HAL ENVT (Ecole Nationale Vétérinaire de Toulouse)
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HiCDOC: chromatin compartment prediction and differential analysis from Hi-C data with replicates
No full textMotivation: The spatial organization of the genome plays an essential role in regulating cellular functions, with A/B chromatin compartments reflecting broad differences in transcriptional and epigenetic activity. Hi-C enables genome-wide identification of such compartments, but robust differential analysis between groups of samples remains challenging. Existing approaches largely rely on Principal Component Analysis, which, applied on Hi-C matrices separately, requires heuristic sign choices to merge results and does not naturally incorporate replicates.Results: Here we present HiCDOC, a Bioconductor package for the prediction and differential analysis of chromatin compartments from Hi-C data with replicates. HiCDOC uses constrained k-means clustering to jointly analyze multiple Hi-C matrices, incorporating replicate information to enhance robustness, and provides empirical statistical support for predicted compartment switches. Applied to Hi-C datasets from human tissues and mouse cell lines, HiCDOC identified biologically relevant compartment changes supported by transcriptional differences. Comparisons with existing tools showed both overlap and complementarity, while a controlled benchmark with artificially introduced changes confirmed high sensitivity. Although extensively tested on pairwise comparisons, HiCDOC offers a flexible framework compatible with more complex designs and, in principle, with more than two compartment states. By combining replicate-aware clustering, automatic A/B assignment across chromosomes, extensive quality control, and statistical evaluation, HiCDOC provides an alternative and complementary approach to PCA-based methods for compartment analysis. HiCDOC thus expands the methodological toolkit for exploring 3D genome dynamics and its role in cellular processes
Fluorescent ivermectin probe reveals differential drug accumulation in susceptible and resistant Caenorhabditis elegans strains
No full textInternational audienceGastrointestinal nematodes pose a significant health challenge in livestock, further exacerbated by widespread resistance to anthelmintic drugs. Macrocyclic lactones (MLs) and, in particular, ivermectin (IVM) are among the most affected classes. The mechanism underlying resistance to MLs are complex and multifactorial. Among the key hypotheses is the overexpression of nematode P-glycoproteins (Pgps), which actively pump the drug out of the worms, limiting its effectiveness. But the gap in our understanding of the complete molecular landscape significantly impedes the design of precise diagnostic tools. Early detection of resistance is critical for effective parasite management, but current diagnostics often detect resistance only after it is established. We previously demonstrated that a stable fluorescent IVM derivative, F-IVM, can discriminate between susceptible and resistant adult Caenorhabditis elegans. In this study, we investigated F-IVM accumulation in eggs from a susceptible wild-type strain (N2) and an IVM-resistant strain (IVR10) selected through prolonged IVM exposure. Fluorescence was quantified by flow cytometry in eggs incubated with F-IVM, and confocal microscopy was used to visualize fluorescence distribution. After 30 minutes of incubation, F-IVM generated in eggs a clear and quantifiable fluorescence signal. Susceptible eggs showed about twice the fluorescence intensity of resistant eggs, consistent with the hypothesis that resistant worms express more Pgps, leading to enhanced efflux and thus lower intracellular IVM levels. Our results demonstrate that F-IVM can rapidly discriminate susceptible and resistant nematode populations at the egg stage. This is the first direct visualization and quantification of an IVM fluorescent probe in C. elegans eggs, showing the relationship between F-IVM signal and resistance. Future work will extend testing to other C. elegans strains resistant to IVM and other MLs such as moxidectin and eprinomectin. Although still in the model phase, this tool offers promising perspectives for parasitic nematodes of livestock such as Haemonchus contortus. Ultimately, F-IVM could support both mechanistic studies and improved resistance diagnostics in the field
Single-cell omics uncover gene dynamics shaping embryonic and extra embryonic lineages in pig blastocysts
No full textInternational audienceLate blastocyst development before implantation is a unique feature of ungulates, during which the epiblast proliferates and maintains pluripotency while extra-embryonic tissues expand dramatically, elongating to several tens of centimeters. The mechanisms coordinating these processes are not well understood. We performed single-cell omics profiling of porcine blastocysts from the hatched stage (E7) through early (E9) and late ovoid stages (E11). From 15,370 cells, we identified distinct embryonic and extra-embryonic populations with characteristic chromatin accessibility profiles. We reconstructed gene regulatory networks using enhancer-based eRegulons and validated them through motif occupancy analysis. Extra-embryonic tissues showed strong shifts in gene regulatory module activity at the onset of elongation, reflecting major transitions in morphogenesis and differentiation and the activation of pathways linked to cell morphology, proliferation, metabolism, trafficking, and biomolecule transport. In contrast, epiblast cells retained a stable transcriptional and regulatory identity from day 7 to day 11, immediately preceding the onset of gastrulation
