Predictive Analysis Using Chemical-Gene Interaction Networks Consistent with Observed Endocrine Activity and Mutagenicity of U.S. Streams
| Autor: | Sarah H. Warren, Dana W. Kolpin, Paul M. Bradley, Jason P. Berninger, David M. DeMarini, Mikayla D Armstrong, Daniel L. Villeneuve, Vickie S. Wilson, Kathryn M. Kuivila, Justin M. Conley, Jane Ellen Simmons, Luke R. Iwanowicz, Timothy J. Reilly, Kristin M. Romanok |
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| Rok vydání: | 2019 |
| Předmět: |
Male
Mutagenicity Tests In vitro toxicology Estrogens General Chemistry 010501 environmental sciences Biology 01 natural sciences Article Glucocorticoid receptor Rivers Biochemistry Gene interaction Estrogenic Effects Chemical contaminants Animals Environmental Chemistry Endocrine system Bioassay Biological Assay Toxicogenomics Water Pollutants Chemical Environmental Monitoring Mutagens 0105 earth and related environmental sciences |
| Zdroj: | Environ Sci Technol |
| ISSN: | 1520-5851 0013-936X |
| DOI: | 10.1021/acs.est.9b02990 |
| Popis: | In a recent U.S. Geological Survey/U.S. Environmental Protection Agency study assessing more than 700 organic compounds in 38 streams, in vitro assays indicated generally low estrogen, androgen, and glucocorticoid receptor activities, with 13 surface waters with 17β-estradiol-equivalent (E2Eq) activities greater than a 1-ng/L estimated effects-based trigger value for estrogenic effects in male fish. Among the 36 samples assayed for mutagenicity in the Salmonella bioassay (reported here), 25% had low mutagenic activity and 75% were not mutagenic. Endocrine and mutagenic activities of the water samples were well correlated with each other and with the total number and cumulative concentrations of detected chemical contaminants. To test the predictive utility of knowledge-base-leveraging approaches, site-specific predicted chemical-gene (pCGA) and predicted analogous pathway-linked (pPLA) association networks identified in the Comparative Toxicogenomics Database were compared with observed endocrine/mutagenic bioactivities. We evaluated pCGA/pPLA patterns among sites by cluster analysis and principal component analysis and grouped the pPLA into broad mode-of-action classes. Measured E2eq and mutagenic activities correlated well with predicted pathways. The pPLA analysis also revealed correlations with signaling, metabolic, and regulatory groups, suggesting that other effects pathways may be associated with chemical contaminants in these waters and indicating the need for broader bioassay coverage to assess potential adverse impacts. |
| Databáze: | OpenAIRE |
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