Alterations of the Gut Microbiome Associated With the Treatment of Hyperuricaemia in Male Rats

The worldwide prevalence of obesity and type 2 diabetes mellitus (T2DM) continues to rise at an alarming pace. Recently the potential role of the gut microbiome in these metabolic disorders has been identified. Obesity is associated with changes in the composition of the intestinal microbiota, and the obese microbiome seems to be more efficient in harvesting energy from the diet. Lean male donor fecal microbiota transplantation (FMT) in males with metabolic syndrome resulted in a significant improvement in insulin sensitivity in conjunction with an increased intestinal microbial diversity, including a distinct increase in butyrate-producing bacterial strains. Such differences in gut microbiota composition might function as early diagnostic markers for the development of T2DM in high-risk patients. Products of intestinal microbes such as butyrate may induce beneficial metabolic effects through enhancement of mitochondrial activity, prevention of metabolic endotoxemia, and activation of intestinal gluconeogenesis via different routes of gene expression and hormone regulation. Future research should focus on whether bacterial products (like butyrate) have the same effects as the intestinal bacteria that produce it, in order to ultimately pave the way for more successful interventions for obesity and T2DM. The rapid development of the currently available techniques, including use of fecal transplantations, has already shown promising results, so there is hope for novel therapies based on the microbiota in the future. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Dysregulated immune responses to gut microbes are central to inflammatory bowel disease (IBD), and gut microbial activity can fuel chronic inflammation. Examining how IBD-directed therapies influence gut microbiomes may identify microbial community features integral to mitigating disease and maintaining health. However, IBD patients often receive multiple treatments during disease flares, confounding such analyses. Preclinical models of IBD with well-defined disease courses and opportunities for controlled treatment exposures provide a valuable solution. Here, we surveyed the gut microbiome of the T-bet −/− Rag2 −/− mouse model of colitis during active disease and treatment-induced remission. Microbial features modified among these conditions included altered potential for carbohydrate and energy metabolism and bacterial pathogenesis, specifically cell motility and signal transduction pathways. We also observed an increased capacity for xenobiotics metabolism, including benzoate degradation, a pathway linking host adrenergic stress with enhanced bacterial virulence, and found decreased levels of fecal dopamine in active colitis. When transferred to gnotobiotic mice, gut microbiomes from mice with active disease versus treatment-induced remission elicited varying degrees of colitis. Thus, our study provides insight into specific microbial clades and pathways associated with health, active disease and treatment interventions in a mouse model of colitis.

The gut microbiome plays a central role in inflammatory bowel diseases (IBDs) pathogenesis and propagation. To determine whether the gut microbiome may predict responses to IBD therapy, we conducted a prospective study with Crohn's disease (CD) or ulcerative colitis (UC) patients initiating anti-integrin therapy (vedolizumab). Disease activity and stool metagenomes at baseline, and weeks 14, 30, and 54 after therapy initiation were assessed. Community α-diversity was significantly higher, and Roseburia inulinivorans and a Burkholderiales species were more abundant at baseline among CD patients achieving week 14 remission. Several significant associations were identified with microbial function; 13 pathways including branched chain amino acid synthesis were significantly enriched in baseline samples from CD patients achieving remission. A neural network algorithm, vedoNet, incorporating microbiome and clinical data, provided highest classifying power for clinical remission. We hypothesize that the trajectory of early microbiome changes may be a marker of response to IBD treatment.