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

A Review of Mechanistic Models for Predicting Adverse Effects in Sediment Toxicity Testing

Since recognizing the importance of bioavailability for understanding the toxicity of chemicals in sediments, mechanistic modeling has advanced over the last 40 years by building better tools for estimating exposure and making predictions of probable adverse effects. Our review provides an up-to-date survey of the status of mechanistic modeling in contaminated sediment toxicity assessments. Relative to exposure, advances have been most substantial for non-ionic organic contaminants (NOCs) and divalent cationic metals, with several equilibrium partitioning-based (Eq-P) models having been developed. This has included the use of Abraham equations to estimate partition coefficients for environmental media. As a result of the complexity of their partitioning behavior, progress has been less substantial for ionic/polar organic contaminants. When the EqP-based estimates of exposure and bioavailability are combined with water-only effects measurements, predictions of sediment toxicity can be successfully made for NOCs and selected metals. Both species sensitivity distributions and toxicokinetic and toxicodynamic models are increasingly being applied to better predict contaminated sediment toxicity. Furthermore, for some classes of contaminants, such as polycyclic aromatic hydrocarbons, adverse effects can be modeled as mixtures, making the models useful in real-world applications, where contaminants seldomly occur individually. Despite the impressive advances in the development and application of mechanistic models to predict sediment toxicity, several critical research needs remain to be addressed. These needs and others represent the next frontier in the continuing development and application of mechanistic models for informing environmental scientists, managers, and decisions makers of the risks associated with contaminated sediments. Environ Toxicol Chem 2024;43:1778-1794. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Recommended updates to the USEPA Framework for Metals Risk Assessment: Aquatic ecosystems

In 2007, the USEPA issued its "Framework for Metals Risk Assessment." The framework provides technical guidance to risk assessors and regulators when performing human health and environmental risk assessments of metals. This article focuses on advances in the science including assessing bioavailability in aquatic ecosystems, short- and long-term fate of metals in aquatic ecosystems, and advances in risk assessment of metals in sediments. Notable advances have occurred in the development of bioavailability models for assessing toxicity as a function of water chemistry in freshwater ecosystems. The biotic ligand model (BLM), the multiple linear regression model, and multimetal BLM now exist for most of the common mono- and divalent metals. Species sensitivity distributions for many metals exist, making it possible for many jurisdictions to develop or update their water quality criteria or guidelines. The understanding of the fate of metals in the environment has undergone significant scrutiny over the past 20 years. Transport and toxicity models have evolved including the Unit World Model allowing for estimation of concentrations of metals in various compartments as a function of loading and time. There has been significant focus on the transformation of metals in sediments into forms that are less bioavailable and on understanding conditions that result in resolubilization or redistribution of metals in and from sediments. Methods for spiking sediments have advanced such that the resulting chemistry in the laboratory mimics that in natural systems. Sediment bioavailability models are emerging including models that allow for prediction of toxicity in sediments for copper and nickel. Biodynamic models have been developed for several organisms and many metals. The models allow for estimates of transport of metals from sediments to organisms via their diet as well as their water exposure. All these advances expand the tool set available to risk assessors. Integr Environ Assess Manag 2024;20:924-951. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Identification of the single and combined acute toxicity of Cr and Ni with Heterocypris sp. and the quantitative structure-activity relationship (QSAR) model

Mining wastewater with heavy metals poses a serious threat to the ecological environment. However, the acute single and combined ecological effects of heavy metals, such as chromium (Cr) and nickel (Ni), on freshwater ostracods, and the development of relevant prediction models, remain poorly understood. In this study, Heterocypris sp. was chosen to investigate the single and combined acute toxicity of Cr and Ni. Then, the quantitative structure-activity relationship (QSAR) model was used to predict the combined toxicity of Cr and Ni. The single acute toxicity experiments revealed high toxicity for both Cr and Ni. In addition, Cr exhibited greater toxicity compared to Ni, as evidenced by its lower 96-hour half-lethal concentration (LC50) of 1.07 mg/L compared to 4.7 mg/L for Ni. Furthermore, the combined acute toxicity experiments showed that the toxicity of Cr-Ni was higher than Ni but lower than Cr. Compared with the concentration addition (CA) and independent action (IA) models, the predicted results of the QSAR model were more consistent with the experimental results for the Cr-Ni combined acute toxicity. So, the high accuracy of QSAR model identified its feasibility to predict the toxicity of heavy metal pollutants in mining wastewater.

Using Multiple Metal Mixture Models to Predict Toxicity of Riverine Sediment Porewater to the Benthic Life Stage of Juvenile White Sturgeon (Acipenser transmontanus)

Five metal mixture dose-response models were used to predict the toxicity of porewater to young sturgeon at areas of interest in the Upper Columbia River (WA, USA/BC, Canada) and to evaluate these models as tools for risk assessments. Dose components of metal mixture models included exposure to free metal ion activities or metal accumulation by biotic ligands or humic acid, and links of dose to response used logistic equations, independent joint action equations, or additive toxicity functions. Laboratory bioassay studies of single metal exposures to juvenile sturgeon, porewater collected in situ in the fast-flowing Upper Columbia River, and metal mixture models were used to evaluate toxicity. The five metal mixture models were very similar in their predictions of adverse response of juvenile sturgeon and in identifying copper (Cu) as the metal responsible for the most toxic conditions. Although the modes of toxic action and the 20% effective concentration values were different among the dose models, predictions of adverse response were consistent among models because all doses were tied to the same biological responses. All models indicated that 56% ± 5% of 122 porewater samples were predicted to have <20% adverse response, 25% ± 5% of samples were predicted to have 20% to 80% adverse response, and 20% ± 4% were predicted to have >80% adverse response in juvenile sturgeon. The approach of combining bioassay toxicity data, compositions of field porewater, and metal mixture models to predict lack of growth and survival of aquatic organisms due to metal toxicity is an important tool that can be integrated with other information (e.g., survey studies of organism populations, life cycle and behavior characteristics, sediment geochemistry, and food sources) to assess risks to aquatic organisms in metal-enriched ecosystems. Environ Toxicol Chem 2024;43:62-73. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.

Development and Validation of Multiple Linear Regression Models for Predicting Chronic Zinc Toxicity to Freshwater Microalgae

Multiple linear regression (MLR) models were developed for predicting chronic zinc toxicity to a freshwater microalga, Chlorella sp., using three toxicity-modifying factors (TMFs): pH, hardness, and dissolved organic carbon (DOC). The interactive effects between pH and hardness and between pH and DOC were also included. Models were developed at three different effect concentration (EC) levels: EC10, EC20, and EC50. Models were independently validated using six different zinc-spiked Australian natural waters with a range of water chemistries. Stepwise regression found hardness to be an influential TMF in model scenarios and was retained in all final models, while pH, DOC, and interactive terms had variable influence and were only retained in some models. Autovalidation and residual analysis of all models indicated that models generally predicted toxicity and that there was little bias based on individual TMFs. The MLR models, at all effect levels, performed poorly when predicting toxicity in the zinc-spiked natural waters during independent validation, with models consistently overpredicting toxicity. This overprediction may be from another unaccounted for TMF that may be present across all natural waters. Alternatively, this consistent overprediction questions the underlying assumption that models developed from synthetic laboratory test waters can be directly applied to natural water samples. Further research into the suitability of applying synthetic laboratory water-based models to a greater range of natural waters is needed. Environ Toxicol Chem 2023;42:2630-2641. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Acute Toxicity of Copper to Three Species of Pacific Salmon Fry in Water with Low Hardness and Low Dissolved Organic Carbon

