Assessment of chemical mixtures and groundwater effects on Daphnia magna transcriptomics

Metabolomics revealed disruptions in amino acid and antioxidant biochemistry in Daphnia magna exposed to industrial effluents associated with plastic and polymer production

Industrial wastewater effluents are a major source of chemicals in aquatic environments, and many of these chemicals may negatively impact aquatic life. In this study, the crustacean Daphnia magna, a common model organism in ecotoxicity studies, was exposed for 48 h to nine different industrial effluent samples from manufacturing facilities associated with the production of plastics, polymers, and coating products at a range of dilutions: 10, 25, 50, 100% (undiluted). A targeted metabolomic-based approach using liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to quantify polar metabolites from individual daphnids that survived the 48 h exposure. Multivariate analyses and metabolite changes revealed metabolic perturbations across all effluent samples studied, with non-monotonic responses and both up and downregulation relative to the unexposed control. Pathway analyses indicated the disruption of similar and distinct pathways, mostly connected to protein synthesis, amino acid metabolism, and antioxidant processes. Overall, we observed disruptions in Daphnia biochemistry that were similar across the effluent samples, but with unique features for each effluent sample. Additionally, non-monotonic heightened responses suggested additive and/or synergistic interactions between the chemicals within the industrial effluents. These findings demonstrate that targeted metabolomic approaches are a powerful tool for the biomonitoring of aquatic ecosystems in the context of complex mixtures, such as industrial wastewater effluents.

Effects of Single and Combined Low Concentrations of Neuroactive Drugs on Daphnia magna Reproduction and Transcriptomic Responses

Assessing the risk of neuroactive pharmaceuticals in the environment requires an understanding of their joint effects at low concentrations across species. Here, we assessed reproductive and transcriptional effects of single and ternary equi-effective mixture exposure to propranolol, diazepam, and carbamazepine on the crustacean Daphnia magna at environmentally relevant concentrations. The three compounds enhanced reproduction in adults and induced specific transcriptome changes in preadolescent individuals. Comparison of the results from single exposures to a ternary equi-effective mixture of the three compounds showed additive action. Transcriptomic analyses identified 3248 genes affected by at least one of the treatments, which were grouped into four clusters. Two clusters (1897 gene transcripts in total) behaved similarly, appearing either over- or under-represented relative to control, in all single and mixture treatments. The third and fourth clusters grouped genes differently transcribed upon exposure to diazepam and propranolol, respectively. Functional transcriptomics analysis indicated that the four clusters shared major deregulated signaling pathways implicated on energy, growth, reproduction, and neurologically related processes, which may be responsible for the observed reproductive effects. Thus, our study showed additive effects at the transcriptional and physiological level and provides a novel approach to the analysis of environmentally relevant mixtures of neuroactive compounds.

Deciphering the Combined Effects of Environmental Stressors on Gene Transcription: A Conceptual Approach

The use of classical mixture toxicity models to predict the combined effects of environmental stressors based on toxicogenomics (OMICS) data is still in its infancy. Although several studies have made attempts to implement mixture modeling in OMICS analysis to understand the low-dose interactions of stressors, it is not clear how interactions occur at the molecular level and how results generated from such approaches can be better used to inform future studies and cumulative hazard assessment of multiple stressors. The present work was therefore conducted to propose a conceptual approach for combined effect assessment using global gene expression data, as illustrated by a case study on assessment of combined effects of gamma radiation and depleted uranium (DU) on Atlantic salmon ( Salmo salar). Implementation of the independent action (IA) model in reanalysis of a previously published microarray gene expression dataset was performed to describe gene expression patterns of combined effects and identify key gene sets and pathways that were relevant for understanding the interactive effects of these stressors. By using this approach, 3120 differentially expressed genes (DEGs) were found to display additive effects, whereas 279 (273 synergistic, 6 antagonistic) were found to deviate from additivity. Functional analysis further revealed that multiple toxicity pathways, such as oxidative stress responses, cell cycle regulation, lipid metabolism, and immune responses were enriched by DEGs showing synergistic gene expression. A key toxicity pathway of DNA damage leading to enhanced tumorigenesis signaling is highlighted and discussed in detail as an example of how to take advantage of the approach. Furthermore, a conceptual workflow describing the integration of combined effect modeling, OMICS analysis, and bioinformatics is proposed. The present study presents a conceptual framework for utilizing OMICS data in combined effect assessment and may provide novel strategies for dealing with data analysis and interpretation of molecular responses of multiple stressors.

