-linear operations other neurons in other neuronal systems would be able to perform . Hence it is crucial to understand its properties , its role in behaviour and to evaluate whether its responses can be explained in simpler terms . Our results emphasize the role of network architecture and distributed computation as opposed to local complex non-linear computation . We show that our model reliably reproduces the known properties of the LGMD and can be used to control a high-speed robot . | [
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"theory"... | 2010 | Non-Linear Neuronal Responses as an Emergent Property of Afferent Networks: A Case Study of the Locust Lobula Giant Movement Detector |
Leprosy is a chronic infectious disease that is caused by the obligate intracellular pathogen Mycobacterium leprae ( M . leprae ) , which is the leading cause of all non-traumatic peripheral neuropathies worldwide . Although both myelinating and non-myelinating Schwann cells are infected by M . leprae in patients with lepromatous leprosy , M . leprae preferentially invades the non-myelinating Schwann cells . However , the effect of M . leprae infection on non-myelinating Schwann cells has not been elucidated . Lipid droplets ( LDs ) are found in M . leprae-infected Schwann cells in the nerve biopsies of lepromatous leprosy patients . M . leprae-induced LD formation favors intracellular M . leprae survival in primary Schwann cells and in a myelinating Schwann cell line referred to as ST88-14 . In the current study , we initially characterized SW-10 cells and investigated the effects of LDs on M . leprae-infected SW-10 cells , which are non-myelinating Schwann cells . SW-10 cells express S100 , a marker for cells from the neural crest , and NGFR p75 , a marker for immature or non-myelinating Schwann cells . SW-10 cells , however , do not express myelin basic protein ( MBP ) , a marker for myelinating Schwann cells , and myelin protein zero ( MPZ ) , a marker for precursor , immature , or myelinating Schwann cells , all of which suggests that SW-10 cells are non-myelinating Schwann cells . In addition , SW-10 cells have phagocytic activity and can be infected with M . leprae . Infection with M . leprae induces the formation of LDs . Furthermore , inhibiting the formation of M . leprae-induced LD enhances the maturation of phagosomes containing live M . leprae and decreases the ATP content in the M . leprae found in SW-10 cells . These facts suggest that LD formation by M . leprae favors intracellular M . leprae survival in SW-10 cells , which leads to the logical conclusion that M . leprae-infected SW-10 cells can be a new model for investigating the interaction of M . leprae with non-myelinating Schwann cells .
Leprosy is a chronic infectious disease that is caused by the obligate intracellular pathogen Mycobacterium leprae ( M . leprae ) . Although the introduction of multidrug therapy ( MDT ) to leprosy program in 1982 resulted in a significant reduction in the prevalence of the disease , 210 , 758 new leprosy cases were detected globally in 2014 [1] . Leprosy is the leading cause of all non-traumatic peripheral neuropathies worldwide . M . leprae almost exclusively infects macrophages and Schwann cells . The Schwann cells , the principal glial cells of the peripheral nervous system , provide support and nutrition to the axons of neurons and are a major target of M . leprae . Physical contact of M . leprae to Schwann cells and immune reactions against either M . leprae or the infected cells damage the peripheral nerves , which results in a demyelination of the peripheral nerve fibers , and leads to irreversible nerve damage [2–5] . Depending on the level of cellular immune response , infection with M . leprae shows a diverse clinical spectrum . At one end of the spectrum , tuberculoid leprosy , a paucibacillary type , is characterized by a well-formed granuloma and a strong T-cell immune response to M . leprae . At the opposite end of the spectrum , lepromatous leprosy , a multibacillary type , is characterized by extensive bacterial multiplication within host cells and a low cell-mediated immune response to M . leprae [6 , 7] . Foamy or lipid-laden macrophages are also a hallmark of lepromatous leprosy and are referred to as Virchow or Lepra cells [8] . The lipids , which accumulate in M . leprae-infected macrophages in lepromatous leprosy lesions , are composed of host-derived oxidized phospholipids , fatty acids , and cholesterol [9 , 10] , and are organized in cytoplasmic organelles known as lipid droplets ( LDs ) that are not bound to a membrane [11] . The LDs are also found in M . leprae-infected Schwann cells in nerve biopsies from lepromatous leprosy patients [12 , 13] . In addition , Mattos et al . [12 , 13] reported that inhibition of M . leprae-induced LD formation decreased the viability of M . leprae in primary Schwann cells , suggesting that M . leprae-induced LD formation favors intracellular M . leprae survival in Schwann cells . However , the authors did not define whether the primary Schwann cells used in their studies were myelinating or non-myelinating . There are two types of Schwann cells: myelinating and non-myelinating cells . Myelinating Schwann cells wrap around the axons of motor and sensory neurons to form a myelin sheath . Non-myelinating Schwann cells each surround several small diameter axons , ensheathing each in a pocket of cytoplasm . Although demyelination is the ultimate consequence of leprosy neuritis , non-myelinated fibers are also injured in leprosy [14] . M . leprae infects both myelinating and non-myelinating Schwann cells in patients with lepromatous leprosy [15 , 16] . In addition , Rambukkana et al . [4] have reported that , compared with myelinating Schwann cells , the non-myelinating Schwann cell is more susceptible to M . leprae invasion and preferentially harbor M . leprae , which suggests that non-myelinating Schwann cells are a natural shelter for the multiplication of M . leprae . The effect of M . leprae infection on non-myelinating Schwann cells , however , has never been elucidated in an in vitro infection model . Previous studies that investigated M . leprae–Schwann cell interactions have been performed mainly in primary Schwann cells or in myelinating Schwann cell lines , such as with ST88-14 cells . Thus , we needed a non-myelinating Schwann cell line as an in vitro model for investigating the interaction of M . leprae with Schwann cells , since it is difficult to get enough primary non-myelinating Schwann cells from peripheral nerves to perform the experiments . We found that SW-10 cells , mouse immortalized Schwann cells , express S100 , a marker for cells from the neural crest , but neither myelin basic protein ( MBP ) , a marker for myelinating Schwann cells , nor myelin protein zero ( MPZ ) , a marker for precursor , immature , or myelinating Schwann cells [17] . Thus , we thought that M . leprae-infected SW-10 cells could be used as a new model to investigate the interactions of M . leprae with non-myelinating Schwann cells . In the current study , we investigated the effects of LDs on M . leprae-infected non-myelinating Schwann cells . We initially characterized SW-10 cells by examining their expression of molecules , which is classically associated with myelin and Schwann cells . We then assessed the effects of LD formation by M . leprae on the maturation of phagosomes containing M . leprae and on M . leprae survival in non-myelinating Schwann cells .
All experimental procedures were examined and approved by the Animal Research Ethics Committee of the Catholic University of Korea ( CUMC-2016-0058-02 ) , in conformity with the National Institutes of Health Guidelines . C75 , Celecoxib , Hoechst 333342 , Staurosporine and Auramine O were obtained from Sigma-Aldrich Co . Ltd . ( St . Louis , MO ) . Latex beads were obtained from Polysciences ( Warrington , PA ) . C75 and Celecoxib were dissolved in DMSO . Antibodies against S100 , myelin basic protein ( MBP ) , and myelin protein zero ( MPZ ) were obtained from Abcam ( Cambridge , MA ) . Antibodies against nerve growth factor receptor ( NGFR ) p75 , adipose differentiation-related protein ( ADRP ) , active caspase-3 , and β-actin were obtained from Millipore ( Billerica , MA ) , Fitzgerald ( Acton , MA ) , Cell Signaling ( Danvers , MA ) , and Santa Cruz Biotechnology ( Santa Cruz , CA ) , respectively . Cy3-conjugated secondary antibody , Cy5-conjugated secondary antibody , and horseradish peroxidase-conjugated secondary antibody were obtained from Jackson ImmunoResearch ( West Grove , PA ) . BALB/c nude mice were obtained from Orient Bio ( Seong Nam , Gyunggi-do , Korea ) and maintained under specific pathogen-free conditions at the Department of Laboratory Animals , the Catholic University of Korea . Standard mouse chow ( Ralston Purina , St Louis , MO ) and water were provided ad libitum . The foot-pads of M . leprae-infected BALB/c nude mice were treated with potadine solution and washed with ice-cold DPBS to remove exogenous contamination . The foot-pads were excised , cut into small pieces , and ground with a MACs isolator ( Miltenyl Biotec , Teterow , Germany ) . The extract was filtered using a cell strainer ( BD Falcon , Durham , NC ) to remove tissue debris and centrifuged at 3 , 000 rpm ( Rotanta 460R , Hettich , Japan ) for 25 min at 4°C . The pellet was resuspended in 1 ml of ice-cold DPBS and treated with 2 N sodium hydroxide for 5 min . Adding 13 ml of ice-cold DPBS neutralized the reaction . After centrifugation and resuspension , acid-fast staining was performed and the number of bacteria was counted under an oil immersion field of light microscopy using a procedure established by Shepard and McRae [18] . The SW-10 ( CRL-2766 ) , a mouse neuronal Schwann cell line , was acquired from ATCC ( Manassas , VA ) and grown as described previously [17] . The cells were cultured in DMEM ( Biowest , Lane Riverside , MO ) supplemented with 10% fetal bovine serum ( Biowest ) and antibiotics ( Gibco , Grand Island , NY ) . For immunostaining , the cells were fixed in 4% paraformaldehyde in PBS . The fixed cells were rinsed with PBS and incubated in blocking solution ( 5% goat serum and 0 . 001% Tween-20 in TBS ) for 20 min . The cells were then incubated overnight with antibody against NGFR p75 , S100 , MBP , MPZ or active caspase-3 in an incubation solution ( 5% goat serum and 0 . 1% Tween-20 in TBS ) at 4°C . After washing with PBS , the cells were incubated with a rabbit Cy5- or a rat Cy5-conjugated secondary antibody at room temperature for 2 h . Nuclei were counterstained for 15 min with 10 μM Hoechst 33342 ( Sigma-Aldrich Co . Ltd ) . The negative control was processed without the presence of the primary antibody . Immunofluorescence was visualized by confocal microscope ( LSM 500 Meta , Zeiss , Germany ) . The SW-10 cells were plated in 96-well plates and pretreated with Cytochalasin D , an inhibitor of actin polymerization , at the designated concentration for 1 h . The cells were incubated with pre-labeled Zymosan ( 1x106 particles ) for 2 h . The amount of engulfed Zymosan particles was determined using the CytoSelect 96-well phagocytosis Zymosan Colorimetric assay ( Cell Biolabs , SanDiego , CA ) . The absorbance was measured by 405 nm in a μQuant Universal Microplate Spectrophotometer ( Bio-Tek , Winooski , VT ) . The SW-10 cells were cultured on coverslide in a 6-well plate . The cells were infected with M . leprae at multiplicities of infection ( MOI ) of 10:1 , 20:1 , 50:1 and 100:1 for 6 h at 37°C . For complement opsonization , appropriate concentrations of M . leprae were suspended in SW-10 cells culture media containing 10% human serum ( Sigma-Aldrich Co . Ltd . ) as a source of complement components and incubated for 2 h at 37°C before infection . After extracellular M . leprae were washed with PBS , M . leprae were stained with AFB or Auramine O , and examined in the oil immersion field of a light microscope . The SW-10 cells were cultured in 4-channel chamber slides ( Lab-Tek II chamber slide , Thermo Fisher Scientific , Waltham , MA ) and incubated overnight at 37°C under 5% CO2 . The cells were pretreated with 20 μM Celecoxib or 157 μM C-75 for 1 h . The cells were infected with M . leprae ( MOI 100:1 ) for 6 h and washed with warmed complete media to remove extracellular bacteria . Pre-warmed complete media was added to the cells , followed by the incubation for another 24 h . During the final 2 h of incubation , the cells were incubated with medium containing 250 nM LysoTracker Red DND-99 ( Molecular Probes , Eugene , OR ) according to the manufacturer’s instructions . The cells were fixed in 2% paraformaldehyde for 30 min . The level of co-localization of Auramine O-labeled M . leprae and LysoTracker was analyzed using the ZEN program ( Zeiss , Oberkochen , Germany ) under a LSM 510 Meta confocal microscope ( Zeiss , Oberkochen , Germany ) . The SW-10 cells were fixed with 2 . 5% glutaraldehyde for 2 h . The cells were then post fixed by treatment with 1% osmium tetroxide , dehydrated in ethanol , and embedded in Epon 812 ( Polyscience , Warrington , PA ) . Ultrathin sections were contrasted with uranyl acetate and lead citrate . The Sections were examined via transmission electron microscopy ( JEOL , Arishima , Japan ) . At designated times , the treated cells were removed from the incubator and placed on ice . The cells were then washed 3 times with ice-cold PBS and lysed for 30 min with RIPA lysis buffer [50 mM Tris–HCl ( pH 7 . 4 ) , 1% Triton X-100 , 150 mM NaCl , 0 . 1% SDS , 0 . 5% sodium deoxycholate , 100 mM phenylmethylsulfonyl fluoride , 1 μg/ml of leupeptin , 1 mM Na3VO4 , and 1× Complete Protease Inhibitor Cocktail ( Santa Cruz Biotechnology ) ] . Equal amounts of protein were loaded onto 10–15% SDS-PAGE gels , electrophoresed , and transferred onto PVDF membranes ( Millipore , Bedford , MA ) . The membranes were blocked in Tris-buffered saline with 0 . 05% Tween 20 ( TBST ) supplemented with 5% powdered milk , and then incubated with primary antibody against ADRP or β-actin . The blots were then washed with TBST and incubated with a horseradish peroxidase-conjugated secondary antibody in TBST plus a 5% solution of powdered milk . The bound antibodies were detected with Amersham ECL Prime Western Blotting Detection ( GE Healthcare , Buckingharmshire , UK ) . The SW-10 cells were plated on 6-well plates . After 24 h , the cells were pre-treated with the designated inhibitors for 1 h , followed by incubation with M . leprae at the indicated MOI . After incubation for the designated times , the cells were harvested for the next experiment . The concentrations of inhibitors used were as follows: Celecoxib , 20 μM and C-75 , 157 μM . None of the inhibitors used had a significant effect on the viability of SW-10 cells . The M . leprae-infected SW-10 cells were lysed with 0 . 1N NaOH for 5 min at room temperature and centrifuged 10 , 000 g for 5 min . The bacilli were washed three times with PBS . ATP was extracted from bacilli by the modified Tris-boiling method [19] . The bacilli were suspended in 50 μl the lysis reagent [sodium dodecyl sulfate ( 2% ) , triton X-100 ( 10% ) and Tris-EDTA buffer ( pH 8 . 0 ) ] , then heated at 100°C for 5 min , and cooled on ice for 1 min . The suspension was diluted with 250 μl of deionized water . The amount of ATP was quantified using the BacTiter-Glo Microbial Cell Viability Assay kit ( Promega , Madison , WI ) , according to the manufacturer’s instructions . Briefly , 100 μl of each diluted sample was mixed with an equal volume of freshly prepared BacTiter-Glo reagent in black 96-well plate and incubated for 5 min in the dark . The emitted luminescence was detected using a SpectraMax L microplate reader ( Molecular Device , Sunnyvale , CA ) . All results are expressed as the means ±SD . of data from at least three separate experiments . Statistical significance was determined via the Student’s t-test for two points or one-way ANOVA . p<0 . 05 was considered to be statistically significant .
We initially characterized SW-10 cells , a mouse Schwann cell line . As shown in Fig 1 , SW-10 cells express S100 , a marker for cells from neural crest , and NGFR p75 , a marker for immature or non-myelinating Schwann cell , but neither MBP , a marker of myelinating Schwann cell , nor MPZ , a marker for precursor , immature , or myelinating Schwann cells [17 , 20] . Thus , these results indicate that SW-10 cells are non-myelinating Schwann cells . Schwann cells are well known to have phagocytic activity . We used the CytoSelect 96-well phagocytosis Zymosan colorimetric assay ( Cell Biolabs ) to investigate the possibility that SW-10 cells could have phagocytic activity . As shown in Fig 2 , SW-10 cells phagocytosed Zymosan . In addition , pre-treatment with Cytochalasin D , an inhibitor of phagocytosis and actin polymerization , inhibited the phagocytic activity of Schwann cells ( Fig 2 ) . These results indicate that SW-10 cells have phagocytic activity . M . leprae almost exclusively infects macrophages and Schwann cells . We investigated whether M . leprae infects SW-10 cells . SW-10 cells were incubated with M . leprae using MOI of 10:1 , 20:1 , 50:1 and 100:1 for 6 h at 37°C . At the MOI of 100:1 , 83 . 6% of cells were infected with M . leprae and the average number of M . leprae in a cell was 5 . 1 ( Fig 3 ) . Based on these findings , for the remainder of the current study we incubated SW-10 cells with M . leprae at the MOI of 100:1 . Apoptosis of Schwann cells is frequently found in human leprosy lesions [21] . Thus , we investigated whether M . leprae infection induces apoptosis in SW-10 cells . However , under our experimental conditions , M . leprae infection did not induce the expression of active caspase-3 , an indicator of apoptosis , in SW-10 cells , whereas treatment with 1 μΜ staurosporine , a well-known inducer of apoptosis , induced the expression of active caspase-3 ( Fig 4 ) . M . leprae infection is known to induce the formation of LDs in primary Schwann cells and in ST 88–14 cells , which make up the human Schwann cell line [12 , 13] . We investigated whether in vitro M . leprae infection induces the formation of LDs in SW-10 cells . As shown in Fig 5A , infection with live M . leprae , but neither dead M . leprae nor latex bead , induced the formation of LDs in SW-10 cells . Consistent with these results , live M . leprae induced the expression of ADRP , a marker of LD , whereas dead M . leprae or latex bead did not affect expression ( Fig 5B ) . Treatment with NS-398 , a non-steroidal anti-inflammatory drug , or C-75 , an inhibitor of fatty acid synthetase , inhibits M . leprae-induced prostaglandin E2 ( PGE2 ) production and LDs formation , subsequently leading to a decrease in M . leprae-survival in primary Schwann cells [13] . Thus , we used celecoxib , an inhibitor of cyclo-oxygenase ( COX ) -2 , or C-75 , an inhibitor of fatty acid synthetase to investigate the effect that the LD formation caused by M . leprae can exert on the maturation of phagosomes containing live M . leprae and on M . leprae survival in SW-10 cells . Treatment with celecoxib or C-75 did not affect the phagocytic activity of SW-10 cells ( Fig 6B and 6C ) , but it inhibited M . leprae–induced ADRP expression ( Fig 6A ) , which resulted in an increase in the co-localization of Auromine O-labelled M . leprae with Lysotracker , a marker of lysosome ( Fig 7A and 7B ) and in a subsequent decrease in the ATP content of M . leprae in SW-10 cells ( Fig 8 ) . Taken together , our results show that LD formation by M . leprae also favors M . leprae survival in non-myelinating Schwann cells .
The findings reported herein indicate that SW-10 cells express S100 , a marker for cells from the neural crest , and NGFR p75 , a marker for immature or non-myelinating Schwann cells , but neither MBP , a marker of myelinating Schwann cells , nor MPZ , a marker for precursor , immature , or myelinating Schwann cells [17 , 20] , which suggests that SW-10 cells are non-myelinating Schwann cells ( Fig 1 ) . In addition , SW-10 cells have phagocytic activity ( Fig 2 ) and are subjected to infection with M . leprae ( Fig 3 ) . Infection with M . leprae induces LD formation ( Fig 5 ) . Furthermore , the inhibition of M . leprae-induced LD formation enhances the maturation of phagosomes containing live M . leprae ( Fig 7 ) and decreases the ATP content of M . leprae ( Fig 8 ) in SW-10 cells , which suggests that LD formation by M . leprae favors M . leprae survival in SW-10 cells . These results support the role of non-myelinating Schwann cells as a shelter for M . leprae multiplication . Because M . leprae preferentially infects Schwann cells of the peripheral nerves in cooler regions of the body , the temperature below the body’s core temperature ( 37°C ) is suggested to be ideal condition for the growth and maintenance of M . leprae . In experimental conditions , an incubation of 33°C is also suggested as optimal for studying the effect of M . leprae on Schwann cells . Hagge et al . [22] reported that M . leprae showed 56% viability in Schwann cells for 3 weeks after infection at 33°C , compared with 3 . 6% viability at 37°C . However , Itty et al . [23] reported that the number of M . leprae adhering to mouse primary Schwann cells during incubation at 37°C was more than twice as great as that at 34°C . Since the adherence of M . leprae to Schwann cells is a prerequisite for phagocytosis and our results focused on the early ( 24–72 h ) effects of M . leprae infection on Schwann cells , we performed in vitro infections of Schwann cells with M . leprae at 37°C . Adenosine-5-triphosphate ( ATP ) is used in all living cells as a co-enzyme for energy transfer . The ATP content is fairly constant for each cell type and decreases quickly following cell death [19] . In the current study , we determined the viability level of M . leprae that is derived from SW-10 cells by measuring its ATP content ( Fig 8 ) . Katoch et al . [24] have reported that the ATP content of cultivable mycobacteria , M . tuberculosis and M . lufu , directly correlated with viable numbers of mycobacteria . In addition , measuring the ATP content of M . leprae has also been used as an in vitro method to determine the viability of M . leprae [19 , 24] . LDs are cytoplasmic lipid storage organelles that are found in most eukaryotic cells . LDs composed of a hydrophobic core of neutral lipids ( triglycerides and cholesterol esters ) surrounded by a phospholipid monolayer and by specific proteins , including perilipin , ADRP , and tail-interacting protein 47 ( TIP47 ) [25 , 26] . LDs basically play an important role in lipid metabolism and provide a site for the generation of inflammation mediators , prostaglandins and leukotrienes [13 , 27] . These LDs also support pathogen growth or survival in host cells [28] . LDs serve as a site for the replication of viruses , including the hepatitis C virus [29] , Dengue virus [30] , and Rotavirus [31] . LDs are also used for the survival of Chlamydia trachomatis , an obligate intracellular bacteria [32 , 33] . In addition , LDs are also involved in the pathogenesis of mycobacterial infection . Infection with M . tuberculosis induces the formation of LDs in macrophages [34] . In lepromatous leprosy , M . leprae-infected macrophages in dermal lesions and Schwann cells in peripheral nerves show a foamy , lipid-laden appearance [8 , 11] . The foamy appearance is at least in part derived from the accumulation of LDs in M . leprae-infected cells [8 , 11] . LDs are recruited to M . leprae-containing phagosome in M . leprae-infected Schwann cells [12] . Although how LDs inhibit the maturation of M . leprae-containing phagosomes in Schwann cells is unknown , M . leprae-induced LD formation favors intracellular M . leprae survival in primary Schwann cells [12 , 13] . Consistent with these results , our results also show that LDs formation by live M . leprae inhibits the maturation of M . leprae-containing phagosome , leading to an increase in the viability of M . leprae in SW-10 cells , non-myelinating Schwann cells ( Figs 7 and 8 ) . M . leprae infection induces demyelination and axonal injury of peripheral nerves via the immune reaction to M . leprae-infected cells and/or via the physical contact of M . leprae to Schwann cells [2–5] . Apoptotic Schwann cells are frequently found in human leprosy lesions [21] . M . leprae infection induces apoptosis in ST88-14 cells , a human Schwann cell line [35] . In addition , treatment with M . leprae 19-kDa lipoprotein induces apoptosis in ST88-14 and in primary human Schwann cells [21] . However , our results show that in vitro infection with M . leprae does not induce apoptosis in SW-10 cells ( Fig 4 ) . Consistent with our results , Rambukkana et al . [3] reported that in in vitro and in vivo infection models , non-myelinating Schwann cells harbor M . leprae in large numbers rather than showing apoptosis . Thus , further detailed studies are needed to assess the influence of M . leprae on myelinating and non-myelinating Schwann cells through a pathway that is either dependent or independent of immune reactions . Upon nerve damage , M . leprae invades Schwann cells where it can survive for long periods [36] . In addition , M . leprae infection reprograms the adult Schwann cells to a stem cell type , which promotes the dissemination of M . leprae [37] . Although M . leprae infection is detected in both myelinating and non-myelinating Schwann cells of patients with lepromatous leprosy [15 , 16] , M . leprae preferentially invades the non-myelinating Schwann cells , where it multiplies , releases , and re-infects more non-myelinating Schwann cells [3 , 4] . However , the effect of M . leprae infection on non-myelinating Schwann cells has not been elucidated . We wondered if SW-10 cells would be non-myelinating Schwann cells , which would make them targets of M . leprae . Our results indicate that SW-10 cells show similar phenotypes in response to M . leprae infection , as shown in primary Schwann cells and in ST88-14 cells , which is the myelinating Schwann cell line ( Table 1 ) [35] . The results of this study suggest that M . leprae-infected SW-10 cells could be a new model that can be used to investigate the interactions of M . leprae with non-myelinating Schwann cells . | Leprosy is a chronic infectious disease that is caused by the obligate intracellular pathogen Mycobacterium leprae ( M . leprae ) . Leprosy is the leading cause of all non-traumatic peripheral neuropathies worldwide . Both myelinating and non-myelinating Schwann cells are infected by M . leprae in lepromatous leprosy , but the non-myelinating Schwann cells show greater susceptibility to M . leprae invasion . However , the effect of M . leprae infection on non-myelinating Schwann cells has not been elucidated . Our results show that SW-10 cells are non-myelinating Schwann cells . Infection with M . leprae induces lipid droplet ( LD ) formation . Furthermore , inhibition of M . leprae-induced LD formation enhances the maturation of phagosomes containing live M . leprae and decreases the ATP content of M . leprae in SW-10 cells , suggesting that LD formation by M . leprae favors M . leprae survival in SW-10 cells . Based on these findings , it should be clear that M . leprae-infected SW-10 cells can serve as a new model for investigating the interaction of M . leprae with non-myelinating Schwann cells . | [
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"di... | 2017 | The formation of lipid droplets favors intracellular Mycobacterium leprae survival in SW-10, non-myelinating Schwann cells |
X chromosome inactivation ( XCI ) is the mammalian mechanism of dosage compensation that balances X-linked gene expression between the sexes . Early during female development , each cell of the embryo proper independently inactivates one of its two parental X-chromosomes . In mice , the choice of which X chromosome is inactivated is affected by the genotype of a cis-acting locus , the X-chromosome controlling element ( Xce ) . Xce has been localized to a 1 . 9 Mb interval within the X-inactivation center ( Xic ) , yet its molecular identity and mechanism of action remain unknown . We combined genotype and sequence data for mouse stocks with detailed phenotyping of ten inbred strains and with the development of a statistical model that incorporates phenotyping data from multiple sources to disentangle sources of XCI phenotypic variance in natural female populations on X inactivation . We have reduced the Xce candidate 10-fold to a 176 kb region located approximately 500 kb proximal to Xist . We propose that structural variation in this interval explains the presence of multiple functional Xce alleles in the genus Mus . We have identified a new allele , Xcee present in Mus musculus and a possible sixth functional allele in Mus spicilegus . We have also confirmed a parent-of-origin effect on X inactivation choice and provide evidence that maternal inheritance magnifies the skewing associated with strong Xce alleles . Based on the phylogenetic analysis of 155 laboratory strains and wild mice we conclude that Xcea is either a derived allele that arose concurrently with the domestication of fancy mice but prior the derivation of most classical inbred strains or a rare allele in the wild . Furthermore , we have found that despite the presence of multiple haplotypes in the wild Mus musculus domesticus has only one functional Xce allele , Xceb . Lastly , we conclude that each mouse taxa examined has a different functional Xce allele .
The eutherian female is a mosaic of two cell populations that have either a transcriptionally active maternal or paternal chromosome X . This is a consequence of the mammalian dosage compensation mechanism called X chromosome inactivation ( XCI ) that balances X-linked gene expression between the sexes [1] . The choice of which X chromosome undergoes XCI occurs early during female embryogenesis on a small population of epiblast cells within the embryo proper [2] , [3] , [4] , [5] . By an unknown mechanism , each cell randomly chooses to inactivate one of the two parental X-chromosomes and then commits to that choice by initiating a cascade of transcriptional and epigenetic regulation that modifies both chromosomes to distinguish the future inactive X from the active X [6] , [7] , [8] , [9] , [10] , [11] . Ultimately , the inactive X chromosome becomes physically condensed and sequestered within the nucleus rendering it almost completely nonfunctional [12] , [13] , [14] . The initial choice each epiblast cell makes is preserved and transmitted mitotically to all its daughter cells [15] . As a result , each female is a unique mosaic of somatic cells that express either the maternally or paternally derived X chromosome . The degree of mosaicism ( overall ratio and spatial distribution of cells ) is determined by the initial number of cells that undergo independent choice , by the developmental fate of each epiblast cell and its multiplication rate . A role for genetics in XCI choice was initially discovered by skewed XCI ratios in female hybrids between certain stocks derived from classical inbred mouse strains . These female hybrids , on average , preferentially inactivated one X chromosome over the other in a strain dependent manner [16] , [17] . The effect was later mapped to a single location on the X chromosome and given the name X-chromosome controlling element ( Xce ) for its role in XCI choice [18] . Since its initial discovery , four functional alleles of Xce have been characterized in Mus inbred strains , ( Xcea , Xceb , Xcec and Xced ) and are distinguished by their relative resistance or susceptibility to inactivation [17] , [19] , [20] , [21] , 22 , 23 , 24 . The four Xce alleles form an allelic series of XCI skewing , the magnitude and direction of which depends on the Xce genotype of the female . Furthermore , XCI skewing is only observed in Xce heterozygotes while female homozygotes display no preference towards inactivating either parental X chromosome [25] . The order of known Xce allele strength is Xcea < Xceb < Xcec < Xced ( Figure 1A ) . In other words , in female heterozygotes the X chromosome carrying the stronger Xce allele has a higher probability of remaining active and thus , these females will have a larger number of cells with that X chromosome active ( Figure 1B ) . From a genetic standpoint , alleles at Xce are overdominant and therefore Xce acts in cis . Xce has been mapped within a 1 . 85 Mb candidate interval that overlaps with the current definition of the X inactivation center ( Xic ) which includes three long non-coding RNAs Xist , Tsix and Xite that play major roles in murine XCI [26] . It has been postulated that the Xce allelic series can be explained by genetic variation within these long non-coding RNAs , specifically Xite [27] . An alternative hypothesis is that XCI choice is controlled by X-linked and autosomal dosage factors [28] , [29] , [30] and thus Xce would serve as a binding site for a trans-acting factor ( s ) that influences Tsix or Xist expression [28] , [30] , [31] , [32] . Nonetheless , the identity of Xce remains unknown . This is in part due to the technical challenges of measuring XCI choice and to the relatively high level of stochastic variation in XCI in isogenic female populations that together make it difficult to infer with certainty the Xce allele present in an individual female ( Figure 1B ) . Mapping Xce is further complicated by the comparatively low recombination rate of the X chromosome and the fact that only females are informative for the phenotype . Although Xce is the major locus controlling XCI choice , previous studies have demonstrated that parent-of-origin and autosomal factors significantly influence XCI choice [23] , [24] , [33] , [34] , [35] . A large mapping experiment identified suggestive loci on five autosomes but none reached genome–wide significance [26] . The parent-of-origin effect was first described by Forrester and Ansell in 1985 as a difference in XCI skewing depending on whether the Xcec allele was maternally or paternally inherited in Xcec/b heterozygotes . The evidence available at the time , however , could not discriminate among Xce , another X-linked locus or autosomal loci . A more recent study provided additional evidence of a parent-of-origin effect and postulated that its cause could be Xce itself or epigenetic differences of one or more X-linked loci [34] . The same study showed an increased variance in XCI skewing in F2 females heterozygous for the same combination of Xce alleles as F1 hybrids , indicating the existence of autosomal factors that influence XCI choice [34] . A more recent study used mouse lines with recombinant X chromosomes derived from two genetically divergent mouse inbred strains ( 129S1/SvlmJ and CAST/EiJ ) to show that multiple regions along the X chromosome influence XCI choice , but was unable to map any of them , including Xce [36] . Lastly , there are well-documented cases of secondary XCI skewing that influence the XCI patterns observed in adults [37] , [38] , [39] . Secondary skewing occurs when an X linked mutation impacts cell survival or proliferation . Technical issues associated with measuring XCI choice further complicate the identification of Xce . A well-established surrogate for XCI choice is X-linked allele-specific gene expression . Nonetheless , gene expression in a female mouse can be influenced by many factors in addition to XCI choice itself . And thus , it is important to carefully choose X-linked genes that most accurately reflect the true ratio of XCI while minimizing the presence of misleading factors such as differential expression due to cis-acting regulatory variants , tissue-specific skewing , or XCI escape . As a general rule , estimation of XCI skewing improves with the number of X-linked genes used . In this study , we developed an approach that overcomes major challenges of mapping Xce . Our approach is based on association mapping of XCI skewing phenotypes in classical inbred strains that have recently been genotyped at very high density [40] or had their genome sequenced ( whole genome sequence , WGS ) [41] . Our analysis was restricted to the previously defined candidate interval [26] and generated a new candidate interval of much smaller size . By generating multiple F1 hybrid females between inbred strains we accurately determined the mean and the variance in XCI ratio within genetically identical mice . We also generated reciprocal crosses to determine the parent-of-origin effects . Lastly , we performed these analyses in multiple tissues and thus determined whether tissue choice had an effect on the estimation of skewing of XCI . In order to analyze the X-linked expression phenotype data we developed a hierarchical Bayesian model and inference procedure that allows to us to estimate both the mean and the variability of XCI within an individual female or female population . We extended our phenotyping to wild-derived inbred strains with different haplotypes of known subspecific origin [40] , and used these data to reconstruct the evolutionary history of the Xce locus itself .
In our initial approach to reduce the candidate interval we first identified a subset of inbred mouse strains that had both a known Xce allele and high-density genotype [40] or sequence data [41] available . Over the past four decades , several inbred mouse strains have been phenotyped for XCI skewing and these strains include representatives of each one of the four known Xce alleles ( Figure 2A ) . At the Xce candidate interval defined by Chadwick and coworkers ( 2006 ) , referred hereafter as the Chadwick interval , these strains have haplotypes derived from two different Mus species , Mus spretus and Mus musculus , and two subspecies of the latter , M . m . castaneus and M . m . domesticus [40] . Two strains , CAST/EiJ and SPRET/EiJ , cannot be used to refine the candidate interval using single locus association mapping techniques because they are singletons for both an Xce allele and the specific or subspecific origin ( Figure 2A ) . The remaining 25 strains are almost evenly distributed between Xcea and Xceb carriers and all have a M . m . domesticus haplotype in the candidate interval [40] . Furthermore , all of them are classical inbred strains descended from a small pool of founders [42] which makes extremely unlikely the possibility that one or more recurring mutations that exactly generate either the Xcea or the Xceb allele arose multiple times independently . Thus , it is reasonable to assume that Xcea and Xceb alleles are inherited from a recent common ancestor rather than spontaneously arising over multiple times within this complex multifamily pedigree . Eleven of these strains ( or a closely related sister strain ) have been genotyped at high density and eight have been sequenced [40] , [41] . Importantly , both alleles are represented among genotyped and sequenced strains ( Xcea , seven genotyped and five sequenced strains and Xceb , four genotyped and three sequenced strains , Figure 2A ) . For every SNP and indel present within the Chadwick interval , we determined the pattern of allelic similarities and differences among the subset of inbred strains with known Xce alleles ( Strain Distribution Pattern ( SDP ) , see Materials and Methods and Figure S1 ) [43] , [44] . SDPs were then classified into three categories based on consistency between phenotype and genotype: 1 ) fully consistent with the Xce phenotype ( black tick marks ) , 2 ) inconsistent with the Xce phenotype ( red tick marks ) , or 3 ) partially consistent ( gray tick marks ) ( Figure 2B and Table S1 ) . We focused our association analysis within the Chadwick interval , which is based on genetic mapping in populations segregating for the Xcea , Xceb , and Xcec alleles . Analysis of Mouse Diversity Array ( MDA , [44] ) genotypes and sequence data shows an enrichment of consistent SDPs ( eight MDA SNPs , 120 Sanger SNPs and indels ) at an 194 kb interval spanning from rs29082048 to Sanger Mouse Genomes Project ( SMGP ) SNP position at 100 , 119 , 750 bp ( Table S1 ) . This interval does not contain any inconsistent SNPs . In addition , there are 23 SNPs with consistent SDPs randomly distributed throughout the distal portion of the Chadwick candidate interval ( Figure 2B ) . These SNPs do not cluster and this region is punctuated with inconsistent SNPs . We conclude that the minimum Xce candidate interval is located approximately 558 kb proximal to Xist ( note that the maximum Xce candidate interval based on this analysis spans from inconsistent SMGP-SNP at position 99 , 091 , 507 bp to inconsistent SMGP-indel at 100 , 460 , 107 bp ) . Within this candidate interval all phenotyped strains with the Xcea allele share the same haplotype and all strains with the Xceb allele share a different haplotype based on MDA genotypes . Our ability to reduce further the Xce candidate interval depended on the number of inbred strains with known Xce allele and high-density genotype data available . Ideally we would like to phenotype inbred strains that have Xcea and Xceb recombinant haplotypes in the candidate interval . Furthermore , we would like to characterize the Xce alleles of additional M . m . domesticus strains with haplotypes that are not associated with known Xce allele carriers . These strains will provide additional information about Xce functional diversity within M . m . domesticus and depending on their Xce phenotype , may further refine the Xce candidate interval . We selected three strains with Xcea/b recombinant haplotypes ALS/LtJ , SJL/J and WLA/Pas because of their availability and their ability to refine further the new candidate interval . Based on phylogenetic analysis of the new candidate interval ( See Methods ) , we selected six wild-derived inbred strains , PERA/EiJ , TIRANO/EiJ , ZALENDE/EiJ , LEWES/EiJ , and WSB/EiJ to represent each of the major haplotypes present in M . m . domesticus ( with the exception of b3 which has only been observed in wild mice ) . We selected PWK/PhJ to characterize the Xce allele in a third M . musculus subspecies , M . m . musculus . We selected WSB/EiJ and PWK/PhJ because they are wild-derived strains of M . m . domesticus and M . m . musculus origin , they have available whole genome sequence [41] and they are founder strains in mouse genetic resources such as the Collaborative Cross [45] and Diversity Outbred [46] . Finally , we selected PANCEVO/EiJ to characterize the Xce allele present in a third species of mouse , Mus spicilegus . A summary of the justification for selecting each mouse strain and the information it provided towards mapping Xce is provided in Table S2 . To determine which Xce allele is present in each strain , we generated genetically defined F1 female hybrids by crossing the unknown strain to inbred strains with well-characterized Xce alleles: Xcea , A/J and 129S1/SvImJ; Xceb , C57BL/6J; and Xcec , CAST/EiJ . To estimate the presence , direction and extent of XCI skewing in each F1 hybrid female , we developed highly quantitative pyrosequencing assays and measured allele-specific X-linked gene expression ( see Methods ) . On average , for each strain with an unknown Xce allele , we tested allele-specific expression in 69 F1 females ( ranging from 40 to 120 females per strain , Table S3 ) . To analyze and integrate the X-linked expression data set , we developed a hierarchical Bayesian model and inference procedure . The method is described briefly in the Methods section , and full description will be reported elsewhere . Briefly , our model parameterizes gene-tissue bias and precision , parent-of-origin effects , and genetic background effects ( strain ) to account for gross sources of uncertainty and error associated with our XCI phenotyping method . This allows us to combine the different gene measurements and tissues from individual females and establish a mean XCI ratio ( see Materials and Methods ) for a given cross . For each F1 cross , we tested whether the two parental strains carry the same Xce allele . Figure 3 shows the gene expression data ( panel A ) and posterior mean and confidence intervals inferred from it ( Panel B ) for the SJL/J F1 crosses performed . The posteriors in Panel B estimate the mean inactivation proportion associated with each cross . They show where and how posterior probability for the underlying cross mean is concentrated on the scale of 0 ( representing full maternal inactivation ) to 1 ( representing full paternal inactivation ) , with 0 . 5 indicating a cross average of about 50% paternal and maternal X-inactivation . By choosing regions of 95% posterior coverage , we see that the data allows us to measure mean X inactivation proportions accurately within 7 . 7% ( +/−5% ) , placing for instance , the ( SJL/JxCAST/EiJ ) F1 firmly to the left of 50% , around 33 . 6% of cells with an active SJL/J X chromosome . As a rule , when a distribution shows a strong bias , in other words , when most of the posterior is concentrated on one side of 0 . 5 boundary , we use this as evidence to conclude that the two strains involved the cross have functionally different Xce alleles . To quantify this bias , we used the tail posterior probability ( i . e . , the amount of posterior probability that lies on the side of 0 . 5 line , Figure 3C ) . These tail probabilities are like p-values and their small values strongly support the presence of skewed XCI . Using this approach , we conclude that seven inbred strains , ALS/LtJ , SJL/J , LEWES/EiJ , PERA/EiJ , TIRANO/EiJ , WSB/EiJ and ZALENDE/EiJ carry an Xceb allele ( Figure 3 and Figure S3 ) . The M . m . musculus strain , PWK/PhJ has a new allele , named herein Xcee . Within the allelic series , the strength of this new allele falls between Xcea and Xceb ( Figure 1A ) . Finally , PANCEVO/EiJ has an allele that is similar in strength to Xcea ( Figure S3 ) . The results for the WLA/Pas strain are inconclusive and will be discussed later . Incorporation of the ALS/LtJ and SJL/J strains to our association mapping further reduced the proximal boundary of the new Xce candidate interval by 9 . 6 kb . Furthermore , by including ALS/LtJ , SJL/J , LEWES/EiJ , PERA/EiJ , TIRANO/EiJ , WSB/EiJ and ZALENDE/EiJ into our SDP analysis , we reduced the number of SNPs with consistent SDPs within the Xce interval to 69 and further reduced the proximal boundary by 8 . 2 kb ( Figure 2B , blue tick marks and Table S4 ) . The minimum refined Xce candidate interval is bounded by SMGP-SNPs at positions 99 , 943 , 259 bp and 100 , 119 , 750 bp . Outside of the refined candidate interval but within the Chadwick interval only 14 SNPs ( WGS and MDA data ) have consistent SDPs ( Table S4 ) . These SNPs ( highlighted blue in Figure 2B ) do not cluster and are interspersed with SNPs with inconsistent SDPs . Lastly , only three SNPs on the entire X chromosome ( rs29079362 , rs73483921 and rs29081860 ) outside of the Chadwick interval have SDP patterns consistent with the Xce alleles . After phenotyping of the additional strains , the minimum candidate interval spans 176 kb and its size and relative position with respect to the Xic does not change in the latest mouse genome assembly ( GrCm38/mm10 ) . The final interval contains five protein coding genes , six pseudogenes , and three novel rRNAs . The G+C content is elevated compared to the X chromosome average ( 44% versus 39% , respectively [47] ) . Repeat masker [48] identified 50 LINEs and 60 SINEs as well as 194 other DNA features such as LTRs and regions of low complexity . However , the most dramatic feature is the presence of a set of tandem duplications and inversion ( Figure 4A ) . The NCBI37/mm9 ( and the GrCm38/mm10 ) reference assembly contains four tandem duplications and one inversion herein referred as segmental duplication ( SD ) 1 ( 99 , 909 , 337–99 , 942 , 773 bp ) , SD2 ( 99 , 940 , 942–99 , 961 , 388 bp ) , SD3 ( 99 , 959 , 575–100 , 013 , 166 bp ) , SD4 ( 100 , 013 , 346–100 , 035 , 061 bp ) , and inversion ( I ) 5 ( 100 , 040 , 370–100 , 084 , 982 bp ) ( Figure 4A ) . The average size of the duplications is 35 kb , the C+G content is 45% , and they typically span three genes , nine LINEs and 13 SINEs . The phylogenetic tree reveals that two pairs of duplications ( SD1 and SD2 and SD3 and I5 ) are relatively recent events while duplication 4 is the oldest ( Figure 4B ) . The topological arrangement of these SDs cannot be explained simply by a set of tandem duplications . In particular , the phylogentic origin , location and orientation of SD3 , SD4 and I5 requires both an inversion and a deletion after the duplication event of their common ancestor ( Figure 4B ) . Because genotypes in segmental duplications are notoriously unreliable [40] , [44] , we investigated whether probes designed to track the duplications in the newly released MegaMUGA array ( to be reported elsewhere ) support our haplotype assignment and mapping conclusions . The MegaMUGA array was designed on Illumina's ( San Diego , CA ) Infinium BeadChips platform that consistently produces high signal-to-noise ratio compared to conventional hybridization based arrays as demonstrated by previous studies [49] , [50] . These probes ( Figure 4B , C and Table S5 ) consist of standard SNPs and probes with off target variants ( VINOs ) [51] , [52] in addition to probes designed specifically to target the five duplications within the Xce candidate interval . Haplotype inference based on probe hybridization has been used successfully in other mouse populations such as the Collaborative Cross [45] , [52] . We found a striking consistency between the haplotypes defined by nominal genotypes and the haplotypes based on principal component analysis ( PCA ) of probe intensities in the segmental duplications . In fact , MegaMUGA probe intensities perfectly partition all mouse inbred strains according to their experimentally defined Xce alleles . This is true not only for Xcea and Xceb carriers , but also for known Xcec , Xced , Xcee , and Xcef carriers ( Figure 5B ) . We extended this approach to analyze 110 genotyped samples with unknown Xce alleles ( Figure 5A and Table S10 ) . Samples with M . m . domesticus haplotypes in the candidate interval are partitioned into two groups corresponding to known carriers of Xcea and Xceb alleles , matching perfectly the results obtained by standard phylogenetic analysis . In addition , we found that wild-derived inbred strains as well as wild-caught mice with M . spretus , M . spicilegus , M . m . castaneus and M . m . musculus haplotypes cluster with the appropriate known carriers of an Xced , Xcef , Xcec , and Xceb , respectively . We note that the probes used in the PCA do not share sequence similarity and they do not track homologous regions within the duplications and inversion . Finally , no single probe ( nor pair of probes ) is able to partition all samples according to Xce haplotype or functional allele . There are , however , certain probes that contribute to the partitioning of the Xce alleles more than others ( highlighted in Figure 4B ) . These results indicate that no single probe can explain the Xce allelic series and that each probe does not track a different Xce allele . Structural variation has been reported among inbred strains in the region encompassing the segmental duplications [53] . These structural variants are likely responsible for the difference in hybridization intensities and thus for the different haplotypes observed by PCA . These analyses strongly support the hypothesis that variation in the segmental duplications is associated with the five different functional Xce alleles . To investigate the evolutionary history of the Xce locus , we generated phylogenetic trees based on genotype or sequence data ( depending on availability ) within the final minimum Xce candidate interval for 99 classical inbred strains , 66 wild-derived inbred strains and 124 wild-caught mice ( Figure 5B and Table S6 ) . This tree partitions these samples among five taxa , M . spicilegus , M . spretus , M . m . castaneus , M . m . musculus and M . m . domesticus that are consistent with previous studies [40] , [41] . The Xce phenotype has been determined for at least one strain from each one of these taxa ( Table S6 ) . We found that each taxon ( species or major subspecies ) has a different functional Xce allele and there is no evidence of shared of alleles among taxa ( Figure 5B ) . Skewed XCI is present in all crosses between wild-derived strains belonging to different taxa . In contrast , skewing is not present in crosses involving strains from the same taxon . Within the M . m . domesticus subspecies we identified five haplotypes ( a , b1 , b2 , b3 and b4 ) . The a haplotype is associated with Xcea while two haplotypes , b1 and b2 are associated with Xceb . The b3 haplotype can be explained as recombination between a proximal b2 and distal b1 haplotype . The b3 haplotype has been observed in either a small mouse population on the Farallon islands off the coast of San Francisco , CA , and in one wild-caught mouse from Barcelona , Spain . The b4 haplotype appears to be a recombination between the a and b1 haplotypes and is found only in the WLA/Pas strain that carries an ambiguous Xce allele . Interestingly , there is an unequal distribution in the number and origin of M . m . domesticus stocks that carry each haplotype . For example , classical inbred strains are almost evenly divided among the a haplotype ( n = 52 ) and the b1 haplotype ( n = 47 ) ( Figure 5B ) . One classical inbred strain , CE/J carries the b2 haplotype . CE/J has been reported to be an outlier among classical inbred strain because it has the smallest fraction of haplotype sharing genome wide with strains with WGS available [54] . In contrast , wild-derived and wild-caught M . m . domesticus mice exclusively carry the b1 , b2 , b3 and b4 haplotypes ( Figure 5B ) . Note that we have determined experimentally the Xce allele for a wild derived representative of these two haplotypes . WSB/EiJ , PERA/EiJ , TIRANO/EiJ and ZALENDE/EiJ carry the b1 haplotype and LEWES/EiJ carries the b2 haplotype . All five wild-derived strains ( WSB/EiJ , PERA/EiJ , TIRANO/EiJ , ZALENDE/EiJ and LEWES/EiJ ) carry the Xceb allele . We conclude that in natural populations M . m . domesticus mice predominantly ( or exclusively ) carry the Xceb allele . We further conclude that given its absence among 121 wild mice and wild-derived strains the a haplotype associated with the Xcea allele is likely a derived allele that arose concurrently with the domestication of fancy mice . Another possibility is that Xcea represents a rare allele in the wild ( See Discussion , Figure 5B and Figure S4 ) . Previous studies have shown that the parent-of-origin of the Xce allele can influence the skewing of XCI [23] , [24] , [33] , [34] . To investigate this effect in our data set , we examined the XCI skewing in reciprocal F1 female hybrids ( Table S3 ) and tested whether the effect of the parent-of-origin on X inactivation ratio was statistically significant . In order to increase the statistical power to detect parent-of-origin effects we aggregated crosses with the same combination of Xce alleles , doing so under the assumption that the parent-of-origin effects are substantially greater than putative effects of genetic background [34] . We found that the parent-of-origin effect was highly significant overall ( p = 0 . 0023 ) and was consistent in its direction , magnifying XCI skewing in the F1 female hybrids inheriting the stronger Xce allele from their mothers ( Figure 6 ) . The magnitude of its effect varied between 18% ( the X-inactivation proportion in ( CAST/EiJxWSB/EiJ ) F1 females minus that in ( WSB/EiJxCAST/EiJ ) F1 females ) and 2% ( WSB/EiJxA/J ) F1 females minus ( A/JxWSB/EiJ ) F1 females ) , averaging 9% among all crosses where reciprocals were tested . We note that the parent-of-origin effect is observed independent of whether XCI measurement is based on pyrosequencing or RNAseq data . We found less support for the parent-of-origin effect on X inactivation skewing in reciprocal F1 females generated by crosses between the WSB/EiJ strain ( Xceb ) and Xcea allele carriers ( Table S3 ) . Retrospective analysis of reported parent-of-origin effects is fully consistent with our hypothesis that maternal origin of a strong Xce allele magnifies the skewing ( data not shown ) .
Recent advances in mouse genetic resources [40] , [41] provide an opportunity to resolve unanswered biological questions . Our method for association mapping integrates historical phenotyping data with these new genetic resources enabling us to reduce rapidly existing candidate intervals to a size amenable to mechanistic studies . This method is similar to approaches to identify candidate genes within candidate intervals reported previously [55] , [56] . The method guides subsequent experiments by identifying additional mouse strains that could reduce the candidate interval through informative historical recombinations . Moreover , our comparative analysis of different subspecies of mouse provides unique insight into the evolutionary history of the locus that is key to explaining its allelic series [40] . The validity of our approach relies on the fulfillment of several assumptions . These include the requirement that the locus under study explains a large fraction of the genetic variance and its action to be largely independent of other loci; that the causative mutation ( s ) for each functional allele has arisen once during evolutionary history; and that the genetic markers used in the analysis reflect the true haplotype diversity in the entire candidate interval . In our mapping of the Xce locus , fulfillment of the first assumption of a large genetic effect relies on 40 years of evidence that support the existence of a single major locus on the X chromosome near Xic that influence XCI choice [17] , [19] , [20] , [21] , [22] , [23] , [26] , [57] , [58] . Note that these studies arrive at the same conclusion regardless of the combination of Xce alleles ( Xcea , Xceb and Xcec ) used in each particular study . Although parent-of-origin and autosomal effects have been reported , the consensus is that their contribution to XCI skewing variation is small compared with that of Xce [23] , [26] , [34] . The need to fulfill the second assumption , that each allele arose once , guided the decision to restrict our initial association mapping analysis to classical inbred strains only , since the probability of multiple recurring mutations are extremely low based on their history [40] , [41] , [54] . Lastly , fulfilling the third assumption , we have previously shown that the marker density in MDA is sufficient to accurately reflect the underlying haplotype diversity genome wide and in particular in regions with lower levels of recombination such as the X chromosome [40] , [41] , [54] . We have shown that this approach was effective at rapidly reducing the Xce candidate interval 10-fold and that it may prove useful to map other genetic traits of interest provided that they meet the above listed criteria . In fact , Xce is a particularly difficult test case because of complexity of the XCI process and the reduced recombination rate on the X chromosome . We tailored our experimental design to anticipate the challenges of phenotyping mouse strains with unknown Xce alleles . First , the functional allele in a strain with an unknown Xce allele can be determined only by generating heterozygous females with known Xce alleles and then determining the ratio of XCI in the heterozygous progeny . The precision in identifying the unknown allele increases with the number of different alleles to which it is paired in the experimental F1 hybrids . We , therefore , crossed each strain with an unknown Xce allele to at least two strains with known and different Xce alleles . To estimate mean XCI skewing accurately , we phenotyped multiple females per cross . Moreover , for most females , we measured XCI skewing in at least three different tissues that roughly represent the three germ layers , brain ( ectoderm ) , liver ( endoderm ) and kidney ( mesoderm ) . Our results confirm previous reports that mean XCI skewing is similar between different tissues [25] , [35] , [59] , [60] . We do , however , observe differences in the variance of XCI skewing between different tissues ( brain ±6% kidney ±7 . 5% , and liver ±8 . 2% ) . From a practical standpoint , whole brain had the smallest variance and thus would require fewer animals to accurately determine mean XCI skewing . It is appropriate to use gene expression to measure the proportion of cells using the maternal versus paternal X chromosomes . However , expression at single genes can be misleading because of measurement bias or allelic imbalance independent of XCI choice such as cis-acting regulatory variants or XCI escape . To mitigate these potential issues , we measured multiple X-linked genes using pyrosequencing and/or RNAseq . By combining multiple gene measurements , we can better estimate the mean XCI skewing . Both technologies simultaneously measure maternal and paternal expression , reducing the concern of parent-specific measurement bias . Despite our thoroughness , we could not conclusively assign an Xce allele to the WLA/Pas strain , although we can exclude both Xcec and Xced . A possible reason for this is that in all crosses involving WLA/Pas the XceWLA/Pas allele was inherited through the paternal germline and in the absence of reciprocal crosses the parent-of-origin can potentially complicate Xce allele calling . A second , and more interesting explanation is that WLA/Pas has a b4 haplotype that appears to be a/b1 recombinant whose breakpoints fall within the SD4 in the candidate interval ( see below and Figure 4 ) . Although only a small number of readily available mouse strains carry M . m . castaneus or M . m . musculus haplotypes , a previous study measured XCI skewing in reciprocal F1 hybrids between PWD/PhJ and AKR/J [61] . This study reported that PWD/PhJ has an Xce allele that is weaker than Xceb . This result matches our conclusion that PWK/PhJ , a closely related wild-derived inbred strain [40] , carries the Xcee allele . Furthermore , we conclude that M . m . musculus do not carry the Xcec allele as reported in a congenic mouse line believed to be of M . m . musculus origin within the Xce candidate interval [59] . Our conclusion that the structural variants in the duplications within the candidate interval are likely to be responsible for the different Xce alleles provides simple and satisfactory answers to questions such as the presence of the allelic series , the overdominant nature and mechanism of action of Xce , and the evolutionary origin of the interspecific differences for XCI choice . Copy number variation within a region with complex segmental duplications and inversions can explain the large number ( six alleles described so far in Mus ) and different strength of the alleles at Xce . For example , the different strength of Xce alleles can be attributed to the number of copies of a binding site for a transfactor that is critical for the initiation of XCI [28] , [29] , [30] , [31] , [32] . One of the conclusions of our study is that each one of the five taxa ( species or major subspecies ) analyzed for XCI choice in Mus has a different functional allele and that there is no evidence of shared alleles between them . The rate of mutation for CNV at segmental duplicated regions fits well with the observed functional diversity at Xce . Given that unequal recombination is thought to be the primary process generating CNVs , it is noteworthy that two of the haplotypes reported here ( b3 and b4 ) involve crossing over within the duplications . In fact , we observe an apparently correct heterozygous call at SNP rs29082017 in two males with the b3 haplotype . Given that males cannot be true heterozygotes for X linked markers , the result strongly suggests that an unequal crossing over has generated a new haplotype with paralogous variation . Resequencing the candidate interval in these strains should provide important information on the relationship between CNVs and functional Xce alleles . It is striking that each species and subspecies examined thus far has a different functional allele . Furthermore , in the six wild-derived M . m . domesticus mouse strains phenotyped in this study , we do not find the occurrence of multiple functional alleles . We conclude that in M . m . domesticus , Xceb is the prevalent allele and other functional alleles are either rare or absent . The broad geographic origin of the wild-derived strains analyzed here strongly support this conclusion ( Table S6 ) . The only apparent exception to this rule is the presence of two functional alleles in classical inbred strains , Xcea and Xceb . That said , it is likely that Xceb is the ancestral allele within the domesticus subspecies and Xcea is a new , derived allele that originated early during the domestication of fancy mice . However , the phylogenetic tree shown in Figure 5B reveals deep branching between Xcea and Xceb haplotypes that at first glance suggests that both are old alleles . Upon further investigation , there is evidence that the deep branching observed in Figure 5B may be an artifact generated by genotyping and alignment problems in regions with segmental duplications ( i . e . , the apparent SNP are paralogous variants rather that allelic ones ) . Figure S4 provides evidence in favor of this later scenario as the deep branching disappears immediately proximal ( Figure S4A ) and distal ( Figure S4C ) to the duplicated regions . Furthermore , there is a dramatic increase in the density of heterozygous calls in the WGS data for inbred strains that overlaps the region of segmental duplications ( Figure S4D ) . The phylogenetic analysis also provides an explanation for the apparent differences in the genetics of XCI choice between mouse and humans . Mouse geneticists were able to find evidence of genetic control of XCI because they used mice derived from multiple taxa and because Xcea and Xceb are equally represented among classical laboratory inbred strains . In fact , were we to have studied only wild-derived or wild mice of M . m . domesticus origin , we would very likely have concluded that XCI choice is not under the control of a X chromosome linked locus . We speculate that this is probably the situation in humans too , but note that this conclusion would be due to a lack of functional variation at the Xce locus and not proof of the absence of a locus controlling XCI choice . We conclude that Xce is the major determinant of primary XCI choice and maps 500 kb proximal to key components of the murine Xic ( Xist , Tsix and Xite ) . Our results are compatible with the general conclusions reached by Thorvaldenson and coworkers ( 2012 ) . Nonetheless a direct comparison of both studies is difficult . Thorvenson and colleagues ( 2012 ) used only two functional alleles , Xcea and Xcec from highly divergent mouse strains to map roughly X-linked regions influencing XCI choice . They found that all their crosses , regardless of heterozygosity within the Chadwick interval , there is some degree of skewing in favor of the 129S1/SvlmJ and CAST/EiJ recombinant chromosome X . This led to the conclusion that multiple X-linked loci influence XCI choice . Although we provide strong evidence that the Xce allelic series is due to structural variation in the Xce candidate interval , we cannot exclude that a selected few SNPs within the Chadwick interval may also contribute to XCI choice . There are 14 SNPs distal to the Xce interval reported here with consistent SDPs in M . m . domesticus after the incorporation of the four strains with M . m . domesticus phenotyped . None of these SNPs individually can explain the allelic series and no simple combination of them within a single gene can be directly tied to the phenotype . On the other hand our reciprocal crosses between ALS/LtJ and C57BL/6J agree with Thorvenson's hypothesis that additional loci may have an effect in XCI choice as we find that the parent-of-origin effect is present despite homozygosity at the Xce locus ( Figure S3 ) . Both studies strongly predict the presence of an additional X-linked locus ( or loci ) controlling the parent-of-origin effect . The genetic analysis of the Xce locus presented in this study sets the stage for the molecular characterization of Xce . However , the most direct experiments will require access to the cells and biological material of the critical window at which XCI choice is made either by in vivo or ex vivo using ES cell lines .
Mice from nine inbred strains ( 129S1/SvlmJ , A/J , ALS/LtJ , C57BL/6J , CAST/EiJ , LEWES/EiJ , PWK/EiJ , SJL/J , and WSB/EiJ , ) were originally obtained from the Jackson Laboratory ( Bar Harbor , ME ) . Mice of the WLA/Pas strain were generously provided by Xavier Montagutelli from the Pasteur Institute ( Paris , FR ) . Mice were bred at UNC-Chapel Hill for multiple generations and interbred to generate F1 hybrids . Litters of F1 mouse pups were sacrificed within 24 hours after birth . We harvested whole brain , whole liver , right kidney , tail and a forepaw ( for sexing , [62] ) . Tissues were infused with RNAlater ( Qiagen ) and frozen at −80°C to preserve RNA integrity until extraction . Whole brain was isolated from mouse pups derived from crosses ( DDKxC57BL/6J ) F1 X PANCEVO/EiJ , ( C57BL/6J X DDK ) F1 X TIRANO/Ei and ( C57BL/6J X DDK ) F1 X ZALENDE/Ei [63] and ( C57BL/6J X PERA ) F1 X C57BL/6J [64] . These mouse crosses were generated for previous studies and reported elsewhere . All mice were treated according to the recommendations of the Institutional Animal Care and Use Committee ( IACUC ) of the University of North Carolina at Chapel Hill . All mice were treated according to the recommendations of the Institutional Animal Care and Use Committee ( IACUC ) of the University of North Carolina at Chapel Hill . To minimize the number of animals bred to determine the X inactivation pattern associated with a given Xce genotype we used whole brain from samples generated an stored as part of a previous study from crosses ( DDKxC57BL/6J ) F1 X PANCEVO/EiJ , ( C57BL/6J X DDK ) F1 X TIRANO/EiJ , ( C57BL/6J X DDK ) F1 X ZALENDE/Ei and ( C57BL/6J X PERA ) F1 X C57BL/6J . These mouse crosses have been reported elsewhere . For samples generated in this study , mice were bred at UNC-Chapel Hill to generate the required F1 hybrid females . Litters of F1 mouse pups were sacrificed within 24 hours after birth using an approved protocol that minimizes pain and suffering of newborn pups . Mouse genotypes were acquired from recent studies that employed next-generation sequencing [41] , [53] and high-density genotyping array technology [40] , [44] . Tables S1 , S4 , and S6 provide a list of all mice ( inbred and wild-caught ) and the origin of the genotype information . As an initial filtering step , heterozygous and low-confidence genotyping calls were removed from the data set . Heterozygosity within the Xce candidate interval was determined in F2 mouse pups using microsatellite marker DXMit16 ( ∼99 . 3 Mb ) [65] . Genomic DNA was amplified according to previously reported conditions with the exception of a fluorescent label covalently bound to one DXMit16 primer ( 6-FAM-5′-CTgCAATgCCTgCTgTTTTA-3′ ) . 0 . 5 µl of amplified products were resuspended in 9 . 0 µl of HIDI formamide ( Life Technologies ) and 0 . 5 µl of LIZ1200 sizing ladder ( Life Technologies ) . Samples were run on the ABI 3730xl DNA analyzer using long-run fragment analysis conditions . Traces were analyzed with ABI PeakScanner software . At each diallelic variant within the Chadwick interval , we represented the C57BL/6J ( or C57BL/6JN ) allele as zero and all other strains with the same genotype as zero . Strains with the alternative allele are represented with the number one . We then generated strain distribution patterns for each variant as a series of ones and zeros for the strains in the following order: 129S1/SvlmJ , A/J , BALB/cByJ , C3H/HeJ , CBA/J , DDK/Pas , C57L/J , DBA/1J , DBA/2J , and AKR/J ( Table S1 ) . We classified an SDP as completely consistent when all Xcea allele carriers are ones ( share the same allele ) and all Xceb allele carriers are zeros ( share the same allele as C57BL/6J ) ( Tables S1 and S4 ) . We defined an inconsistent SDP when one or more Xcea strain ( s ) are zeros and one or more Xceb strain ( s ) are ones ( i . e . A/J , 129S1/SvlmJ , BALB/cByJ , C3H/HeJ , CBA/J , AKR/J opposite to DDK , C57BL/6J , DBA/1J , DBA/2J ) ( Tables S1 and S4 ) . Lastly , we defined a diallelic variant as partially consistent when one or more Xcea strain ( s ) are zeros or one or more Xceb strain ( s ) are ones ( Tables S1 and S4 ) . mRNA was extracted from tissues of F1 mice using an automated bead-based capture technology ( Maxwell 16 LEV TotalRNA Kits , Promega ) . Purified mRNA was checked for quality and quantity using a Nanodrop spectrophotometer ( Thermo Scientific ) . For each sample , mRNA was retrotranscribed ( SuperScript III , Life Technologies ) to produce cDNA . We designed primers ( Table S7 ) to capture expression SNPs ( Table S8 ) within X-linked genes to serve as surrogates for maternal and paternal XCI status . In individual reactions , we amplified 1 µl of cDNA in a final volume of 30 µl for 35 cycles ( See Table S7 for PCR cycling conditions ) . One primer for each assay was biotinylated in order to immobilize and purify the amplified products using streptavidin beads ( GE Healthcare ) according to the manufacturer's protocol ( Qiagen ) . We used Pyrosequencing technology to measure the proportion of maternal and paternal X-linked gene expression simultaneously . Pyrosequencing quantitatively measures , in real-time , the release of pyrophosphate as a result of nucleotide incorporation during the polymerase chain reaction [66] . Purified , single-stranded amplicons were primed for pyrosequencing using gene-specific primers ( Table S7 ) and pyrosequenced using the PyroMark Q96 MD instrument ( Qiagen ) and PyroMark Gold Q96 Reagents ( Qiagen ) according to manufacturer's protocols . Allelic proportions were determined by the quantitative analysis option of the PyroMark Q96 MD Software . Raw results are show in Table S9 . RNAseq data used in this study is reported elsewhere ( Crowley et al . , 2013 , unpublished ) . Briefly , we generated cDNA libraries ( Illumina ( San Diego , CA ) TruSeq RNA Sample Preparation Kit v2 ) from whole brain mRNA of female reciprocal F1 hybrids between CAST/EiJ , PWK/PhJ , and WSB/EiJ . Using the Illumina HiSeq 2000 instrument , we sequenced 100 bp paired end reads ( 2×100 ) . For each F1 hybrid , we mapped 100 bp paired-end RNAseq reads to pseudogenomes of each parent ( CAST/EiJ , PWK/PhJ and WSB/EiJ ) using TopHat . Pseudogenomes are approximations of CAST/EiJ , PWK/PhJ and WSB/EiJ strain genomes constructed by incorporating all known SNPs and indels into the C57BL/6 genome ( mm9 ) [67] . We allowed two mismatches total per 100 bp read . For each read , we annotated the number of maternal and paternal alleles ( using SNPs and indels ) . XCI ratios were determined by counting the number of maternal reads versus the number of paternal reads . To measure XCI ratios , we selected 10 X-linked genes that are distributed across the X chromosome ( Wdr13 , Atp6ap2 , Usp9x , Cask , Cd99l2 , Idh3g , Dlg3 , Zcchc18 , Tsc22d3 , Iqsec2 ) . For each gene , we selected two informative SNPs between PWK , CAST , and WSB so that at least five of the ten genes were informative for a given F1 hybrid . For each informative SNP , we counted allele-specific reads to determine XCI ratios . Results are summarized in Table S9 . Pyrosequencing and RNAseq provided estimates of the X-inactivation ratios obtaining for particular genes in specific tissues in particular individuals . In order to infer X-inactivation ratios pertaining to individual mice and to the crosses that generated them , we developed a hierarchical Bayesian model linking the observed experimental measurements to a structured set of higher order parameters . These parameters reflected not only the stochastic relationships between measurements , individuals and crosses , but also between different sources of experimental variation . Let be the measured X-inactivation proportion from pyrosequencing or RNAseq in the th gene-tissue combination of the th mouse , and let be the F1 cross to which mouse belongs , where for instance , crosses ( 129S1/SvlmJxPWK/PhJ ) F1 and ( PWK/PhJx129S1/SvlmJ ) F1 are distinct . We first model a latent variable representing the X-inactivation proportion inherent to the individual mouse as if arising from a beta distributionwith cross-specific mean governed by and cross-specific variance proportional to . This individual-specific parameter then forms the basis of a further beta distribution , which models tissue-gene specific measurements as if generated bywhere and are the bias and variance introduced by tissue-gene combination , and where allows for cross-specific variance in X-inactivation . All higher order parameters are themselves modeled in loosely-specified grouped hierarchies based realistic but vague priors ( as in , eg [68] ) . This hierarchical structure allows information and uncertainty to propagate within and between parameters , and results in improved estimation through shrinkage ( see , eg , [69] ) . We obtain posterior distributions for all parameters , including those representing unobserved data , using Markov Chain Monte Carlo ( MCMC ) . Marginal posterior probability densities are computed for parameters for crosses between mice with unknown Xce alleles using information from mice with known alleles . The posterior density that includes the most support for is taken as the most plausible candidate for having Xce allele shared by the unknown strain . In general , posteriors for concentrated near 0 . 5 are more consistent with there being a shared allele between maternal and paternal pairs , whereas posterior densities shifted from 0 . 5 suggest that the Xce is different . The statistical significance of parent-of-origin effects was determined by permutation . We first estimated the difference in specimen-level X-inactivation , , between genetically matched individuals of reciprocal parentage and unequal Xce alleles , and used this estimate as our test statistic . We then repeated this estimation under 10000 shuffles of the parent-of-origin labels in order to generate a null distribution of the test statistic , and thereby estimate a p-value for the parent-of-origin effect in the real data . For each sample , we constructed a vector of Illumina probe intensities of MegaMUGA markers within the refined Xce candidate interval ( Table S10 ) . We then performed principal component analysis on these vectors and report the projection of each sample onto the first three principal components . For each inbred strain and wild-caught mouse , we assigned the subspecific origin of the Chadwick and new Xce candidate interval based on diagnostic alleles from SNP and VINO calls 40 , 51 . We then built DNA distance , maximum likelihood , and DNA parsimony phylogenetic trees ( PHYLIP ( Phylogeny Inference Package ) [70] ) based on all variation within the candidate interval . No major differences were observed between analysis types , so we chose maximum likelihood with 100 bootstraps to represent the phylogenetic relationship between mice in Figure 5B . | Although mammalian females have two X chromosomes in each cell , only one is functional , while gene expression from the other is silenced through a process called X chromosome inactivation . Little is known about the early stages of this process including how one parental X chromosome is inactivated over the other on a cell-by-cell basis . It has been shown , however , that certain inbred mouse strains are functionally different at a locus that controls this choice that provides an opportunity to identify the locus and determine its molecular mechanism . This has been the goal of many researchers over the past 40 years with incremental success . Here we took advantage of new mouse genotype and whole genome sequencing data to pinpoint the locus controlling choice . Our results identified a smaller region on the X chromosome that contains large duplicated sequences . We propose an explanation for multiple functional alleles in mouse and provide insight into the possible molecular mechanism of X chromosome inactivation choice . Our evolutionary analysis reveals why functional diversity at this locus appears to be common in laboratory mice and offers an explanation as to why we do not see this level of diversity in humans . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2013 | Genetic Architecture of Skewed X Inactivation in the Laboratory Mouse |
Antibodies against the prion protein PrPC can antagonize prion replication and neuroinvasion , and therefore hold promise as possible therapeutics against prion diseases . However , the safety profile of such antibodies is controversial . It was originally reported that the monoclonal antibody D13 exhibits strong target-related toxicity , yet a subsequent study contradicted these findings . We have reported that several antibodies against certain epitopes of PrPC , including antibody POM1 , are profoundly neurotoxic , yet antibody ICSM18 , with an epitope that overlaps with POM1 , was reported to be innocuous when injected into mouse brains . In order to clarify this confusing situation , we assessed the neurotoxicity of antibodies D13 and ICSM18 with dose-escalation studies using diffusion-weighted magnetic resonance imaging and various histological techniques . We report that both D13 and ICSM18 induce rapid , dose-dependent , on-target neurotoxicity . We conclude that antibodies directed to this region may not be suitable as therapeutics . No such toxicity was found when antibodies against the flexible tail of PrPC were administered . Any attempt at immunotherapy or immunoprophylaxis of prion diseases should account for these potential untoward effects .
Active and passive immunotherapy that foster the clearance of pathological aggregates represent potential therapeutic strategies against diseases caused by the inappropriate aggregation of proteins [1] . While considerable effort has been devoted to the immunotherapy of Alzheimer's disease with antibodies against the Aβ protein [2 , 3] , transmissible spongiform encephalopathies ( TSE ) represent equally plausible candidates for this approach . TSEs are caused by self-propagating aggregates of PrPSc , a conformer of the cellular prion protein PrPC encoded by the Prnp gene . Active immunotherapeutic strategies in preclinical disease models have rarely yielded significant improvements in survival time after prion inoculation [4 , 5] . In addition , it has proven difficult to induce high-affinity immune responses to PrPC in wild-type mice even in the presence of a variety of adjuvants [6] . Passive immunotherapeutic strategies may be more likely to succeed . A first proof of concept for immunotherapies in prion disease was established with mice genetically engineered to express the heavy chain of an anti-PrPC antibody . These mice were found to be protected against peripheral prion infection [7] . Later , it was observed that passive intraperitoneal immunization with antiprion antibodies ICSM18 and ICSM35 blocked peripheral infection with Rocky Mountain Laboratory strain mouse-adapted scrapie prions ( RML ) , although no beneficial effect was seen upon intracerebral inoculation [8] . With intravenous delivery of the antibodies 31C6 , 110 and 44B1 , a trend towards longer survival could be detected after intracerebral inoculation of the Chandler and Obihiro prion strains [9] . Additionally , osmotic minipumps were used to deliver antibody 31C6 intraventricularly , and this intervention led to a significant prolongation of survival in mice inoculated with prions intracerebrally [10] . Table 1 summarizes the features and outcomes of preclinical active and passive immunization attempts that have been published thus far . On the other hand , chronic intracerebral administration of the antiprion antibody 4H11 resulted in severe side effects , including nerve cell loss , gliosis , and microglial activation [13] . Similar toxic side effects were detected by us and others after stereotaxic injection of various anti-PrPC antibodies , apparently strictly dependent on the particular PrPC epitope targeted by the respective antibody [14 , 15] . Whilst all of the above findings have raised concerns about the safety of anti-PrPC immunotherapies , Klöhn et al . [16] reported that they did not reproduce the neurotoxicity described for antibody D13 . Furthermore , they reported no acute toxicity in vivo for their own antibodies ICSM18 and ICSM35 . The study by Klöhn et al . is surprising , not only because it contradicted earlier reports of D13 toxicity , including our findings of lesions upon injection of D13 into PrPC-overexpressing tga20 mice [17] , but also because of our previously published results that 7/12 antibodies to the globular domain of PrPC are acutely neurotoxic [15] . Interestingly , crystallographic studies revealed that ICSM18 and the neurotoxic antibody POM1 share a conspicuous overlap in their respective epitopes . In particular , both antibodies have close intermolecular contacts ( <4Å ) to the amino acid side chains Ser143 , Asp144 , Tyr145 and Lys204 of human PrP [18 , 19] . The first three amino acids correspond to the murine residues Asn143 , Asp144 and Trp145 , which are part of the murine PrP binding interface of ICSM18 [20] , confirming epitope similarities between the two species . If residues with an interaction distance shorter than 5 Å are included , the shared interface between the two antibodies is even more impressive and encompasses 9 amino acids ( S1 Fig ) . The apparent discrepancy in the toxicity of POM1 and ICSM18 is of great theoretical and practical interest . Toxic anti-PrPC antibodies induce damage by triggering pathways similar to those detected in bona fide prion infections , including activation of calpains and the PERK pathway as well as the production of reactive oxygen species [21] . Mechanistically , the flexible tail at the amino-terminus of the prion protein mediates the toxicity of antiprion antibodies by binding to the globular domain of PrP [15] . Therefore , aside from the obvious issues of safety for human clinical trials , understanding why two antibodies directed against extremely similar epitopes might display such divergent on-target toxicity may advance our understanding of prion pathogenesis . In order to address the above questions , we set out to replicate the experiments described by Klöhn et al . In addition , as behooves any systematic toxicological study , we expanded our experiments to include the dose-response analyses that had not been performed in previous studies .
We stereotaxically injected antibody D13 ( 2 μg in 2 μl PBS ) into the left Cornu ammonis region-1 ( CA1 ) of the hippocampus of male 3–4 month old C57BL/6 ( designated BL6 ) mice . The coordinates were identical to those used in previous studies with this antibody [14 , 16] . For control , D13 antibody pre-incubated ( 1h , room temperature ) with a three-fold molar excess of a recombinant murine PrP fragment encompassing residues 90–231 ( rmPrP ) was injected into the right ( contralateral ) hippocampus . Histological examination at 48h post injection ( p . i . ) and diffusion weighted magnetic-resonance imaging ( DWI ) 24h p . i . failed to reveal any lesion at either the injection site , other than mild traumatic damage and acute extravasation limited to the immediate vicinity of the stereotaxic needle track ( Fig 1A–1C , upper row ) . We then reasoned that despite their monoclonal origin , the biological activity of antibodies can vary between batches . Furthermore , even the assessment of protein concentration can vary between labs and can depend on the specific methodology utilized . As the dose dependence of antiprion antibodies ( e . g . POM1 , D13 ) has already been demonstrated ex vivo [15]; therefore , we examined the toxicity of D13 over a range of antibody concentrations . Indeed , when 6 μg or 12 μg of D13 were injected , a conspicuous hyperintense lesion became apparent at 48h p . i . by DWI in the hippocampus and/or cortex ( Fig 1A , middle and lower row; S1 Table ) . Again , the contralateral hippocampi were injected with D13 antibody preincubated with its cognate antigen using the procedure described above did not display any DWI signal alteration . Histologically , D13 ( 48h p . i . ) caused conspicuous edema and widespread acute neuronal damage affecting widespread cortical and/or hippocampal areas ( Fig 1B and 1C , middle and lower row ) . Affected neurons displayed condensed hyperchromatic nuclei and hypereosinophilic cytoplasm ( Fig 1C , middle and lower ) . Some neurons showed prominent nuclear fragmentation . We then quantified the hyperintense signal by volumetry ( S1 Table ) : statistical analysis revealed significant lesion induction at 6 μg and 12 μg D13 compared with D13 injection at 2 μg and injection of D13 ( 12 μg ) preincubated with rmPrP ( Fig 1D ) . In order to estimate the upper limit of the D13 intracerebrally injected safe dose , we performed a benchmark dose analysis which yielded a dose of 3 . 7–5 . 4 μg ( S2A Fig ) [22] . It was originally reported [14] that D13 injection results in apoptosis , as visualized by positive labelling for terminal deoxynucleotidyl transferase dUTP nick end labelling ( TUNEL ) [16] . We found TUNEL-positive cells in lesions of mice injected with 6 μg , but not in the control injections with antigen-preincubated D13 ( Fig 1E ) . In contrast , activated caspase-3 ( aC3 ) immunohistochemistry labelled only a few cells ( Fig 1F ) . This result is in line with the previous report that the neurotoxicity of anti-PrPC antibodies does not lead to caspase activation and cannot be suppressed by caspase inhibition [23] . Next , we addressed the possible toxicity of antibody ICSM18 after intracerebral injection . Again we performed stereotaxic inoculations into the left CA1 region of the hippocampus . In order to exclude gender and strain-dependent confounders , we performed this experiment in female C57BL/10 ( henceforth designated BL10 ) mice as in Klöhn et al [16] . For control , we administered IgG1 isotype control ( BRIC222 , 6 μg ) into the contralateral stereotaxic position , in order to replicate all details of the Klöhn study [16] . Because only limited amounts of ICSM18 were available , we were unable to perform control experiments with antigen-blocked ICSM18 antibody . DWI visualized a small lesion 24h p . i . in 1/5 mice injected with 6 μg of ICSM18 , whereas no lesions were seen in the control group ( Fig 2A , S1 Table ) . Serial sections ( 48h p . i . ) stained with haematoxylin-eosin ( HE ) revealed a lesion histologically similar to those observed after D13 injection and eminently distinguishable from the traumatic needle track damage by the presence of widespread condensed nuclei ( Fig 2B and 2C ) . This finding raised concern that ICSM18 might be neurotoxic , yet statistical analysis failed to reveal significant differences between ICSM18 injections and contralateral isotype control injections in BL10 mice ( Fig 2K ) . The above finding merited a more complete investigation . However , the limited amounts of ICSM18 available to us precluded extensive dose-escalation experiments . We therefore performed CA1 injection into tga20 ( females ) and into prion protein-ablated mice ( Prnp°/° females ) for control . We found that ICSM18 induced lesions in tga20 but not in Prnp°/° mice ( S3A and S3B Fig , upper row , S3C and S3D Fig ) . No lesions were observed after injection of the POM2 antibody which had been previously established to be innocuous [15] . We considered that injection into an anatomical area with a denser and distinct neuronal population might influence lesion induction . We therefore administered ICSM18 ( 6 μg ) into the hippocampal CA3 region close to the dentate gyrus of tga20 mice . Here , we found a more robust induction of neurotoxicity in contrast to the CA1 injection ( S3A and S3B Fig , lower row , S3D Fig ) . Using the CA3 injection coordinates , we then performed injections at 2 μg and 6 μg ICSM18 into BL10 mice , in order to estimate the boundaries of a safe dose . A dose of 6 μg ICSM18 induced significant hyperintense lesions in contrast to 6 μg of BRIC222 ( Fig 2D , upper row , Fig 2K; S1 Table ) , subsequently confirmed by histological analysis ( Fig 2E and 2F , upper row ) . No lesions were found after injection of 2 μg ICSM18 ( Fig 2J and 2K ) . Accordingly , we were able to estimate 3 . 1 μg as the upper limit of the ICSM18 intracerebrally injected safe dose ( S2B Fig ) . To test for gender and strain-dependent effects , we injected 6 μg ICSM18 into BL6 males and females . We identified a trend towards more severe lesions in BL6 compared to BL10 females , but the differences were not significant ( Fig 2D–2F , middle and lower row , Fig 2K ) . As the binding interface of ICSM18 and POM1 overlaps we next asked if the deleterious effect of both antibodies is comparable . Quantitative analysis revealed no significant difference between the toxicity of ICSM18 and POM1 , whereas injection of POM1 pre-incubated with mrPrP did not induce a lesion ( Fig 2G–2I and 2K ) . In order to obtain information about the tissue penetration of intracerebrally injected antiprion antibodies , we used a previously described approach for chronically administering antiprion antibodies [10] . We used antibody POM2 [24] , which recognizes the PrPC octapeptide repeat motif , conjugated to the fluorescent dye Cy5 . POM2 was previously shown to be nontoxic , and elevated interstitial fluid pressure within the lesions may increase tissue penetration [25] . Therefore , POM2 could help evaluate the diffusion of high-affinity antiprion antibodies in the absence of tissue damage . According to previous studies , diffusion is inversely proportional to the density of antigen [26] but independent of affinity as long as the dissociation constant Kd is <10nM . [27] . As in previous experiments , we administered the Cy5-POM2 conjugate ( 2 or 6 μg in a volume of 2μl ) into the CA3 region . Frozen sections were obtained 24h post injection . We found labeled antibody to be distributed mainly within the hippocampus ( Fig 3A and 3B ) . As reported previously , the fluorescence pattern showed a relatively sharp border between labeled and unlabeled tissue rather than a continuous gradient [26 , 28] . This property allowed us to define a distribution volume of 1 . 8 and 5 mm3 for the injection of 2 and 6 μg , respectively ( Fig 3C ) . This observation is in line with the known dependence of antibody diffusion velocity on concentration [29] . The estimated distribution volumes appeared larger than the lesional volumes at the investigated doses ( e . g . 1 . 2 vs . 5 mm3 , respectively , for antibody D13 at 6 μg ) . In order to better understand this relationship , we determined the ratio between lesional and distribution volume at 6 μg ( S1 Table ) , and found it to be 25% for D13 and 4–8% for ICSM18 . In both dose groups , only minimal Cy5 fluorescence was detected within the brain in one out of three injections ( Fig 3C ) . This phenomenon may possibly result from accidental intravascular injection , and may provide another explanation for the variability in the size of the lesions ( e . g . 12 μg of D13 ) . Because of limited penetration , intrathecal injection of high-affinity antiprion holoantibodies will unlikely represent the optimal therapeutic choice against prion diseases , a disease that affects the entire brain . Antibody derivatives with a more efficient tissue penetration are preferred , including lower-molecular weight binders [29] . Furthermore , stereotaxic intracerebral administration of a single dose of antiprion antibodies does not represent a realistic approximation of clinical drug administration . To better simulate potential clinical situations , we administrated continuously a single-chain variable fragment ( scFv ) version of antibody POM1 ( Kd: 800nM [24] ) using an osmotic minipump . The osmotic minipumps were loaded with 75 μg POM1 ( 0 . 6 μg/μl ) and dispensed antibody at a rate of 0 . 25 μl/h for 21 days to tga20 . Echoplanar DWI at 4 days after pump implantation showed that POM1 induced hyperintense lesions spreading from the area around the implanted cannula . No lesions were seen in Prnp°/° mice subjected to the same procedure ( Fig 4A ) . The hyperintense signal regressed 11 days post implantation ( Fig 4B ) . Manganese enhanced magnetic resonance imaging ( MEMRI , Fig 4C ) and HE-stained histological sections ( Fig 4D and S4 Fig ) confirmed the presence of large cystic lesions at 21 days post implantation . Volumetric quantification of the lesions seen by MEMRI image indicated that 9±3% of the total brain volume in tga20 mice , and 1±0% in Prnp°/° mice , was affected . This quantification may underestimate the overall tissue damage , as conspicuous astrogliosis and microgliosis were found in both hemispheres indicative of generalized brain involvement ( Fig 4E and S4 Fig ) .
Klöhn et al . were unable to reproduce the initial report [14] of D13 toxicity , and concluded from their experiments that "PrP antibodies do not trigger mouse hippocampal neuron apoptosis" [16] . However , the results presented here indicate that this conclusion is not universally correct . We found that both the ICSM18 and D13 antibodies are neurotoxic in paradigms seemingly identical to those used in the studies of Klöhn et al . In all likelihood the lesions described here may have been missed by Klöhn et al . , because their chosen dosage approximated but did not reach the minimal toxic concentration . This outcome vividly depicts the necessity to perform accurate dose-escalation studies when studying the toxicity of potential therapeutics . Beyond the obvious dosage-related issues , several additional confounders and pitfalls may have contributed to the inability of others to detect toxicity . For example , the purity and age of antibody batches can affect toxicity in ways that may be subtle and difficult to control . Next , we have found that variations in the injection coordinate can influence the volume of lesions . Possible explanations for this finding include the selective vulnerability of different neuronal populations in the hippocampus to antiprion antibodies . Similar differences are seen in other pathological conditions such as ischemia [30] , toxins [31] and various neurodegenerative diseases [32] . Another explanation is that extracellular fluid is drained differentially from distinct brain sites . Interestingly , we found a trend towards larger lesion in BL6 mice in contrast to the BL10 mice used by Klöhn et al [14] , which probably also affected the detection of ICSM18 induced neurotoxicity . In fact , these two mouse wild type strains have been found to display different responses to pathogens in other settings [33 , 34] . Whilst we could reproduce the initial report of D13 neurotoxicity , we found the toxicity threshold to be higher than originally reported by Williamson et al . This quantitative discrepancy is suggestive of different biological activities of the antibody batches used in previous studies and may be related to the specific methodologies used for protein generation and purification . The estimated hypothetical upper safe dose was higher for ICSM18 than for D13 . A difference in biological activities of both antibodies cannot be fully excluded , as it was not possible to generate both antibodies in our laboratory . Thus , our data may not be sufficient to directly compare the two antibodies . However , the POM1 antibody , whose epitope overlaps with that of ICSM18 , shows an equivalent response to the latter . We therefore speculate that there is a relation between the binding epitope and dose-response relationship , which in line with the observation that toxicity is epitope-dependent [15] . Our results are not surprising considering that neurotoxicity was identified as a potential hazard of antiprion immunotherapy by many laboratories [13–15] . Since toxicity was found to be reproduced with single-chain variable fragments and F ( ab ) 1 fragments of antibodies , it seems related to "on-target" interaction with PrP , rather than antibody effector functions . Depending on the ratio between the dosage required for effectiveness and the toxicity threshold , such vulnerability may represent a surmountable obstacle for the development of therapeutic antibodies . The first patients envisaged for clinical studies will likely be those suffering from sporadic CJD ( sCJD ) , since this is the most frequent prion disease in humans . sCJD is hypothesized to begin with the spontaneous misfolding and aggregation of prion protein within the brain . Accordingly , informative pre-clinical studies should prove the efficacy in disease models where prions are inoculated intracerebrally . However , a cumulative dose of 8 mg of ICSM18 ( injection of 2 mg intraperitoneal twice weekly ) was shown to be ineffective against intracerebral prion inoculation [8] . It is plausible that the antibody passes through the blood brain barrier in sufficient amounts only at the terminal stage of the disease , as was found in the case of antibody 31C6 [9] . Thus , it may be necessary to select an intracerebroventricular route of administration . The only published study on delivering anti-prion antibody via this route ( 31C6 ) used 336 μg ( 0 . 5 μl/h , 14 days , 2 mg/ml ) to achieve a significant but small prolongation of survival in prion inoculated mice [10] . However , when we administered POM1 in a similar dose range intracerebroventricularly using osmotic minipumps , we found massive destruction of brain matter . These results along with the lack of preclinical data on the chronic toxicity of ICSM18 mandate particular caution with respect to the possible intrathecal administration of ICSM18 . We considered the possible impact of species-specific Prnp polymorphisms on antibody toxicity . Although we have only investigated the interaction of ICSM18 with murine PrPC , similar effects are likely to occur in humans since the atomic pivots contributing to the binding were found to be similar in the two species [20] . The minor differences between the binding of ICSM18 to the human and murine α3 helix are likely due to the inferior resolution of mutational scanning compared to crystallographic epitope mapping . After chronic scFvPOM1 delivery by osmotic minipumps , we found lesions similar in size and distribution to the previously described diffusion pattern of antiprion antibodies [10 , 13] . In contrast , after a single stereotactic injection we identified lesions in only 4–25% of the total antibody distribution volume . Hence chronic administration induces cumulative damage over days [10] with lesion size being superimposable to the distribution volume , even at relatively low antibody concentrations ( 0 . 5 μg/μl scFvPOM1 ) . While sobering , these results do not indicate that antiprion immunotherapy is inherently unsafe . In fact , we reported earlier that 5 of 12 “POM” antibodies tested against PrPC did not show any cytotoxicity in organotypic slice cultures , and the innocuousness of the octapeptide repeat ligand POM2 was confirmed in vivo with up to 6 μg in PrPC-overexpressing tga20 mice [15] . Moreover , other antibodies including 31C6 , 44B1 , and 110 [9 , 10] , did not show untoward effects at high doses in preclinical efficacy studies . A meta-analysis of many published studies ( Table 2 ) points to a relationship between binding epitopes and neurotoxicity in vivo , with toxicity appears to be strictly dependent on well-defined epitopes of the globular domain of PrPC . Antibody 31C6 was reported to bind residues 143–149 on the α1 helix of PrPC , thus encompassing three amino acids with close intermolecular contacts to POM1 and ICSM18 . Also antibody D18 , reported to be innocuous , binds to these residues . Neither of these two antibodies is described to engage epitopes on the α3 helix ( e . g . Lys204 ) . Hence engagement of the α3 helix may be important in mediating neurotoxicity . However , this interpretation is currently speculative since D18 has not been tested in a rigorous dose-escalation study , nor has high-resolution epitope mapping been applied to these antibodies . Conversely , antibodies binding the flexible tail of PrPC seem to be generally well-tolerated and , in our view , are more amenable to the development of safe and effective antiprion immunotherapies . POM1 was toxic to wild-type organotypic cerebellar slices at 167 nM ( 25 ng/μl ) [15] which is ca . 100-fold lower than the toxic concentration in vivo ( 20 μM; 3 μg/μl ) . This is unsurprising , since organotypic slices were exposed continuously to POM1 and diffusion from the site of injection would massively reduce the half-life of the antibody at the site of injection , whereas little degradation of the antibody is expected to occur in vitro . For antibody D13 , whose epitope is similar to that of POM3 , the situation may be more complex . In organotypic slices , D13 showed limited intrinsic toxicity at relatively high concentrations . However , when administered at lower concentration , D13 protected slices from POM1 toxicity . This behavior is compatible with the hypothesis that D13 is a partial competitive agonist which competes with POM1 for a pathogenic target . In summary , these data illustrate that the efficacy profile ( i . e . the curative effectiveness versus the potential toxicity ) of antiprion antibodies is complex and depends both on intrinsic factors such as , crucially , the nature of the engaged epitope , and extrinsic factors such as the route of administration . Detailed analyses and mapping of the involved epitopes and—most importantly—appropriate dose-escalation studies in vivo are prerequisite not only for preparing clinical trials in humans , but also to avoid the reporting of contradictory , confusing , and potentially misleading results .
