[Show abstract][Hide abstract] ABSTRACT: Juvenile hormone (JH) plays an important role in honeybee development and the regulation of age-related division of labor. However, honeybees can be exposed to insect growth regulators (IGRs), such as JH analogs developed for insect pest and vector control. Although their side effects as endocrine disruptors on honeybee larval or adult stages have been studied, little is known about the subsequent effects on adults of a sublethal larval exposure. We therefore studied the impact of the JH analog pyriproxyfen on larvae and resulting adults within a colony under semi-field conditions by combining recent laboratory larval tests with chemical analysis and behavioral observations. Oral and chronic larval exposure at cumulative doses of 23 or 57 ng per larva were tested.
Pyriproxyfen-treated bees emerged earlier than control bees and the highest dose led to a significant rate of malformed adults (atrophied wings). Young pyriproxyfen-treated bees were more frequently rejected by nestmates from the colony, inducing a shorter life span. This could be linked to differences in cuticular hydrocarbon (CHC) profiles between control and pyriproxyfen-treated bees. Finally, pyriproxyfen-treated bees exhibited fewer social behaviors (ventilation, brood care, contacts with nestmates or food stocks) than control bees.
Larval exposure to sublethal doses of pyriproxyfen affected several life history traits of the honeybees. Our results especially showed changes in social integration (acceptance by nestmates and social behaviors performance) that could potentially affect population growth and balance of the colony.
PLoS ONE 07/2015; 10(7):e0132985. DOI:10.1371/journal.pone.0132985 · 3.23 Impact Factor
[Show abstract][Hide abstract] 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.
PLoS ONE 05/2015; 10(5-5):e0125841. DOI:10.1371/journal.pone.0125841 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: An attempt was made to derive structure-activity models allowing the prediction of the larvicidal activity of structurally diverse chemicals against mosquitoes. A database of 188 chemicals with their activity on Aedes aegypti larvae was constituted from analysis of original publications. The activity values were expressed in log 1/IC50 (concentration required to produce 50% inhibition of larval development, mmol). All the chemicals were encoded by means of CODESSA and autocorrelation descriptors. Partial least squares analysis, classification and regression tree, random forest and boosting regression tree analyses, Kohonen self-organizing maps, linear artificial neural networks, three-layer perceptrons, radial basis function artificial neural networks and support vector machines with linear, polynomial, radial basis function and sigmoid kernels were tested as statistical tools. Because quantitative models did not give good results, a two-class model was designed. The three-layer perceptron significantly outperformed the other statistical approaches regardless of the threshold value used to split the data into active and inactive compounds. The most interesting configuration included eight autocorrelation descriptors as input neurons and four neurons in the hidden layer. This led to more than 96% of good predictions on both the training set and external test set of 88 and 100 chemicals, respectively. From the overall simulation results, new candidate molecules were proposed which will be shortly synthesized and tested.
SAR and QSAR in environmental research 04/2015; 26(4):1-16. DOI:10.1080/1062936X.2015.1026571 · 1.60 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Human arboviral diseases have emerged or re-emerged in numerous countries worldwide due to a number of factors including the lack of progress in vaccine development, lack of drugs, insecticide resistance in mosquitoes, climate changes, societal behaviours, and economical constraints. Thus, Aedes aegypti is the main vector of the yellow fever and dengue fever flaviviruses and is also responsible for several recent outbreaks of the chikungunya alphavirus. As for the other mosquito species, the A. aegypti control relies heavily on the use of insecticides. However, because of increasing resistance to the different families of insecticides, reduction of Aedes populations is becoming increasingly difficult. Despite the unquestionable utility of insecticides in fighting mosquito populations, there are very few new insecticides developed and commercialized for vector control. This is because the high cost of the discovery of an insecticide is not counterbalanced by the ‘low profitability’ of the vector control market. Fortunately, the use of quantitative structure–activity relationship (QSAR) modelling allows the reduction of time and cost in the discovery of new chemical structures potentially active against mosquitoes. In this context, the goal of the present study was to review all the existing QSAR models on A. aegypti. The homology and pharmacophore models were also reviewed. Specific attention was paid to show the variety of targets investigated in Aedes in relation to the physiology and ecology of the mosquito as well as the diversity of the chemical structures which have been proposed, encompassing man-made and natural substances.
