As the world burden of environmental contamination increases, it is of the utmost importance to develop streamlined approaches to environmental risk assessment in order to prioritize mitigation measures. Whole-cell biosensors or bioreporters and speciation modeling have both become of increasing interest to determine the bioavailability of pollutants, as bioavailability is increasingly in use as an indicator of risk. Herein, we examine whether bioreporter results are able to reflect expectations based on chemical reactivity and speciation modeling, with the hope to extend the research into a wider framework of risk assessment. We study a specific test case concerning the bioavailability of lead (Pb) in aqueous environments containing Pb-complexing ligands. Ligands studied include ethylene diamine tetra-acetic acid (EDTA), meso-2,3 dimercaptosuccinic acid (DMSA), leucine, methionine, cysteine, glutathione, and humic acid (HA), and we also performed experiments using natural water samples from Lake Tai (Taihu), the third largest lake in China. We find that EDTA, DMSA, cysteine, glutathione, and HA amendment significantly reduced Pb bioavailability with increasing ligand concentration according to a log-sigmoid trend. Increasing dissolved organic carbon in Taihu water also had the same effect, whereas leucine and methionine had no notable effect on bioavailability at the concentrations tested. We find that bioreporter results are in accord with the reduction of aqueous Pb2+ that we expect from the relative complexation affinities of the different ligands tested. For EDTA and HA, for which reasonably accurate ionization and complexation constants are known, speciation modeling is in agreement with bioreporter response to within the level of uncertainty recognised as reasonable by the United States Environmental Protection Agency for speciation-based risk assessment applications. These findings represent a first step toward using bioreporter technology to streamline the biological confirmation or validation of speciation modeling for use in environmental risk assessment.
Environmental Pollution – Elsevier
Published: Oct 1, 2017
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