The roles of plasticity and evolutionary change in shaping gene expression variation in natural populations of extremophile fish

The notorious plasticity of gene expression responses and the complexity of environmental gradients complicate the identification of adaptive differences in gene regulation among populations. We combined transcriptome analyses in nature with common-garden and exposure experiments to establish cause-effect relationships between the presence of a physiochemical stressor and expression differences, as well as to test how evolutionary change and plasticity interact to shape gene expression variation in natural systems. We studied two evolutionarily independent population pairs of an extremophile fish (Poecilia mexicana) living in toxic, hydrogen sulphide (H₂ S)-rich springs and adjacent nontoxic habitats and assessed genomewide expression patterns of wild-caught and common-garden-raised individuals exposed to different concentrations of H₂ S. We found that 7.7% of genes that were differentially expressed between sulphidic and nonsulphidic ecotypes remained differentially expressed in the laboratory, indicating that sources of selection other than H₂ S-or plastic responses to other environmental factors-contribute substantially to gene expression patterns observed in the wild. Concordantly differentially expressed genes in the wild and the laboratory were primarily associated with H₂ S detoxification, sulphur processing and metabolic physiology. While shared, ancestral plasticity played a minor role in shaping gene expression variation observed in nature, we documented evidence for evolved population differences in the constitutive expression as well as the H₂ S inducibility of candidate genes. Mechanisms underlying gene expression variation also varied substantially across the two ecotype pairs. These results provide a springboard for studying evolutionary modifications of gene regulatory mechanisms that underlie expression variation in locally adapted populations.

Complexities of gene expression patterns in natural populations of an extremophile fish (Poecilia mexicana, Poeciliidae)

Variation in gene expression can provide insights into organismal responses to environmental stress and physiological mechanisms mediating adaptation to habitats with contrasting environmental conditions. We performed an RNA-sequencing experiment to quantify gene expression patterns in fish adapted to habitats with different combinations of environmental stressors, including the presence of toxic hydrogen sulphide (H2 S) and the absence of light in caves. We specifically asked how gene expression varies among populations living in different habitats, whether population differences were consistent among organs, and whether there is evidence for shared expression responses in populations exposed to the same stressors. We analysed organ-specific transcriptome-wide data from four ecotypes of Poecilia mexicana (nonsulphidic surface, sulphidic surface, nonsulphidic cave and sulphidic cave). The majority of variation in gene expression was correlated with organ type, and the presence of specific environmental stressors elicited unique expression differences among organs. Shared patterns of gene expression between populations exposed to the same environmental stressors increased with levels of organismal organization (from transcript to gene to physiological pathway). In addition, shared patterns of gene expression were more common between populations from sulphidic than populations from cave habitats, potentially indicating that physiochemical stressors with clear biochemical consequences can constrain the diversity of adaptive solutions that mitigate their adverse effects. Overall, our analyses provided insights into transcriptional variation in a unique system, in which adaptation to H2 S and darkness coincide. Functional annotations of differentially expressed genes provide a springboard for investigating physiological mechanisms putatively underlying adaptation to extreme environments.

An Overview of Literature Topics Related to Current Concepts, Methods, Tools, and Applications for Cumulative Risk Assessment (2007-2016)

Cumulative risk assessments (CRAs) address combined risks from exposures to multiple chemical and nonchemical stressors and may focus on vulnerable communities or populations. Significant contributions have been made to the development of concepts, methods, and applications for CRA over the past decade. Work in both human health and ecological cumulative risk has advanced in two different contexts. The first context is the effects of chemical mixtures that share common modes of action, or that cause common adverse outcomes. In this context two primary models are used for predicting mixture effects, dose addition or response addition. The second context is evaluating the combined effects of chemical and nonchemical (e.g., radiation, biological, nutritional, economic, psychological, habitat alteration, land-use change, global climate change, and natural disasters) stressors. CRA can be adapted to address risk in many contexts, and this adaptability is reflected in the range in disciplinary perspectives in the published literature. This article presents the results of a literature search and discusses a range of selected work with the intention to give a broad overview of relevant topics and provide a starting point for researchers interested in CRA applications.

