Poncha Karl F, Paparella Alyssa T, Young Nicolas L
Verna & Marrs McLean Department of Biochemistry & Molecular Pharmacology, Baylor College of Medicine, Houston Texas.
Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas.
bioRxiv. 2024 Nov 18:2024.11.18.624157. doi: 10.1101/2024.11.18.624157.
Histone proteoforms, often presenting multiple co-occurring post-translational modifications (PTMs), are central to chromatin regulation and gene expression. A proteoform is a specific form of a protein that includes variations arising from genetic changes, alternative RNA splicing, proteolytic processing, and PTMs. Genomic context-dependent histone proteoforms define the histone code, influencing cellular phenotype by dictating interactions with DNA and chromatin-associated proteins. Understanding the dynamics of histone proteoforms is essential for elucidating chromatin-based regulatory mechanisms. Advances in middle-down and top-down proteomics methods enable accurate identification and quantitation of hundreds to thousands of proteoforms in a single run. However, the resulting data complexity presents significant challenges for analysis and visualization. Here, we introduce new computational methods to analyze the dynamics of histone PTMs and demonstrate their use in mouse organs during aging. We have developed and benchmarked two novel PTM crosstalk scores. The score that we term 'Normalized Interplay' addresses limitations of the original crosstalk score 'Interplay' providing a more complete and accurate measure of PTM crosstalk. The second score, 'delta I' or Directional Interplay is an asymmetric measure quantifying the magnitude and directionality of crosstalk between PTMs. Applying our two-stage scoring approach to data from CrosstalkDB, a community resource that curates proteoform-level data, reveals the dynamics of histone H3 modifications during aging. The source code is available under an Apache license at https://github.com/k-p4/ptm_interplay_scoring.
组蛋白蛋白质变体通常呈现多种同时发生的翻译后修饰(PTM),是染色质调控和基因表达的核心。蛋白质变体是蛋白质的一种特定形式,包括由基因变化、可变RNA剪接、蛋白水解加工和PTM产生的变异。基因组背景依赖的组蛋白蛋白质变体定义了组蛋白密码,通过决定与DNA和染色质相关蛋白的相互作用来影响细胞表型。了解组蛋白蛋白质变体的动态对于阐明基于染色质的调控机制至关重要。中向下和自上而下蛋白质组学方法的进展使得能够在一次运行中准确鉴定和定量数百到数千种蛋白质变体。然而,由此产生的数据复杂性给分析和可视化带来了重大挑战。在这里,我们介绍了新的计算方法来分析组蛋白PTM的动态,并展示了它们在衰老过程中在小鼠器官中的应用。我们开发并基准测试了两种新的PTM串扰分数。我们称为“归一化相互作用”的分数解决了原始串扰分数“相互作用”的局限性,提供了更完整和准确的PTM串扰测量。第二个分数“δI”或方向性相互作用是一种不对称测量,量化了PTM之间串扰的大小和方向性。将我们的两阶段评分方法应用于来自CrosstalkDB(一个整理蛋白质变体水平数据的社区资源)的数据,揭示了衰老过程中组蛋白H3修饰的动态。源代码可根据Apache许可证在https://github.com/k-p4/ptm_interplay_scoring获得。