Toxicity of trace metals to plants at mixed contamination in soil: experimental analysis, modelling and implementation in risk-assessment

The widespread contamination of soils with trace metals such as zinc (Zn), cadmium (Cd), nickel (Ni) or copper (Cu) can have an adverse ecological effect. The evaluation of the toxic effects of metals in soils has almost exclusively been estimated from toxicity studies with single metal dosing. As a rule, metals occur as mixtures in a contaminated environment, e.g. Cd is usually enriched where higher Zn concentrations are found. The premise in the current assessment is that risks can be excluded provided that all metal concentrations are below their corresponding limits. This assumption is questioned and has been the starting point of this work. A mixture of different metals can have a larger effect than each metal individually, e.g. because the effects of each metal add up or because metals can even interact and act synergistically. There is a need to understand how metals act together in producing combination effects, especially at low effect concentrations and at a large number of metals in the mixture. It is predictable that metals do interact since they compete for sorption, uptake in biota, translocation and detoxification. The general objective of this thesis was to analyze low level metal mixture effects in soil grown plants. The scientific questions were (i) to identify which of two reference mixture models to predict the toxic effect of a mixture applies. These models are the concentration addition (CA) or independent action (IA) models, respectively assuming that there is an equal or an independent mode of action of the different metals; (ii) to identify if deviations from additivity (‘interactions’) can be explained based on soil metal bioavailability. The environmental question was to identify if metal mixture effects occur and if they are relevant. More specifically, a relevant mixture effect occurs when metals dosed in isolation are not affecting plant growth, but become toxic when dosed as a mixture at equal concentrations. First, a study was set up to investigate the toxicity of multiple metal mixtures of Cu, Ni, Cd and Zn to plants at metal doses individually causing low level effects. Barley (Hordeum vulgare L.) root elongation toxicity tests were performed in resin buffered nutrient solutions to control metal speciation. Mixtures of different metals at free ion concentrations each causing <10% inhibition, yielded significant mixture effects when dosed in combination at equal concentrations, with inhibition reaching up to 50%. The IA model predicted mixture toxicity statistically better than the CA model, but some synergisms relative to the independent action model were observed. These synergisms relative to IA were most pronounced in quaternary mixtures and when the dose response curves had steep slopes. Generally, antagonistic interactions relative to the CA model were observed. Increasing solution Zn concentrations shifted metal interactions (CA based) from additive or slightly synergistic at background to antagonistic at higher supply, suggesting a protective effect of Zn. Overall, this study showed that the CA model can be used as a conservative model to predict metal mixture toxicity to barley. Second, interactions at biochemical level in plant roots were investigated. Net toxic effects and interactions of mixtures on plant growth may be better explained by biochemical parameters than by exposure information, and therefore effects of mixtures of Zn, Cd and Cu on barley plants were analyzed using antioxidant and oxidative stress parameters and root K+-efflux. Root elongation in Cu+Cd mixtures was well predicted from solution concentrations, using CA or IA reference models. In contrast, Zn acted antagonistically when combined with Cu and/or Cd, relative to both CA and IA. This protective effect of Zn correlated with the biomarkers, i.e. oxidative stress (indicated by e.g. MDA and H2O2 levels) decreased upon addition of Zn. However, external solution metal concentrations, i.e. the exposure, explained mixture effects better than any of the 16 antioxidant and oxidative stress biomarkers, i.e. the biochemical effects. It was concluded that the biomarkers are no robust indicators for metal mixture toxicity, potentially because different metals have different parallel modes of action on growth that are insufficiently indexed by the biomarkers. Next, interactions at the exposure and uptake level were investigated by incorporating bioavailability in the interpretation of metal interactions. The Biotic Ligand Model (BLM) and the WHAM-Ftox model that assume that toxicity depends on the concentration of metal bound to a biological binding site (the biotic ligand), were used. That concentration bound to the biotic ligand, is in turn calculated from the speciation of the metals in (soil) solution and the concentrations of ions competing with metal binding. First, Cu2+ and Zn2+ mixture toxicity was tested in resin buffered solutions at three different Ca2+ concentrations. Antagonistic interactions between Cu2+ and Zn2+ were found at low Ca2+ concentrations, but became smaller or insignificant at higher Ca2+, illustrating that mutual competition is eliminated at high concentration of a third competing ion (Ca2+). These effects obeyed the BLM combined with the IA reference mixture toxicity model. In a second test in nutrient solution, the complexity was increased by adding the metal chelator NTA (nitrilotriacetic acid) in solution. Metals compete for binding to NTA and this model molecule represents general complexation of metals in the environment. Mixture toxicity of Cu and Zn was investigated at contrasting NTA supply (-NTA and +NTA). In the +NTA solutions, Cu and Zn acted synergistically (IA based) when evaluation of toxicity was based on total metal concentration in solution. This interaction shifted to antagonism when the toxicity evaluation was based on the solution free ion activities of the metal, thus by accounting for competition effects on the NTA ligand and, hence, by accounting for bioavailability. In a final test, mixture toxicity and interactions of Cu and Zn were investigated in three different soil samples. The toxic effects of Cu and Zn mixtures on barley root elongation were synergistic in soils with high and medium cation exchange capacity (CEC), but antagonistic in a low CEC soil. This was found when expressing the dose as the conventional total soil concentration. In contrast, antagonism was found in all soils when expressing the dose as free ion activities in soil solution, indicating, again, that there is metal ion competition for binding to the plant roots. Neither a CA, nor an IA model fully explained mixture effects, irrespective of the dose expressions. In contrast, a multi-metal BLM model and a WHAM-Ftox model successfully explained the mixture effects from pore water composition across all soils and showed that bioavailability factors mainly explain the interactions in soils. Concluding, metal mixture effects can be predicted from the effects of each metal separately and the CA reference model is more conservative (protective) than the IA model, however the latter was statistically more accurate. This suggests that different metals, in general, act independently for toxicity. Metals can act synergistically in solution-plant or soil-plant systems when considering the total metal concentration, however, that almost always reverted to antagonism when considering the bioavailability, i.e. metal speciation in the exposure medium and competition for uptake. Biomarkers were no robust indicators for physiological effects and offer little opportunities to address mixture effects in the environment. A multi-metal BLM model and a WHAM-Ftox model successfully explained mixture effects in different soil samples. From risk-assessment point of view, this work showed that mixture effects are relevant and that, for metals, something can happen from nothing, especially when individual dose-response curves have steep slopes. Validated chronic mixture toxicity models accounting for bioavailability can be included in tiered risk assessment approaches.status: publishe

