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Current Protein & Peptide Science

Editor-in-Chief

ISSN (Print): 1389-2037
ISSN (Online): 1875-5550

Review Article

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

Author(s): Daniele Musiani, Enrico Massignani, Alessandro Cuomo, Avinash Yadav and Tiziana Bonaldi*

Volume 21 , Issue 7 , 2020

Page: [725 - 739] Pages: 15

DOI: 10.2174/1389203721666200426232531

Price: $65

Abstract

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.

Keywords: Protein arginine methylation, mass spectrometry, proteomics, computational pipelines, methyl-peptide enrichment, protein arginine methyltransferases.

Graphical Abstract
[1]
Bulau, P.; Zakrzewicz, D.; Kitowska, K.; Wardega, B.; Kreuder, J.; Eickelberg, O. Quantitative assessment of arginine methylation in free versus protein-incorporated amino acids in vitro and in vivo using protein hydrolysis and high-performance liquid chromatography. Biotechniques, 2006, 40(3), 305-310.
[http://dx.doi.org/10.2144/000112081] [PMID: 16568819]
[2]
Uhlmann, T.; Geoghegan, V.L.; Thomas, B.; Ridlova, G.; Trudgian, D.C.; Acuto, O. A method for large-scale identification of protein arginine methylation. Mol. Cell. Proteomics, 2012, 11(11), 1489-1499.
[http://dx.doi.org/10.1074/mcp.M112.020743] [PMID: 22865923]
[3]
Paik, W.K.; Kim, S. Protein methylation. Science, 1971, 174(4005), 114-119.
[http://dx.doi.org/10.1126/science.174.4005.114] [PMID: 5119619]
[4]
Gary, J.D.; Lin, W.J.; Yang, M.C.; Herschman, H.R.; Clarke, S. The predominant protein-arginine methyltransferase from Saccharomyces cerevisiae. J. Biol. Chem., 1996, 271(21), 12585-12594.
[http://dx.doi.org/10.1074/jbc.271.21.12585] [PMID: 8647869]
[5]
Evich, M.; Stroeva, E.; Zheng, Y. G.; Germann, M. W. Effect of methylation on the side-chain pKa value of arginine. Protein science : A publication of the Protein Society, 2016, 25(2), 479-86.
[6]
Bezzi, M.; Teo, S.X.; Muller, J.; Mok, W.C.; Sahu, S.K.; Vardy, L.A.; Bonday, Z.Q.; Guccione, E. Regulation of constitutive and alternative splicing by PRMT5 reveals a role for Mdm4 pre-mRNA in sensing defects in the spliceosomal machinery. Genes Dev., 2013, 27(17), 1903-1916.
[http://dx.doi.org/10.1101/gad.219899.113] [PMID: 24013503]
[7]
Auclair, Y.; Richard, S. The role of arginine methylation in the DNA damage response. DNA Repair (Amst.), 2013, 12(7), 459-465.
[http://dx.doi.org/10.1016/j.dnarep.2013.04.006] [PMID: 23684798]
[8]
Blanc, R.S.; Richard, S. Arginine Methylation: The Coming of Age. Mol. Cell, 2017, 65(1), 8-24.
[http://dx.doi.org/10.1016/j.molcel.2016.11.003] [PMID: 28061334]
[9]
Bedford, M.T.; Clarke, S.G. Protein arginine methylation in mammals: who, what, and why. Mol. Cell, 2009, 33(1), 1-13.
[http://dx.doi.org/10.1016/j.molcel.2008.12.013] [PMID: 19150423]
[10]
Chang, B.; Chen, Y.; Zhao, Y.; Bruick, R.K. JMJD6 is a histone arginine demethylase. Science, 2007, 318(5849), 444-447.
[http://dx.doi.org/10.1126/science.1145801] [PMID: 17947579]
[11]
Walport, L.J.; Hopkinson, R.J.; Chowdhury, R.; Schiller, R.; Ge, W.; Kawamura, A.; Schofield, C.J. Arginine demethylation is catalysed by a subset of JmjC histone lysine demethylases. Nat. Commun., 2016, 7, 11974.
[http://dx.doi.org/10.1038/ncomms11974] [PMID: 27337104]
[12]
Böttger, A.; Islam, M.S.; Chowdhury, R.; Schofield, C.J.; Wolf, A. The oxygenase Jmjd6--a case study in conflicting assignments. Biochem. J., 2015, 468(2), 191-202.
[http://dx.doi.org/10.1042/BJ20150278] [PMID: 25997831]
[13]
Webby, C.J.; Wolf, A.; Gromak, N.; Dreger, M.; Kramer, H.; Kessler, B.; Nielsen, M.L.; Schmitz, C.; Butler, D.S.; Yates, J.R., III; Delahunty, C.M.; Hahn, P.; Lengeling, A.; Mann, M.; Proudfoot, N.J.; Schofield, C.J.; Böttger, A. Jmjd6 catalyses lysyl-hydroxylation of U2AF65, a protein associated with RNA splicing. Science, 2009, 325(5936), 90-93.
