Metal mixtures modeling evaluation project: 1. Background

Acute toxicity of binary-metal mixtures of copper, zinc, and nickel to Pimephales promelas: Evidence of more-than-additive effect

Metal mixture toxicity has been studied for decades. However, the results are not consistent, and thus ecological risk assessment and regulation of mixtures has been difficult. The objective of the present study was to use a systematic experimental design to characterize the toxicity of binary-metal mixture of Cu, Zn, and Ni to Pimephales promelas, typically to determine whether the effect of these binary-metal mixtures on P. promelas is more-than-additive. Standard 96-h toxicity tests were conducted with larval P. promelas based on US Environmental and Protection Agency methods to determine metal mixture effects. All experiments were conducted in synthetic moderately hard water with no addition of dissolved organic matter. Three different effect analysis approaches, the MixTox model, the Finney model, and the toxic unit method, were used for comparison. The results indicate that the toxicity of Cu+Zn, Cu+Ni, and Zn+Ni mixtures to P. promelas was more-than-additive. Among the 3 mixtures, the effect of the Cu+Ni mixture was the most profound. The results of the present study are useful for applications to models such as the metal mixture biotic ligand model. More research should be conducted to determine the mechanisms of acute and chronic toxicity of metal mixtures.

Interactions and Toxicity of Cu-Zn mixtures to Hordeum vulgare in Different Soils Can Be Rationalized with Bioavailability-Based Prediction Models

Soil contamination with copper (Cu) is often associated with zinc (Zn), and the biological response to such mixed contamination is complex. Here, we investigated Cu and Zn mixture toxicity to Hordeum vulgare in three different soils, the premise being that the observed interactions are mainly due to effects on bioavailability. The toxic effect of Cu and Zn mixtures on seedling root elongation was more than additive (i.e., synergism) in soils with high and medium cation-exchange capacity (CEC) but less than additive (antagonism) in a low-CEC soil. This was found when we expressed the dose as the conventional total soil concentration. In contrast, antagonism was found in all soils when we expressed the dose as free-ion activities in soil solution, indicating that there is metal-ion competition for binding to the plant roots. Neither a concentration addition nor an independent action model explained mixture effects, irrespective of the dose expressions. In contrast, a multimetal BLM model and a WHAM-Ftox model successfully explained the mixture effects across all soils and showed that bioavailability factors mainly explain the interactions in soils. The WHAM-Ftox model is a promising tool for the risk assessment of mixed-metal contamination in soils.

Uptake and toxicity of Cd, Cu and Pb mixtures in the isopod Asellus aquaticus from waterborne exposure

The present study evaluated interactions of waterborne Cd, Cu and Pb mixtures on metal uptake rates in the isopod Asellus aquaticus and related this to mixture effects on toxicity. Secondly, it was assessed whether observed mixture effects were better related to isopod body concentrations compared to exposure concentrations. Isopods were exposed for 10 days to single, binary and tertiary mixtures including five different concentrations of Cd (0.107 to 277 μg L(-1)), Cu (3.35 to 2117 μg L(-1)) and Pb (0.782 to 443 μg L(-1)). Mortality was assessed every day while isopod body concentrations, growth (biomass) and energy reserves (glycogen, lipid and protein reserves) were assessed at the end of the experiment. Synergistic interactions of combined Cd and Pb exposure on Cd and Pb uptake as well as on growth rates and mortality rates were observed. Mixture effects of combined Cd and Pb exposure on toxicity endpoints were directly related to increased Cd uptake in the Cd+Pb treatment. No mixture interactions of Cu on Cd or Pb uptake (and vice versa), nor on toxicity endpoints were observed. All toxicity endpoints were related to body concentrations. However, mixture effects disappeared when growth and mortality rates were expressed on body concentrations instead of exposure concentrations. By combining information of mixture effects on metal uptake with mixture toxicity data, the present study provides more insight in the way metal mixtures interfere with aquatic organisms and how they can induce toxic effects.

