Biology subjects

Le Chatelier, E.

Publications and source records attributed to Le Chatelier, E..

9 recordsLinked to original sources

bioRxiv2026

Hydrogen metabolism shapes gut microbiome into health-associated configurations

The human gut microbiome exhibits reproducible configurations, yet the ecological forces connecting them to health remain unclear. Here, using enterosignature-based stratification of 5,170 individuals from the Le French Gut cohort, we identified hydrogen disposal as a key determinant of population-scale microbiome configurations, independently replicated in a meta-cohort (n = 5,107). Microbial configurations followed a continuum of hydrogen recycling capacity and redox-associated functions, aligned with dietary patterns and health indicators. Methanogenesis-dominant partitions were associated with more favorable health profiles, whereas acetogenesis-enriched partitions exhibited features of low-grade inflammation, and increased digestive symptoms, perceived stress and antidepressant use. Experimental characterization of mucin profiles highlighted differences across partitions and alterations in Bacteroides-enriched configurations. Together, our findings support an ecological host-microbiome framework linking hydrogen metabolism, redox ecology, and host health, offering microbiome-informed targets for precision intervention. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/722951v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@e7b8d1org.highwire.dtl.DTLVardef@116ab09org.highwire.dtl.DTLVardef@136f1f8org.highwire.dtl.DTLVardef@480097_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

NeighborFinder: an R package inferring local microbial network around a species of interest

1MotivationUnderstanding interactions from microbiome data is a central aspect in microbial ecology, as it provides insights into ecosystem stability, disease mechanisms, and can be used to design synthetic communities. Current network inference tools reconstruct global networks from co-abundance data, which means they capture the overall correlation structure for the entire set of taxa considered. These approaches are computationally intensive and suboptimal when the focus is on the local neighborhood of specific taxa of interest. ResultsWe introduce NeighborFinder, a local network inference method that enables the targeted discovery of direct neighbors around a species of interest. Using cross-validated multiple linear regression with[l] 1 penalty and microbiome-specific filters, our approach infers interpretable species-centered interactions, with F1 score [≥] 0.95 on simulated cohorts ranging from 250 to 1000 samples. This method is well-suited for large metagenomic datasets and is particularly valuable for exploratory studies where the targeted hypotheses outweigh the need for global community structure. The approach complements existing methods by being a biologically intuitive and computationally efficient. Availability and ImplementationThe R package is freely available on GitHub: https://github.com/metagenopolis/NeighborFinder. The data and source code used to calculate performances and produce the use case example in this paper can be found respectively at: https://doi.org/10.57745/UPITJ0 and https://doi.org/10.57745/HJLWW4. Supplementary informationSupplementary data are available

systems biology↗

bioRxiv2025

CroCoDeEL: accurate control-free detection of cross-sample contamination in metagenomic data

Metagenomic sequencing provides profound insights into microbial communities, but it is often compromised by technical biases, including cross-sample contamination. This phenomenon arises when microbial content is inadvertently exchanged among concurrently processed samples, distorting microbial profiles and compromising the reliability of metagenomic data and downstream analyses. Existing detection methods often rely on negative controls, which are inconvenient and do not detect contamination within real samples. Meanwhile, strain-level bioinformatics approaches fail to distinguish contamination from natural strain sharing and lack sensitivity. To fill this gap, we introduce CroCoDeEL, a decision-support tool for detecting and quantifying cross-sample contamination. Leveraging linear modeling and a pre-trained supervised model, CroCoDeEL identifies specific contamination patterns in species abundance profiles. It requires no negative controls or prior knowledge of sample processing positions, offering improved accuracy and versatility. Benchmarks across three public datasets demonstrate that CroCoDeEL accurately detects contaminated samples and identifies their contamination sources, even at low rates (<0.1%), provided sufficient sequencing depth. Notably, we discovered critical contamination cases in highly cited studies, calling some of their results into question. Our findings suggest that cross-sample contamination is a widespread yet underexplored issue in metagenomics and emphasize the necessity of systematically integrating contamination detection into sequencing quality control.

