Dufourcq Sekatcheff Elizabeth, Jeong Jaeseong, Choi Jinhee
School of Environmental Engineering, University of Seoul, Seoul, Korea.
Environ Toxicol Chem. 2024 Jul 9. doi: 10.1002/etc.5940.
Although ecotoxicological and toxicological risk assessments are performed separately from each other, recent efforts have been made in both disciplines to reduce animal testing and develop predictive approaches instead, for example, via conserved molecular markers, and in vitro and in silico approaches. Among them, adverse outcome pathways (AOPs) have been proposed to facilitate the prediction of molecular toxic effects at larger biological scales. Thus, more toxicological data are used to inform on ecotoxicological risks and vice versa. An AOP has been previously developed to predict reproductive toxicity of silver nanoparticles via oxidative stress on the nematode Caenorhabditis elegans (AOPwiki ID 207). Following this previous study, our present study aims to extend the biologically plausible taxonomic domain of applicability (tDOA) of AOP 207. Various types of data, including in vitro human cells, in vivo, and molecular to individual, from previous studies have been collected and structured into a cross-species AOP network that can inform both human toxicology and ecotoxicology risk assessments. The first step was the collection and analysis of literature data to fit the AOP criteria and build a first AOP network. Then, key event relationships were assessed using a Bayesian network modeling approach, which gave more confidence in our overall AOP network. Finally, the biologically plausible tDOA was extended using in silico approaches (Genes-to-Pathways Species Conservation Analysis and Sequence Alignment to Predict Across Species Susceptibility), which led to the extrapolation of our AOP network across over 100 taxonomic groups. Our approach shows that various types of data can be integrated into an AOP framework, and thus facilitates access to knowledge and prediction of toxic mechanisms without the need for further animal testing. Environ Toxicol Chem 2024;00:1-14. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
尽管生态毒理学和毒理学风险评估是相互独立进行的，但最近这两个学科都在努力减少动物试验，并转而开发预测方法，例如通过保守的分子标记以及体外和计算机模拟方法。其中，有人提出了不良结局途径（AOPs），以促进在更大生物尺度上预测分子毒性效应。因此，更多的毒理学数据被用于了解生态毒理学风险，反之亦然。此前已经开发了一个AOP，通过对线虫秀丽隐杆线虫的氧化应激来预测银纳米颗粒的生殖毒性（AOPwiki ID 207）。在这项先前研究的基础上，我们目前的研究旨在扩展AOP 207在生物学上合理的适用分类域（tDOA）。我们收集了先前研究中的各种类型的数据，包括体外人类细胞、体内以及从分子到个体的数据，并将其构建成一个跨物种AOP网络，该网络可为人类毒理学和生态毒理学风险评估提供信息。第一步是收集和分析文献数据，以符合AOP标准并构建第一个AOP网络。然后，使用贝叶斯网络建模方法评估关键事件关系，这使我们对整个AOP网络更有信心。最后，使用计算机模拟方法（基因到途径物种保守性分析和序列比对以预测跨物种易感性）扩展生物学上合理的tDOA，这导致我们的AOP网络外推到100多个分类组。我们的方法表明，各种类型的数据可以整合到AOP框架中，从而有助于获取知识和预测毒性机制，而无需进一步的动物试验。《环境毒理学与化学》2024年；00:1 - 14。© 2024作者。《环境毒理学与化学》由Wiley Periodicals LLC代表SETAC出版。