[http://dx.doi.org/10.1126/science.1175865] [PMID: 19574390]
[14]
Carlson, S.M.; Gozani, O. Emerging technologies to map the protein methylome. J. Mol. Biol., 2014, 426(20), 3350-3362.
[http://dx.doi.org/10.1016/j.jmb.2014.04.024] [PMID: 24805349]
[15]
Bikkavilli, R.K.; Avasarala, S.; Van Scoyk, M.; Karuppusamy Rathinam, M.K.; Tauler, J.; Borowicz, S.; Winn, R.A. In vitro methylation assay to study protein arginine methylation. J. Vis. Exp., 2014, (92)e51997
[http://dx.doi.org/10.3791/51997] [PMID: 25350748]
[16]
Dhar, S.; Vemulapalli, V.; Patananan, A.N.; Huang, G.L.; Di Lorenzo, A.; Richard, S.; Comb, M.J.; Guo, A.; Clarke, S.G.; Bedford, M.T. Loss of the major Type I arginine methyltransferase PRMT1 causes substrate scavenging by other PRMTs. Sci. Rep., 2013, 3, 1311.
[http://dx.doi.org/10.1038/srep01311] [PMID: 23419748]
[17]
Musiani, D.; Bok, J.; Massignani, E.; Wu, L.; Tabaglio, T.; Ippolito, M.R.; Cuomo, A.; Ozbek, U.; Zorgati, H.; Ghoshdastider, U.; Robinson, R.C.; Guccione, E.; Bonaldi, T. Proteomics profiling of arginine methylation defines PRMT5 substrate specificity. Sci. Signal., 2019, 12(575)eaat8388
[http://dx.doi.org/10.1126/scisignal.aat8388] [PMID: 30940768]
[18]
Bremang, M.; Cuomo, A.; Agresta, A.M.; Stugiewicz, M.; Spadotto, V.; Bonaldi, T. Mass spectrometry-based identification and characterisation of lysine and arginine methylation in the human proteome. Mol. Biosyst., 2013, 9(9), 2231-2247.
[http://dx.doi.org/10.1039/c3mb00009e] [PMID: 23748837]
[19]
Sylvestersen, K.B.; Horn, H.; Jungmichel, S.; Jensen, L.J.; Nielsen, M.L. Proteomic analysis of arginine methylation sites in human cells reveals dynamic regulation during transcriptional arrest. Mol. Cell. Proteomics, 2014, 13(8), 2072-2088.
[http://dx.doi.org/10.1074/mcp.O113.032748] [PMID: 24563534]
[20]
Larsen, S.C.; Sylvestersen, K.B.; Mund, A.; Lyon, D.; Mullari, M.; Madsen, M.V.; Daniel, J.A.; Jensen, L.J.; Nielsen, M.L. Proteome-wide analysis of arginine monomethylation reveals widespread occurrence in human cells. Sci. Signal., 2016, 9(443), rs9.
[http://dx.doi.org/10.1126/scisignal.aaf7329] [PMID: 27577262]
[21]
Ong, S.E.; Mittler, G.; Mann, M. Identifying and quantifying in vivo methylation sites by heavy methyl SILAC. Nat. Methods, 2004, 1(2), 119-126.
[http://dx.doi.org/10.1038/nmeth715] [PMID: 15782174]
[22]
Guo, A.; Gu, H.; Zhou, J.; Mulhern, D.; Wang, Y.; Lee, K.A.; Yang, V.; Aguiar, M.; Kornhauser, J.; Jia, X.; Ren, J.; Beausoleil, S.A.; Silva, J.C.; Vemulapalli, V.; Bedford, M.T.; Comb, M.J. Immunoaffinity enrichment and mass spectrometry analysis of protein methylation. Mol. Cell. Proteomics, 2014, 13(1), 372-387.
[http://dx.doi.org/10.1074/mcp.O113.027870] [PMID: 24129315]
[23]
Shishkova, E.; Zeng, H.; Liu, F.; Kwiecien, N.W.; Hebert, A.S.; Coon, J.J.; Xu, W. Global mapping of CARM1 substrates defines enzyme specificity and substrate recognition. Nat. Commun., 2017, 8, 15571.
[http://dx.doi.org/10.1038/ncomms15571] [PMID: 28537268]
[24]
Gayatri, S.; Cowles, M.W.; Vemulapalli, V.; Cheng, D.; Sun, Z.W.; Bedford, M.T. Using oriented peptide array libraries to evaluate methylarginine-specific antibodies and arginine methyltransferase substrate motifs. Sci. Rep., 2016, 6, 28718.
[http://dx.doi.org/10.1038/srep28718] [PMID: 27338245]
[25]
McNulty, D.E.; Annan, R.S. Hydrophilic interaction chromatography reduces the complexity of the phosphoproteome and improves global phosphopeptide isolation and detection. Mol. Cell. Proteomics, 2008, 7(5), 971-980.
[http://dx.doi.org/10.1074/mcp.M700543-MCP200] [PMID: 18212344]
[26]
Wang, K.; Dong, M.; Mao, J.; Wang, Y.; Jin, Y.; Ye, M.; Zou, H. Antibody-Free Approach for the Global Analysis of Protein Methylation. Anal. Chem., 2016, 88(23), 11319-11327.