SAR and QSAR in Environmental Research 10/2014; 25(10). DOI:10.1080/1062936X.2014.958291 · 1.60 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The circulating endogenous steroids are transported in the bloodstream. These are bound to a highly specific sex hormone-binding globulin (SHBG) and in lower affinity to proteins such as the corticosteroid-binding protein and albumin in vertebrates, including fish. It is generally believed that the glycoprotein SHBG protects these steroids from rapid metabolic degradation and thus intervenes in its availability at the target tissues. Endocrine disrupters binding to SHBG affect the normal activity of natural steroids. Since xenobiotics are primarily released in the aquatic environment, there is a need to evaluate the binding affinity of xenosteroid mimics on fish SHBG, especially in zebrafish (Danio rerio), a small freshwater fish originating in India and widely employed in ecotoxicology, toxicology, and genetics. In this context, a zebrafish SHBG (zfSHBG) homology model was developed using the human SHBG (hSHBG) receptor structure as template. It was shown that interactions with amino acids Ser-36, Asp-59 and Thr-54 were important for binding affinity. A ligand-based pharmacophore model was also developed for both zfSHBG and hSHBG inhibitors that differentiated binders from non-binders, but also demonstrated structural requirements for zfSHBG and hSHBG ligands. The study provides insights into the mechanism of action of endocrine disruptors in zebrafish as well as providing a useful tool for identifying anthropogenic compounds inhibiting zfSHBG.
SAR and QSAR in Environmental Research 04/2014; 25(5). DOI:10.1080/1062936X.2014.909197 · 1.60 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Zebrafish (Danio rerio) is a widely used model for toxicological studies, in particular those related to investigations on endocrine disruption. The development and regulatory use of in vivo and in vitro tests based on this species can be enhanced by toxicokinetic modeling. For this reason, we propose a physiologically based toxicokinetic (PBTK) model for zebrafish describing the uptake and disposition of organic chemicals. The model is based on literature data on zebrafish, other cyprinidae and other fish families, new experimental physiological information (volumes, lipids and water contents) obtained from zebrafish, and chemical-specific parameters predicted by generic models. The relevance of available models predicting the latter parameters was evaluated with respect to gill uptake and partition coefficients in zebrafish. This evaluation benefited from the fact that the influence of confounding factors such as body weight and temperature on ventilation rate was included in our model. The predictions for six chemicals (65 data points) yielded by our PBTK model were compared to available toxicokinetics data for zebrafish and all of them were within a factor of 5 of the corresponding experimental values. Sensitivity analysis highlighted that the 1-octanol/water partition coefficient, the metabolism rate, and all the parameters that enable the prediction of assimilation efficiency and partitioning of chemicals need to be precisely determined in order to allow an effective toxicokinetic modeling.
[Show abstract][Hide abstract] ABSTRACT: Biodegradation is an important mechanism for eliminating xenobiotics by biotransforming them into simple organic and inorganic products. Faced with the ever growing number of chemicals available on the market, structure-biodegradation relationship (SBR) and quantitative structure-biodegradation relationship (QSBR) models are increasingly used as surrogates of the biodegradation tests. Such models have great potential for a quick and cheap estimation of the biodegradation potential of chemicals. The Estimation Programs Interface (EPI) Suite™ includes different models for predicting the potential aerobic biodegradability of organic substances. They are based on different endpoints, methodologies and/or statistical approaches. Among them, Biowin 5 and 6 appeared the most robust, being derived from the largest biodegradation database with results obtained only from the Ministry of International Trade and Industry (MITI) test. The aim of this study was to assess the predictive performances of these two models from a set of 356 chemicals extracted from notification dossiers including compatible biodegradation data. Another set of molecules with no more than four carbon atoms and substituted by various heteroatoms and/or functional groups was also embodied in the validation exercise. Comparisons were made with the predictions obtained with START (Structural Alerts for Reactivity in Toxtree). Biowin 5 and Biowin 6 gave satisfactorily prediction results except for the prediction of readily degradable chemicals. A consensus model built with Biowin 1 allowed the diminution of this tendency.
