HAL ENVT (Ecole Nationale Vétérinaire de Toulouse)
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Palmitate potentiates the SMAD3-PAI-1 pathway by reducing nuclear GDF15 levels
No full textInternational audienceNuclear growth differentiation factor 15 (GDF15) reduces the binding of the mothers' against decapentaplegic homolog (SMAD) complex to its DNA-binding elements. However, the stimuli that control this process are unknown. Here, we examined whether saturated fatty acids (FA), particularly palmitate, regulate nuclear GDF15 levels and the activation of the SMAD3 pathway in human skeletal myotubes and mouse skeletal muscle, where most insulin-stimulated glucose use occurs in the whole organism. Human LHCN-M2 myotubes and skeletal muscle from wild-type and Gdf15 -/-mice fed a standard (STD) or a high-fat (HFD) diet were subjected to a series of studies to investigate the involvement of lipids in nuclear GDF15 levels and the activation of the SMAD3 pathway. The saturated FA palmitate, but not the monounsaturated FA oleate, increased the expression of GDF15 in human myotubes and, unexpectedly, decreased its nuclear levels. This reduction was prevented by the nuclear export inhibitor leptomycin B. The decrease in nuclear GDF15 levels caused by palmitate was accompanied by increases in SMAD3 protein levels and in the expression of its target gene SERPINE1, which encodes plasminogen activator inhibitor 1 (PAI-1). HFD-fed Gdf15 -/-mice displayed aggravated glucose intolerance compared to HFD-fed WT mice, with increased levels of SMAD3 and PAI-1 in the skeletal muscle. The increased PAI-1 levels in the skeletal muscle of HFD-fed Gdf15 -/-mice were accompanied by a reduction in one of its targets, hepatocyte growth factor (HGF)α, a cytokine involved in glucose metabolism. Interestingly, PAI-1 acts as a ligand of signal transducer and activator of transcription 3 (STAT3) and the phosphorylation of this transcription factor was exacerbated in HFD-fed Gdf15 -/-mice compared to HFD-fed WT mice. At the same time, the protein levels of insulin receptor substrate 1 (IRS-1) were reduced. These findings uncover a potential novel mechanism through which palmitate induces the SMAD3-PAI-1 pathway to promote insulin resistance in skeletal muscle by reducing nuclear GDF15 levels
Prédictions Inter-Espèces d'Annotations de la Chromatine avec des Réseaux de Neurones Artificiels
No full textInternational audienceA better knowledge of functional annotations of livestock species can be a lever to link genome to phenome. The genomes of most livestock species have already been sequenced. However, data describing gene regulation mechanisms and chromatin state are insufficient. In contrast, abundant human and mouse data allowed the training of powerful deep learning algorithms. Here, we propose to use 3 artificial neural networks (Deepbind, DeepSEA and Enformer), trained with human and mouse data, to predict annotations on the pig, cattle, chicken and European seabass genomes. The predictions are then compared with experimental data to evaluate the cross-species performance of the neural networks.First, human-trained neural network predictions performed on the mouse reference genome showed varying levels of accuracy depending on the experiment, with the higher performance for H3K4me3 (auPRC=0.624). Second, the predictions on the pig, cattle and chicken genomes showed similar (lower mean auPRC=0.385+/-0.233) and better performances than those on the seabass genome (mean auPRC=0.144+/-0.096). Third, the evaluation of the impact of genomic features on the predictions highlighted better performances for CpG island and 5'UTR than other features. Finally, the comparison of predictions between different pig breeds with high genetic diversity demonstrated that genetic variability does not affect the performance, but rather observations.To conclude, we showed that the 3 neural networks evaluated can be used to predict annotations on non-mammalian genomes with similar performances (chicken), but not on genomes of organisms phylogenetically too distant (seabass)
Unraveling the Microbiome-Metabolome Nexus for Innovative One-Health Solution
