Search

The stenohaline zebra mussel, Dreissena polymorpha, is uniquely sensitive to the ionic composition of its aquatic environment. Waterborne copper (Cu) uptake and accumulation in zebra mussels were examined at various conditions in an environmentally relevant range in freshwater, i.e. Cu exposure levels (nominal concentrations of 25 and 50 μg/L), pH (5.8-8.3), and sodium (Na+) concentrations (up to 4.0 mM). Copper accumulation was simulated by a kinetic model covering two compartments, the gills and the remaining tissues. The Cu uptake rate constant decreased with decreasing pH from 8.3 down to 6.5, indicating interactions between H+ and Cu at uptake sites. The kinetic simulation showed dose-dependent effects of Na+ on Cu uptake. At 25 μg/L Cu, addition of Na+ at 0.5 mM significantly inhibited the Cu uptake rate, while no significant differences were found in the uptake rate upon further addition of Na+ up to a concentration of 4.0 mM. At 50 μg/L Cu, the Cu uptake rate was not influenced by Na+ addition. Calibration results exhibited dose-dependent elimination rates with more profound elimination with increasing exposure levels. With kinetic parameters calibrated at environmentally relevant conditions, in terms of pH and Na+ concentrations, the model performed well in predicting Cu accumulation based on independent data sets. Estimates of the Cu concentration in mussels were within a factor of 2 of the measurements. This demonstrates potential application of kinetic models that are calibrated in environmentally relevant freshwater conditions.

A toxicokinetic-toxicodynamic model was constructed to delineate the exposure-response causality. The model could be used: to predict metal accumulation considering the influence of water chemistry and biotic ligand characteristics; to simulate the dynamics of subcellular partitioning considering metabolism, detoxification, and elimination; and to predict chronic toxicity as represented by biomarker responses from the concentration of metals in the fraction of potentially toxic metal. The model was calibrated with data generated from an experiment in which the Zebra mussel Dreissena polymorpha was exposed to Cu at nominal concentrations of 25 and 50 mu g/L and with varied Na+ concentrations in water up to 4.0 mmol/L for 24 days. Data used in the calibration included physicochemical conditions of the exposure environment, Cu concentrations in subcellular fractions, and oxidative stress-induced responses, i.e. glutathione-S-transferase activity and lipid peroxidation. The model explained the dynamics of subcellular Cu partitioning and the effect mechanism reasonably well. With a low affinity constant for Na+ binding to Cu2+ uptake sites, Na+ had limited influence on Cu2+ uptake at low Na+ concentrations in water. Copper was taken up into the metabolically available pool (MAP) at a largely higher rate than into the cellular debris. Similar Cu concentrations were found in these two fractions at low exposure levels, which could be attributed to sequestration pathways (metabolism, detoxification, and elimination) in the MAP. However, such sequestration was inefficient as shown by similar Cu concentrations in detoxified fractions with increasing exposure level accompanied by the increasing Cu concentration in the MAP.

Physiologically based pharmacokinetic (PBPK) models have been applied to simulate the absorption, distribution, metabolism, and elimination of various toxicants in fish. This approach allows for considering metal accumulation in intestinal parasites. Unlike "semi" physiologically-based models developed for metals, metal accumulation in fish was characterised based on metal-specific parameters (the fraction in blood plasma and the tissue-blood partition coefficient) and physiological characteristics of the fish (the blood flow and the tissue weight) in our PBPK model. In the model, intestinal parasites were considered a sink of metals from the host intestine. The model was calibrated with data for the system of the chub Squalius cephalus and the acanthocephalan Pomphorhynchus tereticolliis. Metal concentrations in this fish-parasite system were monitored in Ag and Co treatments in duplicate during a 48-day exposure phase (Ag and Co were added to tap water at concentrations of 1 and 2 µg/L, respectively) and a 51-day depuration phase. Their concentrations in the gills increased during the exposure phase and decreased in the depuration phase. A similar pattern was observed for Ag concentrations in other chub organs, while a relatively stable pattern for Co indicates regulations in the accumulation of essential metals by chubs. The metals were taken up by the acanthocephalans at similar rate constants. These results indicate that metal availability to parasites, which is determined by the internal distribution and fate, is critical to metal accumulation in the acanthocephalans. The high concentration of Ag in the liver as well as the high rate of Ag excretion from the liver to the intestine might contribute to higher concentrations of metals in the bile complexes in the intestine, which are available to the parasites, but not to the reabsorption by the host intestine. The opposite pattern might explain the lower availability of Co to the acanthocephalans.

