Dataset for: Metabolomic Investigations of the Temporal Effects of Exposure to Pharmaceuticals and Personal Care Products and their Mixture in the Eastern Oyster (Crassostrea virginica)
datasetposted on 12.12.2019 by David William Brew, Marsha C. Black, Marina Santos, Jake Rodgers, William Matthew Henderson
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
The eastern oyster (Crassostrea virginica) supports a large aquaculture industry and is a keystone species along the Atlantic seaboard. Native oysters are routinely exposed to a complex mixture of contaminants that increasingly includes pharmaceuticals and personal care products (PPCPs). Unfortunately, the biological effects of chemical mixtures on oysters are poorly understood. Untargeted GC-MS metabolomics was utilized to quantify the response of oysters exposed to fluoxetine, N,N-diethyl-meta-toluamide (DEET), 17α-ethynylestradiol (EE2), diphenhydramine and their mixture. Oysters were exposed to 1 µg/L of each chemical or mixture for ten days, followed by an eight-day depuration period. Adductor muscle (n = 14/treatment) was sampled at days 0, 1, 5, 10 and 18. Trajectory analysis illustrated that metabolic effects and class separation of the treatments varied at each time point, and that overall, the oysters were only able to partially recover from these exposures post-depuration. Altered metabolites were associated with cellular energetics (i.e. Krebs cycle intermediates), as well as amino acid metabolism and the urea cycle. Exposure to these PPCPs also affected metabolic pathways associated with anaerobic metabolism, osmotic stress and oxidative stress, in addition to the physiological effects from each chemical’s postulated mechanism of action. Following depuration, there were fewer metabolites altered, but none of the treatments returned to their initial control values, indicating that metabolic disruptions were long-lasting. Interestingly, the mixture did not directly cluster with individual treatments in the scores plot from partial least squares discriminant analysis and many of its affected metabolic pathways were not well-predicted from the individual treatments. This research highlights the utility of untargeted metabolomics in developing exposure biomarkers for compounds with differing modes of action in bivalves.