No full textMicrobial communities, encompassing a vast taxonomic diversity, are fundamental to ecosystem integrity, biogeochemical cycles, and the health of humans, animals, and plants, along the One Health concept. A major scientific goal is to understand how these complex consortia function, interact, and adapt to environmental changes. Microbial meta-metabolomics has emerged as a powerful approach to tackle this by characterizing the collective metabolome of an entire community, linking it to environmental conditions and biogeochemical processes. It captures the functional output of both cultivable and uncultivable organisms, tracing chemical interactions and the impact of environmental perturbations. However, while meta-metabolomics provides a comprehensive snapshot of community chemistry, it alone cannot decipher the precise dynamics of which microorganisms are producing metabolites, when, where, and why. To address this, we propose the Microbial Metabolomics Framework (MiMetWork). This novel framework expands beyond descriptive meta-metabolomics to integrate spatial and temporal metabolomic characterizations with other omics data and phenotyping techniques. MiMetWork employs high-throughput screening of various microbiome components—from single cells to complex communities—under controlled conditions to elucidate ecophysiological functions and interaction mechanisms. By combining untargeted and targeted metabolomic datasets with microbial composition and pathway information, MiMetWork aims to build causal models of microbiome function and adaptation. This review outlines how this integrative framework leverages technological advances to elucidate microbiome interactions and functional responses across human, animal, and environmental niches, thereby addressing critical research gaps and enhancing our predictive understanding of microbiomes within the One Health paradigm
Single-cell transcriptional landscapes of Aedes aegypti midgut and fat body after a bloodmeal
No full textInternational audienceAedes aegypti mosquitoes are vectors for numerous arboviruses that have an increasingly substantial global health burden. Following a bloodmeal, mosquitoes experience significant physiological changes, primarily orchestrated by the midgut and fat body tissues. These changes begin with digestion and culminate in egg production. However, our understanding of those key processes at the cellular and molecular level remains limited. We have created a comprehensive cell atlas of the mosquito midgut and fat body by employing single-cell RNA sequencing and metabolomics techniques. This atlas unveils the dynamic cellular composition and metabolic adaptations that occur following a bloodmeal. Our analyses reveal highly diverse cell populations, specialized in digestion, metabolism, immunity, and reproduction. While the midgut primarily comprises enterocytes, enteroendocrine and intestinal stem cells, the fat body consists not only of trophocytes and oenocytes, but also harbors a substantial hemocyte population and a newly found fat body-yolk cell population. The fat body exhibits a complex cellular and metabolomic profile and exerts a central role in coordinating immune and metabolic processes. Additionally, an insect-specific virus, PCLV (Phasi Charoen-Like Virus) was detected in single cells, mainly in the midgut a week after the bloodmeal. These findings highlight the complexity of the mosquito abdominal tissues, and pave the way towards the development of exquisitely refined vector control strategies consisting of genetically targeting specific cell populations and metabolic pathways necessary for egg development after a bloodmeal
Oxygenic photogranules change metabolism when exposed to shifts in carbon and light availabilities
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Genotype-by-environment interaction with high-dimensional environmental data: an example in pigs
No full textInternational audienceBackgroundIn traditional genetic prediction models, environments are typically treated as uncorrelated effects, either fixed or random. Environments can be correlated when they share the same location, management practices, or climate conditions. The temperature-humidity index (THI) is often used to address environmental effects related to climate or heat stress. However, it does not fully describe the complete climate profile of a specific location. Therefore, it is more appropriate to use multiple environmental covariates (ECs), when available, to describe the weather in a specific environment. This raises the question of whether publicly available weather information (such as NASA POWER) is useful for genomic predictions. Genotype-by-environment interaction (GxE) can be modeled using multiple-trait models or reaction norms. However, the former requires a substantial number of records per environment, while the latter can result in over-parametrized models when the number of ECs is large. This study investigated whether using ECs is a suitable strategy to correlate environments (herds) and to model GxE in the genomic prediction of purebred pigs for production