Daphnia magna's sense of competition: intra-specific interactions (ISI) alter life history strategies and increase metals toxicity

This work investigates whether the scale-up to multi-animal exposures that is commonly applied in genomics studies provides equivalent toxicity outcomes to single-animal experiments of standard Daphnia magna toxicity assays. Specifically, we tested the null hypothesis that intraspecific interactions (ISI) among D. magna have neither effect on the life history strategies of this species, nor impact toxicological outcomes in exposure experiments with Cu and Pb. The results show that ISI significantly increased mortality of D. magna in both Cu and Pb exposure experiments, decreasing 14 day LC50 s and 95 % confidence intervals from 14.5 (10.9-148.3) to 8.4 (8.2-8.7) µg Cu/L and from 232 (156-4810) to 68 (63-73) µg Pb/L. Additionally, ISI potentiated Pb impacts on reproduction eliciting a nearly 10-fold decrease in the no-observed effect concentration (from 236 to 25 µg/L). As an indication of environmental relevance, the effects of ISI on both mortality and reproduction in Pb exposures were sustained at both high and low food rations. Furthermore, even with a single pair of Daphnia, ISI significantly increased (p < 0.05) neonate production in control conditions, demonstrating that ISI can affect life history strategy. Given these results we reject the null hypothesis and conclude that results from scale-up assays cannot be directly applied to observations from single-animal assessments in D. magna. We postulate that D. magna senses chemical signatures of conspecifics which elicits changes in life history strategies that ultimately increase susceptibility to metal toxicity.

Relating suborganismal processes to ecotoxicological and population level endpoints using a bioenergetic model

Ecological effects of environmental stressors are commonly evaluated using organismal or suborganismal data, such as standardized toxicity tests that characterize responses of individuals (e.g., mortality and reproduction) and a rapidly growing body of "omics" data. A key challenge for environmental risk assessment is relating such information to population dynamics. One approach uses dynamic energy budget (DEB) models that relate growth and reproduction of individuals to underlying flows of energy and elemental matter. We hypothesize that suborganismal information identifies DEB parameters that are most likely impacted by a particular stressor and that the DEB model can then project suborganismal effects on life history and population endpoints. We formulate and parameterize a model of growth and reproduction for the water flea Daphnia magna. Our model resembles previous generic bioenergetic models, but has explicit representation of discrete molts, an important feature of Daphnia life history. We test its ability to predict six endpoints commonly used in chronic toxicity studies in specified food environments. With just one adjustable parameter, the model successfully predicts growth and reproduction of individuals from a wide array of experiments performed in multiple laboratories using different clones of D. magna raised on different food sources. Fecundity is the most sensitive endpoint, and there is broad correlation between the sensitivities of fecundity and long-run growth rate, as is desirable for the default metric used in chronic toxicity tests. Under some assumptions, we can combine our DEB model with the Euler-Lotka equation to estimate longrun population growth rates at different food levels. A review of Daphnia gene-expression experiments on the effects of contaminant exposure reveals several connections to model parameters, in particular a general trend of increased transcript expression of genes involved in energy assimilation and utilization at concentrations affecting growth and reproduction. The sensitivity of fecundity to many model parameters was consistent with frequent generalized observations of decreased expression of genes involved in reproductive physiology, but interpretation of these observations requires further mechanistic modeling. We thus propose an approach based on generic DEB models incorporating few essential species-specific features for rapid extrapolation of ecotoxicogenomic assays for Daphnia-based population risk assessment.

A Bayesian model for the identification of differentially expressed genes in Daphnia magna exposed to munition pollutants

In this article we propose a Bayesian hierarchical model for the identification of differentially expressed genes in Daphnia magna organisms exposed to chemical compounds, specifically munition pollutants in water. The model we propose constitutes one of the very first attempts at a rigorous modeling of the biological effects of water purification. We have data acquired from a purification system that comprises four consecutive purification stages, which we refer to as "ponds," of progressively more contaminated water. We model the expected expression of a gene in a pond as the sum of the mean of the same gene in the previous pond plus a gene-pond specific difference. We incorporate a variable selection mechanism for the identification of the differential expressions, with a prior distribution on the probability of a change that accounts for the available information on the concentration of chemical compounds present in the water. We carry out posterior inference via MCMC stochastic search techniques. In the application, we reduce the complexity of the data by grouping genes according to their functional characteristics, based on the KEGG pathway database. This also increases the biological interpretability of the results. Our model successfully identifies a number of pathways that show differential expression between consecutive purification stages. We also find that changes in the transcriptional response are more strongly associated to the presence of certain compounds, with the remaining contributing to a lesser extent. We discuss the sensitivity of these results to the model parameters that measure the influence of the prior information on the posterior inference.

