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Groundwater is essential for the provision of drinking water in many areas around the world. The performance of the groundwater-bearing aquifer relies on the ecosystem services provided by groundwater-related organisms. Therefore, if remediation of contaminated groundwater is necessary, the remediation method has to be carefully selected to avoid risk-risk trade-offs that might impact these ecosystems. In the present study, the environmental risk of the in situ remediation agent Carbo-Iron was performed. Carbo-Iron® is a composite of zero valent nano-iron and active carbon. Existing ecotoxicity data were complemented by studies with Daphnia magna (Crustacea), Scenedesmus vacuolatus (Algae), Chironomus riparius (Insecta) and nitrifying soil microorganisms. The predicted no effect concentration of 0.1 mg/L was derived from acute and chronic ecotoxicity studies. It was compared to measured and modelled environmental concentrations of Carbo-Iron applied in a groundwater contaminated with chlorohydrocarbons in a field study and risk ratios were derived. A comprehensive assessment approach was developed further based on existing strategies and used to identify changes of the environmental risk due to the remediation of the contaminated site with Carbo-Iron. With the data used in the present study, the total environmental risk decreased by approximately 50% in the heavily contaminated zones after the application of Carbo-Iron. Thus, based on the results of the present study, the benefit of remediation with Carbo-Iron seems to outweigh its negative effects on the environment.

Some recent studies showed that in vitro bioassays based on fish or human estrogen receptor (ER) activation may have distinct responses to environmental samples, highlighting the need to better understand bioassay-specific ER response to environmental mixtures. For this purpose, we investigated a 12-compound mixture in two mixture ratios (M1 and M2) on zebrafish (zf) liver cells stably expressing zfERα (ZELHα cells) or zfERβ2 (ZELHβ2 cells) and on human ER-reporter gene (MELN) cells. The mixture included the well-known ER ligands bisphenol A (BPA) and genistein (GEN), and other compounds representatives of a freshwater background contamination. In this context, the study aimed at assessing the robustness of concentration addition (CA) model and the potential confounding influence of other chemicals by testing subgroups of ER activators, ER inhibitors or ER activators and inhibitors combined. Individual chemical testing showed a higher prevalence of ER inhibitors in zebrafish than human cells (e.g. propiconazole), and some chemicals inhibited zfER but activated hER response (e.g. benzo(a)pyrene, triphenylphosphate). The estrogenic activity of M1 and M2 was well predicted by CA in MELN cells, whereas it was significantly lower than predicted in ZELHβ2 cells, contrasting with the additive effects observed for BPA and GEN binary mixtures. When testing the subgroups of ER activators and inhibitors combined, the deviation from additivity in ZELHβ2 cells was caused by zebrafish-specific inhibiting chemicals. This study provides novel information on the ability of environmental pollutants to interfere with zfER signalling and shows that non-estrogenic chemicals can influence the response to a mixture of xeno-estrogens in a bioassay-specific manner.

Background: Humans and environmental organisms are constantly exposed to complex mixtures of chemicals. Extending our knowledge about the combined effects of chemicals is thus essential for assessing the potential consequences of these exposures. In this context, comprehensive molecular readouts as retrieved by omics techniques are advancing our understanding of the diversity of effects upon chemical exposure. This is especially true for effects induced by chemical concentrations that do not instantaneously lead to mortality, as is commonly the case for environmental exposures. However, omics profiles induced by chemical exposures have rarely been systematically considered in mixture contexts. Objectives: In this study, we aimed to investigate the predictability of chemical mixture effects on the whole-transcriptome scale. Methods: We predicted and measured the toxicogenomic effects of a synthetic mixture on zebrafish embryos. The mixture contained the compounds diuron, diclofenac, and naproxen. To predict concentration- and time-resolved whole-transcriptome responses to the mixture exposure, we adopted the mixture concept of concentration addition. Predictions were based on the transcriptome profiles obtained for the individual mixture components in a previous study. Finally, concentration- and time-resolved mixture exposures and subsequent toxicogenomic measurements were performed and the results were compared with the predictions. Results: This comparison of the predictions with the observations showed that the concept of concentration addition provided reasonable estimates for the effects induced by the mixture exposure on the whole transcriptome. Although nonadditive effects were observed only occasionally, combined, that is, multicomponent-driven, effects were found for mixture components with anticipated similar, as well as dissimilar, modes of action. Discussion: Overall, this study demonstrates that using a concentration- and time-resolved approach, the occurrence and size of combined effects of chemicals may be predicted at the whole-transcriptome scale. This allows improving effect assessment of mixture exposures on the molecular scale that might not only be of relevance in terms of risk assessment but also for pharmacological applications. https://doi.org/10.1289/EHP7773

