Trans-epithelial potential (TEP) response as an indicator of major ion toxicity in rainbow trout and goldfish exposed to 10 different salts in ion-poor water.

ABSTRACT

Freshwater ecosystems are facing increasing contamination by major ions. The Multi-Ion Toxicity (MIT) model, a new tool for risk assessment and regulation, predicts major ion toxicity to aquatic organisms by relating it to a critical disturbance of the trans-epithelial potential (TEP) across the gills, as predicted by electrochemical theory. The model is based on unproven assumptions. We tested some of these by directly measuring the acute TEP responses to a geometric series of 10 different single salts (NaCl, Na2SO4, KCl, K2SO4, CaCl2, CaSO4, MgCl2, MgSO4, NaHCO3, KHCO3) in the euryhaline rainbow trout (Oncorhynchus mykiss) and the stenohaline goldfish (Carassius auratus) acclimated to very soft, ion-poor water (hardness 10 mg CaCO3/L). Results were compared to 24-h and 96-h LC50 data from the literature, mainly from fathead minnow (Pimephales promelas). All salts caused concentration-dependent increases in TEP to less negative/more positive values, in patterns well-described by the Michaelis-Menten equation, or a modified version incorporating substrate inhibition. The ΔTEP above baseline became close to a maximum at the 96-h LC50, except for the HCO3- salts. Furthermore, the range of ΔTEP values at the LC50 within one species was much more consistent (1.6- to 2.1-fold variation) than the molar concentrations of the different salts at the LC50 (19- to 25-fold variation). ΔTEP responses were related to cation rather than anion concentrations. Overall patterns were qualitatively similar between trout and goldfish, with some quantitative differences, and also in general accord with recently published data on three other species in harder water where ΔTEP responses were much smaller. Blood plasma Na+ and K+ concentrations were minimally affected by the exposures. The results are in accord with most but not all of the assumptions of the MIT model and support its further development as a predictive tool.