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活细胞中生物相容性化学交联对蛋白质构象和相互作用的空间分辨分析。

Spatially resolved profiling of protein conformation and interactions by biocompatible chemical cross-linking in living cells.

机构信息

CAS Key Laboratory of Separation Science for Analytical Chemistry, National Chromatographic R. & A. Center, State Key Laboratory of Medical Proteomics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning, China.

University of Chinese Academy of Sciences, Beijing, China.

出版信息

Nat Commun. 2024 Sep 27;15(1):8331. doi: 10.1038/s41467-024-52558-1.

DOI:10.1038/s41467-024-52558-1
PMID:39333085
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11436894/
Abstract

Unlocking the intricacies of protein structures and interactions within the dynamic landscape of subcellular organelles presents a significant challenge. To address this, we introduce SPACX, a method for spatially resolved protein complex profiling via biocompatible chemical cross(x)-linking with subcellular isolation, designed to monitor protein conformation, interactions, and translocation in living cells. By rapidly capturing protein complexes in their native physiological state and efficiently enriching cross-linked peptides, SPACX allows comprehensive analysis of the protein interactome within living cells. Leveraging structure refinement with cross-linking restraints, we identify subcellular-specific conformation heterogeneity of PTEN, revealing dynamic differences in its dual specificity domains between the nucleus and cytoplasm. Furthermore, by discerning conformational disparities, we identify 83 cytoplasm-exclusive and 109 nucleus-exclusive PTEN-interacting proteins, each associated with distinct biological functions. Upon induction of ubiquitin-proteasome system stress, we observe dynamic alterations in PTEN assembly and its interacting partners during translocation. These changes, including the identification of components and interaction sites, are characterized using the SPACX approach. Notably, SPACX enables identification of unique interacting proteins specific to PTEN isoforms, including PTEN and PTEN-Long, through the determination of sequence-specific cross-linking interfaces. These findings underscore the potential of SPACX to elucidate the functional diversity of proteins within distinct subcellular sociology.

摘要

揭示亚细胞细胞器动态景观中蛋白质结构和相互作用的复杂性是一项重大挑战。为了解决这个问题,我们引入了 SPACX,这是一种通过与亚细胞分离的生物相容性化学交联来对蛋白质复合物进行空间分辨分析的方法,旨在监测活细胞中蛋白质构象、相互作用和易位。通过快速捕获其天然生理状态下的蛋白质复合物并有效地富集交联肽,SPACX 允许在活细胞内对蛋白质相互作用组进行全面分析。利用交联限制进行结构细化,我们确定了 PTEN 的亚细胞特异性构象异质性,揭示了其核和细胞质中二特异性结构域之间的动态差异。此外,通过辨别构象差异,我们确定了 83 种细胞质特异性和 109 种核特异性的 PTEN 相互作用蛋白,每种蛋白都与独特的生物学功能相关。在诱导泛素-蛋白酶体系统应激时,我们观察到 PTEN 组装及其在易位过程中的相互作用伙伴的动态变化。这些变化,包括对组成成分和相互作用位点的识别,都可以使用 SPACX 方法进行描述。值得注意的是,SPACX 能够通过确定序列特异性交联界面,鉴定出特定于 PTEN 异构体(包括 PTEN 和 PTEN-Long)的独特相互作用蛋白。这些发现突显了 SPACX 阐明不同亚细胞社会学中蛋白质功能多样性的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/11436894/f7a14de0a9d8/41467_2024_52558_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/11436894/2ec6e4c8b30c/41467_2024_52558_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/11436894/72bdcb48fa05/41467_2024_52558_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/11436894/2d54b12c7eb9/41467_2024_52558_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/11436894/6a65f930ba34/41467_2024_52558_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/11436894/114495bfb1bd/41467_2024_52558_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/11436894/f7a14de0a9d8/41467_2024_52558_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/11436894/2ec6e4c8b30c/41467_2024_52558_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/11436894/72bdcb48fa05/41467_2024_52558_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/11436894/2d54b12c7eb9/41467_2024_52558_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/11436894/6a65f930ba34/41467_2024_52558_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/11436894/114495bfb1bd/41467_2024_52558_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/11436894/f7a14de0a9d8/41467_2024_52558_Fig6_HTML.jpg

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