Background Humans and wildlife are continuously exposed to chemical mixtures. These mixtures vary in composition but typically contain hundreds of micropollutants at low concentrations. As it is not feasible to measure the toxicity of all possibly occurring mixtures, there is a need to predict mixture toxicity. Two models, Concentration Addition (CA) and Independent Action (IA), have been applied to estimate mixture toxicity. Here, we compared measured with predicted toxicity of nine mixtures designed from 15 environmentally relevant substances in zebrafish embryos to investigate the usability of these models for predicting phenotypic effects in a whole organism short term acute assay. Results In total, we compared 177 toxicity values derived from 31 exposure scenarios with their predicted counterparts. Our results show that mixture toxicity was either correctly estimated (86%) by the prediction window, the concentration-effect space that is spanned between both models, or was underestimated with both models (14%). The CA model correctly predicted the measured mixture toxicity in 100% of cases when a prediction deviation factor of 2.5 was allowed. However, prediction accuracy of mixture toxicity prediction was dependent on exposure duration and mixture potency. The CA model showed highest prediction quality for long-term exposure with highly potent mixtures, respectively, whereas IA proved to be more accurate for short-term exposure with less potent mixtures. Obtained mixture concentration–response curves were steep and indicated the occurrence of remarkable combined effects as mixture constituents were applied at concentrations below their respective individual effect threshold in 90% of all investigated cases. Conclusions Experimental factors, such as exposure duration or mixture potency, influence the prediction accuracy of both inspected models. The CA model showed highest prediction accuracy even for a set of diverse mixtures and various exposure conditions. However, the prediction window served as the most robust predicator to estimate mixture toxicity. Overall, our results demonstrate the importance of considering mixture toxicity in risk assessment schemes and give guidance for future experiment design regarding mixture toxicity investigations.

Chemicals considered as neuroactive (such as certain pesticides, pharmaceuticals, and industrial chemicals) are among the largest groups of bioactive substances recently detected in European rivers. However, the determination of nervous-system-specific effects has been limited using in vitro tests or conventional end points including lethality. Thus, neurobehavioral tests using in vivo models (e.g., zebrafish embryo) have been proposed as complementary approaches. To investigate the specificity and sensitivity of a light-dark transition locomotor response (LMR) test in 4 to 5 days post fertilization zebrafish with respect to different modes of action (MoAs), we analyzed a set of 18 environmentally relevant compounds with various anticipated MoAs. We found that exposure-induced behavioral alterations were reproducible and dependent on concentration and time. Comparative and quantitative analyses of the obtained locomotor patterns revealed that behavioral effects were not restricted to compounds primarily known to target the nervous system. A clear distinction of MoAs based on locomotor patterns was not possible for most compounds. Furthermore, chemicals with an anticipated same MoA did not necessarily provoke similar behavioral phenotypes. Finally, we determined an increased sensitivity (≥10-fold) compared to observed mortality in the LMR assay for five of eight neuroactive chemicals as opposed to non-neuroactive compounds.

