Yang Renjun, Liu Shuyu, Yin Nuoya, Zhang Yang, Faiola Francesco
State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 18 Shuangqing Road, Beijing 100085, China.
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
Environ Sci Technol. 2022 Oct 18;56(20):14668-14679. doi: 10.1021/acs.est.2c04467. Epub 2022 Sep 30.
Chemical pollution has become a prominent environmental problem. In recent years, quantitative high-throughput screening (qHTS) assays have been developed for the fast assessment of chemicals' toxic effects. Toxicology in the 21st Century (Tox21) is a well-known and continuously developing qHTS project. Recent reports utilizing Tox21 data have mainly focused on setting up mathematical models for toxicity predictions, with less attention to intuitive qHTS data visualization. In this study, we attempted to reveal and summarize the toxic effects of environmental pollutants by analyzing and visualizing Tox21 qHTS data. Via PubMed text mining, toxicity/structure clustering, and manual classification, we detected a total of 158 chemicals of environmental concern (COECs) from the Tox21 library that we classified into 13 COEC groups based on structure and activity similarities. By visualizing these COEC groups' bioactivities, we demonstrated that COECs frequently displayed androgen and progesterone antagonistic effects, xenobiotic receptor agonistic roles, and mitochondrial toxicity. We also revealed many other potential targets of the 13 COEC groups, which were not well illustrated yet, and that current Tox21 assays may not correctly classify known teratogens. In conclusion, we provide a feasible method to intuitively understand qHTS data.
化学污染已成为一个突出的环境问题。近年来，已开发出定量高通量筛选（qHTS）检测方法用于快速评估化学物质的毒性作用。21世纪毒理学（Tox21）是一个知名且不断发展的qHTS项目。最近利用Tox21数据的报告主要集中在建立毒性预测的数学模型上，而对直观的qHTS数据可视化关注较少。在本研究中，我们试图通过分析和可视化Tox21 qHTS数据来揭示和总结环境污染物的毒性作用。通过PubMed文本挖掘、毒性/结构聚类和人工分类，我们从Tox21库中总共检测到158种环境关注化学物质（COECs），并根据结构和活性相似性将它们分为13个COEC组。通过可视化这些COEC组的生物活性，我们证明COECs经常表现出雄激素和孕激素拮抗作用、外源性受体激动作用以及线粒体毒性。我们还揭示了13个COEC组的许多其他潜在靶点，这些靶点尚未得到很好的阐明，并且当前的Tox21检测可能无法正确分类已知的致畸物。总之，我们提供了一种直观理解qHTS数据的可行方法。
