SteadyCom: Predicting microbial abundances while ensuring community stability.

Genome-scale metabolic modeling has become widespread for analyzing microbial metabolism. Extending this established paradigm to more complex microbial communities is emerging as a promising way to unravel the interactions and biochemical repertoire of these omnipresent systems. While several modeling techniques have been developed for microbial communities, little emphasis has been placed on the need to impose a time-averaged constant growth rate across all members for a community to ensure co-existence and stability. In the absence of this constraint, the faster growing organism will ultimately displace all other microbes in the community. This is particularly important for predicting steady-state microbiota composition as it imposes significant restrictions on the allowable community membership, composition and phenotypes. In this study, we introduce the SteadyCom optimization framework for predicting metabolic flux distributions consistent with the steady-state requirement. SteadyCom can be rapidly converged by iteratively solving linear programming (LP) problem and the number of iterations is independent of the number of organisms. A significant advantage of SteadyCom is compatibility with flux variability analysis. SteadyCom is first demonstrated for a community of four E. coli double auxotrophic mutants and is then applied to a gut microbiota model consisting of nine species, with representatives from the phyla Bacteroidetes, Firmicutes, Actinobacteria and Proteobacteria. In contrast to the direct use of FBA, SteadyCom is able to predict the change in species abundance in response to changes in diets with minimal additional imposed constraints on the model. By randomizing the uptake rates of microbes, an abundance profile with a good agreement to experimental gut microbiota is inferred. SteadyCom provides an important step towards the cross-cutting task of predicting the composition of a microbial community in a given environment.

Farnesoid X Receptor Signaling Shapes the Gut Microbiota and Controls Hepatic Lipid Metabolism.

The gut microbiota modulates obesity and associated metabolic phenotypes in part through intestinal farnesoid X receptor (FXR) signaling. Glycine-ß-muricholic acid (Gly-MCA), an intestinal FXR antagonist, has been reported to prevent or reverse high-fat diet (HFD)-induced and genetic obesity, insulin resistance, and fatty liver; however, the mechanism by which these phenotypes are improved is not fully understood. The current study investigated the influence of FXR activity on the gut microbiota community structure and function and its impact on hepatic lipid metabolism. Predictions about the metabolic contribution of the gut microbiota to the host were made using 16S rRNA-based PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states), then validated using 1H nuclear magnetic resonance-based metabolomics, and results were summarized by using genome-scale metabolic models. Oral Gly-MCA administration altered the gut microbial community structure, notably reducing the ratio of Firmicutes to Bacteroidetes and its PICRUSt-predicted metabolic function, including reduced production of short-chain fatty acids (substrates for hepatic gluconeogenesis and de novo lipogenesis) in the ceca of HFD-fed mice. Metabolic improvement was intestinal FXR dependent, as revealed by the lack of changes in HFD-fed intestine-specific Fxr-null (FxrΔIE) mice treated with Gly-MCA. Integrative analyses based on genome-scale metabolic models demonstrated an important link between Lactobacillus and Clostridia bile salt hydrolase activity and bacterial fermentation. Hepatic metabolite levels after Gly-MCA treatment correlated with altered levels of gut bacterial species. In conclusion, modulation of the gut microbiota by inhibition of intestinal FXR signaling alters host liver lipid metabolism and improves obesity-related metabolic dysfunction. IMPORTANCE The farnesoid X receptor (FXR) plays an important role in mediating the dialog between the host and gut microbiota, particularly through modulation of enterohepatic circulation of bile acids. Mounting evidence suggests that genetic ablation of Fxr in the gut or gut-restricted chemical antagonism of the FXR promotes beneficial health effects, including the prevention of nonalcoholic fatty liver disease in rodent models. However, questions remain unanswered, including whether modulation of FXR activity plays a role in shaping the gut microbiota community structure and function and what metabolic pathways of the gut microbiota contribute in an FXR-dependent manner to the host phenotype. In this report, new insights are gained into the metabolic contribution of the gut microbiota to the metabolic phenotypes, including establishing a link between FXR antagonism, bacterial bile salt hydrolase activity, and fermentation. Multiple approaches, including unique mouse models as well as metabolomics and genome-scale metabolic models, were employed to confirm these results.