bioinformatics↗

bioRxiv2023

Aggregating network inferences: towards useful networks

Modeling microbial interactions as sparse and reproducible networks is a major challenge in microbial ecology. Direct interactions between the microbial species of a biome can help to understand the mechanisms through which microbial communities influence the system. Most state-of-the art methods reconstruct networks from abundance data using Gaussian Graphical Models, for which several statistically grounded and computationnally efficient inference approaches are available. However, the multiplicity of existing methods, when applied to the same dataset, generates very different networks. In this article, we present OneNet, a consensus network inference method that combines seven methods based on stability selection. This resampling procedure is used to tune a regularization parameter by computing how often edges are selected in the networks. We modified the stability selection framework to use edge selection frequencies directly and combine them in the inferred network to ensure that only reproducible edges are included in the consensus. We demonstrated on synthetic data that our method generally led to slightly sparser networks while achieving much higher precision than any single method. We further applied the method to gut microbiome data from liver-cirrothic patients and demonstrated that the resulting network exhibited a microbial guild that was meaningful in terms of human health.

bioinformatics↗

bioRxiv2022

In vitro modelling of oral microbial invasion in the human colon

Recent advances in the human microbiome characterization have revealed significant oral microbial detection in stools of dysbiotic patients. However, little is known about the potential interactions of these invasive oral microorganisms with commensal intestinal microbiota and host. In this proof of concept study, we propose a new model of oral to gut invasion by the combined use of an in vitro model simulating both the physicochemical and microbial (lumen and mucus-associated microbes) parameters of the human colon (M-ARCOL), a salivary enrichment protocol and whole metagenome shotgun sequencing. Oral invasion of the intestinal microbiota was simulated by injection of enriched saliva in the in vitro colon model inoculated with faecal sample from the same healthy adult donor. The mucosal compartment of M-ARCOL was able to retain the highest species richness levels over time, whilst it decreased in the luminal compartment. This study also showed that oral microorganisms preferably colonized the mucosal microenvironment, suggesting potential oral-to-intestinal mucosal competitions. This new model of oral-to-gut invasion can provide useful mechanistic insights into the role of oral microbiome in various disease processes.

microbiology↗

bioRxiv2021

Analysis of viromes and microbiomes from pig fecal samples reveals that phages and prophages are not vectors of antibiotic resistance genes

Understanding the transmission of antibiotic resistance genes (ARGs) is critical for human health. For this, it is necessary to identify which type of mobile genetic elements is able to spread them from animal reservoirs into human pathogens. Previous research suggests that in pig feces, ARGs may be encoded by bacteriophages. However, convincing proof for phage-encoded ARGs in pig viromes is still lacking, because of bacterial DNA contaminating issues. We collected 14 pig fecal samples and performed deep sequencing on both highly purified viral fractions and total microbiota, in order to investigate phage and prophage-encoded ARGs. We show that ARGs are absent from the genomes of active, virion-forming phages (below 0.02% of viral contigs from viromes), but present in three prophages, representing 0.02% of the viral contigs identified in the microbial dataset. However, the corresponding phages were not detected in the viromes, and their genetic maps suggest they might be defective. Furthermore, our dataset allows for the first time a comprehensive view of the interplay between prophages and viral particles.

microbiology↗

bioRxiv2019

Microbiome Determinants and Physiological Effects of the Benzoate-Hippurate Microbial-Host Co-Metabolic Pathway

ObjectiveGut microbial products are involved in type 2 diabetes, obesity and insulin resistance. In particular, hippurate, a hepatic phase 2 conjugation product of microbial benzoate metabolism, has been associated with a healthy phenotype. This study aims to identify metagenomic determinants and test protective effects of hippurate. DesignWe profiled the urine metabolome by 1H Nuclear Magnetic Resonance (NMR) spectroscopy to derive associations with metagenomic sequences in 271 middle-aged Danish individuals to identify dietary patterns in which urine hippurate levels were associated with health benefits. We follow up with benzoate and hippurate infusion in mice to demonstrate causality on clinical phenotypes. ResultsIn-depth analysis identifies that the urine hippurate concentration is associated with microbial gene richness, microbial functional redundancy as well as functional modules for microbial benzoate biosynthetic pathways across several enterotypes. Through dietary stratification, we identify a subset of study participants consuming a diet rich in saturated fat in which urine hippurate, independently of gene richness, accounts for links with metabolic health that we previously associated with gene richness. We then demonstrate causality in vivo through chronic subcutaneous infusions of hippurate or benzoate (20 nmol/day) resulting in improved glycemic control in mice fed a high-fat diet. Hippurate improved insulin secretion through increased {beta}-cell mass and reduced liver inflammation and fibrosis, whereas benzoate treatment resulted in liver inflammation. ConclusionOur translational study shows that the benzoate-hippurate pathway brings a range of metabolic improvements in the context of high-fat diets, highlighting the potential of hippurate as a mediator of metabolic health.

systems biology↗

bioRxiv2018

Laparoscopic Roux-en-Y gastric bypass profoundly changes gut microbiota compared to laparoscopic sleeve gastrectomy: a metagenomic comparative analysis

