Developing Metabolomic Technologies to Advance Environmental Exposure Analysis

开发代谢组学技术以推进环境暴露分析

• 批准号: 9754149
• 负责人: Gary J Patti
• 金额: $ 76.11万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-15 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9754149
• 关键词: Address; Adverse effects; Biochemical; Biochemical Pathway; Biological; Blood; Chemical Exposure; Chemicals; Development; Disease; Embryo; Environment; Environmental Exposure; Environmental Health; Goals; Health; Human; Laboratories; Lead; Measures; Metabolism; Mission; Molecular; Names; Organ; Pathway interactions; Phenotype; Play; Research; Resources; Role; Signal Transduction; Technology; Testing; Zebrafish; human disease; human subject; insight; interest; liquid chromatography mass spectrometry; metabolome; metabolomics; metabolomics resource; new technology; novel; prevent; programs; response; small molecule; toxicant

Project Summary Environmental exposures play a leading role in the development of human disease and are therefore of significant interest, but measuring the myriad of environmental exposures encountered over a lifetime is an immense challenge. Even more complicated is identifying the molecular pathways disrupted by each environmental exposure encountered. Yet, progress on both of these challenges is ultimately fundamental to understanding the contribution of the environment to human health. The overarching mission of my research program is to address this critical need by developing and applying novel metabolomic technologies. Metabolomics is a relatively new analytical approach that is ideally suited to help address these formidable challenges because it comprehensively profiles small molecules of both exogenous and endogenous origin. In practice, however, metabolomics has not fulfilled its potential in the environmental health sciences. Its application has been severely limited due to the tens of thousands of signals detected by liquid chromatography/mass spectrometry (LC/MS) that cannot be identified. Without biochemically naming the metabolomic signals, biological inference is compromised and insights into exposure chemicals or effect mechanisms are prevented. The major goal of my research program is to overcome this barrier in metabolomics to (1) enable unprecedented exposure analysis in humans and (2) to discover toxicant effect mechanisms by using zebrafish. First, with new technologies that my laboratory has developed, we will name each signal detected by LC/MS untargeted metabolomics from human blood and the zebrafish embryo. This will constitute the human and zebrafish “reference metabolomes”. We will then develop a resource to automate identification and quantitation of each metabolite in the reference metabolomes. Second, we will screen the zebrafish reference metabolome to identify effect mechanisms of specific toxicants known to have adverse effects on only a single zebrafish organ. We will test our hypothesis that each organ’s metabolism is similarly disrupted by some toxicants, but that their unique phenotypic responses reflect organ-specific sensitivities to particular pathways. Thus, in addition to building a metabolomics resource that will greatly enhance exposure analysis in human subjects, we also expect that the application of our platform to zebrafish will identify toxicant effect mechanisms and establish biochemical pathways that contribute to particular phenotypes.

项目摘要 环境暴露在人类疾病的发展中起着主导作用，因此 非常感兴趣，但衡量一生中遇到的无数环境暴露是 巨大的挑战。更复杂的是确定它们扰乱的分子通路 遇到环境暴露。然而，在这两个挑战上取得进展最终对 了解环境对人类健康的贡献。我研究的首要任务是 该计划旨在通过开发和应用新的代谢组学技术来满足这一关键需求。 代谢组学是一种相对较新的分析方法，非常适合帮助解决这些令人敬畏的问题 挑战，因为它全面描述了外源和内源来源的小分子。在……里面 然而，在实践中，代谢组学并没有发挥其在环境健康科学中的潜力。它的 由于液体检测到的数以万计的信号，应用受到了严重的限制 无法鉴定的色谱/质谱仪(LC/MS)。在没有生化命名的情况下 代谢信号，生物推断受到损害，对接触化学物质或影响的洞察 机制是被阻止的。我的研究计划的主要目标是在 代谢组学：(1)实现人类前所未有的暴露分析；(2)发现毒物效应 通过使用斑马鱼的机制。 首先，使用我的实验室开发的新技术，我们将命名由 人血和斑马鱼胚胎的LC/MS非靶向代谢组学。这将构成人类 以及斑马鱼的“参考代谢体”。然后，我们将开发一种资源来自动识别和 测定参比代谢物中各代谢物的含量。第二，我们将筛选斑马鱼的参考 代谢组学以确定已知仅对单个毒物有不良影响的特定毒物的作用机制 斑马鱼器官。我们将检验我们的假设，即每个器官的新陈代谢类似地被一些 但它们独特的表型反应反映了器官对特定途径的敏感性。 因此，除了建立代谢组学资源将极大地增强人类暴露分析 受试者，我们也期待我们的平台在斑马鱼上的应用将识别有毒效应 机制，并建立有助于特定表型的生化途径。