Benoit Goussen
Ecotoxicological modeller
Publications
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Considerations for using reproduction data in toxicokinetic–toxicodynamic modeling
Abstract
Toxicokinetic–toxicodynamic (TKTD) modeling is essential to make sense of the time dependence of toxic effects, and to interpret and predict consequences of time-varying exposure. These advantages have been recognized in the regulatory arena, especially for environmental risk assessment of pesticides, where time-varying exposure is the norm. We critically evaluate the link between the modeled variables in TKTD models and the observations from laboratory ecotoxicity tests. For the endpoint reproduction, this link is far from trivial. The relevant TKTD models for sublethal effects are based on dynamic energy budget (DEB) theory, which specifies a continuous investment flux into reproduction. In contrast, experimental tests score egg or offspring release by the mother. The link between model and data is particularly troublesome when a species reproduces in discrete clutches and, even more so, when eggs are incubated in the mother’s brood pouch (and release of neonates is scored in the test). This situation is quite common among aquatic invertebrates (e.g., cladocerans, amphipods, mysids), including many popular test species. In this discussion paper, we treat these and other issues with reproduction data, reflect on their potential impact on DEB-TKTD analysis, and provide preliminary recommendations to correct them. Both modelers and users of model results need to be aware of these complications, as ignoring them could easily lead to unnecessary failure of DEB-TKTD models during calibration, or when validating them against independent data for other exposure scenarios. Integr Environ Assess Manag 2022;18:479–487. © 2021 SETAC
BeeGUTS—A Toxicokinetic–Toxicodynamic Model for the Interpretation and Integration of Acute and Chronic Honey Bee Tests
Abstract
Understanding the survival of honey bees after pesticide exposure is key for environmental risk assessment. Currently, effects on adult honey bees are assessed by Organisation for Economic Co-operation and Development standardized guidelines, such as the acute and chronic oral exposure and acute contact exposure tests. The three different tests are interpreted individually, without consideration that the same compound is investigated in the same species, which should allow for an integrative assessment. In the present study we developed, calibrated, and validated a toxicokinetic–toxicodynamic model with 17 existing data sets on acute and chronic effects for honey bees. The model is based on the generalized unified threshold model for survival (GUTS), which is able to integrate the different exposure regimes, taking into account the physiology of the honey bee: the BeeGUTS model. The model is able to accurately describe the effects over time for all three exposure routes combined within one consistent framework. The model can also be used as a validity check for toxicity values used in honey bee risk assessment and to conduct effect assessments for real-life exposure scenarios. This new integrative approach, moving from single-point estimates of toxicity and exposure to a holistic link between exposure and effect, will allow for a higher confidence of honey bee toxicity assessment in the future. Environ Toxicol Chem 2022;00:1–9. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
Bioenergetics modelling to analyse and predict the joint effects of multiple stressors: Meta-analysis and model corroboration
Abstract
Understanding the consequences of the combined effects of multiple stressors—including stress from man-made chemicals—is important for conservation management, the ecological risk assessment of chemicals, and many other ecological applications. Our current ability to predict and analyse the joint effects of multiple stressors is insufficient to make the prospective risk assessment of chemicals more ecologically relevant because we lack a full understanding of how organisms respond to stress factors alone and in combination. Here, we describe a Dynamic Energy Budget (DEB) based bioenergetics model that predicts the potential effects of single or multiple natural and chemical stressors on life history traits. We demonstrate the plausibility of the model using a meta-analysis of 128 existing studies on freshwater invertebrates. We then validate our model by comparing its predictions for a combination of three stressors (i.e. chemical, temperature, and food availability) with new, independent experimental data on life history traits in the daphnid Ceriodaphnia dubia. We found that the model predictions are in agreement with observed growth curves and reproductive traits. To the best of our knowledge, this is the first time that the combined effects of three stress factors on life history traits observed in laboratory studies have been predicted successfully in invertebrates. We suggest that a re-analysis of existing studies on multiple stressors within the modelling framework outlined here will provide a robust null model for identifying stressor interactions, and expect that a better understanding of the underlying mechanisms will arise from these new analyses. Bioenergetics modelling could be applied more broadly to support environmental management decision making.
Modelling historical mesocosm data: Application of a fish bioenergetics model in semi-natural conditions
Abstract:
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.
DEB(tox) models - Can we predict under different environmental conditions?
