Functional and Quantitative Mass Spectrometry-Based Approaches for Mapping the Lysine Methylome

Abstract

Proteins are frequently modified with small chemical tags, or modifications, that play a key role in controlling their functions within the cell. One modification, lysine methylation, is found on thousands of human proteins and is added and removed by lysine methyltransferases (KMTs) and lysine demethylases (KDMs), respectively. Recognition of methylated lysines by specific reader proteins regulates downstream processes. Lysine methylation, KMTs, KDMs, and reader proteins therefore create a signaling network. Components of lysine methylation signaling networks are frequently dysregulated in human disease, but current methods to detect lysine methylation present barriers for understanding the impact an awry signaling network has on lysine methylation. In this study, we investigated the use of mass spectrometry (MS)-based proteomics to better detect and quantify both lysine methylation sites and methyl regulators across multiple samples. We investigated the sequence bias of commercially available pan-methyllysine antibodies using both a lysine-oriented peptide library and immunoprecipitation mass spectrometry. Our results showed that most antibodies have a preference for certain sequences. Furthermore, we observed that unenriched samples obtained the same number of identified lysine methylation sites as enriched samples. Following the establishment of an efficient and quantitative MS-based proteomics approach, we applied it to profile both lysine methylation and KDMs within breast cancer cell lines. Studies have repeatedly shown that components of the lysine methylation signaling network are overexpressed within breast cancer. Indeed, we characterized distinct lysine methylation and KDM patterns across the cell lines, suggesting the existence of different lysine methylation signaling. Given the ability to quantitatively profile lysine methylation, this work also characterized the impact of a compound known to disrupt the lysine methylation signaling network, 3-deazanplanocin A. The observed transcript, protein, and lysine methylation site abundance changes highlight how dysregulation of methyl mediators impacts lysine methylation and cellular signaling. Overall, we developed a reproducible pipeline that promises to enable a deeper understanding of how a dysregulated lysine methylation landscape influences cellular signaling and associated phenotypes.