文献类型：期刊文献

英文题名：Cell-Based Metabolomics for Untargeted Screening and Prioritization of Vertebrate-Active Stressors in Streams Across the United States

作者：Collette, Timothy W.[1];Ekman, Drew R.[1];Zhen, Huajun[1,3];Nguyen, Ha[1,4];Bradley, Paul M.[2];Teng, Quincy[1]

机构：[1]US Environm Protect Agcy, Natl Exposure Res Lab, Athens, GA 30605 USA;[2]US Geol Survey, South Atlantic Water Sci Ctr, Columbia, SC 29210 USA;[3]East China Univ Sci & Technol, Sch Resources & Environm Engn, Shanghai 200237, Peoples R China;[4]Natl Inst Nutr Vietnam, Hanoi, Vietnam

年份：2019

卷号：53

期号：15

起止页码：9232

外文期刊名：ENVIRONMENTAL SCIENCE & TECHNOLOGY

收录：;EI(收录号：20193507367497);WOS:【SCI-EXPANDED(收录号:WOS:000480370600078)】；

基金：The authors would like to thank our EPA colleagues: John Washington for valuable information and discussions on the geochemical characteristics of some of the sites in this study; John Davis for indispensable advice and suggestions regarding the PLS regression analysis and data interpretation; and Dan Villeneuve for help facilitating this cross-agency collaboration. We would also like to thank Herbert Buxton, Dana Kolpin, Kathy Kuivila, Tim Reilly, and Kristin Romanok of the USGS for field-study design and sampling logistics. The findings and conclusions in this article (funded through EPA's Chemical Safety for Sustainability national research program) do not necessarily represent the views or policies of the EPA. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

语种：英文

外文关键词：Least squares approximations - Metabolites - Cell culture - Polychlorinated biphenyls - Environmental Protection Agency

摘要：The U.S. Geological Survey and the U.S. Environmental Protection Agency have assessed contaminants in 38 streams across the U.S., using an extensive suite of target-chemical analysis methods along with a variety of biological effects tools. Here, we report zebrafish liver (ZFL) cell-culture based NMR metabolomic analysis of these split stream samples. We used this untargeted approach to evaluate the sites according to overall impact on the ZFL metabolome and found that neither the total number of organics detected at the sites, nor their cumulative concentrations, were good predictors of these impacts. Further, we used partial least squares regression to compare ZFL endogenous metabolite profiles to values for 455 potential stressors (organics, inorganics, and physical properties) measured in these waters and found that the profiles covaried with at most 280 of the stressors, which were subsequently ranked into quartiles based on the strength of their covariance. While contaminants of emerging concern (CECs) were well represented in the top, most strongly covarying quartile-suggesting considerable potential for eliciting biological responses at these sites-there was even higher representation of various well-characterized legacy contaminants (e.g., PCBs). These results emphasize the importance of complementing chemical analysis with untargeted bioassays to help focus regulatory efforts on the most significant ecosystem threats.