Skip to main content

Proteomics in Vascular Biology

  • Chapter
  • First Online:
Fundamentals of Vascular Biology

Part of the book series: Learning Materials in Biosciences ((LMB))

  • 1867 Accesses

Abstract

The proteome is the entire set of proteins of a biological sample, and proteomics is the large-scale qualitative (protein composition) and quantitative analysis of the proteome. A collection of dedicated biochemical methods is combined with protein databases to identify the proteins and to allocate them to biological pathways. The work process involves two major steps, the separation of the proteins (electrophoresis and liquid chromatography) and the protein identification by mass spectrometry. In medical research, proteomics is mainly applied to discover proteins that play a role in pathological processes; thus it is also a valuable tool in vascular biology. These disease-related proteins are generally defined as biomarkers and are of great interest to the diagnosis and treatment of patients. In vascular research, biological samples are, for example, plasma, serum, platelets, endothelial cells and vascular smooth muscle cells. This chapter will provide an overview of this technology and will demonstrate its application.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Alban A, David SO, Bjorkesten L, Andersson C, Sloge E, Lewis S, Currie I. A novel experimental design for comparative two-dimensional gel analysis: two-dimensional difference gel electrophoresis incorporating a pooled internal standard. Proteomics. 2003;3(1):36–44. https://doi.org/10.1002/pmic.200390006.

    Article  CAS  PubMed  Google Scholar 

  2. Allin KH, Nordestgaard BG. Elevated C-reactive protein in the diagnosis, prognosis, and cause of cancer. Crit Rev Clin Lab Sci. 2011;48(4):155–70. https://doi.org/10.3109/10408363.2011.599831.

    Article  CAS  PubMed  Google Scholar 

  3. Alonso-Orgaz S, Moreno-Luna R, Lopez JA, Gil-Dones F, Padial LR, Moreu J, de la Cuesta F, Barderas MG. Proteomic characterization of human coronary thrombus in patients with ST-segment elevation acute myocardial infarction. J Proteome. 2014;109:368–81. https://doi.org/10.1016/j.jprot.2014.07.016.

    Article  CAS  Google Scholar 

  4. Baker ES, Liu T, Petyuk VA, Burnum-Johnson KE, Ibrahim YM, Anderson GA, Smith RD. Mass spectrometry for translational proteomics: progress and clinical implications. Genome Med. 2012;4(8):63. https://doi.org/10.1186/gm364.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Beck F, Geiger J, Gambaryan S, Veit J, Vaudel M, Nollau P, Kohlbacher O, Martens L, Walter U, Sickmann A, Zahedi RP. Time-resolved characterization of cAMP/PKA-dependent signaling reveals that platelet inhibition is a concerted process involving multiple signaling pathways. Blood. 2014;123(5):e1–e10. https://doi.org/10.1182/blood-2013-07-512384.

    Article  CAS  PubMed  Google Scholar 

  6. Biomarkers Definitions Working G. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001;69(3):89–95. https://doi.org/10.1067/mcp.2001.113989.

    Article  Google Scholar 

  7. Bittoni MA, Focht BC, Clinton SK, Buckworth J, Harris RE. Prospective evaluation of C-reactive protein, smoking and lung cancer death in the Third National Health and Nutrition Examination Survey. Int J Oncol. 2015;47(4):1537–44. https://doi.org/10.3892/ijo.2015.3141.

    Article  CAS  PubMed  Google Scholar 

  8. Boeddinghaus J, Twerenbold R, Nestelberger T, Badertscher P, Wildi K, Puelacher C, du Fay de Lavallaz J, Keser E, Rubini Gimenez M, Wussler D, Kozhuharov N, Rentsch K, Miro O, Martin-Sanchez FJ, Morawiec B, Stefanelli S, Geigy N, Keller DI, Reichlin T, Mueller C, Investigators A. Clinical validation of a novel high-sensitivity cardiac troponin I assay for early diagnosis of acute myocardial infarction. Clin Chem. 2018;64(9):1347–60. https://doi.org/10.1373/clinchem.2018.286906.