10 pages, 2 figures, 1 table, A toxicokinetic-toxicodynamic model based on subcellular metal partitioning is presented for simulating chronic toxicity of copper (Cu) from the estimated concentration in the fraction of potentially toxic metal (PTM). As such, the model allows for considering the significance of different pathways of metal sequestration in predicting metal toxicity. In the metabolically available pool (MAP), excess metals above the metabolic requirements and the detoxification and elimination capacity form the PTM fraction. The reversibly and irreversibly detoxified fractions were distinguished in the biologically detoxified compartment, while responses of organisms were related to Cu accumulation in the PTM fraction. The model was calibrated using the data on Cu concentrations in subcellular fractions and physiological responses measured by the glutathione S-transferase activity and the lipid peroxidation level during 24-day exposure of the Zebra mussel to Cu at concentrations of 25 and 50 µg/L and varying Na+ concentrations up to 4.0 mmol/L. The model was capable of explaining dynamics in the subcellular Cu partitioning, e.g. the trade-off between elimination and detoxification as well as the dependence of net accumulation, elimination, detoxification, and metabolism on the exposure level. Increases in the net accumulation rate in the MAP contributed to increased concentrations of Cu in this fraction. Moreover, these results are indicative of ineffective detoxification at high exposure levels and spill-over effects of detoxification, This research was financed by the Deutsche Forschungsgemeinschaft (DFG), Germany (LE 3716/2-1)

10 pages, 2 figures, 3 tables, Chronic toxicity of copper (Cu) at sublethal levels is associated with ionoregulatory disturbance and oxidative stress. These factors were considered in a toxicokinetic-toxicodynamic model in the present study. The ionoregulatory disturbance was evaluated by the activity of the Na+/K+-ATPase enzyme (NKA), while oxidative stress was presented by lipid peroxidation (LPO) and glutathione-S-transferase (GST) activity. NKA activity was related to the binding of Cu2+ and Na + to NKA. LPO and GST activity were linked with the simulated concentration of unbound Cu. The model was calibrated using previously reported data and empirical data generated when zebra mussels were exposed to Cu. The model clearly demonstrated that Cu might inhibit NKA activity by reducing the number of functional pump sites and the limited Cu-bound NKA turnover rate. An ordinary differential equation was used to describe the relationship between the simulated concentration of unbound Cu and LPO/GST activity. Although this method could not explain the fluctuations in these biomarkers during the experiment, the measurements were within the confidence interval of estimations. Model simulation consistently shows non-significant differences in LPO and GST activity at two exposure levels, similar to the empirical observation, This research was financed by the Deutsche Forschungsgemeinschaft (DFG), Germany (LE 3716/2-1)

No chemical properties have been found to be a reliable predictor of metal toxicity, attributed to the influence of various specific processes on metal toxicokinetics and toxicodynamics.Metal toxicity is affected by interactions between metal ions and of metals with organisms. The present review aims to provide an outlook on recent progress in estimating toxicity of metal mixtures. Three methods applied recently have the potential of accounting for the interactions between metals as well as the interactions of metals with organisms. The methods are based on the Biotic Ligand Model (BLM), electrostatic interactions, and Windermere Humic Aqueous Model (WHAM). These methods can be generalised to a common principle that affinity of metals for binding sites on sorption surfaces (i.e., biotic ligands on organisms, plasma membrane surface, and humic acid-surrogated biological surface) is a unifying factor for the biological response. The scientific basis for these approaches was reviewed in the present s...

13 pages, 3 tables, 4 figures, Mechanistic models based on chemical properties of metals and body size have received substantial attention for their potential application to various metals and to different conditions without required calibration. This advantage has been demonstrated for a number of metals, such as Cd and Ag. However, the capacity of metal-specific chemical properties to explain variations in the accumulation for platinum-group elements (PGEs) has not been investigated yet, although emission of these metals is of increasing concern. Once being released, PGEs exist in the environment in mixtures with other metals. The present study attempted to model the accumulation of Pd and Pt in mixtures with Ag and Cd in the zebra mussel (Dreissena polymorpha) from the aqueous phase; and to investigate the potential application of mechanistic models to Pd and Pt. The present study showed statistically insignificant differences in metal accumulation among size groups in a narrow range of shell length (16–22 mm). Kinetic models could simulate well the accumulation of Cd, Ag, and Pt when metal-specific responses of zebra mussels are taken into consideration. These responses include enhanced immobilisation as a detoxifying mechanism and exchange between soft tissues and shells via the extrapallial fluid. Environmental conditions, e.g. the presence of abiotic ligands such as chloride, might also play an important role in metal accumulation. Significant relationships between the absorption efficiency and the covalent index indicate the potential application of mechanistic models based on this chemical property to Pt, T.T.Y.L was granted with funding from the Deutsche Forschungsgemeinschaft (DFG), Germany (LE 3716/2-1). M.R.G. acknowledgements financial funding to RTI2018-093560-J-I00 (MCIU/AEI/FEDER, UE)

