Effects of Chemical Compounds on the Activity of the N-acetyl-β-D-Glucosaminidase of the Marine Prawn, Palaemon serratus: Screening In Vitro

N-acetyl-β-D-glucosaminidase (NAGase) is important for crustaceans because the enzyme activity is necessary for the molting process. The present study aimed to assess the sensitivity of Palaemon serratus NAGase activity to a set of compounds of diverse chemical families in the context of in vitro exposures. Compounds representing different chemical families were selected according to their abundance, impact in the environment, and relevance as disruptors of the molting process. In a first step, four solvents (dimethylsulfoxide [DMSO], methanol, acetone, and ethanol) were tested to determine their suitability to dissolve hydrophobic compounds without affecting NAGase activity. Exclusively, ethanol had no effect on enzyme activity and on the integrity of the proteins present in the enzyme extract. The 18 other compounds were tested and four of these compounds, pentoxifylline, fenoxycarb, dithiocarbamate, and RH5849, showed a specific alteration on the activity of NAGase, without affecting the protein content. However, cadmium, zinc, and glyphosate showed a nonspecific alteration, affecting both the enzyme activity and the proteins, whereas ibuprofen exclusively altered the protein content. Finally, 10 of the 22 tested compounds (including DMSO, acetone, and methanol) showed a direct alteration of NAGase activity. Environ Toxicol Chem 2023;42:846-858. © 2023 SETAC.

A 34-year survey under phosphorus decline and warming: Consequences on stoichiometry and functional trait composition of freshwater macroinvertebrate communities

Worldwide, freshwater systems are subjected to increasing temperatures and nutrient changes. Under phosphorus and nitrogen enrichment consumer communities are often thought to shift towards fast-growing and P-rich taxa, supporting the well-known link between growth rate and body stoichiometry. While these traits are also favoured under warming, the temperature effect on stoichiometry is less clear. As recently shown, there is a general link between functional traits and body stoichiometry, which makes the integration of stoichiometric traits a promising tool to help understanding the mechanisms behind taxonomic and functional community responses to nutrient changes and/or warming. Yet, such approaches have been scarcely developed at community level and on a long-term perspective. In this study, we investigated long-term responses in stoichiometry and functional trait composition of macroinvertebrate communities to nutrient changes (decreasing water P; increasing water N:P) and warming over a 34-year period in the Middle Loire River (France), testing the potentially opposing responses to these drivers. Both drivers should cause shifts in species composition, which will alter the overall community stoichiometry and functional composition following assumptions from ecological stoichiometry theory. We found that the macroinvertebrate community shifted towards P-poor taxa, causing significant trends in overall community stoichiometry which indicates long-term changes in the nutrient pool provided by these consumers (i.e. decrease in %N and %P, increase in N:P). Further, while the former high-P conditions favoured traits associated to detritus feeding and fast development (i.e. small maximum body size, short life duration), recent conditions favoured predators and slow-developing taxa. These results suggest nutrients to be a more important driver than temperature over this period. By providing a pivotal link between environmental changes and functional trait composition of communities, approaches based on stoichiometric traits offer sound perspectives to investigate ecological relationships between multiple drivers operating at various scales and ecosystem functioning.

Lessons from linking bio- and ecological traits to stoichiometric traits in stream macroinvertebrates

Ecologists rely on various functional traits when investigating the functioning of ecological systems and its responses to global changes. Changing nutrient levels, for example, can affect taxa expressing different trait combinations in various ways, e.g., favoring small, fast-growing species under high phosphorus conditions. Stoichiometric traits, describing the elemental composition of organism body tissues, can help in understanding the mechanisms behind such functional shifts. So far, mainly life-history traits have been related to body stoichiometry (e.g., the growth rate hypothesis) on a limited number of taxa, and there is little knowledge of the general link between stoichiometric and other functional traits on a taxonomically large scale. Here, we highlight this link in the freshwater macroinvertebrates, testing predictions from underlying trait-based and Ecological Stoichiometry Theory (EST) in >200 taxa belonging to eight larger taxonomic groups. We applied a series of multivariate analyses on six of their stoichiometric traits (%C, %N, %P, C:N, C:P, and N:P) and 23 biological and ecological traits. We found significant relationships between stoichiometric traits and other types of traits when analyzing single-trait and multi-trait profiles. Patterns found within traits related to organism development or nutrient cycling were in line with our assumptions based on EST, e.g., traits describing predators were associated with high %N; traits suggesting a fast development (small maximum body size and high molting frequency) with high %P. Associations between ecological traits and body stoichiometry could be explained by the longitudinal stream gradient: Taxa preferring headwater habitats (i.e., high altitude, coarse substrate, and cold temperature) exhibited high %N and %P. Demonstrating the link between stoichiometric and both bio- and ecological traits on a large diversity of taxa underlines the potential of integrating stoichiometric traits into ecological analyses to improve our understanding of taxonomic and functional responses of communities-and ecosystems-to changing environmental conditions worldwide.