    Article  CAS  PubMed  Google Scholar 

  9. Breitbart RE, Andreadis A, Nadal-Ginard B. Alternative splicing: a ubiquitous mechanism for the generation of multiple protein isoforms from single genes. Annu Rev Biochem. 1987;56:467–95. https://doi.org/10.1146/annurev.bi.56.070187.002343.

    Article  CAS  PubMed  Google Scholar 

  10. Cattaneo M. Resistance to antiplatelet drugs: molecular mechanisms and laboratory detection. J Thromb Haemost. 2007;5(Suppl 1):230–7. https://doi.org/10.1111/j.1538-7836.2007.02498.x.

    Article  CAS  PubMed  Google Scholar 

  11. Cox B, Emili A. Tissue subcellular fractionation and protein extraction for use in mass-spectrometry-based proteomics. Nat Protoc. 2006;1(4):1872–8. https://doi.org/10.1038/nprot.2006.273.

    Article  CAS  PubMed  Google Scholar 

  12. Dunn OJ. Multiple comparisons among means. J Am Stat Assoc. 1961;56:52–64.

    Article  Google Scholar 

  13. DyeAGNOSTICS 2D Protein Labeling Kits. https://www.dyeagnostics.com/site/products/refraction-2d/. Accessed 31 Aug 2018.

  14. Floyd CN, Goodman T, Becker S, Chen N, Mustafa A, Schofield E, Campbell J, Ward M, Sharma P, Ferro A. Increased platelet expression of glycoprotein IIIa following aspirin treatment in aspirin-resistant but not aspirin-sensitive subjects. Br J Clin Pharmacol. 2014;78(2):320–8. https://doi.org/10.1111/bcp.12335.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Fu S, Ping P, Zhu Q, Ye P, Luo L. Brain natriuretic peptide and its biochemical, analytical, and clinical issues in heart failure: a narrative review. Front Physiol. 2018;9:692. https://doi.org/10.3389/fphys.2018.00692.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Gallien S, Bourmaud A, Kim SY, Domon B. Technical considerations for large-scale parallel reaction monitoring analysis. J Proteome. 2014;100:147–59. https://doi.org/10.1016/j.jprot.2013.10.029.

    Article  CAS  Google Scholar 

  17. Gianazza E, Tremoli E, Banfi C. The selected reaction monitoring/multiple reaction monitoring-based mass spectrometry approach for the accurate quantitation of proteins: clinical applications in the cardiovascular diseases. Expert Rev Proteomics. 2014;11(6):771–88. https://doi.org/10.1586/14789450.2014.947966.

    Article  CAS  PubMed  Google Scholar 

  18. Giansanti P, Tsiatsiani L, Low TY, Heck AJ. Six alternative proteases for mass spectrometry-based proteomics beyond trypsin. Nat Protoc. 2016;11(5):993–1006. https://doi.org/10.1038/nprot.2016.057.

    Article  CAS  PubMed  Google Scholar 

  19. Gil-Dones F, Darde VM, Alonso-Orgaz S, Lopez-Almodovar LF, Mourino-Alvarez L, Padial LR, Vivanco F, Barderas MG. Inside human aortic stenosis: a proteomic analysis of plasma. J Proteome. 2012;75(5):1639–53. https://doi.org/10.1016/j.jprot.2011.11.036.

    Article  CAS  Google Scholar 

  20. Gstaiger M, Aebersold R. Applying mass spectrometry-based proteomics to genetics, genomics and network biology. Nat Rev Genet. 2009;10(9):617–27. https://doi.org/10.1038/nrg2633.

