Biology subjects

Chaillou, S.

Publications and source records attributed to Chaillou, S..

10 recordsLinked to original sources

bioRxiv2026

Evidence of active phage replication during vegetable fermentation and implications for the dynamics of bacterial communities

Spontaneous vegetable fermentation is driven by the indigenous microbiota associated with the raw ingredients. The process often involves an initial heterofermentative phase followed by a predominantly homofermentative phase, both ensured by lactic acid bacteria (LAB). While microbial dynamics during fermentation are well characterized, phage communities remain poorly understood, despite evidence linking phage activity to LAB succession. We monitored viral and bacterial succession during sauerkraut and carrot fermentations using a metagenomics approach to characterize community dynamics. To further assess the impact of phage PLE001 on bacterial community dynamics, we developed a simplified carrot fermentation model comprising representative strains of Rahnella aquatilis, Leuconostoc mesenteroides and Lactiplantibacillus plantarum. Two consortia were assembled: one containing the PLE001-susceptible strain L. mesenteroides CIM3004, and the other containing also its phage-resistant derivative, CIM3004 BIM. We observed major shifts in the viral community during the first week of fermentation, coinciding with changes in bacterial structure during hetero- and homofermentative phases transition. In the simplified model, phage PLE001 reduced the population of the host during the heterofermentative phase but did not affect overall fermentation dynamics nor metabolite production. These results suggest that bacteriophages contribute to bacterial succession during fermentation, while communities remain resilient to phage infection, preserving fermentation stability.

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↗

bioRxiv2023

Integration of metataxonomic datasets into microbial association networks highlights shared bacterial community dynamics in fermented vegetables

The management of food fermentation is still largely based on empirical knowledge, as the dynamics of microbial communities and the underlying metabolic networks that produce safe and nutritious products remain beyond our understanding. Although these closed ecosystems contain relatively few taxa, they have not yet been thoroughly characterized with respect to how their microbial communities interact and dynamically evolve. However, with the increased availability of metataxonomic datasets on different fermented vegetables, it is now possible to gain a comprehensive understanding of the microbial relationships that structure plant fermentation. In this study, we present a bioinformatics approach that integrates public metataxonomic 16S datasets targeting fermented vegetables. Specifically, we developed a method for exploring, comparing, and combining public 16S datasets in order to perform meta-analyses of microbiota. The workflow includes steps for searching and selecting public time-series datasets and constructing association networks of amplicon sequence variants (ASVs) based on co-abundance metrics. Networks for individual datasets are then integrated into a core network of significant associations. Microbial communities are identified based on the comparison and clustering of ASV networks using the "stochastic block model" method. When we applied this method to 10 public datasets (including a total of 931 samples), we found that it was able to shed light on the dynamics of vegetable fermentation by characterizing the processes of community succession among different bacterial assemblages. IMPORTANCEWithin the growing body of research on the bacterial communities involved in the fermentation of vegetables, there is particular interest in discovering the species or consortia that drive different fermentation steps. This integrative analysis demonstrates that the reuse and integration of public microbiome datasets can provide new insights into a little-known biotope. Our most important finding is the recurrent but transient appearance, at the beginning of vegetable fermentation, of ASVs belonging to Enterobacterales and their associations with ASVs belonging to Lactobacillales. These findings could be applied in the design of new fermented products.

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↗

bioRxiv2021

Directed evolution of colE1 plasmid replication compatibility: a fast tractable tunable model for investigating biological orthogonality.

Plasmids of the ColE1 family are among the most frequently used plasmids in molecular biology. They were adopted early in the field for many biotechnology applications, and as model systems to study plasmid biology. The mechanism of replication of ColE1 plasmids is well understood, involving the interaction between a plasmid-encoded sense-antisense gene pair (RNAI and RNAII). Because of its mechanism of replication, bacterial cells cannot maintain two different plasmids with the same origin, with one being rapidly lost from the population - a process known as plasmid incompatibility. While mutations in the regulatory genes RNAI and RNAII have been reported to make colE1 plasmids more compatible, there has been no attempt to engineer compatible colE1 origins, which can be used for multi-plasmid applications and that can bypass design constrains created by the current limited plasmid origin repertoire available. Here, we show that by targeting sequence diversity to the loop regions of RNAI (and RNAII), it is possible to select new viable colE1 origins that are compatible with the wild-type one. We demonstrate origin compatibility is not simply determined by sequence divergence in the loops, and that pairwise compatibility is not an accurate guide for higher order interactions. We identify potential principles to engineer plasmid copy number independently from other regulatory strategies and we propose plasmid compatibility as a tractable model to study biological orthogonality. New characterised plasmid origins increase flexibility and accessible complexity of design for challenging synthetic biology applications where biological circuits can be dispersed between multiple independent genetic elements.