Oral indomethacin modifies small intestine biofilms and host-microbe interaction mediators
No full textInternational audienceBackground and aims: Nonsteroidal anti-inflammatory drugs (NSAIDs) can cause small intestinal injury and dysbiosis. Although NSAID-induced dysbiosis is well-characterized and contributes to enteropathy, the changes in host-bacterial interactions during enteropathy remain largely unexplored. Here we assessed the expression pattern of six toll-like receptors (TLRs) and three antimicrobial peptides (AMPs) over the course of indomethacin (IND)-induced enteropathy in rats, and evaluated their correlations with inflammation and dysbiosis. In addition, we assessed for the first time the effect of IND on small intestinal mucosal biofilm structure.Materials and methods: Mucosal injury, inflammation and expression of TLR and AMP genes were evaluated at five time points following IND administration. Gut microbiota composition was determined by 16S rRNA gene sequencing. Small intestinal mucosal biofilms were visualized using fluorescent in situ hybridisation.Key findings: We found that TLR1, TLR2 and cathelicidin were upregulated, TLR5 was downregulated, whereas TLR6 and TLR9 were not altered in enteropathy. TLR4 expression showed only subtle differences, but correlated with α-defensin 5 and β-defensin 2 levels. We found several correlations between TLRs, AMPs, inflammation and gut bacteria in severe enteropathy, but in early disease stage TLR1, TLR2, TLR5 and cathelicidin expression were more strongly associated with inflammation, whereas TLR4 and defensins were more dependent on gut dysbiosis. IND treatment also caused mild damage to the mucosal microbiota biofilm.Significance: This is the first comprehensive characterization of the time-dependent changes in TLRs, AMPs and mucosal biofilm in NSAID-treated rats, which may help to identify new strategies for the treatment of enteropathy
Polyploidy modulates the adaptation to water deficit in citrus scion/rootstock associations evaluated under controlled pot condition and relates to specific changes in root and leaf transcriptome
No full textData availability: The RNA-seq data underlying this article are available in Gene Expression Omnibus (GEO) database at: https://www.ncbi.nlm.nih.gov/geo, and can be accessed with the project accession number: GSE255759.International audienceHighlights: • Tetraploid rootstocks with triploid scions enhance drought tolerance in pots. • In pots, 4x rootstocks better regulate water loss under drought conditions. • ABA levels under stress are higher in 4× than in 2× rootstocks. • DEGs involved in transport, stress response and protective barrier formation. • Polyploidy shows strong potential to improve citrus drought resilience.Abstract: Citrus, one of the world's most important crops, is facing significant challenges due to drought events. Previous studies have demonstrated that tetraploid rootstocks may exhibit greater tolerance to abiotic stresses than their diploid counterparts. The effects of combining a tetraploid rootstock with a triploid scion under water deficit conditions have not been thoroughly explored. A water deficit experiment was conducted under controlled pot conditions using four citrus scion/rootstock combinations: diploid and tetraploid Swingle citrumelo rootstocks grafted with diploid Mexican lime and triploid Persian lime. Physiological, biochemical, and transcriptomic analyses under controlled pot condition revealed that tetraploid rootstocks exhibited significantly improved performance under drought stress, with an even greater effect when the scion was the triploid Persian lime. In that condition, the improved resilience was associated with reduced water consumption, higher photosynthesis, increased stomatal conductance and transpiration under water stress conditions. Elevated abscisic acid levels and stronger antioxidant activity in polyploid rootstocks further contributed to the stress response. Transcriptomic data revealed distinct gene expression changes in roots and leaves, influenced by organ ploidy and rootstock-scion interactions. Taken together our results provide insights into drought adaptation mechanisms including osmotic adjustment, oxidative stress protection, sustained photosynthesis, antioxidant enzyme activity and enhanced synthesis of protective barriers. These findings underscore ploidy's role at both rootstock and scion levels in shaping the plant's response to water deficit, revealing useful interactions between rootstock and scion influencing drought resilience
Simulating transgenerational hologenomes under selection with RITHMS