Mice were housed under specific pathogen-free conditions . Female and male inbred mouse strains C57BL/6JOlaHsd1 ( BL6 ) were bred in-house . C57BL/10 ( BL10 ) were purchased from Harlan or from the Jackson laboratory . Coisogenic BL6 . 129-Prnpo/o , BL6 . 129-Prnpo/o-tga20+/+ ( tga20 ) mice were bred on a mixed 129S2/SvHsd and C57BL/6JOlaHsd1 background [17 , 39 , 40] . Animal care and all experimental protocols were in accordance with the “Swiss Ethical Principles and Guidelines for Experiments on Animals” , and approved by the Animal Experimentation Committee of the Canton of Zurich ( permits 130/2008 and 41/2012 ) . Animal care and protocol guidelines were obtained from http://www . blv . admin . ch/themen/tierschutz/index . html ? lang=en and strictly adhered to by the experimenters and animal facility at the institution where the experiments were performed . All compounds were purchased from Sigma/Aldrich unless otherwise stated . POM [24] and D13 monoclonal antibodies [37] were produced in-house using hybridoma technology and purified by affinity chromatography using protein G sepharose and diluted in PBS . Silver-stained SDS-PAGE gels showed that antibodies were essentially pure . Monoclonal ICSM-18 ( produced based on hybridoma technology and purified by affinity chromatography ) was provided in limited amounts from Simon Hawke and dialyzed against PBS prior to intracerebral injection . Recombinant mouse PrP was generated in E . coli , purified by affinity chromatography and on-column oxidized and refolded into its native state [41] . BRIC222 was purchased from American Research Products ( Waltham MA 02452 , USA ) . For MEMRI , mice received five intraperitoneal injections of MnCl2 ( 40 mg/kg , 20 mM in H2O and bicine , pH 7 . 4 ) at 12h intervals [42] . The final injection was administered immediately after the stereotaxic injection . For imaging acquisition , the mice were placed under isoflurane anesthesia at 4h , 24h and 72h post-surgery . Initially , the mice were placed on a bed equipped with a mouse whole-body radio frequency transmitter coil and a mouse head surface-coil receiver and then into the 4 . 7 Bruker Pharma scan . Body temperature was maintained with a warming blanket . For MEMRI T-1 weighted brain images were obtained using a 3D gradient-echo sequence with the following parameters: TR: 15 ms , TE: 2 . 5 ms , flip angle: 20 deg , average: 10 , Matrix: 265/265/126 Voxel , Field of View: 2x2 . 56x2 cm3 , acquisition time: 1h , Voxel size: 78x100x156 μm3 . For DWI , routine gradient echo sequences with the following parameters were used: TR: 300 ms TE: 28 ms , flip angle: 90 deg , average: 1 , Matrix: 350 x 350 , Field of View: 3 x 3 cm , acquisition time: 17 min , voxel size: 87x87 μm3 , slice thickness: 700 μm3 , Isodistance: 1400 μm3 and b values: 13 , 816 s/mm2 . For chronic treatment , diffusion weighted images were assessed with an echo planar sequence with: TR: 7500 , TE: 44 . 6 , Voxel size: 0 . 1x0 . 1x0 . 7 mm , b value: 500 s/mm2 . Quantification was performed with ParaVision software ( Version 5 , Opl3 , Bruker ) . Lesions were quantified by assessing two regions of interest ( ROIs ) , corresponding to the lesion and the total cerebellar ( or hippocampal ) area . ROIs were set for each optical slice of the data set . In order to quantify hippocampal lesions with MEMRI scans , the volume of non-affected CA3 was measured . ROIs were set on the ipsilateral and contralateral sides of injection . Volumes for each ROI were calculated by multiplying the sum of the ROI area by the voxel height . Data are presented as the lesion volume divided by the total cerebellar volume or hippocampal volume . For hippocampal lesions assessed by MEMRI scans , data are presented as CA3 volume ( mm3 ) , separated by ipsilateral versus the contralateral side . For the statistical analysis of experiments involving the comparison of three or more data sets , we used the one-way ANOVA with Dunnett’s post-hoc test . The two-tailed unpaired Student’s t-test was used to compare two data sets . The results are displayed as mean ±s . d . *: P<0 . 05; **: P<0 . 01; ***: P<0 . 001 , ****: P<0 . 0001 . Dose response analysis and the benchmark dose relation were calculated with benchmark dose software ( BMDS ) 2 . 4 ( United States Environmental Protection Agency ) . Dose-response relations were fitted to the dataset ( log10 values ) using the following equation: ( Y[ dose ] = intercept+v*dosen/ ( kn+dosen ) . The intercept was defined as the mean lesion volume after control injection , which equals 0 . 05 mm3 . The mean lesion volume was calculated by volumetric quantification of the hyperintense signal after BRIC222 and rmPrP preincubation injections at the different doses . The v value of the equation was set to the different maximal lesion volumes in order to model the different scenarios . For the BMD analysis of D13 and ICSM18 we used the mean and maximal lesion volume from the 12 μg D13 injection group ( parameters from the log10 values ) , 3 . 68 mm3 and 40 mm3 respectively , and 453 mm3 the mean brain volume of wild type ( BL6 ) mice [43] , which is the theoretical maximal possible response . Additionally for the BMD analysis of ICSM18 we used the maximal lesion volume after 6 μg ICSM18 injection ( 0 . 4 mm3 ) . The adverse effect level , also referred to as the benchmark response ( BMR ) , equals 0 . 15 mm3 , and was established at 0 . 1 over the mean lesion volume after control injection . Of note , we used the absolute definition of the adverse effect level [22] . The BMR was fitted to the graph with the equation Y[dose] = 0 . 15 . Benchmark doses ( BMD ) represent the intercept of the BMR line with the fitted curve . To estimate the upper limit of the D13 intracerebrally injected safe dose , the lower 95% confidence limit of the BMD was calculated . Mice were anaesthetized with isoflurane and placed in a motorized stereotaxic frame controlled by software with a three-dimensional brain map , allowing for real-time monitoring of needle placement ( Neurostar ) . The skull was exposed by a midline incision and a small hole was drilled using a surgical drill . The needle ( Hamilton , pstAS , gauges 26 s ) was then mounted in an electronic micro-injector unit and was placed for cerebellar injection at the following lambda coordinates: AP -2 . 3 mm , ML 0 mm , DV 2 mm , for CA1 injection at: A/P: -2 mm , ML: 1 . 3 mm , DV: -1 . 4 mm from Bregma or for CA3 injection at the following Bregma coordinates: AP– 2 mm , ML ±1 . 7 mm , DV 2 . 2 mm , angle in ML/DV plane 15° . Antibodies ( 2 μl ) were injected at a flow rate of 0 . 5 μl/min . After termination of the injection , the needle was left in place for 3 min . The surgical wounds were sutured , and mice received an injection of buprenorphinum ( 0 . 1 mg/g body weight ) . Mice were euthanized after the last scan and the brains were fixed in 4% formalin . Cerebella or a 4 mm coronal section from the posterior cortex were paraffin embedded and 2 μm coronal step sections ( standard every 100 μm ) were cut , deparaffinized and routinely stained with hematoxylin and eosin . For immunohistochemistry , sections were deparaffinized through xylol and graded alcohols . Then , heat-induced epitope retrieval in the microwave was performed in 10 mM citrate buffer at pH 6 . Sections were incubated for 1h in blocking buffer ( 0 . 2% Triton X-100 , 10% normal goat serum dissolved in phosphate-buffered saline: PBS ) and incubated with rabbit polyclonal either anti-Caspase3 ( 5 μg/ml , Milipore ) , rabbit polyclonal anti-GFAP ( 10 μg/ml , Dako ) or rat monoclonal anti-CD68 ( 10 μg/ml , Abd Serotec ) diluted in blocking buffer at 4°C overnight . For 3 , 3′-diaminobenzidine tetrahydrochloride hydrate ( DAB ) immunohistochemistry , sections were washed with PBS and incubated for 1 hour at room temperature with the specific biotinylated secondary antibody ( 10 μg/ml , Vector Laboratories ) . Sections were then washed with PBS and incubated with horseradish peroxidase-avidin/biotin complex ( Vector Laboratories ) . For visualization , sections were incubated for 5 minutes in DAB ( 0 . 5 mg/ml ) dissolved in phosphate buffer ( 0 . 1 M , pH 7 . 4 ) , and DAB conversion into an insoluble brown product was induced with hydrogen peroxide . For immunofluorescence detection , brain sections were incubated with fluorescently-labeled secondary antibody ( 1 μg/ml Alexa Fluor 488 ) . In the final PBS wash , 4 , 6-diamidino-2-phenylindole dihydrochloride ( DAPI; Molecular Probes ) was added , and sections were mounted with Fluor Save ( Calbiochem ) . For analysis , pictures were taken with a FluoView FV10i Confocal Laser Scanning System . During apoptotic cell death , DNA is fragmented by endonuclease activity . Free hydroxyl groups at the 3’end can be labeled by the enzyme Terminal deoxynucleotidyl transferase ( TdT ) with labeled nucleotides , a method known as Terminal Uridine Deoxynucleotidyl Transferase dUTP nick end labeling ( TUNEL ) staining . The in situ Cell Death Detection kit ( Roche ) was used according to the manufacturer’s instructions . In brief , two micrometer sections of paraffin-embedded brain tissue were deparaffinized , rehydrated and incubated with proteinase K ( PK ) 20 μg/ml for 10 min at 37°C to break through the formalin fixation induced protein cross links . Then the sections were incubated with the working-strength terminal deoxynucleotidyl transferase ( TdT ) enzyme and digoxigenin labeled dUTP for 60 min at 37°C , following staining with fluorescently labeled anti-digoxigenin antibody . Sections were counterstained with DAPI . The entire antibody POM2 was labeled with using the Cy5 mAB labeling kit ( GE Healthcare Amersham ) and injected into the hippocampus of 3-month-old mice . Twenty-four hours post-antibody injection , mice were euthanized and 4 mm coronal sections of the posterior cortex were embedded in Hanks balanced salt solution and frozen with liquid nitrogen . Cryosections ( 10 μm thick ) were prepared and stained with DAPI ( Molecular Probes ) and mounted with Fluor Save ( Calbiochem ) . Every tenth section was imaged with the virtual microscope AxioScan Z1 ( Zeiss ) . Regions of interest ( ROI ) defining the area of the antibody were set for every image and volumes were calculated by multiplying the total ROI area by the slice thickness . Osmotic minipumps ( Alzet Model 2004 0 . 25 μl/h ) were filled with antibody diluted in PBS , according to the manufacturer’s instructions . Filled pumps were placed in PBS at 37°C for 24h . Tga20 was anaesthetized with isoflurane and placed in a motorized stereotaxic frame as described above . Next , the skull was exposed via an incision along the midline . Using blunt surgical dissection , a paraspinal , subcutaneous pouch was generated , in which the pump was positioned . A MRI compatible polyether etherketone medical microtubing ( Alzet ) was connected to the pump and positioned at the following Bregma coordinates: AP -0 . 22 mm , ML 0 . 9 mm , DV 2 . 5 mm and fixed to the skull with glue ( AdheSe One F Viva Pen Refill and Heraeus Kulzer FLOWline ) . Mice were housed individually after surgery . Post intervention , the mice were treated with subcutaneous injections buprenorphinum ( 0 . 1 mg/kg , Reckitt Benckiser , Switzerland ) , funixin ( 5 mg/kg , Provet AG , Switzerland ) and glucose 5% ( 20 μl/kg ) . Sulfadoxinum ( 2 ml of 24% , Veterinaria AG , Switzerland ) and sugar ( 30 g ) were added per liter of drinking water for one week post-surgery . | The human prion disease , Creutzfeldt-Jakob disease ( CJD ) , is a progressive neurodegenerative syndrome . Although far less prevalent , CJD shows many molecular and clinical similarities to Alzheimer's disease , such as the buildup of protein aggregates in the brain and the absence of effective treatments . Many attempts at immunotherapy for Alzheimer’s disease are being reported in specialized journals and in the lay press , and have been linked to strong hopes for a cure . The same therapeutic strategy appears plausible for Creutzfeldt-Jakob disease , and indeed , there are some encouraging preclinical studies . However , there have also been reports that antibodies against the prion protein ( PrPC ) can also wreak damage on the brain . We have gathered evidence that various antiprion antibodies vary not only in their efficacy but also in their potential to induce serious untoward effects . In a dose-escalation study , we report that all antibodies against a set of epitopes in the globular domain of the prion protein display acute neurotoxicity . These issues need to be carefully assessed before considering any clinical studies involving human subjects . | [
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"magnet... | 2016 | Differential Toxicity of Antibodies to the Prion Protein |
Proneural genes are among the most early-acting genes in nervous system development , instructing blast cells to commit to a neuronal fate . Drosophila Atonal and Achaete-Scute complex ( AS-C ) genes , as well as their vertebrate orthologs , are basic helix-loop-helix ( bHLH ) transcription factors with such proneural activity . We show here that a C . elegans AS-C homolog , hlh-4 , functions in a fundamentally different manner . In the embryonic , larval , and adult nervous systems , hlh-4 is expressed exclusively in a single nociceptive neuron class , ADL , and its expression in ADL is maintained via transcriptional autoregulation throughout the life of the animal . However , in hlh-4 null mutants , the ADL neuron is generated and still appears neuronal in overall morphology and expression of panneuronal and pansensory features . Rather than acting as a proneural gene , we find that hlh-4 is required for the ADL neuron to function properly , to adopt its correct morphology , to express its unusually large repertoire of olfactory receptor–encoding genes , and to express other known features of terminal ADL identity , including neurotransmitter phenotype , neuropeptides , ion channels , and electrical synapse proteins . hlh-4 is sufficient to induce ADL identity features upon ectopic expression in other neuron types . The expression of ADL terminal identity features is directly controlled by HLH-4 via a phylogenetically conserved E-box motif , which , through bioinformatic analysis , we find to constitute a predictive feature of ADL-expressed terminal identity markers . The lineage that produces the ADL neuron was previously shown to require the conventional , transient proneural activity of another AS-C homolog , hlh-14 , demonstrating sequential activities of distinct AS-C-type bHLH genes in neuronal specification . Taken together , we have defined here an unconventional function of an AS-C-type bHLH gene as a terminal selector of neuronal identity and we speculate that such function could be reflective of an ancestral function of an “ur-” bHLH gene .
Nervous system development proceeds through sequential steps , starting with the early commitment to a neuronal fate , followed by the progressive restriction of fates , to finally reaching a terminal , differentiated end state . Proneural genes of the basic helix-loop-helix ( bHLH ) family play a key role in the initial stages of this process [1] . Mutant analysis in Drosophila revealed that loss of members of the Achaete-Scute complex ( AS-C ) , as well as the related Atonal gene , resulted in the loss of the ability to generate neuroblasts in the peripheral nervous system [2–5] . Vertebrate orthologs of proneural AS-C and Atonal genes ( the Mash and Math genes ) also provide critical proneural function in vertebrate nervous system development [1 , 6–8] . Thus , the proneural function of AS-C-type and Atonal bHLH genes is broadly conserved throughout evolution . The C . elegans genome encodes a canonical complement of homologs of proneural bHLH genes , including seven AS-C-like genes ( hlh-4 , hlh-3 , hlh-14 , hlh-19/hnd-1 , hlh-12 , hlh-6 , hlh-16 ) and one Atonal ortholog ( lin-32 ) [9] . The function of many of these C . elegans bHLH genes in the nervous system has not been as extensively studied as their fly and vertebrate orthologs , but it is nevertheless clear that a number of these bHLH genes also provide proneural activities [10–12] . Like in flies and vertebrates , C . elegans proneural bHLH genes operate in a lineage-specific manner . For example , the C . elegans AS-C ortholog hlh-14 and the C . elegans Atonal ortholog , lin-32 , provide proneural activity in several distinct sensory neuron lineages of the peripheral and central nervous system ( CNS ) of the worm [10–12] . In both cases , the proneural activity of hlh-14 and lin-32 is exemplified by a transformation of neuroblasts into cells with a hypodermal identity in the respective mutant backgrounds . One question that has been studied extensively over the years is whether AS-C/Atonal-type bHLH genes have functions in the nervous system that go beyond their proneural activity . In both vertebrates and flies , nonproneural functions of AS-C and Atonal-like genes have indeed been described in the context of later neuronal differentiation events ( reviewed in [1 , 6 , 13] ) . Similarly , C . elegans lin-32/Ato has functions beyond its proneural activity in male ray lineages in which lin-32 also allocates fates in subsequently developing ray sublineages [14] . However , in all these cases , the respective bHLH gene is either transiently expressed; acts through downstream , intermediary regulatory factors; or only affects selected aspects of the differentiated state of the respective neuron . In this study , we describe a novel , nonproneural , and noncanonical function of an AS-C-type bHLH gene . We find that the AS-C homolog hlh-4 displays a spatial and temporal specificity of expression that is unprecedented for any bHLH gene . hlh-4 is exclusively and continuously expressed in a single postmitotic nociceptive sensory neuron class in which it initiates and maintains the terminal identity of this neuron via direct binding to scores of terminal effector genes that are expressed in a neuron class–specific manner and that define the differentiated state of this neuron . Among its many functions in ADL , hlh-4 directly regulates the expression of the unusually large repertoire of olfactory receptor proteins in ADL . We hypothesize that the direct control of “neuron function genes” may have been an ancestral function of bHLH genes .
Strains were maintained by standard methods [15] . A list of all strains used is listed in S3 Table . Green fluorescent protein ( GFP ) reporters for rescue and ectopic expression were generated using RF-cloning [16] . For making G-protein coupled receptor ( GPCR ) transgenic reporters ( listed in S3 Table ) , a PCR fusion approach was used [17] . Genomic fragments were fused to the GFP coding sequence , which was followed by the unc-54 3′ untranslated region . All transgenic lines created in this study were injected at 50 ng/μL with the unc-122::gfp into wild-type animals or with the pha-1 rescuing plasmid ( pBX ) as a coinjection marker ( 50 ng/μL ) into pha-1 mutant animals . For each construct , two independent lines were scored . Fosmid-based reporters for hlh-2 , hlh-3 , and hlh-4 were generated by insertion of yfp at the 5′ end of the hlh-2 locus [18] , 3′ end of hlh-4 ( this paper ) , and gfp at the 3′ end of hlh-3 [19] using standard fosmid recombineering approaches [19 , 20] . The arrd-4 promoter ( 1 , 587 bp ) was cloned together with hlh-4 genomic sequences and unc-54 3′UTR into a pPD95 . 75 backbone and injected ( 50 ng/μL ) into OH14884 as a simple array , with unc-122::gfp ( 50 ng/μL ) as a coinjection marker . The unc-3 promoter fusion was generated by amplification of 558 bp of unc-3 promoter , fused to hlh-4 genomic ( including its own 3′UTR ) , using the PCR fusion approach [17] . Fifty nanograms per milliliter of this construct were injected into OH14884 , with ttx-3::mcherry as a coinjection marker . The eat-4 reporter constructs were generated by PCR and subcloning into pPD95 . 75 vector . eat-4prom6-1 contains 4 , 450 bp of the upstream region of the ATG and eat-4prom2 contains 1 , 150 bp of the genomic region just upstream of the ATG . The E-Box and homeodomain motif are found at positions -693 and -726 relative to the ATG start codon , respectively . The specific sequences deleted are , for the E-Box , AACAGGTGTT , and for the homeodomain site , ATTAGATAAT . The deletions were generated by mutagenesis with the QuickChange Site-Directed Mutagenesis kit ( Stratagene ) . The plasmids were injected into OH13645 [otIs518;him-5 ( e1490 ) ] at 50 ng/μL , using unc-122::gfp ( 50 ng/μL ) as a coinjection marker . Worms were anesthetized using 50 mM sodium azide ( NaN3 ) and mounted on 5% agarose on glass slides . Images were acquired using an automated fluorescence microscope ( Zeiss , AXIO Imager Z . 2 ) or LCS-8 laser point scanning confocal . Representative images are shown following maximum projection of Z-stacks using the maximum intensity projection type . Image reconstruction was performed using Fiji software [21] . ADL neurons were identified by labeling subsets of sensory neurons with DiD or DiO ( Thermo Fisher Scientific ) . For dye filling , worms were washed with M9 and incubated at room temperature with DiD ( 1:500 ) in M9 for 1 hour for Adults or ( 1:250 ) for 2 hours for L1 stage animals . After incubation , worms were washed three times with M9 and plated on agar plates coated with food ( OP50 bacteria ) for 1–3 hours before imaging . The expression of bHLH fosmid reporters was manually lineaged using SIMI BioCell program , as previously described [22] . Briefly , the gravid adults of hlh-4Fosmid::yfp ( otIs683 ) and hlh-3fosmid::gfp ( otIs648 ) were dissected and single two-cell embryos were mounted and visualized on a Zeiss Imager Z1 compound microscope using the 4D microscopy software , Steuerprg ( Caenotec ) . Nomarski stacks were taken every 30 seconds and embryos were illuminated with LED fluorescence light ( 470 nm ) at predetermined time points during development . Avoidance assay was performed as previously described [23 , 24] . L4 stage animals were picked onto OP50 seeded plates before a day of assay . We used 100 nM or 500 nM ascr#3 or 1M glycerol diluted in M13 buffer . In the assay , M13 buffer was firstly dropped in front of animals’ heads . When the animals didn’t respond to M13 buffer , we then dropped ascr#3/glycerol and checked avoidance to the stimulus . Long reversals were counted as avoidance [25] . The tests were done at least 5 times with 10 animals each . Motif discovery was carried out using information-theoretic analysis as implemented in the Finding Informative Regulatory Elements ( FIRE ) algorithm [26] . De novo motifs were discovered by running FIRE in discrete mode , with all the genes in the C . elegans genome labeled as either belonging to class 1: the neuron-specific expression class ( e . g . , 117 ADL-expressed genes ) or class 2: the complementary set of all other remaining genes . The starting k-mer seed length was set to k = 6 and the sequence search space was confined to 2-kb upstream regions . The discovered CACCTG motif had a robustness score of 10/10 with a significance z-score of 18 . 3 . We used TargetOrtho [27] to find whole genome CACCTG motif matches in five nematode genomes searching 2 kb upstream of each gene plus introns . ADL-expressed genes and all C . elegans genes , excluding noncoding RNAs , were compared using the Wilcoxon rank sums test to assess alignment independent species conservation scores , motif match position relative to the start codon , and motif match frequency per gene . Only genes with at least one CACCTG match were analyzed .
As a first step toward a systematic analysis of the neurogenic function of C . elegans bHLH genes , we undertook a nervous system–wide expression pattern analysis of all C . elegans AS-C-like genes . Using fosmid-based reporter transgenes , we found that many bHLH genes are expressed during embryonic development within and outside neuronal lineages , but we noticed that one AS-C-like bHLH gene , hlh-4 , displays an unusual expression pattern , both in terms of spatial and temporal specificity ( Fig 1 ) . hlh-4 expression is not observed in any blast cells during embryonic or postembryonic development but rather is first expressed in two pairs of postmitotic cells in the precomma stage embryo , shortly after their birth ( Fig 1A ) . One pair is the ADL neurons and the other pair is the sisters of ADL , which die shortly after their birth by programmed cell death [28] . Expression of hlh-4 in ADL is observed for the remainder of embryogenesis , continues during larval and adult stages , and is never observed in any other cell throughout the entire organism ( Fig 1A ) . The fosmid on which the yfp reporter construct is based is able to fully rescue the hlh-4 mutant phenotype that we describe below ( rescue data are shown in Table 1 ) . The ADL-specific fosmid-based reporter expression pattern is recapitulated by a 700-bp 5′ promoter fusion reporter ( Fig 1C ) . With the exception of hlh-3 , which is expressed in a subclass of postmitotic motor neurons of the ventral nerve cord [31] , none of the other C . elegans AS-C-like bHLH genes ( hlh-6 , hlh-12 , hlh-14 , hlh-16 , hlh-19/hnd-1 ) share the postmitotic , post-developmental neuronal expression feature of hlh-4 [12 , 32–34] . We note that while our fosmid-based hlh-3 reporter showed extensive expression in blast cells during embryogenesis , it does not recapitulate the postembryonic ADL expression previously reported using a reporter that only contained 1 . 5 kb of 5′ sequences upstream of the gene [35] . The only other bHLH reporter expressed in postmitotic neurons throughout embryonic , larval , and adult stages is the Daughterless homolog hlh-2/Da [29] , a binding partner of many C . elegans AS-C-related bHLH genes [30] . Expression of HLH-2/DA protein in a specific subset of postmitotic neurons , including the nociceptive neurons ADL and ASH , has been previously reported using anti-HLH-2 antibody staining [29] , but it was not reported whether expression persisted into later larval and/or adult stage . Using a fosmid-based reporter of hlh-2/Da expression , we found that ADL and ASH expression of hlh-2/Da , as well as expression in a few other head and tail neurons , is maintained throughout all larval stages into adulthood ( Fig 1B ) . We conclude that hlh-4/AS-C and its heterodimerization partner hlh-2/Da are continuously coexpressed specifically in the nociceptive ADL neuron class . One well-documented mechanism by which transcription factors ensure their continuous expression throughout the life of a neuron is through transcriptional autoregulation ( e . g . , [36–39] ) . To assess whether continuous expression of hlh-4 throughout the life of the ADL neuron is also ensured by autoregulation , we used a 5′ promoter fusion of the hlh-4 locus , which recapitulated the continuous expression of hlh-4 in ADL ( Fig 1C ) . We crossed this reporter into an hlh-4 mutant allele , tm604 , a putative null allele generated by the C . elegans knockout consortium in Tokyo [40] in which the bHLH domain is largely deleted ( Fig 1A ) . We found that hlh-4 reporter expression in the ADL neuron pair is initiated normally in hlh-4 mutant embryos , but expression fails to be maintained beyond the first larval stage ( Fig 1C ) . As yet unknown factors may initiate hlh-4 expression in the embryo and , after its initiation , hlh-4 takes over to regulate its own expression . We furthermore tested whether continuous expression hlh-2/Da in ADL requires hlh-4 activity . Crossing the hlh-2 fosmid reporter into the hlh-4 mutant background , we indeed found this to be the case ( Fig 1B ) . We conclude that the continuous expression of both hlh-4 and its putative cofactor hlh-2/Da is based on transcriptional autoregulation . In most if not all organisms examined , AS-C genes have proneural function , characterized by a loss of neuroblast identity in the absence of the AS-C gene and ensuing conversion into an ectodermal identity [1 , 3 , 6 , 13] . Previous work has demonstrated that in the lineage that produces ADL , as well as other sensory neurons , the transiently and early-expressed AS-C gene hlh-14 acts as a proneural gene , such that loss of hlh-14 results in a neuroblast to hypodermal fate conversion [12] . In striking contrast , we find that the later-expressed hlh-4 gene does not act as a proneural gene . Specifically , in hlh-4 null mutants , the ADL neuron pair is still generated and differentiates as a neuron , as assessed by ( a ) intact expression of a panneuronal reporter , rab-3 , ( b ) intact filling of the ADL neuron with the dye DiI ( which is taken up by the dendritic endings of several sensory neurons , including ADL [41] ) , and ( c ) presence and intact speckled appearance of the ADL neuronal nucleus by Nomarski optics ( Fig 2A ) . Corroborating this notion , we find that the two genes that are expressed by all ciliated sensory neurons , osm-6 and ift-20 [42 , 43] , are still normally expressed in the ADL neurons of hlh-4 mutants ( Fig 2B ) . Even though we could not confirm the previously reported expression of hlh-3 in ADL ( Fig 1A ) , we nevertheless generated hlh-3; hlh-4 double null mutants and found that in these animals the ADL neurons are also still generated normally , as assessed by intact DiI filling and characteristic neuronal nuclear speckles ( Fig 2A ) . The expression of the hlh-4 promoter fusion in hlh-4 mutants until the first larval stage permitted us to visualize the anatomy of the ADL neurons in the absence of hlh-4 gene function . While the cell body of ADL is normally positioned , we find that ADL axons and dendrites display severe morphological defects ( Fig 2C ) . The sensory dendrites of ADL are often detached from the nose . Even when attached , the cilia of ADL often do not display their characteristic bifurcated ciliated endings . The axons of ADL , which in wild-type animals display a highly stereotyped extension and branching pattern , show pathfinding and branching defects ( Fig 2C ) . To examine whether and to what extent hlh-4 is required to specify ADL neuron identity , we examined the differentiation program of the ADL neurons in detail . The ADL nociceptive neuron pair coexpresses an unusually large number of olfactory-type GPCRs [44–46] . Reporter genes generated for about one fifth of the approximately 1 , 300 GPCR encoding reveal the expression of more than 60 GPCR genes from diverse families in ADL [46] . Extrapolating to the complete set of GPCRs encoded in the C . elegans genome , about 300 GPCR-encoding genes may be expressed in ADL . We asked whether hlh-4 is required for the expression of 12 GPCR-encoding genes . We chose these genes to cover the diverse set of GPCR gene families expressed in ADL ( sra , sre , sri , srz , srh , srxa , and srx families ) . We found that expression of all of the tested 12 GPCR reporters is abrogated in hlh-4 mutants ( Fig 3A ) . While all defects were routinely scored at the adult stage , we note that these defects are already apparent at the first larval stage . Consistent with the absence of expression of the hlh-4 paralog hlh-3 in postmitotic ADL neurons , we find that hlh-3 does not affect srh-127 expression in ADL . To test whether hlh-4 does not only affect expression of chemoreceptor proteins but also affects the chemorepulsive function mediated by the ADL neurons , we considered its chemorepulsive function toward a specific nematode pheromone , the ascaroside ascr#3 ( asc-ΔC9 , C9 ) [24] . While wild-type hermaphrodites are repelled by ascr#3 , this repulsion is significantly reduced in hlh-4 hermaphrodites ( Fig 3B ) . This is not a reflection of an overall failure to engage in a nociceptive response because another chemorepulsive behavior , mediated by the ASH neurons ( glycerol avoidance ) [47] , is not affected in hlh-4 mutants ( Fig 3B ) . We tested whether hlh-4 function is restricted to controlling olfactory receptor expression and function in the ADL neurons or whether other identity features of ADL are disrupted as well . A TRP channel protein encoded by the osm-9 gene , expressed in a restricted set of sensory neurons , is required in ADL to signal the response to distinct chemorepulsive sensory inputs [24 , 48 , 49] . We find that osm-9 expression is selectively lost in the ADL neurons of hlh-4 mutant animals ( Fig 4 ) . Going beyond signal perception and transmission , we asked whether ADL requires hlh-4 to communicate with its synaptically connected neurons [50] . Based on the expression of the vesicular glutamate transporter eat-4/VGLUT , the key defining feature of all glutamatergic neurons , ADL neurons have previously inferred to be glutamatergic [51] . We find that the glutamatergic identity of ADL , as assessed by eat-4 fosmid reporter gene expression , is defective in hlh-4 mutant animals ( Fig 4 ) . Apart from using glutamate as a likely fast neurotransmitter , the expression patterns of various neuropeptide-encoding genes indicate that ADL also utilizes distinct peptides for neurotransmission [52 , 53] . We find that the expression of four neuropeptides , previously known to be expressed in ADL , as well as other neurons ( FMRFamides flp-4 and flp-21 and neuropeptides nlp-7 and nlp-10 ) [52 , 53] specifically fail to be expressed in the ADL neurons of hlh-4 mutants , while expression in other neurons is unaffected ( Fig 4 ) . Apart from peptidergic and chemical synaptic transmission , electrical synaptic transmission is likely also affected in hlh-4 mutants . ADL forms electrical synapses with a select number of neighboring neurons [50] . Electrical synapses are formed by transmembrane innexin proteins [54] , and 3 of the 24 C . elegans innexin genes , unc-7 , inx-18 , and che-7 , are expressed in ADL , as well as a specific set of other neuron types [55] . The expression of all three innexin genes is lost specifically in the ADL neurons of hlh-4 mutants ( Fig 4 ) . Transmembrane ion channel expression is also affected in hlh-4 mutants . Na+/Ca2+-K+ exchangers are important regulators of intracellular calcium homeostasis in the nervous system , and members of this family show remarkably specific gene expression profiles in the C . elegans nervous system [56] . Two Na+/Ca2+-K+ exchangers , ncx-6 and ncx-7 , are each exclusively expressed in the ADL neurons of wild-type animals [56] . The expression of both genes in ADL is abrogated in hlh-4 mutants ( Fig 4 ) . To examine whether these defects are a consequence of the failure of solely maintaining the differentiated state versus failure of initiation of the differentiated state , we examined the expression of several ADL markers right after hlh-4 mutant embryos had hatched . Testing four specific markers ( srh-127 , sre-43 , srt-47 , and ncx-6 ) , we found that expression is already affected at this early stage of development . In conclusion , we find that several distinct identity features that define functional features of the ADL neuron are coregulated by the same transcription factor . The affected identity features share the common theme of providing the ADL with a unique molecular signature and identity . In contrast , hlh-4 does not affect generic neuronal features ( i . e . , pansensory or panneuronal features ) . hlh-4 is not only required for the expression of ADL identity genes , but ectopic expression of hlh-4 is also sufficient to induce ADL identity features . We drew this conclusion by driving expression of hlh-4 in many other ciliated sensory neurons , using the arrd-4 promoter [57] ( S1 Fig ) . The arrd-4prom::hlh-4 construct is not only able to rescue the loss of srh-127::gfp expression in ADL in hlh-4 mutants ( Table 1 ) , but these transgenic animals display ectopic expression of the normally ADL-expressed srh-127::gfp reporter in many ciliated sensory neurons ( Fig 5A ) . Similarly , the TRP channel osm-9 , the neuropeptide-encoding flp-4 gene and the vesicular glutamate transporter eat-4 also are ectopically expressed in other sensory neurons in these transgenic animals ( Fig 5A ) . To further probe the ability of hlh-4 to induce ADL identity features in other neurons , we misexpressed hlh-4 under control of a promoter fragment from the unc-3 locus , which is expressed in ventral cord motor neurons and a small set of head neurons ( S1B Fig ) . Transgenic animals expressing a unc-3prom::hlh-4 construct show ectopic expression of the ADL marker srh-127::gfp in head neurons but not in ventral cord motor neurons ( Fig 5B ) . The apparent cellular context dependency of hlh-4 function mimics the context dependence of other master regulators of cellular identity , such as Eyeless/Pax6 [58] . Because gene expression is usually examined in C . elegans via reporter gene constructs , a large library of reporter transgenes that monitors the expression of thousands of genes has been amassed by the C . elegans community over the past few decades . In many cases , expression patterns of these reporter transgenes have been defined on a single neuron level . Almost 200 reporter transgenes have been found to be expressed in the ADL neurons ( www . wormbase . org , S2 Table ) . The genes tested above for their dependence on hlh-4 belong to this dataset . We took a subset of these genes ( 117 ) and asked whether 5′ upstream regulatory regions of genes whose expression is monitored by these reporter transgenes are enriched for the presence of a specific sequence motif using the FIRE motif analysis platform [26] ( see Materials and methods ) . We restricted the search space to the first 2 kb upstream of these genes . As a control , we also considered several other neuron classes that Wormbase associated with a large number of reporter genes ( AIY , ASE , ALM , HSN , ASI , ASK , ASH , PHA; www . wormbase . org ) and interrogated the upstream regulatory control regions of those genes . In the ADL dataset , we indeed identified a motif found in 75% of the ADL-expressed reporter genes ( Table 2 , S1 Table; S2 Table ) . The motif , shown in Fig 6A , has a completely invariant 6-nucleotide core , CACCTG , and no striking sequence features outside this core . There is no orientation preference for this motif on the plus versus minus strand . This motif is not enriched in the control datasets ( AIY , ASE , ALM , HSN , ASI , ASK , ASH , or PHA expressed reporter genes ) . The CACCTG motif matches experimentally determined bHLH binding sites ( CANNTG ) [59] and specifically matches the in vitro binding site of the C . elegans HLH-4/HLH-2 heterodimer , CA ( G/C ) CTG [30] . Probabilistic segmentation analysis of upstream regulatory sequences of ADL neuron-expressed GPCR genes had previously also identified a similar CA ( G/C ) CTG motif [45] . All the 23 terminal effector genes that we described above as depending on hlh-4 in their expression in ADL ( Fig 3; Fig 4 ) contain at least one copy of this motif within 2 kb upstream of the 5′ start of the gene ( Table 2 , S1 Table ) . The one hlh-4-dependent GPCR reporter ( srh-79 ) that does not contain a perfect match to the E-box motif contains a 1-nucleotide-mismatched copy of the motif ( CACGTG versus CACCTG ) . The hlh-4 locus itself and , specifically , the 700-bp 5′ upstream regulatory region that shows hlh-4 autoregulation ( Fig 1C ) contains two copies of the perfectly matched CACCGT motif ( both motifs are located in the 245-bp-long intergenic region ) . Moreover , the upstream region of the hlh-2/Da gene , the putative cofactor of hlh-4 , which is also continuously expressed in ADL , also contains three copies of this motif in its 5′ upstream intergenic region . The regulation of hlh-2/Da expression by hlh-4 ( demonstrated above ) is therefore also likely a reflection of direct autoregulation of the hlh-2 locus by the HLH-4/HLH-2 heterodimer . Three lines of evidence further validate the importance of the CACCGT E-box motif for ADL expression: We used phylogenetic footprinting in the TargetOrtho pipeline [27] to assess the extent of conservation of the CACCTG motif among five Caenorhabditis species , C . elegans , C . briggsae , C . remanei , C . brenneri , and C . japonica ( S2 Table ) . This analysis provided a genome-wide assessment of the location of the CACCTG motif in these five different species and allowed us to define a number of features of the CACCTG motif: Moreover , we find that two of the ADL-expressed genes that do not contain a perfect match to the CACCTG motif ( srh-79 and srh-186 , one of which , srh-79 , we confirmed to be hlh-4-dependent ) contain a motif with a single mismatch to the CACCTG motif ( CACGTG ) , yet all Caenorhabditis species that have orthologues of these two genes contain perfect CACCTG motif matches ( Table 2 , S1 Table ) . In conclusion , a CACCTG motif defines a signature for ADL-expressed genes . Given that this motif is a known in vitro binding site for a HLH-4/HLH-2 dimer [30] , hlh-4 appears the most likely candidate to directly activate the expression of scores of genes that uniquely and combinatorially define the terminally differentiated state of the ADL neuron pair . The partially penetrant effect of hlh-4 on eat-4/VGLUT expression suggested that hlh-4 partly relies on additional factors to control eat-4/VGLUT expression . This notion is further corroborated through an examination of the cis-Regulatory control regions of the eat-4/VGLUT locus . We find that 4 . 5 kb of sequence upstream of the eat-4/VGLUT locus directs reporter gene expression to many glutamatergic neurons , including ADL ( prom6-1; Fig 7A ) . This 4 . 5-kb region contains a phylogenetically conserved CACCTG motif 691 bp upstream of the ATG . Deletion of this motif results in loss of expression in ADL ( Fig 7A ) . However , while this motif is required for ADL expression , it is apparently not sufficient: deleting 3 . 2 kb from the 4 . 5-kb 5′ reporter fusion leaves the E-box unaffected but abolishes expression in ADL ( prom2; Fig 7A ) , suggesting that these deleted sequences contain binding site ( s ) for a transcription factor that cooperates with hlh-4 to activate eat-4/VGLUT expression . The LIM homeobox gene lin-11 was previously shown to be expressed in postmitotic ADL neurons throughout their lifetime [61] . We find that lin-11 expression in ADL is not affected in hlh-4 mutants ( Fig 7B ) . Corroborating a role of lin-11 in parallel to hlh-4 , we find that lin-11 null mutants are defective in the ADL-mediated chemorepulsive response to C9 ascaroside ( Fig 7C ) . Consistent with this behavioral defect , we observed that lin-11 null mutants display defects in the expression of several of hlh-4-dependent and E-box-containing genes , including ncx-6 , srh-234 , and flp-21 ( Fig 7D ) . However , lin-11 does not affect the hlh-4-dependent flp-4 gene , nor does it affect eat-4/VGLUT fosmid reporter expression ( Fig 7D ) . We tested whether a function for lin-11 on eat-4/VGLUT expression could be revealed in the context of an hlh-4 mutant background , in which eat-4/VGLUT fosmid reporter expression is only partially affected . lin-11; hlh-4 double mutants still normally express pansensory markers in ADL , but they display a dye filling defect that neither mutant alone displays , corroborating the parallel nature by which hlh-4 and lin-11 affect ADL differentiation ( Fig 7E ) . Surprisingly , in hlh-4; lin-11 double null mutants , the partially penetrant loss of eat-4/VGLUT expression observed in hlh-4 single mutants was not enhanced but instead completely suppressed ( Fig 7D ) . The same effect is observed on the flp-4 gene . Its completely penetrant loss in hlh-4 mutants is suppressed in hlh-4; lin-11 double mutants ( Fig 7D ) . The reinstatement of eat-4/VGLUT fosmid expression even in the absence of hlh-4 is mirrored by a mutation in the cis-Regulatory control region of eat-4/VGLUT . The 1 . 2-kb upstream region of eat-4/VGLUT , which contains an hlh-4 binding site but is not expressed in ADL , becomes expressed in ADL upon deletion of a predicted homeodomain binding site , a potential recognition motif for LIN-11 ( Fig 7A ) . This result suggests that eat-4/VGLUT expression is controlled via a collaboration of hlh-4 with an as yet unknown transcription factor X whose activating effect is normally antagonized by LIN-11 . If all activators ( hlh-4 and X ) are present , lin-11 cannot prevent activation of eat-4/VGLUT ( eat-4prom6-1delta12 ) ; hence , eat-4/VGLUT is expressed in ADL . If , however , the system is partially destabilized by hlh-4 removal ( or by removal of the E-box sequence in the reporter construct ) , lin-11 can counteract the ability of factor X to activate eat-4/VGLUT expression ( eat-4prom2delta 12 ) ( as assessed by the restoration of eat-4 expression upon removal of lin-11 ) . The effect of lin-11 on ADL-expressed genes is , however , clearly target gene dependent . While in the case of one target gene , eat-4/VGLUT , lin-11 appears to antagonize hlh-4 function , it may positively cooperate with hlh-4 on those other target genes whose expression is either completely or partially lost in hlh-4 and/or lin-11 mutants . We conclude that hlh-4 is a central regulator of ADL identity that may interact in a target gene–dependent manner with distinct collaborating factors .
The identification of proneural genes that act very early in neuronal development to allocate neuroblast identity to distinct neuronal lineages via classic genetic loss of function analysis in Drosophila represents one of the classic landmark achievements of developmental neurogenetics [2 , 3] . The subsequent cloning of vertebrate AS-C and Atonal homologs has revealed the deep conservation of this fundamental neural patterning mechanism [1 , 6–8] . We have described here a novel functional property of an AS-C gene , demonstrating that C . elegans hlh-4 joins the rank of terminal selector-type transcription factors that act in postmitotic neuron classes to initiate and maintain the differentiated state of a specific , postmitotic neuron class . hlh-4 displays all the hallmarks of a terminal selector [62 , 63]: it is required for initiation of the terminal differentiation program of the ADL neuron pair , it is continually expressed throughout the life of the neuron ( suggesting that it also maintains neuronal identity ) , this continuous expression is mediated by direct autoregulation via HLH-2/HLH-4 binding sites in the hlh-2 and hlh-4 loci , and , most importantly , hlh-4 controls the vast majority of neuron class–specific genes whose combinatorial coexpression defines ADL identity , yet it does not control generic neuronal features ( panneuronal and pansensory features ) . Hence , exactly like other terminal selectors [62 , 63] , hlh-4 separates the adoption of neuron type–specific features ( hlh-4-dependent ) from the acquisition of an overall , panneuronal/pansensory identity ( hlh-4-independent ) ( Fig 8A ) . It is important to precisely appreciate this fundamental dichotomy in neuronal gene expression programs , repeatedly observed in many different neuron classes and corroborated here by the hlh-4 mutant phenotype: as schematized in Fig 8A , genes that are expressed in specific subsets of neuron classes are terminal selector dependent , while genes that are expressed in a non-neuron-class–specific manner are regulated by independent means [60] . The terminal selector function of hlh-4 is likely exerted in collaboration with the canonical AS-C cofactor , hlh-2/Da , which shares with hlh-4 the unusual feature of postmitotic expression throughout the life of the ADL neuron class . hlh-2 is also continuously expressed in a small number of additional neuron classes , but its function in these neurons remains unknown . In yeast one-hybrid assays , HLH-4/HLH-2 has been shown to bind to the CACCTG sequence that we describe here [30] . While the HLH-4/HLH2 complex and its cognate binding site is essential—and at least in some context also sufficient—for gene expression in ADL , it is unlikely to act on its own . With its 6-bp length , the recognition element of the HLH-4/HLH-2 heterodimer occurs too frequently in the genome to direct HLH-2/HLH-4 exclusively to ADL-expressed genes . We find that the LIM homeobox gene lin-11 assists hlh-4 in the regulation of some but not all hlh-4-dependent target genes . As no DNA cis-Regulatory motif was found to be significantly enriched in ADL-expressed genes by our bioinformatic analysis in addition to the E-box , we propose that hlh-4 is a central core inducer of all ADL-specific genes but may be assisted in its function , i . e . , provided the proper specificity , by interaction with a suite of distinct , target gene–dependent collaborating factors , such as lin-11 and perhaps other , as yet to be discovered factors ( Fig 8B ) . Previous work on AS-C genes in worms has revealed that the AS-C-type hlh-14 gene acts as a conventional proneural gene during early embryonic patterning to specify the neuronal identity of an AB-blastomere-derived lineage branch that produces several sensory neurons , including ADL [12] . In the absence of hlh-14 , cells in this lineage branch convert to a hypodermal identity [12] ( Fig 8C ) . Hence , the ADL neuron depends on the successive activity of two distinct AS-C-type genes , one acting as a conventional proneural gene ( hlh-14 ) , followed by hlh-4 , which acts in a subbranch of this lineage , to specify terminal ADL identity ( Fig 8C ) . Whether hlh-14 directly activates hlh-4 expression is presently unclear . Notably , though , the E-box motif in the hlh-4 locus that is required for maintaining hlh-4 expression is not required for initiation of hlh-4 expression in the embryo . Even though a proneural function of AS-C-type genes is clearly a deeply conserved function of bHLH genes , our findings prompt the intriguing question as to whether a function of bHLH genes in directly controlling the differentiated state of a neuron may have been an even more ancestral function of AS-C-type bHLH genes . In support of such notion , the AS-C ortholog in the cnidarian Hydra magnipapillata , Cnash , was previously reported to not be expressed in neuronal precursors but rather in differentiating and mature neurons , leading the authors of that report to postulate a role of hydra Cnash in initiating and maintaining the neuronal phenotype [64] , exactly as we propose here for C . elegans hlh-4 . Loss of function studies of the AS-C orthology NvashA of the sea anemone Nematostella vectensis cannot distinguish between a proneural versus terminal differentiation role [65] . Subsequent to such terminal differentiation role , an “ur-” bHLH may then have become co-opted into more upstream regulatory events in proliferating blast cells . A somewhat similar trajectory has been proposed for the Pax6/Eyeless gene , originating with a function in regulating lens protein to subsequent recruitment to earlier steps of eye development [66] . Of course , it is also conceivable that the terminal selector function of hlh-4 may be a derived feature , one that perhaps came into existence via the acquisition of an E-box motif in the hlh-4 locus that lead to hlh-4 expression being “locked” into a terminal and continuous function . More detailed expression pattern analysis of AS-C and Ato-like genes in the adult nervous system of other species will provide hints whether hlh-4-like , terminal selector functions may also be carried by AS-C/Atonal genes in other organisms . In fact , such function may be conceivable in an already previously reported case . Drosophila Atonal is expressed in mature dorsal cluster neurons in the dorsolateral CNS of the flies [67] . In these neurons , Ato has no proneural function but instead serves to control arborization patterns . However , whether Ato has an impact as broad as hlh-4 on controlling the differentiated state of these neurons is not yet known . C . elegans sox-2/SoxB1 is another gene whose orthologs in other organisms ( SoxB factors ) act in early neuronal patterning [68] but that has become employed as a terminal selector in C . elegans [69 , 70] . Here again , the question is whether such late role is a reflection of an ancestral or derived function of this gene . It is important to keep in mind that the existence of such late functions ( in addition to the well-characterized early functions ) may have very easily escaped detection in other organisms , because straight knockout approaches will only reveal the early function of a gene in the lineage . Only if an early function is not existent , as apparently is the case for sox-2 and hlh-4 , will a late function be revealed with relative ease using standard genetic loss of function , i . e . , straight knockout approaches ( this paper ) [69 , 70] . Defining hlh-4 as a terminal selector of ADL identity sheds additional mechanistic context on previous studies about the feeding state–dependent regulation of a sensory-type GPCR gene , srh-234 , in the ADL neuron [35 , 71] . Focusing on this specific gene , the authors found that the MEF-2 transcription factor , a well-known mediator of neuron activity–dependent processes in many different organisms [72] , down-regulates hlh-4-dependent srh-234 expression under starvation conditions . This effect is mediated via a MEF-2 binding site in the srh-234 locus that is located next to the HLH-4/HLH-2 binding E-box [35] . Together with our description of a broad role of hlh-4 in controlling the differentiated state of ADL , an intersectional strategy of a “genetically hardwired” identity factor with a condition-dependent factor becomes apparent . Such an intersectional strategy could perhaps be a general strategy to explain the cellular specificity of broadly acting signals that convey environmental or physiological information . One of the remarkable features of the chemosensory system of C . elegans is the coexpression of multiple sensory receptors of the GPCR family in individual neuron types [44–46] . Even though the expression of only about one fifth of C . elegans chemosensory-type GPCRs has been examined so far [46] , there are several chemosensory neurons that coexpress several dozens of GPCRs . This tremendous extent of coexpression only applies to a select set of chemosensory neurons , with the most prominent set being the nociceptive ADL , ASH , PHA , and PHB neurons [46] . One could have imagined several scenarios by which such coexpression is controlled . A previous bioinformatic analysis already strongly hinted toward coregulation of coexpressed GPCRs via a common cis-Regulatory motif [45] . However , it is only through the present analysis that we can conclude that a single trans-acting factor instructs , apparently via direct binding to a cis-Regulatory element shared by most if not all coexpressed GPCRs , the enormously broad spectrum of chemosensory capacities of one of these nociceptive neurons , ADL . | Across the animal kingdom , transcription factors of the basic helix-loop-helix ( bHLH ) family act during embryonic nervous system patterning as proneural genes to promote neuroblast identity . We describe here a distinct function for a specific member of this family , hlh-4 , in the nematode Caenorhabditis elegans . hlh-4 is exclusively expressed in a nociceptive neuron class and is not required for this neuron class to be generated but is rather required for the execution of its terminal differentiation program . hlh-4 directly controls the expression of scores of terminal identity features of this neuron class , including its large battery of chemoreceptor-encoding genes . We propose that a role of bHLH genes in controlling terminal differentiation may be the ancestral function of members of this gene family . | [
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"systems"... | 2018 | Unconventional function of an Achaete-Scute homolog as a terminal selector of nociceptive neuron identity |
The actin cytoskeleton is a dynamic structure that coordinates numerous fundamental processes in eukaryotic cells . Dozens of actin-binding proteins are known to be involved in the regulation of actin filament organization or turnover and many of these are stimulus-response regulators of phospholipid signaling . One of these proteins is the heterodimeric actin-capping protein ( CP ) which binds the barbed end of actin filaments with high affinity and inhibits both addition and loss of actin monomers at this end . The ability of CP to bind filaments is regulated by signaling phospholipids , which inhibit the activity of CP; however , the exact mechanism of this regulation and the residues on CP responsible for lipid interactions is not fully resolved . Here , we focus on the interaction of CP with two signaling phospholipids , phosphatidic acid ( PA ) and phosphatidylinositol ( 4 , 5 ) -bisphosphate ( PIP2 ) . Using different methods of computational biology such as homology modeling , molecular docking and coarse-grained molecular dynamics , we uncovered specific modes of high affinity interaction between membranes containing PA/phosphatidylcholine ( PC ) and plant CP , as well as between PIP2/PC and animal CP . In particular , we identified differences in the binding of membrane lipids by animal and plant CP , explaining previously published experimental results . Furthermore , we pinpoint the critical importance of the C-terminal part of plant CPα subunit for CP–membrane interactions . We prepared a GST-fusion protein for the C-terminal domain of plant α subunit and verified this hypothesis with lipid-binding assays in vitro .
The actin cytoskeleton represents part of a complex network that is essential for cell motility , organelle movements and cell polarity . Actin filaments are dynamic structures in general and , in plant cells , they serve as tracks for some of the fastest movements on earth . To regulate actin cytoskeleton organization and dynamics , cells use more than a hundred classes of actin-binding proteins ( ABPs ) . To a limited extent , these proteins can be classified based on their binding properties and activities in vitro . Some ABPs bind actin monomers regulating the size and activity of the polymerizable actin pool , whereas others bind to the sides of actin filaments . Side-binding proteins can create higher-order filament structures like meshworks and bundles , or they can create breaks and sever filaments . Another group of ABPs interacts with actin filament ends and regulates the stability and dynamics of polymer assembly/disassembly [1] . A conserved member of this latter group is actin-capping protein ( CP or CapZ ) , which inhibits the addition and loss of actin subunits at the barbed end of actin filaments [2] , [3] . CP is a heterodimeric protein with a mushroom-like structure [4] . Each monomer , α and β subunit ( CPα and CPβ ) , has a molecular weight of approx . 30 kDa and despite their sequence divergence , they have similar structural folds [4] . Several recent studies describe a mode of interaction between CP and the actin filament barbed end [5] , [6] , highlighting the importance of C-terminal domains from both subunits . These C-terminal parts form so-called tentacles laying on the top of the protein and are mainly composed from amphipathic helices [4] . It has been shown previously that binding of CP to actin filaments is regulated by several other proteins , either by competition for filament ends or by direct protein-protein interactions and allosteric regulation [7] . Another set of key regulators that inhibit CP activity are the signaling phospholipids , phosphatidylinositol ( 4 , 5 ) -bisphosphate ( PIP2 ) and phosphatidic acid ( PA ) [8]–[12] . Phospholipids are part of the complex lipid-signaling language of eukaryotic cells and enable communication between plasma membrane , endomembrane compartments and cytoplasm . The role of phosphoinositides ( PPIs ) as signaling molecules was established many years ago [13] . More recently , PA has emerged as an important signaling messenger , especially in plant responses to biotic and abiotic stress [14] . This acidic phospholipid often functions by recruiting effector proteins to membranes in a spatio-temporally specific manner and/or it affects the biophysical properties of membranes [15] . One characteristic feature of PA and PPIs is their rapid turnover , which is mediated by particular enzymes producing and degrading them [16] . Despite the fact that both PA and PIP2 have important signaling functions , they significantly differ in their biophysical properties . PIP2 contains a bulky headgroup , with net charge ranging from −3 to −5 under physiological pH . and an inverted conical shape that promotes positive curvature of membranes . On the other hand , PA has a tiny headgroup with net charge ranging from −1 to −2 and it may induce formation of membrane structures with negative curvature [17] , [18] . Although PIP2 binding by proteins is generally very well described and diverse binding-domains have been discovered [19] , [20] , much less is known about PA-protein interactions [14] . The ability of PIP2 to regulate CP has been known for a long time [7]; however , there is still some controversy about the exact binding site on CP . Kim et al . [11] performed an exhaustive site-directed and truncation mutagenesis of chicken CP ( GgCP ) . These authors report that mutation of basic amino acids located on the α tentacle ( R256 , K260 ) as well as on the β subunit ( R225 ) caused a reduction in PIP2 binding by about 4-fold . A similar reduction in PIP2 binding was observed following deletion of the last 28 C-terminal residues from the α tentacle . Although these results clearly show the importance of the α tentacle for binding to phospholipids , neither mutations or truncations totally abolished PIP2 binding . Kuhn and Pollard [12] studied fission yeast CP and its interactions with PPIs . These authors did not find any effect of various PPIs , including PIP2 , on Schizosaccharomyces pombe CP activity . They constructed a homology model for CP from several species and , based on the comparison of electrostatic potentials mapped onto these structures , they hypothesize that a positively-charged patch located on CPβ close to the basic cluster on the α tentacle ( which is absent in S . pombe CP ) also contributes to the interaction with PPIs . Identification of a PA-binding site on CP remains more elusive; two seminal works that describe the effect of signaling phospholipids on mammalian CP , indicate that PA is not able to inhibit and/or dissociate this protein from actin filaments [8] , [9] . However , we showed that mouse CP was able to bind PA , but with lower affinity than Arabidopsis thaliana CP ( AtCP ) . We also demonstrated that PA is a potent inhibitor of AtCP activity , preventing it from interacting with filament barbed ends [10] . In this study , we focus on the interaction between AtCP , GgCP , PA and PIP2 in the context of phospholipid bilayers . To gain a structural perspective about these interactions , we utilized a combination of different computational methods and experimental approaches . We used the recently described MARTINI force field [21] , [22] to investigate dynamics of CP binding to phospholipid bilayers containing PA or PIP2 . We show different preferences of animal and plant CP towards distinct signaling phospholipids . Our results clearly reveal the importance of C-terminal tentacles from both subunits in these interactions . We further confirm the importance of the α subunit tentacle from AtCP in the PA interaction with an in vitro binding experiment using a GST-fusion protein . Altogether , our results explain and significantly expand upon previously published results [10]–[12] .
Given that CP has been identified as one of the major regulators of actin dynamics in different species , such as animals , fungi and plants [7] , we asked whether CP is a generally distributed actin-regulating protein in eukaryotes . To achieve this goal , we searched more than 50 genomes for different species covering members of almost all eukaryotic superkingdoms [23] . Both CP subunits are well conserved in most eukaryotic lineages and are mostly present as single-copy genes . Nevertheless , in some organisms CP genes are multiplied; for example , vertebrates have three different genes for the α subunit and Trichomonas vaginalis has five genes for the β subunit ( Figure 1 ) . Moreover , the vertebrate gene for β subunit undergoes alternative splicing , producing additional variability [7] . It is worth noting that there is no organism with just one subunit gene for the heterodimer , i . e . an α gene but no β gene , or vice versa; this finding correlates well with genetic and biochemical data indicating strict dependency between α and β subunits . Surprisingly , we have not found CP genes for either subunit in sequenced genomes of green algae , red algae and in certain parasites such as Toxoplasma gondii . Some of these organisms probably lost CP genes during evolution , mainly because of their life strategies , i . e . parasites or extremophiles . The overall phylogeny of both CP subunits mainly follows organismal evolution ( Figure 1 ) . Metazoan genes , together with Choanoflagellate Monosiga brevicollis as a basal clade , cluster with Fungi in the case of both CP subunits . Plant sequences also form well supported groups . The phylogenetic relationships between other sequences of CPα ( from Chromalveolata , Excavata and Amoebozoa groups ) are not so clear . In the case of CPβ , Ameobozoa and Excavata sequences form well supported clusters . We also tried to find homologs of the eukaryotic protein in eubacteria and archeabacteria using more sensitive search tools , such as PSI-BLAST [24] , but we did not found any obvious homologous sequences . Therefore , it is reasonable to speculate that CP is an eukaryotic innovation , similar to other ABPs , e . g . formins [25] . To clarify the mode of animal CP binding to PIP2 and to compare it with the binding of CP from different species to PA and PIP2 , we utilized diverse methods of computational structural biology . First , we constructed a homology model for AtCP using the crystal structure of GgCP α1β1 ( also known as CapZ; [4] ) as a template ( Figure 2A ) . A comparison of electrostatic surface potential for both structures shows marked differences in the distribution of charged residues . AtCP is much more negatively charged than the chicken protein ( Figure 2B ) , but it contains one positively charged patch corresponding to the PIP2-binding region on GgCP identified by Kim et al . [11] . To further test the binding modes between PA and PIP2 binding by AtCP and GgCP , we used a computational molecular docking approach similar to that of Kim et al . [11] . Results for the docking of truncated PA ( diacetyl-PA ) to AtCP ended with a single prediction of binding site and correlate well with the positively-charged patch located on the α tentacle ( Figure S1 ) . We also computed the docking of a truncated PIP2 molecule to AtCP with the same results . As a control for these experiments , we used phosphatidylcholine ( PC ) and docking of this molecule did not result in any single prediction . Phospholipids spontaneously form more complex systems , such as membranes or vesicles; therefore , we thought it important to ask what is the mode of CP binding to signaling phospholipids in the context of a lipid bilayer . Molecular dynamics ( MD ) simulation provides a useful and powerful tool to study complex biological systems , such as membranes or proteins [26]–[28] . We employed coarse-grained MD ( CG-MD ) with the MARTINI force field [21] , [22]; this allowed us to simulate larger systems for longer periods of time and has been successfully applied to describe processes like raft-like structure formation , membrane protein dynamics or SNARE-mediated vesicle fusion [28]–[30] . We modeled self-assembly of a lipid bilayer in the presence of CP protein , as this procedure has been shown to be advantageous for the characterization of peripheral membrane protein dynamics [31] , [32] . Specifically , we simulated several systems comprising different concentrations of 1-palmitoyl-2-oleoyl-phosphatidic acid/1-palmitoyl-2-oleoyl-phosphatidylinositol ( 4 , 5 ) -bisphosphate and 1-palmitoyl-2-oleoyl-phosphatidylcholine ( POPA/POPIP2 and POPC ) in the presence of AtCP or GgCP ( Table 1 ) . Snapshots from 100 ns of self-assembly of a lipid bilayer containing 20% POPA in POPC in the presence of AtCP are shown in Figure 3 . We observed formation of a lipid bilayer within approx . 30 ns in all simulations . This is similar to the time required for membrane formation as described by previous studies [32] , [33] . The membrane initially aggregates in the vicinity of CP ( Figure 3B ) ; however , the protein is very quickly pushed from the core of the lipid bilayer ( Figure 3C , D ) . CP is peripherally bound to the membrane after approx . 50 ns and remains closely attached to the membrane for an additional 50 ns ( Figure 3D ) . In all simulations performed ( i . e . either AtCP or GgCP , and either POPA or POPIP2 in POPC membranes ) , the CP protein faces towards the lipid bilayer via its tentacles ( Figure 3D ) , but the involvement of the tentacles in the interaction with the membrane is slightly different for particular simulations . Importantly , the protein always ends in this position independent of its initial orientation in the simulation box . After 500 ns of simulation , clear differences in the binding mode between AtCP and GgCP proteins and the POPA/POPC lipid bilayer were observed ( Figure 4 and Figure S2 ) . We found that the binding of AtCP to membranes composed from POPA/POPC is dependent on the concentration of POPA and on the PA charge , −1 or −2 . In the case of POPA with a charge −1 , AtCP only binds membranes with a high content of POPA ( 50% ) . By contrast , AtCP binds to membranes comprising 20% POPA with the charge −2 ( Figure 4B ) , but not to 10% POPA . In all positive cases , AtCP binds the membrane via the α tentacle ( Figure 4B and Figure S2A ) . Moreover , and in good agreement with docking results , residues from the positively-charged patch of the α tentacle ( K273 , R276 , K277 , K278 and R283 ) interact with POPA ( Figure 5A ) . Furthermore , the amphipathic helix at the very end of the α tentacle is embedded in the membrane ( Figure 4B ) via its hydrophobic residues ( Figure 4B , L279 , V281 , L285 , F286 and W288 ) . On the other hand , GgCP binds membranes containing POPA solely via the β tentacle ( Figure 4C ) and interacts with the membrane mainly by nonpolar contacts ( Figure 5C ) . To study the mode of CP binding to POPIP2/POPC membranes , we used two different concentrations of POPIP2 ( 1 and 5% ) . AtCP interacts with 5% POPIP2 membranes with both tentacles ( Figure 4E ) and , similarly to POPA , the majority of polar interactions are mediated by the positively-charged region on the α tentacle ( Figure 5B ) . However , we observed a decreased number of nonpolar contacts between AtCP and membranes containing 5% POPIP2/POPC ( Figure 5B ) compared to 20% POPA/POPC ( Figure 5A ) . This correlates very well with density profiles computed for these two simulated systems ( Figure S3 ) , where we found that the α tentacle is much more embedded into the hydrophobic part of the phospholipid bilayer comprising 20% POPA/POPC . Intriguingly , we did not found any preferential binding site when simulating AtCP with membranes containing 1% POPIP2 but rather observed that protein rotates closely to the membrane ( Figure S2B ) . Conversely , we observed GgCP binding to membranes with both concentrations of POPIP2 ( Table 1 ) . The interaction of GgCP with membranes containing 5% POPIP2/POPC is mediated by both tentacles ( Figure 4F and Figure 5D ) . Interestingly , we observed that the binding is mediated just by the α tentacle when we used a lower amount of POPIP2 in the membrane ( 1% , Figure S2C ) . We also performed self-assembly simulations and subsequent extension for conditions without any signaling lipid in the membrane; in this case we did not observe any binding between CP and POPC bilayers ( Figure S2D ) . In summary , we observed that AtCP differs from its vertebrate counterpart GgCP in the way it interacts with membranes containing POPA/POPC or POPIP2/POPC ( Table 1 ) . The interaction between AtCP – POPA/POPC membrane is mediated solely by the α tentacle and the binding is provided by the combination of polar and nonpolar interactions ( Figure 4B and Figure 5A ) . On the other hand , GgCP interacts with the lipid bilayer containing POPA/POPC with the β tentacle and the interaction seems to be mediated preferentially by nonpolar contacts ( Figure 4C and Figure 5C ) . The interaction of either AtCP or GgCP with the membrane consisted of POPIP2/POPC is mediated by both tentacles ( Figure 4E and 4F ) , although there are also significant differences in the POPIP2 binding by AtCP and GgCP . In particular , the longer β tentacle of GgCP provides more nonpolar contacts with the POPIP2-containing bilayer in comparison with AtCP ( Figure 5B and 5D ) . To further confirm the importance of the α tentacle for association of AtCP with POPA/POPC membranes , we performed in silico mutagenesis of two residues with the greatest number of polar ( CPα-K278A and CPα-R283A ) as well as for the two most important nonpolar contacts ( CPα-F286S and CPα-W288S ) . We simulated three 500 ns runs of CG-MD as described above and computed minimal distances between AtCP and membrane during these simulations . As shown in Figure 6A , wild-type AtCP always remains closely associated with the membrane . On the other hand , mutation of the polar residue K278 to alanine leads to complete disruption of AtCP-POPA/POPC association . Similar but weaker effects can be observed for the CPα-R283A mutation . Interestingly , CPα-W288S mutation was also able to disrupt binding of AtCP to the POPA/POPC membrane , although not in every run . On the other hand , we did not observe any effect caused by mutation of CPα-F286S . We also performed analogous simulations for the mutated AtCP proteins with POPIP2/POPC membranes ( Figure 6B ) . In this case , we found that only mutation of W288 has an effect on the association of AtCP with the membrane . Collectively , these results further confirm the critical importance of the CP α tentacle for PA binding that is mediated by interaction site containing positively charged residues K278 and R283 . The effect of the W288S mutation on both POPA/POPC and POPIP2/POPC-binding supports the hypothesis of structural importance of W288 ( homologous to W271 in GgCP ) for stability of the α tentacle as proposed by Kim et al [6] . Previously , we described dissociation constant ( Kd ) values for plant and mouse CP binding to PA and PIP2 micelles , as analyzed by changes in endogenous tryptophan fluorescence [10] . The findings show that AtCP has a somewhat higher apparent affinity for PIP2 micelles than for PA ( 11 µM versus 17 µM , respectively ) . The apparent affinities of the animal protein for PA and PIP2 are markedly different , with mouse CP showing a higher affinity for PIP2 ( 8 µM for PIP2 versus 59 µM for PA ) . Here , we employed the potential of mean force ( PMF ) calculation with the umbrella sampling protocol [34] to gain insight into the quantitative aspects of the computed interactions . We used steered molecular dynamics to pull the protein away from the membrane and to generate sampling windows for PMF calculation . For this type of pulling experiment , we applied position restraints on the lipids to keep them in the membrane . Figure 7 shows PMF curves for four selected systems . We found that GgCP interacts most tightly with membranes containing 5% PIP2/POPC with ΔG −236 kJ/mol . AtCP interacts with membranes of the same composition with ΔG −185 kJ/mol . In comparison to GgCP ( ΔG −69 kJ/mol ) , AtCP interacts more strongly with membranes composed from 20% POPA/POPC ( ΔG −112 kJ/mol ) . Importantly , this is a similar trend compared to the experimental data; there is a huge difference between the binding of PA and PIP2 for GgCP and a much smaller difference in the case of AtCP . A direct alignment of the primary sequences for the C-terminal tentacles from CP proteins across diverse eukaryotes ( Figure 8A and Figure S4 ) revealed that although the positively-charged region located on the α tentacle is generally well conserved , several lineage-specific differences could be identified , which might explain distinct binding properties of AtCP and GgCP . Plant sequences generally have longer α tentacles ( Figure 8A ) with a conserved lysine ( K278 , in GgCP this is Q261 ) , that shows the greatest number of polar contacts with PA ( Figure 5A ) . Moreover , plant α tentacles contain leucine , proline and asparagine ( L285 , P287 and N290 ) instead of lysine , aspartate and lysine in vertebrate sequences ( K268 , D270 and K273 ) , resulting in a decrease of polar residues in this region compared to animal CP . These amino acid changes facilitate the observed embedding of the plant α tentacle into PA-containing membranes ( Figure 8B and Figure S3 ) . Intriguingly , higher plants also have a shorter β tentacle and thus lack a major part of the amphiphatic helix located at this position in vertebrate CP ( Figure S4 ) . To further confirm whether the AtCP α tentacle constitutes a PA-binding domain , we prepared a recombinant fusion protein between GST and the C-terminal 38 amino acids from AtCP α subunit ( GST-CPα-Cterm ) . Protein-lipid overlay assays showed strong binding of the GST-CPα-Cterm to PA ( Figure 8C ) , similar to our previous observations with full-length AtCP protein [10] . In addition , the interaction of GST-CPα-Cterm with a subset of PPIs including PIP2 and phosphatidylinositol ( 3 , 4 , 5 ) -trisphosphate ( PIP3 ) , as well as with cardiolipin and sulfatidate was also observed in this assay . Interestingly , cardiolipin and sulfatidate contain a phosphate/sulphate group and thus resemble PA and PPIs to some extent . However , the binding of PIP3 , cardiolipin and sulfatidate to GST-CPα-Cterm is most probably non-physiological , as PIP3 is not present in plant membranes and cardiolipin is found only in bacteria and in the inner membrane of mitochondria . We also found that GST-CPα-Cterm binds to lipid vesicles containing 20% PA and PC in co-sedimentation experiments ( Figure 8D ) . These two complementary approaches clearly demonstrate that the AtCP α tentacle is sufficient for PA binding .
We previously described different binding affinities for plant and animal CP interacting with two distinct signaling phospholipids , PA and PIP2 [10] . Here , we focused on the structural aspects of these interactions by employing diverse methods of structural bioinformatics . It has been shown that these methods , and particularly CG-MD simulation , can play a crucial role in our understanding of general principles of processes such as lipid bilayer formation , peptide segregation into raft-like structures in the membrane , and characterization of protein-lipid interactions with both integral- and peripheral-membrane proteins [28] . Recently , the combination of homology modeling and CG-MD was used to investigate interactions between diverse voltage sensors and lipid bilayers [35] . Initial all-atom MD studies done on GgCP , in the absence of membranes , revealed that the α tentacle is rather immobile and remains stationary on the protein surface during the simulation [36] . This immobility is mainly stabilized by the interaction of W271 of the amphiphatic helix with the core of the animal protein . Interestingly , we observed that the homologous tryptophan in AtCP ( W288 ) , together with other hydrophobic residues of the α tentacle , is embedded into the membrane after 500 ns MD simulation ( Figure 8B ) . These data support the hypothesis of Wear and Cooper [37] , that proposes the induction of α tentacle mobility by non-ionic detergent . We suggest that a lipid bilayer could have a similar effect on the mobility of the α tentacle and facilitate embedding of hydrophobic residues . In this report , we describe differences between AtCP and GgCP for both C-terminal tentacles ( Figure 8A and Figure S4 ) , which may reflect distinct properties of CP–actin interaction between organisms . Alternatively , given that plant cells contain 10- to 100-fold lower amounts of PIP2 than PA [38] , [39] , one can speculate that differences in the tentacles is an adaptation to the distinct levels of PA and PIP2 in mammals and plants , i . e . increased binding properties of AtCP towards PA . As discussed above , we observed the embedding of the AtCP α tentacle into membranes containing PA . Consistent with this observation , we found a decreased number of polar residues in this tentacle . It is important to note that this difference is rather subtle , but mutations leading to a more nonpolar α tentacle could reduce actin binding [6] . We also observed that plant CPs have a shorter β tentacle and thus they lack the majority of the amphiphatic helix located in this region ( Figure S4 ) . We hypothesize that the PA- and actin-binding properties of plant CP have co-evolved to keep the right balance between actin regulation and responses to lipid signaling . Kooijman et al . [18] described remarkable properties of PA and proposed a model for the electrostatics/hydrogen bond switch , where arginine and lysine residues on binding peptides can increase the charge of PA to −2 . The authors also performed all-atom MD simulation of K8 and R8 peptides with bilayers formed from DOPC/DOPA and found that simulations where DOPA had charge −2 , were in better agreement with experimental results . In our simulations , we observed the dependence of AtCP binding on the charge of PA , but it is important to note , that when we observed the interaction , the binding mode was very similar for each system regardless of the PA charge ( Figure 4B and Figure S2A ) . Moreover , PA has a unique cone shape under physiological conditions and it has been proposed that PA could facilitate the insertion of hydrophobic protein domains into a bilayer [18] . Consistent with this hypothesis , we observed insertion of hydrophobic parts of the AtCP α tentacle into membranes containing PA ( Figure 8B and Figure S3 ) . In our CG-MD simulations with membranes containing 5% POPIP2 and POPC , we observed the involvement of both tentacles with either animal or plant CP ( Figure 4E , F and Figure 5B , D ) , suggesting cooperativity between both tentacles . When we simulated the system containing 1% POPIP2/POPC , we found that GgCP binds the phospholipid bilayer preferentially by the α tentacle ( Table 1 ) . Altogether , these results clearly show the importance of a positively-charged patch located on the α tentacle in both AtCP and GgCP . This region corresponds to lipid-binding site identified by Kim et al . [11] . We did not observe the involvement of the second putative PIP2-binding site proposed by Kuhn and Pollard [12] . Moreover , the latter positively-charged region is completely lacking in AtCP . Importantly , we obtained very similar quantitative trends for the interactions studied herein when compared to experimental approaches [10] . We found a much smaller difference between the binding of PA and PIP2 by AtCP when compared to GgCP . The energies of the interactions computed from experimentally determined Kd values vary from −24 to −29 kJ/mol , whereas from the umbrella sampling protocol , we computed the energy ranging from −62 to −236 kJ/mol . These discrepancies could be explained by different composition of the membrane ( experimental Kds were determined for the system with just one phospholipid , i . e . PA or PIP2 , and the lipids were in micelles rather than bilayers ) . The most recent information on CP–actin interactions comes from a study by Kim et al . [6] , who combined computational approaches with a large scale site-directed mutagenesis . They propose a model in which GgCP interacts with actin mainly via its tentacles and faces the actin filament barbed end with the top of the mushroom structure . The authors identified 49 residues of mammalian CP ( 18 on CPα and 31 on CPβ ) . They mutated 45 of these residues and found that only 10 showed more than a 3-fold increase in Kd . A direct comparison of these residues between GgCP and AtCP shows that 7 residues are highly conserved ( these residues include CPα-E200 , CPα-K256 , CPα-R260 , CPα-K268 , CPβ-R195 , CPβ-K223 and CPβ-R225 of mammalian CP ) . Interestingly , AtCP completely lacks nonpolar residues located on the β tentacle ( L258 , L262 , L266 ) which are responsible for the interaction with the hydrophobic cleft in actin . In our computed modes of the CP-membrane interaction , we observed that CP binds membranes mainly via its tentacles . Therefore , it is tempting to speculate that steric hindrance imposed by CP–membrane binding prevents actin binding . Interestingly , GgCP bound to the PA-containing membrane has the α tentacle and the top of the mushroom-like structure unoccupied ( Figure 4C ) . This could be an explanation why PA has not been described as an inhibitor of the activity of the animal CP [8] , [9] . In summary , our results provide structural insight into the regulation of CP by two signaling phospholipids , PA and PIP2 . A prominent role for the α and β C-terminal tentacles located on the top of the CP structure is apparent . We have shown differences of PA and PIP2 binding between AtCP and GgCP explaining published experimental data . Our results represent a comprehensive view of the interaction between CP and PA- or PIP2-containing membranes and reveal the mode of binding with structural implications for CP regulation . We also identified the PA-binding domain of AtCP and experimentally showed that it is sufficient for binding membranes in vitro . Our results call for intensive future research involving , in particular , a detailed mechanistic description of the phospholipid-induced uncapping of actin filaments . We also suggest that it would be relevant to examine the possible synergistic effects of distinct phospholipids on the inhibition of CP activity .
CP protein sequences were identified by gapped BLAST or PSI-BLAST [24] searching against the non-redundant protein database at the National Center for Biotechnology Information ( http://blast . ncbi . nlm . nih . gov/Blast . cgi ) using Arabidopsis annotated sequences with default settings . In addition , blast searches were conducted using Phytozome web page and DOE Joint Genome Institute ( http://www . phytozome . net/; http://www . jgi . doe . gov/ ) . In most cases , the search parameters were set at the default values; however , occasionally , modifications were used ( the changed parameters included mostly length of the word and type of scoring matrice ) . Putative genes were initially identified based on the automatic annotation at the aforementioned databases . Since gene models based on computer annotations often contain errors , exon-intron structures were manually curated with the aid of experimentally-verified sequences or sequences from closely related species . Multiple alignments were constructed with mafft algorithm ( in einsi mode ) [40] and manually adjusted . Maximum likelihood method using PhyML program [41] was employed for phylogeny inference with the WAG matrix , Γ-corrected among-site rate variation with four rate site categories plus a category for invariable sites , all parameters estimated from the data . Bayesian tree searches were performed using MrBayes 3 . 1 [42] with a WAG amino acid model , where all analyzes were performed with four chains and 1 000 000 generations per analysis and trees sampled every 100 generations . All four runs asymptotically approached the same stationarity after first 500 000 generations which were omitted from the final analysis . The remaining trees were used to infer the posterior probabilities for individual clades . A homology model for AtCP was built on the X-ray structure for GgCP ( rcsb 1IZN ) . The manually edited alignment obtained by PSIPRED [43] was used as input for MODELLER 9v8 [44] . As template contains shorter C-terminus of α subunit , residues ranging from 288 to 302 were forced to α-helix formation according to secondary structure prediction . The best model was selected on the energy and constraint violation values of MODELLER and further evaluated by PROSA and WHAT IF algorithms [45] , [46] . APBS program [47] was used to compute electrostatic potential of CP . To simulate self-assembly of lipid bilayers in the presence of protein , the MARTINI CG force field was used [21] , [22] . The protein was described according to ELNEDIN representation [48] with Rc 0 . 9 nm and K 500 kJ·mol−1·nm−2 . CG model for POPIP2 molecule was prepared according to [49] . GROMACS 4 . 0 . 5 was used for all MD simulations [50] . Lenard-Jones and electrostatic interactions were shifted to 0 between 9 and 12 Å and between 0 and 12 Å , respectively . A relative dielectric constant of 15 was used . Simulations were run in NPT ensemble . The temperature of protein , lipids , and solvent was coupled separately at 310 K using the Berendsen algorithm , with a coupling constant 1 . 0 ps . The system pressure was coupled using the same algorithm with a coupling constant 3 . 0 ps , compressibility of 3·10−5 and reference pressure 1 bar . Simulations were performed using a 20 fs integration time step . The protein , lipids and water were placed randomly in the simulation box . Na+ ions were added to ensure electroneutrality of the system . The whole system was energy-minimized using steepest descent method up to maximum of 500 steps and production runs were performed . In cases where some lipids remained apart from the lipid bilayer , CG water particles were used to replace them and the whole system was again energy-minimized . These systems or the final states of self-assembly were subsequently prolonged under the same conditions as self-assembly simulations . All simulations were repeated 3–5 times . The final configurations of four selected systems were used as inputs for the pulling experiments . The simulation box was extended in the z direction to capture the proposed trajectory of the pulling . Additional CG water particles were added to this extended space . The extended system was energy-minimized and short simulation for 50 ns was run . The CP was extracted from the membrane by applying a constraint force to the centre of mass ( COM ) of the protein in a direction coincident with z axis . Lipid molecules were restrained by position restraints during the pulling experiment ( kpr = 1000 kJ mol−1 nm−2 ) . CP was pulled at a rate of 0 . 5 nm ns−1 and COM pulling was carried out until the COM of CP was 4 nm apart from COM of the lipid bilayer . Snapshots along the pulling trajectory were extracted at COM spacing of 0 . 1 nm to generate starting configurations for umbrella sampling windows . For umbrella sampling calculation , we used approx . 40 windows from the pulling experiment described above . All generated configurations ( windows ) were equilibrated for 50 ns before PMF calculation . Afterwards , for each window a 100 ns long simulation was performed with the biasing potential applied to restrain COM of CP in a required distance from COM of the lipid bilayer . PMF curves were obtained using the WHAM algorithm [51] . It is important to note that times reported in this study are computational times . It was shown that effective times for CG simulations are longer; for proteins and lipids in MARTINI force field , the speed up factor is about four-fold [52] , i . e . 500 ns simulation time would correspond to 2 µs real time . The C-terminus of AtCP α subunit ( AtCPα-Cterm , aa 270–308 ) was amplified by PCR using Phusion DNA polymerase ( Finnzymes ) and cloned into the pGEX-KG vector . The resulting plasmid ( GST–AtCPα-Cterm ) was transformed into Escherichia coli strain BL21 and cells were grown overnight at 37°C . After sub-culturing into fresh medium , cells were grown at 37°C to an OD600 of approximately 1 . 5 , then induced for 4 h with 0 . 4 mM isopropyl thio-β-D-galactoside . Recombinant proteins were purified on glutathione-Sepharose ( GE Healthcare ) according to the manufacturer's instructions . Protein-lipid overlay assays with membrane lipid strips ( Echelon ) were performed according to manufacturer's instructions with protein concentration 0 . 5 µg/ml . To detect lipid binding in vesicles , we used the procedure described by [18] with slight differences; binding buffer comprised 125 mM KCl , 25 mM Tris , pH 7 . 8 , 1 mM dithiothreitol and 0 . 5 mM EDTA . To reveal lipid binding , we incubated 400 nmol of lipids with 1 µg of GST-tagged protein . | The actin cytoskeleton is a prominent feature of eukaryotes and plays a central role in many essential aspects of their lives . This highly malleable structure responds to a wide range of stimuli with rapid changes in organization or dynamics . These responses are thought to be mediated by dozens of actin-binding proteins , the biochemical activities of which have been demonstrated to be tightly controlled by other proteins and/or signal transduction mediators . In this study , we investigated the structural aspects of inhibition of actin-capping protein ( CP ) by phosphatidic acid ( PA ) and phosphatidylinositol ( 4 , 5 ) -bisphosphate ( PIP2 ) . We employed diverse computational methods in combination with experimental approaches to reveal mechanistic details of the direct interaction of CP with the phospholipid membrane containing either PA or PIP2 . Importantly , we found several differences between PA/PIP2–CP interactions from two distinct species , Arabidopsis and chicken , that enable us to explain and expand upon previously published results . Our new data shed light on the nature of interactions between peripheral membrane proteins and PA-containing lipid bilayers . In addition to a description of the phospholipid-mediated regulation of CP activity , our work also significantly contributes to the ongoing debate on structural details of protein interactions with phospholipids . | [
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] | 2012 | Structural Insights into the Inhibition of Actin-Capping Protein by Interactions with Phosphatidic Acid and Phosphatidylinositol (4,5)-Bisphosphate |
Many existing cohorts contain a range of relatedness between genotyped individuals , either by design or by chance . Haplotype estimation in such cohorts is a central step in many downstream analyses . Using genotypes from six cohorts from isolated populations and two cohorts from non-isolated populations , we have investigated the performance of different phasing methods designed for nominally ‘unrelated’ individuals . We find that SHAPEIT2 produces much lower switch error rates in all cohorts compared to other methods , including those designed specifically for isolated populations . In particular , when large amounts of IBD sharing is present , SHAPEIT2 infers close to perfect haplotypes . Based on these results we have developed a general strategy for phasing cohorts with any level of implicit or explicit relatedness between individuals . First SHAPEIT2 is run ignoring all explicit family information . We then apply a novel HMM method ( duoHMM ) to combine the SHAPEIT2 haplotypes with any family information to infer the inheritance pattern of each meiosis at all sites across each chromosome . This allows the correction of switch errors , detection of recombination events and genotyping errors . We show that the method detects numbers of recombination events that align very well with expectations based on genetic maps , and that it infers far fewer spurious recombination events than Merlin . The method can also detect genotyping errors and infer recombination events in otherwise uninformative families , such as trios and duos . The detected recombination events can be used in association scans for recombination phenotypes . The method provides a simple and unified approach to haplotype estimation , that will be of interest to researchers in the fields of human , animal and plant genetics .