Influence of microorganisms on uranium release from mining-impacted lake sediments under various oxygenation conditions

Microbial processes can be involved in the remobilization of uranium (U) from reduced sediments under O₂ reoxidation events such as water table fluctuations. Such reactions could be typically encountered after U-bearing sediment dredging operations. Solid U(IV) species may thus reoxidize into U(VI) that can be released in pore waters in the form of aqueous complexes with organic and inorganic ligands. Non-uraninite U(IV) species may be especially sensitive to reoxidation and remobilization processes. Nevertheless, little is known regarding the effect of microbially mediated processes on the behaviour of U under these conditions.

How does interspecific competition modify the response of grass plants against herbicide treatment? A hierarchical concentration-response approach

Ecological interactions are rarely taken into account in environmental risk assessment. The objective of this work was to assess how interspecific competition affects the way plant species react to herbicides and more specifically how it modifies the concentration-response curves that can be built using ecotoxicological bioassays. To do this, we relied on the results of ecotoxicological bioassays on six herbaceous species exposed to isoproturon under two conditions: in presence and in absence of a competitor. At the end of the experiments, eleven endpoints were measured. We modelled these data using a hierarchical modelling framework designed to assess the effects of competition on each of the four parameters of the concentration response curves (e.g. the level of response at the control or the concentration at the inflection point of the curve) simultaneously for the six species. The modelled effects could be of three types, 1) competition had no effect on the parameter, 2) competition had the same effect on the parameter for all species and 3) competition had a different effect on the parameter for each species. Our main hypothesis was that different species would react differently to competition. Results showed that about a half of the estimated parameters showed a modification under competition pressure among which only a fourth showed a species-specific effect, the three other fourth showing the same effect between the different species. Our initial hypothesis was thus not supported as species tended to react in the same way to competition. The competition effect on plants was mainly negative, thus showing that they were more affected by isoproturon under competition pressure. This study therefore establishes how competition modifies plant responses to chemical stress and how this interaction varies from one species to the other.

How diatom-, invertebrate- and fish-based diagnostic tools can support the ecological assessment of rivers in a multi-pressure context: Temporal trends over the past two decades in France

The degradation of aquatic ecosystems, induced by worldwide intensification in the use of both land and aquatic resources, has highlighted the critical need for innovative methods allowing an objective quantification and ranking of anthropogenic pressure effects on aquatic organisms. Such diagnostic tools have a great potential for defining robust management responses to anthropogenic pressures. Our objective was to explore how the outputs of three diagnostic tools (based on benthic diatoms, macroinvertebrates and fishes) could be combined to (i) disentangle the temporal effects of multiple pressures over two decades and (ii) provide policy-relevant information for stream managers and decision makers. The diagnostic tools estimated, using taxonomy- and trait-based metrics, the impairment probabilities of biotic assemblages over time by different pressure categories, describing the alteration of water quality, hydromorphology and land use related to anthropogenic activities, in French streams (number of sites = 312). The main result shows that a large proportion of the time series exhibited no significant temporal patterns over the two decades (61.5% to 87.8%, depending on the used tests). Among time series exhibiting significant change, positive trends in impairment probabilities (i.e., degradation) were less frequent than negative ones, indicating a modest improvement in water quality at national scale over the study period. However, trends can be substantially different according to hydroecoregion and pressure category. The three biological compartments displayed convergent temporal responses according to the pressure category and regional context (e.g., lowland plains vs. mountains, pristine vs. agricultural regions). Altogether, this study proposes a unifying approach to integrate a vast amount of information in a single ecological diagnosis using an unparalleled database on natural and anthropized environments. Strengthening the synthesis of biological information provided by various biological compartments should be a priority before implementing evidence-based sustainable conservation and restoration actions.

