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hal.structure.identifierScience et Technologie du Lait et de l'Oeuf [STLO]
hal.structure.identifierPleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
dc.contributor.authorLECOMTE, Maxime
hal.structure.identifierScience et Technologie du Lait et de l'Oeuf [STLO]
dc.contributor.authorCAO, Wenfan
hal.structure.identifierMathématiques et Informatique Appliquées [MIA Paris-Saclay]
dc.contributor.authorAUBERT, Julie
hal.structure.identifierPleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
dc.contributor.authorSHERMAN, David James
hal.structure.identifierScience et Technologie du Lait et de l'Oeuf [STLO]
dc.contributor.authorFALENTIN, Hélène
hal.structure.identifierPleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
dc.contributor.authorFRIOUX, Clémence
hal.structure.identifierPleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
hal.structure.identifierBiodiversité, Gènes & Communautés [BioGeCo]
dc.contributor.authorLABARTHE, Simon
dc.date.created2023-05-03
dc.description.abstractEnCheese 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.
dc.description.sponsorshipComputationel models of crop plant microbial biodiversity - ANR-22-PEAE-0011
dc.language.isoen
dc.rights.urihttp://creativecommons.org/licenses/by/
dc.subject.enSystems biology
dc.subject.enFermentation
dc.subject.enMetabolic modeling
dc.subject.enMicrobial community
dc.subject.enCheese
dc.subject.enDynamics
dc.subject.enDigital twin
dc.subject.enFlux Balance Analysis
dc.title.enA digital twin of bacterial metabolism during cheese production
dc.typeDocument de travail - Pré-publication
dc.subject.halSciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]
hal.identifierhal-04088301
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-04088301v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=LECOMTE,%20Maxime&CAO,%20Wenfan&AUBERT,%20Julie&SHERMAN,%20David%20James&FALENTIN,%20H%C3%A9l%C3%A8ne&rft.genre=preprint


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