The estimation of haplotypes from SNP genotypes , commonly referred to as ‘phasing’ , is a well studied problem in the literature . Existing approaches can be categorised according to the type of cohort each method is designed to phase , and the level of relatedness between the individuals in that cohort . Much of the recent literature is devoted to phasing nominally unrelated ( or distantly related ) individuals . Currently , the most accurate methods use hidden Markov models ( HMMs ) to model local haplotype sharing between individuals [1] , [2] , and take advantage of linkage disequilibrium ( LD ) . Some of these methods can also handle mother-father-child trios and parent-child duos [2]–[6] , for more complex pedigrees there are several general pedigree analysis software packages [7]–[10] . However such methods face several limitations; Lander-Green algorithm based approaches have computational and space complexity that scale exponentially with sample size; they can be sensitive to genotyping error and they can only phase sites where at least one member of the pedigree is not heterozygous . The last point is particularly crucial , as it means the haplotypes will not be ‘complete’ and cannot be easily used in pre-phasing and imputation which is now a standard part GWAS pipelines [11] . If founders in these pedigrees have been sequenced with the aim of imputing sequenced variants from founders into descendants who have been assayed on microarrays , then a pedigree phasing method that overcomes these issues will be especially useful . The task of phasing in isolated populations is some what of a special case , as individuals from such populations exhibit much higher levels of relatedness , and will tend to share much longer stretches of sequence identically by descent ( IBD ) than a pair of unrelated individuals from a non-isolated population . Kong at al . ( 2008 ) [12] proposed a method in which surrogate parents are identified for each individual in a given region of the genome . These surrogate parents allow the haplotypes to be determined with high accuracy using Mendelian inheritance rules , effectively as if the true parents had been observed and the family could be phased as a trio . More recently , a model based version of this approach called Systematic Long Range Phasing ( SLRP ) has been proposed [13] . Both of these papers demonstrated accurate haplotype estimates within IBD regions , but suffer from the problem that phase can only be inferred for genomic regions where IBD sharing is detected . Even in IBD regions , if a site is heterozygous in all individuals , the phase at that particular locus cannot be inferred . So far in the literature there has been very little investigation of the performance of methods for phasing in isolated populations . In addition , many GWAS cohorts consist of a range of relatedness between the study individuals . Some cohorts contain mixtures of pedigrees , weakly or cryptically related individuals and more distantly related individuals . Methods for carrying out association studies using related individuals have recently been re-discovered in the literature as a powerful approach , with the additional benefit of implicitly avoiding confounding due to population structure [14]–[16] . In addition , explicit detection of tracts of IBD between pairs of individuals is becoming more widely used for detection of disease genes [17]–[20] and for population genetic analyses [21] , [22] . More generally , isolated populations offer promise for interrogating common complex diseases [23] . For many such cohorts phasing will be a first step in performing imputation from a reference panel [11] or as part of an IBD detection analysis , so it is interesting to consider the performance of alternative phasing methods . We recently compared several methods all designed to phase nominally unrelated samples ( SHAPEIT2 [2] , SHAPEIT1 [5] , Beagle [4] , HAPI-UR [6] , Impute2 [24] , MaCH [25] , fastPHASE [26] ) and found that SHAPEIT2 was the most accurate method in this setting . In this paper we examine the performance of these methods at increasing levels of relatedness between individuals . To do this we used cohorts from six different isolated populations ( and two additional cohorts from non-isolated populations ) . Each of these cohorts contain some extended pedigrees allowing us to assess performance on both nominally unrelated individuals and on explicitly related samples . For cohorts with explicitly related samples we introduce a new hidden Markov model ( which we call duoHMM ) that can estimate the inheritance pattern between between the haplotypes of each parent-child duo . This method can be used to visualise the inheritance status across a chromosome , correct phasing errors that are inconsistent with pedigree information , and detect genotyping errors . We show that after applying this adjustment , SHAPEIT2's haplotypes are accurate enough that we can detect explicit recombination events between parent-child pairs . Applying this method to the SHAPEIT2 inferred haplotypes provides the most accurate performance in the extended pedigree setting . Using our method we are able to demonstrate that the recombination events that we infer from otherwise uninformative duos and trios can add power to association scans for recombination phenotypes . Specifically , at the established PRDM9 locus we are able to show that including these extra recombination events increases the signal of association for a hot spot usage phenotype . Overall , the combination of SHAPEIT2 and duoHMM provides a very general method for accurate phasing of cohorts with any levels of implicit or explicit relatedness between individuals . SHAPEIT2 and duoHMM are available from the website: http://www . stats . ox . ac . uk/marchini/software/gwas/gwas . html
To provide a comprehensive assessment of the accuracy of methods we analysed eight different cohorts that vary in the extent of the relatedness between individuals . The cohorts are summarised in Table S1 , six of these are considered to be from isolated populations . The Orkney Complex Disease Study ( ORCADES ) is an ongoing study in the isolated Scottish archipelago of Orkney [27] . The CROATIA-VIS ( Vis ) and CROATIA-KORCULA ( Korcula ) studies contain individuals recruited from the Dalmation islands of Vis and Korcula [27] , [28] . The INGI-Val Borbera population is a collection of 1 , 664 genotyped individuals collected in the Val Borbera region , a geographically isolated valley located within the Appennine Mountains in Northwest Italy . The valley is inhabited by about 3 , 000 descendants from the original population , living in seven villages along the valley and in the mountains [29] . The INGI-FVG Cohort is a collection of six different isolated villages in the Friuli Venezia Giulia region of northern Italy [30] . The INGI-CARL cohort contains individuals from Carlantino , a small isolated village in the province of Foggia in southern Italy [30] . The CROATIA-Split ( Split ) cohort contains individuals from the Croatian city of Split [31] . Finally , a large sample from the Ugandan General Population Cohort ( GPC ) [32] , covering residents of 25 villages in south-Western Uganda were analysed . These final two cohorts are not considered to be isolated and hence are useful as control samples of unrelated individuals . Each of these cohorts contain pedigrees of varying sizes ( see Table S1 ) which can be used to evaluate phasing accuracy . The GPC cohort was genotyped using the Illumina Human OMNI 2 . 5S chip . All the other cohorts were genotyped using either the Illumina HumanHap300 or HumanCNV370 chips . In addition to quality control ( QC ) performed on each cohort by their respective research groups , we applied stringent filters to remove genotypes inconsistent with pedigree structure . Firstly , we ran Pedstats [33] to detect any genotypes that violated Mendelian constraints , and these loci were marked as missing for all individuals in a pedigree where violations were found . Loci that produced Mendel violations for of samples were filtered for all individuals in a cohort . Secondly , Merlin's error detection algorithm was used on all pedigrees , and genotypes which were unlikely were also flagged as missing . This final set of genotypes were used as input in all subsequent analyses . All software was run as per instructions in their respective manuals . The computation times for each method for the largest experiment conducted on European cohorts are summarised in Figure S1 , a more comprehensive study of running times was conducted in the original SHAPEIT2 paper [2] . The results below show that SHAPEIT2 can implicitly leverage IBD sharing and hence phase a pedigree accurately without any relationships specified . Additional use of explicit relationships is likely to lead to even greater improvements . The Lander-Green algorithm is traditionally the method of choice for phasing pedigrees but has several limitations described previously . We developed a simple HMM applicable to the SHAPEIT2 haplotypes that corrects phasing errors that are inconsistent with pedigree information . The method focuses separately on each parent-child duo and this circumvents several issues with the Lander-Green algorithm , namely; We describe the model and several useful applications of it below . We refer to this framework as the duoHMM in later sections of the paper . In our real data experiments we use haplotypes inferred by Merlin as the ‘true’ haplotypes for our methods comparison . In the Results section we show that SHAPEIT2 phases extended pedigrees with close to perfect concordance with the haplotypes produced by Merlin ( typically average SE ) . This level of discordance is of a similar order to both the number of recombination events , and genotyping error [42] which the Lander-Green algorithm is known to be sensitive to . Whilst we have applied standard quality control procedures ( including Merlin's error checking ) to these data , genotyping errors are likely to still be present . Hence at least some of this discordance may be in fact due to errors in Merlin haplotypes . We also compare the recombination events detected by Merlin in extended families to those detected by our duoHMM approach . Any discordance between these crossover callsets may also be due ( in part ) to Merlin errors . We also wanted to investigate the ability of our method to call crossover events in duos and trios which cannot be done with the Lander-Green algorithm . For these reasons we created several simulated datasets to investigate these issues . We utilised male chromosome X haplotypes as the basis for these simulated datasets . Since males only have one copy of chromosome X , phase is unambiguously known . As in previous phasing studies [2] , [43] , [44] , two male X chromosomes were combined to create a pseudo autosomal diploid founder individual where the true underlying haplotypes are known . We then randomly mate these new diploid individuals to produce offspring with recombined haplotypes . Crossover events were simulated as a Poisson process on the genetic lengths from the HapMap Chromosome X genetic map for females and the same map scaled by 0 . 605 for males ( difference in rates estimated from 2002 deCODE Map ) . In all experiments , we applied a simple rejection sampling scheme to avoid large amounts of consanguinity in our new diploid individuals and their offspring . The X chromosomes used to create pedigree founders were sampled such that no pair of chromosomes came from pairs of males with genome wide relatedness [45] . We conducted these experiments using the 1071 ( 607 females and 464 males ) nominally unrelated individuals from the Val Borbera cohort . This allowed us to create up 232 to diploid individuals with known haplotypes .
Figure 2 ( left ) shows the proportion of heterozygote sites phased by SLRP , which we refer to as the yield . SLRP's yield ranged from 31 . 82% for the Split cohort to 88 . 15% for the ORCADES cohort . Split and GPC were the only cohorts with less than 60% yield demonstrating low levels of IBD sharing between individuals in these cohorts . Following Palin et al . [13] we also examined individuals who were not “closely” related by excluding all individuals with a realised relatedness [45] of . We found the yield was substantially lower in the CARL and FVG cohorts demonstrating some of the IBD sharing present was between closely related individuals rather than distant cousins in these cohorts . All other cohorts did not exhibit as large a drop in yield after removing closely related individuals , highlighting the large amounts of IBD sharing between more distantly related individuals in these cohorts . Similar to Kong et al . ( 2008 ) [12] , we took each individual in turn and at each locus we calculated the number of other individuals that share an IBD segment ( excluding closely related individuals with relatedness ) . We then took the average across all loci on chromosome 10 for each individual and plotted the distribution of this average IBD sharing in Figure 2 ( right ) . The average IBD sharing is a function of both the sample size and the amount of relatedness between individuals in the population . Split again clearly has very small amounts of IBD sharing whilst the other cohorts have broadly similar distributions . It is notable that all cohorts have some individuals with surrogate parent on average while some individuals have surrogate parents . Table 1 shows the SE rates for SHAPEIT2 , SLRP , Beagle and HAPI-UR when run on the founder individuals of each cohort , both within and outside SLRP IBD segments . SHAPEIT2 consistently produced the most accurate haplotypes of all methods within IBD regions . SHAPEIT2 had a mean SE rate of between 0 . 14% ( ORCADES ) and 0 . 75% ( CARL ) , the next closest method was SLRP with SE rates between 0 . 28% ( GPC ) and 1 . 99% ( Split ) , followed by Beagle with SE rates between 0 . 30% ( GPC ) and 4 . 38% ( Split ) . HAPI-UR had high SE rates ranging between 0 . 35% ( GPC ) and 8 . 30% ( Split ) . The GPC cohort stands out here , as all methods perform very accurately ( % SE ) which can be explained by the larger sample size of this cohort ( 2 , 676 individuals in total ) and the much denser chip ( Illumina Human OMNI2 . 5S ) used to genotype this cohort . It is interesting that SHAPEIT2 seems to have the highest SE rates on the CARL cohort , which has only the second lowest level of relatedness between founders ( Figure 2 ( right ) ) . Figure S6 ( left ) shows the SLRP IBD SE rate against the SHAPEIT2 rate for each individual in the Val Borbera cohort . This highlights that both methods produce SE rates close to zero on many individuals but SHAPEIT2 is generally more accurate . When calculating SE rate across the whole of chromosome 10 ( not just in IBD regions ) , SHAPEIT2 also has the lowest error rate , ranging from 0 . 28% ( GPC ) to 2 . 65% ( Split cohort ) as opposed to 0 . 49% and 5 . 57% for Beagle and 0 . 50% and 11 . 10% for HAPI-UR . Switch error rates for SLRP cannot be evaluated across the whole of chromosome 10 due to the method only producing partially phased haplotypes . We observe that all methods perform relatively better within IBD regions than across the whole chromosome . However , the difference for SHAPEIT2 is much larger than for Beagle and HAPI-UR . These results suggest that whilst none of these methods explicitly model IBD sharing , its presence tends to be exploited implicitly , and particularly so in SHAPEIT2 . Figure S6 ( right ) plots the SHAPEIT2 SE rate within IBD regions ( detected by SLRP ) against the rate outside these regions . Switch error is clearly close to zero when IBD sharing is present and has a rate more comparable to non-isolated populations when no IBD sharing is present .
Long range phasing has been a topic of interest since its inception by Kong ( 2008 ) [12] and has great potential for the analysis of genomic data , particularly as cohort sizes increase and hence more IBD sharing becomes present between individuals . Whilst the deCODE project has generated some excellent results , they have the advantage of an extremely powerful data set containing substantial amounts of IBD sharing which allows a rule based approach to long range phasing that yields very accurate haplotypes . This is not a luxury available to many research groups . We demonstrate that SHAPEIT2 implicitly performs this very accurate long range phasing when possible , whilst still leveraging LD when it is not . Using eight cohorts from isolated and non-isolated populations , all containing explicitly related individuals , we have carried out a comprehensive evaluation of approaches for haplotype estimation in the presence of IBD sharing . We compared approaches that are specifically focused on estimation of haplotypes in isolated samples ( SLRP ) and others ( SHAPEIT2 , Beagle and HAPI-UR ) that were designed predominantly for cohorts of nominally unrelated individuals . Our experiments show that the SHAPEIT2 method provides high quality haplotypes that are more accurate than those estimated by SLRP , whereas Beagle and HAPI-UR produce results that are worse than SLRP . We find that the SE rates of SHAPEIT2 are a fraction of a percent in all cohorts , whereas the approaches BEAGLE and HAPI-UR produce SEs that are an order of magnitude larger . A big disadvantage of existing pedigree analysis software is the inability to leverage wider cohort information to resolve sites that are heterozygous throughout a particular pedigree . Hence there is a need for software that can fully leverage the relatedness within pedigrees for accurate phase whilst overcoming the limitations of traditional pedigree analysis software . We propose a two-stage approach in which SHAPEIT2 is first run ignoring all explicit family information . We then apply the duoHMM method to incorporate the pedigree information in a cohort to further increase the accuracy of haplotypes inferred . The duoHMM method infers the inheritance pattern in parent-child duos , detects genotyping errors and can correct switch errors . We have found that the resulting haplotypes from our method are so accurate that we can infer recombination events in parent-child duos . We use the output of our duoHMM to estimate the probability that a recombination event occurs between each pair of heterozygous markers . When applied to all eight cohorts across whole chromosomes we find that the number of recombination events inferred by our method shows close agreement with the genetic length of each chromosome . We also find that the observed number of recombination events per individual closely matches what we expect to observe based on genetic map estimates . These results are also much better than those produced from Merlin , which shows elevated rates of recombination events across all chromosomes . On realistic simulated data our method ( TPR = 92 . 4% , FDR = 3 . 78% ) substantially outperforms Merlin ( TPR = 90 . 57% , FDR = 62 . 48% ) . An additional benefit of our method is that we can attempt to infer recombination events in trios and duos . Methods that explicitly phase trios and duos using the pedigree information cannot infer recombination events since they infer only the transmitted haplotypes of the parents . We evaluated this approach via simulation and found that we have power to detect events at a 5% false discovery rate when the duo is phased in an isolated cohort that may contain close relatives . When close relatives are removed we have power to detect events at a 5% false discovery rate . Cohorts that contain explicit trios and duos could be phased using methods that explicitly use this information if desired although the ability to infer recombination events would be lost and parents would be estimated as a pair of transmitted and untransmitted haplotypes . Using our method we are able to demonstrate that the recombination events that we infer from otherwise uninformative duos and trios can add power to association scans for recombination phenotypes . Specifically , at the established PRDM9 locus we are able to show that including these extra recombination events increases the signal of association for a hot spot usage phenotype . The field of study of recombination continues to be very active [47] . Future studies will look at recombination in isolated populations in sub-saharan Africa . Our method will allow GWAS of recombination phenotypes to be carried out in these populations , extracting as much information as possible from the data . Precisely determining why these large differences in performance between the methods exist is difficult . We suspect that the reason resides in the fact that within the SHAPEIT2 method the haplotypes of each individual are explicitly modelled as a mosaic of the underlying haplotypes of other individuals [48] . In other words the underlying haplotype sharing between two individuals can be explicitly captured by allowing each individual to ‘copy’ the haplotypes of another individual over a long stretch of sequence . BEAGLE takes a different approach by collapsing the haplotype information of the sample into a compact graph . Each individual's haplotypes are then updated within the method conditional upon this graph . Thus no direct comparison between pairs of individuals is made and thus the information regarding long stretches of shared sequence between individuals is lost . These comments also apply to HAPI-UR which uses a different graph to encode the haplotypes of the samples . Our results are consistent across a range of cohorts with differing levels of relatedness . Most of these cohorts are isolated cohorts but the Split and GPC cohorts contain levels of relatedness that might be expected in a GWAS cohort . In this paper we have focused exclusively on genetic data from human samples but our methods may also be useful in the fields of animal and plant genetics where cohorts with high levels of relatedness are prevalent [49] . This method may also find utility in studies that aim to locate IBD segments between individuals . Based on these results we might suggest that a strategy of estimating haplotypes with SHAPEIT2 followed by application of the GERMLINE method [50] for IBD inference from haplotype data may provide an accurate and efficient solution . As cohorts increase in size , or as cohorts are combined , the chance of any individual sharing a close relative in the cohort increases . Methods such as SHAPEIT2 , that can accurately leverage this IBD information when estimating haplotypes may help to extract the most information from such large cohorts . Previous research has demonstrated SHAPEIT2's effectiveness for phasing cohorts of unrelated individuals , in this paper we demonstrate that SHAPEIT2 is in fact effective across the full spectrum of relatedness . This means that researchers with cohorts with any mixture of unrelated , distantly related or directly related individuals have a flexible tool available which can exploit all of these degrees of relatedness for very accurate haplotype estimates . | Every individual carries two copies of each chromosome ( haplotypes ) , one from each of their parents , that consist of a long sequence of alleles . Modern genotyping technologies do not measure haplotypes directly , but the combined sum ( or genotype ) of alleles at each site . Statistical methods are needed to infer ( or phase ) the haplotypes from the observed genotypes . Haplotype estimation is a key first step of many disease and population genetic studies . Much recent work in this area has focused on phasing in cohorts of nominally unrelated individuals . So called ‘long range phasing’ is a relatively recent concept for phasing individuals with intermediate levels of relatedness , such as cohorts taken from population isolates . Methods also exist for phasing genotypes for individuals within explicit pedigrees . Whilst high quality phasing techniques are available for each of these demographic scenarios , to date , no single method is applicable to all three . In this paper , we present a general approach for phasing cohorts that contain any level of relatedness between the study individuals . We demonstrate high levels of accuracy in all demographic scenarios , as well as the ability to detect ( Mendelian consistent ) genotyping error and recombination events in duos and trios , the first method with such a capability . | [
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... | 2014 | A General Approach for Haplotype Phasing across the Full Spectrum of Relatedness |
Venereal syphilis is a multi-stage , sexually transmitted disease caused by the spirochetal bacterium Treponema pallidum ( Tp ) . Herein we describe a cohort of 57 patients ( age 18–68 years ) with secondary syphilis ( SS ) identified through a network of public sector primary health care providers in Cali , Colombia . To be eligible for participation , study subjects were required to have cutaneous lesions consistent with SS , a reactive Rapid Plasma Reagin test ( RPR-titer ≥1∶4 ) , and a confirmatory treponemal test ( Fluorescent Treponemal Antibody Absorption test- FTA-ABS ) . Most subjects enrolled were women ( 64 . 9% ) , predominantly Afro-Colombian ( 38 . 6% ) or mestizo ( 56 . 1% ) , and all were of low socio-economic status . Three ( 5 . 3% ) subjects were newly diagnosed with HIV infection at study entry . The duration of signs and symptoms in most patients ( 53 . 6% ) was less than 30 days; however , some patients reported being symptomatic for several months ( range 5–240 days ) . The typical palmar and plantar exanthem of SS was the most common dermal manifestation ( 63% ) , followed by diffuse hypo- or hyperpigmented macules and papules on the trunk , abdomen and extremities . Three patients had patchy alopecia . Whole blood ( WB ) samples and punch biopsy material from a subset of SS patients were assayed for the presence of Tp DNA polymerase I gene ( polA ) target by real-time qualitative and quantitative PCR methods . Twelve ( 46% ) of the 26 WB samples studied had quantifiable Tp DNA ( ranging between 194 . 9 and 1954 . 2 Tp polA copies/ml blood ) and seven ( 64% ) were positive when WB DNA was extracted within 24 hours of collection . Tp DNA was also present in 8/12 ( 66% ) skin biopsies available for testing . Strain typing analysis was attempted in all skin and WB samples with detectable Tp DNA . Using arp repeat size analysis and tpr RFLP patterns four different strain types were identified ( 14d , 16d , 13d and 22a ) . None of the WB samples had sufficient DNA for typing . The clinical and microbiologic observations presented herein , together with recent Cali syphilis seroprevalence data , provide additional evidence that venereal syphilis is highly endemic in this region of Colombia , thus underscoring the need for health care providers in the region to be acutely aware of the clinical manifestations of SS . This study also provides , for the first time , quantitative evidence that a significant proportion of untreated SS patients have substantial numbers of circulating spirochetes . How Tp is able to persist in the blood and skin of SS patients , despite the known presence of circulating treponemal opsonizing antibodies and the robust pro-inflammatory cellular immune responses characteristic of this stage of the disease , is not fully understood and requires further study .
Syphilis is a sexually transmitted disease ( STD ) caused by the spirochetal bacterium Treponema pallidum ( Tp ) subspecies pallidum [1] , [2] . Despite the existence of inexpensive and effective antibiotic treatment regimens , syphilis continues to be a major public health problem . According to the most recent World Health Organization ( WHO ) estimates , approximately 10 . 6 million new syphilis cases occur yearly throughout the globe [3] . Although venereal syphilis has re-emerged in developed countries [4] , most individuals ( >90% ) who acquire the disease reside in less affluent regions of the world [3] . In Cali , Colombia , our Latin American study site , the yearly incidence of venereal syphilis over the last decade was estimated to be around 32 cases per 100 , 000 ( GE Aristizabal , City of Cali Health Department's STD Division - personal communication ) . This approximation is significantly higher than in Western Europe [5] or in the United States [4] , and based on the very high rates of well documented gestational and congenital syphilis rates in the city [6] , it very likely underestimates the true prevalence of venereal syphilis in Cali . Indeed , in a recent study conducted by our collaborators [7] , 1 . 2–6 . 8% of 23 , 190 sexually active 15–24 year old men and women , from different socioeconomically deprived Cali districts “comunas” , had serum RPR values ≥1∶8 . In the same study , 13 . 8% of men who have sex with men ( MSM ) , 28 . 8% of female commercial sex workers and 39 . 2% of transsexuals in Cali were also found to be sero-positive for syphilis [7] . Strategies to control sexual transmission of Tp are , thus , urgently needed in Colombia , not only because of the harmful consequences of syphilis to infected pregnant women or their unborn children [5] , [8] , [9] , but also because of the strong association of venereal syphilis with an increased risk for acquiring and transmitting human immunodeficiency virus ( HIV ) [4] , [10]–[12] . To begin to curb the spread of venereal syphilis it is very important that health care providers become more adept at distinguishing the typical and atypical signs and symptoms associated with early syphilitic infection . Unlike most invasive bacterial infectious diseases , venereal syphilis is a multistage illness with clinical manifestations that reflect the propensity of Tp to disseminate systemically and to induce persistent chronic inflammation in diverse tissues and organ systems [1] , [2] , [13] , [14] . Infection begins when the bacterium comes in contact with skin or mucosal membranes , multiplying locally over several days , while simultaneously disseminating through blood vessels and lymphatics [2] , [15] . The appearance of a painless ulcer , more commonly known as a “chancre” , typically only appears 2–4 weeks after the initial contact with the spirochete [2] , [15] , [16] . By this time , organisms have disseminated from the primary site of infection to various organ systems and throughout the dermis [2] , [15] , setting the stage for what is classically known as secondary syphilis . This stage of the disease , which is the principal focus of the current study , is characterized by the most overt systemic clinical features , including a variety of dermal manifestations as well as systemic signs and symptoms typically appearing within 4–10 weeks of the initial infection [13] , [14] . Despite the evolving nature of the adaptive immune response [17] , including the presence of opsonic antibodies [18] , it may take weeks and in some cases months for the host to gain the upper hand against the invading pathogen , ultimately giving rise to an asymptomatic stage known as latent syphilis . During early latency ( the first 4 years post-infection ) patients may experience recurrences of spirochetemia as well as clinical relapses [13] , [15] , [19] , both indicative of the host's inability to fully eradicate and control the bacterium . In due course , patients enter late latency and several years later 15–40% of them develops recrudescent forms of the disease; collectively referred to as tertiary syphilis [14] , [20] , [21] . How the bacterium disseminates from its primary or secondary sites of infection , and why it persists in its human host for extended periods of time despite the vigorous cellular and humoral adaptive immune responses it evokes [2] , [17] , remains unresolved . Greater progress towards deciphering the pathogenesis of the paradoxical nature of venereal syphilis has been hampered due to the inability to readily propagate Tp in vitro , as well as the lack of a suitable inbred animal model to study the disease . Nevertheless , much can be learned about the pathogenesis of venereal syphilis through a combined analysis of the epidemiologic , clinical and microbiologic features of the various stages of the disease . In the current study we review the clinical , histopathologic and laboratory features of 57 patients diagnosed with SS through a network of public sector primary health care providers in Cali , Colombia . Concurrently we determined spirochetal DNA burdens in WB and skin samples from a subset of these patients by using a highly sensitive real-time PCR assay . In conjunction with available Cali syphilis seroprevalence data [7] , this study provides clinical and microbiologic evidence that venereal syphilis is highly endemic in this region of Colombia . Our findings also make evident that in this population early syphilis patients may go undiagnosed and untreated for several weeks , in some cases for several months . We also provide , for the first time , quantitative and/or qualitative molecular evidence that spirochetes are present in significant numbers in skin and blood of untreated SS patients . Paradoxically , spirochetes persisted despite the known presence of circulating antitreponemal opsonizing antibodies in the serum of SS patients [18] , as well as the robust pro-inflammatory dermal cellular immune response characteristic of this stage of the disease [17] .
SS patients from Cali , Colombia were recruited from 2003 to 2009 as part of an ongoing syphilis immunology study [10] . Cali is the 3rd largest city in Colombia with a population of 2 , 139 , 535; many of whom belong to middle or low socio-economic strata ( 32 . 1% and 31 . 6% respectively ) . Out of 22 distinct comunas in the city , 11 are considered very poor , have less than adequate access to health care services and as already alluded to above , very high RPR seropositivity rates [7] . Five public health institutions called Empresas Sociales del Estado ( ESEs ) are strategically located throughout the city , and are responsible for providing regional health care to the local population residing in the various comunas ( Figure 1 ) . Prior to study initiation , nurses and physicians working in decentralized hospitals and health care centers affiliated to individual ESEs were trained by study personnel to properly recognize and treat early syphilis patients . Patients who met criteria for a diagnosis of SS and who agreed to participate in the study were referred by participating providers to the “Centro Internacional de Entrenamiento e Investigaciones Médicas” ( CIDEIM ) for further examination by study physicians and for confirmatory blood tests . At CIDEIM all participants were required to sign informed consent . Study procedures were reviewed and approved by the human subjects boards at the Connecticut Children's Medical Center , the University of Connecticut Health Center ( UCHC ) , Walter Reed Army Institute of Research ( WRAIR ) and CIDEIM . The study protocol was also reviewed by ethics committee from each of the participating ESEs . The Institutional review board at the Centers for Disease Control and Prevention ( CDC ) approved the molecular analysis of Tp DNA in blood samples and skin biopsies obtained from secondary syphilis patients and controls . The diagnosis of secondary syphilis was based on a compatible medical history , the appearance of characteristic skin or mucosal lesions ( see below ) , a reactive RPR of ≥1∶4 dilutions , and a positive confirmatory treponemal test ( Fluorescent Treponemal Antibody Absorption , FTA-ABS ) . All subjects had a complete physical examination performed by one of two trained dermatologists ( AC or RT ) who are well versed in the identification of venereal syphilis . Individual case histories , serologic data , and photographs of dermal and cutaneous lesions were then reviewed by at least one of two infectious disease experts ( JR or JS ) . Serologic tests for syphilis and HIV were conducted for all participants at a centralized reference laboratory in Cali . Study subjects were not eligible for participation if they were <18 years old , if they were known to be HIV+ or if they had used antibiotics within 4 weeks prior to study entry . Pregnant women were also excluded from participation . Socio-demographic characteristics and relevant clinical and epidemiological information were obtained by means of a standardized questionnaire . Study dermatologists obtained skin biopsies from 11 patients who had representative syphilis dermal lesions . Whole blood and skin biopsies were also collected from a subset of patients for real time polymerase chain reaction ( PCR ) Tp DNA quantitation ( see below ) . All patients were treated with 2 . 4 million units of intramuscular benzathine penicillin in accordance with Colombian public health guidelines , which are in accord with available CDC treatment guidelines [22] . Patients were asked to return within 45–60 days for a follow-up clinical examination and repeat RPR titers . When possible , partner notification and treatment were done by health care providers from the city of Cali's health department . Diagnosis and treatment of additional STDs was done through the patient's primary health care provider . All patients had non treponemal ( RPR ) , and treponemal ( FTA-ABS ) tests performed at a reference laboratory in Colombia . An ECLIA ( Electro-chemiluminescence Immunoassay ) HIV serum antibody test , a complete blood count ( CBC ) with manual differential , and quantitation of the erythrocyte sedimentation rate ( ESR ) were also done . All women underwent a serum pregnancy test ( none were positive ) . The three positive HIV ECLIAs identified in study patients were subsequently confirmed by Western-blot analysis . HIV-positive patients were referred to a public health care sector HIV clinic for additional testing and treatment . Dark field microscopy was not required in this study . Punch biopsies from affected dermal sites were obtained by the study dermatologist from 11 patients deemed to have distinctive clinical manifestations classically associated with SS . Available tissues from these patients were stained with both hematoxilin-eosin ( H&E ) and Warthin-Starry silver stain ( one ( 9% ) revealed spirochetes by silver stain ) . Individual biopsy samples were then systematically analyzed by trained pathologists in Colombia and subsequently corroborated by a pathologist in the United States . The clinical sensitivity of the polA real-time PCR was determined by testing blood spiked with either purified Tp DNA or Tp organisms . Fifty milliliters of peripheral blood was collected in EDTA tubes from a single donor . The blood sample was maintained at room temperature prior to performing spiking experiments . Tp was grown in the testis of New Zealand white rabbits and harvested as previously described [23] . The cultivation of T . pallidum in rabbits was approved by the CDC animal care committee . Treponemes were diluted to a concentration of 1 . 5×107/ml using prewarmed TpCM ( Tp cultivation medium ) . A ten-fold serial dilution of the suspension was performed using prewarmed TpCM and a 200µl aliquot of each ten-fold dilution was added in duplicate to 1 . 8 ml of blood . One set of tubes was kept at room temperature for 1 hr while the second set was placed in a refrigerator for 26 hrs . DNA was extracted from a 200µl aliquot of the 10−1 dilution of Tp organisms in TpCM using the QIAamp DNA Mini Kit ( Qiagen , Valencia , CA ) . The purified DNA was serially diluted ten-fold in sterile PBS and a 200µl aliquot of each ten-fold dilution was added in duplicate to 1 . 8 ml of blood . Tubes were left at room temperature for 1 hr or stored at 4°C as for blood spiked with Tp organisms . DNA extraction from all spiked blood samples was achieved using the QIAamp DNA Midi kit ( Qiagen ) and the purified DNA was eluted in 500µl Buffer AE . A 10µl sample was tested in duplicate using a real-time PCR that targets the DNA polymerase I gene of Tp ( polA ) . Five to ten milliliters of whole blood were collected in tubes containing EDTA ( 1 . 8mg EDTA per milliliter of blood ) from 26 SS patients enrolled during the last three years of the study . The first 15 WB samples collected were stored frozen for several days and subsequently shipped on dry ice overnight to UCHC . DNA was subsequently extracted from 0 . 4 ml of whole blood using the QIAamp DNA Blood Mini Kit ( Qiagen ) following procedures recommended by the manufacturer . For the last eleven patients enrolled into the study DNA was extracted from whole blood samples on site by CIDEIM personnel , and subsequently shipped on dry ice to UCHC . A 4 mm-punch skin biopsy of SS lesions was also obtained from the same group of patients and controls , snap-frozen and stored in liquid nitrogen in preparation for overnight transportation on dry ice to UCHC . Skin from three healthy controls was also obtained at CIDEIM and handled in the same fashion . Upon arrival at UCHC , DNA was extracted from all skin samples using the Qiagen DNAeasy Blood and Tissue kit ( Qiagen ) . DNA samples from both the skin and WB were eventually shipped on dry ice to the Laboratory Reference and Research Branch , Division of STD Prevention , at the CDC in Atlanta , Georgia for diagnostic PCR testing . Samples were tested using a real-time PCR targeting the Tp polA gene ( Gene Bank Accession No . U57757 ) as described below . PCR amplification was performed using forward primer TP-1 ( 5′CAGGATCCGGCATATGTCC3′ ) , reverse primer TP-2 ( 5′AAGTGTGAGCGTCTCATCATTCC3′ ) , and probe TP-3 ( 5′CTGTCATGCACCA GCTTCGACGTCTT3′ ) as previously published [24] with some exceptions . The probe was labeled with Cyanine ( Cy5 ) at the 5′ end and black-hole quencher 3 ( BHQ3 ) at the 3′ end . PCR was performed in 50µl reaction volumes containing the following: 4µl of deoxynucleoside triphosphate mix ( 2 . 5mM of dATP , dCTP , dGTP , and 5 . 0mM of dUTP ) , 6µl of MgCl2 ( 25 mM ) , 0 . 2µM of each primer , 0 . 6U uracil N-glycosylase , 5U of AmpliTaq Gold polymerase , 5µl of 10× PCR buffer ( All Applied Biosystems , Foster City , CA ) , 0 . 2µM of probe , and 12µl of template DNA . Thermocycling was performed in a Rotor-Gene 6000 instrument ( Qiagen ) as follows: 50°C for 2 min and 95°C for 10 min and 45 cycles of 95°C for 20 sec and 60°C for 1 min . Each PCR run included positive and negative ( no template ) control reactions . The Tp copy numbers for each WB specimen were extrapolated from the standard curve generated using ten-fold serial dilutions of purified Tp DNA . A human ribonuclease ( RNase ) P gene PCR assay was used , as previously described [25] , to test for PCR inhibition in blood samples that were negative by the polA real-time PCR assay . Strain typing was attempted for all WB and skin samples obtained from SS patients , which were Tp-positive by diagnostic PCR . PCR amplification and sizing of the 60-bp tandem repeats within the arp ( acidic repeat protein ) gene and PCR-restriction length polymorphism ( RFLP ) analysis of tpr ( T . pallidum repeat ) E , G , and J genes was done as previously described by Pillay et al . [26] , [27] , with two modifications . First , the tandem repeat region within the arp gene was amplified with a new primer pair , N1 ( 5′ATCTTTGCCGTCCCGTGTGC3′ ) and N2 ( 5′CCGAGTGGGATGGCTGCTTC3′ ) using the existing PCR conditions for the arp assay . Second , all PCR amplicons were analyzed on an Agilent 2100 Bioanalyzer ( Agilent Technologies , San Diego , California ) .
A total of 57 patients ( age 18–64 years , median 31 years ) met the case definition for SS and were recruited by a network of primary health care providers located throughout Cali ( Figure 1 ) . All enrolled SS patients resided in comunas of the city of low or very–low socio-economic conditions . Most participants were either unschooled ( 10 . 5% ) or had only partially completed elementary school education ( 59 . 6% ) . Because we did not directly target more affluent communities in Cali , we are unable to decisively conclude that SS principally affects underprivileged groups . Consistent with prior SS case series [14] , the majority of SS patients enrolled were women ( 64 . 9% ) . Most participants were either Afro-Colombian ( 38 . 6% ) or of mixed race ( mestizo ) ( 56 . 1% ) . Given that 25 . 3% of the general population in this region of the country is of Afro-Colombian background [28] , it is evident that in this study blacks were proportionately over-represented . The majority of subjects self-reported a high-risk sexual behavior history ( 62 . 5% ) , including having multiple sexual partners , rarely using condoms , and/or having contact with commercial sex workers . Almost a quarter ( 24 . 6% ) gave a history of illicit drug use and 59 . 6% stated that they consumed alcohol routinely . One male patient admitted to having had unprotected sex with other men as the principal risk factor for acquiring syphilis . 5 . 3% of the subjects enrolled in our study were newly diagnosed with HIV . A diagnosis of HIV co-infection is consistent with available epidemiologic and biologic evidence demonstrating that infection with Tp increases the likelihood of both transmitting and acquiring HIV [12] , [29]–[31] . The mean duration of signs and symptoms at the time of presentation was 78 . 6 days ( range 5–240 ) , with a median duration of 30 days . A history of undocumented fever was not uncommon ( 15 . 8% ) ; however , none of the patients enrolled was febrile at the time of the initial physical examination . Many patients reported mild to moderate flu-like symptoms ( 42 . 1% ) , and all had dermal and mucosal findings which were in accord with previously described dermatologic manifestations of SS [32] , [33] ( Table 1 ) . The typical palmar and plantar exanthem of SS [13] , [15] , [19] , [32]–[34] was the most common dermal manifestation ( 59 . 6% ) . As seen in figure 2 , palmar and plantar lesions were often surrounded by hyperkeratosis and thin white rings or collar of scales; the latter has been classically known as Biett's collarette [34] . In agreement with Chapel's [32] and Mindel's classic descriptions of SS [32] , [33] , most subjects also had faint macular and papular eruptions , which were diffusely disseminated over the trunk and upper and lower extremities ( Figure 3A–B ) . In many cases , the dermal lesions were hyperpigmented ( Figure 3G ) , a finding which , not surprisingly , was more evident in darker skinned individuals . Condyloma lata , which are known to be highly infectious [1] , [13] , [14] , were present in 15% of patients ( Figure 3C and D ) . In one subject , several very large frambesiform , pustular lesions , a rare manifestation of the disease [34] , were plainly evident over the naso-labial folds and lower jaw ( not shown ) . Three patients had the characteristic patchy “moth-eaten-like” alopecia ( Figure 3E ) , which resolved after penicillin treatment . Mucosal patches in genital areas and/or the oral mucosa , also commonly seen in this stage of the disease , were observed in 14% of patients ( Figure 3F ) . Although early dissemination to the central nervous system ( CNS ) is known to occur in up to 40% of SS patients [1] , [35] , [36] , none of the participants had overt clinical manifestations associated with meningitis or encephalitis ( i . e . meningismus , cranial nerve disorders , visual changes or intense headache ) . The majority of patients ( 94 . 7% ) had RPR titers ≥than 1∶16 and over a third ( 36 . 8% ) had titers ≥1∶128 . RPR titers at follow-up decreased at least four-fold in all patients followed at 40–60 days . Hematologic anomalies , indicative of the systemic inflammatory nature of this stage of the disease , were the norm in most patients studied . Indeed , more than half of all patients had an elevated erythrocyte sedimentation rate ( ESR ) ( 63 . 2% ) , 30% were anemic and several were lymphopenic ( 43 . 9% ) . It is possible , although unlikely , that the hematologic changes described herein are a reflection of other conditions which might be present in underserved individuals from Cali . Table 2 summarizes the various histopathologic anomalies that were seen in lesional punch biopsies obtained from 11 of the 57 SS patients enrolled . In concert with prior histologic descriptions of SS [14] , [34] , [35] , [37]–[40] , skin biopsies revealed superficial and deep dermal cellular infiltrates of varying intensity , often in a perivascular distribution and primarily comprised of lymphocytes and plasma cells . Several other histologic patterns involving the epidermis were also seen . These included areas of focal spongiosis , basal vacuolar changes , parakeratosis , and epidermal acanthosis . Figure 4 depicts representative histopathologic abnormalities from four SS patients . In concert with the known low sensitivity of the Warthin-Starry stains to detect Tp in tissues [39] , [40] , spirochetes were only seen in one ( 9% ) of the 11 biopsies studied . We previously determined that WB was the best sample to detect spirochetes in blood obtained from infected rabbits [41] . In unpublished observations we confirmed that using spiked human blood , WB was better than serum , plasma or peripheral blood mononuclear cells ( PBMCs ) for detecting spirochetes . In this study , we therefore elected to use WB samples to quantitate the level of spirochetemia in untreated SS patients . Using a real-time qPCR assay targeting the polA gene , we first established the sensitivity of the assay to be between 15 and 150 spirochetes/ml , irrespective of whether freshly extracted Tp DNA or live whole spirochetes were used to spike the blood sample ( Table S1 ) . The polA PCR detection limit in blood samples that were immediately refrigerated upon spiking and kept at 4°C for a total of 26 hrs prior to DNA extraction , were one log higher than samples kept at room temperature for 1 hr and then processed . We then used this highly sensitive PCR method to amplify Tp DNA in 46% ( 11/26 ) of the WB samples obtained from SS patients ( Table 3 ) . The polA copy numbers in these patients ranged from 194 . 92 to 1954 . 2 copies/ml of WB , which is well above the cutoff for the assay . PCR inhibition was not observed in any of the DNA samples that tested negative for the Tp polA target . It is important to note that the ability to detect Tp DNA in SS patients' samples greatly improved when WB DNA was extracted within a few hours of procurement of the sample . Indeed , 63% ( 7/11 ) of the samples handled in this fashion had detectable Tp DNA , whereas only 5/15 ( 30% ) WB samples were positive when WB was collected , frozen and shipped to UCHC for subsequent DNA extraction at the CDC . These findings highlight the importance of timely specimen processing and handling , and show how subtle differences in technique can greatly alter the ability to amplify Tp DNA . Tp DNA was also detected by qualitative real-time PCR in 8/12 ( 66% ) skin biopsies studied ( Table 4 ) . Three of the four skin biopsies that did not have detectable Tp DNA by RT-PCR were obtained from hyperkeratotic plantar plaques . Five of the 8 patients had Tp DNA present in both the blood and the skin , one patient with spirochetemia had a negative PCR in the skin; and two patients with detectable DNA in punch biopsy material had negative PCR results in WB . None of the WB samples analyzed had sufficient quantity of Tp DNA to satisfactorily perform molecular strain typing . On the other hand , six of the eight positive skin samples were amenable for typing . By combining the 60-bp arp repeat sizes and the tpr E , G , and J RFLP patterns , we identified four different strain types; two each were 14d and 16d , and one each was 13d and 22a , respectively . The remaining strain was partially typeable by tpr RFLP analysis ( pattern a ) . Although it is not possible to generalize our results due to the small sample size , our data suggests high strain diversity , which reflects the pattern seen in South Africa [27] , where syphilis is known to be highly endemic .
The WHO estimates that up to a quarter of all yearly cases of infectious syphilis occur in Latin America and the Caribbean [3] . Because syphilis is not rigorously notified , and often not recognized by health care providers in the region , country-specific disease prevalence and incidence rates most likely underestimate the true magnitude of the problem . Existing published studies do provide evidence that venereal syphilis is not only highly endemic but also a very important sexually transmitted disease in tropical regions of the Americas [42]–[57] . For instance , syphilis has been shown to be a leading cause of genital ulcerative disease in both Peru and the Dominican Republic [56] , second only to genital herpes . Likewise , in another study from Peru , the prevalence of venereal syphilis was estimated to be 10 . 5% amongst MSM and 2 . 0% in socially marginalized men and women [42] . In a Brazilian study , high syphilis prevalence rates were the norm in prisoners , commercial sex workers , and MSM [47] . High syphilis prevalence rates have also been documented for MSM ( 5% and 13% ) and female sex workers ( 6 . 8% and 15 . 3% ) in Honduras and Guatemala respectively ( Source: PAHO web site http://new . paho . org accessed July , 2009 ) . In one of the few available studies describing the epidemiology of venereal syphilis in Colombia , 10% of female sex workers in Bogota had serologic and clinical evidence of the disease [51] . Although the current study was not designed to be a comprehensive epidemiologic or microbiologic investigation of syphilis in Cali , our combined observations do provide further evidence that venereal syphilis is highly endemic in this region of Colombia . This assertion was further substantiated by the very high syphilis seroprevalence rates documented in 15–24 year old sexually active men and women from poor Cali districts [7] . Our findings also make evident that early syphilis patients in Cali may go undiagnosed and untreated for several weeks , in some cases for several months . This is not at all surprising given that the clinical manifestations of SS are often subtle and can be easily overlooked and/or dismissed by primary care providers and patients alike . A principal objective of the current case series is thus , to review for health care providers , particularly those who practice medicine in tropical regions like Colombia , the typical clinical manifestations associated with SS . Although a large proportion of patients presented with the classic palmo-plantar exanthem of SS [19] , [32] , [34] , some had faint hypo or hyper-pigmented macules and papules that could have easily been dismissed for other dermatologic conditions . Indeed , the rash of SS may be frequently confused for other skin disorders including pityriasis rosea , psoriasis , seborrheic dermatitis and dermato-mycosis , amongst others [13] . Given the relative high prevalence of venereal syphilis in this population , it is not unreasonable to suggest that a diagnosis of SS should be considered in all sexually active individuals who present with any form of unexplained skin and mucous membrane pathology , and perhaps even in individuals with otherwise unexplained constitutional flu-like symptoms . Several other investigators have previously used molecular methods to detect Tp DNA in WB and tissues from untreated early syphilis patients [58]–[65] . Our study is the first to measure spirochetal loads by real time qPCR in the blood of untreated SS patients . The ability to detect spirochetal DNA in these samples has been quite variable and highly dependent on various factors including; the type of sample collected , the stage of the disease ( primary vs . secondary vs . latent ) , and the gene target used . Nevertheless , it is readily apparent that a significant proportion of early syphilis patients , regardless of the stage of the disease , have circulating spirochetal DNA . In the current study , the detection limit in blood samples that were spiked with either DNA or whole Tp organisms and kept at 4°C for 26 hrs was 15 polA copies/ml blood compared to 150 polA copies/ml in the same dilutions stored at room temperature for 1 hr . While frozen blood samples , stored over several days , may not be conducive to diagnostic PCR testing , our spiking experiments do indicate that blood samples can be stored up to 26 hours at 4°C without significantly affecting the capacity to detect Tp DNA . This may prove to be particularly useful in settings where blood samples cannot be processed on the day of collection . No PCR inhibition was observed with the use of 2ml blood for spiking experiments , despite the inherent high concentration of human DNA in these samples . It is possible that several other SS patients enrolled , if not all , were spirochetemic but not detected by qPCR . This may have been due to some patients having spirochetemia which was below the threshold of the assay or alternatively , treponemal DNA might have been degraded as a result of not being extracted within 24 hours of blood collection . For future studies the ability to detect low copy numbers may be enhanced by extracting DNA on site and using a larger volume of blood ( 2ml vs . 400µl ) . In this study we also performed Tp strain type analysis in DNA material obtained from the skin of several SS patients . Using the method described by Pillay [27] , [66] , [67] we provide evidence that in the city of Cali there is considerable heterogeneity in circulating Tp strains . Subtype 14d , which is known to have a worldwide distribution [27] , [62] , [68] , was present in the skin of two SS patients . Subtypes 13d and 16d , which were previously identified in syphilis patients in several cities in South Africa [27] , were also present in skin samples in Cali . Strain type diversity in Cali , provides additional evidence that venereal syphilis is highly endemic in this population . In a much larger molecular epidemiology study conducted in several South African cities [27] , greater geographic Tp strain diversity was found to correlate statistically with higher syphilis prevalence rates . It is our contention that an improved understanding of the heterogeneity of syphilis subtypes , not only helps to identify the introduction of new strains into an endemic population but also helps to evaluate if public health strategies have been successful at eradicated indigenous strains . As already alluded to above , the molecular methods used herein provide evidence that significant numbers of spirochetes are not only present in the skin , but are also capable of spreading in significant numbers through the blood stream of untreated SS patients . Paradoxically , SS patients exhibit robust cellular and humoral adaptive immune responses [10] , [17] , [69] , [70] . A careful analysis of Tp's unique ultrastructural features provides several explanations for this paradox . Unlike the outer membrane of gram-negative bacteria , that of Tp lacks the potent proinflammatory glycolipid lipopolysaccharide ( LPS ) [71] , [72] . In addition , freeze-fracture microscopy studies have shown that the spirochete is largely devoid of integral outer-membrane proteins [73] , [74] . Although Tp does contain an abundance of highly antigenic hydrophilic polypeptides , these molecules are tethered by covalently bound N-terminal lipids to the periplasmic leaflet of the cytoplasmic membrane [74] , [75] . This unusual topology is thought to contribute to the ability of intact spirochetes to avoid recognition by innate immune cell ( i . e . macrophages ) pattern recognition receptors ( PRR ) ; thus delaying or impeding their activation at the sites of initial inoculation or in skin or organs to where spirochetes have disseminated . Inefficient antibody binding to the small number of potential antigenic targets present on the spirochete's outer membrane could also allow the spirochete to shun rapid and efficient binding by opsonizing anti-treponemal antibodies and thus avoid phagocytosis . One can envision a model were the paucity of outer membrane antigenic targets , perhaps in combination with the very slow rate of bacterial replication , facilitates intermittent low level spread of the spirochete from affected skin and mucous lesions into the blood stream of untreated SS patients . Lastly , sequence variation of the Tp repeat ( Tpr ) family of polymorphic multi-copy repeat proteins has been postulated as an additional mechanism of immune evasion and persistent infection by the spirochete [17] , [76]–[78] . Of the several proteins with predicted outer membrane location , TprK has received the most attention . Although controversy remains as to the actual location of TprK [79] , sequence diversity of tprK in samples obtained from several syphilis patients [76] has bolstered the idea that this molecule could play an important role in immune evasion . Several other candidate outer membrane proteins , including Tp92 [80] , are currently being studied to determine if they meet the structural features of other known bacterial outer membrane proteins , if they bind syphilitic opsonic antibodies , and if they too can undergo antigenic variation . We conclude that high syphilis prevalence rates in the region should prompt health care workers in countries like Colombia to maintain a high index of suspicion for the common and uncommon manifestations of early syphilis . In concert with the clinical findings highlighted herein , a diagnosis of SS must be considered as part of the differential diagnosis in any subject who presents with chronic skin and/or mucosal lesions . Public health care authorities must redouble their efforts to enhance early detection of venereal syphilis , to institute timely treatment of the disease and to improve follow-up of patients diagnosed with the disease . Lastly , research efforts designed to better understand the immunopathogenesis of the disease , in particular how the bacterium is able to elude host immunologic defenses and spread from sites of bacterial replication , as demonstrated herein , will greatly contribute to more effective and novel prevention strategies , including the development of an effective vaccine . | Venereal syphilis is a sexually transmitted disease caused by the bacterium Treponema pallidum ( Tp ) . We describe 57 patients ( age 18–68 years ) from Cali , Colombia diagnosed with secondary syphilis ( SS ) . Most were women ( 64 . 9% ) ; predominantly Afro-Colombian ( 38 . 6% ) or mestizo ( 56 . 1% ) , and all of low socio-economic status . Three ( 5 . 3% ) were newly diagnosed with HIV infection at study entry . The typical palmar and plantar rash of SS was the common clinical finding ( 63% ) . Whole blood ( WB ) samples and skin biopsies were assayed for Tp DNA by using molecular methods . 46% of the WB samples had circulating Tp DNA and 64% were positive when the DNA was extracted on the same day of collection . Tp DNA was also present in the skin of 66% ( 12/26 ) of biopsies tested by PCR . We conclude that primary care providers in countries like Colombia need to remain highly vigilant for the clinical presentation of SS . The study also provides , for the first time , qualitative and quantitative evidence that untreated SS patients have significant numbers of spirochetes in blood and skin , and that this occurs despite the known presence of circulating anti-treponemal antibodies and strong cellular immune responses associated with this stage of the disease . | [
"Abstract",
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"Materials",
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] | [
"infectious",
"diseases/sexually",
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] | 2010 | Secondary Syphilis in Cali, Colombia: New Concepts in Disease Pathogenesis |
Small interfering RNAs regulate gene expression in diverse biological processes , including heterochromatin formation and DNA elimination , developmental regulation , and cell differentiation . In the single-celled eukaryote Entamoeba histolytica , we have identified a population of small RNAs of 27 nt size that ( i ) have 5′-polyphosphate termini , ( ii ) map antisense to genes , and ( iii ) associate with an E . histolytica Piwi-related protein . Whole genome microarray expression analysis revealed that essentially all genes to which antisense small RNAs map were not expressed under trophozoite conditions , the parasite stage from which the small RNAs were cloned . However , a number of these genes were expressed in other E . histolytica strains with an inverse correlation between small RNA and gene expression level , suggesting that these small RNAs mediate silencing of the cognate gene . Overall , our results demonstrate that E . histolytica has an abundant 27 nt small RNA population , with features similar to secondary siRNAs from C . elegans , and which appear to regulate gene expression . These data indicate that a silencing pathway mediated by 5′-polyphosphate siRNAs extends to single-celled eukaryotic organisms .
Small RNAs mediate post-transcriptional gene silencing in a multitude of organisms and in diverse biological processes [1] , [2] , [3] , [4] , [5] . Two proteins central to the small RNA mediated gene silencing pathways are Dicer , an RNaseIII enzyme , which generates small RNAs and Argonaute , which associates with the small RNAs and target genes to mediate gene silencing . Multiple classes of small RNAs have recently been described including small interfering RNAs ( siRNAs ) , microRNAs ( miRNAs ) , trans-acting siRNAs ( tasiRNAs ) , tiny noncoding RNAs ( tncRNAs ) , small scan RNA ( scRNA ) , repeat-associated small interfering RNA ( rasiRNA ) , piwi-interacting RNA ( piRNA ) , and secondary siRNAs [6] , [7] , [8] , [9] . Some organisms have multiple populations of small RNAs associated with different mechanisms of gene regulation . Notably siRNAs , miRNAs , tasiRNAs , tncRNA , and scnRNA are all products of Dicer cleavage . In contrast , rasiRNA , piRNA , and secondary siRNA appear to be formed independent of Dicer processing [6] , [7] , [8] , [10] . Primary siRNAs are produced from long double stranded RNAs and can be endogenously derived from repetitive genomic regions , transposon elements , or regions with active antisense transcripts . Primary siRNAs are generated by Dicer processing , which generates a 5′-monophosphate ( 5′-monoP ) and 3′-hydroxyl ( 3′-OH ) structure . Primary siRNAs are subsequently loaded into Argonaute to mediate gene silencing but can also serve as the “trigger” to initiate RNA-dependent RNA polymerase ( RdRP ) generation of secondary siRNAs . In plants , secondary siRNAs , although generated by RdRP , are eventually processed by Dicer and thus the majority have the classic 5′-monoP termini [9] . In C . elegans , secondary siRNAs have a 5′-polyphosphate ( 5′-polyP ) structure , a feature not identified in any other siRNAs to date . C . elegans secondary siRNAs largely map antisense to genes , are biased towards the 5′ side of primary trigger RNAs , and amplify gene silencing by their association with CSR-1 , an Argonaute protein [7] , [8] , [10] , [11] , [12] . Because of their 5′-polyP structure , C . elegans secondary siRNAs are most efficiently cloned in a 5′-phosphate independent manner [7] , [8] . Entamoeba histolytica , a single celled eukaryote , is an important human pathogen and a leading parasitic cause of death worldwide [13] . The parasite has two stages in its life cycle: an invasive trophozoite form , which causes disease and a dormant cyst form , which transmits disease [14] . The genome of E . histolytica is predicted to encode a number of genes conserved in the RNAi pathway including three genes with Piwi and PAZ domains ( EHI_186850 , EHI_125650 , and EHI_177170 ) , and two genes with RdRP domains ( EHI_139420 and EHI_179800 ) [15] . However , no obvious homologue of Dicer was identified , although RNaseIII activity was detected in E . histolytica trophozoites and a protein with an RNaseIII domain ( EHI_068740 ) has been identified in the genome sequence [15] , [16] . Recently it has been shown that dsRNA , siRNA , and short-hairpin RNAs are effective in achieving gene silencing in E . histolytica suggesting that the machinery for small RNA mediated silencing is functional in this parasite [17] , [18] , [19] . Additionally , putative microRNAs were identified in E . histolytica using a bioinformatics-based approach , however , none of those predictions were confirmed using high resolution Northern blot analysis [20] . Thus , although there are hints that a functional RNAi pathway exits in E . histolytica , endogenous small RNAs have not previously been identified in this eukaryotic pathogen . In order to identify endogenous small RNAs in E . histolytica , we used a 5′-phosphate independent cloning method to clone small RNAs from E . histolytica trophozoites . Our analysis identified an abundant population of small RNAs ( ∼27nt ) with features highly reminiscent of secondary siRNAs from C . elegans . E . histolytica 27 nt small RNAs have 5′-polyphosphate termini , largely map antisense to genes with bias towards the 5′ ends of genes , are associated with a Piwi-related protein , and appear to regulate strain-specific gene expression . Thus , Entamoeba histolytica , an organism typically considered a simple eukaryote , appears to use complex regulatory mechanisms to mediate gene silencing . Even though there are some important differences between these small RNAs in E . histolytica and C . elegans ( including the size of the 5′-polyP small RNAs ) , our data indicate that the secondary siRNA mechanism of gene silencing extends deep into the evolutionary spectrum .
In order to visualize small RNAs in E . histolytica trophozoites , we fractionated total RNA with a YM100 column and visualized the samples on 12% denaturing polyacrylamide gel stained with SYBR gold . Three distinct populations of small RNAs were visualized: ∼27 nt , ∼22 nt , and ∼16 nt with the 27 nt population the most abundant ( Figure 1A ) . A similar pattern was seen in trophozoites of the non-invasive human parasite Entamoeba dispar ( ED ) , and the reptilian parasite Entamoeba invadens ( EI ) ( Figure S1 ) . Thus , it appears that the overall pattern of three distinct small RNA populations is conserved in Entamoeba species . Since the 27 nt small RNA population was the most abundant we subsequently focused our efforts on this population . We first attempted to define the features of the 5′ and 3′ termini of this small RNA population . We identified that the E . histolytica 27 nt fraction is likely to have a 3′-OH , as it can be efficiently labeled using RNA ligase and cytidine 3′ , 5′-bisphosphate [5′-32P] ( abbreviated 32pCp hereafter ) ( Figure 1B ) . By contrast , the 5′ end is not likely to be a 5′-monoP , as it could not be efficiently labeled using polynucleotide kinase ( PNK ) , unless first treated with calf intestinal phosphatase ( CIP ) ( Figure 1B ) . To further confirm that the 5′ termini was not a 5′-monoP , we took advantage of the specificity of Terminator exonuclease for 5′-monoP RNA species: 5′-monoP RNAs are efficiently degraded by treatment with Terminator ( a 5′-3′ exonuclease ) , whereas RNAs with a 5′-cap , 5′-polyP , or 5′-OH will be resistant . A substantial portion of the 27 nt small RNA population was resistant to treatment with Terminator enzyme , whereas the control ( PNK labeled RNA ladder with 5′-monoP termini ) was largely degraded by Terminator treatment ( Figure 1C ) . Finally , treatment of the 27 nt fraction with a capping enzyme ( which only caps RNAs with 5′ termini containing di- or tri-phosphate structures ) increases the signal and the size of the 27 nt fraction ( Figure 1D ) . Collectively , these data indicate that a substantial portion of the E . histolytica trophozoite 27 nt small RNAs have 5′-polyP termini . Some of the 27 nt population may be 5′-monoP species , as some RNA was labeled with PNK and there was a slight reduction in RNA abundance after treatment with Terminator enzyme . The standard method for small RNA cloning depends on the presence of a 5′-monoP on the small RNA of interest [10] . However , this 5′-phosphate dependent method of cloning will not efficiently capture small RNAs with a 5′-polyP structure . In order to clone 27 nt small RNAs with 5′-polyP termini from E . histolytica trophozoites , we utilized a 5′-phosphate independent method of cloning and performed limited sequencing [8] . A total of 289 small RNA sequences were obtained , 243 of which were unique , and 196 of which mapped to the E . histolytica genome sequence ( Table S1 and Figure S2 ) . Overall , 27% of small RNAs mapped to ribosomal RNAs , 27% mapped to tRNAs , 20% mapped antisense to ORFs , 13% mapped to intergenic regions , 5% mapped to multiple genomic loci , 3% mapped sense to ORFs , 5% mapped to repetitive regions , and 0 . 5% mapped to retrotransposon elements . The size distribution of the cloned small RNAs peaked at 27–28 nt , matching the size of the population from which they were cloned ( Figure 2A ) . We also cloned small RNAs from a 15–30 nt size selected fraction from E . histolytica trophozoites using a 5′-phosphate dependent method; 802 small RNA sequences were obtained , 544 of which were unique , and 342 of which mapped to the E . histolytica genome sequence ( Table S1 and Figure S2 ) . The majority of the cloned RNAs were smaller in size with a peak size at ∼16 nt . However , high resolution Northern blot analysis demonstrated that small RNAs cloned in a 5′-phosphate dependent manner all mapped at ∼27–32 nt , regardless of the size at which they were cloned , indicating that we had cloned partial degradation products of the 27 nt small RNAs ( Figure S3 ) . In contrast , small RNAs cloned by the 5′-phosphate independent manner were detected by Northern blot analysis at sizes matching the sizes of the cloned products ( Figure 2B ) . This confirms that the full length E . histolytica 27 nt small RNAs with 5′-polyP termini are not efficiently cloned using a 5′-phosphate dependent approach , while full length small RNAs can be cloned using a 5′-phosphate independent method . To confirm that we had not cloned degradation fragments of larger transcripts , we used Northern blot analysis on total RNA using probes for a number of cloned small RNAs and did not detect any signal >200 nt ( data not shown ) . Thus , the majority of small RNAs that map antisense to genes do not appear to be degradation products of larger antisense transcripts . In order to confirm the 5′ and 3′ structure of the cloned 27 nt small RNAs , we tested individual small RNAs that had been identified in our library using biochemical approaches . The E . histolytica 27 nt cloned small RNAs are likely to have a free 3′-OH , as they are susceptible to loss of a single base and generation of a smaller RNA species following a β-elimination reaction , as indicated by faster migration following denaturing PAGE ( Figure 3A ) . A 32P-PNK labeled synthetic RNA 18mer ( with a 3′-OH terminus ) also loses a base after a β-elimination reaction , as indicated by faster migration . In agreement with previous analyses of the whole 27 nt population , individual 27 nt small RNAs are initially resistant to Terminator treatment ( Figure 3B ) , but become sensitive to Terminator exonuclease activity after CIP treatment followed by addition of a 5′-monoP by PNK ( Figure 3C ) . The control synthetic 18mer RNA species , with a 5′-monoP is degraded by Terminator treatment ( Figure 3B ) . We tested three different 27 nt small RNAs and found the same end structures for all three ( some data not shown ) . These results confirmed that small RNAs cloned from the 27 nt population have a 5′-polyP and 3′-OH structure . Thus , the 27 nt small RNAs in E . histolytica are likely not Dicer products ( based on 5′-polyP termini ) . Instead , the structure of these RNAs matches that of secondary siRNAs in C . elegans , the only siRNA species identified to date with 5′-polyP termini , and which are known to be products of RdRP processing [7] , [8] . One major difference between the E . histolytica and C . elegans 5′-polyP small RNAs is the size of the populations: the E . histolytica population is ∼27 nt , whereas the C . elegans 5′-polyP small RNAs are ∼22 nt . The molecular mechanism that determines the sizes of these small RNAs in either system is not currently known . In order to determine if the 27 nt small RNAs are involved in a silencing complex , we tested to see if they associate with E . histolytica Piwi-related protein ( EhPiwi-rp ) ( EHI_125650 ) . Of the three genes in the E . histolytica genome that are predicted to contain PIWI domains , this is the only one that is highly expressed in trophozoites [21] . A construct with N-terminal Myc tagged EhPiwi-rp was generated and transgenic parasites selected . Western blot analysis demonstrated that anti-Myc antibody detected a protein of the appropriate molecular mass specifically in the Myc-EhPiwi-rp transgenic strains ( Figure 4A ) . Immunoprecipitation ( IP ) experiments with α-Myc antibody were performed and small RNAs of ∼27 nt were specifically observed in the α-Myc IP of the Myc-EhPiwi-rp parasite cell line ( Figure 4B ) . The 27 nt small RNA population was significantly enriched in the α-Myc EhPiwi-rp immunoprecipitated sample compared to the starting sample ( data not shown ) . No small RNAs immunoprecipitated with a number of controls including untransfected parasites or transgenic E . histolytica strains expressing one of a number of Myc-tagged proteins ( Green Fluorescent Protein , EhKinase , or EhRNaseIII ) ( Figure 4B ) . These data indicate that 27 nt small RNAs are in a complex specifically with EhPiwi-rp . In order to determine the 5′ and 3′ structure of the small RNAs that immunoprecipitated with Myc-EhPiwi-rp , we performed IP with α-Myc and used the biochemical approaches outlined earlier . In agreement with our analysis of the total 27 nt population , the small RNAs in the IP sample could be successfully labeled at the 3′ end using RNA ligase and 32pCp , consistent with a free 3′-OH . As before , the small RNAs in the IP sample were resistant to labeling at the 5′ end using PNK , unless first dephosphorylated ( CIP+PNK ) , and were able to be efficiently labeled by capping enzyme and 32pGTP ( Figure 4C ) . These data indicate , that as with the bulk of the 27 nt population , the majority of the 27 nt small RNAs that associate with EhPiwi-rp have 5′-polyP termini . In order to determine the composition of the small RNAs that IP with EhPiwi-rp , we generated a small RNA library from the EhPiwi-rp immunoprecipitated sample using a 5′P-independent method . A total of 309 small RNAs that mapped to the E . histolytica genome were cloned ( Table S1 and Figure S2 ) . As expected the amount of rRNA or tRNA contamination was minimal with only 6% of small RNAs mapping to these elements . A total of 36% of small RNAs mapped antisense to genes , 25% mapped to intergenic regions , 10% mapped as mixed hits , 18% mapped sense to genes , 5% mapped to repetitive regions , and 0 . 32% mapped to retrotransposons elements . The overall pattern , with the greatest percentage of small RNAs mapping antisense to ORFs , was the same as seen in the other E . histolytica small RNA libraries ( Figure S2 ) . There was also significant overlap in the genes targeted by the antisense small RNAs cloned from the non-IP and the IP libraries ( Figure 5 ) . Of the 83 genes with antisense small RNAs from the non-IP libraries , 36 genes also had antisense small RNAs cloned from the EhPiwi-rp IP library ( p-value = 1 . 7e−61 ) . Additionally , three small RNAs cloned from the IP library were highly similar ( identical except for a few nucleotides at the 5′ or 3′ end ) to small RNAs cloned from total RNA . Furthermore , one small RNA that was cloned from total RNA and that was previously shown to be detectable by Northern blot analysis ( small RNA EHS-ID-27-1-30 ) ( Figure 2B ) was also cloned from the EhPiwi-rp IP library ( EHS-IP-2-54 and EHS-IP-3-253 ) . In C . elegans 5′-polyP small RNAs are in complex with an Argonaute protein , CSR-1 or with the Piwi protein , NRDE-3 for gene silencing [11] , [22] . The E . histolytica Piwi-related protein has two conserved domains ( PAZ-piwi like and Piwi ) , and the Piwi domain appears to contain the conserved residues necessary for slicer activity [6] . Thus , the fact that E . histolytica 27 nt 5′-polyP small RNAs associate with EhPiwi-rp strongly suggests that these small RNAs could be part of a silencing complex in E . histolytica . In order to determine the genomic regions to which cloned small RNAs mapped , we performed BLAST analysis of the small RNA sequences to the E . histolytica genome sequence . No significant differences were identified in the overall characteristics of the genomic regions to which the small RNAs mapped , regardless of whether they were cloned in a 5′-phosphate dependent or 5′-phosphate independent manner ( Figure S2 ) . Of the 847 unique small RNAs that were cloned , 38% were identical to ribosomal and tRNA sequences , 25% mapped antisense to predicted open reading frames ( ORFs ) , 16% mapped to intergenic regions , 8% matched multiple genomic loci , 9% matched the sense strand of ORFs , 4% mapped to repetitive regions , and 0 . 5% mapped to retrotransposon elements . Sequences from ribosomal RNAs , tRNAs , and sense tags to highly expressed loci are often found in small RNA libraries . For these RNAs we have no means to distinguish between biological effects and degradation products; thus , they were not further considered in our analysis . The paucity of matches to retrotransposons , especially in light of the large number of retrotransposons in E . histolytica was in contrast to other parasitic systems such as G . intestinalis and T . brucei where the majority of small RNAs appear to be derived from retrotransposons [15] , [23] , [24] , [25] . Since secondary siRNAs in C . elegans are largely antisense to coding regions , we focused our analysis on E . histolytica small RNAs that map antisense to predicted genes ( Figure 6 and Table S2 ) . Small RNAs cloned from either the 5′-phosphate dependent or 5′-phosphate independent manner and that mapped antisense to predicted ORFs were analyzed . A total of 214 unique small RNAs mapped antisense to predicted genes and a substantial portion ( ∼55% ) mapped to the 5′ end of ORFs or very close upstream of the start codon , in the presumptive 5′-UTR ( Figure 6A and 6C ) . Upon closer inspection , we identified that for several genes multiple , non-overlapping , antisense small RNAs were identified . The limited sequence data does not allow us to address the issue of “phasing” previously noticed for secondary siRNAs in C . elegans , however , the multiple non-overlapping small RNAs identified for a given gene suggests that this may also occur in E . histolytica [7] , [8] . The small RNAs that map antisense to genes appear to be an abundant population since ∼4% of the small RNAs were cloned twice . An alternate explanation is that certain small RNAs were cloned multiple times due to biases with cloning or PCR amplification . We identified genomic regions in which clusters of genes all had antisense small RNAs mapping to them ( Figure 6A and 6C ) . Given the identification of genomic clustering without performing deep sequencing it would appear that this phenomenon is relatively common in E . histolytica . Genomic clusters of genes are coordinately regulated in response to stress and development in E . histolytica [21] . Whether the siRNA mechanism controls expression of adjacent genomic loci is not currently known . Of the 120 genes , which had small RNAs mapping antisense to them , 15% also had small RNAs , which mapped in the sense orientation ( p = 4 . 8e−19 ) ( Table S3 ) . In all cases , the sense and antisense small RNAs were not complementary , however , as of yet we cannot make generalizations about this phenomenon . In C . elegans secondary siRNAs , both sense and antisense tags were seen for genes undergoing amplified silencing [8] . In C . elegans , secondary siRNAs are generated by RdRP processing of mature RNA transcripts; thus , secondary siRNAs that span exon-exon junctions have been identified [7] , [8] . In our work , no antisense small RNAs were identified at exon-exon junctions , but our limited sequencing makes this negative result difficult to interpret . We did identify small RNAs that mapped to intergenic regions in a genomic locus that had antisense small RNAs to adjacent genes . Since the E . histolytica genome is very compact ( ∼9 , 900 predicted genes in a 24 Mb genome ) , one possibility is that the small RNAs that map to intergenic regions represent extension of amplified silencing that occurs downstream of a trigger , a phenomenon noted in C . elegans [7] , [8] , [15] . Alternatively , the intergenic small RNAs could map to unannotated genes . Forty eight unique small RNAs mapped to multiple genomic regions , including antisense to predicted ORFs ( Figure 6A ) . Small RNAs that mapped to multiple genomic loci are likely those that map to closely related gene families or repetitive regions . The overall features of these small RNAs: mapping to the 5′ ends of genes and association with low gene expression of the cognate gene ( see below ) were similar to the small RNAs that exclusively map antisense to genes . The cumulative data on the E . histolytica 27 nt small RNAs ( 5′ polyphosphate termini , antisense orientation , and bias towards 5′ ends of genes ) makes them sufficiently similar to secondary siRNAs involved in amplification of silencing in C . elegans [7] , [8] so that we will subsequently refer to this fraction of small RNAs as siRNAs . In order to determine if the 27 nt 5′-polyP small RNAs that map antisense to genes have any effect on gene expression of the ORF to which they map , data from whole genome expression profiling were analyzed . A custom short oligonucleotide microarray ( Affymetrix ) has probes for 9 , 435 amebic genes and was previously used to generate expression profiles of E . histolytica trophozoites from three strains ( HM-1:IMSS , 200:NIH , and Rahman ) [21] . The data demonstrate that the genes to which antisense small RNAs map had extremely low expression values in E . histolytica HM-1:IMSS trophozoites , the strain and stage of the parasite from which they were cloned ( Figure 6B and Table S3 ) . The median normalized expression value for all genes on the array was 0 . 65±0 . 16 ( median±standard error ) . The expression of genes to which antisense small RNAs mapped was 0 . 04±0 . 09 ( median±standard error ) ( p<0 . 0001 compared to expression data for all genes on the array ) . The expression of genes that had small RNAs from the “mixed” category mapping antisense to them was 0 . 04±0 . 02 ( median±standard error ) ( p<0 . 0001 compared to expression data for all genes on the array ) . A total of 6 genes to which antisense small RNAs map were expressed , but 4 of these were represented by probe sets that completely cross-hybridize with other genes ( as indicated by a probe set identifier that ends with _s_at ) , making it difficult to address the expression of a specific gene . Considering that >80% of genes were expressed under trophozoite conditions [21] , the genes to which antisense small RNAs map have significantly disproportionately low expression profiles . A subset of genes have both antisense small RNAs and sense small RNAs that mapped to them . In these instances , the location of the sense small RNAs was biased towards the middle and 3′-end of the gene , in contrast to the 5′ bias of the antisense small RNAs ( data not shown ) . In instances of C . elegans amplified silencing , sense small RNAs were also identified [8] . Consistent with that data , genes that have antisense and sense small RNAs have low gene expression level ( Table S3 ) . We analyzed the expression profiles of genes to which antisense small RNAs map from trophozoites of other strains including E . histolytica 200:NIH and E . histolytica Rahman [21] . The data demonstrate that some genes to which antisense small RNAs map are expressed in trophozoites of other E . histolytica strains ( Table S3 ) . Of the 101 genes with antisense small RNAs , 73 were not expressed in any of the three E . histolytica strains , 11 were expressed in one strain , 11 were expressed in two strains , and 6 were expressed in all strains ( 4 of these were represented by cross-hybridizing probes ) . In order to determine if there was a correlation between the presence of a small RNA and the corresponding expression level of its putative target gene ( the ORF to which it maps ) , we performed Northern blot analysis of small RNAs where the associated gene had variable expression between amebic strains . We identified that for a given gene , small RNAs were detectable in E . histolytica strains with low gene expression but were not detectable in E . histolytica strains with high gene expression ( Figure 7 ) . The expression data for these genes were confirmed using semi-quantitative reverse transcriptase polymerase chain reaction ( RT-PCR ) and in all cases the results matched the array data . We noted that some small RNAs mapped at sizes larger than 30 nt . Further analysis of E . histolytica trophozoite small RNAs of >30 nt indicates that some ∼32 nt small RNAs have 5′-polyP structure ( Figure S3 and data not shown ) . In selected cases , we sequenced the relevant genomic region in E . histolytica 200:NIH or E . histolytica Rahman strains and confirmed that the regions encompassing the small RNAs were identical among the three E . histolytica strains ( data not shown ) . Thus , the lack of detection of a small RNA in a given amebic strain was not due to genomic sequence divergence in this strain . The inverse correlation between the E . histolytica 27 nt 5′-polyP small RNAs and gene expression level and the association of these small RNAs with EhPiwi-rp strongly suggests parallel functions of amebic and C . elegans siRNAs in mediating target silencing .
The work presented herein suggests that the process of gene silencing , mediated by small RNAs with 5′-polyphosphate termini , is evolutionarily conserved in the single celled parasitic eukaryote Entamoeba histolytica . We have identified an abundant repertoire of ∼27 nt small RNAs in E . histolytica with features reminiscent of secondary siRNAs in C . elegans , including 5′-polyP termini and antisense orientation to genes . The 27 nt small RNAs are in association with EhPiwi-related protein and an inverse correlation between small RNA and gene expression was noted suggesting that these small RNAs could mediate gene silencing . This identification of small RNAs with 5′-polyP termini in E . histolytica indicates that this mechanism of gene regulation is functional in single celled eukaryotes . An increasing number of distinct small RNA species are being identified . The majority are processed by Dicer , an RNaseIII endonuclease , which generates 5′-monophosphate termini , a feature typical of siRNAs , miRNAs , tasiRNAs , tncRNA , and scnRNA [6] . However , recently small RNAs that could be generated independently of Dicer processing ( rasiRNA , piRNA , and secondary siRNA ) have been described [6] , [7] , [8] . To date , the only siRNA species proven to have 5′-polyphosphate termini are the siRNAs from C . elegans . These small RNAs are generated by RdRP amplification of an initial trigger siRNA [7] , [8] and preferentially associate with an Argonaute protein , CSR-1 , to mediate gene silencing via slicer activity [11] . Importantly , polyphosphate small RNAs are more effective than primary monophosphate small RNAs in inducing slicer activity of CSR-1 and are thus more robust at cleaving target mRNA [11] . In E . histolytica 27 nt RNAs with 5′-polyphosphate termini associate with EhPiwi-related protein and appear to silence genes in a strain-specific manner . We observed that genes to which these antisense small RNAs map are not expressed under trophozoite conditions , in the strain and stage of the parasite from which the small RNAs were cloned . However , a number of these genes are expressed in other parasite strains . An inverse correlation between small RNA and gene expression , and the association of the 27 nt 5′-polyP small RNAs with a Piwi-related protein , strongly suggests that the 27 nt small RNAs mediate gene silencing in E . histolytica . Direct proof of the roles of small RNAs in regulating amebic gene expression has been hampered due to significant issues with genetic manipulation of E . histolytica strains ( unpublished data , H . Zhang , GM Ehrenkaufer , and U . Singh ) . One difference between E . histolytica and C . elegans secondary siRNAs is their size: the C . elegans secondary siRNAs are ∼22 nt , whereas the E . histolytica counterparts are ∼27 nt . What determines the sizes of the secondary small RNAs in either species is not known; whether the size reflects an inherent feature of the RdRP or whether other endonucleases cleave secondary siRNAs needs further investigation . In E . histolytica , the siRNAs are a highly abundant endogenous population and were readily identified by limited sequencing . The molecular mechanisms that generate these abundant small RNAs is not known but some architectural features of the E . histolytica genome , including small intergenic regions and an AT rich genome with cryptic TATA-like promoter elements potentially mediating bi-directional transcription , may be contributing factors . One possibility is that in E . histolytica abundant secondary siRNAs are needed to deal with aberrant transcripts , which occur due to specific features of the ameba genome as outlined above . Our preliminary analysis of the E . histolytica trophozoite 22 nt and 16 nt small RNA populations indicates that they likely do not have a 5′-polyP termini , however further investigations will be needed to more clearly define the features of these small RNA populations ( unpublished data , H . Zhang and U . Singh ) . Thus far , we have not identified a small RNA species consistent with the trigger siRNAs in C . elegans ( with a 5′-monoP ) likely due to the rarity of these species and our lack of deep sequencing [7] , [8] . Elucidation of the mechanism by which the 5′ polyP small RNAs are produced should shed some light on the nature and/or existence of such a trigger siRNA in E . histolytica . Based on functional similarity , we presume that similar trigger siRNAs exist in E . histolytica , however , whether other small RNAs or other structures function as triggers for the secondary siRNAs in E . histolytica is not currently known . In summary , Entamoeba histolytica , a protozoan parasite , is the first single celled eukaryote in which gene silencing via siRNAs with 5′-polyphosphate termini has been described . Based on analogies with the amplified silencing pathway as described in C . elegans , our data suggest that this silencing pathway is broadly evolutionarily conserved .
Entamoeba histolytica trophozoites ( HM-1:IMSS , 200:NIH , and Rahman strains ) , E . dispar SAW760 and E . invadens IP-1 were grown under standard conditions as previously published [21] , [23] , [26] . Amebae were harvested in mid log phase and small RNA extracted using a mirVana kit ( Ambion ) . N-terminal Myc tagged constructs for EhPiwi-rp , EhRNaseIII , EhRdRP , and GFP were generated . Briefly , full-length coding regions were PCR amplified and cloned into a vector to express a N-terminal Myc tag [27] . E . histolytica HM-1:IMSS parasites were transfected using previously published protocols , stable transfectants selected with 12–24 µg/ml G418 , and western blot analysis performed using standard protocols [23] , [28] . Anti-Myc antibody ( Cell Signaling ) was used at 1∶1000 dilution; Anti-Lgl antibody ( kind gift of William Petri ) was used at 1∶50 dilution . In order to visualize small RNAs in E . histolytica trophozoites , we fractionated 100 µg of total RNA with a YM100 column , resolved the sample on a 12% denaturing polyacrylamide gel , and stained the gel with SYBR gold . Small RNA cloning was based on two published protocols [8] , [10] . For the 5′-P independent method , 100 µg of small RNA enriched sample was resolved on a denaturing 12% polyacrylamide gel , the 27 nt RNA fraction gel extracted , ligated to a 3′ adapter oligonucleotide ( 5′ rAppCTGTAGGCACCATCAAT/3ddC/ 3′ ) ( 3′-terminal dideoxy-C ( ddC ) base ) ( RT , 4 hours ) and the product gel purified . The material was subjected to RT ( Superscript II , 42°C , 30 min ) , treated with Exonuclease-I ( 37°C , 1 hour ) , a second 3′ ligation performed ( 5′ rAppCACTCGGGCACCAAGGA/3ddC/-3′ ) ( RT , 4 hours ) , and the product gel purified . The material was PCR amplified using the adaptor primers , the final PCR products concatamerized and cloned into the pCR2 . 1-TOPO vector ( Invitrogen ) vector for sequencing . For the 5′-phosphate dependent method , 150 µg of small RNA enriched material was fractionated on a denaturing 12% polyacrylamide gel , RNA from 15–30 nt purified , and ligated to the 3′ adapter oligonucleotide ( 5′-rAppCTGTAGGCACCATCAAT/3ddC/-3′ , 3ddc = 3′-terminal dideoxy-C base ) and the 5′ adapter oligonucleotide ( 5′-TCGTAGGCACCTGaaa-3′; uppercase = DNA , lowercase = RNA ) . After reverse transcription , two rounds of PCR ( 32 cycles total ) were performed , the PCR products concatamerized , cloned and sequenced as outlined above . The library generated from the EhPiwi-rp immunoprecipitated sample was made in a 5′-independent manner ( personal communication , Sam Gu and Andy Fire ) . Briefly , RNA was extracted from immunoprecipitation , directly ligated to the 3′ adapter oligonucleotide , purified , treated with CIP and PNK , and ligated to the 5′ adapter oligonucleotide . Subsequent steps were as for the 5′-P dependent cloning method as outlined above . The small RNA sequences were extracted and BLASTed against the E . histolytica HM-1:IMSS genome sequence ( http://www . tigr . org/tdb/e2k1/eha1/ ) ( http://pathema . jcvi . org/cgi-bin/Entamoeba/PathemaHomePage . cgi ) using search settings for short and nearly exact matches ( expect = 1 , 000 , Word size = 7 ) . Additionally , all E . histolytica sequences annotated as belonging to the SINE/LINE retrotransposons were downloaded and analyzed by BLAST analysis . Sequence tags with 100% match , 1 mismatch , or up to 2 mismatches ( 1 terminal and 1 internal mismatch ) to the E . histolytica genome sequence were analyzed further [29] . Antisense small RNAs are categorized as follows: map to the first 25% of a coding region ( map to the 5′ of a gene ) ; map to the last 25% of a coding region ( map to the 3′ of a gene ) ; and map to the middle 50% of a coding region ( map to the middle of a gene ) . Small RNAs were considered to have genomic clustering if ≥ 2 adjacent genes had antisense small RNAs . The untranslated region ( UTR ) of a gene was defined as the 50 bp region upstream or downstream of a predicted start or stop codon respectively . High resolution Northern blot analysis was done using standard protocols [30] . Briefly , 10 µg–100 µg of RNA was separated on a denaturing 12% polyacrylamide gel , transferred to a membrane , probed with end-labeled 32P-labeled oligonucleotides in perfectHyb buffer ( Sigma ) at 37°C and washed using low ( 2X SSC , 0 . 1% SDS at RT for 15 min ) and medium ( 1X SSC , 0 . 1% SDS at 37°C for 15 min ) stringency conditions . Standard Northern blot analysis was done using 10 µg of total RNA resolved on a denaturing 1 . 2 % agarose gel , probed with end-labeled 32P-labeled oligonucleotides in perfectHyb buffer ( Sigma ) at 37°C and washed using low stringency conditions according to manufacturer's instructions . Biochemical analysis of small RNAs were performed using standard methods [7] , [8] , [11] . Briefly , the structure of the 3′ termini was determined with an RNA ligation reaction using T4 RNA ligase ( NEB ) and α-32P pCp ( RT; 2 hours ) . Additionally , potential modifications at the 3′-OH termini were identified in a β-elimination reaction by treating 10 µg of small RNA with sodium periodate ( 25 mM , RT , 10 min ) , followed by heating to 45°C for 90 min . The 5′-termini were analyzed by CIP , PNK , Capping enzyme , and Terminator treatment [7] , [8] , [11] . Calf intestinal alkaline phosphatase ( NEB ) was used to treat RNA ( 37°C; 1 hour ) , followed by phenol/chloroform extraction . T4 Polynucleotide Kinase ( NEB ) was used to treat RNA ( 37°C; 1 hour ) . Capping was assessed with Guanylyltransferase ( Ambion ) , the vaccinia virus capping enzyme , which was used to add α-32P-GTP to RNA product ( 37°C; 1 hour ) . For Terminator susceptibility , the RNA sample was treated with Terminator enzyme ( 30°C; 1 hour ) . A control sample ( synthetic RNA 5′-end labeled with 32P and a 3′-OH terminus ) was added to the RNA material , the combined sample resolved on a 12% polyacrylamide gel , and probed with a radiolabeled probe to detect the small RNA of interest . For immunoprecipitation experiments , α-Myc antibody was incubated with parasite lysate ( 2 hours , 4°C ) washed x2 and pelleted . RNA was isolated ( mirVANA kit ) , labeled with PNK , 32P-pCp , and Capping enzyme as outlined above and resolved on a 12% denaturing polyacrylamide gel . A custom Affymetrix DNA microarray for E . histolytica with probe sets representing 9 , 435 ORFs has previously been used to determine the expression profile of E . histolytica trophozoites of HM-1:IMSS , 200:NIH , and Rahman strains [21] . For RT-PCR , total RNA was extracted from log phase E . histolytica parasites of the appropriate strain using a mirVana reagent kit ( Ambion ) . cDNA was made using SuperScript II Reverse Transcriptase kit ( Invitrogen ) , including a DNAse treatment before RT . PCR was performed with serial 10-fold dilutions of cDNA and a negative RT control was included with each reaction . Four genes , 152 . t00021 , 18 . t00040 , 77 . t00031 , and 73 . t00015 were analyzed by RT-PCR . Primers used are listed in Table S4 . The ssRNA gene was used as a loading control [21] . Statistical analyses were done using an unpaired Student's t-test ( comparison of expression data for genes with antisense small RNAs compared to all genes in the genome ) or a hypergeometric distribution in R downloaded from the BioConductor project ( http://www . bioconductor . org ) ( comparison of sense small RNA distribution ) . | Regulation of gene expression can occur via multiple conserved pathways . One such mechanism is mediated by RNA molecules of about 21–24 nucleotides ( called small RNAs ) , which can affect rates of RNA degradation or protein production . These small RNA molecules regulate diverse biological processes in a broad range of systems . The vast majority of the published literature about these molecules is from multi-cellular organisms . We have made a number of novel observations with respect to small RNA size , structure , and function in Entamoeba histolytica , a single-celled parasite and an important human pathogen . Our work has identified that E . histolytica has an abundant population of 27 nucleotide small RNAs , which have an unusual structure , indicating that they are generated by a relatively atypical mechanism . A substantial portion of these small RNAs are antisense to target genes and appear to silence them . These data establish a new paradigm for how gene expression is regulated in this organism . Furthermore , the identification of small RNAs with these structural characteristics dramatically broadens the evolutionary spectrum in which this phenomenon has been identified and indicates significant diversity and complexity of small RNAs and their functions in single-celled eukaryotes . | [
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"infectio... | 2008 | Small RNAs with 5′-Polyphosphate Termini Associate with a Piwi-Related Protein and Regulate Gene Expression in the Single-Celled Eukaryote Entamoeba histolytica |
Metazoan genomes encode hundreds of RNA-binding proteins ( RBPs ) . These proteins regulate post-transcriptional gene expression and have critical roles in numerous cellular processes including mRNA splicing , export , stability and translation . Despite their ubiquity and importance , the binding preferences for most RBPs are not well characterized . In vitro and in vivo studies , using affinity selection-based approaches , have successfully identified RNA sequence associated with specific RBPs; however , it is difficult to infer RBP sequence and structural preferences without specifically designed motif finding methods . In this study , we introduce a new motif-finding method , RNAcontext , designed to elucidate RBP-specific sequence and structural preferences with greater accuracy than existing approaches . We evaluated RNAcontext on recently published in vitro and in vivo RNA affinity selected data and demonstrate that RNAcontext identifies known binding preferences for several control proteins including HuR , PTB , and Vts1p and predicts new RNA structure preferences for SF2/ASF , RBM4 , FUSIP1 and SLM2 . The predicted preferences for SF2/ASF are consistent with its recently reported in vivo binding sites . RNAcontext is an accurate and efficient motif finding method ideally suited for using large-scale RNA-binding affinity datasets to determine the relative binding preferences of RBPs for a wide range of RNA sequences and structures .
