7 research outputs found

    Identification of Novel Seroreactive Antigens in Johne’s Disease Cattle by Using the Mycobacterium tuberculosis Protein Array

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    Johne’s disease, a chronic gastrointestinal inflammatory disease caused by Mycobacterium avium subspecies paratuberculosis, is endemic in dairy cattle and other ruminants worldwide and remains a challenge to diagnose using traditional serological methods. Given the close phylogenetic relationship between M. aviumsubsp. paratuberculosis and the human pathogen Mycobacterium tuberculosis, here, we applied a whole-proteome M. tuberculosis protein array to identify seroreactive and diagnostic M. avium subsp. paratuberculosis antigens. A genome-scale pairwise analysis of amino acid identity levels between orthologous proteins in M. avium subsp. paratuberculosis and M. tuberculosis showed an average of 62% identity, with more than half the orthologous proteins sharing 75% identity. Analysis of the M. tuberculosis protein array probed with sera from M. avium subsp. paratuberculosis- infected cattle showed antibody binding to 729 M. tuberculosis proteins, with 58% of them having 70% identity to M. avium subsp. paratuberculosis orthologs. The results showed that only 4 of the top 40 seroreactive M. tuberculosis antigens were orthologs of previously reported M. avium subsp. paratuberculosis antigens, revealing the existence of a large number of previously unrecognized candidate diagnostic antigens. Enzyme-linked immunosorbent assay (ELISA) testing of 20 M. avium subsp. paratuberculosis recombinant proteins, representing reactive and nonreactive M. tuberculosis orthologs, further confirmed that the M. tuberculosis array has utility as a screening tool for identifying candidate antigens for Johne’s disease diagnostics. Additional ELISA testing of field serum samples collected from dairy herds around the United States revealed that MAP2942c had the strongest seroreactivity with Johne’s disease-positive samples. Collectively, our studies have considerably expanded the number of candidate M. avium subsp. paratuberculosis proteins with potential utility in the next generation of rationally designed Johne’s disease diagnostic assays

    The taxonomic name resolution service : an online tool for automated standardization of plant names

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    © The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in BMC Bioinformatics 14 (2013): 16, doi:10.1186/1471-2105-14-16.The digitization of biodiversity data is leading to the widespread application of taxon names that are superfluous, ambiguous or incorrect, resulting in mismatched records and inflated species numbers. The ultimate consequences of misspelled names and bad taxonomy are erroneous scientific conclusions and faulty policy decisions. The lack of tools for correcting this ‘names problem’ has become a fundamental obstacle to integrating disparate data sources and advancing the progress of biodiversity science. The TNRS, or Taxonomic Name Resolution Service, is an online application for automated and user-supervised standardization of plant scientific names. The TNRS builds upon and extends existing open-source applications for name parsing and fuzzy matching. Names are standardized against multiple reference taxonomies, including the Missouri Botanical Garden's Tropicos database. Capable of processing thousands of names in a single operation, the TNRS parses and corrects misspelled names and authorities, standardizes variant spellings, and converts nomenclatural synonyms to accepted names. Family names can be included to increase match accuracy and resolve many types of homonyms. Partial matching of higher taxa combined with extraction of annotations, accession numbers and morphospecies allows the TNRS to standardize taxonomy across a broad range of active and legacy datasets. We show how the TNRS can resolve many forms of taxonomic semantic heterogeneity, correct spelling errors and eliminate spurious names. As a result, the TNRS can aid the integration of disparate biological datasets. Although the TNRS was developed to aid in standardizing plant names, its underlying algorithms and design can be extended to all organisms and nomenclatural codes. The TNRS is accessible via a web interface at http://tnrs.iplantcollaborative.org/ webcite and as a RESTful web service and application programming interface. Source code is available at https://github.com/iPlantCollaborativeOpenSource/TNRS/ webcite.BJE was supported by NSF grant DBI 0850373 and TR by CSIRO Marine and Atmospheric Research, Australia,. BB and BJE acknowledge early financial support from Conservation International and TEAM who funded the development of early prototypes of taxonomic name resolution. The iPlant Collaborative (http://www.iplantcollaborative.org) is funded by a grant from the National Science Foundation (#DBI-0735191)

    A238 ALTERED GUT MICROBIOME COMPOSITION AND FUNCTION ARE ASSOCIATED WITH GUT BARRIER DYSFUNCTION IN HEALTHY RELATIVES OF CROHN’S DISEASE PATIENTS

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    Abstract Background The gut microbiome may play a role in gut barrier homeostasis including epithelial barrier function, but data are scarce and limited to animal studies Aims To assess if alterations in gut microbiome are associated with gut barrier function Methods We utilized the Genetic Environmental Microbial (CCC GEM) cohort of healthy first-degree relatives (FDRs) of Crohn’s disease (CD) patients. Gut barrier function was assessed using the ratio of urinary fractional excretion of lactulose to mannitol (LMR). Stool bacterial DNA was extracted and sequenced for the V4 hypervariable region of the 16S rRNA gene using MiSeq and processed using QIIME2. Microbial functions were imputed using PICRUSt2. The cohort was divided into a North American discovery cohort (n=2,472) and non-North American external validation cohort (n=655). LMR>0.025 was defined as abnormal. LMR-microbiome associations were assessed using multivariable regression model and Random Forest (RF) classifier algorithm. q<0.05 was considered significant when multiple tests were performed Results The median age of the entire cohort was 17.0 years [IQR 12.0; 24.0], 52.6% were females and 25.4% had LMR>0.025. In the discovery cohort, subjects with LMR>0.025 had markedly reduced alpha diversity (Chao1 index, estimate= -0.0037, p=4.0e-04) and altered beta diversity (Bray-Curtis dissimilarity index, PERMANOVA: pseudo-F statistic = 2.99, p=1.0e-03). We identified eight bacterial genera and 52 microbial pathways associated with LMR>0.025 (q<0.05). Four genera (decreased Adlercreutzia [odds ratio(OR)=0.74, 95% confidence interval (CI) 0.6–0.91], Clostridia-UCG-014 [OR=0.71, 95%CI 0.59–0.86], and Clostridium-sensu-stricto-1 [OR=0.75, 95%CI 0.61–0.92] and increased Colidextribacter [OR=1.65, 95%CI 1.2–2.26]) and eight pathways (including decreased biosynthesis of glutamate [OR=0.4, 95%CI 0.21–0.74], tryptophan [OR=0.06, 95%CI 0.01–0.27] and threonine [OR=0.038, 95%CI 0.003–0.41]) were replicated. Bacterial community composition was associated with gut barrier homeostasis as defined by the RF analysis (p= 1.4e-6) Conclusions Gut microbiome community and pathways are associated with gut barrier function. These findings may identify potential microbial targets to modulate barrier function Submitted on behalf of the CCC-GEM Consortium Funding Agencies CCC, CIHRCrohn’s and Colitis Canada Genetics Environment Microbial (CCC-GEM) III; The Leona M. and Harry B. Helmsley Charitable Trust; Kenneth Croitoru is the recipient of the Canada Research Chair in Inflammatory Bowel Disease

    Large-scale association analyses identify host factors influencing human gut microbiome composition

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    To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P < 5 x 10(-8)) threshold. One locus, the lactase (LCT) gene locus, reached study-wide significance (genome-wide association study signal: P = 1.28 x 10(-20)), and it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.95 x 10(-10) < P < 5 x 10(-8)) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization identified enrichment of microbiome trait loci in the metabolic, nutrition and environment domains and suggested the microbiome might have causal effects in ulcerative colitis and rheumatoid arthritis
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