Mega-scale Identification tools for xenobiotic metabolism

项目摘要 人类进化创造了复杂的新陈代谢系统，以转化和消除潜在的有害物质。 我们接触的化学物质。现有的证据表明，这些系统产生了100万或 更多不同的化学代谢物，其中大部分是完全未知的。广泛使用质量 基于光谱的代谢组学方法表明，许多未识别的质谱特征， 与人类疾病密切相关。大量的流行病学研究表明， 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。我们有一个既定的和成功的人类麻烦 该研究中心致力于提高对环境对疾病影响的认识。的 目前的建议是在此基础上开发强大的新化学鉴定工具， 可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令人头疼的研究团队，他们拥有质谱分析、异生物质 代谢，计算化学和机器人方法，以开发和测试新的化学鉴定 鉴定成千上万种外来化学代谢物的工具。我们的方法依赖于专业知识， 1)计算化学预测可能的异生物质代谢物、各自的加合物形式和离子 质谱中的解离模式，2）酶和细胞异生素生物转化的使用 系统，其允许创建含有特定生物转化系统的多孔板，以产生 异源代谢物，3）离子碎裂质谱和NMR光谱方法，以确认 化学特性和4）机器人系统的专业知识，可用于扩展方法以识别 成千上万的环境化学物质的代谢产物。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， 利益相关者参与和计划协调中心（SEPCC）。实验核心 将开发并提供超高分辨率质谱分析的化合物鉴定能力 支持.计算核心将开发一个预测的异生物质代谢物数据库，以支持 代谢物鉴定管理核心将与HERCULES Exposome保持互动 研究中心并支持与潜在核心用户的互动。设立军事委员会是为了监测 朝着建立化合物鉴定工具的目标取得进展，这些工具可以扩展到鉴定数百种 数以千计的外来化学代谢物这些结果将通过提供新的 识别环境化学物质未知代谢物的方法，并支持识别更广泛的 一系列药物、食物、微生物组、膳食补充剂和商业产品的代谢物。

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.