Synergistic interactions of biotic and abiotic environmental stressors on gene expression

Understanding the response of organisms to multiple stressors is critical for predicting if populations can adapt to rapid environmental change. Natural and anthropogenic stressors often interact, complicating general predictions. In this study, we examined the interactive and cumulative effects of two common environmental stressors, lowered calcium concentration, an anthropogenic stressor, and predator presence, a natural stressor, on the water flea Daphnia pulex. We analyzed expression changes of five genes involved in calcium homeostasis — cuticle proteins (Cutie, Icp2), calbindin (Calb), and calcium pump and channel (Serca and Ip3R) — using real-time quantitative PCR (RT-qPCR) in a full factorial experiment. We observed strong synergistic interactions between low calcium concentration and predator presence. While the Ip3R gene was not affected by the stressors, the other four genes were affected in their transcriptional levels by the combination of the stressors. Transcriptional patterns of genes that code for cuticle proteins (Cutie and Icp2) and a sarcoplasmic calcium pump (Serca) only responded to the combination of stressors, changing their relative expression levels in a synergistic response, while a calcium-binding protein (Calb) responded to low calcium stress and the combination of both stressors. The expression pattern of these genes (Cutie, Icp2, and Serca) were nonlinear, yet they were dose dependent across the calcium gradient. Multiple stressors can have complex, often unexpected effects on ecosystems. This study demonstrates that the dominant interaction for the set of tested genes appears to be synergism. We argue that gene expression patterns can be used to understand and predict the type of interaction expected when organisms are exposed simultaneously to natural and anthropogenic stressors.

Inter- and intraspecies chemical sensitivity: a case study using 2,4-dinitroanisole

Insensitive munitions offer increased safety because of their "insensitivity" to unintended detonation relative to historically used formulations such as 2,4,6-trinitrotoluene (TNT). Dinitroanisole (DNAN) is an insensitive munition constituent, and its solubility and stability warrant investigations of potential toxicological hazard related to manufacturing discharges and training ranges. Although ecotoxicology data are available for other insensitive munition constituents, few data are available for DNAN. In the present study, acute and chronic exposures of a fish (Pimephales promelas) and 2 cladocerans (Ceriodaphnia dubia, Daphnia pulex) were conducted. The 50% lethal concentration (LC50) values of DNAN ranged from 14.2 mg/L to 42.0 mg/L, depending on species. In chronic exposures, fish survival (LC50 = 10.0 mg/L) was more sensitive than cladoceran survival (LC50 = 13.7 to >24.2 mg/L). However, cladoceran reproduction was equally or more sensitive to DNAN (50% inhibition values 2.7-10.6 mg/L, depending on species) than fish endpoints. Daphnia pulex was the most sensitive species, with only slight differences between the 3 populations tested. Although the aquatic toxicity of DNAN was lower than previously reported in the literature for TNT, future research is needed to determine the potential synergistic toxicity of all the constituents in insensitive munition mixtures and the implications of photo-oxidation.

Quantitative structure-toxicity relationship of the aquatic toxicity for various narcotic pollutants using the norm indexes

The aquatic toxicity value of hazardous contaminants plays an important role in the risk assessments of aquatic ecosystems. The following study presents a stable and accurate structure-toxicity relationship model based on the norm indexes for the prediction of toxicity value (log(LC50)) for 190 diverse narcotic pollutants (96 h LC50 data for Poecilia reticulata). Research indicates that this new model is very efficient and provides satisfactory results. The suggested prediction model is evidenced by R(2) (square correlation coefficient) and ARD (average relative difference) values of 0.9376 and 10.45%, respectively, for the training set, and 0.9264 and 13.90% for the testing set. Comparison results with reference models demonstrate that this new method, based on the norm indexes proposed in this work, results in significant improvements, both in accuracy and stability for predicting aquatic toxicity values of narcotic pollutants.