synthetic biology↗

bioRxiv2020

Evolution of fungal community associated with ready-to-eat pineapple during storage under different temperature conditions

The international market of fresh-cut products has witnessed dramatic growth in recent years, stimulated by consumers demand for healthy, nutritious and convenient foods. One of the main challenging issues for the quality and safety of these products is the potential microbial spoilage that can significantly reduce their shelf-life. The complete identification of fresh-cut product microbiota together with the evaluation of environmental factors impact on microbial composition is of primary importance. We therefore assessed the fungal communities associated with the spoilage of ready-to-eat (RTE) pineapple using a metagenetic amplicon sequencing approach, based on the ITS2 region. Our results revealed a significant variability on fungal species composition between the different batches of RTE pineapple. The initial microbiota composition was the main influencing factor and determined the progress of spoilage. Temperature and storage time were the secondary factors influencing spoilage and their impact was depending on the initial prevalent fungal species, which showed different responses to the various modifications. Our results strongly suggest that further large-scale sampling of RTE pineapple production should be conducted in order to assess the full biodiversity range of fungal community involved in the spoilage process and for unravelling the impact of important environmental factors shaping the initial microbiota.

microbiology↗

bioRxiv2020

Positive effect of combining high pressure and biopreservation treatments on lowering the bacterial growth during storage of diced cooked ham with reduced nitrite salt

We investigated the combined effects of biopreservation and high pressure treatment on bacterial communities of diced cooked ham prepared with diminished nitrite salt. First, bacterial communities of four commercial brands of dice cooked ham from local supermarkets, were characterised and stored frozen. Second, sterile diced cooked ham, prepared with reduced level of nitrite was inoculated with two different microbiota collected from the aforementioned commercial samples together with a nisin producing Lactococcus lactis protective strain able to recover from a 500 MPa high pressure treatment. Dices were then treated at 500 MPa for 5 minutes and bacterial dynamics was monitored during storage at 8{degrees}C. Depending on samples, ham microbiota were dominated by different Proteobacteria (Pseudomonas, Serratia, Psychrobacter, or Vibrio) or by Firmicutes (Latilactobacillus and Leuconostoc). Applied alone, none of the treatments stabilized durably the growth of hams microbiota. Nevertheless, the combination of biopreservation and high pressure treatment was efficient to reduce the growth of Proteobacteria spoilage species. However, this effect was dependent on the nature of the initial microbiota, showing that use of biopreservation and high pressure treatment as an alternative to nitrite reduction for ensuring cooked ham microbial safety merits attention but still requires improvement.

microbiology↗

bioRxiv2019

Heme uptake in Lactobacillus sakei evidenced by a new ECF-like transport system.

Lactobacillus sakei is a non-pathogenic lactic acid bacterium and a natural inhabitant of meat ecosystems. Although red meat is a heme-rich environment, L. sakei does not need iron or heme for growth, while possessing a heme-dependent catalase. Iron incorporation into L. sakei from myoglobin and hemoglobin was formerly shown by microscopy and the L. sakei genome reveals a complete equipment for iron and heme transport. Here, we report the characterization of a five-gene cluster (lsa1836-1840) encoding a putative metal iron ABC transporter. Interestingly, this cluster, together with a heme dependent catalase gene, is also conserved in other species from the meat ecosystem. Our bioinformatic analyses revealed that the locus might refer to a complete machinery of an Energy Coupling Factor (ECF) transport system. We quantified in vitro the intracellular heme in wild-type (WT) and in our {Delta}lsa1836-1840 deletion mutant using an intracellular heme sensor and ICP-Mass spectrometry for quantifying incorporated 57Fe heme. We showed that in the WT L. sakei, heme accumulation occurs fast and massively in the presence of hemin, while the deletion mutant was impaired in heme uptake; this ability was restored by in trans complementation. Our results establish the main role of the L. sakei Lsa1836-1840 ECF-like system in heme uptake. This research outcome shed new light on other possible functions of ECF-like systems. ImportanceLactobacillus sakei is a non-pathogenic bacterial species exhibiting high fitness in heme rich environments such as meat products, although it does not need iron nor heme for growth. Heme capture and utilization capacities are often associated with pathogenic species and are considered as virulence-associated factors in the infected hosts. For these reasons, iron acquisition systems have been deeply studied in such species, while for non-pathogenic bacteria the information is scarce. Genomic data revealed that several putative iron transporters are present in the genome of the lactic acid bacterium L. sakei. In this study, we demonstrate that one of them, is an ECF-like ABC transporter with a functional role in heme transport. Such evidence has not yet been brought for an ECF, therefore our study reveals a new class of heme transport system.

