High-resolution mass spectrometry is advantageous for monitoring physiological impacts and contaminant biotransformation products in fish exposed to complex wastewater effluent. We evaluated this technique using skin mucus from male and female fathead minnows (Pimephales promelas) exposed to control water or treated wastewater effluent at 5%, 20%, and 100% levels for 21 d, using an onsite, flow-through system providing real-time exposure. Both sex-specific and non-sex-specific responses were observed in the mucus metabolome, the latter suggesting the induction of general compensatory pathways for xenobiotic exposures. Altogether, 85 statistically significant treatment-dependent metabolite changes were observed and 30 of those annotated with probable structures. The mummichog software package was used to elucidate impacted biochemical pathways and enhance metabolite annotation. Partial least squares regression models revealed relationships between the mucus metabolomes and upregulated hepatic mRNA transcripts reported previously for these same fish. These regression models suggest that mucus metabolomic changes reflected, in part, processes by which the fish biotransformed xenobiotics in the effluent. Further, we detected a phase II transformation product of bisphenol A in the skin mucus of male fish. Collectively, these findings demonstrate the utility of mucus as a minimally invasive matrix for simultaneously assessing exposures and effects of real-world mixtures of contaminants. This dataset is associated with the following publication: Mosley, J., D. Ekman, J.E. Cavallin, D. Villeneuve, G. Ankley, and T. Collette. High‐resolution mass spectrometry of skin mucus for monitoring physiological impacts and contaminant biotransformation products in fathead minnows exposed to wastewater effluent. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(3): 788-796, (2018).

High-resolution mass spectrometry is advantageous for monitoring physiological impacts and contaminant biotransformation products in fish exposed to complex wastewater effluent. We evaluated this technique using skin mucus from male and female fathead minnows (Pimephales promelas) exposed to control water or treated wastewater effluent at 5%, 20%, and 100% levels for 21 d, using an onsite, flow-through system providing real-time exposure. Both sex-specific and non-sex-specific responses were observed in the mucus metabolome, the latter suggesting the induction of general compensatory pathways for xenobiotic exposures. Altogether, 85 statistically significant treatment-dependent metabolite changes were observed and 30 of those annotated with probable structures. The mummichog software package was used to elucidate impacted biochemical pathways and enhance metabolite annotation. Partial least squares regression models revealed relationships between the mucus metabolomes and upregulated hepatic mRNA transcripts reported previously for these same fish. These regression models suggest that mucus metabolomic changes reflected, in part, processes by which the fish biotransformed xenobiotics in the effluent. Further, we detected a phase II transformation product of bisphenol A in the skin mucus of male fish. Collectively, these findings demonstrate the utility of mucus as a minimally invasive matrix for simultaneously assessing exposures and effects of real-world mixtures of contaminants. This dataset is associated with the following publication: Mosley, J., D. Ekman, J.E. Cavallin, D. Villeneuve, G. Ankley, and T. Collette. High‐resolution mass spectrometry of skin mucus for monitoring physiological impacts and contaminant biotransformation products in fathead minnows exposed to wastewater effluent. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(3): 788-796, (2018).

Results of partial least squares (PLS) analysis of metabolite changes and contaminant concentrations to determine contaminants most likely to responsible for biological effects and to screen against those contaminants not responsible. This dataset is associated with the following publication: Ekman, D., K. Keteles, J. Beihoffer, J. Cavallin, K. Dahlin, J. Davis, A. Jastrow, J. Lazorchak, M. Mills, M. Murphy, D. Nguyen, A. Vajda, D. Villeneuve, D. Winkelman, and T. Collette. Evaluation of targeted and untargeted effects-based monitoring tools to assess impacts of contaminants of emerging concern on fish in the South Platte River, CO. ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 239: 706-713, (2018).

Results of partial least squares (PLS) analysis of metabolite changes and contaminant concentrations to determine contaminants most likely to responsible for biological effects and to screen against those contaminants not responsible. This dataset is associated with the following publication: Ekman, D., K. Keteles, J. Beihoffer, J. Cavallin, K. Dahlin, J. Davis, A. Jastrow, J. Lazorchak, M. Mills, M. Murphy, D. Nguyen, A. Vajda, D. Villeneuve, D. Winkelman, and T. Collette. Evaluation of targeted and untargeted effects-based monitoring tools to assess impacts of contaminants of emerging concern on fish in the South Platte River, CO. ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 239: 706-713, (2018).

Positive and negative dreissenid mussel DNA quantitiative PCR results from environmental DNA water samples collected in Montana, Wisconsin and Minnesota to assess if environmental DNA can extend the seasonal window for dreissenid mussel early detection.

Positive and negative dreissenid mussel DNA quantitiative PCR results from environmental DNA water samples collected in Montana, Wisconsin and Minnesota to assess if environmental DNA can extend the seasonal window for dreissenid mussel early detection.

Prioritization of environmental contaminants can be aided by detecting glucuronidated biotransformation products in fish using untargeted mass spectrometry-based metabolomics. This dataset is associated with the following publication: Evich, M., J. Mosley, I. Ntai, J. Cavallin, D. Villeneuve, G. Ankley, T. Collette, and D. Ekman. Untargeted MSn-Based Monitoring of Glucuronides in Fish: Screening Complex Mixtures for Contaminants with Biological Relevance.. ACS ES&T Water. American Chemical Society, Washington, DC, USA, 2(12): 2481–2490, (2022).

Prioritization of environmental contaminants can be aided by detecting glucuronidated biotransformation products in fish using untargeted mass spectrometry-based metabolomics. This dataset is associated with the following publication: Evich, M., J. Mosley, I. Ntai, J. Cavallin, D. Villeneuve, G. Ankley, T. Collette, and D. Ekman. Untargeted MSn-Based Monitoring of Glucuronides in Fish: Screening Complex Mixtures for Contaminants with Biological Relevance.. ACS ES&T Water. American Chemical Society, Washington, DC, USA, 2(12): 2481–2490, (2022).

The dataset contains sequencing read counts of fish prey eDNA metabarcoding (using primers targeting the 16S rRNA mitochondrial gene) that were extracted from fecal and cloacal swab samples collected from common loons (Gavia immer) captured on the Whitefish Chain of Lakes, Crow Wing County, Minnesota during 2015-2106. Sample type (cloacal or fecal); loon identification, age, and sex; capture date and location; and prey detections for each sample are provided.