MethylQuant: A Tool for Sensitive Validation of Enzyme-Mediated Protein Methylation Sites from Heavy-Methyl SILAC Data

Tracking DOT1L methyltransferase activity by stable isotope labelling using a selective synthetic co-factor

Epigenetic processes influence health and disease through mechanisms which alter gene expression. In contrast to genetic changes which affect DNA sequences, epigenetic marks include DNA base modifications or post-translational modification (PTM) of proteins. Histone methylation is a prominent and versatile example of an epigenetic marker: gene expression or silencing is dependent on the location and extent of the methylation. Protein methyltransferases exhibit functional redundancy and broad preferences for multiple histone residues, which presents a challenge for the study of their individual activities. We developed an isotopically labelled analogue of co-factor S-adenosyl-L-methionine (13CD3-BrSAM), with selectivity for the histone lysine methyltransferase DOT1L, permitting tracking of methylation activity by mass spectrometry (MS). This concept could be applied to other methyltransferases, linking PTM discovery to enzymatic mediators.

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.

Advances in enrichment methods for mass spectrometry-based proteomics analysis of post-translational modifications

Post-translational modifications (PTMs) occur during or after protein biosynthesis and increase the functional diversity of proteome. They comprise phosphorylation, acetylation, methylation, glycosylation, ubiquitination, sumoylation (among many other modifications), and influence all aspects of cell biology. Mass-spectrometry (MS)-based proteomics is the most powerful approach for PTM analysis. Despite this, it is challenging due to low abundance and labile nature of many PTMs. Hence, enrichment of modified peptides is required for MS analysis. This review provides an overview of most common PTMs and a discussion of current enrichment methods for MS-based proteomics analysis. The traditional affinity strategies, including immunoenrichment, chromatography and protein pull-down, are outlined together with their strengths and shortcomings. Moreover, a special attention is paid to chemical enrichment strategies, such as capture by chemoselective probes, metabolic and chemoenzymatic labelling, which are discussed with an emphasis on their recent progress. Finally, the challenges and future trends in the field are discussed.

Differential Proteome and Interactome Analysis Reveal the Basis of Pleiotropy Associated With the Histidine Methyltransferase Hpm1p

The methylation of histidine is a post-translational modification whose function is poorly understood. Methyltransferase histidine protein methyltransferase 1 (Hpm1p) monomethylates H243 in the ribosomal protein Rpl3p and represents the only known histidine methyltransferase in Saccharomyces cerevisiae. Interestingly, the hpm1 deletion strain is highly pleiotropic, with many extraribosomal phenotypes including improved growth rates in alternative carbon sources. Here, we investigate how the loss of histidine methyltransferase Hpm1p results in diverse phenotypes, through use of targeted mass spectrometry (MS), growth assays, quantitative proteomics, and differential crosslinking MS. We confirmed the localization and stoichiometry of the H243 methylation site, found unreported sensitivities of Δhpm1 yeast to nonribosomal stressors, and identified differentially abundant proteins upon hpm1 knockout with clear links to the coordination of sugar metabolism. We adapted the emerging technique of quantitative large-scale stable isotope labeling of amino acids in cell culture crosslinking MS for yeast, which resulted in the identification of 1267 unique in vivo lysine-lysine crosslinks. By reproducibly monitoring over 350 of these in WT and Δhpm1, we detected changes to protein structure or protein-protein interactions in the ribosome, membrane proteins, chromatin, and mitochondria. Importantly, these occurred independently of changes in protein abundance and could explain a number of phenotypes of Δhpm1, not addressed by expression analysis. Further to this, some phenotypes were predicted solely from changes in protein structure or interactions and could be validated by orthogonal techniques. Taken together, these studies reveal a broad role for Hpm1p in yeast and illustrate how crosslinking MS will be an essential tool for understanding complex phenotypes.

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.

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hmSEEKER 2.0 identifies methyl-peptides from hmSILAC data through machine learning.

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Arginine methylation plays a role in modulating protein–protein interactions.

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Arginine methylations occur more frequently in proximity of phosphorylation sites.

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hmSEEKER 2.0 was used to identify methylations occurring on nonstandard amino acids.

Discovery of Arginine Methylation, Phosphorylation, and Their Co-occurrence in Condensate-Associated Proteins in Saccharomyces cerevisiae

The formation of condensates in membraneless organelles is thought to be driven by protein phase separation. Arginine methylation and serine/threonine phosphorylation are important in the phase separation process; however, these post-translational modifications are often present in intrinsically disordered regions that are difficult to analyze with standard proteomic techniques. To understand their presence and co-occurrence in condensate-associated proteins, here, we use a multiprotease and multi-tandem mass spectrometry (MS/MS) fragmentation approach, coupled with heavy methyl stable isotope labeling of amino acids in cell culture (SILAC) and phospho- or methyl-peptide enrichment. For Saccharomyces cerevisiae, we report a 50% increase in the known arginine methylproteome, involving 15 proteins that are all condensate-associated. Importantly, some of these proteins have arginine methylation on all predicted sites-providing evidence that this modification can be pervasive. We explored whether arginine-methylated, condensate-associated proteins are also phosphorylated and found 12 such proteins to carry phosphorylated serine or threonine. In Npl3, Ded1, and Sbp1, single peptides were found to carry both modifications, indicating a co-occurrence in close proximity and on the same protein molecule. These co-modifications occur in regions of disorder, whereas arginine methylation is typically on regions of disorder that are also basic. For phosphorylation, its association with charged regions of condensate-associated proteins was less consistent, although some regions with multisite phosphorylation sites were strongly acidic. We conclude that arginine-methylated proteins associated with condensates are typically also modified with protein phosphorylation.

