HAL ENVT (Ecole Nationale Vétérinaire de Toulouse)
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How scientific networks can help advancing both scientific knowledge and public policies: the case study of the “Plastics, Environment and Health” network
No full textInternational audienceThe “Plastics, Environment and Health” research network (groupement de recherche, GDR) created in 2019 gathers the French scientific community working on plastic pollution in all environments (soil, air, water) and their impact on ecosystems and human health. The scientific objective is to rapidly increase knowledge on plastic pollution by supporting collaboration of researchers from different fields such as ecotoxicology, chemistry, physics, microbiology, oceanography and social science. Research is carried out at each stage of the plastic life cycle, (from resource extraction all the way to removal and remediation) and across the entire air-soil-water continuum, integrating transfers of both plastic particles (macro, micro- and nanoplastics) and plastic chemicals (e.g., additives) between different environmental compartments. In this context, the GDR supports the development of multi-scale and transdisciplinary approaches across three main axes: Axis 1 - Air-soil-water continuum: contamination levels and transfer between compartments; Axis 2 - Interactions and transformation of plastics in environmental compartments and living organisms; Axis 3. Plastic pollution risk assessment for ecosystems and human health. To do so, the GDR’s actions focus on (1) training and sharing of scientific knowledge, including developments towards innovation, (2) support for collaboration and interdisciplinarity between network members, (3) dissemination, structuring of the community and its national and international influence, and (4) support for public policy and/or decision-making by strengthening the link between scientists, decision-makers and the plastic industry. To date the research network includes more than 50 laboratories spread across France and over 300 scientists in the field of physics, chemistry, biology, ecology and social sciences. Such a network constitutes a powerful tool to build robust science-based knowledge significantly contributing to the international effort, to disseminate state-of-the-art scientific advances and research priorities needed to tackle plastic pollution to Society and to inform policy makers. This talk will present the French taskforce addressing 'Plastic, Environment, and Health' within the national research network, where the entire community works collaboratively to tackle the urgent challenges of plastic pollution, its environmental consequences, and the associated risks to human health. We will also discuss the importance of building a French-speaking community to support multilingualism in international political science interactions
G+E copula model to improve the estimation of the genetic parameters in bivariate mixed model
No full textIn environmental sciences, especially in breeding, phenotypes are measured to improve traits of interest. These phenotypes can be decomposed into genetic and environmental components (G+E) and are therefore modelled using a mixed model. As the genetic part is unobservable, the breeding values are latent variables in the model, characterized by a covariance matrix associated with the system's pedigree. In most studies, multiple phenotypes are observed simultaneously, and their joint distribution is generally assumed to be Gaussian. Then, the estimates are obtained using a restricted maximum likelihood (REML) approach or a Bayesian inference, under Gaussian assumptions. However, even if each of the phenotypes is Gaussian, their joint distribution may not be due to a non-Normal dependence structure, which can be characterized using copula functions. When the joint distribution is atypical, such as in the case of heavy-tailed distributions, and the offspring arise from a selection process of the reproducers, the estimates of the variance components can be strongly biased. In this paper, we introduce a G+E mixed inference model, which generalizes the standard model used in genetics by incorporating copulas to account for various joint distributions of the phenotypes. We propose a stochastic gradient descent approach coupled with a Monte Carlo Markov Chain step to estimate the variance components and predict the genetic values. The performance of the algorithm is tested through simulations. Finally, the algorithm is applied on a true dataset of pig breeding, where the assumption of normality for the joint phenotype seems unrealistic. The estimates are compared with those obtained by REML under Gaussian assumptions.</div
Circular RNA and backsplicing: unraveling the real, the misconceptions, and the unknown