Metal accumulation in roots was modelled with WHAM VII using humic acid (HA) as a surrogate for root surface. Metal accumulation was simulated as a function of computed metal binding to HA, with a correction term (E(HA)) to account for the differences in binding site density between HA and root surface. The approach was able to model metal accumulation in roots to within one order of magnitude for 95% of the data points. Total concentrations of Mn in roots of Vigna unguiculata, total concentrations of Ni, Zn, Cu and Cd in roots of Pisum sativum, as well as internalized concentrations of Cd, Ni, Pb and Zn in roots of Lolium perenne, were significantly correlated to the computed metal binding to HA. The method was less successful at modelling metal accumulation at low concentrations and in soil experiments. Measured concentrations of Cu internalized in L. perenne roots were not related to Cu binding to HA modelled and deviated from the predictions by over one order of magnitude. The results indicate that metal uptake by roots may under certain conditions be influenced by conditional physiological processes that cannot simulated by geochemical equilibrium. Processes occurring in chronic exposure of plants grown in soil to metals at low concentrations complicate the relationship between computed metal binding to HA and measured metal accumulation in roots.

Effects of ion-ion interactions on metal toxicity to lettuce Lactuca sativa were studied based on the electrical potential at the plasma membrane surface (c0). Surface interactions at the proximate outside of the membrane influenced ion activities at the plasma membranesurface({M nþ }0).AtagivenfreeCu 2þ activityinthebulkmedium({Cu 2þ }b),additionsofNa þ ,K þ ,Ca 2þ ,andMg 2þ resulted in substantial decreases in {Cu 2þ }0. Additions of Zn 2þ led to declines in {Cu 2þ }0, but Cu 2þ and Ag þ at the exposure levels tested had negligible effects on the plasma membrane surface activity of each other. Metal toxicity was expressed by the {M nþ }0-based strength coefficient, indicating a decrease of toxicity in the order: Ag þ >Cu 2þ >Zn 2þ . Adsorbed Na þ ,K þ ,C a 2þ , and Mg 2þ had significant and dose-dependent effects on Cu 2þ toxicity in terms of osmolarity. Internal interactions between Cu 2þ and Zn 2þ and between Cu 2þ and Ag þ were modeled by expanding the strength coefficients in concentration addition and response multiplication models. These extended models consistently indicated that Zn 2þ significantly alleviated Cu 2þ toxicity. According to the extended concentration addition model, Ag þ significantly enhanced Cu 2þ toxicity whereas Cu 2þ reduced Ag þ toxicity. By contrast, the response multiplication model predicted insignificant effects of adsorbed Cu 2þ and Ag þ on the toxicity of each other. These interactions were interpreted using c0, demonstrating its influence on metal toxicity. Environ Toxicol Chem 2014;33:1988-1995. # 2014 SETAC

Bioinvasions are a major cause of biodiversity and ecosystem changes. The rapid range expansion of the invasive quagga mussel (Dreissena rostriformis bugensis) causing a dominance shift from zebra mussels (Dreissena polymorpha) to quagga mussels, may alter the risk of secondary poisoning to predators. Mussel samples were collected from various water bodies in the Netherlands, divided into size classes, and analysed for metal concentrations. Concentrations of nickel and copper in quagga mussels were significantly lower than in zebra mussels overall. In lakes, quagga mussels contained significantly higher concentrations of aluminium, iron and lead yet significantly lower concentrations of zinc66, cadmium111, copper, nickel, cobalt and molybdenum than zebra mussels. In the river water type quagga mussel soft tissues contained significantly lower concentrations of zinc66. Our results suggest that a dominance shift from zebra to quagga mussels may reduce metal exposure of predator species.

Soil properties, i.e., pH and contents of soil organic matter (SOM), dissolved organic carbon (DOC), clay, oxides, and reactive metals, are required inputs to both mechanistic and empirical modeling in assessing metal solid-solution partitioning. Several of these properties are rarely measured in site-specific risk assessment. We compared the uncertainties induced by lacking data on these soil properties in estimating metal soil solution concentrations. The predictions by the Orchestra framework were more sensitive to lacking soil property data than the predictions by the transfer functions. The deviations between soil solution concentrations of Cd, Ni, Zn, Ba, and Co estimated with measured SOM and those estimated with generic SOM by the Orchestra framework were about 10 times larger than the deviations in the predictions by the transfer functions. High uncertainties were induced by lacking data in assessing solid-solution partitioning of oxy-anions like As, Mo, Sb, Se, and V. Deviations associated with lacking data in predicting soil solution concentrations of these metals by the Orchestra framework reached three-to-six orders of magnitude. The solid-solution partitioning of metal cations was strongly influenced by pH and contents of organic matter, oxides, and reactive metals. Deviations of more than two orders of magnitude were frequently observed between the estimates of soil solution concentrations with the generic values of these properties and the estimates based on the measured data. Reliable information on these properties is preferred to be included in the assessment by either the Orchestra framework or transfer functions.

