Instrumentation Development: MS Array for Quantitative Proteomics

仪器开发：用于定量蛋白质组学的 MS 阵列

• 批准号: 8084749
• 负责人: James Edward Bruce
• 金额: $ 42.52万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-01 至 2015-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8084749
• 关键词: Address; Advanced Development; Base Pairing; Biological; Cardiovascular Diseases; Cell physiology; Cells; Communities; Complex; Cyclotrons; Data; Data Analyses; Detection; Development; Device or Instrument Development; Diagnosis; Disease; Future; Gene Expression; Genes; Genome; Genomics; Goals; Human; Individual; Ions; Lead; Liquid substance; Malignant Neoplasms; Mass Spectrum Analysis; Measurement; Measures; Methods; Mind; Molecular; Pathway interactions; Pattern; Peptide Fragments; Peptides; Population; Post-Translational Protein Processing; Process; Proteins; Proteome; Proteomics; Research; Resolution; Role; Sampling; Scanning; Scheme; Serum; Signal Transduction; Speed; System; Technology; Technology Transfer; Time; base; biological systems; computerized data processing; functional outcomes; gene function; genome sequencing; human disease; improved; insight; instrument; instrumentation; liquid chromatography mass spectrometry; mass spectrometer; multiple reaction monitoring; nervous system disorder; new technology; normal aging; novel; physical property; prevent; protein expression; research study; stem

DESCRIPTION (provided by applicant): The study of human diseases at the molecular level has benefitted greatly by rapid advances in technology for genome sequencing. However, major impediments for effective utilization of current and future genomic information relates to the major challenges that are inherent in functional assignment of genes. The field of proteomics has arisen to help address this need, since proteins are the predominant functional outcome of gene expression. Measurement of proteomic content, including protein expression levels, posttranslational modifications and protein interactions can yield critical insight relevant to gene function. The major challenges in proteomics research relate to the complexity of samples and the dynamic range over which measurements must be performed. In general terms, these demands are far greater than encountered in genomics since, protein abundances can vary much more than gene do, proteins have much wider diversity in physical properties than genes do, and proteins have no means for signal amplification, nor analogous Watson-Crick base pairing as genes do. Thus the field of proteomics employs technology largely based on mass spectrometry measurements of peptides since these measurements have shown capabilities for large-scale protein identification and quantitation. However, since each protein can produce on average, 50-100 peptides, measurements of peptide mixtures are far more complex than measurements on proteins. In addition, current data-dependent measurement strategies lead to significant compression of achievable dynamic range, since such MS/MS measurements are only normally feasible on peptides observed with higher abundance. Ideally, every peptide in a proteome-wide digest would be subjected to MS/MS to gain maximal information from proteomics experiments. This project will advance capabilities for large-scale proteomics through the development of a mass spectrometer array capable of MS/MS acquisition an order of magnitude faster than current state-of-the art technology. The MS array technology to be developed under this project will involve ion cyclotron resonance mass spectrometry that will yield higher mass resolving power, higher mass measurement accuracy as well as higher throughput acquisition. As a result, an order of magnitude or more peptides can be identified during a given experiment which will dramatically increase the information content of each proteomics analysis as well as the dynamic range of proteins that can be studied. PUBLIC HEALTH RELEVANCE: Proteins are the functional molecules in all important processes in disease and normal healthy state. This project will develop new technology that will enable improved understanding of human diseases such as cancer, cardiovascular disease, and neurological diseases by allowing identification of at least an order of magnitude more proteins, posttranslational modifications and protein interactions in human cells, serum and other biological fluids.

描述（申请人提供）：基因组测序技术的快速发展极大地促进了分子水平上的人类疾病研究。然而，有效利用当前和未来基因组信息的主要障碍涉及基因功能分配中固有的主要挑战。蛋白质组学领域的出现有助于解决这一需求，因为蛋白质是基因表达的主要功能产物。蛋白质组学内容的测量，包括蛋白质表达水平，翻译后修饰和蛋白质相互作用，可以产生关键的洞察力相关的基因功能。蛋白质组学研究的主要挑战涉及样品的复杂性和必须进行测量的动态范围。一般来说，这些需求远远大于基因组学中遇到的，因为蛋白质丰度的变化可能比基因的变化大得多，蛋白质在物理性质上的多样性比基因的多样性大得多，蛋白质没有信号放大的手段，也没有类似的沃森-克里克碱基配对。因此，蛋白质组学领域主要采用基于肽的质谱测量的技术，因为这些测量已经显示出大规模蛋白质鉴定和定量的能力。然而，由于每种蛋白质平均可以产生50-100种肽，因此肽混合物的测量比蛋白质的测量复杂得多。此外，当前的数据依赖性测量策略导致可实现的动态范围的显著压缩，因为这样的MS/MS测量通常仅在以较高丰度观察到的肽上可行。理想情况下，蛋白质组范围内消化的每一个肽都将经过MS/MS，以从蛋白质组学实验中获得最大信息。该项目将通过开发能够比当前最先进技术快一个数量级的MS/MS采集的质谱仪阵列来提高大规模蛋白质组学的能力。在本项目下开发的质谱阵列技术将涉及离子回旋共振质谱法，该技术将产生更高的质量分辨能力、更高的质量测量准确度以及更高的通量采集。因此，在给定的实验期间可以鉴定数量级或更多的肽，这将显著增加每个蛋白质组学分析的信息内容以及可以研究的蛋白质的动态范围。 公共卫生相关性：蛋白质是疾病和正常健康状态中所有重要过程的功能分子。该项目将开发新技术，通过识别人类细胞、血清和其他生物液体中至少一个数量级的蛋白质、翻译后修饰和蛋白质相互作用，提高对癌症、心血管疾病和神经系统疾病等人类疾病的认识。