Literature DB >> 28696678

Benchmarking Water Quality from Wastewater to Drinking Waters Using Reduced Transcriptome of Human Cells.

Pu Xia1, Xiaowei Zhang1, Hanxin Zhang1, Pingping Wang1, Mingming Tian1, Hongxia Yu1.   

Abstract

One of the major challenges in environmental science is monitoring and assessing the risk of complex environmental mixtures. In vitro bioassays with limited key toxicological end points have been shown to be suitable to evaluate mixtures of organic pollutants in wastewater and recycled water. Omics approaches such as transcriptomics can monitor biological effects at the genome scale. However, few studies have applied omics approach in the assessment of mixtures of organic micropollutants. Here, an omics approach was developed for profiling bioactivity of 10 water samples ranging from wastewater to drinking water in human cells by a reduced human transcriptome (RHT) approach and dose-response modeling. Transcriptional expression of 1200 selected genes were measured by an Ampliseq technology in two cell lines, HepG2 and MCF7, that were exposed to eight serial dilutions of each sample. Concentration-effect models were used to identify differentially expressed genes (DEGs) and to calculate effect concentrations (ECs) of DEGs, which could be ranked to investigate low dose response. Furthermore, molecular pathways disrupted by different samples were evaluated by Gene Ontology (GO) enrichment analysis. The ability of RHT for representing bioactivity utilizing both HepG2 and MCF7 was shown to be comparable to the results of previous in vitro bioassays. Finally, the relative potencies of the mixtures indicated by RHT analysis were consistent with the chemical profiles of the samples. RHT analysis with human cells provides an efficient and cost-effective approach to benchmarking mixture of micropollutants and may offer novel insight into the assessment of mixture toxicity in water.

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Year:  2017        PMID: 28696678     DOI: 10.1021/acs.est.7b02648

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  5 in total

1.  A Reduced Transcriptome Approach to Assess Environmental Toxicants Using Zebrafish Embryo Test.

Authors:  Pingping Wang; Pu Xia; Jianghua Yang; Zhihao Wang; Ying Peng; Wei Shi; Daniel L Villeneuve; Hongxia Yu; Xiaowei Zhang
Journal:  Environ Sci Technol       Date:  2018-01-02       Impact factor: 9.028

2.  Assessing the impact of wastewater treatment plant effluent on downstream drinking water-source quality using a zebrafish (Danio Rerio) liver cell-based metabolomics approach.

Authors:  Huajun Zhen; Drew R Ekman; Timothy W Collette; Susan T Glassmeyer; Marc A Mills; Edward T Furlong; Dana W Kolpin; Quincy Teng
Journal:  Water Res       Date:  2018-08-14       Impact factor: 11.236

Review 3.  Toward Sustainable Environmental Quality: Priority Research Questions for Asia.

Authors:  Kenneth M Y Leung; Katie W Y Yeung; Jing You; Kyungho Choi; Xiaowei Zhang; Ross Smith; Guang-Jie Zhou; Mana M N Yung; Carlos Arias-Barreiro; Youn-Joo An; S Rebekah Burket; Robert Dwyer; Nathalie Goodkin; Yii Siang Hii; Tham Hoang; Chris Humphrey; Chuleemas Boonthai Iwai; Seung-Woo Jeong; Guillaume Juhel; Ali Karami; Katerina Kyriazi-Huber; Kuan-Chun Lee; Bin-Le Lin; Ben Lu; Patrick Martin; Mae Grace Nillos; Katharina Oginawati; I V N Rathnayake; Yenny Risjani; Mohammad Shoeb; Chin Hon Tan; Maria Claret Tsuchiya; Gerald T Ankley; Alistair B A Boxall; Murray A Rudd; Bryan W Brooks
Journal:  Environ Toxicol Chem       Date:  2020-07-20       Impact factor: 3.742

4.  Metabolomic and Transcriptomic Analysis of MCF-7 Cells Exposed to 23 Chemicals at Human-Relevant Levels: Estimation of Individual Chemical Contribution to Effects.

Authors:  Min Liu; Shenglan Jia; Ting Dong; Fanrong Zhao; Tengfei Xu; Qin Yang; Jicheng Gong; Mingliang Fang
Journal:  Environ Health Perspect       Date:  2020-12-16       Impact factor: 9.031

5.  Photodegradation of carbon dots cause cytotoxicity.

Authors:  Yue-Yue Liu; Nan-Yang Yu; Wen-Di Fang; Qiao-Guo Tan; Rong Ji; Liu-Yan Yang; Si Wei; Xiao-Wei Zhang; Ai-Jun Miao
Journal:  Nat Commun       Date:  2021-02-05       Impact factor: 14.919

  5 in total

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