Advancing Protein Identification for Imaging Mass Spectrometry for Pathology

描述（由申请人提供）：通过MALDI成像质谱法（MALDI IMS）从完整组织切片收集的分子特征显示出在临床环境中作为预后或诊断病理工具的巨大潜力。然而，广泛部署MALDI IMS的一个主要障碍是难以识别参与签名的蛋白质。研究人员已经尝试了许多方法，包括原位消化，MALDI TOF/TOF串联质谱，以及特定图像区域的自上而下蛋白质组学。在前期工作中，我们利用自上而下的蛋白质组学方法对2 - 20 kDa范围内的完整蛋白进行了研究，获得了很好的实验结果。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是一个主要的瓶颈。特别是，现有的自上而下的蛋白质组学软件严重依赖于高精度的质谱分析。对高精度的要求排除了一些最敏感的质量分析仪的使用，如线性离子阱，特别适用于这些非常小和复杂的样品。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20kda左右的完整蛋白质。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，专门用于组装由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允许我们进行对照研究，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。将成像质谱法转化为常规临床病理学应用将推动疾病诊断和治疗的最新技术，并促进医学成像和公共卫生。

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.