Effect-Directed Analysis Based on the Reduced Human Transcriptome (RHT) to Identify Organic Contaminants in Source and Tap Waters along the Yangtze River

Jing Guo; Yanhong Shen; Xiaowei Zhang; Die Lin; Pu Xia; Maoyong Song; Lu Yan; Wenjun Zhong; Xiao Gou; Chang Wang; Si Wei; Hongxia Yu; Wei Shi

doi:10.1021/acs.est.1c08676

Effect-Directed Analysis Based on the Reduced Human Transcriptome (RHT) to Identify Organic Contaminants in Source and Tap Waters along the Yangtze River

Jing Guo, Yanhong Shen, Xiaowei Zhang, Die Lin, Pu Xia, Maoyong Song, Lu Yan, Wenjun Zhong, Xiao Gou, Chang Wang, Si Wei, Hongxia Yu, Wei Shi^*

^*Corresponding author for this work

Biosciences

Research output: Contribution to journal › Article › peer-review

Abstract

Since a large number of contaminants are detected in source waters (SWs) and tap waters (TWs), it is important to perform a comprehensive effect evaluation and key contributor identification. A reduced human transcriptome (RHT)-based effect-directed analysis, which consisted of a concentration-dependent RHT to reveal the comprehensive effects and noteworthy pathways and systematic identification of key contributors based on the interactions between compounds and pathway effects, was developed and applied to typical SWs and TWs along the Yangtze River. By RHT, 42% more differentially expressed genes and 33% more pathways were identified in the middle and lower reaches, indicating heavier pollution. Hormone and immune pathways were prioritized based on the detection frequency, sensitivity, and removal efficiency, among which the estrogen receptor pathway was the most noteworthy. Consistent with RHT, estrogenic effects were widespread along the Yangtze River based on in vitro evaluations. Furthermore, 38 of 100 targets, 39 pathway-related suspects, and 16 estrogenic nontargets were systematically identified. Among them, diethylstilbestrol was the dominant contributor, with the estradiol equivalent (EEQ) significantly correlated with EEQ_water. In addition, zearalenone and niclosamide explained up to 54% of the EEQ_water. The RHT-based EDA method could support the effect evaluation, contributor identification, and risk management of micropolluted waters.

Original language	English
Pages (from-to)	7840-7852
Number of pages	13
Journal	Environmental Science and Technology
Volume	56
Issue number	12
Early online date	26 May 2022
DOIs	https://doi.org/10.1021/acs.est.1c08676
Publication status	Published - 21 Jun 2022

Bibliographical note

Funding Information:
This work was supported by the National Natural Science Foundation of China (21922603), the Natural Science Foundation of Jiangsu Province for Young Scholars (BK20210190), the Environmental Protection Research Project of Jiangsu Province (2021003 and 2018001), the National Key R&D Program of China (2018YFC1801604), the Fundamental Research Funds for the Central Universities (021114380139), the Fund from State Key Laboratory of Environmental Chemistry and Ecotoxicology (KF2021-08), and the Fund from State Key Laboratory of Pollution Control and Resource Reuse (PCRR-ZZ-202103). The authors appreciate Chunyan Yin from Chongqing Ecological Environment Monitoring Station and Guoqing Li from Yibin Ecological Environment Monitoring Station for their help in the sampling processes. The computational calculations were performed in the High-Performance Computing Center (HPCC) of Nanjing University and the National Supercomputing Center in Shenzhen.

Publisher Copyright:
© 2022 American Chemical Society. All rights reserved.