SAR and QSAR in environmental research 12/2013; 24(12):979-93. DOI:10.1080/1062936X.2013.848632 · 1.60 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The juvenile hormone esterase (JHE) regulates juvenile hormone titre in insect hemolymph during its larval development. It has been suggested that JHE could be targeted for use in insect control. This enzyme can also be considered as involved in the phenomenon of endocrine disruption by xenobiotics in beneficial insects. Consequently, there is a need to know the characteristics of the molecules able to act on the JHE. Trifluoromethylketones (TFKs) are the most potent JHE inhibitors found to date and different quantitative structure-activity relationships (QSARs) have been derived for this group of chemicals. In this context, a set of 181 TFKs (118 active and 63 inactive compounds), tested on Trichoplusia ni for their JHE inhibition activity and described by physico-chemical descriptors, was split into different training and test sets to derive structure-activity relationship (SAR) models from support vector classification (SVC). A SVC model including 88 descriptors and derived from a Gaussian kernel was selected for its predictive performances. Another model computed only with 13 descriptors was also selected due to its mechanistic interpretability. This study clearly illustrates the difficulty in capturing the essential structural characteristics of the TFKs explaining their JHE inhibitory activity.
SAR and QSAR in environmental research 05/2013; 24(6). DOI:10.1080/1062936X.2013.792499 · 1.60 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Structure-activity relationship (SAR) and quantitative structure-activity relationship (QSAR) models are increasingly used in toxicology, ecotoxicology, and pharmacology for predicting the activity of the molecules from their physicochemical properties and/or their structural characteristics. However, the design of such models has many traps for unwary practitioners. Consequently, the purpose of this chapter is to give a practical guide for the computation of SAR and QSAR models, point out problems that may be encountered, and suggest ways of solving them. Attempts are also made to see how these models can be validated and interpreted.
[Show abstract][Hide abstract] ABSTRACT: Certain chemicals possess the ability of modulating the endocrine systems, associated with reproductive and developmental dysfunctions and abnormal levels of circulating steroids hormones. There have been increasing concerns regarding endocrine disrupting chemicals (EDCs) and their potential harmful effects on humans and wildlife, including fish. Among model species for ecotoxicological investigations, zebrafish is a vertebrate organism extensively used for scientific purposes and an increasing amount of (eco)-toxicological data of EDCs toward zebrafish have been gathered during the past years. The translation of subtle functional deficits within individuals into population-level effects is a challenge for the ecotoxicological risk assessment of EDCs. Mathematical models can provide the framework in which the effects on many endpoints and the cross regulations between these endpoints can be integrated. The aim of MOZAIC project is to develop an integrated modelling framework for zebrafish to assess how EDCs modify the level of hormones in individuals (with inclusion of regulations in the model) and how such disruption will impact individual fitness and population dynamics. To this purpose, we propose to develop and to integrate three models: (i) hypothalamicpituitary- gonadal (HPG) axis model for male and female zebrafish, (ii) Physiologically-based pharmacokinetic (PBPK) models for zebrafish for a panel of EDCs, and (iii) an agent-based model for a relevant description of zebrafish population dynamics and of its perturbation due to exposure to EDCs. Our final goal is to relate hormone levels to effects on reproduction in zebrafish using relevant dose responses. The calibration of the models will be based on available data, on new QSAR models and on new experimental data on the zebrafish reproductive physiology. Experimental data will be acquired to fulfil the two main gaps identified in the literature: variation of sex steroid concentrations during the reproductive cycles in control conditions and when exposed to an EDC. In fine, MOZAIC project will provide an integrated generic (i.e. not restricted to a single chemical) model linking the effects of EDCs at cellular, organism and population levels. This model could be applied to different endocrine disruptor compounds to assess long-term consequences of an endocrine disruption.
