Biology subjects

Plaza Onate, F.

Publications and source records attributed to Plaza Onate, F..

7 recordsLinked to original sources

bioRxiv2026

Competitive advantage of hypervirulent Group B Streptococcus for neonatal colonization revealed by metagenomic analysis of gut microbiota

Group B Streptococcus (GBS) is the leading cause of neonatal invasive infections. Late-onset infections (7-89 days after birth) are caused by GBS clonal complex 17 (CC17) in 50-80% of cases, likely resulting from bacterial translocation across the intestinal barrier. However, the factors influencing GBS colonization in neonates are incompletely understood. We used shotgun metagenomics on fecal samples from 100 neonates aged 21 days and identified taxonomic signatures of GBS colonization, including decreased Enterobacter hormaechei abundance in neonates colonized by non-CC17 GBS. Using in vitro assays with representative isolates, we demonstrate that GBS CC17 competes more effectively than GBS non-CC17 against E. hormaechei, with enhanced adherence to enterocytes mediated by the CC17-specific HvgA adhesin. Our findings highlight lineage-dependent interspecies interactions of GBS that likely influence its ability to colonize the neonatal gut. These interactions must be considered when developing microbiota-based strategies to mitigate neonatal colonization and infection by GBS.

microbiology↗

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↗

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

StrainFLAIR: Strain-level profiling of metagenomic samples using variation graphs

Current studies are shifting from the use of single linear references to representation of multiple genomes organised in pangenome graphs or variation graphs. Meanwhile, in metagenomic samples, resolving strain-level abundances is a major step in microbiome studies, as associations between strain variants and phenotype are of great interest for diagnostic and therapeutic purposes. We developed StrainFLAIR with the aim of showing the feasibility of using variation graphs for indexing highly similar genomic sequences up to the strain level, and for characterizing a set of unknown sequenced genomes by querying this graph. On simulated data composed of mixtures of strains from the same bacterial species Escherichia coli, results show that StrainFLAIR was able to distinguish and estimate the abundances of close strains, as well as to highlight the presence of a new strain close to a referenced one and to estimate its abundance. On a real dataset composed of a mix of several bacterial species and several strains for the same species, results show that in a more complex configuration StrainFLAIR correctly estimates the abundance of each strain. Hence, results demonstrated how graph representation of multiple close genomes can be used as a reference to characterize a sample at the strain level. Availabilityhttp://github.com/kevsilva/StrainFLAIR

bioinformatics↗

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

Abundance-based reconstitution of microbial pan-genomes from whole-metagenome shotgun sequencing data

MotivationAnalysis toolkits for shotgun metagenomic data achieve strain-level characterization of complex microbial communities by capturing intra-species gene content variation. Yet, these tools are hampered by the extent of reference genomes that are far from covering all microbial variability, as many species are still not sequenced or have only few strains available. Binning co-abundant genes obtained from de novo assembly is a powerful reference-free technique to discover and reconstitute gene repertoire of microbial species. While current methods accurately identify species core parts, they miss many accessory genes or split them into small gene groups that remain unassociated to core clusters.\n\nResultsWe introduce MSPminer, a computationally efficient software tool that reconstitutes Metagenomic Species Pan-genomes (MSPs) by binning co-abundant genes across metagenomic samples. MSPminer relies on a new robust measure of proportionality coupled with an empirical classifier to group and distinguish not only species core genes but accessory genes also. Applied to a large scale metagenomic dataset, MSPminer successfully delineates in a few hours the gene repertoires of 1 661 microbial species with similar specificity and higher sensitivity than existing tools. The taxonomic annotation of MSPs reveals microorganisms hitherto unknown and brings coherence in the nomenclature of the species of the human gut microbiota. The provided MSPs can be readily used for taxonomic profiling and biomarkers discovery in human gut metagenomic samples. In addition, MSPminer can be applied on gene count tables from other ecosystems to perform similar analyses.\n\nAvailabilityThe binary is freely available for non-commercial users at enterome.fr/site/downloads/ Contact: florian.plaza-onate@inra.fr\n\nSupplementary informationAvailable in the file named Supplementary Information.pdf

bioinformatics↗