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A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

文献类型：期刊论文

作者Gao, Shan1; Zhang, Nan1; Jing, Haiming1; Zhang, Wenjing1,2; Han, Gaochao1,2; Zeng, Yingxin1; Li, Guojun1,2; Chen, Weiyang5; Xu, Chi3; Han, Jing-Dong J.3
刊名JOVE-JOURNAL OF VISUALIZED EXPERIMENTS
出版日期2019
卷号-期号:145页码:e59082
关键词Environmental Sciences Issue 145 Chemicals toxicity Caenorhabditis elegans image analysis phenotype quantification
ISSN号1940-087X
DOI10.3791/59082
文献子类Article
英文摘要Applying toxicity testing of chemicals in higher order organisms, such as mice or rats, is time-consuming and expensive, due to their long lifespan and maintenance issues. On the contrary, the nematode Caenorhabditis elegans (C. elegans) has advantages to make it an ideal choice for toxicity testing: a short lifespan, easy cultivation, and efficient reproduction. Here, we describe a protocol for the automatic phenotypic profiling of C. elegans in a 384-well plate. The nematode worms are cultured in a 384-well plate with liquid medium and chemical treatment, and videos are taken of each well to quantify the chemical influence on 33 worm features. Experimental results demonstrate that the quantified phenotype features can classify and predict the acute toxicity for different chemical compounds and establish a priority list for further traditional chemical toxicity assessment tests in a rodent model.
学科主题Science & Technology - Other Topics
WOS关键词NEMATODE
语种英语
WOS记录号WOS:000462909500059
出版者JOURNAL OF VISUALIZED EXPERIMENTS
版本出版稿
源URL[http://202.127.25.144/handle/331004/590]  
专题中国科学院上海生命科学研究院营养科学研究所
作者单位1.Beijing Ctr Dis Prevent & Control, Beijing Ctr Prevent Med Res, Beijing Key Lab Diagnost & Traceabil Technol Food, Beijing, Peoples R China;
2.Capital Med Univ, Sch Publ Hlth, Beijing Key Lab Environm Toxicol, Beijing, Peoples R China;
3.Chinese Acad Sci, Max Planck Partner Inst Computat Biol, Collaborat Innovat Ctr Genet & Dev Biol,Shanghai, Key Lab Computat Biol,Ctr Excellence Mol Cell Sci, Shanghai, Peoples R China;
4.La Trobe Univ, Sch Life Sci, Melbourne, Vic, Australia,
5.Qilu Univ Technol, Shandong Acad Sci, Coll Comp Sci & Technol, Jinan, Shandong, Peoples R China;
推荐引用方式
GB/T 7714		 Gao, Shan,Zhang, Nan,Jing, Haiming,et al. A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans[J]. JOVE-JOURNAL OF VISUALIZED EXPERIMENTS,2019,-(145):e59082.
APA Gao, Shan.,Zhang, Nan.,Jing, Haiming.,Zhang, Wenjing.,Han, Gaochao.,...&,.(2019).A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans.JOVE-JOURNAL OF VISUALIZED EXPERIMENTS,-(145),e59082.
MLA Gao, Shan,et al."A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans".JOVE-JOURNAL OF VISUALIZED EXPERIMENTS -.145(2019):e59082.

入库方式： OAI收割

来源：上海营养与健康研究所

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