Thomas Clavel

A microbiota-derived protease links phage susceptibility to host epithelial responses

This study identifies a bacterial protease that influences phage susceptibility and links it to host epithelial responses in ulcerative colitis.

Swimming motility in the gut microbiota is diverse and increased in inflammation.

This study directly analyzes gut bacterial motility in health and inflammation, finding increased motility in inflamed conditions and diverse swimming behaviors.

Mixed acid fermentation products from Lachnospira eligens counteract myotube atrophy

This study shows that mixed acid fermentation products from Lachnospira eligens counteract myotube atrophy and links reduced gut anaerobiosis in AML patients to decreased muscle strength.

Modulation of intestinal bile acids influences colonic mucosal responses

This study examines how bile acid modulation affects colonic epithelial responses in mice and humans, finding altered cell populations and gene expression associated with DCA exposure.

A mixture of plant polyphenols unexpectedly aggravates liver metastasis of colorectal cancer in mice

This study shows that a plant polyphenol mixture accelerates liver metastasis in mice, suggesting potential immunomodulatory effects that require validation in immunocompetent models.

Macrophage renewal in the small intestine governs early-life control of streptococci

This study shows that small intestine macrophage dynamics control GBS colonization and invasion in infant mice, with region-specific responses to the pathogen.

Neonatal liver niches program T cell tolerance

The paper identifies a neonatal liver program that expands regulatory T cells while limiting conventional T cell activation, influencing susceptibility to viral infections and protection against liver disease.

Robust genome-based delineation of bacterial genera

This paper introduces a robust method for bacterial genus classification using POCPu, showing it outperforms traditional POCP calculations.

The adhesion molecules β7 integrin and L-selectin contribute to cholestatic liver disease in male mice

This study shows that β7 integrin and L-selectin contribute to DDC-induced cholangiopathy in male mice by promoting immune cell infiltration, gut barrier dysfunction, and microbiota shifts.

Broad diversity of human gut bacteria accessible via a traceable strain deposition system

The paper establishes a publicly available collection of 340 human gut bacterial strains, including 29 newly described species, and identifies plasmids and megaplasmids within these isolates.

Intercellular adhesion molecule-1 protects against adipose tissue inflammation and insulin resistance but promotes liver inflammation and hepatic fibrosis in mice

This study shows ICAM-1 protects against adipose tissue inflammation and insulin resistance but worsens liver inflammation and fibrosis in mice with diet-induced obesity.

Lineage-specific microbial protein prediction enables large-scale exploration of protein ecology within the human gut

The paper develops a lineage-specific gene prediction method for metagenomic data, improving protein prediction accuracy and enabling functional analysis of the human gut microbiome.

Benchmarking of shotgun sequencing depth highlights limitations of strain-level analysis and shallow metagenomics

This study benchmarks shotgun sequencing depth in metagenomics, showing that strain-level analysis and functional insights require deep sequencing, while shallow sequencing has significant limitations.

Function-Based Selection of Synthetic Communities Enables Mechanistic Microbiome Studies

The paper develops a method to design synthetic microbial communities based on metagenomic data, demonstrating its ability to model disease-associated microbiomes.

A physiologically based model of bile acid metabolism in mice

This study develops a physiologically-based model of bile acid metabolism in mice to understand its dynamics and implications for disease.

Swarm Learning as a privacy-preserving machine learning approach for disease classification

This paper introduces Swarm Learning, a decentralized machine learning approach for disease classification using transcriptomic data, demonstrating its effectiveness in developing classifiers for COVID-19, tuberculosis, and leukemias while preserving privacy.