Systematic Exploration of the Human Interactome

人类相互作用组的系统探索

• 批准号: 10187621
• 负责人: STEVEN P GYGI
• 金额: $ 72.72万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-21 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10187621
• 关键词: Address; Affinity Chromatography; Alleles; Architecture; Atlases; Benchmarking; Biological; Biology; Biotinylation; Cell Culture Techniques; Cell Lineage; Cell membrane; Cells; Cellular Membrane; Collection; Communities; Data; Data Set; Databases; Defect; Detergents; Discipline; Disease; Follow-Up Studies; Funding; Future; Gene Expression; Gene Mutation; Genes; Genetic Diseases; Genetic Variation; Genome; HCT116 Cells; Health; Human; Human Genetics; Human Genome; Individual; Intracellular Membranes; Label; Location; Maps; Mass Spectrum Analysis; Mediating; Membrane Proteins; Molecular; Molecular Cloning; Mutation; Network-based; Organelles; Peptides; Point Mutation; Protein Analysis; Protein Isoforms; Proteins; Proteome; Proteomics; Publications; Regulation; Reporting; Research; Research Personnel; Resource Development; Resources; Retrieval; Role; Sampling; Signal Transduction; Site; Specificity; Structure; System; Technology; Translating; Validation; Vesicle; Work; base; candidate identification; cell type; design; human disease; human interactome; insight; instrumentation; mutant; network architecture; protein function; protein protein interaction; searchable database; self assembly; synthetic polymer Bioplex; web portal

SUMMARY Although the publication of a human genome blueprint occurred more than 15 years ago, we remain far from understanding the complexities of the human proteome – the collections of proteins and their interactions that define individual human cells. The complexity of the proteome is both immense and dynamic, reflecting diverse, context-specific expression of genes in individual cells and distinct isoforms for individual proteins. In addition, individual proteins may participate in several distinct protein assemblies during their lifetime and undergo dynamic signal-dependent re-organization in order to impart distinct functions and cellular attributes. Moreover, numerous protein assemblies self-combine and compartmentalize to generate organelles and signaling modules within the cell, which are inherently dynamic. During the past 5 years, we have designed, validated, and applied a platform for the large scale analysis of protein interaction partners using affinity purification-mass spectrometry (AP-MS) termed BioPlex, which has allowed us to profile interaction partners for 10,000 nonredundant human bait proteins in HEK293T. In total, an atlas of nearly 120,000 protein-protein interactions was identified. The majority have not been reported through independent efforts. The robustness of BioPlex, when benchmarked against other studies as well as our initial analysis of a similar effort in another cell line (HCT116), parallels or exceeds available resources, allowing us to broadly define human protein communities, predict functions and localizations of unstudied proteins based on interaction partners, and define a large number of domain-domain enrichments that begin to impart structural architecture upon the network. In this renewal, we seek to greatly enhance and extend these efforts in three major ways: First, we will complete a full-pass, 10K-bait interactome in HCT116 cells and further address cell type diversity in interactomes by performing an analysis of 2000 high-priority bait proteins in 4 or more additional cell lines. Second, in order to systematically address the complexities of membrane protein interactomes, we will perform proximity labeling (biotinylation) across a broad range of 500 proteins known or predicted to reside in cellular membranes, more than half of which lack sub-cellular locations in UNIPROT. This will begin to provide a global understanding of membrane protein assemblies and will help to define the spatial architecture of the proteome. Third, we will develop a platform for quantitative analysis of the interactomes of 200 high-priority, mutant disease genes, thereby providing an in-depth view of how mutations drive reorganization of key networks. Together, these studies will: i) define interactomes across multiple cell types, ii) provide a spatial view of membrane protein architecture, and iii) begin to globally define how mutant alleles short-circuit key cellular systems to promote disease. 1

概括 尽管人类基因组蓝图的发表发生在15年前，但我们远离 了解人类蛋白质组的复杂性 - 蛋白质的集合及其相互作用 定义单个人类细胞。蛋白质组的复杂性既巨大又动态，反映 潜水员，基因在单个细胞中的基因表达和单个蛋白质的不同同工型。在 此外，单个蛋白质在其一生中可能会参与几个不同的蛋白质组件，并且 进行动态信号依赖性重组，以赋予不同的功能和细胞属性。 此外，众多蛋白质组件自结合并分隔以产生细胞器和 单元内的信号模块本质上是动态的。在过去的5年中，我们设计了 经过验证，并应用了一个平台，用于使用亲和力对蛋白质相互作用伙伴进行大规模分析 称为Bioplex的纯化 - 质量光谱法（AP-MS），这使我们能够介绍相互作用伙伴 HEK293T中的10,000个非冗余人类诱饵蛋白。总共是一个近120,000个蛋白质蛋白的地图集 确定了相互作用。大多数尚未通过独立努力进行报告。坚固的 Bioplex，当对其他研究进行基准测试以及我们对另一个类似努力的初步分析 细胞系（HCT116），平行或超过可用资源，使我们可以广泛定义人类蛋白质 社区，根据互动伙伴预测未研究蛋白质的功能和本地化，以及 定义大量的域域富集，这些域开始在 网络。在这种续约中，我们寻求通过三种主要方式来大力增强和扩展这些努力：首先，我们 将在HCT116细胞中完成全通，10K诱饵相互作用，并进一步解决细胞类型的多样性 通过对4个或更多其他细胞系中的2000个高优先诱饵蛋白进行分析来进行相互作用。 第二，为了系统地解决膜蛋白相互作用的复杂性，我们将 在已知或预测居住的500种蛋白质上执行接近标记（生物素化） 细胞膜，其中一半以上缺乏Uniprot中的亚细胞位置。这将开始提供 对膜蛋白组件的全球理解，并将有助于定义 蛋白质组。第三，我们将开发一个平台，用于定量分析200个高优先级的相互作用体， 突变疾病基因，从而对突变如何驱动钥匙的重组提供了深入的观点 网络。这些研究将在一起：i）定义多种细胞类型的相互作用，ii）提供空间 膜蛋白结构的视图和iii）开始在全球范围内定义突变等位基因如何短路键 促进疾病的细胞系统。 1