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International audience; Preservation of biodiversity and ecosystem services is critical for sustainable development and human well-being. However, an unprecedented erosion of biodiversity is observed and the use of plant protection products (PPP) has been identified as one of its main causes. In this context, at the request of the French Ministries responsible for the Environment, for Agriculture and for Research, a panel of 46 scientific experts ran a nearly 2-year-long (2020-2022) collective scientific assessment (CSA) of international scientific knowledge relating to the impacts of PPP on biodiversity and ecosystem services. The scope of this CSA covered the terrestrial, atmospheric, freshwater, and marine environments (with the exception of groundwater) in their continuity from the site of PPP application to the ocean, in France and French overseas territories, based on international knowledge produced on or transposable to this type of context (climate, PPP used, biodiversity present, etc.). Here, we provide a brief summary of the CSA's main conclusions, which were drawn from about 4500 international publications. Our analysis finds that PPP contaminate all environmental matrices, including biota, and cause direct and indirect ecotoxicological effects that unequivocally contribute to the decline of certain biological groups and alter certain ecosystem functions and services. Levers for action to limit PPP-driven pollution and effects on environmental compartments include local measures from plot to landscape scales and regulatory improvements. However, there are still significant gaps in knowledge regarding environmental contamination by PPPs and its effect on biodiversity and ecosystem functions and services. Perspectives and research needs are proposed to address these gaps.

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories ofmodels were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment.

Abstract The zebrafish eleutheroembryo model is increasingly used to assess the toxicity and developmental adverse effects of xenobiotics. However, the actual exposure is seldom measured (poorly accessible), while a predictive model could estimate these concentrations. The predictions with a new eleutheroembryo physiologically based pharmacokinetic (PBPK) model have been evaluated using datasets obtained from literature data for several bisphenols. The model simulated the toxicokinetics of bisphenols A (BPA), AF, F, and S through the eleutheroembryo tissues while considering the body and organ growth. We further improved the predictions by adding dynamic flows through the embryo and/or its chorion, impact of experimental temperature, metabolic clearance, and saturation of the absorption by Bayesian calibration. The model structure was determined using the BPA dataset and generalized to the other bisphenols. This model revealed the central role of the chorion in the compound uptake in the first 48 h post-fertilization. The predictions for the BPA substitutes estimated by our PBPK model were compared to available toxicokinetics data for zebrafish embryos, and 63% and 88% of them were within a twofold and fivefold error intervals of the corresponding experimental values, respectively. This model provides a tool to design new eleutheroembryo assays and evaluate the actual exposure. Graphical abstract

An increasing number of pharmaceuticals found in the environment potentially impose adverse effects on organisms such as fish. Physiologically based kinetic (PBK) models are essential risk assessment tools, allowing a mechanistic approach to understanding chemical effects within organisms. However, fish PBK models have been restricted to a few species, limiting the overall applicability given the countless species. Moreover, many pharmaceuticals are ionizable, and fish PBK models accounting for ionization are rare. Here, we developed a generalized PBK model, estimating required parameters as functions of fish and chemical properties. We assessed the model performance for five pharmaceuticals (covering neutral and ionic structures). With biotransformation half-lives (HLs) from EPI Suite, 73 and 41% of the time-course estimations were within a 10-fold and a 3-fold difference from measurements, respectively. The performance improved using experimental biotransformation HLs (87 and 59%, respectively). Estimations for ionizable substances were more accurate than any of the existing species-specific PBK models. The present study is the first to develop a generalized fish PBK model focusing on mechanism-based parameterization and explicitly accounting for ionization. Our generalized model facilitates its application across chemicals and species, improving efficiency for environmental risk assessment and supporting an animal-free toxicity testing paradigm.

International audience; Before their placing on the market, the safety of plant protection products (PPP) towards both human and animal health, and the environment has to be assessed using experimental and modelling approaches. Models are crucial tools for PPP risk assessment and some even help to avoid animal testing. This review investigated the use of modelling approaches in the ecotoxicology section of PPP active substance assessment reports prepared by the authorities and opened to consultation from 2011 to 2021 in the European Union. Seven categories of models (Structure-Activity, ToxicoKinetic, ToxicoKinetic-ToxicoDynamic, Species Sensitivity Distribution, population, community, and mixture) were searched for into the reports of 317 active substances. At least one model category was found for 44 % of the investigated active substances. The most detected models were Species Sensitivity Distribution, Structure-Activity and ToxicoKinetic for 27, 21 and 15 % of the active substances, respectively. The use of modelling was of particular importance for conventional active substances such as sulfonylurea or carbamates contrary to microorganisms and plant derived substances. This review also highlighted a strong imbalance in model usage among the biological groups considered in the European Regulation (EC) No 1107/2009. For example, models were more often used for aquatic than for terrestrial organisms (e.g., birds, mammals). Finally, a gap between the set of models used in reports and those existing in the literature was observed highlighting the need for the implementation of more sophisticated models into PPP regulation.

Bisphenol A (BPA) is a chemical of major concern due to its endocrine disrupting function, high production volume, and persistence in the aquatic environment. Consequently, organisms such as fish are subject to chronic exposure to BPA. However, physiologically-based toxicokinetic (PBTK) models, which are valuable tools to improve the understanding of a chemical's fate in an organism, have never been specifically adapted to model BPA toxicokinetics (TK) in fish. In our work, an existing PBTK developed for four different fish species was modified to model BPA ADME processes (absorption, distribution, metabolization and excretion). The metabolization of BPA into BPA-monoglucuronide (BPA gluc) and BPA-monosulfate (BPA sulf) and their TK in various organs was taking into account in the model. Experiments were performed to generate BPA TK data in a model species commonly used in ecotoxicology, the stickleback. The model structure had to include two sites of metabolization to simulate BPA TK accurately in stickleback organs. Thus, the fish liver may not be the only site of the metabolization of BPA: plasma or gills could also play a role in BPA metabolization. The PBTK model predictive performance evaluated on literature data in zebrafish and rainbow trout concurs with this conclusion. Finally, a calibration mixing data from the three species was compared to the calibration on stickleback data only.