A multi-omics concentration-response framework uncovers novel understanding of triclosan effects in the chlorophyte Scenedesmus vacuolatus

In aquatic ecosystems, the biocide triclosan represents a hazard for the non-target microalgae. So far, algal responses were mainly investigated at apical levels hampering the acquisition of a holistic view on primary, adaptive, and compensatory stress responses. We assessed responses of the chlorophyte Scenedesmus vacuolatus to triclosan at apical (growth, photosynthesis) and molecular (transcriptome, metabolome) levels for comparative pathway sensitivity analysis. For each responsive signal (contigs, metabolites), a concentration-response curve was modeled and effect concentrations were calculated leading to the setting of cumulative sensitivity distributions. Molecular responses showed higher sensitivity than apical observations. The functional annotation of contigs and metabolites revealed 118 metabolic pathways putatively impaired by triclosan, highlighting a wide repercussion on the algal metabolism. Metabolites involved in the lipid metabolism showed decreasing trends along the concentration gradient and a globally highest sensitivity, pointing to the primary target of triclosan. The pathways involved in xenobiotic degradation and membrane transporters were mainly regulated in the transcriptome with increasing response trends comprising compensatory responses. The suggested novel approach, combining apical and multi-omics analyses in a concentration-response framework improves mechanistic understanding and mode of action analysis on non-targeted organisms and is suggested to better implement high-throughput multi-omics data in environmental risk assessment.

Effect of interspecific competition on species sensitivity distribution models: Analysis of plant responses to chemical stress

Species Sensitivity Distributions (SSD) are widely used in environmental risk assessment to predict the concentration of a contaminant that is hazardous for 5% of species (HC₅). They are based on monospecific bioassays conducted in the laboratory and thus do not directly take into account ecological interactions. This point, among others, is accounted for in environmental risk assessment through an assessment factor (AF) that is applied to compensate for the lack of environmental representativity. In this study, we aimed to assess the effects of interspecific competition on the responses towards isoproturon of plant species representative of a vegetated filter strip community, and to assess its impact on the derived SSD and HC₅ values. To do so, we realized bioassays confronting six herbaceous species to a gradient of isoproturon exposure in presence and absence of a competitor. Several modelling approaches were applied to see how they affected the results, using different critical effect concentrations and investigating different ways to handle multiple endpoints in SSD. At the species level, there was a strong trend toward organisms being more sensitive to isoproturon in presence of a competitor than in its absence. At the community level, this trend was also observed in the SSDs and HC₅ values were always lower in presence of a competitor (1.12-11.13 times lower, depending on the modelling approach). Our discussion questions the relevance of SSD and AF as currently applied in environmental risk assessment.

Microplastics enhance Daphnia magna sensitivity to the pyrethroid insecticide deltamethrin: Effects on life history traits

The aim of the study was to investigate the influence of microplastics (MPs) on the ecotoxicity of common contaminants of aquatic ecosystems. As a model contaminant, the hydrophobic pesticide deltamethrin (DM) was chosen, and its effects on life history traits of Daphnia magna were studied in the presence or absence of polyethylene MPs. Commercialized DM and MPs obtained as dry powder were used in the experiment. According the manufacturer (Cospheric, Santa Barbara, CA, USA) MPs were spherical (1-4 μm in diameter), had a density of 0.96 g/cm^-3 and were without any solvent. Three concentrations of polyethylene MPs were tested (0, 1, 10 mg/L) with two realistic concentrations of DM (0 and 40 ng/L) and a solvent control (acetone). During the 21 d experiment, D. magna neonates were individually exposed to the treatments, and the effects of MPs and DM alone and together were evaluated by assessing survival, number of cumulative molts, days to first brood, number of broods, number of neonates per surviving adult, and body length. Significant detrimental effects on survival were only observed for the two mixture treatments. DM alone (40 ng/L) delayed the days to first brood and reduced the number of neonates per surviving adult, whereas MPs alone (10 mg/L) induced significant reduction in the number of juveniles by surviving adults. The combined exposure to DM and MPs clearly had a synergistic effect on survival, brood number, and number of neonates per surviving female. For example, compared to exposure to 40 ng/L of DM alone, the addition of 1 mg/L of MPs resulted in a 51.1% reduction in number of neonates per surviving female and a 46% reduction in brood number. These results suggest the potential drastic effects of this kind of mixed exposure on daphnid populations, which are key components of freshwater food webs.

