Martina G. Vijver

Response predictions for organisms water-exposed to metal mixtures: a meta-analysis.

To develop a multimetal toxicity model requires insight into the relationships between the composition of metal mixtures and their toxicological effects on organisms. As a first step in developing such a model, quantitative data from binary and higher mixture studies of Cu, Cd, and Zn were compiled and used to assess trends in toxicological effects on various organisms. The findings of this meta-analysis show relatively little occurrence of additive effects compared with antagonistic and synergistic effects. This observation held true irrespective of test species, environmental compartment, or metal concentrations in the mixture. However, the type of effect was significantly correlated with the metal combination tested and the selected toxicological endpoint. It was also found that different methods were used for assessing deviation from additivity in the various individual studies. For robust comparison, standardization on this point is required. Toxicological responses of organisms to metal mixtures were shown to be hard to predict and were often slightly less than or slightly more than additive. The interactions observed could not be explained by metal-metal interactions alone. We therefore conclude that with current scientific knowledge it is not yet possible to predict responses to metal mixtures in individual cases; at best this is possible only in terms of general patterns. Nevertheless, in the context of environmental risk policy, the assumption of additivity produces a conservative prediction of toxicity, because toxicity of a metal mixture will be either predicted correctly or overpredicted by default in approximately 75% of all cases. The use of models based on noninteraction is satisfactory from this regulatory perspective.

Biological significance of metals partitioned to subcellular fractions within earthworms (Aporrectodea caliginosa)

Metal ions in excess of metabolic requirements are potentially toxic and must be removed from the vicinity of important biological molecules to protect organisms from adverse effects. Correspondingly, metals are sequestrated in various forms, defining the accumulation pattern and the magnitude of steady-state levels reached. To investigate the subcellular fractions over which Ca, Mg, Fe, Cu, Zn, Cd, Pb, Ni, and As are distributed, earthworms (Aporrectodea caliginosa) collected from the field were analyzed by isolating metal-rich granules and tissue fragments from intracellular microsomal and cytosolic fractions (i.e., heat-stable proteins and heat-denatured proteins). The fractions showed metal-specific binding capacity. Cadmium was mainly retrieved from the protein fractions. Copper was equally distributed over the protein fraction and the fraction comprising tissue fragments, cell membranes, and intact cells. Zinc, Ca, Mg, and As were mainly found in this fraction as well. Lead, Fe, and Ni were mainly isolated from the granular fraction. To study accumulation kinetics in the different fractions, three experiments were conducted in which earthworms were exposed to metal-spiked soil and a soil contaminated by anthropogenic inputs and, indigenous earthworms were exposed to field soils. Although kinetics showed variation, linear uptake and steady-state types of accumulation patterns could be understood according to subcellular compartmentalization. For risk assessment purposes, subcellular distribution of metals might allow for a more precise estimate of effects than total body burden. Identification of subcellular partitioning appears useful in determining the biological significance of steady-state levels reached in animals.

Toxicity and Accumulation of Cu and ZnO Nanoparticles in Daphnia magna

There is increasing recognition that the wide use of nanoparticles, such as Cu (CuNPs) and ZnO nanoparticles (ZnONPs), may pose risks to the environment. Currently there is insufficient insight in the contribution of metal-based nanoparticles and their dissolved ions to the overall toxicity and accumulation. To fill in this gap, we combined the fate assessment of CuNPs and ZnONPs in aquatic test media with the assessment of toxicity and accumulation of ions and particles present in the suspensions. It was found that at the LC50 level of Daphnia magna exposed to the nanoparticle suspensions, the relative contributions of ions released from CuNPs and ZnONPs to toxicity were around 26% and 31%, respectively, indicating that particles rather than the dissolved ions were the major source of toxicity. It was additionally found that at the low exposure concentrations of CuNPs and ZnONPs (below 0.05 and 0.5 mg/L, respectively) the dissolved ions were predominantly accumulated, whereas at the high exposure concentrations (above 0.1 mg/L and 1 mg/L, respectively), particles rather than the released ions played a dominant role in the accumulation process. Our results thus suggest that consideration on the contribution of dissolved ions to nanoparticle toxicity needs to be interpreted with care.

Species-specific toxicity of copper nanoparticles among mammalian and piscine cell lines.

Abstract The four copper nanoparticles (CuNPs) with the size of 25, 50, 78 and 100 nm and one type of micron-sized particles (MPs) (∼500 nm) were exposed to two mammalian (H4IIE and HepG2) and two piscine (PLHC-1 and RTH-149) cell lines to test the species-specific toxicities of CuNPs. The results showed that the morphologies, ion release and size of the particles all played an important role when investigating the toxicity. Furthermore, the authors found that the particle forms of CuNPs in suspensions highly contribute to the toxicity in all exposed cell lines whereas copper ions (Cu2+) only caused significant responses in mammalian cell lines, indicating the species-specific toxicity of CuNPs. This study revealed that the morphologies, ion release rate of NPs as well as the species-specific vulnerabilities of cells should all be considered when explaining and extrapolating toxicity test results among particles and among species.

