Suppr超能文献

通过16重串联质量标签标记结合二维色谱和质谱进行高通量和深度蛋白质组分析

High-throughput and Deep-proteome Profiling by 16-plex Tandem Mass Tag Labeling Coupled with Two-dimensional Chromatography and Mass Spectrometry.

作者信息

Wang Zhen, Kavdia Kanisha, Dey Kaushik Kumar, Pagala Vishwajeeth Reddy, Kodali Kiran, Liu Danting, Lee Dong Geun, Sun Huan, Chepyala Surendhar Reddy, Cho Ji-Hoon, Niu Mingming, High Anthony A, Peng Junmin

机构信息

Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital.

Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital.

出版信息

J Vis Exp. 2020 Aug 18(162). doi: 10.3791/61684.

Abstract

Isobaric tandem mass tag (TMT) labeling is widely used in proteomics because of its high multiplexing capacity and deep proteome coverage. Recently, an expanded 16-plex TMT method has been introduced, which further increases the throughput of proteomic studies. In this manuscript, we present an optimized protocol for 16-plex TMT-based deep-proteome profiling, including protein sample preparation, enzymatic digestion, TMT labeling reaction, two-dimensional reverse-phase liquid chromatography (LC/LC) fractionation, tandem mass spectrometry (MS/MS), and computational data processing. The crucial quality control steps and improvements in the process specific for the 16-plex TMT analysis are highlighted. This multiplexed process offers a powerful tool for profiling a variety of complex samples such as cells, tissues, and clinical specimens. More than 10,000 proteins and posttranslational modifications such as phosphorylation, methylation, acetylation, and ubiquitination in highly complex biological samples from up to 16 different samples can be quantified in a single experiment, providing a potent tool for basic and clinical research.

摘要

等压串联质量标签(TMT)标记因其高复用能力和深入的蛋白质组覆盖范围而在蛋白质组学中被广泛使用。最近,一种扩展的16重TMT方法被引入,这进一步提高了蛋白质组学研究的通量。在本手稿中,我们提出了一种基于16重TMT的深度蛋白质组分析的优化方案,包括蛋白质样品制备、酶解、TMT标记反应、二维反相液相色谱(LC/LC)分级分离、串联质谱(MS/MS)和计算数据处理。重点介绍了16重TMT分析过程中的关键质量控制步骤和改进。这种复用过程为分析各种复杂样品(如细胞、组织和临床标本)提供了一个强大的工具。在一个实验中,可以对来自多达16个不同样品的高度复杂生物样品中的10000多种蛋白质以及磷酸化、甲基化、乙酰化和泛素化等翻译后修饰进行定量,为基础研究和临床研究提供了一个有力的工具。

相似文献

引用本文的文献

本文引用的文献

1
Single-cell analysis targeting the proteome.针对蛋白质组的单细胞分析。
Nat Rev Chem. 2020 Mar;4(3):143-158. doi: 10.1038/s41570-020-0162-7. Epub 2020 Feb 17.
10
Multibatch TMT Reveals False Positives, Batch Effects and Missing Values.多批次 TMT 揭示了假阳性、批次效应和缺失值。
Mol Cell Proteomics. 2019 Oct;18(10):1967-1980. doi: 10.1074/mcp.RA119.001472. Epub 2019 Jul 22.

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