A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegansShan Gao *1, Weiyang Chen *2, Nan Zhang 1, Chi Xu 3, Haiming Jing 1,4, Wenjing Zhang 1,4, Gaochao Han 1,4, Matthew Flavel 5, Markandeya Jois 5, Yingxin Zeng 1, Jing-Dong J. Han 3, Bo Xian 3, Guojun Li 1,4
1Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Prevention and Control/Beijing Center of Preventive Medicine Research, China, 2College of Computer Science and Technology, Qilu University of Technology(Shandong Academy of Sciences), China, 3Key Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, China, 4Beijing Key Laboratory of Environmental Toxicology, School of Public Health, Capital Medical University, China, 5School of Life Sciences, La Trobe University, Australia
A quantitative method has been developed to identify and predict the acute toxicity of chemicals by automatically analyzing the phenotypic profiling of Caenorhabditis elegans. This protocol describes how to treat worms with chemicals in a 384-well plate, capture videos, and quantify toxicological related phenotypes.