Uptake kinetics of metals by the earthworm Eisenia fetida exposed to field-contaminated soils.

It is well known that earthworms can accumulate metals. However, most accumulation studies focus on Cd-, Cu-, Pb- or Zn-amended soils, additionally few studies consider accumulation kinetics. Here we model the accumulation kinetics of 18 elements by Eisenia fetida, exposed to 8 metal-contaminated and 2 uncontaminated soils. Tissue metal concentration was determined after 3, 7, 14, 21, 28 and 42 days. Metal elimination rate was important in determining time to reach steady-state tissue metal concentration. Uptake flux to elimination rate ratios showed less variation and lower values for essential than for non-essential metals. In theory kinetic rate constants are dependent only on species and metal. Therefore it should be possible to predict steady-state tissue metal concentrations on the basis of very few measurements using the rate constants. However, our experiments show that it is difficult to extrapolate the accumulation kinetic constants derived using one soil to another.

Metal uptake from soils and soil-sediment mixtures by larvae of Tenebrio molitor (L.) (Coleoptera).

Bioassays were performed to evaluate the impact of soil characteristics on Cd, Cu, Pb, and Zn uptake by larvae of Tenebrio molitor. Metal accumulation was determined in 13 natural field soils, one metal-spiked field soil, four soil-sediment mixtures, and Cd- or Zn-spiked OECD artificial soil. Statistical analyses were used to investigate covariation of accumulation patterns with various soil metal pools and soil properties. Body concentrations of Cu and Zn in Zn-spiked OECD soils, field soils, and soil-sediment mixtures mostly remained constant. Considerable variation was noted for all Cd and Pb steady-state body concentrations among field soils and soil-sediment mixtures. For the spiked field soil and in the Cd-spiked OECD soil, body concentrations increased almost linearly with time. For the nonessential metals Cd and Pb, larval body concentrations correlated mainly to the total metal pool of the soil. Cd uptake at similar total Cd concentrations was within the same range among spiked OECD soils, field soils, and mixtures. A comparison of the findings with studies on other soil-inhabiting species shows that metal uptake patterns depend on metal type, soil type, and exposed species. It is suggested that soil organisms can be categorized according to gross divergence in ecophysiological characteristics, determined by, for instance, (non)permeability of the outer integument. These characteristics appear as similarities among multivariate functions as derived for the beetle.

Modeling toxicity of binary metal mixtures (Cu2+–Ag+, Cu2+–Zn2+) to lettuce, Lactuca sativa, with the biotic ligand model

The biotic ligand model (BLM) was applied to predict metal toxicity to lettuce, Lactuca sativa. Cu(2+) had the lowest median effective activity (EA50(M) ), compared with Ag(+) and Zn(2+) (EA50(Cu)  = 2.60 × 10(-8) M, EA50(Ag) = 1.34 × 10(-7)  M, EA50(Zn) = 1.06 × 10(-4)  M). At the 50% response level, the fraction of the total number of biotic ligands occupied by ions (f50(M) ) was lowest for Ag(+) among the metals (f50(Ag) = 0.22, f50(Cu) = 0.36, f50(Zn) = 0.42). Cu(2+) had the highest affinity for biotic ligands compared with Ag(+) and Zn(2+) , as shown by stability constants of the cation-biotic ligand binding, expressed as log K(MBL) (log K(CuBL) = 7.40, log K(AgBL) = 6.39, log K(ZnBL) = 4.00). Furthermore, the BLM was combined with the toxic equivalency factor approach in predicting toxicity of mixtures of Cu(2+) -Zn(2+) and Cu(2+) -Ag(+) . The fraction of biotic ligands occupied by ions was used to determine the relative toxic potency of metals and the toxic equivalency quotient (TEQ) of mixtures. This approach allowed for including interactions in estimating mixture toxicity and showed good predictive power (r(2) = 0.64-0.84). The TEQ at the 50% response level (TEQ50, Cu(2+) equivalents) for Cu(2+) -Zn(2+) mixtures was significantly lower than the value for Cu(2+) -Ag(+) mixtures. Joint toxicity depended on both TEQ and specific composition of the mixture. The present study supports the use of the accumulation of metal ions at the biotic ligands as a predictor of toxicity of single metals and mixtures.