Abstract:
The lack of ecological realism in current prospective environmental risk assessment is widely recognised as a limitation in this field. As organisms are living in a multistressed environment, involving both chemical and environmental stressors, it is worth understanding how these combined stressors will affect the organisms and subsequently the populations. A way forward to include more ecological relevance in ERAs is the use of environmental scenarios that will represent key differences in environmental factors such as the food availability, the temperature variability, the predation, etc. and in exposure factors.
All these factors will influence the capability of an organism to grow and reproduce as well as its resilience to additional stressors. As growth and reproduction are driven by an organisms’ energy balance, Dynamic Energy Budget models are particularly well suited to integrate toxicant and environmental stressors. Indeed, the DEB theory analyses the fluxes of energy within an organism, how stressors can impact these fluxes, and how this will affect the organism’s life history traits.
In this project, we assessed how DEB modelling can predict effects of various chemicals in variable environmental conditions. To do so, we produced two set of data for each chemical. In the first one, Ceriodaphnia dubia individuals fed ad-libitum and were maintained at reference temperature (25°C). In the second set of data, C. dubia individuals were maintained at a different temperature and feeding regime. For the purpose of this exercise, this second set of data was not disclosed to the team in charge of the DEB modelling.
We used the first set of data only to calibrate the DEB model for C. dubia. Then knowing only the experimental conditions of the second set, we performed a blinded prediction of the growth, reproduction, and survival of C. dubia under environmental conditions that have not been used for the calibration. Blinded predictions and datasets were then compared and the ability of the DEB model to handle and accurately predict non-tested environmental conditions (temperature and feeding level) was analysed and discussed.
Combined environmental and chemical stress: impact on bioenergetic fluxes
Abstract:
The lack of ecological realism in current prospective environmental risk assessment (ERA) is widely recognised as a limitation in this field. Since organisms live in a multistressed environment, involving both chemical and environmental stressors, it is important to understand how these combined stressors can affect individuals and subsequently their populations. One way of including more ecological relevance in ERAs is the use of environmental scenarios that represent variation in environmental factors such as food, temperature, predation, competition and in factors that influence exposure.
All these factors will influence the capability of an organism to grow and reproduce as well as its resilience to additional stressors. Since growth and reproduction are driven by an organisms’ energy balance, Dynamic Energy Budget models are particularly well suited to integrate toxicant and environmental stressors. Indeed, the DEB theory analyses the fluxes of energy within an individual, how stressors can impact these fluxes, and how this will affect the organism’s life history traits. This mechanistic description of an individual can then be used as a building block for a population model.
In this project, we performed a meta-analysis of the literature in order to analyse the effects of combinations of ecological and chemical stressors on individuals. We then used this analysis to derive quantitative relationships that describe the effects on their bioenergetic fluxes. We analysed how these stressor combinations affected the life-history traits of the organisms and their ability to cope.
We assessed the implementation of these patterns using a DEB based model for Ceriodaphnia dubia. Using the derived quantitative relationships, we predicted the effects of mixtures of environmental and/or chemical stressors on the growth, the reproduction and the survival of individuals. This mechanistic description of the organisms can then be used as a building block in order to assess the effects of these mixtures on a higher level of organisation, through a population model for instance. The accuracy of our predictions was evaluated by comparison with experimental data.
The resulting models will have the potential to account for the effect of chemicals on individuals and populations in different environmental scenarios
Adaptation costs to constant and alternating polluted environments
Abstract:
Some populations quickly adapt to strong and novel selection pressures caused by anthropogenic stressors. However, this short-term evolutionary response to novel and harsh environmental conditions may lead to adaptation costs, and evaluating these costs is important if we want to understand the evolution of resistance to anthropogenic stressors. In this experimental evolution study, we exposed Caenorhabditis elegans populations to uranium (U populations), salt (NaCl populations), alternating uranium/salt treatments (U/NaCl populations), and to a control environment (C populations), over 22 generations. In parallel, we ran common-garden and reciprocal-transplant experiments to assess the adaptive costs for populations that have evolved in the different environmental conditions. Our results showed rapid evolutionary changes in life history characteristics of populations exposed to the different pollution regimes. Furthermore, adaptive costs depended on the type of pollutant: pollution-adapted populations had lower fitness than C populations, when the populations were returned to their original environment. Fitness in uranium environments was lower for NaCl populations than for U populations. In contrast, fitness in salt environments was similar between U and NaCl populations. Moreover, fitness of U/NaCl populations showed similar or higher fitness in both the uranium and the salt environments compared to populations adapted to constant uranium or salt environments. Our results show that adaptive evolution to a particular stressor, can lead to either adaptive costs or benefits once in contact with another stressor. Furthermore, we did not find any evidence that adaptation to alternating stressors was associated with additional adaption costs. This study highlights the need to incorporate adaptive cost assessments when undertaking ecological risk assessments of pollutants.