Agricultural and domestic pesticides in house dust from different agricultural areas in France

Pesticides have been associated with various pathologies, and there is growing evidence of pesticide presence in domestic environments. However, most available studies focused on a limited number of pesticides or households, and few have been conducted in Europe. We aimed to assess indoor pesticide contamination by screening the prevalence of 276 pesticides and ten pesticide metabolites, in French households from different agricultural and urban areas. We sampled indoor dust from 239 households in 2012, proximate to orchards (n = 69), cereals (n = 66) and vineyard (n = 68) crops, or from urban area (n = 36). we used cellulose wipes moistened with isopropanol and polypropylene dust traps to collect recent (7 and 30 days, respectively) and settled dust (> 6 months). Overall, 125 pesticides and piperonyl butoxide were detected at least once in households, mostly at low prevalence: 97 in recent dust, and 111 in settled dust. In recent dust, the most prevalent compounds were o-phenylphenol (168 households, 70%), pentachlorophenol (86, 36%), and piperonyl butoxide (82, 34%). In addition to agricultural pesticides, we found a high proportion of domestic and banned compounds in recent and settled house dust. Several pesticides were identified in house dust, from different pesticide groups and sources. Our results suggest that domestic usage and persistence of banned pesticides may contribute substantially to indoor pesticide contamination. Graphical abstract 97 pesticides detected in households' recent indoor dust.

Does intraspecific variability matter in ecological risk assessment? Investigation of genotypic variations in three macrophyte species exposed to copper

To limit anthropogenic impact on ecosystems, regulations have been implemented along with global awareness that human activities are harmful to the environment. Ecological risk assessment (ERA) is the main procedure which allows to assess potential impacts of stressors on the environment as a result of human activities. ERA is typically implemented through different steps of laboratory testing. The approaches taken for ERA evolve along with scientific knowledge, to improve predictions on ecological risks for ecosystems. We here address the importance of intraspecific variability as a potential source of error in the laboratory evaluation of pollutants. To answer this question, three aquatic macrophyte species with different life-history traits but with their leaves directly in contact with the water were chosen; Lemna minor and Myriophyllum spicatum, two OECD model species, and Ceratophyllum demersum. For each species, three or four genotypes were exposed to 7-8 copper concentrations (up to 1.9 mg/L, 2 mg/L or 36 mg/L for C. demersum, L. minor and M. spicatum, respectively). To assess species sensitivity, growth-related endpoints such as Relative Growth Rate (RGR), based either on biomass production or on length/frond production, and chlorophyll fluorescence F_v/F_m, were measured. For each endpoint, the effective concentration 50% (EC₅₀) was calculated. Almost all endpoints were affected by Cu exposure, except F_v/F_m of M. spicatum, and resulted in significant differences among genotypes for Cu sensitivity. Genotypes of L. minor exhibited up to 35% of variation in EC50 values based on F_v/F_m, showing differential sensivity among genotypes. Significant differences in EC₅₀ values were found for RGR based on length for M. spicatum, with up to 72% of variation. Finally, C. demersum demonstrated significant sensitivity differences among genotypes with up to 78% variation for EC₅₀ based on length. Overall, interspecific variation was higher than intraspecific variation, and explained 77% of the variation found among genotypes for RGR based on biomass, and 99% of the variation found for F_v/F_m. Our results highlight that depending on the endpoint, sensitivity can vary greatly within a species, and that pollutant- and species-specific endpoints should be considered in ERA.

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

Omics 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 modeling 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 modeling of significant responses and effect concentration (EC) derivation. Furthermore, handling high-throughput data sets 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 great number of tested doses rather than a great number of replicates and also to handle properly monotonic and biphasic trends. The tool finally provides restitution for a table of results that can be directly used to perform ERA approaches.

High stoichiometric food quality increases moulting organism vulnerability to pollutant impacts: An experimental test with Gammarus fossarum (Crustacea: Amphipoda)

Headwater organisms are most often simultaneously faced with multiple stressors such as low resource quality and pollutants. Higher food quality has been hypothesized to enhance the tolerance of organisms to pollutants, but the interactive effects of food quality and pollutants on species and ecosystems remain poorly studied. To better understand these interactive effects, we experimentally manipulated the phosphorus (P) content of two leaf litters with contrasted carbon quality (alder and maple). During four weeks, individuals of the detritivorous crustacean Gammarus fossarum were exposed to low levels of cadmium ([Cd] = 0, 0.35 or 0.70 μg L^-1) while being fed with one of the leaf P treatments. When organisms were not exposed to Cd, their high survival rate was more driven by the carbon quality of the resource (litter species) than by its stoichiometric quality. In contrast, their number of moults and growth rates were primarily increased by the P content of resources. When exposed to Cd, G. fossarum survival rate was reduced, but this effect was largely magnified by a higher P level in resources. Our results showed that despite positive effects of resource stoichiometric quality on organism life history traits (growth, survival), a resource of high stoichiometric quality might be detrimental for organisms exposed to low and environmentally realistic levels of pollutants. Two non-exclusive hypotheses are proposed to explain these results. First, organisms fed on the highest quality resource exhibited the highest moulting frequencies (moults being the most critical life cycle step of arthropods), which could have rendered them more sensitive to pollutants. Secondly, the metabolism of organisms fed on higher quality resources was potentially enhanced, increasing the uptake of dissolved Cd by gammarids. This study suggests that species sensitivity to pollutants might be underestimated in ecosystems facing both nutrient constraint and pollutants.

