Protein Lys methylation plays a critical role in numerous cellular processes, but it is challenging to identify Lys methylation in a systematic manner. Here we present an approach combining in silico prediction with targeted mass spectrometry (MS) to identify Lys methylation (Kme) sites at the proteome level. We develop MethylSight, a program that predicts Kme events solely on the physicochemical properties of residues surrounding the putative methylation sites, which then requires validation by targeted MS. Using this approach, we identify 70 new histone Kme marks with a 90% validation rate. H2BK43me2, which undergoes dynamic changes during stem cell differentiation, is found to be a substrate of KDM5b. Furthermore, MethylSight predicts that Lys methylation is a prevalent post-translational modification in the human proteome. Our work provides a useful resource for guiding systematic exploration of the role of Lys methylation in human health and disease.Biggar et al. develop an algorithm to identify lysine methylation sites and use this resource to provide insight into the potential of the methyllysine proteome. The results also validate 45 new histone methylation sites by targeted mass spectrometry and show that one of these sites, H2B-K43me2, is a substrate of the KDM5B demethylase.

histone H1, histone H2B, histone marks, KDM5b, lysine methylation, machine learning, methyllysine proteome, non-histone methylation
Cell Reports
Institute of Biochemistry

Biggar, K.K, Charih, F. (Francois), Liu, H. (Huadong), Ruiz-Blanco, Y.B. (Yasser B.), Stalker, L. (Leanne), Chopra, A. (Anand), … Li, S.S.-C. (Shawn S.-C.). (2020). Proteome-wide Prediction of Lysine Methylation Leads to Identification of H2BK43 Methylation and Outlines the Potential Methyllysine Proteome. Cell Reports, 32(2). doi:10.1016/j.celrep.2020.107896