[http://dx.doi.org/10.1021/acs.analchem.6b02872] [PMID: 27801567]
[27]
Batth, T.S.; Francavilla, C.; Olsen, J.V. Off-line high-pH reversed-phase fractionation for in-depth phosphoproteomics. J. Proteome Res., 2014, 13(12), 6176-6186.
[http://dx.doi.org/10.1021/pr500893m] [PMID: 25338131]
[28]
Hartel, N.; Chew, B.; Qin, J.; Xu, J.; Graham, N.A. Deep protein methylation profiling by combined chemical and immunoaffinity approaches reveals novel PRMT1 targets. Mol. Cell. Proteomics, 2019, 18(11), 2149-2164.
[http://dx.doi.org/10.1074/mcp.RA119.001625]] [PMID: 31451547]
[29]
Huesgen, P.F.; Lange, P.F.; Rogers, L.D.; Solis, N.; Eckhard, U.; Kleifeld, O.; Goulas, T.; Gomis-Rüth, F.X.; Overall, C.M. LysargiNase mirrors trypsin for protein C-terminal and methylation-site identification. Nat. Methods, 2015, 12(1), 55-58.
[http://dx.doi.org/10.1038/nmeth.3177] [PMID: 25419962]
[30]
Chen, C.; Nott, T.J.; Jin, J.; Pawson, T. Deciphering arginine methylation: Tudor tells the tale. Nat. Rev. Mol. Cell Biol., 2011, 12(10), 629-642.
[http://dx.doi.org/10.1038/nrm3185] [PMID: 21915143]
[31]
Gayatri, S.; Bedford, M.T. Readers of histone methylarginine marks. Biochim. Biophys. Acta, 2014, 1839(8), 702-710.
[http://dx.doi.org/10.1016/j.bbagrm.2014.02.015] [PMID: 24583552]
[32]
Moore, K.E.; Carlson, S.M.; Camp, N.D.; Cheung, P.; James, R.G.; Chua, K.F.; Wolf-Yadlin, A.; Gozani, O. A general molecular affinity strategy for global detection and proteomic analysis of lysine methylation. Mol. Cell, 2013, 50(3), 444-456.
[http://dx.doi.org/10.1016/j.molcel.2013.03.005] [PMID: 23583077]
[33]
Bian, Y.; Li, L.; Dong, M.; Liu, X.; Kaneko, T.; Cheng, K.; Liu, H.; Voss, C.; Cao, X.; Wang, Y.; Litchfield, D.; Ye, M.; Li, S.S.; Zou, H. Ultra-deep tyrosine phosphoproteomics enabled by a phosphotyrosine superbinder. Nat. Chem. Biol., 2016, 12(11), 959-966.
[http://dx.doi.org/10.1038/nchembio.2178] [PMID: 27642862]
[34]
Wu, Z.; Cheng, Z.; Sun, M.; Wan, X.; Liu, P.; He, T.; Tan, M.; Zhao, Y. A chemical proteomics approach for global analysis of lysine monomethylome profiling. Mol. Cell. Proteomics, 2015, 14(2), 329-339.
[http://dx.doi.org/10.1074/mcp.M114.044255] [PMID: 25505155]
[35]
Spadotto, V.; Giambruno, R.; Massignani, E.; Mihailovich, M.; Maniaci, M.; Patuzzo, F.; Ghini, F.; Nicassio, F.; Bonaldi, T. PRMT1-mediated methylation of the microprocessor-associated proteins regulates microRNA biogenesis. Nucleic Acids Res., 2020, 48(1), 96-115.
[http://dx.doi.org/10.1093/nar/gkz1051] [PMID: 31777917]
[36]
Eng, J.K.; McCormack, A.L.; Yates, J.R. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom., 1994, 5(11), 976-989.
[http://dx.doi.org/10.1016/1044-0305(94)80016-2] [PMID: 24226387]
[37]
Cox, J.; Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol., 2008, 26(12), 1367-1372.
[http://dx.doi.org/10.1038/nbt.1511] [PMID: 19029910]
[38]
Cox, J.; Neuhauser, N.; Michalski, A.; Scheltema, R.A.; Olsen, J.V.; Mann, M. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res., 2011, 10(4), 1794-1805.
[http://dx.doi.org/10.1021/pr101065j] [PMID: 21254760]
[39]
Perkins, D.N.; Pappin, D.J.; Creasy, D.M.; Cottrell, J.S. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis, 1999, 20(18), 3551-3567.
[http://dx.doi.org/10.1002/(SICI)1522-2683(19991201)20:18<3551:AID-ELPS3551>3.0.CO;2-2] [PMID: 10612281]
[40]
Geer, L.Y.; Markey, S.P.; Kowalak, J.A.; Wagner, L.; Xu, M.; Maynard, D.M.; Yang, X.; Shi, W.; Bryant, S.H. Open mass spectrometry search algorithm. J. Proteome Res., 2004, 3(5), 958-964.
