Samples from in vitro colonic fermentation model
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PROVIDER: PRJNA803451 | ENA |
REPOSITORIES: ENA
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Project description:Changes in microbiome composition have been associated with a wide array of human diseases, turning the human microbiota into an attractive target for therapeutic intervention. Yet clinical translation of these findings requires the establishment of causative connections between specific microbial taxa and their functional impact on host tissues. Here, we infused gut organ cultures with longitudinal microbiota samples collected from therapy-naïve irritable bowel syndrome (IBS) patients under low-FODMAP (fermentable Oligo-, Di-, Mono-saccharides and Polyols) diet. We show that post-diet microbiota regulates intestinal expression of inflammatory and neuro-muscular gene-sets. Specifically, we identify Bifidobacterium adolescentis as a diet-sensitive pathobiont that alters tight junction integrity and disrupts gut barrier functions. Collectively, we present a unique pathway discovery approach for mechanistic dissection and identification of functional diet-host-microbiota modules. Our data support the hypothesis that the gut microbiota mediates the beneficial effects of low-FODMAP diet and reinforce the potential feasibility of microbiome based-therapies in IBS.
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Project description:Changes in microbiome composition have been associated with a wide array of human diseases, turning the human microbiota into an attractive target for therapeutic intervention. Yet clinical translation of these findings requires the establishment of causative connections between specific microbial taxa and their functional impact on host tissues. Here, we infused gut organ cultures with longitudinal microbiota samples collected from therapy-naïve irritable bowel syndrome (IBS) patients under low-FODMAP (fermentable Oligo-, Di-, Mono-saccharides and Polyols) diet. We show that post-diet microbiota regulates intestinal expression of inflammatory and neuro-muscular gene-sets. Specifically, we identify Bifidobacterium adolescentis as a diet-sensitive pathobiont that alters tight junction integrity and disrupts gut barrier functions. Collectively, we present a unique pathway discovery approach for mechanistic dissection and identification of functional diet-host-microbiota modules. Our data support the hypothesis that the gut microbiota mediates the beneficial effects of low-FODMAP diet and reinforce the potential feasibility of microbiome based-therapies in IBS.
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Project description:The human gut microbiota is crucial for degrading dietary fibres from the diet. However, some of these bacteria can also degrade host glycans, such as mucins, the main component of the protective gut mucus layer. Specific microbiota species and mucin degradation patterns are associated with inflammatory processes in the colon. Yet, it remains unclear how the utilization of mucin glycans affects the degradation of dietary fibres by the human microbiota. Here, we used three dietary fibres (apple pectin, β-glucan and xylan) to study in vitro the dynamics of colon mucin and dietary fibre degradation by the human faecal microbiota. The dietary fibres showed clearly distinguishing modulatory effects on faecal microbiota composition. The utilization of colon mucin in cultures led to alterations in microbiota composition and metabolites. Metaproteome analysis showed the central role of the Bacteroides in degradation of complex fibres while Akkermansia muciniphila was the main degrader of colonic mucin. This work demonstrates the intricacy of complex glycan metabolism by the gut microbiota and how the utilization of host glycans leads to alterations in the metabolism of dietary fibres. Metaproteomics analysis of this data reveals the functional activities of the bacteria in consortia, by this contributing to a better understanding of the complex metabolic pathways within the human microbiota that can be manipulated to maximise beneficial microbiota-host interactions. In this study two different mucin samples were used: commercial porcine gastric mucin and in house prepared porcine colonic mucin. This dataset analyses the proteome of: A) autoclaved porcine colonic mucin; B) not autoclaved porcine colonic mucin; C) porcine gastric mucin.
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