American Association for the Advancement of Science (AAAS) Science and Technology Policy Fellow at the US Environmental Protection Agency (EPA), 2009-10, USA.
Toxicol Appl Pharmacol. 2013 Sep 15;271(3):372-85. doi: 10.1016/j.taap.2011.11.011. Epub 2011 Nov 28.
A critical challenge for environmental chemical risk assessment is the characterization and reduction of uncertainties introduced when extrapolating inferences from one species to another. The purpose of this article is to explore the challenges, opportunities, and research needs surrounding the issue of how genomics data and computational and systems level approaches can be applied to inform differences in response to environmental chemical exposure across species. We propose that the data, tools, and evolutionary framework of comparative genomics be adapted to inform interspecies differences in chemical mechanisms of action. We compare and contrast existing approaches, from disciplines as varied as evolutionary biology, systems biology, mathematics, and computer science, that can be used, modified, and combined in new ways to discover and characterize interspecies differences in chemical mechanism of action which, in turn, can be explored for application to risk assessment. We consider how genetic, protein, pathway, and network information can be interrogated from an evolutionary biology perspective to effectively characterize variations in biological processes of toxicological relevance among organisms. We conclude that comparative genomics approaches show promise for characterizing interspecies differences in mechanisms of action, and further, for improving our understanding of the uncertainties inherent in extrapolating inferences across species in both ecological and human health risk assessment. To achieve long-term relevance and consistent use in environmental chemical risk assessment, improved bioinformatics tools, computational methods robust to data gaps, and quantitative approaches for conducting extrapolations across species are critically needed. Specific areas ripe for research to address these needs are recommended.
环境化学风险评估的一个关键挑战是在将推断从一个物种外推到另一个物种时,对引入的不确定性进行特征描述和减少。本文旨在探讨围绕以下问题的挑战、机遇和研究需求:如何将基因组学数据和计算及系统水平方法应用于告知不同物种对环境化学暴露的反应差异。我们提出,比较基因组学的数据、工具和进化框架应适应于告知化学作用机制的种间差异。我们比较和对比了现有的方法,这些方法来自进化生物学、系统生物学、数学和计算机科学等不同学科,可以以新的方式加以利用、修改和组合,以发现和描述化学作用机制的种间差异,进而可以探索其在风险评估中的应用。我们考虑了如何从进化生物学的角度来探讨遗传、蛋白质、途径和网络信息,以有效地描述生物体中与毒性相关的生物过程的变化。我们得出结论,比较基因组学方法有望对作用机制的种间差异进行特征描述,并且进一步提高我们对在生态和人类健康风险评估中跨物种推断的内在不确定性的理解。为了在环境化学风险评估中实现长期相关性和一致使用,迫切需要改进生物信息学工具、对数据空白具有稳健性的计算方法以及进行跨物种推断的定量方法。建议了一些适合解决这些需求的研究领域。