Frontiers in Environmental Science (Oct 2022)
Expression of biomarkers connected to endocrine disruption in Cottus gobio and Salmo trutta fario in relation to sewage treatment plant-efflux and pesticides
Abstract
The increasing efflux on a large scale of organic contaminants holding endocrine disrupting activity from sewage treatment plants produces detrimental biological effects to various fish species. However, the impact of small-scale sewage treatment plant-efflux in small river streams and narrow creeks is largely unknown. Extensive pesticide output especially in vineyards and orchards also causes adverse effects on the endocrine system of wildlife fish species inhabiting nearby rivers. To elaborate whether fish species and populations in the areas of interest were at risk of experiencing endocrine disruption, we identified different biomarkers related to endocrine disruption in Cottus gobio and Salmo trutta fario and applied this approach to selected Austrian freshwater streams pre and post sewage treatment plants and permanent cultures with extensive pesticide output in South Tyrol. Overall, mRNA expression levels of vitellogenin, estrogen receptor α and zona pellucida genes in wildlife fish, compared to a control population reared under constant conditions in the laboratory were significantly increased. Sewage-treatment plant efflux did not significantly affect the mRNA expression levels while extensive use of pesticides altered mRNA expression significantly in C. gobio. C. gobio and S. trutta fario display different levels of mRNA expression. Cadmium and copper concentrations in liver tissues varied but did not indicate significant levels of contamination. Our results demonstrate the presence of endocrine disrupting chemicals in the tested freshwater streams. We anticipate our study to be a starting point for further studies focusing on the effects of endocrine disrupting chemicals on individuals and populations. Especially the fact that the two selected species reveal highly different levels of mRNA expression levels is of interest when applying biomarker approaches which can be a useful tool for monitoring projects and risk-assessment associated studies.
Keywords
