Mixture toxicity of three toxicants with similar and dissimilar modes of action to Daphnia magna

Mixture toxicity of similar- and dissimilar-acting toxicants can be predicted by the models concentration addition (CA) and independent action (IA) using single substance toxicity data. Knowledge of the toxicants mode of action is thus required in order to use the models. In order to test the predictive capability of the models, we conducted Daphnia magna 48 h immobilization experiments with three toxicants with known modes of action (dimethoate, pirimicarb and linear alkyl benzene sulfonate) singly, and in binary and ternary mixtures. Our results indicate that CA and IA predict binary mixtures of similar- and dissimilar-acting toxicants equally well. CA and IA also equally predicted the ternary mixture consisting of both similar- and dissimilar-acting chemicals. The paper discusses the concept of mode of action and the implications the definition of mode of action has on the choice of reference model for mixture toxicity studies.     

Predicting mixture toxicity of seven phenolic compounds with similar and dissimilar action mechanisms to Vibrio qinghaiensis sp.nov.Q67

The predictions of mixture toxicity for chemicals are commonly based on two models: concentration addition (CA) and independent action (IA). Whether the CA and IA can predict mixture toxicity of phenolic compounds with similar and dissimilar action mechanisms was studied. The mixture toxicity was predicted on the basis of the concentration-response data of individual compounds. Test mixtures at different concentration ratios and concentration levels were designed using two methods. The results showed that the Weibull function fit well with the concentration-response data of all the components and their mixtures, with all relative coefficients (Rs) greater than 0.99 and root mean squared errors (RMSEs) less than 0.04. The predicted values from CA and IA models conformed to observed values of the mixtures. Therefore, it can be concluded that both CA and IA can predict reliable results for the mixture toxicity of the phenolic compounds with similar and dissimilar action mechanisms.     

Estimating the combined toxicity by two-step prediction model on the complicated chemical mixtures from wastewater treatment plant effluents

The toxicities of chemical mixtures containing 10 compounds, detected in wastewater treatment plant (WWTP) effluents, were investigated using Daphnia magna in a two-step prediction (TSP) model. The 10 chemicals determined by gas chromatography/ mass spectrometry in WWTP effluents included three groups: Three acetylcholinesterase inhibitors, six narcosis inhibitors, and one seedling root inhibitor. In the first step, a concentration addition (CA) model was used to predict the mixture toxicities for the three component groups with similar modes of action; in the second step, an independent action (IA) model was used for the newly developed concentration-response curves from the three CA predictions. The CA predictions did not show a statistically significant difference from the observed results with respect to the three groups of chemicals, whereas the IA model did not conform to the experimental results. Therefore, the concentration-response curves obtained from the mixture toxicity tests in each group was considered as a single curve and applied in the next step of the mixture toxicity prediction. However, the observed toxicity of the 10-chemical mixture showed large differences from the results of the IA and CA model predictions, whereas the TSP model predicted the toxicity well and with statistical significance (p = 0.0501, n = 17). This suggests that the TSP model would provide a valid prediction for a randomly selected chemical mixture having various modes of action if the concentration-response function for an individual component is obtained.     

Is mixture toxicity measured on a biomarker indicative of what happens on a population level? A study with Lemna minor

For plants, pigment content has shown to be a remarkably consistent biomarker across chemicals with different modes of action. In this study, we evaluated the use of pigment content as endpoint in binary mixture toxicity studies compared to three growth endpoints on the floating plant Lemna minor. Six binary combinations of six herbicides with different mode of action were used. Data were tested against both the concentration addition (CA) and independent action (IA) reference models. For CA, two statistical approaches were used. The study showed that for some herbicide combinations the mixture toxicity measured on pigment content did not reflect the results measured on plant population growth, emphasizing the importance of measuring growth in parallel with biomarkers. CA explained the data just as well as IA, and the two different statistical models used to test the data in relation to CA showed very similar results.     

Co-exposure of Freshwater Microalgae to Tetrabromobisphenol A and Sulfadiazine: Oxidative Stress Biomarker Responses and Joint Toxicity Prediction

Combined toxicity and oxidative stress biomarker responses were determined for tetrabromobisphenol A (TBBPA) and sulfadiazine (SDZ) to the unicellular green alga Scenedesmus obliquus. Concentration–response analyses were performed for single toxicants and for mixtures containing TBBPA and SDZ with two different mixture ratios. The effect concentrations and the observed effects of the mixtures were compared to the predictions of the joint toxicity by the concentration addition (CA) model and independent action (IA) model. Results showed that the observed joint toxicity was within the scope of the highest (TBBPA) and lowest (SDZ) toxicity observed for the individual components. Furthermore, co-exposure of S. obliquus to TBBPA and SDZ provided preliminary evidence that the mixtures induced oxidative stress leading to cell damage. The CA and IA models proved to be valid for the prediction of the joint toxicity of TBBPA and SDZ. This study highlights a combined environmental risk assessment for two emerging pollutants.     

