Biology subjects

Loux, V.

Publications and source records attributed to Loux, V..

11 recordsLinked to original sources

bioRxiv2025

Scratching on French PDO cheese surfaces sheds light on an unexplored microbial genomic and metabolic diversity

Cheeses are fermented dairy products consumed worldwide. Their global diversity results from various local variables, including technological practices, as well as the metabolic activity of diverse microorganisms. In Europe, this typicity is exemplified by Protected Designation of Origin (PDO) cheeses, for which genetic diversity remains largely unexplored. Combining culturomics (n = 373 bacterial genomes) and metagenomic (n = 146 metagenomes), we performed a national-scale survey of the microbial diversity encompassing 44 French PDO cheeses. Taxonomic (bacteria, fungi and viruses) and functional profiling reveal a high diversity in the cheese rind, mainly driven by the cheese technology. We also reconstructed 1,119 bacterial metagenome-assembled genomes (MAGs) encompassing seven phyla, including Actinomycetota, Bacillota, Pseudomonadota and Bacteroidota. Using GTDB as a reference, we identified 221 MAGs encompassing 46 genera, as well as 44 bacterial isolate genomes encompassing eight genera, which represent potentially 81 new species (based on <95% ANI). These species were particularly numerous among the genera Halomonas, Psychrobacter and Brachybacterium. Similar results were observed when compared with the cFMD database. We combined our genomic and metagenomic datasets into a catalog of 26.2 million protein clusters, with 50% of these clusters remaining unassigned to a known function and taxonomy. We illustrated the potential of this resource by searching for methionine gamma-lyase (MGL), an enzyme playing a significant role in cheese flavor. This protein was predominantly found in Pseudoalteromonas, a potentially new MGL-producing genus, Serratia, Pseudomonas, Proteus and Hafnia, and its prevalence varied with cheese technology. Our study provides a substantial genomic resource for food microbiologists and cheesemakers to further explore the biotechnological potential of PDO cheese biodiversity.

microbiology↗

bioRxiv2025

Atypical Replication Error Pattern and Limited Repair Efficiency Contribute to Elevated Mutation Rate in Phage lambda

Understanding the rate and nature of spontaneous mutations is crucial for understanding and modulating the pace and trajectory of evolution. Yet, both remain poorly characterized in double-stranded DNA (dsDNA) phages, despite their relevance for phage-based therapies. Here, we address this gap for the dsDNA phage lambda, using four complementary approaches: mutation accumulation assay combined with whole-genome sequencing, mutation visualization assay, duplex sequencing and fluctuation assay. We find that the mutation rate of wild-type phage lambda is 4.9 {+/-} 1.8 x10-9 per base per replication, approximately 15 times lower than previously estimated and about 20 times higher than that of its host, Escherichia coli (E. coli). Inactivation of Mismatch Repair (MMR), a major conserved cellular system for mutation avoidance, increases the lambda mutation rate by only 2-to 10-fold, in contrast to the approximately 150-fold increase in E. coli, however lambda does not exhibit the characteristic mutational bias associated with MMR deficiency. Interestingly replication of the lambda genome generates an error spectrum distinct from that of E. coli, characterized by a marked increase in transversions, poorly repaired by MMR. Together, these results reveal that lambda exhibits a replication error profile that is less amenable to repair, likely contributing to its elevated mutation rate.

microbiology↗

bioRxiv2025

Food Microbiome Metabolic Modules (F3M), a tool suite for functional profiling of food microbiomes

The study of microbial metabolic interactions within food microbiomes represents a key scientific approach for improving the quality and health benefits of food. In such studies, methods based on gene expression levels (metatranscriptomic) analysis are promising. However specific tools are required to overcome the challenges posed by food microbiomes, in particular the high variability of microbiomes between samples and the difficulty of automatically inferring the annotation of metabolic functions across taxa. To adress this gap, we present the Food Microbiome Metabolic Modules (F3M) tool suite, which comprises (1) a curated database containing about 1,985 functional genes representing key fermentative metabolic reactions in food microbiomes, (2) a F3M Builder for generating F3M-annotated gene catalogs and mapping of metatranscriptomic reads, and then (3) an F3M R package to parse and aggregate gene expression data by taxonomic and functional categories for downstream analysis. The F3M taxonomy is organized according to the Genome Taxonomy Database (GTDB) nomenclature, whereas the F3M functional repertoire is structured hierarchically into 183 metabolic modules, which enable multi-scale analysis of inter-organism metabolic interactions and meaningful fermentative outputs (e.g., primary alcohols, acetate). Notably, a dedicated redox module captures oxido-reduction mechanisms and NADH-dependent pathways central to fermentation, while an uptake module complements the metabolic pathways to trace potential metabolite exchanges across taxa. Together, the F3M suite provides a robust framework for uncovering functional dynamics within food microbiomes. The F3M tool suite is available as open-source.

