In silicoidentification of switching nodes in metabolic networks

A bstract Cells modulate their metabolism according to environmental conditions. A major challenge to better understand metabolic regulation is to identify, from the hundreds or thousands of molecules, the key metabolites where the re-orientation of fluxes occurs. Here, a method called ISIS (for In Silico Identification of Switches) is proposed to locate these nodes in a metabolic network, based on the analysis of a set of flux vectors (obtained e.g. by parsimonious flux balance analysis with different inputs). A metabolite is considered as a switch if the fluxes at this point are redirected in a different way when conditions change. The soundness of ISIS is shown with four case studies, using both core and genome-scale metabolic networks of Escherichia coli, Saccharomyces cerevisiae and the diatom Phaeodactylum tricornutum . Through these examples, we show that ISIS can identify hot-spots where fluxes are reoriented, some of these nodes corresponding to reporter metabolites identified with transcriptomic data. Additionally, switch metabolites are deeply involved in post-translational modification of proteins, showing their key role in cellular regulation. Finally, we show that Erythrose 4-phosphate is an important switch metabolite for mixotrophy in P. tricornutum , highlighting the (somehow overlooked) importance of this metabolite in the non-oxidative pentose phosphate pathway to orchestrate the flux variations between glycolysis, the Calvin cycle and the oxidative pentose phosphate pathway when the trophic mode changes. Overall, ISIS opens up new possibilities for studying cellular metabolism and regulation, as well as potentially for developing metabolic engineering.