LECOMTE, Maxime; CAO, Wenfan; AUBERT, Julie; SHERMAN, David James; FALENTIN, Hélène; FRIOUX, Clémence; LABARTHE, Simon

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Licence d’utilisation du document

LECOMTE, Maxime
Science et Technologie du Lait et de l'Oeuf [STLO]
Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]

CAO, Wenfan
Science et Technologie du Lait et de l'Oeuf [STLO]

AUBERT, Julie
Mathématiques et Informatique Appliquées [MIA Paris-Saclay]

Langue

Document de travail - Pré-publication

Résumé en anglais

Cheese organoleptic properties result from complex metabolic processes occurring in microbial communities. A deeper understanding of such mechanisms makes it possible to improve both industrial production processes and end-product quality through the design of microbial consortia. In this work, we caracterise the metabolism of a three-species community consisting of Lactococcus lactis, Lactobacillus plantarum and Propionibacterium freudenreichii during a seven-week cheese production process. Using genome-scale metabolic models and omics data integration, we modeled and calibrated individual dynamics using monoculture experiments, and coupled these models to capture the metabolism of the community. This digital twin accurately predicted the dynamics of the community, enlightening the contribution of each microbial species to organoleptic compound production. Further metabolic exploration raised additional possible interactions between the bacterial species. This work provides a methodological framework for the prediction of community-wide metabolism and highlights the added-value of dynamic metabolic modeling for the comprehension of fermented food processes.< Réduire

Mots clés en anglais

Systems biology

Fermentation

Metabolic modeling

Microbial community

Cheese

Dynamics

Digital twin

Flux Balance Analysis

Project ANR

Computationel models of crop plant microbial biodiversity - ANR-22-PEAE-0011

Origine

Importé de hal

Unités de recherche

BioGeCo (Biodiversité Gènes & Communautés) - UMR 1202