DEB(tox) models - Can we predict under different environmental conditions?

Conference paperPoster
Benoit Goussen, Cecilie Rendal, Emma Butler, Roman Ashauer, Oliver R. Price
SETAC Brussels 2017. Brussels, Belgium
Publication year: 2017

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

Conference paperPlatform
Benoit Goussen, Emma Butler, Antonio Franco, Stuart Marshall, Oliver R. Price, Cecilie Rendal, Roman Ashauer
SETAC Brussels 2017. Brussels, Belgium
Publication year: 2017

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

Journal paper
Morgan Dutilleul, Denis Réale, Benoit Goussen, Catherine Lecomte, Simon Galas, Jean‐Marc Bonzom
Evolutionary Applications, DOI 10.1111/eva.12510
Publication year: 2017

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

Conference paperPlatform
Sandrine Charles, Carlo Albert, Benoit Goussen, Tjalling Jager, Soeren Vogel, Roman Ashauer
SETAC Nantes 2016. Nantes, France
Publication year: 2016

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

Journal paper
Roman Ashauer, Carlo Albert, Starrlight Augustine, Nina Cedergreen, Sandrine Charles, Virginie Ducrot, Andreas Focks, Faten Gabsi, André Gergs, Benoit Goussen, Tjalling Jager, Nynke I. Kramer, Anna-Maija Nyman, Veronique Poulsen, Stefan Reichenberger, Ralf B. Schäfer, Paul J. Van den Brink, Karin Veltman, Sören Vogel, Elke I. Zimmer, Thomas G. Preuss
Scientific Reports 6:29178. DOI 10.1038/srep29178
Publication year: 2016

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.

Supporting information

Integrated presentation of ecological risk from multiple stressors

Journal paper
Benoit Goussen , Oliver R. Price, Cecilie Rendal, Roman Ashauer
Scientific Reports 6:36004. DOI 10.1038/srep36004
Publication year: 2016

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

Conference paperPlatform
Benoit Goussen, Cécilie Rendal, Antonio Franco, Oliver R. Price, Roman Ashauer
SETAC Nantes 2016. Nantes, France.
Publication year: 2016

Presenting author: Benoit Goussen

Abstract:

The lack of ecological realism is widely recognised as a limitation in current prospective chemical risk assessment, as is the failure of making variability explicit and transparent. The integration of ecological scenarios with chemical effect models to achieve quantitative ERA promises to increase ecological relevance. Probabilistic environmental risk assessment (PERA) has been suggested as a way to account for spatial, temporal, and environmental variability. Probabilistic plots area new way of presenting ecotoxicological data whilst accounting also for ecologically relevant parameters. They provide an indication of the maximum population-relevant impact of an effect of interest (e.g. biomass reduction) and the prevalence of this impact. Essentially they answer two related questions: How strong is the effect? In how many locations will we see the effect? We discuss some of the challenges and opportunities involved in bringing these new concepts into everyday risk assessment for down-the-drain chemicals. One of the key questions revolves around understanding the protection goal for anthropogenic stressors in specific ecological scenarios, and indeed whether certain scenarios require specific modified protection goals. Once the specific protection goal has been established, a metric to suit both the specific ecological scenario and protection goal needs to be defined and agreed. The selection of this endpoint must be carefully considered as different options will lead to different interpretation. We present a framework to integrate probabilistic approaches with mechanistic effect models to assess variable chemical and environmental scenarios. We present a hypothetical case study risk assessment for an ingredient used universally in all laundry products across Europe and illustrate the potential benefits of the framework. To do so, we use an individual based model integrating a dynamic energy budget model to assess the potential impact of chemicals associated with local environmental characteristics. We then map the outcomes based on probabilistic plots and on potential policy makers’ decisions of the maximal ecologically acceptable impact and the maximal prevalence of this impact. This new framework has the potential to better present ecologically relevant risk by using integrated biological endpoints and to aid more transparent risk communication.

A DEB analysis of responses to baseline toxicant in C. dubia and D. magna

Conference paperPoster
Benoit Goussen, Cecilie Rendal, Emma Butler, Jayne Roberts, Oliver R. Price, Antonio Franco, Todd Gouin, Geoff Hodges, Tjalling Jager
SETAC Nantes 2016. Nantes, France.
Publication year: 2016

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

Journal paper
Benoit Goussen, Alexandre R.R. Péry, Jean-Marc Bonzom, Rémy Beaudouin
Environmental Science & Technology 49(20):12500–12508. DOI 10.1021/acs.est.5b03405
Publication year: 2015

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

Conference paperPoster
Benoit Goussen, Cécilie Rendal, Antonio Franco, Oliver R. Price, Roman Ashauer
Salt Lake City 2015. Salt Lake City, UT, USA
Publication year: 2015

Presenting author: Oliver R. Price

Abstract:

