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Section: New Results

Inferring and analysing the networks of molecular elements

Metabolic impact of a change of conditions. The increasing availability of metabolomics data enables to better understand the metabolic processes involved in the immediate response of an organism to environmental changes, where the latter can be related to the presence of other species. The data usually come in the form of a list of metabolites whose concentrations significantly changed under some conditions, and are thus not easy to interpret without being able to precisely infer how such metabolites are interconnected. The team introduced a method that enables to organise the data from any metabolomics experiment into what we initially called metabolic stories when we were working with a simpler, graph representation of metabolism, and which have now become metabolic hyperstories as more accurate directed hypergraphs representations are considered. Each (hyper)story corresponds to a possible scenario explaining the flow of matter between the metabolites of interest. The initial work on a graph representation led to the Gobbolino + Touché software (Milre et al., Bioinformatics, 30(1):61-70, 2014). Two newer works working with directed hypergraphs were presented in the PhD of Alice Julien-Laferrière (defended in 2016). Two papers are currently in preparation. They led to the software Totoro (which uses a qualitative measurement of concentrations in two steady-states) and Kotoura (which infers quantitative changes of the reactions) which are both already publicly available.

Metabolic network reconstruction and comparison for understanding virulence. The respiratory tract of swines is colonised by several bacteria among which are three Mycoplasma species: Mycoplasma flocculare, Mycoplasma hyopneumoniae and Mycoplasma hyorhinis. While colonisation by M. flocculare is virtually asymptomatic, M. hyopneumoniae is the causative agent of enzootic pneumonia and M. hyorhinis is present in cases of pneumonia, polyserositis and arthritis. The genomic resemblance among these three Mycoplasma species combined with their different levels of pathogenicity is an indication that they have unknown mechanisms of virulence and differential expression, as for most mycoplasmas. We performed whole-genome metabolic network reconstructions for the three mycoplasmas, as well as cultivation tests and metabolomic experiments through nuclear magnetic resonance spectroscopy (NMR) (Ferrarini et al., BMC Genomics, 17(1):353, 2016). We were able to infer from such reconstructed networks that the lack of pathogenicity of M. flocculare if compared to the highly pathogenic M. hyopneumoniae may be related to its incapacity to produce cytotoxic hydrogen peroxide. A second, more experimentally oriented-paper is currently under revision.