Pharmaceutical substances are ubiquitous in the aquatic environment and their concentration levels typically range from ng/L up to several μg/L. Furthermore, as those compounds are designed to be highly biologically active, assessing their impacts on non-target organisms is important. Here, we conducted a mesocosm experiment testing a mixture of five pharmaceuticals (diclofenac, carbamazepine, irbesartan, acetaminophen and naproxen) on fish, three-spined stickleback (Gasterosteus aculeatus). The mixture concentration levels were chosen on the basis of the contamination of the Meuse river in Belgium which had been measured previously during a monitoring campaign undertaken in 2015 and 2016. Three nominal mixture concentration levels were tested: the lowest concentration level mixture was composed by environmentally-relevant concentrations that approximate average realistic values for each pharmaceuticals (Mx1); the two other levels were 10 and 100 times these concentrations. Although no impact on stickleback prey was observed, the mixture significantly impaired the survival of female fish introduced in the mesocosms at the highest treatment level without causing other major differences on fish population structure. Impacts on condition factors of adults and juveniles were also observed at both individual and population levels. Using a modelling approach with an individual-based model coupled to a bioenergetic model (DEB-IBM), we concluded that chronic exposure to environmentally-relevant concentrations of five pharmaceuticals often detected in the rivers did not appear to strongly affect the three-spined stickleback populations. Mechanisms of population regulation may have counteracted the mixture impacts in the mesocosms.

Developing ecological models for accurately predicting the dynamics of a population and individual physiological processes in field conditions is a challenging task for ecosystem management and ecological risk assessment. Here, we propose to assess the relevance of a dynamic energy budget (DEB) model calibrated using data previously generated from laboratory experiments for adult three‐spined sticklebacks (Gasterosteus aculeatus) living in semi‐natural conditions. We compared different ways of integrating different data sets such as temperature and prey abundance obtained in mesocosm experiments to assess the predictive capacity of the model. By this study, we provide recommendations for developing an appropriate environmental scenario (e.g. natural variations of food and temperature) for using a DEB model in a field context. We conclude that a DEB model calibrated with laboratory data can be used to predict the physiological processes of an organism living in semi‐natural conditions, but that the reproductive behaviour of the organism can affect the predictions. At last, we suggest that further studies on the feeding behaviour may be necessary for immature organisms.

We developed a simulation model for quantifying the spatio-temporal distribution of contaminants (e.g., xenobiotics) and assessing the risk of exposed populations at the landscape level. The model is a spatio-temporal exposure-hazard model based on (i) tools of stochastic geometry (marked polygon and point processes) for structuring the landscape and describing the exposed individuals, (ii) a dispersal kernel describing the dissemination of contaminants from polygon sources, and (iii) an (eco)toxicological equation describing the toxicokinetics and dynamics of contaminants in affected individuals. The model was implemented in the briskaR package (biological risk assessment with R) of the R software. This article presents the model background, the use of the package in an illustrative example, namely, the effect of genetically modified maize pollen on nontarget Lepidoptera, and typical comparisons of landscape configurations that can be carried out with our model (different configurations lead to different mortality rates in the treated example). In real case studies, parameters and parametric functions encountered in the model will have to be precisely specified to obtain realistic measures of risk and impact and accurate comparisons of landscape configurations. Our modeling framework could be applied to study other risks related to agriculture, for instance, pathogen spread in crops or livestock, and could be adapted to cope with other hazards such as toxic emissions from industrial areas having health effects on surrounding populations. Moreover, the R package has the potential to help risk managers in running quantitative risk assessments and testing management strategies.

International audience; Aquatic organisms are exposed to mixtures of chemicals that may interact. Mixtures of atrazine (ATR) and chlorpyrifos (CPF) may elicit synergic effects on the permanent inhibition of acetylcholinesterase (AChE) in certain aquatic organisms, causing severe damage. Mechanistic mathematical models of toxicokinetics and toxicodynamics (TD) may be used to better characterize and understand the interactions of these two chemicals. In this study, a previously published generic physiologically-based toxicokinetic (PBTK) model for fish was adapted to ATR and CPF. A sub-model of the kinetics of one of the main metabolites of CPF, chlorpyrifos-oxon (CPF-oxon), was included, as well as a TD model. Inhibition of two esterases, AChE and carboxylesterase, by ATR, CPF and CPF-oxon, was modeled using TD modeling of quantities of total and inactive esterases. Specific attention was given to the parameterization and calibration of the model to accurately predict the concentration and effects observed in the fish using Bayesian inference and published data from fathead minnow (Pimephales promelas), zebrafish (Dunn) rerio) and common carp (Cyprinus carpio L.). A PBTK-TD for mixtures was used to predict dose-response relationships for comparison with available adult fish data. Synergistic effects of a joint exposure to ATR and CPU could not be demonstrated in adult fish.