RBPs act in the post-transcriptional regulation ( PTR ) of gene expression by binding to target RNAs to control splicing , stability , localization and translation . Recent draft networks of RBP-transcript physical interaction in yeast [1] , fruit flies [2] , and humans [3] reveal a complex and combinatorial pattern of RBP targeting and supports an RNA regulon model [4] in which cis-regulatory transcript sequence dictates the post-transcriptional fate of an mRNA at multiple , distinct stages of regulation . Deciphering this operon code as well as the role of individual RBPs in post-transcriptional regulation requires the detailed characterization of the binding preferences of RBPs . We have recently introduced the RNAcompete assay [5] , a microarray-based in vitro method to estimate the binding affinity of selected RBPs to a defined population of short RNA sequences . RNAcompete , along with in vivo methods such as RIP-seq [6] and CLIP-seq [7] , can be used to determine binding preferences of individual RBPs for a large number of RNA sequences . Motif representation generated from these data can be used to scan mRNA transcripts to identify potential RBP binding sites . However , this step can prove challenging because many RBPs show a preference for both specific sequences and secondary structure contexts in their binding sites [8]–[12] . Despite these structural preferences , motif finding algorithms that ignore RNA secondary structure work surprisingly well for some RBPs . This approach has been successful for both in vitro and in vivo binding data [1] , [2] , [5] , [13] , [14] . For example , structure-naive motif finding applied to mRNAs targeted by yeast proteins Puf3p and Puf4p recover sequence preferences confirmed by crystal structures of the RBP-RNA complexes [15] , [16]; and motif models for YB-1 , SF2 and PTB fit to in vitro binding data from the RNAcompete assay predict their in vivo targets with high accuracy [5] . However , this approach can give misleading results when an RBP has non-trivial structural preferences . For example , Vts1p is a yeast RBP that preferentially binds loop sequences within RNA hairpins [17] , however , this binding preference can be difficult to detect without consideration of this structural preference ( e . g . , [1] ) . RBP motif finding can made more reliable by training structure-naive algorithms only on RNA sequence likely to be in the preferred context [9] , [18] . For example , Foat and Stormo [18] could reliably extract the Vts1p sequence binding preferences from in vivo binding data by using only loop sequences ( from likely hairpin loops ) to train the MatrixREDUCE[19] motif finding algorithm . Similarly , the MEMERIS [9] algorithm adapts the MEME [20] motif finding algorithm to search for RNA motifs enriched in single-stranded regions by assessing a prior on each word according to its structural accessibility . MEMERIS predicts binding sites more accurately than MEME for a number of proteins , including the mammalian stem-loop binding RBP U1A . However , applying this strategy only allows a single , pre-defined structural preference to be queried . Ideally , an RBP motif finding method should consider multiple possible structural contexts simultaneously , and detect the relative preferences of a particular RBP for each . Covariance models ( CMs ) [21] are RNA motif models often used for modeling families of ncRNAs ( e . g . , [22] ) and have the capacity , in theory , to represent both the sequence and ( arbitrary ) structure preferences of RBPs . However , CMs have a reported tendency to overpredict secondary structure [23] . Indeed , recent CM-based motif models of Puf3p , Puf4p , and HuR [24] , [25] predict they preferentially bind RNA hairpins and contradict structural , in vitro and in vivo evidence [5] , [12] , [26] , [27] , that they bind unstructured ssRNA . We present a new strategy for modeling RBP binding sites that learns both the sequence and structure binding preferences of an RBPs . Our method assumes that the primary role of RNA secondary structure in RBP binding is to establish a structural context ( e . g . , loop or unstructured ) for the RNA sequence recognized by the RBP . As such , we annotate each nucleotide in terms of its secondary structure context ( e . g . , paired , in a hairpin loop or bulge ) . Cognizant of the fact that a given RNA sequence can have multiple , distinct stable secondary structures , this annotation takes the form of a distribution over all its possible contexts . These distributions are estimated using computational models of RNA folding . Our new model can be discriminatively trained ( as [19] , [28] , [29] ) thus facilitating its use with either binding affinity data or sets of bound sequences . We apply RNAcontext to several RNA-binding affinity datasets , demonstrating that it can infer the RBP structure and sequence-binding preferences with greater accuracy than other motif-finding methods . RNAcontext recovers previously reported sequence and structure binding preferences for well-charactered RBPs including Vts1p , HuR , and PTB and predicts new structure binding preferences for FUSIP1 , SF2/ASF , SLM2 , and RBM4 .
We use computational algorithms to predict RNA secondary structures though our algorithm can use experimentally determined RNA secondary structures when they are available . Instead of focusing on the single minimum free energy structure which is often not representative of the full ensemble of possible structures [30] , we consider the ensemble of secondary structures that the RNA can form . In the experiments reported here , we used SFOLD [30] to estimate the marginal distribution at each nucleotide over structural contexts ( e . g . paired , unpaired , hairpin loop ) for each position of the sequence by sampling a large number of structures for the sequence according to the Boltzmann distribution . We annotated each base in each structure using our context annotation alphabet ( described below ) and then we set the structural context distribution ( hereafter called the annotation profile ) to be the empirical annotation frequencies for that base across these samples . In all experiments described herein we used 1 , 000 samples . Our motif model can use any annotation alphabet . However , in this manuscript , we only use the alphabet P , L , U , M indicating that the nucleotide is paired ( P ) , in a hairpin loop ( L ) , or in an unstructured ( or external ) region ( U ) . The last annotation , M , stands for miscellaneous because we combine the remaining unpaired contexts ( i . e . , the nucleotide is in a bulge , internal loop or multiloop ) . This group of structural contexts are expressive enough to distinguish most known RBP structure preferences . Figure 1 shows an overview of our method . A set of sequences together with SFOLD predicted structure annotation profiles serve as input to the model . Each input RNA molecule is scored using the sequence and structure parameters . Formally , let represent the input set of sequences and let be a set of real-valued matrices that represent the annotation profiles of the corresponding sequences . We use A to represent the alphabet which is composed of the structure features and associate each annotation in A with one of the rows of . The columns of correspond to the positions in sequence and are discrete probability distributions over the annotations in the alphabet A . Let represent the model parameters where is the width of the binding site , is a position weight matrix ( PWM ) of sequence features with dimensions , is a vector of structure annotation parameters with one element for each letter in the alphabet . For instance if = then will consist of parameters ( , , , ) for the structure annotations , , and , respectively . Lastly , and stands for the bias terms in sequence affinity model and structural context model respectively . We use to assign a score , , to a sequence and its corresponding annotation profile . For an RBP with a binding site of width , following [31] , we define as the probability that at least one of its subsequences of length ( which we call -mers ) is bound by the RBP , that is: ( 1 ) where is an estimate of the probability that the -mer with base content and with structural context defined by the probability profile matrix is bound . Here , indicates the subsequence of between -th element and -th element , inclusive , and is a matrix whose columns are the annotation distributions for each of the bases between -th and -th position . We set to be the product between a term that depends only its base content , , and one that depends only upon its structural context , i . e . : ( 2 ) We interpret the term as an estimate of the probability that the RBP will bind in the ideal structural context . We use a standard biophysical model [28] , [31] , [32] to define ( please see Protocol S1 for more details on this model ) : ( 3 ) where is the well-known logistic function . The logistic function takes value at where it is an approximately linear function of , but it quickly saturates toward for negative and for positive . We also model the structural context term using a logistic function of the sum of the structure parameters weighted by corresponding profile values plus a bias term : ( 4 ) where represents the probability that the base at position of has structural annotation . In a preferred structural context , as represented by an annotation associated with large positive values of , the score for a -mer approximately equals and is thus determined by the base content . Whereas in a highly disfavored structural context , as represented by highly negative values of , and therefore the score regardless of because is bounded above by for all . So , the context term licenses binding in favored structured contexts . In the following section , we describe how to estimate the parameters of our motif model from binding data . However , in theory , our motif model has the flexibility to represent many different modes of RBP binding . For example , the binding preferences of RBPs , like HuR and Vts1p , that bind their preferred sequences within a specific structural context , unstructured ( U ) [33] and hairpin ( H ) [17] respectively , can be represented by setting to match their sequence binding preferences and to have negative elements except for the elements of that corresponds to their preferred structural context ( either or respectively ) . The binding preferences of RBPs , like U1A , that have multiple preferred contexts ( e . g . , hairpin loops [34] or unstructured ssRNA [35] ) can be captured by setting and to large positive values . RBPs , like Staufen , that bind dsRNA without obvious sequence preferences [36] , can be represented by setting the elements of to constant values , and setting to a large positive value . Similarly , RBPs without strong structure preferences can be represented by setting the elements of to zero and setting to a large positive value . Our model thus extends previous efforts that model RBP binding preferences [8] by associating each RBP with a single preferred structured context which is required for binding . In the next section , we describe how we can estimate the sequence and structure preferences of new RBPs by training our model using RBP binding or RBP binding affinity data for short RNA sequences . We learn by using our model to attempt to reproduce the observed affinity data given the associated sequences . In particular , we model the affinity of a sequence as a linear function of the sequence score with unknown slope and -intercept and search for settings of , , and that minimize the sum of the squared differences between the measured affinity and our predicted affinities . When we only know whether or not a given sequence is bound we use for all bound sequences and for sequences not bound . This formulation leads to the following least squares cost function , , that we attempt to minimize with respect to , , and using the L-BFGS method [37]: ( 5 ) Here , we have added a regularization term scaled by a small constant to avoid indeterminancy thus ensuring a unique global minimum . We use the same value of this constant in all experiments . We use the bound constraints feature of the L-BFGS-B package to constrain to take positive values so that the estimated affinity increases as a function of the sequence score . The cost function optimized by RNAcontext is multimodal , so different initializations can generate different results . For the experiments reported here , we used ten different initialization for each motif width . For motif lengths , , longer than the minimum length , two of these initial settings are generated by taking the optimal matrix learned for and adding a column of zeros to its left and right sides , respectively . The elements of matrix for the other initializations are randomly sampled uniformly between −0 . 05 and 0 . 05 . In all cases , the other parameters ( , , , , ) are randomly sampled uniformly between −0 . 05 and 0 . 05 .
We evaluated our motif model on RNAcompete-derived datasets [5] comprised of the measured binding preferences of nine RBPs ( i . e . , HuR , Vts1p , PTB , FUSIP1 , U1A , SF2/ASF , SLM2 , RBM4 and YB1 ) to a pool of 213 , 130 unique short ( 29- to 38-nt ) RNA sequences ( see GEO record GSE15769 and/or Agilent array design: AMADID # 022053 for the array design and data ) . RNAcompete estimates an RBP's binding affinity for each sequence in an RNA pool based on the relative enrichment of that RNA sequence in the bound fraction versus the total RNA pool ( as measured by transformed microarray intensity ratios ) . The RNA pool can be divided into two separate sets , Set A and Set B , that each individually satisfy the following constraints: ( i ) each loop of length 3 to 7 ( inclusive ) is represented on at least one sequence flanked by RNA stems of 10 bases; and ( ii ) a population of “weakly structured RNAs” wherein each possible 7-mer is represented in at least 64 different sequences that have high folding free energy , and therefore are linear or form weak secondary structures . We call the group satisfying the first constraint the stem-loop sequences . This group also contains 60% of the possible length eight loops . We call the sequences satisfying the second constraint the weakly structured sequences . There is no overlap between the stem-loop and weakly structured sequences . So in summary , there are two different groups of stem-loops , one in Set A and one in Set B , and similarly , two different groups of weakly structured sequences . It is important to note two things . First , though we attempted to design these sequences to be linear or hairpins , there are many unintended structures represented in the pool . For example , some of the sequences contain bulge or internal loops and some of the weakly structured sequences contain stem-loops . Second , no two sequences within the pool share a common subsequence more than 12 nt long . The design and properties of these sequences are described in greater detail in [5] . The division of the RNA sequence pool into Set A and Set B provides a natural strategy for evaluating our motif models using two-fold cross-validation: we train our algorithm on one of the two sets and test its predictive power on the other set . This strategy provides us with two independent measurements of performance on non-overlapping training sets . Table S1 contains more information on the sizes and compositions of the sequences used for training and testing . The categorizations “Positive” , “Negative” , and “Other” that appear in this table are described below . Note due to stringent RNAcompete quality controls , some affinity data is missing for some of the sequences , so the numbers in the table do not add up to 213 , 130 for each RBP . We evaluated RNAcontext against two other motif finding methods: MEMERIS [9] and MatrixREDUCE [19] . MEMERIS and RNAcontext use similar approaches to model the structural context of an RNA binding site except that MEMERIS only models a single structural context where RNAcontext considers multiple contexts simultaneously . In contrast , MatrixREDUCE does not consider the structural context of RBP binding sites and therefore can help determine the value of considering structural context in RNA motif finding . Additionally , MatrixREDUCE outperforms many standard DNA motif finding algorithms on a similar experimental assay [38] and therefore provides a strong algorithm to benchmark to compare RNAcontext and MEMERIS against . Also , like RNAcontext , MatrixREDUCE learns its motif model by trying to predict RNA sequence affinity whereas MEMERIS searches for motif models enriched in a set of bound sequences . In this subsection we describe our protocol for using the training data to fit the MEMERIS , MatrixREDUCE and RNAcontext motif models . Note that for all three methods , we fit all parameters , including those of the motif models and any free parameters ( like motif width ) , using the training data . One of the free parameters that we consider for each method is whether it is better to train their motif model on the whole training set , or a defined subset of the training set . All of the free parameters that we consider for each method are described below . For every setting of the free parameters , we fit one motif model . The “best” motif model for each method was selected based on its ability to correctly classify “Positive” and “Negative” RNA sequences in the training set , as defined in the next paragraph . The final result of training is a single motif model for each method that we then evaluate on the test set . The parameters of some motif models are fit using subsets of the training set because: ( i ) MatrixREDUCE does not model RNA secondary structure and it is possible that its performance would degrade when trained on stem-loop sequences ( most of whose bases are paired ) ; and ( ii ) MEMERIS takes as input a set of “bound” sequences that contain RBP binding sites . For MEMERIS , “bound” sequences are selected using a manual cutoff that captures the right tail of the distribution of the RNAcompete affinity estimates . We used a different cutoff for each RBP and each training set and the number of bound sequences ranged between 234 and 792 for the RBPs analyzed . Additionally , we used these bound sequence as the “Positive” sequences for Area Under the Precision-Recall Curve ( AUC-PR ) . For the “Negative” sequences required by the AUC-PR calculation , we used those with estimated affinities below the median affinity of the training set . Any sequence not deemed a “Positive” or “Negative” is labeled as “Other” in Table S1 . We score each motif model's performance by using it to estimate RNA-binding affinities for the “Positive” and “Negative” sequences and then evaluating classification accuracy using the AUC-PR . Because each algorithm models RBP binding preferences in a slightly different manner , in this section , we also describe how we estimate RNA-binding affinity for each sequence using the motif models for each algorithm . For each method , we trained two sets of motif models . One set of models was fit using the full training set which consists of all RNA sequences in the training set for MatrixREDUCE and RNAcontext and all bound RNA sequences in the training set for MEMERIS . The other set of models was fit using only the weakly structured sequences in the training set ( i . e . , removing the stem-loops ) . We consider a wide range of combinations of free parameters for MEMERIS . In particular , we tried all possible combinations of the following free parameter choices: the EF and PU options for measurement of single-strandedness; OOPS , ZOOPS and TCM options for the expected number of motifs per sequence ( see Protocol S1 for details on these options ) ; motif lengths between 4 and 12 nts ( inclusive ) ; different values for the pseudocount parameter ( i . e . 0 . 1 , 1 and 3 ) ; and selecting the training set using a permissive cutoff ( i . e . , the bound sequences ) or a stringent cutoff ( i . e . , the top half of bound sequences ) . The final option means that we consider four different subsets of the training set for each setting of the other free parameters ( i . e . permissive/full , stringent/full , permissive/weak , stringent/weak ) . In total , we fit 648 different motif models for MEMERIS for each training set . We estimate affinity for each RNA sequence using a MEMERIS Position Frequency Matrix ( PFM ) motif model by following an approach similar to that used by MotifRegressor [39] . Namely , we calculated the foreground probability of a K-mer under the product-multinomial distribution defined by the PFM and calculated the background probability using a third-order Markov model trained on either the full training set ( or test set , as appropriate ) . As explained in Protocol S1 , the ratio of the foreground and background probabilities is an estimate of the relative affinity of the RBP for that K-mer . For some RBPs , when it led to a performance increase , we also multiplied this affinity by the probability that the site was accessible , as determined using the optimized settings of the EF/PU and pseudocount parameters for that training set . To estimate the affinity of the entire sequence , we summed its k-mer relative affinities . Note that we also tried MAST [40] to score the sequences using MEMERIS's motif models but test set performance decreased ( data not shown ) . We used MatrixREDUCE to generate single motifs with widths ranging from to by setting to . The MatrixREDUCE program automatically selects the appropriate motif width , so we only needed to choose between two different MatrixREDUCE motifs on each training set ( one trained on the full set and the other only on the weakly structured sequences ) . Note that MatrixREDUCE's PSAM motif model directly estimates relative binding affinity of the RBP for each k-mer , so to estimate RNA sequence affinity , we summed PSAM scores for each constituent k-mer . We ran RNAcontext with motifs width ranging from to , thus creating 18 motif models per training set , and used equation ( 1 ) to score RNA sequences using these models . For all three methods , for each training set , we used the AUC-PR on training set “Positives” and “Negatives” , to select the best single model among the fitted models . The free parameters settings for the selected models are in Table S2 . RNAcontext achieved higher average AUC-PR values than MEMERIS and MatrixREDUCE on all of the nine RBPs analyzed ( Table 1 ) . It also had significantly higher AUC-PRs than either method on 15 of the 18 test sets encompassing seven of the nine RBPs ( the largest P-value was , Wilcoxon's sign-rank test on the AUC-PR values of 1 , 000 bootstrap samples; See Table S3 for the complete results of bootstrap analysis ) . The improvement in AUC-PR of RNAcontext compared with MatrixREDUCE is largest for proteins whose preferred structural context is less common in the RNA pool , reflecting the fact these are the hardest binding sites for MatrixREDUCE to predict . For example , RNAcontext performs much better than MatrixREDUCE on Vts1p which binds to CNGG in the loop of an RNA stem-loop . This sequence appears frequently outside of a loop context in the RNA pool . We also see large improvements for RBM4 that binds to CG containing sequences in an unpaired context , likely because these sequences often appear in stems . In contrast , HuR's binding site is U-rich and , as such , is rarely paired in either the training or test set . In this circumstance , MatrixREDUCE's lack of a structural model does little harm to its performance . Although MEMERIS has higher average AUC-PR than MatrixREDUCE for stem-loop binding proteins Vts1p and U1A , reflecting the value of its model of structural context , its average AUC-PR was otherwise worse than that of MatrixREDUCE and always worse than that of RNAcontext . This is likely due to its inability to make use of the affinity data associated with each sequence . One consequence of this is that it can only trained on a small subset of the data . Some of the loss in AUC-PR on the test set may also be due to overfitting because of the large number of parameter combinations that needed to be considered . Having established that RNAcontext can capture RBP binding preferences better than comparable motif models that either do not model RNA secondary structure ( MatrixREDUCE ) , or use a limited representation ( MEMERIS ) , we then attempted to confirm that the added predictive value was due to the incorporation of structural context , rather than differences in how we estimate sequence affinity . To do this , we compared our model based on the structural annotation alphabet to a simplified version of our model whose alphabet only contains a single letter ( i . e . all bases have an identical structural annotation ) . As in previous sections , the two models were fit to the data for each of the nine RBPs using a variety of motif widths ( 4–12 ) . Also , as before , we used training set AUC-PR to choose the optimal motif width and to choose between the full training set and only the weakly structured sequences . After selecting the single best model for the two methods , we compared RNAcontext against the structure-naive model using AUC-PR on the full test set . To assess the significance of difference in AUC-PR , we used 95% confidence interval of the difference estimated from 1 , 000 bootstrap samples . Figure 2 shows these differences for nine RBPs on the two cross-validation test sets . Using structural context lead to a significant improvement in AUC-PR for eight of the nine RBPs . In some cases , the difference was dramatic , particularly for Vts1p , RBM4 , FUSIP1 and U1A . We then sought to assess the accuracy of position-specific scoring matrix ( PSSM ) approximations of RNA-sequence binding preferences by comparing the predictive power of inferred 7-mers affinities to that of the three PSSM-based models . We trained a “fully-specified 7-mer model” that estimates the binding affinity of an RBP for every 7-mer by taking a trimmed average of the transformed intensity ratios of the weakly-structured sequences that contain the 7-mer in the training set ( see [5] for more details of this model ) . We then used these estimated affinities to assign a score to RNA sequences longer than seven nucleotides , by taking the mean of the affinities of each 7-mer in each sequence in the test set . We also trained and evaluated RNAcompete , MatrixREDUCE and MEMERIS motif models as previously described except that we always restricted the training and test sets to the weakly-structured sequences . We used only the weakly-structured sequences in this comparison so that we could more readily evaluate the ability of PSSM models to assess sequence binding preferences separately from each method's ability to capture RBP structure binding preferences . Figure 3 compares the 7-mer model against the three methods with respect to average AUC-PR on the test sets . PSSM-based motif models perform significantly better than the 7-mer model for every RBP except U1A ( and only on test set A ) , YB1 , and SF2/ASF ( the Wilcoxon sign-rank P-values for the best PSSM motif model are all less than ) . Notice that because MatrixREDUCE performs significantly better than the RNAcompete method for five of the nine RBPs , this performance gain can not be explained by the incorporation of structural context in RNAcontext . Having established that RNAcontext accurately predicts the in vitro affinity for seven of the nine RBPs ( with the exception of YB-1 and U1A ) , we applied RNAcontext to the entire dataset to make the best possible prediction for their binding preferences . The results are shown in Figure 4 and Figure 5 . Figure 4 shows the relative structural context preference of each RBP . RNAcontext's predicted structural preferences are consistent with co-crystal structures for Vts1p [17] ( loop ) and PTB [41] ( ssRNA ) and in vitro and in vivo binding data for HuR [5] , [8] , [12] . RNAcontext also predicts new structural preferences for SLM2 , RBM4 and SF2/ASF . Of particular interest , is that RNAcontext predicts that SF2/ASF has a slight preference for RNA binding sites in bulges , internal loops , and/or multiloops ( the M annotation ) . For FUSIP1 , we report the motif model trained using only the weakly structured sequences even though the model trained on the full set ( shown in Figure S1 ) had higher AUC-PR . As mentioned in the legend of Figure S1 , we could not rule out the possibility that this model reflected an artifact of our pool design despite the fact that the two models both suggest that FUSIP1 prefers its binding site to be 5′ to an RNA stem . Figure 5 compares the motif logo representations ( generated by Enologos software[42] ) of RNAcontext's parameters with previously reported motifs for those RBPs . To derive the energy parameters required by Enologos , we uniformly rescaled the elements of the matrix so that of the optimal binding site , , would be 0 . 5 ( as suggested by [31] ) . Underneath each of the logos for the RNAcontext motifs , we have displayed an estimate of the preferred structural context for each base . In order to identify this context , we found the top 20 best scoring k-mers in the test set under each motif model , averaged the annotation profiles for these 20 k-mers and deemed the annotation with the highest average frequency to be the preferred context for each position in the k-mer . These estimates recover the fact that the Vts1p binding site ( CNGG ) occurs at the 5′ end of the hairpin loop . Our RNAcontext motifs match previously reported binding sites [12] , [17] , [43]–[45] and the motifs that we have previously derived from the RNAcompete data[5] . In both Figure 4 and Figure 5 , we observe a preference for the M structural context for the SF2/ASF motif . This preference has not been previously reported for SF2/ASF [43] . To confirm this unusual preference , we collected data on the in vivo targets of SF2/ASF from [13] . These targets were generated using the CLIP-Seq assay and consist of 296 short RNA fragments that cross-link to the protein in cultured cells which we call “bound”; and 314 transcript sequences not observed to cross-link which we call “unbound” . These data supported our inferred structure preferences for SF2/ASF . In particular , by manual inspection , we discovered a number of cases of the RNAcontext motif within bulge and internal loops within the bound sequences . Also , using our model trained on the RNAcompete data , we were able to distinguish between bound and unbound sequences with higher accuracy using our model ( AUC-PR 0 . 915 ) compared with the version of our model with a single letter annotation alphabet ( AUC-PR 0 . 898 ) and MatrixREDUCE ( AUC-PR 0 . 898 ) . Furthermore , when we train our RNAcontext model on the in vivo data , assigning bound sequences an affinity of 1 and unbound ones an affinity of −1 , we recover the same structural preference for SF2/ASF ( Figure S2 ) .
We have demonstrated that RNAcontext represents an advance over existing methods for modeling mRNA-binding protein binding preferences . Motifs learned by RNAcontext more accurately predicted a held out in vitro binding dataset for all of the nine RBPs tested . Seven of these differences were statistically significant . As expected , the size of an improvement depends on the relative representation of the preferred binding site in the preferred structural context ( or contexts ) in the RNAcontext dataset . RNAcontext motif models reflect previously reported sequence and structure preferences for well-studied RBPs like HuR , Vts1p and PTB and predict new structure binding preferences for SLM2 , RBM4 and SF2/ASF . RNAcontext's predictions are supported by in vivo binding data for SF2/ASF: the RNAcontext in vitro motif model more accurately predicts in vivo binding of SF2/ASF , and RNAcontext motif models trained using the in vivo data recover the same structural context preference . We expect similar success with our other new predictions because , as we have previously established ( in [5] ) , binding preferences inferred from RNAcompete data are consistent with in vivo binding preferences and that more accurate prediction of RNAcompete-measured binding affinity translates into more accurate prediction of in vivo binding . We have also provided evidence that the position-specific scoring matrix ( PSSM ) motif representation is a better approximation for the RNA binding preferences of RBPs than it is for dsDNA binding preferences of TFs . In particular , in previous work [38] , using a similar evaluation framework , we had found that that a “fully-specified 8-mer model” trained on protein-binding microarray ( PBM ) [46] data had greater predictive power for 7 of 10 TFs than a set of standard DNA motif-finding algorithms , including MatrixREDUCE , trained on the same data . These observations were consistent with many others ( e . g . , [47]–[49] ) that PSSMs were inaccurate approximations dsDNA binding affinities for the majority of TFs . In Figure 3 , we show that the opposite holds for RNA-binding data: PSSM models learned by MatrixREDUCE , which does not consider RNA structure , had greater predictive power than a fully-specified 7-mer model for a majority of RBPs . Although the sample size is small , this result may reflect the increased flexibility of RNA compared with dsDNA which may permit more independent movement and recognition of individual bases . Our observations further suggests that modifications of the basic PSSM model made for TFs that incorporate interactions between bases may not be as indispensible for modeling RBP binding preferences . Note that our conclusions here differ from our previous analyses on the same data [5] . We suspect that this difference is due our use , in the present study , of motif finding methods that take full advantage of the affinity data associated with each sequence . Indeed , MEMERIS , one of the algorithms we also used in [5] performed worse than the fully 7-mer model in Figure 3 for eight of the nine RBPs . In summary , we have introduced a new motif model of RBP binding preferences and a corresponding algorithm for fitting this model to quantitative estimates of RBP binding affinity for short RNA sequences . Our RNAcontext model makes use of a new technique for representing RNA structure based on a structural context alphabet that we use to annotate individual bases of RNA sequence . This representation is particularly amenable to modeling RBP binding preferences . Although we provide a pipeline to annotate RNA sequences according to the PLUM alphabet , our motif finding code does not require a particular structural context annotation alphabet for bases or even a particular RNA structure prediction method . Hence , RNAcontext can easily be expanded to integrate more parsimonious annotations of structural context or improvements in RNA structure prediction methods . | Many disease-associated mutations do not change the protein sequence of genes; instead they change the instructions on how a gene's mRNA transcript should be processed . Translating these instructions allows us to better understand the connection between these mutations and disease . RNA-binding proteins ( RBP ) perform this translation by recognizing particular “phrases” that occupy short regions of the transcript . Recognition occurs by the binding of the RBP to the phrase . The set of phrases bound by a particular RBP is defined by the RNA base content of the binding site as well as the 3D configuration of these bases . Because it is impossible to assess RBP binding to every possible phrase , we have developed a mathematical model called RNAcontext that can be trained by measuring RBP binding strength on one set of phrases . Once trained , this model can then be used to accurately predict binding strength to any possible phrase . Compared to previously described methods , RNAcontext learns a more precise description of the 3D shapes of binding sites . This precision translates into more accurate generalization of RBP binding preferences to new phrases and allows us to make new discoveries about the binding preferences of well-studied RBPs . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"molecular",
"biology/rna-protein",
"interactions",
"computational",
"biology/sequence",
"motif",
"analysis"
] | 2010 | RNAcontext: A New Method for Learning the Sequence and Structure Binding Preferences of RNA-Binding Proteins |
Hepatitis D virus ( HDV ) is the smallest virus known to infect human . About 15 million people worldwide are infected by HDV among those 240 million infected by its helper hepatitis B virus ( HBV ) . Viral hepatitis D is considered as one of the most severe forms of human viral hepatitis . No specific antivirals are currently available to treat HDV infection and antivirals against HBV do not ameliorate hepatitis D . Liver sodium taurocholate co-transporting polypeptide ( NTCP ) was recently identified as a common entry receptor for HDV and HBV in cell cultures . Here we show HDV can infect mice expressing human NTCP ( hNTCP-Tg ) . Antibodies against critical regions of HBV envelope proteins blocked HDV infection in the hNTCP-Tg mice . The infection was acute yet HDV genome replication occurred efficiently , evident by the presence of antigenome RNA and edited RNA species specifying large delta antigen in the livers of infected mice . The resolution of HDV infection appears not dependent on adaptive immune response , but might be facilitated by innate immunity . Liver RNA-seq analyses of HDV infected hNTCP-Tg and type I interferon receptor 1 ( IFNα/βR1 ) null hNTCP-Tg mice indicated that in addition to induction of type I IFN response , HDV infection was also associated with up-regulation of novel cellular genes that may modulate HDV infection . Our work has thus proved the concept that NTCP is a functional receptor for HDV infection in vivo and established a convenient small animal model for investigation of HDV pathogenesis and evaluation of antiviral therapeutics against the early steps of infection for this important human pathogen .
Hepatitis D virus ( HDV ) is the smallest virus known to infect humans with a single—stranded , circular RNA genome of about 1 . 7 kilobases in length . It is enveloped by surface proteins from its helper hepatitis B virus ( HBV ) and undergoes a unique replication cycle via an intermediate , antigenomic RNA [1 , 2] . Prevalence of HDV infection remains high in many areas around the world despite the implementation of vaccine programs against HBV . Currently 15 million people are infected by HDV among the 240 million chronic HBV carriers . Viral hepatitis D is considered as one of the most severe forms of human viral hepatitis . However , there are no specific antivirals available for clinical treatment of the infection and antiviral therapies against HBV do not ameliorate hepatitis D . The mechanisms that determine whether an individual clears HDV spontaneously or becomes chronically infected are unclear [3 , 4] . Understanding HDV infection and developing antivirals against HDV have been hampered by the lack of reliable cell culture systems and convenient small animal models susceptible for efficient HDV infection . Sodium taurocholate co—transporting polypeptide ( NTCP ) , a multiple transmembrane transporter predominantly expressed in the liver [5] , was recently identified as a common entry receptor for HDV and HBV [6] . This finding has enabled cell culture systems that support HDV and HBV infection in vitro . For instance , exogenous expression of human NTCP ( hNTCP ) rendered HDV infection of multiple mammalian cell lines , while successful HBV infection has only been achieved in hNTCP—expressing human hepatoma cells [6–9] . It is reasonable to speculate that additional human hepatocyte—specific factors are required for HBV infection of mice , however , transgenic expression of hNTCP may confer susceptibility of mouse hepatocytes to de novo HDV infection , which may provide a much—needed convenient small animal model for investigation of HDV pathogenesis and evaluation of antiviral drugs against HDV in vivo . In addition , as no other virus is simpler than HDV yet still can infect mammals , studying HDV infection in a susceptible mouse model may also help to illuminate how an animal reacts to the invading of the smallest pathogen . We report herein that transgenic mice expressing hNTCP in hepatocytes , designated as hNTCP—Tg , support de novo HDV infection . Active HDV genome replication in the livers of infected mice was demonstrated by the presence of antigenomic RNA and edited RNA species . Infection kinetic studies revealed that HDV infection of hNTCP-Tg mice was acute and age—dependent . The infection was efficiently blocked by monoclonal antibodies specifically recognizing the critical regions of HBV envelope proteins . In our efforts toward unraveling the mechanism underlying the resolution of HDV infection in the hNTCP-Tg mice , we obtained evidence suggesting that adaptive immunity was not required for the clearance of HDV infection in the mouse model . Instead , HDV infection of hNTCP-Tg mice induced a type-I interferon ( IFN ) response that might have contributed to the suppression of HDV replication . Intriguingly , HDV infection could also be efficiently cleared in hNTCP-Tg type I interferon receptor 1 ( IFNα/βR1 ) null mice . RNA—seq analyses of liver transcriptome of the HDV infected hNTCP-Tg and hNTCP-Tg/IFNα/βR1-/- mice revealed that , in addition to known interferon—stimulated genes ( ISGs ) , HDV infection was also associated with up—regulation of novel cellular genes yet uncharacterized for antiviral activity .
We and others previously demonstrated that HDV infection is restricted by murine Ntcp in cell cultures , various mammalian cells complemented with human— but not mouse NTCP supported HDV infection [7 , 8] . To generate a mouse model for HDV infection , we created C57BL/6 mouse lines expressing hNTCP with a C—terminal tag ( C9 ) , driven by a mouse albumin enhancer/promoter ( Fig 1A ) . Mice were screened for the transgene by real—time PCR with primers specific for the human NTCP , and the expression levels of hNTCP mRNA in the liver were examined by real—time PCR after reverse transcription ( qRT-PCR ) . One hNTCP transgenic ( hNTCP-Tg ) C57BL/6 mouse line that was confirmed for germline transmission of the hNTCP transgene by Southern blot analysis ( Fig 1B ) and expression of high level human NTCP mRNA in liver ( Fig 1C—left ) was selected for breeding and subsequent experiments . The expression level of hNTCP transgene was similar to that of the endogenous murine Ntcp ( Fig 1C-right ) . There was no significant difference in the expression of hNTCP transgene between the homozygotes and heterozygotes at both mRNA level quantified by qRT-PCR ( Fig 1C—right ) and protein level examined by Western blot using antibodies against the C9 tag ( Fig 1D ) . Immunofluorescent staining of liver sections with a C9—tag specific antibody showed hNTCP only expressed in the hepatocytes of hNTCP transgenic mice ( Fig 1E ) . Homozygous and heterozygous hNTCP-Tg C57BL/6 mice were both tested for their susceptibility to HDV infection . The viral infection efficiency in hNTCP-Tg mice of 9–10 days old ( n = 10 ) correlated with the dose of inoculating virus and was independent of the hNTCP transgene homozygosity or gender of the transgenic mice ( Fig 2A ) . At the highest HDV dose ( 5×1010 genome equivalents , GEq ) tested , no infection was observed in the wild—type littermates ( n = 6 ) that shared the same genetic background , microbiota and environment with the hNTCP-Tg mice . In the hNTCP-Tg mice , approximately 3% hepatocyte was being infected as examined by immunofluorescent staining positive for HDV delta antigens and the infection occurred in randomly scattered hepatocytes ( Fig 2B ) . No significant liver histopathological changes were observed in the infected mice . There was only modest apoptosis , which was about 0 . 8% of the total cells , in the liver of HDV infected mice ( S1 Fig ) . The HDV infection of hNTCP-Tg mice could be efficiently blocked by monoclonal antibody 2D3 specifically recognizing the pre-S1 domain of HBV large envelope protein ( n = 6 ) [6] , but not a control antibody ( 1C10 ) recognizing the core protein of HBV ( n = 6 ) ( Fig 2C ) . Similarly , a monoclonal antibody 17B9 targeting the S domain of the HBV envelope [6] that presumably attaches with the heparan sulfate proteoglycan on hepatocytes [10] also greatly reduced HDV infection in the mice ( n = 5 ) ( Fig 2D ) . These results show that HDV infection of hNTCP-Tg mice depends on both the pre-S1 and the S region of HBV envelop proteins , and suggest these animals are useful for evaluating inhibitors against HDV entry . HDV undergoes a unique replication cycle via an intermediate , antigenomic RNA [11] . In the hNTCP-Tg but not wild—type littermates , both genomic and antigenomic HDV RNA were readily detectable by Northern blot analysis ( Fig 2E ) , indicating HDV effectively replicated in the hNTCP-Tg mice . We next tested the susceptibility of the hNTCP-Tg mice to HDV infection at different age . Interestingly , while challenge of hNTCP-Tg mice younger than 17 days by intraperitoneal ( i . p . ) injection resulted in marked HDV infection , as indicated by the presence of approximately 1000 copies of HDV RNAs per cell ( ~106 copies/20ng liver total RNA ) at 9 days post infection in the livers of mice ( S2A Fig ) , challenge of the transgenic mice older than 4 weeks with HDV failed to establish effective infection ( S2B and S2C Fig ) , although these mice efficiently expressed hNTCP in the livers regardless of their genotype of being homozygote or heterozygote of the transgene . Together these results demonstrate that hNTCP transgenic mice support HDV entry and RNA replication in hepatocytes in vivo in an age—dependent manner . Because HDV infection of hNTCP-Tg mice should only result in a single—round infection of hepatocytes , it is interesting to know how the host immune system responds to the virus infection . In addressing this question , we first determined the kinetics of HDV replication in the liver of transgenic mice . hNTCP-Tg mice were infected by about 1×1010 GEq of HDV at 9 day after birth and sacrificed on 2 , 6 , 10 , 14 , and 18 days post infection . Intrahepatic HDV RNA reached peak level around 6 day post infection and then declined from the peak by approximately 1000 fold within next 12 days ( Fig 3A ) . These observations suggest that HDV infection of the hNTCP-Tg mice is transient . To explore host factors responsible for controlling the HDV infection in vivo , we first investigated the role of adaptive immunity . Specifically , a hNTCP-Tg scid mouse line was established by crossing hNTCP-Tg with adaptive immunity deficient Prkdcscid mice which bear a premature stop codon in the Prkdc gene whereby the differentiation of lymphoid cells was disrupted in these mice [12] . Similar to that observed in hNTCP-Tg mice , HDV infection was cleared rapidly in hNTCP-Tg mice with a homozygous Prkdc gene mutation ( hNTCP / Prkdcscid ) ( n = 8 ) ( Fig 3B ) , indicating that adaptive immunity is dispensable for viral clearance in these mice . Interestingly , on day 6 after viral inoculation , intrahepatic HDV RNA level in the hNTCP+/+/Prkdcscid mice was significantly lower than that of the hNTCP+/+ mice ( Fig 3C ) ; perhaps a higher level of innate immunity activity in the Prkdcscid mice may have contributed to the rapid HDV clearance at early time [13 , 14] . We further examined HDV infection in hNTCP-Tg mice with deficiency in IFNα/βR1 ( hNTCP-Tg/ IFNα/βR1 -/- ) , which were established by crossing hNTCP-Tg with IFNα/βR1 null mice . It’s known that IFNα/βR1 is essential for type I IFN-mediated signal transduction and its deficiency greatly reduces host antiviral activities in general [15 , 16] . Consistent with this notion , the efficiency of HDV infection in hNTCP-Tg/IFNα/βR1 -/- mice was significantly higher than that in the normal hNTCP-Tg mice examined by qPCR ( Fig 4A ) and immunofluorescent staining of HDV delta antigen ( S3A Fig ) , with about 10 folds increase of HDV RNA copies and 3–5 folds of more delta antigen positive cells , respectively . However , to our surprise , HDV infection was also efficiently cleared within 2 weeks in the hNTCP-Tg/IFNα/βR1 -/- mice ( n = 14 ) ( Fig 4B ) , suggesting that clearance of HDV infection in the transgenic mice may also be achieved via type I IFN-independent mechanism ( s ) . In order to further investigate the mechanisms of HDV clearance in the infected mice , we performed RNA—seq analysis to capture the transcriptomic landscapes in the liver of different hNTCP-Tg mouse lines upon HDV infection ( n = 3 in each group ) . The cellular factors that mediate the type I interferon antiviral response are ISGs [17] . We first compiled a list of 583 mouse ISGs based on the previously reported datasets [18 , 19] , and analyzed their expression fold changes in the infected mice ( S1 Table ) . Comparing to the mock—infected hNTCP-Tg mice , hNTCP-Tg mice infected by HDV exhibited an elevated level of ISGs in the liver sample ( S3B Fig ) . A dot plot for ISG expression fold change is shown in Fig 4C . Ifit1 , Ifi44 , Rsad2 , Ccl7 , Slfn1 , Isg15 , Mx1 , Tgtp1 , Gbp3 , Ifit3 , Ifit2 , Ddx60 , Oasl1 , Zbp1 , Oasl2 , Cxcl10 and Irf7 were among the most significantly up—regulated ISGs in the hNTCP-Tg mice comparing to the wild—type mice similarly inoculated with HDV ( Fig 4C , left ) . In marked contrast , no ISGs were significantly induced in HDV—infected hNTCP-Tg/IFNα/βR1 -/- mice , although the virus infection was also efficiently cleared in those mice ( Fig 4C , right ) . Together these results indicate that although HDV infection of hNTCP-Tg mice induces a type I IFN response , which may subsequently suppress the replication of the virus , other cellular factors may mediate IFN—independent clearance of HDV infection . To identify cellular factors mediating IFN—independent innate immune response against HDV , a systematic investigation using hierarchical clustering analysis of total 7802 genes expressed in the livers of infected mice was performed . The transcriptome analysis revealed multiple genes were up—regulated in HDV inoculated hNTCP-Tg/IFNα/βR1 -/- mice . Among them , 22 genes ( Gm26130 , mt-Ts2 , Mgst2 , Cyp7a1 , Vps45 , etc . ) were clustered as a hot block next to a block containing Irf7 gene that is the master regulator for the induction of type I interferon during viral infection ( Honda et al . , 2005 ) ( S4 Fig ) . Interestingly , most of these 22 genes apparently do not have a known function in the host anti—pathogen process or innate immunity . Together , these results unveiled the interaction landscape of HDV and the hosts , and they also indicate that multiple ISGs in hNTCP-Tg and additional novel cellular factors identified in hNTCP-Tg/ IFNα/βR1 null mice may be relevant to the clearance of HDV infection in the animals . HDV RNA editing is a crucial step late in theHDV lifecycle for switching from viral RNA replication to packaging . HDV RNA editing was detected in mouse liver injected with copies of HDV DNA genome using hydrodynamics—based transfection in vivo [20] . It has been shown by in vitro studies that HDV RNA editing is controlled by ADAR1 which is also an ISG [21] [22] . Using the novel mouse models , we examined the levels of ADAR1 and HDV editing upon the viral infection in vivo . The expression level of both ADAR1 variants , ADAR1S and ADAR1L , was induced in hNTCP-Tg mice upon the infection ( Fig 4D ) . Consistent with ADAR2 not being an ISG , HDV infection did not induce ADAR2 level in hNTCP-Tg mice . Intriguingly , the degree of HDV RNA editing was comparable in hNTCP-Tg/IFNα/βR1-/- and hNTCP-Tg mice ( S5A and S5B Fig ) , hence it is tempting to speculate that the baseline expression of ADAR1 in these mice may be sufficient for HDV RNA editing . We further examined the degree of viral RNA editing as a function of time upon de novo HDV infection of hNTCP-Tg mice . The result showed the degree of viral RNA editing in the animals increased from day 6 to day 18 after infection; nonetheless , during the entire experiment period , only a small fraction of viral RNA was edited with the highest ratio of 4 . 6% on day 18 after viral infection ( S5C Fig ) .
HDV is enveloped by glycoproteins derived from HBV [23] , and it shares species restriction with its helper virus HBV at entry level . Mice are not a natural host for both HDV and HBV and do not support de novo infection by either virus . In this study , we demonstrated that hNTCP-Tg C57BL/6 mice can be infected by HDV . Unlike HDV , HBV infection may be restricted by unknown host factors in mice as successful HBV infection has only been achieved in hNTCP expressing hepatoma cells from human but not mouse [7 , 8] . It is speculated that in addition to hNTCP that facilitates HBV entry , other human hepatocyte—specific factors may be required to enable the mouse hepatocytes to support efficient formation of HBV cccDNA , which is essential for establishment of HBV infection [24 , 25] . Nevertheless , our work reported herein provides strong genetic evidence suggesting that hNTCP is a functional receptor for HDV infection in vivo . Both human— and mouse NTCP can co—transport bile salts from circulation into hepatocytes with sodium [26] . In agreement with the results from cell—based studies suggesting that mouse Ntcp is not a functional receptor for HDV , the wild—type neonatal C57BL/6 mice which express mouse Ntcp at a level similar to that of hNTCP in the hNTCP-Tg littermates , did not support HDV infection . In contrast , mice bearing hNTCP , irrespective of the sex or the homozygosis of hNTCP transgene , were readily susceptible to HDV infection . Intriguingly , the receptor binding pre-S1 lipopeptide was shown to be able to bind to mouse hepatocyte in vitro [27] and in vivo [28] , and to mouse NTCP albeit at a lower efficiency as elucidated by us [7] . The mRNA level of hNTCP was comparable to that of endogenous mNTCP in the hNTCP-Tg mice . It is unclear from current study whether the endogenous mNTCP competes for the pre-S1 domain mediated HDV interaction with hNTCP and thereby negatively affects the viral infection . Apparently mNTCP did not exert a trans—dominant negative effect on hNTCP in the transgenic mice . It will be interesting to compare HDV infection efficiency between hNTCP-Tg mice and mice with their endogenous NTCP genes replaced by hNTCP . Nonetheless , HDV effectively replicated in the liver of hNTCP transgenic mice , Northern blot analysis readily detected antigenomic RNA that is the intermediate and a diagnostic marker of HDV replication . Moreover , although quantifying the degree of RNA editing was limited by the resolution of the RNA editing assays , the study showed that HDV underwent evident RNA editing , an event essential for production of large delta antigen and switch to viral assembly , in the hNTCP-Tg mice during the in vivo infection . Importantly , the HDV infection of hNTCP-Tg mice could be effectively blocked by monoclonal antibodies recognizing either pre-S1 or S domain of HBV envelope proteins , suggesting that interactions between pre-S1 and hNTCP as well as S and heparan sulfate proteoglycans on hepatocytes are essential for HDV infection in vivo . In contrast to immune—deficient uPA/SCID mice implanted with human hepatocytes , which have been used for studying HDV infection and drug candidate evaluation [29 , 30] , hNTCP transgenic mice and their derivatives are heritable , easier to handle and more consistent among individual animals . They can serve as valuable and convenient models for evaluating antivirals , in particular HDV entry inhibitors . Because entry of HBV and HDV are both mediated by envelope proteins of HBV , hNTCP-Tg mice thus may also be used for evaluating HBV entry inhibitors using HDV as a surrogate . Moreover , by crossing with other mice bearing well—defined mutation ( s ) of various immunodeficiency and large—scale analysis of liver transcriptome , they created an unprecedented opportunity for in—depth studies of HDV viral infection and the host immune defense against HDV infection in vivo . In fact , our work reported herein has already revealed several unique characteristics of HDV infection in the transgenic mice . First , we showed that neonatal but not adult hNTCP-Tg C57BL/6 mice supported readily detectable HDV infection in the liver . It is known that significant differences exist between adults and neonates in innate as well as adaptive immunity . For example , the neonatal innate immune system is biased against the production of pro—inflammatory cytokines [31] and dendritic cells ( DC ) may be immature until about 5 weeks of age [32] . In addition , age—dependent susceptibility of mice to virus infection has been reported for many different viruses and frequently the infection efficiency is related to the mouse genetic background [33–35] . It remains to be tested whether the HDV infection efficiency differs by age in other mouse strain ( s ) . In addition , effects of intrahepatic immunity maturation and other age—dependent physiological changes on the susceptibility of HDV infection can also not be ruled out [36 , 37] . Second , concerning the infection efficiency of HDV infection in mice in vivo , we showed that inoculating hNTCP-Tg C57BL/6 mice at 9 days after birth with 3 . 3X1010 mge of HDV resulted in about 3% cells infected by the virus as indicated by the immunofluorescent staining of the delta antigen . It was reported that passage of HDV to woodchucks chronically infected by WHV could infect 10 to 40% hepatocyte , depending on whether the inoculated virus was first or second passage of HDV in woodchucks [38] . However , as there was no HBV infection in hNTCP-Tg mice , HDV only underwent single round infection in the mouse model reported here . The observed infection rate in the animals may also be affected by other factors , such as the route of inoculation and variations among HDV preparations . Direct intravenous injection of the virus may increase the infection rate in hNTCP-Tg mice , but it was not feasible for the 9-days animals . Third , we observed that HDV infection of hNTCP-Tg mice was transient , irrespective to the status of their immune competency ( with Prkdcscid or IFNα/βR1-/- ) . Previous studies reported that no significant liver histopathological changes were found in HDV transgenic mice [39 , 40] or in experimental HDV infected chimpanzees [41] . Reports on experimental HDV inoculation into neonatal or SCID mice with WHV enveloped HDV , which took advantage of HDV ribonucleoprotein’s compatibility with WHV envelops thereby bypassing the species restriction at entry level of HDV , showed a transient infection in the livers of infected animals [42] . We showed herein that the receptor mediated , de novo infection of HDV was cleared in about two weeks in the hNTCP-Tg mice upon viral inoculation with no obvious liver pathological changes . Interestingly , only few cells positive for HDV delta antigen were found to be TUNEL positive in the liver samples of infected mice . More studies , ideally using hNTCP-Tg mice deficient in hepatic apoptosis or necrosis , are needed to clarify whether HDV infection results in the death of the hepatocytes in the mice . Surprisingly , intrahepatic HDV RNA was cleared after infection at comparable kinetics among normal , homozygous Prdkcscid and IFNα/βR1-/- hNTCP-Tg mice; this suggested that the clearance of HDV infection in hNTCP-Tg mice was either due to the activation of innate immune response or accumulation of large delta antigen that suppressed HDV RNA replication . However , the latter hypothesis is not supported by a recent finding that HDV mono—infection of immune deficient ( SCID/beige ) mice transplanted with human hepatocytes persisted intrahepatically for more than 6 weeks [29] . It will be interesting to further investigate the underlying mechanisms controlling the apparently different outcome of the HDV infection in the hNTCP transgenic versus the human hepatocyte—transplanted mouse models , for example whether the difference is due to the activity of NK cells presented in the hNTCP-Tg/Prdkcscid but not in the xenotransplanted SCID/beige mice . Another possible explanation of the discrepancy between the two models is that HDV infection may induce production of cytokines or other soluble factors by non—parenchymal cells that species—specifically inhibit HDV replication in hepatocytes of the infected mice . Forth , two lines of independent evidence presented in this study strongly suggest that HDV infection of hNTCP-Tg mice induces a type I IFN response suppressing HDV replication in hepatocytes . Firstly , intrahepatic HDV RNA in IFNα/βR1 null hNTCP-Tg mice is about 10-fold higher than that in normal hNTCP-Tg mice . In addition , dozens ISGs , among which some have been characterized for their antiviral activities against various other viral infections , for example Mx1 , Ifit1 , Isg15 , Ifi44 , Ddx60 , Oasl ( Liu et al . , 2012; Schoggins et al . , 2011 ) and Irf7 were up-regulated upon HDV inoculation in hNTCP-Tg mice . This is the first report demonstrating that HDV infection induces an early activation of IFN response in vivo . Of note , Hartwig et al . showed that treatment of cultured cells with IFNα increased both ADAR expression levels and RNA editing [43] and enhanced HDV RNA editing was shown to increase the expression level of large delta antigen which could further restrict the HDV replication in cells [44] . It will be interesting to further investigate how the type I IFN response restricts HDV replication in hepatocytes in vivo . Finally , liver RNA-seq analyses of HDV-infected normal and IFNα/βR1 null hNTCP-Tg mice also revealed that expression of additional cellular genes was associated with HDV infection . The majority of these genes have not been characterized for activity in immune response or antiviral infection . Interestingly , 22 genes including Gm26130 , a snoRNA gene , and Cyp7a1 , the rate-limiting enzyme in the synthesis of bile acid from cholesterol via the classic pathway , and several mitochondrial tRNAs are clustered in the analysis of 7802 liver genes of the infected mice . Although further experiments are needed to dissect the possible antiviral roles of these molecules , it is tempting to speculate that at least some of them may function in parallel or in addition to the known ISGs , and be relevant in HDV viral clearance . Of note , as the smallest virus known to infect humans , HDV encodes only one protein ( delta antigen ) , which modulates viral replication through interaction with cellular DNA-dependent RNA polymerases and other host factors [1 , 2] . Studying of HDV infection in hNTCP-Tg mouse model thus opens a unique door for understanding how an animal reacts to invasion by the smallest viral pathogen . In summary , our studies of HDV infection in hNTCP-Tg mice not only proved that NTCP is a functional receptor for HDV infection in vivo and hNTCP-Tg mouse is a useful model for studying antivirals against the infection , and they also shed new light on the interaction between HDV and host immunity , and laid a foundation for future investigation toward better understanding the pathogenesis of HDV infection .
All animals were housed in the animal facility of the National Institute of Biological Sciences ( NIBS ) , Beijing . Animal experiments were conducted following the National Guidelines for Housing and Care of Laboratory Animals and performed in accordance with NIBS institutional regulations after approved by the institution's Institutional Animal Care and Use Committee ( IACUC ) . The protocol number is NIBS-0012 . The human NTCP gene with a C9 tag [6] was cloned into a vector with an expression cassette driven by mouse albumin enhancer/promoter . The recombinant plasmid was linearized and introduced into the pronuclei of C57BL/6NCrlVr mouse zygotes . PCR primers for identifying hNTCP transgene are hNTCP-F ( 5′- GGATAGGGATCCGCCACCATGGAGGCCCACAACGCG-3′ ) and hNTCP-BGH-R ( 5′-ATTTCCCTCGA GCCATAGAGCCCACCGCAT-3′ ) . Fox Chase SCID® ( CB17/Icr-Prkdcscid/IcrlcoCrlVr , homozygous for the severe combined immune deficiency spontaneous mutation Prkdc ) mice were from the Vital River , Beijing , China; Interferon ( alpha and beta ) receptor 1 knockout ( B6 . 129S2-Ifnar1tm1Agt/Mmjax ) mice [15] backcrossed to C57BL/6 for at least 5 generations were from the Jackson Laboratory , Maine , USA . hNTCP transgenic mice homogeneous for Prkdc mutation or null for IFNα/βR1 were obtained by cross breed hNTCP transgenic mice with the corresponding immune deficient mice , respectively . The genotypes of the mice were determined by PCR with DNA isolated from mouse tail . Animals were hosted in an SPF mouse facility and all animal experiments were conducted following the national guidelines for housing and care of laboratory animals and performed in accordance with institutional regulations after approval by the IACUC at National Institute of Biological Sciences , Beijing . RNA from mouse liver or kidney was extracted using TRIzol® Reagent ( Invitrogen ) . The total RNA was reverse transcribed into cDNA with PrimeScriptTM RT-PCR Kit ( Takara ) , cDNA obtained from 20ng RNA was used for real time PCR assay . See S1 Text . Supplemental experimental procedures for details . Western blot analysis for the expression of hNTCP was performed by using liver samples collected from hNTCP transgenic or wild-type mice , total 30 μg protein was loaded and 10μg/ml 1D4 antibody ( Santa Cruz Biotech ) was used for detecting the C9 tag fused at the C-terminus of the hNTCP transgene . Mouse GAPDH was used as a loading control . HDV was produced as previously described by using two plasmids transfection in Huh-7 cells [6] . Mice were inoculated with purified HDV by intraperitoneal ( i . p . ) injection . To minimize the influence of variables , in each experiment ( usually presented as one panel of a figure in the manuscript ) , mouse littermates were injected with HDV from same viral preparation . Mouse liver samples were homogenized in liquid nitrogen immediately after collection , and then lysed by TRIzol® reagent . The total RNA was reverse transcribed into cDNA with PrimeScriptTM RT-PCR Kit ( Takara ) , cDNA from 20ng RNA was used for real time PCR assay . See S1 Text . Supplemental experimental procedures for details . Liver tissue RNA was extracted using TRIzol® reagent . 2μg total RNA was electrophoresed through formaldehyde-containing 1% agarose gels , blotted onto a nitrocellulose membrane ( Hybond-C Extra , Amersham ) , and hybridized with digoxigenin ( DIG ) -labeled RNA probes for HDV genome , HDV antigenome , or mouse GAPDH , respectively . For detecting HDV RNA editing , Nco I restriction digestion of PCR-amplified cDNA derived from HDV RNA was used . 300 ng total RNA was reverse transcribed using random hexamers , followed by PCR using primers specific to HDV cDNAs . PCR products were purified and subjected to overnight digestion with restriction enzyme Nco I ( NEB ) . The total digestion products were separated by 4% polyacrylamide gel electrophoresis ( PAGE ) , and the gel was stained with silver nitrate . In independent experiments , HDV RNA editing was also examined using the [32P] dCTP labeling method as reported by Casey et al [45] or quantified by microcapillary electrophoresis analysis using an Agilent 2100 bioanalyzer . See S1 Text . Supplemental experimental procedures for details . RNA-seq analysis was conducted using the total RNA of livers from 3 mock-inoculated hNTCP transgenic ( hNTCP+/- ) mice , and HDV-inoculated mice including three hNTCP+/- , three hNTCP+/-/IFNα/βR-/- , and three wild-type mice . Mice were inoculated on day 9 after birth , and sacrificed 6 days after the inoculation . RNA-seq was performed using Illumina Genome Analyzer IIx system . Sequence data was deposited at Sequence Read Archive ( SRA ) of the NCBI under BioProject PRJNA236433 . See S1 Text . Supplemental experimental procedures for details . | Currently 15 million people worldwide are infected by hepatitis D virus ( HDV ) . HDV is the smallest virus known to infect human . With co-infection of its helper hepatitis B virus ( HBV ) , viral hepatitis D is considered as the most severe form of viral hepatitis . No specific anti-HDV drugs are available; antivirals against HBV do not ameliorate hepatitis D . We report mice expressing a human bile acids transporter sodium taurocholate co-transporting polypeptide ( NTCP ) in the liver support HDV infection , providing a useful model for studying antivirals against HDV and understanding how the simplest virus interacts with a host in vivo . Our transcriptome analyses of livers of infected mice have unveiled interaction landscape of HDV and the hosts , laying a foundation for further studies . | [
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Notch ( N ) signaling is central to the self-renewal of neural stem cells ( NSCs ) and other tissue stem cells . Its deregulation compromises tissue homeostasis and contributes to tumorigenesis and other diseases . How N regulates stem cell behavior in health and disease is not well understood . Here we show that N regulates bantam ( ban ) microRNA to impact cell growth , a process key to NSC maintenance and particularly relied upon by tumor-forming cancer stem cells . Notch signaling directly regulates ban expression at the transcriptional level , and ban in turn feedback regulates N activity through negative regulation of the Notch inhibitor Numb . This feedback regulatory mechanism helps maintain the robustness of N signaling activity and NSC fate . Moreover , we show that a Numb-Myc axis mediates the effects of ban on nucleolar and cellular growth independently or downstream of N . Our results highlight intricate transcriptional as well as translational control mechanisms and feedback regulation in the N signaling network , with important implications for NSC biology and cancer biology .
Balancing self-renewal with differentiation is a key property of all stem cells [1–3] . Tipping such balance can have detrimental consequences , resulting in lineage depletion or tumorigenesis . N signaling is critically required for lineage homeostasis of both Drosophila and mammalian NSCs [3–5] . In the Drosophila larval central brain , there are two different types of neuroblast ( NB ) lineages , the type I and type II NBs . N signaling appears to be dispensable for the homeostasis of type I NB lineages . In contrast , in the type II NB lineages , which differs from type I NB lineages by possessing transit-amplifying intermediate progenitors ( IPs ) and are hierarchically similar to mammalian NSCs , impaired N signaling leads to NB loss whereas N hyperactivation causes the dedifferentiation of IPs into cancer stem cell ( CSC ) -like tumor-initiating NBs [6–8] . Dedifferentiation has also been recognized as a key mechanism in tumorigenesis in mammals , highlighting the relevance of Drosophila type II NBs to the understanding of human cancer biology . The mechanism by which N signaling maintains NB lineage homeostasis is not well defined . Cell growth regulation has recently been implicated as a key mechanism by which N maintains NSCs [7] , and is particularly relied upon by CSC-like NSCs [7 , 9] . Understanding how N signaling regulates the growth and maintenance of normal NSCs and CSC-like NSCs will therefore have important implications for NSC biology and cancer biology . MicroRNAs are non-coding mRNAs that regulate gene expression by base-pairing with target mRNAs to inhibit their translation or stability . The mode of microRNA action in regulating gene expression tends to be fine-tuning instead of on-or-off , making them excellent candidate players in the maintenance of the robustness of cell fates and tissue homeostasis . The microRNA pathway has emerged as a fundamental gene regulatory pathway with important roles in cell metabolism , proliferation , differentiation , and survival [10–15] . Although recent studies have implicated the involvement of microRNAs in stem cell regulation in various organisms , the molecular mechanisms and logic of microRNA action remain to be elucidated . In this study we set out to examine the role of the bantam ( ban ) microRNA in the regulation of NB homeostasis in the Drosophila brain . We show that ban is a direct transcriptional target of the N signaling pathway , and that ban feedback regulates N through negative regulation of its target mRNA numb , which encodes an inhibitor of N . We show that this feedback regulation of N helps maintain the robustness of NB cell fate . Our results further show that ban also impinges on a Numb-Myc axis of cell growth regulation , apparently in a N-independent manner , thus revealing novel mechanisms in NSC regulation by the N signaling network . These findings have important implications for both the basic biology of NSCs and the therapeutic intervention of cancers caused by deregulated Numb-N signaling .
To identify new players in the N signaling network important for NSC and CSC-like growth , we tested the microRNA pathway . In the fly larval central brain , N signaling is normally required for the maintenance of type II but not type I NBs , and N hyperactivation results in the formation of CSC-like NB within the type II but not type I NB lineages [6–8] . We used clonal overexpression ( OE ) of N intracellular domain ( N-intra ) , an activated form of N , to induce ectopic formation and overproliferation of type II NBs and ensuing tumorous brain growth ( Fig 1A and 1B ) . Inactivation of Dicer-1 ( Dcr-1 ) , a key component of the miRNA pathway [16] , effectively rescued N-intra induced ectopic NB formation and tumorous growth , supporting a critical role for miRNA in N-regulated NSC lineage homeostasis ( Fig 1A and 1B ) . Given the role of ban miRNA in controlling tissue growth , cell proliferation , and survival [17 , 18] , we tested its involvement in NSC regulation by N . Loss of ban function as in banΔ1 null mutant had similar effect as dcr-1 mutation in rescuing N-intra induced ectopic NB formation ( Fig 1A and 1B ) , implicating ban as a key miRNA influencing NB homeostasis . To further confirm these results , we used a transgene overexpressing ban-sponge ( ban-sp ) , which could effectively interfere with ban function [19] . CSC-like ectopic NB proliferation induced by OE of N [7 , 9] was partially blocked by ban-sp ( Fig 1C and 1D ) . Conversely , ban OE enhanced the N OE effect ( S1 Fig ) . Overexpression of Dpn , a putative effector of the N pathway in NBs , caused the formation of CSC-like NB within the type II but not type I NB lineages [20 , 21] . NB overproliferation caused by Dpn-OE was also attenuated by ban-sp ( Fig 1E and 1F ) . Intriguingly , in banΔ1 mutant type II NB clones without N OE , the parental NBs were preserved ( Figs 2A and S2E ) , suggesting that ban is not essential for NB formation or maintenance under normal condition . The number of IPs , however , is reduced in banΔ1 mutant type II NB clones ( S2F Fig ) . These results are consistent with a recent report [18] , which showed that both type I and type II NBs are reduced in ban mutant brains . However , in clonal analysis , each ban mutant clone still contains a NB with appropriate marker expression , albeit with reduced cell size [18] . These results suggest that ban may act cell autonomously to regulate NB cell size , but its effect on NB number may be mediated by a non-autonomous mechanism . Together , these results suggest that ban is preferentially required for the formation and proliferation of CSC-like cells induced by N pathway hyperactivation . We next tested whether cell growth regulation is a main mechanism by which ban mediates N effect on NSC/CSC regulation . Compared to WT NBs , banΔ1 mutant NBs in NB clones are smaller in size , consistent with a previous report [18] . This is true in type I and type II NB lineages ( S2A–S2C Fig ) . banΔ1 mutant IPs in type II NB lineages are also smaller in size ( S2D Fig ) . Conversely , overexpression of ban using a UAS-ban-D transgene increased the size of IPs , without obvious change of type II NB size ( S2G–S2I Fig ) . These results support the notion that ban is involved in the growth control of NBs and IPs [18] . Previous studies demonstrated that nucleolar growth is a key aspect of cell growth in the dedifferentiation of IPs into ectopic NBs induced by N hyperactivation [7] . We found that the nucleolar sizes of both NBs and IPs in banΔ1 type II NB lineages were smaller than WT ( Fig 2A–2C ) . Conversely , when ban was overexpressed , the nucleolar size of IPs was increased ( Fig 2A–2C ) . The growth regulator Myc is a key mediator of N-regulated nucleolar growth in NB lineages [7] . Knockdown of dMyc effectively attenuated ban OE induced nucleolar growth ( Fig 2A and 2C ) , whereas dMyc OE rescued the nucleolar growth defect in banΔ1 mutant ( Fig 2A and 2C ) . As reported before [7] , dMyc OE promotes nucleolar growth in IP but not NBs , whereas the depletion of dMyc leads to reduction of nucleolar size in both NBs and IPs . It appears that the nucleolar size in NBs has reached a limit making it hard for dMyc to further increase it . These results suggest that ban influences NB cell growth at least in part through Myc-mediated nucleolar growth , although we do not rule out the possibility that ban and dMyc may act in parallel to regulate nucleolar growth . To better understand how ban regulates NB lineage homeostasis , we examined its expression and activity in type II NB lineages , which is the source of the ectopic NBs induced by N hyperactivity . Using a ban-lacZ transcriptional reporter , we found that ban expression is highly enriched in NBs ( Fig 3A and 3C ) . This is true for both type I and type II NBs . In type II NB lineages , low level of ban expression was detected in IPs but not the differentiated neurons . Correlating with this expression pattern , ban activity as detected with a GFP sensor , the expression of which correlates inversely with ban activity [17] , was high in NBs and adjacent IPs but low in differentiated neurons ( Fig 3B and 3D ) . Given that ban expression and activity are highly enriched in NBs , we next tested whether this is under N regulation . We found that ban expression and activity were elevated by N OE ( Fig 3A–3D , S3 Fig ) , or in α-adaptin ( ada ) mutant condition ( S4A and S4B Fig ) , where N activity is high due to compromised turnover of N receptor on the cell surface [22]; conversely , ban expression and activity were diminished when N was knocked down by RNAi ( Fig 3A–3D , S3 Fig ) . These results suggest that ban not only mediates the effect of N on NB lineage homeostasis but its expression and activity are under the control of N . qRT-PCR analysis showed that mature ban miRNA level in larval brain was increased by N-OE but decreased by N-RNAi ( Fig 3E ) , similar to the response of known N pathway targets genes ( S4C Fig ) . We next tested whether ban is a direct transcriptional target of N signaling . Through chromatin immunoprecipitation ( ChIP ) using a Su ( H ) antibody [22] , we found that regions of ban locus including its promoter region containing putative Su ( H ) binding sites were preferentially pulled down in the ChIP assay . This is true in both larval brain ( Fig 3F ) or wing imaginal discs ( S4D Fig ) . qRT-PCR analysis showed that ban miRNA level was increased by N-OE but decreased by N-RNAi in the wing discs ( S4E Fig ) as well . Collectively , these results support that ban is a direct transcriptional target of the N pathway . The differential expression and activity of ban in progenitor cells and differentiated daughter cells , and the sharp boundary between cells with high and low ban expression and activity , raised the possibility that ban may regulate N activity to form a positive feedback loop , a mechanism commonly used to generate “all-or-none” switches during cell fate determination [23] . Using a Notch activity reporter , E ( spl ) mγ-GFP [24] , we found that N activity in NBs was increased by ban OE , but decreased by ban-sp OE ( Fig 3G and 3H ) . This is true for both type II and type I NBs . We chose type I NBs located at stereotypic positions in the posterior brain for analysis because they express the E ( spl ) mγ-GFP reporter at a higher level than other NBs , and their scattered distribution made it easier to do GFP signal quantification . We assume that what is learned from type I NBs on the regulation of N activity by ban may well be relevant to type II NBs , but given the differences in Notch function between these cell types , this is an assumption that requires further testing in the future . Our qRT-PCR analysis revealed that other known targets of N were also transcriptionally activated by ban OE but repressed by ban-sp OE ( S4C Fig ) . These results indicate that ban participates in a regulatory network with N to help maintain NSC cell fate . We next sought to identify the target of ban that participates in the regulatory network underlying NB fate determination . Although numb 3'-UTR has been reported to contain two predicted ban binding sites [18] , the ban binding site ( s ) responsible for numb translational repression remains to be determined . Using the RNAHybrid program [25] for miRNA target prediction , we identified several candidate ban-binding sites in Drosophila numb mRNA 3´-UTR as well as CDS ( S5A Fig ) . In translational reporter assays , the addition of numb 3´-UTR made the translation of the luciferase reporter specifically sensitive to the presence of ban but not let-7 miRNA ( Fig 4A ) . Mutating the seed sequence in a best-predicted ban-binding site in numb 3´-UTR , which is distinct from the two predicted sites reported previously [18] , abolished the sensitivity of the reporter to ban ( Figs 4A and S5B ) . These results suggest that numb mRNA is a potential target of ban . To gather in vivo evidence of ban regulation of numb , we first examined the effect of ban LOF and GOF on endogenous Numb expression . Western blot and qRT-PCR analyses showed that in banΔ1 mutant or when ban-sp was ubiquitously expressed , levels of Numb protein ( Fig 4B ) and mRNA ( S5C Fig ) expression were significantly increased in the brain , whereas ban OE led to a moderate reduction of Numb protein and mRNA levels ( Figs 4B and S5C ) . We next examined the in vivo functional relationship between ban and numb in NB regulation . Knockdown of numb by RNAi in type II NB lineages resulted in enlarged nucleolar size in newly born IPs , and numb RNAi rescued the nucleolar size reduction caused by ban-sp OE ( Fig 2D and 2E ) . Importantly , the nucleolar size increase caused by numb RNAi was Myc-dependent ( Fig 2D and 2E; S6A–S6C Fig ) , as in ban OE case ( Fig 2A and 2C ) . These results support the notion that Numb is a key target mediating the effect of ban on nucleolar growth . We further examined the biochemical relationship between Numb and Myc underlying their functional interaction in ban-regulated nucleolar growth . In mammalian HEK293 cells , Numb and c-Myc exhibited physical interaction ( Fig 4C ) . Overexpression of Numb led to reduced level of endogenous cMyc ( Fig 4D and 4E ) , an effect abolished by treatment with the proteasome inhibitor MG132 ( Fig 4F and 4G ) , suggesting that Numb affects Myc protein level through the ubiquitin-proteosome system ( UPS ) . We have also examined Myc levels in Drosophila larval brain NBs with altered Numb activities . We found that dMyc level is increased when Numb is inhibited by RNAi , and decreased when Numb is overexpressed . This is true for both endogenous dMyc ( S7A ) or overexpressed dMyc ( S7B ) . We have also tried to examine the effect of altered ban activities on dMyc expression . The immunostaining did not reveal consistent clear-cut results as seen in Numb manipulation case , probably because ban acts through Numb to indirectly affect dMyc expression , making its effect on dMyc protein level not as robust as Numb . However , when we examined the effect of altered ban activity on endogenous dMyc expression by western blot analysis of brain extracts , we saw increased dMyc protein level in ban GOF condition and reduced dMyc level in ban LOF condition ( S7C Fig ) . Numb has previously been shown to regulate transcription factor stability by stimulating E3 ligase activity [26] . We found that the effect of Numb in promoting Myc degradation was attenuated by knocking down Huwe1 in HEK293 cells ( S7D and S7E Fig ) . In fly larval brain , Huwe1 RNAi resulted in increased nucleolar sizes of NBs and IPs in type II NB lineages in a Myc-dependent manner ( S8A–S8C Fig ) . Moreover , Huwe1 functionally interacted with Numb and Myc to regulate type II NB maintenance , as indicated by the ability of Huwe1 RNAi to facilitate Myc in rescuing the type II NB loss caused by Numb OE ( S8D and S8E Fig ) . To examine the effect of ban on Numb protein expression specifically in NBs , we first examined Numb protein expression in the NBs in ban LOF and GOF FLP-out clones . Our results showed that Numb expression level change in the NBs displays similar trends as detected by the western blot analysis of brain tissues ( S9A and S9B Fig ) , although the difference did not achieve statistical significance . This may be due to the sensitivity of the immunostaining method , the specificity of the antibody , or the relatively high basal expression of Numb in the otherwise wild type NBs . Consistent with the last scenario , when we examined Numb expression in N-V5 overexpression NBs that have lower basal level of Numb , the effect of ban-sp in elevating endogenous Numb expression became more significant ( S10A and S10B Fig ) . This result further supports the notion that the translation of numb mRNA is regulated by ban in vivo . Previous studies showed that OE of a phospho-mimetic form of Numb ( Numb-TS4D ) caused ectopic NB formation and tumorous brain growth , an effect likely reflecting a dominant-negative effect of Numb-TS4D in inhibiting endogenous Numb , as co-expression of Numb-WT completely rescued the Numb-TS4D effect [27] . We found that the Numb-TS4D effect was also rescued by ban-sp ( Fig 4H and 4I ) , presumably due to elevation of the level of endogenous Numb by ban-sp that counteracted Numb-TS4D action . In contrast , co-overexpression of ban using UAS-ban-D did not change Numb-TS4D effect ( Fig 4H and 4I ) , presumably because endogenous Numb activity has been sufficiently inhibited by Numb-TS4D such that its further translational repression by ban-D OE will not have additional phenotypic effect . To further test for a critical role of Numb in mediating the effects of ban on N activity and CSC-like growth , we performed genetic epistasis experiments . First , we found that the effect of ban inhibition by ban-sp in attenuating N activity was mediated by Numb , as numb RNAi or removal of one copy of numb ( Fig 5A and 5B; S11A and S11B Fig ) blocked the ban-sp effect . In contrast , removal of one copy of pros or brat , two other genes that were recently identified as ban targets that regulate normal NB growth and proliferation [18] , was without effect ( S11A andS11C–S11E Fig ) . Consistently , numb RNAi or removing one copy of numb , but not pros or brat , effectively rescued the effect of ban-sp in attenuating ectopic NB formation and tumor-like growth induced by N hyperactivation ( Fig 5C and 5D ) . In N-OE condition , numb RNAi or removing one copy of numb alone had no obvious effect on NB number ( S12A and S12B Fig ) . Moreover , promotion of cell growth by Myc-OE , but not cell cycle progression by Cyclin E-OE , which failed to affect nucleolar growth ( S12C and S12D Fig ) , suppressed the effect of ban-sp on ectopic NB formation and tumorous growth ( Fig 5E ) . Consistent with Huwe1 being a negative regulator of dMyc , Huwe1 RNAi also suppressed the effect of ban-sp on ectopic NB number and tumorous growth ( S12E and S12F Fig ) . Together , these results suggest that at least in N-induced CSC-like NB growth and proliferation , Numb is a key target that mediates the effect of ban , and cell growth conferred by the Numb-Myc axis is a key mechanism of NB homeostasis regulation by ban .
By revealing the involvement of the miRNA pathway , here we highlight the complexity of the N signaling network in normal NSCs and tumor-forming CSC-like NSCs . Previous studies implicated critical roles for both canonical and non-canonical N signaling pathways in NSCs and CSC-like NSCs , and revealed particular dependence of CSC-like NB growth on non-canonical N signaling , which involves PINK1 , mTORC2 , and mitochondrial quality control [9] . Our current study reveals a particular requirement for ban in CSC-like NBs induced by N hyperactivation . The CSC-like NB overproliferation induced by hyperactivation of N or N pathway component Dpn ( Figs 1A , 1B , 1C–1F , 4I , 4J , 5C and 5D ) can all be assumed to be of type II NB origin , since previous studies have clearly established that Notch signaling is essential for the development and/or maintenance of type II NBs , but dispensable for type I NBs , and that hyperactivation of Notch or its downstream effector Dpn induced ectopic CSC-like NB growth by altering the lineage homeostasis of the type II but not type I NBs [3–8 , 20 , 21] . It would be interesting to test whether , in addition to ban’s role in canonical N signaling , there exists a link between ban and non-canonical N signaling . Our data indicate that the ban-Numb signaling motif regulates NSC/CSC behavior through at least two mechanisms . On one hand , it regulates cell growth and particularly nucleolar growth , through Myc , a known regulator of cellular and nucleolar growth [28] . Consistently , we observed negative regulation of Myc protein level by Numb through Huwe1 and the UPS . c-Myc is an essential regulator of embryonic stem cell ( ESC ) self-renewal and cellular reprogramming [29] , and Myc level and stability can be controlled in stem cells through targeted degradation by the UPS [30 , 31] , suggesting conserved mechanisms . A key function of the nucleolus is the biogenesis of ribosomes , the cellular machinery for mRNA translation , and previous studies in Drosophila have supported the critical role of nucleolar growth in NSC self-renewal and maintenance [7 , 32] . On the other hand , the ban-Numb axis feedback regulates the activity of N by a double negative regulation , with the end result being positive feedback regulation . This feedback mechanism may help transform initial not so dramatic differences in N activity between NB and its daughter cell generated by the asymmetric segregation of Numb during NB division [33] into “all-or-none” decision of cell fates ( Fig 6 ) . Feed-forward regulatory loops , both coherent and incoherent , are frequently found in gene regulatory networks [23] , and although ban miRNA is not conserved in mammals , miRNAs have been implicated in an incoherent feed-forward loop in the Numb/Notch signaling network in colon CSCs in mammals [34] . Given the role of ban in a positive feedback regulation of N and the potency of N hyperactivity in inducing tumorigenesis , one may wonder why ban overexpression is not sufficient to cause tumorigenesis . As in any biological systems , feedback regulation is meant to increase the robustness and maintain homeostasis of a pathway . Feedback alone , either negative or positive , should not override the main effect of the signaling pathway . Thus , in the NB system feedback regulation by ban is built on top of the available N signaling activity in a given cell and serving to maintain N activity . Because of ban’s “fine-tuning” rather than “on/off switching” of Numb expression , its effect on N activity during feedback regulation will also be “fine-tuning” , serving to maintain N activity in NB within a certain range . Overexpression of ban in a wild type background may not be sufficient to cause tumorigenesis because N activity is not be elevated to the level sufficient to induce brain tumor as in N-v5 overexpression condition . Consistent with this , the extent of Numb inhibition by ban is also modest , not reaching the threshold level of Numb inhibition needed to cause tumorigenesis . Consistent with the notion that feedback regulation by ban is built on top of the available N signaling activity in a given cell , and that there is dosage effect of N activity in tumorigenesis , overexpression of ban in N-v5 overexpression background further enhanced N-v5 induced tumorigenesis ( S1 Fig ) . It is likely that ban or other miRNAs may participate in additional regulatory mechanisms in the N signaling network in Drosophila . Of particular interest , it would be interesting to test whether miRNAs may impinge on the asymmetric cell division machinery to influence the symmetric vs . asymmetric division pattern [35] , a key mechanism employed by NSCs and transit-amplifying IPs to balance self-renewal with differentiation . Our results emphasize the critical role of translational control mechanisms in NSCs and CSC-like NSCs . Compared to the heavily studied transcriptional control , our knowledge of the translational control of NSCs and CSCs is rather limited . As fundamental regulators of mRNA translation , miRNAs can interact with both positive and negative regulators of translation to influence gene expression [36 , 37] . Thus , miRNA activity can be regulated context-dependently at both the transcriptional and translational levels , which may account for the opposite effect of N on ban activity in the fly brain and wing disc [38] , although the ban genomic locus is bound by Su ( H ) in both tissues . Whether N regulates the transcription of ban or its activity as a translational repressor in the wing disc remains to be tested . With regard to the translation of numb mRNA , the conserved RNA-binding protein ( RNA-BP ) Musashi [39] has been shown to critically regulate the level of Numb protein in mammalian hematopoietic SCs and leukemia SCs [40 , 41] . Further investigation into the potential interplay between miRNAs and RNA-BPs in the translational control of Numb in NBs and CSC-like NBs promises to reveal new mechanisms and logic in stem cell homeostasis regulation , with important implications for stem cell biology and cancer biology .
Fly culture and crosses were performed according to standard procedures and were raised at indicated temperatures . Drosophila stocks were obtained from the Bloomington Drosophila Stock Center , the Vienna Drosophila Resource Center ( VDRC ) , or individual investigators in the Drosophila research community . Please see Supplementary Materials and Methods for details . For immunostaining of Drosophila brains , late third instar larva were dissected , processed for immunohistochemistry , and imaged by confocal microscopy essentially as described [7] . Please see Supplementary Materials and Methods for details of the antibodies used for immunostaining . The primary antibodies used for western blot analysis in HEK293T were: chicken anti-GFP ( 1:20 , 000; Abcam ) , mouse anti-c-myc ( 1:500; 9E10 , Santa Cruz Biotechnologies ) , rabbit anti-c-Myc ( 1:2000; Y69 , Abcam ) , rabbit anti-c-Myc ( 1:1000; Cell Signaling Technology ) , rabbit anti-β-actin ( 1:20 , 000; Millipore ) , mouse anti-Actin ( 1:20 , 000; AbD Serotec ) . Nuclear and cytosolic extracts were obtained using the NE-PER Nuclear and Cytoplasmic Extraction Kit ( Thermo Scientific ) . For western blot analysis of ban LOF , GOF , and additional mutants in larval brains , protein extracts were prepared from late third instars of various genotypes , resolved on SDS-PAGE , transferred to Immobilon-P membrane ( Millipore ) and probed with the indicated antibodies . Please see Supplementary Materials and Methods for details of the other antibodies used for western blotting . Target protein versus loading control band intensities was measured from three independent blots with the Tina2 . 0 software ( raytest Isotopenmessgeraete GmbH , Straubenhardt , Germany ) or Image Studio Lite . To generate MARCM clones , larva at 24 h after larval hatching ( ALH ) were heat-shocked for 1 hr at 38°C and further aged for 72–96 h at 25°C before dissection . For ban mutant MARCM clonal analysis , hsFLP , elav-Gal4; UAS-mCD8-GFP; FRT2A , tubP-Gal80/TM6b were crossed to FRT2A , banΔ1 /TM6b to examine ban LOF effects in normal NSCs , or crossed to Nact; FRT2A , banΔ1/TM6b to examine ban LOF effects in CSC-like NBs . For flip-out clonal analysis , w , hsFLP; Actin 5c>CD2>Gal4 , UAS-GFP-NLS was crossed with the indicated UAS lines , and 24 h ALH larva were heat-shocked for 1 hr at 38°C and further aged for 72–96 h at 25°C before dissection . Occasionally , two clones may be adjacent to each other , especially in brain tumor backgrounds . These large “fused clones” can be distinguished from true “tumor clones” derived from single CSC-like NBs by the lack of GFP signal at the clone boundary in the former , and the distinct topologies in the organization of the stem cells and differentiated progenies in these two types of clones . For NB cell size or nucleolar size quantification , measurements were performed as previously described [7] . In all Figures , unpaired Student’s t-tests were used for statistical analysis between two groups . | Stem cells are functional units in the development , maintenance , and regeneration of tissues in multicellular organisms . Defects in stem cell regulation can compromise tissue homeostasis and result in proliferative or degenerative diseases . Our understanding of the molecular and cellular mechanisms regulating the in vivo behavior of stem cells is still incomplete . The Drosophila central nervous system neural stem cells called neuroblasts have offered an excellent model system for uncovering key mechanisms and player involved in stem cell regulation . Previous genetic studies have uncovered the evolutionarily conserved Numb-N signaling pathway that regulates the self-renewal vs . differentiation choices of the cell fates of NSCs during their asymmetric division . Our understanding of how Numb-N signaling regulates NSC fate is still rudimentary . Recent studies have implicated the involvement of microRNAs in stem cell regulation in both mammalian and Drosophila systems . But the molecular mechanism and logic of miRNA action remain to be delineated . In this study we show that the bantam microRNA is a direct transcriptional target of the N signaling pathway , and that bantam feedback regulates N by negatively regulating the expression of Numb , an inhibitor of N . This feedback regulation of N helps maintain the robustness of NSC fate . We further show that bantam also impinges on a Numb-Myc axis of cell growth regulation , apparently in a N-independent manner . Together , our results highlight the importance of both transcriptional and translational control mechanisms in NSC regulation by the N signaling network . These findings have important implication for our understanding of the basic biology of NSCs and the therapeutic intervention of N-induced cancers . | [
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... | 2017 | The bantam microRNA acts through Numb to exert cell growth control and feedback regulation of Notch in tumor-forming stem cells in the Drosophila brain |
The evolution of heteromorphic sex chromosomes has repeatedly resulted in the evolution of sex chromosome-specific forms of regulation , including sex chromosome dosage compensation in the soma and meiotic sex chromosome inactivation in the germline . In the male germline of Drosophila melanogaster , a novel but poorly understood form of sex chromosome-specific transcriptional regulation occurs that is distinct from canonical sex chromosome dosage compensation or meiotic inactivation . Previous work shows that expression of reporter genes driven by testis-specific promoters is considerably lower—approximately 3-fold or more—for transgenes inserted into X chromosome versus autosome locations . Here we characterize this transcriptional suppression of X-linked genes in the male germline and its evolutionary consequences . Using transgenes and transpositions , we show that most endogenous X-linked genes , not just testis-specific ones , are transcriptionally suppressed several-fold specifically in the Drosophila male germline . In wild-type testes , this sex chromosome-wide transcriptional suppression is generally undetectable , being effectively compensated by the gene-by-gene evolutionary recruitment of strong promoters on the X chromosome . We identify and experimentally validate a promoter element sequence motif that is enriched upstream of the transcription start sites of hundreds of testis-expressed genes; evolutionarily conserved across species; associated with strong gene expression levels in testes; and overrepresented on the X chromosome . These findings show that the expression of X-linked genes in the Drosophila testes reflects a balance between chromosome-wide epigenetic transcriptional suppression and long-term compensatory adaptation by sex-linked genes . Our results have broad implications for the evolution of gene expression in the Drosophila male germline and for genome evolution .
Heteromorphic sex chromosomes—e . g . , XY males in Drosophila and mammals and ZW females in birds and butterflies—have evolved independently numerous times in animals and in plants [1 , 2] . The different chromosome copy numbers between the sexes and the general lack of recombination between X and Y ( Z and W ) chromosomes have resulted in the evolution of sex chromosome-specific gene contents , rates of mutation , rates of evolution , and chromosome-wide forms of regulation [3–8] . Two types of sex chromosome regulation have evolved independently in disparate taxa: sex chromosome dosage compensation , a process that results in roughly equal X:autosome expression levels between the sexes [9 , 10] , and meiotic sex chromosome inactivation ( MSCI ) , the precocious heterochromatinization and transcriptional silencing of the sex chromosomes during meiosis I in the heterogametic sex [11–13] . Sex chromosome dosage compensation has evolved in taxa with XY ( Drosophila , mammal ) , XO ( nematode ) , and , to varying degrees , ZW systems [14–17] . While the mode and molecular basis of dosage compensation differs among taxa , the function is the same [10 , 18] . In the somatic cells of Drosophila melanogaster males , the single X chromosome is dosage compensated by two mechanisms . First , generic basal dosage compensation mechanisms—including buffering and gene-specific regulation—result in an average ~1 . 5-fold increase in expression from the X [19] . Second , sex chromosome-specific dosage compensation up-regulates X-linked genes a further ~1 . 35-fold via the recruitment of the Male-Specific Lethal ( MSL ) protein-RNA complex to chromatin entry sites enriched for a GA-rich ~21-bp MSL recognition element ( MRE ) [20 , 21] . In several Drosophila lineages , neo-X chromosomes—i . e . , ancestral autosomes that now segregate as sex chromosomes—have independently co-opted MSL-mediated dosage compensation via the de novo evolution of MREs [22–24] . MSCI has also evolved independently in taxa with XY ( e . g . , mammal ) and XO systems ( e . g . , nematode , grasshoppers [25–27] ) ; it is unclear if MSCI acts in ZW systems [28 , 29] . During MSCI in XY and XO systems , sex chromosomes are sequestered into a subcompartment of the nucleus and decorated with epigenetic modifications characteristic of heterochromatin formation and/or transcriptional silencing [26–29] . In mice , MSCI strongly impacts gene expression , resulting in the ~10-fold down-regulation of ~80% of X-linked genes in spermatocytes [30 , 31] . Like sex chromosome dosage compensation , the molecular basis of MSCI differs among taxa [12 , 13] , but , unlike dosage compensation , the function of MSCI is still unclear [13] . It has been suggested that MSCI is an epigenetic form of host genome defense against selfish genetic elements [13 , 32 , 33] or that it functions to prevent recombination events between non-homologous X and Y chromosomes [34] . How sex chromosome gene expression is regulated in the Drosophila male germline has proved surprisingly difficult to resolve . Despite early claims that the X chromosome and autosomes are expressed at similar levels ( e . g . , [35 , 36] ) , sex chromosome-specific dosage compensation appears absent in the Drosophila male germline . First , key components of the MSL complex are not expressed in testes , and those that are do not localize to the X chromosome , indicating a lack of MSL-mediated sex chromosome dosage compensation [37–39] . Second , median expression of the X chromosome is ~1 . 5-fold lower relative to autosomes , consistent with basal but not sex chromosome dosage compensation [40–42] . Similarly , MSCI may also be absent from the Drosophila male germline , as previous data from cytology , microarray analyses , and indirect genetic evidence have failed to settle the question . Direct cytological evidence is inconclusive or lacking [34 , 43–46] , and microarray analyses do not demonstrate the expected strong global down-regulation of X-linked gene expression as cells progress from premeiotic to meiotic stages of spermatogenesis ( [40 , 47]; but see [48 , 49] ) . Two genetic findings have been suggested as evidence for MSCI in Drosophila . First , ~75% of X-autosome reciprocal translocations cause dominant male sterility ( autosome-autosome translocations do not ) , as might be expected if putative allocyclic condensation of the sex chromosomes , and hence MSCI , is disrupted ( [50]; but see Results below ) . Second , and more direct , the expression levels of transgene reporters in the Drosophila male germline are consistently lower for X-linked insertions than autosomal ones ( [51–53]; see also [54] ) . In particular , promoters from five genes ( two autosomal , three X-linked ) with normally strong testis expression have been found to drive 3- to 8-fold lower expression of the lacZ reporter when the transgenes reside on the X chromosome ( [51–53]; see also [54] ) . If the X chromosome undergoes MSCI , then X-linked transgenes may be prematurely silenced in primary spermatocytes , yielding lower average expression than autosomal transgenes [51 , 54] . The transgene findings are compelling , but some aspects of the data are difficult to reconcile with MSCI . For one , endogenous X-linked genes are not expressed ≥3-fold lower than autosomal genes in testes [40 , 41 , 48] . For another , RNA in situ analyses show that some X-linked transgene reporters initiate transcription relatively late in primary spermatocytes—i . e . , at precisely the stage that MSCI is expected to silence the X [53] . Finally , the transcriptional suppression of some X-linked transgene reporters is detectable early in the male germline , in cells enriched for mitotic gonialblasts , prior to any putative MSCI [40] . Thus , while the transcriptional suppression of X-linked transgenes—which , for convenience , we hereafter term X suppression—is a real and robust phenomenon , it probably does not correspond to canonical MSCI ( as in mammals or worms ) . Here we further characterize the regulation of X chromosome gene expression in the Drosophila male germline . First , we test if X suppression is restricted to genes with testis-specific promoters or is more general . Second , we test if X suppression is limited to transgene constructs having transposable elements as vectors—i . e . , does X suppression correspond to a form of transposon silencing that differs between the X and autosomes ? Third , we test if X suppression is specific to the male germline . Fourth , we test if X-autosome translocations show evidence of X suppression ( or MSCI ) in Drosophila testes . Finally , we present evidence that X-linked genes have adapted to X suppression via the recruitment of strong testis-specific promoters . We computationally identify and then functionally validate a promoter element that drives strong expression in the testis , is especially enriched in the promoters of testis-specific genes on the X chromosome , and is evolutionarily conserved . Our results reveal that the X chromosome has evolved strong testis-specific promoters via the gene-by-gene recruitment of sequence elements that counteract sex chromosome-wide transcriptional suppression in the Drosophila male germline . The strong promoters on the X chromosome effectively compensate the effects of transcriptional suppression , rendering X suppression undetectable except via genetic manipulations that move genes between the X and autosomes . These findings lead to a new model for the control of gene expression in the male germline and have clear implications for the evolution of gene expression , gene duplication , and gene location in the genome .
