Abstract
Peptide identification relies in the majority of mass spectrometry-based proteomics experiments on matching of experimental data against peptide and fragment ion masses derived from in silico digests of protein databases. One of the main drawbacks of this approach is that modifications have to be defined for database searching and therefore no unexpected modifications can be identified in a standard setup. Consequently, in many bottom-up proteomics experiments, unexpected modifications are not identified, even if high-quality fragment ion spectra of the modified peptides were acquired. It is therefore often not straightforward to identify unexpected modifications. In this protocol, we describe a stepwise procedure to identify unexpected modifications at peptides using the database search algorithm Mascot. The workflow includes parallel searches for the identification of known modifications at unexpected amino acids, error tolerant searches for modifications unexpected in the sample but known to the community, and mass tolerant searches for entirely unknown modifications. Furthermore, we suggest a follow-up strategy consisting of (1) verification of identified modifications in the initial dataset and (2) targeted experiments using synthetic peptides.
Key words
- Mass spectrometry
- Unexpected modifications
- Posttranslational modifications
- Bottom-up proteomics
- Data analysis
- Mascot
- Error tolerant search
- Mass tolerant search
This is a preview of subscription content, access via your institution.
Buying options








References
Aebersold R, Mann M (2016) Mass-spectrometric exploration of proteome structure and function. Nature 537:347–355. https://doi.org/10.1038/nature19949
Kalli A, Smith GT, Sweredoski MJ et al (2013) Evaluation and optimization of mass spectrometric settings during data-dependent acquisition mode: focus on LTQ-orbitrap mass analyzers. J Proteome Res 12:3071–3086. https://doi.org/10.1021/pr3011588
Eng JK, McCormack AL, Yates JR (1994) An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J Am Soc Mass Spectrom 5:976–989. https://doi.org/10.1016/1044-0305(94)80016-2
Griss J, Perez-Riverol Y, Lewis S et al (2016) Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets. Nat Methods 13:651–656. https://doi.org/10.1038/nmeth.3902
Nielsen ML, Savitski MM, Ra Z (2006) Extent of modifications in human proteome samples and their effect on dynamic range of analysis in shotgun proteomics. Mol Cell Proteomics 5:2384–2391. https://doi.org/10.1074/mcp.M600248-MCP200
Nesvizhskii AI, Roos FF, Grossmann J et al (2006) Dynamic spectrum quality assessment and iterative computational analysis of shotgun proteomic data: toward more efficient identification of post-translational modifications, sequence polymorphisms, and novel peptides. Mol Cell Proteomics 5:652–670. https://doi.org/10.1074/mcp.M500319-MCP200
Chick JM, Kolippakkam D, Nusinow DP et al (2015) A mass-tolerant database search identifies a large proportion of unassigned spectra in shotgun proteomics as modified peptides. Nat Biotechnol 33:743–749. https://doi.org/10.1038/nbt.3267
Tanner S, Shu H, Frank A et al (2005) InsPecT: identification of posttranslationally modified peptides from tandem mass spectra. Anal Chem 77:4626–4639. https://doi.org/10.1021/ac050102d
Jensen ON (2004) Modification-specific proteomics: characterization of post-translational modifications by mass spectrometry. Curr Opin Chem Biol 8:33–41. https://doi.org/10.1016/j.cbpa.2003.12.009
Zhao Y, Jensen ON (2009) Modification-specific proteomics: strategies for characterization of post-translational modifications using enrichment techniques. Proteomics 9:4632–4641. https://doi.org/10.1002/pmic.200900398
Müller T, Winter D (2017) Systematic evaluation of protein reduction and alkylation reveals massive unspecific side effects by iodine-containing reagents. Mol Cell Proteomics 16:1173–1187. https://doi.org/10.1074/mcp.M116.064048
Laemmli UK (1970) Cleavage of structural proteins during the assembly of the head of bacteriophage T4. Nature 227:680–685. https://doi.org/10.1038/227680a0
Boersema PJ, Raijmakers R, Lemeer S et al (2009) Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics. Nat Protoc 4:484–494. https://doi.org/10.1038/nprot.2009.21
