Mega-scale Identification tools for xenobiotic metabolism

外源代谢的大规模鉴定工具

• 批准号: 9981744
• 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/9981744
• 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.

项目概要 人类进化创造了复杂的新陈代谢系统来转化和消除潜在的有害物质 我们接触到的化学物质。现有证据表明这些系统产生了一百万或 更多不同的化学代谢物，其中大多数完全没有特征。质量的广泛使用 基于光谱分析的代谢组学方法表明，许多未识别的质谱特征是 与人类疾病密切相关。大量流行病学研究表明环境 对许多疾病过程的贡献，我们相信许多未识别的质谱特征 是环境化学物质的代谢物。我们拥有成熟且成功的人体暴露试验 研究中心致力于提高人们对环境对疾病影响的认识。这 目前的建议是在此基础上开发强大的新型化学品识别工具，这些工具可以 可以扩展以识别人体内数十万种外来化学代谢物。我们有 组建了一个由分析科学家组成的暴露组研究团队，他们具有质谱、外源性物质的专业知识 新陈代谢、计算化学和机器人方法，开发和测试新的化学鉴定 识别数十万种外来化学代谢物的工具。我们的方法依赖于以下方面的专业知识 1) 计算化学来预测可能的外源代谢物、各自的加合物形式和离子 质谱法中的解离模式，2) 使用酶促和细胞外源生物转化 系统，它允许创建包含特定生物转化系统的多孔面板，以产生 外源代谢物，3）离子碎裂质谱和核磁共振波谱方法确认 化学特性和 4) 机器人系统的专业知识，可用于扩展识别方法 数十万种环境化学物质的代谢物。行政核心将维持 实验核心和计算核心之间的组织结构和协调活动， NIH 和利益相关者参与和项目协调中心 (SEPCC)。实验核心 将开发并提供超高分辨率质谱的化合物识别能力 支持。计算核心将开发一个预测的外源代谢物数据库来支持 代谢物鉴定。行政核心将与 HERCULES Exposome 保持互动 研究中心并支持与潜在核心用户的互动。设立里程碑来监控 在建立化合物鉴定工具的目标方面取得进展，这些工具可以扩展以鉴定数百种 数千种外来化学代谢物。研究结果将通过提供新的方法来促进代谢组学研究 识别环境化学品未知代谢物的方法，并支持更广泛的识别 药物、食品、微生物组、膳食补充剂和商业产品的一系列代谢物。