Optimized Metabolite Extraction, Separation, and Identification for Metabolomics

代谢组学的优化代谢物提取、分离和鉴定

• 批准号: 8545853
• 负责人: Andrew Patterson
• 金额: $ 33.73万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-15 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8545853
• 关键词: Academia; Address; Affect; Alcohol abuse; Bioinformatics; Biological Process; Characteristics; Chemistry; Communities; Complex Mixtures; Consensus; Coupled; Data; Data Analyses; Data Quality; Databases; Diet; Discipline; Disease; Drug abuse; Drug toxicity; Ensure; European; Fatty Liver; Foundations; Future; Gas Chromatography; Goals; Healthcare Systems; Hepatic; High Pressure Liquid Chromatography; Inflammation; Institutes; Journals; Laboratories; Left; Lipids; Liquid Chromatography; Liquid substance; Liver; Liver Extract; Liver diseases; Mass Spectrum Analysis; Mechanics; Medical Research; Metabolic; Metabolic Pathway; Metabolic syndrome; Metadata; Methodology; Monitor; NMR Spectroscopy; National Cancer Institute; Nature; Necrosis; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Pattern; Peer Review; Pharmaceutical Preparations; Phase; Preparation; Prevalence; Process; Protocols documentation; Publications; Recovery; Research; Research Personnel; System; Time; Tissues; Toxic effect; Universities; Work; adduct; base; chemical fingerprinting; design; genetic manipulation; improved; interest; liver injury; metabolomics; open source; repository; research study; tool; ultra high pressure

DESCRIPTION (provided by applicant): The overall goal of this proposal is to help define key metabolic changes in the liver metabolome to aid research into a variety of diseases including hepatic steatosis, inflammation, and drug toxicity. These diseases of the liver are an increasing burden on the healthcare system with growing prevalence of obesity, type II diabetes, and drug and alcohol abuse. Metabolomics, or the study of chemical fingerprints that biological processes leave behind, is a rapidly advancing discipline that has great promise to improve our understanding of these pathological conditions. However, there remain significant gaps in our understanding of how extraction methodologies and separation approaches influence the data used in downstream chemometric analyses. Therefore, we have designed the four specific aims that address fundamentally essential aspects of any metabolomic study based on liquid chromatography coupled with mass spectrometry: extraction, separation, and identification with specific reference to the mammalian liver. We hypothesize that reproducible extraction and separation methodologies can be developed that are independent of disease state. To date, there has not been an organized, concerted effort to optimize and standardize these most essential steps when conducting a metabolomic study. While here we focus on liver tissue, these approaches will serve as a foundation for other tissues and biofluids as well as platforms including nuclear magnetic resonance spectroscopy and gas chromatography coupled with mass spectrometry. Based on the efforts of three independent laboratories with well-recognized expertise in metabolomics (Griffin Lab at the University of Cambridge and the UK Medical Research Council, Gonzalez Lab at the National Cancer Institute, and the Patterson Lab at Penn State University) we plan to systematically address and optimize each step (metabolite extraction, separation by liquid chromatography, and identification by mass spectrometry) across a range of metabolite classes, polarities and metabolic pathways, thus ensuring the delivery of high quality data to the vast array of already existing metabolomic data analysis platforms. Furthermore, in addition to publication in peer-reviewed journals, we will make our protocols and data freely available to the wider scientific community, including both academia and pharma, in an open format by making use of community-led open source facilities such as the European Bioinformatics Institute's MetaboLight (central repository for experimental metabolomics data) and the ISA-TAB initiative (a unified tool for meta data description of omic experiments).

描述（由申请人提供）：该提案的总体目标是帮助定义肝脏代谢组中的关键代谢变化，以帮助研究各种疾病，包括肝脂肪变性、炎症和药物毒性。随着肥胖、二型糖尿病以及药物和酒精滥用的流行，这些肝脏疾病给医疗保健系统带来了越来越大的负担。代谢组学，或者说对生物过程留下的化学指纹的研究，是一门快速发展的学科，有望提高我们对这些病理状况的理解。然而，我们对提取方法和分离方法如何影响下游化学计量分析中使用的数据的理解仍然存在重大差距。因此，我们设计了四个具体目标，解决基于液相色谱与质谱联用的任何代谢组学研究的基本基本方面：提取、分离和鉴定，特别是针对哺乳动物肝脏。我们假设可以开发出独立于疾病状态的可重复的提取和分离方法。迄今为止，在进行代谢组学研究时，还没有一个有组织、一致的努力来优化和标准化这些最重要的步骤。虽然我们在这里关注肝脏组织，但这些方法将作为其他组织和生物流体以及包括核磁共振波谱和气相色谱与质谱联用的平台的基础。基于三个在代谢组学方面拥有公认专业知识的独立实验室（剑桥大学和英国医学研究委员会的 Griffin 实验室、国家癌症研究所的 Gonzalez 实验室和宾夕法尼亚州立大学的 Patterson 实验室）的努力，我们计划系统地解决和优化各个步骤（代谢物提取、液相色谱分离和质谱鉴定），涵盖一系列代谢物类别、极性和质量。 代谢途径，从而确保向大量现有的代谢组数据分析平台提供高质量的数据。此外，除了在同行评审期刊上发表之外，我们还将利用社区主导的开源设施，例如欧洲生物信息学研究所的 MetaboLight（实验代谢组学数据的中央存储库）和 ISA-TAB 计划（用于元数据描述的统一工具），以开放的格式向更广泛的科学界（包括学术界和制药界）免费提供我们的方案和数据。 组学实验）。