All previous evidence for transcriptional suppression on the X chromosome in the Drosophila male germline ( hereafter , “X suppression” ) has come from the study of P-element transgenes in which testis-specific promoters drive the expression of reporter genes [51 , 53 , 54] . It is therefore unclear if X suppression is restricted to testis-specific promoters or affects all promoters . We therefore tested if promoters that drive less tissue-specific expression profiles are subject to X suppression . We first confirmed X suppression for lacZ transgene reporters driven by the promoter of the autosomal testis-specific gene ocnus with a subset of X-linked and autosomal inserts used in previous work [51]: ocnus transgenes inserted into X chromosome locations ( n = 5 ) are expressed 14 . 5-fold lower than those inserted into autosomal ones ( n = 5; Table 1 ) . To test if X suppression occurs for less tissue-specific promoters , we assayed testis expression of mini-white for the same transgenes ( white is expressed in the male germline [40] ) : mini-white is expressed 1 . 7-fold lower from X-linked transgenes than autosomal transgenes ( Table 1 ) . Next , to test if X suppression affects promoters that mediate broad expression profiles , we assayed testis expression of transgene reporters driven by Actin 5c ( Act5c ) and Ubiquitin ( Ubi ) . As Table 1 shows , Act5c and Ubi transgenes are expressed 23 . 2-fold and 9 . 6- to 13 . 8-fold lower on the X compared to autosomes . These results show , for a small sample of promoters ( but see below ) , that X suppression is not limited to genes with testis-specific expression . All previous studies of X suppression in the Drosophila male germline have involved transgene reporters embedded in transposable element vectors . It is therefore possible that X suppression is transposon-specific , reflecting an X chromosome versus autosome difference in the efficacy of transposon silencing in the male germline . To test if X suppression affects endogenous genes , we assayed expression in whole testes of genes in X chromosome segments transposed to autosomal locations . These experiments allow us to directly compare expression of endogenous X-linked genes when located on the X chromosome versus an autosome . We used two large ( ~2 . 5 Mb ) transposition genotypes ( e . g . , X/Y; Tp ( 1;2 ) /+ ) and four small ( ~63 kb ) “synthetic transposition” deficiency-duplication genotypes ( e . g . , Df ( 1 ) /Y; Dp ( 1;3 ) /+ ) made by combining X chromosome deficiencies with complementing X-to-autosome duplications ( Fig 1A; see Materials and Methods ) . Importantly , gene dose is controlled in these experiments , as we contrast expression of one gene copy on the X in wild-type males with one gene copy on an autosome in males heterozygous for transpositions . In total , we assayed expression of 26 genes from two large transpositions and four small synthetic transpositions , with transposed X chromosome segments ranging in size from 2 . 55 Mb ( Tp ( 1;2 ) rb+71g ) to 63 kb ( Dp ( 1;3 ) DC523 ) ( Table 2 ) . Notably , the Tp ( 1;2 ) sn+72d and Tp ( 1;2 ) rb+71g transpositions each include genes—CG10920 , CG12681 and Act5C—whose promoters show evidence of X suppression in previous transgene reporter assays [53] . We find that 23 of 26 ( 85% ) X chromosome genes have higher expression when transposed to an autosome with an average 3 . 69-fold increase in expression ( Wilcoxon signed-rank test , p = 1 . 82 x 10−6; Table 2 ) . Twenty-one of twenty-six ( 81% ) genes , including CG10920 , CG12681 , and Act5C , have significantly higher expression when transposed to an autosome , with individually significant transposed genes showing an average 3 . 85-fold increase in expression . Only one X-linked gene shows significantly lower expression when transposed to an autosome ( CG8758; Table 2 ) . These results recapitulate and extend findings from the transgene reporter assays and show that X suppression is not limited to genes in transposon vectors . Furthermore , we find no difference in the magnitude of escape from X suppression for small ( ~63 kb ) versus large ( ~2 . 55 Mb ) transpositions ( unpaired t test , p = 0 . 610 ) suggesting that X suppression does not depend on the size of the transposition . To further test the effect of chromosomal scale on X suppression , we compared the magnitude of escape from X suppression for four genes ( CG17764 , CG3323 , snf , Rnp4f ) when in either a small versus large transposition and again found no difference ( paired t test , p = 0 . 421 ) . These results show that X suppression holds across multiple transpositions that vary in size and genomic location . We next examined the effect of testis-specificity on X suppression by comparing whole testes expression of 14 testis-specific genes versus 12 non-specific genes across the six transposition genotypes ( Table 2 ) . All 14 testis-specific genes and 8 of 12 non-specific genes are significantly overexpressed when transposed from X to autosome ( Table 2 and Fig 1C ) . Transposed testis-specific genes show an average 4 . 66-fold increased expression , whereas transposed non-specific genes show an average 1 . 95-fold increased expression ( Mann-Whitney test , PMWU < 2 . 2e-16 ) . Among transposed genes with individually significant over-expression , non-specific genes show an average 2 . 42-fold increase in expression . While suggestive that endogenous X-linked testis-specific genes may be more strongly suppressed ( ~4-fold ) than non-specific genes ( ~2-fold ) , there is an alternative possibility . In particular , testis-specific genes tend to be strongly expressed in testes . We therefore asked if the magnitude of wild-type gene expression is predictive of the magnitude of escape from X suppression . We find that testis expression in Tp ( X;A ) males is significantly correlated with endogenous wild-type X-linked expression for all genes ( r2 = 0 . 36 , p = 0 . 0005 , Fig 2 ) . This relationship is not significant within housekeeping genes ( p = 0 . 2 ) and only marginally significant within testis-specific genes ( r2 = 0 . 26 , p = 0 . 05 ) , although there is no significant difference in the regression slope estimate between these two groups , ( p = 0 . 66; Fig 2 ) . These results suggest that the magnitude of escape from X suppression for the testis-specific genes assayed is greater owing to their higher endogenous wild-type expression levels in testes compared to the non-specific genes assayed . Genes with higher expression in testis may simply show a comparably greater release from X suppression when transposed to an autosome . To determine if X suppression is limited to the male germline or occurs in other tissues , we tested for evidence of escape from X suppression in the female germline and in gonadectomized male and female carcass . First , we assayed expression of a transgene reporter gene driven by one of the Ubi promoters previously assayed in whole testes . We find no evidence of X suppression in these samples ( S4 Table ) . Moreover , the X-linked inserts show higher expression compared to the autosomal inserts in the female and male carcass , which the opposite direction expected if X suppression is acting in the soma . Second , we assayed expression of six non-specific genes from the two large X/Y; Tp ( 1;2 ) /+ genotypes and wild-type controls . We find little evidence for X suppression in these samples ( Fig 1D and S1–S3 Tables ) . None of the X-linked genes is overexpressed when transposed to an autosome in male carcass , whereas two are significantly overexpressed in female carcass ( Fig 1D and S1 and S2 Tables ) . In ovaries , one X-linked gene is overexpressed when transposed to an autosome , and two are significantly underexpressed ( Fig 1D and S3 Table ) . These findings suggest X suppression is limited to gene expression in testes . As the epithelial cells of the testis sheath are somatic , it remains possible that X suppression acts in these cells and perhaps to a lesser degree in the male germline cells . Previous gene expression analyses from male germline samples with testis sheath dissected away [40] and previous RNA in situ analyses [53] suggest that X suppression is germline-specific . We nevertheless assayed expression from 16 endogenous genes ( 10 testis-specific , 6 non-specific ) from the two large X/Y; Tp ( 1;2 ) /+ genotypes in purified male germline samples with testes sheaths removed ( see Materials and Methods ) [42 , 50] . We find that 13/16 genes show significant evidence of escape from X suppression , with non-specific and testis-specific genes showing 3 . 34- and 5 . 0-fold average increases in expression , respectively ( one-sample t test , p = 0 . 034 and p = 0 . 0011 , respectively; Fig 1E and Table 3 ) . These findings strongly suggest that X suppression is specific to the Drosophila male germline . Promoter sequences in transgenes and endogenous genes in small and large transpositions can escape X suppression when moved from X-linked to autosomal locations ( Fig 1 and Tables 1 and 2 ) . To further investigate the physical scale of X suppression , we assayed expression of the same 26 genes used in the transposition experiments ( Table 2 ) in whole testes of males bearing X-autosome reciprocal translocations . In contrast to transgenes and transpositions , X-autosome translocations are large chromosome-scale aberrations . To identify translocations , we screened all publicly available T ( 1;A ) translocation stocks with known breakpoints from the Bloomington ( n = 6 ) and Kyoto Stock Centers ( n = 7 ) but found only two translocations—T ( 1;3 ) OR17 and T ( 1;3 ) l-v455—still segregating in the stocks , the others being lost prior to receipt . For T ( 1;3 ) OR17 , cytological divisions 1–19EF of the X are translocated to cytological division 67C on chromosome arm 3L , and cytological divisions 61–67C are translocated to cytological division 19EF the X ( S1 Fig ) . For T ( 1;3 ) l-v455 , cytological divisions 1–3C are translocated to cytological division 81 on 3R , and cytological divisions 81–100 are translocated to cytological division 3C on the X ( S1 Fig ) . T ( 1;3 ) OR17 is male-fertile , and T ( 1;3 ) l-v455 is male-sterile . In T ( 1;3 ) OR17 males , all 26 X chromosome genes are translocated to 3L ( S1 Fig ) , but none are overexpressed relative to wild-type controls ( Table 4 ) . Instead , only five genes differ significantly from wild type , and all are underexpressed when translocated to 3L—the opposite pattern expected for escape from X suppression . We conclude that there is no escape from X suppression in T ( 1;3 ) OR17 males . In T ( 1;3 ) l-v455 males , only three of the 26 X chromosome genes are translocated to 3R ( S1 Fig ) . It is important to note that the amount of the X-linked material translocated to the autosome in T ( 1;3 ) l-v455 ( ~3 Mb ) is similar to that for largest transposition assayed ( 2 . 55 Mb in Tp ( 1;2 ) rb+71g ) . However , unlike the large transposition , only one gene ( CG12740 ) shows a marginally significant ~1 . 9-fold increase in expression relative to wild-type controls when translocated to 3R ( Table 4 ) . To further test if escape from X suppression acts in translocations , we assayed seven additional genes ( five testis-specific , two non-specific ) located within the X-linked region transposed to the autosome in T ( 1;3 ) l-v455 and in T ( 1;3 ) OR17 ( S1 Fig ) . None differ in expression from wild-type controls for either translocation ( Table 4 , lines 4–10 ) . These findings suggest that the increased expression of CG12470 in T ( 1;3 ) l-v455 is incidental to escape from X suppression . We therefore conclude that X-linked genes do not escape X suppression in X-autosome translocations . We next tested if naïve autosomal genes experience X suppression when translocated to the X chromosome . We assayed an additional five testis-specific genes and four non-specific genes located on autosomal arm 3R ( Table 4 ) . One of these testis-specific genes is ocnus , an autosomal gene known to undergo X suppression in transgene reporter assays [51 , 53] . In T ( 1;3 ) l-v455 males , all nine genes are translocated from 3R to the X ( none are translocated in T ( 1;3 ) OR17 ) , but none show a significant change in expression relative to wild-type controls ( Table 4 ) . It is important to note , however , that T ( 1;3 ) l-v455 males retain a wild-type third chromosome ( S1 Fig ) , decreasing our power to detect reduced expression . Overall , these findings suggest that , in contrast to genes that have been relocated via transposition or trangenesis , translocated X chromosome genes do not escape X suppression and translocated autosomal genes show little evidence of X suppression . Assaying gene expression from fertile and sterile X-autosome translocations allows us to test for another form of X chromosome regulation hypothesized to act in the male germline: MSCI . The male sterility of ~75% of X-autosome translocations has been interpreted as evidence that these chromosome rearrangements disrupt MSCI [50] . In particular , X-autosome translocations could disrupt MSCI in two ways: X-linked genes translocated to an autosome could escape MSCI , resulting in their aberrant overexpression [50]; or , autosomal genes translocated to the X could be transcriptionally silenced by MSCI , resulting in their aberrant underexpression ( as in mouse; [27 , 55 , 56] ) . We tested both possibilities . First , we compared the expression of ten X chromosome genes translocated to chromosome 3 in testes from T ( 1;3 ) l-v455 males , which are sterile , versus T ( 1;3 ) OR17 males , which are fertile . Only one of the genes shows a significant increase in expression in T ( 1;3 ) l-v455 males compared to T ( 1;3 ) OR17 males when translocated to chromosome 3 ( CG12470; p = 0 . 013 , Table 4 ) . Second , we compared testis expression of eight autosomal genes that are translocated to the X in T ( 1;3 ) l-v455 males ( sterile ) but remain autosomal in T ( 1;3 ) OR17 males ( fertile ) . None of the eight autosomal genes show a significant decrease in expression when translocated to the X in male-sterile T ( 1;3 ) l-v455 flies ( Table 4 ) . These results show that any putative MSCI in the Drosophila male germline does not appear to be disrupted in a way that results in aberrant transcriptional expression of genes translocated between the X chromosome and autosomes . Alternatively , the effects of MSCI could be too subtle to detect via our whole testis dissections [49] . We note , however , that whole testis dissections are easily sufficient to detect X suppression ( and escape from X suppression ) using transgenes and transpositions ( Tables 1 and 2; [40 , 51 , 53 , 57] ) . From the transgene and transposition experiments , we infer that transcription from the X chromosome is 2- to 4-fold suppressed in the male germline . And yet , in the testes of wild-type males , global germline expression levels from the X chromosome are not ~2- to 4-fold lower than that from the autosomes [40 , 42] , implying that X suppression is compensated . We speculated that transcription from the X is suppressed in the male germline but that X-linked testes-specific genes may have evolved strong promoters that counteract suppression . We tested the possibility that promoters of testis-specific X-linked genes might have recruited particular sequence elements that drive strong expression . Using the MEME motif-discovery software [58] , we computationally queried sequence coordinates from -250 bp upstream to +50 bp downstream of the transcription start sites ( TSS ) of subsets of genes in the D . melanogaster reference genome ( see Materials and Methods; S2 Fig ) . In our query of testis-specific X-linked genes , we identified eight DNA sequence motifs , one of which was significantly enriched in promoter regions of testis-specific genes compared to housekeeping genes ( Fisher’s exact PFET < 2 . 2 x 10−16; S5 Table ) . This ~19-bp sequence ( hereafter “AG[tagg]C” , based on the seven least-degenerate core nucleotides within the sequence ) has a complex sequence , is abundant ( being present in the promoter regions of 1 , 189 genes ( 7 . 8%; Fig 3A and Table 5 ) and not only shows a 3 . 5-fold enrichment at genes with testis-specific expression versus housekeeping genes ( S5 Table ) but , among testis-specific genes , is 2-fold overrepresented on the X chromosome relative to autosomes ( PFET < 1 . 04 x 10−5; Fig 3B and 3C and Table 5 ) . Indeed , the X chromosome enrichment increases with expression level in testis ( Fig 3C ) . The greatest X-autosome disparity occurs for the most strongly expressed testis-specific genes , peaking at 31% of autosomal genes versus 58% of X-linked genes ( Fig 3C ) . In contrast , the AG[tagg]C motif is found upstream of just 4 . 8% to 7 . 6% of X-linked and autosomal housekeeping genes and non-testis tissue-specific genes ( Table 5 ) . As might be expected given its enrichment at testis-specific genes , the AG[tagg]C motif shows no similarity to the GA-motif that mediates somatic sex chromosome dosage compensation via recruitment of the MSL complex [20] . Being enriched in the upstream regions of X-linked testis-specific genes , the AG[tagg]C motif is a plausible candidate promoter element that might mediate the strength and/or specificity of testis expression . Several statistical analyses provide further support for its functional significance . First , testis-specific genes with at least one copy of AG[tagg]C have ~1 . 8-fold higher median expression than those lacking AG[tagg]C ( PMWU = 2 . 2 x 10−9 ) ; however , housekeeping genes with or without AG[tagg]C show no difference in expression ( PMW = 0 . 144 ) . Second , the AG[tagg]C element shows DNA strand bias in testis-specific genes: 80% of single-copy AG[tagg]C motifs are found on the coding strand and 20% on the template strand ( binomial test p < 2 . 2 x 10−16 ) ; in contrast , housekeeping genes show no such bias ( p = 0 . 158 ) . This strand bias is associated with significant differences in expression among testis-specific genes ( Kruskal-Wallis , PKW = 3 . 1 x 10−8 ) : those with the AG[tagg]C motif on the coding strand have 1 . 9-fold higher expression than those lacking the motif ( PMW = 3 . 0 x 10−8 ) , whereas those with the AG[tagg]C motif on the template strand do not differ in expression from those lacking the motif ( PMW = 0 . 070 ) . There is no evidence that AG[tagg]C presence or orientation affects the expression of housekeeping genes ( PKW = 0 . 059 ) . Third , within the 300-bp promoter regions queried , AG[tagg]C motif locations are concentrated about a modal position centered at -40 bp upstream of the TSSs of testis-specific genes ( χ2 goodness-of-fit compared to a uniform distribution , p < 2 . 2 x 10−16 ) ; in contrast , the AG[tagg]C motif location shows no strong pattern in housekeeping genes ( p = 0 . 574; Fig 3D ) . Finally , if AG[tagg]C is indeed important for wild-type function , then we should find evidence of functional constraints in its DNA sequence evolution . As AG[tagg]C is repeated many times in the genome , nucleotide bit height in the logo plot ( a measure of nucleotide frequency at a particular site ) provides quantitative information on the relative importance of particular nucleotides to motif function ( Fig 3A ) . We therefore examined DNA sequence divergence of homologous AG[tagg]C elements on coding-strands between D . melanogaster and its related species , D . yakuba , for both testis-specific genes and housekeeping genes . We find that AG[tagg]C nucleotide bit height is negatively correlated with interspecific divergence for testis specific genes ( R2 = 0 . 676 , p = 1 . 6 x 10−5; Fig 2E ) but not housekeeping genes ( p = 0 . 588; S3 Fig ) . For testis genes , the least degenerate nucleotide positions in AG[tagg]C are also the most evolutionarily constrained . Taken together , these findings on abundance and strand bias ( Fig 3B and Table 5 ) , expression level ( Fig 3C ) , position relative to TSS ( Fig 3D ) , and evolutionary constraint ( Fig 3E ) strongly imply that the AG[tagg]C promoter element is functional and important for expression of testis-specific , but not housekeeping , genes in the male germline . To functionally validate the AG[tagg]C motif , we compared expression of a lacZ reporter driven either by wild-type or mutant AG[tagg]C sequences . We cloned the upstream noncoding sequence from CG12681 , a testis-specific gene on the X chromosome . We found that CG12681 escapes X suppression when transposed to an autosomal location ( Table 2 ) , and previous work showed that the CG12681 promoter region drives strong lacZ reporter gene expression in testes and escapes from X suppression when moved to an autosomal site via transgene [53] . We therefore cloned the identical 766-bp upstream noncoding region of CG12681 [53] which we determined includes two copies of the AG[tagg]C motif , –193 bp and –51 bp upstream of the TSS . After cloning the wild-type sequence , we used site-directed mutagenesis to generate lesions that alter the proximal AG[tagg]C element , the distal AG[tagg]C element , or both ( Table 6 , column 2; Materials and Methods; S4 Fig ) . The wild-type AG[tagg]C sequence and the four mutant AG[tagg]C sequences were then separately cloned upstream of the lacZ reporter gene , and the resulting AG[tagg]C-lacZ sequences subcloned into the attB vector [59] , yielding attB{w+; AG[tagg]C-lacZ} ( Materials and Methods; S4 Fig ) . We then generated ten transgenic genotypes: each of the five attB{w+; AG[tagg]C-lacZ} constructs ( wild type and the four mutant AG[tagg]C motifs ) in a common X chromosome attP insertion landing site at cytological position 5B8; and each of the five attB{w+; AG[tagg]C-lacZ} constructs into a common autosomal attP landing site at cytological position 75A10 on arm 3L . Finally , we assayed lacZ expression by qRT-PCR to determine if , and to what extent , mutations in the AG[tagg]C motifs affect gene expression from the X-linked versus third chromosome insertion sites . Wild-type AG[tagg]C-bearing transgenes show 2 . 9-fold higher expression from the autosomal site than the X chromosome site ( Table 6 ) , recapitulating the escape from X suppression observed in transposition and in previous transgene genotypes [53] . For X-linked insertions , mutant AG[tagg]C sequences have 2 . 6- to 6 . 1-fold lower expression relative to wild-type controls , two significantly so and one marginally ( Table 6 ) . For autosomal insertions , three of four mutant promoters have significant 2 . 0- to 4 . 5-fold lower expression ( Table 6 ) . These findings show that both the distal and the proximal AG[tagg]C motif sequences of the CG12681 promoter region contribute to strong expression in testis from both X-linked and autosomal sites . Notably , relative to the disrupted AG[tagg]C sequences , the X-linked wild-type AG[tagg]C promoter element provides , on average , a ~3 . 7-fold boost to expression , the approximate magnitude increase required to compensate for X suppression ( see above ) . Indeed , the expression level achieved by the wild-type promoter at the X-linked insert is comparable to that achieved by mutant promoters at the autosomal site . Put differently , X and autosomal expression levels are comparable when suppression of the X-linked copy is offset by a wild-type AG[tagg]C motif . These general quantitative conclusions are , however , provisional as we have only surveyed expression from a single X-linked site and a single autosomal site . We next asked if the AG[tagg]C sequences contribute to testis specificity per se , as opposed to overall testis expression level: if the AG[tagg]C motif mediates testis specificity , then disruption of the motif could yield less specific , aberrantly broad expression . To test if mutations in the AG[tagg]C motif compromise testis specificity , we compared wild-type versus mutant transgene expression in gonadectomized male carcasses . Among the autosomal insertions , all four mutant AG[tagg]C sequences drive significantly lower expression in the male carcass relative to wild type ( on average , ~2 . 8-fold lower; Table 7 ) . For this autosomal site , then , disrupting the AG[tagg]C motif reduces expression in testis and in the rest of the male carcass . The X-linked AG[tagg]C transgenes behave qualitatively differently . For the X-linked insertions , all four mutant AG[tagg]C sequences drive higher expression in the male carcass ( on average , ~8 . 3-fold higher ) , three significantly so ( on average , ~9 . 9-fold higher; Table 7 ) . At the X-linked site , then , disrupting the AG[tagg]C motif reduces expression in testis but increases expression in the male carcass . These findings show that the AG[tagg]C motif contributes to strong testis expression and , for the X-linked site , to testis-specificity .
The findings reported here lead to several conclusions concerning gene expression from the X chromosome in the Drosophila male germline . First , genes on the X chromosome are transcriptionally suppressed several-fold: both transgene reporters and endogenous genes show 2- to 4-fold higher expression when moved from the transcriptionally repressive environment of the X chromosome to the more permissive environment of the autosomes . Second , testis-specific genes experience larger , more consistent increases in expression than non-specific genes when moved from X-linked to autosomal positions . Preliminary evidence suggests , however , that this may be mediated by the higher absolute wild-type expression of testis-specific genes in the testes ( Fig 2 ) rather than testis-specificity per se . Third , the AG[tagg]C motif is enriched in the upstream promoter regions of testis-specific genes , especially those on the X chromosome . The AG[tagg]C motif is evolutionarily conserved at critical nucleotide positions , drives higher average expression in testis , and , when X-linked , may contribute to testis-specificity . While the AG[tagg]C element can compensate for X suppression , we identified several other motifs with overrepresentation on the X chromosome ( S1 Table ) , suggesting that other promoter sequences may also compensate for X suppression . Overall these findings show that expression of X-linked genes in the Drosophila male germline results from a balance between chromosome-wide transcriptional suppression and the evolution of strong , compensatory promoters . The mechanism of X suppression remains unknown . It is clear that X suppression is not mediated by the promoter sequences of X-linked genes , as identical promoters drive systematically different expression levels depending on whether they reside in X chromosome or autosomal contexts . Notably , X-autosome translocations do not cause aberrant suppression of translocated autosomal genes or allow general escape from suppression by translocated X-linked genes . This is best seen in comparisons of the same genes assayed across transgene , transposition , and translocation genotypes: Act5c and CG10920 [53] both escape X suppression in transgenes and transpositions but not in translocations ( Tables 1 , 2 and 6 ) . From these findings , we infer that escape from X suppression results from separating X chromosome genes from their native sex chromosome-specific context . When autosomal and X-linked genes move as part of large chromosome arm-scale reciprocal translocations , they are not necessarily separated from their larger native chromosomal contexts . We speculate that sex chromosome-specific context is in this case determined by chromatin status in the male germline and/or to residence in the distinct sex chromosome territory or subcompartment of the nucleus . These alternatives are not of course mutually exclusive , as chromatin state and transcriptional activity are often mediated by subnuclear localization [60–62] . In somatic cells , 59% of our testis-specific genes ( compared to just 2% of our housekeeping genes ) reside in BLACK chromatin , which is characterized by a transcriptionally repressive state and a frequent association with the nuclear lamin B protein ( among others; [63]; see also [64] ) . One possibility is that during spermatogenesis , the testis-specific genes on the X chromosome dissociate less readily from the more transcriptionally quiescent nuclear periphery than those on the autosomes . Whatever the mechanism , a characteristic ~3- to 4-fold transcriptional suppression of the X chromosome is detectable very early in the male germline ( in cells enriched for premeiotic spermatogonia ) and stably maintained through later stages of spermatogenesis [40] . There is no evidence for a dynamic , primary spermatocyte-specific , sex chromosome-wide down-regulation of gene expression , as might be expected for MSCI ( [40 , 47]; but see [48] ) . Our translocation experiments also fail to reveal the kinds of aberrant expression expected if MSCI is grossly disrupted . MSCI must therefore be so weak as to be undetectable in whole- and sub-testis dissections [40] , or it is altogether absent in the Drosophila male germline . We therefore conclude that X suppression is distinct from canonical MSCI . We identified eight sequence motifs enriched in promoter regions of X-linked testis-specific genes ( S4 Table ) . We focused on the AG[tagg]C motif , the most abundant motif with strong overrepresentation among testis versus housekeeping genes and a strong enrichment on the X chromosome versus autosomes . While this motif bears no resemblance to the dosage compensation GA motif [65] , the same sequence motif ( or a very similar one ) was found independently to be enriched near the TSSs of testis-expressed de novo genes that segregate in natural populations of D . melanogaster [65] . Our statistical and experimental analyses show that the AG[tagg]C promoter element drives 2- to 4-fold higher expression in testis on both the X chromosome and the autosomes . Stronger expression might be achieved via the recruitment of positive regulators of transcription or of proteins that facilitate relocation of testis-specific genes from the nuclear lamina to less peripheral , more transcriptionally active nucleoplasm . Our test of the AG[tagg]C element’s contribution to testis-specificity revealed an interesting X versus autosome difference: in testes , disruption of the AG[tagg]C element reduces lacZ expression for both autosomal and X-linked transgenes; in contrast , in the ( somatic ) male carcass , disruption of the AG[tagg]C element decreases expression for the autosomal transgene but increases expression for the X-linked transgene . This qualitative difference suggests that , for testis genes on the X , functional AG[tagg]C elements may contribute to somatic silencing , with disruption of the AG[tagg]C element releasing it from silencing . The fact that this occurs for the X-linked , but not the autosomal site , raises the possibility of an interaction between the AG[tagg]C element and the somatic sex chromosome dosage compensation system . The absence of ~3- to 4-fold lower global gene expression from the X chromosome versus the autosomes in wild-type Drosophila testes [40 , 41] indicates that X suppression is compensated , as shown here , by the gene-by-gene recruitment of strong promoters . The balance between chromosome-wide X suppression and compensatory promoters is a curious arrangement , raising the obvious question of why X suppression exists at all—i . e . , why would X suppression evolve only for its effects to be cancelled by the evolution of strong promoters ? There are at least two broad possibilities . First , X chromosome-wide transcriptional suppression may be an incidental pleiotropic consequence of some other , still unknown phenomenon . Second , X suppression may have evolved deep in the past for reasons that no longer hold and , since then , strong promoters have evolved en masse to compensate . Regardless of its function ( s ) or its evolutionary history , the constrained transcriptional environment of the X chromosome in the male germline has consequences for gene expression and genome evolution . For instance , X suppression , while generally compensated , may impose an upper limit on the expression level achievable in testis . Consistent with this possibility , we find that the proportion of all X linked genes expressed in testis declines as expression level increases , a pattern that holds equally for testis-specific genes and housekeeping genes ( Fig 4; see also [4 , 66] ) . X suppression , and the constraint it imposes on maximum expression , may help to explain the genomic distribution of gene duplications . The Drosophila genome has an excess of parent genes on the X chromosome that have spawned testis-expressed duplicate genes on the autosomes [67 , 68] . This pattern of gene duplication may , along with strong promoters , reflect a complementary means to boost expression and compensate for X suppression .
The P{wFl-ocn-lacZ} transgene lines were generously provided by John Parsch ( University of Munich ) . The T ( 1;3 ) OR17 stock was obtained from the Kyoto Drosophila Genetic Resource Center , and all other stocks were obtained from Bloomington Stock Center ( for the full list , see S4 Table ) . All flies were raised on standard cornmeal media at 22–23°C . We assayed expression of GFP driven by Actin promoters from P{Act-GFP} transgenes ( n = 5; [70] ) , and from Ubiquitin promoters from P{Ubi-GFP} ( n = 4; [71] ) and P{Ubi-GFP ( S65T ) nls} transgenes ( n = 8; Bloomington stock center ) . We also assayed expression of mini-white from the P{wFl-ocn-lacZ} transgenes ( n = 10 ) [51] . We assayed gene expression from two X/Y; Tp ( 1;2 ) /+ transpositions and four synthetic Df ( 1 ) /Y; Dp ( 1;3 ) /+ transpositions along with wild-type controls for each . To generate Tp ( 1;2 ) rb+71g males and FM6; CyO/+ control males , we crossed FM6/Y; CyO/Gla virgin females to Tp ( 1;2 ) rb+71g , ct6 v1 males . Tp ( 1;2 ) rb+71g ct1 v1/FM6;CyO female progeny were then crossed to y1 w* males . We selected Tp ( 1;2 ) rb+71g , ct1 , v1/Y and FM6/Y;CyO/+ males for gene expression assays ( see below ) . Similarly , to generate Tp ( 1;2 ) sn+72d males and FM6/w*; CyO/+ control males , FM6;CyO/Gla virgin females were crossed with Tp ( 1;2 ) sn+72d , f1 car1 males . Tp ( 1;2 ) sn+72d , f1 car1/FM6;CyO female progeny were crossed to y1 w* males . We selected Tp ( 1;2 ) sn+72d , f1 car1/Y males and FM6/Y;CyO/+ males for gene expression assays ( see below ) . To transpose region 1A1–1A3 , we crossed Df ( 1 ) BSC843 w1118/Binsinscy females with w1118; Dp ( 1;3 ) DC004 , PBac{DC004}VK00033/TM6C , Sb1 males . Experimental Df ( 1 ) BSC843 , w1118; Dp ( 1;3 ) DC004 , PBac{DC004}VK00033/+ males and control Binsinscy; TM6C , Sb1/+ males were recovered , and referred to as Df-Dp ( 1;3 ) 1A1-1A3 males and control males , respectively . To transpose 4F4-4F5 to 3L , w1118; Dp ( 1;3 ) DC130 , PBac{DC130}VK00033 females were crossed to TM3 , Ser1/TM6C , Tb1 , Sb1 males , and w1118; Dp ( 1;3 ) DC130 , PBac{DC130}VK00033/ TM3 , Ser1 sons were recovered . These males were crossed to Df ( 1 ) BSC823 , w1118/Binsinscy females . Experimental Df ( 1 ) BSC823 , w1118; Dp ( 1;3 ) DC130 , PBac{DC130}VK00033/+ males and control Binsinscy; TM31 , Ser1/+ males were recovered , and referred to as Df-Dp ( 1;3 ) 4F4-4F5 males and control males , respectively . To transpose region 6C2-6C8 , w1118; Dp ( 1;3 ) DC026 , PBac{DC026}VK00033 females were crossed to TM3 , Ser1/TM6C , Tb1 , Sb1 males , and w1118; Dp ( 1;3 ) DC026 , PBac{DC026}VK00033/ TM3 , Ser1 sons were recovered . These males were crossed to Df ( 1 ) BSC535 , w1118/FM7h females . Experimental Df ( 1 ) BSC535 , w1118; Dp ( 1;3 ) DC026 , PBac{DC026}VK00033/+ males and control FM7h; TM31 , Ser1/+ males were recovered , and referred to as Df-Dp ( 1;3 ) 6C2-6C8 and control males , respectively . To transpose region 13F1-13F17 , Df ( 1 ) Exel6251 , w1118 P{XP-U}Exel6251/FM7c females were crossed to w1118; Dp ( 1;3 ) DC523 , PBac{DC523}VK00033/TM6C , Sb1 males . Experimental Df ( 1 ) Excel6251 , w1118 P{XP-U}Excel6251; Dp ( 1;3 ) DC523 , PBac{DC523}VK00033/+ males and control FM7c; TM6C , Sb1/+ males were recovered , and referred to as Df-Dp ( 1;3 ) 13F1-13F17 males and control males , respectively . We attempted to generate 17 different autosome-to-X synthetic transpositions as well , but all were inviable . To generate Tp ( 1;2 ) rb+71g females we crossed FM6/w*; CyO/Gla virgin females to Tp ( 1;2 ) rb+71g , ct6 v1 males . Tp ( 1;2 ) rb+71g ct1 v1/FM6;CyO daughters were crossed to Tp ( 1;2 ) rb+71g , ct6 v1 males , and homozygous Tp ( 1;2 ) rb+71g , ct6 v1 females were selected . To generate FM6/ y1 w*; CyO/+ control females , we crossed FM6/w*; CyO/Gla virgin females to Tp ( 1;2 ) rb+71g , ct6 v1 males . Tp ( 1;2 ) rb+71g ct1 v1/FM6;CyO/ daughters were crossed to y1 w* males , and FM6/ y1 w*; CyO/+ females were selected . To generate Tp ( 1;2 ) sn+72d females we crossed FM6/w*; CyO/Gla virgin females to Tp ( 1;2 ) sn+72d , f1 car1 males . Tp ( 1;2 ) sn+72d , f1 car1/FM6;CyO daughters were crossed to Tp ( 1;2 ) sn+72d , f1 car1 males , and homozygous Tp ( 1;2 ) sn+72d , f1 car1 females were selected . To generate FM6/ y1 w*; CyO/+ control females , we crossed FM6/ w*; CyO/Gla virgin females to Tp ( 1;2 ) sn+72d , f1 car1 males . Tp ( 1;2 ) sn+72d , f1 car1 /FM6; CyO daughters were crossed to y1 w* males , and FM6/ y1 w*; CyO/+ females were selected . We attempted to validate the status of seven putative translocation stocks from the Drosophila Genetic Resource Center in Kyoto [106092 ( T ( 1;3 ) OR60 ) , 102069 ( T ( 1;3 ) OR45 ) , 102066 ( T ( 1;3 ) sc[260-15T ( 1;3 ) OR49 ) , 102070 ( T ( 1;3 ) OR49 ) , 102020 ( T ( 1;2;3 ) r24 ) , 102067 ( T ( 1;3 ) OR17 ) , 102068 ( T ( 1;3 ) OR34 ) ] and six from the Bloomington Stock Center: 3830 ( T ( 1;3 ) l-v455 ) , 4636 ( T ( 1;3 ) GA91 ) , 4639 ( T ( 1;3 ) JA29 ) , 4633 ( T ( 1;3 ) GA119 ) , 4677 ( T ( 1;3 ) GA41 ) , 840 ( T ( 1;3 ) OR60 ) . All translocations except T ( 1;3 ) l-v455 and T ( 1;3 ) OR17 were lost from the stocks prior to arrival in the lab . All dissections were done in Ringer’s Solution . For all testis samples , seminal vesicles and accessory glands were removed to isolate whole testes . For gonadectomized samples , testes were removed from whole males and ovaries were removed from whole females . All samples were collected from 2–5 day-old mated males or virgin females . For testis dissections , ten testes = one biological replicate; for ovary dissections , two ovaries = one biological replicate; and for carcass dissections , one gonadectomized carcass = one biological replicate . Sheath-removed male germline dissections followed previously published protocols except that here a single dissection included both “apical” and “proximal” material from individual testes [42 , 50] . Twenty sheath-removed germline dissections = one biological replicate . For the motif transgene experiments , five testes = one biological replicate; and for the corresponding carcass , one gonadectomized male = one biological replicate . We isolated RNA using the Nucleospin RNA XS kit ( Clontech ) , which includes a DNase step to prevent genomic DNA contamination . cDNA was synthesized from the SuperScript III kit ( Invitrogen ) . All qRT-PCR primers were optimized to 90%–110% efficiency ( S7 Table ) . We determined by Sanger sequencing that the Actin and Ubiquitin transgenes had different GFP alleles . We therefore designed and optimized different qPCR primers for Actin-GFP and Ubiquitin-GFP samples . Whenever possible , primers were designed to span exon-exon junctions to ensure amplification from cDNA . If primers could not be optimized that spanned an exon-exon junction , primers were made that spanned an intron . For all qPCR , a melt curve was performed at the end as a check against spurious amplification . As many testis-specific genes lack introns , the melt curve results of intron-spanning primers from other genes from the same samples provided evidence against genomic DNA contamination . Because control genes are assayed in all experiments , the exon-exon junction-spanning primers in these genes provide controls against genomic DNA contamination in every sample . For all reactions , 2 μl of cDNA was used in a 20 μl qRT-PCR reaction with SYBR-Green I nucleic acid gel stain ( Invitrogen ) . Two technical replicate qRT-PCR reactions were run for each biological replicate . Ct values were averaged across technical replicate wells for each biological replicate . The mean Ct value for the control genes within each sample was calculated to control for the amount of RNA in each sample . When two control genes were used , the averaged Ct of the mean of the two control genes was used . For synthetic transpositions and Ubi-GFP transgenes , RpS3 was used as the control gene . For all other samples ( except T ( 1;3 ) ) Rpl32 and RpS3 were used as control genes . As Rpl32 and RpS3 are transposed to the X in T ( 1;3 ) l-v455 , Rpl24 was used as a control gene for the T ( 1;3 ) samples . Normalized Ct values for target genes were obtained by subtracting the mean control Ct values from target gene Ct values . For the transposition experiments , five biological replicates were collected for each genotype; for the translocation experiments , three biological replicates were collected for each genotype; and for the motif validation experiments , four biological replicates were collected for each genotype . We used the MEME suite of programs for motif discovery and preliminary analysis . MEME v4 . 9 . 0 [58] was used to identify motifs in a focal sequence dataset , while FIMO v . 4 . 9 . 0 was used to locate occurrences of those motifs in other sequence datasets . MEME was run using the default “zoops” ( zero or one occurrence per sequence ) model of motif distribution and dirichlet prior on background nucleotide frequencies . We searched for the top ten motifs of size 5–20 bp and allowed motifs to occur on either strand of the sequences in the main discovery dataset . FIMO was run using the search criterion of p < 0 . 0001 for a motif occurrence , allowing for hits to occur on either strand . The initial discovery sequence dataset used for motif discovery consisted of regions surrounding ( -250 bp , +50 bp ) transcription start sites of known testis-specific genes on the X chromosome of D . melanogaster . We restricted our analysis to -250 bp upstream , and +50 bp downstream of the transcription start site , as this region is known to contain core promoter elements [72] . We obtained sequences from the D . melanogaster genome version r5 . 51 and expression data from FlyAtlas [69] microarrays as well as RNAseq expression data [73]; FlyBase . org gene-level summaries of tissue-based RNAseq experiments and D . melanogaster annotation release 5 . 50 . Testis-specific genes were defined using FlyAtlas data , where genes with specificity measure of τ ≥ 0 . 8 [74] and maximum expression in testes were designated “testis-specific . ” For subsequent analyses , we also defined “housekeeping” genes as those broadly expressed across multiple tissues with τ ≤ 0 . 2 . For thoroughness , we used MEME to characterize motif profiles for several different sets of D . melanogaster genes . These gene sets included: genome-wide housekeeping ( τ ≤ 0 . 2 ) genes; autosomal housekeeping genes; X-linked housekeeping genes; and the same sets ( genome-wide , autosomal , X-linked ) for testis-specific ( τ ≥ 0 . 8 ) gene sets . The AG[tagg]C motif ( or quantitative variants ) appeared in all of the motif profiles of testis-specific upstream regions ( S2 Fig ) . For the genome-wide and X-linked gene sets , it appeared as the second most significant motif , while for the autosomal subset it appeared as the fourth most significant motif . No similar motifs appeared in the top ten hits of any of the housekeeping sets , nor did we find the motif enriched in the upstream regions of X-linked genes with highly specific expression ( τ ≥ 0 . 8 ) in tissues other than testis . Finally , we did not recover the AG[tagg]C motif among the top ten hits using a gene set compromising genes highly expressed in , but not specific to , testes ( log2RPKM ≥ 5 , τ ≤ 0 . 8 ) . To study the evolution of the AG[tagg]C promoter element , we wrote scripts that extracted -300 bp upstream to +100 bp downstream of TSSs of all genes with at least one motif hit and used BLAST ( v . 2 . 2 . 28+ ) to identify putatively homologous sequences in D . yakuba ( Flybase , genome version r1 . 3 ) . Genes with no hits or multiple HSPs were removed from the analysis . For each successful ( 400 bp ) BLAST we reconstructed as much of the smaller 300 bp region used in motif-finding ( -250 bp upstream to +50 bp downstream of the TSS ) as could be clearly aligned by BLAST between the two species . For each instance of a motif found in the D . melanogaster sequences , we extracted the corresponding putatively homologous sites in D . yakuba by sequence coordinates within the 300 bp region . We then calculated divergence at each of the 19 motif positions , counting single-base indels ( ~9%–10% of all changes ) as single events . For each of the 19 motif positions , we used the initial MEME search description of the motif to calculate a “position information” score as 2-Σfilog2 ( fi ) , with fi the frequency of the ith nucleotide found at a position . The position information score corresponds to the summed height of the four letters at a position in the MEME logo , and , ranging between 0 ( for four equally frequent nucleotides ) to 2 ( for a single invariant nucleotide ) gives a sense of the conservation of the position within the motif occurrences . In addition to the position-specific motif divergence , we also calculated overall divergence at positions inside identified motifs and outside identified motifs . We validated a promoter motif using site-directed mutagenesis and transgenic assays . First , we PCR-amplified 766 bp upstream of the testis-specific gene , CG12681 , using forward 5′ CAA ATT ACG TTT CAT TAC GC and reverse 5′ CAA ATT TCC GTA CTT AAT G primers . The amplicon was cloned into TOPO pCR2 . 1 vector ( Life Technologies ) and transformed into frozen competent Top10 cells ( Invitrogen ) . We PCR-screened transformed cells , sequenced clones to check for PCR mutations , and then purified plasmid DNA for use in site-directed mutagenesis . We altered nucleotide states at multiple positions in the wild-type sequence ( see Table 3 ) , using the following primers: B2 forward 5′ GCG GCC ACT GTG GAA AGT GTA ATC GCT GTC AG; B2 reverse 5′ GAT TAC ACT TTC CAA GTG GCC GCA AGA AAA TG; B5 forward 5′ GCG GCC AAG TGG GAA GTG TAA TCG CTG TCA G; B5 reverse 5′ GAT TAC ACT TCC CAC TTG GCC GCA AGA AAA TG; A5 forward 5′ TGT AAG TTT AAA AGT GGT TGC CCA TCC GTG TG; A5 reverse 5′ GCA ACC ACT TTT AAA CTT ACA TTT TCC GTT GG; AB forward 5′ GAC TTG GTT GAG TAC TCA CCG TCA C; AB reverse 5′ GTG ACT GGT GAG TAC TCA ACC AAG TC . The PCR amplicons were digested with DpnI ( NEB ) and transformed into Top10 competent cells by Gibson cloning ( Invitrogen ) . Each plasmid was subsequently opened with NotI ( NEB ) and phosphatased with Fast AP ( Thermoscientific ) , to prevent vector religation . pCMV-sport ( Life Technologies ) was also digested with NotI to obtain the 3 . 4 kb lacZ fragment . lacZ was then ligated into each of five plasmids—four with mutant CG12681 promoters and one with wild-type CG12681 promoter . The pCMV-sport[CG12681-lacZ] plasmids were transformed into chemically competent Top10 cells and verified by restriction digests and sequencing . We next subcloned the CG12681-lacZ sequences into P[acman]-Apr F-2-5-attB vectors ( hereafter , attB [59] , donated by Hugo Bellen [Baylor College of Medicine] and distributed to us by the Drosophila Genome Resource Center ) . We digested each of the five pCMV-sport[CG12681-lacZ] plasmids with SpeI , ScaI , and XhoI , ( NEB ) with the sticky ends filled-in with Klenow; the resulting 4 . 3 kb fragments were ligated into the attB vector previously cut with SpeI and phosphatased with Fast AP . Ligations were electroporated into Epi300 frozen competent cells ( Epicentre ) , clones were verified by restriction digest and sequencing , and the new attB constructs were isolated using an Endo Free Qiagen Maxi kit . The attB constructs were injected into embryos from two stocks , one with an attP landing site on the X chromosome ( genomic coordinate X:5 , 757 , 560 ) and another on 3L ( cytological position 75A10; genomic coordinate 3L:17 , 952 , 108 ) at BestGene ( http://www . thebestgene . com ) . Finally , we confirmed the transformation status and promoter sequences of all transgenic fly lines by a further round of sequencing of the CG12681 promoter . | The evolution of different sex chromosomes ( e . g . , X and Y ) has occurred many times in animals and plants . One consequence of having different chromosome copy numbers between the sexes ( XY males and XX females ) is the evolution of sex chromosome-specific regulation , both in the soma ( i . e . , X chromosome dosage compensation ) and in the male germline ( i . e . , meiotic sex chromosome inactivation ) . Understanding how the X is regulated in the male germline has implications for gene expression , the evolution of sex chromosome-specific gene content , and speciation . Surprisingly , how the X chromosome is regulated in the Drosophila melanogaster male germline remains unclear . We have characterized X suppression , a novel form of X chromosome transcriptional regulation specific to the Drosophila male germline . Our results reveal that transcription of the X is suppressed 2- to 4-fold for endogenous genes . We show that the X chromosome has evolved strong testis-specific promoters via the gene-by-gene recruitment of sequence elements that counteract transcriptional suppression of the X chromosome . These findings reveal a novel form of X chromosome regulation and lead to a new model for the control of gene expression in the Drosophila male germline . | [
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"biology"... | 2016 | Sex Chromosome-wide Transcriptional Suppression and Compensatory Cis-Regulatory Evolution Mediate Gene Expression in the Drosophila Male Germline |
Mutations in the gene encoding transcription factor TFAP2A result in pigmentation anomalies in model organisms and premature hair graying in humans . However , the pleiotropic functions of TFAP2A and its redundantly-acting paralogs have made the precise contribution of TFAP2-type activity to melanocyte differentiation unclear . Defining this contribution may help to explain why TFAP2A expression is reduced in advanced-stage melanoma compared to benign nevi . To identify genes with TFAP2A-dependent expression in melanocytes , we profile zebrafish tissue and mouse melanocytes deficient in Tfap2a , and find that expression of a small subset of genes underlying pigmentation phenotypes is TFAP2A-dependent , including Dct , Mc1r , Mlph , and Pmel . We then conduct TFAP2A ChIP-seq in mouse and human melanocytes and find that a much larger subset of pigmentation genes is associated with active regulatory elements bound by TFAP2A . These elements are also frequently bound by MITF , which is considered the “master regulator” of melanocyte development . For example , the promoter of TRPM1 is bound by both TFAP2A and MITF , and we show that the activity of a minimal TRPM1 promoter is lost upon deletion of the TFAP2A binding sites . However , the expression of Trpm1 is not TFAP2A-dependent , implying that additional TFAP2 paralogs function redundantly to drive melanocyte differentiation , which is consistent with previous results from zebrafish . Paralogs Tfap2a and Tfap2b are both expressed in mouse melanocytes , and we show that mouse embryos with Wnt1-Cre-mediated deletion of Tfap2a and Tfap2b in the neural crest almost completely lack melanocytes but retain neural crest-derived sensory ganglia . These results suggest that TFAP2 paralogs , like MITF , are also necessary for induction of the melanocyte lineage . Finally , we observe a genetic interaction between tfap2a and mitfa in zebrafish , but find that artificially elevating expression of tfap2a does not increase levels of melanin in mitfa hypomorphic or loss-of-function mutants . Collectively , these results show that TFAP2 paralogs , operating alongside lineage-specific transcription factors such as MITF , directly regulate effectors of terminal differentiation in melanocytes . In addition , they suggest that TFAP2A activity , like MITF activity , has the potential to modulate the phenotype of melanoma cells .
Melanocytes are responsible for pigment deposition in skin and hair follicles , and the dysregulation of melanocyte differentiation underlies both pigmentation disorders and melanoma . Because melanocytes are dispensable for life , the melanocyte lineage can also serve as a model for investigation of developmental processes important in all cell types . Many transcription factors and other regulatory molecules that drive melanocyte development have been identified through genetic analyses of patients with congenital pigmentation disorders , including piebaldism ( SNAI2 ) [1] , Waardenburg syndrome types I and III ( PAX3 ) [2] , Waardenburg syndrome type II ( SNAI2 , MITF , SOX10 ) [3–5] , and Waardenburg-Shah syndrome ( EDN3/EDNRB , SOX10 ) [6 , 7] . Epistasis experiments in model organisms have begun to assemble these genes into functional hierarchies , also called gene regulatory networks ( GRNs ) , that govern specific processes in the development of melanocytes from the neural crest . For example , work in mouse and chick indicates that during melanocyte lineage specification , PAX3 and SOX10 activate expression of MITF [8] and FOXD3 represses it [9–11] , while SOX2 and MITF appear to cross-regulate expression of each other [12 , 13] . A recent integrated analysis of ChIP-seq and expression profile data in mouse found that SOX10 directly activates expression of many genes implicated in melanocyte differentiation , and suppresses those that promote pluripotency [14] . Similarly , MITF ChIP-seq and enhancer deletion studies in human cell lines have shown that in addition to its role in melanocyte fate specification , MITF directly stimulates the expression of many genes encoding effectors of melanin synthesis , including Dopachrome Tautomerase ( DCT ) [15 , reviewed in 16 , 17 , 18] . Because mice with loss-of-function mutations in Mitf lack melanocytes , and ectopic expression of MITF activates expression of melanin synthesis genes in heterologous cell types , MITF is considered a “master regulator” of melanocyte development [19–21] . MITF activity has also been described as a rheostat that regulates melanoma phenotype by driving senescence at low levels , an invasive phenotype at mid-levels , and melanocyte proliferation and differentiation at higher levels [22] . Continued exploration of the GRNs controlling melanocyte differentiation will add to the value of the melanocyte as a model cell type , and may also guide the design of differentiation-promoting therapies in melanoma . Mutations in Transcription Factor Activating Enhancer-Binding Protein 2 Alpha ( TFAP2A ) result in pigmentation phenotypes similar to those caused by mutations in established members of the melanocyte differentiation GRN . In humans , a variety of missense mutations in TFAP2A cause branchio-oculo-facial syndrome , which frequently includes premature hair graying due to dysregulation of melanocyte stem cells [23] . Mice with Wnt1-Cre-mediated deletion of Tfap2a in neural crest usually die from exencephaly , but rare surviving animals exhibit a white belly spot analogous to the phenotype of mutants heterozygous for a null allele of Kit [24] , which is thought to be a direct target of TFAP2A [25 , 26] . We also observe a greater-than-additive belly-spot phenotype in Tfap2a and Kit double heterozygous mice , signifying a genetic interaction between these genes ( TW , unpublished observations ) . In zebrafish embryos homozygous for strong loss-of-function alleles of tfap2a , melanocytes are fewer in number and exhibit reduced migration relative to melanocytes in wildtype embryos [27–29] . This phenotype resembles zebrafish kita mutants , and there is also evidence of genetic interaction between tfap2a and kita in zebrafish [29] . However , zebrafish tfap2a mutants also have a phenotype of delayed melanization that is not present in zebrafish kita mutants [27–29] , and we previously showed that tfap2a and its paralog tfap2e are cell-autonomously required for melanocyte differentiation in zebrafish [30] . These phenotypes imply that TFAP2A contributes to the GRN governing melanocyte migration , possibly upstream of KIT , as well as to a GRN governing melanocyte differentiation by mediating expression of unknown targets . The precise contribution of TFAP2A to the melanocyte differentiation GRN has been obscured by pleiotropic functions of TFAP2A and its redundantly-acting paralogs during earlier steps in neural crest development . TFAP2A belongs to a family of five paralogs , TFAP2A-E , of which all but TFAP2D have an identical sequence binding preference [reviewed in 31] . In all species thus far analyzed , TFAP2A and one or more additional TFAP2 paralogs with potential for redundant activity are expressed in the neural plate border , premigratory neural crest , and melanocytes , but the identity of the additional paralogs varies among species . Zebrafish melanocytes express tfap2a , tfap2c , and tfap2e [32] , and embryos depleted of both tfap2a and tfap2e display a greater-than-additive reduction in both melanocyte number and pigmentation compared to embryos depleted of either gene alone [30] . However , it has not yet been possible to examine the consequence of removing all three Tfap2 paralogs in melanocytes due to another example of redundancy , the lack of neural crest in zebrafish depleted of both Tfap2a and Tfap2c [33 , 34] . This is also true in mouse , where Tfap2a and Tfap2b are expressed in early neural crest [35] as well as the melanocyte lineage , resulting in almost complete loss of migrating trunk neural crest prior to specification of the melanocyte lineage in Tfap2a/Tfap2b double mutants [36] . Thus , the specific contributions of these factors to the GRN governing melanocyte differentiation have not been thoroughly evaluated . In this study , we investigate the role of TFAP2A in melanocyte differentiation , utilizing the different advantages of zebrafish , mouse , and cell line models . While pigmentation is clearly reduced in zebrafish tfap2a mutants , mitfa expression levels appear to be normal in the remaining melanocytes [30] . Likewise , it was reported that in 501mel melanoma cells depleted of TFAP2A , the expression levels of MITF were unchanged compared to control cells , while expression of TYR , encoding the rate limiting enzyme of melanin synthesis , was decreased [37] . Pigmentation phenotypes in zebrafish tfap2a mutants are therefore unlikely to be an effect of altered Mitf expression levels . However , MITF activity is regulated by post-translational modifications [38–40] , and the expression of enzymes mediating these modifications may depend on TFAP2A . Alternatively , TFAP2A and MITF could directly co-regulate expression of melanocyte differentiation effectors . In support of this model , there is evidence that both proteins regulate expression of CDKN1A/p21 [41 , 42] and IRF4 [37] . Furthermore , a recent integrative analysis of chromatin mark data in 111 cell types indicated that enhancers active in melanocytes are enriched in the TFAP2A binding site [43] , although other , non-TFAP2 family transcription factors may bind similar sites . Co-occupancy of enhancers by MITF and TFAP2A was also reported in human melanoma cell lines [44] . However , melanomas often have reduced TFAP2A expression , accompanied by methylation of the TFAP2A promoter , and so are not ideal systems to study the role of TFAP2A in normal melanocyte development and function [26 , 45 , 46] . Here we examine the relationship between TFAP2A and MITF in the context of melanocytes using a combination of molecular , genetic , and bioinformatic analyses in human , mouse , and zebrafish systems . The results confirm that TFAP2A frequently co-occupies regulatory elements with MITF , identify genes underlying pigmentation phenotypes in model organisms and patients with TFAP2A mutations , and reveal TFAP2A as a candidate locus to modify diseases associated with MITF , including melanoma .
Zebrafish homozygous for a strong loss-of-function mutation in tfap2a ( i . e . , lockjaw allele , hereafter tfap2a-/- mutants ) lack detectable anti-TFAP2A immunoreactivity [28 , 47] and exhibit approximately one-third reduction of embryonic melanocytes , impaired melanocyte migration , and delayed melanization relative to wildtype and tfap2a+/- siblings ( Fig 1A and 1B ) [27 , 30 , 48] . In order to better characterize the melanization phenotype , we compared tfap2a-/- mutants to tfap2a+/- siblings over a ten-hour period , starting with the first emergence of melanocytes around 28 hours post fertilization ( hpf ) ( S1 Fig ) . While melanocytes are initially pale in both genotypes , individual melanocytes in the tfap2a+/- siblings pigmented more quickly than individual melanocytes in tfap2a-/- mutants . This supports earlier evidence that , in addition to reduced numbers and migration , melanocytes in tfap2a-/- mutants have defects in differentiation [30] . To extend previous analyses of gene expression in the melanocytes of tfap2a-/- mutants [30 , 34 , 48 , 49] , we generated expression profiles of tfap2a-/- mutant zebrafish and their wildtype siblings at 36 hpf . Prior to harvesting RNA , we decapitated animals to eliminate the retinal pigmented epithelium , which appears to be normally pigmented in tfap2a-/- mutants ( Fig 1A and 1B ) . Generating cDNA and probing microarrays revealed that 2 , 337 unique Ensembl transcripts ( corresponding to 2 , 324 genes ) are differentially expressed in the trunks of tfap2a-/- mutants versus siblings ( FDR p<0 . 05 ) . Of these , the expression levels of 124 transcripts in tfap2a-/- mutants are decreased to ≤0 . 7-fold of wildtype levels and 358 transcripts are increased to ≥1 . 25-fold ( expression profile in S1 Table ) . We referred to zebrafish gene expression patterns at an online database ( ZFIN ) to identify 19 genes annotated as “melanoblast , ” “melanocyte , ” or “pigment cell” [50] . An additional gene , slc24a4a , is annotated as “neural crest , ” but is expressed in a pattern resembling that of dct [51] . Most of these 20 genes encode proteins that have known roles in melanocyte differentiation ( Fig 1C , S2 Table ) . In tfap2a-/- mutants , 11 of these genes were expressed between 0 . 2- to 0 . 55-fold of wildtype levels , a much greater fraction of melanocyte genes than expected by chance ( hypergeometric test , p<0 . 0001 ) , and were therefore considered Tfap2a-dependent ( Fig 1C ) . The levels of several others , including trpm1a , were not significantly changed or were reduced by no more than expected from the one-third decrease in melanocyte cell number , and we considered these to be Tfap2a-independent . qRT-PCR validation of microarray results confirmed that expression of multiple pigmentation genes depends on Tfap2a in zebrafish ( Fig 1D ) . Because TFAP2A is expressed in multiple tissues , including the skin where melanocytes reside , the Tfap2a-dependent gene expression in zebrafish melanocytes could reflect an indirect requirement for Tfap2a rather than a cell-autonomous one . To clarify this issue , we conducted a microarray expression profile of immortalized mouse melanocytes ( melan-a cells ) [52] depleted of Tfap2a . We identified two independent siRNAs that reduced expression of Tfap2a to below 0 . 25-fold of the level in cells transfected with control siRNAs . Comparison of microarray profiles showed that the expression levels of 30 genes were consistently decreased ( ≤0 . 7-fold ) and the expression levels of 38 genes were consistently increased ( ≥1 . 4-fold ) in cells transfected with either Tfap2a-targeted siRNA relative to control siRNAs ( S3 Table ) . Among the 30 genes with decreased expression , Mc1r and Slc24a4 are implicated in pigmentation . qRT-PCR verified significant reduction of these two genes , as well as Dct , Mlph , and Pmel , which narrowly missed the threshold cut-off in the array analysis ( Fig 1E ) . Of note , several of the other genes with decreased expression upon knockdown of Tfap2a have been reported in the literature as activated ( Aldh1a3 , Igf2bp1 , Ephb2 , Pbk ) or downregulated ( Qpct , Wfdc1 ) in melanoma [53–59] . In summary , expression of a subset of melanocyte differentiation genes , including Slc24a4 , Mc1r , Mlph , Pmel , and Dct , was TFAP2A-dependent in both mouse melanocytes and zebrafish trunks , while expression of Mitf orthologs was TFAP2A-independent . Certain pigmentation genes , including oca2 and slc45a2 , appeared Tfap2a-dependent in zebrafish but not in mouse melanocytes , perhaps reflecting a more thorough depletion of Tfap2a in the former , or potentially distinct homeostatic mechanisms induced by siRNA versus gene mutation . Nonetheless , these results indicate that TFAP2A , whether directly or indirectly , regulates the expression of genes involved in melanocyte differentiation . To determine the direct transcriptional targets of TFAP2A in melanocytes , we conducted chromatin immunoprecipitation followed by high-throughput sequencing ( ChIP-seq ) in mouse melan-a cells ( two replicates ) and in human primary melanocytes ( one replicate ) . Anti-TFAP2A immunoreactivity is strong and concentrated in the nucleus of human primary melanocytes ( S2A Fig ) but appears weaker and more diffuse in several melanoma cell lines ( S2B–S2E Fig ) , consistent with a reduction of TFAP2A RNA levels in melanoma [45] . ChIP-seq detected 16 , 305 TFAP2A-bound loci in mouse melanocytes , and 13 , 690 TFAP2A-bound loci in human melanocytes ( hereafter , TFAP2A peaks ) . De novo motif analysis [60] of sequences precipitated by the anti-TFAP2A antibody from mouse or human melanocytes revealed that a known TFAP2A binding site ( MA0003 . 2 , JASPAR ) is strongly enriched and tends to be centrally located within peaks ( S3A and S3C Fig ) . Anti-TFAP2A ChIP followed by quantitative PCR ( ChIP-qPCR ) confirmed TFAP2A binding enrichment for selected peaks at genes of interest in mouse or human melanocytes , as well as in the M21 melanoma cell line , which has detectable TFAP2A expression ( S3B , S3D and S3E Fig ) . Published comparisons of ChIP-seq results for a given transcription factor in mouse and human melanocytes have suggested rapid divergence of binding events during evolution [61–63] . Consistent with these studies , we found that only about 11% of TFAP2A peaks in human primary melanocytes coincide with the orthologs of TFAP2A peaks lifted over from mouse ( S4 Table ) , and conversely , about 9% of the TFAP2A peaks identified in mouse melanocytes coincide with peaks lifted over from human ( S5 Table ) . TFAP2A peaks shared between species are enriched near promoters ( S6 Table ) . In contrast to the modest concordance of peaks and orthologous sequences , the concordance of genes associated with TFAP2A peaks in the two species is very high , as shown below . In both mouse and human melanocytes , TFAP2A peaks are more likely to be found within genes , including introns , than in intergenic regions ( Fig 2A , S4A Fig ) . Overall , genes with higher expression in melanocytes are enriched for promoter-proximal peaks of TFAP2A ( mouse GSE87051 , human GSM958174 [64] ) ( Fig 2B , S4B Fig ) . To assess patterns of TFAP2A binding at enhancers , we compared the TFAP2A ChIP-seq data from mouse melan-a cells to a published profile of candidate enhancers also in these cells , which were defined by H3K4me1 peaks flanking a p300 peak [65] . Remarkably , 70% ( 1 , 752 of 2 , 489 ) of enhancer elements marked in this way overlap with a TFAP2A peak ( hypergeometric test , p<0 . 0001 ) . Conversely , about 10% of TFAP2A peaks are fully marked as enhancers , while another 35% are partially marked ( i . e . , either overlapping p300 or flanked by at least one H3K4me1 peak ) . Fig 2C illustrates this pattern upstream of the melanocyte differentiation gene Slc45a2 , as well as a TFAP2A peak at the promoter ( additional examples in S5A–S5F Fig ) . In agreement with estimates that the median distance between promoters and cis-acting enhancers is 15kb , genes with high expression are enriched for a TFAP2A peak overlapping the active enhancer signature at a distance of 5–50kb from the TSS ( Fig 2D ) [66] . However , the promoter-proximal TFAP2A peaks are just as likely to possess a TFAP2A binding site as the promoter-distal peaks ( about 50% in both cases ) . This is in contrast to observations from mouse chondrocytes , where promoter-distal SOX9 peaks are more likely to contain a SOX9 binding site than promoter-proximal ones [67] . Altogether , the binding profile of TFAP2A indicates that it acts at both enhancers and promoters of melanocyte genes . Because TFAP2A is widely expressed , the extent to which TFAP2A peaks would be melanocyte-specific was unclear . We found that about 15% of TFAP2A peaks in mouse melanocytes overlap those reported in either primary mouse kidney or primary mouse epididymis cells ( but not both ) , and 19% are shared by all three cell types [68] ( Fig 2E ) . MEME-ChIP analysis [69] showed that melanocyte-unique TFAP2A peaks are enriched for the binding motifs of transcription factors active in melanocytes , including SOX10 , FOS/JUN , TEAD , and the M-box binding site for MITF [70] ( Fig 2F ) . These transcription factors are also highly enriched in candidate melanocyte enhancers [65] . Kidney-unique and epididymis-unique peaks showed less significant or no enrichment for these binding motifs , although the E-box , recognized by MITF and many other bHLHZip transcription factors , was enriched in all three cell types . The enrichment of binding sites for melanocyte transcription factors like SOX10 and MITF in melanocyte-unique peaks suggests that TFAP2A binds cell-type specific loci in addition to generic ones; binding to any particular locus is presumably a function of cofactor availability and chromatin accessibility [reviewed in 71] . We used Genomic Regions Enrichment of Annotations Tool ( GREAT ) [72] to identify genes associated with TFAP2A peaks in mouse and human melanocytes , with an assignment rule of basal promoter plus 100kb distal , and found that these genes are enriched for ontology terms relevant to melanocyte differentiation , including “pigmentation” , “melanosome” , and “melanoma” ( S6A and S6B Fig ) . However , TFAP2A can both activate and repress gene expression [73] . To find genes likely to be activated by TFAP2A , we integrated our TFAP2A ChIP-seq with H3K27ac ChIP-seq data from human melanocytes ( GSM1127072 [64] ) and mouse melanocytes [14] , as H3K27ac marks active regulatory elements [reviewed in 74 , 75] . We found that 55% of TFAP2A peaks in human melanocytes and 58% of TFAP2A peaks in mouse melanocytes either overlap H3K27ac peaks or are flanked by H3K27ac peaks , and we refer to them hereafter as active TFAP2A peaks ( human Fig 3A , mouse S6C Fig , S7 Table ) . Analysis with GREAT revealed that genes associated with active TFAP2A peaks include 15 of the 30 genes with significantly decreased expression in Tfap2a-depleted mouse melanocytes , among them Mc1r and Slc24a4 ( S8 Table ) . Similarly , orthologs of eight out of ten Tfap2a-dependent melanocyte genes in zebrafish tfap2a-/- mutants ( excepting slc24a5 and tyr ) are associated with active TFAP2A peaks in mouse or human melanocytes . These genes are candidates to be direct transcriptional targets of TFAP2A , suggesting that the phenotype of delayed melanization in zebrafish tfap2a-/- mutants can be explained in part by a direct effect on certain melanocyte differentiation effector genes ( e . g . , dct , mlpha , mc1r , and pmela ) , and indirect regulation of others ( e . g . , slc24a5 and tyr ) . The presence of TFAP2A peaks at a majority of active melanocyte enhancers , as well as the enrichment of the MITF binding motif in TFAP2A peaks , implies that TFAP2A binds many of the same regulatory elements as MITF in melanocytes . To evaluate overlap between TFAP2A and MITF across the genome , we compared our human TFAP2A ChIP-seq results to a set of 16 , 572 MITF ChIP-seq peaks also from human primary melanocytes [18] . 5 , 367 ( 39% ) of TFAP2A peaks are shared with MITF , overlapping by at least one base pair . Integrating MITF and H3K27ac ChIP-seq data yielded 61% of MITF peaks ( Fig 3B ) and 76% of TFAP2A/MITF shared peaks ( Fig 3C ) that overlap , or lie between , H3K27ac peaks and are thus considered to be active . Using GREAT , we found that about 77% of the genes associated with active TFAP2A peaks are also associated with active MITF peaks , a highly significant overlap ( hypergeometric test , p<0 . 0001 ) ( Fig 3D ) . Furthermore , 79% of these genes are associated with active TFAP2A/MITF shared peaks , suggesting that TFAP2A and MITF are co-bound at many , but not all , shared targets . GO term analysis [76 , 77] revealed that the subset of genes associated with both TFAP2A and MITF peaks are enriched for the terms “melanosome” and “pigment granule” ( p = 9 . 08E-07 ) , as well as “DNA repair” ( p = 5 . 98E-08 ) , “mitotic cell cycle process” ( p = 5 . 59E-09 ) , “regulation of cell proliferation” ( p = 2 . 40E-03 ) , and “regulation of cell differentiation” ( p = 2 . 60E-03 ) ( all p-values Bonferroni corrected , S9 Table ) . This supports a regulatory role for TFAP2A not only in differentiation , but across other categories of genes proposed to be regulated by MITF in melanocytes and melanoma , as with the MITF rheostat [22] . To assess the overlap between targets of TFAP2A and MITF with respect to pigmentation , we focused on a list of 170 genes that cause coat color phenotypes in mice [78] , adding TRPM1 based on its role in the coat color phenotype of appaloosa horses [79–82] . Orthologs of 97 genes on this list are associated with active TFAP2A peaks in human melanocytes and/or active TFAP2A peaks in mouse melanocytes ( Table 1 , asterisks ) . Of these , 72 genes are also associated with active MITF peaks ( Table 1 ) , 46 being active shared TFAP2A/MITF peaks ( Table 1 , bold ) . We then examined overlap of MITF and TFAP2A binding at clusters of closely spaced enhancers , sometimes called stretch or super-enhancers ( SEs ) [83] , that are linked to cell type-specific gene expression [84 , 85] . Following published methods , we used H3K27ac data to identify 652 SEs in human primary melanocytes [85] ( S7 Fig ) . Of these , 530 ( 81% ) are bound by both MITF and TFAP2A ( Fig 3E , S10 Table ) . Interestingly , genes involved in melanocyte differentiation , including those encoding proteins expressed in the melanosome , are associated with SEs bound by MITF only ( e . g . TYR , MLANA , SLC24A5 , DCT ) and SEs bound by both MITF and TFAP2A ( MLPH , OCA2 , TRPM1 , MC1R ) . Exceptions to this pattern include KIT , which is associated with one SE bound solely by TFAP2A and one SE bound solely by MITF , and TYRP1 , which is associated with an SE bound by neither ( Fig 3E ) . Taken together , these results show that TFAP2A and MITF bind regulatory elements associated with melanocyte differentiation effectors . Notably , 409 ( 63% ) of all SEs are bound by TFAP2A peaks that overlap with MITF peaks . It remains to be determined whether TFAP2A and MITF exhibit cooperative binding at these loci . While several of the pigmentation genes associated with active TFAP2A and MITF peaks showed TFAP2A-dependent expression in both zebrafish and mouse , we also noted many apparently TFAP2A-independent genes on this list . One possible explanation is that the presence of a TFAP2A peak does not signify contribution of TFAP2A to the activity of a given regulatory element . Alternatively , activity of a redundantly-expressed TFAP2 paralog may compensate for the loss of TFAP2A . To rule out the first possibility , we focused on the gene TRPM1 , which has a promoter-proximal TFAP2A peak in both mouse and human melanocytes but is expressed at high levels in melanocytes in a TFAP2A-independent manner . In addition , expression of TRPM1 is a sensitive readout of MITF activity levels [79] , and a minimal TRPM1 promoter , which has an MITF peak in melanoma cells [17] and primary melanocytes [18] , has activity in melanoma cells that is lost upon deletion of the MITF binding sites [86] . We engineered the TRPM1 promoter into a vector suitable for quantitative luciferase reporter assays and created variants with mutations in either the E-Box MITF binding site shown previously to be most important for promoter activity ( ΔE1 ) [86] , or four predicted TFAP2 binding sites ( ΔAP2 ) ( Fig 3F ) . These constructs , together with a control vector , were transfected into M21 melanoma cells , which express TFAP2A ( S2C Fig ) . The intact TRPM1 promoter drove much higher luciferase expression than the empty reporter vector , while the ΔE1 promoter variant drove about 50% of intact , and the ΔAP2 variant drove about 10% of intact ( p = 0 . 01 ) ( Fig 3G ) . These results show that TFAP2A directly activates the TRPM1 promoter , supporting the hypothesis that other TFAP2 paralogs are able to compensate for the absence of TFAP2A at certain melanocyte genes . Testing whether TFAP2 paralogs function redundantly in melanocyte development requires simultaneous depletion of all such paralogs expressed in melanocytes . In mouse melanocytes , Tfap2a and Tfap2b have the highest and second highest expression , respectively , while Tfap2c and Tfap2e are undetectable [87 , 88] . To determine whether Tfap2 paralogs function redundantly in murine melanocyte development , we generated double conditional mutants ( DCM ) using a previously published Wnt1-Cre transgenic line [89] and conditional alleles of Tfap2a [24] and Tfap2b ( EVO and TW , in preparation ) . We then utilized two approaches to assess melanocyte development in DCM embryos , corresponding single conditional mutant ( SCM ) embryos , and control embryos . First , embryos in which the Rosa26-reporter ( r26r ) -allele [90] was also incorporated were dissected at embryonic day 12 . 0 ( E12 . 0 ) and subsequently stained for β-galactosidase ( β-gal ) activity . The r26r-allele used in combination with the Wnt1-Cre transgene results in β-gal positive staining of premigratory neural crest cells and subsequent derivatives ( Fig 4A–4D , S8A–S8D Fig ) . β-gal-positive melanoblasts and corresponding melanocytes migrate ventrolaterally from the dorsal neural tube and can be identified by their position just below the developing surface ectoderm , most easily observed dorsal to the hindlimb . Examination of control ( Fig 4A ) , Tfap2a SCM ( Fig 4B ) , and Tfap2b SCM ( Fig 4C ) embryos revealed roughly equivalent numbers of stained cells with a similar distribution . In contrast , Tfap2a/Tfap2b DCM embryos have many fewer β-gal-positive cells in this location ( Fig 4D ) . Second , embryos were processed for in situ hybridization with Pmel [91] and Dct [92 , 93] riboprobes , detecting melanoblasts and differentiated melanocytes ( Fig 4E–4L ) . As with the r26r experiments , this staining labeled similar numbers of Pmel-positive and Dct-positive cells in control ( Fig 4E and 4I ) , Tfap2a SCM ( Fig 4F and 4J ) , and Tfap2b SCM ( Fig 4G and 4K ) embryos , but far fewer cells in Tfap2a/Tfap2b DCM embryos ( Fig 4H and 4L ) . The absence of Pmel-positive and Dct-positive melanoblasts in DCMs was evident from the time these cells emerged in control embryos at E10 . 5 and E11 . 5 , suggesting that the reduced melanoblast number in DCMs is not the result of impaired melanoblast migration ( S8E–S8L Fig ) . Because TFAP2 paralogs have been shown to function during the early stages of neural crest induction [33 , 34] , we next tested whether the observed reduction in melanocytes could be explained by a disruption in this step . Both lineage tracing with the r26r-reporter line ( S9A–S9F Fig ) and in situ hybridization with a Sox10 riboprobe at E9 . 5 ( S9G and S9H Fig ) revealed relatively normal neural crest induction in DCMs , as in controls . Consistent with this observation , α-neurofilament immunostaining ( Fig 4M and 4N ) and lineage tracing ( Fig 4O and 4P , S10A–S10D Fig ) identified the initial formation of an alternate trunk neural crest derivative , dorsal root ganglia ( DRG ) , in both DCMs and controls . However , similar to the melanocyte lineage , the neural crest-derived enteric nervous system ( ENS ) was disrupted in Tfap2a SCM embryos and completely failed to populate the gastrointestinal tract of DCM embryos ( S10E–S10L Fig ) . Broadly , these analyses suggest that in mouse embryos , paralogous proteins TFAP2A and TFAP2B act redundantly subsequent to neural crest induction within distinct neural crest lineages . The virtual absence of melanoblasts in Tfap2a/Tfap2b DCM embryos implies that they contribute to specification and differentiation of the melanocyte lineage , similar to the functions of MITF . Given the widespread co-occupancy of regulatory elements by TFAP2A and MITF , we predicted that mitfa;tfap2a double mutant zebrafish would have a greater-than-additive melanocyte phenotype consistent with synergistic interaction between these genes . To test this , we used the hypomorphic allele mitfaz25 to reduce Mitfa levels without eliminating the melanocyte lineage , as occurs with total loss-of-function alleles such as mitfaw2 [94 , 95] . Compared to wildtype embryos at 72 hpf ( Fig 5A ) , mitfaz25/z25 homozygotes have fewer and less dendritic melanocytes ( Fig 5B ) . Melanocytes are further reduced , punctate , and noticeably paler in mitfaw2/z25 trans-heterozygous embryos ( Fig 5C ) . Incrosses of mitfaw2/z25;tfap2a+/- double heterozygous adults and mitfa+/+;tfap2a+/- single heterozygous adults yielded various combinations of mitfa;tfap2a genotypes . Embryos were sorted into phenotypic bins at 72 hpf , photographed individually , and genotyped for both mitfaz25 ( when appropriate ) and tfap2a . Relative to wildtype embryos ( Fig 5A ) , mitfa+/+;tfap2a-/- homozygous mutants exhibited a clear reduction of melanocytes in the ventral stripe caudal to the tail , reflecting decreased melanocyte migration and/or proliferation ( Fig 5G ) . However , mitfa+/+;tfap2a+/- heterozygous mutants could not be distinguished from wildtypes ( compare Fig 5A and 5D ) . Quantification of ventral tail melanocytes ( count area indicated by brackets in Fig 5A–5I ) revealed that there is some variation within each genotype , but we detected no genotype/phenotype correlation between tfap2a+/+ and tfap2a+/- embryos ( Fig 5J , one-way ANOVA ) . In contrast , both the mitfaz25/z25 ( Fig 5B , 5E and 5H ) and mitfaw2/z25 ( Fig 5C , 5F and 5I ) backgrounds had three distinguishable phenotypic groups corresponding to the tfap2a genotype , with tfap2a+/- embryos showing significant differences in the number of ventral tail melanocytes compared to both tfap2a+/+ and tfap2a-/- embryos ( Fig 5K , one-way ANOVA ) . Thus , the phenotype of double mutants appears to be more severe than the combination of the phenotypes in single mutants . The biochemical underpinning of this genetic interaction is unknown; Mitfa and Tfap2a may interact synergistically at one or more regulatory elements , or Mitfa may regulate tfap2a expression in melanocytes . Genetic interaction between tfap2a and mitfa supports the idea that the factors encoded by these genes regulate shared targets in melanocytes , possibly within single or converging pathways . Previously , we found that elevating expression of mitfa ( under the sox10 promoter ) partially compensates for the reduction of Tfap2 in tfap2a/tfap2e-depleted zebrafish embryos [30] . Thus , we next investigated whether the reciprocal experiment , artificially elevating expression of tfap2a , could rescue melanocyte development in the absence or reduction of Mitfa . To test this , we engineered the tfap2a cDNA to encode 6 Myc epitopes at the carboxy terminus . To confirm that the epitope-tagged Tfap2a was still functional , we injected tfap2a-Myc mRNA into embryos depleted of tfap2a and tfap2c and observed differentiated melanocytes , which are otherwise completely absent from such animals [33] . We then fused tfap2a-Myc cDNA downstream of the mitfa promoter , which is active in melanocytes ( mitfa promoter described in [96] ) , and injected the mitfa:tfap2a-Myc plasmid into embryos derived from an incross of mitfaw2/z25 adults . At 48 hpf , embryos were sorted into three groups based on the mitfa mutant phenotype , fixed , and subsequently processed for anti-Myc immunoreactivity . Ten plasmid-injected embryos and ten uninjected control embryos were documented in each group . We detected brightly-labeled cells , including several melanocytes , in both mitfaz25/z25 ( Fig 6A and 6B ) and mitfaw2/z25 ( Fig 6C and 6D ) plasmid-injected embryos , whereas uninjected controls had no labeled cells . However , the anti-Myc immunoreactive melanocytes were phenotypically indistinguishable from neighboring unlabeled melanocytes by morphology , dendricity , or pigmentation ( Fig 6B and 6D , arrows ) . The mitfaw2/w2 plasmid-injected embryos had similar numbers of anti-Myc immunoreactive cells to the other genotypes , but none showed any hint of pigmentation ( Fig 6E and 6F ) . We did observe a highly dendritic but wholly unmelanized cell , which is likely to be a xanthophore ( Fig 6F , arrow ) . In summary , elevating tfap2a expression under the mitfa promoter was not sufficient to rescue melanocytes in mitfaw2/w2 null mutants , nor did it improve the quality or pigmentation of melanocytes in mitfaz25/z25 and mitfaw2/z25 mutants . We conclude that , despite regulating many of the same targets , Tfap2a is unable to replace Mitfa in the melanocyte lineage , at least at the dose of over-expression tested here .
The current work presents an explanation for the basis of pigmentation phenotypes in zebrafish and mouse Tfap2a mutants , suggests that redundant activity of TFAP2 paralogs is responsible for the relative mildness of these phenotypes , and reveals a previously unappreciated role for TFAP2 alongside MITF in melanocyte differentiation . Microarray analysis on the trunks of zebrafish tfap2a-/- mutants showed that several genes with Tfap2a-dependent expression in vivo are known to be important for melanization of embryonic melanophores ( oca2 [97] , tyr [98] , and slc45a2/albino [99] ) . The phenotype of delayed melanization in these mutants is plausibly explained by reduction of these genes , as well as others that may have escaped detection due to Tfap2a-dependent expression in melanocytes but not in other cell types ( one example of this is kita [27 , 29] ) . Analysis of mouse melanocytes depleted of Tfap2a revealed an overlapping but shorter list of TFAP2A-dependent genes , potentially due to incomplete Tfap2a knockdown in these cells . Species dependent differences are also possible . For example , expression of Dct , but not of Irf4 or Tyr , was TFAP2A-dependent in mouse melanocytes , while the opposite trend was seen in the human 501mel cell line [37] . TFAP2A ChIP-seq results from mouse and human melanocytes integrated with H3K27ac ChIP-seq , marking active regulatory elements , revealed that the majority of TFAP2A-dependent pigmentation genes were direct transcriptional targets of TFAP2A . Indeed , far more genes , including most of those mutated in mice with coat color phenotypes , were associated with TFAP2A-bound active regulatory elements than were found to have TFAP2A-dependent expression ( at the level of detection of our assays ) . Three results indicate that compensation by other TFAP2 paralogs is the most likely explanation for why more genes do not appear to be TFAP2A-dependent . First , deletion of TFAP2 binding sites reduced the promoter activity of a gene that was relatively unaffected by loss of TFAP2A in the expression analyses . Second , depletion of tfap2e in zebrafish delays melanocyte differentiation , but only in the context of tfap2a-/- mutants [30] , suggesting that these paralogs are at least partially redundant in function . Third , we find here that in the mouse embryo , neural crest-specific deletion of either Tfap2a or Tfap2b alone does not greatly impact embryonic development of the melanocyte lineages , but the combined knockout of both genes causes a significant loss of melanocytes . Thus , TFAP2 paralogs promote induction of the neural crest lineage and subsequently promote differentiation of one of its derivatives; they have a similar feed-forward quality in epidermis [100] . It is important to note the possibility that TFAP2 paralogs act throughout the specification , proliferation , and differentiation of both neural crest and melanocyte lineages such that disruption at any of these steps ultimately results in a melanocyte phenotype . For example , almost complete loss of melanoblasts in Tfap2a/Tfap2b DCM mice could reflect a requirement for TFAP2 in neural crest survival or lineage specification of certain derivatives . Similarly , the genetic interaction between mitfa and tfap2a in zebrafish appears to be primarily due to reduced cell number , as well as defects in melanoblast migration . While further study will be required to uncouple these various functions of TFAP2 paralogs at each step of melanocyte development , the results described here strongly support a role for TFAP2A in the terminal differentiation of melanocytes . Overall , our findings suggest that TFAP2A , acting in partial redundancy with other TFAP2 paralogs , joins MITF , SOX10 , YY1 , LEF1 , and IRF4 in directly regulating the expression of melanocyte differentiation effector genes [20 , 37 , 101] . We observed widespread co-occupancy of TFAP2A and MITF at active regulatory elements , but it is unknown whether the two transcription factors bind such elements cooperatively . In support of this possibility , we observed a genetic interaction between mitfa and tfap2a affecting melanocyte development in zebrafish . However , an interaction would also be expected if Tfap2a and Mitfa act in a single pathway . Although mitfa expression in melanocytes is not strongly Tfap2a-dependent , it is possible that expression of tfap2a in melanocytes is Mitfa-dependent , as levels of TFAP2A protein were reduced in 501mel cells depleted of MITF with an shRNA [37] . In a published mass-spectrometric analysis of proteins that immunoprecipitate with MITF , TFAP2A peptides were not identified [44] . However , another similar experiment did identify low levels of TFAP2A peptides , although TFAP2A did not detectably co-immunoprecipitate with an epitope-tagged MITF ( J . P . Lambert , A . C . Gingras , personal communication ) . The strength and importance of any physical interaction among TFAP2A , MITF , SOX10 , and other transcription factors bound at regulatory elements active in melanocytes requires further investigation . There is evidence that TFAP2A serves as a pioneer transcription factor for androgen receptor in epididymis cells [68] , and as TFAP2A expression precedes MITF expression in the melanocyte lineage , it is conceivable that TFAP2A plays a similar role for MITF . Conversely , the inability of Tfap2a to substitute for loss of Mitfa in zebrafish , at least at the doses tested here , is consistent with MITF serving as a pioneer factor for TFAP2A . It is also possible that TFAP2A and MITF bind independently , but nonetheless have a cooperative effect on gene expression , as indicated by in vitro tests of an intronic enhancer of the IRF4 gene [37] . Analysis of TFAP2A chromatin binding in cells depleted of MITF , and of MITF chromatin binding in cells depleted of relevant TFAP2 paralogs , might address whether either protein is required to make the chromatin accessible for the other . In metastatic melanoma , the levels of MITF activity have been proposed to control the cellular phenotype: high levels promote melanocyte proliferation and differentiation , while lower levels confer an invasive state [22 , 102] . It is notable that TFAP2A levels are decreased in advanced-stage melanoma tumors versus earlier stage melanoma and nevi , whereas MITF expression levels are relatively constant ( data from The Cancer Genome Atlas [46] ) . Furthermore , elevating levels of TFAP2A in A375SM cells was reported to inhibit tumorigenicity and metastatic potential in nude mice [103] . Based on this evidence , it is possible that the level of MITF activity is adjusted through loss or gain of an essential collaborator , TFAP2A ( and perhaps its paralogs ) . Here , we find that TFAP2A peaks are associated with many genes encoding regulators not only of melanocyte differentiation , but also of other cellular phenotypes purported to be governed by MITF , such as growth and senescence . The melanoma subtype that is most difficult to target therapeutically , and which is thought to depend on a relatively low level of MITF activity , has stem cell qualities , an invasive phenotype , and an expression profile resembling that of neural crest [104] . Thus , early requirements for Tfap2a and its paralog Tfap2c observed in zebrafish neural crest induction [33 , 34] may suggest a role for TFAP2 in this invasive subtype of melanoma as well . Further investigation will be necessary to determine the potential tumor-promoting or tumor-inhibiting consequences of TFAP2A expression ( or activity ) levels in melanoma .