Additive toxicity of zinc and arsenate on barley (Hordeum vulgare) root elongation

Zinc (Zn) and arsenic (As) are typically present as mixed contaminants in mining-impacted areas; however, their joined effects have rarely been evaluated. The present study was set up to test whether the Zn2+ and H2 AsO4- (hereafter, As) mixture toxicity to plants is additive or whether interactions occur. Barley (Hordeum vulgare) root elongation was measured in resin buffered nutrient solutions. The design included ranges of single-element concentrations and combinations at 3 different Ca2+ concentrations (0.5 mM, 2.2 mM, and 15.0 mM) to vary the relative toxicity of Zn2+ . Increasing Ca concentrations decreased Zn toxicity, whereas As toxicity was unaffected by Ca. Root elongation was generally more affected in Zn-As mixtures than in corresponding single-element treatments. This is merely a joint additive effect, as 96% of the root elongation data were within a factor of 1.2 from predictions using the independent action (IA) or concentration addition (CA) model. The CA and IA predictions were similar, and data did not allow identification of equal or dissimilar modes of action. Small but significant Zn-As antagonisms were only found at high effects (>50% inhibition). The present study suggests that mixture effects of Zn and As are environmentally relevant and that current risk assessment underestimates toxicity in multielement-contaminated environments. The CA model can be used as a conservative model for risk assessment; however, for soil-grown plants, soil-exposed studies are needed. Environ Toxicol Chem 2017;36:1556-1562. © 2016 SETAC.status: publishe