microbiology↗

bioRxiv2025

Cell-free genome-wide transcriptomics through machine learning optimization

1Despite advances in transcriptomics, understanding of genome regulation remains limited by the complex interactions within living cells. To address this, we performed cell-free transcriptomics by developing a platform using an active learning workflow to explore over 1,000,000 buffer conditions. This enabled us to identify a buffer that increased mRNA yield by 20-fold, enabling cell-free transcriptomics. By employing increasingly complex conditions, our approach untangles the regulatory layers controlling genome expression.

synthetic biology↗

bioRxiv2025

MilkOligoCorpus: a semantically annotated resource for knowledge extraction on mammalian milk oligosaccharides

Milk oligosaccharides are bioactive components that regulate the composition of the neonatal microbiota and exert immunomodulatory functions. Their beneficial effects depend on their structure. Numerous studies have shown intra- and inter-species variation in the structural composition and concentration of these compounds in mammalian milk, yet the biological significance of such variation remains poorly understood. Automated natural language processing methods are promising tools for extracting and gathering structured data from unstructured texts to get insight into the biological significance of milk oligosaccharide variation across mammals. These methods require training and evaluation on manually annotated text corpora. While annotated corpora exist for chemical substances, none are specifically designed for training natural language processing models to extract information on milk oligosaccharides. To this end, we propose MilkOligoCorpus, a new gold standard for milk oligosaccharide composition in mammalian species. MilkOligoCorpus annotation scheme is a rich entity/relation model designed to describe the diversity pattern of milk oligosaccharides according to female factor variability and to help better understand the structure-related function of milk oligosaccharides. MilkOligoCorpus consists of 30 PubMed texts fully annotated with entities related to individuals, samples, oligosaccharides and oligosaccharide quantification linked by binary and n-ary relationships. To address data interoperability across disparate publications and databases, four terminological resources were also developed to assign unique identifiers to the entities, supported by external ontologies. This paper presents the creation of the MilkOligoCorpus and its associated schema, along with the development of annotation guidelines and terminological resources. We also present experimental results obtained by baseline information extraction models on the corpus.

bioinformatics↗

bioRxiv2023

Holistic integration of omics data reveals the drivers that shape the ecology of microbial meat spoilage scenarios

The use of omics data for monitoring the microbial flow of fresh meat products along a production line and the development of spoilage prediction tools from these data is a promising but challenging task. In this context, we produced a large multivariate dataset (over 600 samples) obtained on the production lines of two similar types of fresh meat products (poultry and raw pork sausages).We describe a full analysis of this dataset in order to decipher how the spoilage microbial ecology of these two similar products may be shaped differently depending on production parameter characteristics. Our strategy involved a holistic approach to integrate unsupervised and supervised statistical methods on multivariate data (OTU-based microbial diversity; metabolomic data of volatile organic compounds; sensory measurements; growth parameters), and a specific selection of potential uncontrolled (initial microbiota composition) or controlled (packaging type; lactate concentration) drivers. Our results demonstrate that the initial microbiota, which is shown to be very different between poultry and pork sausages, has a major impact on the spoilage scenarios and on the effect that a downstream parameter such as packaging type has on the overall evolution of the microbial community. Depending on the process, we also show that specific actions on the pork meat (such as deboning and defatting) elicit specific food spoilers such as Dellaglioa algida, which becomes dominant during storage. Finally, ecological network reconstruction allowed us to map six different metabolic pathways involved in the production of volatile organic compounds involved in spoilage. We were able connect them to the different bacterial actors and to the influence of packaging type in an overall view. For instance, our results demonstrate a new role of Vibrionaceae in isopropanol production, and of Latilactobacillus fuchuensis and Lactococcus piscium in methanethiol/disylphide production. We also highlight a possible commensal behavior between Leuconostoc carnosum and Latilactobacillus curvatus around 2,3-butanediol metabolism. We conclude that our holistic approach combined with large-scale multi-omic data was a powerful strategy to prioritize the role of production parameters, already known in the literature, that shape the evolution and/or the implementation of different meat spoilage scenarios.