Proposed development of a mine within Alaska's Bristol Bay watershed (USA) has raised concerns about the potential impact of copper (Cu) on Pacific salmon (Oncorhynchus spp.). We conducted 96-h flow-through bioassays using low-hardness and low dissolved organic carbon water to determine the acute lethal toxicity of Cu to sockeye (Oncorhynchus nerka), Chinook (Oncorhynchus tshawytscha), and coho salmon (Oncorhynchus kisutch) fry. We aimed to determine Cu toxicity under field-relevant water quality conditions and to assess three methods of calculating ambient Cu criteria: the biotic ligand model (BLM), a multiple linear regression model endorsed by the US Environmental Protection Agency, and the hardness-based model currently used by the State of Alaska. The criteria generated by all models were below 20% lethal Cu concentrations by factors ranging from 2.2 to 54.3, indicating that all criteria would be protective against mortality. The multiple linear regression-based criteria were the most conservative and were comparable to BLM-based criteria. The median lethal concentrations (LC50s) for sockeye, Chinook, and coho were 35.2, 23.9, and 6.3 µg Cu/L, respectively. We also used the BLM to predict LC50s for each species. Model predictions differed from empirical LC50s by factors of 0.7 for sockeye and Chinook salmon, and 1.1 for coho salmon. These differences fell within the acceptable range of ±2, indicating the model's accuracy. We calculated critical lethal Cu accumulation values for each species to account for differing water chemistry in each bioassay; the present study revealed that coho salmon were most sensitive to Cu, followed by sockeye and Chinook salmon. Our findings underscore the importance of considering site- and species-specific factors when modeling Cu toxicity. The empirical data we present may enhance Cu risk assessments for Pacific salmon. Environ Toxicol Chem 2023;42:2440-2452. © 2023 SETAC.

Evaluation of effects-based methods as monitoring tools for assessing ecological impacts of metals in aquatic ecosystems

Effects-based methods (EBMs) are considered part of a more integrative strategy for regulating substances of concern under the European Union Water Framework Directive. In general, EBMs have been demonstrated as useful indicators of effects on biota, although links to population and community-level effects are sometimes uncertain. When EBMs are sufficiently specific and sensitive, and links between measured endpoints and apical or higher level effects are established, they can be a useful tool in assessing effects from a specific toxicant or class of toxicants. This is particularly valuable for toxicants that are difficult to measure and for assessing the effects of toxicant mixtures. This paper evaluates 12 EBMs that have been proposed for potential use in the assessment of metals. Each EBM was evaluated with respect to metal specificity and sensitivity, sensitivity to other classes of toxicants, and the strength of the relationship between EBM endpoints and effects observed at the whole organism or population levels of biological organization. The evaluation concluded that none of the EBMs evaluated meet all three criteria of being sensitive to metals, insensitive to other classes of toxicants, and a strong indicator of effects at the whole organism or population level. Given the lack of suitable EBMs for metals, we recommended that the continued development of mixture biotic ligand models (mBLMs) may be the most effective way to achieve the goal of a more holistic approach to regulating metals in aquatic ecosystems. Given the need to further develop and validate mBLMs, we suggest an interim weight-of-evidence approach that includes mBLMs, macroinvertebrate community bioassessment, and measurement of metals in key macroinvertebrate species. This approach provides a near-term solution and simultaneously generates data needed for the refinement and validation of mBLMs. Once validated, it should be possible to rely primarily on mBLMs as an alternative to EBMs for metals. Integr Environ Assess Manag 2023;19:24-31.  © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Refining our understanding of metal bioavailability in sediments using information from porewater: Application of a multimetal biotic ligand model as an extension of the equilibrium partitioning sediment benchmarks

The equilibrium partitioning sediment benchmarks (ESBs) derived by the US Environmental Protection Agency (USEPA) in 2005 provide a mechanistic framework for understanding metal bioavailability in sediments by considering equilibrium partitioning (EqP) theory, which predicts that metal bioavailability in sediments is determined largely by partitioning to sediment particles. Factors that favor the partitioning of metals to sediment particles, such as the presence of acid volatile sulfide (AVS) and sediment organic matter, reduce metal bioavailability to benthic organisms. Because ESBs link metal bioavailability to partitioning to particles, they also predict that measuring metals in porewater can lead to a more accurate assessment of bioavailability and toxicity to benthic organisms. At the time of their development, sediment ESBs based on the analysis of porewater metal concentrations were limited to comparison with hardness-dependent metals criteria for the calculation of interstitial water benchmark units (IWBUs). However, the multimetal biotic ligand model (mBLM) provides a more comprehensive assessment of porewater metal concentrations, because it considers factors in addition to hardness, such as pH and dissolved organic carbon, and allows for interactions between metals. To evaluate the utility of the various sediment and porewater ESBs, four Hyalella azteca bioassay studies were identified that included sediment and porewater measurements of metals and porewater bioavailability parameters. Evaluations of excess simultaneously extracted metals, IWBUs, and mBLM toxic units (TUs) were compared among the bioassay studies. For porewater, IWBUs and mBLM TUs were calculated using porewater metal concentrations from samples collected using centrifugation and peepers. The percentage of correct predictions of toxicity was calculated for each benchmark comparison. The mBLM-based assessment using peeper data provided the most accurate predictions for the greatest number of samples among the evaluation methods considered. This evaluation demonstrates the value of porewater-based evaluations in conjunction with sediment chemistry in understanding toxicity observed in bioassay studies. Integr Environ Assess Manag 2022;18:1335-1347. © 2021 SETAC.

Collection and use of porewater data from sediment bioassay studies for understanding exposure to bioavailable metals

The US Environmental Protection Agency Procedures for the Derivation of Equilibrium Partitioning Sediment Benchmarks (ESBs) for the Protection of Benthic Organisms: Metal Mixtures (Cadmium, Copper, Lead, Nickel, Silver and Zinc) equilibrium partitioning approach causally link metal concentrations and toxicological effects; they apply to sediment and porewater (i.e., interstitial water). The evaluation of bioavailable metal concentrations in porewater, using tools such as the biotic ligand model, provides an advancement that complements sediment-based evaluations. However, porewater characterization is less commonly performed in sediment bioassays than sediment chemistry characterization due to the difficulty and expense of porewater collection as well as concerns about interpretation of porewater data. This study discusses the advantages and disadvantages of different porewater extraction methods for analysis of metals and bioavailability parameters during laboratory sediment bioassays, with a focus on peepers and centrifugation. The purpose is to provide recommendations to generate bioassay porewater data of sufficient quality for use in risk-based decision-making, such as for regulated cleanup actions. Comparisons of paired data from previous bioassay studies indicate that metal porewater concentrations collected via centrifugation tend to be higher than those collected via peepers. However, centrifugation disrupts the redox status of the sediment; also, metal concentrations can vary markedly based on centrifugation conditions. Data to compare the concentrations of peeper- and centrifugation-collected bioavailability parameters (e.g., major ions, pH) are much more limited, but indicate smaller differences than those observed for metal concentrations. While peepers can be sampled without altering the redox status of the porewater, the small volume of porewater peepers collected is enough for metal concentration analysis, but insufficient for analysis of all metal bioavailability parameters. Given the benefits of metal collection via peepers, it is optimal to use centrifugation and peepers in tandem for bioassay porewater collection to improve bioavailability predictions. Environ Assess Manag 2022;18:1321-1334. © 2021 SETAC.

