The extent to which microbiota alterations define or influence the outcome of metabolic diseases is still unclear, but the byproducts of microbiota metabolism are known to have an important role in mediating the host-microbiota interaction. Here, we identify that in both pre-clinical and clinical settings, metabolic syndrome is associated with the reduced capacity of the microbiota to metabolize tryptophan into derivatives that are able to activate the aryl hydrocarbon receptor. This alteration is not merely an effect of the disease as supplementation with AhR agonist or a Lactobacillus strain, with a high AhR ligand-production capacity, leads to improvement of both dietary- and genetic-induced metabolic impairments, particularly glucose dysmetabolism and liver steatosis, through improvement of intestinal barrier function and secretion of the incretin hormone GLP-1. These results highlight the role of gut microbiota-derived metabolites as a biomarker and as a basis for novel preventative or therapeutic interventions for metabolic disorders.

Adaptation proceeds through the selection of mutations. The distribution of mutant fitness effect and the forces shaping this distribution are therefore keys to predict the evolutionary fate of organisms and their constituents such as enzymes. Here, by producing and sequencing a comprehensive collection of 10,000 mutants, we explore the mutational landscape of one enzyme involved in the spread of antibiotic resistance, the beta-lactamase TEM-1. We measured mutation impact on the enzyme activity through the estimation of amoxicillin minimum inhibitory concentration on a subset of 990 mutants carrying a unique missense mutation, representing 64% of possible amino acid changes in that protein reachable by point mutation. We established that mutation type, solvent accessibility of residues, and the predicted effect of mutations on protein stability primarily determined alone or in combination changes in minimum inhibitory concentration of mutants. Moreover, we were able to capture the drastic modification of the mutational landscape induced by a single stabilizing point mutation (M182T) by a simple model of protein stability. This work thereby provides an integrated framework to study mutation effects and a tool to understand/define better the epistatic interactions.epistasis | adaptive landscape | distribution of fitness effects T he distribution of fitness effects (DFE) of mutations is central in evolutionary biology. It captures the intensity of the selective constraints acting on an organism and therefore how the interplay between mutation, genetic drift, and selection will shape the evolutionary fate of populations (1). For instance, the DFE determines the size of the population required to see fitness increase or decrease (2