Section: Mathematical & Computational Biology
Topic: Biophysics and computational biology, Microbiology, Systems biology

In silico identification of switching nodes in metabolic networks

Mairet, Francis1  
1 Ifremer, PHYTOX, Laboratoire PHYSALG, F-44000 Nantes, France

Corresponding author(s): Mairet, Francis (francis.mairet@ifremer.fr)

10.24072/pcjournal.480 - Peer Community Journal, Volume 4 (2024), article no. e102.

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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. Additionally, switch metabolites are deeply involved in post-translational modification of proteins, showing their importance in cellular regulation. In P. tricornutum, we show that Erythrose 4-phosphate is an important switch metabolite for mixotrophy suggesting the 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. Finally, a comparison between ISIS and reporter metabolites identified with transcriptomic data confirms the key role of metabolites such as L-glutamate or L-aspartate in the yeast response to nitrogen input variation. Overall, ISIS opens up new possibilities for studying cellular metabolism and regulation, as well as potentially for developing metabolic engineering.

Published online:
DOI: 10.24072/pcjournal.480
Type: Research article
Keywords: Genome-scale metabolic model, Branching point, Reporter metabolites, Flux Balance Analysis

Mairet, Francis 1

1 Ifremer, PHYTOX, Laboratoire PHYSALG, F-44000 Nantes, France
License: CC-BY 4.0
Copyrights: The authors retain unrestricted copyrights and publishing rights 
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Mairet, Francis. In silico identification of switching nodes in metabolic networks. Peer Community Journal, Volume 4 (2024), article  no. e102. doi : 10.24072/pcjournal.480. https://peercommunityjournal.org/articles/10.24072/pcjournal.480/

PCI peer reviews and recommendation, and links to data, scripts, code and supplementary information: 10.24072/pci.mcb.100193

Conflict of interest of the recommender and peer reviewers:
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.

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