    Article  CAS  PubMed  Google Scholar 

  21. Hell L, Lurger K, Gebhart S, Koder S, Ay C, Pabinger I, Maria Z. Differences in the platelet proteome between lupus anticoagulant positive individuals with or without thrombotic manifestations and healthy controls. 2017. http://www.professionalabstracts.com/isth2017/iplanner/#/presentation/856.

  22. Hernandez B, Parnell A, Pennington SR. Why have so few proteomic biomarkers “survived” validation? (sample size and independent validation considerations). Proteomics. 2014;14(13-14):1587–92. https://doi.org/10.1002/pmic.201300377.

    Article  PubMed  Google Scholar 

  23. Hingorani AD, Sofat R, Morris RW, Whincup P, Lowe GD, Mindell J, Sattar N, Casas JP, Shah T. Is it important to measure or reduce C-reactive protein in people at risk of cardiovascular disease? Eur Heart J. 2012;33(18):2258–64. https://doi.org/10.1093/eurheartj/ehs168.

    Article  CAS  PubMed  Google Scholar 

  24. Hochberg Y, Benjamini Y. More powerful procedures for multiple significance testing. Stat Med. 1990;9(7):811–8.

    Article  CAS  PubMed  Google Scholar 

  25. Iwanaga Y, Nishi I, Furuichi S, Noguchi T, Sase K, Kihara Y, Goto Y, Nonogi H. B-type natriuretic peptide strongly reflects diastolic wall stress in patients with chronic heart failure: comparison between systolic and diastolic heart failure. J Am Coll Cardiol. 2006;47(4):742–8. https://doi.org/10.1016/j.jacc.2005.11.030.

    Article  CAS  PubMed  Google Scholar 

  26. James P. Protein identification in the post-genome era: the rapid rise of proteomics. Q Rev Biophys. 1997;30(4):279–331.

    Article  CAS  PubMed  Google Scholar 

  27. Karas M, Hillenkamp F. Laser desorption ionization of proteins with molecular masses exceeding 10,000 daltons. Anal Chem. 1988;60(20):2299–301.

    Article  CAS  PubMed  Google Scholar 

  28. Klose J. Protein mapping by combined isoelectric focusing and electrophoresis of mouse tissues. A novel approach to testing for induced point mutations in mammals. Humangenetik. 1975;26(3):231–43.

    CAS  PubMed  Google Scholar 

  29. Lange V, Picotti P, Domon B, Aebersold R. Selected reaction monitoring for quantitative proteomics: a tutorial. Mol Syst Biol. 2008;4:222. https://doi.org/10.1038/msb.2008.61.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Leon IR, Schwammle V, Jensen ON, Sprenger RR. Quantitative assessment of in-solution digestion efficiency identifies optimal protocols for unbiased protein analysis. Mol Cell Proteomics. 2013;12(10):2992–3005. https://doi.org/10.1074/mcp.M112.025585.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Lin HQ, Wang Y, Chan KL, Ip TM, Wan CC. Differential regulation of lipid metabolism genes in the brain of acetylcholinesterase knockout mice. J Mol Neurosci. 2014;53(3):397–408. https://doi.org/10.1007/s12031-014-0267-x.

    Article  CAS  PubMed  Google Scholar 

  32. Marcone S, Dervin F, Fitzgerald DJ. Proteomic signatures of antiplatelet drugs: new approaches to exploring drug effects. J Thromb Haemost. 2015;13(Suppl 1):S323–31. https://doi.org/10.1111/jth.12943.

    Article  CAS  PubMed  Google Scholar 

  33. Mateos-Caceres PJ, Macaya C, Azcona L, Modrego J, Mahillo E, Bernardo E, Fernandez-Ortiz A, Lopez-Farre AJ. Different expression of proteins in platelets from aspirin-resistant and aspirin-sensitive patients. Thromb Haemost. 2010;103(1):160–70. https://doi.org/10.1160/TH09-05-0290.