Organisms are simultaneously exposed to various stressors, including parasites and pollutants, that may interact with each other. Research on the accumulation of organic compounds in host–parasite systems is scant compared to studies on parasite–metal interactions and mainly focuses on intestinal endoparasites. We reviewed factors that determine the accumulation of persistent organic pollutants (POPs) in host–parasite systems. The wet/dry weight-based concentration of POPs in these parasites is usually lower than that in host tissues because of lower lipid contents in the parasites. However, the fractionation of the pollutants into parasites and their hosts may vary, depending on developmental stages in the life cycle of the parasites. Developmental stages determine the trophic relationship and the taxon of the parasite in the host–parasite systems because of different feeding strategies between the stages. Lipid-corrected concentrations of organic chemicals in the host are usually higher than those in the endoparasites studied. This phenomenon is attributed to a number of physiological and behavioural processes, such as feeding selectivity and strategy and excretion. Moreover, no significant relationship was found between the accumulation factor (i.e. the ratio between the lipid-corrected concentrations in parasites and in their hosts) for polychlorinated biphenyls and either hydrophobicity or molecular size. At the intermediate hydrophobicity, larger and more lipophilic compounds are accumulated at higher levels in both parasites and the host than smaller and less lipophilic compounds. The bioaccumulation of POPs in parasites is affected by some other abiotic, e.g. temperature, and biotic factors, e.g. the number of host species infected by parasites.

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.

Metal toxicity to lettuce Lactuca sativa was determined following mixture exposure based on the concepts of concentration addition (CA) and response addition (RA). On the basis of conventional models assuming no interaction between mixture components, Ag(+) was the most toxic, followed by Cu(2+) and Zn(2+). Furthermore, ion-ion interactions were included in quantitatively estimating toxicity of interactive mixtures of Cu(2+)-Zn(2+) and Cu(2+)-Ag(+) by linearly expanding the CA and RA models. About 80-92% of the variability in the root growth could be explained by this approach. Estimates by the extended models indicate significant alleviative effects of Zn(2+) on Cu(2+) toxicity whereas Cu(2+) did not significantly affect Zn(2+) toxicity. According to the extended CA model, Cu(2+) significantly reduced Ag(+) toxicity while Ag(+) enhanced Cu(2+) toxicity. Similar effects were not found by the extended RA model. These interactions might result from their individual uptake mechanisms and toxic actions as published in literature.

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.

The metal-specific covalent index and the species-specific size-based filtration rate were integrated into a biokinetic model estimating metal bioaccumulation in mussels from the dissolved phase and phytoplankton. The model was validated for zebra (Dreissena polymorpha) and quagga (Dreissena rostriformis bugensis) mussels in the rivers Rhine and Meuse, the Netherlands. The model performed well in predicting tissue concentrations in different-sized zebra mussels from various sampling sites for (55) Mn, (56) Fe, (59) Co, (60) Ni, (82) Se, (111) Cd, (118) Sn, and (208) Pb (r(2) =0.71-0.99). Performance for (52) Cr, (63) Cu, (66) Zn, (68) Zn, and (112) Cd was moderate (r(2)0.20). In quagga mussels, approximately 73 to 94% of the variability in concentrations of (82) Se, (111) Cd, (112) Cd, and (208) Pb was explained by the model (r(2) =0.73-0.94), followed by (52) Cr, (55) Mn, (56) Fe, (60) Ni, and (63) Cu (r(2) =0.48-0.61). Additionally, in both zebra and quagga mussels, average modeled concentrations were within approximately one order of magnitude of the measured values. In particular, in zebra mussels, estimations of (60) Ni and (82) Se concentrations were equal to 51 and 76% of the measurements, respectively. Higher deviations were observed for (52) Cr, (59) Co, (55) Mn, (56) Fe, (111) Cd, (63) Cu, and (112) Cd (underestimation), and (66) Zn, (68) Zn, (208) Pb, and (118) Sn (overestimation). For quagga mussels, modeled concentrations of (66) Zn and (68) Zn differed approximately 14% from the measured levels. Differences between predictions and measurements were higher for other metals.