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Guo J, Luo Y, Fang C, Jin J, Xia P, Wu B, Zhang X, Yu H, Ren H, Shi W. Advancing the Effect-Directed Identification in Combined Pollution: Using Pathways to Link Effects and Toxicants. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:18642-18653. [PMID: 39392738 DOI: 10.1021/acs.est.4c07735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/13/2024]
Abstract
The difficulty in associating diverse pollutants with mixture effects has led to significant challenges in identifying toxicants in combined pollution. In this study, pathways were used to link effects and toxicants. By pathways evaluated by the concentration-dependent transcriptome, individual effects were extended to molecular mechanisms encompassing 135 pathways corresponding to 6 biological processes. Accordingly, mechanism-based identification of toxicants was achieved by constructing a pathway toxicant database containing 2413 chemical-pathway interactions and identifying pathway active fragments of 72 pathways. The developed method was applied to two different wastewaters, industrial wastewater OB and municipal wastewater HL. Although lethality and teratogenesis were both observed at the individual level, different molecular mechanisms were revealed by pathways, with cardiotoxicity- and genotoxicity-related pathways significantly enriched in OB, and neurotoxicity- and environmental information processing-related pathways significantly enriched in HL. Further suspect and nontargeted screening generated 59 and 86 causative toxicants in OB and HL, respectively, among which 29 toxicants were confirmed, that interacted with over 90% of enriched pathways and contributed over 50% of individual effects. After upgrading treatments based on causative toxicants, consistent removal of toxicants, pathway effects, and individual effects were observed. Mediation by pathways enables mechanism-based identification, supporting the assessment and management of combined pollution.
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Affiliation(s)
- Jing Guo
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
- State Environmental Protection Key Laboratory of Aquatic Ecosystem Health in the Middle and Lower Reaches of Yangtze River, School of the Environment, Nanjing University, Nanjing 210023, China
- Jiangsu Province Ecology and Environment Protection Key Laboratory of Chemical Safety and Health Risk, Nanjing 210023, China
| | - Yiwen Luo
- Environmental Protection Key Laboratory of Chemical Ecological Effects and Pollution Control, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment of China, Nanjing 210042, China
| | - Chao Fang
- National Engineering Research Centre of Energy-Efficient Semi-conductor Devices and Materials, School of Electronic Science and Engineering, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Jinsha Jin
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Pu Xia
- Environmental Genomics Group, School of Biosciences, the University of Birmingham, Birmingham B15 2TT, U.K
| | - Bing Wu
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Xiaowei Zhang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
- State Environmental Protection Key Laboratory of Aquatic Ecosystem Health in the Middle and Lower Reaches of Yangtze River, School of the Environment, Nanjing University, Nanjing 210023, China
- Jiangsu Province Ecology and Environment Protection Key Laboratory of Chemical Safety and Health Risk, Nanjing 210023, China
| | - Hongxia Yu
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Hongqiang Ren
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Wei Shi
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
- State Environmental Protection Key Laboratory of Aquatic Ecosystem Health in the Middle and Lower Reaches of Yangtze River, School of the Environment, Nanjing University, Nanjing 210023, China
- Jiangsu Province Ecology and Environment Protection Key Laboratory of Chemical Safety and Health Risk, Nanjing 210023, China
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Wang X, Qi R, Li S, Ding M, Miao J, Han L, Fan Q, Li Y, Pan L. Species sensitivity distribution for nonylphenol: Acute toxicity and ecological risk in Bohai Region. MARINE POLLUTION BULLETIN 2024; 206:116765. [PMID: 39068711 DOI: 10.1016/j.marpolbul.2024.116765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Revised: 07/20/2024] [Accepted: 07/22/2024] [Indexed: 07/30/2024]
Abstract
Nonylphenol (NP), a main byproduct of nonylphenol polyethoxylates (NPEs) degradation, is prevalent across diverse environmental settings. Given its widespread presence, evaluating the ecological risks associated with NP in coastal waters and sediments is essential for the protection of the marine environment. This study evaluates the acute toxicity of NP on ten representative aquatic species from the Bohai Sea, determining the Aquatic Life Criteria (ALC) through two distinct methods. The Criteria Maximum Concentration (CMC) for NP in seawater was established at 12.0 μg/L, with a Predicted No-Effect Concentration (PNEC) for water at 15.2 μg/L and for sediment at 33.3 μg/kg. Additionally, a tiered ecological risk assessment (ERA) of both surface seawater and sediment in the Bohai Sea revealed significant ecological risks at various sediment sites. These results offer crucial insights for assessing the ecological risks to coastal ecosystem and provide foundational data necessary for informed environmental protection and management strategies.
