Delineation of the exposure-response causality chain of chronic copper toxicity to the zebra mussel, Dreissena polymorpha, with a TK-TD model based on concepts of biotic ligand model and subcellular metal partitioning model

Chemosphere. 2022 Jan;286(Pt 3):131930. doi: 10.1016/j.chemosphere.2021.131930. Epub 2021 Aug 18.

Abstract

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 μg/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.

Keywords: Biomarkers; Biotic ligand model; Bivalves; Chronic toxicity; Subcellular partitioning; Toxicokinetic-toxicodynamic model.

MeSH terms

  • Animals
  • Copper / toxicity
  • Dreissena*
  • Ligands
  • Metals
  • Water Pollutants, Chemical* / toxicity

Substances

  • Ligands
  • Metals
  • Water Pollutants, Chemical
  • Copper