: 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.

ProMetheusDB: An In-Depth Analysis of the High-Quality Human Methyl-proteome / E. Massignani, R. Giambruno, M. Maniaci, L. Nicosia, A. Yadav, A. Cuomo, F. Raimondi, T. Bonaldi. - In: MOLECULAR & CELLULAR PROTEOMICS. - ISSN 1535-9484. - 21:7(2022 Jul), p. 100243. [10.1016/j.mcpro.2022.100243]

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

E. Massignani
Primo
Software
;
M. Maniaci
Investigation
;
L. Nicosia
Investigation
;
T. Bonaldi
Ultimo
Project Administration
2022

Abstract

: 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.
PTM crosstalk; heavy methyl SILAC; machine learning; mass spectrometry; protein methylation; protein–protein interactions
Settore BIO/13 - Biologia Applicata
Settore INF/01 - Informatica
Settore BIO/10 - Biochimica
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/951172
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