Assessing anthropogenic pressures on streams: A random forest approach based on benthic diatom communities

Benthic diatoms have been widely used to assess the ecological status of freshwater ecosystems, especially in the context of recent international water framework directive policies (e.g. the WFD). Despite diatom-based indices are known to respond fastly to water quality degradation, they are not designed to precisely identify the nature of pressures co-occurring in the environment. Based on large scale monitoring data, we aimed at building models able to estimate the risk of stream impairment by many types of anthropogenic pressures from taxonomy-based and trait-based characteristics of diatom assemblages. Random forest models were built to individually evaluate the impairment risk of diatom assemblages for six chemical and five hydromorphological or land-use related pressure categories. Eight models provided good impairment risk assessment (Area Under the Curve≥0.70). Under multi-pressure scenarios, models built for chemical pressures exhibited a better accuracy than hydromorphological or land-use related ones. Models were able to detect both ecological restoration and degradation, based on long-term surveys. These models have been implemented in a R user-friendly routine, to help stream managers to early identify degrading processes and prioritize management actions.

[Single-donor protocol: Transfusion practices and multiple transfusion risk factors in neonatal intensive care unit]

In France since 2002, the single-donor transfusion protocol, using four pediatric units from the same adult donor's packed red blood cells (PRBCs) in multiply transfused newborns, is recommended in preterm neonates to reduce the risks of infection and alloimmunization. This protocol is controversial, however, because it causes the transfusion of stored blood, which could have adverse consequences. Before the new recommendations of the French Haute Autorité de santé (National authority for health) in 2015, we conducted a national practice survey in 63 neonatal intensive care units (NICU) and a retrospective study of the characteristics of 103 children transfused within our unit, to better target beneficiaries. The practice survey showed that 30 % of French NICUs no longer used the protocol in 2014, due to logistical or financial problems, or concerns about the transfusion of stored blood. The practices were heterogeneous. Few NICUs used a written protocol. In our NICU, the use of single-donor protocol involved the use of units stored for more than 20 days in half of the cases beginning with the third unit used. Six-term newborns were mainly transfused once, which does not seem to warrant the single-donor transfusion protocol. The use of this protocol caused the loss of 50 % of the manufactured units, which go unused. In multivariate analysis, two factors were predictive of multiple transfusion within our population of 95 premature neonates undergoing transfusion: low-term and a high Clinical Risk Index for Babies (CRIB) score. The risk of multiple transfusions would be reduced by about 15 % for each additional week of gestation and approximately 16 % per point within the CRIB score. These variables integrated into a statistical model predict the risk of multiplying transfusions. According to the ROC curve, a calculated risk higher than 50 % is the appropriate cut-off value to transfuse with the single-donor transfusion protocol. This would limit its indications, saving more than 130 pediatric units of blood for 100 transfused children. A prospective study in our department will allow internal validation of this test.

A biodynamic model predicting waterborne lead bioaccumulation in Gammarus pulex: Influence of water chemistry and in situ validation

Metals bioaccumulated in aquatic organisms are considered to be a good indicator of bioavailable metal contamination levels in freshwaters. However, bioaccumulation depends on the metal, the species, and the water chemistry that influences metal bioavailability. In the laboratory, a kinetic model was used to describe waterborne Pb bioaccumulated in Gammarus pulex. Uptake and elimination rate constants were successfully determined and the effect of Ca(2+) on Pb uptake was integrated into the model. Thereafter, accumulated Pb concentrations in organisms were predicted with the model and compared with those measured in native populations from the Seine watershed (France). The predictions had a good agreement with the bioaccumulation levels observed in native gammarids and particularly when the effect of calcium was considered. To conclude, kinetic parameters experimentally derived for Pb in G. pulex are applicable in environmental conditions. Moreover, the consideration of the water's chemistry is crucial for a reliable interpretation of bioaccumulation.