Sensitivity of Ostracods to U, Cd and Cu: The Case of Cypridopsis vidua

The development of uranium mines has been necessary to obtain abundant and scarce uranium resources, but they also bring inevitable radioactive contamination to the surrounding soil, rivers and lakes. This paper explores the sensitivity of Cypridopsis vidua to the radioactive element uranium and the heavy elements cadmium and copper with single and combined acute toxicity experiments and combined toxicity model predictions. The results from the single toxicity experiments showed that the degree of toxic effects was cadmium > copper > uranium. The combined toxicity experiments showed that the compound toxicity of U-Cd and U-Cu was higher than the weakest component and lower than the strongest component, whereas the compound toxicity of Cd-Cu was higher than either of its components. When the overall proportion of a more toxic metal was increased, its mixed toxicity also increased, and vice versa. Combined toxicity predictions showed that the U-Cd combination was best described by the concentration additive (CA) model, the independent action (IA) model was more applicable to the Cd-Cu combination, and the most applicable model for the U-Cu combination changed depending on the concentration gradient. The acute toxicity data from this study provide a reference for the development of wastewater discharge standards for uranium mines, enriches the data related to the toxicity of uranium for ostracods and deepens the understanding of the threat of uranium pollution to aquatic ecosystems.

A Review of Water Quality Factors that Affect Nickel Bioavailability to Aquatic Organisms: Refinement of the Biotic Ligand Model for Nickel in Acute and Chronic Exposures

A review of nickel (Ni) toxicity to aquatic organisms was conducted to determine the primary water quality factors that affect Ni toxicity and to provide information for the development and testing of a biotic ligand model (BLM) for Ni. Acute and chronic data for 66 aquatic species were compiled for the present review. The present review found that dissolved organic carbon (DOC) and hardness act as toxicity-modifying factors (TMFs) because they reduced Ni toxicity to fish and aquatic invertebrates, and these effects were consistent in acute and chronic exposures. The effects of pH on Ni toxicity were inconsistent, and for most organisms there was either no effect of pH or, in some cases, a reduction in toxicity at low pH. There appears to be a unique pH effect on Ceriodaphnia dubia that results in increased toxicity at pHs above 8, but otherwise the effects of TMFs were consistent enough across all organisms and endpoints that a single set of parameters in the Ni BLM worked well with all acute and chronic toxicity data for fish, amphibians, aquatic invertebrates, and aquatic plants and algae. The unique effects of pH on C. dubia may be due to mixture toxicity involving both Ni and bicarbonate. The implications of this mixture effect on BLM modeling and a proposed set of BLM parameters for C. dubia are addressed in the review. Other than this exception, the Ni BLM with a single set of parameters could successfully predict toxicity to all acute and chronic data compiled in the present review. Environ Toxicol Chem 2021;40:2121-2134. © 2021 SETAC.

The use of WHAM-FTOX, parameterized with laboratory data, to simulate zooplankton species richness in acid- and metal- contaminated lakes

The WHAM-F_TOX model quantifies cation toxicity towards freshwater organisms, assuming an additive toxic response to the amounts of protons and metals accumulated by an organism. We combined a parameterization of the model, using data from multi-species laboratory toxicity tests, with a fitted field species sensitivity distribution, to simulate the species richness (n_sp) of crustacean zooplankton in acid- and metal-contaminated lakes near Sudbury, Ontario over several decades, and also in reference (uncontaminated) lakes. A good description of variation in toxic response among the zooplankton species was achieved with a log-normal distribution of a new parameter, β, which characterizes an organism's intrinsic sensitivity towards toxic cations; the greater is β, the more sensitive is the species. The use of β assumes that while species vary in their sensitivity, the relative toxicities of different metals are the same for each species (common relative sensitivity). Unbiased agreements between simulated and observed n_sp were obtained with a high correlation (r² = 0.81, p < 0.0001, n = 217). Variations in zooplankton species richness in the Sudbury lakes are calculated to be dominated by toxic responses to H, Al, Cu and Ni, with a small contribution from Zn, and negligible effects of Cd, Hg and Pb. According to the model, some of the Sudbury lakes were affected predominantly by acidification (H and Al), while others were most influenced by toxic heavy metals (Ni, Cu, Zn); for lakes in the latter category, the relative importance of heavy metals, compared to H and Al, has increased over time. The results suggest that, if common relative sensitivity operates, n_sp can be modelled on the basis of a single set of parameters characterizing the average toxic effects of different cations, together with a species sensitivity distribution.

Time-dependent accumulation of Cd, Co, Cu, Ni, and Zn in natural communities of mayfly and caddisfly larvae: Metal sensitivity, uptake pathways, and mixture toxicity

Conceptual and quantitative models were developed to assess time-dependent processes in four sequential experimental stream studies that determined abundances of natural communities of mayfly and caddisfly larvae dosed with single metals (Cd, Co, Cu, Ni, Zn) or multiple metals (Cd + Zn, Co + Cu, Cu + Ni, Cu + Zn, Ni + Zn, Cd + Cu + Zn, Co + Cu + Ni, Cu + Ni + Zn). Metal mixtures contained environmentally relevant metal ratios found in mine drainage. Free metal ion concentrations, accumulation of metals by periphyton, and metal uptake by four families of aquatic insect larvae were either measured (Brachycentridae) or predicted (Ephemerellidae, Heptageniidae, Hydropsychidae) using equilibrium and biodynamic models. Toxicity functions, which included metal accumulations by larvae and metal potencies, were linked to abundances of the insect families. Model results indicated that mayflies accumulated more metal than caddisflies and the relative importance of metal uptake by larvae via dissolved or dietary pathways highly depended on metal uptake rate constants for each insect family and concentrations of metals in food and water. For solution compositions in the experimental streams, accumulations of Cd, Cu, and Zn in larvae occurred primarily through dietary uptake, whereas uptake of dissolved metal was more important for Co and Ni accumulations. Cd, Cu, and Ni were major contributors to toxicity in metal mixtures and for metal ratios examined. Our conceptual approach and quantitative results should aid in designing laboratory experiments and field studies that evaluate metal uptake pathways and metal mixture toxicity to aquatic biota.

Toward Sustainable Environmental Quality: Priority Research Questions for Asia

Environmental and human health challenges are pronounced in Asia, an exceptionally diverse and complex region where influences of global megatrends are extensive and numerous stresses to environmental quality exist. Identifying priorities necessary to engage grand challenges can be facilitated through horizon scanning exercises, and to this end we identified and examined 23 priority research questions needed to advance toward more sustainable environmental quality in Asia, as part of the Global Horizon Scanning Project. Advances in environmental toxicology, environmental chemistry, biological monitoring, and risk-assessment methodologies are necessary to address the adverse impacts of environmental stressors on ecosystem services and biodiversity, with Asia being home to numerous biodiversity hotspots. Intersections of the food-energy-water nexus are profound in Asia; innovative and aggressive technologies are necessary to provide clean water, ensure food safety, and stimulate energy efficiency, while improving ecological integrity and addressing legacy and emerging threats to public health and the environment, particularly with increased aquaculture production. Asia is the largest chemical-producing continent globally. Accordingly, sustainable and green chemistry and engineering present decided opportunities to stimulate innovation and realize a number of the United Nations Sustainable Development Goals. Engaging the priority research questions identified herein will require transdisciplinary coordination through existing and nontraditional partnerships within and among countries and sectors. Answering these questions will not be easy but is necessary to achieve more sustainable environmental quality in Asia. Environ Toxicol Chem 2020;39:1485-1505. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Model-based rationalization of mixture toxicity and accumulation in Triticum aestivum upon concurrent exposure to yttrium, lanthanum, and cerium

Rare earth elements (REEs) often co-exist in the environment, but predicting their 'cocktail effects' is still challenging, especially for high-order mixtures with more than two components. Here, we systematically investigated the toxicity and accumulation of yttrium, lanthanum, and cerium mixtures in Triticum aestivum following a standardized bioassay. Toxic effects of mixtures were predicted using the reference model of Concentration Addition (CA), Ternary model, and Ternary-Plus model. Interactions between the REEs in binary and ternary mixtures were determined based on external and internal concentrations, and their magnitude estimated from the parameters deviated from CA. Strong antagonistic interactions were found in the ternary mixtures even though there were no significant interactions in the binary mixtures. Predictive ability increased when using the CA model, Ternary model, and Ternary-Plus model, with R²= 0.78, 0.80, and 0.87 based on external exposure concentrations, and R²= 0.72, 0.73, and 0.79, respectively based on internal concentrations. The bioavailability-based model WHAM-F_TOX explained more than 88 % and 85 % of the toxicity of binary and ternary REE treatments, respectively. Our result showed that the Ternary-Plus model and WHAM-F_TOX model are promising tools to account for the interaction of REEs in mixtures and could be used for their risk assessment.