traits.ResultsWe evaluated different models to account for environmental effects and GxE. When environments were correlated based on ECs, we observed an increase in environmental variance, which was accompanied by an increase in phenotypic variance and a decrease in heritability. Furthermore, including environments as an uncorrelated random effect yielded the same accuracy of estimated breeding values as treating them as correlated based on weather information. All the tested models exhibited the same bias, but the predictions from the multiple-trait models were under-dispersed. Evidence of GxE was observed for both traits; however, there were more genetically unconnected environments for backfat thickness than for average daily gain.ConclusionsUsing outdoor weather information to correlate environments and model GxE offers limited advantages for genomic predictions in pigs. Although it adds complexity to the model and increases computing time without improving accuracy, it does enhance model fit. Including environment information (e.g. herd effect) as an uncorrelated random effect in the model could help address GxE and environmental effects
Chemical attribution signature of organophosphorus pesticide chlorpyrifos syntheses by mass spectrometry-based untargeted metabolomics
No full textInternational audienceThesis aims : Setting up the untargeted metabolomics-based methodology (MP1) 7 combinations of chlorpyrifos synthesis raw materials 01 Validation of the methodology (UNKNOWN) Blind analysis of new unknown samples to classify their synthesis route on the basis of discriminating impurities 02 Ruggedness and complexification (MP2) Spiking complex environmental matrix samples to simulate real cases (concentrations, ageing, etc.) 03 Sand Soil River surface wate
Humans as a potential reservoir for the emerging ST301 Shiga toxin-producing Escherichia coli clones of serotype O80:H2?
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Élaboration de jeux d’évasion virtuels à but pédagogique pour l’apprentissage de l’anatomie vétérinaire du cœur et de l’œil à destination des élèves de l’École Vétérinaire de Toulouse
No full textTraditional learning methods face challenges with the emergence of new generations of veterinary students. Integrating interactive technological tools into educational resources has become essential to making veterinary education more dynamic and engaging. This drive for innovation is particularly evident in the 2024 curriculum reform at the Toulouse National Veterinary School, especially within the veterinary anatomy teaching unit, which was among the first to explore these new approaches. The growing interest in serious games, such as escape games, in higher education is undeniable, although their use remains limited in veterinary medicine. Given the scarce documentation on their development and pedagogical integration, this study proposes a methodological guide for designing virtual escape games using the Genially© platform. The objective is to complement and diversify the teaching of veterinary anatomy of the heart and eye at ENVT. To achieve this, we will first analyze the objectives, methods, and limitations of anatomy education at ENVT, before exploring the benefits of serious games through the theoretical foundations of learning.Les méthodes d’apprentissage traditionnelles rencontrent des difficultés avec l’arrivée des nouvelles générations d’étudiants vétérinaires. L’intégration des outils technologiques interactifs dans les supports pédagogiques devient essentielle pour rendre l’enseignement vétérinaire plus dynamique et stimulant. Cette volonté d’innovation apparait notamment dans la nouvelle maquette pédagogique 2024 de l’Ecole Nationale Vétérinaire de Toulouse, et plus particulièrement au sein de l’unité d’enseignement de l’anatomie vétérinaire, qui a été parmi les premières à s’y intéresser. L’intérêt pour les jeux sérieux, tels que les escape games1, dans l’enseignement supérieur est en pleine expansion bien qu’il demeure encore marginal en médecine vétérinaire. Leur développement et intégration pédagogique étant peu documentés, cette étude propose un guide méthodologique pour la conception d’escape games virtuels via la plateforme Genially©, dans le but de compléter et de diversifier l’enseignement de l’anatomie vétérinaire du cœur et de l’œil à l’Ecole Nationale Vétérinaire de Toulouse. Pour cela, nous analyserons d’abord les objectifs, les modalités et les limites de l’enseignement de l’anatomie à l’Ecole Nationale Vétérinaire de Toulouse, avant d’examiner l’intérêt des jeux sérieux à travers les fondements théoriques de l’apprentissage
