Rémy Beaudouin

A physiologically based toxicokinetic model for the zebrafish Danio rerio.

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.

Biodistribution and Clearance of TiO2 Nanoparticles in Rats after Intravenous Injection

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.

Biology-Based Modeling To Analyze Uranium Toxicity Data on Daphnia magna in a Multigeneration Study

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.

Energy-based modelling to assess effects of chemicals on Caenorhabditis elegans: A case study on uranium

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.

Effects of bisphenol A on different trophic levels in a lotic experimental ecosystem

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 μg/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 μg/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 μg/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.

Toxicokinetic models and related tools in environmental risk assessment of chemicals

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.

An individual-based model of zebrafish population dynamics accounting for energy dynamics.

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level.

Individual-based model of Chironomus riparius population dynamics over several generations to explore adaptation following exposure to uranium-spiked sediments

Natural populations are chronically exposed to various pollutants over many generations. It is thus crucial to understand and quantify adaptive dynamics of stressed populations in order to increase the relevance of ecotoxicological risk assessment. However, long-term consequences to population exposure are not much studied yet. The present study investigated evolutionary responses of Chironomus riparius populations exposed to uranium (heavy metal pollutant) and to assess the underlying mechanisms. To fulfil our objective, we produced data with organisms exposed to four relevant concentrations of uranium through eight successive generations. We built an individual-based (IBM) model of C. riparius population dynamics to analyse these data and to test several assumptions about the mechanisms involved in the phenotypic changes. The IBM was based on a dynamic energy budget (DEB) model for C. riparius by Pery et al. (2002). DEB models account mathematically for the acquisition and use of energy to describe and predict growth, maintenance, development and reproduction of living organisms. The IBM accounted for the influence of the test conditions on the observations over eight generations and highlighted some trait evolution such as time to emergence and adult size in control conditions. The model was then used to analyse the exposed population data. Our results showed that exposure to uranium led to a phenotypic selection via a differential survival characterised by longer time to emergence and smaller larval maximal size. As a general conclusion, IBMs based on DEB-based modelling developed to analyse multi-generation experiments are very promising for understanding and quantifying long term selection and tolerance mechanisms in a population under toxic stress.

Improving mesocosm data analysis through individual-based modelling of control population dynamics: a case study with mosquitofish (Gambusia holbrooki)

Experimental ecosystems such as mesocosms have been developed to improve the ecological relevance of ecotoxicity test. However, in mesocosm studies, the number of replicates is limited by practical and financial constraints. In addition, high levels of biological organization are characterized by a high variability of descriptive variables. This variability and the poor number of replicates have been recognized as a major drawback for detecting significant effects of chemicals in mesocosm studies. In this context, a tool able to predict precisely control mesocosms outputs, to which endpoints in mesocosms exposed to chemicals could be compared should constitute a substantial improvement. We evaluated here a solution which consists in stochastic modelling of the control fish populations to assess the probabilistic distributions of population endpoints. An individual-based approach was selected, because it generates realistic fish length distributions and accounts for both individual and environmental sources of variability. This strategy was applied to mosquitofish (Gambusia holbrooki) populations monitored in lentic mesocosms. We chose the number of founders as a so-called “stressor” because subsequent consequences at the population level could be expected. Using this strategy, we were able to detect more significant and biologically relevant perturbations than using classical methods. We conclude that designing an individual-based model is very promising for improving mesocosm data analysis. This methodology is currently being applied to ecotoxicological issues.

Transgenerational Adaptation to Pollution Changes Energy Allocation in Populations of Nematodes.

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.