New Tools for Metabolite Identification and Quantitation

代谢物鉴定和定量的新工具

• 批准号: 9430743
• 负责人: Habtom W Ressom
• 金额: $ 10.89万
• 依托单位: GEORGETOWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-19 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9430743
• 关键词: Algorithms; Biochemical Pathway; Biological; Coupled; Data; Detection; Disease; Evaluation; Ions; Knowledge; Libraries; Lipids; Mass Fragmentography; Measurement; Methods; Monitor; Network-based; Organism; Phenotype; Reaction; Research Personnel; Sampling; Software Tools; Specific qualifier value; Time; base; biomarker discovery; design; experimental study; indexing; innovation; liquid chromatography mass spectrometry; metabolomics; prevent; selected ion monitoring; success; tool

PROJECT SUMMARY Targeted metabolomics offers a sensitive and accurate platform to compare the levels of pre-specified metabolites in biological samples. In particular, the use of selected ion monitoring (SIM) and selected reaction monitoring (SRM) has become an ideal method for quantitative analysis of metabolite targets using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS), respectively. Although targeted metabolomics allows more sensitive and accurate measurements than untargeted metabolomics, the ability to determine the identity of most of the potential targets from untargeted studies as well as the lack of tools for designing targeted experiments have been a challenge for researchers aiming to conduct large-scale targeted metabolomic studies. Our team recently developed a software tool (MetaboSearch) for metabolite identification and an R-package SIMAT for designing targeted metabolomics experiments by GC-SIM-MS and analyzing the resulting data. In this application, we propose to develop: (1) an R-package metID for a network-based prioritization of putative metabolite IDs identified by mass-based search tools such as MetaboSearch; and (2) an R-package SRMAT that selects optimal transitions for targeted metabolomic experiments by LC-SRM-MS. Together with MetaboSearch, metID will enable users to prioritize putative metabolite IDs for analytes that may be associated with disease based on findings from previous untargeted metabolomic studies. For highly-scored putative metabolite IDs, SIMAT and SRMAT will choose transitions and retention times/indices for targeted experiments by GC-SIM-MS and LC-SRM-MS, respectively, and perform quantitation of the levels of target metabolites. Successful implementation of the proposed suite of tools will enable researchers to capitalize on the power of targeted metabolomics for accurate evaluation of the levels of promising metabolites in biological samples to uncover the relationships of the metabolites with the phenotypes of the samples.

项目摘要 靶向代谢组学提供了一个敏感而准确的平台，以比较预先指定的水平 生物样品中的代谢产物。特别是，使用选定的离子监测（SIM）和选定的反应 监测（SRM）已成为使用气体定量分析代谢物靶标的理想方法 色谱 - 质量光谱法（GC-MS）和液相色谱 - 质谱法（LC-MS）， 分别。尽管针对目标的代谢组学允许比 未靶向的代谢组学，确定来自未靶向的大多数潜在目标的身份的能力 研究以及缺乏设计目标实验的工具对研究人员来说是一个挑战 旨在进行大规模的靶向代谢组学研究。我们的团队最近开发了一个软件工具 （MetaboSearch）用于代谢物识别和用于设​​计目标代谢组学的R包装SIMAT 通过GC-SIM-MS进行实验并分析所得数据。在此应用程序中，我们建议开发：（1） R包装METID用于基于网络的优先级，用于通过质量搜索确定的推定代谢物ID 诸如MetaBosearch之类的工具； （2）选择目标的最佳过渡 LC-SRM-MS代谢组实验。 METID与MetaBosearch一起，将使用户优先级 根据以前的发现，可能与疾病相关的分析物的推定代谢物ID 非靶向代谢组学研究。对于高得分的推定代谢物ID，Simat和SRMAT将选择 GC-SIM-MS和LC-SRM-MS的靶向实验的过渡和保留时间/指数， 并执行靶代谢物水平的定量。成功实施拟议的套件 工具将使研究人员能够利用目标代谢组学的力量，以准确评估 生物样品中有希望的代谢物的水平，以发现代谢物与 样品的表型。