Validation of Bioavailability-Based Toxicity Models for Metals

Regulatory jurisdictions worldwide are increasingly incorporating bioavailability-based toxicity models into development of protective values (PVALs) for freshwater and saltwater aquatic life (e.g., water quality criteria, standards, and/or guidelines) for metals. Use of such models for regulatory purposes should be contingent on their ability to meet performance criteria as specified through a model-validation process. Model validation generally involves an assessment of a model's appropriateness, relevance, and accuracy. We review existing guidance for validation of bioavailability-based toxicity models, recommend questions that should be addressed in model-validation studies, discuss model study type and design considerations, present several new ways to evaluate model performance in validation studies, and suggest a framework for use of model validation in PVAL development. We conclude that model validation should be rigorous but flexible enough to fit the user's purpose. Although a model can never be fully validated to a level of zero uncertainty, it can be sufficiently validated to fit a specific purpose. Therefore, support (or lack of support) for a model should be presented in such a way that users can choose their own level of acceptability. We recommend that models be validated using experimental designs and endpoints consistent with the data sets that were used to parameterize and calibrate the model and validated across a broad range of geographically and ecologically relevant water types. Environ Toxicol Chem 2019;39:101-117. © 2019 SETAC.

Much ado about interaction: A combination of linear processes yields non-linear toxic effects in chemical mixtures

Predicting chemical mixture toxicity is an important issue for risk assessment. Loewe's concentration addition (CA) is a major model for predicting such toxicity. The CA is an additivity-based model, and if the results of toxicity test deviate from the CA prediction, it is considered that the toxic effect of the mixture is non-additive, and that "interaction" has played some role. In the present study, using as an example a biotic ligand model (BLM), which predicts metal toxicities, we theoretically investigated the toxic effect of mixture and found that the effects are almost always non-additive if the effects are evaluated by total metal concentrations, and the non-additivity is not derived by interactions among metals but by a combination of processes of metal kinetics. Once non-additive effects are observed in chemical mixture, it is often expected that there should be some complex toxic mechanisms or some toxic interaction. Our results suggest that the expectation may not be always true. Since at least two processes are entrained in the metal toxicity (metal speciation and binding of metals to biotic ligand in BLM framework), there is a possibility that the non-additivity is generated by the combination of processes and interaction is nothing to do with it. Our results imply that toxic effects of metal mixture can be predicted more easily than we generally expected.

Using the Biotic Ligand Model framework to investigate binary metal interactions on the uptake of Ag, Cd, Cu, Ni, Pb and Zn in the freshwater snail Lymnaea stagnalis

There is growing interest in the development of mechanistically-based models, such as the Biotic Ligand Model (BLM), for assessing the environmental risk of metal mixtures. However, the derivation of such models requires insights into the mechanisms of multimetal interactions that are often lacking for aquatic organisms. In the present study, we investigated how binary mixtures of six metals (Ag, Cd, Cu, Ni, Pb and Zn) interact for uptake in the great pond snail Lymnaea stagnalis, a freshwater species particularly sensitive to metals in chronic exposure. For each metal, short-term (2-3 h) uptake experiments on juvenile snails were performed with the metal alone and in combination with a second metal, at concentrations encompassing the chronic toxicity concentration range. These experiments showed significant binary metal interactions for 7 out of 15 mixtures. Most interactions were inhibitory in nature, not reciprocal and caused by either Ag or Cu. They led to relative changes of uptake that did not exceed 50% within the range of metal chronic toxicity. The BLM proved to be successful at explaining most of the interactions, via competitive inhibition. This study is in support of using bioavailability-based models, such as the BLM, to model metal mixture interactions in L. stagnalis.

Characterizing toxicity of metal-contaminated sediments from the Upper Columbia River, Washington, USA, to benthic invertebrates

Sediments from the Upper Columbia River, Washington, USA, are contaminated with metals from smelting operations. We conducted short-term and long-term tests with the midge Chironomus dilutus and the amphipod Hyalella azteca and short-term tests with the freshwater mussel Lampsilis siliquoidea with 54 sediments from the Upper Columbia River to characterize thresholds for toxicity of metals to benthic invertebrates. Test sediments were screened for toxicity by comparisons with low-metal reference sediments. Toxic effects on amphipods occurred primarily in sediments from the upstream (riverine) reach, and toxic effects on midges occurred in sediments from both the upstream reach and the downstream (reservoir) reach. Little toxicity was observed in mussel tests. Toxicity thresholds (20% effect concentrations [EC20s]) for metals in sediment and porewater were estimated from logistic concentration-response models. Copper (Cu) concentrations in the simultaneously extracted metal fraction of sediments and bioavailable Cu in porewater, as characterized by biotic ligand models, had consistent associations with toxicity endpoints. Concentration-response models for sediment Cu produced EC20s for 6 endpoints, with long-term amphipod survival and reproduction being the most sensitive. A logistic regression model fitted to an endpoint sensitivity distribution for sediment Cu predicted that approximately one-half of the sediments tested would be toxic to at least one endpoint and that approximately 20% of test sediments would be toxic to more than half of the endpoints. These results indicate that sediments from the upstream reach of the Upper Columbia River, which contain high concentrations of metals associated with slags, cause a wide range of toxic effects in laboratory tests and are likely to have adverse effects on benthic invertebrate communities. Environ Toxicol Chem 2018;37:3102-3114. Published 2018 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

Responses of Daphnia magna to chronic exposure of cadmium and nickel mixtures

The present study assessed the chronic toxicity of cadmium (Cd) and nickel (Ni) mixtures to Daphnia magna. Using a titration design, Ni concentrations of 20, 40, 80, 100, 120, 140, and 160 μg/L were tested alone and simultaneously titrated in increments against a constant concentration of 1.5 μg/L Cd. The results demonstrated that Cd at 1.5 μg/L was highly toxic to D. magna, and Ni alone concentrations ≥80 μg/L were toxic to D. magna survival, reproduction, and growth. No Ni alone concentration was found to induce a toxic effect on undeveloped embryos and the time to first brood. Only the Ni alone treatment containing 200 μg/L affected the reproductive rates of D. magna. For CdNi mixtures, Ni concentrations of 20, 40, and 80 μg/L were found to strongly protect D. magna from Cd toxicity at the survival and growth endpoints, resulting in less-than-additive effects, but not on the reproductive endpoint. At higher concentrations, Ni exceeded the necessary concentration needed to protect D. magna, and appeared to contribute to the toxicity. Overall, the results of metal uptake support the competitive binding mechanism at the biotic ligand and explain the less-than-additive effects observed in the CdNi mixtures concentration. The embryonic effects of CdNi mixtures are not explained by the competitive binding mechanism at the biotic ligand. More research is needed to determine the mechanisms that produce embryonic impairment when cellular metals interact. Overall, the results of the present study are relevant for the development of improved environmental quality guidelines for metal mixtures.

