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Field-based Metabolomics for Assessing Contaminated Surface Waters
Citation:
Ekman, D., J. Beihoffer, G. Ankley, J. Cavallin, J. Davis, K. Jensen, M. Kahl, K. Keteles, D. Skelton, Q. Teng, Dan Villeneuve, AND Tim Collette. Field-based Metabolomics for Assessing Contaminated Surface Waters. Aquatic Toxicity Workshop, Ottawa, ON, CANADA, September 29 - October 01, 2014.
Impact/Purpose:
Presented at the Aquatic Toxicity Workshop in Ottawa, Ontario, CA (Sept 29- Oct 1, 2014)
Description:
Metabolomics is becoming well-established for studying chemical contaminant-induced alterations to normal biological function. For example, the literature contains a wealth of laboratory-based studies involving analysis of samples from organisms exposed to individual chemical toxicants. These lab studies have demonstrated the ability to rapidly screen and prioritize individual chemicals for adverse effects, and also to inform with regard to toxic modes-of-action. However, metabolomics has rarely been used for characterizing the impacts of exposure to complex "real-world" chemical mixtures, or for biomonitoring in the natural environment. This is unfortunate, because metabolomics is well suited for these applications as well. For example, metabolomics is applicable to virtually any species because a sequenced genome is not required. Also, it can be applied with relatively low per-sample cost, is "open-ended" (requiring no pre-selection of targets), and highly reproducible with modern NMR and MS instruments. Furthermore, biological matrices that can be sampled in a minimally-invasive manner are suitable for use in metabolomics studies, opening up the possibility for sampling larger numbers of individuals in wild populations or for repeated sampling of individuals. Recognizing that these are considerable advantages for in situ effects-based monitoring, we have been conducting numerous biomonitoring studies with metabolomics in, and around, various sites in the U.S. Most of this work involves caged fathead minnows (Pimephales promelas), which are strategically deployed at various sites in relation to point and nonpoint sources of contamination (e.g., WWTPs, agricultural operations, etc.) Where reasonable, the metabolomic data are linked with other 'omic measurements, classical whole-animal outcomes, and site characterization and chemical monitoring data. These studies - which will be discussed here - clearly indicate the unique potential for effectsbased monitoring with metabolomics.
