Abstract
Citrullination, the Ca2+-driven enzymatic conversion of arginine residues to citrulline, is a posttranslational modification, implicated in several physiological and pathological processes. Several methods to detect citrullinated proteins have been developed, including color development reagent, fluorescence, phenylglyoxal, and antibody-based methods. These methods yet suffer from limitations in sensitivity, specificity, or citrullinated site determination. Mass spectrometry (MS)-based proteomic analysis has emerged as a promising method to resolve these problems. However, due to low abundance of citrullinated proteins and similar MS features to deamidation of asparagine and glutamine, confident identification of citrullinated proteome is challenging. Here, we present a systematic approach to identify a compendium of steps to enhance the number of detected citrullinated residue and implement diagnostic MS feature that allow the confidence of MS-based identifications. Our method is based on the concept of generation of hyper-citrullinated library with high-pH reversed-phase peptide fractionation that allows to enrich in low abundance citrullinated peptides and amplify the effect of charge loss upon citrullination. Application of our approach to complex global citrullino-proteome datasets demonstrates the confident assessment of citrullinated peptides, thereby enhancing the size and functional interpretation of citrullinated proteomes.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
György B, Tóth E, Tarcsa E et al (2006) Citrullination: a posttranslational modification in health and disease. Int J Biochem Cell Biol 38:1662–1677
Slade DJ, Subramanian V, Fuhrmann J et al (2014) Chemical and biological methods to detect posttranslational modifications of arginine. Biopolymers 101:133–143
van Venrooij WJ, Pruijn GJ (2000) Citrullination: a small change for a protein with great consequences for rheumatoid arthritis. Arthritis Res 2:249–251
Fearon WR (1939) The carbamido diacetyl reaction: a test for citrulline. Biochem J 33:902–907
Orgován G, Noszál B (2011) The complete microspeciation of arginine and citrulline. J Pharm Biomed Anal 54:965–971
Chirivi RGS, van Rosmalen JWG, Jenniskens GJ et al (2013) Citrullination: a target for disease intervention in multiple sclerosis and other inflammatory diseases? J Clin Cell Immunol 4:146
Tarcsa E, Marekov LN, Mei G et al (1996) Protein unfolding by Peptidylarginine deiminase: substrate specificity and structural relationships of the natural substrates trichohyalin and filaggrin. J Biol Chem 271:30709–30716
Tilvawala R, Nguyen SH, Maurais AJ et al (2018) The rheumatoid arthritis-associated Citrullinome. Cell Chem Biol 25:691–704.e6
Christophorou MA, Castelo-Branco G, Halley-Stott RP et al (2014) Citrullination regulates pluripotency and histone H1 binding to chromatin. Nature 507:104–108
Amin B, Voelter W (2017) Human deiminases: isoforms, Substrate specificities, kinetics, and detection. Prog Chem Org Nat Prod 106:203–240
Fert-Bober J, Giles JT, Holewinski RJ et al (2015) Citrullination of myofilament proteins in heart failure. Cardiovasc Res 108:232–242
Hill JA, Bell DA, Brintnell W et al (2008) Arthritis induced by posttranslationally modified (citrullinated) fibrinogen in DR4-IE transgenic mice. J Exp Med 205:967–979
Ludwig RJ, Vanhoorelbeke K, Leypoldt F et al (2017) Mechanisms of autoantibody-induced pathology. Front Immunol 8:603
Bitoun S, Roques P, Larcher T et al (2017) Both systemic and intra-articular immunization with Citrullinated peptides are needed to induce arthritis in the macaque. Front Immunol 8:1816
Hensen SMM, Pruijn GJM (2014) Methods for the detection of peptidylarginine deiminase (PAD) activity and protein citrullination. Mol Cell Proteomics 13:388–396
Hao G, Wang D, Gu J et al (2009) Neutral loss of isocyanic acid in peptide CID spectra: a novel diagnostic marker for mass spectrometric identification of protein citrullination. J Am Soc Mass Spectrom 20:723–727
Lee C-Y, Wang D, Wilhelm M et al (2018) Mining the human tissue proteome for protein Citrullination. Mol Cell Proteomics 17:1378–1391
Raijmakers R, van Beers JJBC, El-Azzouny M et al (2012) Elevated levels of fibrinogen-derived endogenous citrullinated peptides in synovial fluid of rheumatoid arthritis patients. Arthritis Res Ther 14:R114
Fert-Bober J, Venkatraman V, Hunter CL et al (2019) Mapping Citrullinated sites in multiple organs of mice using Hypercitrullinated library. J Proteome Res 18:2270–2278
Escher C, Reiter L, MacLean B et al (2012) Using iRT, a normalized retention time for more targeted measurement of peptides. Proteomics 12:1111–1121
Wiśniewski JR (2016) Quantitative evaluation of filter aided sample preparation (FASP) and multienzyme digestion FASP protocols. Anal Chem 88:5438–5443
Wiśniewski JR, Mann M (2012) Consecutive proteolytic digestion in an enzyme reactor increases depth of proteomic and phosphoproteomic analysis. Anal Chem 84:2631–2637
Schilling B, Rardin MJ, MacLean BX et al (2012) Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation. Mol Cell Proteomics 11:202–214
Pino LK, Searle BC, Bollinger JG et al (2020) The skyline ecosystem: informatics for quantitative mass spectrometry proteomics. Mass Spectrom Rev 39:229–244
Chambers MC, Maclean B, Burke R et al (2012) A cross-platform toolkit for mass spectrometry and proteomics. Nat Biotechnol 30:918–920
Keller A, Eng J, Zhang N et al (2005) A uniform proteomics MS/MS analysis platform utilizing open XML file formats. Mol Syst Biol 1:2005.0017
Elias JE, Gygi SP (2007) Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat Methods 4:207–214
Craig R, Beavis RC (2004) TANDEM: matching proteins with tandem mass spectra. Bioinformatics 20:1466–1467
Eng JK, Jahan TA, Hoopmann MR (2013) Comet: an open-source MS/MS sequence database search tool. Proteomics 13:22–24
Keller A, Nesvizhskii AI, Kolker E et al (2002) Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal Chem 74:5383–5392
Shteynberg D, Deutsch EW, Lam H et al (2011) iProphet: multi-level integrative analysis of shotgun proteomic data improves peptide and protein identification rates and error estimates. Mol Cell Proteomics 10:M111.007690
Collins BC, Gillet LC, Rosenberger G et al (2013) Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3-3 system. Nat Methods 10:1246–1253
Lam H, Deutsch EW, Eddes JS et al (2007) Development and validation of a spectral library searching method for peptide identification from MS/MS. Proteomics 7:655–667
Schubert OT, Gillet LC, Collins BC et al (2015) Building high-quality assay libraries for targeted analysis of SWATH MS data. Nat Protoc 10:426–441
Acknowledgments
The study was supported by Polish National Agency for Academic Exchange (NAWA) and R01 HL111362.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Stachowicz, A., Sundararaman, N., Venkatraman, V., Van Eyk, J., Fert-Bober, J. (2022). pH/Acetonitrile-Gradient Reversed-Phase Fractionation of Enriched Hyper-Citrullinated Library in Combination with LC–MS/MS Analysis for Confident Identification of Citrullinated Peptides. In: Corrales, F.J., Paradela, A., Marcilla, M. (eds) Clinical Proteomics. Methods in Molecular Biology, vol 2420. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1936-0_9
Download citation
DOI: https://doi.org/10.1007/978-1-0716-1936-0_9
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-1935-3
Online ISBN: 978-1-0716-1936-0
eBook Packages: Springer Protocols