Potential Toxicity of Dissolved Metal Mixtures (Cd, Cu, Pb, Zn) to Early Life Stage White Sturgeon ( Acipenser transmontanus) in the Upper Columbia River, Washington, United States

The Upper Columbia River (UCR) received historical releases of smelter waste resulting in elevated metal concentrations in downstream sediments. Newly hatched white sturgeon hide within the rocky substrate at the sediment-water interface in the UCR for a few weeks before swim-up. Hiding behavior could expose them to metal contaminants, and metal toxicity could contribute to population declines in white sturgeon over the past 50 years. This study evaluates whether there is a link between the toxicity of dissolved metals across the sediment-water interface in the UCR and the survival of early life stage (ELS) white sturgeon. Toxicity of dissolved metal mixtures is evaluated using a combination of previously collected laboratory and field data and recently developed metal mixture toxicity models. The laboratory data consist of individual metal (Cd, Cu, Pb, and Zn) toxicity studies with ELS white sturgeon. The field data include the chemical composition of surface and pore water samples that were collected across the sediment-water interface in the UCR. These data are used in three metal accumulation and two response models. All models predict low toxicity in surface water, whereas effects concentrations greater than 20% are predicted for 60-72% of shallow pore water samples. The flux of dissolved metals, particularly Cu, from shallow pore water to surface water likely exposes prime ELS sturgeon habitat to toxic conditions.

A FTIRM study of the interactive effects of metals (zinc, copper and cadmium) in binary mixtures on the biochemical constituents of the gills in rainbow trout (Oncorhynchus mykiss)

We employed Fourier Transform Infrared Microspectroscopy to examine, in situ, the effects of waterborne Cu, Cd and Zn, alone and in binary mixtures, during acute exposure on the integrity of major lipid and protein constituents of the gill of a model teleost species, rainbow trout (Oncorhynchus mykiss). Our findings demonstrated that acute exposure to metals, both individually and in binary mixture, resulted in the degradations of various components of proteins and lipids in the gill tissue. Generally, when comparing the effects of individual metals, Cu was found to induce the maximum adverse effects followed by Cd and Zn, respectively. Among the binary metal-mixture combinations, Cu and Cd produced additive effects on the degradation of major proteins and lipid moieties, whereas the co-exposure of Zn with Cd or Cu elicited ameliorative effects, indicating antagonistic (less than additive) interactions between Zn and Cd or Cu in the rainbow trout gill. Overall, the present study demonstrates that FTIRM can be a useful tool to gain novel mechanistic insights into the biochemical changes induced by metals in the fish gill, which could influence the overall toxicity of metals to fish.

Metal accumulation and expression of genes encoding for metallothionein and copper transporters in a chronically exposed wild population of the fish Hyphessobrycon luetkenii

In the present study, metal (As, Cd, Cu, Fe, Mn, Pb and Zn) accumulation and expression of genes involved in metal metabolism (metallothioneins, ATP7A and CTR1) were evaluated in gills and muscle of the fish Hyphessobrycon luetkenii living in the João Dias creek, a site historically (~1870-1996) contaminated with a metal mixture associated with copper mining (Minas do Camaquã, southern Brazil). Fish were collected in a metal impacted site of the João Dias creek and kept in a cage at this site (PP fish) or translocated to a non-metal impacted reach of this creek (PC fish). Gill metal concentrations and metallothionein gene expression were lower in PC fish than in PP fish at any experimental time (24, 48 and 72 h). In muscle, no significant changes were observed. These findings indicate that metal accumulated in gills of wild fish chronically exposed to the metal mixture are more easily excreted than those accumulated in the muscle. In this case, expression of gene encoding for metallothionein is shown to play a key role in the regulation of metal accumulation in gills of H. luetkenii living in an area historically contaminated with a metal mixture associated with copper mining.

Development of multi-metal interaction model for Daphnia magna: Significance of metallothionein in cellular redistribution

Despite the great progress made in metal-induced toxicity mechanisms, a critical knowledge gap still exists in predicting adverse effects of heavy metals on living organisms in the natural environment, particularly during exposure to multi-metals. In this study, a multi-metal interaction model of Daphnia manga was developed in an effort to provide reasonable explanations regarding the joint effects resulting from exposure to multi-metals. Metallothionein (MT), a widely used biomarker, was selected. In this model, MT was supposed to play the role of a crucial transfer protein rather than detoxifying protein. Therefore, competitive complexation of metals to MT could highly affect the cellular metal redistribution. Thus, competitive complexation of MT in D. magna with metals like Pb²⁺, Cd²⁺ and Cu²⁺ was qualitatively studied. The results suggested that Cd²⁺ had the highest affinity towards MT, followed by Pb²⁺ and Cu²⁺. On the other hand, the combination of MT with Cu²⁺ appeared to alter its structure which resulted in higher affinity towards Pb²⁺. Overall, the predicted bioaccumulation of metals under multi-metal exposure was consisted with earlier reported studies. This model provided an alternative angle for joint effect through a combination of kinetic process and internal interactions, which could help to develop future models predicting toxicity to multi-metal exposure.

Distribution and speciation of zinc in the gills of rainbow trout (Oncorhynchus mykiss) during acute waterborne zinc exposure: Interactions with cadmium or copper

We utilized micro X-ray fluorescence imaging (μ-XFI) and micro X-ray absorption near-edge spectroscopy (μ-XANES), which are both synchrotron-based techniques to investigate Zn distribution profile, its co-localization patterns with Ca, S, and Fe and speciation in the gills of rainbow trout (RBT). Fish (~100 g) were exposed to acutely toxic levels of waterborne Zn alone and in combination with waterborne Cd or Cu for 24 h (each at 1 × 96 h LC₅₀). Gill sections were prepared and analyzed at the VESPERS beamline of the Canadian Light Source. The primary lamellae of the fish gill were found to be the primary area of Zn accumulation. These regions also correspond to the zones of mitochondria rich cells localization in fish gills, supporting the putative roles of these cells in metal uptake. Zn was also found to predominantly co-localize with Ca and S, but not with Fe, indicating the roles of Ca and S in intracellular Zn handling. Zn distribution in the gill was markedly reduced during co-exposure to Cd, but not to Cu, suggesting a competitive interaction between Zn and Cd for uptake. The speciation of Zn in the gill was dominated by Zn-phosphate, Zn-histidine and Zn-cysteine species; however, the interactions of Zn with Cd or Cu resulted in the loss of Zn-cysteine. Overall, our findings provide important novel insights into the interactions of Zn, Cd and Cu in the fish gill, which may ultimately help to explain the mechanisms underlying the acute toxicity of these metals in binary mixture to fish.

A framework for ecological risk assessment of metal mixtures in aquatic systems

Although metal mixture toxicity has been studied relatively intensely, there is no general consensus yet on how to incorporate metal mixture toxicity into aquatic risk assessment. We combined existing data on chronic metal mixture toxicity at the species level with species sensitivity distribution (SSD)-based in silico metal mixture risk predictions at the community level for mixtures of Ni, Zn, Cu, Cd, and Pb, to develop a tiered risk assessment scheme for metal mixtures in freshwater. Generally, independent action (IA) predicts chronic metal mixture toxicity at the species level most accurately, whereas concentration addition (CA) is the most conservative model. Mixture effects are noninteractive in 69% (IA) and 44% (CA) and antagonistic in 15% (IA) and 51% (CA) of the experiments, whereas synergisms are only observed in 15% (IA) and 5% (CA) of the experiments. At low effect sizes (∼ 10% mixture effect), CA overestimates metal mixture toxicity at the species level by 1.2-fold (i.e., the mixture interaction factor [MIF]; median). Species, metal presence, or number of metals does not significantly affect the MIF. To predict metal mixture risk at the community level, bioavailability-normalization procedures were combined with CA or IA using SSD techniques in 4 different methods, which were compared using environmental monitoring data of a European river basin (the Dommel, The Netherlands). We found that the simplest method, in which CA is directly applied to the SSD (CA_SSD ), is also the most conservative method. The CA_SSD has median margins of safety (MoS) of 1.1 and 1.2 respectively for binary mixtures compared with the theoretically more consistent methods of applying CA or IA to the dose-response curve of each species individually prior to estimating the fraction of affected species (CA_DRC or IA_DRC ). The MoS increases linearly with an increasing number of metals, up to 1.4 and 1.7 for quinary mixtures (median) compared with CA_DRC and IA_DRC , respectively. When our methods were applied to a geochemical baseline database (Forum of European Geological Surveys [FOREGS]), we found that CA_SSD yielded a considerable number of mixture risk predictions, even when metals were at background levels (8% of the water samples). In contrast, metal mixture risks predicted with the theoretically more consistent methods (e.g., IA_DRC ) were very limited under natural background metal concentrations (<1% of the water samples). Based on the combined evidence of chronic mixture toxicity predictions at the species level and evidence of in silico risk predictions at the community level, a tiered risk assessment scheme for evaluating metal mixture risks is presented, with CA_SSD functioning as a first, simple conservative tier. The more complex, but theoretically more consistent and most accurate method, IA_DRC , can be used in higher tier assessments. Alternatively, the conservatism of CA_SSD can be accounted for deterministically by incorporating the MoS and MIF in the scheme. Finally, specific guidance is also given related to specific issues, such as how to deal with nondetect data and complex mixtures that include so-called data-poor metals. Environ Toxicol Chem 2018;37:623-642. © 2017 SETAC.

