Abstract
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.
| Original language | English |
|---|---|
| Article number | 107896 |
| Journal | Cell Reports |
| Volume | 32 |
| Issue number | 2 |
| DOIs | |
| State | Published - 14 Jul 2020 |
| Externally published | Yes |
Keywords
- KDM5b
- histone H1
- histone H2B
- histone marks
- lysine methylation
- machine learning
- methyllysine proteome
- non-histone methylation
ASJC Scopus subject areas
- General Biochemistry, Genetics and Molecular Biology