Systems Metabolomics for Biomarker Discovery

用于生物标志物发现的系统代谢组学

• 批准号: 10581892
• 负责人: Habtom W Ressom
• 金额: $ 25万
• 依托单位: GEORGETOWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-22 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10581892
• 关键词: Address; Administrative Supplement; Award; Biological; Biological databases; Computing Methodologies; Coupled; Data; Disease; Gas Chromatography; Goals; Libraries; Liquid Chromatography; Mass Spectrum Analysis; Methods; Monitor; Network-based; Parents; Pattern; Performance; Play; Proteomics; Reaction; Research; Resources; Role; Sampling; System; Systems Biology; Time; Validation; biomarker discovery; biomarker selection; candidate marker; computerized tools; computing resources; deep learning; glycoproteomics; high throughput analysis; innovation; instrument; learning strategy; mass spectrometer; metabolomics; multiple omics; phosphoproteomics; platform-independent; programs; small molecule; tool

TSQ Altis Plus Triple Quadrupole Mass Spectrometer for Targeted Quantitation of Biomarker Candidates PROJECT SUMMARY Metabolomics offers a comprehensive analysis of thousands of small molecules in biological samples. It can play an indispensable role in the growing systems biology approaches to unravel the relationships between metabolites and diseases. Liquid chromatography coupled to mass spectrometry (LC-MS) and gas chromatography coupled to mass spectrometry (GC-MS) have been used for high-throughput analysis of thousands of metabolites. However, the potential values of many disease-associated metabolites discovered by using these platforms have been inadequately explored in systems biology approaches for biomarker discovery due to lack of computational tools and resources to: (1) accurately determine the identity of most of the analytes; (2) investigate the rewiring interactions among the metabolites due to diseases; and (3) integrate metabolite profiles with those from other omics studies to evaluate the relationships between the metabolites and the diseases at the systems level. Partly due to these limitations, poor generalizability of previously identified metabolite biomarker candidates has been observed, especially when they are evaluated through independent platforms and validation sets. The parent award aims to fill the gaps in metabolite identification and multi-omics integration by using systems metabolomics approaches that enhance the role of metabolomics in systems biology approaches for biomarker discovery. Specifically, it utilizes multiple resources (biological databases, mass spectral libraries, etc.) and innovative statistical, deep learning, and network-based methods for: (1) developing a comprehensive workflow for ranking putative metabolite IDs; (2) differential analysis of metabolite profiles and integration of metabolomics data with proteomics, glycomics, glycoproteomics. and phosphoproteomics data to identify highly promising metabolite biomarker candidates. The selected candidates are evaluated by targeted quantitation using independent samples and platforms compared to those used for discovery. However, successful implementation of one of the critical tasks proposed in the parent award relies heavily on an analytical platform that has high sensitivity for targeted quantitative analysis of selected analytes. To this end, in this administrative supplement application, we request support to purchase the Thermo Scientific TSQ Altis Plus Triple Quadrupole Mass Spectrometer, which offers the sensitivity, selectivity, and throughput needed for targeted quantitation of analytes by selected reaction monitoring (SRM). Availability of this instrument will not only provide the much needed sensitive, robust, reliable, quantitation platform but also address unforeseen circumstances that occurred due to the significant amount of machine time required to develop instrument methods for targeted quantitation of biomarker candidates selected by the parent award.

TSQ Altis Plus三重四极杆质谱仪 生物标志物候选物的定量 项目摘要 代谢组学提供了对生物样品中数千种小分子的全面分析。它可以 在不断发展的系统生物学方法中发挥着不可或缺的作用，以揭示 代谢物和疾病。液相色谱-质谱联用（LC-MS）和气相色谱法 色谱-质谱联用（GC-MS）已用于高通量分析， 成千上万的代谢物。然而，许多疾病相关代谢物的潜在价值， 在用于生物标记物发现的系统生物学方法中， 由于缺乏计算工具和资源：（1）准确地确定大多数分析物的身份; (2)研究疾病引起的代谢物之间的相互作用;（3）整合代谢物 与其他组学研究的结果进行比较，以评估代谢产物与 系统层面的疾病。部分由于这些局限性，以前确定的 已经观察到代谢物生物标志物候选物，特别是当它们通过独立的 平台和验证集。该奖项旨在填补代谢物鉴定和多组学方面的空白 通过使用系统代谢组学方法进行整合，增强代谢组学在系统中的作用 生物标记物发现的生物学方法。具体来说，它利用多种资源（生物数据库， 质谱库等）以及创新的统计、深度学习和基于网络的方法，用于：（1） 开发一个综合的工作流程，对推定的代谢物ID进行排序;（2）代谢物的差异分析 代谢组学数据与蛋白质组学、糖组学、糖蛋白组学的整合。和 磷酸蛋白质组学数据，以确定非常有前途的代谢物生物标志物候选者。选定的候选人 通过使用独立样品和平台进行靶向定量评价， 的发现然而，成功实施母公司合同中提出的关键任务之一， 主要是在分析平台上，该分析平台对于选定分析物的目标定量分析具有高灵敏度。 为此，在本行政补充申请中，我们请求支持购买Thermo Scientific TSQ Altis Plus三重四极杆质谱仪，提供灵敏度、选择性和通量 通过选择性反应监测（SRM）对分析物进行目标定量所需。本文书的提供情况 将不仅提供急需的灵敏、稳健、可靠的定量平台， 由于开发所需的大量机器时间而发生的不可预见的情况 仪器方法，用于有针对性地定量由母公司奖选择的生物标志物候选物。