HIGH-THROUGHPUT PROTEOMIC ANALYSIS OF SIGNALING PATHWAYS

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目和 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 质谱分析中的新兴方法通过应用于药理学和细胞生物学中持续存在的难题而发挥其效用。质谱仪能够在复杂的肽混合物中指定磷酸化位点，这为极大地加速信号通路的阐明提供了独特的机会。 在这里，我们建议开发一种磷酸蛋白质组技术平台，能够自动分析全细胞裂解物的磷酸化位点。 我们将利用这个平台来辨别与肥大细胞和肝细胞癌（HCC）信号传导相关的信号传导通路的架构。新型信号传导通路成员的鉴定将为合理开发选择性抑制该通路的药物提供靶标。 拟议新研究的长期目标是：（1）利用最先进的质谱技术平台来确定所有蛋白质、其磷酸化位点以及细胞信号传导中涉及的磷酸化的时间和空间模式； (2) 提高复杂细胞裂解物中极低丰度信号分子的检测灵敏度； (3) 开发用于可视化、组织和存储大型磷酸化蛋白质组数据集的生物信息学工具。 我们的具体目标是（1）部署一个技术平台来确定信号通路相关的磷酸化事件并说明其与肥大细胞激活的可行性； (2) 鉴定对肝癌细胞增殖和迁移至关重要的关键磷酸化事件； (3) 开发并彻底测试我们的磷酸化蛋白质组平台的生物信息学和分析改进。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Emerging methodologies in mass spectrometry derive their utility through application to persistent, difficult problems in pharmacology and cellular biology. The ability of the mass spectrometer to assign sites of phosphorylation in complex mixtures of peptides represents an unique opportunity to greatly accelerate the elucidation of signaling pathways. Here we propose the development of a phosphoproteomic technology platform capable of the automated analysis of sites of phosphorylation derived from whole cell lysates. We will exploit this platform to discern the architecture of signaling pathways relevant to mast cell and hepatocellular carcinoma (HCC) signaling. Identification of novel signaling pathway members will provide targets for rational development of drugs that selectively inhibit the pathways. The long term goals of the proposed new studies are: (1) to exploit a state-of-the-art mass spectrometry technology platform to determine all of the proteins, their sites of phosphorylation, and the temporal and spatial pattern of phosphorylation involved in cell signaling; (2) to increase the sensitivity of detection of extremely low abundance signaling molecules from complex cell lysates; (3) to develop bioinformatic tools for the visualization, organization, and storage of large phosphoproteomic data sets. Our specific aims are (1) to deploy a technology platform to determine the signaling pathway-related phosphorylation events and illustrate its viability with mast cell activation; (2) to identify the key phosphorylation events important in HCC cell proliferation and migration; (3) to develop and thoroughly test bioinformatic and analytical improvements to our phosphoproteomic platform.