Efficiency of wipe sampling on hard surfaces for pesticides and PCB residues in dust

Pesticides and polychlorinated biphenyls (PCBs) are commonly found in house dust and have been described as a valuable matrix to assess indoor pesticide and PCB contamination. The aim of this study was to assess the efficiency and precision of cellulose wipe for collecting 48 pesticides, eight PCBs, and one synergist at environmental concentrations. First, the efficiency and repeatability of wipe collection were determined for pesticide and PCB residues that were directly spiked onto three types of household floors (tile, laminate, and hardwood). Second, synthetic dust was used to assess the capacity of the wipe to collect dust. Third, we assessed the efficiency and repeatability of wipe collection of pesticides and PCB residues that was spiked onto synthetic dust and then applied to tile. In the first experiment, the overall collection efficiency was highest on tile (38%) and laminate (40%) compared to hardwood (34%), p<0.001. The second experiment confirmed that cellulose wipes can efficiently collect dust (82% collection efficiency). The third experiment showed that the overall collection efficiency was higher in the presence of dust (72% vs. 38% without dust, p<0.001). Furthermore, the mean repeatability also improved when compounds were spiked onto dust (<30% for the majority of compounds). To our knowledge, this is the first study to assess the efficiency of wipes as a sampling method using a large number of compounds at environmental concentrations and synthetic dust. Cellulose wipes appear to be efficient to sample the pesticides and PCBs that adsorb onto dust on smooth and hard surfaces.

Sample size calculation in metabolic phenotyping studies

The number of samples needed to identify significant effects is a key question in biomedical studies, with consequences on experimental designs, costs and potential discoveries. In metabolic phenotyping studies, sample size determination remains a complex step. This is due particularly to the multiple hypothesis-testing framework and the top-down hypothesis-free approach, with no a priori known metabolic target. Until now, there was no standard procedure available to address this purpose. In this review, we discuss sample size estimation procedures for metabolic phenotyping studies. We release an automated implementation of the Data-driven Sample size Determination (DSD) algorithm for MATLAB and GNU Octave. Original research concerning DSD was published elsewhere. DSD allows the determination of an optimized sample size in metabolic phenotyping studies. The procedure uses analytical data only from a small pilot cohort to generate an expanded data set. The statistical recoupling of variables procedure is used to identify metabolic variables, and their intensity distributions are estimated by Kernel smoothing or log-normal density fitting. Statistically significant metabolic variations are evaluated using the Benjamini-Yekutieli correction and processed for data sets of various sizes. Optimal sample size determination is achieved in a context of biomarker discovery (at least one statistically significant variation) or metabolic exploration (a maximum of statistically significant variations). DSD toolbox is encoded in MATLAB R2008A (Mathworks, Natick, MA) for Kernel and log-normal estimates, and in GNU Octave for log-normal estimates (Kernel density estimates are not robust enough in GNU octave). It is available at http://www.prabi.fr/redmine/projects/dsd/repository, with a tutorial at http://www.prabi.fr/redmine/projects/dsd/wiki.

SRV: an open-source toolbox to accelerate the recovery of metabolic biomarkers and correlations from metabolic phenotyping datasets

MOTIVATION

Supervised multivariate statistical analyses are often required to analyze the high-density spectral information in metabolic datasets acquired from complex mixtures in metabolic phenotyping studies. Here we present an implementation of the SRV-Statistical Recoupling of Variables-algorithm as an open-source Matlab and GNU Octave toolbox. SRV allows the identification of similarity between consecutive variables resulting from the high-resolution bucketing. Similar variables are gathered to restore the spectral dependency within the datasets and identify metabolic NMR signals. The correlation and significance of these new NMR variables for a given effect under study can then be measured and represented on a loading plot to allow a visual and efficient identification of candidate biomarkers. Further on, correlations between these candidate biomarkers can be visualized on a two-dimensional pseudospectrum, representing a correlation map, helping to understand the modifications of the underlying metabolic network.

AVAILABILITY

SRV toolbox is encoded in MATLAB R2008A (Mathworks, Natick, MA) and in GNU Octave. It is available free of charge at http://www.prabi.fr/redmine/projects/srv/repository with a tutorial.

CONTACT

benjamin.blaise@chu-lyon.fr or vincent.navratil@univ-lyon1.fr.

Time-dependent species sensitivity distributions

Time is a central component of toxicity assessments. However, current ecotoxicological practice marginalizes time in concentration-response (C-R) modeling and species sensitivity distribution (SSD) analyses. For C-R models, time is invariably fixed, and toxicity measures are estimated from a function fitted to the data at that time. The estimated toxicity measures are used as inputs to the SSD modeling phase, which similarly avoids explicit recognition of the temporal component. The present study extends some commonly employed probability models for SSDs to derive theoretical results that characterize the time-dependent nature of hazardous concentration (HCx) values. The authors' results show that even from very simple assumptions, more complex patterns in the SSD time dependency can be revealed.

