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Associating Changes in Endogenous Metabolite Profiles of Field-Deployed Fish with Chemical Contaminants and Other Stressors
Citation:
Collette, Tim. Associating Changes in Endogenous Metabolite Profiles of Field-Deployed Fish with Chemical Contaminants and Other Stressors. SETAC North America 35th Annual Meeting, Vancouver, BC, CANADA, November 09 - 13, 2014.
Impact/Purpose:
Presented at SETAC North America 35th Annual Meeting
Description:
Assessing risk from contaminant exposure in the aquatic environment typically begins (and often ends) with identification of “listed” chemicals in water samples. While providing useful information about potential exposures, this approach to monitoring – in the absence of site-specific effects information – has some well known limitations. For example, just because a chemical is detected, there is no certainty that it will illicit a biological response. For this and other reasons, effects-based monitoring of stressor exposure in being increasingly employed to help address some of these limitations, and to serve as a complement to chemical occurrence data. For example, we have deployed caged fathead minnows at strategic locations relative to wastewater treatment plants (WWTPs) in both flowing streams and large water bodies such as the Great Lakes. Using metabolomics, we have been able to demonstrate changes in endogenous metabolite profiles that comport with land-use and WWTP characteristics at these field study sites. Results of this type have proven to be a valuable complement to chemical occurrence data. Indeed, effects-based monitoring provides information on the integrated biological response to all chemicals occurring in the complex mixture at a given site following exposure. But, while very useful, this still is not a panacea. Undeniable, the most valuable data would provide information on specifically which chemicals in the complex mixture are responsible for the biological response. This illusive information – which is, unfortunately, not available directly from either the chemical or the biological data – would allow for the most impactful and efficient remediation actions. In a step toward providing this information, we have begun to use multivariate data analysis to link anthropogenic chemical occurrence data with changes in metabolite profiles measured with fish caged in impacted field sites. The hypothesis is that the abundances of chemicals that are responsible for eliciting biological responses will co-vary (from site-to-site) with changes in endogenous metabolite profiles. This approach is limited in its ability to assign specific “cause and effect” (e.g., biological responses could still be due to undetected contaminants), but it is well suited for ruling out chemicals that do not contribute to observed effects. In this talk, the underlying concepts behind this approach will be presented, along with some preliminary proof-of-concept results.
