Li Roman A, Talikka Marja, Gubian Sylvain, Vom Berg Colette, Martin Florian, Peitsch Manuel C, Hoeng Julia, Zupanic Anze
Eawag, Dübendorf, Switzerland.
PMI R&D, Philip Morris Products S.A., Neuchâtel, Switzerland.
Front Genet. 2021 Jun 15;12:652632. doi: 10.3389/fgene.2021.652632. eCollection 2021.
Adverse outcomes that result from chemical toxicity are rarely caused by dysregulation of individual proteins; rather, they are often caused by system-level perturbations in networks of molecular events. To fully understand the mechanisms of toxicity, it is necessary to recognize the interactions of molecules, pathways, and biological processes within these networks. The developing brain is a prime example of an extremely complex network, which makes developmental neurotoxicity one of the most challenging areas in toxicology. We have developed a systems toxicology method that uses a computable biological network to represent molecular interactions in the developing brain of zebrafish larvae. The network is curated from scientific literature and describes interactions between biological processes, signaling pathways, and adverse outcomes associated with neurotoxicity. This allows us to identify important signaling hubs, pathway interactions, and emergent adverse outcomes, providing a more complete understanding of neurotoxicity. Here, we describe the construction of a zebrafish developmental neurotoxicity network and its validation by integration with publicly available neurotoxicity-related transcriptomic datasets. Our network analysis identified consistent regulation of tumor suppressors p53 and retinoblastoma 1 (Rb1) as well as the oncogene Krüppel-like factor (Klf8) in response to chemically induced developmental neurotoxicity. The developed network can be used to interpret transcriptomic data in a neurotoxicological context.
化学毒性导致的不良后果很少是由单个蛋白质的失调引起的；相反，它们通常是由分子事件网络中的系统级扰动引起的。要全面了解毒性机制，有必要认识这些网络中分子、信号通路和生物过程之间的相互作用。发育中的大脑是一个极其复杂网络的典型例子，这使得发育神经毒性成为毒理学中最具挑战性的领域之一。我们开发了一种系统毒理学方法，该方法使用一个可计算的生物网络来表示斑马鱼幼体发育大脑中的分子相互作用。该网络是根据科学文献精心策划的，描述了生物过程、信号通路以及与神经毒性相关的不良后果之间的相互作用。这使我们能够识别重要的信号枢纽、通路相互作用和新出现的不良后果，从而更全面地了解神经毒性。在此，我们描述了斑马鱼发育神经毒性网络的构建及其通过与公开可用的神经毒性相关转录组数据集整合进行的验证。我们的网络分析确定了肿瘤抑制因子p53和视网膜母细胞瘤1（Rb1）以及原癌基因Krüppel样因子（Klf8）在化学诱导的发育神经毒性反应中的一致调控。所开发的网络可用于在神经毒理学背景下解释转录组数据。