[http://dx.doi.org/10.1021/pr0499491] [PMID: 15473683]
[41]
Craig, R.; Beavis, R.C. TANDEM: matching proteins with tandem mass spectra. Bioinformatics, 2004, 20(9), 1466-1467.
[http://dx.doi.org/10.1093/bioinformatics/bth092] [PMID: 14976030]
[42]
Thandapani, P.; O’Connor, T.R.; Bailey, T.L.; Richard, S. Defining the RGG/RG motif. Mol. Cell, 2013, 50(5), 613-623.
[http://dx.doi.org/10.1016/j.molcel.2013.05.021] [PMID: 23746349]
[43]
Mortensen, P.; Gouw, J.W.; Olsen, J.V.; Ong, S.E.; Rigbolt, K.T.; Bunkenborg, J.; Cox, J.; Foster, L.J.; Heck, A.J.; Blagoev, B.; Andersen, J.S.; Mann, M. MSQuant, an open source platform for mass spectrometry-based quantitative proteomics. J. Proteome Res., 2010, 9(1), 393-403.
[http://dx.doi.org/10.1021/pr900721e] [PMID: 19888749]
[44]
Tyanova, S.; Temu, T.; Carlson, A.; Sinitcyn, P.; Mann, M.; Cox, J. Visualization of LC-MS/MS proteomics data in MaxQuant. Proteomics, 2015, 15(8), 1453-1456.
[http://dx.doi.org/10.1002/pmic.201400449] [PMID: 25644178]
[45]
Hart-Smith, G.; Yagoub, D.; Tay, A.P.; Pickford, R.; Wilkins, M.R. Large Scale Mass Spectrometry-based Identifications of Enzyme-mediated Protein Methylation Are Subject to High False Discovery Rates. Mol. Cell. Proteomics, 2016, 15(3), 989-1006.
[http://dx.doi.org/10.1074/mcp.M115.055384] [PMID: 26699799]
[46]
Ong, S.E.; Mann, M. Identifying and quantifying sites of protein methylation by heavy methyl SILAC. Curr Protoc Protein Sci, 2006, Chapter 14 : Unit 14.9; , 2006.
[http://dx.doi.org/10.1002/0471140864.ps1409s46]
[47]
Geoghegan, V.; Guo, A.; Trudgian, D.; Thomas, B.; Acuto, O. Comprehensive identification of arginine methylation in primary T cells reveals regulatory roles in cell signalling. Nat. Commun., 2015, 6, 6758.
[http://dx.doi.org/10.1038/ncomms7758] [PMID: 25849564]
[48]
Tay, A.P.; Geoghegan, V.; Yagoub, D.; Wilkins, M.R.; Hart-Smith, G. MethylQuant: A Tool for Sensitive Validation of Enzyme-Mediated Protein Methylation Sites from Heavy-Methyl SILAC Data. J. Proteome Res., 2018, 17(1), 359-373.
[http://dx.doi.org/10.1021/acs.jproteome.7b00601] [PMID: 29057651]
[49]
Massignani, E.; Cuomo, A.; Musiani, D.; Jammula, S.; Pavesi, G.; Bonaldi, T. hmSEEKER: Identification of hmSILAC Doublets in MaxQuant Output Data. Proteomics, 2019, 19(5)e1800300
[http://dx.doi.org/10.1002/pmic.201800300] [PMID: 30656827]
[50]
Wang, H.; Huang, Z.Q.; Xia, L.; Feng, Q.; Erdjument-Bromage, H.; Strahl, B.D.; Briggs, S.D.; Allis, C.D.; Wong, J.; Tempst, P.; Zhang, Y. Methylation of histone H4 at arginine 3 facilitating transcriptional activation by nuclear hormone receptor. Science, 2001, 293(5531), 853-857.
[http://dx.doi.org/10.1126/science.1060781] [PMID: 11387442]
[51]
Sun, L.; Wang, M.; Lv, Z.; Yang, N.; Liu, Y.; Bao, S.; Gong, W.; Xu, R.M. Structural insights into protein arginine symmetric dimethylation by PRMT5. Proc. Natl. Acad. Sci. USA, 2011, 108(51), 20538-20543.
[http://dx.doi.org/10.1073/pnas.1106946108] [PMID: 22143770]
[52]
Brame, C.J.; Moran, M.F.; McBroom-Cerajewski, L.D. A mass spectrometry based method for distinguishing between symmetrically and asymmetrically dimethylated arginine residues. Rapid Commun. Mass Spectrom., 2004, 18(8), 877-881.
[http://dx.doi.org/10.1002/rcm.1421] [PMID: 15095356]
[53]
Dorl, S.; Winkler, S.; Mechtler, K.; Dorfer, V. PhoStar: Identifying Tandem Mass Spectra of Phosphorylated Peptides before Database Search. J. Proteome Res., 2018, 17(1), 290-295.
[http://dx.doi.org/10.1021/acs.jproteome.7b00563] [PMID: 29057658]
[54]
Kelstrup, C.D.; Frese, C.; Heck, A.J.; Olsen, J.V.; Nielsen, M.L. Analytical utility of mass spectral binning in proteomic experiments by SPectral Immonium Ion Detection (SPIID). Mol. Cell. Proteomics, 2014, 13(8), 1914-1924.