Optimizing experimental design for calibration of GUTS model
Presenting author: Sandrine Charles
Abstract:
The General Unified Threshold model of Survival (GUTS) provides a theoretical framework for analysing stressor effects on survival over time through consistent model equations based on different assumptions about the stressor quantification, the compensatory processes and the nature of the death process. In ecotoxicology, stressors are toxicants characterised by a dose metric, e.g. the concentration in the medium surrounding an organism or inside the organism, or by the damage quantity they cause. The key GUTS feature is that mortality is estimated when the dose metric exceeds a certain threshold. Several GUTS flavours can be derived according to the assumption underlying the death process: (i) the threshold is distributed within a population, and when exceeded, the individual dies (individual tolerance, IT); (ii) there is one common threshold for all individuals, and when exceeded, the probability to die increases (stochastic death, SD); (iii) a unification of both previous assumptions (GUTS proper). While more realistic, GUTS proper requires the estimation of one additional parameter. Because environmental risk assessment of chemicals depends on robust estimates of GUTS parameters, we investigated parameter identification for GUTS proper, in relation to the experimental design of ‘short-term’ laboratory bioassays. In practice, standard survival datasets generally do not contain enough information to estimate all parameters of GUTS proper with sufficient precision. This is because a large number of individuals is required to provide strong information on probabilistic events. Hence, based on simulated datasets we identify appropriate experimental designs suitable to estimate all parameters of GUTS proper with the best possible precision. We show that datasets with a high number of animals per treatment allow for parameter estimation of GUTS proper with reasonable accuracy and precision. Moreover, increasing the number of animals or the duration of the experiment substantially reduce the uncertainty around the median value of the threshold. Nevertheless, general statements about optimisation for any chemical, any species, any test duration and/or any exposure concentration profile remain difficult. As take-home message, to the extent possible, we recommend not to use fixed experimental set-up for GUTS analyses, but rather tailor dedicated designs according to the chemical, the species and/or the research/regulatory question at hand.
Modelling survival: exposure pattern, species sensitivity and uncertainty
Abstract:
The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.
Integrated presentation of ecological risk from multiple stressors
Abstract:
Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic
How to map ecological risk assessments of chemicals
Presenting author: Benoit Goussen
Abstract:
A DEB analysis of responses to baseline toxicant in C. dubia and D. magna
Presenting author: Benoit Goussen
Abstract:
Mechanistic effects models are gaining interest in the scientific community and in regulatory settings. These models have the potential to facilitate species extrapolation, thereby decreasing the need for toxicity testing for risk assessment. They also provide an opportunity to quantify the complexities of multiple interacting stressors on environmental scenarios. Dynamic energy budget (DEB) theory represents a unifying framework for assessing the mechanisms that drive toxicant effects on life history traits. We report here on the progress of two case studies for an example chemical tested on two species of Cladocerans, Ceriodaphnia dubia and Daphnia magna. Over 70% of the ingredients in home and personal care products are considered baseline toxicants. We use phenol as a model baseline toxicant. A dynamic energy budget model was calibrated for each species, and differences in parameters and physiological mode of action are discussed. This work also explores how DEB based modelling can incorporate environmental factors such as food availability and temperature into risk assessment. In conclusion, the present study demonstrates the potential utility of DEB based models for species extrapolation and chemical risk assessment in an AOP framework.
Transgenerational Adaptation to Pollution Changes Energy Allocation in Populations of Nematodes
Abstract:
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
Towards ecological relevance in PERA: a DEB-IBM approach
Presenting author: Oliver R. Price
Abstract:
Pollution breaks down genetic architecture of life history traits in Caenorhabditis elegans
Abstract:
When pollution occurs in an environment, populations present suffer numerous negative and immediate effects on their life history traits. Their evolutionary potential to live in a highly stressful environment will depend on the selection pressure strengths and on the genetic structure, the trait heritability, and the genetic correlations between them. If expression of this structure changes in a stressful environment, it becomes necessary to quantify these changes to estimate the evolutionary potential of the population in this new environment. We studied the genetic structure for survival, fecundity, and early and late growth in isogenic lines of a Caenorhabditis elegans population subject to three different environments: a control environment, an environment polluted with uranium, and a high salt concentration environment. We found a heritability decrease in the polluted environments for fecundity and early growth, two traits that were the most heritable in the control environment. The genetic structure of the traits was particularly affected in the uranium polluted environment, probably due to generally low heritability in this environment. This could prevent selection from acting on traits despite the strong selection pressures exerted on them. Moreover, phenotypic traits were more strongly affected in the salt than in the uranium environment and the heritabilities were also lower in the latter environment. Consequently the decrease in heritability was not proportional to the population fitness reduction in the polluted environments. Our results suggest that pollution can alter the genetic structure of a C. elegans population, and thus modify its evolutionary potential.