Effects of binary mixtures on the life traits of Daphnia magna

The environment is constantly exposed to a cocktail of contaminants mainly due to human activities. Because polluted ecosystems are characterized by an amalgam of chemical compounds, the objective of the present study was to assess the joint effect of chemical mixtures to the life—history traits of Daphnia magna Straus. For that a binary mixture of two neonicotinoid insecticides, imidacloprid and thiacloprid, and another one of imidacloprid with nickel chloride were tested. Theoretical models have been developed and applied in studies with chemical mixtures, predicting toxicity based on their modes of action: concentration addition (CA) and independent joint action (IA) models. Still there are cases where deviations are observed (e.g. synergistic or antagonistic behaviors, dose ratio or level dependency). In this study, the effects of the individual compounds and their mixtures were studied in a chronic test where reproduction, survival and body length were evaluated in D. magna. Regarding single compound effects, it was observed that the most toxic was nickel chloride followed by thiacloprid and imidacloprid. For the mixture exposure of imidacloprid and thiacloprid, a synergistic pattern was observed in the sublethal doses used for the number of neonates produced, while for the body length the best fit was shown with the CA model. In the mixture exposure of imidacloprid and nickel, no deviation from the IA was observed for the neonate production data; for the body length parameter, a synergistic pattern was observed in low doses of the chemicals while an antagonistic pattern was observed.     

Joint toxicity of chlorpyrifos and esfenvalerate to fathead minnows and midge larvae

The joint toxicity of esfenvalerate and chlorpyrifos to the fathead minnow (Pimephales promelas) and the aquatic midge larvae (Chironomus tentans) was determined using comparisons to independent action (IA) and concentration addition (CA) models. Equipotent mixtures of the two insecticides were used for initial testing of both species. A secondary study evaluating the effects of low-level chlorpyrifos on esfenvalerate toxicity also was performed. For fathead minnows, the equipotent mixture and the low-level chlorpyrifos exposure resulted in toxicity greater than that predicted by either model. In both studies, however, the observed concentrations causing 50% effect (EC50) were within a factor of two of the values predicted by the CA model. For midges, the observed EC50s were similar to the values predicted by the CA model, whereas the IA model slightly underpredicted toxicity. The observance of toxicity that was not predicted by either of the conceptual models tested likely results from a toxicokinetic interaction occurring between the toxicants.     

Risk Characterization and Probabilistic Concentration–Response Modeling of Complex Environmental Mixtures Using New Approach Methodologies (NAMs) Data from Organotypic in Vitro Human Stem Cell Assays

Background: Risk assessment of chemical mixtures or complex substances remains a major methodological challenge due to lack of available hazard or exposure data. Therefore, risk assessors usually infer hazard or risk from data on the subset of constituents with available toxicity values.Objectives: We evaluated the validity of the widely used traditional mixtures risk assessment paradigms, Independent Action (IA) and Concentration Addition (CA), with new approach methodologies (NAMs) data from human cell-based in vitro assays.Methods: A diverse set of 42 chemicals was tested both individually and as mixtures for functional and cytotoxic effects in vitro. A panel of induced pluripotent stem cell (iPSCs)-derived models (hepatocytes, cardiomyocytes, endothelial, and neurons) and one primary cell type (HUVEC) were used. Bayesian concentration–response modeling of individual chemicals or their mixtures was performed for a total of 47 phenotypes to derive point-of-departure (POD) values. Probabilistic IA or CA was conducted to estimate the mixture effects based on the bioactivity profiles from the individual chemicals and compared with mixture bioactivity.Results: All mixtures showed significant bioactivity, even though some were constructed using individual chemical concentrations considered “low” or “safe.” Even though CA is much more accurate as a predictor of mixture effects in comparison with IA, with CA-based POD typically within an order of magnitude of the actual mixture, in some cases, the bioactivity of the mixtures appeared to be much greater than that of their components under either additivity assumption.Discussion: These results suggest that CA is a preferred first approximation for predicting mixture toxicity when data for all constituents are available. However, because the accuracy of additivity assumptions varies greatly across phenotypes, we posit that mixtures and complex substances need to be directly tested for their hazard potential. NAMs provide a practical solution that rapidly yields highly informative data for mixtures risk assessment. https://doi.org/10.1289/EHP7600     

