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邻近标记扩展显微镜 (PL-ExM) 评估互作组标记技术。

Proximity labeling expansion microscopy (PL-ExM) evaluates interactome labeling techniques.

机构信息

Center for Complex Biological Systems, University of California, Irvine, Irvine, CA 92697, USA.

Physiology and Biophysics, University of California, Irvine, Irvine, CA 92697, USA.

出版信息

J Mater Chem B. 2024 Aug 28;12(34):8335-8348. doi: 10.1039/d4tb00516c.

Abstract

Understanding protein-protein interactions (PPIs) through proximity labeling has revolutionized our comprehension of cellular mechanisms and pathology. Various proximity labeling techniques, such as HRP, APEX, BioID, TurboID, and μMap, have been widely used to biotinylate PPIs or organelles for proteomic profiling. However, the variability in labeling precision and efficiency of these techniques often results in limited reproducibility in proteomic detection. We address this persistent challenge by introducing proximity labeling expansion microscopy (PL-ExM), a super-resolution imaging technique that combines expansion microscopy with proximity labeling techniques. PL-ExM enabled up to 17 nm resolution with microscopes widely available, providing visual comparison of the labeling precision, efficiency, and false positives of different proximity labeling methods. Our mass spectrometry proteomic results confirmed that PL-ExM imaging is reliable in guiding the selection of proximity labeling techniques and interpreting the proteomic results with new spatial information.

摘要

通过邻近标记来理解蛋白质-蛋白质相互作用 (PPIs) 已经彻底改变了我们对细胞机制和病理学的理解。各种邻近标记技术,如 HRP、APEX、BioID、TurboID 和 μMap,已被广泛用于生物素化 PPIs 或细胞器以进行蛋白质组学分析。然而,这些技术在标记精度和效率方面的可变性常常导致蛋白质组学检测的重现性有限。我们通过引入邻近标记扩展显微镜 (PL-ExM) 来解决这一持续存在的挑战,这是一种将扩展显微镜与邻近标记技术相结合的超分辨率成像技术。PL-ExM 可以在广泛使用的显微镜上实现高达 17nm 的分辨率,从而可以对不同邻近标记方法的标记精度、效率和假阳性进行直观比较。我们的质谱蛋白质组学结果证实,PL-ExM 成像在指导邻近标记技术的选择和利用新的空间信息解释蛋白质组学结果方面是可靠的。

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本文引用的文献

2
Expansion microscopy: A chemical approach for super-resolution microscopy.
Curr Opin Struct Biol. 2023 Aug;81:102614. doi: 10.1016/j.sbi.2023.102614. Epub 2023 May 28.
3
Heat denaturation enables multicolor X10-STED microscopy.
Sci Rep. 2023 Apr 1;13(1):5366. doi: 10.1038/s41598-023-32524-5.
5
Radius measurement via super-resolution microscopy enables the development of a variable radii proximity labeling platform.
Proc Natl Acad Sci U S A. 2022 Aug 9;119(32):e2203027119. doi: 10.1073/pnas.2203027119. Epub 2022 Aug 1.
6
Molecular Spatiomics by Proximity Labeling.
Acc Chem Res. 2022 May 17;55(10):1411-1422. doi: 10.1021/acs.accounts.2c00061. Epub 2022 May 5.
8
In situ proximity labeling identifies Lewy pathology molecular interactions in the human brain.
Proc Natl Acad Sci U S A. 2022 Feb 1;119(5). doi: 10.1073/pnas.2114405119.
10
Label-retention expansion microscopy.
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