Interactive effects of waterborne metals in binary mixtures on short-term gill-metal binding and ion uptake in rainbow trout (Oncorhynchus mykiss)

Metal binding to fish gills forms the basis of the biotic ligand model (BLM) approach, which has emerged as a useful tool for conducting site-specific water quality assessments for metals. The current BLMs are designed to assess the toxicity of individual metals, and cannot account for the interactive effects of metal mixtures to aquatic organisms including fish. The present study was designed mainly to examine the interactive effects of waterborne metals (Cd, Zn, Cu, Ag, and Ni) in specific binary combinations on short-term (3h) gill-metal binding and essential ion (Ca(2+) and Na(+)) uptake (a physiological index of toxicity) in fish, using juvenile freshwater rainbow trout (Oncorhynchus mykiss) as the model species. We hypothesized that binary mixtures of metals that share a common mode of uptake and toxicity (e.g., Cd and Zn - Ca(2+) antagonists, Cu and Ag - Na(+) antagonists) would reduce the gill binding of each other via competitive interactions and induce less than additive effects on ion transport. In addition, the mixture of metals that have different modes of uptake and toxicity (e.g., Cd and Cu, or Cd and Ni) would not exhibit any interactive effects either on gill-metal binding or ion transport. We found that both Zn and Cu reduced gill-Cd binding and vice versa, however, Ni did not influence gill-Cd binding in fish. Surprisingly, Ag was found to stimulate gill-Cu binding especially at high exposure concentrations, whereas, Cu had no effect on gill-Ag binding. The inhibitory effect of Cd and Zn in mixture on branchial Ca(2+) uptake was significantly greater than that of Cd or Zn alone. Similarly, the inhibitory effect of Cu and Ag in mixture on branchial Na(+) uptake was significantly greater than that of Cu or Ag alone. The inhibitory effects of Cd and Zn mixture on Ca(2+) uptake as well as Cu and Ag mixture on Na(+) uptake were found to follow the principles of simple additivity. In contrast, no significant additive effect on either Ca(2+) or Na(+) uptake was recorded in fish exposed to the mixture of Cd and Cu. Overall, we found that although the effects of metal mixture interactions on gill-metal binding did not always match with our original assumptions, the effects of metal mixtures on toxicity in fish were generally consistent with our predictions. The findings of the present study have important implications for improving the BLM approach to assess metal mixture toxicity in fish.

Modeling and interpreting biological effects of mixtures in the environment: introduction to the metal mixture modeling evaluation project

The fate and biological effects of chemical mixtures in the environment are receiving increased attention from the scientific and regulatory communities. Understanding the behavior and toxicity of metal mixtures poses unique challenges for incorporating metal-specific concepts and approaches, such as bioavailability and metal speciation, in multiple-metal exposures. To avoid the use of oversimplified approaches to assess the toxicity of metal mixtures, a collaborative 2-yr research project and multistakeholder group workshop were conducted to examine and evaluate available higher-tiered chemical speciation-based metal mixtures modeling approaches. The Metal Mixture Modeling Evaluation project and workshop achieved 3 important objectives related to modeling and interpretation of biological effects of metal mixtures: 1) bioavailability models calibrated for single-metal exposures can be integrated to assess mixture scenarios; 2) the available modeling approaches perform consistently well for various metal combinations, organisms, and endpoints; and 3) several technical advancements have been identified that should be incorporated into speciation models and environmental risk assessments for metals.

Testing WHAM-FTOX with laboratory toxicity data for mixtures of metals (Cu, Zn, Cd, Ag, Pb)

The Windermere humic aqueous model using the toxicity function (WHAM-FTOX ) describes cation toxicity to aquatic organisms in terms of 1) accumulation by the organism of metabolically active protons and metals at reversible binding sites, and 2) differing toxic potencies of the bound cations. Cation accumulation (νi , in mol g(-1) ) is estimated through calculations with the WHAM chemical speciation model by assuming that organism binding sites can be represented by those of humic acid. Toxicity coefficients (αi ) are combined with νi to obtain the variable FTOX (= Σ αi νi ) which, between lower and upper thresholds (FTOX,LT , FTOX,UT ), is linearly related to toxic effect. Values of αi , FTOX,LT , and FTOX,LT are obtained by fitting toxicity data. Reasonable fits (72% of variance in toxic effect explained overall) were obtained for 4 large metal mixture acute toxicity experiments involving daphnids (Cu, Zn, Cd), lettuce (Cu, Zn, Ag), and trout (Zn, Cd, Pb). Strong nonadditive effects, most apparent in results for tests involving Cd, could be explained approximately by purely chemical competition for metal accumulation. Tentative interpretation of parameter values obtained from these and other experimental data suggests the following order of bound cation toxicity: H < Al < (Cu Zn Pb UO2 ) < (Cd Ag). Another trend is a strong increase in Cd toxicity relative to that of Zn as organism complexity increases (from bacteria to fish).

