New tool suite - Food Microbiome Metabolic Modules (F3M)

Published: Nov 6, 2025 by FME Lab

The FME team has published a new preprint in Open Research Europe entitled
“Food Microbiome Metabolic Modules (F3M): a tool suite for functional profiling of food microbiomes.”
Read the article

Understanding microbial interactions within food ecosystems is essential for improving the quality, safety, and health properties of fermented foods. However, analyzing these interactions at the functional and metabolic levels remains technically challenging.To address this gap, the FME team developed F3M, an open-source suite designed specifically for the metatranscriptomic analysis of food microbiomes.

Overview of different classes among the F3M main functional modules allowing the linkage of the major functional processes in microbial interactions.
Overview of different classes among the F3M main functional modules allowing the linkage of the major functional processes in microbial interactions:: the modules for metabolism (illustrated by the pathways within the two bacterial cells), redox processes (central oxido-reduction mechanisms between the two cells), and uptake processes (various transporters in the cell membrane of the two cells).

The F3M suite includes:

  • A curated database of nearly 2,000 functional genes representing key fermentative reactions
  • The F3M Builder, a workflow for constructing annotated gene catalogs and mapping sequencing data
  • The f3mr R package, which enables aggregation and analysis of gene expression data across taxonomic and functional levels

Together, these tools provide a coherent framework for exploring metabolic interactions within food microbiomes and for identifying functional signatures associated with fermentation processes.

The article1, authored by Julien Tap, Nacer Mohellibi, Colin Tinsley, Valentin Loux, and Stéphane Chaillou, describes the conceptual framework, design, and open-access resources of F3M.

Access the resources:

Learn and practice with the F3M R tutorial

A complete tutorial and training guide is available online for users who wish to become familiar with the F3M workflow:
https://fme_team.pages-forge.inrae.fr/f3mr/getting-started.html

This hands-on guide introduces the main steps of analysis with the f3mr R package, including:

  1. Build a reference database from functional and taxonomic annotations.
  2. Import sample count data .
  3. Aggregate counts by taxonomic and functional levels.
  4. Build a count matrix for downstream statistical analyses.

Each section of the tutorial includes example code and data to help users reproduce a full workflow, from raw annotations to interpretable metatranscriptomic profiles.

Share

Latest Posts

New tool suite - Food Microbiome Metabolic Modules (F3M)
New tool suite - Food Microbiome Metabolic Modules (F3M)

The FME team has published a new preprint in Open Research Europe entitled
“Food Microbiome Metabolic Modules (F3M): a tool suite for functional profiling of food microbiomes.”
Read the article

A seed meeting between INRAE Micalis Institute and Imperial College London
A seed meeting between INRAE Micalis Institute and Imperial College London

Last week on October 3rd, scientists from Imperial College London (ICL) and from INRAE Micalis Institute were hosted by the French embassy in London for a seed meeting around synthetic biology and synthetic microbial ecology as scientific strategies for biotechnology and food production. A special thanks to the organizer: Ludovic Drouin (French Embassy), Young-Kyoung Park (Micalis) and Rodriguo Ledesma-Amaro (ICL). Our several groups with complementary research discussed about perspectives of future collaborations on the field together with Ferment du Futur or Bezos Centre.

School of Artificial Intelligence Applied to Microbiomes
School of Artificial Intelligence Applied to Microbiomes

Earlier this month, Julien had the pleasure of participating as a lecturer at the School of Artificial Intelligence Applied to Microbiomes, hosted at AgroParisTech and organized by Aristeidis Litos, Daniel Garza, and Ariane Bize. The event brought together an exceptional group of researchers and students exploring how AI, data science, and mathematical modeling are reshaping our understanding of microbial ecosystems.