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The obesity pandemic and its comorbidities cause very high societal and economic costs and treatment options are limited (Karlsson, 2013). The intestinal microbiome is altered in obese patients, but a faecal microbiome transplantation (FMT) could be an alternative treatment to obesity (Bäckhed, 2004; Zhang, 2019). To understand how the stability of the intestinal microbiota is maintained before and after transplantation it is necessary to use a mathematical model capable of rationally designing a stable microbial community and predicting the desired metabolic interactions both qualitatively and quantitatively. The SImplified HUMan Intestinal microbiota Consortium (SIHUMIx) has established the continuous cultivation of 8 species in bioreactors under continuous controlled conditions, thus allowing the examination of pH, nutrient availability, and waste products (Becker, 2011; Schäpe, 2019). Therefore, we will develop an atom-level modelling framework capable of connecting directly with the experimental evidence available through mass spectrometry (MS) experiments. We will model the chemical reactions of the SIHUMIx microbiota using directed hypergraphs, where the reactions are the hyperarcs and the molecules are the vertices. These vertices are also graphs representing the structure of the molecules, thus making it possible to track atoms across reactions, before further examination using MS. The modelling approaches developed in SIHUMIx will be applied in more complex communities derived from the human gut and, in in vivo systems from bariatric surgery patients, where the effects of perturbation can be studied. Finally, the results will be transferred to FMT experiments in mice. We will examine existing genomic metabolic network software for the reconstruction of the SIHUMIx species. A total of 10 publicly available software packages were chosen and are now being compared for their completeness and capability of creating community metabolic networks. The work presented in this poster is supported by the Novo Nordisk Foundation grant NF21OC0066551.

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1	Natasha Jorge(natasha@bioinf.uni-leipzig.de)

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1	Bäckhed, F., Ding, H., Wang, T., et al. (2004). The gut microbiota as an environmental factor that regulates fat storage. In: Proceedings of the National Academy of Sciences of the United States of America, 101(44), 15718–15723. Becker, N., Kunath, J., Loh, G., Blaut, M. Human intestinal microbiota: characterization of a simplified and stable gnotobiotic rat model. (2011) In. Gut Microbes. 2(1):25-33 Karlsson, F., Tremaroli, V., Nielsen, J., & Bäckhed, F. (2013). Assessing the human gut microbiota in metabolic diseases. In: Diabetes. American Diabetes Association. Schäpe, S.S., Krause, J.L., Engelmann, B., et al.The simplified human intestinal microbiota (SIHUMIx) shows high structural and functional resistance against changing transit times in in vitro bioreactors. (2019) In: Microorganisms. 7(12):641 Zhang, M., Cai, D., Slater, D., et al. (2019). Impact of Faecal Microbiota Transplantation on Obesity and Metabolic Syndrome—A Systematic Review. In: Nutrients, 11(10), 2291.

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