The ChIP-seq Tool Set in Galaxy was used for all peak overlap analyses [107] . For comparison of human ChIP-seq peaks to gene expression , we used a published RNA-seq expression profile of human penis foreskin melanocytes from the Roadmap Epigenomics Project ( GEO accession number , GSM958174 ) [64] . Motif enrichment analysis was carried out using the MEME-ChIP suite [108] , including CentriMo [60] , MEME-ChIP [69] , and AME [109] tools . For gene set enrichment analysis , we used the Genomic Regions Enrichment of Annotations Tool ( GREAT ) , with the association rule basal plus extension , proximal: 5 kb upstream , 1 kb downstream , plus distal: up to 100 kb [72] . ChIP-seq read density clustering analysis and quantitative comparisons were performed using k-means linear enrichment cluster function in seqMINER with the following parameters: window size = -5K to +5K , read extension = 200bp , seed = 12 [110] ( http://bips . u-strasbg . fr/ ) . The Panther Classification System was used for GO term enrichment analysis on gene lists [76 , 77] . RNA sequencing ( RNA-seq ) libraries were prepared with the TrueSeq stranded mRNA kit ( Illumina ) and sequenced on the Illumina HiSeq 2000 platform . The ten 5’-most bases were trimmed from all of the raw RNA-seq reads . Reads were aligned to the mouse reference genome sequence ( mm9 ) using the STAR alignment software ( v . 2 . 3 . 0e ) . RNA-seq reads derived from rRNAs were removed using the split_bam . py script available in RSeQC ( v . 2 . 3 . 7 ) , using genomic locations of known rDNAs that were downloaded from UCSC . Counts for RNA-seq reads mapping to Ensembl-annotated transcripts ( release 67 ) were calculated using the htseq-count software ( v . 0 . 5 . 3p3 ) . These raw RNA-seq counts were used for differential gene expression analysis that was performed using DESeq2 ( v . 1 . 10 . 1 ) . The following versions of the TRPM1 promoter sequence ( 748 bp ) were obtained as double stranded gBlocks gene fragments from IDT: intact sequence , ΔAP2A with mutations in four TFAP2A binding sites , and ΔE1 with a mutation in the main MITF binding site . The consensus TFAP2A binding site GCCNNNGG was disrupted by changing the two underlined bases to T , whereas the E1 MITF site was changed as previously published by [86] . Fragments were cloned into a Tol2-cfos-FFluc vector via Gibson assembly and confirmed with Sanger sequencing . M21 melanoma cells were grown to 70–90% confluency in a 24-well culture plate . In each well , the reporter plasmid ( 1μg ) and a β-galactosidase plasmid ( 100ng ) were transfected using Lipofectamine 3000 ( Life Technologies ) . Approximately 48 hours after transfection , luciferase assays were conducted using the Dual-Light System from Applied Biosystems , and 20/20n Luminometer ( Turner Biosystems , Sunnyvale , CA ) according to the manufacturer protocols . Briefly , cells were washed with cold PBS and incubated in 40 μL lysis solution on a shaker for 15 minutes . Cell lysates were transferred to tubes and centrifuged at 12000 rpm for 2 minutes at 4°C , and supernatant was transferred to a clean tube . 10 μL of cell lysate was added to 25 μL of Buffer A and placed in the luminometer , where the injector adds 100 μL Buffer B/Galacton-Plus substrate and reads the signal after 1 second . Samples were incubated in the dark for 30 minutes before injection of 100 μL Accelerator-II and measurement of the β-gal signal after 1 second . For each version of the TRPM1 promoter element , transfection was carried out in triplicate . Firefly luciferase reads from each sample were normalized to the respective β-gal reads , and an average signal was calculated within groups . Experiments utilizing mice in this study were 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 Colorado Denver . Noon on the day a copulatory plug was present was denoted as embryonic day 0 . 5 . Mice used in this study included males that were heterozygous for a Tfap2a-null allele [113] , heterozygous for a newly generated Tfap2b-null allele ( EVO/TW , in preparation ) , and hemizygous for the Wnt1-Cre transgene [89] ( Tfap2anull/wt;Tfap2bnull/wt;Wnt1-Cre ) . These males were crossed with females that were homozygous for both a Tfap2a-conditional [24] and Tfap2b-conditional ( EVO/TW , in preparation ) allele , resulting in a 1:8 frequency of generating single or double conditional mutants , as well as various other genotype combinations . Mice were maintained on an outbred Black Swiss background . Of note , by virtue of this breeding scheme , the single conditional mutants would always be conditionally heterozygous for the alternate paralog . For r26r [90] and ‘tomato’ [114] experiments , the female was also homozygous for the reporter allele . Yolk sacs or tail clips were used for genotyping . DNA for PCR was extracted using DirectPCR Lysis Reagent ( Viagen Biotech . Inc ) plus 10 ug/ml Proteinase K ( Roche ) followed by heat inactivation at 85°C for 45 min . Samples were then used directly for PCR-based genotyping using allele specific primers ( available upon request ) at a concentration of 200 nM using the Qiagen DNA polymerase kit , including the optional Q Buffer solution ( Qiagen ) . With the exception of whole-mount β-galactosidase ( β-gal ) staining , procedures used for mouse embryo analysis ( in situ hybridization , ɑ-neurofilament immunostaining , and immunofluorescence ) have all been previously described [115] . Following euthanasia , embryos were collected at the indicated time-points in DEPC-PBS and subsequently processed . Briefly , for in situ hybridization , after embryo collection , trunks were removed , fixed overnight in 4% paraformaldehyde ( PFA ) , and stained using the indicated riboprobe ( Pmel , Dct , Sox10 ) . For immunostaining , embryos were processed using an ɑ-neurofilament primary antibody [116] ( IgG clone 2H3 , obtained from the Developmental Studies Hybridoma Bank–University of Iowa ) , followed by colorimetric staining using a standard secondary antibody and DAB-detection . For β-gal immunofluorescence , collected embryos underwent a short fixation in 0 . 25% glutaraldehyde , were taken through a series of sucrose/O . C . T . solutions ( Tissue-Tek O . C . T . Compound , Electron Microscopy Sciences ) , until being embedded in 100% O . C . T . and frozen on dry-ice . Cryosections were then cut at ~12μM on a Leica CM 1900 cryostat ( Leica Biosystems Inc . ) using the hindlimb as a delimiting rostral-caudal boundary between samples . Following sectioning , slides were washed in PBS , 2 x 10 min , blocked in 3% BSA ( in PBS ) 1 hr at room temperature , incubated over-night with a rabbit polyclonal anti-β-gal antibody ( Product 55976 , MP Biomedicals , LLC ) diluted 1:200 in block solution . Subsequently , sections were washed 2 x 10 min in PBS , followed by a 1 hr incubation in goat-anti-rabbit Alexa Fluor 488 ( Thermo Fisher ) and counterstained with DRAQ5 ( Abcam ) , washed again 2 x 10 min in PBS , and then cover-slipped . Processed samples were imaged on a Leica TCS SP5 II confocal microscope and representative images taken . Finally , for β-gal staining , embryos were collected at appropriate time points and fixed ~1hr at room temperature with 0 . 25% glutaraldehyde in PBS . Subsequently , embryos were washed 3 x 30 minutes in a ‘lacZ rinse buffer’ ( 0 . 2M sodium phosphate , 2mM magnesium chloride , 0 . 02% NP40 , and 0 . 01% sodium deoxycholate ) , and then incubated overnight in a ‘lacZ staining solution’ ( lacZ rinse buffer plus 5mM potassium ferricyanide , 5mM potassium ferrocyanide , and 1 mg/ml X-gal ) at 37°C . Following adequate staining , embryos were post-fixed in 4% PFA overnight , moved to PBS , and subsequently imaged . Zebrafish alleles used in this study include tfap2alow [lockjaw allele , 28] , mitfaw2 [94] , and mitfaz25 [95] . Lines were maintained as mitfa trans-heterozygous and tfap2a heterozygous ( mitfaw2/z25;tfap2a+/- ) or mitfa wildtype and tfap2a heterozygous ( tfap2a+/- ) . For genetic interaction experiments , mitfaw2/z25;tfap2a+/- animals were incrossed to generate tfap2a+/+ , tfap2a+/- , and tfap2a-/- genotypes in each of mitfaz25/z25 and mitfaw2/z25 backgrounds . To obtain control animals in the mitfa+/+ background , mitfa+/+;tfap2a+/- animals were also incrossed . At 72 hpf , embryos were binned according to melanocyte phenotype , photographed , and genotyped via High Resolution Melt Analysis ( HRMA ) using Precision Melt Supermix ( Bio-Rad ) on a CFX96 Real-Time PCR Detection system ( Bio-Rad ) according to the default settings . Precision Melt Analysis Software ( Bio-Rad ) was used to analyze melt curves . HRMA primer sequences are as follows: tfap2alow ( forward: GTA GCT ATG TTT CGT GGT TA; reverse: ACA ATA AGC AGC TGC TTT AC ) , mitfaz25 ( forward: GCA GAA GTC AGA GCC CTG GC; reverse: ACG GAT CAT TTG ACT TGG GAA TTA AAG ) . Ventral stripe melanocytes were counted from lateral-view images taken at 72 hpf and statistical significance between groups was tested using a one-way ANOVA with multiple test correction . For zebrafish rescue experiments , mitfaw2/z25 trans-heterozygotes were incrossed to obtain mitfaz25/z25 , mitfaw2/z25 , and mitfaw2/w2 genotypes , which were clearly distinguishable based on melanocyte phenotype at 48 hpf . 3-way Gateway cloning technology was used to generate a pDestTol2CG2 plasmid [117] containing 5’ entry mitfa promoter [96] , middle entry tfap2a cDNA , and 3’ entry 6x Myc epitope tag followed by polyA , resulting in the presence of Myc epitope tags on the carboxy terminus of Tfap2a . This construct was then injected into the above cross along with Tol2 mRNA , both at a concentration of 30 ng/uL . Due to the presence of a cmlc2:GFP reporter in the vector , injected embryos were screened for successful plasmid integration based on expression of GFP in the heart at 28–30 hpf . GFP positive embryos and uninjected control embryos were fixed overnight in 4% paraformaldehyde at 48 hpf . After fixation , embryos were rinsed 3x in PBS , blocked in PBDT+2 . 5% goat serum for 1 hr at room temperature , and incubated in anti-Myc primary overnight at 4°C ( 9E10 , obtained from the Developmental Studies Hybridoma Bank—University of Iowa , 1:100 diluted in block solution ) . The following day , embryos were rinsed 4x in PBS + 0 . 1% Triton X-100 ( PBS-Tx ) and incubated overnight at 4°C in Alexa Fluor goat-anti-mouse 488 secondary ( Thermo Fisher ) diluted in block solution . Embryos were then rinsed 4x15 minutes in PBS-Tx and mounted on slides . Ten individual embryos of each genotype with plasmid injection or uninjected control were viewed at 40x and photographed . Cells were grown to approximately 75% confluency in 24-well plate on poly-lysine coated disks and fixed with 4% paraformaldehyde for 1 hr at 4°C . Following fixation , cells were rinsed 3x20 minutes with 1x PBS , permeabilized in 1x PBS + 0 . 3% Triton X-100 for 30 min at 37°C , rinsed 3x10 minutes in PBS-Tx , and blocked ( 1% BSA in PBS-Tx ) overnight at 4°C . Cells were then incubated in anti-TFAP2A primary overnight at 4°C ( 3B5 , Santa Cruz Biotechnology , Inc . , 1:100 , 250ug/mL stock diluted in block solution ) . The following day , cells were rinsed 3x20 minutes in PBS-Tx and incubated for 2 hr at room temperature in Alexa Fluor goat-anti-mouse 488 secondary ( Thermo Fisher ) diluted in block solution . Cells were then rinsed 4x15 minutes in PBS-Tx and disks mounted in Prolong Gold antifade reagent and DAPI SlowFade solution ( Life Technologies ) . Slides were imaged on a Zeiss LSM 700 Flexible Confocal Microscope ( Carl Zeiss Microscopy ) . Briefly , for quantification of immunofluorescent intensity approximately three 20x images were taken of each slide , and three slides of each cell line processed ( including a no primary control ) . Each image included both the antibody of interest as well as DAPI staining to identify cell nuclei . All experiments were approved by the University of Iowa or University of Colorado Institutional Animal Care and Use Committee ( IACUC ) . We abide by PHS Policy , USDA-Animal Welfare regulations , the Guide for the Care and Use of Laboratory Animals , University of Iowa policies and regulations and any state and local laws and regulations . | Identifying the elements and structure of the gene regulatory network governing melanocyte differentiation may yield insight into the mechanisms of pigmentation diseases and melanoma progression . Pigmentation is abnormal in Tfap2a mutants , but deciphering the exact role of TFAP2A in the network has been complicated by pleiotropic requirements for TFAP2A during development and the redundant function of TFAP2 paralogs in melanocytes . In this study , we find that TFAP2A directly regulates genes involved in melanocyte differentiation and melanin synthesis by binding at both promoters and enhancers associated with these genes . Furthermore , we report evidence that TFAP2A shares many targets with the melanocyte “master regulator” MITF . These findings indicate that TFAP2A drives melanocyte differentiation in parallel with MITF and affects the net pro-differentiation activity that is lost in melanoma . | [
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"cell... | 2017 | TFAP2 paralogs regulate melanocyte differentiation in parallel with MITF |
Resistance-nodulation-division ( RND ) efflux systems are ubiquitous transporters in Gram-negative bacteria that are essential for antibiotic resistance . The RND efflux systems also contribute to diverse phenotypes independent of antimicrobial resistance , but the mechanism by which they affect most of these phenotypes is unclear . This is the case in Vibrio cholerae where the RND systems function in antimicrobial resistance and virulence factor production . Herein , we investigated the linkage between RND efflux and V . cholerae virulence . RNA sequencing revealed that the loss of RND efflux affected the activation state of periplasmic sensing systems including the virulence regulator ToxR . Activation of ToxR in an RND null mutant resulted in ToxR-dependent transcription of the LysR-family regulator leuO . Increased leuO transcription resulted in the repression of the ToxR virulence regulon and attenuated virulence factor production . Consistent with this , leuO deletion restored virulence factor production in an RND-null mutant , but not its ability to colonize infant mice; suggesting that RND efflux was epistatic to virulence factor production for colonization . The periplasmic sensing domain of ToxR was required for the induction of leuO transcription in the RND null mutant , suggesting that ToxR responded to metabolites that accumulated in the periplasm . Our results suggest that ToxR represses virulence factor production in response to metabolites that are normally effluxed from the cell by the RND transporters . We propose that impaired RND efflux results in periplasmic metabolite accumulation , which then activates periplasmic sensors including ToxR and two-component regulatory systems to initiate the expression of adaptive responses .
Antimicrobial resistance is an expanding global health threat . A ubiquitous mechanism in Gram-negative bacteria that contributes to drug resistance is the ability to reduce antimicrobial uptake . Reduced uptake involves decreasing the rate of antimicrobial diffusion across the outer membrane ( OM ) combined with the expression of efflux systems ( reviewed in [1] ) . Reduced OM permeability is most often mediated by lipid A modification and/or altered porin production . Efflux systems function synergistically with reduced OM permeability to export antimicrobial compounds that have crossed the OM . The Resistance-Nodulation-Division ( RND ) efflux systems play a predominant role in this process because they often exhibit broad substrate specificity that provides cross-resistance to multiple classes of antimicrobials . The RND efflux systems are ubiquitous in Gram-negative bacteria . They consist of an inner membrane pump protein , a periplasmic membrane fusion protein , and an outer membrane pore protein [1] . These three components function together to efflux substrates from the cytoplasm and periplasm to the external environment . Although many RND systems are linked to antimicrobial resistance , recent studies have implicated them in diverse phenotypes including metabolism , biofilm production , iron acquisition , and virulence [2–4] . These latter observations suggest that individual RND transporters fulfill specific phenotypes in the cell , but the mechanisms by which they contribute to these phenotypes is poorly understood . Vibrio cholerae is a Gram-negative bacterium that causes cholera; an acute diarrheal disease affecting ~3 million people per year [5] . To cause disease , V . cholerae must adapt to the host gastrointestinal tract . This includes expressing genes that allow it to resist host antimicrobials and to produce virulence factors that facilitate colonization . This process is mediated in part by the membrane associated transcription factor ToxR . ToxR is a global regulator that regulates antimicrobial resistance and virulence genes in response to environmental cues ( reviewed in [6] ) . ToxR is an essential member of the ToxR virulence regulon where it functions with TcpP to activate the expression of genes encoding for the virulence factors cholera toxin ( CT ) and the toxin coregulated pilus ( TCP ) . Independent of TcpP , ToxR contributes to antimicrobial resistance by regulating porin production and lipid A remodeling [7 , 8] . The in vivo cues that modulate ToxR activity are poorly understood , but studies suggest that the ToxR periplasmic domain ( PPD ) serves as a sensor to transduce environmental cues to alter the activity of its DNA binding domain [9–12] . V . cholerae encodes six RND efflux systems that share TolC as their OM pore [13 , 14] . Mutants lacking RND transporters , or wild type ( WT ) treated with RND efflux inhibitors , are hypersensitive to antibiotics , bile salts , fatty acids , and cationic antimicrobial peptides ( CAPs ) [14 , 15] . In addition , the V . cholerae RND efflux systems are required for CT and TCP production and colonization of the infant mouse intestine [14] . The mechanism linking RND efflux to CT/TCP production is unknown , but was correlated with reduced tcpP transcription [14] . Collectively these results indicated that the RND transporters have pleiotropic effects on V . cholerae pathogenesis . Herein , we investigated the function of the RND transporters in V . cholerae virulence . We document that RND efflux had wide-ranging effects on the V . cholerae transcriptome , suggesting that they have critical functions in cell physiology . In the absence of RND efflux , cellular metabolites that are normally effluxed by the RND transporters appeared to accumulate in the periplasm where they affected the activation state of periplasmic sensing proteins like ToxR and two-component systems . We further show that RND efflux plays a dual role in pathogenesis , being required for the expression of virulence genes and for resistance to antimicrobial compounds that are present in the host . Altogether our results suggest that RND efflux can influence the expression of adaptive responses by modulating the intracellular concentration of cell metabolites .
The loss of RND efflux in V . cholerae resulted in attenuated CT and TCP production [14] . To identify genes involved in this process , we determined the transcriptome of RND efflux negative V . cholerae strain JB485 by RNA sequencing ( RNAseq ) . Total RNA was isolated and sequenced from JB485 and WT following growth under virulence inducing conditions ( AKI conditions ) . The data from three independent experiments was then analyzed as described in the methods to identify differentially expressed genes . The RNAseq identified 373 genes that were differentially expressed in JB485 ( S1 Table ) . The largest category of differentially expressed genes were those of unknown function ( 132 genes ) followed by metabolism ( 60 genes ) , transport and binding ( 75 genes ) and regulatory genes ( 30 genes ) ( Table 1 ) . Consistent with previous studies , the expression of many virulence genes was reduced in JB485 ( S1 Table ) . This included genes involved in the production of CT , TCP and multifunctional-autoprocessing repeats-in-toxin ( MARTX ) . Surprisingly , the operons encoding for the VexAB , VexCD , VexGH , VexIJK and VexLM RND efflux systems were upregulated . Additionally , many porin genes were also differentially expressed including the upregulation of VC0972 , ompK , ompW and downregulation of ompV and ompS . As reduced OM permeability functions synergistically with active efflux to effect high-level antimicrobial resistance [1] , it is possible that the altered expression of the RND systems and porins reflects adaptive responses to modulate the OM barrier properties in response to the loss of RND efflux . Altogether these results suggest that impaired RND efflux activates global responses that facilitate the expression genes involved in environmental adaptation . We hypothesized that the link between RND efflux and virulence factor production was being mediated by a transcription factor . There were 30 differentially expressed regulatory genes identified in the RNAseq results ( S1 Table ) ; 21 of which were upregulated . Two-component signal transduction regulatory systems ( TCS ) made up 57% of these identified regulatory genes , which is highly enriched compared to TCSs represented in the V . cholerae genome ( ~17% ) . TCS consist of a membrane sensor that relays environmental signals to a response regulator to induce a cellular response . As such , the enrichment of TCSs among the identified regulatory genes suggests that the loss of RND efflux may have resulted in physiological alterations in the periplasmic compartment; perhaps due to the accumulation of substrates that are normally effluxed from the periplasm by the RND systems . Several of the identified TCSs contribute to environmental adaptation and pathogenesis including CpxRA [16–18] , CarRS [19 , 20] , VieSAB [21] , and OmpR [22] . We excluded several of the identified genes as virulence regulators in JB485 including cpxRA , vexR , and breR as previous studies suggested that they did not affect CT and TCP production [18 , 23 , 24] . Among the remaining regulatory genes , the LysR-family transcription factor leuO was one of the most highly upregulated ( ~6-fold ) in JB485 . LeuO is a global regulator that has been linked to multiple V . cholerae phenotypes including ToxR regulon expression [11 , 12 , 25–27] . We therefore further investigated leuO in JB485 . To confirm that leuO expression was increased in JB485 we introduced a leuO-lacZ reporter into WT and JB485 and quantified leuO expression over time during growth under AKI conditions . The results showed increased leuO expression in JB485 relative to WT at each time point ( Fig 1A ) . leuO expression was ~4-fold higher in JB485 than WT at 3 . 5h and its expression continued to increase through the duration of the experiment , confirming the RNAseq results . Previous studies showed differential contributions of the six V . cholerae RND transporters to antimicrobial resistance and virulence factor production [28 , 29] . VexB , VexD , VexH , and VexK pumps functioned in in vitro antimicrobial resistance while all six pumps contributed to CT and TCP production . Given this , we tested if individual RND pumps differentially affected leuO expression by quantifying leuO-lacZ expression in a panel of RND mutant strains following growth under AKI conditions . The results showed that cells lacking the vexB , vexD or vexBD RND pumps did not affect leuO expression ( S1 Fig ) . The expression of leuO-lacZ significantly increased in the ΔvexBDH mutant . Deletion of four RND pumps ( ΔvexBDHK ) increased leuO expression to a level similar to JB485 ( ΔvexBDFHKM ) . This indicated that vexBDHK were linked to the increased leuO transcription . The expression of leuO was unaffected in strains DT422 ( ΔvexBFHKM; vexD+ ) and JB464 ( ΔvexDFHKM , vexB+ ) , suggesting that the presence of vexB or vexD alone could suppress the RND efflux-dependent induction of leuO transcription . The fact that vexB or vexD suppressed leuO expression is consistent with previous studies showing redundancy among the RND efflux systems [14 , 28 , 29] . Increased leuO expression in the RND negative mutant JB485 suggested that LeuO repressed CT and TCP production . To test this , we compared CT and TcpA production in WT , JB485 , ΔleuO and JB485ΔleuO following growth under AKI conditions . Consistent with previous results [14] , CT and TcpA production were attenuated in JB485 relative to WT ( Fig 1B ) . Deletion of leuO in WT did not significantly affect CT or TcpA production . By contrast , leuO deletion in JB485 restored CT and TcpA production to WT levels ( Fig 1B ) , confirming that increased leuO expression was responsible for reduced CT and TcpA production in JB485 . Transcription of tcpPH was reported to be repressed in JB485 [14] . We therefore tested if leuO deletion in JB485 affected TcpP production under AKI conditions . As shown in Fig 1C , TcpP production in WT peaked at 4h and then declined to very low levels following overnight growth . TcpP production in JB485 was greatly reduced relative to WT , and still declined over time . Deletion of leuO in JB485 elevated TcpP production , with TcpP peaking at 6h before declining . In contrast to WT , TcpP was still relatively abundant in overnight JB485ΔleuO cultures ( Fig 1C ) . Although TcpP production appeared to be higher in JB485ΔleuO at 6h and 24h , CT and TcpA production in JB485ΔleuO was like WT ( Fig 1B ) ; this is likely due to TcpP indirectly regulating CT and TCP production . Collectively these results suggested that the loss of RND efflux increased leuO expression and that LeuO was responsible for reduced TcpP , CT and TcpA production . We hypothesized that if leuO was repressing specific genes in the ToxR regulon , then ectopic expression of the repressed genes would restore CT production . We tested this by overexpressing aphA , aphB , tcpPH and toxT in JB485 and quantifying CT production following growth under AKI conditions . Both toxT and tcpPH restored CT production ( S2A Fig ) . As toxT is downstream of tcpPH in the ToxR regulon , this is consistent with previous studies linking tcpPH repression to attenuated CT/TCP production in JB485 . AphA and AphB function upstream of tcpPH and bind to the tcpPH promoter to activate its expression [30] . The expression of aphA restored CT production in an arabinose-concentration dependent manner ( S2B Fig ) . The expression of aphB partially restored CT production in JB485 , but in contrast to aphA , CT production was independent of the arabinose concentration ( S2B Fig ) . This suggested that decreased tcpPH expression may be due to LeuO repressing aphA transcription . We further tested this by using qRT-PCR to quantify aphA , aphB , leuO , and tcpP expression in WT and JB485 during growth under AKI conditions . The results showed ~6-fold increase in leuO expression and a ~2-fold decrease in tcpP expression in JB485 relative to WT ( Fig 2A ) , while aphA expression was reduced by ~1 . 5-fold . By contrast , the expression of aphB and toxR was not significantly changed . Consistent with the qRT-PCR results we also observed that ToxR and AphB protein production was not different between WT and JB485 ( Fig 2C and S3 Fig ) . These results suggested that leuO repressed aphA expression in JB485 . To further confirm that LeuO repressed aphA transcription in JB485 , we compared aphA expression in JB485ΔleuO to WT . We hypothesized that if leuO was responsible for reduced aphA expression , then aphA expression should increase in JB485ΔleuO . The results showed an approximately 3-fold increase in aphA expression in JB485ΔleuO relative to WT , but no change in aphB expression , confirming our hypothesis ( Fig 2B ) . Increased aphA transcription in JB485ΔleuO potentially explains the elevated TcpP protein observed in JB485ΔleuO ( Fig 1C ) . These results provide additional evidence to suggest that LeuO-dependent repression of aphA decreased tcpPH expression and CT and TcpA production in JB485 . To address if LeuO was acting directly at the aphA promoter , we introduced pBAD33-leuO into E . coli bearing an aphA-lacZ reporter . Cultures were grown in the presence of arabinose to induce leuO expression before quantifying aphA-lacZ expression . The results showed an arabinose dose-dependent decrease in aphA-lacZ expression in the pBAD33-leuO culture and no effect on aphA expression in the pBAD33 control ( Fig 2D ) . As an additional control we examined the effect of pBAD33-leuO on rtxB , which was also differentially regulated in JB485 ( S1 Table ) . Overexpression of leuO did not affect rtxB expression in E . coli , indicating that LeuO did not directly regulate rtxB and exhibited specificity for the aphA promoter ( Fig 2E ) . Gel-shift assays were also performed and showed that LeuO can directly bind to the aphA promoter ( S4 Fig ) . Based on these results we concluded that LeuO directly repressed aphA transcription . ToxR positively regulates leuO transcription in response to extracellular cues [11 , 12] . We therefore tested if ToxR activated leuO transcription in cells lacking RND-mediated efflux . We cultured WT , ΔtoxRS , JB485 , and JB485ΔtoxRS bearing pXB266 ( leuO-lacZ ) under AKI conditions and quantified leuO expression at 3h and 5h . The results showed increased leuO expression in JB485 by ~3 . 5-fold at 3h and 4 . 5-fold at 5h relative to WT ( Fig 3A ) . By contrast , leuO expression was greatly diminished in JB485ΔtoxRS , indicating that toxRS was required for leuO expression in the absence of RND efflux . To confirm that ToxR was responsible for leuO expression in JB485 , we complemented toxRS mutants during growth under AKI conditions by introducing pBAD33::toxRS ( pXB302 ) into the ΔtoxRS and JB485ΔtoxRS mutants bearing pXB266 ( leuO-lacZ ) . Strains grown in the presence of arabinose increased leuO expression relative to the no arabinose control ( Fig 3B ) . Interestingly , the magnitude of leuO expression in JB485ΔtoxRS was ~30% greater than the efflux positive ΔtoxRS mutant at the same arabinose concentration . While the significance of this is unclear , we speculate that it reflects differences in ToxR activation in the RND negative mutant vs WT background . These results support the conclusion that ToxR positively regulates leuO and that ToxR is responsible for increased leuO transcription in JB485 . These results also suggest that RND mediated efflux may influence ToxR activation . The ToxR PPD is thought to function as an environmental sensor and is required for the activation of leuO transcription in response to extracellular cues [11 , 12] . Since leuO expression in JB485 was dependent on ToxR ( Fig 3A ) , we tested if the ToxR PPD was required for leuO expression in the RND null mutant . Therefore , we generated chromosomal ToxRΔPPD mutants in WT and JB485 by truncating ToxR at amino acid 188 to remove the C-terminal PPD as previously reported ( hereafter referred to as toxRΔPPD ) [31] . We then introduced pXB266 ( leuO-lacZ ) and pAL144 ( ompU-lacZ ) into WT , ΔtoxRS , toxRΔPPD , JB485 , JB485ΔtoxRS and JB485toxRΔPPD , grew the resulting strains under AKI conditions , and quantified leuO and ompU expression . We first validated that the toxRΔPPD allele was functional by examining ompU expression . Expression of ompU is dependent on ToxR , but independent of the ToxR PPD in rich media [31] . Consistent with this , toxRS deletion ablated ompU expression in WT and JB485 while PPD deletion had no effect on ompU expression ( Fig 3D ) . In fact , ompU expression was elevated in the toxRΔPPD mutants relative to their WT parental strains; as previously observed [31] . These studies also revealed elevated ompU expression in JB485 relative to WT . Since ToxR protein abundance is correlated with increased ompU expression in nutrient limiting conditions [32] , we assessed if the loss of RND-mediated efflux affected ToxR protein abundance . ToxR Western blots revealed similar levels of ToxR production in WT and JB485 ( Fig 2C ) and their isogenic ΔPPD mutants ( Fig 3C ) . Similarly , deletion of the PPD in WT did not affect aphA , toxT , ctxA , and tcpA expression ( S5 Fig ) , as previously reported [31] . Together these results confirmed that the toxRΔPPD allele was functional in WT and JB485 and indicated that the PPD was dispensable for ompU expression and ToxR regulon expression . We next quantified leuO expression in the above strains . The results showed increased leuO transcription in JB485 relative to WT and impaired leuO expression in the isogenic ΔtoxRS mutants of both strains ( Fig 3E ) ; confirming that toxR positively regulated leuO expression in JB485 . In contrast , deletion of the ToxR PPD in WT resulted in a ~5-fold reduction in leuO expression , indicating that the PPD differentially affects ToxR activity at the ompU and leuO promoters . Deletion of the PPD in JB485 did not abolish leuO expression , but rather reduced leuO expression to WT levels ( Fig 3E ) . This suggests that ToxR lacking its PPD ( i . e . ToxRΔPPD ) maintains the capacity to activate leuO expression in JB485 , but not in WT . From these results , we concluded that the ToxR PPD is important for leuO transcription including increased leuO expression in cells lacking RND efflux . However , since leuO was still expressed in JB485toxRΔPPD , albeit at a reduced level , other factors also influence leuO expression in the absence of RND efflux . The above data suggested that ToxR was activated upon loss of RND efflux . From this we speculated that cell metabolites accumulated in in the RND negative strain JB485 and were responsible for the changes in ToxR activity and increased leuO expression . The RNAseq results revealed differential expression of genes involved in malate metabolism with fumC ( fumarate hydratase ) being downregulated ( S1 Table ) and mdh ( malate dehydrogenase ) being upregulated by ~1 . 6-fold . As gene expression can be regulated by product feedback , this suggested that malate may accumulate in JB485 to effect ToxR activation . To test this , we quantified malate in JB58 and JB485 cells and culture supernatants following growth under AKI conditions . The results showed differential malate accumulation between WT and JB485 . Cell lysates of strain JB485 contained elevated levels of malate relative to WT whereas WT culture supernatants contained more malate than JB485 supernatants ( Fig 4A ) . These results supported the hypothesis that the absence of RND-mediated efflux resulted in intracellular malate accumulation which could be influencing ToxR activity in JB485 . We next asked if the addition of exogenous malate stimulated ToxR-dependent expression of leuO . To test this , we quantified leuO-lacZ expression in WT , toxRΔPPD and ΔtoxRS following growth under AKI conditions for 1hr in the presence of varying concentrations of malate . We found that malate addition did not affect leuO expression in the toxRΔPPD and ΔtoxRS mutants , but increased leuO expression in a concentration-dependent manner in WT ( Fig 4B ) , suggesting that malate can influence the activation state of ToxR by a process that was dependent upon the ToxR PPD . The effects of exogenous malate on leuO expression in WT were somewhat reduced relative to what was observed in JB485 . The reasons for this are unclear , but could reflect physiological differences in WT that limit periplasmic malate accumulation in WT including active efflux by the RND systems and the production of the cation-selective porin OmpU which could restrict malate diffusion across the outer membrane [33] . When this assay was repeated with fumarate we did not observe changes in leuO expression ( S6 Fig ) , suggesting that the effects of malate on ToxR were not the due to nonspecific effects of C4 dicarboxylic acids on the cell . The RND null mutant JB485 was highly attenuated in the infant mouse model and was not recovered from the small intestine following challenge [14] . Since the loss of RND-mediated efflux was pleiotropic , with cells exhibiting antimicrobial hypersensitivity and attenuated virulence factor production , the relative contribution of these two phenotypes to colonization was unclear . As the studies here revealed that leuO deletion restored in vitro virulence factor production in JB485 , we tested whether leuO deletion also restored the ability of JB485 to colonize infant mice . To test this , we performed colonization competition assays between JB485ΔleuO and WT . The results showed that neither JB485ΔleuO nor JB485 could be recovered from the intestine of challenged mice , further confirming that the RND transporters were essential for colonization . We considered the possibility that deletion of leuO may have dysregulated virulence factor production in vivo and thus led to a colonization defect . To address this , we performed a competition assay between JB485 and JB485toxRΔPPD; ToxRΔPPD mutants have been shown to activate virulence factors normally ( S5 Fig and [31] ) . However , we were again unable to recover JB485 or JB485toxRΔPPD from the challenged mice . Taken together , these results suggest that the function of the RND transporters in antimicrobial resistance , and/or their contribution to unknown physiological functions , is likely epistatic to virulence factor production for colonization .
The broad effects of RND efflux on the V . cholerae transcriptome suggested that RND-mediated efflux impacts multiple aspects of bacterial physiology . It was noteworthy that 5 of the 6 RND operons ( i . e . vexRAB , vexCD , vexGH , vexIJK , and vexLM ) , the two local RND regulators breR and vexR , and tolC , were upregulated in JB485 . This suggests that the RND efflux systems autoregulate their own expression . While the mechanism for this remains unclear , RND systems are usually regulated in response to their substrates . From this we infer that cell metabolites are accumulating in the absence of RND efflux and activating RND systems expression via a feedback mechanism . This conclusion is bolstered by reports showing that biosynthetic pathway mutants , which are predicted to accumulate metabolic intermediates , induce RND transporter expression in V . cholerae and E . coli [23 , 34] . These findings also support the conclusion that a native function of at least some of the RND transporters is to maintain cell homeostasis by removing potentially toxic metabolites from within the cell . One of the most highly upregulated genes in the RND-negative mutant was leuO . leuO expression is regulated by ToxR in response to environmental cues [11 , 12 , 25–27] . Genetic studies suggest that leuO expression is induced by small molecules interacting with the ToxR PPD [11 , 12] . Here we showed that ToxR-mediated leuO expression in the absence of RND efflux was dependent upon the ToxR PPD . We documented that leuO expression increased in the absence of RND-mediated efflux , while the amount of ToxR protein remained the same . This indicated that ToxR was activated in the absence of RND-mediated efflux , and that this process was dependent upon the ToxR PPD . These findings alluded to the possibility that cell metabolites may influence ToxR activity . The fact that malate addition enhanced leuO expression via a ToxR PPD-dependent process supported this hypothesis . Based on these data we propose that ToxR can function as a metabolic sensor . Previous reports , together with this study , have shown that ToxR can respond to multiple metabolites ( e . g . cyclic dipeptides , bile salts and malate ) via its PPD , suggesting that ToxR may be promiscuous in agonist recognition . Exactly how ToxR can sense multiple agonists is unknown . However , recent studies showing that destabilization of the PPD promoted ToxR activation provides an intriguing model that could accommodate multiple agonists [10] . In this study , we documented that exogenous malate stimulated leuO expression by a process that was dependent on the ToxR PPD . We also documented increased cell-associated malate in RND deficient V . cholerae . Taken together these results suggest that malate might function as a ToxR agonist in RND deficient cells and that malate may be a substrate for the RND transporters . It is interesting to note that malate was shown to repress toxT expression in classical biotypes while TCA cycle mutants that diminished malate production ( i . e . fumarase mutants ) exhibited increased toxT expression [35] . While the mechanism responsible for these phenotypes is unclear , it is tempting to speculate that the effects of malate on toxT expression were mediated through malate-dependent effects on ToxR activation as described here . Malate is produced in the cytoplasm and thus needs to be transported to the periplasm to access the ToxR PPD . The mechanism by which this might occur is unknown . Malate efflux systems belonging to PET ( Putative Efflux Transporter ) family are present in plants and homologs of these efflux systems are found in many bacteria [36 , 37] , but we were not able to identify PET homologs in V . cholerae . It is unclear if malate was the sole agonist that was responsible for increased leuO expression in RND-deficient cells . The fact that the magnitude of leuO induction in WT cells treated with malate was lower than what was observed in JB485 could suggest that other metabolites also contributed to ToxR activation in RND deficient cells . For example , it is possible that malate indirectly affects ToxR activation by a feedback mechanism . If malate was an efflux substrate , it could serve as a competitive efflux inhibitor and thus alter the export of a second metabolite . Malate accumulation could also alter cell metabolism and lead to the generation of other unknown metabolites that serve as ToxR agonists , or that malate could function cooperatively with other metabolites ( which may be limiting in WT ) to affect the activation state of ToxR . Discrimination between these possibilities will require further work . The link between RND efflux and ToxR activity suggests a novel paradigm for RND-mediated efflux in sensing and responding to environmental cues ( Fig 5 ) . Under normal conditions , the RND transporters maintain homeostasis by exporting metabolites from the cytoplasm and periplasm ( Fig 5A ) . In cells with impaired RND efflux , metabolites accumulate within the cell and interact with environmental sensors like ToxR to stimulate the expression of adaptive responses ( Fig 5B ) . In the case of ToxR , this results in elevated leuO expression and the subsequent repression of CT and TCP production . It is unclear how metabolites affect ToxR activation , but a recent report showing that bile salts enhance ToxR activity by binding to the PPD to promote heterodimer formation with ToxS provides a compelling model by which this could occur [10] . While increased leuO transcription serves as a marker for ToxR activation , the loss of RND efflux clearly affected several other environmental sensing systems . This is evidenced by the fact that 17 out of the 30 differentially expressed regulatory genes belong to TCSs . This included the CpxRA system where 14 of the 25 genes in the Cpx regulon were differentially expressed in the RND mutant [18]; a finding consistent with a recent study showing that vibriobactin secretion by VexGH RND system was required to maintain the CpxRA system in an inactive state [4] . The preferential activation of TCSs in cells lacking RND efflux supports the conclusion that the RND systems influence homeostasis by effluxing cell metabolites . The above model suggests the intriguing possibility that RND efflux systems may affect in vivo gene expression in response to host-derived compounds . For example , upon ingestion V . cholerae encounters high concentrations of bile salts in the lumen of the small intestine . Since bile salts are major RND transporter substrates , they could serve as competitive inhibitors for metabolite export and thus affect metabolite accumulation within the cell . Metabolites likely also accumulate late in infection , when V . cholerae is present at high cell titers in the small intestine , and may affect transcriptional responses via periplasmic sensors . A number of late infection phenotypes are important for V . cholerae pathogenesis including repression of the ToxR regulon and the expression of dissemination and transmission phenotypes ( reviewed in [38] ) . While the regulation of these phenotypes remains unknown , the expression of leuO late during infection [12] , and the suppression of virulence factor production in human and animal shed V . cholerae [39 , 40] , argue that the proposed model may be relevant in vivo . This model could also be extended to other Gram-negative bacteria where the RND transporters have broad effects on physiology and virulence [2 , 3] . RND efflux deficient V . cholerae exhibited decreased tcpPH expression , reduced CT and TCP production , and a colonization defect in the infant mouse model [12] . Here we show that the defect in CT/TCP production was due to increased leuO expression as evidenced by the observation that deletion of leuO in JB485 restored tcpPH expression and CT and TCP production . This provided additional evidence to support the novel conclusion that ToxR can function as a virulence repressor . Interestingly , leuO deletion did not restore the ability of RND mutant strain JB485 to colonize infant mice . The reasons for this are unclear , but may be related to increased sensitivity of JB485 to antimicrobial compounds that are abundant in the intestine including CAPs , bile salts and other detergent-like molecules . It is also possible that the loss of RND efflux imparted unknown effects on cell physiology that negatively impacted V . cholerae pathogenesis or resulted in dysregulation of virulence gene expression in vivo . For example , dysregulated TCP production would impact the ability of V . cholerae to access colonization niches in the intestine or to adhere to the intestinal epithelium . Overall our results support the conclusion that RND efflux has pleiotropic effects on pathogenesis; being required for virulence gene expression , resistance to antimicrobial compounds that are present in the host , and perhaps other unknown aspects of pathogenesis .
The bacterial strains used in this study are listed in Table 2 . E . coli strain EC100λpir was used for cloning experiments . E . coli strain SM10λpir was used for conjugating plasmids into V . cholerae . Bacterial strains were routinely grown in Lysogeny Broth ( LB ) broth or on LB agar at 37°C . AKI growth conditions were used to induce virulence gene expression in V . cholerae as previously described [41] . Antibiotics were used at the following concentrations: carbenicillin ( Cb ) , 100 μg/ml; kanamycin ( Km ) , 50 μg/ml; and streptomycin ( Sm ) , 100 μg/ml . The plasmids and oligonucleotides used in this study are listed in Table 2 and S3 , respectively . Chromosomal DNA from strain N16961 was used as the template for cloning experiments . Transcriptional reporter plasmids were constructed as described below . The promoter regions of ctxAB , tcpA and rtxB were generated by PCR using the PctxAB-F/PctxAB-R , PtcpA-F/PtcpA-R , or PrtxB-F/PrtxB-R oligonucleotide primers . The resulting amplicons were digested with XhoI and XbaI restriction endonucleases and ligated into similarly digested pTL61T to generate the plasmids pXB193 , pXB194 and pVA195 , respectively . pXB209 was constructed similarly using the aphB-F/aphB-R primers with the resulting PCR amplicon being digested with EcoRI and XbaI restriction endonucleases before being ligated into similarly digested pBAD18Km . Deletion of leuO and the toxR PPD domain was generated using the plasmid pWM91ΔleuO or pWM91::ΔtoxRppd as previously described [11 , 12] . Repair of lacZ in JB485 was accomplished by using PCR to amplify the lacZ locus from N16961 strain JB3 using the Vc . lacZ . F . BamHI and Vc . lacZ . R . SacI PCR primers . The resulting 5 . 1 kb amplicon , containing the lacZ locus and ~1 kb of flanking DNA sequence , was digested with BamHI and SacI restriction endonucleases before being ligated into similarly digested pWM91 to generate pWM91-lacZ . The resulting plasmid was then used to repair the lacZ allele by allelic exchange as previously described [11 , 12] . V . cholerae strains were grown under AKI conditions in AKI broth . Total RNA was then isolated from the cultures at 3h using Trizol per the manufacturer’s directions . cDNA was generated from the total RNA using the Superscript III RT ( Invitrogen ) and used as a template for qRT-PCR with the SYBR Green Dye Kit ( Fisher Scientific ) . The expression level of specific genes was quantified by amplifying 25 ng cDNA with 0 . 3 μM primers using the SYBR green PCR mix on a StepOnePlus real-time PCR System ( Applied Biosystems ) . The gene encoding for DNA gyrase ( gryA ) was used as the internal control . Gene expression changes were calculated using the 2−ΔΔCT method and the presented results are the means ± standard error of the means ( SEM ) from three biological replicates , with each biological replicate generated from three technical replicates . Total RNA from V . cholerae strains JB58 and JB485 grown under AKI conditions for 3h were isolated using TRIzol per the manufacturer’s directions ( Invitrogen ) and further purified using an RNeasy kit with in column DNase treatment ( Qiagen ) . The resulting RNA samples were assessed using a Qubit 2 . 0 fluorimeter ( Thermo Scientific ) and Agilent Tapestation 2200 ( Agilent Technologies ) . Sequencing libraries were generated using the Illumina TruSeq RNA Access library prep kit ( Illumina ) . Cluster generation and 75-bp single-read single-indexed sequencing was performed on Illumina NextSeq 500 ( Illumina ) . The resulting raw reads were trimmed to remove adaptor/primer sequences . CLC Genomics Workbench version 10 . 1 ( Qiagen ) was then used to map the reads from three independent experiments to the N16961 genome [42] . The identification of differentially expressed genes was accomplished using the CLC Genomics Workbench RNA-Seq Analysis tool . Genes showing a 2-fold or greater difference in expression and a P-value and False Discovery Rate P-value of less than or equal to 0 . 05 were identified as differentially expressed genes . The RNA sequencing data was deposited in the National Center for Biotechnology Information Sequence Read Archive under accession number SRP109296 . Expression of promoters that were transcriptionally fused to lacZ were assayed following growth under AKI conditions . Samples from the cultures were taken at the indicated time points and processed in triplicate to assay for β-galactosidase activity as previously described [43] . The reporter experiments were independently performed at least three times . Statistical analyses were determined using the Student’s t-test . The concentrations of malate and fumarate used in the reporter assays was based on the physiological concentrations reported for E . coli ( i . e . 1 . 7 mM for malate and 0 . 12 mM for fumarate ) [44] . CT production in V . cholerae strains grown under AKI conditions was determined by GM1 enzyme-linked immunosorbent CT assays as previously described using purified CT ( Sigma ) as a standard [28] . The production of TcpA , ToxR , AphB and TcpP was determined respectively by Western immunoblotting as previously described using the polyclonal rabbit antisera against TcpA , ToxR , AphB , and TcpP [12] . Immunoreactive proteins on the Western blots were visualized using the SuperSignal West Pico chemiluminescent detection kit ( Thermo Scientific ) . LeuO was purified from middle logarithmic phase LB broth cultures of E . coli ER2566 bearing pVA175 ( pMAL-c2::leuO ) following induction with isopropyl β-D-1-thiogalactopyranoside ( 0 . 3 mM ) for 2h as previously described [11 , 25] . The cells were then harvested by centrifugation , resuspended in column buffer ( 20 mM Tris-HCl , 200 mM NaCl , 1 mM EDTA , 1 mM phenylmethylsulfonyl fluoride ) , and lysed using a M-11P Microfluidizer according to the manufacturer’s instructions ( Microfluidics ) . The lysates were cleared by centrifugation at 15 , 000 x g for 20 min and the clarified lysates were diluted 1:6 with column buffer and run over an amylose resin chromatography column ( New England Biolabs ) . Proteins bound to the amylose resin were then eluted with elution buffer ( 20 mM Tris-HCl , 200 mM NaCl , 1 mM EDTA , 10 mM maltose ) , before LeuO was liberated from the MBP using factor Xa protease . Protein purity was assessed by SDS–PAGE with Coomassie brilliant blue R-250 staining . Protein concentration was determined using the Bradford Assay kit according to the manufacturer’s instructions ( Thermo Scientific ) . The gel-shift assays were performed as previously described [25] . Briefly , biotinylated probes were generated by PCR using primers that were purchased from the manufacturer ( IDT ) with a 5’ biotin label . The biotinylated probes were gel purified before being used in the gel shift assays . The DNA binding reactions were performed in a final volume 10 μl of binding buffer ( 10 mM Tris-HCl ( pH 7 . 4 ) , 5 mM NaCl , 50 mM KCl , 1 mM EDTA , 50 μg/ml BSA , 1 . 5 nM biotinylated probe and 10 μg/ml sheared salmon sperm DNA ) . The binding reactions were incubated at 30°C for 30 minutes before being subjected to electrophoresis on non-denaturing 5% polyacrylamide TBE gels . The resolved gels were electroblotted to positively charged nylon membrane before the membranes were subjected to UV crosslinking at 120 , 000 microjoules using a Stratalinker 1800 Crosslinker ( Strategene ) . The biotinylated probes were then detected using the Pierce Chemiluminescent Nucleic Acid Detection Module ( Thermo Scientific ) and visualized using a FluorChem E imaging system ( Protein Simple ) . JB58 and JB485 were cultured under AKI conditions for 3 . 5h when the culture optical density at 600 nm was recorded and a one mL culture aliquot was collected . The cells were separated from the supernatant by centrifugation and the supernatant and cell pellet retained . Cell lysates were generated by resuspending the cell pellet in one mL of ddH2O before subjecting the cells to three freeze-thaw cycles followed by sonication . Aliquots of the culture supernatant and cell lysates were then assayed for malate using the Malate Assay Kit ( Sigma ) according to the manufacturer’s directions and normalized by optical density . The reported results are the means ± standard deviation from six biological replicates , with each biological replicate generated from two technical replicates . Cultures of XBV255 ( JB485ΔleuOΔlacZ ) and WT strain JB3 ( N16961 lacZ positive ) or DK296 ( RND null , lacZ positive ) and XBV468 ( JB485 ΔPPD ΔlacZ ) were combined at a 1:1 ratio before being delivered perorally to infant mice as previously described [14] . The following day the small intestine from the stomach to the cecum was excised and homogenized in phosphate buffered saline . Serial dilutions of the homogenates were then plated onto LB agar containing X-gal and streptomycin to enumerate the bacterial strains based on colony color . A competitive index was then calculated as the ratio of the test strains in the input divided by the ratio of test strains in the output . Animal protocols were approved by the University of Pittsburgh Institutional Animal Care and Use Committee ( Protocol number 15015310 ) and met the standards for humane animal care and use as set by the Animal Welfare Act and the NIH Guide for the Care and Use of Laboratory Animals . | Multidrug efflux systems belonging to the RND superfamily contribute to the expression of diverse phenotypes in Gram-negative bacteria , but the mechanisms linking RND efflux to these phenotypes is unclear . Herein , we provide evidence suggesting that the V . cholerae RND systems influence global transcription patterns by extruding cell metabolites . Inhibition of RND efflux causes cell metabolites to accumulate intracellularly where they stimulate periplasmic sensors including the virulence regulator ToxR . The sensor proteins then initiate the expression of transcriptional responses , which in V . cholerae includes ToxR-mediated repression of virulence factor production . This study sheds light on the native functions of RND systems in Gram-negative bacteria and suggests a new paradigm for RND-mediated efflux in environmental sensing and adaptation . | [
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"organic",... | 2018 | The Vibrio cholerae RND efflux systems impact virulence factor production and adaptive responses via periplasmic sensor proteins |
During blood feeding , sand flies inject Leishmania parasites in the presence of saliva . The types and functions of cells present at the first host-parasite contact are critical to the outcome on infection and sand fly saliva has been shown to play an important role in this setting . Herein , we investigated the in vivo chemotactic effects of Lutzomyia intermedia saliva , the vector of Leishmania braziliensis , combined or not with the parasite . We tested the initial response induced by Lutzomyia intermedia salivary gland sonicate ( SGS ) in BALB/c mice employing the air pouch model of inflammation . L . intermedia SGS induced a rapid influx of macrophages and neutrophils . In mice that were pre-sensitized with L . intermedia saliva , injection of SGS was associated with increased neutrophil recruitment and a significant up-regulation of CXCL1 , CCL2 , CCL4 and TNF-α expression . Surprisingly , in mice that were pre-exposed to SGS , a combination of SGS and L . braziliensis induced a significant migration of neutrophils and an important modulation in cytokine and chemokine expression as shown by decreased CXCL10 expression and increased IL-10 expression . These results confirm that sand fly saliva modulates the initial host response . More importantly , pre-exposure to L . intermedia saliva significantly modifies the host's response to L . braziliensis , in terms of cellular recruitment and expression of cytokines and chemokines . This particular immune modulation may , in turn , favor parasite multiplication .
The intracellular protozoan parasites of the Leishmania species are transmitted to vertebrate host through the bites of sand flies . Within the vertebrate host , Leishmania parasites reside in phagocytes and induce a spectrum of diseases ranging from a single self-healing cutaneous lesion to the lethal visceral form . It is currently estimated that leishmaniasis affects two million people per year worldwide [1] . Leishmania braziliensis , the main causative agent of cutaneous leishmaniasis ( CL ) in Brazil , can be transmitted to the human host by the bite of the sand fly Lutzomyia intermedia . [2] , [3] . Several studies have shown that pre-exposure to saliva or to bites from uninfected sand flies results in protection against subsequent infection with Leishmania major [4]–[7] , Leishmania . amazonensis [8] , and Leishmania chagasi [9] . On the contrary , pre-exposure to Lutzomyia intermedia saliva enhanced infection with L . braziliensis in the mouse model; disease exacerbation was correlated with generation of a Th2 response evidenced by a reduction in the IFN-γ/IL-4 ratio [10] . Importantly , individuals with active CL showed higher humoral immune responses to L . intermedia saliva compared with control subjects , a finding also demonstrated with Old World CL [11] . These data indicate an association between disease and immune response to L . intermedia saliva in humans . In the case of L . intermedia , the lack of protection observed following pre-exposure to saliva in the murine model may be related to differences in the initial inflammatory response induced by the salivary proteins . Several studies have shown the potential of salivary antigens from Lutzomyia longipalpis , Phlebotomus duboscqi , Phlebotomus papatasi and Phlebotomus ariasi to modulate cell recruitment and production of immune response mediators [12]–[17] however , little is known regarding these effects when using L . intermedia saliva . Our group has previously shown that pre-treatment of human monocytes with L . intermedia followed by L . braziliensis infection led to a significant increase in TNF-α , IL-6 , and IL-8 production [18] , indicating the ability of L . intermedia saliva to alter the inflammatory milieu . To gain further information regarding the events associated with the initial host response to L . intermedia saliva , we employed the air pouch model of inflammation . This model simulates inoculation of the sand fly in a closed environment and allows for subsequent analysis of inflammatory parameters and mediators induced in vivo by distinct stimuli [19] . Using this model , we showed that saliva from L . longipalpis rapidly induced CCL2 expression and macrophage recruitment , in synergy with L . chagasi parasites , in BALB/c mice [20] . Here we describe the ability of L . intermedia salivary gland sonicate ( SGS ) to modulate the host immune response in naïve and in SGS-sensitized mice . We have demonstrated that L . intermedia salivary proteins induce neutrophil recruitment and modulate cytokine and chemokine expression . Crucially , a downregulation in CXCL10 paralleled by an increase in IL-10 expression was observed in SGS-sensitized mice stimulated with saliva+L . braziliensis . This correlates with disease exacerbation previously observed in mice immune to L . intermedia SGS and challenged with L . braziliensis [10] .
Leishmania braziliensis promastigotes ( strain MHOM/BR/01/BA788 [21] ) were grown in Schneider medium ( Sigma Chemical Corporation , St . Louis , MO , USA ) supplemented with 100 U/ml of penicillin , 100 µg/ml of streptomycin , 10% heat-inactivated fetal calf serum ( all from Invitrogen , San Diego , CA , USA ) , and 2% sterile human urine . Stationary-phase promastigotes from second passage culture were used in all experiments . Female BALB/c mice ( 6–8 weeks of age ) were obtained from CPqGM/FIOCRUZ Animal Facility where they were maintained under pathogen-free conditions . All procedures involving animals were approved by the local Ethics Committee on Animal Care and Utilization ( CEUA—CPqGM/FIOCRUZ ) . Adult Lutzomyia intermedia sand flies were captured in Corte de Pedra , Bahia , and were used for dissection of salivary glands . Salivary glands were stored in groups of 20 pairs in 20 µl NaCl ( 150 mM ) -Hepes buffer ( 10 mM; pH7 . 4 ) at −70°C . Immediately before use , salivary glands were disrupted by ultrasonication in 1 . 5-ml conical tubes . Tubes were centrifuged at 10 , 000×g for two minutes , and the resultant supernatant—salivary gland sonicate ( SGS ) —was used for the studies . The level of lipopolysaccharide ( LPS ) contamination of SGS preparations was determined using a commercially available LAL chromogenic kit ( QCL-1000; Lonza Biologics , Portsmouth , NH , USA ) ; LPS concentration was <0 . 1 ng/ml . BALB/c mice ( groups of five to six ) were immunized three times with SGS ( equivalent to one pair of salivary glands ) in 10 µl of PBS in the dermis of the right ear using a 27 . 5 G needle . Immunizations were performed at two-week intervals . Control mice were injected with PBS . Development of an immune response against L . intermedia saliva was confirmed by ELISA as previously described [10] . Immune sera were pooled from SGS-immunized mice and employed in neutralization experiments . Immune mice were employed in air pouch experiments . Air pouches were raised on the dorsum of anesthetized BALB/c mice ( groups of five to six ) by injection of 3 ml of air , as described elsewhere [22] . Air pouches were inoculated with either one of the following stimuli: L . intermedia SGS ( equivalent to one pair of salivary glands/animal ) ; L . intermedia SGS pre-incubated with a pool of anti-SGS immune sera ( SGS+50 µl of immune serum pre-incubated for one hour at 37°C ) ; a pool of anti-SGS immune sera alone; stationary-phase L . braziliensis promastigotes ( 105 parasites ) ; or L . braziliensis+SGS . Air pouches in control mice were injected with endotoxin-free saline ( negative control ) or with LPS ( Calbiochem , San Diego , CA , USA ) ( 20 µg/ml; positive control ) . After twelve hours , animals were euthanized and pouches washed with 5 ml of endotoxin-free saline for collection of exudates containing leukocytes . Lavage fluids were washed , and cell pellets were resuspended in saline , stained in Turk's solution , and counted in a Neubauer hemocytometer . Cells were cytoadhered to glass slides using Shandon cytospin2 and stained with hematoxylin and eosin to determine proportions of monocytes/macrophages , neutrophils , lymphocytes , basophils , and eosinophils . Air pouch lining tissue was placed in 5–10 volumes of RNAlater ( Ambion Inc . , Austin , TX , USA ) , and samples were stored at −80°C . Total RNA was extracted from the air pouch lining tissue using the RNeasy Protect Mini Kit ( Qiagen , Inc . , Santa Clara , CA , USA ) according to manufacturer's instructions . The resulting RNA was resuspended in 20 µl diethyl pyrocarbonate ( DEPC ) -treated water and stored at −80°C until use . cDNA synthesis for detection of cytokine mRNA was performed after reverse transcription ( Im Prom-II™ reverse transcription system ) . Real-time PCR was performed in triplicate on the Abi Prism 7500 ( Applied Biosystems , Inc . , Fullerton , CA , USA ) ; thermal cycle conditions consisted of a two-minute initial incubation at 50°C followed by ten-minute denaturation at 95°C and 50 cycles at 95°C for 15 seconds and 60°C for one minute each . Each sample and the negative control were analyzed in triplicate for each run . The comparative method was used to analyze gene expression . Chemokine or cytokine cycle threshold ( Ct ) values were normalized to GAPDH expression as determined by ΔCt = Ct ( target gene ) −Ct ( GAPDH gene ) . Fold change was determined by 2−ΔΔCt , where ΔΔCt = ΔCt ( target ) −ΔCt ( saline ) [23] . The following primers were employed: GAPDH ( Forward: 5′-TGTGTCCGTCGTGGATCT GA-3′; Reverse: 5′-CCTGCTTCACCACCTTCTTGA-3′ ) ; CCL2 ( Forward: 5′-CAGGTC CCTGTCATGCTTCTG-3′; Reverse: 5′-GAGCCAACACGTGGATGCT-3′ ) ; CCL3 ( Forward: 5′-TCTTCTCAGCGCCATATGGA-3′; Reverse: 5′-CGTGGAATCTTCCGG CTGTA-3′ ) ; CCL4 ( Forward: 5′-TGCTCGTGGCTGCCTTCT-3′; Reverse: 5′-CAGGAA GTGGGAGGGTCAGA-3′ ) ; CXCL1: ( Forward: 5′-CCGAAGTCATAGCCACACTCAA-3′; Reverse: 5′-AATTTTCTGAACCAAGGGAGCTT-3′ ) ; CXCL10: ( Forward: 5′-GGACGG TCCGCTGCAA-3′; Reverse: 5′-CCCTATGGCCCTCATTCTCA-3′ ) ; IFN-γ ( Forward: 5′-CTACACACTGCATCTTGGCTTTG-3′; Reverse: 5′-TGACTGCGTGGCAGTA-3′ ) ; TNF-α ( Forward: 5′-GGTCCCCAAAGGGATGAGAA-3′; Reverse: 5′-TGAGGGTCT GGGCCATAGAA-3′ ) ; and IL-10 ( Forward: 5′-CAGCCGGGAAGACAATAACTG-3′; Reverse: 5′-CGCAGCTCTAGGAGCATGTG-3′ ) . Primers were designed using Primer Express Software ( Applied Biosystems ) . BALB/c mice ( n = 5 ) were intradermally immunized with L . intermedia SGS ( equivalent to one pair of salivary glands ) or injected with PBS three times in the right ear at two-week intervals . After the third injection , pre-sensitized or control animals were intradermally inoculated with L . intermedia SGS , in the opposite ( left ) ear dermis . Twenty-four and forty-eight hours after SGS injection , animals were euthanized and the ear was biopsied and stored in 10% neutral buffered formalin . Ears were mounted in paraffin blocks , sectioned at 5-µm intervals , and stained with hematoxylin and eosin for histologic analysis . Paraffin-embedded sections of ears fixed in 10% neutral buffered formalin were used for immunohistochemistry . Myeloperoxidase rabbit anti-mouse ( Dako , Carpenteria , CA , USA ) was used at 1∶1000 dilution . A secondary biotinylated goat anti-rabbit antibody was used at 1∶500 for 15 minutes ( Vector Laboratories , Burlingame , CA , USA ) and detected by R . T . U . Vectastin Elite ABC reagent ( Vector Laboratories ) and DAB chromagen . Data are presented as the mean with 95%CI . The significance of the results was calculated using nonparametric statistical tests: two-sided Mann-Whitney for comparisons between two groups; Kruskal-Wallis followed by Dunn's multiple comparison test for comparisons between three groups . Analyses were conducted using Prism ( GraphPad Software Inc . , San Diego , CA , USA ) ; a P-value of <0 . 05 was considered significant .
We initially studied the cellular recruitment induced by L . intermedia SGS inoculation . Air pouches were induced in BALB/c mice and subsequently probed with different stimuli: endotoxin-free saline; L . intermedia SGS; or LPS . L . intermedia SGS induced a significant increase in leukocyte accumulation in the air pouch compared with saline injection ( Figure . 1A ) . Most cells recruited by inoculation of L . intermedia SGS into air pouches were neutrophils , followed by monocytes ( Figure 1B ) . LPS inoculation was used as a positive control for cell recruitment and , as expected , led to a predominant recruitment of neutrophils ( Figure 1B ) . Moreover , inoculation of L . intermedia SGS did not lead to significant changes in either eosinophil or lymphocyte recruitment . To confirm that the effect of L . intermedia SGS on leukocyte accumulation within air pouches was specific , we pre-incubated SGS with anti-SGS immune sera obtained from mice immunized with L . intermedia SGS ( data not shown , [10] ) . Pre-incubation of L . intermedia SGS with anti-SGS immune sera inhibited leukocyte accumulation induced by L . intermedia SGS by 56% ( Figure 2A ) , whereas air-pouch inoculation with immune sera alone led to a cellular recruitment similar to that induced by saline ( Figure 2A ) . Notably , the significant decrease in cellular recruitment following incubation of L . intermedia SGS with antisera was associated with a significant reduction ( 81% ) in the number accumulating neutrophils ( Figure 2B ) . Recruitment of monocytes , lymphocytes , and eosinophils , however , remained unchanged ( Figure 2B ) . L . intermedia SGS was able to induce a significant increase in leukocyte recruitment in the air-pouch model of inflammation when compared with saline ( Figure 1 ) . This effect was particularly powerful on neutrophil migration and was abrogated when SGS was pre-incubated with anti-SGS-specific antiserum ( Figure 2B ) . We then investigated the initial inflammatory response in mice that had been previously immunized with L . intermedia SGS . Air pouches were raised on the back of immune mice , and pouches were stimulated with L . intermedia SGS . Control mice were injected with endotoxin-free PBS . Mice immunized with L . intermedia SGS showed a significant increase in the total number of leukocytes ( Figure 3A ) accumulating in the air pouch compared with control mice injected with PBS . Surprisingly , this increase was associated with an accumulation of neutrophils ( 53% ) migrating to the air pouch ( Figure 3B ) , whereas migration of monocytes , eosinophils , and lymphocytes remained unaltered in SGS-immunized mice compared with control mice injected with PBS . Because chemokines , together with adhesion molecules , are key controllers of leukocyte migration , we tested for chemokine expression in the pouch lining tissue . CXC-class chemokines act mainly on neutrophils , whereas CC-class chemokines act on a larger group of cells including monocytes , eosinophils , and lymphocytes . Additionally , cytokines have long been recognized as key elements in the host response against Leishmania ( reviewed in [24] . As shown in Figure 3C , expression of CXCL1 , CCL2 , and CCL4 was significantly upregulated in SGS-immunized mice compared with control mice injected with PBS . Moreover , SGS-immune mice also displayed a significant increase in TNF-α expression without significant modulation in expression of IL-10 or IFN-γ ( Figure 3D ) . We then investigated whether the neutrophil accumulation effect observed in air pouches raised in SGS-immune mice and stimulated with SGS could be replicated in the ear dermis . As shown in Figure 4 , ear sections from control mice injected with PBS showed very few inflammatory cells at either 24 or 48 hours after SGS challenge . In contrast , ear sections from SGS-immunized mice displayed , 24 hours after SGS-challenge , numerous polymorphonuclear and few mononuclear cells ( Figure 4 ) ; at 48 hours , the inflammatory infiltrate was further increased . Presence of neutrophils was confirmed by myeloperoxidase staining and was not observed in control mice injected with PBS . Because SGS-immune mice displayed enhanced neutrophil recruitment , we investigated whether the presence of L . braziliensis , the parasite transmitted by L . intermedia sand flies , would exert any effect in this outcome . Therefore , air pouches were raised on the back of either naïve or SGS-immunized mice and pouches were stimulated with L . braziliensis ( Lb ) or L . braziliensis+L . intermedia SGS ( Lb+SGS ) . In naïve mice , we did not detect significant differences in the number of accumulating leukocytes ( Figure 5A ) or in the recruited cell subsets ( Figure 5B ) following inoculation with Lb or Lb+SGS ( Figure 5B ) . On the contrary , in SGS-immunized mice , Lb+SGS led to a robust and significant increase in the number of accumulating leukocytes compared with Lb alone ( Figure 5C ) . The increase in the number of leukocytes was due to accumulation of neutrophils in the pouches upon inoculation of Lb+SGS ( Figure 5D ) . There was no significant modulation in the recruitment of monocytes , eosinophils , or lymphocytes in naïve or SGS-immunized mice upon inoculation of Lb or Lb+SGS ( Figure 5B and 5D , respectively ) . We then investigated the modulation in cytokine and chemokine expression induced by L . braziliensis alone or in the presence of saliva in naïve and in SGS-immunized mice . In naïve mice , pouch stimulation with Lb+SGS induced a significant increase in CXCL10 and CCL2 expression compared with pouch inoculation with Lb alone ( Figure 6A ) . In SGS-immunized mice , chemokine expression was over two-fold higher compared with naïve mice ( Figure 6B ) . More important , pouch inoculation with Lb+SGS led to a different pattern of chemokine expression as indicated by a significant upregulation in expression of CXCL1 , CCL3 , and CCL4 compared with inoculation of Lb alone ( Figure 6B ) . Of note , in SGS-immunized mice , pouch inoculation with Lb+SGS led to a significant decrease in CXCL10 expression ( Figure 6B ) as opposed to naïve mice , in which pouch inoculation with Lb+SGS led to upregulation in CXCL10 expression ( Figure 6A ) . Regarding cytokine expression , naïve mice displayed augmented expression of both TNF-α and IL-10 upon pouch inoculation with Lb+SGS ( Figure 6C ) compared with inoculation with Lb alone . In SGS-immunized mice , stimulation with Lb+SGS led to specific increase in IL-10 expression ( Figure 6D ) . In this same group , inoculation of Lb+SGS was not capable of significantly decreasing expression of IFN-γ and TNF-α ( Figure 6D ) .
Sand flies use saliva to manipulate host homoeostasis , favoring the acquisition of a blood meal . These sand fly salivary molecules modify the skin microenvironment and this , in turn , may favor infection by Leishmania parasites ( rev . in [25] ) . Indeed , we previously observed that L . intermedia SGS-immune mice show a higher disease burden when challenged with L . braziliensis [10] . To gain understanding of the early events associated with inoculation of L . intermedia sand fly saliva , we evaluated leukocyte migration and chemokine/cytokine expression induced in the air-pouch model of inflammation . Importantly , the L . intermedia sand fly is the vector of L . braziliensis [2] , [3] , the main etiologic agent of cutaneous leishmaniasis . Injection of L . intermedia SGS into air pouches led to a significant increase in the recruitment of neutrophils and monocytes , corroborating previous findings that both of these cell populations are recruited to the site of saliva inoculation [7] , [10] , [12] , [17] , [20] , [26] . Indeed , the initial events following saliva inoculation have recently been explored by in vivo live imaging [27] . It was shown that sand fly biting leads to potent neutrophil migration and that these cells are efficiently infected by L . major , indicating that neutrophils may serve as host cells for Leishmania in the early phase of infection , as previously suggested [28] , [29] . Differently from L . longipalpis saliva [20] , L . intermedia did not lead to accumulation of eosinophils , which are strongly related to mosquito bites and allergies . This distinction in the cellular recruitment induced by L . intermedia vs . L . longipalpis saliva may be explained by variation in the salivary components within sand flies , such as maxadilan , present only in L . longipalpis [30] , and hyaluronidase , present in both L . longipalpis and various species within the genus Phlebotomus [31] , [32] . Pre-incubation of L . intermedia SGS with specific antisera was able to partially neutralize the leukocyte-recruiting effects of SGS , mainly decreasing the number of accumulating neutrophils , without a significant effect on monocytes . Similarly , Belkaid et al . showed that anti-SGS antibodies could neutralize the ability of P . papatasi SGS to enhance L . major infection in BALB/c mice [5]; however , SGS-immune mice showed an enhanced neutrophil recruitment upon stimulation with SGS in pre-sensitized animals . The actual levels of anti-saliva antibodies into the pouch exudates are unknown and may not be sufficient to neutralize the in vivo effects of the saliva . Another possibility for the in vivo findings is that salivary molecules are able to trigger cytokine/chemokine expression , despite the presence of neutralizing antibodies , leading to enhanced neutrophil recruitment . Leukocyte recruitment to sites of inflammation is a key event in both innate and adaptive immunity , and chemokines are major players that regulate the sequential steps of leukocyte rolling , firm adherence , and transmigration . In this sense , we tested for CXC-class chemokines , that act mainly on neutrophils , and CC-class chemokines that act on a larger group of cells including monocytes , eosinophils , and lymphocytes . In mice sensitized and stimulated with L . intermedia SGS , we saw increased neutrophil recruitment and significant upregulation in the expression of CXCL1 , CCL2 , and CCL4 . Indeed , CXC chemokines , such as CXCL1 , are critical molecules for neutrophil recruitment [33] , and CXCL1 is also a dominant chemokine in murine inflammatory responses [34] . CCL2 mediates neutrophil adherence and transmigration , a process dependent on activation of mast cells and release leukotrienes and PAF [35] , and CCL4 expression has been associated with a type 1 immune response [36] . Therefore , the enhanced neutrophil chemotaxis in SGS-immunized mice may result from a concomitant upregulation in CXCL1 and CC chemokines ( CCL2 and CCL4 ) and may be further amplified by upregulation in TNF-α , favoring a pro-inflammatory environment as shown by upregulation in CCL4 expression . Indeed , OVA-immunized mice displayed increased neutrophil migration upon antigen stimulation [37]; this effect was dependent on the release of TNF-α , and leukotriene B ( 4 ) [38] and mediated by CCL3 [39] . Increased neutrophil recruitment was also observed when SGS immunization was conducted in the ear dermis: SGS challenge led to development of an inflammatory reaction characterized by the presence of numerous neutrophils , confirming previously published results [10] . Similarly , exposure of mice to the bites of uninfected L . longipalpis , the vector of L . chagasi , induced an analogous effect [12] . In addition , it has been shown that PSG , the proteophosphoglycan-rich gel secreted by L . mexicana , also leads to potent neutrophil and macrophage recruitment [40] . In naïve mice , sand fly saliva [4] , [5] , [41]–[43] and fPPG , a component in PSG [44] , favor the initial establishment of Leishmania infection . In naïve mice , pouch stimulation with L . braziliensis+SGS was unable to alter the cellular recruitment induced by L . braziliensis alone ( Figure 5A ) , as opposed to previous studies conducted with L . longipalpis SGS+L . chagasi [20] or with L . major+L . longipalpis SGS [45]; however , pouch stimulation with Lb+SGS induced significant upregulation in the expression of CCL2 , CXCL10 , TNF-α , and IL-10 ( Figure 6A ) . Accordingly , experimental infection with L . braziliensis leads to increased leukocyte recruitment , CCL2 and CXCL10 expression [46] , and production of IL-10 [21] . More recently , increase CXCL10 and IL-10 expression were observed upon infection of human monocytes with L . braziliensis [47] . Therefore , we can suggest that , although presence of sand fly saliva does not add to the cellular recruitment induced by L . braziliensis , salivary antigens modulate the microenvironment , which may favor parasite establishment as previously suggested [48] . Here we were unable to determine parasite load in cellular exudates obtained from stimulated pouches; however , earlier work from our group also showed that pre-treatment of human monocytes with L . intermedia SGS followed by L . braziliensis infection led to a significant increase in TNF-α production without significant augmentation in the parasite load [18] . Pre-exposure to L . longipalpis [9] or P . papatasi saliva [5] or to bites from uninfected P . papatasi [49] results in protection against leishmaniasis; however , pre-exposure to L . intermedia saliva does not generate a protective effect upon a challenge infection with L . braziliensis+L . intermedia SGS [10] although SGS immunized mice do show a significantly lower initial parasite burden after challenge with L . braziliensis+SGS . We hypothesized that this early control in parasite load could be exerted by inflammatory cells ( mono and polymorphonuclear cells ) that are recruited following stimulation with saliva [10] . Indeed , the results herein show that SGS-immune mice displayed increased leukocyte recruitment , with a marked neutrophil influx ( Figure 3 ) and a similar finding was observed upon inoculation of Lb+SGS ( Figure 5 ) . We have recently shown that macrophages and neutrophils collaborate towards L . braziliensis elimination from infected macrophages [50] . Therefore , the current results support our previous hypothesis that an initial inflammatory environment may account for the early control of parasite load in SGS-immunized mice upon challenge with Lb+SGS . This control , however , is limited and L . braziliensis multiplication is later on observed , probably resulting from the pathogen favorable immune response ( lower IFN-γ to IL-4 ratio ) developed in SGS-immunized mice [10] . Indeed , in the present work , SGS-immunized mice stimulated with Lb+SGS showed decreased CXCL10 expression paralleled with an increased IL-10 expression . Presence of CXCL10 is seen in many Th1-type inflammatory diseases , where it is thought to play an important role in recruiting activated T cells into sites of tissue inflammation [51] . IL-10 , on the contrary , is associated with a non-healing L . major infection [52] and L . major persistence [53] . Consequently , lack of CXCL10 and presence of IL-10 may create a de-activating environment , favoring L . braziliensis expansion in the context of SGS-immunized mice . We cannot exclude that the increased neutrophil recruitment observed in SGS-immunized mice may also be relevant to the “Trojan horse” model , as documented for L . major infection [29] , in which parasites within neutrophils are silently transferred to macrophages and successfully establish infection . Indeed , the early influx and persistence of neutrophils after sand fly transmission of L . major appears critical for the development of cutaneous disease [27] . Additionally , L . major internalization delays the neutrophil apoptotic death program and induces CCL4 release , which recruits macrophages to the infection site [29] , [54] . Indeed , increased CCL4 expression was observed upon inoculation of Lb+SGS . Collectively , our data show that in naïve mice , inoculation of L . intermedia saliva plus L . braziliensis modifies the initial inflammatory environment as seen by increased neutrophil recruitment and IL-10 and TNF-α expression . Crucially , in mice sensitized with L . intermedia saliva and stimulated with L . braziliensis , these initial events are further modulated , as seen by a specific decrease in CXCL10 and a persistently increased IL-10 expression . We can speculate that the resulting effects leads to the higher disease burden as previously documented [10] . This study again shows important effects of the L . intermedia sand fly and L . braziliensis interaction . More important , it emphasizes how the immune response to sand fly may exert an under-appreciated role in endemic areas . We are currently characterizing L . intermedia salivary antigens to further identify the components that may induce the effects described here . | Transmission of Leishmania parasites occurs during blood feeding , when infected female sand flies inject humans with parasites and saliva . Chemokines and cytokines are secreted proteins that regulate the initial immune responses and have the potential of attracting and activating cells . Herein , we studied the expression of such molecules and the cellular recruitment induced by salivary proteins of the Lutzomyia intermedia sand fly . Of note , Lutzomyia intermedia is the main vector of Leishmania braziliensis , a parasite species that causes cutaneous leishmaniasis , a disease associated with the development of destructive skin lesions that can be fatal if left untreated . We observed that L . intermedia salivary proteins induce a potent cellular recruitment and modify the expression profile of chemokines and cytokines in mice . More importantly , in mice previously immunized with L . intermedia saliva , the alteration in the initial inflammatory response was even more pronounced , in terms of the number of cells recruited and in terms of gene expression pattern . These findings indicate that an existing immunity to L . intermedia sand fly induces an important modulation in the initial immune response that may , in turn , promote parasite multiplication , leading to the development of cutaneous leishmaniasis . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"immunology/immunomodulation",
"immunology/immune",
"response",
"immunology/immunity",
"to",
"infections"
] | 2010 | Immunity to Lutzomyia intermedia Saliva Modulates the Inflammatory Environment Induced by Leishmania braziliensis |
Hookworm disease is one of the most common infections and cause of a high disease burden in the tropics and subtropics . Remotely sensed ecological data and model-based geostatistics have been used recently to identify areas in need for hookworm control . Cross-sectional interview data and stool samples from 6 , 375 participants from nine different sites in Mbeya region , south-western Tanzania , were collected as part of a cohort study . Hookworm infection was assessed by microscopy of duplicate Kato-Katz thick smears from one stool sample from each participant . A geographic information system was used to obtain remotely sensed environmental data such as land surface temperature ( LST ) , vegetation cover , rainfall , and elevation , and combine them with hookworm infection data and with socio-demographic and behavioral data . Uni- and multivariable logistic regression was performed on sites separately and on the pooled dataset . Univariable analyses yielded significant associations for all ecological variables . Five ecological variables stayed significant in the final multivariable model: population density ( odds ratio ( OR ) = 0 . 68; 95% confidence interval ( CI ) = 0 . 63–0 . 73 ) , mean annual vegetation density ( OR = 0 . 11; 95% CI = 0 . 06–0 . 18 ) , mean annual LST during the day ( OR = 0 . 81; 95% CI = 0 . 75–0 . 88 ) , mean annual LST during the night ( OR = 1 . 54; 95% CI = 1 . 44–1 . 64 ) , and latrine coverage in household surroundings ( OR = 1 . 02; 95% CI = 1 . 01–1 . 04 ) . Interaction terms revealed substantial differences in associations of hookworm infection with population density , mean annual enhanced vegetation index , and latrine coverage between the two sites with the highest prevalence of infection . This study supports previous findings that remotely sensed data such as vegetation indices , LST , and elevation are strongly associated with hookworm prevalence . However , the results indicate that the influence of environmental conditions can differ substantially within a relatively small geographic area . The use of large-scale associations as a predictive tool on smaller scales is therefore problematic and should be handled with care .
Hookworm disease caused by Ancylostoma duodenale and Necator americanus is among the most common infections in sub-Saharan Africa ( SSA ) and affects up to 198 million people in this region [1]–[3] . It causes iron deficiency anemia and protein malnutrition , and has been shown to potentially cause growth retardation as well as intellectual and cognitive impairments in children [2]–[4] . Although hookworm disease causes only limited mortality , it ranks 49th in terms of years lost due to disability globally and between 30 and 49 in SSA countries [5] . The educational , economic , and public-health importance of hookworm infection necessitates comprehensive control strategies . To assure the effectiveness of control programs , financial as well as human resources have to be targeted to areas of greatest need . This warrants reliable estimates of hookworm distribution and of population numbers requiring intervention [6] . As hookworms do not replicate inside the human body and larvae become infective only under favorable conditions once excreted , environmental factors are crucial to hookworm development and therefore to possible transmission to humans . In recent years , the use of remotely sensed data has helped to enhance the understanding of the epidemiology and spatial distribution of hookworm infection [7] , [8] . Model-based geostatistics have been used to map helminth infection prevalence and to predict prevalence at unsampled locations at national , provincial , and regional levels [6] , [9]–[11] , however , under the assumption that the estimated associations are the same at all levels and not modified by regional characteristics . This study aimed to investigate the relationship between hookworm infection and remotely sensed ecological factors , such as elevation , vegetation density , land surface temperature ( LST ) , and rainfall , at an individual level in a cross-sectional survey of the “Evaluating and Monitoring the Impact of New Interventions” ( EMINI - http://www . mmrp . org/projects/cohort-studies/emini . html ) cohort in Mbeya region in south-western Tanzania . Furthermore , we analyzed the influence of potential confounders , such as age , sex and socio-economic status ( SES ) , on these associations . The main focus was on the investigation of site-specific effects and their comparison to effects in the pooled data set to ascertain if associations between ecological factors and hookworm infection found on a larger scale can equally be applied at smaller scales . Additional articles pointing to Ascaris lumbricoides , Trichuris trichiura , Schistosoma mansoni , and Schistosoma haematobium infection are in preparation .
The study was approved by the ethics committee of the Tanzanian National Institute for Medical Research and conducted according to the principles expressed in the Declaration of Helsinki . All participants provided written informed consent before enrolment into the study; parents consented for their minor children . Mbeya region is situated in south-western Tanzania . The region is predominantly rural and most income-generating activities are related to agriculture . Data for this study were collected from June 2008 to June 2009 as part of the third annual survey of the EMINI cohort study . In preparation for EMINI , a complete census was undertaken in nine distinct sites of Mbeya region . Over 42 , 000 households were identified and their locations were georeferenced using hand-held global positioning system ( GPS ) receivers ( SporTrak handheld GPS , Magellan Navigation Inc . , Santa Clara , CA , United States of America ) . A geographically stratified random sample of approximately 10% of these households was selected to participate in the cohort study . During the first two EMINI surveys only blood ( for HIV and Plasmodium falciparum malaria testing ) , urine ( for S . haematobium diagnosis ) , and sputum samples ( from participants with persistent cough for tuberculosis diagnosis ) were collected . Interventions during this time included HIV and tuberculosis counseling and referral , treatment of malaria ( with artemether/lumefantrine ) and S . haematobium infections ( with praziquantel ) . Stool collection only started at the third annual survey , and only included inhabitants of a 50% random sample of the EMINI households . Before this survey , intestinal nematodes were neither diagnosed nor treated as part of this study , and to our knowledge no other treatment programs had been conducted in the region . Stool samples were collected in pre-labeled screw-top containers , refrigerated at 4°C directly after collection using mobile refrigerators ( WAECO CoolFreeze CF-50 , WAECO , Emsdetten , Germany ) and kept cool until examined in the laboratory within two days of collection . The hookworm infection status of participants was established by Kato-Katz examination of two sub-samples ( 41 . 7 mg each ) from a single stool specimen which was thoroughly mixed before slide preparation . Kato-Katz slides were examined for hookworm eggs by experienced staff within one hour and for other helminth eggs within two days after slide preparation . Hookworm infection was defined as the presence of at least one hookworm egg in any of the two slides . Helminth-infected participants were offered treatment with albendazole ( for hookworm and other intestinal nematode infections ) and/or praziquantel ( for schistosome infections ) , according to their respective diagnoses . Interviews were conducted to collect socio-demographic information . Age , sex , latrine type , and previous worm treatment were included as potential confounders to be adjusted for during analyses . In order to adjust for possible socio-economic confounding , we constructed an SES score using polychoric principal component analysis ( PCA ) [12] , [13] to characterize the socio-economic situation of each household . This score combines information on the availability of certain items in the household ( radio , TV , mobile telephone , refrigerator , hand cart , bicycle , motor cycle , car , savings account ) ; sources of energy and drinking water; quality of materials used to build the main house; and number of persons per room in the household . Information on elevation was retrieved using the NASA Shuttle Radar Topography Mission ( SRTM ) global digital elevation model ( DEM ) version 2 . 1 with a nominal resolution of 90 m [14] . Rainfall and ambient temperature interpolated surfaces with 1 km spatial resolution [15] were downloaded from the WorldClim – Global Climate Data website ( http://www . worldclim . org/ ) . LST during the day ( LSTday ) and during the night ( LST-night ) , and vegetation density ( EVI = enhanced vegetation index ) were retrieved from data collected during NASA's Moderate-Resolution Imaging Spectroradiometer ( MODIS ) mission and were acquired from the Land Processes Distributed Active Archive Center ( LP DAAC ) , located at the U . S . Geological Survey ( USGS ) Earth Resources Observation and Science ( EROS ) Center [16] . LST data ( version MOD11A2 ) have 8 days temporal and ∼1 km spatial resolution . Vegetation data ( version MOD13Q1 ) have 16 days temporal and 250 m spatial resolution [17] . Both , LST and vegetation data were processed in the following way to produce long-term averages: data surfaces for every 8-day period ( LST ) and every 16-day period ( EVI ) for the years 2003 to 2008 were imported into Idrisi GIS software v . 32 ( Clark Labs , Worcester , MA , United States of America ) . In Idrisi , long-term averages of day- and night-LST and EVI were calculated utilizing only those pixels that were “good data” according to the quality assessment layers that are distributed together with the actual data . Then LST was converted to °C and EVI was converted back to its native range between −1 and +1 . Population and household densities , ambient temperature , rainfall , LST , EVI , and elevation variables were averaged for a buffer area within a 1000 m radius around each household in order to characterize the ecological situation around the household . Stata statistics software ( version 11 , StataCorp , College Station , TX , United States of America ) was used for all statistical analyses . Some of the variables were transformed in order to yield interpretable results . Reported odds ratios ( OR ) for continuous variables correspond to an increase of 10 years for age , 100 m for elevation , 10 mm for mean annual rainfall , 1 , 000 people/km2 for population density , and 0 . 1 units for EVI . Univariable logistic regression was performed with each variable , adjusting for within-household clustering using Huber/White/Sandwich variance estimates [18]–[20] . Variables that either had a Wald's p-value<0 . 2 or were considered to be causally linked to hookworm infection were included in the following selection process . This study mainly focused on ecological data which by their nature are prone to be correlated . To avoid problems in effect estimation such as variance inflation , all variables of interest were tested for multicollinearity by calculating the variance inflation factor ( VIF ) [18] . A VIF above 10 was considered as an indicator for serious multicollinearity [19] , [20] and the respective variables were removed from further analyses . Subsequently , two separate logistic models were developed: the first contained solely variables collected on an individual level , i . e . , age , sex , and previous worm treatment variables; the second model grouped together variables that were collected at the household level . These included environmental variables as well as the SES score , latrine coverage , and latrine type . Model selection was based on a 5% significance level , i . e . , removal of variables that had p>0 . 05 , and on the contribution to the goodness of model fit according to the Bayesian information criterion ( BIC ) . When the removal of a variable whose effect estimate did not reach statistical significance resulted in a major increase of the BIC , the variable was not excluded from the model . Remaining variables from the separate models were merged into a final model where variables with p>0 . 05 were removed by hand . The resulting model was then run on a reduced dataset restricted to the two sites with the highest hookworm prevalence . To detect differences in effects on a site level , a moderated multiple regression was performed by introducing a site dummy variable as the moderator and interactions of this moderator with each environmental variables . Furthermore , the final model was applied to each of these two sites separately and compared to the results of the moderated model .