Energy-based modelling to assess effects of chemicals on Caenorhabditis elegans: A case study on uranium
Abstract:
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.
Can mechanistic effects models coupled with geo-referenced exposure models add ecological relevance to risk assessment?
An Individual-Based Model of Zebrafish Population Dynamics Accounting for Energy Dynamics
Abstract:
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.
Rapid evolutionary responses of life history traits to different experimentally-induced pollutions in Caenorhabditis elegans
Abstract:
Background
Anthropogenic disturbances can lead to intense selection pressures on traits and very rapid evolutionary changes. Evolutionary responses to environmental changes, in turn, reflect changes in the genetic structure of the traits, accompanied by a reduction of evolutionary potential of the populations under selection. Assessing the effects of pollutants on the evolutionary responses and on the genetic structure of populations is thus important to understanding the mechanisms that entail specialization to novel environmental conditions or resistance to novel stressors.
Results
Using an experimental evolution approach we exposed Caenorhabditis elegans populations to uranium, salt and alternating uranium-salt environments over 22 generations. We analyzed the changes in the average values of life history traits and the consequences at the demographic level in these populations. We also estimated the phenotypic and genetic (co)variance structure of these traits at different generations. Compared to populations in salt, populations in uranium showed a reduction of the stability of their trait structure and a higher capacity to respond by acclimation. However, the evolutionary responses of traits were generally lower for uranium compared to salt treatment; and the evolutionary responses to the alternating uranium–salt environment were between those of constant environments. Consequently, at the end of the experiment, the population rate of increase was higher in uranium than in salt and intermediate in the alternating environment.
Conclusions
Our multigenerational experiment confirmed that rapid adaptation to different polluted environments may involve different evolutionary responses resulting in demographic consequences. These changes are partly explained by the effects of the pollutants on the genetic (co)variance structure of traits and the capacity of acclimation to novel conditions. Finally, our results in the alternating environment may confirm the selection of a generalist type in this environment.
Effects of chronic gamma irradiation: a multigenerational study using Caenorhabditis elegans
Abstract:
The effects of chronic exposure to 137Cs gamma radiation (dose rate ranging from 6.6 to 42.7 mGy h−1) on growth and reproductive ability were carried out over three generations of Caenorhabditis elegans (F0, F1, and F2). Exposure began at the egg stage for the first generation and was stopped at the end of laying of third-generation eggs (F2). At the same time, the two subsequent generations from parental exposure were returned to the control conditions (F1’ and F2’). There was no radiation-induced significant effect on growth, hatchability, and cumulative number of larvae within generations. Moreover, no significant differences were found in growth parameters (hatching length, maximal length, and a constant related to growth rate) among the generations. However, a decrease in the cumulative number of larvae across exposed generations was observed between F0 and F2 at the highest dose rate (238.8 ± 15.4 and 171.2 ± 13.1 number of larvae per individual, respectively). Besides, the F1′ generation was found to lay significantly fewer eggs than the F1 generation for tested dose rates 6.6, 8.1, 19.4, and 28.1 mGy h−1. Our results confirmed that reproduction (here, cumulative number of larvae) is the most sensitive endpoint affected by chronic exposure to ionizing radiation. The results obtained revealed transgenerational effects from parental exposure in the second generation, and the second non-exposed generation was indeed more affected than the second exposed generation.