Application of a generalized linear mixed model to analyze mixture toxicity: survival of brown trout affected by copper and zinc

Increased concerns about the toxicity of chemical mixtures have led to greater emphasis on analyzing the interactions among the mixture components based on observed effects. The authors applied a generalized linear mixed model (GLMM) to analyze survival of brown trout (Salmo trutta) acutely exposed to metal mixtures that contained copper and zinc. Compared with dominant conventional approaches based on an assumption of concentration addition and the concentration of a chemical that causes x% effect (ECx), the GLMM approach has 2 major advantages. First, binary response variables such as survival can be modeled without any transformations, and thus sample size can be taken into consideration. Second, the importance of the chemical interaction can be tested in a simple statistical manner. Through this application, the authors investigated whether the estimated concentration of the 2 metals binding to humic acid, which is assumed to be a proxy of nonspecific biotic ligand sites, provided a better prediction of survival effects than dissolved and free-ion concentrations of metals. The results suggest that the estimated concentration of metals binding to humic acid is a better predictor of survival effects, and thus the metal competition at the ligands could be an important mechanism responsible for effects of metal mixtures. Application of the GLMM (and the generalized linear model) presents an alternative or complementary approach to analyzing mixture toxicity.

Metal mixture modeling evaluation project: 2. Comparison of four modeling approaches

As part of the Metal Mixture Modeling Evaluation (MMME) project, models were developed by the National Institute of Advanced Industrial Science and Technology (Japan), the US Geological Survey (USA), HDR|HydroQual (USA), and the Centre for Ecology and Hydrology (United Kingdom) to address the effects of metal mixtures on biological responses of aquatic organisms. A comparison of the 4 models, as they were presented at the MMME workshop in Brussels, Belgium (May 2012), is provided in the present study. Overall, the models were found to be similar in structure (free ion activities computed by the Windermere humic aqueous model [WHAM]; specific or nonspecific binding of metals/cations in or on the organism; specification of metal potency factors or toxicity response functions to relate metal accumulation to biological response). Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single vs multiple types of binding sites on the organism) and specific calibration strategies that affected the selection of model parameters. The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results. Less-than-additive toxicity was more difficult to describe with the available models. Because of limitations in the available datasets and the strong interrelationships among the model parameters (binding constants, potency factors, toxicity response parameters), further evaluation of specific model assumptions and calibration strategies is needed.

Development and application of a multimetal multibiotic ligand model for assessing aquatic toxicity of metal mixtures

A multimetal, multiple binding site version of the biotic ligand model (mBLM) has been developed for predicting and explaining the bioavailability and toxicity of mixtures of metals to aquatic organisms. The mBLM was constructed by combining information from single-metal BLMs to preserve compatibility between the single-metal and multiple-metal approaches. The toxicities from individual metals were predicted by assuming additivity of the individual responses. Mixture toxicity was predicted based on both dissolved metal and mBLM-normalized bioavailable metal. Comparison of the 2 prediction methods indicates that metal mixtures frequently appear to have greater toxicity than an additive estimation of individual effects on a dissolved metal basis. However, on an mBLM-normalized basis, mixtures of metals appear to be additive or less than additive. This difference results from interactions between metals and ligands in solutions including natural organic matter, processes that are accounted for in the mBLM. As part of the mBLM approach, a technique for considering variability was developed to calculate confidence bounds (called response envelopes) around the central concentration-response relationship. Predictions using the mBLM and response envelope were compared with observed toxicity for a number of invertebrate and fish species. The results show that the mBLM is a useful tool for considering bioavailability when assessing the toxicity of metal mixtures.

Metal mixture modeling evaluation project: 3. Lessons learned and steps forward

A comparison of 4 metal mixture toxicity models (that were based on the biotic ligand model [BLM] and the Windermere humic aqueous model using the toxicity function [WHAM-FTOX ]) was presented in a previous paper. In the present study, a streamlined version of the 4 models was developed and applied to multiple data sets and test conditions to examine key assumptions and calibration strategies that are crucial in modeling metal mixture toxicity. Results show that 1) a single binding site on or in the organism was a useful and oftentimes sufficient framework for predicting metal toxicity; 2) a linear free energy relationship (LFER) for bidentate binding of metals and cations to the biotic ligand provided a good first estimate of binding coefficients; 3) although adjustments in metal binding coefficients or adjustments in chemical potency factors can both be used in model calibration for single-metal exposures, changing metal binding coefficients or chemical potency factors had different effects on model predictions for metal mixtures; and 4) selection of a mixture toxicity model (based on concentration addition or independent action) was important in predicting metal mixture toxicity. Moving forward, efforts should focus on reducing uncertainties in model calibration, including development of better methods to characterize metal binding to toxicologically active binding sites, conducting targeted exposure studies to advance the understanding of metal mixture toxicity, and further developing LFERs and other tools to help constrain the model calibration.