Suppr超能文献

临近标记及其他新型质谱方法在蛋白质时空动态研究中的应用。

Proximity labeling and other novel mass spectrometric approaches for spatiotemporal protein dynamics.

机构信息

Department of Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, PA, USA.

Department of Proteomics and Aging, Buck Institute for Research on Aging, Novato, CA, USA.

出版信息

Expert Rev Proteomics. 2021 Sep;18(9):757-765. doi: 10.1080/14789450.2021.1976149. Epub 2021 Sep 15.

Abstract

BACKGROUND

Proteins are highly dynamic and their biological function is controlled by not only temporal abundance changes but also via regulated protein-protein interaction networks, which respond to internal and external perturbations. A wealth of novel analytical reagents and workflows allow studying spatiotemporal protein environments with great granularity while maintaining high throughput and ease of analysis.

AREAS COVERED

We review technology advances for measuring protein-protein proximity interactions with an emphasis on proximity labeling, and briefly summarize other spatiotemporal approaches including protein localization, and their dynamic changes over time, specifically in human cells and mammalian tissues. We focus especially on novel technologies and workflows emerging within the past 5 years. This includes enrichment-based techniques (proximity labeling and crosslinking), separation-based techniques (organelle fractionation and size exclusion chromatography), and finally sorting-based techniques (laser capture microdissection and mass spectrometry imaging).

EXPERT OPINION

Spatiotemporal proteomics is a key step in assessing biological complexity, understanding refined regulatory mechanisms, and forming protein complexes and networks. Studying protein dynamics across space and time holds promise for gaining deep insights into how protein networks may be perturbed during disease and aging processes, and offer potential avenues for therapeutic interventions, drug discovery, and biomarker development.

摘要

背景

蛋白质具有高度动态性,其生物学功能不仅受到时间丰度变化的控制,还受到受调控的蛋白质-蛋白质相互作用网络的控制,这些网络会对外界和内部的干扰作出响应。大量新的分析试剂和工作流程允许以很高的通量和易于分析的方式,对时空蛋白质环境进行高分辨率研究。

涵盖领域

我们综述了用于测量蛋白质-蛋白质邻近相互作用的技术进展,重点介绍了邻近标记技术,并简要总结了其他时空方法,包括蛋白质定位及其随时间的动态变化,特别是在人类细胞和哺乳动物组织中。我们特别关注过去 5 年内出现的新技术和工作流程。这包括基于富集的技术(邻近标记和交联)、基于分离的技术(细胞器分级分离和排阻色谱),以及基于分类的技术(激光捕获显微切割和质谱成像)。

专家意见

时空蛋白质组学是评估生物复杂性、理解精细调控机制以及形成蛋白质复合物和网络的关键步骤。研究蛋白质在空间和时间上的动态变化有望深入了解蛋白质网络在疾病和衰老过程中可能受到的干扰,并为治疗干预、药物发现和生物标志物开发提供潜在途径。

相似文献

1
Proximity labeling and other novel mass spectrometric approaches for spatiotemporal protein dynamics.
Expert Rev Proteomics. 2021 Sep;18(9):757-765. doi: 10.1080/14789450.2021.1976149. Epub 2021 Sep 15.
6
7
Proximity labeling approaches to study protein complexes during virus infection.
Adv Virus Res. 2021;109:63-104. doi: 10.1016/bs.aivir.2021.02.001. Epub 2021 Apr 16.
8
Proximity labeling: an emerging tool for probing molecular interactions.
Plant Commun. 2020 Dec 15;2(2):100137. doi: 10.1016/j.xplc.2020.100137. eCollection 2021 Mar 8.
9
Identifying novel protein interactions: Proteomic methods, optimisation approaches and data analysis pipelines.
Methods. 2016 Feb 15;95:46-54. doi: 10.1016/j.ymeth.2015.08.022. Epub 2015 Aug 29.
10
Proximity Labeling Techniques: A Multi-Omics Toolbox.
Chem Asian J. 2022 Jan 17;17(2):e202101240. doi: 10.1002/asia.202101240. Epub 2021 Dec 10.

引用本文的文献

1
Recent Advancements in Subcellular Proteomics: Growing Impact of Organellar Protein Niches on the Understanding of Cell Biology.
J Proteome Res. 2024 Aug 2;23(8):2700-2722. doi: 10.1021/acs.jproteome.3c00839. Epub 2024 Mar 7.
2
3
Endothelial cilia dysfunction in pathogenesis of hereditary hemorrhagic telangiectasia.
Front Cell Dev Biol. 2022 Nov 10;10:1037453. doi: 10.3389/fcell.2022.1037453. eCollection 2022.
4
Recent Advances in the Prediction of Subcellular Localization of Proteins and Related Topics.
Front Bioinform. 2022 May 19;2:910531. doi: 10.3389/fbinf.2022.910531. eCollection 2022.
5
Deciphering Spatial Protein-Protein Interactions in Brain Using Proximity Labeling.
Mol Cell Proteomics. 2022 Nov;21(11):100422. doi: 10.1016/j.mcpro.2022.100422. Epub 2022 Oct 2.

本文引用的文献

1
Improved SILAC Quantification with Data-Independent Acquisition to Investigate Bortezomib-Induced Protein Degradation.
J Proteome Res. 2021 Apr 2;20(4):1918-1927. doi: 10.1021/acs.jproteome.0c00938. Epub 2021 Mar 25.
2
Native Mass Spectrometry Imaging of Proteins and Protein Complexes by Nano-DESI.
Anal Chem. 2021 Mar 16;93(10):4619-4627. doi: 10.1021/acs.analchem.0c05277. Epub 2021 Mar 4.
3
Advanced Cross-Linking Mass Spectrometry Platform to Characterize Proteome-Wide Protein Interactions.
Anal Chem. 2021 Mar 9;93(9):4166-4174. doi: 10.1021/acs.analchem.0c04430. Epub 2021 Feb 22.
5
The secrets of protein secretion: what are the key features of comparative secretomics?
Expert Rev Proteomics. 2020 Nov-Dec;17(11-12):785-787. doi: 10.1080/14789450.2020.1881890. Epub 2021 Feb 7.
6
Deciphering molecular interactions by proximity labeling.
Nat Methods. 2021 Feb;18(2):133-143. doi: 10.1038/s41592-020-01010-5. Epub 2021 Jan 11.
8
Proximity labeling in mammalian cells with TurboID and split-TurboID.
Nat Protoc. 2020 Dec;15(12):3971-3999. doi: 10.1038/s41596-020-0399-0. Epub 2020 Nov 2.
9
Emerging mass spectrometry-based proteomics methodologies for novel biomedical applications.
Biochem Soc Trans. 2020 Oct 30;48(5):1953-1966. doi: 10.1042/BST20191091.
10
Quantitative analysis of global protein stability rates in tissues.
Sci Rep. 2020 Sep 29;10(1):15983. doi: 10.1038/s41598-020-72410-y.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验