A review of independent action compared to concentration addition as reference models for mixtures of compounds with different molecular target sites

From a theoretical point of view, it has often been argued that the model of independent action (IA) is the most correct reference model to use for predicting the joint effect of mixtures of chemicals with different molecular target sites. The theory of IA, however, relies on a number of assumptions that are rarely fulfilled in practice. It has even been argued that, theoretically, the concentration addition (CA) model could be just as correct. In the present study, we tested the accuracy of both IA and CA in describing binary dose-response surfaces of chemicals with different molecular targets using statistical software. We compared the two models to determine which best describes data for 158 data sets. The data sets represented 98 different mixtures of, primarily, pesticides and pharmaceuticals tested on one or several of seven test systems containing one of the following: Vibrio fischeri, activated sludge microorganisms, Daphnia magna, Pseudokirchneriella subcapitata, Lemna minor, Tripleurospermum inodorum, or Stellaria media. The analyses showed that approximately 20% of the mixtures were adequately predicted only by IA, 10% were adequately predicted only by CA, and both models could predict the outcome of another 20% of the experiment. Half of the experiments could not be correctly described with either of the two models. When quantifying the maximal difference between modeled synergy or antagonism and the reference model predictions at a 50% effect concentration, neither of the models proved significantly better than the other. Thus, neither model can be selected over the other on the basis of accuracy alone.     

Effects of Three Antifouling Agents on Algal Communities and Algal Reproduction: Mixture Toxicity Studies with TBT, Irgarol, and Sea-Nine

The toxicity of three antifoulants (Sea-Nine, Irgarol, and TBT) was determined individually and in mixtures in two tests with microalgae. Effects on periphyton community photosynthesis and reproduction of the unicellular green algae Scenedesmus vacuolatus were investigated. The tested antifoulants were highly toxic in both tests. Observed mixture toxicities were compared with predictions derived from two concepts: Independent Action (IA), assumed to be more relevant for the tested mixtures that were composed of dissimilarly acting substances, and Concentration Addition (CA), regarded as a reasonable worst-case approach in predictive mixture hazard assessment. Despite the corresponding mechanistic basis, IA failed to provide accurate predictions of the observed mixture toxicities. Results show the same pattern in both assays. Mixture effects at high concentrations were slightly overestimated and effects at low concentrations were slightly underestimated. Maximum observed deviations between observed and IA-predicted concentrations amount to a factor of 4. The suggested worst-case approach using CA was protective only in effect regions above 20%. Nevertheless, the application of any concept that accounts for possible mixture effects is more realistic than the present chemical-by-chemical assessment.     

Prediction for the mixture toxicity of six organophosphorus pesticides to the luminescent bacterium Q67

Organophosphorus (OP) pesticides are ubiquitous in the surface water as mixtures. To examine the mixture toxicity in the multi-component space, the uniform design (UD) which can explore the concentration changes with few experimental efforts was employed to design the mixtures. On the other hand, the fixed concentration ratio ray was applied into six UD mixtures and two equivalent-effect concentration mixtures to build the whole concentration–response curves to overcome the demerit of the classical “point-to-point” method. The experimental toxicities of six pesticides and their mixtures to the luminescent bacterium Q67 were determined. The mixture toxicities were predicted by two models, concentration addition (CA) and independent action (IA). The results showed that all the mixture toxicities observed had no significant differences from the ones predicted by CA. However, the mixture toxicities were also well predicted by IA especially at the low-concentration section.     