[http://dx.doi.org/10.1074/mcp.O113.035915] [PMID: 24895383]
[55]
Megger, D.A.; Pott, L.L.; Ahrens, M.; Padden, J.; Bracht, T.; Kuhlmann, K.; Eisenacher, M.; Meyer, H.E.; Sitek, B. Comparison of label-free and label-based strategies for proteome analysis of hepatoma cell lines. Biochim. Biophys. Acta, 2014, 1844(5), 967-976.
[http://dx.doi.org/10.1016/j.bbapap.2013.07.017] [PMID: 23954498]
[56]
Ong, S.E.; Blagoev, B.; Kratchmarova, I.; Kristensen, D.B.; Steen, H.; Pandey, A.; Mann, M. Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell. Proteomics, 2002, 1(5), 376-386.
[http://dx.doi.org/10.1074/mcp.M200025-MCP200] [PMID: 12118079]
[57]
Fong, J. Y.; Pignata, L.; Goy, P. A.; Kawabata, K. C.; Lee, S. C.; Koh, C. M.; Musiani, D.; Massignani, E.; Kotini, A. G.; Penson, A.; Wun, C. M.; Shen, Y.; Schwarz, M.; Low, D. H.; Rialdi, A.; Ki, M.; Wollmann, H.; Mzoughi, S.; Gay, F.; Thompson, C.; Hart, T.; Barbash, O.; Luciani, G. M.; Szewczyk, M. M.; Wouters, B. J.; Delwel, R.; Papapetrou, E. P.; Barsyte-Lovejoy, D.; Arrowsmith, C. H.; Minden, M. D.; Jin, J.; Melnick, A.; Bonaldi, T.; Abdel-Wahab, O.; Guccione, E. Therapeutic Targeting of RNA Splicing Catalysis through Inhibition of Protein Arginine Methylation. Cancer Cell,, 2019, 36(2), 194-209.e9
[http://dx.doi.org/10.1016/j.ccell.2019.07.003]
[58]
Cheung, N.; Fung, T.K.; Zeisig, B.B.; Holmes, K.; Rane, J.K.; Mowen, K.A.; Finn, M.G.; Lenhard, B.; Chan, L.C.; So, C.W. Targeting Aberrant Epigenetic Networks Mediated by PRMT1 and KDM4C in Acute Myeloid Leukemia. Cancer Cell, 2016, 29(1), 32-48.
[http://dx.doi.org/10.1016/j.ccell.2015.12.007] [PMID: 26766589]
[59]
Haynes, S.E.; Majmudar, J.D.; Martin, B.R. DIA-SIFT: A Precursor and Product Ion Filter for Accurate Stable Isotope Data-Independent Acquisition Proteomics. Anal. Chem., 2018, 90(15), 8722-8726.
[http://dx.doi.org/10.1021/acs.analchem.8b01618] [PMID: 29989796]
[60]
Ross, P.L.; Huang, Y.N.; Marchese, J.N.; Williamson, B.; Parker, K.; Hattan, S.; Khainovski, N.; Pillai, S.; Dey, S.; Daniels, S.; Purkayastha, S.; Juhasz, P.; Martin, S.; Bartlet-Jones, M.; He, F.; Jacobson, A.; Pappin, D.J. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol. Cell. Proteomics, 2004, 3(12), 1154-1169.
[http://dx.doi.org/10.1074/mcp.M400129-MCP200] [PMID: 15385600]
[61]
Thompson, A.; Schäfer, J.; Kuhn, K.; Kienle, S.; Schwarz, J.; Schmidt, G.; Neumann, T.; Johnstone, R.; Mohammed, A.K.; Hamon, C. Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal. Chem., 2003, 75(8), 1895-1904.
[http://dx.doi.org/10.1021/ac0262560] [PMID: 12713048]
[62]
Schoof, E.M.; Rapin, N.; Savickas, S.; Gentil, C.; Lechman, E.; Haile, J.S.; dem Keller, U.a.; Dick, J.E.; Porse, B.T. A Quantitative Single-Cell Proteomics Approach to Characterize an Acute Myeloid Leukemia Hierarchy. bioRxiv, 2019, •••745679
[63]
Hogrebe, A.; von Stechow, L.; Bekker-Jensen, D.B.; Weinert, B.T.; Kelstrup, C.D.; Olsen, J.V. Benchmarking common quantification strategies for large-scale phosphoproteomics. Nat. Commun., 2018, 9(1), 1045.
[http://dx.doi.org/10.1038/s41467-018-03309-6] [PMID: 29535314]
[64]
Wang, X.; Shen, S.; Rasam, S.S.; Qu, J. MS1 ion current-based quantitative proteomics: A promising solution for reliable analysis of large biological cohorts. Mass Spectrom. Rev., 2019, 38(6), 461-482.