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Affiliation(s)
- Xuening Wang
- The Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China
| | - Ruicheng Qi
- The Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China
| | - Shang Li
- Key Laboratory of Marine chemistry Theory and Technology (Ocean University of china), Ministry of Education, Qingdao 266100, China
| | - Min Ding
- The Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China; Qinhuangdao Marine Environmental Monitoring Central Station of SOA, Qinhuangdao 066002, China
| | - Jingjing Miao
- The Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China.
| | - Lianxue Han
- The Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China
| | - Qichao Fan
- The Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China
| | - Yanbin Li
- Key Laboratory of Marine chemistry Theory and Technology (Ocean University of china), Ministry of Education, Qingdao 266100, China
| | - Luqing Pan
- The Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao 266003, China
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Liu J, Xiang T, Song XC, Zhang S, Wu Q, Gao J, Lv M, Shi C, Yang X, Liu Y, Fu J, Shi W, Fang M, Qu G, Yu H, Jiang G. High-Efficiency Effect-Directed Analysis Leveraging Five High Level Advancements: A Critical Review. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:9925-9944. [PMID: 38820315 DOI: 10.1021/acs.est.3c10996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2024]
Abstract
Organic contaminants are ubiquitous in the environment, with mounting evidence unequivocally connecting them to aquatic toxicity, illness, and increased mortality, underscoring their substantial impacts on ecological security and environmental health. The intricate composition of sample mixtures and uncertain physicochemical features of potential toxic substances pose challenges to identify key toxicants in environmental samples. Effect-directed analysis (EDA), establishing a connection between key toxicants found in environmental samples and associated hazards, enables the identification of toxicants that can streamline research efforts and inform management action. Nevertheless, the advancement of EDA is constrained by the following factors: inadequate extraction and fractionation of environmental samples, limited bioassay endpoints and unknown linkage to higher order impacts, limited coverage of chemical analysis (i.e., high-resolution mass spectrometry, HRMS), and lacking effective linkage between bioassays and chemical analysis. This review proposes five key advancements to enhance the efficiency of EDA in addressing these challenges: (1) multiple adsorbents for comprehensive coverage of chemical extraction, (2) high-resolution microfractionation and multidimensional fractionation for refined fractionation, (3) robust in vivo/vitro bioassays and omics, (4) high-performance configurations for HRMS analysis, and (5) chemical-, data-, and knowledge-driven approaches for streamlined toxicant identification and validation. We envision that future EDA will integrate big data and artificial intelligence based on the development of quantitative omics, cutting-edge multidimensional microfractionation, and ultraperformance MS to identify environmental hazard factors, serving for broader environmental governance.
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Affiliation(s)
- Jifu Liu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tongtong Xiang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- College of Sciences, Northeastern University, Shenyang 110004, China
| | - Xue-Chao Song
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shaoqing Zhang
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Qi Wu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jie Gao
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Meilin Lv
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- College of Sciences, Northeastern University, Shenyang 110004, China
| | - Chunzhen Shi
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Xiaoxi Yang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yanna Liu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Jianjie Fu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Shi
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Mingliang Fang
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Guangbo Qu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- Institute of Environment and Health, Jianghan University, Wuhan, Hubei 430056, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hongxia Yu
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
| | - Guibin Jiang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
- College of Sciences, Northeastern University, Shenyang 110004, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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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. 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 & TECHNOLOGY 2022; 56:7840-7852. [PMID: 35617516 DOI: 10.1021/acs.est.1c08676] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
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.