Shevchenko A, Wilm M, Vorm O et al (1996) Mass spectrometric sequencing of proteins from silver-stained polyacrylamide gels. Anal Chem 68:850–858. https://doi.org/10.1021/ac950914h
Chin Y, Aiken GR, O’Loughlin E (1994) Molecular weight, polydispersity, and spectroscopic properties of aquatic humic substances. Environ Sci 28:1853–1858. https://doi.org/10.1021/es00060a015
Williams A, Frasca V (2001) Ion-exchange chromatography. Curr Protoc Protein Sci 15:8.2.1–8.2.30
Chen J, Lee CS, Shen Y et al (2002) Integration of capillary isoelectric focusing with capillary reversed-phase liquid chromatography for two-dimensional proteomics separation. Electrophoresis 23:3143–3148. https://doi.org/10.1002/1522-2683(200209)23:18<3143::AID-ELPS3143>3.0.CO;2-7
Nühse TS, Stensballe A, Jensen ON et al (2003) Large-scale analysis of in vivo phosphorylated membrane proteins by immobilized metal ion affinity chromatography and mass spectrometry. Mol Cell Proteomics 2:1234–1243. https://doi.org/10.1074/mcp.T300006-MCP200
Beausoleil SA, Jedrychowski M, Schwartz D et al (2004) Large-scale characterization of HeLa cell nuclear phosphoproteins. Proc Natl Acad Sci 101:12130–12135. https://doi.org/10.1073/pnas.0404720101
Michel PE, Reymond F, Arnaud IL et al (2003) Protein fractionation in a multicompartment device using Off-GelTM isoelectric focusing. Electrophoresis 24:3–11. https://doi.org/10.1002/elps.200390030
Huber LA, Pfaller K, Vietor I (2003) Organelle proteomics: implications for subcellular fractionation in proteomics. Circ Res 92:962–968. https://doi.org/10.1161/01.RES.0000071748.48338.25
Rappsilber J, Ishihama Y, Mann M (2003) Stop and go extraction tips for matrix-assisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics. Anal Chem 75:663–670. https://doi.org/10.1021/ac026117i
Verheggen K, Raeder H, Berven FS et al (2017) Anatomy and evolution of database search engines-a central component of mass spectrometry based proteomic workflows. Mass Spectrom Rev. https://doi.org/10.1002/mas.21543
Brosch M, Yu L, Hubbard T et al (2009) Accurate and sensitive peptide identification with mascot percolator. J Proteome Res 8:3176–3181. https://doi.org/10.1021/pr800982s
Bantscheff M, Schirle M, Sweetman G et al (2007) Quantitative mass spectrometry in proteomics: a critical review. Anal Bioanal Chem 389:1017–1031. https://doi.org/10.1007/s00216-007-1486-6
Creasy DM, Cottrell JS (2002) Error tolerant searching of uninterpreted tandem mass spectrometry data. Proteomics 2:1426–1434. https://doi.org/10.1002/1615-9861(200210)2:10<1426::AID-PROT1426>3.0.CO;2-5
Seidler J, Zinn N, Boehm ME et al (2010) De novo sequencing of peptides by MS/MS. Proteomics 10:634–649. https://doi.org/10.1002/pmic.200900459
Winter D, Steen H (2011) Optimization of cell lysis and protein digestion protocols for the analysis of HeLa S3 cells by LC-MS/MS. Proteomics 11:4726–4730. https://doi.org/10.1002/pmic.201100162
Yu YQ, Gilar M, Lee PJ et al (2003) Enzyme-friendly, mass spectrometry compatible surfactant for in-solution enzymatic digestion of proteins. Anal Chem 75:6023–6028. https://doi.org/10.1021/ac0346196
Kollipara L, Zahedi RP (2013) Protein carbamylation: in vivo modification or in vitro artefact? Proteomics 13:941–944. https://doi.org/10.1002/pmic.201200452
Deutsch EW, Mendoza L, Shteynberg D et al (2015) Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics. Proteomics Clin Appl 9:745–754. https://doi.org/10.1002/prca.201400164
Holman JD, Tabb DL, Mallick P (2014) Employing ProteoWizard to convert raw mass spectrometry data. Curr Protoc Bioinformatics 46:13.24.1–13.24.9. https://doi.org/10.1002/0471250953.bi1324s46
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Ahmadi, S., Winter, D. (2019). Identification of Unexpected Protein Modifications by Mass Spectrometry-Based Proteomics. In: Wang, X., Kuruc, M. (eds) Functional Proteomics. Methods in Molecular Biology, vol 1871. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8814-3_15
Download citation
DOI: https://doi.org/10.1007/978-1-4939-8814-3_15
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-8813-6
Online ISBN: 978-1-4939-8814-3
eBook Packages: Springer Protocols