No full textInternational audienceThe analysis of circular RNAs (circRNAs) critically relies on identifying circular junctions through computational tools. In our perspective document, we emphasized the potential of datasets not originally generated to study circRNAs to reveal valuable information about the circular transcriptome. These transcripts exist in diverse forms, making it oversimplified to define them solely by their backsplicing origin. However, while backspliced circRNAs display unique signatures distinct from those derived from intronic lariats, many identification tools inaccurately label all circular junctions as 'backsplicing junctions' (BSJs), leading to significant misinterpretation. Based on our experience, we provide recommendations to improve the management of circRNA output lists, which often vary between detection tools. In particular, no single tool provides a universally optimal performance. We suggest key strategies including focusing on backspliced circRNAs between canonical exons, consistent detection across biological replicates, and stringent BSJ read coverage thresholds. Additionally, we explored the impact of uncharacterized splice sites on backsplicing, revealing both genuine and false circRNA signatures. Our findings also highlight circRNA-like patterns arising from in-vitro processes during dataset generation. Ultimately, we underscore that backsplicing is fundamentally a splicing event and that no bioinformatic method can definitively distinguish true circRNAs from false signatures
Spatial risk modelling of highly pathogenic avian influenza in France: Fattening duck farm activity matters
No full textInternational audienceIn this study, we present a comprehensive analysis of the key spatial risk factors and predictive risk maps for HPAI infection in France, with a focus on the 2016–17 and 2020–21 epidemic waves. Our findings indicate that the most explanatory spatial predictor variables were related to fattening duck movements prior to the epidemic, which should be considered as indicators of farm operational status, e.g., whether they are active or not. Moreover, we found that considering the operational status of duck houses in nearby municipalities is essential for accurately predicting the risk of future HPAI infection. Our results also show that the density of fattening duck houses could be used as a valuable alternative predictor of the spatial distribution of outbreaks per municipality, as this data is generally more readily available than data on movements between houses. Accurate data regarding poultry farm densities and movements is critical for developing accurate mathematical models of HPAI virus spread and for designing effective prevention and control strategies for HPAI. Finally, our study identifies the highest risk areas for HPAI infection in southwest and northwest France, which is valuable for informing national risk-based strategies and guiding increased surveillance efforts in these regions
Exploring endogenous retroviruses in ruminant genomes: They might not be all dead after all
No full textInternational audienceEndogenous retroviruses (ERVs) are traces of ancestral retroviral infections, constituting an important portion of mammalian genomes and playing crucial roles in host evolution. Some ERVs have retained their coding capacities, enabling them to act as active transposable elements, capable of duplicating within host genomes and influencing genomic architecture. Despite their extensive research in human genomics, ERVs remain understudied in livestock species, notably in ruminants. Using de novo repeat identification approaches, we charac- terized ERV elements belonging to 24 families across reference assemblies of domestic and wild sheep and goats, and cattle. Among these families, 13 were shared across the five analyzed species, eight were exclusive to small ruminants and three to cattle. The evolu- tionary origin of these families was traced by identifying similar elements in other ruminant genomes and revealed multiple endogenization events over the last 40 million years. A high- resolution annotation of 100,534 ERV insertions was generated, representing 0.5 to 1% of the ruminant genomes. The number of copies varied among ERV families and between species, with a significantly higher number of copies from two specific families in the domestic goat. Population-level analyses of over a hundred domestic goat genomes from 37 different breeds, revealed an abundance of low-frequency copies from these two families, indicative of recent insertions. Whereas the youngest family includes insertions with complete coding capacities and is closely related to oncogenic circulating exogenous oncogenic retroviruses circulating in small ruminants; the second family displays uncomplete elements; suggesting different duplication mechanisms associated to a potential ongoing endogenization. These findings demonstrate recent transpositional activity of ERV copies in the domestic goat genome and highlight distinct ERV evolutionary dynamics among ruminant species. This study under- scores the significance of ERVs as models for understanding species evolution and host-virus interactions and calls for further research into their impact on the genomic landscapes of livestock species
Meat enriched-diet and inflammation promote PI3Kα-dependent pancreatic cell plasticity that limit tissue regeneration
No full textWe identify PI3K activation as a common molecular pathway activated by increased consumption of red and processed meat and by inflammatory condition to promote pancreatic plasticity and precancer lesion development. How this study might affect research, practice or policyAs we show that treatments with the clinically available PI3Kα inhibitor block pancreatic plasticity under inflammatory stress while maintaining pancreas mass and limiting inflammatory reaction damage, they may represent an efficient and safe preventive interception drug in patients at risk of developing pancreatic cancer. PI3K pro-cancer action is exacerbated by the loss of serine synthesis enzyme; hence, diets that alter amino acid synthesis should be tightly controlled in those patients.</div
Is there an advantage of using genomic information to estimate gametic variances and improve recurrent selection in animal populations?