[http://dx.doi.org/10.1002/mas.21595] [PMID: 30920002]
[65]
Wenger, C.D.; Phanstiel, D.H.; Lee, M.V.; Bailey, D.J.; Coon, J.J. COMPASS: a suite of pre- and post-search proteomics software tools for OMSSA. Proteomics, 2011, 11(6), 1064-1074.
[http://dx.doi.org/10.1002/pmic.201000616] [PMID: 21298793]
[66]
Horn, D. M.; Ueckert, T.; Fritzemeier, K.; Tham, K.; Paschke, C.; Berg, F.; Pfaff, H.; Jiang, X.; Li, S.; Lopez-Ferrer, D. New Method for Label-Free Quantification in the Proteome Discoverer Framework., 2016.
[67]
Bekker-Jensen, D.B.; Bernhardt, O.M.; Hogrebe, A.; del Val, A.M.; Verbeke, L.; Gandhi, T.; Kelstrup, C.D.; Reiter, L.; Olsen, J.V. Rapid and site-specific deep phosphoproteome profiling by data-independent acquisition (DIA) without the need for spectral libraries. bioRxiv, 2019, •••657858
[68]
Olsen, J.V.; Vermeulen, M.; Santamaria, A.; Kumar, C.; Miller, M.L.; Jensen, L.J.; Gnad, F.; Cox, J.; Jensen, T.S.; Nigg, E.A.; Brunak, S.; Mann, M. Quantitative phosphoproteomics reveals widespread full phosphorylation site occupancy during mitosis. Sci. Signal., 2010, 3(104), ra3.
[http://dx.doi.org/10.1126/scisignal.2000475] [PMID: 20068231]
[69]
Schneider, T.D.; Stephens, R.M. Sequence logos: a new way to display consensus sequences. Nucleic Acids Res., 1990, 18(20), 6097-6100.
[http://dx.doi.org/10.1093/nar/18.20.6097] [PMID: 2172928]
[70]
Crooks, G.E.; Hon, G.; Chandonia, J.M.; Brenner, S.E. WebLogo: A sequence logo generator. Genome Res., 2004, 14(6), 1188-1190.
[http://dx.doi.org/10.1101/gr.849004] [PMID: 15173120]
[71]
Maddelein, D.; Colaert, N.; Buchanan, I.; Hulstaert, N.; Gevaert, K.; Martens, L. The iceLogo web server and SOAP service for determining protein consensus sequences. Nucleic Acids Res., 2015, 43(W1)W543-6
[http://dx.doi.org/10.1093/nar/gkv385] [PMID: 25897125]
[72]
O’Shea, J.P.; Chou, M.F.; Quader, S.A.; Ryan, J.K.; Church, G.M.; Schwartz, D. pLogo: a probabilistic approach to visualizing sequence motifs. Nat. Methods, 2013, 10(12), 1211-1212.
[http://dx.doi.org/10.1038/nmeth.2646] [PMID: 24097270]
[73]
Schwartz, D.; Gygi, S.P. An iterative statistical approach to the identification of protein phosphorylation motifs from large-scale data sets. Nat. Biotechnol., 2005, 23(11), 1391-1398.
[http://dx.doi.org/10.1038/nbt1146] [PMID: 16273072]
[74]
Cheng, A.; Grant, C.E.; Noble, W.S.; Bailey, T.L. MoMo: discovery of statistically significant post-translational modification motifs. Bioinformatics, 2019, 35(16), 2774-2782.
[http://dx.doi.org/10.1093/bioinformatics/bty1058] [PMID: 30596994]
[75]
El-Gebali, S.; Mistry, J.; Bateman, A.; Eddy, S.R.; Luciani, A.; Potter, S.C.; Qureshi, M.; Richardson, L.J.; Salazar, G.A.; Smart, A.; Sonnhammer, E.L.L.; Hirsh, L.; Paladin, L.; Piovesan, D.; Tosatto, S.C.E.; Finn, R.D. The Pfam protein families database in 2019. Nucleic Acids Res., 2019, 47(D1), D427-D432.
[http://dx.doi.org/10.1093/nar/gky995] [PMID: 30357350]
[76]
Letunic, I.; Bork, P. 20 years of the SMART protein domain annotation resource. Nucleic Acids Res., 2018, 46(D1), D493-D496.
[http://dx.doi.org/10.1093/nar/gkx922] [PMID: 29040681]
[77]
Eden, E.; Navon, R.; Steinfeld, I.; Lipson, D.; Yakhini, Z. GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics, 2009, 10, 48.
[http://dx.doi.org/10.1186/1471-2105-10-48] [PMID: 19192299]
[78]
Supek, F.; Bošnjak, M.; Škunca, N.; Šmuc, T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS One, 2011, 6(7)e21800
[http://dx.doi.org/10.1371/journal.pone.0021800] [PMID: 21789182]
[79]
Reimand, J.; Kull, M.; Peterson, H.; Hansen, J.; Vilo, J. g:Profiler--a web-based toolset for functional profiling of gene lists from large-scale experiments. Nucleic Acids Res., 2007, 35W193-200
[80]
Sherman, B.T.; Huang, W.; Tan, Q.; Guo, Y.; Bour, S.; Liu, D.; Stephens, R.; Baseler, M.W.; Lane, H.C.; Lempicki, R.A. DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis. BMC Bioinformatics, 2007, 8, 426.