Effects of chronic gamma irradiation: A multigenerational study using Caenorhabditis elegans
Presenting author: Adeline Buisset-Goussen
Abstract:
The assessment of environmental impact of exposure to ionizing radiation (natural and ubiquitous phenomenon enriched by human activities) has become a major concern. However, this environmental risk assessment is currently hampered by the lack of knowledge, and hence, is often based on extrapolation from data obtained for acute exposure. Studies on chronic exposure over several generations are so needed to understand the disturbances related to ionizing radiation and their possible consequences on the population. Regarding this background, we assessed the effects of chronic exposure to ionizing radiation over three generations of the ubiquitous nematode Caenorhabditis elegans. In this study C. elegans were chronically and individually exposed to gamma radiation (dose rates ranging from 6.6 to 42.7 mGy/h). The evolution of growth and reproduction (here, cumulated number of larvae per individual) of individuals were followed daily. Comparisons within and between the generations of C. elegans subjected to different exposure statuses: (i) three generations continuously exposed (F0, F1, and F2) and (ii) parental generation exposed (F0) and the following generations placed in recovery (F1’ and F2’) were performed. Our experiment showed no significant difference in growth between the control and the exposed individuals whatever the generation and the exposed status. However we observed a decrease in the reproductive ability between F0 and F2 at the highest dose rate (42.7 mGy/h). We also observed significant differences in the same generation subjected to different exposure statuses (exposed (F1) or recovery (F1’)). Surprisingly, the non-exposed generation (F1’) laid out less number of eggs than the exposed generation (F1). Our results confirmed that reproduction is the most sensitive endpoint affected by ionizing radiation and revealed transgenerational effects from parental exposure in the second generation (F1’) and the third generation (F2). Using these results on reproduction, molecular and cellular effects of chronic exposure to ionizing radiations on germline are examined to better understand the mechanisms underlying the observed effects
Un modèle mathématique pour mieux comprendre l’impact des polluants sur la dynamique évolutive des populations
Presenting author: Benoit Goussen
Abstract (French):
L’évaluation des effets des polluants à des échelles biologiquement et écologiquement pertinentes est un important problème dans la protection des écosystèmes. En effet, les conséquences à long terme de polluants sur les populations sont très peu étudiées alors que les populations naturelles sont souvent exposées à des polluants de façon chronique sur de nombreuses générations. Dans ce contexte, nous avons élaboré un nouveau modèle de type individu-centré couplé avec un modèle bioénergétique de type Dynamic Energy Budget (DEB) afin d’étudier la dynamique évolutive de populations soumises à des contraintes environnementales. Il s’agit d’une base pertinente pour comprendre et modéliser les liens entre (i) les perturbations liées à l’assimilation et (ii) les fluctuations de croissance et de reproduction chez des individus exposés à des stress anthropiques (e.g. polluant, changements globaux). Ce modèle permet une meilleure évaluation des conséquences potentielles sur les populations sur plusieurs générations.
Afin d’illustrer la pertinence de ce type de modélisation, nous présenterons les résultats obtenus suite à des travaux concernant les effets multi-générationnels d’un métal lourd radioactif, l’uranium, sur deux modèles d’invertébrés (Chironomus riparius et Caenorhabditis elegans).
Par exemple, les résultats obtenus chez C. riparius nous ont permis de modéliser la dynamique des populations au cours des générations et de caractériser les effets de l’uranium sur les populations exposées. Ces résultats montrent que (i) l’uranium conduit à une sélection de phénotypes particuliers via une survie différentielle et (ii) entraîne une augmentation de la tolérance des populations exposées au fil des générations.
En conclusion, l’application de ce type de modèle nous a permis de quantifier et de mieux comprendre les effets d’un stress sur la dynamique d’une population à partir des règles de comportement et de structuration de ses différents éléments (i.e. les individus, avec leurs propres caractéristiques biologiques et toxicologiques).
Evaluating effects of a multi-generation pollution on Caenorhabditis elegans’ population
Presenting author: Benoit Goussen
Consequences on Caenorhabditis elegans life parameters and sensitivity of multi-generation exposure to uranium
Abstract:
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.
