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Transcriptional pathway and de novo network-based approaches to effects-based monitoring in the Great Lakes
Citation:
Vinas, N., Dan Villeneuve, L. Escalon, G. Ankley, AND E. Perkins. Transcriptional pathway and de novo network-based approaches to effects-based monitoring in the Great Lakes. SETAC North America, Salt Lake City, UT, November 01 - 05, 2015.
Impact/Purpose:
not applicable
Description:
Transcriptomics provides unique solutions for understanding the impact of complex mixtures and their components on aquatic systems. Here we describe the application of transcriptomics analysis of in situ fathead minnow exposures for assessing biological impacts of wastewater treatment plants (WWTP) in three different rivers. Analysis of biological effects on fathead minnow deployed near WWTP outfalls in the in the Saint Louis River, near Duluth (MN) found estrogenic effects, at both the transcriptional and hormonal levels, in male fish caged near a discharge site. De novo chemical:gene network analysis suggested that polyaromatic hydrocarbons (PAHs) and bisphenol A (BPA) dominated biological impacts across the sites examined. To determine if effluent effects diminished with distance from the point of discharge, the estrogenicity of the WWTP outfall was further examined with fathead minnow deployed at proximal, distal and far distal sites from the effluent outfall Estrogenic effects at the transcriptional pathway and male plasma estradiol levels decreased with distance further implicating effluent as a source of estrogenicity. Our data suggested that estrogen levels were decreased below normal in the far distal site due to the presence of aromatic hydrocarbons. In a second study, we examined whether de novo chemical:gene association methods developed in the previous study could be useful in identifying the effects of specific chemicals on adult male fathead minnows (Pimephales promelas) exposed to complex mixtures near four WWTPs and two sites upstream of treatment plants on the Maumee (OH) and Detroit (MI) Rivers. The number of genes associated with a chemical by network analysis was related to the known potency of individual chemicals. In addition, this approach identified specific chemicals and classes of chemicals that could be responsible for biological pathway and plasma testosterone impacts in male fish suggesting that chemical:gene associations are a reasonable measure of biological impacts at the transcriptional and higher levels. These results demonstrate that the combination of transcriptomics with hormone analysis of caged fish is a useful tool for understanding impacts of complex mixtures and identification of specific chemical:gene interactions for further monitoring.