Biomarkers in tigerfish (Hydrocynus vittatus) as indicators of metal and organic pollution in ecologically sensitive subtropical rivers.

Ecotoxicol Environ Saf

Water Research Group, Unit for Environmental Sciences and Management, North-West University, Private Bag X6001, Potchefstroom 2520, South Africa.

Published: August 2018

Studies have shown high levels of contamination of both metals and organochlorine pesticides (OCPs) in aquatic systems of the world renowned Kruger National Park, South Africa. With effects evident in top predators, including, unexplained Crocodylus niloticus deaths and organ level and histological changes in Hydrocynus vittatus. A suite of biomarkers reflecting exposure and were selected to evaluate biological responses of H. vittatus to anthropogenic stressors as well as to evaluate whether the chosen suite of biomarkers could successfully distinguish between the different pollution profiles present in the selected rivers. During this study a clear relationship was found between exposure to environmental contaminants and the concomitant responses of H. vittatus to these stressors. The ensuing biomarker responses indicated that there is a physiological attempt to deal with, and mitigate the deleterious effects that metals and OCPs may induce. In the Luvuvhu River there is a clear indication in H. vittatus of the stimulation of anti-oxidant protective mechanisms in response to internal OCP exposure. This is reflected by the increasing cytochrome P-450, superoxide dismutase, and more specifically reduced glutathione, which resulted in decreased lipid and protein breakdown (reflected in decreased lipid peroxidation and protein carbonyl levels). Consequently H. vittatus populations of the Luvuvhu River are under greater cumulative stress and this is reflected in the lower energy budgets. Our results further show the integrated application value of the current suite of biomarkers in assessing responses of subtropical fish to metal and OCP exposure as the entire suite of biomarkers when used in conjunction were able to explain 100% of the variation in the data.

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http://dx.doi.org/10.1016/j.ecoenv.2018.03.091DOI Listing

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