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Deciphering the Combined Effects of Environmental Stressors on Gene Transcription: A Conceptual Approach

机译：解读环境应激因素对基因转录的综合影响：一种概念方法

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摘要

The use of classical mixture toxicity models to predict the combined effects of environmental stressors based on toxicogenomics (OMICS) data is still in its infancy. Although several studies have made attempts to implement mixture modeling in OMICS analysis to understand the low-dose interactions of stressors, it is not clear how interactions occur at the molecular level and how results generated from such approaches can be better used to inform future studies and cumulative hazard assessment of multiple stressors. The present work was therefore conducted to propose a conceptual approach for combined effect assessment using global gene expression data, as illustrated by a case study on assessment of combined effects of gamma radiation and depleted uranium (DU) on Atlantic salmon (Salmo salar ). Implementation of the independent action (IA) model in reanalysis of a previously published microarray gene expression dataset was performed to describe gene expression patterns of combined effects and identify key gene sets and pathways that were relevant for understanding the interactive effects of these stressors. By using this approach, 3120 differentially expressed genes (DEGs) were found to display additive effects, whereas 279 (273 synergistic, 6 antagonistic) were found to deviate from additivity. Functional analysis further revealed that multiple toxicity pathways, such as oxidative stress responses, cell cycle regulation, lipid metabolism, and immune responses were enriched by DEGs showing synergistic gene expression. A key toxicity pathway of DNA damage leading to enhanced tumorigenesis signaling is highlighted and discussed in detail as an example of how to take advantage of the approach. Furthermore, a conceptual workflow describing the integration of combined effect modeling, OMICS analysis, and bioinformatics is proposed. The present study presents a conceptual framework for utilizing OMICS data in combined effect assessment and may provide novel strategies for dealing with data analysis and interpretation of molecular responses of multiple stressors.
机译：基于毒理基因组学（OMICS）数据的经典混合毒性模型用于预测环境胁迫的综合作用仍处于起步阶段。尽管已有数项研究尝试在OMICS分析中实施混合物建模以了解应激源的低剂量相互作用，但尚不清楚如何在分子水平发生相互作用以及如何更好地将此类方法产生的结果用于未来的研究和研究。多个压力源的累积危害评估。因此，本工作旨在提出一种利用全球基因表达数据进行联合效应评估的概念性方法，如对γ射线和贫铀（DU）对大西洋鲑鱼（Salmo salar）联合效应进行评估的案例研究所示。 ）。在重新分析以前发布的微阵列基因表达数据集中执行了独立作用（IA）模型，以描述组合效应的基因表达模式，并确定与理解这些应激源的相互作用有关的关键基因集和途径。通过使用这种方法，发现3120个差异表达基因（DEG）表现出加和效应，而发现279个（273个协同作用，6个拮抗作用）与可加性背离。功能分析进一步显示，DEG丰富了多种毒性途径，例如氧化应激反应，细胞周期调控，脂质代谢和免疫反应，这些基因显示出协同的基因表达。作为如何利用该方法的一个实例，重点介绍了DNA损伤导致增强的肿瘤发生信号转导的关键毒性途径。此外，提出了一个概念性的工作流，该工作流描述了组合效果建模，OMICS分析和生物信息学的集成。本研究提出了一个在综合效应评估中利用OMICS数据的概念框架，并可能为处理数据分析和解释多种应激源的分子反应提供新颖的策略。

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  • 来源
    《Environmental Science & Technology》 |2018年第9期|5479-5489|共11页
  • 作者

    You Song; Jana Asselman; Karel A. C. De Schamphelaere; Brit Salbu; Knut Erik Tollefsen;

  • 作者单位

    Section of Ecotoxicology and Risk Assessment, Norwegian Institute for Water Research (NIVA), Gaustadalléen 21, N-0349 Oslo, Norway,Centre for Environmental Radioactivity (CERAD), Norwegian University of Life Sciences (NMBU), P.O. Box 5003, N-1432 Ås, Norway;

    Faculty of Bioscience Engineering, Laboratory of Environmental Toxicology and Aquatic Ecology (GhEnToxLab), Ghent University, Campus Coupure Building F, Second Floor, Coupure Links 653, B9000 Ghent, Belgium;

    Faculty of Bioscience Engineering, Laboratory of Environmental Toxicology and Aquatic Ecology (GhEnToxLab), Ghent University, Campus Coupure Building F, Second Floor, Coupure Links 653, B9000 Ghent, Belgium;

    Centre for Environmental Radioactivity (CERAD), Norwegian University of Life Sciences (NMBU), P.O. Box 5003, N-1432 Ås, Norway;

    Section of Ecotoxicology and Risk Assessment, Norwegian Institute for Water Research (NIVA), Gaustadalléen 21, N-0349 Oslo, Norway,Centre for Environmental Radioactivity (CERAD), Norwegian University of Life Sciences (NMBU), P.O. Box 5003, N-1432 Ås, Norway;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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