[Show abstract][Hide abstract] ABSTRACT: A tight control of juvenile hormone (JH) titre is crucial during the life cycle of a holometabolous insect. JH metabolism is made through the action of enzymes, particularly the juvenile hormone esterase (JHE). Trifluoromethylketones (TFKs) are able to inhibit this enzyme to disrupt the endocrine function of the targeted insect. In this context, a set of 96 TFKs, tested on Trichoplusia ni for their JHE inhibition, was split into a training set (n = 77) and a test set (n = 19) to derive a QSAR model. TFKs were initially described by 42 CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis) descriptors, but a feature selection process allowed us to consider only five descriptors encoding the structural characteristics of the TFKs and their reactivity. A classical and spline regression analysis, a three-layer perceptron, a radial basis function network and a support vector regression were experienced as statistical tools. The best results were obtained with the support vector regression (r(2) and r(test)(2) = 0.91). The model provides information on the structural features and properties responsible for the high JHE inhibition activity of TFKs.
SAR and QSAR in environmental research 03/2012; 23(3-4):357-69. DOI:10.1080/1062936X.2012.664562 · 1.60 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: More than 20 years ago, Ashby and Tennant showed the interest of structural alerts for the prediction of the carcinogenicity of chemicals. These structural alerts are functional groups or structural features of various sizes that are linked to the level of carcinogenicity of chemicals. Since this pioneering work it has been possible to refine the alerts over time, as more experimental results have become available and additional mechanistic insights have been gained. To date, one of the most advanced lists of structural alerts for evaluating the carcinogenic potential of chemicals is the list proposed by Benigni and Bossa and that is implemented as a rule-based system in Toxtree and in the OECD QSAR Application Toolbox. In order to gain insight into the applicability of this system to the detection of potential carcinogens we screened about 200 pesticides and biocides showing a high structural diversity. Prediction results were compared with experimental data retrieved from an extensive bibliographical review. The prediction correctness was only equal to 60.14%. Attempts were made to analyse the sources of mispredictions.
SAR and QSAR in environmental research 03/2011; 22(1-2):89-106. DOI:10.1080/1062936X.2010.548349 · 1.60 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Losses of foraging bees are sometimes attributed to altered flight pattern between a meliferous plant treated with an insecticide and the hive. Only a limited number of studies has investigated the impact of pesticides on homing flight due to the difficulty of measuring the flight time between the food source and the hive. Monitoring the flights of the foraging bees needs their individual identification. The number of bees monitored simultaneously and the time span during which observations can be made limit most of the monitoring techniques. However, techniques of automatic tracking and identification of individuals have the potential to revolutionize the study of the ecotoxicological effects of xenobiotics on the bee behaviors. Radio Frequency Identification (RFID) offer numerous advantages such as an unlimited number of codes, a large number of simultaneous recording, and a quick reading, especially through materials (e.g., wood). The aim of this study was to show how the RFID device can be used to study the effects of pesticides on both the behavioral traits and the lifespan of bees. In this context, we have developed a method under tunnel to automatically record the displacements of foragers individualized with RFID tags and to detect the alteration of the flight pattern between an artificial feeder and the hive. Fipronil was selected as test substance due to the lack of information on the effects of this insecticide on the foraging behavior of free-flying bees. We showed that oral treatment of 0.3 ng of fipronil per bee (LD50/20) reduced the number of foraging trips. The strengths of our approach were briefly discussed.