Not much is known about the biotransformation capability of zebrafish (Danio rerio) embryos. For understanding possible toxicity differences to adult fish, it might be crucial to understand the biotransformation of chemicals in zebrafish embryos i.e. as part of toxicokinetics. The biotransformation capabilities were analysed for two different stages of zebrafish embryos in conjunction with the internal concentrations of a xenobiotic. Zebrafish embryos of the late cleavage/early blastula period (2–26 hpf) and the early pharyngula period (26–50 hpf) were exposed for 24 h to the AhR binding compound benz[a]anthracene (BaA). Time dependent changes in cyp transcription (cyp1a, cyp1b1, cyp1c1 and cyp1c2) as well as concentration & time-dependent courses of BaA in the fish embryo and the exposure medium were analysed. Additionally, the CYP mediated formation of biotransformation products was investigated. We found correlations between transcriptional responses and the internal concentration for both exposure types. These correlations were depending on the start of the exposure i.e. the age of the exposed embryo. While no significant induction of the examined gene transcripts was observed in the first 12 h of exposure beginning in the blastula period a correlation was apparent when exposure started later i.e. in the pharyngula period. A significant induction of cyp1a was detected already after 1.5 h of BaA exposure. Gene transcripts for cyp1b1, cyp1c1 and cyp1c2 showed expressions distinctly different from cyp1a and were, in general, less inducible by BaA in both exposure windows. The toxicokinetic analysis showed that the biotransformation capability was fivefold higher in the older fish embryos. Biotransformation products of phase I reactions were found between 32 hpf and 50 hpf and were tentatively identified as benz[a]anthracene-phenol and benz[a]anthracene-dihydrodiol-epoxide. In conclusion, not only duration but also onset of exposure in relation to the developmental stage of zebrafish embryos is important in the analysis and interpretation of effects due to different biotransformation capabilities.

The exposome encompasses an individual's exposure to exogenous chemicals, as well as endogenous chemicals that are produced or altered in response to external stressors. While the exposome concept has been established for human health, its principles can be extended to include broader ecological issues. The assessment of exposure is tightly interlinked with hazard assessment. Here, we explore if mechanistic understanding of the causal links between exposure and adverse effects on human health and the environment can be improved by integrating the exposome approach with the adverse outcome pathway (AOP) concept that structures and organizes the sequence of biological events from an initial molecular interaction of a chemical with a biological target to an adverse outcome. Complementing exposome research with the AOP concept may facilitate a mechanistic understanding of stress-induced adverse effects, examine the relative contributions from various components of the exposome, determine the primary risk drivers in complex mixtures, and promote an integrative assessment of chemical risks for both human and environmental health. Keywords: Exposome, AOP, Systems toxicology, Systems biology, Systems chemistry, Risk assessment

Lack of consistent findings in different experimental settings remains a major challenge in toxicogenomics. The present study investigated whether consistency between findings of different microarray experiments can be improved when the analysis is based on a common reference frame (“toxicogenomic universe”), which can be generated using the machine learning algorithm of the self-organizing map (SOM). This algorithm arranges and clusters genes on a 2-dimensional grid according to their similarity in expression across all considered data. In the present study, 19 data sets, comprising of 54 different adult fathead minnow liver exposure experiments, were retrieved from Gene Expression Omnibus and used to train a SOM. The resulting toxicogenomic universe aggregates 58 872 probes to 2500 nodes and was used to project, visualize, and compare the fingerprints of these 54 different experiments. For example, we could identify a common pattern, with 14% of significantly regulated nodes in common, in the data sets of an interlaboratory study of ethinylestradiol exposures. Consistency could be improved compared with the 5% total overlap in regulated genes reported before. Furthermore, we could determine a specific and consistent estrogen-related pattern of differentially expressed nodes and clusters in the toxicogenomic universe by applying additional clustering steps and comparing all obtained fingerprints. Our study shows that the SOM-based approach is useful for generating comparable toxicogenomic fingerprints and improving consistency between results of different experiments. Environ Toxicol Chem 2020;39:526–537. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Background Chemicals induce compound-specific changes in the transcriptome of an organism (toxicogenomic fingerprints). This provides potential insights about the cellular or physiological responses to chemical exposure and adverse effects, which is needed in assessment of chemical-related hazards or environmental health. In this regard, comparison or connection of different experiments becomes important when interpreting toxicogenomic experiments. Owing to lack of capturing response dynamics, comparability is often limited. In this study, we aim to overcome these constraints. Results We developed an experimental design and bioinformatic analysis strategy to infer time- and concentration-resolved toxicogenomic fingerprints. We projected the fingerprints to a universal coordinate system (toxicogenomic universe) based on a self-organizing map of toxicogenomic data retrieved from public databases. Genes clustering together in regions of the map indicate functional relation due to co-expression under chemical exposure. To allow for quantitative description and extrapolation of the gene expression responses we developed a time- and concentration-dependent regression model. We applied the analysis strategy in a microarray case study exposing zebrafish embryos to 3 selected model compounds including 2 cyclooxygenase inhibitors. After identification of key responses in the transcriptome we could compare and characterize their association to developmental, toxicokinetic, and toxicodynamic processes using the parameter estimates for affected gene clusters. Furthermore, we discuss an association of toxicogenomic effects with measured internal concentrations. Conclusions The design and analysis pipeline described here could serve as a blueprint for creating comparable toxicogenomic fingerprints of chemicals. It integrates, aggregates, and models time- and concentration-resolved toxicogenomic data.

