MiFoDB, a workflow for microbial food metagenomic characterization, enables high-resolution analysis of fermented food microbial dynamics

Fermented foods, which contain a diversity of microbes and microbial metabolites, have been used for millennia to increase food security, flavor, and nutritional content; more recently, they have been recognized as potential mediators of human health. Metagenomics is a powerful approach to characterize microbes in fermented foods, providing high taxonomic resolution and functional insights. Here, we introduce the Microbial Food DataBase, a metagenomics-based approach designed for the identification of fermentation-associated microbes. Using this primary database of metagenome-assembled genomes and relevant deposited genomes of prokaryotes, eukaryotes, and common food-relevant substrates, we investigated 89 fermented food samples. We present a streamlined high-confidence characterization of microbial diversity in fermented food, identifying previously undiscovered genomes and facilitating strain-level tracking across food environments. The easy and robust functionality of the workflow has significant implications for advancing food safety, promoting desired microbial communities, and increasing sustainability in food production.IMPORTANCEFermented foods have microbial communities that influence food safety, flavor, and human health. Microbial Food DataBase (MiFoDB), an alignment-based sequencing workflow and database, addresses the limitations of existing tools by enabling strain-level resolution, identifying novel genomes, and providing functional insights into microbial communities. Applying MiFoDB to fermented food samples, we demonstrate its ability to uncover novel species, track microbial strains across substrates, and integrate functional annotations. Additionally, the outlined workflow is highly customizable and can be used to generate alignment-based databases for other microbial ecosystems. This work highlights the importance of fermentation-specific workflows for studying microbial food ecosystems, advancing food safety, sustainability, and innovation in fermented food research.

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Publication Details

Journal
mSystems
Published
2025-08-19
DOI
https://doi.org/10.1128/msystems.00141-25
Primary Topic
Probiotics and Fermented Foods
Type
article
Field-Weighted Citation Impact
0.00

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article

MiFoDB, a workflow for microbial food metagenomic characterization, enables high-resolution analysis of fermented food microbial dynamics

Matthew R. Olm, Caroline Isabel Kothe, Justin Laine Sonnenburg, Joshua D. Evans et al.
mSystems
Probiotics and Fermented Foods
article

MiFoDB, a workflow for microbial food metagenomic characterization, enables high-resolution analysis of fermented food microbial dynamics

Matthew R. Olm, Caroline Isabel Kothe, Justin Laine Sonnenburg, Joshua D. Evans, Elisa B. Caffrey, Hannah C. Wastyk
article en

Abstract

Fermented foods, which contain a diversity of microbes and microbial metabolites, have been used for millennia to increase food security, flavor, and nutritional content; more recently, they have been recognized as potential mediators of human health. Metagenomics is a powerful approach to characterize microbes in fermented foods, providing high taxonomic resolution and functional insights. Here, we introduce the Microbial Food DataBase, a metagenomics-based approach designed for the identification of fermentation-associated microbes. Using this primary database of metagenome-assembled genomes and relevant deposited genomes of prokaryotes, eukaryotes, and common food-relevant substrates, we investigated 89 fermented food samples. We present a streamlined high-confidence characterization of microbial diversity in fermented food, identifying previously undiscovered genomes and facilitating strain-level tracking across food environments. The easy and robust functionality of the workflow has significant implications for advancing food safety, promoting desired microbial communities, and increasing sustainability in food production.IMPORTANCEFermented foods have microbial communities that influence food safety, flavor, and human health. Microbial Food DataBase (MiFoDB), an alignment-based sequencing workflow and database, addresses the limitations of existing tools by enabling strain-level resolution, identifying novel genomes, and providing functional insights into microbial communities. Applying MiFoDB to fermented food samples, we demonstrate its ability to uncover novel species, track microbial strains across substrates, and integrate functional annotations. Additionally, the outlined workflow is highly customizable and can be used to generate alignment-based databases for other microbial ecosystems. This work highlights the importance of fermentation-specific workflows for studying microbial food ecosystems, advancing food safety, sustainability, and innovation in fermented food research.

mSystemsVol. 10(9)
Novo Nordisk Foundation (DK), Chan Zuckerberg Initiative (United States) (US), Stanford University (US)
U.S. Department of Health and Human Services, Bill and Melinda Gates Foundation, Novo Nordisk
Openalex Percentile: Top 75%
Probiotics and Fermented Foods
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