Endocrinology: advances through omics and related technologies

The rapid development of new omics technologies to measure changes at genetic, transcriptomic, proteomic, and metabolomics levels together with the evolution of methods to analyze and integrate the data at a systems level are revolutionizing the study of biological processes. Here we discuss how new approaches using omics technologies have expanded our knowledge especially in nontraditional models. Our increasing knowledge of these interactions and evolutionary pathway conservation facilitates the use of nontraditional species, both invertebrate and vertebrate, as new model species for biological and endocrinology research. The increasing availability of technology to create organisms overexpressing key genes in endocrine function allows manipulation of complex regulatory networks such as growth hormone (GH) in transgenic fish where disregulation of GH production to produce larger fish has also permitted exploration of the role that GH plays in testis development, suggesting that it does so through interactions with insulin-like growth factors. The availability of omics tools to monitor changes at nearly any level in any organism, manipulate gene expression and behavior, and integrate data across biological levels, provides novel opportunities to explore endocrine function across many species and understand the complex roles that key genes play in different aspects of the endocrine function.

Genome-wide transcription profiles reveal genotype-dependent responses of biological pathways and gene-families in Daphnia exposed to single and mixed stressors

The present study investigated the possibilities and limitations of implementing a genome-wide transcription-based approach that takes into account genetic and environmental variation to better understand the response of natural populations to stressors. When exposing two different Daphnia pulex genotypes (a cadmium-sensitive and a cadmium-tolerant one) to cadmium, the toxic cyanobacteria Microcystis aeruginosa, and their mixture, we found that observations at the transcriptomic level do not always explain observations at a higher level (growth, reproduction). For example, although cadmium elicited an adverse effect at the organismal level, almost no genes were differentially expressed after cadmium exposure. In addition, we identified oxidative stress and polyunsaturated fatty acid metabolism-related pathways, as well as trypsin and neurexin IV gene-families as candidates for the underlying causes of genotypic differences in tolerance to Microcystis. Furthermore, the whole-genome transcriptomic data of a stressor mixture allowed a better understanding of mixture responses by evaluating interactions between two stressors at the gene-expression level against the independent action baseline model. This approach has indicated that ubiquinone pathway and the MAPK serine-threonine protein kinase and collagens gene-families were enriched with genes showing an interactive effect in expression response to exposure to the mixture of the stressors, while transcription and translation-related pathways and gene-families were mostly related with genotypic differences in interactive responses to this mixture. Collectively, our results indicate that the methods we employed may improve further characterization of the possibilities and limitations of transcriptomics approaches in the adverse outcome pathway framework and in predictions of multistressor effects on natural populations.

Assessing mechanisms of toxicant response in the amphipod Melita plumulosa through transcriptomic profiling

This study describes the function of transcripts with altered abundance in the epibenthic amphipod, Melita plumulosa, following whole-sediment exposure to a series of common environmental contaminants. M. plumulosa were exposed for 48 h to sediments spiked and equilibrated with the following contaminants at concentrations predicted to cause sublethal effects to reproduction: porewater ammonia 30 mg L(-1); bifenthrin at 100 μg kg(-1); fipronil at 50 μg kg(-1); 0.6% diesel; 0.3% crude oil; 250 mg Cu kg(-1); 400 mg Ni kg(-1); and 400 mg Zn kg(-1). RNA was extracted and hybridized against a custom Agilent microarray developed for this species. Although the microarray represented a partial transcriptome and not all features on the array could be annotated, unique transcriptomic profiles were generated for each of the contaminant exposures. Hierarchical clustering grouped the expression profiles together by contaminant class, with copper and zinc, the petroleum products and nickel, and the pesticides each forming a distinct cluster. Many of the transcriptional changes observed were consistent with patterns previously described in other crustaceans. The changes in the transcriptome demonstrated that contaminant exposure caused changes in digestive function, growth and moulting, and the cytoskeleton following metal exposure, whereas exposure to petroleum products caused changes in carbohydrate metabolism, xenobiotic metabolism and hormone cycling. Functional analysis of these gene expression profiles can provide a better understanding of modes of toxic action and permits the prediction of mixture effects within contaminated ecosystems.