Environmental water quality monitoring aims to provide the data required for safeguarding the environment against adverse biological effects from multiple chemical contamination arising from anthropogenic diffuse emissions and point sources. Here, we integrate the experience of the international EU-funded project SOLUTIONS to shift the focus of water monitoring from a few legacy chemicals to complex chemical mixtures, and to identify relevant drivers of toxic effects. Monitoring serves a range of purposes, from control of chemical and ecological status compliance to safeguarding specific water uses, such as drinking water abstraction. Various water sampling techniques, chemical target, suspect and non-target analyses as well as an array of in vitro, in vivo and in situ bioanalytical methods were advanced to improve monitoring of water contamination. Major improvements for broader applicability include tailored sampling techniques, screening and identification techniques for a broader and more diverse set of chemicals, higher detection sensitivity, standardized protocols for chemical, toxicological, and ecological assessments combined with systematic evidence evaluation techniques. No single method or combination of methods is able to meet all divergent monitoring purposes. Current monitoring approaches tend to emphasize either targeted exposure or effect detection. Here, we argue that, irrespective of the specific purpose, assessment of monitoring results would benefit substantially from obtaining and linking information on the occurrence of both chemicals and potentially adverse biological effects. In this paper, we specify the information required to: (1) identify relevant contaminants, (2) assess the impact of contamination in aquatic ecosystems, or (3) quantify cause–effect relationships between contaminants and adverse effects. Specific strategies to link chemical and bioanalytical information are outlined for each of these distinct goals. These strategies have been developed and explored using case studies in the Danube and Rhine river basins as well as for rivers of the Iberian Peninsula. Current water quality assessment suffers from biases resulting from differences in approaches and associated uncertainty analyses. While exposure approaches tend to ignore data gaps (i.e., missing contaminants), effect-based approaches penalize data gaps with increased uncertainty factors. This integrated work suggests systematic ways to deal with mixture exposures and combined effects in a more balanced way, and thus provides guidance for future tailored environmental monitoring. © 2019, The Author(s)., Funding text #1 1 UFZ‑Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig, Germany. 2 Institute for Environmental Research, RWTH Aachen University, 52074 Aachen, Germany. 3 Office of Research and Development, Atlantic Ecology Division, United States Environmental Protection Agency, Narragansett, RI, USA. 4 Center for Applied Geoscience, Eberhard Karls Uni‑ versity Tübingen, 72074 Tübingen, Germany. 5 Alterra, Wageningen University and Research Centre, P.O. Box 47, 6700 AA Wageningen, The Netherlands. 6 Environment and Climate Change Canada, Burlington, ON, Canada. 7 Sophus Bauditz Vej 19 B, 2800 Kgs. Lyngby, Denmark. 8 Water and Soil Quality Research Group, Institute of Environmental Assessment and Water Research (IDAEA‑ CSIC), Jordi Girona 18‑26, 08034 Barcelona, Spain. 9 Unité d’Ecotoxicologie Funding text #2 The SOLUTIONS Project is supported by the Seventh Framework Programme (FP7‑ENV‑2013) of the European Union under Grant Agreement No. 603437. G.A. Umbuzeiro thanks FAPESP Projects 2013/16956‑6 and 2015/24758‑5. We like to thank all partners for their continued efforts in making this project a success story. Funding text #3 The SOLUTIONS Project is supported by the Seventh Framework Programme (FP7‑ENV‑704 2013) of the European Union under Grant Agreement No. 603437. G.A. Umbuzeiro thanks 705 FAPESP Projects 2013/16956‑6 and 2015/24758‑5.