No full textInternational audienceBackground Gametic variances can be predicted from the outcomes of a genomic prediction for any genotyped individual. This is widely used in plant breeding, applying the utility criterion (UC). This paper aims to examine the conditions to use UC for recurrent selection in livestock. Here, the UC for a selection candidate is the linear combination of the expected value of the future progeny (half of the candidate's breeding value) and its predicted gametic variance weighted by a coefficient θ to be optimized. Results First, generalizing previous results, we derived analytically the ratio of the variance of the candidate's gametic variance and that of half of the candidate's breeding value. This ratio depends strongly on the number of quantitative trait loci (QTL) affecting the trait and, to a lesser extent, on the distribution of QTL allele frequencies: highly unbalanced frequencies and a limited number of QTL (<10) favor higher values of the ratio. Then, changes in average breeding values and genetic variances when recurrent selection in a population of infinite size is applied were analytically derived and analyzed for selection up to 15 generations: in this ideal situation, after 5 to 10 generations (depending on θ ), the expected breeding values were higher with selection on UC and the genetic variance was always higher than with selection on estimated breeding values. To describe the potential of the UC in more general situations, simulations were applied to a population of 1000 males and 1000 females, with various selection rates, numbers and allele frequencies of QTL, and θ . These simulations were performed assuming independent QTL with known positions and effects. The best values for θ (i.e. providing the best genetic progress) were generally lower than 1, limiting the weight on the gametic variance. As expected from the analytical derivations, the gain in genetic progress from using UC was greatest when there were few QTL and allele frequencies were unbalanced, but they barely exceeded 5%. ConclusionsWe conclude that the key factor to choose selection on UC rather than on estimated breeding values is the ratio between the variance of the gametic standard deviations and the variance of the breeding values (GEBV), which should be carefully evaluated
Causes of Death and Screening for Toxicants and Hemopathogens of European Hedgehogs (Erinaceus europaeus) from a Wildlife Rehabilitation Center in Northern France
No full textInternational audienceTo understand the dynamics of a pathogen in an animal population, one must assess how the infection status of individuals changes over time. With wild animals, this can be very challenging because individuals can be difficult to trap and sample, even more so since they are tested with imperfect diagnostic techniques. Multi-event capture-recapture models allow analysing longitudinal capture data of individuals whose infection status is assessed using imperfect tests. In this study, we used a two-year dataset from a longitudinal field study of peridomestic wild bird populations in the United Arab Emirates during which thousands of birds from various species were captured, sampled and tested for Newcastle disease virus exposure using a serological test. We developed a multi-event capture-recapture model to estimate important demographic and epidemiological parameters of the disease. The modelling outputs provided important insights into the understanding of Newcastle disease dynamics in peridomestics birds, which varies according to ecological and epidemiological parameters, and useful information in terms of surveillance strategies. To our knowledge, this study is the first attempt to model the dynamics of Newcastle disease in wild bird populations by combining longitudinal capture data and serological test results. Overall, it showcased that multi-event capture-recapture models represent a suitable method to analyse imperfect capture data and make reliable inferences on infectious disease dynamics in wild populations
Workflow4Metabolomics (W4M): A User-Friendly Metabolomics Platform for Analysis of Mass Spectrometry and Nuclear Magnetic Resonance Data