Ecological relevance is increasingly recognised as an important challenge for environmental risk assessment (ERA). The integration of ecological scenarios with chemical effect models to achieve quantitative ERA promises to increase ecological relevance of ERA. We discuss some of the challenges and opportunities involved in bringing these new concepts into everyday risk assessment for down-the-drain chemicals. One of the key questions revolves around understanding the protection goal for anthropogenic stressors in specific ecological scenarios, and
indeed whether certain scenarios require specific modified protection goals. Once the specific protection goal has been established, a metric to suit both the specific ecological scenario and protection goal needs to be defined and agreed. The selection of this endpoint must be carefully considered as different options will lead to different interpretation. Population-level models linked with mechanistically based bioenergetics models are potential powerful tools for ecologically relevant ERA because they provide a quantitative link between chemical effects and ecological factors. However, the practical use and communication of ecological model predictions for decision making may not always be straight forward. Probabilistic environmental risk assessment (PERA) has been suggested as a way to make uncertainty more explicit and to account for biological, spatial and temporal variability. The outcome of a PERA is typically a measure of expected risk with an associated uncertainty interval. We present how probabilistic approaches and advancements in population modeling can be linked to incorporate more ecological relevance into risk assessments while keeping both uncertainty and variability explicit and transparent. To do so, we use an individual based model integrating a dynamic energy budget model to assess the potential impact of chemicals associated with local environmental characteristics. This mechanistic model must be applicable to multiple types of stress,
both anthropogenic (e.g., chemicals, wastewater plant effluents) and environmental (e.g., temperature, predation, starvation, competition). We also discuss how the magnitude of an adverse event will impact the level of risk we are willing to accept and argue that the relation between the level of acceptable risk and the severity of the effect should be made explicit to facilitate decision-making.

Pollution breaks down genetic architecture of life history traits in Caenorhabditis elegans

Journal paper
Morgan Dutilleul, Benoit Goussen, Jean-Marc Bonzom, Simon Galas, Denis Réale
Plos One 10(2):e0116214 DOI 10.1371/journal.pone.0116214
Publication year: 2015

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

Journal paper
Benoit Goussen, Rémy Beaudouin, Morgan Dutilleul, Adeline Buisset-Goussen, Jean-Marc Bonzom, Alexandre R.R. Péry
Chemosphere 120:507-514. DOI 10.1016/j.chemosphere.2014.09.006
Publication year: 2015

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?

Conference paperPoster
Cecilie Rendal, Benoit Goussen, Oliver R. Price, Jayne Roberts, Emma Butler, Roman Ashauer
SETAC Barcelona 2015. Barcelona, Spain.
Publication year: 2015
 Presenting authors: Cecilie Rendal & Benoit Goussen
Abstract:
Population-level models are increasingly recognised as potentially powerful tools in environmental risk assessment. However, the practical application of dynamic population predictions for decision making is not straight forward in everyday risk assessment of down-the-drain chemicals. Probabilistic environmental risk assessment (PERA) has been suggested as a way to make uncertainty more explicit and to account for spatial and temporal variability. The outcome of a PERA is typically a measure of expected risk with an associated uncertainty interval. We present a conceptual framework that explores how probabilistic approaches can be applied in population models to incorporate more ecological relevance into risk assessments while keeping both uncertainty and variability explicit and transparent. One of the key challenges is understanding the protection goals for ecological scenarios exposed to anthropogenic stressors. For instance, systems that are already impaired by high volume emissions of untreated wastewater may require modified protection goals (e.g. protection of microbial purification processes and recovery of food web structure and diversity). For higher organisms, the protection goals must be reflected by a defined set of endpoint metrics that can quantify changes in population-level dynamics. These metrics must be carefully selected based on both the specific scenario and protection goal, as different options will lead to very different interpretations of effect. Finally we discuss the importance of making the relation between the willingness to accept risk and the severity of the effect explicit to facilitate decision-making. We consider these discussions a necessary first step in bringing the full potential of population-level models into risk assessment of down-the-drain chemicals.

An Individual-Based Model of Zebrafish Population Dynamics Accounting for Energy Dynamics

Journal paper
Rémy Beaudouin , Benoit Goussen, Benjamin Piccini, Starrlight Augustine, James Devillers, François Brion, Alexandre R. R. Péry
PloS ONE 10(5): e0125841. DOI 10.1371/journal.pone.0125841
Publication year: 2015

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

Journal paper
Morgan Dutilleul, Jean-Marc Bonzom, Catherine Lecomte, Benoit Goussen, Fabrice Daian, Simon Galas, Denis Réale
BMC Evolutionary Biology 14:252 DOI 10.1186/s12862-014-0252-6
Publication year: 2014

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

Conference paperPlatform
Adeline Buisset-Goussen, Benoit Goussen, Claire Della-Vedova, Simon Galas, Christelle Adam-Guillermin, Catherine Lecomte-Pradines
SETAC Basel 2014. Basel, Switzerland.
Publication year: 2014

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

Effects of chronic gamma irradiation: a multigenerational study using Caenorhabditis elegans

Journal paper
Adeline Buisset-Goussen, Benoit Goussen, Claire Della-Vedova, Simon Galas, Christelle Adam-Guillermin, Catherine Lecomte-Pradines
Journal of Environmental Radioactivity 127:190-197. DOI 10.1016/j.jenvrad.2014.07.014
Publication year: 2014

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.