Environmental quality monitoring of water resources is challenged with providing the basis for safeguarding the environment against adverse biological effects from exposure to anthropogenic chemicals originating from diffuse and point sources. Although current regulatory efforts focus on monitoring and assessing a few legacy chemicals, many more anthropogenic chemicals are and will become detected in aquatic resources as a result of progress in analytical techniques. Assessing this type of exposure information based on available standard approaches from prospective risk assessment for single chemicals inevitably leads to indication of risk in most surface water bodies. As an alternative to generic assessment approaches, effect-based monitoring approaches are suggested. This offers the advantage of reducing uncertainties of effect extrapolation and additionally accounts for mixture effects. To become a credible complement to chemical monitoring information, however, a better understanding of the capabilities and gaps of available effect-based tools is needed. The authors therefore undertook to 1) compile organic contaminants detected in freshwater monitoring studies, 2) provide a synopsis of the mode of action knowledge available for the detected compounds, 3) perform a hazard ranking to identify priority mixtures, and 4) reflect on the challenges to make bioassays fit for effect-based monitoring. The present Focus article shows that chemical occurrence in European freshwaters seems to be highly variable in composition and relative abundancies. Further, although the present mode of action knowledge remains limited, the authors already see the need for batteries of effect-based tools if a more comprehensive coverage of prevailing effect qualities for mixtures is to be targeted. Finally, they suggest a list of organic compounds that could serve as a reference list for effect-based tool validation studies. Environ Toxicol Chem 2016;35:1887-1899. © 2016 SETAC.

International audience; The numbers of potential neurotoxicants in the environment are raising and pose a great risk for humans and the environment. Currently neurotoxicity assessment is mostly performed to predict and prevent harm to human populations. Despite all the efforts invested in the last years in developing novel in vitro or in silico test systems, in vivo tests with rodents are still the only accepted test for neurotoxicity risk assessment in Europe. Despite an increasing number of reports of species showing altered behaviour, neurotoxicity assessment for species in the environment is not required and therefore mostly not performed. Considering the increasing numbers of environmental contaminants with potential neurotoxic potential, eco-neurotoxicity should be also considered in risk assessment. In order to do so novel test systems are needed that can cope with species differences within ecosystems. In the field, online-biomonitoring systems using behavioural information could be used to detect neurotoxic effects and effect-directed analyses could be applied to identify the neurotoxicants causing the effect. Additionally, toxic pressure calculations in combination with mixture modelling could use environmental chemical monitoring data to predict adverse effects and prioritize pollutants for laboratory testing. Cheminformatics based on computational toxicological data from in vitro and in vivo studies could help to identify potential neurotoxicants. An array of in vitro assays covering different modes of action could be applied to screen compounds for neurotoxicity. The selection of in vitro assays could be guided by AOPs relevant for eco-neurotoxicity. In order to be able to perform risk assessment for eco-neurotoxicity, methods need to focus on the most sensitive species in an ecosystem. A test battery using species from different trophic levels might be the best approach. To implement eco-neurotoxicity assessment into European risk assessment, cheminformatics and in vitro screening tests could be used as first approach to identify eco-neurotoxic pollutants. In a second step, a small species test battery could be applied to assess the risks of ecosystems.