Developing population models is of great interest as these models enable to extrapolate toxicity observed at the molecular or individual levels to the population level, and thus improve environmental risk assessment of chemical substances. For this purpose, accounting for natural variations of environmental conditions and prey dynamics along with the chemical stress is needed. In this study, an individual-based model (IBM) coupled to a Dynamic Energy Budget (DEB) model was developed in order to predict three-spined stickleback population dynamics in semi-controlled stream experiments (in mesocosms). Datasets obtained in mesocosms offer the opportunity to develop and evaluate the model predictions. The most sensitive parameters of the DEB-IBM were identified by sensitivity analyses and were calibrated based on data from two independent mesocosm experiments. The predictive capacities of our model were subsequently evaluated using three independent mesocosm datasets under different environmental scenarios. Finally, our model was applied to a theoretical case of toxic effects to show an example of application of the model in a regulatory context. While the most uncertain population processes (in particular, competition for food in mesocosms) in our three-spined stickleback DEB-IBM could be modelled more accurately, our model can already serve to assess the impacts of toxicants at the population level by improving the analyses of mesocosm experiments, in decreasing the uncertainty of the experimental results. Therefore, in a second step, it could be used to predict the consequences on viability of a population exposed to a contaminant under various environmental and exposure scenarios.

Bisphenol A (BPA), a well-known endocrine-disrupting chemical, is ubiquitously present in the aquatic environment. Its impacts at the population level on three-spined sticklebacks (Gasterosteus aculeatus) have been studied in artificial streams with low-dose BPA concentrations. The causes explaining the observed effects remained unclear. Here, we used an individual-based model coupled to a Dynamic Energy Budget model to (i) assess the potential of modelling to predict impacts at the population level using individual level laboratory ecotoxicological endpoints and (ii) provide insight on the mechanisms of BPA toxicity in these mesocosms. To do that, both direct and indirect effects of BPA on three-spined sticklebacks were incorporated in the model. Indeed, direct BPA effects on fish have been identified based on literature data whereas indirect effects on sticklebacks have been taken into account using sampling data of their prey from the exposed artificial streams. Results of the modelling showed that direct BPA effects on fish (impacts on gonad formation, growth, male reproductive behavior, eggs and larvae survival) mainly explained the three-spined stickleback population structure in the mesocosms, but indirect effects were not negligible. Hence, this study showed the potential of modelling in risk assessment to predict the impacts on fish population viability from behavioral and physiological effects measured on organisms.

Human biomarkers of exposure to pyrethroid insecticides are usually urinary concentrations of metabolites that can be specific to a pyrethroid or common to several compounds. We developed a global toxicokinetic model that links the external exposure to four widely-used pyrethroids and their isomers (deltamethrin and cis and trans isomers of permethrin, cypermethrin, and cyfluthrin) to the urinary concentrations of metabolites (cis- and trans-DCCA, 3-PBA, F-PBA and DBCA). This global model includes physiologically based pharmacokinetic models for each parent compound and one-compartment models for the metabolites. Existing in vivo, in vitro and in silico data were used for model calibration, and human toxicokinetic data for model evaluation. Overall, the global model reproduced the data accurately as about 90% of predictions were inside the 3-fold error interval. A sensitivity analysis showed that the most influent parameter for each urinary metabolite concentration was the fraction of parent compound that is transformed into that metabolite. The global model was then tested with realistic exposures for the French population: the predictions were consistent with biomonitoring data. The global model is a tool that will improve the interpretation of biomonitoring data for pyrethroids.

Following outbreaks of feed and food adulterations with a melamine and cyanuric acid mixture in 2007 and melamine in 2008 respectively, the kinetics and toxicodynamics of the mixture have been investigated particularly in sensitive species such as the rainbow trout. Tissue concentrations and intensity of the adverse effect, melamine-cyanurate crystal formation in kidney, were reported in similar experimental conditions. Here, a recent PBTK model for rainbow trout has been applied to model the kinetics of both single compounds based on residue levels in tissues. Both PBTK models for the single compounds were combined and a model of crystal formation for the mixture melamine-cyanuric acid was also added to predict the intensity of crystal formation under the assumptions that crystals formed either in urine or in kidney tissue. Modelling the kinetics of melamine and cyanuric acid provided a better understanding and prediction of intensity of crystal formation in case of sequential exposures with varying intensity or co-exposure. This study demonstrates, for the first time, how fish PBTK models can play a key role in the understanding and prediction of toxicokinetics and toxicodynamics of mixtures. This study also illustrates how adverse effects may potentially occur even when the compounds are not administered together as a mixture.

International audience; Per- and poly-fluorinated substances (PFAS) are widely found in freshwater ecosystems because of their resistance to degradation. Among them, several long-chain perfluoroalkyl acids bioaccumulate in aquatic vertebrates, but our understanding of the mechanisms of absorption, distribution and elimination is still limited in fish. For this purpose, we developed a 10-compartment physiologically-based toxicokinetic (PBTK) model to elucidate perfluorooctane sulfonate (PFOS) kinetics in adult rainbow trout. This PBTK model included various physiological characteristics: blood perfusion to each organ, plasmatic fraction, PFOS free fraction, and growth of individuals. The parameters were optimized using Bayesian inferences. First, only PFOS absorption by diet was considered in the model as well as its elimination by urine, bile and feces. Then two mechanistic hypotheses, assumed to govern PFOS toxicokinetics in fish, namely the enterohepatic cycle and the absorption and elimination though gills, were tested. Improvement of the model's fit to the data was studied in each organ by comparing predictions with observed data using relative error. The experimental data set was obtained from an exposure experiment, where adult rainbow trout were fed with a PFOS-spiked diet for 42 days, followed by a 35-day depuration period. In all cases, PFOS concentrations were accurately predicted in organs and feces by the model. The results of this PBTK model demonstrated that feces represented the major elimination route for PFOS while urine was a minor route. Also, PFOS branchial uptake can be substantial despite low concentrations of the compound in water, and elimination through gills should not be neglected. Finally, the enterohepatic cycle is likely to play a minor role in PFOS toxicokinetics. Overall, this PBTK model accurately described PFOS distribution in rainbow trout and provides information on the relative contribution of absorption and elimination pathways.