Keywords

effect-directed analysis
estrogenic effects
key contributor identification
reduced human transcriptome
source water
tap water

ASJC Scopus subject areas

General Chemistry
Environmental Chemistry

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10.1021/acs.est.1c08676

Cite this

Guo, J., Shen, Y., Zhang, X., Lin, D., Xia, P., Song, M., Yan, L., Zhong, W., Gou, X., Wang, C., Wei, S., Yu, H., & Shi, W. (2022). Effect-Directed Analysis Based on the Reduced Human Transcriptome (RHT) to Identify Organic Contaminants in Source and Tap Waters along the Yangtze River. Environmental Science and Technology, 56(12), 7840-7852. https://doi.org/10.1021/acs.est.1c08676

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title = "Effect-Directed Analysis Based on the Reduced Human Transcriptome (RHT) to Identify Organic Contaminants in Source and Tap Waters along the Yangtze River",

abstract = "Since a large number of contaminants are detected in source waters (SWs) and tap waters (TWs), it is important to perform a comprehensive effect evaluation and key contributor identification. A reduced human transcriptome (RHT)-based effect-directed analysis, which consisted of a concentration-dependent RHT to reveal the comprehensive effects and noteworthy pathways and systematic identification of key contributors based on the interactions between compounds and pathway effects, was developed and applied to typical SWs and TWs along the Yangtze River. By RHT, 42% more differentially expressed genes and 33% more pathways were identified in the middle and lower reaches, indicating heavier pollution. Hormone and immune pathways were prioritized based on the detection frequency, sensitivity, and removal efficiency, among which the estrogen receptor pathway was the most noteworthy. Consistent with RHT, estrogenic effects were widespread along the Yangtze River based on in vitro evaluations. Furthermore, 38 of 100 targets, 39 pathway-related suspects, and 16 estrogenic nontargets were systematically identified. Among them, diethylstilbestrol was the dominant contributor, with the estradiol equivalent (EEQ) significantly correlated with EEQwater. In addition, zearalenone and niclosamide explained up to 54% of the EEQwater. The RHT-based EDA method could support the effect evaluation, contributor identification, and risk management of micropolluted waters.",

keywords = "effect-directed analysis, estrogenic effects, key contributor identification, reduced human transcriptome, source water, tap water",

author = "Jing Guo and Yanhong Shen and Xiaowei Zhang and Die Lin and Pu Xia and Maoyong Song and Lu Yan and Wenjun Zhong and Xiao Gou and Chang Wang and Si Wei and Hongxia Yu and Wei Shi",

note = "Funding Information: This work was supported by the National Natural Science Foundation of China (21922603), the Natural Science Foundation of Jiangsu Province for Young Scholars (BK20210190), the Environmental Protection Research Project of Jiangsu Province (2021003 and 2018001), the National Key R&D Program of China (2018YFC1801604), the Fundamental Research Funds for the Central Universities (021114380139), the Fund from State Key Laboratory of Environmental Chemistry and Ecotoxicology (KF2021-08), and the Fund from State Key Laboratory of Pollution Control and Resource Reuse (PCRR-ZZ-202103). The authors appreciate Chunyan Yin from Chongqing Ecological Environment Monitoring Station and Guoqing Li from Yibin Ecological Environment Monitoring Station for their help in the sampling processes. The computational calculations were performed in the High-Performance Computing Center (HPCC) of Nanjing University and the National Supercomputing Center in Shenzhen. Publisher Copyright: {\textcopyright} 2022 American Chemical Society. All rights reserved.",

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Guo, J, Shen, Y, Zhang, X, Lin, D, Xia, P, Song, M, Yan, L, Zhong, W, Gou, X, Wang, C, Wei, S, Yu, H & Shi, W 2022, 'Effect-Directed Analysis Based on the Reduced Human Transcriptome (RHT) to Identify Organic Contaminants in Source and Tap Waters along the Yangtze River', Environmental Science and Technology, vol. 56, no. 12, pp. 7840-7852. https://doi.org/10.1021/acs.est.1c08676

TY - JOUR

T1 - Effect-Directed Analysis Based on the Reduced Human Transcriptome (RHT) to Identify Organic Contaminants in Source and Tap Waters along the Yangtze River