Identification of metabolic pathways in Daphnia magna explaining hormetic effects of selective serotonin reuptake inhibitors and 4-nonylphenol using transcriptomic and phenotypic responses

The molecular mechanisms explaining hormetic effects of selective serotonin reuptake inhibitors (SSRIs) and 4-nonylphenol in Daphnia magna reproduction were studied in juveniles and adults. Transcriptome analyses showed changes in mRNA levels for 1796 genes in juveniles and 1214 genes in adults (out of 15000 total probes) exposed to two SSRIs (fluoxetine and fluvoxamine) or to 4-nonylphenol. Functional annotation of affected genes was improved by assuming the annotations of putatively homologous Drosophila genes. Self-organizing map analysis and partial least-square regression coupled with selectivity ratio procedures analyses allowed to define groups of genes with specific responses to the different treatments. Differentially expressed genes were analyzed for functional enrichment using Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes databases. Serotonin metabolism, neuronal developmental processes, and carbohydrates and lipid metabolism functional categories appeared as selectively affected by SSRI treatment, whereas 4-nonylphenol deregulated genes from the carbohydrate metabolism and the ecdysone regulatory pathway. These changes in functional and metabolic pathways are consistent with previously reported SSRIs and 4-nonylphenol hormetic effects in D. magna, including a decrease in reserve carbohydrates and an increase in respiratory metabolism.

Gene expression profiling of three different stressors in the water flea Daphnia magna

Microarrays are an ideal tool to screen for differences in gene expression of thousands of genes simultaneously. However, often commercial arrays are not available. In this study, we performed microarray analyses to evaluate patterns of gene transcription following exposure to two natural and one anthropogenic stressor. cDNA microarrays compiled of three life stage specific and three stressor-specific EST libraries, yielding 1734 different EST sequences, were used. We exposed juveniles of the water flea Daphnia magna for 48, 96 and 144 h to three stressors known to exert strong selection in natural populations of this species i.e. a sublethal concentration of the pesticide carbaryl, infective spores of the endoparasite Pasteuria ramosa, and fish predation risk mimicked by exposure to fish kairomones. A total of 148 gene fragments were differentially expressed compared to the control. Based on a PCA, the exposure treatments were separated into two main groups based on the extent of the transcriptional response: a low and a high (144 h of fish or carbaryl exposure and 96 h of parasite exposure) stress group. Firstly, we observed a general stress-related transcriptional expression profile independent of the treatment characterized by repression of transcripts involved in transcription, translation, signal transduction and energy metabolism. Secondly, we observed treatment-specific responses including signs of migration to deeper water layers in response to fish predation, structural challenge of the cuticle in response to carbaryl exposure, and disturbance of the ATP production in parasite exposure. A third important conclusion is that transcription expression patterns exhibit stress-specific changes over time. Parasite exposure shows the most differentially expressed gene fragments after 96 h. The peak of differentially expressed transcripts came only after 144 h of fish exposure, while carbaryl exposure induced a more stable number of differently expressed gene fragments over time.

Mixture toxicity revisited from a toxicogenomic perspective

The advent of new genomic techniques has raised expectations that central questions of mixture toxicology such as for mechanisms of low dose interactions can now be answered. This review provides an overview on experimental studies from the past decade that address diagnostic and/or mechanistic questions regarding the combined effects of chemical mixtures using toxicogenomic techniques. From 2002 to 2011, 41 studies were published with a focus on mixture toxicity assessment. Primarily multiplexed quantification of gene transcripts was performed, though metabolomic and proteomic analysis of joint exposures have also been undertaken. It is now standard to explicitly state criteria for selecting concentrations and provide insight into data transformation and statistical treatment with respect to minimizing sources of undue variability. Bioinformatic analysis of toxicogenomic data, by contrast, is still a field with diverse and rapidly evolving tools. The reported combined effect assessments are discussed in the light of established toxicological dose-response and mixture toxicity models. Receptor-based assays seem to be the most advanced toward establishing quantitative relationships between exposure and biological responses. Often transcriptomic responses are discussed based on the presence or absence of signals, where the interpretation may remain ambiguous due to methodological problems. The majority of mixture studies design their studies to compare the recorded mixture outcome against responses for individual components only. This stands in stark contrast to our existing understanding of joint biological activity at the levels of chemical target interactions and apical combined effects. By joining established mixture effect models with toxicokinetic and -dynamic thinking, we suggest a conceptual framework that may help to overcome the current limitation of providing mainly anecdotal evidence on mixture effects. To achieve this we suggest (i) to design studies to establish quantitative relationships between dose and time dependency of responses and (ii) to adopt mixture toxicity models. Moreover, (iii) utilization of novel bioinformatic tools and (iv) stress response concepts could be productive to translate multiple responses into hypotheses on the relationships between general stress and specific toxicity reactions of organisms.