Heavy Methyl SILAC Metabolic Labeling of Human Cell Lines for High-Confidence Identification of R/K-Methylated Peptides by High-Resolution Mass Spectrometry.

Protein methylation is a widespread post-translational modification (PTM) involved in several important biological processes including, but not limited to, RNA splicing, signal transduction, translation, and DNA repair. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is considered today the most versatile and accurate technique to profile PTMs with high precision and proteome-wide depth; however, the identification of protein methylations by MS is still prone to high false discovery rates. In this chapter, we describe the heavy methyl SILAC metabolic labeling strategy that allows high-confidence identification of in vivo methyl-peptides by MS-based proteomics. We provide a general protocol that covers the steps of heavy methyl labeling of cultured cells, protein sample preparation, LC-MS/MS analysis, and downstream computational analysis of the acquired MS data.

ProMetheusDB: An In-Depth Analysis of the High-Quality Human Methyl-proteome.

Protein arginine (R) methylation is a post-translational modification involved in various biological processes, such as RNA splicing, DNA repair, immune response, signal transduction, and tumor development. Although several advancements were made in the study of this modification by mass spectrometry, researchers still face the problem of a high false discovery rate. We present a dataset of high-quality methylations obtained from several different heavy methyl stable isotope labeling with amino acids in cell culture experiments analyzed with a machine learning-based tool and show that this model allows for improved high-confidence identification of real methyl-peptides. Overall, our results are consistent with the notion that protein R methylation modulates protein-RNA interactions and suggest a role in rewiring protein-protein interactions, for which we provide experimental evidence for a representative case (i.e., NONO [non-POU domain-containing octamer-binding protein]-paraspeckle component 1 [PSPC1]). Upon intersecting our R-methyl-sites dataset with the PhosphoSitePlus phosphorylation dataset, we observed that R methylation correlates differently with S/T-Y phosphorylation in response to various stimuli. Finally, we explored the application of heavy methyl stable isotope labeling with amino acids in cell culture to identify unconventional methylated residues and successfully identified novel histone methylation marks on serine 28 and threonine 32 of H3. The database generated, named ProMetheusDB, is freely accessible at https://bioserver.ieo.it/shiny/app/prometheusdb.

A Mass Spectrometry-Based Proteomics Approach for Global and High-Confidence Protein R-Methylation Analysis.

Protein Arginine (R)-methylation is a widespread protein post-translational modification (PTM) involved in the regulation of several cellular pathways, including RNA processing, signal transduction, DNA damage response, miRNA biogenesis, and translation. In recent years, thanks to biochemical and analytical developments, mass spectrometry (MS)-based proteomics has emerged as the most effective strategy to characterize the cellular methyl-proteome with single-site resolution. However, identifying and profiling in vivo protein R-methylation by MS remains challenging and error-prone, mainly due to the substoichiometric nature of this modification and the presence of various amino acid substitutions and chemical methyl-esterification of acidic residues that are isobaric to methylation. Thus, enrichment methods to enhance the identification of R-methyl-peptides and orthogonal validation strategies to reduce False Discovery Rates (FDR) in methyl-proteomics studies are required. Here, a protocol specifically designed for high-confidence R-methyl-peptides identification and quantitation from cellular samples is described, which couples metabolic labeling of cells with heavy isotope-encoded Methionine (hmSILAC) and dual protease in-solution digestion of whole cell extract, followed by off-line High-pH Reversed Phase (HpH-RP) chromatography fractionation and affinity enrichment of R-methyl-peptides using anti-pan-R-methyl antibodies. Upon high-resolution MS analysis, raw data are first processed with the MaxQuant software package and the results are then analyzed by hmSEEKER, a software designed for the in-depth search of MS peak pairs corresponding to light and heavy methyl-peptide within the MaxQuant output files.

Systematic Analysis of the Impact of R-Methylation on RBPs-RNA Interactions: A Proteomic Approach.

RNA binding proteins (RBPs) bind RNAs through specific RNA-binding domains, generating multi-molecular complexes known as ribonucleoproteins (RNPs). Various post-translational modifications (PTMs) have been described to regulate RBP structure, subcellular localization, and interactions with other proteins or RNAs. Recent proteome-wide experiments showed that RBPs are the most representative group within the class of arginine (R)-methylated proteins. Moreover, emerging evidence suggests that this modification plays a role in the regulation of RBP-RNA interactions. Nevertheless, a systematic analysis of how changes in protein-R-methylation can affect globally RBPs-RNA interactions is still missing. We describe here a quantitative proteomics approach to profile global changes of RBP-RNA interactions upon the modulation of type I and II protein arginine methyltransferases (PRMTs). By coupling the recently described Orthogonal Organic Phase Separation (OOPS) strategy with the Stable Isotope Labelling with Amino acids in Cell culture (SILAC) and pharmacological modulation of PRMTs, we profiled RNA-protein interaction dynamics in dependence of protein-R-methylation. Data are available via ProteomeXchange with identifier PXD024601.

PRMT1 Is Recruited via DNA-PK to Chromatin Where It Sustains the Senescence-Associated Secretory Phenotype in Response to Cisplatin.

Protein arginine methyltransferase 1 (PRMT1) is overexpressed in various human cancers and linked to poor response to chemotherapy. Various PRMT1 inhibitors are currently under development; yet, we do not fully understand the mechanisms underpinning PRMT1 involvement in tumorigenesis and chemoresistance. Using mass spectrometry-based proteomics, we identified PRMT1 as regulator of arginine methylation in ovarian cancer cells treated with cisplatin. We showed that DNA-dependent protein kinase (DNA-PK) binds to and phosphorylates PRMT1 in response to cisplatin, inducing its chromatin recruitment and redirecting its enzymatic activity toward Arg3 of histone H4 (H4R3). On chromatin, the DNA-PK/PRMT1 axis induces senescence-associated secretory phenotype through H4R3me2a deposition at pro-inflammatory gene promoters. Finally, PRMT1 inhibition reduces the clonogenic growth of cancer cells exposed to low doses of cisplatin, sensitizing them to apoptosis. While unravelling the role of PRMT1 in response to genotoxic agents, our findings indicate the possibility of targeting PRMT1 to overcome chemoresistance in cancer.

PRMT1-mediated methylation of the microprocessor-associated proteins regulates microRNA biogenesis.

MicroRNA (miRNA) biogenesis is a tightly controlled multi-step process operated in the nucleus by the activity of the Microprocessor and its associated proteins. Through high resolution mass spectrometry (MS)- proteomics we discovered that this complex is extensively methylated, with 84 methylated sites associated to 19 out of its 24 subunits. The majority of the modifications occurs on arginine (R) residues (61), leading to 81 methylation events, while 30 lysine (K)-methylation events occurs on 23 sites of the complex. Interestingly, both depletion and pharmacological inhibition of the Type-I Protein Arginine Methyltransferases (PRMTs) lead to a widespread change in the methylation state of the complex and induce global decrease of miRNA expression, as a consequence of the impairment of the pri-to-pre-miRNA processing step. In particular, we show that the reduced methylation of the Microprocessor subunit ILF3 is linked to its diminished binding to the pri-miRNAs miR-15a/16, miR-17-92, miR-301a and miR-331. Our study uncovers a previously uncharacterized role of R-methylation in the regulation of miRNA biogenesis in mammalian cells.