DRomics: A Turnkey Tool to Support the Use of the Dose–Response Framework for Omics Data in Ecological Risk Assessment

International audienceOmics approaches (e.g. transcriptomics, metabolomics) are promising for ecological risk assessment (ERA) since they provide mechanistic information and early warning signals. A crucial step in the analysis of omics data is the modelling of concentration-dependency which may have different trends including monotonic (e.g. linear, exponential) or biphasic (e.g. U shape, bell shape) forms. The diversity of responses raises challenges concerning detection and modelling of significant responses and effect concentration (EC) derivation. Furthermore, handling high-throughput datasets is time-consuming and requires effective and automated processing routines. Thus, we developed an open source tool (DRomics,available as an R-package and as a web-based service) which, after elimination of molecular responses (e.g. gene expressions from microarrays) with no concentration-dependency and/or high variability, identifies the best model for concentration-response curve description. Subsequently, an EC (e.g. a benchmark dose) is estimated from each curve and curves are classified based on their model parameters. This tool is especially dedicated to manage data obtained from an experimental design favoring a greatnumber of tested doses rather than a great number of replicates and also to handle properly monotonic and biphasic trends. The tool finally restitutes a table of results that can be directly used to perform ERA approaches

Design development and implementation of an irradiation station at the neutron time-of-flight facility at CERN

A new parasitic, mixed-field, neutron-dominated irradiation station has been recently commissioned at the European Laboratory for Particle Physics (CERN). The station is installed within the neutron time-of-flight (n_TOF) facility, taking advantage of the secondary radiation produced by the neutron spallation target, with neutrons ranging from 0.025 eV to several hundreds of MeV. The new station allows radiation damage studies to be performed in irradiation conditions that are closer to the ones encountered during the operation of particle accelerators; the irradiation tests carried out in the station will be complementary to the standard tests on materials, usually performed with gamma sources. Samples will be exposed to neutron-dominated doses in the MGy range per year, with minimal impact on the n_TOF facility operation. The station has 24 irradiation positions, each hosting up to 100 cm3 of sample material. In view of its proximity to the n_TOF target, inside protective shielding, the irradiation station and its operating procedures have been carefully developed taking into account the safety of personnel and to avoid any unwanted impact on the operation of the n_TOF facility and experiments. Due to the residual radioactivity of the whole area around the n_TOF target and of the irradiated samples, access to the irradiation station is forbidden to human operators even when the n_TOF facility is not in operation. Robots are used for the remote installation and retrieval of the samples, and other optimizations of the handling procedures were developed in compliance with radiation protection regulations and the aim of minimizing doses to personnel. The sample containers were designed to be radiation tolerant, compatible with remote handling, and subject to detailed risk analysis and testing during their development. The whole life cycle of the irradiated materials, including their post-irradiation examinations and final disposal, was considered and optimized

