Functional Omics of Native Fish Species for Improved Environmental Risk Assessment

目前旨在解决污染物对水生生态系统构成威胁的监管决策过程依赖于选定动物模型的标准化实验室测试。最近的研究(包括我的小组的研究)表明，这种方法存在巨大的不确定性，导致对当地生态系统中受关注的本地物种的风险估计不准确，从而阻碍决策。此外，与目前的检测方法相关的时间、必要的资源和伦理问题(使用大量活动物)使其在目前要求对社会使用的数千种化学品进行检测的监管任务的背景下是不切实际的。为了解决这些问题，现在越来越多地努力使用机械性数据来支持风险评估，因为它可以更经济地生成。已提出的一种方法是不良结局途径(AOP)。AOPS是一种概念性框架，在分子扰动和调节相关性的不利结果之间建立了生物学上看似合理的联系。AOPS适用于所有物种，并且不是特定于化学物质的。到目前为止，AOPS的发展依赖于使用选择的模式物种产生基因表达数据。然而，由于从基因表达到功能蛋白的大量调控步骤，仍然不确定基因表达的变化是否真的预测蛋白质的变化，而蛋白质的变化是生物体适应性的更重要的指标。这个项目将建立在我过去研究的基础上，通过整合整个转录组和整个蛋白质组分析来建立先进的AOPS。然后，这些组学结果将与生理和一般健康终点联系起来，以组装AOPS，该AOPS将提供分子终点变化的定量和功能评估，作为对有机体适应性的影响的指标。这将允许确定关键基因，这些基因可用作鱼类污染物风险评估中的相关生物标记物。此外，这种组合分析方法将为在基线和应激条件下将目标基因翻译成功能蛋白质提供新的见解。为了解决将研究转移到北部生态系统中感兴趣的物种的问题，将研究4种原产于加拿大的鱼类(虹鲑鱼、肥头小鱼、湖鲑鱼和白鲟鱼)。该项目将侧重于与石油和天然气(苯并[a]芘)、采矿(硒)和城市废水(乙烯基雌二醇)有关的3种令人关切的化学品。该项目将产生的数据和工具将为科学家、监管机构和行业提供关键信息，以满足他们的测试任务，因为它们将允许对污染物对野生动物构成的风险进行更有针对性、更可靠的经济和伦理评估。

Current regulatory decision-making processes that aim to address the threats pollutants pose to aquatic ecosystems rely on standardized laboratory tests with select animal models. Recent studies (including those by my group) have shown that there is tremendous uncertainty associated with this approach resulting in inaccurate estimates of risks to native species of concern in local ecosystems, thus hampering decision-making. Also, the time, resources necessary and ethical concerns (use of large numbers of live animals) associated with current testing approaches render them impractical in context with current regulatory mandates that require testing of thousands of chemicals used by society. To address these issues, there are now increasing efforts to use mechanistic data in support of risk assessments as it can be generated more economically. One approach that has been proposed is that of the adverse outcome pathway (AOP). AOPs are conceptual frameworks that establish biologically plausible links between molecular perturbations and adverse outcomes of regulatory relevance. AOPs are applicable across species and are not chemical specific. To date, the development of AOPs relies on the generation of gene expression data using select model species. Due to the large number of regulatory steps that lead from the expression of a gene to a functional protein, however, it remains uncertain whether gene expression changes are truly predictive of alterations of proteins, which are a more consequential proxy for the fitness of an organism. This project will build on my past research and will establish advanced AOPs by integrating whole transcriptome with whole proteome analysis. These omics outcomes will then be linked with physiological and general health endpoints to assemble AOPs that will provide a quantitative and functional assessment of the alterations of molecular endpoints as indicators of impacts on the fitness of an organism. This will allow to identify critical genes that can be used as relevant biomarkers in the risk assessment of contaminants across fishes. Also, this combinatory analytical approach will provide novel insights into the translation of target genes to functional proteins under baseline and stressed conditions. To address the transferability of the research to species of interest in northern ecosystems 4 fishes native to Canada (rainbow trout, fathead minnow, lake trout and white sturgeon) will be studied. This project will focus on 3 chemicals of concern that are relevant to the oil and gas (benzo[a]pyrene), mining (selenium), and municipal wastewater (ethinylestradiol) sectors. The data and tools to be generated by this project will provide critical information for scientists, regulators and industry to meet their testing mandates because they will allow for more targeted, reliable, economic and ethical assessments of the risks contaminants pose to wildlife.