Mixture toxicity of copper and zinc to barley at low level effects can be described by the Biotic Ligand Model

Background and aims: The biotic ligand model (BLM) is a bioavailability model for metals based on the concept that toxicity depends on the concentration of metal bound to a biological binding site; the biotic ligand. Here, we evaluated the BLM to interpret and explain mixture toxicity of metals (Cu and Zn). Methods: The mixture toxicity of Cu and Zn to barley (Hordeum vulgare L.) was tested with a 4 days root elongation test in resin buffered nutrient solutions. Toxicity of one toxicant was tested in presence or absence of a low effect level of the other toxicant or in a ray design with constant toxicant ratios. All treatments ran at three different Ca concentrations (0.3, 2.2 and 10mM) to reveal ion interaction effects. Results: The 50 % effect level (EC50) of one metal, expressed as the free ion in solution, significantly (p<0.05) increased by adding a low level effect of the other metal at low Ca. Such antagonistic interactions were smaller or became insignificant at higher Ca levels. The Cu EC10 was unaffected by Zn whereas the Zn EC10 increased by Cu at low Ca. These effects obeyed the BLM combined with the independent actionmodel for toxicants. Conclusions: The BLM model explains the observed interactions by accounting for competition between both metals free ions and Ca2+ at the Cu and Zn biotic ligands. The implications of these findings for Cu/Zn interactions in soil are discussed

Systematic evaluation of chronic metal-mixture toxicity to three species and implications for risk assessment

Metal contamination generally occurs as mixtures. However, it is yet unresolved how to address metal mixtures in risk assessment. Therefore, using consistent methodologies, we have set up experiments to identify which mixture model applies best at low level effects, i.e. the independent action (IA) or concentration addition (CA) reference model. Toxicity of metal mixtures (Ni, Zn, Cu, Cd, and Pb) to Daphnia magna, Ceriodaphnia dubia, and Hordeum vulgare was investigated in different waters or soils, totaling 30 different experiments. Some mixtures of different metals, each individually causing <10% inhibition, yielded much larger inhibition (up to 66%) when dosed in combination. In general, IA was most accurate in predicting mixture toxicity, while CA was most conservative. At low effect levels important in risk assessments, CA overestimated mixture toxicity to daphnids and H. vulgare on average with a factor 1.4 to 3.6. Observed mixture interactions could be related to bioavailability, or by competition interactions either for binding sites of dissolved organic carbon or for biotic ligand sites. Our study suggests that the current metal-by-metal approach in risk evaluations may not be conservative enough for 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-<i>F</i>_tox model successfully explained the mixture effects across all soils and showed that bioavailability factors mainly explain the interactions in soils. The WHAM-<i>F</i>_tox model is a promising tool for the risk assessment of mixed-metal contamination in soils

Incorporating bioavailability into toxicity assessment of Cu-Ni, Cu-Cd, and Ni-Cd mixtures with the extended biotic ligand model and the WHAM-Ftox 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 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\ua0days. 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\ua0% of toxicity variation explained. There were no significant differences in the values of f (i.e., the overall amounts of metal ions bound to the biotic ligand inducing 50\ua0% effect) for the three mixture combinations, showing the possibility of extrapolating these values to other binary metal combinations. The WHAM-F approach showed a similar level of precision in estimating mixture toxicity while requiring fewer parameters than the BLM-f model. External validation of the WHAM-F approach using literature data showed its applicability for other species and other mixtures. The WHAM-F 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 as an effective approach to incorporate bioavailability in quantifying mixture toxicity