Survival data analyses in ecotoxicology: critical effect concentrations, methods and models. What should we use?

In ecotoxicology, critical effect concentrations are the most common indicators to quantitatively assess risks for species exposed to contaminants. Three types of critical effect concentrations are classically used: lowest/ no observed effect concentration (LOEC/NOEC), LC( x) (x% lethal concentration) and NEC (no effect concentration). In this article, for each of these three types of critical effect concentration, we compared methods or models used for their estimation and proposed one as the most appropriate. We then compared these critical effect concentrations to each other. For that, we used nine survival data sets corresponding to D. magna exposition to nine different contaminants, for which the time-course of the response was monitored. Our results showed that: (i) LOEC/NOEC values at day 21 were method-dependent, and that the Cochran-Armitage test with a step-down procedure appeared to be the most protective for the environment; (ii) all tested concentration-response models we compared gave close values of LC50 at day 21, nevertheless the Weibull model had the lowest global mean deviance; (iii) a simple threshold NEC-model both concentration and time dependent more completely described whole data (i.e. all timepoints) and enabled a precise estimation of the NEC. We then compared the three critical effect concentrations and argued that the use of the NEC might be a good option for environmental risk assessment.

Population-level modeling to account for multigenerational effects of uranium in Daphnia magna

As part of the ecological risk assessment associated with radionuclides in freshwater ecosystems, toxicity of waterborne uranium was recently investigated in the microcrustacean Daphnia magna over a three-generation exposure (F0, F1, and F2). Toxic effects on daphnid life history and physiology, increasing over generations, were demonstrated at the organism level under controlled laboratory conditions. These effects were modeled using an approach based on the dynamic energy budget (DEB). For each of the three successive generations, DEBtox (dynamic energy budget applied to toxicity data) models were fitted to experimental data. Lethal and sublethal DEBtox outcomes and their uncertainty were projected to the population level using population matrix techniques. To do so, we compared two modeling approaches in which experimental results from F0, F1, and F2 generations were either considered separately (F0-, F1-, and F2-based simulations) or together in the actual succession of F0, F1, and F2 generations (multi-F-based simulation). The first approach showed that considering results from F0 only (equivalent to a standard toxicity test) would lead to a severe underestimation of uranium toxicity at the population level. Results from the second approach showed that combining effects in successive generations cannot generally be simplified to the worst case among F0-, F1-, and F2-based population dynamics.

Comparison of bioassays with different exposure time patterns: the added value of dynamic modelling in predictive ecotoxicology

The purpose of this study was to compare Daphnia magna responses to cadmium between two toxicity experiments performed in static and flow-through conditions. As a consequence of how water was renewed, the two experiments were characterised by two different exposure time patterns for daphnids, time-varying and constant, respectively. Basing on survival, growth and reproduction, we addressed the questions of organism development and sensitivity to cadmium. Classical analysis methods are not designed to deal with the time dimension and therefore not suitable to compare effects of different exposure time patterns. We used instead a dynamic modelling framework taking all timepoints and the time course of exposure into account, making comparable the results obtained from our two experiments. This modelling framework enabled us to detect an improvement of organism development in flow-through conditions compared to static ones and infer similar sensitivity to cadmium for both exposure time patterns.

A new perspective on the Dunnett procedure: filling the gap between NOEC/LOEC and ECx concepts

The no-observed-effect concentration (NOEC) is known to be based on a wrong usage of hypothesis tests, and the use of confidence intervals is preferred. The purpose of the present study is to provide an easy and proper way to interpret ecotoxicological tests based on simultaneous confidence intervals associated with the commonly used Dunnett procedure, and to show how these intervals may allow one to infer ECx values (effective concentrations).

Bayesian modelling of daphnid responses to time-varying cadmium exposure in laboratory aquatic microcosms

Experiments were carried out to test the effects of cadmium on five aquatic species in 2-L indoor freshwater/sediment microcosms. Experimental data were collected over 21 days in static conditions, i.e. the microcosms evolved without water renewal. Because of speciation, the total cadmium concentration in water decreased with time. Here we present a focus on Daphnia magna responses. For the three life history traits we considered (survival, growth and reproduction), mathematical effect models were built based on threshold stress functions involving no effect concentrations (NECs). These models took the time-varying conditions of exposure into account through a time-recurrent formalism. Within a Bayesian framework, four kinds of data were fitted simultaneously (exposure, survival, growth and reproduction), using an appropriate error model for each endpoint. Hence, NECs were determined as well as their associated estimation uncertainty. Through this modelling approach, we demonstrate that thresholds for stress functions can be successfully inferred even in experimental setup more complex than standard bioassays.