Toxicological Mixture Models are Based on Inadequate Assumptions

The interactions of thousands of chemicals in the environment with millions of biological species ultimately determine whether a given mixture of chemicals has marginal or catastrophic consequences. The foundations for toxicological effect models of mixtures were laid by pharmacologists in the 1920s (1, 2). At the time, the problem of joint action was solved mathematically by simply adding doses and responses, on the assumption that compounds do not influence each other’s physiological action. In environmental risk assessment and human toxicology, our understanding of the toxicity of mixtures is still based on these concepts, with addition forming the basis for all models, regardless of the sophistication of the mixture models employed or the number of additional interactions (e.g., with respect to exposure) defined (3). We believe the time is ripe for a new approach, for there is evidence that additivity is not in all cases as universal as has been postulated for more than 80 years. To determine whether classical mixture models are valid, we performed a metastudy on metal mixture responses compiled from the literature. Our metastudy was performed by assembling data of peer-reviewed articles published from 1981 to 2007 available via the ISI Web of Science database. The aim was not full coverage of all papers concerning mixtures, but to obtain a representative overview of papers on metal mixtures. The articles were a selection of binary or tertiary mixture toxicity studies on the effects of Cd, Cu, and/ or Zn. In total, 19 studies were included, giving 91 records on metal combinations: 67 binary mixture combinations and 24 tertiary mixture combinations. To properly deal with multiple modes of exposure, possibly leading to different interactions, we made a distinction between metal toxicity via oral uptake and via passive uptake from the environment. For this study, only organisms for which the latter constituted the primary route were considered. Studies on freshwater (41 records) and marine organisms (31 records) as well as on soil-dwelling organisms (19 records) were included, with the proviso for terrestrial studies that only soil-dwelling organisms exposed to pore water were considered. Fate of metals in the solutions was not explicitly accounted for because of lack of information on the physicochemical water properties determining metal speciation. More details on the records used in our study are available upon request. With regard to the toxic effects of mixtures, two reference models are available for the analysis of noninteractive joint action (1, 2). Joint action is classified as similar when the primary site of action is the same for both or all the compounds (eq 1), and dissimilar when the site of action differs (eq 2).

How subcellular partitioning can help to understand heavy metal accumulation and elimination kinetics in snails

To understand bioaccumulation kinetics of metals within biota inhabiting industrially contaminated soils, toxicokinetic dynamics and subcellular fractionation were carried out with the terrestrial snail Helix aspersa in a long-term (six-month) laboratory experiment. Accumulation and elimination kinetics were determined for Cd, Pb, and Zn in both viscera and foot of snails and were described accurately by one-compartment models. The subcellular fractions were obtained by sequential centrifugations and were analyzed by isolating metal-rich granules, tissue fragments, and cytosolic fractions. Different fractions showed metal-specific binding capacities that might be useful in identifying the biological significance of accumulated metal levels in snails. Cadmium was retrieved mainly from the cytosolic fraction, where it was stored in the long term and not excreted, thus explaining the linear accumulation patterns. Most of the accumulated Pb was found in the granular fraction, and snails appeared able to excrete these concretions, leading to achievement of a steady state in internal Pb body burdens. Significant levels of Pb, however, were retrieved at the end of the depuration phase and retained in the cell debris fraction. Zinc showed affinities for both cytosolic and granular fractions, leading to intermediate uptake and excretion patterns. The dynamics of the different sequestration forms at the subcellular level support the observed kinetics of metal body burdens and, in association with the determination of uptake fluxes, allow precise assessment of metal accumulation in snails.

Predicting effects of cations on copper toxicity to lettuce (lactuca sativa) by the biotic ligand model

A biotic ligand model (BLM) was developed to estimate Cu toxicity to lettuce (Lactuca sativa) in terms of root elongation after 4 d of exposure. Effects of Na(+), K(+), Ca(2+), and Mg(2+) on Cu toxicity were examined. The addition of these cations resulted in a 50-fold difference in the copper median effective activity (EC50 cu2+). However, these variations could not be interpreted entirely as a function of the concentrations of these cations alone. In particular, only the relationship between EC50 cu2+ and the activity of protons was found to be significant in the whole range of pH examined from 5.0 to 7.0. The addition of K(+), Na(+), Ca(2+), and Mg(2+) at concentrations up to 20 mM resulted in a 16-fold difference in EC50 cu2+ values. This difference was significant, as indicated by non-overlapping standard deviations of the negative logarithm of EC50 cu2+ pEC50 cu2+) obtained with (7.37 ± 0.22) and without (6.76 ± 0.22) additions of K(+), Na(+), Ca(2+), and Mg(2+). The variations were not statistically significantly related to concentrations of these cations; therefore, only protons can be integrated in the BLM predicting Cu toxicity to lettuce L. sativa with the important parameters: log K(HBL) =6.27, log K(CuBL) =7.40, and [formula in text]. The lack of significant relationships between EC50 cu2+ and concentrations of the cations was not in line with the main assumption of the BLM about the competition between cations for binding sites.