The present work aimed to assess the efficiency of a constructed wetland as tertiary treatment on urban wastewater with a multibiomarker approach using caged three-spined sticklebacks (Gasterosteus aculeatus L.). Fish were caged on three sites: at the entrance of the Constructed Wetland (CW), directly inside the wastewater effluent, at the exit of the CW, and in a weakly impacted site considered as a reference. After 21 days of caging, sticklebacks state of health was assessed using several biomarkers representing some biological functions such as innate immune and antioxidant systems, biotransformation enzymes, reproduction parameters and synaptic transmission. A strong inhibition of the innate immune system, an induction of EROD activity and an alteration of the hepatosomatic index were observed in fish caged at the entrance of the CW compared to those caged in the reference site. In addition, wastewater effluent induced a decrease of antioxidant system without induced oxidative damage on cell membranes. No improvement of these biomarkers was observed for antioxidant parameters at the exit of the CW. However, in fish caged at the exit of the CW, the EROD induction observed at the entrance was reduced and the innate immune system presented the same level compared to fish caged in the reference site, underlying the beneficial effect of the CW for these parameters. Integrated Biomarker response (IBR) was equal to 25.2 at the entrance of the CW and 17.4 at the exit of the CW which highlighted the global positive effect of the CW on water quality based on fish biomarker measurement.

Due to their sensitivity to environmental contamination and their link with fish health status, innate immunomarkers are of great interest for environmental risk assessment studies. Nevertheless, the lack of knowledge about the effect of confounding factors can lead to data misinterpretation and false diagnostics. So, the determination of reference values was of huge interest for the integration of biomarkers in biomonitoring programs. Laboratory immunomarker reference ranges (including cellular mortality, leucocyte distribution, phagocytosis activity, respiratory burst and lysosomal presence) that consider three confounding factors (season, sex and body size) were previously developed in three-spined stickleback, Gasterosteus aculeatus, from our husbandry. Usefulness of these reference ranges in biomonitoring programs depends on how they can be transposed to various experimental levels, such as mesocosm (outdoor artificial pond) and field conditions. Immunomarkers were therefore measured every 2 months over 1 year in one mesocosm and in one site assumed to uncontaminated (Houdancourt, field). Differences between immunomarker seasonal variations in mesocosm and field fish on one side and laboratory fish on the other side were quantified: in some cases, seasonal trends were not significant or did not differ between mesocosm and laboratory conditions, but overall, models developed based on data obtained in laboratory conditions were poorly predictive of data obtained in mesocosm or field conditions. To propose valuable field reference ranges, mesocosm and field data were integrated in innate immunomarker modelling in order to strengthen the knowledge on the effect of confounding factors. As in laboratory conditions, sex was overall a confounding factor only for necrotic cell percentage and granulocyte-macrophage distribution and size was a confounding factor only for cellular mortality, leucocyte distribution and phagocytosis activity. Confounding factors explained a large proportion of immunomarker variability in particular for phagocytosis activity and lysosomal presence. Further research is needed to test the field models in a biomonitoring program to compare the sensitivity of immunomarkers to the confounding factors identified in this study and the sensitivity to various levels of pollution.

International audience; BPA is one of the most investigated substances for its endocrine disruptor (ED) properties and it is at the same time in the center of many ED-related controversies, the analysis on how BPA fits to the regulatory identification as an ED is a challenge in terms of methodology. It is also a great opportunity to test the regulatory framework with a uniquely data-rich substance and learn valuable lessons for future cases. From this extensive database, it was considered important to engage in a detailed analysis so as to provide specific and strong evidences of ED while reflecting accurately the complexity of the response as well the multiplicity of adverse effects. An appropriate delineation of the scope of the analysis was therefore critical. Four effects namely, alterations of estrous cyclicity, mammary gland development, brain development and memory function, and metabolism, were considered to provide solid evidence of ED-mediated effects of BPA.

One of the goals of environmental risk assessment is to protect the whole ecosystem from adverse effects resulting from exposure to chemicals. Many research efforts have aimed to improve the quantification of dose-response relationships through the integration of toxicokinetics. For this purpose, physiologically-based toxicokinetic (PBTK) models have been developed to estimate internal doses from external doses in a time-dependent manner. In this study, a generic PBTK model was developed and adapted for rainbow trout (Onchorhynchus mykiss), zebrafish (Danio rerio), fathead minnow (Pimephales promelas), and three-spined stickleback (Gasterosteus aculeatus). New mechanistic approaches were proposed for including the effects of growth and temperature in the model. Physiological parameters and their inter-individual variability were estimated based on the results of extensive literature searches or specific experimental data. The PBTK model was implemented for nine environmental contaminants (with log k(ow) from - 0.9 to 6.8) to predict whole-body concentrations and concentrations in various fish's organs. Sensitivity analyses were performed for a lipophilic and a hydrophilic compound to identify which parameters have most impact on the model's outputs. Model predictions were compared with experimental data according to dataset-specific exposure scenarios and were accurate: 50% of predictions were within a 3-fold factor for six out of nine chemicals and 75% of predictions were within a 3-fold factor for three of the most lipophilic compounds studied. Our model can be used to assess the influence of physiological and environmental factors on the toxicokinetics of chemicals and provide guidance for assessing the effect of those critical factors in environmental risk assessment.

