Quantifying Diet-Induced Metabolic Changes of the Human Gut Microbiome

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Shoaie, Saeed | Ghaffari, Pouyan | Kovatcheva-Datchary, Petia | Mardinoglu, Adil | Sen, Partho | Pujos-Guillot, Estelle | de Wouters, Tomas, T. | Juste, Catherine | Rizkalla, Salwa | Chilloux, Julien | Hoyles, Lesley | Nicholson, Jeremy k. | Consortium, Micro-Obes | Doré, Joël | Dumas, Marc e. | Clément, Karine | Bäckhed, Fredrik | Nielsen, Jens | Kennedy, Sean P. | Prifti, Edi | Pons, Nicolas | Le Chatelier, Emmanuelle | Almeida, Mathieu | Quinquis, Benoit | Levenez, Florence | Galleron, Nathalie | Batto, Jean-Michel | Ehrlich, Stanislav, D. | Blottiere, Herve | Lepage, Patricia | Maguin, Emmanuelle | van de Guchte, Maarten

Edité par CCSD ; Elsevier -

International audience. The human gut microbiome is known to be associated with various human disorders, but a major challenge is to go beyond association studies and elucidate causalities. Mathematical modeling of the human gut microbiome at a genome scale is a useful tool to decipher microbe-microbe, diet-microbe and microbe-host interactions. Here, we describe the CASINO (Community And Systems-level INteractive Optimization) toolbox, a comprehensive computational platform for analysis of microbial communities through metabolic modeling. We first validated the toolbox by simulating and testing the performance of single bacteria and whole communities in vitro. Focusing on metabolic interactions between the diet, gut microbiota, and host metabolism, we demonstrated the predictive power of the toolbox in a diet-intervention study of 45 obese and overweight individuals and validated our predictions by fecal and blood metabolomics data. Thus, modeling could quantitatively describe altered fecal and serum amino acid levels in response to diet intervention.

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