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Affiliation(s)
- Jing Guo
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Yanhong Shen
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
- Environmental Monitoring Station of Suzhou Industrial Park, Suzhou 215027, China
| | - Xiaowei Zhang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Die Lin
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Pu Xia
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Maoyong Song
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Lu Yan
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Wenjun Zhong
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Xiao Gou
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Chang Wang
- Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances, Institute of Environment and Health, Jianghan University, Wuhan 430056, China
| | - Si Wei
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Hongxia Yu
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Wei Shi
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
- Jiangsu Province Ecology and Environment Protection Key Laboratory of Chemical Safety and Health Risk, Nanjing 210023, China
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5
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Recent Advances in Sampling and Sample Preparation for Effect-Directed Environmental Analysis. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116654] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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6
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Xie P, Yan Q, Xiong J, Li H, Ma X, You J. Point or non-point source: Toxicity evaluation using m-POCIS and zebrafish embryos in municipal sewage treatment plants and urban waterways. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 292:118307. [PMID: 34626713 DOI: 10.1016/j.envpol.2021.118307] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 10/02/2021] [Accepted: 10/05/2021] [Indexed: 06/13/2023]
Abstract
Municipal sewage treatment plants (STPs) have been regarded as an important source of organic contaminants in aquatic environment. To assess the impact of STPs on occurrence and toxicity of STP-associated contaminants in receiving waterways, a novel passive sampler modified from polar organic chemical integrative sampler (m-POCIS) was deployed at the inlet and outlet of a STP and several upstream and downstream sites along a river receiving STP effluent in Guangzhou, China. Eighty-seven contaminants were analyzed in m-POCIS extracts, along with toxicity evaluation using zebrafish embryos. Polycyclic musks were the predominant contaminants in both STP and urban waterways, and antibiotics and current-use pesticides (e.g., neonicotinoids, fiproles) were also ubiquitous. The m-POCIS extracts from downstream sites caused significant deformity in embryos, yet the toxicity could not be explained by the measured contaminants, implying the presence of nontarget stressors. Sewage treatment process substantially reduced embryo deformity, chemical oxygen demand, and contamination levels of some contaminants; however, concentrations of neonicotinoids and fiproles increased after STP treatment, possibly due to the release of chemicals from perturbed sludge. Source identification showed that most of the contaminants found in urban waterways were originated from nonpoint runoff, while cosmetics factories and hospitals were likely point sources for musks and antibiotics, respectively. Although the observed embryo toxicity could not be well explained by target contaminants, the present study showed a promising future of using passive samplers to evaluate chemical occurrence and aquatic toxicity concurrently. Zebrafish embryo toxicity significantly decreased after sewage treatment, but higher toxicity was observed for downstream samples, demonstrating that urban runoff may produce detrimental effects to aquatic life, particularly in rainy season. These results highlight the relevance of monitoring nonpoint source pollution along with boosting municipal sewage treatment infrastructure.
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Affiliation(s)
- Peihong Xie
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China
| | - Qiankun Yan
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China
| | - Jingjing Xiong
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China; South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou, 510655, China
| | - Huizhen Li
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China
| | - Xue Ma
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China
| | - Jing You
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, China.
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Cheng F, Li H, Brooks BW, You J. Signposts for Aquatic Toxicity Evaluation in China: Text Mining using Event-Driven Taxonomy within and among Regions. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:8977-8986. [PMID: 34142809 DOI: 10.1021/acs.est.1c00152] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Selection of toxicity endpoints affects outcomes of risk assessment. Scientific decisions based on more holistic evidence is preferable for designing bioassay batteries rather than subjective selections, particularly when systems are poorly understood. Here, we propose a novel event-driven taxonomy (EDT)-based text mining tool to prioritize stressors likely to elicit water quality deterioration. The tool integrated automated literature collection, natural language processing using adverse outcome pathway-based toxicological terminologies and machine learning to classify event drivers (EDs). From aquatic toxicity assessments within China over the past decade, we gathered over 14 000 sources of information. With a dictionary that included 1039 toxicological terms, 15 bioassay-related modes of actions were mapped, yet less than half of the bioassays could be elucidated by available adverse outcome pathways. To fill these mechanistic knowledge gaps, we developed a Naïve Bayesian ED-classifier to annotate apical responses. The classifier's 4-fold cross-validation reached 74% accuracy and labeled 85% bioassays as 26 EDs. Narcosis, estrogen receptor-, and aryl hydrogen receptor-mediators were the major EDs in aquatic systems across China, whereas individual regions had distinct ED fingerprints. The EDT-based tool provides a promising diagnostic strategy to inform region-specific bioassay design and selection for water quality assessments in a big data era.
