Janssen K A, Sidoli S, Garcia B A
Epigenetics Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Epigenetics Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Methods Enzymol. 2017;586:359-378. doi: 10.1016/bs.mie.2016.10.021. Epub 2017 Jan 6.
Functional epigenetic regulation occurs by dynamic modification of chromatin, including genetic material (i.e., DNA methylation), histone proteins, and other nuclear proteins. Due to the highly complex nature of the histone code, mass spectrometry (MS) has become the leading technique in identification of single and combinatorial histone modifications. MS has now overcome antibody-based strategies due to its automation, high resolution, and accurate quantitation. Moreover, multiple approaches to analysis have been developed for global quantitation of posttranslational modifications (PTMs), including large-scale characterization of modification coexistence (middle-down and top-down proteomics), which is not currently possible with any other biochemical strategy. Recently, our group and others have simplified and increased the effectiveness of analyzing histone PTMs by improving multiple MS methods and data analysis tools. This review provides an overview of the major achievements in the analysis of histone PTMs using MS with a focus on the most recent improvements. We speculate that the workflow for histone analysis at its state of the art is highly reliable in terms of identification and quantitation accuracy, and it has the potential to become a routine method for systems biology thanks to the possibility of integrating histone MS results with genomics and proteomics datasets.
功能性表观遗传调控通过染色质的动态修饰发生,包括遗传物质(即DNA甲基化)、组蛋白和其他核蛋白。由于组蛋白密码的高度复杂性,质谱(MS)已成为鉴定单个和组合组蛋白修饰的主要技术。由于其自动化、高分辨率和准确定量,质谱现在已经克服了基于抗体的策略。此外,已经开发了多种分析方法用于翻译后修饰(PTM)的全局定量,包括修饰共存的大规模表征(中向下和自上而下蛋白质组学),这是目前任何其他生化策略都无法实现的。最近,我们小组和其他团队通过改进多种质谱方法和数据分析工具,简化并提高了分析组蛋白PTM的效率。本综述概述了使用质谱分析组蛋白PTM的主要成就,重点关注最新的改进。我们推测,就鉴定和定量准确性而言,最先进的组蛋白分析工作流程高度可靠,并且由于有可能将组蛋白质谱结果与基因组学和蛋白质组学数据集整合,它有潜力成为系统生物学的常规方法。