microbiology↗

bioRxiv2023

Comparison of metabarcoding taxonomic markers to describe fungal communities in fermented foods

AO_SCPLOWBSTRACTC_SCPLOWNext generation sequencing offers several ways to study microbial communities. For agri-food sciences, identifying species in diverse food ecosystems is key for both food sustainability and food security. The aim of this study was to compare metabarcoding pipelines and markers to determine fungal diversity in food ecosystems, from Illumina short reads. We built mock communities combining the most representative fungal species in fermented meat, cheese, wine and bread. Four barcodes (ITS1, ITS2, D1/D2 and RPB2) were tested for each mock and on real fermented products. We created a database, including all mock species sequences for each barcode to compensate for the lack of curated data in available databases. Four bioinformatics tools (DADA2, QIIME, FROGS and a combination of DADA2 and FROGS) were compared. Our results clearly showed that the combined DADA2 and FROGS tool gave the most accurate results. Most mock community species were not identified by the RPB2 barcode due to unsuccessful barcode amplification. When comparing the three rDNA markers, ITS markers performed better than D1D2, as they are better represented in public databases and have better specificity to distinguish species. Between ITS1 and ITS2, differences in the best marker were observed according to the studied ecosystem. While ITS2 is best suited to characterize cheese, wine and fermented meat communities, ITS1 performs better for sourdough bread communities. Our results also emphasized the need for a dedicated database and enriched fungal-specific public databases with novel barcode sequences for 118 major species in food ecosystems.

microbiology↗

bioRxiv2022

Comparative genome analysis of Enterococcus cecorum reveals intercontinental spread of a lineage of clinical poultry isolates.

Enterococcus cecorum is an emerging pathogen responsible for osteomyelitis, spondylitis, and femoral head necrosis causing animal suffering, mortality, and requiring antimicrobial use in poultry. Paradoxically, E. cecorum is a common inhabitant of the intestinal microbiota of adult chickens. Despite evidence suggesting the existence of clones with pathogenic potential, the genetic and phenotypic relatedness of disease-associated isolates remains little investigated. Here, we sequenced and analyzed the genomes and characterized the phenotypes of more than 100 isolates, the majority of which were collected over the last ten years in 16 French broiler farms. Comparative genomics, genome-wide association study, and measured susceptibility to serum, biofilm forming capacity, and adhesion to chicken type II collagen were used to identify features associated with clinical isolates. We found that none of the tested phenotypes could discriminate origin of the isolates or phylogenetic group. Instead, we found that most clinical isolates are grouped phylogenetically and our analyses selected six genes that discriminate 94% of isolates associated with disease from those that are not. Analysis of the resistome and the mobilome revealed that multidrug-resistant clones of E. cecorum cluster in few clades and that integrative conjugative elements and genomic islands are the main carriers of antimicrobial resistance. This comprehensive genomic analysis shows that disease-associated clones of E. cecorum belong mainly to one phylogenetic clade. IMPORTANCEEnterococcus cecorum is an important pathogen in poultry worldwide. It causes a number of locomotor disorders and septicemia, particularly in fast-growing broilers. Animal suffering, antimicrobial use, and associated economic losses require a better understanding of disease-associated E. cecorum isolates. To address this need, we performed whole genome sequencing and analysis of a large collection of isolates responsible for outbreaks in France. By providing the first dataset on the genetic diversity and resistome of E. cecorum strains circulating in France, we pinpoint an epidemic lineage probably also circulating elsewhere and which should be targeted preferentially by preventive strategies in order to reduce the burden of E. cecorum-related diseases.

genomics↗

bioRxiv2022

Omnicrobe, an open-access database of microbial habitats and phenotypes using a comprehensive text mining and data fusion approach