AU - Guo, Jing

AU - Shen, Yanhong

AU - Zhang, Xiaowei

AU - Lin, Die

AU - Xia, Pu

AU - Song, Maoyong

AU - Yan, Lu

AU - Zhong, Wenjun

AU - Gou, Xiao

AU - Wang, Chang

AU - Wei, Si

AU - Yu, Hongxia

AU - Shi, Wei

N1 - Funding Information: This work was supported by the National Natural Science Foundation of China (21922603), the Natural Science Foundation of Jiangsu Province for Young Scholars (BK20210190), the Environmental Protection Research Project of Jiangsu Province (2021003 and 2018001), the National Key R&D Program of China (2018YFC1801604), the Fundamental Research Funds for the Central Universities (021114380139), the Fund from State Key Laboratory of Environmental Chemistry and Ecotoxicology (KF2021-08), and the Fund from State Key Laboratory of Pollution Control and Resource Reuse (PCRR-ZZ-202103). The authors appreciate Chunyan Yin from Chongqing Ecological Environment Monitoring Station and Guoqing Li from Yibin Ecological Environment Monitoring Station for their help in the sampling processes. The computational calculations were performed in the High-Performance Computing Center (HPCC) of Nanjing University and the National Supercomputing Center in Shenzhen. Publisher Copyright: © 2022 American Chemical Society. All rights reserved.

PY - 2022/6/21

Y1 - 2022/6/21

N2 - Since a large number of contaminants are detected in source waters (SWs) and tap waters (TWs), it is important to perform a comprehensive effect evaluation and key contributor identification. A reduced human transcriptome (RHT)-based effect-directed analysis, which consisted of a concentration-dependent RHT to reveal the comprehensive effects and noteworthy pathways and systematic identification of key contributors based on the interactions between compounds and pathway effects, was developed and applied to typical SWs and TWs along the Yangtze River. By RHT, 42% more differentially expressed genes and 33% more pathways were identified in the middle and lower reaches, indicating heavier pollution. Hormone and immune pathways were prioritized based on the detection frequency, sensitivity, and removal efficiency, among which the estrogen receptor pathway was the most noteworthy. Consistent with RHT, estrogenic effects were widespread along the Yangtze River based on in vitro evaluations. Furthermore, 38 of 100 targets, 39 pathway-related suspects, and 16 estrogenic nontargets were systematically identified. Among them, diethylstilbestrol was the dominant contributor, with the estradiol equivalent (EEQ) significantly correlated with EEQwater. In addition, zearalenone and niclosamide explained up to 54% of the EEQwater. The RHT-based EDA method could support the effect evaluation, contributor identification, and risk management of micropolluted waters.

AB - Since a large number of contaminants are detected in source waters (SWs) and tap waters (TWs), it is important to perform a comprehensive effect evaluation and key contributor identification. A reduced human transcriptome (RHT)-based effect-directed analysis, which consisted of a concentration-dependent RHT to reveal the comprehensive effects and noteworthy pathways and systematic identification of key contributors based on the interactions between compounds and pathway effects, was developed and applied to typical SWs and TWs along the Yangtze River. By RHT, 42% more differentially expressed genes and 33% more pathways were identified in the middle and lower reaches, indicating heavier pollution. Hormone and immune pathways were prioritized based on the detection frequency, sensitivity, and removal efficiency, among which the estrogen receptor pathway was the most noteworthy. Consistent with RHT, estrogenic effects were widespread along the Yangtze River based on in vitro evaluations. Furthermore, 38 of 100 targets, 39 pathway-related suspects, and 16 estrogenic nontargets were systematically identified. Among them, diethylstilbestrol was the dominant contributor, with the estradiol equivalent (EEQ) significantly correlated with EEQwater. In addition, zearalenone and niclosamide explained up to 54% of the EEQwater. The RHT-based EDA method could support the effect evaluation, contributor identification, and risk management of micropolluted waters.

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Effect-Directed Analysis Based on the Reduced Human Transcriptome (RHT) to Identify Organic Contaminants in Source and Tap Waters along the Yangtze River

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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