| Project Detail |
The gut microbiota is essential to human health: microorganisms in the human body help to digest nutrients, engage in host metabolism, immunity, behaviour and brain functions. Since the gut microbiota, in contrast to the human genome, can be modified through dietary and therapeutic interventions, modulating the microbiota is a promising path to improve human health and to prevent or treat diseases. However, predicting the effects of microbiota perturbations on the host metabolic phenotype remains extremely challenging due to our limited understanding of bacterial metabolic functions, molecular interactions within microbial communities, and the mechanisms of microbial interactions with the host.
I propose to tackle these challenges with a combination of experimental and computational approaches in a synthetic community of 14 common human gut bacteria, which has been associated with > 150 health-relevant metabolites involved in amino acid, vitamin, and hormone metabolism in vivo. We will follow a bottom-up strategy to i) systematically characterize the capacity of single bacteria to consume and produce metabolites of interest and identify the responsible enzymes; ii) investigate the metabolism of these compounds in compositionally diverse synthetic communities; and iii) quantify and modulate microbiota contribution to the host metabolism of these compounds in mouse models. To this aim, we will combine high-throughput bacterial culturing, metabolomics, transcriptomics and proteomics assays with genome-scale metabolic modelling, graph-based multi-omics integration methods and physiology-based models of microbiota-host interactions. This project will provide a generalized framework to systematically resolve microbiota contributions to the host metabolic phenotype, and elucidate the fundamental principles governing microbiota-host metabolic interactions, thus enabling targeted microbiota interventions to modulate the host metabolic phenotype and improve human health. |