microbiology↗

bioRxiv2019

LARGE MICROBIOTA SURVEY REVEALS HOW THE MICROBIAL ECOLOGY OF COOKED HAM IS SHAPED BY DIFFERENT PROCESSING STEPS

The production of cooked ham involves numerous steps shaping the microbial communities of the final product, with consequences on spoilage metabolites production. To identify the main factors driving the ecology of ham and its spoilage, we designed a study encompassing five variables related to ham production: type of storage during meat transportation, churning speed, drain-off time, slicing line and O2 packaging permeability. We obtained about 200 samples from the same facility and we characterized i) their microbiota based on gyrB amplicon sequencing ii) their production of spoilage-related metabolites based on E-Nose analysis and enzymatic assays. The slicing was the most critical step, shaping two general types of microbiota according to the slicing line: one dominated by Carnobacterium divergens and another one dominated by Leuconostoc carnosum and Serratia proteamaculans. Regarding metabolites production, L. carnosum was associated to D-lactic acid, ethanol and acetic acid production, whereas Serratia proteamaculans was associated to acetic acid production. This last species prevailed with highly O2-permeable packaging. Within a given slicing line, we observed campaign-based variations, with Lactobacillus sakei, Leuconostoc mesenteroides and Carnobacterium maltaromaticum prevalent in summer. L. sakei was associated with L-lactic acid production and C. maltaromaticum with formic and acetic acid productions.

microbiology↗

bioRxiv2018

Viral metagenomic analysis of the cheese surface: a comparative study of rapid procedures for extracting virus-like particles

The structure and functioning of microbial communities from fermented foods, including cheese, have been extensively studied during the past decade. However, there is still a lack of information about both the occurrence and the role of viruses in modulating the function of this type of spatially structured and solid ecosystems. Viral metagenomics was recently applied to a wide variety of environmental samples and standardized procedures for recovering virus-like particles from different type of materials has emerged. In this study, we adapted a procedure originally developed to extract viruses from fecal samples, in order to enable efficient virome analysis of cheese surface. We tested and validated the positive impact of both addition of a filtration step prior to virus concentration and substitution of purification by density gradient ultracentrifugation by a simple chloroform treatment to eliminate membrane vesicles. Viral DNA extracted from the several procedures, as well as a vesicle sample, were sequenced using Illumina paired-end MiSeq technology and the subsequent clusters assembled from the virome were analyzed to assess those belonging to putative phages, plasmid-derived DNA, or even from bacterial chromosomal DNA. The best procedure was then chosen, and used to describe the Epoisses cheese virome. This study provides the basis of future investigations regarding the ecological importance of viruses in cheese microbial ecosystems.\n\nIMPORTANCEWhether bacterial viruses (phages) are necessary or not to maintain food ecosystem function is not clear. They could play a negative role by killing cornerstone species that are necessary for fermentation. But they might also be positive players, by preventing the overgrowth of unwanted species (e.g. food spoilers). To assess phages contribution to food ecosystem functioning, it is essential to set up efficient procedures for extracting viral particles in solid food matrix, then selectively sequence their DNA without being contaminated by bacterial DNA, and finally to find strategies to assemble their genome out of metagenomic sequences. This study, using cheese rind surface as a model, describes a comparative analysis of procedures for selectively extracting viral DNA from cheese and to efficiently characterize the genome of dominant phages with cross-sample assembly.

microbiology↗