Mixtures of Cu, Ni, and Zn act mostly noninteractively on Pseudokirchneriella subcapitata growth in natural waters

Freshwater biota are usually exposed to mixtures of different metals in the environment, which raises concern because risk-assessment procedures for metals are still mainly based on single-metal toxicity. Because microalgae are primary producers and therefore at the base of the food web, it is of utmost importance to understand the effects of metal mixtures on these organisms. Most studies that have investigated the combined interactive effects of mixtures on microalgae performed tests in only one specific water. The objective of the present study was to test if combined effects of mixtures to Pseudokirchneriella subcapitata were the same or different across natural waters showing diverse water-chemistry characteristics. This was done by performing experiments with ternary Cu-Ni-Zn mixtures in 3 natural waters and with binary Cu-Ni mixtures in 5 natural waters. We showed that the ternary mixture acted noninteractively on algal growth, except in one water in which the mixture acted antagonistically. We suggest that a low-cationic competition situation in the latter water could be the reason for the antagonistic interaction between the metals. On the other hand, the binary mixture acted noninteractively on algal growth in all tested waters. We showed that both the concentration addition and independent action models can serve as accurate models for toxicity of ternary Cu-Ni-Zn and binary Cu-Ni mixtures to P. subcapitata in most cases and as protective models in all cases. In addition, we developed a metal mixture bioavailability model, by combining the independent action model and the single-metal bioavailability models, that can be used to predict Cu-Ni-Zn and Cu-Ni toxicity to P. subcapitata as a function of metal concentration and water characteristics. Environ Toxicol Chem 2018;37:587-598. © 2017 SETAC.

Metal bioavailability in ecological risk assessment of freshwater ecosystems: From science to environmental management

Metal contamination in freshwater ecosystems is a global issue and metal discharges to aquatic environments are monitored in order to protect aquatic life and human health. Bioavailability is an important factor determining metal toxicity. In aquatic systems, metal bioavailability depends on local water and sediment characteristics, and therefore, the risks are site-specific. Environmental quality standards (EQS) are used to manage the risks of metals in aquatic environments. In the simplest form of EQSs, total concentrations of metals in water or sediment are compared against pre-set acceptable threshold levels. Now, however, the environmental administration bodies have stated the need to incorporate metal bioavailability assessment tools into environmental regulation. Scientific advances have been made in metal bioavailability assessment, including passive samplers and computational models, such as biotic ligand models (BLM). However, the cutting-edge methods tend to be too elaborate or laborious for standard environmental monitoring. We review the commonly used metal bioavailability assessment methods and introduce the latest scientific advances that might be applied to environmental management in the future. We present the current practices in environmental management in North America, Europe and China, highlighting the good practices and the needs for improvement. Environmental management has met these new challenges with varying degrees of success: the USA has implemented site-specific environmental risk assessment for water and sediment phases, and they have already implemented metal mixture toxicity evaluation. The European Union is promoting the use of bioavailability and BLMs in ecological risk assessment (ERA), but metal mixture toxicity and sediment phase are still mostly neglected. China has regulation only for total concentrations of metals in surface water. We conclude that there is a need for (1) Advanced and up-to-date guidelines and legislation, (2) New and simple scientific methods for assessing metal bioavailability and (3) Improvement of knowledge and skills of administrators.

Is the Factor-of-2 Rule Broadly Applicable for Evaluating the Prediction Accuracy of Metal-Toxicity Models?

In aquatic toxicology, a toxicity-prediction model is generally deemed acceptable if its predicted median lethal concentrations (LC50 values) or median effect concentrations (EC50 values) are within a factor of 2 of their paired, observed LC50 or EC50 values. However, that rule of thumb is based on results from only two studies: multiple LC50 values for the fathead minnow (Pimephales promelas) exposed to Cu in one type of exposure water, and multiple EC50 values for Daphnia magna exposed to Zn in another type of exposure water. We tested whether the factor-of-2 rule of thumb also is supported in a different dataset in which D. magna were exposed separately to Cd, Cu, Ni, or Zn. Overall, the factor-of-2 rule of thumb appeared to be a good guide to evaluating the acceptability of a toxicity model's underprediction or overprediction of observed LC50 or EC50 values in these acute toxicity tests.

Characterization of the effects of binary metal mixtures on short-term uptake of Cd, Pb, and Zn by rainbow trout (Oncorhynchus mykiss)

Biotic Ligand Models (BLMs) for individual metals improve our ability to regulate metals in the aquatic environment by considering the effects of water quality parameters (ionic composition, pH, DOC) on metal bioavailability. However, in natural aquatic systems, organisms are often simultaneously exposed to multiple metals and these interactions are not currently considered in BLMs or most environmental regulations. Recently, several different mixture BLMs (mBLMs) have been developed to begin assessing this issue. Some of these models assume competitive interactions between all metals, while others assume only metals with similar modes of action (e.g., Na⁺ or Ca²⁺ antagonists) will competitively interact. In this study, we used standard in vivo 3-h gill metal binding assays to characterize the uptake of Cd, Pb, and Zn individually and in binary mixtures with Ag, Cd, Cu, Pb, Ni, and Zn across a range of concentrations that encompassed the 96-h LC50 for each metal. Inhibition of Cd, Pb, and Zn uptake at the gill by introduction of a second metal was consistent with mode of action in some cases, but not others. Further, contrary to expectations, inhibition was always either non-competitive or could not be defined statistically. We also observed one example of stimulated metal uptake (Ni stimulated Zn uptake). Consistent with our previous experiments on Ag, Cu, and Ni, these studies suggest that current mBLM frameworks will need revision to better reflect the mechanisms underlying metal mixture interactions.

Chronic toxicity of binary-metal mixtures of cadmium and zinc to Daphnia magna

The present study characterized the chronic effect of binary-metal mixtures of cadmium (Cd) and zinc (Zn) on Daphnia magna. The titration design was chosen to characterize the 21-d chronic effects of the binary-metal mixtures on survival, growth, reproduction, and metal accumulation in D. magna. Using this design, increasing concentrations of Zn (10, 20, 40, 80, 120, 160, and 200 μg/L) were titrated against a constant concentration of 1.5 μg/L Cd. The results demonstrated that Cd was highly toxic to D. magna. In a mixture with Cd and Zn, sublethal concentrations of 10 and 20 μg/L Zn were insufficient to protect D. magna from chronic Cd toxicity, whereas mixtures containing 40, 80, and 120 μg/L Zn provided strong protective effects to D. magna at all endpoints and resulted in less-than-additive effects. At higher Zn concentrations, such as 160 and 200 μg/L, Zn appeared to contribute to the toxicity. The less-than-additive effects observed in the Cd-Zn mixture can be explained by the decrease in body Cd concentration when the Zn concentration was increased in the exposure media. Embryos analyzed for morphological alterations in the Cd-Zn mixtures demonstrated severe developmental defects. The effect of Cd on undeveloped embryos while both Zn and Cd are present in the organisms raises a question of whether the competitive binding mechanism of Zn and Cd is still happening at the cellular level in the organisms. The results of the present study are useful for development of the biotic ligand model and environmental quality guidelines for metal mixtures. Environ Toxicol Chem 2017;36:2739-2749. © 2017 SETAC.

