META-ANALYSIS OF GUT MICROBIAL ASSOCIATIONS WITH MURINE ULCERATIVE COLITIS

There has been a growing interest in understanding the microbiome and the role it plays in disease and maintaining homeostasis since the launch of the Human Microbiome Project. While some members of the gut flora have proven to be beneficial to the host other commensals have been linked to all sorts of disease. Inflammatory bowel diseases (IBD) are one of the most investigated group of diseases within the realm of intestinal microbial communities. Pathogenesis of ulcerative colitis (UC), one of the two main forms of IBD, is highly dependent and influenced by gut microbial composition. Despite the amount of substantial research conducted on the microbiome within the context of IBD, the role played by microbes in this group of diseases remains poorly understood. Some microbial associations have been defined and are consistently found in UC patients. However, there is a lack of consistent microbial associations in colitis mouse models owed to multiple factors, like genetics, diet, and the environment, introducing variability in the structure of the gut microbiome. Variations in bioinformatics pipelines used in microbiome analysis is one of the shortcomings contributing to the absence of reproducible links between with gut microbiome and UC. Using meta-analysis, this thesis aims to reduce the heterogeneity of microbiome data by standardising computational methods across 13 published datasets. In doing that, first relevant datasets were screened, selected, and pre-processed prior to analysis. A pipeline using the ASV method was optimised and tested before the analysis. Initially, a total of 27 datasets were used for the meta-analysis only to find that the different types of colitis mouse models introduced a strong batch effect making it even more difficult to decipher an already complex community. Based on that, the focus of the meta-analysis shifted to investigating gut microbial patterns associated with colitis in the DSS mouse model, which is one of the most commonly used models in experimental colitis. To untangle microbiota data further, two additional meta-analyses were done on different groupings of the chosen DSS datasets. Prior to that each dataset was analysed individual to better understand the nature of the data and the inter-population differences encountered in the meta-analysis. Links between members of the gut microbiota and both colitogenic and colitis states in mice were established in this thesis. Consistent with the current literature, the meta-analysis identified a decrease in the phyla Firmicutes and increase in Bacteroidetes in mice prone to colitis. Peptostreptococaceae species, Erysipelotrichales species, as well as, described pathogens like Helicobacter and Esherichia/Shigella spp were found predominantly in both colitogenic and colitis conditions in mice. Furthermore, this thesis first reports associative links between the genera Terrisporobacter and Herbinix and experimental UC. The last chapter of this thesis focuses on the role of the microbiome in phenotypic modulations in the intestinal epithelial lining elicited by dietary inulin. This work was done in collaboration with the Laboratory of Immunoinflammation in University of Campinas, Brazil. Using flow cytometry, immunostaining, clonogenicity assay, and transcriptomic sequencings they described enhanced proliferative activity of Lgr5+ cells in colonic crypts when mice were put on an inulin diet. Additional experiments, including 16S analysis of microbiome data from SPF mice, GF mice with faecal matter transplant (FMT) and gnotobiotic mice showed that the observed phenotype is dependent on gut microbial composition.