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Titre : Modeling the gut microbiota from metagenomic data.
 
Abstract : The human gut harbors a complex bacterial community, the gut microbiota, that maintains a symbiotic relationshiwith its host: the microbiota ecology is then linked to the host’s health. This microbial community is usually studied in vivo through metagenomic data, i.e. counts ofmicrobial genes taken randomly in the mixture of the genomes of the microbes composing the microbiota. Mathematical models of the microbial population dynamics are a promising tool to study microbiota fate and models able to simulate metagenomic data comparable to biological experiments would be an important step for model validation enhancement. 

Different levels of gut microbiota modeling are introducedFunctional metagenomic data are analyzed through non-negative matrix factorization (NMF) to identify metabolic profiles that are interpreted as functional potential of microbial meta-populations. Metabolic models of the meta-populations are built to predict the metabolite consumptions and the growth rates, and are plugged to a PDE population dynamics model to account for the interactions between the bacterial populations and the intestinal environment. Conversely, the model outputs can be interpreted as synthetic metagenomic counts that can be compared to experimental data. 

This work is a collaboration with B. Laroche, and with M. Ribot, B. Polizzi, T. Phan and T. Goudon for the population/fluid dynamics of the microbiota and its environment, and with L. Darrigade and M.Leclerc for the metapopulation construction.

salle 178, LaBRI et remote (https://u-bordeaux-fr.zoom.us/j/82532998606?pwd=a0Q3aWZ3ZjZMdC9udXcxem85clJPUT09)