Analyse par modélisation mécanistique des réponses microévolutives d’une population de Caenorhabditis elegans exposée à un stress métallique radioactif
Résumé:
L’évaluation des effets toxiques à des échelles pertinentes est un challenge important pour la protection des écosystèmes. En effet, les polluants peuvent impacter les populations sur le long terme et représenter une nouvelle force évolutive qui peut s’ajouter aux autres forces de sélection. Il est par conséquent nécessaire d’acquérir des connaissances sur les changements phénotypiques et génétiques apparaissant dans une population exposée à un stress durant plusieurs générations. En général les études multi-générations sont analysées à partir d’approches purement statistiques. La modélisation mécanistique a le potentiel de comprendre pleinement les effets des polluants sur la dynamique des populations. Ce type de modèle permet d’intégrer des processus biologiques et toxiques à l’analyse de données d’écotoxicologie et d’étudier les interactions entre ces processus. L’objectif de ce doctorat était d’étudier les apports de la modélisation mécanistique, par rapport à une analyse statistique classique, dans l’analyse de données d’évolution expérimentale suite à l’exposition sur le long terme à un contaminant. Pour ce faire, une stratégie en trois temps a été menée. Tout d’abord, une expérience multigénérationnelle a été réalisée sur deux populations de C. elegans (contrôle et exposée à 1,1 mM U) dérivées d’une population ancestrale présentant une forte diversité génétique. Toutes les trois générations, des individus ont été extraits des populations et soumis à une gamme de concentrations en uranium (de 0 à 1,2 mM U). Une première analyse statistique classique a alors été menée. Dans un second temps, un modèle bioénergétique adapté à l’analyse de données d’écotoxicologie (DEBtox) a été mis au point pour C. elegans et son comportement numérique a été analysé. Enfin, ce modèle a été appliqué à l’ensemble des générations étudiées afin d’inférer les valeurs des paramètres pour les deux populations et d’étudier leur évolution. Les résultats obtenus ont mis en évidence un impact de l’uranium à la fois sur la croissance et la reproduction de C. elegans à partir de 0,4 mM U. Les résultats de l’analyse mécanistique indiquent que cet effet est la résultante d’un impact sur l’assimilation d’énergie depuis la nourriture. Les deux approches, tant mécanistique que classique, ont mis en évidence une adaptation des individus des deux populations aux conditions expérimentales. Malgré cela, les analyses ont également mis en évidence une évolution différentielle des individus de la population soumise à l’uranium par rapport à ceux de la population témoin. Ces résultats ont été plus finement décrits par l’analyse mécanistique. Globalement, ce travail contribue à accroître nos connaissances sur les effets des polluants sur la dynamique des populations, et démontre les apports de la modélisation mécanistisque qui pourra être appliquée dans d’autres contextes afin de réaliser in fine une meilleure évaluation des risques écologiques des polluants.
English title:
Mechanistical modelling assessment of microevolutionary responses of Caenorhabditis elegans population submitted to a radioactive heavy metal
Abstract:
The evolution of toxic effects at a relevant scale is an important challenge for the ecosystem protection. Indeed, pollutants may impact populations over long-term and represent a new evolutionary force which can be adding itself to the natural selection forces. Thereby, it is necessary to acquire knowledge on the phenotypics and genetics changes that may appear in populations submitted to stress over several generations. Usually statistical analyses are performed to analyse such multigenerational studies. The use of a mechanistic mathematical model may provide a way to fully understand the impact of pollutants on the populations’ dynamics. Such kind of model allows the integration of biological and toxic processes into the analysis of ecotoxicological data and the assessment of interactions between these processes. The aim of this Ph.D. project was to assess the contributions of the mechanistical modelling to the analysis of evolutionary experiment assessing long-term exposure. To do so, a three step strategy has been developed. Foremost, a multi-generational study was performed 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, and dose-responses relationships, through exposure to a range of concentrations (from 0 to 1.2 mM U) with all endpoints measured daily. A first statistical analysis was then performed. In a second step, a bioenergetic model adapted to the assessment of ecotoxicological data (DEBtox) was developed on C. elegans. Its numerical behaviour was analysed. Finally, this model was applied to all the selected generations in order to infer parameters values for the two populations and to assess their evolutions. Results highlighted an impact of the uranium starting from 0.4 mM U on both C. elegans’ growth and reproduction. Results from the mechanistical analysis indicate this effect is due to an impact on the assimilation of energy from food. Both the mechanistic and the classic approaches highlighted individuals’ adaptation to environmental conditions. Despite this, differential evolutions of the individuals from the uranium-selected population were also highlighted. All these results were more in-depth described by the mechanistical analysis. Overall, this work contributes to our knowledge on the effects of pollutants on population dynamics, and demonstrates the contributions of mechanistical modelling which can be applied in other contexts to achieve in fine a better assessment of environmental risks of pollutants.
Suivi multigénérationnel d’une toxicité chronique : le cas de la reproduction chez Caenorhabditis elegans
Presenting author: Florian Parisot
Evolutionary changes in life history traits in a Caenorhabditis elegans population exposed to pollutants
Presenting author: Morgan Dutilleul
Évaluation des effets de la pollution sur la dynamique de population de Caenorhabditis elegans à travers une approche de type bioénergétique
Presenting author: Benoit Goussen
Evaluating effects of pollution on Caenorhabditis elegans’ population dynamic through a bio-energetic approach
Presenting author: Benoit Goussen
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