We owe the mouth-watering Parmigiano that we enjoy with a glass of good wine to tiny microscopic artisans, who cooperate harmoniously to craft delicious and healthy food products.

Microorganisms have specific but complementary and interdependent roles during food-making processes. They create a functional network where different species/strains are related, share many substrates, products, and enzymes, and have different tasks in common. On the other hand and at the sub-cellular level, each specific microorganism has its own molecular networks that ensure its functions, like signalling networks, regulatory networks and metabolic networks between enzymes and metabolites.

In order to study these inter and intra-species interactions and predict their outcome, we are using machine learning and network theory approaches to reconstruct and analyse these networks. These approaches allow the integration of multi-omics data (genomics, transcriptomics, metabolomics…) and, thus, allow a more realistic representation of the complex biological processes that govern food making.