International audience; Innate immunomarkers reflect both environmental contamination and fish health status, providing useful information in environmental risk assessment studies. Nevertheless, the lack of knowledge about the effect of confounding factors can lead to data misinterpretation and false diagnoses. The aim of this study was to evaluate the impact of three confounding factors (season, sex and body size) on three-spined stickleback innate immunomarkers in laboratory conditions. Results shown strong seasonal variations in stickleback innate immunomarkers, with higher immune capacities in late winter-early spring and a disturbance during the spawning period in late spring-summer. Sex and body size had a season dependant effect on almost all tested immunomarkers. Reference ranges were established in laboratory-controlled conditions (i.e. laboratory reference ranges) and compared with data obtained from in vivo chemical expositions. The predictive power of the statistical model depended on the immunomarker, but the control data of the in vivo experiments, realized in same laboratory conditions, were globally well include in the laboratory reference ranges. Moreover, some statistical effects of the in vivo exposures were correlated with an augmentation of values outside the reference ranges, indicating a possible harmful effect for the organisms. As confounding factors influence is a major limit to integrate immunomarkers in biomonitoring programs, modelling their influence on studied parameter may help to better evaluated environmental contaminations.

A whole life-cycle bioenergetic model based on the dynamic energy budget (DEB) theory was proposed for the three-spined stickleback (Gasterosteus aculeatus). To develop this model, experiments on growth and reproduction were performed: adult and juvenile growth, size at first reproduction and amount of eggs spawned by females were monitored under different feeding levels and temperatures. The DEB parameters were estimated, using Bayesian statistics, based on the data produced during these experiments and on other data found in the literature. The model fitted accurately the different data used for the calibration process and, in addition, predicted accurately the data sets used to assess its predictability. Our bioenergetic model of the whole life cycle of the three-spined stickleback accounting for environmental variations could contribute in many ways to improved ecological assessment: supporting change of scale from individual to populations; developing new biomarkers of exposure and effect; analysing ecotoxicity tests with biology-based models.

The aims of this study were to determine depuration rates for a range of per- and polyfluoroalkyl substances (PFASs) using Chironomus riparius, and to test a concentration-dependency hypothesis for the long-chain perfluorotridecanoic acid (PFTrDA) for this species. Midge larvae were exposed to field sediments collected downstream of a fluorotelomer plant, and to the same sediment spiked with PFTrDA. Elimination kinetics results indicated complete elimination of all PFASs by chironomids after 42 h. These data were used to develop two PFTrDA bioaccumulation models accounting for chironomid growth and for compound concentration dependency or not. There was much better agreement between observed and simulated data under the concentration-dependency hypothesis than under the alternative one (passive diffusion). The PFTrDA uptake rate derived from the concentration-dependency model equaled 0.013 ± 0.008 goc gww h−1, and the depuration rate 0.032 ± 0.009 h−1.

The ubiquitous free-living nematode Caenorhabditis elegans is a powerful animal model for measuring the evolutionary effects of pollutants which is increasingly used in (eco) toxicological studies. Indeed, toxicity tests with this nematode can provide in a few days data on the whole life cycle. These data can be analysed with mathematical tools such as toxicokinetic-toxicodynamic modelling approaches. In this study, we assessed how a chronic exposure to a radioactive heavy metal (uranium) affects the life-cycle of C. elegans using a mechanistic model. In order to achieve this, we exposed individuals to a range of seven concentrations of uranium. Growth and reproduction were followed daily. These data were analysed with a model for nematodes based on the Dynamic Energy Budget theory, able to handle a wide range of plausible biological parameters values. Parameter estimations were performed using a Bayesian framework. Our results showed that uranium affects the assimilation of energy from food with a no-effect concentration (NEC) of 0.42 mM U which would be the threshold for effects on both growth and reproduction. The sensitivity analysis showed that the main contributors to the model output were parameters linked to the feeding processes and the actual exposure concentration. This confirms that the real exposure concentration should be measured accurately and that the feeding parameters should not be fixed, but need to be reestimated during the parameter estimation process.

Polyfluoroalkyl and perfluoroalkyl substances (PFASs) are ubiquitous in the environment, in particular in aquatic systems. Their unique physicochemical properties, leading to their stability, give them a complex hazard profile. PFASs behave differently compared to “classical” organic compounds and the mechanisms of absorption, distribution and elimination (ADE) remain incompletely understood, especially in aquatic vertebrates in which some of them are bioaccumulated. The aim of the present study is to describe the fundamental processes involved in ADE mechanisms in rainbow trout (Oncorhynchus mykiss) exposed to three model PFASs (perfluorooctane sulfonic acid - PFOS, perfluorohexane sulfonic acid – PFHxS, and perfluorononanoic acid - PFNA) through their diet, using a physiologically based toxicokinetic (PBTK) model. Also, this model will take into account the growth of individuals during their exposure. To develop our PBTK model, bioaccumulation and tissue distribution data are collected by feeding rainbow trout with contaminated pellets for 28 days, followed by a depuration period. Since temperature influences several physiological processes, the experiments will be carried out at three different temperatures (8°C, 12°C and 18°C). This poster will show the first results of this project obtained until now and will illustrate the progression of the present PBTK model.

