Biochemical and computational methods for large-scale protein-arginine methylation analysis

Methylation (namely addition of a methyl group) of arginine amino acid residues of proteins is a post-translational modification (PTM) catalyzed by a family of nine enzymes called Protein Arginine Methyl-Transferases (PRMTs).

PRMTs have been gaining increasing attention in the scientific landscape due their role in several essential physiological processes and implication in various diseases, including cancer and neurological disorders; loss of PRMT1 is lethal at the early developmental stages, while overexpression is frequently observed in different tumor types and correlates with poor patient prognosis, suggesting that inhibition of PRMTs may represent an effective therapeutic approach in oncology. Moreover, PTM levels are deregulated in different tumor types, and both local and global changes in PTM of the DNA-associated proteins - the histones - are linked to Amyotrophic Lateral Sclerosis. Due to the large body of scientific evidence indicating their role in cell pathophysiology, several PRMT inhibitors have been designed and developed as a potential new class of drugs. For instance, a potent, reversible type I PRMT inhibitor has been shown to have anti-tumor effects in human cancer models and some of the molecular candidates have entered clinical trials for solid tumors and lymphomas.

Although it was first described in 1968, for almost 30 years, very little was known about the extent of protein arginine methylation, its effect on protein activity, and its biological role. The first PRMT, capable of catalyzing arginine methylation, was discovered in 1996 and, since then, nine proteins exerting the same functions have been discovered. However, inefficient analytical approaches have largely limited a comprehensive understanding of their biological function. Quantitative Mass spectrometry has emerged as the ideal analytical strategy to study the extent of protein arginine-methylation in model systems and identify PRMT targets, thus contributing substantial knowledge in this field."

Dr Tiziana Bonaldi, Group Leader at the European Institute of Oncology

In their article published in Current Protein & Peptide Science, Dr. Bonaldi and co-workers offer an overview on state-of-the-art arginine methyl-proteomics, describing the innovations that led - from the description by Mathias Mann's group of the first high-quality methyl-proteome in 2004 - to the latest studies that profile protein-methylation events occurring on hundreds of cellular proteins. Throughout this review, the authors describe the implementations both in the biochemical methods and in the computational methods for Mass spectrometry data analysis or the identification of sites of arginine methylation, discussing the pros and cons of the most common strategies employed.

Furthermore, relevant issues related to protein-arginine methylation analysis that are still under development are also discussed, such as the discrimination of symmetric and asymmetric arginine-di-methylation from Mass spectrometry fragmentation spectra. "These two modifications have identical mass, yet they are catalyzed by different PRMTs and have substantially different biological outcomes," explains Bonaldi; "Indeed, even though, for instance, both have a role in regulation of transcription, while asymmetric di-methylation is activating, symmetric di-methylation is repressive. Therefore, being able to distinguish between the two processes is crucial."

Finally, major emphasis is devoted to the heavy methyl SILAC strategy, a variation of the more conventional SILAC (Stable Isotope Labelling with Amino acids in Cell culture). "The heavy methyl SILAC strategy was designed to increase the confidence of in vivo arginine methyl-peptides identification by Mass spectrometry," - continues Bonaldi - "and the use will be facilitated by the recent development of ad hoc algorithms tailored for processing of heavy methyl SILAC datasets, such as MethylQuant and hmSEEKER."

Importantly, the authors conclude that optimization of the currently available analytical approaches and their systematic application will play a key role in the future research on the involvement of protein methylation in biological processes, providing critical insights in the related cellular biology processes and likely offering potential novel targets to be exploited in a clinical context.