Pesticides and biocides (PaB) are ubiquitously present in aquatic ecosystems due to their widespread application and have been detected in rivers at concentrations that may cause distress to aquatic life. Many of these compounds accumulate in sediments acting as long-term source for aquatic ecosystems. However, data on sediment contamination with current-use PaB in Europe are scarce. Thus, in this study, we elucidated PaB patterns and associated risks in sediments of seven major European rivers focusing on their last stretch as an integrative sink of particles transported by these rivers. Sediments were extracted with pressurized liquid extraction (PLE) using a broad-spectrum method recovering many compound classes with a wide range of physicochemical properties. Altogether 126 compounds were analyzed and 81 of them were detected with LC-HRMS and GC-NCI-MS/MS at least in one of the sediments. The highest number of compounds was detected (59) in River Elbe sediments close to Cuxhaven with outstanding concentrations ranging from 0.8 to 1691 mg/g organic carbon. Multivariate analysis identified a cluster with 3 ubiquitous compounds (cyhalothrin, carbendazim, fenpropimorph) and three clusters of chemicals with higher variability within and between rivers. Risk assessment indicates an acute toxic risk to benthic crustaceans at all investigated sites with the pyrethroids tefluthrin and cyfluthrin together with the fungicide carbendazim as the main drivers. Risks to algae were driven at most sites almost exclusively by photosynthesis inhibitors with estuary-specific herbicide mixtures, while in the rivers Po and Gironde cell division inhibitors played an important role at some sites. Mixtures of specific concern have been defined and suggested for integration in future monitoring programs.

In vitro bioassays are increasingly used for water quality monitoring. Surface water samples often need to be enriched to observe an effect and solid-phase extraction (SPE) is commonly applied for this purpose. The applied methods are typically optimised for the recovery of target chemicals and not for effect recovery for bioassays. A review of the few studies that have evaluated SPE recovery for bioassays showed a lack of experimentally determined recoveries. Therefore, we systematically measured effect recovery of a mixture of 579 organic chemicals covering a wide range of physicochemical properties that were spiked into a pristine water sample and extracted using large volume solid-phase extraction (LVSPE). Assays indicative of activation of xenobiotic metabolism, hormone receptor-mediated effects and adaptive stress responses were applied, with non-specific effects determined through cytotoxicity measurements. Overall, effect recovery was found to be similar to chemical recovery for the majority of bioassays and LVSPE blanks had no effect. Multi-layer SPE exhibited greater recovery of spiked chemicals compared to LVSPE, but the blanks triggered cytotoxicity at high enrichment. Chemical recovery data together with single chemical effect data were used to retrospectively estimate with reverse recovery modelling that there was typically less than 30% effect loss expected due to reduced SPE recovery in published surface water monitoring studies. The combination of targeted experiments and mixture modelling clearly shows the utility of SPE as a sample preparation method for surface water samples, but also emphasizes the need for adequate controls when extraction methods are adapted from chemical analysis workflows.

Environment international 114, 95-106 (2018). doi:10.1016/j.envint.2018.02.013, Published by Elsevier Science, Amsterdam [u.a.]

Sites of wastewater discharge are hotspots for pollution of freshwaters with organic micropollutants and are often associated with adverse effects to aquatic organisms. The assessment, monitoring and managment of these hotspots is challenged by variations in the pollutant mixture composition due to season, weather conditions and random spills. In this study, we unraveled temporal exposure patterns in organic micropollutant mixtures from wastewater discharge and analyzed respective acute and sublethal risks for aquatic organisms. Samples were taken from two components of a separate sewer system i) a wastewater treatment plant (WWTP) and ii) a rain sewer of a medium size town as well as from the receiving river in different seasons. Rain sewer samples were separately collected for rain and dry - weather conditions. We analyzed 149 compounds by liquid chromatography-tandem mass spectrometry (LC-MS/MS). By considering the pollution dynamics in the point sources, we reduced the complexity of pollutant mixtures by k-means clustering to a few emission groups representing temporal and weather-related pollution patterns. From these groups, we derived biological quality element (BQE) - specific risk patterns. In most cases, one main risk driving emission group and a few individual risk driving compounds were identified for each BQE. While acute risk for fish was quite low, algae were exposed to seasonally emitted herbicides (terbuthylazine, spiroxamine) and crustaceans to randomly spilled insecticides (diazinon, dimethoate). Sublethal risks for all BQE were strongly influenced by constantly emitted pollutants, above all, pharmaceuticals. Variability of risks in the river was mainly driven by water discharge of the river rather than by season or peak events. Overall, the studied WWTP represented the major pollution source with a specific emission of agricultural compounds. However, the investigated rain sewer showed to be a constant pollution source due to illicit connections and was an important entry route for high loads of insecticides and biocides due to spills or incorrect disposal. By considering these pollution and risk dynamics, monitoring strategies may be optimized with a special focus on times of low flow conditions in the river, rain events and seasonally emitted risk drivers.

