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  • Quantifying Diet-Induced Me...
    Shoaie, Saeed; Ghaffari, Pouyan; Kovatcheva-Datchary, Petia; Mardinoglu, Adil; Sen, Partho; Pujos-Guillot, Estelle; de Wouters, Tomas; Juste, Catherine; Rizkalla, Salwa; Chilloux, Julien; Hoyles, Lesley; Nicholson, Jeremy K.; Dore, Joel; Dumas, Marc E.; Clement, Karine; Bäckhed, Fredrik; Nielsen, Jens

    Cell metabolism, 08/2015, Letnik: 22, Številka: 2
    Journal Article

    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. Display omitted •Community And Systems-level INteractive Optimization toolbox•Modeling the effect of diet and gene richness on the gut microbiota•Revealing altered amino acid and SCFA levels after diet interventions Shoaie et al. describe a computational platform designed to elucidate the complex metabolic interactions between gut microbes, host, and diet. The model predictions are validated in humans and reveal how microbial gene richness and diet affect gut microbiota composition, as well as amino acid and SCFA levels.