Of the 6 , 375 subjects ( from 1 , 617 households ) participating in this study , 17% ( 1 , 080 participants ) were tested positive for hookworm infection . Most infected participants had low intensity infections ( 1 , 061 ) , whereas medium ( 14 ) and high intensity infections ( 5 ) were rare [21] . The diverse environmental conditions in the study area are indicated by large ranges for elevation ( Figure 1 ) and other environmental variables ( Table 1 ) . The study population included slightly more female than male participants . The median age of 16 . 6 years indicates that the majority of study subjects were children and adolescents . The prevalence of hookworm infection rose sharply from birth to adolescence and reached a plateau in early adulthood , after which it stayed relatively constant ( Figure 2 ) . Most households had simple or improved ventilated pit latrines , whereas water flush toilets were uncommon . Site-specific hookworm prevalences ranged from less than 2% in Iyunga to more than 50% in Itaka ( Figure 3 ) . With 931 participants , Kyela was the biggest site and Iyunga with 444 participants the smallest . Due to exceptionally high hookworm prevalences , Itaka ( 53 . 1% ) and Kyela ( 40 . 8% ) were selected for the site-specific analyses . In univariable logistic regression analyses of the complete dataset which included all nine sites ( Table 2 ) the estimates for all considered variables had p-values below 0 . 2 , which was chosen as the cut-off for inclusion into further analyses . Population density , elevation and slope were inversely associated with hookworm infection , whereas the other ecological variables showed positive associations . SES , previous anthelmintic treatment , and latrine coverage were again inversely related to hookworm infection . Multicollinearity analysis revealed a VIF above 10 for the variables LST-night ( VIF = 15 . 77 ) , elevation ( VIF = 75 . 18 ) , and mean ambient temperature ( VIF = 46 . 84 ) . Elevation and mean annual ambient temperature were therefore excluded from subsequent analyses , and LST-night included since soil temperature seems more directly related to the development of hookworm larvae than ambient temperature and elevation . Removal of these two variables reduced the VIF for LST-night to 2 . 5 . In the multivariable regression model including only household-level data ( not shown ) , the p-values for mean annual rainfall , slope , and latrine type exceeded the 5% threshold and were excluded from the model . When including individual-level data into the model , only sex yielded a p-value above 0 . 05 and was excluded , whereas age and previous anthelmintic treatment remained significantly associated with hookworm infection . Compared to univariable regression results , the direction of the effect in the multivariable models changed for several variables: the ORs for EVI and LST-day switched from above to below unity; the negative univariable association of latrine coverage changed to positive in multivariable analysis . In the multivariable model combining household-level and individual-level variables ( Table 3 , “All sites” ) all included variables yielded significant p-values . No qualitative changes in the ORs compared to the separate models for household-level and individual-level variables ( data not shown ) were observed . Equally , the magnitude of effects in the combined model is comparable to those of the separate models , indicating that the effects of both sets of variables are independent of each other . Running a model with the same variables on data from Kyela ( Table 3 , “Kyela site” ) only yielded statistically significant ORs for LST-day ( OR = 1 . 38; p = 0 . 005 ) , SES score ( OR = 0 . 68; p = 0 . 015 ) , and age ( OR = 1 . 12; p = 0 . 002 ) . While the magnitude of ORs for SES score and age differed only marginally from the all-sites model , a qualitative difference was observed for LST-day where the association with hookworm infection switched from negative in the all sites model to positive in the Kyela site model . Site-specific analysis for Itaka ( Table 3 , “Itaka site” ) resulted in significant ORs for population density ( OR = 0 . 08; p = 0 . 008 ) , LST-night ( OR = 1 . 56; p = 0 . 010 ) , latrine coverage ( OR = 0 . 94; p = 0 . 022 ) , age ( OR = 1 . 16; p = 0 . 001 ) , and prior anthelmintic treatment ( OR = 0 . 42; p = 0 . 042 ) , of which only latrine coverage differed qualitatively from the all-sites model . To test the presence of site-specific effects , we introduced site-interaction terms for environmental variables . In the moderated model , which was estimated on a data set restricted to observations from Itaka and Kyela sites , only the interaction term for population density yielded a significant p-value ( p = 0 . 008 ) . The p-values for the interaction terms for EVI and latrine coverage slightly exceeded the 5% threshold ( p = 0 . 052 and 0 . 086 , respectively ) and were therefore also considered as relevant . The main effects of the moderated model represent the effects in Itaka , i . e . , site = 0 , whereas the effects for Kyela ( site = 1 ) can be calculated by multiplying the main effect with the respective effect of the interaction term . Keeping all variables at their average value , infection odds did not vary significantly between Kyela and Itaka ( OR = 3 . 26; p = 0 . 592 ) . However , the effect of population density , EVI and latrine coverage on infection odds was strongly dependent on the site . The data in Table 4 summarize the conditions in Kyela and Itaka , and the site-specific predictions of hookworm infection probability in Figure 4 demonstrate that a qualitative difference between the two sites was present for the association of population density and EVI with hookworm infection , whereas the association of latrine coverage differed only quantitatively between Itaka and Kyela sites .
Our results demonstrate that hookworm infection in the study population is strongly associated with ecological factors . The univariable analyses further show that infection is favored when these factors entail more tropical conditions . This is in agreement with the literature , where similar associations of infection with elevation , temperature , rainfall , and vegetation ( as an indicator of soil humidity and shade ) are reported [22]–[24] . It also concurs with laboratory studies which show that hookworm larvae require warm and moist conditions in order to survive [25] , [26] , a fact that is also demonstrated by the absence of hookworm infection in more temperate climates world-wide [27] and very low prevalences in the high-altitude sites within our study area . However , our data also show that some of these associations switch direction in multivariable analysis . The associations of EVI and LSTday with hookworm infection change from positive in univariable analysis to negative in the all-sites multivariable model , whereas the association of latrine coverage changes from negative to positive . These switches in direction are mainly due to the inclusion of LST-night , which appears to be the best predictor of hookworm infection among the environmental variables . When excluding LST-night from the all-sites multivariable model shown in Table 3 , both EVI and LST-day maintain the significant positive association with infection ( data not shown ) that they have in univariable analysis ( Table 2 ) and latrine coverage maintains its negative association , although this is no longer significant . For LST-day this makes sense in an area including high altitude sites with rather low temperatures . In this setting , the minimum temperature ( for which LST-night is a better proxy than LST-day ) is the main limiting factor for the survival of hookworm larvae . Therefore , in the complete model that includes both LST-night and LST-day , LST-night explains most of the variation that is due to unsuitably low minimum temperatures , whereas the role of LST-day in this model is limited to explain the variation that is due to unsuitably high maximum temperatures . In our study area , LST-day ranges from 22 to 39°C . Thus our finding corresponds with experimental study results suggesting that development of hookworm larvae reaches its peak between 20 and 30°C and ceases at around 40°C [25] . The switches in direction of the associations of EVI and latrine coverage with hookworm infection in multivariable analysis are harder to explain but are most likely based on similar effects . Contrary to the above described differences between univariable and multivariable models , population density , SES , age , and previous deworming show similar associations with hookworm infection in uni- and multivariable analyses . The negative associations of SES and deworming with infection are highly plausible and have also been reported in other studies [1] , [28] . This also applies to the positive association of age with infection [29] , [30] . Regarding the relationship of population density with infection , the interpretation is more complicated . While higher population densities increase the chance of hookworm larvae to find a host and could thus favor transmission , in our study area , they are also an indicator of more urban and thus more developed conditions , which would reduce transmission . Thus , the negative association with hookworm infection found in this study is also plausible , and accordingly both negative and positive associations have been reported in the literature [10] , [24] . Another interesting phenomenon are the differences in association of several factors , when comparing the two site specific multivariable models for Kyela and Itaka ( columns “Kyela site” and “Itaka site” in Table 3 ) with each other and when comparing each of them with the all-sites model ( “All sites” in Table 3 ) . When comparing Tables 1 and 4 , it is obvious that ecological variables in the all-sites model cover a much wider range of conditions than in each site-specific model , which is a plausible reason for the differences of the site-specific models versus the all-sites model . Figure 4 demonstrates that the above reasoning may also apply to the contradictory results when comparing the two site-specific models with each other: population density and latrine coverage show far more variation in Kyela than in Itaka , and the EVI ranges for both sites do not show any overlap , with much lower vegetation cover in Itaka . Thus , the different conditions in the two sites are a likely explanation for the different associations of these factors in the two sites . However , it is also possible that these differences in association are a consequence of one or more unobserved factors that our analysis is unable to account for . Strengths of this study include the large number of participants of all age groups and the detailed information that we have for each individual , including the place of residence . This allows for a detailed assessment of individual exposure to environmental factors . In contrast , most other studies into the spatial epidemiology of hookworm and other soil-transmitted helminth infections are school-based [9]–[11] , [24] , [31]–[33] . Thus , they do not examine hookworm infection in adults and rely on the geographical position of the school to quantify participant's exposure to environmental factors [34] . However , our study also has some limitations . The use of only one stool specimen for the determination of hookworm infection status is known to lack sensitivity due to the intra-specimen and day-to-day variation in hookworm egg output [35] , [36] . Although we prepared two Kato-Katz thick smears from each stool specimen to increase sensitivity , it is likely that we missed some of the lighter infections . Unfortunately the Kato-Katz examination of stool is unable to differentiate between N . americanus and A . duodenale . However , previous studies indicate that N . americanus is the predominant species in East Africa [32] , and stool-PCR data from our own ongoing WHIS study , where we only find N . americanus infections , seem to indicate that this is also the case for our study area . Thus it is likely that most or all of the hookworm infections in our study population were caused by N . americanus , although we cannot completely exclude that A . duodenale is also present . Unfortunately , we are also lacking information about soil composition in the study area which has been shown to strongly influence hookworm infection [24] , [31] . Motility of the hookworm larvae is crucial to avoid adverse environmental conditions and is thus important for their survival . The porosity of sandy soils facilitates larval movement deeper into the soil to escape desiccation and upwards movement to avoid rising water levels after heavy rainfall . Soils with high clay content are less porous and thus inhibit larval motility [23] , [37]–[39] . Furthermore , apart from previous worm treatment which was assessed by interview , our study does not account for behavioral factors which also can strongly influence hookworm transmission and prevalence . However , although soil composition and behavior are both important determinants of hookworm infection which would likely have improved our models if included , data on these factors are rarely available in tropical developing countries where hookworm is most prevalent . Thus , their potential to predict infection in order to plan helminth control is limited , especially in those regions where control is urgently needed . This study and many others have shown that remotely sensed data such as vegetation indices , LST , and elevation are strongly associated with hookworm prevalence [2] , [8] . However , our study also shows that these associations are scale-dependent and that predictions using these data should be handled with care . On a large scale , they can provide powerful tools to identify regions that warrant control and intervention programs , their big advantage being public availability and global coverage . Nevertheless , when making predictions of hookworm infection on a smaller scale , regional characteristics , such as seasonal flooding , dry spells , etc . , have to be taken into account . As our study has shown , even within a relatively small geographic area the effects of environmental conditions can differ to a large extent . Thus , large-scale findings cannot necessarily be used for prediction on smaller scales and vice versa . | Hookworm disease , caused by the nematodes Ancylostoma duodenale and Necator americanus , is an important cause of maternal and child morbidity in the developing countries of the tropics and subtropics . In children , hookworm disease has been shown to potentially result in growth retardation as well as intellectual and cognitive impairments . In a cross-sectional survey in Mbeya region , Tanzania , we assessed the effects of possible risk factors for hookworm infection with a focus on remotely sensed ecological factors such as elevation , vegetation density , land surface temperature , and rainfall . We found that several ecological variables were significantly associated with hookworm infection . However , differing effects for these factors were estimated when performing the analyses separately for the two sites with the highest hookworm prevalence . Our study shows that effects are scale-dependent and that prediction at smaller scales using large-scale data and vice versa should be handled with caution , because regional variation can substantially influence the presence of hookworm infection . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"medicine",
"global",
"health",
"infectious",
"disease",
"epidemiology",
"epidemiology"
] | 2013 | Hookworm Infection and Environmental Factors in Mbeya Region, Tanzania: A Cross-Sectional, Population-Based Study |
Virus satellites are widespread subcellular entities , present both in eukaryotic and in prokaryotic cells . Their modus vivendi involves parasitism of the life cycle of their inducing helper viruses , which assures their transmission to a new host . However , the evolutionary and ecological implications of satellites on helper viruses remain unclear . Here , using staphylococcal pathogenicity islands ( SaPIs ) as a model of virus satellites , we experimentally show that helper viruses rapidly evolve resistance to their virus satellites , preventing SaPI proliferation , and SaPIs in turn can readily evolve to overcome phage resistance . Genomic analyses of both these experimentally evolved strains as well as naturally occurring bacteriophages suggest that the SaPIs drive the coexistence of multiple alleles of the phage-coded SaPI inducing genes , as well as sometimes selecting for the absence of the SaPI depressing genes . We report similar ( accidental ) evolution of resistance to SaPIs in laboratory phages used for Staphylococcus aureus typing and also obtain the same qualitative results in both experimental evolution and phylogenetic studies of Enterococcus faecalis phages and their satellites viruses . In summary , our results suggest that helper and satellite viruses undergo rapid coevolution , which is likely to play a key role in the evolution and ecology of the viruses as well as their prokaryotic hosts .
Satellites are defined as viruses which have a life cycle dependent on a helper virus , but lack extensive nucleotide sequence homology to the helper virus and are dispensable for helper virus proliferation [1–4] . These infectious elements , present both in eukaryotic and prokaryotic cells , have far-reaching consequences . First , they can play a major role in the population dynamics of viruses and their hosts , with satellite viruses able to greatly limit the proliferation of their helper viruses . For example , the presence of Staphylococcus aureus pathogenicity islands ( SaPIs ) , a type of satellite virus , reduces phage proliferation [5 , 6] . Given the crucial role of viruses in shaping microbial communities [7] , satellite viruses may themselves be a key driver of microbial community structure and function . Second , satellite viruses can have a dramatic role in virulence by controlling the symptoms induced by their helper viruses or by encoding relevant virulence genes . For example , Hepatitis B virus ( HBV ) is a major health problem of global impact . Among the HBV chronically infected patients , many are co-infected with the Hepatitis delta virus ( HDV ) , a satellite virus that needs the HBV for propagation . HDV is the smallest virus known to infect humans and is clinically relevant because it causes a fulminant hepatitis or a more rapid progression of liver disease in the setting of chronic HBV infection [8] . Satellite prokaryotic viruses ( satellite phages ) are also relevant both in the virulence and in the emergence of novel bacterial pathogens . In addition to the SaPIs , which have a relevant role in bacterial evolution and pathogenesis by encoding relevant virulence factors [9 , 10] , Vibrio cholerae phage satellites control not only the expression of the clinically relevant CTX phage-coded cholera toxin , but also the transmission of their helper CTX phage [11 , 12] . Interactions between hosts and their parasites frequently result in antagonistic coevolution , with host evolving defence and parasites evolving counter defence [13] . Given that satellite viruses typically have negative consequences for their helper viruses , while the satellite viruses require ‘susceptible” viruses for their proliferation , antagonistic coevolution is a feasible outcome . Antagonistic coevolution can have major impacts on the ecology and evolution of viruses and their hosts . Specifically , the degree of resistance of helpers to their satellites will determine the spread of both helper and satellite viruses between their prokaryotic or eukaryotic hosts , which in turn affects host population dynamics and evolutionary trajectories . While the existence of satellite viruses clearly shows adaptation of satellites to helper viruses , it is currently unclear if satellite viruses drive significant evolutionary change in helper virus resistance and , if so , whether satellite viruses in turn evolve to overcome helper virus resistance . Here we address these questions for the interaction between the SaPIs and their inducing phages . The SaPIs are the prototypical members of a widespread family of highly mobile pathogenicity islands , the PICIs ( phage-inducible chromosomal islands ) , that exploit the life cycle of their helper phages with elegant precision to enable their rapid replication and promiscuous spread [4 , 10] . In the absence of helper phage lytic growth , the island is maintained in a quiescent prophage-like state by a global repressor , Stl , which controls expression of most of the SaPI genes [14] . Following infection by a helper phage or induction of a helper prophage , SaPI de-repression is effected by specific , non-essential “moonlighting” phage proteins that bind to Stl , disrupting the Stl-DNA complex and thereby initiating the excision-replication-packaging ( ERP ) cycle of the island [15 , 16] . Different SaPIs encode different Stl proteins , so each SaPI commands a specific phage protein for its induction [15 , 16] . Since SaPIs require phage proteins to be packaged [17 , 18] , this strategy couples the SaPI and phage cycles , but imposes a very significant transmission cost on the helper phages . In previous work , we observed that different helper phages encoded allelic variants of the inducing genes with different affinity for the SaPI-encoded repressors [15] . Moreover , we also observed that phage mutants capable of forming plaques on SaPI-positive strains had mutations in the phage-coded inducing genes [15] . Here , we experimentally show that phages that fail to induce SaPIs as a result of spontaneous mutations of the inducing proteins are strongly favoured by selection , but that these mutants carry fitness cost in the absence of SaPIs . Propagation of SaPIs on these non-inducing phages results in strong selection of spontaneous SaPI stl-mutants that can be packaged and transferred by the evolved non-inducing phages , imposing a large transmission cost on the helper phages . Furthermore , bioinformatics data supports the view that SaPIs are an important selective pressure driving the diversity of both genes and gene content in S . aureus phages . Finally , to show the generality of this result we report similar experimental and bioinformatic results for Enterococcus faecalis phages . Taken together , our results suggest that helper and satellite viruses undergo extensive antagonistic coevolution .
To determine if SaPIs play an obvious role in phage evolution , we initially analysed the phage sequences deposited in GenBank and identified allelic variants of the phage-coded SaPIbov1 , SaPI1 and SaPIbov2 inducing proteins , corresponding to the dUTPase ( Dut ) , Sri and 80α ORF15-like proteins , respectively [15] . Representative examples of the different SaPI inducers are shown in S1 Fig . We tested the different selective forces that may have been shaping these proteins during their evolution in vivo by calculating and comparing the dN−dS values of the representative SaPI inducer genes ( S1 Table ) . The dN−dS , which measures the difference in substitutions rates between non-synonymous site ( dN ) and synonymous site ( dS ) , is classically used as an indicator of selective pressure acting on a protein-coding gene . As is summarised in Table 1 and shown in S1 Table , all the dN−dS comparisons were significantly lower than 0 ( p < 0 . 005 ) , indicating that the SaPI inducers are under purifying selection . It is assumed that the main consequence of the purifying selection is a reduction in the level of variation present in the locus under selection , produced by the removal from the population of less-adapted variants . However , the existence of multiple alleles in the phage-coded SaPI inducers suggests the existence of an evolutionary force operating in opposite direction that maintains the diversity observed in the SaPI inducer proteins . In previous studies , we demonstrated that variants of the SaPIbov1 and SaPIbov2 derepressing proteins differentially induce the SaPIbov1 and SaPIbov2 cycles , respectively [15] . Moreover , we also demonstrated that the highly divergent region present in the Dut proteins ( motif VI; S1 Fig ) determines the capacity of the phages to induce the SaPIbov1 cycle by controlling the affinity between the SaPIbov1 Stl repressor and the Dut protein [15 , 16] . These results suggest that SaPIs could favour certain alleles in the phage population because they have reduced capacity to induce the SaPI cycles . To test the hypothesis that phages are under strong selection to resist SaPIs , we experimentally determined if the interaction with the SaPIs resulted in the evolution of phages carrying variants in the SaPI inducing proteins . Phage 80α was used as a model because it induces three different SaPIs: SaPIbov1 , SaPIbov2 and SaPI1 . Strains RN4220 ( SaPI-negative; a control ) or JP1996 ( RN4220 derivative carrying SaPIbov1 ) were initially infected with phage 80α ( 1:1 ratio , see scheme in S2 Fig ) . The resulting lysates were then used to infect again the same strains and after the third passage phages were phenotypically characterised . The phage lysates obtained after the third passage in strain JP1996 ( SaPIbov1-positive ) were used to infect strain JP2129 , an RN4220 derivative carrying SaPIbov2 . After the third passage done in strain JP2129 , the evolved phages were then used to infect JP2966 , an RN4220 derivative carrying SaPI1 . As a control , phages only infecting RN4220 were propagated and analysed through the experiment ( see scheme in S2 Fig ) . We first determined growth of the ancestral and evolved phages . As observed in Fig 1A , while SaPIs blocked plaque formation by the ancestral 80α phage or by the phages evolved on the SaPI negative strain , they did not obviously interfere with the reproduction of the evolved phage mutant . These results demonstrate that phages evolved in the presence of SaPI no longer suffer reduced costs of SaPI parasitism . The most likely explanation of this reduction in cost is that the evolved phages were resistant to the SaPIs . This was investigated by generating lysogens from two evolved phages , which incidentally carried mutations in all three SaPI inducers ( see below and S2 Table ) . Next we introduced into the different lysogens derivatives of SaPI1 , SaPIbov1 or SaPIbov2 carrying a tetM marker , which facilitates transfer studies . The different SaPI-positive strains were then SOS ( mitomycin C ) induced and the capacity of the different phages to induce the SaPIs cycle was analysed . As shown in Fig 1B and S3 Table , none of the phage mutants induced the SaPIs . Moreover , uniquely the titre of the ancestral 80α phage , but not that from the evolved phages , was reduced by the presence of the islands ( S3 Table ) . These experiments show that culturing phages with SaPIs results in the evolution of phage resistant to SaPIs ( i . e no longer induce the SaPI cycle ) , and this resistance results in greatly increased phage proliferation on susceptible bacterial hosts . From the aforementioned experiment , five 80α phages evolved after the third passage on strain JP1996 ( SaPIbov1-positve ) and 5 from the third passage on the RN4220 ( SaPI-negative ) branch were completely sequenced and analysed . Only phages that interacted with SaPIbov1 contained mutations in their genomes , which were in all cases located in the SaPIbov1 inducer gene dut ( dUTPase ) . This result was further confirmed by sequencing the dut gene from other 120 evolved phages ( 60 infecting RN4220 and 60 infecting JP1996 ) , obtained from 3 independent experiments . As summarised in Table 2 and shown in S2 Table , 100% of the phages infecting the SaPIbov1-positive strain showed mutations in the SaPIbov1-inducing gene dut . By contrast , no mutations were observed either in the other SaPI inducer genes , corresponding to sri and ORF15 , or in the phages infecting the SaPIbov1-negative strain ( Tables 2 and S2 ) . To determine the genetic basis of resistance to the other SaPIs , SaPIbov2 and SaPI1 , the SaPI inducer genes from 120 evolved phages ( from 3 independent experiments , 60 after interacting with SaPIbov2 and 60 after interacting with SaPI1 ) were analysed . The SaPI inducer genes were also sequenced from 60 phages that had only infected the SaPI-negative RN4220 strain ( S2 Fig ) . As occurred with SaPIbov1 , interaction with SaPIbov2 and SaPI1 selected for phages carrying missense and nonsense mutations in the SaPI inducer genes ( Tables 2 and S2 ) . In previous work , we demonstrated that expression of the cloned SaPI inducing genes in a SaPI-containing strain was sufficient to induce the SaPI cycles [15] . As shown in Fig 1C , the cloned dut genes from the evolved phages did not induce SaPIbov1 , while the wild-type gene did . As the Dut protein levels produced from these constructs are comparable ( Fig 1C ) , this result confirms that the mutations present in the inducing genes are the cause of the inability of the evolved phages to de-repress the SaPI cycles . Given the high cost imposed by SaPIs on helper phages and the apparent ease at which they can evolve resistance , why isn’t resistance to SaPI exploitation ubiquitous ? Part of the explanation might be that there are costs associated with resistance . Indeed , in the absence of the SaPIs both the phage titres and the phage plaque sizes were slightly but consistently reduced in the phage mutants , compared with the wt phage ( S3 Table ) . Moreover , the number of phages carrying the wild-type versions of the SaPIbov1 and SaPIbov2 inducing genes increased in absence of the interference ( Table 2 ) . This putative cost was confirmed by competition experiments ( in duplicate ) among the ancestral 80α and two different evolved phages on the SaPI-negative host ( RN4220 ) . Two thousand p . f . u . of a mixed population ( ratio 1:1 ) of the wt and one of the evolved phages was used to infect a plate containing 1 x 106 RN4220 cells . Confluent phage plaques were collected , the lysate filtered and the procedure repeated four more times . After the fifth passage , 20 independent plaques from each of the different experiments were selected and the percentage of the phages under competition was evaluated by PCR and sequencing analyses of SaPI inducing genes . While the 80α wt and the evolved 80α phages were present in equal numbers in the mixed initial population , passages through the SaPI-negative RN4220 strain selected for the wt phage ( p < 0 . 01; Table 3 ) , confirming there is obvious cost to being resistant to single or multiple SaPIs in this experimental context . We next determined whether SaPIs can in turn adapt to the presence of the experimentally evolved non-inducing phages . We made use of two different phage mutants that had evolved resistance to two SaPIs ( SaPIbov1 and SaPIbov2 ) in the previous experiments ( Table 4 ) . The SaPIbov1 tst::tetM and SaPIbov2 bap::tetM islands , carrying a tetM marker that facilitates the SaPI transfer analyses , were introduced both in the two mutants and in the wt 80α phages . The different lysogenic SaPI positive strains were SOS ( mitomycin C ) induced and the islands transferred to the cognate recipient strains carrying the same phage that was present in the donor strain . After the transfer , the SaPI-positive strains were recollected and the procedure repeated 7 more times . After the eighth passage , the SaPI titre obtained was compared with that obtained with the original SaPIs . Remarkably , at the end of the experiment the SaPIs that interacted with the mutant phages increased their titres more than 104-fold ( Table 4 ) , suggesting that the SaPIs had adapted to the presence of the SaPI insensitive phages . By contrast , the titres of those SaPIs interacting with the wt phage 80α did not change significantly through time . Note that these experiments were done four independent times and the obtained results were consistent in the parallel experiments . To determine the genetic basis of SaPI adaption to “resistant” phage , 21 different colonies , randomly chosen from the different replicates , were individually analysed and the evolved SaPIs sequenced . As shown in S4 Table , the analysis of the individual colonies confirmed that the SaPIs had evolved in the presence of the mutant phages , but not in presence of the wt phage 80α . Importantly , the evolved SaPIs all had mutations in the stl gene . These mutations , located in the coding or in the promoter region of the stl gene ( S4 Table ) , generated in all the cases an stl- mutant genotype . Thus , all the evolved SaPIs replicated autonomously in absence of any inducing phage . Previous work has shown that stl mutant SaPIs can be transferred by non-helper phages [14] , and this is presumably why stl mutations massively increased SaPI transfer rates in the presence of the evolved “resistant” phages . Finally , we analysed if the coevolved SaPIs blocked reproduction of the evolved phages . As shown in Fig 2 , this was the case . Thus , while the evolved phages were resistant to the presence of the original islands , the evolved SaPIs reduced phage reproduction . Given the likely importance of SaPI-imposed selection , we speculated simple amplification of phages to obtain high titers of phage stock may have itself resulted in significant SaPI-imposed evolution . Phage collections have been traditionally used to type S . aureus strains . These collections are generated , maintained and amplified by infecting different propagating strains with specific phages . Interestingly , and as occurs in nature , most propagating strains carry uncharacterised prophages and SaPIs . In view of this , we hypothesised that the phage populations used for typing could contain mixed populations that have evolved in response to the SaPIs present in the propagating strains . To test this , we obtained 3 phage samples ( ϕ29 , ϕ52A and ϕ55 ) from a reference laboratory , and isolated , from each of these samples , five single phages , which were amplified using the non-lysogenic RN4220 strain . We used both the amplified phages obtained from the single plaques as well as the original phage populations to infect the non-lysogenic strain RN4220 , as well as derivatives of this strain carrying SaPI1 , SaPIbov1 or SaPIbov2 . The rationale for this experiment was to compare the interference observed with these different phage samples . We hypothesised that if both samples had the same plating efficiency ( interference ) rate when infecting any of the SaPI-positive strains , both phage populations would be genetically homogenous ( related to the SaPI inducers ) . By contrast , if a different behaviour was observed , and one of the samples infected the SaPI-positive strain better than the other sample , this would imply that the original population contained a mixed phage population that probably had evolved in response to the SaPI interference . Although the analysis of the ϕ29 and ϕ52A phage populations did not reveal any difference between the purified phages and those present in the samples from the reference laboratory , 1% of the original ϕ55 phage population generated plaques in the SaPI1-positive strain . By contrast , only 0 . 001% ( 1000 x reduction ) of the purified ϕ55 phages generated plaques in this strain . This result suggested that the original phage lysate contained at least two different phage populations , evolved from a common ancestor , carrying variants of the SaPI1 inducing gene . To test this , one of the previously purified phages infecting RN4220 but showing interference to the SaPI-positive strain was completely sequenced ( ϕ55–2 ) . One phage having no interference to SaPI1 was also purified and sequenced ( ϕ55–3 ) . The genome length of ϕ55–2 is 41 , 898 bp , containing the information for approximately 81 ORFs of 50 or more codons , and is deposited in GenBank under accession number KR709302 . The genome length of ϕ55–3 is 42 , 309 bp , with approximately 83 ORFs , and is deposited in GenBank under accession number KR709303 . Both ϕ55–2 and ϕ55–3 belong to a class of related staphylococcal Siphoviridae [19] . Overall , both phages are >99 . 9% identical except for a divergent region of ∼1800 bp that contains the gene coding for the SaPI1 inducer ( Fig 3A ) . In the ϕ55–2 phage , this region encodes 3 ORFs , the last one being the SaPI1 inducer . By contrast , phage ϕ55–3 encodes 5 different ORFs , including a variant of the SaPI1 inducer ( Fig 3B ) . Since the ORFs present in phage ϕ55–3 were also contained in other S . aureus phages , one of many plausible explanations for the differences between these two phages is that recombination occurred between ϕ55–2 and a prophage residing in the propagating strains . To verify that the aforementioned changes observed in phage ϕ55–3 were not generated during the purification and amplification of the phage , PCR experiments with specific oligonucleotides for each of the phages were performed , using DNA samples obtained from the original phage population ( without amplification ) . To confirm that the mutations present in phage ϕ55–3 conferred an advantage for the phage in the presence of a SaPI1-positive strain , competition experiments ( in triplicate ) were performed in which a SaPI1-negative or a SaPI1-positive strain were infected ( phage:bacteria ratio 1:3 ) with a mixed population ( 1:1 ) of the ϕ55–2 and ϕ55–3 phages . The lysates obtained from each experiment were used to infect again the same strains , and after the third passage , the number of the ϕ55–2 and ϕ55–3 phages was evaluated by PCR using oligonucleotides that specifically recognise the different allelic variants of the phage coded SaPI1 inducers . While both phages were present in equal numbers after infecting the SaPI-negative strain ( ϕ55–2: 55%; ϕ55–3: 45% ) , passages through the SaPI1-positve strain selected for ϕ55–3 ( >95% ) . The previous results suggested that it would be possible to find closely related phages encoding different alleles of the SaPI inducers as a consequence of the phage interaction with the SaPIs . To address this , we initially performed a phylogenetic analysis of 33 randomly selected staphylococcal phages ( S3A Fig ) . Next , we compared the SaPI inducer sequences from closely related phages . As hypothesised , the genes coding for the SaPI inducers’ proteins represent a source of variation among closely related phages . S3B Fig shows representative examples of these comparisons . Moreover , since distantly related phages encode the same SaPI derepressing protein , our analysis revealed that SaPI inducer diversity is independent of phage phylogeny ( S1A , S1C , S1E and S3 Figs ) . Interestingly , this analysis also revealed one additional strategy by which phages might avoid SaPI repression , namely , losing the genes encoding for the SaPI inducers . Thus , the SaPI1 inducer sri was absent in phages ϕ11 , ϕPVL or ϕNM3 and the SaPIbov2 inducer was not present in phages ϕ11 , ϕNM2 , ϕPVL-CN125 , ϕPVL , ϕNM3 or ϕ52a , although closely related phages coded for the missing inducers ( S3A Fig ) . With regards to the SaPIbov1 inducer ( trimeric Dut ) , it is absent in phages ϕ69 , ϕNM1 , ϕNM2 , ϕPVL108 , and ϕ55 . Surprisingly , instead of the trimeric form , these phages code for a dimeric Dut , which based on the structure of some homologue proteins deposited in the protein data bank ( PDB ) , we predict to be functionally related but structurally completely different . Why some phages encode a dimeric or a trimeric Dut is under study . This analysis suggests SaPI-imposed selection can drive significant and rapid evolutionary change in natural phage populations . Since our laboratory passage experiments suggested that only a few mutations are required to generate phages that escape from SaPI interference , we hypothesised that a similar process will have occurred in nature . To test this , we looked for proteins with high ( but not complete ) similarity to the 80α or ϕ11 Duts . Two promising candidate were the Dut proteins encoded by the prophages ϕSaov3 and B2 ( accession numbers YP_005736587 and ERS400827 ) , which have only 5 amino acid changes compared with the 80α and ϕ11 Duts , respectively ( Fig 3C ) . As shown in Fig 3D , the ϕSaov3 and B2 Dut variants were unable to induce the SaPIbov1 cycle , validating the results obtained with the in vitro evolved phages . These variants , however , are not widespread in nature . Since the SaPI inducers are moonlighting proteins with a relevant role in the phage biology [20] , we hypothesised that these variants have probably also affected their function for the phage . This was analysed by testing the enzymatic activity of 3 Dut variants ( the natural Dut B2 and the evolved Dut 80α I75N and Dut 80α G164S ) . This analysis revealed that the B2 Dut protein is insoluble and completely inactive , while the two evolved variants had significantly reduced ( p < 0 . 01 , Student’s t-test ) their dUTPase activity ( S4 Fig ) . In addition , of note is the existence in the evolved phages of some dut genes carrying nonsense and frameshifts mutations , which encode non-functional proteins ( S2 Table ) . This loss of function probably explains why these variants do not exist or are not widespread in nature . To demonstrate that phage-inducible chromosomal islands are important for phage evolution and ecology in general , we analysed the interaction between the enterococcal pathogenicity island EfCIV583 and its inducing phage ϕ1 [21] . To do this , we initially demonstrated that the EfCIV583 element interferes with the phage ϕ1 reproduction ( S5 Fig ) . Next , strains JP10983 or JP10982 ( JP10983 derivative carrying EfCIV583 ) were infected with phage ϕ1 , as previously reported in the analysis of the SaPI-phage interaction . After the third passage , 6 phages ( 3 infecting JP10983 and 3 infecting JP10982 ) were completely sequenced and analysed . Only those phages that had interacted with EfCIV583 contained mutations in their genomes , always located in the ϕ1 xis ( EF0309 ) gene ( S5 Table ) . Remarkably , and in a parallel study , we have demonstrated that the ϕ1 xis gene is the inducer for the EfCIV583 island [22] . Next , to test if this process is relevant in vivo , we analysed whether related enterococcal phages encoded allelic variants of the EfCIV583 inducer , and if these variants are under purifying selection . As shown in Fig 4 and Tables 1 and S1 , this was the case , confirming that satellite phages are a major force driving phage evolution .
The significance of coevolution between prokaryotes and their viruses [23 , 24] , and between viruses and their associated viral defective interfering particles [29] is well established . Here , we investigate coevolution between helper and satellite viruses of S . aureus . We confirm previous results that parasitism by SaPIs , which exploit phages for their own transmission , impose a massive growth rate cost on the phages [23–25] . We then show real-time evolution of phage resistance against SaPIs , and in turn the evolution of SaPI exploitation of “resistant” phages . We identify the genetic basis of experimentally evolved resistance and exploitation , and confirm the importance of SaPI-imposed selection on phage evolution in both natural populations of S . aureus phages through bioinformatic analyses and in laboratory populations of S . aureus phages used in phage typing . Finally , we report comparable experimental and bioinformatics results in E . faecalis . We have previously demonstrated that one of the key features of the SaPIs is to interfere with helper phage reproduction , using a variety of mechanisms . These include i ) blocking of phage DNA packaging by expression of the SaPI-coded Ppi protein , which interferes with the phage coded TerS protein [5]; ii ) diversion of phage proteins to produce the SaPI-specific particles [5]; iii ) expression of the PtiA homologs [6] , which block phage growth by binding to the helper phage Ltr proteins [26 , 27] , directly inhibiting their ability to activate phage late gene transcription; or iv ) carriage by the SaPIs of the phage cos or pac sites in order to compete with the inducing phages to be packaged in the phage particles [28 , 29] . In this work we describe two complementary strategies by which the phages evolve to overcome the SaPI interference: one involves the generation of allelic variants in the SaPI de-repressing proteins with lower affinity for SaPI coded Stl repressor; the other , even more drastic , involves complete loss of the phage-encoded SaPI inducing genes . Since SaPI interference depends on the induction of the SaPI cycle , both strategies select for non-inducing phages that are not affected by the presence of a quiescent SaPI integrated in the bacterial chromosome . Crucially , we show that SaPIs in turn adapt to resistant helper phage by loss of function of the global Stl repressor that removes the need for specific phage proteins for induction , allowing transmission of SaPIs by any infecting phages rather than specific helper phages [14] . While our results show that coevolution between satellite and helper viruses can occur very rapidly , it opens up a number of key questions . Specifically , how is the intimate association between phages and SaPIs maintained given that SaPI adaptation resulted in the loss of the need of specific helper phages for induction ? First , there are massive costs associated with loss of function of the SaPI global repressor . As previously reported , mutations in the stl gene severely affects bacterial physiology and growth , probably because of the uncontrolled replication of the stl mutant SaPIs [14] . This explains why the SaPIs characterised to date encode a functional Stl protein that block the SaPI cycle in the absence of the helper phage , although it is entirely feasible that de-repressed SaPIs can be favoured by selection in natural populations , at least for short periods of time . Second , there are costs associated with loss or alteration of the phage inducing proteins , as apparent from the increase in the number of phages carrying the wild-type versions of the SaPIbov1 and SaPIbov2 inducing genes in the absence of the interference caused by these islands , as well as the results from competition experiments between wildtype and mutant phage . As a result of such costs , wild-type phages are likely to be maintained in the population , further weakening selection for SaPI stl mutants . These costs of SaPI resistance presumably arise because the phage-coded SaPI inducers are proteins that perform their functions through protein-protein interactions with other phage- or bacterial-coded proteins [30] , and that the Stl repressors have merged the structure of the partners to which the SaPI inducers interact in order to be targeted [16] . Although this has not been demonstrated yet for the SaPIbov1 ( dut ) and SaPIbov2 ( 80α ORF15 ) inducers , the Sri protein ( SaPI1 inducer ) interact with the cellular DnaI protein inhibiting staphylococcal replication [20] . Based on this and previous in vitro results discussed above , one type of dynamic of continual phage-SaPI coevolution in nature may therefore be cycles of the following specific events: i ) Phages evolve SaPI resistance by alteration or loss of the inducing protein , assuming that the short term benefits of SaPI resistance outweigh fitness costs ( if any ) associated with changes in the inducing protein; ii ) SaPIs respond by loss of the need to be induced by a helper phage , again assuming benefits to the SaPI of being transmitted to new hosts outweigh the costs of reducing the fitness of hosts they infect; iii ) As a result of the mutant SaPIs being able to exploit both the original and mutant “resistant” phages , phages with the original unaltered SaPI inducing proteins are able to outcompete mutant phages because of the costs associated with altered inducing proteins which no longer confer resistance; and iv ) SaPIs that require induction by helper phage proteins can now outcompete SaPIs that do not require an inducer because there are large numbers of inducing phage present , starting the cycle again . This type of coevolutionary dynamic can be described as range fluctuating selection [31] , and can arise when increased resistance and infectivity ranges are associated with increased fitness costs [31] . Note that ranges here refer to the number of SaPI and phage genotypes that can be resisted and infected , respectively . The high diversity of phage inducing protein alleles suggests however alternative coevolutionary dynamics are operating in nature in addition to or instead of the model described above . Specifically , SaPI-imposed selection may cause diversifying selection if SaPIs adapt to changes in inducing proteins by switching to exploit the modified or an alternative protein , rather than losing the need for specific helper phages , and hence evolving more general infectivity . Consistent with this model , SaPIs , encoding different Stl repressors , have acquired the ability to exploit entirely unrelated phage proteins as antirepressors , and SaPIs tend to be induced by single rather than multiple proteins [15] . This coevolutionary dynamic can be described as specialism fluctuating selection , and again can arise when mutations that confer host or parasite generalism are too costly [32] . We have also demonstrated that another member of the PICI family of mobile genetic elements , the EfCIV583 island , drives phage evolution . Since one of the key features of the PICI elements is to interfere with the phage biology , we anticipate that these elements will have developed multiple interference functions that will have to be overcome by the helper phages in order to prevent PICI interference . Since PICI elements have been found in most Gram-positive bacteria , we anticipate that the strategies reported here by which the phages evolve in response to the SaPIs are widespread in nature . Our work shows that virus satellites associated with both S . aureus and E . faecalis can have important ecological and evolutionary implications on their helper viruses . Crucially , these findings add another layer of complexity to the increasingly recognised role of coevolution between viruses and their bacterial hosts in driving ecological and evolutionary dynamics of these organisms [33] . For example , whether or not phages are resistant to the dominant satellite viruses they encounter at a given point in time , will in turn determine the how phages affect their bacterial hosts . Arguably , it may be necessary to explicitly consider the role of satellite viruses to understand the structure of any natural microbial community , over and above their well-recognised role in horizontal gene transfer .
The bacterial strains used in these studies are listed in S6 Table . The procedures for preparation and analysis of phage lysates , in addition to transduction and transformation of S . aureus , were performed essentially as previously described [14 , 28 , 34] . E . faecalis lysates were obtained and prepared as previously indicated [21] . General DNA manipulations were performed using standard procedures . The plasmids and oligonucleotides used in this study are listed in S7 and S8 Tables , respectively . The labelling of the probes and DNA hybridization were performed according to the protocol supplied with the PCR-DIG DNA-labelling and Chemiluminescent Detection Kit ( Roche ) . Southern and western blots experiments were performed by standard procedures [15] . To test if the phages evolved in the presence of the different islands , 5 x 107 cells of the SaPIbov1-positive strain JP1996 were initially infected with phage 80α ( 1:1 ratio ) . Once the culture lysed , which occurred normally 4–5 hours post-infection , the resulting phage population was titred and used to infect again the SaPIbov1-positive strain , using always the aforementioned cells:phage ratio . The phage lysates obtained after the third passage done in strain JP1996 were used to infect strain JP2129 , an RN4220 derivative carrying SaPIbov2 . After the third passage done in this strain ( JP2129 ) , the evolved phages were then used to infect JP2966 , an RN4220 derivative carrying SaPI1 . As a control , phages only infecting RN4220 were propagated and analysed through the experiment ( see scheme in S2 Fig ) . The different phage genes under study were PCR amplified using oligonucleotides listed in S8 Table . PCR products were cloned into pCN51 [35] or pET28a ( E . coli; Novagen ) , and the resulting plasmids ( S7 Table ) were sequenced and introduced into the appropriate recipient strains ( S6 Table ) . Selective pressures operating on SaPI or EfsCIV583 inducers were analysed using the average difference between substitution rates per nonsynonymous and synonymous sites , dN−dS , over all pairs of sequences . A zero value indicates neutral evolution ( no selection ) ; greater than zero supports positive directional selection , and lower than zero is taken as evidence of purifying ( stabilising ) selection . Substitution rates were computed using Nei-Gojobori modified method with Jukes-Cantor correction ( with transitions to transversions bias equal to 0 . 66 ) . Standard errors were estimated by a bootstrap procedure ( 1000 replicates ) . These analyses were done using MEGA5 [36] . Sequence alignments were screened for the presence of recombination using all the algorithms implemented in the RDP4 program [37] as well as the SBP and GARD [38] algorithms implemented in the Datamonkey server ( www . datamonkey . org ) . No evidence for recombination was found for the SaPI1 ( Sri ) , SaPIbov2 and EfsCIV583 inducers . However , a weak evidence was found by RDP4 for the SaPIbov1 inducers ( Duts ) , but this was not supported by the other algorithms . Thus , we decided not to consider any Dut sequence as a truly recombinant . The genome of selected phages was aligned using MAUVE version 2 . 3 . 1 [39] with its default parameters . Genetic relatedness among phages in the presence of possible recombination events and of parallel evolutionary changes was evaluated through a NeighborNet network reconstructed with SplitsTree version 4 . 11 . 3 [40] . The Jukes-Cantor model of nucleotide substitutions was used to estimate genetic divergences among pairs of sequences . Statistical support for the edges in the split graph was evaluated with 1000 bootstrap resamplings of the sequence data . dUTPase activity was assayed using His ( 6 ) -dUTPase proteins purified after expression in E . coli , using standard procedures . Enzyme assays were performed using the EnzCheck Pyrophosphate Assay Kit ( Molecular Probes ) , as previously reported [16] . | Satellites are defined as viruses that have a life cycle dependent on a helper virus . Thus , they can be considered as parasites of parasites . In addition to their fascinating life cycle , these widespread infectious elements , present both in eukaryotic and prokaryotic cells , have a dramatic role in virulence by controlling the symptoms induced by their eukaryotic helper viruses or by encoding key bacterial virulence genes . While satellites can play an important role in the ecology of the viruses they parasitise , the evolutionary impact on their helper viruses is unclear . Here we show that staphylococcal pathogenicity islands ( SaPIs ) , an example of a virus satellite , are a major selective force on the viruses ( bacteriophages ) they parasitise . Using both bioinformatic and experimental evolution data we have been able to confirm that pathogenicity islands are a major selective pressure enhancing the diversity of both genes and gene content in Staphylococcus aureus phages . Since SaPIs exploit the life cycle of their helper phages to enable their rapid replication and promiscuous spread , these strategies are mechanisms that reduce SaPI interference , thus facilitating the infectivity and dissemination of the helper phages in nature . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | Virus Satellites Drive Viral Evolution and Ecology |
Proteolytic processing is an irreversible posttranslational modification affecting a large portion of the proteome . Protease-cleaved mediators frequently exhibit altered activity , and biological pathways are often regulated by proteolytic processing . Many of these mechanisms have not been appreciated as being protease-dependent , and the potential in unraveling a complex new dimension of biological control is increasingly recognized . Proteases are currently believed to act individually or in isolated cascades . However , conclusive but scattered biochemical evidence indicates broader regulation of proteases by protease and inhibitor interactions . Therefore , to systematically study such interactions , we assembled curated protease cleavage and inhibition data into a global , computational representation , termed the protease web . This revealed that proteases pervasively influence the activity of other proteases directly or by cleaving intermediate proteases or protease inhibitors . The protease web spans four classes of proteases and inhibitors and so links both recently and classically described protease groups and cascades , which can no longer be viewed as operating in isolation in vivo . We demonstrated that this observation , termed reachability , is robust to alterations in the data and will only increase in the future as additional data are added . We further show how subnetworks of the web are operational in 23 different tissues reflecting different phenotypes . We applied our network to develop novel insights into biologically relevant protease interactions using cell-specific proteases of the polymorphonuclear leukocyte as a system . Predictions from the protease web on the activity of matrix metalloproteinase 8 ( MMP8 ) and neutrophil elastase being linked by an inactivating cleavage of serpinA1 by MMP8 were validated and explain perplexing Mmp8−/− versus wild-type polymorphonuclear chemokine cleavages in vivo . Our findings supply systematically derived and validated evidence for the existence of the protease web , a network that affects the activity of most proteases and thereby influences the functional state of the proteome and cell activity .
Proteolysis , the hydrolysis of peptide and isopeptide bonds in protein substrates by proteases ( also termed peptidases or proteinases [1] ) , affects every protein at some point during its lifetime . The outcomes of proteolysis are of two kinds: Protein degradation ablates protein function by breakdown to amino acids , whereas proteolytic processing is an irreversible posttranslational modification to precisely produce modified , stable protein chains . The length of this cleavage product is defined by the substrate site specificity of the protease catalyzing the reaction , which can be exquisite . Processed proteins often have radically altered activity , protein interactions , structure , or cellular location and hence are implicated in many human diseases [2]–[4] . Recent research has focused on identifying the cleavage products of protease activity in cell culture and in vivo as a means of understanding their biological roles and hence guiding drug target identification and validation [5] . This need has led to the development of genomics and proteomics approaches that have come to be termed degradomics [6] , [7] in which the specialized subfield known as terminomics that identifies N termini [8]–[10] and C termini [11] , [12] has seen recent rapid development . In one such terminomics analysis of murine skin in vivo , ∼44% of identified N termini mapped to internal positions in proteins , revealing proteolytic cleavage after translation as part of protein maturation and function [13] . With ∼68% of identified N-termini being internal , human erythrocytes have been found to possess an even higher proportion of processed proteins [14] . These recent findings demonstrate that proteolytic processing is a widespread and functionally important posttranslational modification . Thereby , proteolytic processing modifies the activity of many more proteins than currently appreciated from conventional shotgun proteomics analyses and biological studies . As exemplified by N-terminal cleavage of chemokines [6] , the activity of a protein often depends on the exact position and nature of its N and C termini [15] . Therefore , identifying the termini of proteins is essential for functional insight into protein bioactivity , annotation of proteins in the Human Proteome Project , and drug development [14] . However , deeper biological insight requires identifying the protease responsible for generation of neo-termini that distinguish cleavage products from the original protein termini . Whereas low- and high-throughput methods to identify the in vitro substrate repertoire of proteases , also known as the substrate degradome [7] , are well established , in vivo identification is problematic [16] . In vitro experiments can only indicate potential cleavage in vivo because of difficulties assigning precise parameters governing cleavage in the actual biological system , such as protease and substrate colocalization spatially and temporally , presence of inhibitors , zymogen activation , pH , ion concentrations , interaction with nonprotein compounds [17] , as well as O-glycosylation or phosphorylation of the protease or substrate [18] . Hence , posttranslational modifications of proteases , inhibitors , and their substrates add complexity to the dynamic nature of the proteome and cell responses . Thus , an observed cleavage in vitro might not occur in vivo—that is , “just because it can ( in vitro ) does not mean it does ( in vivo ) ” [5] . In vivo studies , which rely on comparing samples of protease knockout or inhibition to controls , are hampered in particular because the underlying biological system reacts to the removal of a protease or inhibitor in complex and unpredictable ways . For example , a protease knockout can lead to alterations in gene expression profiles of proteases , inhibitors , and substrates [13] , [19] , due to the biological consequences of altered substrate cleavages in vivo , including cleavage of transcription factors [20] . Another factor is the activation of other proteases in the system through increasingly recognized activation cascades of protease zymogens by other proteases and the proteolytic regulation of protease inhibitor activity by nontarget proteases that cleave and inactivate the inhibitor . For example , serpins and cystatins inhibit serine and cysteine proteases , respectively , but when cleaved by a matrix metalloproteinase ( MMP ) , the inhibitor is inactivated and the protease remains active [13] , [21]–[23] . Through activating and inactivating cleavages of other proteases and inhibitors , a protease thereby indirectly influences the activity of additional proteases . Such interactions can lead to knock-on effects that alter the cleavage of a range of additional protein substrates that are not direct substrates of the protease . Furthermore , titration of inhibitors upon covalent or tight interaction with one protease can reduce the availability of free inhibitors to regulate other proteases . Consequently , phenotyping protease and inhibitor genetic knockout mice is complicated , which also hampers biological understanding and drug target validation of proteases . Protease biology is also complex due to the large protease numbers in humans ( 460 ) and mice ( 525 ) , which form the second largest enzyme family after ubiquitin ligases in these organisms [24] . Moreover , an additional 93 and 103 are predicted to be inactive proteases in human and mouse , respectively , which often can function as dominant negative counterparts [24] . Protease numbers are almost equally distributed in the intracellular and extracellular environments , and other than some proteases that segue between these two compartments , this distribution partitions and limits their potential interactions with each other . In an effort to systematically comprehend this complex biology , proteases are grouped by the MEROPS database , which is assembled from biochemical experimental data curated from the literature , into seven classes , five of which are found in human and mouse , according to the active site residue catalyzing substrate cleavage , and into clans based on the structure of the active site [25] . Similarly , inhibitors are commonly grouped according to the class of proteases they inhibit , with several inhibitors exhibiting broad inhibitory activity against proteases from more than one class . Interactions between proteases of the same class are well established as part of classically described cascades of proteases such as the complement [26]–[28] and coagulation [29] , [30] systems , and newer recognized cascades such as kallikreins [31] and caspases in apoptosis [2] , [32]–[34] . However , wide-ranging additional protease interactions have also been proposed to extend more globally to link networks forming what was termed the protease web [35] . The protease web was defined as the universe of cleavage and inhibition interactions between proteases and their inhibitors . Stemming from examples in simple systems such as in vitro biochemical analyses and early in vitro and cell culture degradomics analyses of protease substrates [36]–[38] , and mRNA transcript analyses in cancer upon administration of protease inhibitors or tissue inhibitor of metalloproteinase ( TIMP ) overexpression and knockout studies [19] , the protease web concept has been well supported . Extending terminomics analyses to in vivo situations , for example skin inflammation in wild-type versus Mmp2 knockout mice in vivo , has revealed hitherto biologically relevant and unsuspected critical connections of MMPs in regulating the complement and coagulation cascades and the plasma kallikrein system , which regulates vessel permeability through bradykinin excision and release from kininogen [13] . Such interactions between protease families were shown to create small networks in specific cases [13] , [19] , [39] , [40] , but the full extent of the protease web , the fraction of proteases and inhibitors involved , and hence the regulatory potential of this network remain underexplored and underappreciated despite the potentially wide impact on the functional state of proteomes . Furthermore , the protease web is a black box with an unknown mechanism of regulation—it is unclear whether it follows a super structure of known cascades , where signals are amplified downstream , or forms more of a network , where signals can flow in multiple directions with multiple positive and negative feedback loops [35] , [40] . Similarly , it is unclear which are the main regulatory protein switches controlling subparts of the network . Descriptions of the protease web are difficult to assemble , as many proteases remain poorly studied and characterized . Likewise , many proteases have no described inhibitors and many predicted inhibitors have unknown protease targets and deorphanization examples are uncommon [41] . Here , we assessed the global extent and structure of protease interactions computationally . Graph models are used to describe multiple interactions between many elements and have been applied extensively in research on various biological networks . We represented existing biochemically validated data on protease cleavages and inhibition as annotated in the manually curated database TopFIND [42] as organism-specific networks . TopFIND stores established biochemical information on substrate cleavage and protease inhibition from MEROPS [25] , the most complete collection of such data , most of it published , and combines it with published high-throughput terminomics and degradomics datasets as well as protein annotations from UniProt [43] for five different organisms . Our analyses revealed a large and pervasive network spanning all known cascades and four of the five protease classes present in human and mouse tissues . The network is highly connected in that via a few connections a protease can potentially influence many other proteases , with inhibitors often taking a special role as key connectors in the protease web . We demonstrate the utility of our analysis by applying the network to gain mechanistic in vivo insights into protease web effects , which we then validated in vitro , in cell culture , and in vivo .
Functional protease interactions comprising cleavage and inhibition events influence the in vivo cleavage of substrates in many ways . Cleavage of a substrate by a protease is a direct event , and as shown in Figure 1 , by cleaving other proteases and protease inhibitors , one protease can activate , inactivate , or alter the activity of a second protease , thereby indirectly influencing the cleavage of substrates of another protease . To assess the global extent of such effects , we represented protease interactions as a graph , connecting proteases and protease inhibitors to their established substrates and protease targets , respectively . The resulting graph contains nodes , which are proteins , and edges , which represent cleavages or inhibitions . Edges link proteases to their substrates and protease inhibitors to their target proteases . Therefore , edges are directed: an edge from protein X to protein Y signifies cleavage or inhibition of Y by X but does not contain information about cleavage or inhibition of X by Y . In graph theory , the latter would require another edge with the opposite directionality . Figure 1 outlines functional protease interactions and how they are represented in small graph models , which were then aggregated to represent the full complexity of the protease web based on curated biochemical data as described below . As input to our analysis of the protease network , we used the TopFIND v 2 . 0 knowledgebase [44] to retrieve validated cleavage and inhibition data mostly annotated from published experiments . TopFIND contained 4 , 774 cleavages for Homo sapiens , 3 , 679 for Mus musculus , 426 for Escherichia coli , 190 for yeast , and 43 for Arabidopsis thaliana . Due to the low number of cleavages annotated for other organisms , we focused our analysis on human and mouse . Only proteins performing an annotated cleavage or inhibition were added , and then these were connected via edges representing the biochemical reactions as explained in Figure 1 . These networks extend the protease web , which contains only proteases and inhibitors , by also including all other substrates of proteases , and hence represent the annotated functional proteolytic interactions between the substrates in the proteome and the protease web . The human and murine networks ( with 1 , 230 and 1 , 393 nodes , respectively ) are shown in high resolution upon click-to-zoom in Figure S1 and available for download as a Cytoscape file , gml file , and R objects at www . chibi . ubc . ca/ProteaseWeb and http://clipserve . clip . ubc . ca/supplements/protease-web . The human and murine proteolytic networks show that the majority of proteins are connected and only very few are in unconnected components . Thus , in both networks , the Largest Connected Component ( i . e . , the biggest group of nodes directly or indirectly connected ) encompasses the vast majority of these proteins—1 , 183 of 1 , 230 ( 96% ) in human and 1 , 377 of 1 , 393 ( 99% ) in mouse ( Table 1 ) . This remarkable connectivity is particularly surprising given the incompleteness of annotation currently available in the databases . Indeed , Table 1 shows that of 460 human proteases , only 244 ( 53% ) have one or more known and annotated substrates . In mouse this number is even lower , with only 88 of 525 ( 17% ) proteases having a substrate annotated . Furthermore , even the data on these proteases are incomplete and biased , with most substrates assigned to few , well-studied proteases . Figure S2 shows the out-degree ( i . e . , the sum of cleavages catalyzed by a protease or the sum of inhibitions caused by a protease inhibitor ) for proteases and inhibitors having any annotated cleavage or inhibition , respectively . Although few proteases have a large known substrate repertoire ( higher out-degree ) , most proteases have very few known substrates . Although this could be due to high substrate specificity , it is more likely that these proteases simply received less attention in studies dedicated to discover substrate repertoires . This effect is especially pronounced for the mouse data , where 80% of total cleavages ( 2 , 938 of 3 , 679 ) are assigned to three proteases—cathepsin D ( UniProt: P18242 ) , cathepsin E ( UniProt: P70269 ) , and MMP2 ( UniProt: P33434 ) —and are mostly derived from high-throughput proteomics screens . Accordingly , the annotations differ strongly between human and mouse . Although the networks have similar size ( 1 , 230 and 1 , 393 nodes , respectively ) , they overlap minimally , with only 126 of 3 , 852 connections in mouse ( 3 . 3% ) reflected in 122 of 4 , 905 human connections ( 2 . 5% ) . However , we suggest that the small overlap is mostly due to differences in the state of data annotation between the networks rather than to actual differences in the evolution of these networks . The human data are further biased in that proteases and inhibitors are largely overrepresented as substrates themselves ( Figure S3 ) . Strong representation of protease–protease cleavages is expected because many proteases are synthesized as zymogens requiring proteolytic cleavage for activation by other proteases . Indeed , this strong enrichment is found in the human TopFIND/MEROPS data , but less so in mouse . We compared these values to a terminomics data set of cleavages in mouse skin [13] , which more accurately reflects reality because terminomics analyzes N termini in an unbiased fashion . However , in this in vivo data set , inhibitors , and not proteases , were overrepresented as processed proteins , indicating that the overrepresentation of proteases as cleavage substrates in the human in vitro database is likely exaggerated . The observed data biases likely resulted from the nature of biochemical studies , where many substrates were identified for some “interesting” proteases ( target bias ) and “interesting” proteins are more likely to be tested as substrates ( substrate bias ) . Substrate bias is especially found for proteases themselves , which are preferably tested as substrates in zymogen activation studies . With the advent of degradomics utilizing proteomics methods dedicated to substrate discovery , we anticipate both an increase in target bias in the future with many substrates identified for a few proteases , and a decrease in substrate bias where any protein can be identified as a substrate without prior selection of interesting candidates . Therefore , the cleavages annotated represent a biased fraction of the biochemically possible cleavages in the organism compared with an unknown number of as yet uncharacterized cleavages . On these grounds , the high connectivity in both the mouse and human networks is even more noteworthy because future information can only further increase connectivity . The observed , extensive interactions between proteases and inhibitors are further characterized as described in the following . In the interactions between proteases in proteolytic signaling pathways , there are major upstream regulators or initiation factors , whose proteolytic activity leads to the cleavage of downstream proteases , which in turn activate even further downstream factors that finally cleave and activate the effector molecules at the end of the pathway . A special case of proteolytic pathways are activation cascades , where signal amplification occurs to generate large quantities of the end protein products in seconds as classically described for coagulation [29] , [30] . To investigate whether the connections in the overarching protease web follow such a pathway or cascade ( hierarchical ) structure , we used a graph measure termed reachability . Reachability of node X denotes the number of other nodes Y where there is a path from X to Y in the network . A path is a sequence of directed edges connecting X and Y , following the directionality of edges in the network . The path from X to Y can therefore be different from the path from Y to X ( and the existence of one does not guarantee the existence of the other ) . In the protease web , reachability corresponds to the number of proteins that can be influenced by one protease or inhibitor . Figure 2A outlines reachability values of nodes in three theoretical examples: ( i ) an unconnected ( single ) , ( ii ) a strongly connected ( circle ) , and ( iii ) a cascade-like network ( cascade ) . Figure 2B shows the respective distribution of reachability values of these three theoretical examples . We next compared the theoretical reachability distributions with the distributions observed in our human and mouse protease networks . In order to specifically describe the selective connectivity between proteases and inhibitors , which form the protease web , we excluded from further analysis other simple substrates ( nonprotease and noninhibitor proteins ) , whose reachability in the network is 1 by definition . Table 2 summarizes the resulting protease web networks for human ( 340 ) and mouse ( 220 ) proteins that have annotated cleavages or inhibitions . In analyzing the human and mouse protease webs , we further identified one dominant “largest connected component” comprised of 255 proteins for human and 187 proteins for mouse . Figure 2C compares the distribution of reachability scores in the largest connected component in mouse ( blue curve ) and human ( red curve ) . In mouse , reachability indicates a cascade-like , hierarchical network , where most nodes have a very low reachability and fewer nodes have gradually higher reachability . In contrast , the reachability distribution of the human network follows a strongly bimodal distribution: 158 ( 62% ) nodes reach 153 ( 60% ) or more nodes . This is very high reachability that is most similar to the circle graph in Figure 2B , where any node can reach any other node . For a biological system , this implies that 158 proteases or inhibitors have the potential to regulate the activity of 153 or more other proteases and inhibitors in the network . In other words , there are one or more directed paths between 24 , 166 pairs of proteases in the human protease web , which are 37% of all 64 , 770 possible directed connections between pairs of 255 proteins . This number of connections between pairs rises to 141 , 523 paths when substrates are added ( network with 1 , 230 nodes ) . This highlights the high degree of connectivity between proteases and inhibitors . Reachability between nodes does not take the path length between nodes into account and so might be the result of very long and hence biologically irrelevant paths in the network . However , this possibility can be excluded as most paths have a length of just four ( Figure 2D ) . The lack of connectivity in the mouse network is not surprising given the small overlap between the two networks . We assume that this difference is due to data biases rather than a real biological difference , and accordingly we focused on characterizing the extensive and more complete human network . High connectivity in the human protease web is due to a strongly connected component ( 87 nodes ) , a subgroup of nodes within the largest connected component , that can directly or indirectly reach each other and hence have the same reachability value of 153 ( Table 3 ) . We visualized this effect in Figure 3 , where nodes of the human protease web are shown separated by their reachability . Upstream of the strongly connected component are 71 nodes with reachability higher than 153; these nodes can reach the strongly connected component , but cannot be reached from it . Downstream ( with reachability smaller than 7 ) are 97 nodes , which cannot reach the strongly connected component . The nodes in Figure 3 are also colored according to their centrality in the network , as measured by node betweenness [45] . Betweenness is calculated by first finding the shortest paths ( as explained above ) between all 64 , 770 pairs of nodes in the network and then counting the number of times a node appears in these paths . Notably , all nodes with high betweenness are found in the strongly connected component; these nodes tether the network together . Nodes with high betweenness or reachability are listed in Table S1 . Figure 3 shows that our network data from MEROPS/TopFIND contain all the known proteolytic pathways ( e . g . , coagulation , complement system , apoptosis , and kallikreins ) as they were discovered , published , and annotated previously in MEROPS ( detailed in Figure S4 ) . In addition , these proteolytic pathways are extended by connections linking known pathways with other pathways and additional proteases . Details of these connections can be found in Figure 4A , which shows separated protease groups in the strongly connected component after removing inhibitors . Figures 3 , 4A , and S4 show that the observed connectivity in the protease web is caused by the concerted action of defined protease cascades and key protease inhibitors: alpha-2-macroglobulin ( A2M , UniProt: P01023 ) , amyloid precursor protein ( APP , UniProt: P05067 ) , kininogen 1 ( KNG1 , UniProt: P01042 ) , and alpha-1-antitrypsin ( also known as serpin A1 ) ( SERPINA1 , UniProt: P01009 ) . Whereas intragroup connections are pervasive as expected , intergroup connections are also considerable , in particular between coagulation factors and kallikreins or MMPs , but also including cathepsins and caspases . These findings are confirmed in Figure 4B , which shows that connections among four of the five classes of proteases and protease inhibitors in human are extensive . Importantly , Figure 4B also shows proteases frequently cleaving inhibitors of other protease classes , an important regulatory aspect of protease activity . Only threonine proteases , which are found exclusively in large specialized cell organelles termed the proteasome and immunoproteasome , remain isolated from connections with other proteases and inhibitors according to current data . Note added in proof: However , a recent publication shows that the threonine proteasomal proteases are cleaved by intracellular MMP-12 . Thus , all five classes of proteases in human and mouse are interconnected [81] . From a biological standpoint , the highly interconnected ( reachable ) nature of the protease web was surprising and underappreciated in the literature . To explore the degree to which this result is statistically surprising given the properties of the proteins making up the network , we investigated theoretical network models as well as randomized versions of the network . We first compared the protease web to two commonly used generative network models , the Erdős-Rényi model ( ER ) and the Barabasi-Albert model ( BA ) , with parameters chosen to mimic the properties of the real network's member proteins ( see Materials and Methods ) . We found that neither model ( each 500 networks ) adequately explains the data , yielding networks that have either much higher ( ER ) or lower ( BA ) reachability on average ( Figure S5A–C ) . These experiments therefore leave open the statistical nature of the process that generates the network , which we stress currently involves both biological components and experimenter biases , the latter being due to the incomplete nature of the underlying biochemical analyses ( many potential edges have not been tested ) . We next generated two types of edge-shuffled networks , one maintaining in- and out-degree of each node ( “Shuffled” ) and a second preserving overall in- and out-degree distributions of the network , but not for each node ( “Shuffled2” ) . The mean reachability was lower in the real network ( 72 . 09 ) than in 353 Shuffled networks ( 70 . 6% of all 500; average reachability was 73 . 96 across all 500 networks; see Figure S5D ) but higher than all 500 Shuffled2 networks ( average 34 . 8; Figure S5C ) . Taken together , these results indicate that high reachability emerges quite readily in a network composed of proteins with the measured in- and out-degrees found in a real biological network , such as the protease web described here . In fact , a network without such high reachability—as it is often assumed in biochemistry and cell biology—would be surprising from these results . Importantly , this further suggests that the current biochemical description of cascades and individual proteases working in isolation is unlikely . To assess reliability of high connectivity in the protease web , which we observed assuming that all cleavage and inhibition data are trustworthy , we addressed the possibility of erroneous data passing through database annotations into our network . A possibility of validating our findings is to compare the network to another second network derived from an orthologous data source . However , MEROPS being the only database of similar coverage , we instead tested whether the same connectivity can be observed by removing nodes in anticipation that some interactions are wrongly annotated . Protease specificity is mostly influenced by three factors: substrate sequence , substrate folding , and the encounter of protease and substrate [46] . In MEROPS/TopFIND , annotations are mostly derived from in vitro experiments where a protease is incubated with a substrate . Although some proteases are specific for given substrate sequences , others will cleave a wider range of sequences , but in both cases , possible cleavage sites can be masked in the protein structure of the substrate . Hence , experimental parameters of protease cleavage assays are designed to preserve protein folding and activity of both the protease and substrate in order to prevent unspecific cleavage of denatured substrates . Colocalization of proteases and substrates in vivo is an important factor but not unambiguously determinable , with unexpected localization recently revealed [20] , [37] , [47]–[49] , [81] . In addition , most experiments are only performed if it can be assumed that the protease and substrate will colocalize in vivo . Assuming that most annotations are correct but individual assignments can be wrong , we randomly and selectively removed edges from the protease web ( focusing on the regulatory core , the largest connected component with 255 nodes ) to test how reachability is maintained or influenced by such modifications . We utilized the term “physiological relevance , ” as annotated in MEROPS and TopFIND , to first create a high-confidence network ( abbreviated as “hc” in Figure 5A ) by removing all edges that were annotated with physiological relevance other than “yes . ” As a consequence , the reachability of the resulting network was markedly decreased ( Figure 5A ) , with the area under the curve ( AUC ) reduced to 22% of the original network . This was mostly due to the removal of all inhibitors ( abbreviated as “i” below ) as all 131 human inhibitions in TopFIND have a physiological relevance annotation of “unknown”; that is , their physiological relevance is not annotated in MEROPS from which TopFIND data are largely derived . Upon adding back the inhibitors to the high confidence network ( “hc+i” ) , but still removing all “low confidence” nonphysiological cleavages , high reachability was largely recovered as indicated by an AUC of 88% of the original network . The observation that limiting the cleavages to high-confidence cleavages only barely reduces network connectivity strengthens the result that the protease web is not due to incorrect annotations . Moreover , removing inhibitions from the network severely impacted reachability and thus connectivity , highlighting the essential role of inhibitors in connecting the protease web . Given the observed importance of inhibitors , we assessed the possibility of incorrect annotation of cleavages of inhibitors . The molecular mechanism of cysteine or serine protease inhibition by serpins involves cleavage of the serpin at its flexible reactive loop , which displays “bait” amino acids . Following cleavage , an induced conformational change leads to entrapment and inactivation of the protease [50] , [51] . Because the trap occurs after formation of the acyl intermediate during catalysis , the inhibited serine proteases , but also some cysteine proteases , remain covalently bound to the inhibitor . In contrast , metalloproteinase and aspartic protease cleavage of serpins in the reactive loop does not result in their inhibition , as the nucleophile of these proteases classes is a water molecule . Thus , these proteases are not trapped and therefore escape inhibition , but the serpin is now inactivated . Mechanisms of trapping upon cleavage have also been observed for some metalloprotease inhibitors [52] and for A2M or pregnancy zone protein ( PZP , UniProt: P20742 ) , which use a physical trapping mechanism to inhibit all classes of proteases , except exopeptidases [53] , [54] . Therefore , annotated cleavages of a protease inhibitor comprise cleavages that reflect either a regulatory inhibition of the protease or a regulatory inactivation cleavage of the inhibitor . To date , this distinction is not annotated in the databases , but is one that we suggest implementing . As a conservative estimate , we removed all cleavages of serpins by serine or cysteine proteases and from any protease to A2M or PZP ( “inh rm” in Figure 5B ) . Therefore 144 edges were deleted from the original 1 , 238 edges of the largest connected component of the protease web ( “orig” in Figure 5B ) . Notably , this removal only moderately reduced reachability ( AUC 74% of original ) and preserved a bimodal distribution . Thus , the high connectivity is not a result of unspecific inhibitors . Hence , the observed connectivity in the network is not an artifact attributable to ambiguous annotation of inhibitor cleavage and so further supports the importance of inhibitors in connecting the protease web . We next assessed the dependence of reachability on individual nodes of the network . By removing each node individually , we found that reachability in the protease web is not dependent on any one single node ( Figure S6 ) . Indeed , by iteratively removing all nodes with the highest betweenness from the network , we identified the six most important nodes: plasminogen ( PLG; UniProt: P00747 ) , alpha-1-antitrypsin , A2M , cathepsin L1 ( CTSL1; UniProt: P07711 ) , alpha-1-antichymotrypsin ( also known as serpin A3 ) ( SERPINA3; UniProt: P01011 ) , and kallikrein-4 ( KLK4; UniProt: Q9Y5K2 ) ( Figure 5C ) . Removing all six nodes simultaneously removes 227 edges whereupon this significantly breaks down the bimodal distribution of reachability values , an effect not observed when removing any combination of five out of the six connectors . Thus , high connectivity in the protease web is robust in that it depends not on a single protein , but rather on six important connectors . Furthermore , even after removal of those six nodes the reachability for many proteins remains high with many long paths in the network . Notably , none of these six important nodes are digestive tract proteases , such as trypsin or chymotrypsin , which are broad-acting proteases and ones that might have been expected to form many connections . However , we predict that the identity and number of these key connector proteins will change as more information on the protease web is uploaded to the databases with further experimentation . Finally , we addressed the possibility of incorrect annotations by removing a fixed percentage of edges , thereby simulating a situation where these edges are incorrect cleavage or inhibition annotations and therefore would have to be removed from the network ( Figure 5D ) . We randomly removed 10% , 20% , 30% , and 40% of all edges ( cleavages and inhibitions ) 200 times and then plotted the worst case for each experiment . The AUC was reduced to 78% , 65% , 47% , and 52% , respectively , but nonetheless even removal of 40% of edges still preserved the bimodality of the reachability values . Therefore , again the protease web shows a strong resistance to removal of elements , which further increases confidence in the description of a highly connected protease web with inherent robustness to change . This also leads to biological resilience and shows the importance of proteases that can nonetheless be resiliently maintained in genetic deficiencies or pathological perturbations of the system . Our analyses suggested that the protease web represents a robust regulatory system of high complexity and flexibility enabling complex patterns of regulation of proteins at the posttranslational level . We next assessed how this system is implemented in vivo where only a fraction of proteases and inhibitors is expressed or active at the same time in the same cell , compartment , or tissue . We constructed tissue-specific networks based on protease and inhibitor gene expression levels in 23 different human tissues quantified by CLIP-CHIP microarray ( Kappelhoff et al . , unpublished data available at http://clipserve . clip . ubc . ca/supplements/protease-web ) . We used negative control spots on this microarray to define a threshold of expression at detectable levels and then limited networks to those proteins expressed above this threshold . We next plotted the reachability of the nodes in the largest connected component of the resulting networks for all 23 tissue-specific protease webs ( Figure 6A ) . Figure 6B shows liver , spleen , and skin results in more detail . Although most tissue-specific networks ( e . g . , skin ) show low reachability values , some preserve the strong connectivity of the original network totally ( e . g . , kidney and liver ) or partially ( e . g . , spleen , small intestine , pancreas , lung , colon ) . Notably , the tissue-specific networks also show that reachability is highly dependent on expression of the same six network connectors shown in Figure 5C ( Figure S7 ) . In agreement with our findings based on biochemical interactions , general biological literature also shows that proteases and their inhibitors can be involved in multiple biological processes ( Figure 7A ) . It is easy to imagine that this multifunctionality is partly due to the interplay in the protease web . Indeed most of the proteins in Figure 7A are found in the strongly connected component of our protease web , indicating that they serve in connecting different biological processes . One example is TIMP1 ( UniProt: P01033 ) . Protein expression levels of TIMP1 , an MMP inhibitor mainly involved in extracellular matrix remodeling and organization , were found associated with hemostasis [55] . This finding , which is derived from orthogonal data to the protease web , primed us to search for connections linking TIMP1 to coagulation factors , which we could indeed identify ( Figure 7B ) . Together , these provide a plausible mechanism of action of TIMP1 and hence MMPs on coagulation and could explain the association observed . Hence , the protease web can be used to explain multifunctionality of proteases , which in turn strengthens our conclusion of a large interplay between proteases . We were able to test the utility of our graph representation of the protease web by deciphering a previously inexplicable result in vivo . We analyzed the MMP8-dependent cleavage of the murine chemokine C-X-C motif chemokine 5 ( CXCL5 , UniProt: P50228 ) , also known as lipopolysaccharide ( LPS ) -induced C-X-C chemokine LIX ( LIX ) . LIX is a potent chemoattractant chemokine for polymorphonuclear ( PMN ) leukocytes , and MMP8 ( UniProt: O70138 ) is PMN specific . It was previously demonstrated in an in vivo airpouch model that MMP8 knockout mice showed reduced PMN migration in response to LPS [56] . This was attributed to MMP8 processing and activation of LIX at position Ser4↓Val5 , with a second cleavage at Lys79↓Arg80 of the 92-residue protein . Indeed the MMP8-truncated activated form of LIX ( 5–79 ) showed equal cell migration in wild-type and knockout mice , validating LIX as a physiological MMP8-dependent mechanism for promoting neutrophil infiltration in vivo . However , a neoepitope antibody specific to the MMP8-generated neo-N terminus failed to detect truncations at Ser4↓Val5 in the airpouch model . Thus , cleavage of LIX is a MMP8-dependent but MMP8-indirect event in vivo that could not be explained , prompting a further analysis of alternate MMP8-dependent proteolytic pathways predicted using our representation of the protease web . To examine the importance of neutrophil-derived MMP8 in LIX processing and activation , we isolated bone marrow neutrophils from wild-type and MMP8 knockout mice . Neutrophils were stimulated with phorbol myristate acetate ( PMA ) followed by incubation of the activated neutrophils with chemokine for up to 3 h . Truncations of LIX generating the bioactive products LIX ( 9–92 ) and LIX ( 9–78 ) , as determined by MALDI-TOF mass spectrometry from the still inactive form LIX ( 1–78 ) , were readily apparent , even after only 1 h of incubation ( Figure 8A ) . However , both the MMP8 knockout and wild-type neutrophils showed identical cleavage sites ( Ala8↓Thr9 and Ala78↓Lys79 ) and cleavage kinetics . Because these sites differ from the MMP8 cleavage sites ( Figures S8 , S9 , and 8B ) , MMP8 is not the dominant neutrophil protease cleaving LIX in the cellular context . Investigating protease web effects that may account for this , we found that LIX cleavage by neutrophils was inhibited by the serine protease inhibitor 2-aminoethyl benzenesulfonyl fluoride hydrochloride ( Figure 8C ) . This showed that one or more of the four serine proteases in neutrophils—neutrophil elastase ( UniProt: Q3UP87 ) , cathepsin G ( UniProt: P28293 ) [57] , proteinase-3 ( UniProt: Q61096 ) , or the recently described neutrophil serine proteinase 4 ( UniProt: Q14B24 ) [58]—were responsible for LIX cleavage . Using low concentrations of the endogenous serine proteinase inhibitors α1-proteinase inhibitor ( α1-PI , UniProt: P07758 ) [21] and secreted leukocyte proteinase inhibitor ( SLPI , UniProt: P97430 ) ( Figure 8C ) , we excluded proteinase-3 and neutral serine proteinase 4 as candidates , as SLPI does not inhibit these proteinases [58] , [59] . Moreover , neutral serine proteinase 4 has a stringent substrate specificity that does not fit our observed cleavage sites . Cathepsin G did not cut after Ala8 and required high enzyme concentrations ( >100 nM ) in generating the C-terminal cleavage ( Figure S9 ) as it was inefficient with a kcat/KM 60 M−1 s−1 . Thus , neutrophil elastase was the strongest candidate , and indeed 1 nM elastase efficiently cleaved LIX with a kcat/KM 1 , 200 M−1 s−1 at Ala8↓Thr9 and Ala78↓Lys79 ( Figures 8D , S8 , and S9 ) . Because MMP8 cleaves N-terminal to the Ala8↓Thr9 elastase site and C-terminal to the Ala78↓Lys79 elastase site , truncations by elastase will remove evidence of any MMP8 cleavage . Furthermore , MMP8 is less efficient ( kcat/KM 600 M−1 s−1 ) than elastase in cleaving LIX . Thus , elastase is the dominant protease for LIX cleavage by neutrophils in vivo . To explain the paradoxical result that in the Mmp8−/− mouse LIX is not cleaved in vivo despite the presence of neutrophil elastase , we employed path finding in the protease web to identify potential regulatory effects from MMP8 on neutrophil elastase . Although no path was found in the murine network , the more extensive human network contains a path that had potential to explain this perplexing result ( Figure 8E ) . Human MMP8 is known to cleave and inactivate human α1-PI [21] , the potent inhibitor of neutrophil elastase , but SLPI is resistant to MMP8 cleavage [60] . We verified α1-PI cleavage by MMP8 using mouse proteins for the first time at various enzyme-to-substrate ratios and in time course experiments ( Figure 8F ) from which we found that murine MMP8 efficiently cleaves and inactivates murine α1-PI in vitro with a kcat/KM 7 . 7×103 M−1 s−1 . We next validated the in vitro results in vivo . In murine bronchioalveolar lavage collected following 24 h of treatment with LPS , both the full-length and high molecular weight forms of α1-PI , which were present as inhibitor-serine protease complexes , were greatly enhanced in Mmp8−/− mice compared to wild type ( Figure 8G ) . Together , these in vitro and in vivo data show that efficient cleavage of α1-PI occurs by MMP8 in vivo and indicates the importance of MMP8 in modulating the balance of functional α1-PI protein and activity in vivo and hence elastase activity . This result further shows that MMP9 , which also cleaves alpha1-PI in vitro , does not functionally compensate for MMP8 in vivo . This is despite MMP9 being in the same cytosolic granules as MMP8 and being present at elevated concentrations in the neutrophils from the MMP8 knock out mouse . Finally , we confirmed neutrophil elastase-dependent LIX cleavage in vivo using a specific neutrophil elastase chemical inhibitor ( GW311616 ) . Specific elastase inhibition reduced the relative numbers of neutrophils in wild-type mouse bronchioalveolar lavage similar to the decrease in cell migration in the MMP8 knockout versus the wild-type mouse bronchioalveolar lavage ( Figure 8H ) . We conclude that MMP8 cleaves and inactivates α1-PI in vivo acting as the “metallo-serpin” switch leading to increased neutrophil elastase activity and LIX activation , which thereby promotes neutrophil infiltration in vivo . Evidence of LIX cleavage by MMP8 is lost following elastase cleavage in vivo , which is also catalytically more efficient than MMP8 . Thus , the protease web enabled deconvolution of a complex biologically relevant proteolytic event and in turn formulation of a testable hypothesis that was confirmed in vitro and in vivo .
Critical control of protease activity is exerted at the protein level . Proteases from one class ( e . g . , metalloproteases ) frequently cleave proteases from other classes ( e . g . , serine proteases ) or their cognate inhibitors ( serpins ) , and subnetworks can thereby be activated or inactivated . In this process , we found that protease inhibitors take an important connecting role in the web—they are highly enriched as substrates of all classes of proteases and removal of inhibition strongly decreases reachability of all nodes in the network . Protease inhibitors often lack specificity and inhibit families of proteases rather than just individual enzymes . Thus , inhibitors function as key on/off switches of entire subnetworks within the protease web , enabling rapid and efficient activation of proteolytic processes upon their cleavage . We provided a new example of a metallo-serpin switch controlling chemokine activation . As an important biological consequence of this , removal of inhibition is therefore recognized to be as important as zymogen activation in cascades in controlling proteolysis . Indeed this was recently demonstrated in skin inflammation in vivo , where MMP2 was found to cleave and inactivate serpin G1 , also known as complement C1 inhibitor [13] . Dynamically regulating the activity levels of serpin G1 inhibition allowed complement activation to cascade , which otherwise was greatly reduced in the Mmp2−/− mouse , where excess amounts of intact functional serpin G1 were proteomically quantified by TAILS terminomics . The central role of this metallo-serpin inhibitor switch in the protease web was further shown in the regulation of another subnetwork involving plasma kallikrein cleavage of kininogen to release the vasoactive peptide bradykinin . The network representation of the protease web emphasizes that proteases of one family and class can markedly regulate the activity of proteases from different families and classes . Understanding a complex biological network , such as the protease web , can only be achieved via systematic storing and sharing of biochemical information in order to enable network-based predictions to generate testable hypotheses . Applying this strategy , we gained in silico insights into in vivo processes and validated these biochemically , in culture and in vivo . We forecast that through further identification and biochemical characterization of cleavage and inhibition events , the representation of protease interactions can be improved to strengthen its predictive power . The resulting network could then be used to simulate the effects of protease and inhibitor knockouts and protease drug targeting in disease , which will enhance confidence of targeting the correct protease and thereby increase the success rate of clinical trials by reducing unexpected side effects . In conclusion , our analysis of the protease web reveals a multidirectional rather than a hierarchical structure , as has been proposed [40] , with deep connections in regulation of the proteome by specific proteolytic processing in addition to degradation . As the structure of the human protease web is multidirectional rather than cascade-like and hierarchical , it has high connectivity that is robust to change . Biologically this implies that regulation by proteolysis is a consistent and pervasive force in all tissues . In comparison to phosphorylation , which is limited to intracellular proteins and pathways , proteolysis affects all proteins and pathways inside and outside the cell , and it is irreversible and pervasive and needs to be considered in functional analyses of the proteome .
Tables containing proteases and their substrates ( cleavages ) and protease inhibitors and their target proteases ( inhibitions ) as well as tables mapping UniProt IDs to MEROPS IDs and gene names were collected from the TopFIND MySQL database ( http://clipserve . clip . ubc . ca/topfind/; downloaded January 15 , 2012 ) . Proteases were classified based on their MEROPS IDs in TopFIND . Determining the inhibitor class specificity of human protease inhibitors was performed by downloading lists of UniProt ACs for Gene Ontology [61] annotations cysteine-type ( GO:0004869 , n = 49 proteins ) , metallo- ( GO:0008191 , n = 11 proteins ) , or serine-type ( GO:0004867 , n = 95 proteins ) endopeptidase inhibitor from neXtProt [62] on May 24 , 2012 . A term “aspartic-type endopeptidase inhibitor” ( GO:0019828 ) exists , but no proteins are annotated with this term . Inhibitors were labeled “broad” if they are annotated to inhibit more than one class of protease based on ( i ) their GO terms from neXtProt or ( ii ) their annotated inhibitions from TopFIND . The network representation of cleavages and inhibitions was obtained via R [63] scripts , heavily relying on the use of the igraph library [64] . Proteins are represented as nodes . Cleavages are represented as directed edges from the proteases node to the substrate node . Accordingly , inhibitions were represented as directed edges from the inhibitor to the inhibited protease . Reachability of a node was calculated by counting all proteins where a shortest path can be found using the shortest . path function of igraph . Betweenness of nodes was calculated using the betweenness function of the igraph package . By recalculating betweenness after removing each node , the iterative identification of nodes with the highest betweenness was performed . Paths from MMP8 to neutrophil elastase were identified in the network using the get . all . shortest . paths function of the igraph package . Erdős-Rényi networks with the same number of nodes and edges as the original graph were generated using the erdos . renyi . game function of the igraph package , and Barabasi-Albert networks were generated with the barabasi . game function , forcing the same out-degree distribution as the protease web . Edge-shuffled random graphs were generated using the degree . sequence . game function once keeping out- and in-degree distributions the same so that each node has the same in- and out-degree as in the original network ( Shuffled ) and once shuffling those distributions before passing them to the method ( Shuffled2 ) . Inverse empirical cumulative distribution functions were calculated and plotted using an inverted version of the empirical cumulative function “ecdf” in R . The AUC was calculated by calling the integrate function in R on the cumulative function . Mouse and human networks were compared by identifying connections , which occur between homologous proteins . The homology mapping between UniProt ACs of the two species was performed by mapping UniProt ACs to Ensembl protein IDs via the Ensembl database of the biomaRt package [65] in R obtained from Bioconductor [66] . The homology mapping between Ensembl protein IDs was performed using the InParanoid [67] database via the hom . Hs . inp . db [68] package in R/Bioconductor . Network figures were plotted using Cytoscape 2 . 8 . 3 [69] . Proteins involved in selected , protease-specific biological processes were identified by obtaining Gene Ontology [61] annotation of proteins using the org . Hs . eg . db package [70] in R/Bioconductor on August 8 , 2013 . N-terminal cleavage sites in normal and inflamed murine skin were obtained from Supplementary table S8 from [13] . The data for the analysis of the protease and inhibitor expression profile was achieved by analysis of commercially available RNAs from 23 different healthy human tissues on the protease- and inhibitor-specific oligonucleotide-based CLIP-CHIP microarray [71] . Data from 84 CLIP-CHIP microarrays representing biological and technical replicates of antisense RNA of these tissues were used , and average signal intensity values ( A-Value ) of each gene were combined . An expression cutoff was determined at an A-Value of 7 . 5 , where 95% of the intensities of the negative oligonucleotide probes on the microarray were below this cutoff ( data are available at http://clipserve . clip . ubc . ca/supplements/protease-web ) . | Proteases modify the structure and activity of all proteins by peptide bond hydrolysis and are increasingly recognized as integral regulatory components of numerous biological mechanisms . Deregulated protease activity is a common characteristic of many diseases . However , protease drug development is complicated by an incomplete understanding of protease biology . One missing piece in this puzzle is the interplay between proteases: Some proteases activate other proteases , whereas some proteases inactivate inhibitors , leading to currently unpredictable cleavage of additional proteins . Using database annotations we mathematically modeled protease interactions . Our model includes 1 , 230 proteins and shows connections between 141 , 523 pairs of proteases , substrates , and inhibitors . Thus , proteases interact on a large scale to form the protease web , which links most studied groups of proteases and their inhibitors , indicating that the potential of regulation through this network is very large . We found that this interplay is robust to targeted or untargeted pruning of the protease web and that protease inhibitors are central to network connectivity . Our model was used to decipher proteolytic pathways that drive inflammatory processes in vivo . Consequently , protease regulatory interactions should be recognized and explored further to understand in vivo roles and to select better drug targets that avoid side effects arising from inhibition of unexpected activities . | [
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"proteins",
"r... | 2014 | Network Analyses Reveal Pervasive Functional Regulation Between Proteases in the Human Protease Web |
The down-regulation of the tumor-suppressor gene RASSF1A has been shown to increase cell proliferation in several tumors . RASSF1A expression is regulated through epigenetic events involving the polycomb repressive complex 2 ( PRC2 ) ; however , the molecular mechanisms modulating the recruitment of this epigenetic modifier to the RASSF1 locus remain largely unknown . Here , we identify and characterize ANRASSF1 , an endogenous unspliced long noncoding RNA ( lncRNA ) that is transcribed from the opposite strand on the RASSF1 gene locus in several cell lines and tissues and binds PRC2 . ANRASSF1 is transcribed through RNA polymerase II and is 5′-capped and polyadenylated; it exhibits nuclear localization and has a shorter half-life compared with other lncRNAs that bind PRC2 . ANRASSF1 endogenous expression is higher in breast and prostate tumor cell lines compared with non-tumor , and an opposite pattern is observed for RASSF1A . ANRASSF1 ectopic overexpression reduces RASSF1A abundance and increases the proliferation of HeLa cells , whereas ANRASSF1 silencing causes the opposite effects . These changes in ANRASSF1 levels do not affect the RASSF1C isoform abundance . ANRASSF1 overexpression causes a marked increase in both PRC2 occupancy and histone H3K27me3 repressive marks , specifically at the RASSF1A promoter region . No effect of ANRASSF1 overexpression was detected on PRC2 occupancy and histone H3K27me3 at the promoter regions of RASSF1C and the four other neighboring genes , including two well-characterized tumor suppressor genes . Additionally , we demonstrated that ANRASSF1 forms an RNA/DNA hybrid and recruits PRC2 to the RASSF1A promoter . Together , these results demonstrate a novel mechanism of epigenetic repression of the RASSF1A tumor suppressor gene involving antisense unspliced lncRNA , in which ANRASSF1 selectively represses the expression of the RASSF1 isoform overlapping the antisense transcript in a location-specific manner . In a broader perspective , our findings suggest that other non-characterized unspliced intronic lncRNAs transcribed in the human genome might contribute to a location-specific epigenetic modulation of genes .
