Hoopoe uropygial microbiota
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB27904 | ENA |
REPOSITORIES: ENA
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Project description:Antibiotic use is a risk factor for development of inflammatory bowel diseases (IBDs). IBDs are characterized by a damaged mucus layer, which does not properly separate the host intestinal epithelium from the microbiota. Here, we hypothesized that antibiotics might affect the integrity of the mucus barrier. By systematically determining the effects of different antibiotics on mucus layer penetrability we found that oral antibiotic treatment led to breakdown of the mucus barrier and penetration of bacteria into the mucus layer. Using fecal microbiota transplant, RNA sequencing followed by machine learning and ex vivo mucus secretion measurements, we determined that antibiotic treatment induces ER stress and inhibits colonic mucus secretion in a microbiota-independent manner. This mucus secretion flaw led to penetration of bacteria into the colonic mucus layer, translocation of microbial antigens into circulation and exacerbation of ulcerations in a mouse model of IBD. Thus, antibiotic use might predispose to development of intestinal inflammation by impeding mucus production.
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Project description:Human saliva microbiota is phylogenetically divergent among host individuals yet their roles in health and disease are poorly appreciated. We employed a microbial functional gene microarray, HuMiChip 1.0, to reconstruct the global functional profiles of human saliva microbiota from ten healthy and ten caries-active adults. Saliva microbiota in the pilot population featured a vast diversity of functional genes. No significant distinction in gene number or diversity indices was observed between healthy and caries-active microbiota. However, co-presence network analysis of functional genes revealed that caries-active microbiota was more divergent in non-core genes than healthy microbiota, despite both groups exhibited a similar degree of conservation at their respective core genes. Furthermore, functional gene structure of saliva microbiota could potentially distinguish caries-active patients from healthy hosts. Microbial functions such as Diaminopimelate epimerase, Prephenate dehydrogenase, Pyruvate-formate lyase and N-acetylmuramoyl-L-alanine amidase were significantly linked to caries. Therefore, saliva microbiota carried disease-associated functional signatures, which could be potentially exploited for caries diagnosis. The DMFT INDEX (Decayed, Missing, Filled [DMF] teeth index used in dental epidemiology) values are provided for each sample
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