Ontology type: schema:ScholarlyArticle Open Access: True
2015-01
AUTHORSCharlie G. Buffie, Vanni Bucci, Richard R. Stein, Peter T. McKenney, Lilan Ling, Asia Gobourne, Daniel No, Hui Liu, Melissa Kinnebrew, Agnes Viale, Eric Littmann, Marcel R. M. van den Brink, Robert R. Jenq, Ying Taur, Chris Sander, Justin R. Cross, Nora C. Toussaint, Joao B. Xavier, Eric G. Pamer
ABSTRACTThe gastrointestinal tracts of mammals are colonized by hundreds of microbial species that contribute to health, including colonization resistance against intestinal pathogens. Many antibiotics destroy intestinal microbial communities and increase susceptibility to intestinal pathogens. Among these, Clostridium difficile, a major cause of antibiotic-induced diarrhoea, greatly increases morbidity and mortality in hospitalized patients. Which intestinal bacteria provide resistance to C. difficile infection and their in vivo inhibitory mechanisms remain unclear. Here we correlate loss of specific bacterial taxa with development of infection, by treating mice with different antibiotics that result in distinct microbiota changes and lead to varied susceptibility to C. difficile. Mathematical modelling augmented by analyses of the microbiota of hospitalized patients identifies resistance-associated bacteria common to mice and humans. Using these platforms, we determine that Clostridium scindens, a bile acid 7α-dehydroxylating intestinal bacterium, is associated with resistance to C. difficile infection and, upon administration, enhances resistance to infection in a secondary bile acid dependent fashion. Using a workflow involving mouse models, clinical studies, metagenomic analyses, and mathematical modelling, we identify a probiotic candidate that corrects a clinically relevant microbiome deficiency. These findings have implications for the rational design of targeted antimicrobials as well as microbiome-based diagnostics and therapeutics for individuals at risk of C. difficile infection. More... »
PAGES205
http://scigraph.springernature.com/pub.10.1038/nature13828
DOIhttp://dx.doi.org/10.1038/nature13828
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PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/25337874
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JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/nature13828'
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curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/nature13828'
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curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/nature13828'
This table displays all metadata directly associated to this object as RDF triples.
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