RASSF1A ( RAS-association domain family member 1A ) is a tumor suppressor gene that modulates a broad range of cellular functions essential for normal growth , such as the maintenance of genomic stability , cell cycle control , the modulation of apoptosis , and cell motility and invasion [1] . RASSF1A is one of seven alternatively spliced isoforms ( RASSF1A to G ) generated at the gene locus through the differential usage of two promoters or alternative splicing [2] , [3] . The biological relevance of only two isoforms , RASSF1A and RASSF1C , has been demonstrated . Both isoforms are ubiquitously expressed in non-tumor tissues , whereas in tumors and tumor cell lines , the expression of RASSF1A is frequently low , leading to increased cell proliferation [3] . RASSF1A promoter CpG island hypermethylation and reduced gene expression are frequently observed in a wide range of cancers [4]–[9] . The epigenetic silencing of RASSF1A requires the HOXB3-mediated induction of DNMT3B DNA methyltransferase expression and the recruitment of the DNMT3B protein to the RASSF1A promoter [10] . The recruitment of DNMT3B and the polycomb repressor complex 2 ( PRC2 ) is dependent on MYC proto-oncogene protein , which is bound to the RASSF1A promoter [10] . Although MYC is required for PRC2 recruitment to the RASSF1A promoter [10] , MYC is generally not sufficient to recruit PRC2 [10] , [11] , and other regulatory factors and mechanisms underlying the recruitment of this epigenetic silencing machinery have not yet been identified . The human genome encodes thousands of long ( >200 nt ) noncoding RNAs ( lncRNAs ) [12] , [13] that might function via diverse mechanisms [14]–[16] . Intergenic lncRNAs have been associated with gene silencing through guiding enzymes involved in chromatin remodeling , particularly PRC2 , causing the posttranslational modification of histones in target genes [17]–[19] . In addition , recent reports have shown that thousands of lncRNAs are associated with PRC2 and that many of these are sense and antisense intronic lncRNAs [20] , [21] , not intergenic . In the present study , we identified a novel unspliced antisense intronic lncRNA , ANRASSF1 , which is expressed in the RASSF1 gene locus independently from the protein-coding gene . The modulation of ANRASSF1 abundance through ectopic overexpression or transient knockdown affected the expression level of RASSF1A , with no effect on RASSF1C . We demonstrated that ANRASSF1 formed an lncRNA/DNA hybrid , which mediated the recruitment of SUZ12 , a member of PRC2 , to the RASSF1A promoter . The recruitment of SUZ12 resulted in a marked increase in the H3K27me3 levels only at the RASSF1A promoter region , without accumulation of the repressive mark either at the RASSF1C promoter or the four neighboring loci . ANRASSF1-mediated gene repression occurred in a highly location-specific manner , as only the RASSF1A isoform , which overlaps the antisense transcript , was affected .
We surveyed the public Expressed Sequence Tags ( ESTs ) database and identified a long RNA transcript that mapped to an intronic region of the RASSF1 genomic locus . This transcript was represented by a cluster of ESTs covering 580 bp of the genome , which mapped just upstream of the RASSF1C isoform ( Figure 1A , light gray rectangle ) and overlapped exon 2 of RASSF1A . Indeed , this transcript was one of 67 , 731 putative unspliced lncRNAs mapping to intronic regions of 74% of all protein-coding genes , which were previously described by our group [22] , being part of a genome-wide pervasive lncRNA expression involving between 75 and 90% of the human genome [12] , [13] , [23] . The ESTs described above originated from non-strand specific cDNA libraries produced from a number of different human tissues , and we used strand-oriented RT-PCR to confirm the expression of this long RNA in several cell lines . Figure 1B shows the expression of an RNA transcribed in the antisense direction relative to protein-coding mRNAs encoded in the RASSF1 locus in nine different cell lines . This transcript will hereafter be referred to as ANRASSF1 , for Antisense Intronic Noncoding RASSF1 RNA . Next , we used the Rapid Amplification of cDNA Ends ( RACE ) approach to extend both the 5′ and 3′ ends of the ANRASSF1 transcript . The 3′ RACE-PCR product was sequenced , showing a 38-nt extension beyond the existing ESTs , with 5 nt of the extended sequence matching the genome and the additional sequence showing a poly ( A ) tail of 33 adenines ( Figure 1A ) . We also identified a conserved polyadenylation signal ( ATTAAA ) [24] 17 nt upstream of the poly ( A ) tail . Using a combined approach involving 5′ RACE-PCR with primer-walking PCR and sequencing , we extended the transcript 205 nt at the 5′ end ( Figure 1A , red box ) , resulting in a full-length ANRASSF1 transcript of 790 nt . High-throughput strand-specific RNA-seq of poly ( A ) + RNA from LNCaP prostate cancer cells showed transcription from the plus strand in the RASSF1 locus ( Figure 1C ) , and the assembly of these RNA-seq reads using the Cufflinks tool generated a consensus sequence mapping to the genomic plus strand in the locus . These data essentially confirmed the length and antisense orientation of ANRASSF1 , which were previously identified through strand-specific RT-PCR , RACE-PCR and sequencing . Using the Coding Potential Calculator tool [25] , no coding potential was predicted for the full-length ANRASSF1 , confirming ANRASSF1 as an lncRNA . Because ANRASSF1 is represented by an Affymetrix probe set in the HG-U133 Plus2 microarray platform and the entire RASSF1 locus is represented by a different probe set , we performed a meta-analysis of the ANRASSF1 and RASSF1 expression patterns on publicly available microarray data . We identified a statistically significant inverse correlation ( Figure 1D ) between the expression levels of ANRASSF1 and RASSF1 in HeLa , MDA-MB-231 and MCF-7 cells , which are three cell lines in which we had previously confirmed ANRASSF1 expression using RT-PCR ( Figure 1B ) . In addition , this meta-analysis revealed that in Jurkat cells under mitotic stress ( Figure 1E ) , RASSF1 showed a 1 . 5-fold increase within the first hour following mitogen stimulation with a phorbol ester and ionomycin; this response was inversely correlated with ANRASSF1 expression . Notably , the expression of RASSF1 and Daxx was described to define a mitotic stress checkpoint that enables cells to exit mitosis and eventually die [26] . Our meta-analysis also detected an inverse correlation between ANRASSF1 and RASSF1 in three other studies using cell lines and human tissue samples ( Figure S1 ) . Overall , these data highlight a functional role for ANRASSF1 in the host locus . Next , we measured ANRASSF1 and RASSF1A expression in tumor and non-tumor immortalized cell lines obtained from the breast ( Figure 2A ) and prostate ( Figure 2B ) . Interestingly , we detected the reduced expression of ANRASSF1 in non-tumor cell lines compared with tumors in both tissues , and an opposite pattern for RASSF1A expression , which was higher in non-tumor cells compared with tumor cell lines . Thus , the inverse correlation between ANRASSF1 and RASSF1 expression in the public array datasets was confirmed in the one non-tumor and two tumor cell lines obtained from two different tissues . To determine whether ANRASSF1 lncRNA is transcribed through RNA Polymerase II , we treated HeLa cells with α-amanitin at a concentration of 10 µg/mL , which inhibits only RNAPII . Figure S2A shows that ANRASSF1 transcription was abolished in α-amanitin-treated cells . ANRASSF1 contained a 5′ end methyl-guanosine cap modification , as shown by its resistance to 5′-exonucleolytic digestion in vitro ( Figure S2B ) . To determine ANRASSF1 stability , HeLa cell cultures were treated for 1 to 8 h with the RNA polymerase inhibitor actinomycin D . ANRASSF1 levels decayed with a half-life of ∼50 min following transcriptional inhibition ( Figure S2C ) . For comparison , c-Myc mRNA displayed a half-life of ∼20 min under similar conditions ( Figure S2C ) . Nuclear and cytoplasmic total RNA fractions were prepared from HeLa cells , and the relative abundance of ANRASSF1 was measured using qPCR . Figure S2D shows that ANRASSF1 was 100-fold enriched in the nuclear fraction relative to the cytoplasm . A comparison of the expression levels of ANRASSF1 with those of abundant intergenic lncRNAs ( lincRNAs ) , such as MALAT1 [27] , HOTAIR [19] and lincRNA SFPQ [18] showed that endogenous ANRASSF1 was much less abundant ( approximately 500- to 1 , 000-fold lower ) than these lincRNAs in HeLa cells ( Figure S2E ) . Similarly , endogenous ANRASSF1 was approximately 500- to 1 , 000-fold less abundant than the protein-coding RASSF1A and RASSF1C mRNAs , which are expressed from the same host locus ( Figure S2E ) , demonstrating that ANRASSF1 was expressed at low levels in the cell . A putative bidirectional promoter region spanning the transcription start-sites of ANRASSF1 and RASSF1C has been predicted in silico [28] . We referred to the region on the genomic plus strand upstream of ANRASSF1 as the “antisense promoter” and the region in the minus strand upstream of RASSF1C as the “sense promoter” ( Figure S3A ) . The activity of both promoters was measured in vitro , and both promoters showed a significant induction of the firefly luciferase reporter relative to the control ( p<0 . 01 ) ( Figure S3B ) . This result confirmed the presence of a bidirectional promoter , specifically indicating promoter activity upstream of the ANRASSF1 lncRNA , thus supporting an independent antisense transcriptional unit in this locus . The observation of an inverse correlation between ANRASSF1 and RASSF1 expression ( Figures 1D , 1E , 2 and S1 ) prompted us to determine whether ANRASSF1 could act in cis to modulate the expression of the protein-coding gene in the same locus . We overexpressed ANRASSF1 and subsequently measured the levels of the RASSF1 transcript isoforms . When the expression levels of ANRASSF1 were increased to 40-fold compared with the control cells ( Figure 3A ) , RASSF1A expression was significantly decreased to 21% of its endogenous level ( Figure 3B ) . Interestingly , the overexpression of ANRASSF1 did not affect the abundance of the RASSF1C mRNA isoform ( Figure 3C ) . In parallel , the levels of RASSF1A protein were determined through western blot . Figure 3D shows that RASSF1A was reduced in pCEP4 ANRASSF1-transfected HeLa cell lines compared with control cells . Densitometric analysis of western blots from three replicates of cells overexpressing ANRASSF1 showed a 57% decrease in the levels of RASSF1A protein compared with the normal levels observed in the control cells ( Figure 3E ) . To determine whether the decrease in RASSF1A protein due to overexpression of ANRASSF1 would result in detectable phenotypic changes , cell-proliferation assays were performed . First , we observed that cells overexpressing ANRASSF1 proliferated at a significantly faster rate than the control cells ( Figure 4A ) , with a significant 22% average increase in the proliferation rate ( p<0 . 03 ) determined using an MTS assay . We also measured cell population growth by directly counting the number of cells over time in culture in a Neubauer chamber ( Figure 4B ) ; the adjusted exponential growth functions ( R2 ranging from 0 . 93 to 0 . 99 throughout the replicates ) showed calculated doubling times of 20 . 2±1 . 9 and 25 . 0±3 . 7 h for the cells overexpressing ANRASSF1 and the control cells , respectively , with a significant 24% average increase in the cell growth rate ( p<0 . 05 ) upon ANRASSF1 overexpression ( Figure 4B ) . The 22 to 24% increase in cell proliferation rate observed in the MTS and cell number counting assays upon the increase in ANRASSF1 expression , with a resulting decrease of RASSF1A abundance , is consistent with the tumor suppressor function of this protein . This increase is comparable to the 26% increase in cell proliferation over one day previously observed with RASSF1A siRNA [29] . In addition to reducing cell proliferation , RASSF1A exerts a proapoptotic signaling function [30] . We therefore measured the cell death caused by exposure to UVC light or the cytotoxic anti-cancer drug staurosporine to determine whether the overexpression of ANRASSF1 and the resulting decrease in RASSF1A would affect the course of cell death . Figure 4C shows that UVC irradiation ( 40 J/m2 ) caused an important increase in cell death , as shown by the increase in the sub-G1 population of cells , and the overexpression of ANRASSF1 substantially decreased the UVC-induced sub-G1 population , which is indicative of a reduction in cell death . Figure 4D shows the average increase in the sub-G1 population in the control cells ( empty pCEP4 ) exposed to UVC compared with no-UV , as measured in three independent replicas , and a significant decrease in the percentage of the sub-G1 population in cells overexpressing ANRASSF1 after exposure to UVC ( t-test p<0 . 05 ) , which is indicative of reduced cell death in the latter condition compared with the control ( empty pCEP4 ) cell line . Next , we measured cell death in response to the cytotoxic drug staurosporine ( 100 nM ) , a classical initiator of apoptosis by both caspase-dependent and caspase-independent pathways [31] , and again tested the effect of ANRASSF1 overexpression on cell death . We employed the xCELLigence platform microelectric assay based on the changing impedance of electrodes in the presence of live cells to examine the drug-induced cytotoxicity over an extended period of time in culture ( 170 h ) . Figure 4E shows that after exposure to staurosporine for 96 h , the cells overexpressing ANRASSF1 were considerably more resistant to death , remaining attached to the culture plates , even after 170 h; the measured cell index , which corresponded with the number of live cells attached to the plate ( Figure 4E ) , showed a significant 4 . 2-fold average increase in cells overexpressing ANRASSF1 compared with the control cells ( empty pCEP4 ) at 170 h in the three biological replicates ( p<0 . 001 ) . These findings are consistent with the proapoptotic signaling function of RASSF1A [30] and indicate that RASSF1A silencing through the overexpression of ANRASSF1 attenuated the cell death signal induced through UVC irradiation or staurosporine treatment . To further document the effect of ANRASSF1 abundance on the expression of RASSF1A , we designed specific siRNAs to silence ANRASSF1 . A pool of three different siRNAs targeting ANRASSF1 significantly reduced ANRASSF1 expression to 39% of its endogenous level compared with a scrambled siRNA control ( Figure 5A ) . Concomitantly , we observed a 2 . 25-fold increase in the relative abundance of RASSF1A mRNA ( Figure 5B ) . The decrease in ANRASSF1 expression did not affect the abundance of the RASSF1C isoform ( Figure 5C ) , which is consistent with the lack of effect of ANRASSF1 overexpression on RASSF1C previously observed . Next , we performed cell-proliferation assays to determine whether ANRASSF1 knockdown and the consequent increase in the RASSF1A mRNA levels affected the cell proliferation rate . We observed that cells with silenced ANRASSF1 expression proliferated at a significantly slower rate than control cells ( Figure 5D ) , with an average 15% decrease in the proliferation rate compared with control cells ( p<0 . 02 ) . We sought to gain mechanistic insight into the involvement of the lncRNA ANRASSF1 in regulating RASSF1A expression . ANRASSF1 has nuclear localization , suggesting that this protein might be involved in the recruitment of other factors ( MYC/PRC2 ) involved in RASSF1A gene silencing through H3K27 trimethylation and/or DNA promoter methylation [10] . First , we examined whether endogenous ANRASSF1 was physically associated with PRC2 using a native non-cross linked RNA immunoprecipitation ( RNA-IP ) with an antibody specific to SUZ12 , a member of the PRC2 complex . Figure 6A shows that the endogenous ANRASSF1 was 5 . 3-fold enriched with respect to negative control RNA , which was not expected to bind PRC2 , namely GAPDH mRNA . The endogenous lincRNA SFPQ , which binds PRC2 , as determined with anti-SUZ12 and anti-EZH2 antibodies [18] , was used as positive control and showed a 2 . 8-fold enrichment ( Figure 6B ) . Using an antibody specific to EZH2 , another member of the PRC2 complex ( Figure S4 ) , we observed that endogenous ANRASSF1 was enriched in the anti-EZH2 RNA-IP fraction relative to the input compared with the IgG fraction . Next , we determined whether the PRC2 complex was bound to the promoter region of RASSF1A and if the overexpression of ANRASSF1 affects PRC2 occupancy in this region . We performed chromatin immunoprecipitation ( ChIP ) using an anti-SUZ12 antibody and observed a significant 8-fold increase of the RASSF1A promoter DNA bound to PRC2 in cells overexpressing ANRASSF1 compared with control cells expressing endogenous levels of ANRASSF1 ( Figure 6C ) . Interestingly , no significant change in PRC2 occupancy upon ANRASSF1 overexpression was observed either at the promoter region of the RASSF1C isoform or the promoter of the four neighboring genes , two on either side at the RASSF1 locus ( Figure 6C ) , including the two well-characterized tumor suppressor genes TUSC2 [32] and NPRL2 [33] . As additional controls , no significant change was detected at either the promoter of GAPDH , a gene not regulated through SUZ12 , or the promoter of HOXA9 , a gene regulated through SUZ12 [34] and encoded in chromosome 7 , away from the RASSF1 locus in chromosome 3 . These results indicate a correlation between the higher levels of ANRASSF1 and the higher PRC2 occupancy at the RASSF1A promoter . PRC2 is a histone-modifying enzyme complex responsible for adding di- and trimethylation marks onto H3K27 . We determined whether ANRASSF1 overexpression , which increases PRC2 occupancy , also affected the level of H3K27me3 at the RASSF1A promoter region . Figure 6D shows that there was a 5 . 1-fold enrichment of the RASSF1A promoter DNA associated with histone H3K27me3 when ANRASSF1 was overexpressed compared with control cells with endogenous levels of ANRASSF1 , confirming that H3K27 trimethylation in the RASSF1A promoter is dependent on the level of ANRASSF1 binding to PRC2 . No significant changes in H3K27me3 were observed at either the promoter region of RASSF1C or the promoter region of the four other genes in the vicinity of RASSF1 ( Figure 6D ) . In addition , no change was detected at the promoter region of HOXA9 . These results suggest highly location-specific epigenetic modulation . Because DNA methylation of the RASSF1A promoter involves PRC2 and DNMT3B [10] , we examined whether the increased recruitment of PRC2 through ANRASSF1 overexpression also affected DNMT3B occupancy at the RASSF1A promoter or DNA methylation at the locus . Figure 6E shows that the DNMT3B occupancy at the RASSF1A promoter is not affected by ANRASSF1 overexpression in HeLa cells . A methylation-dependent endonuclease assay showed no significant effect on the DNA methylation at the promoter region of RASSF1A in cells overexpressing ANRASSF1 compared with the control ( Figure 6F ) . Recent reports have shown that lincRNAs , such as lncRNACCND1 [35] and Mistral [36] , bind to DNA and recruit proteins that act at the promoter regions of neighboring protein-coding genes to regulate their expression . We determined whether ANRASSF1 might act in a similar manner through binding to DNA and recruiting the PRC2 complex in cis to the promoter of RASSF1A . For this purpose , we treated permeabilized HeLa cells with RNase H to deplete endogenous ANRASSF1 associated with DNA , followed by ChIP using an anti-SUZ12 antibody . First , we measured the endogenous ANRASSF1 levels in cells treated either with RNase inhibitor ( Figure 7A , black bar ) or RNase H ( Figure 7A , red bar ) . With RNase H treatment , which digests RNA/DNA hybrids , the ANRASSF1 level was reduced to 13% , suggesting that ANRASSF1 is part of an RNA/DNA hybrid . Alpha-tubulin RNA , which was used as a control in this study , was only digested by RNase A ( Figure 7B , blue bar ) , not RNase H ( Figure 7B , red bar ) , as anticipated for an RNA that is not expected to form RNA/DNA hybrids . In parallel , we measured the PRC2 occupancy at the RASSF1A and RASSF1C promoter regions and observed that the maximum occupancy was obtained in the presence of RNase inhibitor ( Figure 7C and 7D , black bars ) . Treatment with RNase H resulted in an almost total release of PRC2 from the RASSF1A promoter region ( Figure 7C , red bar ) , while a low PRC2 occupancy at the RASSF1C promoter region ( Figure 7D , black bar ) and no significant reduction upon RNase H or RNase A treatment was observed ( Figure 7D , red and blue bars ) ; these data indicate that the PRC2 occupancy at the RASSF1A promoter region — not the RASSF1C promoter region — is driven by ANRASSF1 . We also performed an RNase-ChIP assay using an anti-DNMT3B antibody , and no differences in the occupancy at the RASSF1A or RASSF1C promoter regions were detected under RNase H or RNase A treatments ( Figure 7E and 7F ) . This result indicates that the DNMT3B occupancy at the RASSF1 locus is not driven by ANRASSF1; consistent with the observation described above , the DNMT3B occupancy at the RASSF1A promoter was not affected through ANRASSF1 overexpression ( Figure 6E ) . Finally , a negative control RNase-ChIP with anti-RNA Pol II , a factor whose occupancy at the promoters of RASSF1A and RASSF1C is not expected to be affected by RNase H treatment , was included; treatment with RNase H or RNase A did not change the RASSF1A or RASSF1C promoter occupancy by RNA Pol II ( Figure 7G and 7H ) , ruling out the notion that the effect on PRC2 would result from the toxic effect of RNase treatment on the cells . Notably , in cells treated with RNase A , which digests single-stranded RNA ( ssRNA ) , we observed both a reduction in the endogenous ANRASSF1 ( Figure 7A , blue bar ) and the PRC2 occupancy at the RASSF1A promoter ( Figure 7C , blue bar ) ; however , the reduction was considerably smaller than that obtained with RNase H treatment ( see Figure 7A and 7C , red bars ) , suggesting that the ssRNA in the nucleoplasm was in rapid equilibrium with the RNA/DNA hybrids and that a shift from hybrids to single-strand occurred as the hybrid was digested . Alternatively , there could be two distinct populations of ssRNA and RNA-DNA hybrids , and both could play a role in the association of PRC2 with chromatin . A similar pattern of RNase H digestion and PRC2 occupancy at the RASSF1A promoter was observed in cells overexpressing ANRASSF1 ( Figure S5 ) . Notably , the amount of ANRASSF1 under overexpression conditions was 40-fold higher than that endogenously expressed ( see Figure 3A ) ; therefore , the similar percentage of ANRASSF1 depletion achieved through RNase H treatment ( Figure S5B ) indicates that the absolute amount of the remaining ANRASSF1 was also approximately 40-fold higher in overexpressing cells , resulting in a smaller reduction of PRC2 binding at the RASSF1A promoter in overexpressing cells treated with RNase H ( 45% reduction with respect to the inhibitor , Figure S5A ) compared with cells with endogenous lncRNA treated with RNase H ( 90% reduction with respect to the inhibitor , Figure 7C ) . RNAi was employed to determine whether the reduction of PRC2 occupancy at the RASSF1A promoter is specifically associated with ANRASSF1 expression . The knockdown of ANRASSF1 to 40% of the endogenous level ( data not shown ) caused a 55% reduction in PRC2 occupancy at the RASSF1A promoter ( Figure 8A ) . Similarly , Palakurthy et al . [10] knocked down EZH2 expression using RNAi and observed an increase in the expression of RASSF1A . Taken together , these results indicate that the recruitment of PRC2 complex to the promoter of RASSF1A specifically relies on the association of PRC2 with an ANRASSF1/DNA hybrid structure . In parallel , we also measured the DNMT3B occupancy and levels of DNA methylation at the RASSF1A promoter ( Figure 8B and 8C ) ; neither condition was affected by ANRASSF1 knockdown , which is consistent with our observations of a lack of effect on DNMT3B occupancy when ANRASSF1 was either overexpressed or digested by RNase .
Some of the features identified for ANRASSF1 , such as the presence of a 5′ cap , transcription through RNAPII , nuclear enrichment and binding to PRC2 , are shared with other lncRNAs [18] , [37] . However , the ANRASSF1 half-life is short ( ∼50 min ) compared with other moderately stable lncRNAs that exert epigenetic roles , such as Air , Kcnq1ot1 and Xist , which have half-lives of 2 . 1 , 3 . 4 and 4 . 6 h , respectively [38] . ANRASSF1 is an unspliced intronic lncRNA and a member of a poorly characterized class of RNAs , as intronic unspliced RNAs are occasionally suspected as technical artifacts or transcriptional noise [39] . Notably , the intronic ANRASSF1 in HeLa cells showed considerably lower expression levels compared with the well-studied intergenic lncRNAs ( Figure S2 ) . Nevertheless , changes in ANRASSF1 abundance through ectopic overexpression or siRNA-mediated knockdown have specifically affected RASSF1A gene expression through PRC2 recruitment . Most importantly , the changes in ANRASSF1 abundance did not affect the expression of RASSF1C , another mRNA isoform expressed in the RASSF1 locus under a different promoter , or the levels of H3K27me3 and PRC2 recruitment to the RASSF1C promoter and the promoters of neighboring genes in the RASSF1 locus , including two other well-characterized tumor suppressor genes , namely TUSC2 [32] and NPRL2 [33] . These data suggest a highly location-specific epigenetic regulation at the histone level that is driven by lncRNA ANRASSF1 . DNA methylation of the RASSF1A promoter involves PRC2 and DNMT3B DNA-methyl transferase in lung carcinoma cell lines that have high HOX3B expression [10] . We observed a limited , non-significant effect on DNA methylation at the RASSF1A promoter when the PRC2 occupancy was changed through ANRASSF1 overexpression or knockdown in HeLa cells . Other factors , such as HOXB3 expression and DNMT3B occupancy at the RASSF1A promoter , are involved in DNA methylation [10] , and the observed limited increase in DNA methylation in HeLa cells overexpressing ANRASSF1 might reflect the eventual limited availability of these factors in HeLa cells . Indeed , the promoter region of RASSF1A in HeLa cells is hypomethylated [3] . Recently , many intronic RNA sequences capable of binding the PRC2 core component EZH2 have been detected in human cancer cells [20] . These authors characterized an EZH2-bound intronic unspliced RNA for the methyltransferase gene SMYD3 in more detail and observed that EZH2 binds to sense intronic ncRNA either at the pre-mRNA stage or after splicing and intron removal [20] . The overexpression of sense ncRNA from the SMYD3 locus caused the epigenetic in cis regulation of SMYD3 and a decrease in cell proliferation [20] . Different from ANRASSF1 , this intronic unspliced lncRNA is not derived from an independent transcriptional unit in the locus . Another example of intronic unspliced lncRNA recruiting PRC2 is Kcnq1ot1 , which is transcribed from the Kcnq1 locus . The lncRNA Kcnq1ot1 regulates the expression of ten genes at the Kcnq1 imprinted cluster [40] through a mechanism clearly distinct from the location-specific cis-acting regulation of the RASSF1A isoform observed here . In the present study , we demonstrated that the unspliced intronic ANRASSF1 binds to PRC2 and is required for PRC2 occupancy at the RASSF1A promoter region . We postulate an in cis mechanism ( Figure 9 ) by which the interaction of ANRASSF1 with both DNA at its transcription site and PRC2 induces the recruitment of PRC2 to the RASSF1A and not the RASSF1C promoter . In turn , PRC2 recruitment induces the accumulation of the repressive mark H3K27me3 , which culminates in the transcriptional down-regulation of only the RASSF1A isoform ( Figure 9 ) . This model , which involves a lncRNA/DNA hybrid , would be analogous to that of the intergenic lncRNA Mistral; however , different from the model proposed here , the intergenic lncRNA Mistral mediates the activation of HOXA6 and HOXA7 transcription in trans [36] . The MLL1 SET domain is involved in recognizing and binding the Mistral/DNA hybrid , thus triggering dynamic changes in the chromosome conformation [36] that involve the formation of a loop in the DNA at the promoter of the HOXA6 and HOXA7 neighboring genes . A loop conformation at the RASSF1A promoter , similar to that proposed for the Mistral locus , could be the subject of further investigation . ANRASSF1 is one of the thousands of unspliced lncRNAs , named TIN and PIN RNAs , transcribed from the intronic regions of 74% of the protein-coding genes in the human genome [22] , [41] . The formation of an RNA/DNA hybrid at the transcription locus could result in a highly location-specific effect for a number of these unspliced intronic lncRNAs . Indeed , 141 lncRNAs map to the intronic regions of 127 protein-coding genes and are associated with chromatin , as identified through chromatin-RNA isolation and high-throughput sequencing [42]; of these , 52% are TIN/PIN RNAs [42] . We hypothesize that other non-characterized unspliced intronic lncRNAs transcribed in the human genome might contribute to a diverse location-specific epigenetic modulation at the loci where they are transcribed [43] . There is increasing evidence that lncRNAs are involved in a number of human diseases [44]–[46] , particularly in cancer [46]–[50] . Taken together , our results reveal a novel mechanism for epigenetic regulation at the RASSF1 locus that involves the antisense unspliced lncRNA ANRASSF1 , suggesting an inverse correlation between ANRASSF1 and RASSF1A expression in both tumor and non-tumor cell lines . Further studies on the potential involvement of ANRASSF1 expression in tumorigenesis are warranted . These results could be the tip of the iceberg of an epigenetic modulation mechanism driven through unspliced intronic lncRNAs that might act at highly gene-specific loci in the human genome .
All cell lines were obtained from the American Type Culture Collection ( ATCC ) and grown as recommended in media supplemented with 10% fetal bovine serum and 1% penicillin/streptomycin ( Gibco ) . Total RNA was extracted using Trizol ( Invitrogen ) and purified using the RNAspin Mini kit ( GE Healthcare ) according to the manufacturer's instructions , except for an extended 1 h treatment with DNase I . Total RNA was quantified on a NanoDrop ND-1000 Spectrophotometer ( NanoDrop Technologies ) . Total RNA integrity was assessed using an Agilent 2100 Bioanalyzer ( Agilent Technologies ) . For RACE-PCR , we used a commercial Human Colon Marathon-Ready cDNA library ( Clontech ) prepared from poly ( A ) RNA and Advantage 2 polymerase ( Clontech ) according to the manufacturer's instructions . Primer-walking PCR , using the sequence obtained from the in silico prediction of the transcriptional start site ( TSS ) , was performed as described in the supporting information ( Protocol S1 ) . All primers are listed in Table S1 . The PCR products were sequenced using the Sanger method . The ANRASSF1 full-length sequence has been deposited in GenBank under accession number KC330992 . Orientation-specific RT-PCR was performed with 1 . 5 µg total RNA using a gene-specific primer complementary to the antisense or sense strand of ANRASSF1 according to the recommendations of Super Script III kit protocol ( Invitrogen ) . Subsequently , PCR was performed using the internal primer pair indicated in Figure 1B . The primers are listed in Table S1 . To control for DNA contamination in the RNA sample , reverse transcription with no RT-primer was performed , followed by PCR . Oligo-dT-primed reverse transcription ( RT ) was performed using 1 µg of total RNA according to the Super Script III kit protocol ( Invitrogen ) . The relative levels of the ANRASSF1 and RASSF1 isoforms and other lncRNAs were determined through quantitative real-time PCR ( qPCR ) ( primers are shown in Table S2 ) with Power SYBR Green ( Applied Biosystems ) using the 7500 Real Time PCR System ( Applied Biosystems ) . The levels of these transcripts were normalized to the level of tubulin and represented as a fold-change using the delta Ct method [51] . Poly ( A ) +-RNA was extracted from LNCaP cells in culture using the FastTrack MAG Maxi mRNA Isolation Kit ( Invitrogen ) according to the manufacturer's instructions with the following modifications: treatment with 25 U of amplification grade DNase I ( Invitrogen ) for 1 h at room temperature . RNA was quantified using the Quant-iT RiboGreen RNA Reagent ( Invitrogen ) and assessed for integrity through electrophoresis with the Bioanalyzer RNA Pico LabChip ( Agilent Technologies ) . Poly ( A ) +-RNA from three biological replicates was processed for Illumina sequencing using the standard protocol for strand-oriented paired-end 75-nt read sequencing , and a total of ∼430 million reads were obtained and mapped with TopHat [52] to the hg19 version of the human genome , followed by an ab-initio assembly using the Cufflinks tool [53] , with the default parameters . A meta-analysis was performed using the publicly available microarray expression data from the Affymetrix HG-U133 Plus2 platform . The purification strategy , RNA processing method and hybridization strategy have been described in the original publications . The expression and sample annotation data were downloaded from the NCBI GEO website: GSE5823 [54] , GSE11118 [55] , GSE10879 [56] , GSE12056 [57] and GSE13471 [58] . A Pearson correlation analysis between the expression signals of probe sets 240278_at ( ANRASSF1 ) and 204346_s_at ( RASSF1 entire locus ) was used in each study . For overexpression , the ANRASSF1 cDNA was amplified through PCR ( primers in Table S1 ) , inserted into the pCEP4 expression vector ( Invitrogen ) to generate pCEP4 ANRASSF1 and subsequently sequenced . The cells were transfected with a linearized pCEP4 ANRASSF1 or a linearized empty vector ( NheI ) using FuGENE 6 Transfection Reagent ( Roche ) . After transfection , the resistant cells were selected using 100 µg/mL hygromycin B ( Invitrogen ) . For silencing , the HeLa cells were plated on 60-mm plates in medium without FBS . Twenty-four hours after plating , a pool of three distinct 25-mer siRNAs ( 5 nM each , final concentration ) targeting ANRASSF1 or a pool of three 25-mer scrambled siRNAs ( Invitrogen ) ( Table S3 ) were transfected using Lipofectamine RNAimax ( Invitrogen ) . The total RNA was extracted at 48 h after transfection . Alternatively , 120 nM of a modified 20-mer oligo ( Table S3 ) was used for ANRASSF1 silencing in the ChIP assays , which were performed at 24 h after transfection using Lipofectamine RNAimax ( Invitrogen ) . The cells were washed with PBS , lysed on ice in 20 mM imidazole ( pH 7 . 2 ) containing 1 mM EDTA and 250 mM sucrose with complete protease inhibitor cocktail ( Roche ) and sonicated . The protein content in the lysates was determined using the BCA protein assay ( Bio-Rad ) . Equal protein amounts ( 40 µg ) were resolved through SDS-PAGE . The primary antibodies were anti-RASSF1A ( Abcam – ab23950 ) and anti-actin ( Millipore – mab1501 ) ; and secondary antibodies were labeled with Alexa Fluor 680 ( Invitrogen ) . The signals were detected using an Odyssey Infrared Imaging System ( LI-COR Biosciences ) . The signal intensities were quantified using Odyssey Application Software v3 ( LI-COR Biosciences ) . HeLa cells transfected with empty pCEP4 or pCEP4 ANRASSF1 were seeded onto 96-well plates . Each pair of biological replicates was seeded onto the same plate . Cell proliferation was evaluated in an MTS assay by measuring formazan absorbance at 24 and 48 h using the CellTiter 96 Aqueous One Solution Cell Proliferation Assay ( Promega ) in a SpectraMax Paradigm ( Molecular Devices ) . Three independent replicate transfections were tested . The proliferation coefficient was defined as the ratio between the average measurements at 24 and 48 h . For the RNAi assay , HeLa cells were seeded onto 96-well plates in media without FBS . The transfections were performed at 24 h after the seeding , and the cells were evaluated for proliferation at 24 and 48 h , as described above . To measure the effect of ANRASSF1 overexpression on the cellular proliferation phenotype , 2×104 cells overexpressing ANRASSF1 or control cells were seeded onto a 6-well plate . The cells were trypsinized every 24 h for 5 days and counted on a Neubauer chamber . The adjustment of exponential functions to the curves and statistical analyses were performed using GraphPad Prism software . To measure the UV-induced sub-G1 population , which is indicative of cell death , plates containing pre-seeded cells at 70% confluence were washed with PBS and irradiated with 40 J/m2 UVC light with a germicidal lamp ( primary emission at 254 nm ) at a rate of 1 . 0 J . m−2 . s−1 , as measured with a VLX 3W radiometer ( Vilber Lourmat ) . After 48 h , the supernatant and the attached cells were collected and fixed with 70% ethanol . Staining with propidium iodide ( PI ) was performed at room temperature for 1 h in PBS solution containing 20 µg/mL PI ( Sigma-Aldrich ) , 200 µg/mL RNase A ( Invitrogen ) and 0 . 1% Triton X-100 ( Sigma-Aldrich ) . These samples were loaded onto a Guava PCA-96 System cytometer ( Millipore ) , and the analyses were performed using CytoSoft software ( Millipore ) . The cytotoxicity induced through staurosporine treatment was evaluated with a real time cytotoxicity assay using the xCELLigence system ( Roche ) . Briefly , 2×103 cells overexpressing ANRASSF1 or control cells were seeded in triplicate onto the wells of a 96-well E-plate ( Roche ) . After 18 h , these samples were treated with 100 nM staurosporine ( Sigma ) or mock-treated with the same concentration of DMSO ( zero time ) . Thereafter , the impedance was continuously measured according to the manufacturer's instructions and as previously described [59] . Three independent biological replicate experiments were performed , each with technical triplicates . Native , non-cross linked RIP was performed using the Magna RIP RNA-Binding Protein Immunoprecipitation Kit ( Millipore ) according to the manufacturer's instructions . The following antibodies were used from Millipore: Normal Mouse IgG ( 12-371 ) and anti-SUZ12 ( 03-179 ) ; and Abcam: anti-EZH2 ( ab3748 ) . The RNAs were extracted using Trizol , treated with TURBO DNase ( Ambion ) at 37°C for 30 min , purified using an RNeasy Micro Kit ( Qiagen ) and quantified with RiboGreen ( Invitrogen ) . All RIP assays were performed in biological triplicate and were detected by RT-qPCR ( primers in Table S2 ) . ChIP was performed using the EZ-Magna ChIP Chromatin Immunoprecipitation Kit ( Millipore ) . The following antibodies were used from Millipore: normal mouse IgG ( 12-371 ) , normal rabbit IgG ( 12-370 ) and anti-SUZ12 ( 03-179 ) ; and Abcam: anti-H3K27me3 ( ab6002 ) , anti-H3 ( ab1791 ) and anti-DNMT3B ( ab2851 ) . The DNA was detected through qPCR ( primers in Table S2 ) . Permeabilization of HeLa cells and RNase treatment were performed as previously described [36] . After the RNase treatment , an aliquot ( 70% vol ) was processed as described above in the ChIP protocol using the following antibodies from Millipore: normal mouse IgG ( 12-371 ) , anti-SUZ12 ( 03-179 ) and anti-RNA Pol II clone CTD4H8 ( 05-623B ) ; and Abcam: anti-DNMT3B ( ab2851 ) . The remaining aliquot ( 30% vol ) was processed as described in the RNA extraction protocol and analyzed through RT-qPCR ( the primers are listed in Table S2 ) . DNA was extracted using phenol/chloroform and Proteinase K using a previously published method [60] and fragmented through sonication . A 1-µg sample of this DNA was treated with 100 U of methylation-dependent McrBC endonuclease ( New England Biolabs ) at 37°C for 16 h . The amount of RASSF1A promoter DNA was measured using qPCR ( primers in Table S2 ) . As a control , an assay with no endonuclease was run in parallel . Three biological replicates were tested . | RASSF1A is a tumor suppressor gene whose expression is repressed through epigenetic events in a wide range of different cancers . Repression is effected by DNA hypermethylation of the RASSF1A promoter , which in turn is triggered through histone H3K9/H3K27 trimethylation repressive marks . The addition of the H3K27me3 mark at the RASSF1A promoter locus involves the polycomb repressive complex 2 ( PRC2 ) . The molecular mechanisms that control the recruitment of PRC2 to the promoter to initiate H3K27 trimethylation and repress RASSF1A expression have not been described . Here , we identified a long noncoding RNA ( lncRNA ) , termed ANRASSF1 for antisense noncoding RASSF1 , that is transcribed from the opposite strand of the RASSF1A gene and is responsible for recruiting PRC2 to the RASSF1A promoter region in a highly location-specific manner . No effect of ANRASSF1 was detected on the promoter of the RASSF1C isoform or the promoters of the four other genes within the vicinity of RASSF1 , including two other well-characterized tumor suppressor genes . This work provides evidence that the epigenetic modulation of the tumor suppressor gene RASSF1A is dependent on the lncRNA ANRASSF1 and highlights the importance of further studies on the involvement of ANRASSF1 in tumorigenesis . | [
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] | 2013 | The Intronic Long Noncoding RNA ANRASSF1 Recruits PRC2 to the RASSF1A Promoter, Reducing the Expression of RASSF1A and Increasing Cell Proliferation |
The sex chromosomes are enriched with germline genes that are activated during the late stages of spermatogenesis . Due to meiotic sex chromosome inactivation ( MSCI ) , these sex chromosome-linked genes must escape silencing for activation in spermatids , thereby ensuring their functions for male reproduction . RNF8 , a DNA damage response protein , and SCML2 , a germline-specific Polycomb protein , are two major , known regulators of this process . Here , we show that RNF8 and SCML2 cooperate to regulate ubiquitination during meiosis , an early step to establish active histone modifications for subsequent gene activation . Double mutants of Rnf8 and Scml2 revealed that RNF8-dependent monoubiquitination of histone H2A at Lysine 119 ( H2AK119ub ) is deubiquitinated by SCML2 , demonstrating interplay between RNF8 and SCML2 in ubiquitin regulation . Additionally , we identify distinct functions of RNF8 and SCML2 in the regulation of ubiquitination: SCML2 deubiquitinates RNF8-independent H2AK119ub but does not deubiquitinate RNF8-dependent polyubiquitination . RNF8-dependent polyubiquitination is required for the establishment of H3K27 acetylation , a marker of active enhancers , while persistent H2AK119ub inhibits establishment of H3K27 acetylation . Following the deposition of H3K27 acetylation , H3K4 dimethylation is established as an active mark on poised promoters . Together , we propose a model whereby regulation of ubiquitin leads to the organization of poised enhancers and promoters during meiosis , which induce subsequent gene activation from the otherwise silent sex chromosomes in postmeiotic spermatids .
Worldwide , 15% of couples have difficulty conceiving a child . In situations of male infertility , approximately 90% of cases are the result of sperm abnormalities [1] . Male infertility is a complex condition with an estimated 15% of cases caused by genetic disorders . However , the etiology of male infertility remains unknown for 40% of cases , which are thus termed idiopathic [2] . To produce unimpaired sperm , precise regulation of germline-specific genes is essential during the late stages of spermatogenesis . These genes are preferentially encoded by the sex chromosomes and have specialized functions in reproduction [3] . Dysregulation leads to sperm abnormalities commonly related to male infertility [4–12] . In vitro fertilization ( IVF ) is a major form of treatment for infertility , but a high failure rate persists , stemming in part from sperm abnormalities [13] . Although the activation of sex-linked genes in late spermatogenesis is a critical step for sperm maturation , the mechanism that underlies this activation remains largely unknown . Meiosis is the central event in germ cell development , followed by postmeiotic stages that form round spermatids and then mature sperm . During male meiosis , in response to the lack of synapsis , the X and Y sex chromosomes undergo forms of regulation distinct from synapsed autosomes , inactivated in a process known as meiotic sex chromosome inactivation ( MSCI ) ( Fig 1A ) . MSCI is an essential event in germ cell development that involves almost complete chromosome-wide silencing [14–19] , and this chromosome-wide silencing is maintained into postmeiotic spermatids following two rounds of meiotic division [19 , 20] . However , a relatively large group of sex-linked male reproduction genes ( ~100 genes ) escape from chromosome-wide silencing for activation in postmeiotic spermatids , ensuring their functions for male reproduction [19–22] . The mechanism by which genes escape from sex chromosome inactivation to become activated persists as an unsolved mystery . DNA damage response ( DDR ) pathways are adapted to act on the meiotic sex chromosomes to initiate MSCI [23] . At the onset of early pachytene stage , ATR phosphorylates histone variant H2AX ( γH2AX ) , which , along with the γH2AX-binding partner MDC1 ( Mediator of DNA damage checkpoint protein 1 ) , initiates MSCI [24–26] . Our recent study demonstrated that DDR signaling also sets up escape gene activation through an RNF8 ( Ring finger protein 8 ) -dependent pathway , although RNF8 is not required for gene silencing in MSCI [27] . RNF8 is an E3 ubiquitin ligase that interacts with MDC1 to mediate the somatic DDR [28–30] . During meiosis , RNF8 promotes ubiquitination on the sex chromosomes [31 , 32] and , subsequently , establishes a downstream cascade of active epigenetic modifications , which lead to gene activation in spermatids [27] . Notably , histone crotonylation , a recently identified histone modification , is associated with gene activation on the sex chromosomes in spermatids [33] , and the chromodomain protein CDYL is a major regulator of histone crotonylation in this context [34] . We have also found that , during meiosis , a germline-specific Polycomb protein , SCML2 ( Sex comb on midleg-like 2 ) , suppresses mono-ubiquitination of histone H2A at Lys119 ( H2AK119ub ) on the sex chromosomes , leading to the activation of a subset of sex-linked genes in spermatids [35] . Since H2AK119ub is mediated by Polycomb repressive complex 1 ( PRC1 ) in the context of gene silencing [36] , the removal of H2AK119ub could potentially be an important step for gene activation . SCML2 is also required for formation of open chromatin on the sex chromosomes during meiosis [37] . These results raise the possibility that RNF8 and SCML2 cooperate to establish epigenetic memories during meiosis through two distinct ubiquitin-mediated regulatory pathways , and that the epigenetic memories induce gene activation later in spermatids . However , given the different functions of these pathways in the regulation of ubiquitination , it remains unknown how they function together to regulate ubiquitination and epigenetic modifications on the sex chromosomes . In this study , we examined the genetic relationship between Rnf8 and Scml2 by generating mice with a double knockout of both genes , and we defined the functions of RNF8 and SCML2 in the regulation of ubiquitination . We show that RNF8 and SCML2 cooperate to regulate distinct forms of ubiquitination on the sex chromosomes . Subsequent to ubiquitin regulation , H3K27 acetylation , a marker of active enhancers [38] , is established as an essential preparatory step for gene activation in the round spermatid phase . Our results offer fundamental information on the epigenetic programming of the sex chromosomes and provide a paradigm for understanding ubiquitin regulation in the context of gene activation .
RNF8 promotes polyubiquitination of unknown substrates on the sex chromosomes at the onset of the early pachytene stage of meiotic prophase , when homologous chromosomes complete synapsis [27 , 35]; subsequently , SCML2 functions in the early-to-mid pachytene transition to remove monoubiquitination of histone H2A ( H2AK119ub ) from the sex chromosomes [35 , 39] ( Fig 1A and 1B ) . To determine how these separate forms of ubiquitin regulation lead to gene activation , we investigated the localization of different forms of ubiquitination on the sex chromosomes during male meiosis via immunofluorescence microscopy . We used an anti-SYCP3 antibody to judge the stages of meiotic prophase , which can be distinguished based on the status of chromosome synapsis ( [40]; see Materials and Methods ) . We began by investigating the signals detected by FK2 , a monoclonal antibody that detects both mono- and polyubiquitinated conjugates [41] ( Fig 1 ) . By immunostaining with FK2 , we anticipated the detection of all ubiquitin signals established on the sex chromosomes . Our detailed analysis revealed that , in wild-type spermatocytes , FK2 signals accumulated on the sex chromosomes beginning in the early pachytene stage , and accumulation persisted through to the early diplotene stage , when homologous autosomes begin to desynapse ( Fig 1C ) . However , FK2 signals were not detected on the sex chromosomes in the late diplotene stages ( Fig 1C ) , suggesting that ubiquitin conjugates are largely removed from the sex chromosomes by the late diplotene stage . Consistent with our previous studies , FK2 signals depended on the presence of RNF8 and were thus absent in spermatocytes from Rnf8 knockout ( Rnf8-KO ) mice ( Fig 1D and [27] ) . Further , FK2 signals did not change in Scml2-KO spermatocytes as compared to wild-type spermatocytes ( Fig 1E and [35] ) . Although SCML2 catalyzes the removal of monoubiquitination , resulting in a likely increase in ubiquitination of the sex chromosomes in Scml2-KO spermatocytes , FK2 signals appeared comparable between wild-type and Scml2-KO mice . We expect that comparable levels of immunofluorescence signals result from an overall abundance of polyubiquitination . Because the FK2 antibody allows us to detect many forms of ubiquitination , we sought to determine a possible genetic relationship between Rnf8 and Scml2 by testing global ubiquitination in a mouse model deficient for both Rnf8 and Scml2 , termed the Rnf8;Scml2 double knockout ( Rnf8;Scml2-dKO ) . Rnf8;Scml2-dKO mice had smaller testes than the wild-type , or the Rnf8-KO , and were infertile ( S1A and S1B Fig ) . Although Rnf8;Scml2-dKO spermatocytes underwent normal chromosomes synapsis ( S1C Fig ) and did not show meiotic arrest , the Rnf8;Scml2-dKO mice appeared to have more profound testicular defects than that of Rnf8 or Scml2 single mutants ( S1D–S1F Fig ) . For example , the population of histone H1T ( testis-specific histone H1 , which begins to accumulate after the mid pachytene stage ) -positive differentiated cells were reduced in the Rnf8;Scml2-dKO testes ( S1F Fig ) . These results suggest that the functions of RNF8 and SCML2 are largely independent . The severe phenotype of Rnf8;Scml2-dKO is unlikely due to a block in spermatogenesis because 96 . 9% of tubules ( n = 65 ) evinced H1T-positive spermatids ( S1G Fig ) . If Rnf8 is solely required to establish all ubiquitin modifications on the sex chromosomes , there should not be any ubiquitination on the sex chromosomes in the Rnf8;Scml2-dKO . However , to our surprise , FK2 signals were present on the sex chromosomes of Rnf8;Scml2-dKO spermatocytes ( Fig 1F ) , although signal intensities were markedly reduced in comparison to accumulation patterns observed in wild-type spermatocytes . Thus , the phenotype of the Rnf8;Scml2-dKO suggests that , while RNF8 mediates polyubiquitination conjugates of unknown substrates , an unknown E3 ligase mediates H2AK119ub independent of RNF8 . Given that SCML2 removes H2AK119ub from the sex chromosomes [35 , 39] , H2AK119ub mediated by an unknown E3 ligase is likely to remain on the sex chromosomes in the absence of SCML2 in Rnf8;Scml2-dKO . A schematic of ubiquitin detected by FK2 in each mutant is shown in Fig 1G . To independently dissect the ubiquitination profiles of the sex chromosomes , we performed immunofluorescence microscopy using a specific monoclonal antibody against H2AK119ub ( clone D27C4 ) , which we previously confirmed to recognize H2AK119ub [35] . In wild-type spermatocytes , H2AK119ub signals were present on the sex chromosomes beginning in the early pachytene stage , although H2AK119ub signals on the sex chromosomes decreased through the mid pachytene and subsequent diplotene stages ( Fig 2A ) . Likewise , in Rnf8-KO spermatocytes , the H2AK119ub signals decreased on the sex chromosomes; however , the depletion of H2AK119ub signals was evident even in the early pachytene stage , and this decrease continued through subsequent pachytene and diplotene stages ( Fig 2B; independent pictures are shown in S2 Fig ) . This difference suggests that RNF8 is required for the temporal presence of H2AK119ub on the sex chromosomes in early pachytene spermatocytes . However , in both wild-type and Rnf8-KO spermatocytes , the decrease of H2AK119ub occurred on the sex chromosomes in the presence of SCML2; in Scml2-KO spermatocytes , an intense H2AK119ub signal accumulated on sex chromosomes starting in the early pachytene stage and persisted until the early diplotene stage ( Fig 2C ) . We explored the genetic relationship between Rnf8 and Scml2 by testing the accumulation of H2AK119ub in Rnf8;Scml2-dKO spermatocytes . To our surprise , the accumulation of H2AK119ub on the sex chromosomes of Rnf8;Scml2-dKO spermatocytes was decreased in comparison to Scml2-KO spermatocytes . The Rnf8;Scml2-dKO demonstrated an intermediate intensity of H2AK119ub on the sex chromosomes between that of wild-type and Scml2-KO beginning in the early pachytene stage and continuing through the early diplotene stage . This intermediate phenotype reveals two distinct forms of H2AK119ub regulation: one is RNF8-dependent H2AK119ub ( Fig 2E ) , and the other is RNF8-independent H2AK119ub mediated by an unknown E3 ligase . Both types of H2AK119ub were detected in the Scml2-KO , but only RNF8-independent H2AK119ub was detected in the Rnf8;Scml2-dKO ( Fig 2F ) , as demonstrated by the intermediate intensity of H2AK119ub signals observed in the Rnf8;Scml2-dKO . Taken together , these results indicate that RNF8 mediates both mono- and polyubiquitination of the sex chromosomes , including H2AK119ub , and SCML2 removes two mechanistically distinct H2AK119ub signals ( i . e . , RNF8-dependent and RNF8-independent signals ) from the sex chromosomes ( Fig 2E ) . Since we found that the timing of the H2AK119ub signal decrease was different between wild-type and Rnf8-KO spermatocytes in the early-to-mid pachytene transition , we carefully dissected the decrease of H2AK119ub in the early pachytene stage of wild-type spermatocytes . Surprisingly , we observed dynamic changes in H2AK119ub on the sex chromosomes during this relatively brief window of meiotic prophase . In a rare population , H2AK119ub accumulated on the entire domain of sex chromosomes ( “Accumulation” in Fig 3A ) , followed by a decrease of the signal in a stepwise fashion . H2AK119ub started to disappear from the Y chromosome but remained on the X chromosome ( “Partial accumulation” in Fig 3A ) . Next , the level of H2AK119ub became comparable between the sex chromosomes and autosomes ( “No enrichment” in Fig 3A ) , and a decrease in H2AK119ub relative to autosomes occurred by the end of the early pachytene stage ( “Decreased” in Fig 3A ) . Population analysis revealed that the accumulation of H2AK119ub was transient at the beginning of the early pachytene stage ( Fig 3B ) . Because we found the accumulation of H2AK119ub at the very beginning of the early pachytene stage , we tested whether this H2AK119ub is established downstream of MDC1 , an interacting partner of RNF8 that directs chromosome-wide spreading of γH2AX to initiate MSCI at the onset of the early pachytene stage [25] . We previously showed that RNF8 functions downstream of MDC1 in male meiosis because RNF8-mediated FK2 signals on the sex chromosomes are abolished in Mdc1-KO spermatocytes [25] . Further analysis of Mdc1-KO spermatocytes found that MDC1 is required for the accumulation of H2AK119ub ( Fig 3C ) . Because MDC1 is required for the chromosome-wide domain formation of DNA damage signaling on the sex chromosomes , thereby initiating meiotic sex chromosome inactivation [25] , there is no chromosome-wide domain formation of the sex chromosomes in Mdc1-KO spermatocytes ( Fig 3C ) . Together with the data showing RNF8-dependent H2AK119ub in the early pachytene stage ( Fig 2B ) , these results demonstrate that the chromosome-wide establishment of H2AK119ub occurs downstream of MDC1 and RNF8 on sex chromosomes at the onset of the early pachytene stage . To confirm our conclusion , we performed additional immunostaining using another monoclonal antibody ( clone E6C5 ) confirmed to recognize polyubiquitination of unknown substrates and not H2AK119ub [35] . As polyubiquitination is mediated by RNF8 ( Fig 4A and 4B ) and is independent of SCML2 ( Fig 4C ) [35] , we observed no accumulation of polyubiquitination on the sex chromosomes in the Rnf8;Scml2-dKO spermatocytes ( Fig 4D ) . Therefore , based on the results from our four mouse models , our findings support our conclusion that polyubiquitination is exclusively mediated by RNF8 and not by SCML2 ( Fig 4E ) . Taken together , our results clarify the functional relationship between RNF8 and SCML2 in the regulation of ubiquitination on the sex chromosomes , and we demonstrate that RNF8 has a previously unrecognized role in mediating H2AK119ub on the sex chromosomes . Further , while the functions of RNF8 and SCML2 are largely independent , they are , in part , functionally connected through the removal of RNF8-dependent H2AK119ub by SCML2 ( Fig 2E ) . On the sex chromosomes , both RNF8 and SCML2 function downstream of a DDR pathway centered on γH2AX and MDC1 [27 , 35] . Given that RNF8 is an interacting partner of MDC1 , and given that SCML2 is recruited to the sex chromosomes during the early-to-mid pachytene transition after the establishment of RNF8-dependent ubiquitination [35 , 39] , we sought to clarify the involvement of RNF8 in the recruitment of SCML2 to the sex chromosomes ( Fig 5A ) . In Rnf8-KO spermatocytes , the recruitment of SCML2 to the sex chromosomes was delayed: accumulation occurred not in the early pachytene stage , as in wild-type spermatocytes ( Fig 5A ) , but during the late pachytene stage ( Fig 5B ) . Furthermore , SCML2 accumulation on the sex chromosomes disappeared in the late diplotene stage of Rnf8-KO spermatocytes , in contrast to persistent accumulation on wild-type sex chromosomes . These results suggest that RNF8 is involved in the efficient recruitment and stability of SCML2 on the sex chromosomes during meiosis . In concert with the ubiquitination analysis above , our results establish a hierarchy of pathways , centered on RNF8 and SCML2 , that act downstream of γH2AX-MDC1 signaling for the regulation of ubiquitination on the sex chromosomes ( Fig 5C ) . We next sought to dissect how this ubiquitin regulatory network coordinates downstream active epigenetic modifications for escape gene activation . Since RNF8 is required to establish dimethylation of H3K4 ( H3K4me2 ) [27] , an active epigenetic modification , we examined the accumulation dynamics of H3K4me2 downstream of the ubiquitin regulatory network . In wild-type spermatocytes , H3K4me2 was depleted from the sex chromosomes at the onset of the pachytene stage; however , we observed a gradual establishment of H3K4me2 in the late pachytene stage , and this accumulation persisted into the later stages of diplotene ( Fig 6A ) . In both Rnf8-KO and Rnf8;Scml2-dKO spermatocytes , H3K4me2 was depleted from the sex chromosomes throughout meiotic prophase ( Fig 6B and 6D ) , indicating that RNF8 is necessary for the establishment of H3K4me2 . Interestingly , in Scml2-KO spermatocytes , the establishment of H3K4me2 in the late pachytene stage never surpassed an intermediate level of signal intensity , less than that in wild-type spermatocytes but greater than the depletion observed in Rnf8-KO and Rnf8;Scml2-dKO spermatocytes ( Fig 6C ) . This intermediate level of accumulation intensity was maintained through the diplotene stages of Scml2-KO spermatocytes ( Fig 6C ) . Together with our ubiquitination analysis , these results suggest that RNF8-mediated polyubiquitination is required for the establishment of H3K4me2 , while H2AK119ub inhibits the establishment of H3K4me2 ( Fig 6E ) . Intrigued by the intermediate signal intensity of H3K4me2 in SCML2-deficient spermatocytes , we carefully detailed the accumulation dynamics of H3K4me2 in late pachytene spermatocytes from our wild-type and Scml2-KO models . Our analysis revealed a delay in the establishment of H3K4me2 in Scml2-KO spermatocytes ( Fig 6F and 6G ) . Because of the gradual accumulation of H3K4me2 on the sex chromosomes , H3K4me2 intensity on the sex chromosomes reached a similar level to that on the autosomes in 90% of wild-type late pachytene spermatocytes ( Fig 6F and 6H ) . The remaining 10% of nuclei showed clear enrichment of H3K4me2 signals on the sex chromosomes ( Fig 6F and 6H ) . However , in the Scml2-KO spermatocytes , H3K4me2 signals remained at a lower level on the sex chromosomes relative to autosomes in 40% of late pachytene spermatocytes ( “Decreased” in Fig 6G and 6H ) ; in the other 60% of late spermatocytes , the level of H3K4me2 intensity was increased on sex chromosomes , reaching an intensity similar to that of autosomes ( “No enrichment” in Fig 6G and 6H ) . Therefore , these results suggest that the SCML2-dependent removal of H2AK119ub facilitates RNF8-dependent establishment of H3K4me2 . While H3K4me2 is established on the sex chromosomes during meiosis , actual gene activation of escape genes occurs in the postmeiotic round spermatid stage [27] , suggesting that escape genes are poised for activation during meiosis . Since H3K4me2 accumulates on the promoters of poised genes during spermatogenesis [42] , we sought to determine whether enhancers on the sex chromosomes are similarly poised during meiosis for escape gene activation in round spermatids . To test this , we investigated the localization of acetylation of H3K27 ( H3K27ac ) , a marker of active enhancers [38] , during meiosis . In wild-type spermatocytes , H3K27ac accumulated on the sex chromosomes in the late pachytene stage ( Fig 7A ) and persisted there through the early diplotene stage , after which the intensity rapidly decreased through the late diplotene stage . However , in Rnf8-KO spermatocytes , H3K27ac accumulation on the sex chromosomes was largely depleted throughout meiotic prophase ( Fig 7B ) , indicating that RNF8 is required for the establishment of H2K27ac on the sex chromosomes during meiosis . In Scml2-KO spermatocytes , H2K27ac accumulated on the sex chromosomes in the late pachytene stage , as seen by comparison to signals on autosomes , but the intensity of H3K27ac was at an intermediate level between the signal intensities observed on wild-type and Rnf8-KO sex chromosomes ( Fig 7C ) . Therefore , it is possible that H2AK119ub must be removed for efficient establishment of H3K27ac , as is the case for H3K4me2 . Finally , in Rnf8;Scml2-dKO spermatocytes , H3K27ac did not accumulate on the sex chromosomes . These results indicate that RNF8 is essential for H3K27ac accumulation . Taken together , our data reveal that the regulation of H3K27ac occurs in the same pathway as the regulation of H3K4me2 , where RNF8 plays an essential role and H2AK119ub is inhibitory to the establishment of the active epigenetic modifications ( Fig 7E ) . Importantly , the accumulation of H3K27ac was fully established in the late pachytene stage of wild-type spermatocytes prior to the establishment of H3K4me2 ( Figs 6A and 7A ) . Thus , we infer that poised enhancers marked with H3K27ac are organized prior to the formation of poised promoters marked with H3K4me2 . Notably , H3K27ac persisted on sex chromosomes into the postmeiotic round spermatid stage and was detected on postmeiotic sex chromatin ( PMSC; Fig 7F ) , a silent chromatin compartment housing either of the two male sex chromosomes [20] . In round spermatids of the Rnf8;Scml2-dKO , the DAPI-dense structure of PMSC is present but H3K27ac was depleted from the PMSC ( S3 Fig ) . Therefore , H3K27ac may serve as a persistent epigenetic memory established during meiosis , maintained through meiotic divisions , and translated to gene activation days after its initial accumulation . Since we determined the regulatory pathways for H3K4me2 and H3K27ac , we next sought to describe the genomic distribution of these modifications on the sex chromosomes using the chromatin immunoprecipitation with sequencing ( ChIP-seq ) assay . We analyzed two representative stages of spermatogenesis: ( 1 ) to identify the establishment of H3K4me2 and H3K27ac modifications , we analyzed pachytene spermatocytes ( PS ) purified from adult testes; and ( 2 ) to determine the persistence of these modifications in postmeiotic stages , we analyzed round spermatids ( RS ) purified from adult testes . For the analysis of H3K4me2 , we used our publish data [42] , and for the analysis of H3K27ac , we carried out ChIP-seq for two independent biological replicates , confirming high levels of reproducibility between the replicates ( S4A Fig ) . In PS , we found that H3K4me2 and H3K27ac were associated with promoter and intergenic regions of the Gm9 and Prdx4 loci , which both represent a class of X-linked RNF8-dependent escape genes ( Fig 8A ) . For the quantitative analyses of ChIP-seq peaks between PS and RS , we used the peak analysis software MAnorm to compare peaks derived from two pairwise next-generation sequencing datasets [43] . On the sex chromosomes , H3K4me2 peaks tend to be distributed in promoter and intergenic regions , and this distribution is maintained from PS into postmeiotic stages ( Fig 8B ) . On the other hand , we detected many H3K27ac peaks unique to intergenic and intronic regions on the sex chromosomes in PS , consistent with its role at enhancers , and only a portion of these peaks persisted into RS ( Fig 8B ) . H3K4me2 and H3K27ac peaks on the sex chromosomes largely overlapped each other at promoter regions , while many H3K27ac peaks unique to intergenic and intronic regions on the sex chromosomes did not overlap with H2K4me2 peaks ( S4B Fig ) . The establishment and persistence of these modifications from PS to RS suggest that H3K4me2 and H3K27ac act on the regulatory regions of sex chromosomes for escape gene activation . To determine the set of escape genes regulated by both SCML2 and RNF8 , we performed RNA-sequencing ( RNA-seq ) using PS and RS purified from the Rnf8;Scml2-dKO . The RNA-seq results of Rnf8;Scml2-dKO cells ( two-biological replicates ) were analyzed with our previous data obtained from wild-type , Rnf8-KO , and Scml2-KO mice [35 , 42] . To identify differentially expressed genes , we applied the following criteria: genes evincing a >1 . 5-fold change in expression , expression in wild-type RS ≥3 RPKM , and Padj < 0 . 05 . Although gene expression profiles remained largely unchanged in wild-type and mutant PS , escape genes were largely down-regulated in the RS of Rnf8;Scml2-dKO ( S1 and S2 Tables ) . 68 genes were down-regulated in Scml2-KO RS , 59 genes were down-regulated in Rnf8-KO RS , and among those , 28 genes were commonly down-regulated in the RS of both the Rnf8-KO and Scml2-KO ( Fig 8C , S3 Table ) . Many of these genes were down-regulated in the Rnf8;Scml2-dKO RS , while 33 genes were exclusively down-regulated in Rnf8;Scml2-dKO RS . Next , we investigated the expression levels of groups of X-linked genes to determine the nature of escape gene regulation by both RNF8 and SCML2 . The group of genes down-regulated in Scml2-KO RS were also down-regulated in Rnf8-KO RS , and vice versa: the group of genes down-regulated in Rnf8-KO RS were also down-regulated in Scml2-KO RS ( Fig 8D ) . Both groups of genes were further down-regulated in the RS of the Rnf8;Scml2-dKO ( Fig 8D ) . These results demonstrate that the functions of RNF8 and SCML2—while largely independent—converge to cooperatively activate escape genes on the X chromosome in RS . We previously demonstrated that H3K4me2 is enriched on escape genes in RS in an RNF8-dependent manner , while H3K4me2 is also enriched on X-linked genes repressed in meiotic and post-meiotic cells [42] . These genes , which are subject to postmeiotic silencing , are proposed to be poised for activation after fertilization [42] . Thus , H3K4me2 is associated with both escape gene activation and gene poising during postmeiotic silencing . To further define the mechanism for escape gene activation , we sought to determine whether H3K27ac accumulates on escape genes more than on non-escape genes on the RS X chromosome . Indeed , H3K27ac is highly enriched on escape genes that are regulated by RNF8 and SCML2 in comparison to other genes that are regulated by neither RNF8 nor SCML2 ( Fig 8E ) . Therefore , these results suggest that H3K27ac , like H3K4me2 , is associated with escape gene activation in RS .
In this study , we elucidate the genetic relationship between RNF8 and SCML2 , two regulatory factors necessary for escape gene activation [27 , 35] . We also illuminate a ubiquitin regulatory network that facilitates the deposition of active histone modifications on the sex chromosomes during meiosis for postmeiotic escape gene activation . Using three independent antibodies that recognize different forms of ubiquitination , we found that SCML2 facilitates the removal of RNF8-dependent H2AK119ub , demonstrating an important form of interplay between RNF8 and SCML2 ( Fig 2E ) . Interestingly , SCML2 also facilitates the removal of RNF8-independent H2AK119ub , and we also confirmed the presence of RNF8-dependent polyubiquitination that is not deubiquitinated in an SCML2-dependent manner . Considering how they are jointly regulated by RNF8 and/or SCML2 , polyubiquitination , RNF8-dependent H2AK119ub , and RNF8-independent H2AK119ub are distinct from each other . H2AK119ub is a characteristic mark mediated by RNF2 , which is a major catalytic subunit of PRC1 [36] . In somatic cells , DNA damage triggers RNF2-dependent H2AK119ub ( monoubiquitination ) [44] . Therefore , it is possible that RNF8-independent H2AK119ub during meiosis is mediated by RNF2 downstream of γH2AX-MDC1 signaling . Furthermore , in somatic cells , RNF8 mediates both mono- and polyubiquitination of H2A and H2AX [29 , 30] . Our identification of RNF8-dependent H2AK119ub on the sex chromosomes reveals a commonality between the somatic DDR pathway and the DDR pathway on sex chromosomes . This finding further supports the notion that DNA damage response pathways are adapted to regulate the sex chromosomes during meiosis [25] . Based on work presented here , we conclude that two distinct forms of regulation for H2AK119ub ( RNF8-independent and RNF8-dependent ) take place downstream of γH2AX-MDC1 signaling on the chromosome-wide domain of the sex chromosomes . While MDC1 recruits RNF8 in the somatic DDR [28–30] , these proteins appear to have largely distinct functions during male meiosis . In contrast to MDC1 , which promotes chromosome-wide silencing of the sex chromosomes during meiosis [25] , RNF8 instead promotes the expression of escape genes [27] . Still , we find that both MDC1 and RNF8 are required for H2AK119ub on the chromosome-wide domain of the sex chromosomes , and therefore may cooperate in this process , perhaps analogous to the cooperation of MDC1 and RNF8 in mediating polyubiquitination/monoubiquitination of H2A and H2AX during the somatic DDR . A cooperative role of MDC1 and RNF8 in mediating histone ubiquitination may therefore represent its “primordial” function since it appears to be shared between the somatic DDR and male meiosis . We also find that RNF8 promotes , but is not required for , the accumulation of SCML2 on the sex chromosomes . Since SCML2 accumulation is delayed and attenuated , but not abrogated in the Rnf8-KO ( Fig 5 ) , the accumulation of SCML2 may not be due to a physical interaction between these proteins . Perhaps RNF8-mediated ubiquitination of chromatin , whether in the form of polyubiquitination or monoubiquitination , or both , creates an environment that promotes the accumulation of SCML2 . Although SCML2 accumulates on the sex chromosomes during the transition between early-to-mid pachytene stages , we found that the abnormal H2AK119ub signals were obvious in the early pachytene stage of Scml2-KO mice . Therefore , these results suggest that SCML2’s function does not necessarily reflect its accumulation status on the sex chromosomes . With the analysis of active histone modifications , we reveal the functional significance of a ubiquitin network on the sex chromosomes . RNF8 is required to establish H3K27ac and H3K4me2 , and deubiquitination of H2K119ub by SCML2 appears to be necessary for levels commensurate with the accumulation of H3K27ac and H3K4me2 on wild-type sex chromosomes . There are at least two possible mechanisms for the regulation of H3K27ac and H3K4me2 active marks . First , as we propose in a model described in Figs 6E and 7E , RNF8-dependent polyubiquitination may establish H3K27ac and H3K4me2 , while the presence of H2AK119ub is inhibitory to these modifications . Since RNF8 mediates polyubiquitination of unknown substrates during meiosis , identifying theses substrates is an important next step to dissect the link between DDR pathways and the establishment of active epigenetic modifications . The second possibility is that RNF8-dependent H2AK119ub is involved in establishing H3K27ac and H3K4me2 , perhaps in conjunction with RNF8-dependent polyubiquitination events . Subsequently , SCML2-dependent deubiquitination of H2AK119ub might promote the normal accumulation of H3K27ac and H3K4me2 marks . This second model is based upon the possibility that completion of a ubiquitination-deubiquitination cycle at H2AK119 regulates active marks on H3 . Since SCML2 is recruited after initial RNF8-dependent ubiquitination of chromatin on the sex chromosomes , subsequent deubiquitination of H2AK119 by SCML2 could provide a mechanism that controls the timing of H3K27ac and H3K4me2 accumulation . Based on our data , we propose that there are two critical steps for escape gene activation: the first step is epigenetic programming that establishes active epigenetic memories on silent sex chromosomes during meiosis , and the second step occurs after meiotic division when genes are activated in spermatids based on established epigenetic memories . Here , we identify H3K4me2 , a modification associated with active transcription [45] , and H3K27ac , a marker of active enhancers [38] , as candidate factors for epigenetic memories that persist from meiosis to spermatids . The identification of regulatory mechanisms and the genomic distribution of two active epigenetic modifications , H3K4me2 and H3K27ac , allow us to speculate how escape genes are targeted for activation via RNF8- and SCML2-dependent mechanisms . Since H3K27ac establishment precedes H3K4me2 establishment on the sex chromosomes , it is possible that specific enhancers serve as initiation sites by which escape genes can be selected ( Fig 8C ) . Our cytological analysis reveals that RNF8- and SCML2-dependent modifications occur in a coordinated manner during specific substages of meiotic prophase . RNF8 mediates ubiquitination while SCML2 removes H2AK119ub in the early pachytene stage , and H3K27ac appears on the sex chromosome in the late pachytene stage . We therefore speculate that intrinsic genomic and epigenomic features of escape gene enhancers provide the initial mark ( s ) that allow ( s ) escape genes to be selected for RNF8- and/or SCML2-dependent epigenetic modification in the early pachytene stage . We speculate that specific transcription factors ( TFs ) and H3K4me2 are then established on escape genes during the pachytene-to-diplotene transition . This is a new view of how escape genes are activated downstream of a chromosome-wide ubiquitin regulatory network on the sex chromosomes , and the identification and functional determination of enhancers marked by H3K27ac makes for an intriguing follow-up goal . Although this study is based on mouse models , the findings are relevant to key issues pertaining to human male infertility , specifically the regulation of sex-linked genes essential for sperm development . Our study provides fundamental information regarding epigenetic programming and serves as a general paradigm for epigenetic gene activation . The essential epigenetic mechanism of sex-linked gene expression is highly conserved in human and mouse spermatogenesis [19] . Thus , elucidating a gene activation mechanism in a mouse model should directly increase our knowledge of human male infertility .
Rnf8- and Scml2-knockout ( KO ) mice are described in the literature [35 , 46] . Both mouse models are on a C57BL/6 background . Heterozygous Rnf8 males and females were bred to produce Rnf8-KO male pups . Because Scml2 is an X-linked gene , heterozygous Scml2 females were bred with wild-type C57BL/6 male mice to produce Scml2-KO male pups . Heterozygous Rnf8 male mice and double heterozygous Rnf8;Scml2 female mice were bred to produce Rnf8;Scml2-double knockout ( dKO ) male pups . All animals were handled in strict accordance with good animal practice as defined by the relevant national animal welfare bodies . All experimental work was approved by the Institutional Animal Care and Use Committee protocol no . IACUC2015-0032 . To evaluate the sizes of testes between mouse models , the weight of the 2 testes obtained from a mouse were recorded in milligrams and summed; then , this value was divided by the mouse body weight recorded in grams . Data were collected from 9 , 5 , 7 , and 7 independent mice from each mouse model ( wild-type , Rnf8-KO , Scml2-KO , and Rnf8;Scml2-KO , respectively ) for comparison at the ages of 6–48 weeks postpartum . Statistical analyses were performed using Prism 7 ( GraphPad ) ; data underwent unpaired t-test between each mouse line . For preparation of testicular paraffin blocks , testes of mutants and littermate controls were fixed with 4% paraformaldehyde at 4°C overnight . Testes were then dehydrated and embedded in paraffin . For histological analyses , 6 μm-thick paraffin sections were deparaffinized and autoclaved in Target Retrieval Solution ( DAKO; S-1700 ) at 121°C for 20 min . The sections were blocked with Blocking One Histo ( Nacalai USA; 06349–64 ) for 10 min at room temperature , and then incubated with primary antibodies at 4°C overnight . The following primary antibodies were used at the described dilutions: rabbit monoclonal anti-Wilm’s Tumor 1 , WT1 ( Abcam; ab89901 ) , 1:200; mouse monoclonal anti-promyelocytic leukemia zinc finger antibody , PLZF ( Santa Cruz Biotechnology; sc-28319 ) , 1:100; guinea pig polyclonal anti-testis-specific histone H1 , H1T ( gift from Mary Ann Handel ) , 1:500; mouse monoclonal anti-phosphorylated H2AX ( Ser139 ) , γH2AX ( Millipore; 05–636 ) , 1:2500; rabbit polyclonal anti-acetylated-histone H3 ( Lys27 ) , H3K27ac ( Diagenode; C15410196 ) , 1:50; and rabbit polyclonal anti-dimethyl-Histone H3 ( Lys4 ) , H3K4me2 ( Millipore; 07–030 ) , 1:100 . Resulting signals were detected by incubation with secondary antibodies: Alexa Fluors 488 ( ThermoFisher Scientific; A-11017 or A-11070 ) and 594 ( ThermoFisher Scientific; A-11020 or A-11072 ) . Sections were counterstained with DAPI ( 1 μg/ml ) . Images were obtained with a Nikon Eclipse Ti-E microscope equipped with a Zyla 5 . 5 sCMOS camera ( Andor Technology ) using a 20x Plan Apo objective , NA 0 . 75 ( Nikon ) . Images were processed using NIS-Elements ( Nikon ) and Photoshop ( Adobe ) software . For analysis , a minimum of 10 images per experimental group was captured . For hematoxylin and eosin ( H&E ) staining , slides were deparaffinized and then placed in hematoxylin for 10 min . Then , slides were rinsed in warm water for 10 min and placed in eosin stain for 10 min . Following dehydration , coverslips were mounted on slides with mounting medium ( Fisher Scientific; SP15-500 ) . All images of H&E-stained sections were acquired with a Nikon Eclipse E800 microscope equipped with a Nikon DXM1200 digital camera using a 20x Plan Fluor objective , NA 0 . 50 ( Nikon ) . Image acquisition was performed using NIS-Elements ( Nikon ) software . For analysis , a minimum of 5 images per experimental group was captured . Meiotic chromosome spreads were prepared as previously described [40 , 47] . For immunostaining experiments , surface spreads were washed in PBST for 30 min at room temperature and blocked with antibody dilution buffer ( 0 . 15% BSA , 0 . 1% Tween 20 in PBS ) for 30 min at room temperature . Primary antibodies were added to surface spreads and incubated overnight in humid chambers at room temperature . The following primary antibodies were used with the corresponding dilutions: mouse monoclonal anti-SYCP3 ( Abcam; ab97672 ) , 1:5000; rabbit polyclonal anti-SYCP3 ( Novus; NB300-231 ) , 1:500; rabbit polyclonal anti-SYCP1 ( Abcam , ab15090 ) , 1:1500; mouse monoclonal anti-ubiquitinated proteins , clone FK2 ( Millipore; 04–263 ) , 1:500; rabbit polyclonal anti-monoubiquitinated histone H2A , H2AK119ub ( clone D27C4; Cell Signaling Technology; #8240 ) , 1:1000; mouse monoclonal anti-monoubiquitinated histone H2A , clone E6C5 ( Millipore; 05–678 ) , 1:1000; rabbit polyclonal anti-acetylated histone H3 Lys27 , H3K27ac ( Active Motif; 39133 ) , 1:500; and rabbit polyclonal anti-dimethyl histone H3 Lys4 , H3K4me2 ( Millipore; 07–030 ) , 1:500 . The slides were incubated for 1 h at room temperature in humid chambers in darkness with various combinations of the following secondary antibodies: Alexa Fluors 488 , 594 , 647 ( ThermoFisher Scientific; A-21237 , A-21246; Jackson ImmunoResearch; 706-606-148 ) , and/or Cy3 ( Jackson ImmunoResearch; 115-167-003 or 111-166-003 ) . Slides were mounted with #1 . 5 thickness coverslips ( ThermoFisher Scientific; 12-544G ) using ProLong Gold ( ThermoFisher Scientific; P36930 ) after incubation in PBST containing DAPI ( 1 μg/ml ) for 10 min at room temperature in darkness . Images were obtained with a Nikon Eclipse Ti-E microscope equipped with a Zyla 5 . 5 sCMOS camera ( Andor Technology ) and a 60x CFI Apochromat TIRF oil immersion objective , NA 1 . 4 ( Nikon ) . Images were processed with NIS-Elements ( Nikon ) , Fiji ImageJ ( NIH [48] ) , Photoshop ( Adobe ) , and Illustrator ( Adobe ) software . A minimum of 30 spermatocyte nuclei images per substage of meiotic prophase , from at least 3 independent mice per mouse model , was captured for analysis . Analysis of chromosome spreads included comparison of accumulation , depletion , and relative intensity patterns on the sex chromosomes using antibodies of interest , and between matched substages of meiotic prophase between the four mouse models . Stages of spreads were distinguished by immunostaining with anti-SYCP3 antibody as previously described [40] . To dissect the dynamic accumulation of different factors on the sex chromosomes in late prophase , we categorized diplotene spermatocytes into two stages: early and late . Briefly , early diplotene spermatocytes were distinguished by partial desynapsis of <50% of autosomes and the stretched status of sex chromosome axes; late diplotene spermatocytes were distinguished by increasingly broad desynapsis of >50% of autosomes and the compaction of sex chromosome axes . To generate the line traces , we exported the adjusted images to the NIH’s ImageJ software and performed the quantitative analysis along a single transect as shown as performed previously [27] . Round spermatids were examined with slides preserving the relative nuclear organization of spermatogenic cells , prepared as previously described [20 , 49 , 50] and imaged as described above except with a 100x CFI Apochromat TIRF oil immersion objective , NA 1 . 4 ( Nikon ) . For ChIP-seq , pachytene spermatocytes and round spermatids were isolated from wild-type testes through BSA gravity sedimentation as described [51] . To perform RNA-seq of cells isolated from Rnf8;Scml2-dKO testes , the same method of BSA gravity sedimentation was performed on a small scale , which enabled the purification of PS and RS from a single male mouse . Briefly , a pair of testes from one Rnf8;Scml2-dKO mouse underwent digestion by treatments with collagenase and trypsin , along with DNase I . The cells were isolated and suspended in Krebs-Ringer Bicarbonate Buffer containing 0 . 5% BSA . Subsequently , the cell suspension was loaded into a gradient of Krebs-Ringer Bicarbonate Buffer containing 2% and 4% BSA , generated by a gradient maker ( VWR; GM-100 ) . The cell suspension was allowed to settle for 3 h at 4°C before fractions were collected . Purity was confirmed by nuclear staining of a sample aliquot of each collected fraction with Hoechst 33342 via fluorescence microscopy . Greater than 90% purity was confirmed for each purification . Cells were suspended in chilled 1x PBS . One-eleventh volume of crosslinking solution ( 50 mM HEPES-NaOH pH 7 . 9 , 100 mM NaCl , 1 mM EDTA , 0 . 5 mM EGTA , and 8 . 8% formaldehyde ) was added to the cell suspension and incubated on ice for 8 min . One-twentieth volume of 2 M glycine was added to the cell suspension and incubated at room temperature for 5 min to stop the reaction . Cells were washed twice with PBS , frozen at -80°C , and lysed at 4°C for 10 min each in ChIP lysis buffer 1 ( 50 mM HEPES pH 7 . 9 , 140 mM NaCl , 10% glycerol , 0 . 5% IGEPAL-630 , 0 . 25% Triton X-100 ) . After centrifugation at 2 , 000xg for 10 min at 4°C , pellets were resuspended with ChIP lysis buffer 2 ( 10 mM Tris-HCl pH 8 . 0 , 200 mM NaCl , 1 mM EDTA , 0 . 5 mM EGTA ) and incubated at 4°C for 10 min . After centrifugation at 2 , 000xg for 10 min at 4°C , pellets were washed with TE containing 0 . 1% SDS and protease inhibitors ( Sigma; 11836145001 ) , and resuspended with the same buffer . Chromatin was sheared to approximately 200–500 bp by sonication using a Covaris sonicator at 10% duty cycle , 105 pulse intensity , 200 burst for 2 min . Sheared chromatin was cleared by centrifugation at 20 , 000xg for 20 min , followed by pre-incubation with Dynabeads Protein G . Chromatin immunoprecipitation was carried out on an SX-8X IP-STAR compact automated system ( Diagenode ) . Briefly , Dynabeads Protein G were pre-incubated with 0 . 1% BSA for 2 h . Then , the cleared chromatin was incubated with beads conjugated to antibodies against H3K27ac ( Active Motif; 39133 ) at 4°C for 8 h , washed sequentially with wash buffer 1 ( 50 mM Tris-HCl pH 8 . 0 , 150 mM NaCl , 1 mM EDTA , 0 . 1% SDS , 0 . 1% NaDOC , and 1% Triton X-100 ) , wash buffer 2 ( 50 mM Tris-HCl pH 8 . 0 , 250 mM NaCl , 1 mM EDTA , 0 . 1% SDS , 0 . 1% NaDOC , and 1% Triton X-100 ) , wash buffer 3 ( 10 mM Tris-HCl pH 8 . 0 , 250 mM LiCl , 1 mM EDTA , 0 . 5% NaDOC , and 0 . 5% NP-40 ) , wash buffer 4 ( 10 mM Tris-HCl pH 8 . 0 , 1 mM EDTA , and 0 . 2% Triton X-100 ) , and wash buffer 5 ( 10 mM Tris-HCl ) . DNA libraries were prepared through the ChIPmentation method [52] . Briefly , beads were resuspended in 30 μl of the tagmentation reaction buffer ( 10 mM Tris-HCl pH 8 . 0 and 5 mM MgCl2 ) containing 1 μl Tagment DNA Enzyme from the Nextera DNA Sample Prep Kit ( Illumina ) and incubated at 37°C for 10 min in a thermal cycler . The beads were washed twice with 150 μl cold wash buffer 1 , incubated with elution buffer ( 10 mM Tris-HCl pH 8 . 0 , 1 mM EDTA , 250 mM NaCl , 0 . 3% SDS , 0 . 1 μg/μl Proteinase K ) at 42°C for 30 min , and then incubated at 65°C for another 5 h to reverse cross-linking . DNA was purified with the MinElute Reaction Cleanup Kit ( Qiagen ) and amplified with NEBNext High-Fidelity 2x PCR Master Mix ( NEB ) . Amplified DNA was purified by Agencourt AMPure XP ( Beckman Coulter ) . Afterward , DNA fragments in the 250- to 500-bp size range were prepared by agarose gel size selection . DNA libraries were adjusted to 5 nM in 10 mM Tris-HCl pH 8 . 0 and sequenced with an Illumina HiSeq 2500 . Data analysis was performed in the Wardrobe Experiment Management System ( https://code . google . com/p/genome-tools/ [53] ) . For the analysis of H3K4me2 , we used our publish data [42] . Briefly , reads were aligned to the mouse genome ( mm10 ) with Bowtie ( version 1 . 0 . 0 [54] ) and displayed on a local mirror of UCSC genome browser as coverage . Islands of H3K27ac- and H3K4me2-enrichment were identified using MACS2 ( version 2 . 0 . 10 . 20130712 [55] ) . MAnorm , software designed for the quantitative comparison of ChIP-seq datasets [43] , was applied to compare the enrichment profile of H3K27ac or H3K4me2 between pachytene spermatocytes and round spermatids . Total RNA was purified from pachytene spermatocytes or round spermatids using an RNeasy Micro Kit ( Qiagen ) according to the manual provided . RNA quality and quantity were checked via Bioanalyzer ( Agilent ) and Qubit ( Life Technologies ) , respectively . The initial amplification step was performed with the Ovation RNA-Seq System v2 ( NuGEN ) . The assay was used to amplify RNA samples and create double-stranded cDNA . Libraries were then created with the Nextera XT DNA Sample Preparation Kit ( Illumina ) and sequenced with an Illumina HiSeq 2500 . The RNA-seq results of Rnf8;Scml2-dKO cells ( two-biological replicates ) were analyzed with our previous data obtained from wild-type , Rnf8-KO , and Scml2-KO mice ( GSE55060 , GSE69946 ) [35 , 42] . Data analysis for RNA-seq was performed in the Wardrobe Experiment Management System . [56] . FASTQ files from the Illumina pipeline were aligned via the Spliced Transcripts Alignment to a Reference ( STAR ) software ( version STAR_2 . 4 . 2a ) [57] with the following parameters:--outFilterMultimapNmax 1--outFilterMismatchNmax 2 ( to see the full manual , go to this STAR GitHub page: https://github . com/alexdobin/STAR/blob/master/doc/STARmanual . pdf ? raw=true ) . RefSeq annotation from the UCSC genome browser ( 11/2012 ) [58] for the mm10 genome was used . The--outFilterMultimapNmax parameter was used to allow unique alignment only , and the--outFilterMismatchNmax parameter was used to allow a maximum of only 2 errors . All reads from resulting bam files were split for related isoforms with respect to RefSeq annotation . Then , an expectation-maximization algorithm was used to estimate appropriate numbers of reads for each isoform [56] . To estimate differences between experiments , the DESeq2 package [59] was used . ChIP-seq and RNA-seq datasets generated in this study were deposited to the NCBI Gene Expression Omnibus ( GEO; http://www . ncbi/nlm . nih . gov/geo/ ) under accession number GSE107398 . | To produce unimpaired sperm , precise activation of germline-specific genes is an essential step during the late stages of spermatogenesis . However , sex chromosomes carrying these genes become silenced in a chromosome-wide manner during meiosis in a process called meiotic sex chromosome inactivation . Sex chromosome inactivation is maintained from meiosis into postmeiotic spermatids . Thus , to ensure the function of sex chromosome-linked ( sex-linked ) genes required for male reproduction , these genes must escape silencing for activation in spermatids . Here , we unravel the epigenetic mechanisms that underlie the activation of sex-linked genes from otherwise inactive sex chromosomes in the male germline . We determine the mechanism by which two factors regulate gene activation: one is RNF8 , a DNA damage response protein , and the other is SCML2 , a germline-specific Polycomb protein . Our data suggest that , during meiosis , RNF8 and SCML2 cooperate to regulate ubiquitination , which establishes active epigenetic modifications on enhancers and promoters for subsequent gene activation; these memories are maintained through meiotic divisions to induce gene activation in spermatids . Importantly , this study uncovers novel epigenetic mechanisms that underlie specific gene activation in spermatids and illuminates potential causes of male infertility . | [
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"preparation",... | 2018 | RNF8 and SCML2 cooperate to regulate ubiquitination and H3K27 acetylation for escape gene activation on the sex chromosomes |
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