Modeling species sensibility variability for community protection

Les activités humaines ont de nombreux effets sur les écosystèmes. Elles peuvent se traduire par exemple par le déversement ou la fuite de contaminants dans les écosystèmes, comme lors de l'épandage de pesticides dans une zone agricole. L'évaluation du risque environnemental permet de caractériser et de quantifier ces effets afin de les maintenir à un niveau considéré acceptable. Cette évaluation se fait le plus souvent à partir de bioessais monospécifiques, mais les relations concentration-réponse ainsi décrites peuvent ensuite être intégrées au sein d'une distribution de sensibilité des espèces (ou SSD pour Species Sensitivity Distribution). Ces SSD, largement utilisées en évaluation du risque environnemental, permettent alors de définir une concentration n'ayant d'effets que sur une petite fraction des espèces présentes dans un écosystème (le plus souvent 5% donnant ainsi des concentrations dangereuses pour 5% des espèces). L'un des problèmes importants de ce type d'approches reste cependant une représentativité environnementale encore limitée. En effet, les bioessais monospécifiques fournissant l’information de base pour produire ces SSD sont le plus souvent réalisés dans des conditions non réalistes (organismes isolés et donc non soumis aux interactions biotiques, conditions expérimentales éloignées de la réalité environnementale, obtention d'une valeur de sensibilité unique pour une espèce alors que cette sensibilité peut être variable d'une population à l'autre...). Ce manque de réalisme est compensé par l'application d'un facteur de sécurité venant diviser la valeur finale par une valeur d'autant plus grande que l'estimation réalisée est éloignée de la réalité environnementale, donnant ainsi des valeurs d'autant plus basses et donc considérées plus protectrices. Les travaux présentés ici ont cherché à intégrer (i) l’effet de la variabilité intraspécifique sur les paramètres des courbes SSD, et notamment la concentration dangereuse pour 5% des espèces et (ii) l’effet combiné d’un herbicide et de la compétition interspécifique sur les communautés végétales des bandes enherbées, en adoptant plusieurs démarches de modélisation, à chaque étape du processus d’analyse de données. Les résultats mettent en évidence l’importance d’intégrer toute cette complexité biologique dans les démarches d’évaluation du risque environnemental, ainsi que le risque de sous-estimation des facteurs de sécurité généralement appliqués sur les résultats issus d’une modélisation SSD.Human activities have numerous effects on ecosystems. They can for example result in spillage or leakage of contaminants in ecosystems as during spreading of pesticides in agricultural lands. Environmental risk assessment allows to characterize those effects to maintain them at a level considered acceptable. This assessment is usually based on monospecific bioassays, but concentration-response relationships thus described can then be included in Species Sensitivity Distributions (SSD). Those SSD, widely used in environmental risk assessment, then allows to define a concentration that only have an effect on a small fraction of the species found in an ecosystem (usually 5%, leading to hazardous concentrations for 5% of species). One of the most important problems of this kind of approaches is that it still lacks environmental relevance. Monospecific bioassays indeed providing the information to model SSD are usually realised in non realist conditions (organisms isolated and thus not subject to biotic interactions, experimental conditions far from environmental reality, obtention of a unique sensitivity value for a species whereas this sensibility can be variable from one population to another...). This lack of realism is compensated by the application of an assessment factor which divides the final value by a value that increases as the realised estimation is distant from environmental reality, thus giving lower values that are considered more protectives. The work presented here sought to integrate (i) the effect of intraspecific variability on SSD curves parameters, in particular on hazardous concentrations for 5% of species and (ii) the combined effect of an herbicide and interspecific competition on the vegetal communities that are grass stripes following several modeling approaches for each data processing step. Results show the importance of the integration of all this biological complexity in environmental risk assessment procedures as well as the risk of underestimation of assessment factors usually applied on results from SSD modeling

Modélisation de distribution de sensibilité des espèces pour la protection des communautés

Human activities have numerous effects on ecosystems. They can for example result in spillage or leakage of contaminants in ecosystems as during spreading of pesticides in agricultural lands. Environmental risk assessment allows to characterize those effects to maintain them at a level considered acceptable. This assessment is usually based on monospecific bioassays, but concentration-response relationships thus described can then be included in Species Sensitivity Distributions (SSD). Those SSD, widely used in environmental risk assessment, then allows to define a concentration that only have an effect on a small fraction of the species found in an ecosystem (usually 5%, leading to hazardous concentrations for 5% of species). One of the most important problems of this kind of approaches is that it still lacks environmental relevance. Monospecific bioassays indeed providing the information to model SSD are usually realised in non realist conditions (organisms isolated and thus not subject to biotic interactions, experimental conditions far from environmental reality, obtention of a unique sensitivity value for a species whereas this sensibility can be variable from one population to another...). This lack of realism is compensated by the application of an assessment factor which divides the final value by a value that increases as the realised estimation is distant from environmental reality, thus giving lower values that are considered more protectives. The work presented here sought to integrate (i) the effect of intraspecific variability on SSD curves parameters, in particular on hazardous concentrations for 5% of species and (ii) the combined effect of an herbicide and interspecific competition on the vegetal communities that are grass stripes following several modeling approaches for each data processing step. Results show the importance of the integration of all this biological complexity in environmental risk assessment procedures as well as the risk of underestimation of assessment factors usually applied on results from SSD modeling.Les activités humaines ont de nombreux effets sur les écosystèmes. Elles peuvent se traduire par exemple par le déversement ou la fuite de contaminants dans les écosystèmes, comme lors de l'épandage de pesticides dans une zone agricole. L'évaluation du risque environnemental permet de caractériser et de quantifier ces effets afin de les maintenir à un niveau considéré acceptable. Cette évaluation se fait le plus souvent à partir de bioessais monospécifiques, mais les relations concentration-réponse ainsi décrites peuvent ensuite être intégrées au sein d'une distribution de sensibilité des espèces (ou SSD pour Species Sensitivity Distribution). Ces SSD, largement utilisées en évaluation du risque environnemental, permettent alors de définir une concentration n'ayant d'effets que sur une petite fraction des espèces présentes dans un écosystème (le plus souvent 5% donnant ainsi des concentrations dangereuses pour 5% des espèces). L'un des problèmes importants de ce type d'approches reste cependant une représentativité environnementale encore limitée. En effet, les bioessais monospécifiques fournissant l’information de base pour produire ces SSD sont le plus souvent réalisés dans des conditions non réalistes (organismes isolés et donc non soumis aux interactions biotiques, conditions expérimentales éloignées de la réalité environnementale, obtention d'une valeur de sensibilité unique pour une espèce alors que cette sensibilité peut être variable d'une population à l'autre...). Ce manque de réalisme est compensé par l'application d'un facteur de sécurité venant diviser la valeur finale par une valeur d'autant plus grande que l'estimation réalisée est éloignée de la réalité environnementale, donnant ainsi des valeurs d'autant plus basses et donc considérées plus protectrices. Les travaux présentés ici ont cherché à intégrer (i) l’effet de la variabilité intraspécifique sur les paramètres des courbes SSD, et notamment la concentration dangereuse pour 5% des espèces et (ii) l’effet combiné d’un herbicide et de la compétition interspécifique sur les communautés végétales des bandes enherbées, en adoptant plusieurs démarches de modélisation, à chaque étape du processus d’analyse de données. Les résultats mettent en évidence l’importance d’intégrer toute cette complexité biologique dans les démarches d’évaluation du risque environnemental, ainsi que le risque de sous-estimation des facteurs de sécurité généralement appliqués sur les résultats issus d’une modélisation SSD