National audience; La compréhension des mécanismes d'effets toxiques et l'évaluation du risque des substances pour les écosystèmes sont des enjeux majeurs des recherches en écotoxicologie. Les effets écotoxicologiques : de la molécule à la population présente, au travers d'exemples concrets et de résultats de recherches récents, des concepts, des méthodes et des outils de mesure et de modélisation, qui permettent de comprendre, d'expliquer et de prédire l'impact des polluants chimiques de la cellule à la population. Cet ouvrage illustre la complexité et la richesse des questions scientifiques concernant les impacts toxiques sur différents niveaux d'organisation biologique. Il apporte des réponses aux lecteurs intéressés par les enjeux de compréhension et de prédiction des risques toxiques chimiques.

International audience; Zebrafish (Danio rerio) is a widely used model for toxicological studies, in particular those related to investigations on endocrine disruption. The development and regulatory use of in vivo and in vitro tests based on this species can be enhanced by toxicokinetic modeling. For this reason, we propose a physiologically based toxicokinetic (PBTK) model for zebrafish describing the uptake and disposition of organic chemicals. The model is based on literature data on zebrafish, other cyprinidae and other fish families, new experimental physiological information (volumes, lipids and water contents) obtained from zebrafish, and chemical-specific parameters predicted by generic models. The relevance of available models predicting the latter parameters was evaluated with respect to gill uptake and partition coefficients in zebrafish. This evaluation benefited from the fact that the influence of confounding factors such as body weight and temperature on ventilation rate was included in our model. The predictions for six chemicals (65 data points) yielded by our PBTK model were compared to available toxicokinetics data for zebrafish and 88% of them were within a factor of 5 of the corresponding experimental values. Sensitivity analysis highlighted that the 1-octanol/water partition coefficient, the metabolism rate, and all the parameters that enable the prediction of assimilation efficiency and partitioning of chemicals need to be precisely determined in order to allow an effective toxicokinetic modeling.

International audience; Bisphenol A (BPA) is commonly used by manufacturers and can be found in many aquatic ecosystems. Data relative to BPA ecotoxicity are only available for studies in laboratory conditions on macro-invertebrates and fish. There is thus a lack of information for other trophic levels such as macrophytes. Moreover, the impacts of BPA within an ecosystem context, i.e. with populations from different trophic levels studied at long term in environmental conditions, have never been assessed. We carried out a long-term lotic mesocosm study in 20 m long channels under three exposure concentrations of BPA (nominal concentrations of 0, 1, 10 and 100 mu g/L) delivered continuously for 165 days. Three trophic levels were followed: macrophytes, macro-invertebrates (with a focus on Radix balthica) and fish (Gasterosteus aculeatus). Significant effects were shown at 100 mu g/L BPA on the three trophic levels. BPA had a direct impact on macrophyte community structure, direct and indirect impacts on macro-invertebrates and on fish population structure. Gonad morphology of fish was affected at 1 and 10 mu g/L of BPA, respectively for female and male sticklebacks. In addition to these ecotoxicity data, our results suggest that fish are good integrators of the responses of other communities (including macro-invertebrates and macrophytes) in mesocosm systems.

Species sensitivity distributions (SSDs) developed from individual and population endpoints were compared based on simulations and a case study. The simulations were performed with five invertebrate species accounting for the diversity of benthic macroinvertebrate communities in large European lowland rivers and for five benthic invertebrates used as laboratory species. Population growth rate 10% effective concentration (EC10) values were, in most of the simulations, higher than the lowest of the EC10 values at the individual level. However, for the set of ecologically representative species, the fifth percentile level of this distribution (HC5) was more protective for population endpoints than for individual endpoints. This was the opposite for the set of laboratory species. Population and individual SSDs were also compared based on existing data on Cu for the five laboratory invertebrate species. In this case, the calculated population HC5 value was almost twice the individual value, and the authors showed much reduced variability between species sensitivities at population level compared with individual level. They conclude that population-based HC5 would generally be more protective than individual-based HC5. However, the change of level could reveal higher homogeneity at population level than at individual level, supporting the use of population-based HC5 to avoid overprotection. The authors thus advise the derivation of population-based HC5, as soon as it is possible, to derive such value with a relevant panel of species.

Environmental risk assessment of chemicals for the protection of ecosystems integrity is a key regulatory and scientific research field which is undergoing constant development in modelling approaches and harmonisation with human risk assessment. This review focuses on state-of-the-art toxicokinetic tools and models that have been applied to terrestrial and aquatic species relevant to environmental risk assessment of chemicals. Both empirical and mechanistic toxicokinetic models are discussed using the results of extensive literature searches together with tools and software for their calibration and an overview of applications in environmental risk assessment. These include simple tools such as one-compartment models, multi-compartment models to physiologically-based toxicokinetic (PBTK) models, mostly available for aquatic species such as fish species and a number of chemical classes including plant protection products, metals, persistent organic pollutants, nanoparticles. Data gaps and further research needs are highlighted.

The principal response curve (PRC) method is a constrained ordination method developed specifically for the analysis of community data collected in mesocosm experiments, which provides easily understood summaries and graphical representations of community response to stress. It is a redundancy analysis method and is usually performed on log-transformed abundance data. The choice of a measure of dissimilarity between samples and the choice of the data transformation significantly affect the results of multivariate analysis. Dissimilarity measures that are more ecologically meaningful than the Euclidean distance can be incorporated into the PRC using distance-based redundancy analysis. The present study investigates the ordinations produced by a small selection of dissimilarity measures: the Euclidean distance using log-transformed and Hellinger-transformed data and the Bray-Curtis dissimilarity using raw and log-transformed data. It compares 2 data sets from experiments on the effect of the anti-inflammatory drug diclofenac and the insecticide chlorpyrifos on macroinvertebrate communities. The choice of dissimilarity measure can determine the outcome of a risk assessment. For the diclofenac data set, the PRCs were different depending on the dissimilarity measure: the community no-effect concentration was lowest for the Bray-Curtis on log-transformed data and Hellinger dissimilarity measures. For chlorpyrifos, however, the PRCs were similar for all dissimilarity measures. Environ Toxicol Chem 2017;36:1667-1679. © 2016 SETAC.