    Article  CAS  PubMed  Google Scholar 

  34. McEvoy JW, Chen Y, Ndumele CE, Solomon SD, Nambi V, Ballantyne CM, Blumenthal RS, Coresh J, Selvin E. Six-year change in high-sensitivity cardiac troponin T and risk of subsequent coronary heart disease, heart failure, and death. JAMA Cardiol. 2016;1(5):519–28. https://doi.org/10.1001/jamacardio.2016.0765.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Meissner F, Mann M. Quantitative shotgun proteomics: considerations for a high-quality workflow in immunology. Nat Immunol. 2014;15(2):112–7. https://doi.org/10.1038/ni.2781.

    Article  CAS  PubMed  Google Scholar 

  36. Miller I, Crawford J, Gianazza E. Protein stains for proteomic applications: which, when, why? Proteomics. 2006;6(20):5385–408. https://doi.org/10.1002/pmic.200600323.

    Article  CAS  PubMed  Google Scholar 

  37. Nanjappa V, Thomas JK, Marimuthu A, Muthusamy B, Radhakrishnan A, Sharma R, Ahmad Khan A, Balakrishnan L, Sahasrabuddhe NA, Kumar S, Jhaveri BN, Sheth KV, Kumar Khatana R, Shaw PG, Srikanth SM, Mathur PP, Shankar S, Nagaraja D, Christopher R, Mathivanan S, Raju R, Sirdeshmukh R, Chatterjee A, Simpson RJ, Harsha HC, Pandey A, Prasad TS. Plasma proteome database as a resource for proteomics research: 2014 update. Nucleic Acids Res. 2014;42(Database issue):D959–65. https://doi.org/10.1093/nar/gkt1251.

    Article  CAS  PubMed  Google Scholar 

  38. National Human Genome Research Institute. Why mouse matters. 2010. https://www.genome.gov/10001345/importance-of-mouse-genome/. Accessed 11 Sept 2018.

  39. O’Farrell PH. High resolution two-dimensional electrophoresis of proteins. J Biol Chem. 1975;250(10):4007–21.

    PubMed  Google Scholar 

  40. Pan Y, Li D, Ma J, Shan L, Wei M. NT-proBNP test with improved accuracy for the diagnosis of chronic heart failure. Medicine (Baltimore). 2017;96(51):e9181. https://doi.org/10.1097/MD.0000000000009181.

    Article  CAS  Google Scholar 

  41. Pascovici D, Handler DC, Wu JX, Haynes PA. Multiple testing corrections in quantitative proteomics: a useful but blunt tool. Proteomics. 2016;16(18):2448–53. https://doi.org/10.1002/pmic.201600044.

    Article  CAS  PubMed  Google Scholar 

  42. Patrie SM, Roth MJ, Kohler JJ. Introduction to glycosylation and mass spectrometry. Methods Mol Biol. 2013;951:1–17. https://doi.org/10.1007/978-1-62703-146-2_1.

    Article  CAS  PubMed  Google Scholar 

  43. Pepe MS, Etzioni R, Feng Z, Potter JD, Thompson ML, Thornquist M, Winget M, Yasui Y. Phases of biomarker development for early detection of cancer. J Natl Cancer Inst. 2001;93(14):1054–61.

    Article  CAS  PubMed  Google Scholar 

  44. Rabilloud T, Lelong C. Two-dimensional gel electrophoresis in proteomics: a tutorial. J Proteome. 2011;74(10):1829–41. https://doi.org/10.1016/j.jprot.2011.05.040.

    Article  CAS  Google Scholar 

  45. Ramaiola I, Padro T, Pena E, Juan-Babot O, Cubedo J, Martin-Yuste V, Sabate M, Badimon L. Changes in thrombus composition and profilin-1 release in acute myocardial infarction. Eur Heart J. 2015;36(16):965–75. https://doi.org/10.1093/eurheartj/ehu356.

