Gut microbial metabolomic predictors of dietary-induced obesity and diabetes

International audiencePhenotype heterogeneity is classically infl uenced by genetic, epigenetic and environmental factors but the gut microbiome is also thought to contribute to this phenomenon. Here we studied a population of 50 isogenic C57BL/6J mice developing a range of dietary-induced diabetes, obesity and anxiety sub-phenotypes after 20 days of high-fat feeding. We then profi led the urinary metabolome of these mice by untargeted 1H Nuclear Magnetic Resonance spectroscopy before high-fat-diet feeding and sequentially afterwards. Multivariate statistical models were constructed to predict phenotype heterogeneity and disease sub-phenotypes (lean non diabetics, lean diabetics, obese diabetics) from using baseline metabolic profi les. Among the markers, we found that excretion of gut microbial detoxifi cation metabolites such as phenylacetylglycine (PAG), hippurate, dimethylamine and trimethylamine-N-oxide (TMAO) was strongly predictive of obesity and disease sub-phenotypes, insulin resistance, body/organ weights as well as anxiety/activity outcomes. Genome-wide adipose tissue gene expression profi ling tissue suggests that TMAO excretion correlates with reduced lipogenesis and insulin action. We then set up cellular investigations to further document the causative role of these microbial metabolites. For instance, we tested whether TMAO, PAG, hippurate affect cellular phenotypes associated with obesity and diabetes, through inhibition of in vitro cell differentiation, glucose uptake and lipid accumulation in adipocytes. This work describes new mechanistic detail that underpins the role of the microbiome in cardiovascular disease and also suggests future possibilities for disease prognosis based on microbial signatures and new therapeutic interventional approaches

Broad-Ranging Natural Metabotype Variation Drives Physiological Plasticity in Healthy Control Inbred Rat Strains

Maintaining homeostasis in higher organisms involves a complex interplay of multiple ubiquitous and organ-specific molecular mechanisms that can be characterized using functional genomics technologies such as transcriptomics, proteomics, and metabonomics and dissected out through genetic investigations in healthy and diseased individuals. We characterized the genomic, metabolic, and physiological divergence of several inbred rat strains-Brown Norway, Lewis, Wistar Kyoto, Fisher (F344)-frequently used as healthy controls in genetic studies of the cardiometabolic syndrome. Hierarchical clustering of H-1 NMR-based metabolic profiles (n = 20 for urine, n = 16 for plasma) identified metabolic phenotype (metabotype) divergence patterns similar to the phylogenetic variability based on single nucleotide polymorphisms. However, the observed urinary metabotype variation exceeded that explainable by genetic polymorphisms. To understand further this natural variation, we used an integrative, knowledge-based network biology metabolic pathway analysis approach, coined Metabolite-Set Enrichment Analysis (MSEA). MSEA reveals that homeostasis and physiological plasticity can be achieved despite widespread divergences in glucose, lipid, amino acid, and energy metabolism in the host, together with different gut microbiota contributions suggestive of strain-specific transgenomic interactions. This work illustrates the concept of natural metabolomic variation, leading to physiologically stable albeit diverse strategies within the range of normality, all of which are highly relevant to animal model physiology, genetical genomics, and patient stratification in personalized healthcare