Proteomics in Systems Biology pp 275-286

Part of the Methods in Molecular Biology book series (MIMB, volume 1394) | Cite as

A Simple Workflow for Large Scale Shotgun Glycoproteomics

  • Astrid Guldbrandsen
  • Harald Barsnes
  • Ann Cathrine Kroksveen
  • Frode S. Berven
  • Marc Vaudel
Protocol

Abstract

Targeting subproteomes is a good strategy to decrease the complexity of a sample, for example in body fluid biomarker studies. Glycoproteins are proteins with carbohydrates of varying size and structure attached to the polypeptide chain, and it has been shown that glycosylation plays essential roles in several vital cellular processes, making glycosylation a particularly interesting field of study. Here, we describe a method for the enrichment of glycosylated peptides from trypsin digested proteins in human cerebrospinal fluid. We also describe how to perform the data analysis on the mass spectrometry data for such samples, focusing on site-specific identification of glycosylation sites, using user friendly open source software.

Key words

Glycoproteomics Enrichment Data interpretation 

References

  1. 1.
    Gevaert K, Van Damme P, Ghesquiere B et al (2007) A la carte proteomics with an emphasis on gel-free techniques. Proteomics 7:2698–2718CrossRefPubMedGoogle Scholar
  2. 2.
    Zhang H, Li XJ, Martin DB et al (2003) Identification and quantification of N-linked glycoproteins using hydrazide chemistry, stable isotope labeling and mass spectrometry. Nat Biotechnol 21:660–666CrossRefPubMedGoogle Scholar
  3. 3.
    Gamblin DP, Scanlan EM, Davis BG (2009) Glycoprotein synthesis: an update. Chem Rev 109:131–163CrossRefPubMedGoogle Scholar
  4. 4.
    Shental-Bechor D, Levy Y (2008) Effect of glycosylation on protein folding: a close look at thermodynamic stabilization. Proc Natl Acad Sci U S A 105:8256–8261CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Sola RJ, Rodriguez-Martinez JA, Griebenow K (2007) Modulation of protein biophysical properties by chemical glycosylation: biochemical insights and biomedical implications. Cell Mol Life Sci 64:2133–2152CrossRefPubMedGoogle Scholar
  6. 6.
    Varki A (1993) Biological roles of oligosaccharides: all of the theories are correct. Glycobiology 3:97–130CrossRefPubMedGoogle Scholar
  7. 7.
    Roth J (2002) Protein N-glycosylation along the secretory pathway: relationship to organelle topography and function, protein quality control, and cell interactions. Chem Rev 102:285–303CrossRefPubMedGoogle Scholar
  8. 8.
    Sato Y, Endo T (2010) Alteration of brain glycoproteins during aging. Geriatr Gerontol Int 10 Suppl 1:S32–S40Google Scholar
  9. 9.
    Ruggeri ZM, Mendolicchio GL (2007) Adhesion mechanisms in platelet function. Circ Res 100:1673–1685CrossRefPubMedGoogle Scholar
  10. 10.
    Berger MS, Locher GW, Saurer S et al (1988) Correlation of c-erbB-2 gene amplification and protein expression in human breast carcinoma with nodal status and nuclear grading. Cancer Res 48:1238–1243PubMedGoogle Scholar
  11. 11.
    Hudziak RM, Schlessinger J, Ullrich A (1987) Increased expression of the putative growth factor receptor p185HER2 causes transformation and tumorigenesis of NIH 3T3 cells. Proc Natl Acad Sci U S A 84:7159–7163CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Vogelzang NJ, Lange PH, Goldman A et al (1982) Acute changes of alpha-fetoprotein and human chorionic gonadotropin during induction chemotherapy of germ cell tumors. Cancer Res 42:4855–4861PubMedGoogle Scholar
  13. 13.
    Bosl GJ, Lange PH, Fraley EE et al (1981) Human chorionic gonadotropin and alphafetoprotein in the staging of nonseminomatous testicular cancer. Cancer 47:328–332CrossRefPubMedGoogle Scholar
  14. 14.
    Thompson DK, Haddow JE (1979) Serial monitoring of serum alpha-fetoprotein and chorionic gonadotropin in males with germ cell tumors. Cancer 43:1820–1829CrossRefPubMedGoogle Scholar
  15. 15.
    Catalona WJ, Richie JP, Ahmann FR et al (1994) Comparison of digital rectal examination and serum prostate specific antigen in the early detection of prostate cancer: results of a multicenter clinical trial of 6,630 men. J Urol 151:1283–1290PubMedGoogle Scholar
  16. 16.
    Canney PA, Moore M, Wilkinson PM et al (1984) Ovarian cancer antigen CA125: a prospective clinical assessment of its role as a tumour marker. Br J Cancer 50:765–769CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Topol EJ, Byzova TV, Plow EF (1999) Platelet GPIIb-IIIa blockers. Lancet 353:227–231CrossRefPubMedGoogle Scholar
