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加三倍四极杆质谱仪针对目标 生物标志物候选者的定量 项目摘要 代谢组学对生物样品中数千个小分子进行了全面分析。它可以 在不断增长的系统生物学方法中起着不可或缺的作用 代谢物和疾病。液相色谱与质谱（LC-MS）和气体耦合 耦合到质谱法（GC-MS）的色谱已用于高通量分析 成千上万的代谢产物。但是，许多与疾病相关的代谢产物的潜在值 在系统生物标志物发现的系统生物学方法中，使用这些平台的探索不足 由于缺乏计算工具和资源：（1）准确确定大多数分析物的身份； （2）研究由于疾病引起的代谢产物之间的重新连接相互作用； （3）整合代谢物 与其他OMICS研究的概况，以评估代谢物与该代谢之间的关系 在系统层面的疾病。部分由于这些局限性，先前识别的概括性差 已经观察到了代谢物生物标志物候选物，尤其是当它们通过独立评估时 平台和验证集。父母奖的目的是填补代谢物识别和多派的空白 通过使用系统代谢组学方法的集成，从而增强代谢组学在系统中的作用 生物标志物发现的生物学方法。具体而言，它利用多个资源（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：（1） 开发一个全面的工作流程，以对推定的代谢物ID进行排名； （2）代谢物的差分分析 代谢组学数据与蛋白质组学，糖蛋白酶学，糖蛋白质组学的概况和整合。和 磷蛋白质组学数据以识别高度有希望的代谢物生物标志物候选物。选定的候选人 通过使用独立的样本和平台进行定量评估，与用于 发现。但是，成功实施父母奖中提出的关键任务之一依赖 在一个分析平台上，对选定分析物的靶向定量分析具有高灵敏度。 为此，在此行政补充申请中，我们要求支持购买Thermo Scientific TSQ Altis加三倍四极杆质谱仪，可提供灵敏度，选择性和吞吐量 通过选定的反应监测（SRM）对分析物进行靶向定量所需。该乐器的可用性 不仅将提供急需的敏感，健壮，可靠，定量平台，而且还可以解决 由于开发所需的大量机器时间而发生的不可预见的情况 由父母奖选择的生物标志物候选者定量定量的仪器方法。