Surface waters can contain a diverse range of organic pollutants, including pesticides, pharmaceuticals and industrial compounds. While bioassays have been used for water quality monitoring, there is limited knowledge regarding the effects of individual micropollutants and their relationship to the overall mixture effect in water samples. In this study, a battery of in vitro bioassays based on human and fish cell lines and whole organism assays using bacteria, algae, daphnids and fish embryos was assembled for use in water quality monitoring. The selection of bioassays was guided by the principles of adverse outcome pathways in order to cover relevant steps in toxicity pathways known to be triggered by environmental water samples. The effects of 34 water pollutants, which were selected based on hazard quotients, available environmental quality standards and mode of action information, were fingerprinted in the bioassay test battery. There was a relatively good agreement between the experimental results and available literature effect data. The majority of the chemicals were active in the assays indicative of apical effects, while fewer chemicals had a response in the specific reporter gene assays, but these effects were typically triggered at lower concentrations. The single chemical effect data were used to improve published mixture toxicity modeling of water samples from the Danube River. While there was a slight increase in the fraction of the bioanalytical equivalents explained for the Danube River samples, for some endpoints less than 1% of the observed effect could be explained by the studied chemicals. The new mixture models essentially confirmed previous findings from many studies monitoring water quality using both chemical analysis and bioanalytical tools. In short, our results indicate that many more chemicals contribute to the biological effect than those that are typically quantified by chemical monitoring programs or those regulated by environmental quality standards. This study not only demonstrates the utility of fingerprinting single chemicals for an improved understanding of the biological effect of pollutants, but also highlights the need to apply bioassays for water quality monitoring in order to prevent underestimation of the overall biological effect.

Three water contaminants were selected to be tested in the zebrafish embryo toxicity test (DarT) in order to investigate the sensitivity of the zebrafish embryo toxicity test with respect to mixture effect detection. The concentration-response curves for the observed effects lethality and hypo-pigmentation were calculated after an exposure of the embryos for 96 h with a fungicide (carbendazim), a plasticizer or propellent precursor (2,4-DNT: 2,4- dinitrotoluene) and an aromatic compound (AαC: 2-amino-9H-pyrido[2,3-b]indol), respectively. Follow-up mixture tests were based on the calculated LC50 or EC50 of the single compounds and combined effects were predicted according to the mixture concepts of concentration addition (CA) and independent action (IA). The order of toxicity for the single substances was carbendazim (LC50 = 1.25 μM) < AαC (LC50 = 8.16 μM) < 2,4-DNT (LC50 = 177.05 μM). For AαC and 2,4 DNT hypo-pigmentation was observed in addition (AαC EC50 = 1.81 μM; 2,4-DNT EC50 = 8.81 μM). Two binary and one ternary mixture were studied on lethality and one on hypo-pigmentation: 2,4-DNT/AαC (LC50 = 119.21 μM, EC50 = 5.37 μM), carbendazim/AαC (LC50 = 4.49 μM) and AαC/Carbendazim/2,4 DNT (LC50 = 108.62 μM). Results showed that the effects were in agreement with the CA model when substances were tested in mixtures. Therefore, in a reasonable worst case scenario substance combination effects in fish embryos were at maximum only prone to overestimation when using CA as the mixture concept.

Aquatic environments are often contaminated with complex mixtures of chemicals that may pose a risk to ecosystems and human health. This contamination cannot be addressed with target analysis alone but tools are required to reduce this complexity and identify those chemicals that might cause adverse effects. Effect-directed analysis (EDA) is designed to meet this challenge and faces increasing interest in water and sediment quality monitoring. Thus, the present paper summarizes current experience with the EDA approach and the tools required, and provides practical advice on their application. The paper highlights the need for proper problem formulation and gives general advice for study design. As the EDA approach is directed by toxicity, basic principles for the selection of bioassays are given as well as a comprehensive compilation of appropriate assays, including their strengths and weaknesses. A specific focus is given to strategies for sampling, extraction and bioassay dosing since they strongly impact prioritization of toxicants in EDA. Reduction of sample complexity mainly relies on fractionation procedures, which are discussed in this paper, including quality assurance and quality control. Automated combinations of fractionation, biotesting and chemical analysis using so-called hyphenated tools can enhance the throughput and might reduce the risk of artifacts in laboratory work. The key to determining the chemical structures causing effects is analytical toxicant identification. The latest approaches, tools, software and databases for target-, suspect and non-target screening as well as unknown identification are discussed together with analytical and toxicological confirmation approaches. A better understanding of optimal use and combination of EDA tools will help to design efficient and successful toxicant identification studies in the context of quality monitoring in multiply stressed environments.