Nitrogen to phosphorus ratio shapes bacterial community involved in cellulose decomposition and copper contamination alters their stoichiometric demand

International audienceAbstract All living organisms have theoretically an optimal stoichiometric nitrogen: phosphorus (N: P) ratio below and beyond which their growth is affected but data remain scarce for microbial decomposers. Here, we evaluated optimal N: P ratios of microbial communities involved in cellulose decomposition and assessed their stability when exposed to copper Cu(II). We hypothesized that (1) cellulose decomposition is maximized for an optimal N: P ratio, (2) copper exposure reduces cellulose decomposition and (3) increases microbial optimal N: P ratio, (4) N: P ratio and copper modify the structure of microbial decomposer communities. We measured cellulose disc decomposition by a natural inoculum in microcosms exposed to a gradient of N: P ratios at three copper concentrations (0, 1 and 15 µM). Bacteria were most probably the main decomposers. Without copper, cellulose decomposition was maximized at an N: P molar ratio of 4.7. Contrary to expectations, at high copper concentration, the optimal N: P ratio (2.8) and the range of N: P ratios allowing decomposition were significantly reduced and accompanied by a reduction of bacterial diversity. Copper contamination led to the development of tolerant taxa probably less efficient in decomposing cellulose. Our results shed new lights on the understanding of multiple stressor effects on microbial decomposition in an increasingly stoichiometrically imbalanced world

Effet de stresseurs environnementaux sur les ratios N:P optimaux de décomposeurs microbiens

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La réponse des biofilms phototrophes au stress thermique dépend-elle de leur complexité, de leur histoire thermique, ou des deux ?

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Can the functional stability of microbial communities exposed to multiple disturbances of the same nature be predicted?

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Disentangling the effects of microalgal diversity and thermal history on freshwater phototrophic biofilms facing heat stress: A thermal dose approach

International audience1. The increase in heatwave intensity and duration is challenging microalgal photosynthesis in shallow waters. In particular, the extent of photosynthesis impairment or limitation due to short extreme heat stress events occurring during a heatwave remains unknown.2. In this study, we investigated the importance of microalgal diversity and thermal history in the response of phototrophic biofilms to severe heat stress. We exposed isolated microalgal strains, synthetic communities previously acclimated at three temperatures, and natural phototrophic biofilms sampled at different seasons to several temperature/duration pairs (from 31 to 44 °C for 30, 60, 120 or 180 min). Microalgal photosynthetic activity (FV/FM) was measured after each heat stress and was shown to be a function of thermal dose, defined as the product of time and an exponential function of temperature.3. It appeared that the thermal history plays an important role in tolerance to heat stress, with synthetic communities acclimated at highest temperature being more tolerant. However, the responsiveness (i.e., the strength of the response) to heat stress was driven by the microalgal diversity of the community.4. Synthesis: Our analysis showed that although photosynthetic activity was negatively impacted by heat stress, gross primary productivity was even more strongly and rapidly impacted, highlighting the fact that in situ, even moderate heat stress can significantly impair primary productivity in shallow waters

Can SSD models help assessing interspecific competition impact on organisms' tolerance against chemical stress?

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