Proteomics Core

蛋白质组学核心

基本信息

批准号：
10428137
负责人：
ARTHUR Robert SALOMON
金额：
$ 14.53万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-07-15 至 2027-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10428137
关键词：
Affinity Chromatography Alleles Amino Acids Biochemical Biological Assay CBLB gene CD8B1 gene Cell Culture Techniques Cell Line Cell physiology Cells Cellular Structures Collaborations Collection Computer Analysis Computer Models Coupled Custom Data Data Set Detection Effectiveness Evaluation Event Feedback Funding Generations Guanine Nucleotide Exchange Factors High Pressure Liquid Chromatography Immunology Infrastructure Knowledge Label Mass Spectrum Analysis Mediating Methods Modernization Molecular Mus Nature PTPRC gene Paper Pathologic Peptides Peripheral Phase Phosphopeptides Phosphorylation Phosphorylation Site Phosphotyrosine Post-Translational Protein Processing Process Property Protein Analysis Proteins Proteome Proteomics Publications Publishing Receptor Signaling Research Personnel Role Sampling Signal Pathway Signal Transduction Signaling Protein Site Source Speed Stable Isotope Labeling Statistical Data Interpretation Stimulus Structure System T-Cell Receptor T-Lymphocyte Techniques Therapeutic Intervention Time Tyrosine Tyrosine Phosphorylation Site Universities ZAP-70 Gene analog base computational suite computerized tools data acquisition data analysis pipeline design experimental study improved instrument intermolecular interaction liquid chromatography mass spectrometry mass spectrometer mutant nanofabrication new technology novel phosphoproteomics programs protein profiling protein protein interaction protein purification recruit response senior faculty src Homology Region 2 Domain tool

项目摘要

ABSTRACT – PROTEOMICS CORE Signaling networks are crucial for the orchestration of cellular functions in response to stimuli. Knowledge of the structure of these networks provides a basis for understanding the pathological consequences of their malfunction and offers opportunities for designing therapeutic interventions. The complexity of these networks and the speed with which signals are transmitted in cells makes mapping them a formidable challenge. The typical approach for elucidating the structure of cellular signaling networks involves an iterative process of creating signaling protein disruptions, domain mutants and site-directed mutants followed by characterization of each mutant through a battery of cellular activation assays. As a complementary approach, modern proteomic methods using quantitative mass spectrometry can facilitate the hypothesis-driven characterization of signaling pathways by providing a global view of cellular phosphorylation and protein-protein interactions through a variety of activation states. The Core B, Proteomics core will make cutting-edge, quantitative proteomic capabilities and computational analysis available to the investigators of this program project. The core will provide identification and relative quantitation of the protein composition and post-translational modification state of proteins using modern LC/MS techniques. This core has a strong track record of fruitful collaboration with the PI's of the program project culminating in the generation of 7 large phosphoproteomic and 8 CoIP-LCMS protein interaction datasets and publication of collaborative papers which elucidated the molecular details of how ZAP-70 is recruited to LAT and how the catalytic activity of ZAP-70 mediates basal signaling and negative feedback of T cell receptor signaling. The core has recently developed new technologies for the characterization of protein interaction networks in living cells using TurboID and the deepest possible characterization of phosphorylation networks using Src SH2 domain Superbinder and TMT BOOST channels. These newly developed methods will be leveraged to support the project PIs to determine protein-protein interactors and phosphorylation sites from T cell lines and primary mouse T cells. The core also has a suite of computational tools to provide rigorous statistical analysis of the proteomic data and to make new signaling pathway predictions.

摘要 - 蛋白质组学核心信号网络对于响应刺激的响应细胞功能的编排至关重要。知识这些网络的结构提供了理解其病理后果的基础故障并提供设计治疗干预措施的机会。这些网络的复杂性信号在单元格中传输的速度使它们成为巨大的挑战。这阐明细胞信号网络结构的典型方法涉及一个迭代过程创建信号蛋白质破坏，域突变体和位置突变体，然后进行表征每个突变体通过一系列细胞激活测定法。作为一种完整的方法，现代使用定量质谱法的蛋白质组学方法可以促进假设驱动的表征信号通路通过提供细胞磷酸化和蛋白质 - 蛋白质相互作用的全局视图通过各种激活状态。核心B，蛋白质组学核心将使最先进的定量蛋白质组学能力和计算能力该计划项目的调查人员可提供分析。核心将提供识别和相对使用现代的蛋白质成分和翻译后修饰状态的定量 LC/MS技术。该核心与该计划的PI合作有着良好的绩效记录在7个大型磷蛋白质组学和8个COIP-LCMS蛋白相互作用的产生中达到最终形式数据集和合作论文的发布，阐明了ZAP-70的分子细节招募到LAT以及ZAP-70的催化活性如何介导基本信号传导和T的负反馈细胞受体信号传导。核心最近开发了用于表征蛋白质的新技术活细胞中使用涡轮的相互作用网络和磷酸化的最深表征使用SRC SH2域Superbinder和TMT提升通道的网络。这些新开发的方法将利用以支持PIS的PIS来确定蛋白质 - 蛋白质相互作用者和磷酸化位点来自T细胞系和原代小鼠T细胞。核心还具有一套计算工具来提供蛋白质组学数据的严格统计分析并做出新的信号通路预测。