Project description:Inflammatory bowel disease (IBD) is associated with altered microbiota composition and metabolism, but it is unclear whether these changes precede inflammation or are the result of it since current studies have mainly focused on changes after the onset of disease. We previously showed differences in mucus gut microbiota composition preceded colitis-induced inflammation and stool microbial differences only became apparent at colitis onset. In the present study, we aimed to investigate whether microbial dysbiosis was associated with differences in both predicted microbial gene content and endogenous metabolite profiles. We examined the functional potential of mucus and stool microbial communities in the mdr1a -/- mouse model of colitis and littermate controls using PICRUSt on 16S rRNA sequencing data. Our findings indicate that despite changes in microbial composition, microbial functional pathways were stable before and during the development of mucosal inflammation. LC-MS-based metabolic phenotyping (metabotyping) in urine samples confirmed that metabolite profiles in mdr1a -/- mice were remarkably unaffected by development of intestinal inflammation and there were no differences in previously published metabolic markers of IBD. Metabolic profiles did, however, discriminate the colitis-prone mdr1a -/- genotype from controls. Our results indicate resilience of the metabolic network irrespective of inflammation. Importantly as metabolites differentiated genotype, genotype-differentiating metabolites could potentially predict IBD risk.
Project description:Instability in the composition of gut bacterial communities, referred as dysbiosis, has been associated with important human intestinal disorders such as Crohn’s disease and colorectal cancer. Our data showed that Nod2-mediated risk of intestinal inflammation in colitis model is communicable to WT mice by cohousing. Here, we investigated if Nod2-deficient mice microbiota is able to change transcript profiles in Nod2-immunocompetent mice (C57Bl6/J mice) independently of colitis. Analysis used RNA extracted from colonic mucosa of C57Bl/6J mice co-housed with Nod2-deficient mice and C57Bl/6J mice alone. Direct comparisons of 4 biologicals replicates of C57Bl/6J mice cohoused with Nod2-deficient mice vs C57Bl/6J mice were performed.
Project description:Instability in the composition of gut bacterial communities, referred as dysbiosis, has been associated with important human intestinal disorders such as Crohn’s disease and colorectal cancer. Our data showed that Nod2-mediated risk of intestinal inflammation in colitis model is communicable to WT mice by cohousing. Here, we investigated if Nod2-deficient mice microbiota is able to change transcript profiles in Nod2-immunocompetent mice (C57Bl6/J mice) independently of colitis.
Project description:Human Ulcerative colitis (UC) is characterized by chronic colonic inflammation and has been associated with an increased risk of colorectal carcinoma. Gene and protein expression profiles of ABCB1/MDR1 have been shown to be dysregulated in UC and sporadic colorectal cancer. We demonstrated that in a murine model of colitis-associated tumorigenesis, MDR1A KO mice showed reduced tumor load when compared to wildtype (WT) mice. The aim of this study was to identify gene alterations in colitis-associated tumors in the context of MDR1A deficiency. We used microarrays to assess gene expression profiles of colitis-associated colonic tumors from WT or MDR1A KO mice.
Project description:Inflammatory bowel disease (IBD) is associated with altered microbiota composition and metabolism, but it is unclear whether these changes precede inflammation or are the result of it since current studies have mainly focused on changes after the onset of disease. We previously showed differences in mucus gut microbiota composition preceded colitis-induced inflammation and stool microbial differences only became apparent at colitis onset. In the present study, we aimed to investigate whether microbial dysbiosis was associated with differences in both predicted microbial gene content and endogenous metabolite profiles. We examined the functional potential of mucus and stool microbial communities in the mdr1a -/- mouse model of colitis and littermate controls using PICRUSt on 16S rRNA sequencing data. Our findings indicate that despite changes in microbial composition, microbial functional pathways were stable before and during the development of mucosal inflammation. LC-MS-based metabolic phenotyping (metabotyping) in urine samples confirmed that metabolite profiles in mdr1a -/- mice were remarkably unaffected by development of intestinal inflammation and there were no differences in previously published metabolic markers of IBD. Metabolic profiles did, however, discriminate the colitis-prone mdr1a -/- genotype from controls. Our results indicate resilience of the metabolic network irrespective of inflammation. Importantly as metabolites differentiated genotype, genotype-differentiating metabolites could potentially predict IBD risk.
Project description:The goal of this project is to find out whether human intestinal IgA1 and IgA2 secretion, transport and reactivity towards the microbiota might be involved in dysbiosis induction during Crohn’s disease and Ulcerative colitis. Mass spectrometry was used to characterize SIgA from Crohn’s disease patient and Ulcerative colitis patient, in term of O- and N-glycosylation in order to study their reverse transcytosis capacity and their role in intestinal inflammation.
Project description:In the DSS-induced colitis model, the epithelial damage and resulting inflammation is restricted to the colon, with a potential influence on the microbial composition in the adjacent cecum. Several studies have reported changes of the gut microbiota in the DSS-induced colitis model and other mouse models of IBD. Furthermore, metaproteomics analysis of the gut microbiome in a mouse model of Crohn’s disease demonstrated that disease severity and location are microbiota-dependent, with clear evidence for the causal role of bacterial dysbiosis in the development of chronic ileal inflammation. We have developed a refined model of chronic DSS-induced colitis that reflects typical symptoms of human IBD without a risky body weight loss usually observed in DSS models [Hoffmann et al., submitted]. In this study, we used metaproteomics to characterize the disease-related changes in bacterial protein abundance and function in the refined model of DSS-induced colitis. To assess the structural and functional changes, we applied 16S rRNA gene sequencing and metaproteomics analysis of the intestinal microbiota in three different entities of the intestinal environment, i.e. colon mucus, colon content and cecum content.
Project description:Antibiotics have long-lasting consequences on the gut microbiota with the potential to impact host physiology and health. However, little is known about the transgenerational impact of an antibiotic-perturbed microbiota. Here we demonstrated that adult pregnant female mice inoculated with a gut microbial community shaped by antibiotic exposure passed on their dysbiotic microbiota to their offspring. This dysbiotic microbiota remained distinct from controls for at least 5 months in the offspring without any continued exposure to antibiotics. By using IL-10 deficient mice, which are genetically susceptible to colitis, we showed mice that received an antibiotic-perturbed gut microbiota from their mothers had increased risk of colitis. Taken together, our findings indicate that the consequences of antibiotic exposure affecting the gut microbiota can extend to a second generation.
Project description:Microbiota dysbiosis has been reported to contribute to the pathogenesis of colitis, to demonstrate whether IL-17D protects against DSS-induced colitis through regulation of microflora, we performed 16S rRNA sequencing in feces from WT and Il17d-deficient mice. Our data indicate that Il17d deficiency results in microbiota dysibiosis in both steady state and DSS-induced colitis.
Project description:This study aimed to analyze changes in gut microbiota composition in mice after transplantation of fecal microbiota (FMT, N = 6) from the feces of NSCLC patients by analyzing fecal content using 16S rRNA sequencing, 10 days after transplantation. Specific-pathogen-free (SPF) mice were used for each experiments (N=4) as controls.