Assessment of the Probabilistic Ecological Risk Assessment-Toxic Equivalent Combination Approach for Evaluating Pesticide Mixture Toxicity to Zooplankton in Outdoor Microcosms

The probabilistic ecological risk assessment-toxic equivalent (PERA-TE) combination approach was recently introduced in response to the increased demand for risk assessment approaches that can accommodate mixtures. The effectiveness and validity of the PERA-TE approach was assessed using two types of pesticide mixtures tested in outdoor microcosms. The first type of mixture consisted of pesticides with similar modes of action (the organophosphorus insecticides chlorpyrifos and diazinon) and the second of pesticides with different modes of action (chlorpyrifos, endosulfan, and trifluralin). To assess the toxicity of, and potential interaction within, each type of mixture, theoretically equitoxic TE mixtures were prepared in different proportional ratios. The TE mixtures were based on the 10th centile of acute toxicity effects distributions (data obtained from the literature) and a factor of the sum of the 90th centile field concentrations extrapolated from exposure distributions based on North American surface water monitoring data. Changes in zooplankton population abundances were used as the effect measure. The binary organophosphorus mixtures were equitoxic and conformed to the concentration addition model. The observed response trends of zooplankton exposed to the mixture of chemicals with different modes of action were a result of the susceptibility of individual taxa to the dominating pesticide in each mixture. Overall, the PERA-TE approach was not effective in predicting the toxicity and interaction of all mixture types and should be limited to assessing mixtures of chemicals with similar modes of action.     

Mixture toxicity of wood preservative products in the fish embryo toxicity test

Wood preservative products are used globally to protect wood from fungal decay and insects. We investigated the aquatic toxicity of five commercial wood preservative products, the biocidal active substances and some formulation additives contained therein, as well as six generic binary mixtures of the active substances in the fish embryo toxicity test (FET). Median lethal concentrations (LC50) of the single substances, the mixtures, and the products were estimated from concentration-response curves and corrected for concentrations measured in the test medium. The comparison of the experimentally observed mixture toxicity with the toxicity predicted by the concept of concentration addition (CA) showed less than twofold deviation for all binary mixtures of the active substances and for three of the biocidal products. A more than 60-fold underestimation of the toxicity of the fourth product by the CA prediction was detected and could be explained fully by the toxicity of one formulation additive, which had been labeled as a hazardous substance. The reason for the 4.6-fold underestimation of toxicity of the fifth product could not be explained unambiguously. Overall, the FET was found to be a suitable screening tool to verify whether the toxicity of formulated wood preservatives can reliably be predicted by CA. Applied as a quick and simple nonanimal screening test, the FET may support approaches of applying component-based mixture toxicity predictions within the environmental risk assessment of biocidal products, which is required according to European regulations.     

Measurement and modeling of the toxicity of binary mixtures in the nematode caenorhabditis elegans--a test of independent action

Ecological risk assessments must increasingly consider the effects of chemical mixtures on the environment as anthropogenic pollution continues to grow in complexity. Yet testing every possible mixture combination is impractical and unfeasible; thus, there is an urgent need for models that can accurately predict mixture toxicity from single-compound data. Currently, two models are frequently used to predict mixture toxicity from single-compound data: Concentration addition and independent action (IA). The accuracy of the predictions generated by these models is currently debated and needs to be resolved before their use in risk assessments can be fully justified. The present study addresses this issue by determining whether the IA model adequately described the toxicity of binary mixtures of five pesticides and other environmental contaminants (cadmium, chlorpyrifos, diuron, nickel, and prochloraz) each with dissimilar modes of action on the reproduction of the nematode Caenorhabditis elegans. In three out of 10 cases, the IA model failed to describe mixture toxicity adequately with significant or antagonism being observed. In a further three cases, there was an indication of synergy, antagonism, and effect-level-dependent deviations, respectively, but these were not statistically significant. The extent of the significant deviations that were found varied, but all were such that the predicted percentage effect seen on reproductive output would have been wrong by 18 to 35% (i.e., the effect concentration expected to cause a 50% effect led to an 85% effect). The presence of such a high number and variety of deviations has important implications for the use of existing mixture toxicity models for risk assessments, especially where all or part of the deviation is synergistic.     

Evaluating pharmacokinetic and pharmacodynamic interactions with computational models in supporting cumulative risk assessment

Simultaneous or sequential exposure to multiple chemicals may cause interactions in the pharmacokinetics (PK) and/or pharmacodynamics (PD) of the individual chemicals. Such interactions can cause modification of the internal or target dose/response of one chemical in the mixture by other chemical(s), resulting in a change in the toxicity from that predicted from the summation of the effects of the single chemicals using dose additivity. In such cases, conducting quantitative cumulative risk assessment for chemicals present as a mixture is difficult. The uncertainties that arise from PK interactions can be addressed by developing physiologically based pharmacokinetic (PBPK) models to describe the disposition of chemical mixtures. Further, PK models can be developed to describe mechanisms of action and tissue responses. In this article, PBPK/PD modeling efforts conducted to investigate chemical interactions at the PK and PD levels are reviewed to demonstrate the use of this predictive modeling framework in assessing health risks associated with exposures to complex chemical mixtures.     

