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DIP-MS:用于蛋白质复合物解卷积的超深度互作蛋白质组学。

DIP-MS: ultra-deep interaction proteomics for the deconvolution of protein complexes.

机构信息

Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.

Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA.

出版信息

Nat Methods. 2024 Apr;21(4):635-647. doi: 10.1038/s41592-024-02211-y. Epub 2024 Mar 26.

Abstract

Most proteins are organized in macromolecular assemblies, which represent key functional units regulating and catalyzing most cellular processes. Affinity purification of the protein of interest combined with liquid chromatography coupled to tandem mass spectrometry (AP-MS) represents the method of choice to identify interacting proteins. The composition of complex isoforms concurrently present in the AP sample can, however, not be resolved from a single AP-MS experiment but requires computational inference from multiple time- and resource-intensive reciprocal AP-MS experiments. Here we introduce deep interactome profiling by mass spectrometry (DIP-MS), which combines AP with blue-native-PAGE separation, data-independent acquisition with mass spectrometry and deep-learning-based signal processing to resolve complex isoforms sharing the same bait protein in a single experiment. We applied DIP-MS to probe the organization of the human prefoldin family of complexes, resolving distinct prefoldin holo- and subcomplex variants, complex-complex interactions and complex isoforms with new subunits that were experimentally validated. Our results demonstrate that DIP-MS can reveal proteome modularity at unprecedented depth and resolution.

摘要

大多数蛋白质都组织在大分子组装体中,这些组装体是调节和催化大多数细胞过程的关键功能单元。亲和纯化感兴趣的蛋白质,结合液相色谱串联质谱(AP-MS),是鉴定相互作用蛋白的首选方法。然而,在 AP 样品中同时存在的复杂同种型的组成不能从单个 AP-MS 实验中解析出来,而是需要从多个耗时且资源密集型的相互 AP-MS 实验中进行计算推断。在这里,我们介绍了通过质谱进行的深度互作组学分析(DIP-MS),它将亲和纯化与蓝色 native-PAGE 分离、数据非依赖性采集与质谱以及基于深度学习的信号处理相结合,以在单个实验中解析共享相同诱饵蛋白的复杂同种型。我们将 DIP-MS 应用于探测人类前折叠复合物家族的组织,解析出不同的前折叠全酶和亚复合物变体、复合物-复合物相互作用以及具有新亚基的复合物同种型,这些结果都通过实验得到了验证。我们的结果表明,DIP-MS 可以以前所未有的深度和分辨率揭示蛋白质组的模块性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0cfc/11009110/14640146a336/41592_2024_2211_Fig1_HTML.jpg

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