Toxicity versus accumulation for barley plants exposed to copper in the presence of metal buffers: Progress towards development of a terrestrial biotic ligand model
- 1 November 2007
- journal article
- Published by Wiley in Environmental Toxicology and Chemistry
- Vol. 26 (11), 2282-2289
- https://doi.org/10.1897/06-641r.1
Abstract
Development of a terrestrial biotic ligand model (TBLM) for higher plants requires a root-Cu accumulation value that corresponds to the 50% inhibitory concentration (IC50). However, it is not yet known which of the two previously reported Cu-binding ligands on the root is associated with Cu toxicity. The aim of the present study was therefore to investigate the relationship between Cu binding to each ligand group and toxicity, so that the key toxicological site could be identified. To obtain accumulation and toxicity data that were not biased by limited Cu supply to the root, 2-d-old barley seedlings were exposed for 48 h to a range of free Cu ion activities (i.e., {Cu(2+)}) in simple exposure media buffered by nitrilotriacetic acid (NTA) or ethylenediaminetetraacetic acid (EDTA). Comparison of the amount of predicted root-bound Cu (calculated with the aqueous geochemical program PHREEQC) with root elongation data showed that toxicity likely resulted from Cu binding to low-affinity ligands, as the high-affinity ligands were approximately 99% saturated when a reduction in root elongation was first observed. For plants exposed to both NTA- and the EDTA-buffered {Cu(2+)} solutions, the root-Cu accumulation value corresponding to the IC50 was approximately 80 microg/g root dry weight, which is similar to the value obtained from previous work with wheat. The linear relationship between the amount of Cu bound to the low-affinity ligands and the percent root growth inhibition suggests that this relationship will be a robust predictor of Cu toxicity when incorporated into the TBLM, and applied to varied exposure scenarios. For the simple solutions used here, the TBLM-predicted and measured IC50 values were statistically indistinguishable.Keywords
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