Joint toxicity of mixtures of 8 and 24 chemicals to the guppy (Poecilia reticulata)

The acute median lethal concentrations of equitoxic mixtures of 8 and 24 toxicants with diverse modes of action to guppies were determined. To quantify the joint toxicity, the results are expressed by means of the Mixture Toxicity Index (MTI). The toxicity of the mixtures was near concentration addition. Concentrations of the chemicals of about 0.1 of their LC₅₀'s contributed to the toxicity of the mixtures.     

Mixture toxicity of flubendazole and fenbendazole to Daphnia magna

Nowadays, residual amounts of many pharmaceuticals can be found in various environmental compartments including surface and ground waters, soils and sediments as well as biota. Even though they undergo degradability, their environmental discharge is relatively continuous, thus they may be regarded as quasi-persistent contaminants, and are also frequently regarded as emerging organic pollutants. Benzimidazoles, especially flubendazole (FLU) and fenbendazole (FEN), represent two anthelmintic drugs belonging to this group. Although their presence in environmental matrices has been reported, there is relatively little data concerning their (eco)toxicological impact. Furthermore, no data is available on their mixture toxicity. FLU and FEN have been found to have a strong impact on an environmentally important non-target organism – Daphnia magna. Moreover, these compounds are usually present in the environment as a part of pharmaceutical mixtures. Therefore, there is a need to evaluate their mixture toxicity, which was the main aim of this study. Single substance toxicity tests were carried out in parallel with mixture studies of FLU and FEN, with the application of two well established concepts of Concentration Addition (CA) and Independent Action (IA). As a result, both models (CA and IA) were found to underestimate the toxicity of mixtures, however CA yielded more accurate predictions.     

Environmental quality criteria for organic chemicals predicted from internal effect concentrations and a food web model

Environmental quality criteria (EQC) for hydrophobic organic chemicals were calculated with a model for bioaccumulation in food webs. The model was calibrated and verified using polychlorinated biphenyl concentrations in food webs of shallow lakes. The EQCs in water and sediment were derived based on internal effect concentrations (IECs) for several modes of toxic action. By reverse calculation with the food web model for each organism in the web, a different water or sediment concentration is calculated corresponding to the IEC in each organism. A statistical procedure with an acute-to-chronic value is used to derive chronic EQCs based on bioaccumulation. The model-based chronic EQCs were compared with previously established EQCs. The EQCs calculated with the food web model generally are within an order of magnitude of the previously derived EQCs based on toxicity data on individual chemicals. Some previously derived EQCs are much lower than model predictions and usually based on small samples of toxicity data such as no-observed-effect concentrations (NOECs) with large assessment factors. When faced with data gaps, it is proposed to use model-based chronic EQCs for (polar) narcotic chemicals. Other modes of action require a different model concept to account for receptor-based toxicity.     

A comparison of the lethal and sublethal toxicity of organic chemical mixtures to the fathead minnow (Pimephales promelas)

The joint toxic effects of known binary and multiple organic chemical mixtures to the fathead minnow (Pimephales promelas) were defined at both the 96-h 50% lethal effect concentration (LC50) and sublethal (32-d growth) response levels for toxicants with a narcosis I, narcosis II, or uncoupler of oxidative phosphoralation mode of toxic action. Experiments were designed to define the degree of additive joint toxicity for mixtures of specific xenobiotics that are believed to act through a similar or different primary mode of toxic action. Our results support the general conclusion that concentration addition is expected for the joint toxicity of similarly acting toxicants. When chemicals were thought to act by a dissimilar mechanism, the combined effects we observed at both of the response levels tested were less than predicted by concentration addition, but usually more toxic than that predicted by the independent action/response addition model. It was demonstrated in multichemical mixtures that several toxicants can act together in a nearly additive fashion to produce effects even when they are present at concentrations below their individual no-observed-effect concentration. Concentration-response relationships for test chemicals at both the lethal and sublethal responses were defined for each of the three modes of toxic action studied. When normalized for potency, it was observed that one relationship could be defined to predict lethality to juvenile fathead minnows when exposed to individual chemicals with either a narcosis I, narcosis II, or uncoupler mode of toxic action. These sublethal relationships were similar for the narcosis I and narcosis II test chemicals, but a steeper response was observed for tests conducted with uncouplers.