HAL du Programme national de recherche environnement-santé-travail (PNR EST)
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Assessment of endocrine disruptor impact on carbohydrate metabolism in the HepaRG human hepatic cell line
No full textInternational audienceEndocrine-disrupting chemicals (EDCs) are increasingly implicated in the development of metabolic disorders such as type 2 diabetes mellitus (T2DM). As hepatic dysfunction is a hallmark of early metabolic disease, we investigated how EDCs may contribute to glucose dysregulation using human HepaRG cells. Ten EDCs-bisphenol A (BPA), bisphenol F (BPF), bisphenol S (BPS), cadmium chloride (CdCl2, 1 µM), butylparaben (BP), 1,1-dichloro-2,2-bis(4-chlorophenyl)ethene (p,p'-DDE), dibutyl phthalate (DBP), di(2-ethylhexyl) phthalate (DEHP), perfluorooctanoic acid (PFOA), and perfluorooctanesulfonic acid (PFOS)-were tested at 25 µM for 5 days. We assessed multiple endpoints related to carbohydrate metabolism, including gene expression, mitochondrial function, glycogen content, glucose export, glycolytic capacity, and lactate release. Among the tested compounds, p,p'-DDE induced the most pronounced metabolic disruption, significantly reducing glycogen storage, glycolytic capacity, lactate export, and the expression of key genes involved in glucose metabolism. Using luciferase-based reporter cell lines, p,p'-DDE was found to activate primarily the nuclear receptors constitutive androstane receptor (CAR) and pregnane X receptor (PXR). However, siRNA-mediated knockdown of these receptors did not reverse the changes induced by p,p'-DDE in gene expression, suggesting a more complex or alternative mechanism of action. These findings demonstrate that p,p'-DDE perturbs hepatic carbohydrate metabolism and may contribute to the pathogenesis of T2DM, highlighting the need for further mechanistic investigation
Biodiversity-dependent invasiveness of naive river epilithic biofilms by anthropogenic antibiotic resistance at the interface between the human, animal and environmental spheres
No full textInternational audienceWith more than 1 million deaths attributed each year, antibiotic resistance has become a major societal issue. The emergence and dissemination of antibiotic resistance in bacteria rests on two pillars, the enrichment of resistant variants upon selection and the contagion of the resistant bacteria and their resistance genes within and across the human, animal and environmental spheres. Although poorly described, this contagion process necessarily implies the persistence of invading resistant bacteria from one microbiome to another. In this study, we carefully selected a series of headwater streams located in the Vosges Mountains (North-eastern, France), with a clear pristine-like upstream part and well identified primary exposure to modest anthropic activities, to explore invasion processes while avoiding multiple pollution effect. Using high-throughput qPCR for 45 resistance genes and mobile genetic elements we showed that one third of the markers were already widespread, while another third massively invaded the river epilithic biofilm communities at primary exposure to anthropic activities, with the concomitant entry of fecal pollution. We used 16S rRNA gene metabarcoding to explore the structure of the bacterial biofilm communities along river continuums and showed that the extent of the invasion process was inversely correlated with the level of biodiversity, but positively correlated with the magnitude of propagule pressure
Metabolic characterization of seven bee pollens: Molecular network, metabolite isolation and antioxidant activity assessment
No full textInternational audienc
Heat during Pregnancy and Reduced Fetal Growth: Critical Windows of Exposure and the Intertwined Role of Air Pollution, Vegetation, and Social Stressors
No full textInternational audienceIncreased ambient heat exposure poses a health risk to pregnant women, which may be amplified by environmental and social determinants, but these interactions have been insufficiently characterized. We examined critical windows for the associations between heat exposure during pregnancy and fetal growth and investigated the role of air pollution, vegetation, and social stressors in these associations. Weekly exposure to ambient temperature and air pollutants (PM 2.5 , NO 2 , O 3 ) from highly resolved spatiotemporal models, vegetation, and contextual deprivation were estimated for 20,904 French women (2002-2017). Distributed lag nonlinear models evaluated associations between heat and term birth weight (tBW), tBW Z-score, and small-for-gestational-age. We further adjusted our models for air pollutants and stratified on vegetation and social determinants. Heat exposure during the first two trimesters was associated with reduced fetal growth. A mean temperature of 21.6 °C (95th percentile vs median 13.6 °C) during weeks 2-15 was associated with a reduced tBW (-199 g [95% CI: -268; -131]). These associations differed after adjusting for O 3 exposure. Trends for stronger associations were observed in women with low vegetation exposure, low social position, and high contextual deprivation. This study highlights how heat stress during early pregnancy could reduce birth weight