Development of electrostatic-based bioavailability models for interpreting and predicting differential phytotoxicity and uptake of metal mixtures across different soils

Metals are ubiquitous and normally co-occur as mixtures in soil, but there remains much to do regarding the development of appropriate models which incorporate mixture interactions and bioavailability to estimate their phytotoxicity and phytoaccumulation. Here, we developed a probability-based electrostatic toxicity model (ETM) and a Langmuir-type electrostatic uptake model (EUM) to predict and normalize toxicity and uptake of zinc-copper mixtures in Hordeum vulgare L. in different soils. For model development, the electrical potential (ψ₀) and metal ion activities ({M²⁺}₀) at the cell-membrane surface was computed based on plant physiological properties and soil solution chemistry. Single metal toxicity correlated more closely to their corresponding {M²⁺}₀ than to ion activities in soil solution or total soil metal concentrations. The ETM explained up to 89% of the variance in mixture toxicity across different soils. Incorporation of ψ₀ into the EUM improved the model's ability for predicting metal uptake. Besides, cell-surface H⁺ appeared to significantly inhibit copper uptake via competition or other mechanisms, beyond its effect upon ψ₀. Our results for the first time demonstrate that electrostatic theory can be used to predict and reconcile mixture toxicity and uptake data in different soils, indicating the potential of electrostatic-based models in risk assessment of multimetal-contaminated soils.

Internal versus External Dose for Describing Ternary Metal Mixture (Ni, Cu, Cd) Chronic Toxicity to Lemna minor

Simultaneous determinations of internal dose ([M]_tiss) and external doses ([M]_tot, {M²⁺} in solution) were conducted to study ternary mixture (Ni, Cu, Cd) chronic toxicity to Lemna minor in alkaline solution (pH 8.3). Also, concentration addition (CA) based on internal dose was evaluated as a tool for risk assessment of metal mixture. Multiple regression analysis of dose versus root growth inhibition, as well as saturation binding kinetics, provided insight into interactions. Multiple regressions were simpler for [M]_tiss than [M]_tot and {M²⁺}, and along with saturation kinetics to the internal biotic ligand(s) in the cytoplasm, they indicated that Ni-Cu-Cd competed for uptake into plant, but once inside, only Cu-Cd shared a binding site. Copper inorganic complexes (hydroxides, carbonates) played a role in metal bioavailability in single metal exposure but not in mixtures. Regardless of interactions, the current regulatory approach of using CA based on [M]_tot can sufficiently predict mixture toxicity (∑TU close to 1), but CA based on [M]_tiss was closest to unity across a range of doses. Internal dose integrates all metal-metal interactions in solution and during uptake into the organism, thereby providing a more direct metric describing toxicity.

Modeling interactions and toxicity of Cu-Zn mixtures to zebrafish larvae

Quantitative predictions of metal-metal interactions and toxicity in aquatic organisms meet a unique challenge. Accumulation and toxicity of Cu and Zn mixtures in zebrafish larvae has been quantified in binary metal system with variable combinatorial concentrations in order to understand the interactions between essential trace metals and assess availability of the toxicokinetic-toxicodynamic (TK-TD) model which simulated the uptake of metals over time as well as metal toxicity after 24h of exposure. Competitive uptake experiments showed a straightforward antagonistic competition, as would be predicted by Michaelis-Menten competitive equilibrium model. Zn uptake decreased significantly in the presence of Cu²⁺ concentrations higher than 10^-6M. Cu²⁺ was shown to compete strongly with Zn for uptake, having a higher affinity constant to biotic ligand (BL) sites (K_CuBL=10^5.42M^-1) than Zn (K_ZnBL=10^4.13M^-1). TK-TD model considering potential metal-metal antagonism interactions showed good predictive power in predicting accumulation and toxicity of Cu-Zn mixtures in zebrafish larvae with the high coefficient of determination (r²) and significant level (p). In particular, with the elevated Zn concentrations in mixtures, the TD model showed better predictive power in predicting toxicity of 10^-6M Cu concentration in Cu-Zn mixtures. The TK-TD analysis provided some new insights into the interactive mechanism of binary Cu and Zn exposure in aquatic animals and may have important implications for our understanding of quantitative predictions of metal-metal interactions and toxicity in a field where animals are simultaneously exposed to several metals.

Toxicity Assessment of Binary Metal Mixtures (Copper-Zinc) to Nitrification in Soilless Culture with the Extended Biotic Ligand Model

Metals are always found in the environment as mixtures rather than as solitary elements. Only a limited number of studies have developed appropriate models that incorporate bioavailability to estimate the toxicity of heavy-metal mixtures. In the present study, we explored the applicability of two extended biotic ligand model (BLM) approaches-BLM-f _mix and BLM-toxicity unit (TU)-to predict and interpret mixture toxicity with the assumption that interactions between metal ions obey the BLM theory. Exposure assays of single and mixed metals were performed with inoculums of an ammonia-oxidizing bacterium SD5 isolated from soil. Nitrification of the cultures was the end point used to quantify the toxic response. The results indicated that the developed BLM-f _mix approach could well estimate the single toxicity of Cu²⁺ and Zn²⁺ as well as their binary mixture toxicity to nitrification with >90% of toxicity variation explained. Assuming that metal ions compete with each other for binding at a single biotic ligand, the BLM-f _mix approach (root-mean-square error [RMSE] = 19.66, R ² = 0.8879) showed better predictive power than the BLM-TU approach (RMSE = 31.12, R ² = 0.6892). The present study supports the use of the accumulation of metal ions at the biotic ligands as predictor of toxicity of single metals and metal mixtures.

Development and validation of a metal mixture bioavailability model (MMBM) to predict chronic toxicity of Ni-Zn-Pb mixtures to Ceriodaphnia dubia

Recently, several bioavailability-based models have been shown to predict acute metal mixture toxicity with reasonable accuracy. However, the application of such models to chronic mixture toxicity is less well established. Therefore, we developed in the present study a chronic metal mixture bioavailability model (MMBM) by combining the existing chronic daphnid bioavailability models for Ni, Zn, and Pb with the independent action (IA) model, assuming strict non-interaction between the metals for binding at the metal-specific biotic ligand sites. To evaluate the predictive capacity of the MMBM, chronic (7d) reproductive toxicity of Ni-Zn-Pb mixtures to Ceriodaphnia dubia was investigated in four different natural waters (pH range: 7-8; Ca range: 1-2 mM; Dissolved Organic Carbon range: 5-12 mg/L). In each water, mixture toxicity was investigated at equitoxic metal concentration ratios as well as at environmental (i.e. realistic) metal concentration ratios. Statistical analysis of mixture effects revealed that observed interactive effects depended on the metal concentration ratio investigated when evaluated relative to the concentration addition (CA) model, but not when evaluated relative to the IA model. This indicates that interactive effects observed in an equitoxic experimental design cannot always be simply extrapolated to environmentally realistic exposure situations. Generally, the IA model predicted Ni-Zn-Pb mixture toxicity more accurately than the CA model. Overall, the MMBM predicted Ni-Zn-Pb mixture toxicity (expressed as % reproductive inhibition relative to a control) in 85% of the treatments with less than 20% error. Moreover, the MMBM predicted chronic toxicity of the ternary Ni-Zn-Pb mixture at least equally accurately as the toxicity of the individual metal treatments (RMSE_Mix = 16; RMSE_{Zn only} = 18; RMSE_{Ni only} = 17; RMSE_{Pb only} = 23). Based on the present study, we believe MMBMs can be a promising tool to account for the effects of water chemistry on metal mixture toxicity during chronic exposure and could be used in metal risk assessment frameworks.

