Burkard Michael, Betz Alexander, Schirmer Kristin, Zupanic Anze
Swiss Federal Institute of Technology, Eawag, 8600 Dübendorf, Switzerland.
Institute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, 8092 Zürich, Switzerland.
Environ Sci Technol. 2020 Jan 7;54(1):335-344. doi: 10.1021/acs.est.9b05170. Epub 2019 Dec 13.
The use of omics is gaining importance in the field of nanoecotoxicology; an increasing number of studies are aiming to investigate the effects and modes of action of engineered nanomaterials (ENMs) in this way. However, a systematic synthesis of the outcome of such studies regarding common responses and toxicity pathways is currently lacking. We developed an R-scripted computational pipeline to perform reanalysis and functional analysis of relevant transcriptomic data sets using a common approach, independent from the ENM type, and across different organisms, including , and . Using the pipeline that can semiautomatically process data from different microarray technologies, we were able to determine the most common molecular mechanisms of nanotoxicity across extremely variable data sets. As expected, we found known mechanisms, such as interference with energy generation, oxidative stress, disruption of DNA synthesis, and activation of DNA-repair but also discovered that some less-described molecular responses to ENMs, such as DNA/RNA methylation, protein folding, and interference with neurological functions, are present across the different studies. Results were visualized in radar charts to assess toxicological response patterns allowing the comparison of different organisms and ENM types. This can be helpful to retrieve ENM-related hazard information and thus fill knowledge gaps in a comprehensive way in regard to the molecular underpinnings and mechanistic understanding of nanotoxicity.
组学技术在纳米生态毒理学领域正变得越来越重要;越来越多的研究旨在通过这种方式研究工程纳米材料(ENM)的影响和作用模式。然而,目前缺乏对这类研究关于常见反应和毒性途径结果的系统综合分析。我们开发了一个用R语言编写的计算流程,以一种通用方法对相关转录组数据集进行重新分析和功能分析,该方法独立于ENM类型,且适用于包括[具体生物1]、[具体生物2]和[具体生物3]在内的不同生物体。使用这个能够半自动处理来自不同微阵列技术数据的流程,我们得以在极其多样的数据集中确定纳米毒性最常见的分子机制。正如预期的那样,我们发现了已知的机制,如对能量产生的干扰、氧化应激、DNA合成的破坏以及DNA修复的激活,但也发现不同研究中存在一些对ENM描述较少的分子反应,如DNA/RNA甲基化、蛋白质折叠以及对神经功能的干扰。结果在雷达图中可视化,以评估毒理学反应模式,从而能够比较不同生物体和ENM类型。这有助于获取与ENM相关的危害信息,从而全面填补关于纳米毒性分子基础和机制理解方面的知识空白。