BackgroundBariatric surgery is an effective therapeutic procedure for morbidly obese patients as it induces sustained weight loss. The two most common interventions are Laparoscopic Sleeve Gastrectomy (LSG) and Laparoscopic Roux-en-Y Gastric Bypass (LRYGB).\n\nObjectiveCharacterizing the gut microbiota changes induced by LSG and LRYGB.\n\nDesign89 and 108 patients who underwent LSG and LRYGB respectively, were recruited from three countries: USA, France and Switzerland. Stools were collected before and 6 months after surgery. Microbial DNA was analysed with shotgun metagenomic sequencing (SOLiD 5500xl Wildfire). MSPminer, a novel innovative tool to characterize new in silico biological entities, was used to identify 715 Metagenomic Species Pan-genome (MSPs). 148 functional modules were analysed using GOmixer and KEGG database.\n\nResultsBoth interventions resulted in a similar increase of Shannons diversity index and gene richness of gut microbiota, in parallel with weight loss, but the changes of microbial composition were different. LRYGB led to higher relative abundance of aero-tolerant bacteria, such as Escherichia coli and buccal species, such as Streptococcus and Veillonella spp. In contrast, anaerobes such as Clostridium were more abundant after LSG, suggesting better conservation of anaerobic conditions in the gut. Function-level changes included higher potential for bacterial use of supplements such as vitamin B12, B1 and iron upon LRYGB. Moreover, after LRYGB, potential for nitrate and Trimethylamine oxidized (TMAO) respiration was detected.\n\nConclusionMicrobiota changes after bariatric surgery depend on the nature of the intervention. LRYGB induces greater taxonomic and functional changes in gut microbiota than LSG and may lead to a more dysbiotic microbiome. Possible long-term health consequences of these alterations remain to be established.\n\nSignificance of this studyO_ST_ABSWhat is already known on this subject?C_ST_ABSPrevious studies have reported changes of microbial composition after bariatric surgery with shotgun metagenomics, but lacked statistical power to document the changes. Important shifts in gut microbiome have been observed after LRYGB and LSG with an increase of aerotolerants from buccal microbiota. However, it is not clear how different the changes are between LRYGB and LSG although both procedures induce quite similar results with respect to weight loss, comorbidities remission and global glycaemic improvement outcomes.\n\nWhat are the new findings?LSG and LRYGB have specific but different impacts on gut microbial composition 6 months after bariatric surgery. The changes could be related to specific physiological effects. LRYGB promotes an important invasion of oral colonizers with Veillonella and Streptococcus genera. In contrast, these changes were less important after LSG. Moreover, microbial transportation potential of iron and vitamin B12 were also higher after LRYGB than LSG. We concluded that the type of surgery leads to different gut microbiome and functional profiles.\n\nHow might it impact on clinical practice in the foreseeable future?Microbiome composition and functional profiles are not altered to the same extent by LRYGB and LSG 6 months after surgery. This difference should be considered when advising the patient on the type of bariatric surgery or post op diet.

microbiology↗

bioRxiv2017

Protection of the human gut microbiome from antibiotics

BackgroundAntibiotics are life-saving drugs but severely affect the gut microbiome with short term consequences including diarrhoea, Clostridium difficile infections and selection of antibiotic-resistant bacteria. Long-term links to allergy and obesity are also suggested. We devised a product, DAV132, and previously showed its ability to deliver a powerful adsorbent, activated charcoal, in the late ileum of human volunteers.\n\nMethodsWe performed a randomized controlled trial (ClinicalTrials.gov NCT02176005) in 28 human volunteers treated with a 5-day clinical regimen of the fluoroquinolone antibiotic moxifloxacin in two parallel groups, with or without DAV132 co-administration. Two control goups of 8 volunteers each receiving DAV132 alone, or a non-active substitute, were added.\n\nResultsThe co-administration of DAV132 decreased free moxifloxacin fecal concentrations by 99%, while plasmatic levels were unaffected. Shotgun quantitative metagenomics showed that the richness and composition of the intestinal microbiota were largely preserved in subjects co-treated with DAV132 in addition to moxifloxacin. No adverse effect was observed. In addition, DAV132 efficiently adsorbed a wide range of clinically relevant antibiotics ex-vivo.\n\nConclusionsDAV132 was highly effective to protect the gut microbiome of moxifloxacin - treated healthy volunteers and may constitute a clinical breakthrough by preventing adverse health consequences of a wide range of antibiotic treatments.

clinical trials↗