No full textInternational audienceA holobiont is made up of a host organism together with its microbiota. In the context of animal breeding, the holobiont can be viewed as the single unit upon which selection operates. Therefore, integrating microbiota data into genomic prediction models may be a promising approach to improve predictions of phenotypic and genetic values. Nevertheless, there is a paucity of hologenomic transgenerational data to address this hypothesis, and thus to fill this gap, we propose a new simulation framework. Our approach, an R Implementation of a Transgenerational Hologenomic Model-based Simulator (RITHMS) is an open-source package. It builds upon simulated transgenerational genotypes from the Modular Breeding Program Simulator (MoBPS) package and incorporates distinctive characteristics of the microbiota, notably vertical and horizontal transmission as well as modulation due to the environment and host genetics. In addition, RITHMS can account for a variety of selection strategies and is adaptable to different genetic architectures. We simulated transgenerational hologenomic data using RITHMS under a wide variety of scenarios, varying heritability, microbiability, and microbiota transmissibility. We found that simulated data accurately preserved key characteristics across generations, notably microbial diversity metrics, exhibited the expected behavior in terms of correlation between taxa and of modulation of vertical and horizontal transmission, response to environmental effects and the evolution of phenotypic values depending on selection strategy. Our results support the relevance of our simulation framework and illustrate its possible use for building a selection index balancing genetic gain and microbial diversity and for evaluating the impact of partially observed microbiota data. RITHMS is an advanced, flexible tool for generating transgenerational hologenomes under selection that incorporate the complex interplay between genetics, microbiota and environment
Clustering of the dynamics of milk lactose content throughout lactation and identification of variation factors
No full textInternational audienceInterest in milk lactose content (LC) has grown due to its potential as an indicator of udder health and metabolic disorders in dairy cattle. However, the variability of LC dynamics during lactation remains poorly described, and a better characterization of these dynamics could clarify our understanding of LC variations among cows, and potentially those due to udder health and metabolismrelated variations. The aim of this study was to identify distinct patterns of LC dynamics and assess their environmental and genetic determinants, as well as their phenotypic and genetic associations with milk yield, Na, K, SCC, and their phenotypic associations with fat-toprotein ratio (FPR) and BHB. A total of 1,980,693 testday records were analyzed from 183,150 Holstein cows in 2,239 herds across France. At least 2 records in the first 90 d and 4 records between 7 and 300 DIM were available for each cow, averaging 7.3 records per cow. Functional principal component analysis was used to describe LC dynamics throughout lactation. This approach involved smoothing the LC curves for each cow and then summarizing their overall shape using 3 principal components: average LC throughout lactation, LC slope and LC at mid lactation. Dynamics of LC were grouped into 6 clusters. Three clusters (3, 4, and 5) represented 86% of the data and shared similar dynamics with a flat trend after an initial rise in LC at early lactation and different average LC levels (cluster 3: 4.68%, cluster 4: 5.10%, cluster 5: 4.86%). Environmental and intrinsic animal factors explained 69% of the variability in average LC among clusters 3, 4, and 5, with cow parity and LC EBV identified as the main intrinsic contributors. The remaining clusters (1, 2, and 6) showed LC levels similar to the mean of the dataset (LC: 4.88% ± 0.19%) until 150 DIM. Thereafter, 2 clusters displayed negative LC slopes (cluster 1: -0.13% and cluster 6: -0.07% per month of lactation) and one a positive slope (cluster 2: +0.05% per month). Fifteen percent of the variations in the LC slopes of clusters 1, 2, and 6 was explained by environmental factors, mainly calving season: winter calving was associated with clusters 1 and 6, and summer calving with cluster 2. The remaining unexplained negative slope variation from mid lactation onward appears to be related to distinct patterns characterized by higher FPR and milk BHB concentrations preceding the decline in LC, followed by increased SCC after 150 DIM. The lactosebased clusters also corresponded to distinct curves for milk sodium contents, and there were slight correlations for potassium levels, indicating different equilibria between the 3 main osmotic agents (lactose, sodium, and potassium), probably to maintain milk osmolarity. As a result, LC clustering uncovered meaningful physiological profiles: average LC levels were primarily driven by parity and genetics, whereas LC slope variations appeared to be more sensitive to environmental and health-related factors. These findings support the potential of LC dynamics, accessible via mid-infrared spectra, to serve as functional biomarkers for udder health and, potentially, of metabolic status
Minimum inhibitory concentrations of sulfonamides and trimethoprim for veterinary pathogens: new data for old antibiotics