An efficient approach based on basic strong cation exchange chromatography for enriching methylated peptides with high specificity for methylproteomics analysis

Protein methylation as one of the most important post-translational modifications has been under the spotlight due to its essential role in many biological processes. Development of methods for large-scale analysis of protein methylation greatly accelerates the related researches. To date, antibody-based enrichment strategy is the most common approach for methylproteomics analysis. However, it is still lacking of a pan-specific antibody to enrich peptides or proteins carrying all kinds of lysine and arginine methylation forms. Herein, an online basic strong cation exchange chromatography was developed to enrich methylated peptides from protein digests prepared by two complementary methods, including direct multiple enzymes digestion and carboxylic amidation followed by multiple enzymes digestion. After enrichment, the majority of identifications were obtained from direct multiple enzymes digested sample. The enrichment specificity of methylated peptides was up to 28.5%, and 445 methylation forms corresponding to 376 methylation sites were identified on 194 proteins in one LC-MS/MS run using only 100 μg of digests. This method has great potential in studying protein methylation mediated biological processes.

Non-Histone Protein Methylation: Biological Significance and Bioengineering Potential

Protein methylation is a key post-translational modification whose effects on gene expression have been intensively studied over the last two decades. Recently, renewed interest in non-histone protein methylation has gained momentum for its role in regulating important cellular processes and the activity of many proteins, including transcription factors, enzymes, and structural complexes. The extensive and dynamic role that protein methylation plays within the cell also highlights its potential for bioengineering applications. Indeed, while synthetic histone protein methylation has been extensively used to engineer gene expression, engineering of non-histone protein methylation has not been fully explored yet. Here, we report the latest findings, highlighting how non-histone protein methylation is fundamental for certain cellular functions and is implicated in disease, and review recent efforts in the engineering of protein methylation.

Biochemical and Computational Approaches for the Large-Scale Analysis of Protein Arginine Methylation by Mass Spectrometry

The absence of efficient mass spectrometry-based approaches for the large-scale analysis of protein arginine methylation has hindered the understanding of its biological role, beyond the transcriptional regulation occurring through histone modification. In the last decade, however, several technological advances of both the biochemical methods for methylated polypeptide enrichment and the computational pipelines for MS data analysis have considerably boosted this research field, generating novel insights about the extent and role of this post-translational modification. Here, we offer an overview of state-of-the-art approaches for the high-confidence identification and accurate quantification of protein arginine methylation by high-resolution mass spectrometry methods, which comprise the development of both biochemical and bioinformatics methods. The further optimization and systematic application of these analytical solutions will lead to ground-breaking discoveries on the role of protein methylation in biological processes.

The one-carbon pool controls mitochondrial energy metabolism via complex I and iron-sulfur clusters

Induction of the one-carbon cycle is an early hallmark of mitochondrial dysfunction and cancer metabolism. Vital intermediary steps are localized to mitochondria, but it remains unclear how one-carbon availability connects to mitochondrial function. Here, we show that the one-carbon metabolite and methyl group donor S-adenosylmethionine (SAM) is pivotal for energy metabolism. A gradual decline in mitochondrial SAM (mitoSAM) causes hierarchical defects in fly and mouse, comprising loss of mitoSAM-dependent metabolites and impaired assembly of the oxidative phosphorylation system. Complex I stability and iron-sulfur cluster biosynthesis are directly controlled by mitoSAM levels, while other protein targets are predominantly methylated outside of the organelle before import. The mitoSAM pool follows its cytosolic production, establishing mitochondria as responsive receivers of one-carbon units. Thus, we demonstrate that cellular methylation potential is required for energy metabolism, with direct relevance for pathophysiology, aging, and cancer.

Inhibiting Arginine Methylation as a Tool to Investigate Cross-Talk with Methylation and Acetylation Post-Translational Modifications in a Glioblastoma Cell Line

Glioblastomas (GBM) are the most common grade 4 brain tumours; patients have very poor prognosis with an average survival of 15 months after diagnosis. Novel research lines have begun to explore aberrant protein arginine methylation (ArgMe) as a possible therapeutic target in GBM and ArgMe inhibitors are currently in clinical trials. Enzymes known as protein arginine methyltransferases (PRMT1-9) can lead to mono- or di-ArgMe, and in the latter case symmetric or asymmetric dimethylation (SDMA and ADMA, respectively). Using the most common GBM cell line, we have profiled the expression of PRMTs, used ArgMe inhibitors as tools to investigate post-translational modifications cross-talk and measured the effect of ArgMe inhibitors on cell viability. We have identified novel SDMA events upon inhibition of ADMA in GBM cells and spheroids. We have observed cross-talk between ADMA and lysine acetylation in GBM cells and platelets. Treatment of GBM cells with furamidine, a PRMT1 inhibitor, reduces cell viability in 2D and 3D models. These data provide new molecular understanding of a disease with unmet clinical needs.