[http://dx.doi.org/10.1186/1471-2105-8-426] [PMID: 17980028]
[81]
Kanehisa, M.; Sato, Y.; Kawashima, M.; Furumichi, M.; Tanabe, M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res., 2016, 44(D1), D457-D462.
[http://dx.doi.org/10.1093/nar/gkv1070] [PMID: 26476454]
[82]
Joshi-Tope, G.; Gillespie, M.; Vastrik, I.; D’Eustachio, P.; Schmidt, E.; de Bono, B.; Jassal, B.; Gopinath, G.R.; Wu, G.R.; Matthews, L.; Lewis, S.; Birney, E.; Stein, L. Reactome: a knowledgebase of biological pathways. Nucleic Acids Res., 2005, 33(Database issue), D428-D432.
[http://dx.doi.org/10.1093/nar/gki072] [PMID: 15608231]
[83]
Wingender, E.; Chen, X.; Hehl, R.; Karas, H.; Liebich, I.; Matys, V.; Meinhardt, T.; Prüss, M.; Reuter, I.; Schacherer, F. TRANSFAC: an integrated system for gene expression regulation. Nucleic Acids Res., 2000, 28(1), 316-319.
[http://dx.doi.org/10.1093/nar/28.1.316] [PMID: 10592259]
[84]
Giurgiu, M.; Reinhard, J.; Brauner, B.; Dunger-Kaltenbach, I.; Fobo, G.; Frishman, G.; Montrone, C.; Ruepp, A. CORUM: the comprehensive resource of mammalian protein complexes-2019. Nucleic Acids Res., 2019, 47(D1), D559-D563.
[http://dx.doi.org/10.1093/nar/gky973] [PMID: 30357367]
[85]
Amberger, J.S.; Hamosh, A. Searching Online Mendelian Inheritance in Man (OMIM): A Knowledgebase of Human Genes and Genetic Phenotypes. Curr. Protoc. Bioinformatics, 2017, 58, 121-1212.
[86]
Subramanian, A.; Tamayo, P.; Mootha, V.K.; Mukherjee, S.; Ebert, B.L.; Gillette, M.A.; Paulovich, A.; Pomeroy, S.L.; Golub, T.R.; Lander, E.S.; Mesirov, J.P. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA, 2005, 102(43), 15545-15550.
[http://dx.doi.org/10.1073/pnas.0506580102] [PMID: 16199517]
[87]
Yakubu, R.R.; Silmon de Monerri, N.C.; Nieves, E.; Kim, K.; Weiss, L.M. Comparative Monomethylarginine Proteomics Suggests that Protein Arginine Methyltransferase 1 (PRMT1) is a Significant Contributor to Arginine Monomethylation in Toxoplasma gondii. Mol. Cell. Proteomics, 2017, 16(4), 567-580.
[http://dx.doi.org/10.1074/mcp.M117.066951] [PMID: 28143887]
[88]
Szklarczyk, D.; Morris, J.H.; Cook, H.; Kuhn, M.; Wyder, S.; Simonovic, M.; Santos, A.; Doncheva, N.T.; Roth, A.; Bork, P.; Jensen, L.J.; von Mering, C. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res., 2017, 45(D1), D362-D368.
[http://dx.doi.org/10.1093/nar/gkw937] [PMID: 27924014]
[89]
Kerrien, S.; Alam-Faruque, Y.; Aranda, B.; Bancarz, I.; Bridge, A.; Derow, C.; Dimmer, E.; Feuermann, M.; Friedrichsen, A.; Huntley, R.; Kohler, C.; Khadake, J.; Leroy, C.; Liban, A.; Lieftink, C.; Montecchi-Palazzi, L.; Orchard, S.; Risse, J.; Robbe, K.; Roechert, B.; Thorneycroft, D.; Zhang, Y.; Apweiler, R.; Hermjakob, H. IntAct--open source resource for molecular interaction data. Nucleic Acids Res., 2007, 35(Database issue), D561-D565.
[http://dx.doi.org/10.1093/nar/gkl958] [PMID: 17145710]
[90]
Betts, M.J.; Lu, Q.; Jiang, Y.; Drusko, A.; Wichmann, O.; Utz, M.; Valtierra-Gutiérrez, I.A.; Schlesner, M.; Jaeger, N.; Jones, D.T.; Pfister, S.; Lichter, P.; Eils, R.; Siebert, R.; Bork, P.; Apic, G.; Gavin, A.C.; Russell, R.B. Mechismo: predicting the mechanistic impact of mutations and modifications on molecular interactions. Nucleic Acids Res., 2015, 43(2)e10
[http://dx.doi.org/10.1093/nar/gku1094] [PMID: 25392414]
[91]
Tate, J.G.; Bamford, S.; Jubb, H.C.; Sondka, Z.; Beare, D.M.; Bindal, N.; Boutselakis, H.; Cole, C.G.; Creatore, C.; Dawson, E.; Fish, P.; Harsha, B.; Hathaway, C.; Jupe, S.C.; Kok, C.Y.; Noble, K.; Ponting, L.; Ramshaw, C.C.; Rye, C.E.; Speedy, H.E.; Stefancsik, R.; Thompson, S.L.; Wang, S.; Ward, S.; Campbell, P.J.; Forbes, S.A. COSMIC: the Catalogue Of Somatic Mutations In Cancer. Nucleic Acids Res., 2019, 47(D1), D941-D947.