Probabilistic modeling of the fate of Listeria monocytogenes in diced bacon during the manufacturing process

To assess the impact of the manufacturing process on the fate of Listeria monocytogenes, we built a generic probabilistic model intended to simulate the successive steps in the process. Contamination evolution was modeled in the appropriate units (breasts, dice, and then packaging units through the successive steps in the process). To calibrate the model, parameter values were estimated from industrial data, from the literature, and based on expert opinion. By means of simulations, the model was explored using a baseline calibration and alternative scenarios, in order to assess the impact of changes in the process and of accidental events. The results are reported as contamination distributions and as the probability that the product will be acceptable with regards to the European regulatory safety criterion. Our results are consistent with data provided by industrial partners and highlight that tumbling is a key step for the distribution of the contamination at the end of the process. Process chain models could provide an important added value for risk assessment models that basically consider only the outputs of the process in their risk mitigation strategies. Moreover, a model calibrated to correspond to a specific plant could be used to optimize surveillance.

From individual to population level effects of toxicants in the tubicifid Branchiura sowerbyi using threshold effect models in a Bayesian framework

Effects of zinc were studied in the freshwater worm Branchiura sowerbyi using partial and full life-cycle tests. Only newborn and juveniles were sensitive to zinc, displaying effects on survival, growth, and age at first brood at environmentally relevant concentrations. Threshold effect models were proposed to assess toxic effects on individuals. They were fitted to life-cycle test data using Bayesian inference and adequately described life-history trait data in exposed organisms. The daily asymptotic growth rate of theoretical populations was then simulated with a matrix population model, based upon individual-level outputs. Population-level outputs were in accordance with existing literature for controls. Working in a Bayesian framework allowed incorporating parameter uncertainty in the simulation of the population-level response to zinc exposure, thus increasing the relevance of test results in the context of ecological risk assessment.

A Bayesian approach to analyzing ecotoxicological data

Standardized chronic toxicity tests are usually analyzed using a NOEC (no observed effect concentration) or ECx (x% effect concentration) calculation. However,these methods provide very little information for the material cost they entail. It has been proposed that biology-based methods, such as the DEBtox approach, would make better use of the data available. DEBtox deals with the energy balance between physiological processes, and gives insight on how a compound disturbs it. We propose that data analysis can be further improved by estimating the DEBtox parameters using the considerable expertise available in laboratories and/or the literature. The Bayesian inference appears to be an appropriate estimation method for this purpose, as this technique takes expertise into account as prior probability distribution for each parameter, and provides the corresponding posterior distributions given the data. From these posterior distributions, point estimates can easily be deduced, but also credible intervals which are ideal for use in risk assessment. In this paper, we demonstrate this approach through the analysis of two 21-day Daphnia reproduction tests.

DEBtox theory and matrix population models as helpful tools in understanding the interaction between toxic cyanobacteria and zooplankton

Bioassays were performed to find out how field samples of the toxic cyanobacteria Microcystis aeruginosa affect Moina micrura, a cladoceran found in the tropical Jacarepagua Lagoon (Rio de Janeiro, Brazil). The DEBtox (Dynamic Energy Budget theory applied to toxicity data) approach has been proposed for use in analysing chronic toxicity tests as an alternative to calculating the usual safety parameters (NOEC, ECx). DEBtox theory deals with the energy balance between physiological processes (assimilation, maintenance, growth and reproduction), and it can be used to investigate and compare various hypotheses concerning the mechanism of action of a toxicant. Even though the DEBtox framework was designed for standard toxicity bioassays carried out with standard species (fish, daphnids), we applied the growth and reproduction models to M. micrura, by adapting the data available using a weight-length allometric relationship. Our modelling approach appeared to be very relevant at the individual level, and confirmed previous conclusions about the toxic mechanism. In our study we also wanted to assess the toxic effects at the population level, which is a more relevant endpoint in risk assessment. We therefore incorporated both lethal and sublethal toxic effects in a matrix population model used to calculate the finite rate of population change as a continuous function of the exposure concentration. Alongside this calculation, we constructed a confidence band to predict the critical exposure concentration for population health. Finally, we discuss our findings with regard to the prospects for further refining the analysis of ecotoxicological data.