No full textInternational audienceTargeted interpretation of antimicrobial susceptibility testing (AST) raw data is highly dependent on the availability of appropriate interpretative criteria, such as clinical breakpoints (CBP) or at least epidemiological cut-off values (ECOFF) as potential surrogates for CBPs. However, these criteria have not yet been defined for important first line antibiotics used to treat infections with veterinary pathogens. Therefore, the aims of our study were, (1) to produce minimum inhibitory concentration (MIC) distributions for important veterinary pathogens with trimethoprim - sulfamethoxazole 1:19 combination and with sulfamethoxazole, sulfadiazine, sulfadimethoxine, and trimethoprim alone, furthermore, (2) to estimate the proportion of microbiological resistance to sulfonamides and trimethoprim in the selected bacterial species, and lastly, (3) to propose presumptive quality control (QC) ranges for potential QC strain candidates.MIC determination was carried out by broth microdilution according to the recommendations of the European committee on antimicrobial susceptibility testing (EUCAST). For the majority of the veterinary pathogens analysed, MIC distributions for trimethoprim - sulfamethoxazole 1:19, sulfamethoxazole, and trimethoprim met the EUCAST criteria and presumptive ECOFFs could be proposed. In contrast, for sulfadiazine and sulfadimethoxine the tested concentration ranges (> 256 mg/L) were too low for generating data acceptable for estimation of presumptive ECOFFs.The presented MIC distributions form the basis for an inter-laboratory study with the goal to generate aggregated MIC data to be submitted to the EUCAST steering committee for setting missing ECOFFs for sulfonamides and trimethoprim and thereby supporting the use of these first-line antibiotics
Stage-resolved metabolomics reveals the methionine cycle as a key regulator of Aedes aegypti development and dengue virus susceptibility
No full textPosted December 29, 2025 on bioRxiv.International audienceDevelopmental transitions in the mosquito Aedes aegypti are central to vector competence and disease transmission, yet the underlying metabolic programs remain poorly defined. Here, we use untargeted metabolomics, gene expression analysis, and functional assays to delineate stage-specific metabolic fingerprints across the mosquito life cycle, from egg and larva to pupa and adult. Our profiling of the larval diet reveals comprehensive provisioning of essential nutrients, including B vitamins critical for development. Metabolomic analyses uncover distinct, stage-specific signatures, with the larval stage exhibiting a pronounced enrichment of methionine cycle metabolites and maximal methylation capacity. Notably, while S-adenosylmethionine (SAM) and related metabolites peak in larvae, the transcription of the methionine cycle and histone methyltransferase genes is highest in adults. Functional disruption of the methionine cycle in mosquito cells reveals network-level robustness and regulatory crosstalk within the pathway. However, we also identify a specific vulnerability: silencing the gene adenosylhomocysteinase ( ahcy ) enhances dengue virus 1 replication and infectious particle production. Collectively, our findings identify the methionine cycle as a metabolic–epigenetic hub that integrates nutrition, development, and viral susceptibility, and highlight the larval stage as a strategic target for novel mosquito-control strategies
Induction of human cytochrome P450 enzyme activities by metabolism disrupting chemicals in the hepatic cell line HepaRG
No full textInternational audienceMetabolism disrupting chemicals (MDCs) are a class of endocrine disrupting substances that promote metabolic changes leading to metabolic disorders in humans. Central to assessing their adverse effects is the need to better understand their modes of action (MoA). Cytochrome P450 (CYP) enzymes play a major role in xenobiotic metabolism, but also catalyse many endogenous metabolic reactions. Therefore, modulation of CYP functionality may impact homeostasis, contributing to adverse outcomes. At the functional level, alteration of the activity of human CYPs J o u r n a l P r e -p r o o f by MDCs largely remains unexplored. In this study we investigated the capability of six candidate MDCs, bisphenol A (BPA), perfluorooctanoic acid (PFOA), tributyltin (TBT), dichlorodiphenyldichloroethylene (p,p'-DDE), triclosan (TCS) and triphenylphosphate (TPP) to induce CYP1A2, CYP2B6 and CYP3A4 activities in the human hepatic HepaRG cell line. The CYP induction test method previously validated for pharmaceuticals was optimised and selected MDCs were tested in the context of the European Horizon 2020 GOLIATH project. Induction was revealed using a cocktail of CYP-selective probe substrates, followed by probe metabolite quantification by mass spectrometry. All MDCs except TCS induced CYP activities. PFOA, TBT, p,p'-DDE and TPP induced CYP1A2, TPP being the most potent inducer. BPA, PFOA, TBT and TPP induced CYP2B6, PFOA being the most potent inducer. BPA, PFOA, TBT, p,p'-DDE and TPP all induced CYP3A4, p,p'-DDE and BPA being the most potent inducers. These results highlight the capability of candidate MDCs to induce key CYP activities in a human hepatic relevant model, paving the way for a better understanding of MDCs mechanisms of action