[http://dx.doi.org/10.1093/nar/gky1015] [PMID: 30371878]
[92]
UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res., 2019, 47(D1), D506-D515.
[http://dx.doi.org/10.1093/nar/gky1049] [PMID: 30395287]
[93]
Deutsch, E.W.; Sun, Z.; Campbell, D.; Kusebauch, U.; Chu, C.S.; Mendoza, L.; Shteynberg, D.; Omenn, G.S.; Moritz, R.L. State of the Human Proteome in 2014/2015 As Viewed through PeptideAtlas: Enhancing Accuracy and Coverage through the AtlasProphet. J. Proteome Res., 2015, 14(9), 3461-3473.
[http://dx.doi.org/10.1021/acs.jproteome.5b00500] [PMID: 26139527]
[94]
Hornbeck, P.V.; Zhang, B.; Murray, B.; Kornhauser, J.M.; Latham, V.; Skrzypek, E. PhosphoSitePlus, 2014: mutations, PTMs and recalibrations. Nucleic Acids Res., 2015, 43(Database issue), D512-D520.
[http://dx.doi.org/10.1093/nar/gku1267] [PMID: 25514926]
[95]
Slade, D.J.; Subramanian, V.; Fuhrmann, J.; Thompson, P.R. Chemical and biological methods to detect post-translational modifications of arginine. Biopolymers, 2014, 101(2), 133-143.
[http://dx.doi.org/10.1002/bip.22256] [PMID: 23576281]
[96]
Cuthbert, G.L.; Daujat, S.; Snowden, A.W.; Erdjument-Bromage, H.; Hagiwara, T.; Yamada, M.; Schneider, R.; Gregory, P.D.; Tempst, P.; Bannister, A.J.; Kouzarides, T. Histone deimination antagonizes arginine methylation. Cell, 2004, 118(5), 545-553.
[http://dx.doi.org/10.1016/j.cell.2004.08.020] [PMID: 15339660]
[97]
Hidaka, Y.; Hagiwara, T.; Yamada, M. Methylation of the guanidino group of arginine residues prevents citrullination by peptidylarginine deiminase IV. FEBS Lett., 2005, 579(19), 4088-4092.
[http://dx.doi.org/10.1016/j.febslet.2005.06.035] [PMID: 16023115]
[98]
Raijmakers, R.; Zendman, A.J.; Egberts, W.V.; Vossenaar, E.R.; Raats, J.; Soede-Huijbregts, C.; Rutjes, F.P.; van Veelen, P.A.; Drijfhout, J.W.; Pruijn, G.J. Methylation of arginine residues interferes with citrullination by peptidylarginine deiminases in vitro. J. Mol. Biol., 2007, 367(4), 1118-1129.
[http://dx.doi.org/10.1016/j.jmb.2007.01.054] [PMID: 17303166]
[99]
Jones, J.E.; Causey, C.P.; Knuckley, B.; Slack-Noyes, J.L.; Thompson, P.R. Protein arginine deiminase 4 (PAD4): Current understanding and future therapeutic potential. Curr. Opin. Drug Discov. Devel., 2009, 12(5), 616-627.
[PMID: 19736621]
[100]
Liu, M.; Qu, Y.; Teng, X.; Xing, Y.; Li, D.; Li, C.; Cai, L. PADI4 mediated epithelial mesenchymal transition in lung cancer cells. Mol. Med. Rep., 2019, 19(4), 3087-3094.
[http://dx.doi.org/10.3892/mmr.2019.9968] [PMID: 30816464]
[101]
Chang, X.; Fang, K. PADI4 and tumourigenesis. Cancer Cell Int., 2010, 10, 7.
[http://dx.doi.org/10.1186/1475-2867-10-7] [PMID: 20222985]
[102]
Zheng, Y.; Zhao, G.; Xu, B.; Liu, C.; Li, C.; Zhang, X.; Chang, X. PADI4 has genetic susceptibility to gastric carcinoma and upregulates CXCR2, KRT14 and TNF-α expression levels. Oncotarget, 2016, 7(38), 62159-62176.
[http://dx.doi.org/10.18632/oncotarget.11398] [PMID: 27556695]
[103]
Altan, B.; Yokobori, T.; Ide, M.; Mochiki, E.; Toyomasu, Y.; Kogure, N.; Kimura, A.; Hara, K.; Bai, T.; Bao, P.; Suzuki, M.; Ogata, K.; Asao, T.; Nishiyama, M.; Oyama, T.; Kuwano, H. Nuclear PRMT1 expression is associated with poor prognosis and chemosensitivity in gastric cancer patients. Gastric Cancer, 2016, 19(3), 789-97.

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