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Huajun Zhen

Publications and source records attributed to Huajun Zhen.

3 recordsLinked to original sources

Multi-omic responses of fish exposed to complex chemical mixtures in the Shenandoah River watershed

To evaluate relationships between different anthropogenic impacts, contaminant occurrence, and fish health, we conducted in situ fish exposures across the Shenandoah River watershed at five sites with different land use. Exposure water was analyzed for over 500 chemical constituents, and organismal, metabolomic, and transcriptomic endpoints were measured in fathead minnows. Adverse reproductive outcomes were observed in fish exposed in the upper watershed at both wastewater treatment plant (WWTP) effluent- and agriculture-impacted sites, including decreased gonadosomatic index and altered secondary sex characteristics. This was accompanied with increased mortality at the site most impacted by agricultural activities. Molecular biomarkers of estrogen exposure were unchanged and consistent with low or non-detectable concentrations of common estrogens, indicating that alternative mechanisms were involved in organismal adverse outcomes. Hepatic metabolomic and transcriptomic profiles were altered in a site-specific manner, consistent with variation in land use and contaminant profiles. Integrated biomarker response data were useful for evaluating mechanistic linkages between contaminants and adverse outcomes, suggesting that reproductive endocrine disruption, altered lipid processes, and immunosuppression may have been involved in these organismal impacts. This study demonstrated linkages between human-impact, contaminant occurrence, and exposure effects in the Shenandoah River watershed and showed increased risk of adverse outcomes in fathead minnows exposed to complex mixtures at sites impacted by municipal wastewater discharges and agricultural practices.

Virginia, West Virginia

Untargeted lipidomics for determining cellular and sub-cellular responses in Zebrafish (Danio rerio) liver cells following exposure to complex mixtures in U.S. streams

Surface waters often contain a variety of chemical contaminants potentially capable of producing adverse outcomes in both humans and wildlife due to impacts from industrial, urban, and agricultural activity. Here, we report the results of a zebrafish liver (ZFL) cell-based lipidomics approach to assess the potential ecotoxicological effects of complex contaminant mixtures using water collected from eight impacted streams across the United States mainland and Puerto Rico. We initially characterized the ZFL lipidome using high resolution mass spectrometry, resulting in the annotation of 508 lipid species covering 27 classes. We then identified lipid changes induced by all streamwater samples (nonspecific stress indicators) as well as those unique to water samples taken from specific streams. Subcellular impacts were classified based on organelle-specific lipid changes, including increased lipid saturation (endoplasmic reticulum stress), elevated bis(monoacylglycero)phosphate (lysosomal overload), decreased ubiquinone (mitochondrial dysfunction), and elevated ether lipids (peroxisomal stress). Finally, we demonstrate how these results can uniquely inform environmental monitoring and risk assessments of surface waters.

Environmental Science & Technology

Cell-Based metabolomics for untargeted screening and prioritization of vertebrate-active stressors in streams across the United States

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.

Environmental Science & Technology