Characterization of the effects of binary metal mixtures on short-term uptake of Ag, Cu, and Ni by rainbow trout (Oncorhynchus mykiss)

Single metal Biotic Ligand Models (BLMs) have been developed for a number of metals and model organisms. While these BLMs improve our ability to regulate metals in the aquatic environment, in reality, organisms are often simultaneously exposed to metal mixtures. Recently, several attempts have been made to develop mixture BLMs (mBLMs). Some of these models assume competitive interactions between all metals, while others assume only metals with a similar mode of action (e.g., Na⁺ or Ca²⁺ antagonists) will competitively interact. To begin testing these assumptions in the mBLM framework, standard 3-h gill metal binding assays with Ag, Cu, and Ni (primary metals), were performed in vivo on freshwater rainbow trout. Fish were exposed across a range of concentrations encompassing the 96-h LC50 for that metal to characterize uptake kinetics for each of these three primary metals (radiolabelled) in the presence and absence of a secondary metal (Ag, Cd, Cu, Ni, Pb, or Zn; not radiolabelled). We observed a complex series of interactions in binary mixtures that frequently contradicted theoretical expectations. Metals with similar modes of action did competitively interact in some instances, but not others, and when they did compete the competition was not necessarily reciprocal (e.g., Cu inhibited Ag uptake but Ag did not inhibit Cu uptake). We also observed examples of interactions between metals with dissimilar modes of action and several examples of metals stimulating the uptake of other metals. The underlying mechanisms for these unexpected interactions are unclear, but suggest that many of the current assumptions in mBLMs regarding the number and types of metal uptake sites and corresponding metal interactions are not correct. Careful characterization of metal mixture interactions is clearly needed before a reliable mBLM can be developed.

A test of the additivity of acute toxicity of binary-metal mixtures of ni with Cd, Cu, and Zn to Daphnia magna, using the inflection point of the concentration-response curves

Mixtures of metals are often present in surface waters, leading to toxicity that is difficult to predict. To provide data for development of multimetal toxicity models, Daphnia magna neonates were exposed to individual metals (Cd, Cu, Ni, Zn) and to binary combinations of those metals in standard 48-h lethality tests conducted in US Environmental Protection Agency moderately hard reconstituted water with 3 mg dissolved organic carbon (DOC)/L added as Suwannee River fulvic acid. Toxicity tests were performed with mixtures of Ni and 1) Cd, which is considerably more toxic than Ni; 2) Cu, which is less toxic than Cd but more toxic than Ni; and 3) Zn, which has a toxicity threshold similar to Ni. For each combination of metals in the binary mixtures, the concentration of 1 metal was held constant while the second metal was varied through a series that ranged from nonlethal to lethal concentrations; then the roles of the metals were reversed. Inflection points of the concentration-response curves were compared to test for additivity of toxicity. Sublethal concentrations of Ni caused less-than-additive toxicity with Cd, slightly less-than-additive toxicity with Zn, and greater-than-additive toxicity with Cu. One explanation of these results might be competition among the metals for binding to biological ligands and/or dissolved organic matter. Therefore, models might have to incorporate sometimes competing chemical interactions to accurately predict metal-mixture toxicity. Environ Toxicol Chem 2016;35:1843-1851. © 2015 SETAC.

Reproductive toxicity of binary and ternary mixture combinations of nickel, zinc, and lead to Ceriodaphnia dubia is best predicted with the independent action model

Metals occur as mixtures in the environment. Risk assessment procedures for metals currently lack a framework to incorporate chronic metal mixture toxicity. In the present study, the toxicity of binary and ternary mixture combinations of Ni, Zn, and Pb was investigated in 3 large-scale experiments using the standard chronic (7-d) Ceriodaphnia dubia reproductive toxicity test. These metals were selected because of anticipated differences in mode of action. The toxicity of the metals in most mixtures, expressed as either free metal ion activities or as dissolved metal concentrations, were antagonistic relative to the concentration addition model, whereas no significant (p < 0.05) interactive effects were observed relative to the independent action model. The only exception was the binary Pb-Zn mixture, for which mixture effects were noninteractive based on the dissolved concentrations, but antagonistic based on free ion activities all relative to the independent action model. Overall, the independent action model fitted the observed toxicity better than the concentration addition model, which is consistent with the different modes of action of these metals. The concentration addition model mostly overestimated toxicity. Finally, the present study warns against extrapolation of the type of interactive effects between species, even when they are closely related. Environ Toxicol Chem 2016;35:1796-1805. © 2015 SETAC.

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.

Incorporating bioavailability into toxicity assessment of Cu-Ni, Cu-Cd, and Ni-Cd mixtures with the extended biotic ligand model and the WHAM-F(tox) approach

There are only a limited number of studies that have developed appropriate models which incorporate bioavailability to estimate mixture toxicity. Here, we explored the applicability of the extended biotic ligand model (BLM) and the WHAM-F(tox) approach for predicting and interpreting mixture toxicity, with the assumption that interactions between metal ions obey the BLM theory. Seedlings of lettuce Lactuca sativa were exposed to metal mixtures (Cu-Ni, Cu-Cd, and Ni-Cd) contained in hydroponic solutions for 4 days. Inhibition to root elongation was the endpoint used to quantify the toxic response. Assuming that metal ions compete with each other for binding at a single biotic ligand, the extended BLM succeeded in predicting toxicity of three mixtures to lettuce, with more than 82% of toxicity variation explained. There were no significant differences in the values of f(mix50) (i.e., the overall amounts of metal ions bound to the biotic ligand inducing 50% effect) for the three mixture combinations, showing the possibility of extrapolating these values to other binary metal combinations. The WHAM-F(tox) approach showed a similar level of precision in estimating mixture toxicity while requiring fewer parameters than the BLM-f(mix) model. External validation of the WHAM-F(tox) approach using literature data showed its applicability for other species and other mixtures. The WHAM-F(tox) model is suitable for delineating mixture effects where the extended BLM also applies. Therefore, in case of lower data availability, we recommend the lower parameterized WHAM-F(tox) as an effective approach to incorporate bioavailability in quantifying mixture toxicity.

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).

Metal mixtures modeling evaluation project: 1. Background

Despite more than 5 decades of aquatic toxicity tests conducted with metal mixtures, there is still a need to understand how metals interact in mixtures and to predict their toxicity more accurately than what is currently done. The present study provides a background for understanding the terminology, regulatory framework, qualitative and quantitative concepts, experimental approaches, and visualization and data-analysis methods for chemical mixtures, with an emphasis on bioavailability and metal-metal interactions in mixtures of waterborne metals. In addition, a Monte Carlo-type randomization statistical approach to test for nonadditive toxicity is presented, and an example with a binary-metal toxicity data set demonstrates the challenge involved in inferring statistically significant nonadditive toxicity. This background sets the stage for the toxicity results, data analyses, and bioavailability models related to metal mixtures that are described in the remaining articles in this special section from the Metal Mixture Modeling Evaluation project and workshop. It is concluded that although qualitative terminology such as additive and nonadditive toxicity can be useful to convey general concepts, failure to expand beyond that limited perspective could impede progress in understanding and predicting metal mixture toxicity. Instead of focusing on whether a given metal mixture causes additive or nonadditive toxicity, effort should be directed to develop models that can accurately predict the toxicity of metal mixtures.

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.

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.