[Show abstract][Hide abstract] ABSTRACT: Centre de localisation : Centre de Recherche PACA, 84914 AVIGNON CEDEX 9, FRA
Comité de lecture : false
Compléments : Reprise ProdINRA 1 :
Langue du Titre de la monographie : fra
Les auteurs monographiques : INRA - Réseau des Ecotoxicologues de l'INRA Les auteurs monographiques : INRA - Réseau Ecodynamique des Micropolluants
Cote de localisation : 11-Pub39
Date de début de l'événement : 2011-11-07
Date de fin de l'évenement : 2011-11-09
Date de validation : Tue May 29 08:37:05 CEST 2012
Identifiant : 50902
Identifiant mot-clé : 11377, 21013, 2752, 89321, 1352, 1368, 9784, 10152, 2925, 74519, 58636, 42309
Identifiant ProdInra1 : PROD2012c18e4011
Langue du titre : fra
Mot-clé principal : maïs, zea mays, brassica napus var oleifera, semence, apidae, apis mellifera, hymenoptera, insecticide systémique, butineuse, thiamethoxam, comportement, marquage
Pays de l'éditeur : FRA
Pays de l'événement : FRA
Public visé : Scientifique
, The following values have no corresponding Zotero field:
Author Address: [DECOURTYE, Axel] UMT PrADE, UR 406 Abeilles et Environnement, Association de Coordination Technique Agricole, Avignon, FRA
Author Address: [DECOURTYE, Axel; Béguin, Maxime; henry, Mickaël] UMR 0406 UR 0406 Abeilles et Environnement, AVIGNON CEDEX 9, Avignon, France
Author Address: [Béguin, Maxime; Jourdan, Pascal] UMT PrADE, UR 406 Abeilles et Environnement, Association de développement de l'Apiculture Provençale, Avignon, FRA
Author Address: [Odoux, Jean Francois; REQUIER, Fabrice; Aupinel, Pierrick] UE 1255 UE 1255 Unité expérimentale Entomologie, SURGERES, Saint-Pierre-D'Amilly
Author Address: [Brun, François] UMR AGIR, Association de Coordination Technique Agricole, Castanet Tolosan, FRA
Author Address: [Gauthier, Monique] CNRS, CRCA, Université Toulouse 3, Castanet Tolosan, FRA
Author Address: [Devillers, James] Centre de Traitement de l'Information Scientifique, Rillieux-la-Pape, FRA<br/,
Titre des actes : 4ème Séminaire d'Ecotoxicologie de l'INRA
Type de communication avec actes : Résumé
Type d'événement : Séminaire
Unité de localisation : UR 0406 Abeilles et Environnement
4ème Séminaire d’Ecotoxicologie de l’INRA; 01/2011
[Show abstract][Hide abstract] ABSTRACT: The Ames Salmonella typhimurium mutagenicity assay is a short-term bacterial reverse mutation test that was designed to detect mutagens. For several decades, it has been used in research laboratories and by regulatory agencies throughout the world for the detection and characterization of potential mutagens among natural products and man-made chemicals. Faced with the ever-growing number of chemicals available on the market, congeneric and non-congeneric (Q)SAR models have been designed from Ames test results obtained on specific S. typhimurium strains such as TA 100 or TA 98. Such models have great potential for a quick and cheap identification and classification of large numbers of potential chemical mutagens. The OECD QSAR Application Toolbox and Toxtree, which were developed for facilitating the practical use of (Q)SAR approaches in regulatory contexts, include two mechanistic SAR models for predicting the mutagenicity of aromatic amines and α-β unsaturated aliphatic aldehydes. The aim of this study was to estimate the interest and limitations of the former model. The model was first re-computed to check its transparency and to verify its statistical validity. Then, it was tested on about 150 chemicals not previously used for the design of the model but belonging to its domain of application. A critical analysis of the results was performed and proposals were made for increasing the model performances.
SAR and QSAR in environmental research 10/2010; 21(7-8):753-69. DOI:10.1080/1062936X.2010.528959 · 1.60 Impact Factor