Wisconsin Institute for Discovery, 330 N. Orchard Street, Madison, WI, USA; Department of Biomolecular Chemistry, University of Wisconsin, Madison, 420 Henry Mall, Madison, WI, USA.
Wisconsin Institute for Discovery, 330 N. Orchard Street, Madison, WI, USA; Department of Biomolecular Chemistry, University of Wisconsin, Madison, 420 Henry Mall, Madison, WI, USA.
Methods. 2020 Dec 1;184:53-60. doi: 10.1016/j.ymeth.2019.12.001. Epub 2019 Dec 7.
Advances in mass spectrometry (MS) have revolutionized the ability to measure global changes in histone post-translational modifications (PTMs). The method routinely quantifies over 60 modification states in a single sample, far exceeding the capabilities of traditional western blotting. Thus, MS-based histone analysis has become an increasingly popular tool for understanding how genetic and environmental factors influence epigenetic states. However, histone proteomics experiments exhibit unique challenges, such as batch-to-batch reproducibility, accurate peak integration, and noisy data. Here, we discuss the steps of histone PTM analysis, from sample preparation and peak integration to data analysis and validation. We outline a set of best practices for ensuring data quality, accurate normalization, and robust statistics. Using these practices, we quantify histone modifications in 5 human cell lines, revealing that each cell line exhibits a unique epigenetic signature. We also provide a reproducible workflow for histone PTM analysis in the form of an R script, which is freely available at https://github.com/DenuLab/HistoneAnalysisWorkflow.
质谱(MS)技术的进步彻底改变了测量组蛋白翻译后修饰(PTMs)整体变化的能力。该方法可在单个样本中常规定量超过 60 种修饰状态,远远超过传统的western blot 技术的能力。因此,基于 MS 的组蛋白分析已成为了解遗传和环境因素如何影响表观遗传状态的越来越受欢迎的工具。然而,组蛋白蛋白质组学实验表现出独特的挑战,例如批间重现性、准确的峰积分和嘈杂的数据。在这里,我们讨论了组蛋白 PTM 分析的步骤,从样品制备和峰积分到数据分析和验证。我们概述了确保数据质量、准确归一化和稳健统计的一套最佳实践。使用这些实践,我们在 5 个人类细胞系中定量了组蛋白修饰,揭示了每个细胞系都表现出独特的表观遗传特征。我们还提供了一个以 R 脚本形式呈现的组蛋白 PTM 分析可重复的工作流程,该脚本可在 https://github.com/DenuLab/HistoneAnalysisWorkflow 上免费获得。