Un modèle mathématique pour mieux comprendre l’impact des polluants sur la dynamique évolutive des populations

Conference paperPlatform
Benoit Goussen, Rémy Beaudouin, Victor Dias, Jean-Marc Bonzom, Alexandre R.R. Péry
Association pour la Recherche en Toxicologie (ARET). Paris, France.
Publication year: 2013

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

Conference paperPlatform
Benoit Goussen, Rémy Beaudouin, Florient Parisot, Morgan Dutilleul, Adeline Buisset-Goussen, Jean-Marc Bonzom, Alexandre R.R. Péry
SETAC Glasgow. Glasgow, UK.
Publication year: 2013

Presenting author: Benoit Goussen

Consequences on Caenorhabditis elegans life parameters and sensitivity of multi-generation exposure to uranium

Journal paper
Benoit Goussen, Florian Parisot, Rémy Beaudouin, Morgan Dutilleul, Adeline Buisset-Goussen, Alexandre R. R. Péry, Jean-Marc Bonzom
Ecotoxicology 22(5):869-878. DOI 10.1007/s10646-013-1078-5
Publication year: 2013

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

Ph.D. thesisReport
Benoit Goussen
Institut des Sciences et Industries du Vivant et de l’Environnement (AgroParisTech). Doctorat ParisTech. Ph.D. Thesis
Publication year: 2013

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

Conference paperPoster
Florian Parisot, Jean-Marc Bonzom, Benoit Goussen
Société d’écotoxicologie fondamentale et appliquée (SEFA). Lyon, France.
Publication year: 2012

Presenting author: Florian Parisot

Evolutionary changes in life history traits in a Caenorhabditis elegans population exposed to pollutants

Conference paperPlatform
Morgan Dutilleul, Jean-Marc Bonzom, Benoit Goussen, Simon Galas, Denis Réale
Evolution 2012. Ottawa, Ontario, Canada.
Publication year: 2012

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

Conference paperPlatform
Benoit Goussen, Florian Parisot, Alexandre R.R. Péry, Rémy Beaudouin, Adeline Buisset, Morgan Dutilleul, Catherine Lecomte, Jean-Marc Bonzom
Société d’écotoxicologie fondamentale et appliquée (SEFA). Lyon, France.
Publication year: 2012

Presenting author: Benoit Goussen

Evaluating effects of pollution on Caenorhabditis elegans’ population dynamic through a bio-energetic approach

Conference paperPoster
Benoit Goussen, Florian Parisot, Alexandre R.R. Péry, Rémy Beaudouin, Adeline Buisset, Morgan Dutilleul, Catherine Lecomte, Jean-Marc Bonzom
SETAC Berlin 2012. Berlin, Germany
Publication year: 2012

Presenting author: Benoit Goussen

Poster spotlight

S’adapter, mais à quel coût ? Une étude expérimentale chez C. elegans

Conference paperPlatform
Morgan Dutilleul, Denis Réale, Catherine Lecomte, Benoit Goussen, Simon Galas, Jean-Marc Bonzom
33ème Réunion annuelle du Groupe d’Etude de Biologie et Génétique des Populations. Toulouse, France.
Publication year: 2011

Presenting author: Morgan Dutilleul

Intégration d’un modèle bioénergétique dans un modèle de dynamique adaptative: une population de Caenorhabditis elegans soumise à divers stress anthropiques

Conference paperPoster
Benoit Goussen, Alexandre R.R. Péry, Rémy Beaudouin, Morgan Dutilleul, Catherine Lecomte, Jean-Marc Bonzom
33ème Réunion annuelle du Groupe d’Etude de Biologie et Génétique des Populations. Toulouse, France.
Publication year: 2011

Presenting author: Benoit Goussen

Integrating the Dynamic Energy Budget theory in an adaptive dynamic model for a better evaluation of the ecological risks

Conference paperPoster
Benoit Goussen, Alexandre R.R. Péry, Rémy Beaudouin, Morgan Dutilleul, Catherine Lecomte, Jean-Marc Bonzom
Models in Evolutionary Ecology. Montpellier, France
Publication year: 2011

Presenting author: Benoit Goussen

Integrating the DEB theory in an adaptive dynamic model for a better evaluation of the ecological risks: using of C. elegans as a model organism

Conference paperPoster
Benoit Goussen, Alexandre R.R. Péry, Rémy Beaudouin, Morgan Dutilleul, Catherine Lecomte, Jean-Marc Bonzom
DEB Symposium 2011. Lisboa, Portugal.
Publication year: 2011

Presenting author: Benoit Goussen

Analysis of multi-generation data for Chironomus riparius exposed to uranium-spiked sediments using a DEB-based population dynamics model

Conference paperPlatform
Rémy Beaudouin, Victor Dias, Benoit Goussen, Alexandre R.R. Péry, Jean-Marc Bonzom
DEB Symposium 2011. Lisboa, Portugal.
Publication year: 2011

Presenting author: Benoit Goussen