  18. 18.
    Guldbrandsen A, Vethe H, Farag Y et al (2014) In-depth characterization of the cerebrospinal fluid proteome displayed through the CSF Proteome Resource (CSF-PR). Mol Cell Proteomics 13(11):3152–63CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Tian Y, Zhou Y, Elliott S et al (2007) Solid-phase extraction of N-linked glycopeptides. Nat Protoc 2:334–339CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Berven FS, Ahmad R, Clauser KR et al (2010) Optimizing performance of glycopeptide capture for plasma proteomics. J Proteome Res 9:1706–1715CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Gonzalez J, Takao T, Hori H et al (1992) A method for determination of N-glycosylation sites in glycoproteins by collision-induced dissociation analysis in fast atom bombardment mass spectrometry: identification of the positions of carbohydrate-linked asparagine in recombinant alpha-amylase by treatment with peptide-N-glycosidase F in 18O-labeled water. Anal Biochem 205:151–158CrossRefPubMedGoogle Scholar
  22. 22.
    Vaudel M, Barsnes H, Berven FS et al (2011) SearchGUI: an open-source graphical user interface for simultaneous OMSSA and X!Tandem searches. Proteomics 11:996–999CrossRefPubMedGoogle Scholar
  23. 23.
    Vaudel M, Burkhart JM, Zahedi RP et al (2015) PeptideShaker enables reanalysis of MS-derived proteomics data sets. Nature biotechnology 33:22–24Google Scholar
  24. 24.
    Vizcaino JA, Deutsch EW, Wang R et al (2014) ProteomeXchange provides globally coordinated proteomics data submission and dissemination. Nat Biotechnol 32:223–226CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Martens L, Hermjakob H, Jones P et al (2005) PRIDE: the proteomics identifications database. Proteomics 5:3537–3545CrossRefPubMedGoogle Scholar
  26. 26.
    Vaudel M, Sickmann A, Martens L (2012) Current methods for global proteome identification. Expert Rev Proteomics 9:519–532CrossRefPubMedGoogle Scholar
  27. 27.
    Nesvizhskii AI (2010) A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics. J Proteomics 73:2092–2123CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Chalkley RJ, Clauser KR (2012) Modification site localization scoring: strategies and performance. Mol Cell Proteomics 11:3–14CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Vaudel M, Venne AS, Berven FS et al (2014) Shedding light on black boxes in protein identification. Proteomics 14:1001–1005CrossRefPubMedGoogle Scholar
  30. 30.
    Kohlbacher O, Reinert K, Gropl C et al (2007) TOPP—the OpenMS proteomics pipeline. Bioinformatics 23:e191–e197CrossRefPubMedGoogle Scholar
  31. 31.
    Bertsch A, Gropl C, Reinert K et al (2011) OpenMS and TOPP: open source software for LC-MS data analysis. Methods Mol Biol 696:353–367CrossRefPubMedGoogle Scholar
  32. 32.
    Deutsch EW, Mendoza L, Shteynberg D et al (2010) A guided tour of the Trans-Proteomic Pipeline. Proteomics 10:1150–1159CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26:1367–1372CrossRefPubMedGoogle Scholar
  34. 34.
    Kessner D, Chambers M, Burke R et al (2008) ProteoWizard: open source software for rapid proteomics tools development. Bioinformatics 24:2534–2536CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Apweiler R, Bairoch A, Wu CH et al (2004) UniProt: the Universal Protein knowledgebase. Nucleic Acids Res 32:D115–D119CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Vaudel M, Burkhart JM, Sickmann A et al (2011) Peptide identification quality control. Proteomics 11:2105–2114Google Scholar
  37. 37.
    Flicek P, Amode MR, Barrell D et al (2014) Ensembl 2014. Nucleic Acids Res 42:D749–D755CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Astrid Guldbrandsen
    • 1
    • 2
  • Harald Barsnes
    • 1
    • 3
  • Ann Cathrine Kroksveen
    • 1
    • 2
  • Frode S. Berven
    • 1
    • 2
    • 4
  • Marc Vaudel
    • 1
  1. 1.Proteomics Unit, Department of BiomedicineUniversity of BergenBergenNorway
  2. 2.KG Jebsen Centre for Multiple Sclerosis Research, Department of Clinical MedicineUniversity of BergenBergenNorway
  3. 3.KG Jebsen Center for Diabetes Research, Department of Clinical SciencesUniversity of BergenBergenNorway
  4. 4.Norwegian Multiple Sclerosis Competence Centre, Department of NeurologyHaukeland University HospitalBergenNorway

Personalised recommendations