Two main alternatives are typically used to model mechanistically dose-survival relationship in ecotoxicity tests. Effects are related to a concentration of concern, for instance body concentration, and, to account for their differences relative to time-to-death, individuals have either different concentration thresholds for death (“individual tolerance approach”), or equal probability to die, with death occurring randomly (“stochastic death approach”). A general framework to unify both approaches has recently been proposed. We derived a model from this framework to analyse five datasets (daphnids exposed to selenium, guppies exposed to dieldrin and second, third and fourth instars chironomids exposed to copper), by extending the standard stochastic death approach. We showed the possibility to estimate properly the toxicity parameters together with inter-organisms differences of sensitivity for at least one of these parameters (here the threshold for effect). For the daphnids, there was no improvement of using the extended model, which confirms the expected low variability among genetically identical individuals. For all the other datasets, our model outperformed the standard approach without accounting for differences of sensitivity. We estimated coefficients of variations in the distribution of the logarithm of the threshold from 44% to 4% and showed, for chironomids, a decrease of inter-individual differences of sensitivity with the age of the larvae. All standard threshold estimates were close but above the medium value of the distribution in the new approach, which means that a concentration equal to the standard threshold would ultimately result in the death of more than half of the exposed organisms. A more relevant parameter, such as the concentration protecting 95% of the population, would be 2–4 times inferior to the standard threshold.

International audience; Recent studies have investigated chronic toxicity of waterborne depleted uranium on the life cycle and physiology of Daphnia magna. In particular, a reduction in food assimilation was observed. Our aims here were to examine whether this reduction could fully account for observed effects on both growth and reproduction, for three successive generations, and to investigate through microscope analyses whether this reduction resulted from direct damage to the intestinal epithelium. We analyzed data obtained by exposing Daphnia magna to uranium over three successive generations. We used energy-based models, which are both able to fit simultaneously growth and reproduction and are biologically relevant. Two possible modes of action were compared - decrease in food assimilation rate and increase in maintenance costs. In our models, effects were related either to internal concentration or to exposure concentration. The model that fitted the data best represented a decrease in food assimilation related to exposure concentration. Furthermore, observations of consequent histological damage to the intestinal epithelium, together with uranium precipitates in the epithelial cells, supported the assumption that uranium has direct effects on the digestive tract. We were able to model the data in all generations and showed that sensitivity increased from one generation to the next, in particular through a significant increase of the intensity of effect, once the threshold for appearance of effects was exceeded.

International audience; In food safety, sound risk characterisation requires the integration of external dose (oral exposure), internal dose (toxicokinetics (TK) and toxicodynamic (TD) data. Here, a workflow allowing such integration is presented and illustrated with examples from the human health, animal health and ecological area. Since its creation in 2002, the European Food Safety Authority (EFSA) has performed risk assessments for more than 5000 chemicals. An open source database: OpenFoodTox, designed using OECD harmonised templates, and providing summary toxicological data used by EFSA for setting safe levels (reference points and reference values) of food and feed chemicals in humans, animals and the environment has been recently published. OpenFoodTox is available in a. EFSA's Data Warehouse as a microstrategy tool, b. EFSA's knowledge junction for full download, c. The OECD e-chem portal. Since 2014, EFSA has funded collaborative research to develop generic TK and PB-TK models in the R freeware available on an open source modelling platform: TK Plate, to support integration of exposure, TK and TD parameters under different situations (data poor, data rich). Several models have been developed including TK and PB-TK models in humans, farm and companion animals (pig, chicken, cat, sheep), fish (zebra fish, rainbow trout, fathead minnow) and Dynamic Energy Budget (DEB) models for terrestrial and aquatic organisms. The first prototype of TKPlate has been designed for human TK and PB-PK models using the US-EPA ‘httk’ package and includes variability distributions for human metabolism. Future developments of OpenFoodTox 2.0 and TK Plate include: 1. Data collection for physico-chemical properties, TK, biodegradation and bioaccumulation data, exposure data, 2. Integration of QSAR tools to predict TK and TD properties, 3. Integration of all models in TKplate for all species, 4. Development of a guidance document to illustrate the global use of TK and metabolism data in chemical risk assessment with case studies (e.g. regulated products and contaminants). In conclusion, the importance of international cooperation is emphasised, in particular between national, international scientific advisory bodies and academic institutions as the corner stone for the translation of 21st century toxicology into harmonised methodologies and tools and for the training of the next generation of risk assessors.

Physiologically based pharmacokinetic (PBPK) models have proven to be successful in integrating and evaluating the influence of age- or gender-dependent changes with respect to the pharmacokinetics of xenobiotics throughout entire lifetimes. Nevertheless, for an effective application of toxicokinetic modelling to chemical risk assessment, a PBPK model has to be detailed enough to include all the multiple tissues that could be targeted by the various xenobiotics present in the environment. For this reason, we developed a PBPK model based on a detailed compartmentalization of the human body and parameterized with new relationships describing the time evolution of physiological and anatomical parameters. To take into account the impact of human variability on the predicted toxicokinetics, we defined probability distributions for key parameters related to the xenobiotics absorption, distribution, metabolism and excretion. The model predictability was evaluated by a direct comparison between computational predictions and experimental data for the internal concentrations of two chemicals (1,3-butadiene and 2,3,7,8-tetrachlorodibenzo-p-dioxin). A good agreement between predictions and observed data was achieved for different scenarios of exposure (e.g., acute or chronic exposure and different populations). Our results support that the general stochastic PBPK model can be a valuable computational support in the area of chemical risk analysis.

