Science Inventory

Characterizing Exposures of Fish to Wastewater Treatment Plant Effluent: An Integrated Metabolite and Lipid Profiling Approach

Citation:

Skelton, D., Tim Collette, D. Martinovic-Weigelt, G. Ankley, D. Villeneuve, AND D. Ekman. Characterizing Exposures of Fish to Wastewater Treatment Plant Effluent: An Integrated Metabolite and Lipid Profiling Approach. Presented at SETAC 33rd North American Annual Meeting, Long Beach, CA, November 11 - 15, 2012.

Impact/Purpose:

Presentation for SETAC 33rd North American Annual Meeting. November 11-15, 2012; Long Beach, CA

Description:

Metabolite and lipid profiling are well established techniques for studying chemical-induced alterations to normal biological function in numerous organisms. These techniques have been used successfully to identify biomarkers of chemical exposure, screen for chemical potency, or to infer a chemical’s toxic mode (s)-of-action. While profiling of an organism’s metabolome and lipidome yields complementary data, the combined use of these techniques for biomonitoring has rarely been demonstrated to add value in chemical exposure assessment. Our group has recently investigated the efficacy of integrating metabolite and lipid profiling data for exposure assessment by conducting biomonitoring studies in waterways near wastewater treatment plants (WWTP), using fathead minnows (Pimephales promelas). Caged fish were exposed to effluent from WWTPs as well as water from an upstream and downstream site in the same watershed. A variety of endpoints were measure in the fish, including targeted gene expression, NMR-based metabolite profiles, and GC-MS-based lipid profiles. The results of our investigation demonstrate the utility of combining these complementary techniques for characterizing exposures of fish to chemical contaminants and identifying biomarkers of WWTP effluent exposures.

Record Details:

Record Type:DOCUMENT( PRESENTATION/ SLIDE)
Product Published Date:11/15/2012
Record Last Revised:12/27/2012
OMB Category:Other
Record ID: 248573