Data-driven PINN inference of oocyte dynamics in fish ovaries
No full textEarly oogenesis in juvenile fish establishes the ovarian reserve and thus conditions lifelong reproductive capacity. This process is regulated by local hormonal feedback mechanisms, mainly involving Anti-Müllerian Hormone (AMH). In this work, we develop a mechanistic size-structured population model describing the dynamics of precursor germ cells and growing oocytes in ovary, incorporating an AMH feedback exerted on the precursor germ cells renewal. Using repeated cross-sectional observations of oocyte size distributions in fish ovaries, we formulate and solve a nonlinear inverse problem with Physics-Informed Neural Networks (PINNs) to infer the size-dependent oocyte growth rate, the AMH-regulated renewal rate of precursor cells, and the recruitment rate of new oocytes. The proposed framework enables flexible, data-driven identification of biological rates under minimal prior assumptions. Once calibrated, the model provides in silico access to key unobservable quantities, including cell transit times, the impact of AMH perturbations such as invalidation conditions, and the mechanisms underlying inter-individual variability in the establishment of the pool of small oocytes. This work presents a novel application of PINNs to inverse problems for size-structured partial differential equation models with nonlocal interaction terms, and establishes a quantitative framework for studying early oogenesis in juvenile fish
Chronic cadmium exposure promotes TRPM7-dependent acquisition of a myofibroblast-like phenotype in pancreatic stellate cells
No full textInternational audienceCadmium (Cd) is a metallic pollutant which has been classified as a possible pancreatic carcinogen. Cd uses similar ion channels than divalent cations to accumulate into the cells. These include the Transient Receptor Potential Cation Channel Subfamily M Member 7 (TRPM7) which has been also shown as a biomarker of pancreatic cancer. Pancreatic carcinogenesis is associated with the establishment of a fibrous stroma induced by pancreatic stellate cell (PSC) activation. Although several stress factors have been identified as activators of PSCs, the impact of pollutants, particularly Cd, is still unknown. Here, we chronically exposed human PSCs to Cd and we observed that Cd-exposed cells acquired a myofibroblast-like phenotype. Moreover, TRPM7 expression and activity were upregulated following Cd exposure. Both TRPM7 inhibition by silencing or NS8593 treatment prevented the Cd-induced PSC cell migration indicating that TRPM7 regulated PSC activation. We used a model of indirect co-culture to study the impact of PSC on MIA PaCa-2 cancer cell migration. Interestingly, we showed that Cd-exposed PSCs stimulated MIA PaCa-2 cancer cell migration to a greater extent than non-exposed PSCs. TRPM7 inhibition in PSCs abolished the migration of cancer cells. Finally, in a mouse model with the KRASG12D mutation inducing spontaneous pancreatic intraepithelial neoplasia, Cd exposure aggravates collagen deposition in fibrotic areas showing high α-SMA and TRPM7 expressions. In summary, our study showed that Cd exposure upregulates TRPM7 leading to PSC activation and aggravation of precancerous pancreatic fibrosis in viv
Long-term exposure to particulate air pollution and components in relation to breast cancer risk: A nested case-control study in the E3N-Generations cohort
No full textInternational audienceBackground: Previous studies on the association between airborne particulate matter(PM), particularly PM₂.₅ and PM₁₀, and breast cancer have shown inconsistent results,potentially due to variations in particle composition. To address this, we investigatedthe relationship between breast cancer and exposure to individual PM2.5 and PM10components, as well as their combined effects, in the French E3N-Generation.Methods: We conducted a nested case-control study within the cohort (1990–2011),including 5,222 incident breast cancer cases matched to 5,222 controls. Annual meanconcentrations (μg/m³) of pollutants at residential addresses were estimated usingthe CHIMERE chemistry-transport model from 1990 to the index date. Exposureassessment included nine PM components: ammonium, sulfates, black carbon,polychlorobiphenyl-153 (PCB153), nitrates, benzo[a]pyrene, cadmium, dioxins, andSaharan dust. We evaluated single-pollutant effects using simple and logisticregression, and mixture effects using Quantile G-computation (QGC) and BayesianKernel Machine Regression (BKMR).Results: Significant positive associations with breast cancer (Odds Ratios andconfidence intervals for one SD increase (controls distribution) were found forammonium (OR=1.19; 95%CI:1.05–1.35, sulfate (OR=1.17; 95%CI:1.02–1.34), PCB153(OR=1.16; 95%CI:1.08–1.26), nitrate (OR=1.15; 95%CI:1.01–1.32,black carbon(OR=1.12; 95%CI:1.05–1.19), cadmium (OR=1.05; 95%CI:1.00–1.11). QGC showed apositive association with breast cancer for a one-quartile increase in joint exposure(OR=1.22; 95% CI:1.00–1.50) with cadmium and nitrate as major contributors. BKMRconfirmed a significant positive association between the mixture and breast cancer.Conclusion: The consistency between single-pollutant and mixture analyses supportsa role for multiple PM components acting jointly on breast cancer risk. These resultssuggest that the chemical composition of PM, rather than individual pollutants alone,is a key determinant of breast cancer risk, highlighting the importance of consideringpollutant composition in air pollution research
Is short-term exposure to low and high ambient temperatures associated with an increased risk of sudden unexpected death in infancy? A case-crossover study in France (2015-2022)
No full textInternational audienceBackgroundSudden unexpected death in infancy (SUDI) is a leading cause of infant mortality. Although ambient temperature affects many health outcomes, evidence on its association with SUDI remains limited. We examined short-term effects of high and low temperatures on SUDI in France.MethodsWe performed a time-stratified case-crossover study including lag periods up to six days before death. Conditional logistic regression models assessed associations with both binary temperature indicators (based on percentiles) and continuous metrics using a distributed lag nonlinear model (DLNM). Effect modification by season, sex, social deprivation, urban or rural residence, age at death, and sleeping position was examined.ResultsWe included 1078 SUDI cases in France from 2015 to 2022. Results suggested an increased risk with heat on days close to death. Estimates were imprecise due to the limited sample size, leading to wide confidence intervals for several associations. However, we observed a linear association between temperature and SUDI during summer, particularly for minimum temperature in the last week of life (OR: 1.16, 1.07-1.26). DLNM analyses suggested similar patterns, with elevated risk for minimum temperatures above 15 °C and below 0 °C, though these estimates remain uncertainty.ConclusionsShort-term exposure to both high and low temperatures showed patterns of association with SUDI, with particularly notable effects of heat during summer. Although statistical support for many trends was limited, the alignment of these signals with previous studies suggests that preventive measures to reduce temperature-related risks for infants may be considered, particularly in the context of rising temperatures
Unlocking 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
Bifurcation analysis of a size-structured population model: Application to oocyte dynamics and ovarian cycle
No full textMerci de faire évoluer le preprint en article après publicationInternational audienceWe introduce and analyze a quasilinear size-structured population model with non-linearities accounting for nonlocal interactions between individuals. The recruitment (immigration), growth and death rates are inhomogeneous in time and/or space and depend on weighted averages of the density. We first prove the existence and uniqueness of globally bounded weak solutions using the characteristic curves and Banach fixed point Theorem, after transforming the partial differential equation into an equivalent system of integral equations. We then investigate the long-time behavior of the PDE in the case when the growth rate is separable. Applying a classical time-scaling transformation, the problem boils down to a PDE with linear growth rate and nonlinear inflow boundary condition, entering the theoretical framework of abstract semilinear Cauchy problems. We can then perform a bifurcation analysis which reveals the richness of the model behavior. Depending on the ratio of the recruitment to the growth rate, the model can exhibit multistability and stable oscillatory solutions, emanating respectively through saddle-node and Hopf bifurcations. We illustrate these theoretical results on the biological application motivating this work, oogenesis, the process of production and maturation of female gametes (oocytes) that is critical to reproductive fitness