Bludau Isabell, Heusel Moritz, Frank Max, Rosenberger George, Hafen Robin, Banaei-Esfahani Amir, van Drogen Audrey, Collins Ben C, Gstaiger Matthias, Aebersold Ruedi
Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland.
Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
Nat Protoc. 2020 Aug;15(8):2341-2386. doi: 10.1038/s41596-020-0332-6. Epub 2020 Jul 20.
Most catalytic, structural and regulatory functions of the cell are carried out by functional modules, typically complexes containing or consisting of proteins. The composition and abundance of these complexes and the quantitative distribution of specific proteins across different modules are therefore of major significance in basic and translational biology. However, detection and quantification of protein complexes on a proteome-wide scale is technically challenging. We have recently extended the targeted proteomics rationale to the level of native protein complex analysis (complex-centric proteome profiling). The complex-centric workflow described herein consists of size exclusion chromatography (SEC) to fractionate native protein complexes, data-independent acquisition mass spectrometry to precisely quantify the proteins in each SEC fraction based on a set of proteotypic peptides and targeted, complex-centric analysis where prior information from generic protein interaction maps is used to detect and quantify protein complexes with high selectivity and statistical error control via the computational framework CCprofiler (https://github.com/CCprofiler/CCprofiler). Complex-centric proteome profiling captures most proteins in complex-assembled state and reveals their organization into hundreds of complexes and complex variants observable in a given cellular state. The protocol is applicable to cultured cells and can potentially also be adapted to primary tissue and does not require any genetic engineering of the respective sample sources. At present, it requires ~8 d of wet-laboratory work, 15 d of mass spectrometry measurement time and 7 d of computational analysis.
细胞的大多数催化、结构和调节功能是由功能模块执行的，这些功能模块通常是包含蛋白质或由蛋白质组成的复合物。因此，这些复合物的组成和丰度以及特定蛋白质在不同模块中的定量分布在基础生物学和转化生物学中具有重要意义。然而，在蛋白质组范围内检测和定量蛋白质复合物在技术上具有挑战性。我们最近将靶向蛋白质组学原理扩展到了天然蛋白质复合物分析水平（以复合物为中心的蛋白质组分析）。本文所述的以复合物为中心的工作流程包括：使用尺寸排阻色谱法（SEC）对天然蛋白质复合物进行分级分离；使用数据非依赖采集质谱法，基于一组蛋白质型肽精确量化每个SEC级分中的蛋白质；以及进行靶向的、以复合物为中心的分析，其中利用来自通用蛋白质相互作用图谱的先验信息，通过计算框架CCprofiler（https://github.com/CCprofiler/CCprofiler）以高选择性和统计误差控制来检测和定量蛋白质复合物。以复合物为中心的蛋白质组分析捕获了处于复合物组装状态的大多数蛋白质，并揭示了它们在给定细胞状态下可观察到的组织成数百种复合物和复合物变体的情况。该方案适用于培养的细胞，也可能适用于原代组织，并且不需要对相应的样本来源进行任何基因工程操作。目前，它需要约8天的湿实验室工作时间、15天的质谱测量时间和7天的计算分析时间。
