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协调细胞功能以响应刺激至关重要。这些网络结构的研究为理解其病理后果提供了基础故障并为设计治疗干预措施提供了机会。这些网络的复杂性。信号在细胞中传输的速度使得绘制信号图成为一项艰巨的挑战。阐明细胞信号网络结构的典型方法涉及以下迭代过程创建信号蛋白破坏、结构域突变体和定点突变体，然后进行表征作为一种补充方法，现代的方法是通过一系列细胞激活测定来检测每个突变体。使用定量质谱的蛋白质组学方法可以促进假设驱动的表征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来研究信号通路通过各种激活状态。 Core B，蛋白质组学核心将提供尖端的定量蛋白质组学能力和计算能力该项目的研究人员可以使用的分析核心将提供识别和相关信息。使用现代技术对蛋白质组成和蛋白质翻译后修饰状态进行定量该核心技术与该项目的 PI 有着卓有成效的合作记录。该项目最终产生了 7 个大型磷酸化蛋白质组和 8 个 CoIP-LCMS 蛋白质相互作用阐明 ZAP-70 分子细节的合作论文的数据集和出版物招募到 LAT 以及 ZAP-70 的催化活性如何介导 T 的基础信号传导和负反馈核心最近开发了用于蛋白质表征的新技术。使用 TurboID 分析活细胞中的相互作用网络以及尽可能深入的磷酸化表征网络使用Src SH2域Superbinder和TMT BOOST通道这些新开发的方法。将用于支持项目 PI 以确定蛋白质-蛋白质相互作用物和磷酸化位点来自 T 细胞系和原代小鼠 T 细胞的核心还具有一套计算工具来提供。对蛋白质组数据进行严格的统计分析并做出新的信号通路预测。