Advancing Protein Identification for Imaging Mass Spectrometry for Pathology

推进病理学成像质谱的蛋白质鉴定

基本信息

批准号：
8314708
负责人：
MARSHALL Wayne BERN
金额：
$ 34.86万
依托单位：
PROTEIN METRICS, LLC
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-09-05 至 2014-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8314708
关键词：
Adoption Algorithms Area Bioinformatics Brain Clinical Clinical Pathology Cohort Studies Complex Computer software Controlled Study Cut protein Data Development Diagnostic Digestion Disease Feasibility Studies Heart Valves Histocompatibility Testing Human Image In Situ Ions Kidney Liquid Chromatography Liver Mass Spectrum Analysis Measurable Measures Medical Imaging Methods Metric Modification Molecular Profiling Mus Pathology Peptides Phase Phosphorylation Post-Translational Protein Processing Preparation Proteins Proteomics Protocols documentation Public Health Research Research Personnel Resolution Sampling Shotguns Site Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Sum Tissue Sample Tissues Translations Work data acquisition disease diagnosis glycosylation improved in vivo instrument link protein mass analyzer next generation prognostic software development success tandem mass spectrometry tool

项目摘要

DESCRIPTION (provided by applicant): Molecular signatures collected from intact tissue sections by MALDI imaging mass spectrometry (MALDI IMS) have shown high potential for use as a prognostic or diagnostic pathology tool in the clinical setting. A major obstacle to the widespread deployment of MALDI IMS, however, is the difficulty of identifying the proteins contributing to the signatures. Researchers have tried a number of approaches, including in situ digestion, MALDI TOF/TOF tandem mass spectrometry, and top-down proteomics on specific image regions. In preliminary work, we have obtained promising experimental results using top-down proteomics on intact proteins in the 2 - 20 kDa range. However, the lack of successful algorithms and software to identify the proteins in IMS mass signatures poses a major bottleneck. In particular, available top-down proteomics software relies heavily on high-accuracy mass spectrometry. The requirement for high accuracy precludes the use of some of the most sensitive mass analyzers such as linear ion traps, especially useful for these very small and complex samples. Protein Metrics Inc. is a new software company building on six years of algorithms and software research at Palo Alto Research Center. We plan to extend Byonic, our next- generation proteomics search engine, to intact proteins up to about 20 kDa. For proteins larger than 20 kDa, we will also build software for middle-down proteomics, specifically for assembling large peptides (2 - 20 kDa) produced by limited digestion to recover the identity of the intact proteins observed in IMS. The proposed Phase I feasibility study will allow us to perform controlled studies to determine the best experimental and bioinformatics approaches. Phase II will then build commercial-grade software. The proposed project will advance the state of the art in imaging mass spectrometry. Translation of imaging mass spectrometry to routine clinical pathology use will advance the state-of-the-art in disease diagnosis and treatment, and advance medical imaging and public health. PUBLIC HEALTH RELEVANCE: The project will develop commercial software that will improve our ability to identify the proteins and modifications represented in imaging mass spectrometry molecular signatures. Project success will make imaging mass spectrometry much more useful as a clinical pathology tool.

描述（由申请人提供）：通过 MALDI 成像质谱 (MALDI IMS) 从完整组织切片收集的分子特征已显示出在临床环境中用作预后或诊断病理学工具的巨大潜力。然而，MALDI IMS 广泛部署的一个主要障碍是难以识别有助于签名的蛋白质。研究人员尝试了多种方法，包括原位消化、MALDI TOF/TOF 串联质谱法以及针对特定图像区域的自上而下的蛋白质组学。在初步工作中，我们使用自上而下的蛋白质组学对 2 - 20 kDa 范围内的完整蛋白质进行了有希望的实验结果。然而，缺乏成功的算法和软件来识别 IMS 质量特征中的蛋白质构成了主要瓶颈。特别是，可用的自上而下的蛋白质组学软件在很大程度上依赖于高精度质谱分析。对高精度的要求使得无法使用一些最灵敏的质量分析仪，例如线性离子阱，这对于这些非常小的和复杂的样品特别有用。 Protein Metrics Inc. 是一家新的软件公司，建立在帕洛阿尔托研究中心六年的算法和软件研究基础上。我们计划将下一代蛋白质组学搜索引擎 Byonic 扩展到高达约 20 kDa 的完整蛋白质。对于大于 20 kDa 的蛋白质，我们还将构建中下蛋白质组学软件，专门用于组装通过有限消化产生的大肽（2 - 20 kDa），以恢复 IMS 中观察到的完整蛋白质的身份。拟议的第一阶段可行性研究将使我们能够进行对照研究，以确定最佳的实验和生物信息学方法。第二阶段将构建商业级软件。拟议的项目将推动成像质谱技术的发展。将成像质谱技术转化为常规临床病理学应用将促进疾病诊断和治疗的最先进水平，并促进医学成像和公共卫生。公共健康相关性：该项目将开发商业软件，以提高我们识别成像质谱分子特征中所代表的蛋白质和修饰的能力。项目的成功将使成像质谱作为临床病理学工具更加有用。