International audience; Assessing the evolutionary responses of long-term exposed populations requires multigeneration ecotoxicity tests. However, the analysis of the data from these tests is not straightforward. Mechanistic models allow the in-depth analysis of the variation of physiological traits over many generations, by quantifying the trend of the physiological and toxicological parameters of the model. In the present study, a bioenergetic mechanistic model has been used to assess the evolution of two populations of the nematode Caenorhabditis elegans in control conditions or exposed to uranium. This evolutionary pressure resulted in a brood size reduction of 60%. We showed an adaptation of individuals of both populations to experimental conditions (increase of maximal length, decrease of growth rate, decrease of brood size, and decrease of the elimination rate). In addition, differential evolution was also highlighted between the two populations once the maternal effects had been diminished after several generations. Thus, individuals that were greater in maximal length, but with apparently a greater sensitivity to uranium were selected in the uranium population. In this study, we showed that this bioenergetics mechanistic modeling approach provided a precise, certain, and powerful analysis of the life strategy of C. elegans populations exposed to heavy metals resulting in an evolutionary pressure across successive generations.

International audience; The ban of animal testing has enhanced the development of new in vitro technologies for cosmetics safety assessment. Impedance metrics is one such technology which enables monitoring of cell viability in real time. However, analyzing real time data requires moving from static to dynamic toxicity assessment. In the present study, we built mechanistic biokinetic/toxicodynamic (BK/TD) models to analyze the time course of cell viability in cytotoxicity assay using impedance. These models account for the fate of the tested compounds during the assay. BK/TD models were applied to analyze HepaRG cell viability, after single (48h) and repeated (4 weeks) exposures to three hepatotoxic compounds (coumarin, isoeugenol and benzophenone-2). The BK/TD models properly fit the data used for their calibration that was obtained for single or repeated exposure. Only for one out of the three compounds, the models calibrated with a single exposure were able to predict repeated exposure data. We therefore recommend the use of long-term exposure in vitro data in order to adequately account for chronic hepatotoxic effects. The models we propose here are capable of being coupled with human biokinetic models in order to relate dose exposure and human hepatotoxicity.

Titanium dioxide (TiO2) nanoparticles are used in many applications. Due to their small size, easy body penetration and toxicological adverse effects have been suspected. Numerous studies have tried to characterize TiO2 translocation after oral, dermal or respiratory exposure. In this study, we focused on TiO2 nanoparticle biodistribution, clearance and toxicological effects after intravenous injection, considering TiO2 translocation in the blood occurs. Using ICP-OES, transmission electron microscopy, and histological methods, we found TiO2 accumulation in liver, lungs and spleen. We estimated TiO2 nanoparticles’ half life in the body to about 10 days. Clinical biomarkers were also quantified for 56 days to identify potential toxicological impact on lungs, blood, liver, spleen and kidneys. Results showed absence of toxicological effects after TiO2 intravenous injection at concentrations of 7.7 to 9.4 mg/kg.

International audience

The circulating endogenous steroids are transported in the bloodstream. These are bound to a highly specific sex hormone-binding globulin (SHBG) and in lower affinity to proteins such as the corticosteroid-binding protein and albumin in vertebrates, including fish. It is generally believed that the glycoprotein SHBG protects these steroids from rapid metabolic degradation and thus intervenes in its availability at the target tissues. Endocrine disrupters binding to SHBG affect the normal activity of natural steroids. Since xenobiotics are primarily released in the aquatic environment, there is a need to evaluate the binding affinity of xenosteroid mimics on fish SHBG, especially in zebrafish (Danio rerio), a small freshwater fish originating in India and widely employed in ecotoxicology, toxicology, and genetics. In this context, a zebrafish SHBG (zfSHBG) homology model was developed using the human SHBG (hSHBG) receptor structure as template. It was shown that interactions with amino acids Ser-36, Asp-59 and Thr-54 were important for binding affinity. A ligand-based pharmacophore model was also developed for both zfSHBG and hSHBG inhibitors that differentiated binders from non-binders, but also demonstrated structural requirements for zfSHBG and hSHBG ligands. The study provides insights into the mechanism of action of endocrine disruptors in zebrafish as well as providing a useful tool for identifying anthropogenic compounds inhibiting zfSHBG.

The assessment of toxic effects at biologically and ecologically relevant scales is an important challenge in ecosystem protection. Indeed, stressors may impact populations at much longer term than the usual timescale of toxicity tests. It is therefore important to study the evolutionary response of a population under chronic stress. We performed a 16-generation study to assess the evolution of two populations of the ubiquitous nematode Caenorhabditis elegans in control conditions or exposed to 1.1 mM of uranium. Several generations were selected to assess growth, reproduction, survival, and dose-responses relationships, through exposure to a range of concentrations (from 0 to 1.2 mM U) with all endpoints measured daily. Our experiment showed an adaptation of individuals to experimental conditions (increase of maximal length and decrease of fecundity) for both populations. We also observed an increase of adverse effects (reduction of growth and fertility) as a function of uranium concentration. We pointed out the emergence of population differentiation for reproduction traits. In contrast, no differentiation was observed on growth traits. Our results confirm the importance of assessing environmental risk related to pollutant through multi-generational studies.