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，从而阻碍了决策。此外，与当前测试方法相关的时间、所需资源和伦理问题（使用大量活体动物）使得它们在当前监管要求的背景下不切实际，这些监管要求要求对社会使用的数千种化学品进行测试。为了解决这些问题，现在越来越多地努力使用机械数据来支持风险评估，因为它可以更经济地产生。已经提出的一种方法是adverse outcome pathway （AOP）。AOPs是一个概念性框架，它在分子扰动和调控相关的不良结果之间建立了生物学上合理的联系。AOPs适用于所有物种，不具有化学特异性。迄今为止，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，基因表达变化是否真的能预测蛋白质的改变仍然不确定，而蛋白质的改变是生物体适应性的更重要的代表。这个项目将建立在我过去的研究基础上，通过整合全转录组和全蛋白质组分析来建立先进的aop。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，这将提供分子终点变化的定量和功能评估，作为对生物体适应性影响的指标。这将允许识别关键基因，这些基因可以用作鱼类污染物风险评估中的相关生物标志物。此外，这种组合分析方法将为靶基因在基线和应激条件下转化为功能蛋白提供新的见解。为了将研究转移到北方生态系统中感兴趣的物种，将研究加拿大本土的4种鱼类（虹鳟鱼、黑头鲦鱼、湖鳟鱼和白鲟鱼）。该项目将重点关注与石油和天然气（苯并[a]芘）、采矿（硒）和城市污水（炔雌醇）部门有关的3种令人关注的化学品。该项目产生的数据和工具将为科学家、监管机构和工业界提供关键信息，以满足他们的测试要求，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、更经济和更道德的评估。

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.