Mega-scale Identification tools for xenobiotic metabolism

外源代谢的大规模鉴定工具

• 批准号: 9769022
• 负责人: Dean Paul Jones
• 金额: $ 88.92万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9769022
• 关键词: Address; Automation; Biochemical; Bioinformatics; Biological; Cells; Chemical Structure; Chemicals; Clinical Sciences; Communities; Complex; Databases; Detection; Development; Disease; Dissociation; Drug Metabolic Detoxication; Educational workshop; Environment; Environmental Health; Enzymes; Evolution; Food; Foundations; Genes; Goals; Grant; Human; Human body; Institutes; Ions; Mass Spectrum Analysis; Metabolic; Metabolic Biotransformation; Metabolism; Methods; Monitor; NMR Spectroscopy; National Institute of Environmental Health Sciences; Organism; Pattern; Pharmaceutical Preparations; Preparation; Process; Production; Proteins; Publications; Research; Research Infrastructure; Research Support; Resolution; Robotics; Scientist; Services; Structure; Subcellular Fractions; System; Testing; Time; Training; Translational Research; United States National Institutes of Health; Xenobiotic Metabolism; Xenobiotics; adduct; base; biological systems; computational chemistry; design; dietary supplements; environmental chemical; epidemiology study; human disease; improved; metabolomics; microbiome; organizational structure; outreach; programs; prospective; public health relevance; robotic system; scale up; small molecule libraries; stable isotope; symposium; tool; tool development; ultra high resolution

Project Summary Human evolution has created complex metabolism systems to transform and eliminate potentially harmful chemicals to which we are exposed. Available evidence indicates that these systems generate a million or more different chemical metabolites, most of which are completely uncharacterized. Widespread use of mass spectrometry-based metabolomics methods shows that many unidentified mass spectral features are significantly associated with human diseases. Substantial epidemiological research implicates environmental contributions to many disease processes, and we believe that many of the unidentified mass spectral features are metabolites of environmental chemicals. We have an established and successful human exposome research center focused on improving the understanding of environmental contributions to disease. The present proposal is to build upon this foundation to develop powerful new chemical identification tools that can be scaled to identify hundreds of thousands of foreign chemical metabolites in the human body. We have assembled an exposome research team of analytical scientists with expertise in mass spectrometry, xenobiotic metabolism, computational chemistry and robotic methods, to develop and test new chemical identification tools to identify hundreds of thousands of foreign chemical metabolites. Our approach relies upon expertise in 1) computational chemistry to predict possible xenobiotic metabolites, respective adduct forms and ion dissociation patterns in mass spectrometry, 2) use of enzymatic and cellular xenobiotic biotransformation systems, which allows creation of multi-well panels containing specific biotransformation systems to generate xenobiotic metabolites, 3) ion fragmentation mass spectrometry and NMR spectroscopy methods to confirm chemical identities and 4) expertise with robotic systems which can be used to scale the approach to identify hundreds of thousands of metabolites of environmental chemicals. An Administrative Core will maintain an organizational structure and coordinate activities between the Experimental Core and the Computational Core, NIH and the Stakeholder Engagement and Program Coordination Center (SEPCC). The Experimental Core will develop and provide compound identification capability with ultra-high-resolution mass spectrometry support. The Computational Core will develop a predicted xenobiotic metabolite database to support metabolite identification. The Administrative Core will maintain interactions with HERCULES Exposome Research Center and support interactions with prospective Core users. Milestones are established to monitor progress toward goals to establish tools for compound identification that can be scaled to identify hundreds of thousands of foreign chemical metabolites. The results will catalyze metabolomics research by providing new ways to identify unknown metabolites of environmental chemicals, and also support identification of a broader range of metabolites of drugs, food, microbiome, dietary supplements and commercial products.

项目摘要 人类进化创造了复杂的代谢系统，以改变和消除潜在的有害 我们暴露的化学物质。可用证据表明，这些系统产生了100万或 更多不同的化学代谢产物，其中大多数是完全未表征的。广泛使用质量 基于光谱法的代谢组学方法表明，许多身份不明的质谱特征是 与人类疾病显着相关。大量的流行病学研究暗示了环境 对许多疾病过程的贡献，我们认为许多身份不明的质谱特征 是环境化学物质的代谢物。我们有一个既定而成功的人类博览会 研究中心的重点是改善对疾病的环境贡献的理解。这 目前的建议是建立在这个基础的基础上，以开发强大的新化学识别工具可以 缩放以识别人体中数十万个外国化学代谢产物。我们有 组建了一个具有分析科学家的外界研究团队，具有质谱专业知识，异种生物生物学 代谢，计算化学和机器人方法，开发和测试新的化学识别 识别成千上万的外国化学代谢产物的工具。我们的方法依赖于专业知识 1）计算化学以预测可能的异种生物代谢物，各自的加合物形式和离子 质谱法中的解离模式，2）使用酶和细胞异种生物转化 系统，允许创建包含特定生物转化系统的多孔面板生成 异生物代谢物，3）离子碎片质谱法和NMR光谱法以确认 化学身份和4）具有机器人系统的专业知识，可用于扩展方法以识别 数十万个环境化学品的代谢产物。行政核心将保持 组织结构和协调实验核心与计算核心之间的活动， NIH和利益相关者参与与计划协调中心（SEPCC）。实验核心 将开发并提供具有超高分辨率质谱法的复合识别能力 支持。计算核心将开发一个预测的异生物代谢物数据库以支持 代谢物鉴定。行政核心将维持与大力神的互动 研究中心并支持与潜在核心用户的互动。建立了里程碑以监视 朝着建立复合识别工具的目标迈进，可以缩放以识别数百个 数千种外国化学代谢产物。结果将通过提供新的新代谢组学研究来促进代谢组学研究 识别未知代谢物的环境化学物质的方法，并支持更广泛的识别 药物，食物，微生物组，饮食补充剂和商业产品的代谢物范围。