No full textInternational audienceVarious spectrometric methods can be used to conduct metabolomics studies. Nuclear magnetic resonance (NMR) or mass spectrometry (MS) coupled with separation methods, such as liquid or gas chromatography (LC and GC, respectively), are the most commonly used techniques. Once the raw data have been obtained, the real challenge lies in the bioinformatics required to conduct: (i) data processing (including preprocessing, normalization, and quality control); (ii) statistical analysis for comparative studies (such as univariate and multivariate analyses, including PCA or PLS-DA/OPLS-DA); (iii) annotation of the metabolites of interest; and (iv) interpretation of the relationships between key metabolites and the relevant phenotypes or scientific questions to be addressed. Here, we will introduce and detail a stepwise protocol for use of the Workflow4Metabolomics platform (W4M), which provides user-friendly access to workflows for processing of LC-MS, GC-MS, and NMR data. Those modular and extensible workflows are composed of existing standalone components (e.g., XCMS and CAMERA packages) as well as a suite of complementary W4M-implemented modules. This tool suite is accessible worldwide through a web interface and is hosted on UseGalaxy France. The extensible Virtual Research Environment (VRE) provided offers pre-configured workflows for metabolomics communities (platforms, end users, etc.), as well as possibilities for sharing among users. By providing a consistent ecosystem of tools and workflows through Galaxy, W4M makes it possible to process MS and NMR data from hundreds of samples using an ordinary personal computer, after step-by-step workflow optimization. (c) 2025 Wiley Periodicals LLC.Basic Protocol 1: W4M account creation, working history preparation, and data uploadSupport Protocol 1: How to prepare an NMR zip fileSupport Protocol 2: How to convert MS data from proprietary format to open formatSupport Protocol 3: How to get help with W4M (IFB forum) and how to report a problem on the GitHub repositoryBasic Protocol 2: LC-MS data processingAlternate Protocol 1: GC-MS data processingAlternate Protocol 2: NMR data processingBasic Protocol 3: Statistical analysisBasic Protocol 4: Annotation of metabolites from LC-MS dataAlternate Protocol 3: Annotation of metabolites from NMR dat
Development of intimin-enriched outer membrane vesicles (OMVs) as a vaccine to control intestinal carriage of Enterohemorrhagic Escherichia coli
No full textInternational audienceEnterohemorrhagic Escherichia coli (EHEC) are foodborne pathogens causing severe human infections including hemorrhagic colitis and hemolytic uremic syndrome (HUS), particularly in children. Ruminants are the main reservoir of EHEC which colonize their intestinal tract through a mechanism involving the bacterial outer membrane adhesin intimin. Vaccination of cattle has shown efficacy in reducing EHEC O157:H7 shedding in feces. However, most of these vaccines are based on purified proteins and/or require the addition of adjuvants, resulting in expensive vaccines that are not used by breeders. This study introduces the development of a new type of vaccine based on Outer Membrane Vesicles (OMVs) carrying the C-terminal domain of intimin (Int280). A vaccine which combines OMVs carrying luminal Int280 and OMVs displaying surface-exposed Int280 was produced using two addressing systems based on PelB peptide signal and Lpp-OmpA hybrid protein, respectively. This mixed vaccine was tested in a mouse model as a proof of concept using the murine host-specific intestinal pathogen Citrobacter rodentium which shares a similar intimin-based adhesion mechanism with EHEC. Vaccination of mice with OMV-Int280 elicited a strong anti-intimin IgG response. Interestingly, we observed a shortened C. rodentium fecal shedding duration in immunized mice compared to the control group. This OMVs-intimin vaccine therefore represents a promising candidate for the control of EHEC intestinal carriage and fecal shedding in ruminants. IMPORTANCE Enterohemorrhagic Escherichia coli (EHEC) are foodborne pathogenic bacteria causing intestinal infection that may lead to hemorrhagic colitis and hemolytic uremic syndrome (HUS) particularly in young children. There is no effective treatment, and antibiotics are contraindicated because they promote the development of HUS. Vaccination of ruminants, the main reservoir of EHEC, has been proposed as an important strategy to reduce the fecal shedding of EHEC to reduce transmission to humans. Outer Membrane Vesicles (OMVs) derived from E. coli are a highly attractive vaccine platform. Here, we produced OMVs enriched with the C-terminal part of the intimin (Int280). As a proof of concept, we used a mice model of Citrobacter rodentium colonization as a surrogate for EHEC intestinal colonization. Vaccination elicited antibodies against intimin and decreased the duration of fecal shedding of C. rodentium . Therefore, this OMV-Int280 vaccine is a promising candidate to control EHEC intestinal carriage and fecal shedding in ruminants