Microbiome metabolic modeling as a tool for innovation in fermented foods
At the crossroads of a growing interest in fermented foods as part of a healthy, sustainable diet and advances in multi-omics technologies stands the need for developing new types of fermented foods while improving traditional ones. The scientific path toward these challenges lies in our capacity to rationalize and predict microbial interactions. For this, genome or metagenome-scale metabolic modeling represents a promising approach. We assess its benefits and limits through rare examples in the field of food microbiomes and advocate for community-level metabolic engineering as the superior strategy. We underline their power as a cornerstone in comprehensive and rational strategies for optimization of microbial consortia assembly, whether they are used in bottom-up or top-down approaches. We raise the challenges and bottlenecks of integrating the dynamics of microbial communities and present how we foresee their potential for shaping the future of fermented foods and regulatory science, bridging gaps between knowledge and innovation. • Overview of current research utilizing genome-scale modeling in fermented food science. • Strategies for designing food microbiomes using both bottom-up and top-down approaches. • Challenges, bottlenecks, and perspectives of GSMM in food science.
Authors
- Elham Karimi (ORCID: https://orcid.org/0000-0002-2204-0789)
- Stéphane Chaillou (ORCID: https://orcid.org/0000-0003-2229-0697)
- Julien Tap (ORCID: https://orcid.org/0000-0001-8998-5413)
- Marie‐Christine Champomier‐Vergès
Institutions
- Université Paris-Saclay (FR)
- Microbiologie de l’alimentation au service de la santé (FR)
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
Publication Details
- Journal
- Current Opinion in Food Science
- Published
- 2025-11-21
- DOI
- https://doi.org/10.1016/j.cofs.2025.101368
- Citations
- 1
- Primary Topic
- Microbial Metabolic Engineering and Bioproduction
- Type
- article
- Field-Weighted Citation Impact
- 0.81