The dramatic increase in the amount of microbe descriptions in databases, reports and papers presents a two-fold challenge for accessing the information: integration of heterogeneous data in a standard ontology-based representation and normalization of the textual descriptions by semantic analysis. Recent text mining methods offer powerful ways to extract textual information and generate ontology-based representation. This paper describes the design of the Omnicrobe application that gathers comprehensive information on habitats, phenotypes and usages of microbes from scientific sources of high interest to the microbiology community. The Omnicrobe database contains around 1 million descriptions of microbe properties that are created by analyzing and combining six information sources of various kinds, i.e. biological resource catalogues, sequence database and scientific literature. The microbe properties are indexed by the Ontobiotope ontology and their taxa are indexed by an extended version of the taxonomy maintained by the National Center for Biotechnology Information. The Omnicrobe application covers all domains of microbiology. It provides an easy-to-use support in the resolution of scientific questions related to the habitats, phenotypes and uses of microbes through simple and complex ontology-based queries. We illustrate the potential of Omnicrobe with a use case from the food innovation domain.

bioinformatics↗

bioRxiv2022

Gene co-expression network analysis of the human gut commensal bacterium Faecalibacterium prausnitzii based on WGCNA in R-Shiny

Faecalibacterium prausnitzii is abundant in the healthy human intestinal microbiota, and the absence or scarcity of this bacterium has been linked with inflammatory diseases and metabolic disorders. F. prausnitzii thus shows promise as a next-generation probiotic for use in restoring the balance of the gut microbial flora and, due to its strong anti-inflammatory properties, for the treatment of certain pathological conditions. However, very little information is available about gene function and regulation in this species. Here, we utilized a systems biology approach - weighted gene co-expression network analysis (WGCNA) - to analyze gene expression in three publicly available RNAseq datasets from F. prausnitzii strain A2-165, all obtained in different laboratory conditions. The co-expression network was then subdivided into 24 co-expression gene modules. A subsequent enrichment analysis revealed that these modules are associated with different kinds of biological processes, such as arginine, histidine, cobalamin, or fatty acid metabolism as well as bacteriophage function, molecular chaperones, stress response, or SOS response. Some genes appeared to be associated with mechanisms of protection against oxidative stress and could be essential for F. prausnitziis adaptation and survival under anaerobic laboratory conditions. Hub and bottleneck genes were identified by analyses of intramodular connectivity and betweenness, respectively; this highlighted the high connectivity of genes located on mobile genetic elements, which could promote the genetic evolution of F. prausnitzii within its ecological niche. This study provides the first exploration of the complex regulatory networks in F. prausnitzii, and all of the "omics" data are available online for exploration through a graphical interface at https://feaprau.omics.ovh/.

microbiology↗

bioRxiv2019

The enemy from within: a prophage of Roseburia intestinalis systematically turns lytic in the mouse gut, driving bacterial adaptation by CRISPR spacer acquisition

Despite an overall stability in time of the human gut microbiota at the phylum level, strong temporal variations in species abundance have been observed. We are far from a clear understanding of what promotes or disrupts the stability of microbiome communities. Environmental factors, like food or antibiotic use, modify the gut microbiota composition, but their overall impacts remain relatively low. Phages, the viruses that infect bacteria, might constitute important factors explaining temporal variations in species abundance. Gut bacteria harbour numerous prophages, or dormant viruses. A breakdown of prophage dormancy can evolve through the selection of ultravirulent phage mutants, potentially leading to important bacterial death. Whether such phenomenon occurs in the mammals microbiota has been largely unexplored.\n\nHere we studied temperate phage-bacteria coevolution in gnotoxenic mice colonised with Escherichia coli and Roseburia intestinalis, a dominant symbiont of the human gut microbiota. We show that R. intestinalis harbors two active prophages, Jekyll and Shimadzu, and observed the systematic evolution of ultravirulent Shimadzu phage mutants, leading to a collapse of R. intestinalis population. In a second step, phage infection drove the fast evolution of host phage-resistance mainly through phage-derived spacer acquisition in a Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) array. Alternatively, phage resistance was conferred by a prophage originating from an ultravirulent phage with a restored ability to lysogenize.\n\nOur results demonstrate that prophages are the potential source of ultravirulent phages that can successfully infect most of the susceptible bacteria. This suggests that prophages can play important roles in the short-term temporal variations observed in the composition of the gut microbiota.

microbiology↗