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Affiliation(s)
- Fei Cheng
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China
| | - Huizhen Li
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China
| | - Bryan W Brooks
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China
- Department of Environmental Science, Institute of Biomedical Studies, Center for Reservoir and Aquatic Systems Research, Baylor University, Waco, Texas 76798, United States
| | - Jing You
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China
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Cheng F, Li H, Brooks BW, You J. Retrospective Risk Assessment of Chemical Mixtures in the Big Data Era: An Alternative Classification Strategy to Integrate Chemical and Toxicological Data. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:5925-5927. [PMID: 32356979 DOI: 10.1021/acs.est.0c01062] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Affiliation(s)
- Fei Cheng
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China
| | - Huizhen Li
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China
| | - Bryan W Brooks
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China
- Department of Environmental Science, Institute of Biomedical Studies, Center for Reservoir and Aquatic Systems Research, Baylor University, Waco, Texas United States
| | - Jing You
- Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China
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9
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Lee J, Hong S, Kim T, Lee C, An SA, Kwon BO, Lee S, Moon HB, Giesy JP, Khim JS. Multiple Bioassays and Targeted and Nontargeted Analyses to Characterize Potential Toxicological Effects Associated with Sediments of Masan Bay: Focusing on AhR-Mediated Potency. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:4443-4454. [PMID: 32167753 DOI: 10.1021/acs.est.9b07390] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
An enhanced, multiple lines of evidence approach was applied to assess potential toxicological effects associated with polluted sediments. Two in vitro bioassays (H4IIE-luc and Vibrio fischeri) and three in vivo bioassays (microalgae: Isochrysis galbana and Phaeodactylum tricornutum; zebrafish embryo: Danio rerio) were applied. To identify causative chemicals in samples, targeted analyses (polycyclic aromatic hydrocarbons (PAHs), styrene oligomers (SOs), and alkylphenols) and nontargeted full-scan screening analyses (FSA; GC- and LC-QTOFMS) were performed. First, great AhR-mediated potencies were observed in midpolar and polar fractions of sediment extracts, but known and previously characterized AhR agonists, including PAHs and SOs could not fully explain the total potencies of samples. Enoxolone was identified as a novel AhR agonist in a highly potent sediment fraction by use of FSA. Enoxolone has a relative potency of 0.13 compared to benzo[a]pyrene (1.0) in the H4IIE-luc bioassay. Nonylphenols associated with membrane damage that influenced the viability of the microalgae were also observed. Finally, inhibitions of bioluminescence of V. fischeri and lethality of D. rerio embryos were strongly related to nonpolar compounds. Overall, the present work addressed assay- and end point-specific variations and sensitivities for potential toxicities of mixture samples, warranting a significant utility of the "multiple lines of evidence" approach in ecological risk assessment.
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Affiliation(s)
- Junghyun Lee
- School of Earth and Environmental Sciences & Research Institute of Oceanography, Seoul National University, Seoul 08826, Republic of Korea
| | - Seongjin Hong
- Department of Ocean Environmental Sciences, Chungnam National University, Daejeon 34134, Republic of Korea
| | - Taewoo Kim
- School of Earth and Environmental Sciences & Research Institute of Oceanography, Seoul National University, Seoul 08826, Republic of Korea
| | - Changkeun Lee
- School of Earth and Environmental Sciences & Research Institute of Oceanography, Seoul National University, Seoul 08826, Republic of Korea
| | - Seong-Ah An
- Department of Ocean Environmental Sciences, Chungnam National University, Daejeon 34134, Republic of Korea
| | - Bong-Oh Kwon
- Department of Marine Biotechnology, Kunsan National University, Kunsan 54150, Republic of Korea
| | - Sunggyu Lee
- Department of Marine Science and Convergence Engineering, Hanyang University, Ansan 15588, Republic of Korea
| | - Hyo-Bang Moon
- Department of Marine Science and Convergence Engineering, Hanyang University, Ansan 15588, Republic of Korea
| | - John P Giesy
- Department of Veterinary Biomedical Sciences & Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan S7N 5B4, Canada
- Department of Environmental Sciences, Baylor University, Waco, Texas 76706, United States
- Department of Zoology and Center for Integrative Toxicology, Michigan State University, East Lansing, Michigan 48824, United States
| | - Jong Seong Khim
- School of Earth and Environmental Sciences & Research Institute of Oceanography, Seoul National University, Seoul 08826, Republic of Korea
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