Mapping endogenous protein dynamics in living cells

绘制活细胞内源蛋白质动态图

基本信息

批准号：
10020992
负责人：
Bo Huang
金额：
$ 28.05万
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：
2019
资助国家：
美国
起止时间：
2019-09-20 至 2023-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10020992
关键词：
3-Dimensional Address CRISPR/Cas technology Cell Cycle Cell Line Cell Nucleus Cells Cellular biology Collection Color Comb animal structure Complement Consumption DNA Development Directed Molecular Evolution Engineering Ensure Epitopes Gene Proteins Generations Genes Genomics Human Human Cell Line Human Genome Image Immunoprecipitation Knock-in Label Laboratories Libraries Lighting Mammalian Cell Maps Methods Microscopy Mitosis Nuclear Proteins Organism Performance Photobleaching Process Protein Analysis Protein Dynamics Protein Engineering Protein Fragment Proteins Proteome Resolution Resources Ribonucleoproteins Role Saccharomyces cerevisiae Saccharomycetales Sampling Signal Transduction System Time base design experience fluorescence imaging fluorescence microscope genome-wide imaging platform improved instrumentation live cell microscopy multidisciplinary protein function screening success tool yeast protein

项目摘要

PROJECT SUMMARY/ABSTRACT A central challenge of the post-genomic era is to comprehensively characterize the cellular role of the ~20,000 proteins encoded in the human genome. Functional tagging is a powerful strategy to characterize the cellular role of proteins. In particular, tags allow access to two key features of protein function: localization (using fluorescent tags) and interaction partners (using epitope tags and immuno-precipitation). Hence, by tagging proteins in a systematic manner, a comprehensive functional description of an organism’s proteome can be achieved. For this purpose, we have previously developed FP11 tags based on self-complementing split fluorescent proteins, which, in combination with gene editing using Cas9/sgRNA ribonucleoprotein (RNPs), enable rapid, efficient and highly scalable tagging of endogenous proteins in mammalian cell lines. While our results have paved the way for the large-scale generation of endogenously tagged human cell lines for the proteome-wide analysis of protein localization and interaction networks in a native cellular context. However, for practical generation and analysis of large-scale libraries, several major technical limitations still need to be addressed: brightness, color availability, and live imaging platforms with low photobleaching. In the proposed project, we plan to engineer improved FP11 tags and new split protein fragment tags to address these technical challenges. We will also demonstrate the powerful applications by developing a new selective plane illumination microscopy (SPIM) system to screen an endogenously tagged library.

项目概要/摘要后基因组时代的一个核心挑战是全面描述约 20,000 个细胞的细胞作用人类基因组中编码的蛋白质是表征细胞的强大策略。特别是，标签允许访问蛋白质功能的两个关键特征：定位（使用荧光标签）和相互作用伙伴（使用表位标签和免疫沉淀）因此，通过标记。以系统的方式描述蛋白质，可以对生物体蛋白质组进行全面的功能描述为此，我们之前开发了基于自补分割的FP11标签。荧光蛋白，与使用 Cas9/sgRNA 核糖核蛋白 (RNP) 的基因编辑相结合，能够快速、高效且高度可扩展地标记哺乳动物细胞系中的内源蛋白。结果为大规模产生内源标记的人类细胞系铺平了道路然而，对天然细胞环境中的蛋白质定位和相互作用网络进行蛋白质组范围的分析。对于大规模文库的实际生成和分析，仍需要解决几个主要的技术限制在提议中解决了：亮度、色彩可用性和低光漂白的实时成像平台。项目中，我们计划设计改进的 FP11 标签和新的分割蛋白片段标签来解决这些技术问题我们还将通过开发新的选择性飞机来展示强大的应用程序。照明显微镜（SPIM）系统用于筛选内源标记文库。