A toxicity pathway-oriented approach to develop adverse outcome pathway: AHR activation as a case study

不良结局途径 毒理基因组学 机制(生物学) 毒性 磷脂病 计算生物学 系统生物学 计算机科学 化学 生物 基因 生物化学 认识论 哲学 基因表达 有机化学 磷脂
作者
Jing Yuan,Meiyao Feng,Wanli Ma,Yanhong Wei,Guangshuai Qi,Jiao Luo,Lin Xu,Xinmei Li,Chuanhai Li,Ying Wang,Daochuan Li,Jing Chen,Yanjie Zhao,Yawen Hou,Qianwen Zhao,Lidan Jiang,Mengyue Xie,Yuxin Zheng,Dianke Yu
出处
期刊:Environmental Pollution [Elsevier]
卷期号:268: 115733-115733 被引量:19
标识
DOI:10.1016/j.envpol.2020.115733
摘要

With numerous new chemicals introduced into the environment everyday, identification of their potential hazards to the environment and human health is a considerable challenge. Developing adverse outcome pathway (AOP) framework is promising in helping to achieve this goal as it can bring In Vitro testing into toxicity measurement and understanding. To explore the toxic mechanism underlying environmental chemicals via the AOP approach, an integration of adequate experimental data with systems biology understanding is preferred. Here, we describe a novel method to develop reliable and sensible AOPs that relies on chemical-gene interactions, toxicity pathways, molecular regulations, phenotypes, and outcomes information obtained from comparative toxicogenomics database (CTD) and Ingenuity Pathway Analysis (IPA). Using Benzo(a)pyrene (BaP), a highly studied chemical as a stressor, we identified the pivotal IPA toxicity pathways, the molecular initiating event (MIE), and candidate key events (KEs) to structure AOPs in the liver and lung, respectively. Further, we used the corresponding CTD information of multiple typical AHR-ligands, including 2,3,7,8-tetrachlorodibenzoparadioxin (TCDD), valproic acid, quercetin, and particulate matter, to validate our AOP networks. Our approach is likely to speed up AOP development as providing a time- and cost-efficient way to collect all fragmented bioinformation in published studies. It also facilitates a better understanding of the toxic mechanism of environmental chemicals, and potentially brings new insights into the screening of critical paths in the AOP network.
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