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Field-deployed Metabolomics for Assessing Surface Waters Impacted by Point and Non-Point Sources of Contamination
Citation:
Collette, Tim. Field-deployed Metabolomics for Assessing Surface Waters Impacted by Point and Non-Point Sources of Contamination. International Environmental Omics Synthesis Conference, Liverpool, UK, September 15 - 18, 2014.
Impact/Purpose:
Presentation for International Environmental Omics Synthesis Conference in Liverpool UK, September 15-18, 2014.
Description:
Metabolomics has become 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 outcomes, 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 readily applicable to virtually any species, and it can be employed as an "open-ended" screening tool (requiring no pre-selection of molecular targets) with relatively low per-sample cost. Recognizing that these are considerable advantages for in situ effects-based monitoring, we have conducted numerous biomonitoring studies with metabolomics, including in the Great Lakes and in various rivers and tributaries in the US. Most of this work involves caged fathead minnows, which are strategically deployed at various sites in relation to point and non-point sources of contamination. For much of this work, the metabolomics data are linked with other 'omic measurements, classical whole-animal outcomes, and extensive site characterization and chemical monitoring data. This allows us to, for example, link the observed metabolite profile changes to land uses, point source characteristics, and, ultimately, to specific chemical stressors. These studies clearly indicate the unique potential for effects-based monitoring with metabolomics.
