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Bile Acid Signaling in Inflammatory Bowel Disease.

ABSTRACT: Inflammatory bowel disease is a chronic, idiopathic and complex condition, which most often manifests itself in the form of ulcerative colitis or Crohn's disease. Both forms are associated with dysregulation of the mucosal immune system, compromised intestinal epithelial barrier, and dysbiosis of the gut microbiome. It has been observed for a long time that bile acids are involved in inflammatory disorders, and recent studies show their significant physiological role, reaching far beyond being emulsifiers helping in digestion of lipids. Bile acids are also signaling molecules, which act, among other things, on lipid metabolism and immune responses, through several nuclear and membrane receptors in hepatocytes, enterocytes and cells of the immune system. Gut microbiota homeostasis also seems to be affected, directly and indirectly, by bile acid metabolism and signaling. This review summarizes recent advances in the field of bile acid signaling, studies of inflamed gut microbiome, and the therapeutic potential of bile acids in the context of inflammatory bowel disease.

SUBMITTER: Bromke MA

PROVIDER: S-EPMC8396648 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Introduction:Inflammatory bowel disease (IBD) is thought to arise from an abnormal immune response to the gut microbiota. IBD is associated with altered intestinal microbial community structure and functionality, which may contribute to inflammation and complications such as colon cancer and liver disease. Primary sclerosing cholangitis (PSC) is associated with IBD and markedly increases the risk of colon cancer. We hypothesized that secondary bile acids, which are products of microbial metabolism, are increased in PSC patients. Aim:Here, we profiled the fecal bile acid composition and gut microbiota of participants with IBD and PSC, as well as healthy participants. Additionally, we tested the effects of vancomycin, a proposed treatment for PSC, on gut microbiota and fecal bile acid composition in participants with IBD and PSC. Methods:Fecal samples were collected from patients with IBD, IBD/PSC and healthy controls and fecal bile acids and DNA for microbiota analysis were extracted. Fecal bile acids were averaged over a seven-day period. For subjects with IBD/PSC, oral vancomycin 500mg twice a day was administered and fecal samples were collected for up to eleven weeks. Results:Participants with IBD and PSC had less fecal microbial diversity at baseline relative to controls. While there was some evidence of altered conversion of cholic acid to deoxycholic acid, no substantial differences were found in the fecal bile acid profiles of patients with IBD and PSC (n=7) compared to IBD alone (n=8) or healthy controls (n=8). Oral vancomycin was a potent inhibitor of secondary bile acid production in participants with IBD and PSC, particularly deoxycholic acid, although no changes in liver biochemistry patterns were noted over a two week period. Conclusion:In this pilot study, bile acid profiles were overall similar among patients with IBD and PSC, IBD alone, and healthy controls. Microbiota diversity was reduced in those with PSC and IBD compared to IBD alone or healthy controls.

Project description:BackgroundThe human gut microbiome performs important functions in human health and disease. A classic example for host-gut microbial co-metabolism is host biosynthesis of primary bile acids and their subsequent deconjugation and transformation by the gut microbiome. To understand these system-level host-microbe interactions, a mechanistic, multi-scale computational systems biology approach that integrates the different types of omic data is needed. Here, we use a systematic workflow to computationally model bile acid metabolism in gut microbes and microbial communities.ResultsTherefore, we first performed a comparative genomic analysis of bile acid deconjugation and biotransformation pathways in 693 human gut microbial genomes and expanded 232 curated genome-scale microbial metabolic reconstructions with the corresponding reactions (available at https://vmh.life ). We then predicted the bile acid biotransformation potential of each microbe and in combination with other microbes. We found that each microbe could produce maximally six of the 13 secondary bile acids in silico, while microbial pairs could produce up to 12 bile acids, suggesting bile acid biotransformation being a microbial community task. To investigate the metabolic potential of a given microbiome, publicly available metagenomics data from healthy Western individuals, as well as inflammatory bowel disease patients and healthy controls, were mapped onto the genomes of the reconstructed strains. We constructed for each individual a large-scale personalized microbial community model that takes into account strain-level abundances. Using flux balance analysis, we found considerable variation in the potential to deconjugate and transform primary bile acids between the gut microbiomes of healthy individuals. Moreover, the microbiomes of pediatric inflammatory bowel disease patients were significantly depleted in their bile acid production potential compared with that of controls. The contributions of each strain to overall bile acid production potential across individuals were found to be distinct between inflammatory bowel disease patients and controls. Finally, bottlenecks limiting secondary bile acid production potential were identified in each microbiome model.ConclusionsThis large-scale modeling approach provides a novel way of analyzing metagenomics data to accelerate our understanding of the metabolic interactions between the host and gut microbiomes in health and diseases states. Our models and tools are freely available to the scientific community.

Project description:BACKGROUND:Ionizing Radiation (IR) is a known pro-inflammatory agent and in the process of development of biomarkers for radiation biodosimetry, a chronic inflammatory disease condition could act as a confounding factor. Hence, it is important to develop radiation signatures that can distinguish between IR-induced inflammatory responses and pre-existing disease. In this study, we compared the gene expression response of a genetically modified mouse model of inflammatory bowel disease (Il10-/-) with that of a normal wild-type mouse to potentially develop transcriptomics-based biodosimetry markers that can predict radiation exposure in individuals regardless of pre-existing inflammatory condition. RESULTS:Wild-type (WT) and Il10-/- mice were exposed to whole body irradiation of 7?Gy X-rays. Gene expression responses were studied using high throughput whole genome microarrays in peripheral blood 24?h post-irradiation. Analysis resulted in identification of 1962 and 1844 genes differentially expressed (p <?0.001, FDR?<?10%) after radiation exposure in Il10-/- and WT mice respectively. A set of 155 genes was also identified as differentially expressed between WT and Il10-/- mice at the baseline pre-irradiation level. Gene ontology analysis revealed that the 155 baseline differentially expressed genes were mainly involved in inflammatory response, glutathione metabolism and collagen deposition. Analysis of radiation responsive genes revealed that innate immune response and p53 signaling processes were strongly associated with up-regulated genes, whereas B-cell development process was found to be significant amongst downregulated genes in the two genotypes. However, specific immune response pathways like MHC based antigen presentation, interferon signaling and hepatic fibrosis were associated with radiation responsive genes in Il10-/- mice but not WT mice. Further analysis using the IPA prediction tool revealed significant differences in the predicted activation status of T-cell mediated signaling as well as regulators of inflammation between WT and Il10-/- after irradiation. CONCLUSIONS:Using a mouse model we established that an inflammatory disease condition could affect the expression of many radiation responsive genes. Nevertheless, we identified a panel of genes that, regardless of disease condition, could predict radiation exposure. Our results highlight the need for consideration of pre-existing conditions in the population in the process of development of reliable biodosimetry markers.

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Bile Acid Signaling in Inflammatory Bowel Disease.

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