Development of Mass Spectrometry for Multidimensional Metabolome Analysis

多维代谢组分析质谱技术的发展

• 批准号: RGPIN-2019-06159
• 负责人: Li, Liang
• 金额: $ 7.65万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=738748
• 关键词: Development; Mass; Spectrometry; Multidimensional; Metabolome

My DG research focuses on developing new analytical tools to overcome the current limitations of metabolome analysis, thereby opening new opportunities to use metabolomics for biological and medical applications. The ultimate goal of our research is to be able to analyze the whole metabolome (i.e., all the metabolites) at high temporal and spatial resolutions in biological systems (e.g., tissue, blood, and cells). One example of long-term visions is to produce a time-series of 3D-images of all metabolites from organs at different development stages, at the single cell resolution, to study spatial distributions and temporal changes of these metabolites and their functions. To reach the long-term goal, we need new ideas and tools. My lab is a leader in developing the high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) technology for very comprehensive analysis of the metabolome with high quantification accuracy and precision. We propose to advance this technology to a new level that will have breakthrough-impact on how metabolomics is used for biology studies and disease biomarker discovery. Our short-term research objectives and planned research activities include: Objective and Activity #1: Developing experimental metabolome databases (e-MDBs) for rapid metabolite identification and annotation. We will develop analytical methods to create the world's largest e-MDBs for different types of samples. An example is to create the Human e-MDB where all the metabolites from human sources including biofluids and cell lines will be detected and annotated. Objective and Activity #2: Developing a sensitive method for temporal metabolome analysis. We will develop nano-scale sample preparation methods, in combination with nanoflow LC-MS and e-MDB, to perform temporal metabolome analysis using trace amounts of samples. An example of the impact areas is for analyzing circulating tumor cells (CTCs) in blood of cancer patients for diagnosis and prognosis of cancers. Another example is to analyze 1 µL of finger blood that could be less-invasively taken over a period time for disease and health state monitoring. Objective and Activity #3: Developing a digital mass spectrometry (DMS) technique for spatial metabolome analysis. We will develop tissue cutting tools and fast LC-MS methods to analyze the metabolome of small cubic samples to produce 3D-images of thousands of detectable metabolites in tissues or organs. In summary, this DG research will allow us to create the world's largest e-MDBs for metabolomics of different types of samples, produce the world's most sensitive detection tool for metabolome analysis, and start the new research direction of DMS for 3D-imaging of thousands of metabolites with high spatial resolution. These activities will bring one major step closer to the realization of our ultimate goal. This research will also train HQP to become highly skilled and highly sought-after scientists.

我的DG研究的重点是开发新的分析工具，以克服代谢组学分析目前的局限性，从而打开新的机会，使用代谢组学的生物和医学应用。我们研究的最终目标是能够分析整个代谢组（即，所有的代谢物）在生物系统中以高的时间和空间分辨率（例如，组织、血液和细胞）。长期愿景的一个例子是以单细胞分辨率生成来自不同发育阶段器官的所有代谢物的3D图像的时间序列，以研究这些代谢物及其功能的空间分布和时间变化。为了实现长期目标，我们需要新的想法和工具。我的实验室是开发高性能化学同位素标记（CIL）液相色谱质谱（LC-MS）技术的领导者，该技术用于对代谢组进行非常全面的分析，具有高定量准确性和精度。我们的短期研究目标和计划的研究活动包括：目标和活动#1：开发实验代谢组数据库（e-MDB），用于快速代谢物鉴定和注释。我们将开发分析方法，为不同类型的样品创建世界上最大的e-MDB。例如，创建人类e-MDB，其中将检测和注释来自人类来源的所有代谢物，包括生物流体和细胞系。目的和活动#2：开发一种灵敏的时间代谢组学分析方法。我们将开发纳米尺度的样品制备方法，结合nanoflow LC-MS和e-MDB，使用痕量样品进行时间代谢组学分析。影响领域的一个例子是分析癌症患者血液中的循环肿瘤细胞（CTC），用于癌症的诊断和预后。另一个例子是分析1微升的手指血，可以在一段时间内以较低的侵入性采集，用于疾病和健康状态监测。目标和活动#3：开发用于空间代谢组分析的数字质谱（DMS）技术。我们将开发组织切割工具和快速LC-MS方法来分析小立方体样品的代谢物组，以产生组织或器官中数千种可检测代谢物的3D图像。总之，这项DG研究将使我们能够创建世界上最大的e-MDB，用于不同类型样品的代谢组学，生产世界上最灵敏的代谢组学分析检测工具，并启动DMS的新研究方向，以高空间分辨率对数千种代谢物进行3D成像。这些活动将使我们更接近实现我们的最终目标。这项研究还将培养HQP成为高技能和备受追捧的科学家。