Acetylcholinesterase (AChE) inhibitors are widely used as pesticides and drugs. Their primary effect is the overstimulation of cholinergic receptors which results in an improper muscular function. During vertebrate embryonic development nerve activity and intracellular downstream events are critical for the regulation of muscle fiber formation. Whether AChE inhibitors and related neurotoxic compounds also provoke specific changes in gene transcription patterns during vertebrate development that allow them to establish a mechanistic link useful for identification of developmental toxicity pathways has, however, yet not been investigated. Therefore we examined the transcriptomic response of a known AChE inhibitor, the organophosphate azinphos-methyl (APM), in zebrafish embryos and compared the response with two non-AChE inhibiting unspecific control compounds, 1,4-dimethoxybenzene (DMB) and 2,4-dinitrophenol (DNP). A highly specific cluster of APM induced gene transcripts was identified and a subset of strongly regulated genes was analyzed in more detail. The small heat shock protein hspb11 was found to be the most sensitive induced gene in response to AChE inhibitors. Comparison of expression in wildtype, ache and sop(fixe) mutant embryos revealed that hspb11 expression was dependent on the nicotinic acetylcholine receptor (nAChR) activity. Furthermore, modulators of intracellular calcium levels within the whole embryo led to a transcriptional up-regulation of hspb11 which suggests that elevated intracellular calcium levels may regulate the expression of this gene. During early zebrafish development, hspb11 was specifically expressed in muscle pioneer cells and Hspb11 morpholino-knockdown resulted in effects on slow muscle myosin organization. Our findings imply that a comparative toxicogenomic approach and functional analysis can lead to the identification of molecular mechanisms and specific marker genes for potential neurotoxic compounds.

Surface waters can contain a range of micropollutants from point sources, such as wastewater effluent, and diffuse sources, such as agriculture. Characterizing the source of micropollutants is important for reducing their burden and thus mitigating adverse effects on aquatic ecosystems. In this study, chemical analysis and bioanalysis were applied to assess the micropollutant burden during low flow conditions upstream and downstream of three wastewater treatment plants (VVWTPs) discharging into small streams in the Swiss Plateau. The upstream sites had no input of wastewater effluent, allowing a direct comparison of the observed effects with and without the contribution of wastewater. Four hundred and five chemicals were analyzed, while the applied bioassays included activation of the aryl hydrocarbon receptor, activation of the androgen receptor, activation of the estrogen receptor, photosystem II inhibition, acetylcholinesterase inhibition and adaptive stress responses for oxidative stress, genotoxicity and inflammation, as well as assays indicative of estrogenic activity and developmental toxicity in zebrafish embryos. Chemical analysis and bioanalysis showed higher chemical concentrations and effects for the effluent samples, with the lowest chemical concentrations and effects in most assays for the upstream sites. Mixture toxicity modeling was applied to assess the contribution of detected chemicals to the observed effect. For most bioassays, very little of the observed effects could be explained by the detected chemicals, with the exception of photosystem II inhibition, where herbicides explained the majority of the effect. This emphasizes the importance of combining bioanalysis with chemical analysis to provide a more complete picture of the micropollutant burden. While the wastewater effluents had a significant contribution to micropollutant burden downstream, both chemical analysis and bioanalysis showed a relevant contribution of diffuse sources from upstream during low flow conditions, suggesting that upgrading WWTPs will not completely reduce the micropollutant burden, but further source control measures will be required. (C) 2016 Elsevier B.V. All rights reserved.