    Article  CAS  PubMed  Google Scholar 

  46. Roberts E, Ludman AJ, Dworzynski K, Al-Mohammad A, Cowie MR, McMurray JJ, Mant J. Failure NGDGfAHThe diagnostic accuracy of the natriuretic peptides in heart failure: systematic review and diagnostic meta-analysis in the acute care setting. BMJ. 2015;350:h910. https://doi.org/10.1136/bmj.h910.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Rocchetti MT, Papale M, Gesualdo L. Two-dimensional gel electrophoresis approach for CTL phosphoproteome analysis. Methods Mol Biol. 2014;1186:243–51. https://doi.org/10.1007/978-1-4939-1158-5_13.

    Article  CAS  PubMed  Google Scholar 

  48. Schluter H, Apweiler R, Holzhutter HG, Jungblut PR. Finding one’s way in proteomics: a protein species nomenclature. Chem Cent J. 2009;3:11. https://doi.org/10.1186/1752-153X-3-11.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Serang O, Käll L. Solution to statistical challenges in proteomics is more statistics, not less. J Proteome Res. 2015;14(10):4099–103. https://doi.org/10.1021/acs.jproteome.5b00568.

    Article  CAS  PubMed  Google Scholar 

  50. Shadforth I, Crowther D, Bessant C. Protein and peptide identification algorithms using MS for use in high-throughput, automated pipelines. Proteomics. 2005;5(16):4082–95. https://doi.org/10.1002/pmic.200402091.

    Article  CAS  PubMed  Google Scholar 

  51. Shevchenko A, Wilm M, Vorm O, Mann M. Mass spectrometric sequencing of proteins silver-stained polyacrylamide gels. Anal Chem. 1996;68(5):850–8.

    Article  CAS  PubMed  Google Scholar 

  52. Smith LM, Kelleher NL, Consortium for Top Down P. Proteoform: a single term describing protein complexity. Nat Methods. 2013;10(3):186–7. https://doi.org/10.1038/nmeth.2369.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Song IU, Chung SW, Kim YD, Maeng LS. Relationship between the hs-CRP as non-specific biomarker and Alzheimer’s disease according to aging process. Int J Med Sci. 2015;12(8):613–7. https://doi.org/10.7150/ijms.12742.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Storey JD. A direct approach to false discovery rates. J R Stat Soc Ser B. 2002;64(Part 3):479–98.

    Article  Google Scholar 

  55. Trudgian DC, Ridlova G, Fischer R, Mackeen MM, Ternette N, Acuto O, Kessler BM, Thomas B. Comparative evaluation of label-free SINQ normalized spectral index quantitation in the central proteomics facilities pipeline. Proteomics. 2011;11(14):2790–7. https://doi.org/10.1002/pmic.201000800.

    Article  CAS  PubMed  Google Scholar 

  56. Unlu M, Morgan ME, Minden JS. Difference gel electrophoresis: a single gel method for detecting changes in protein extracts. Electrophoresis. 1997;18(11):2071–7. https://doi.org/10.1002/elps.1150181133.

    Article  CAS  PubMed  Google Scholar 

  57. Unwin RD. Quantification of proteins by iTRAQ. Methods Mol Biol. 2010;658:205–15. https://doi.org/10.1007/978-1-60761-780-8_12.

    Article  CAS  PubMed  Google Scholar 

  58. Wang MC, Lee YH, Liao PC. Optimization of titanium dioxide and immunoaffinity-based enrichment procedures for tyrosine phosphopeptide using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Anal Bioanal Chem. 2015;407(5):1343–56. https://doi.org/10.1007/s00216-014-8352-0.

    Article  CAS  PubMed  Google Scholar 

  59. Westermeier TN, Höpker HR. Proteomics in practice: a guide to successful experimental design. 2nd ed: Wiley Online Library; 2008. https://onlinelibrary.wiley.com/doi/book/10.1002/9783527622290.

  60. Williams SA, Murthy AC, DeLisle RK, Hyde C, Malarstig A, Ostroff R, Weiss SJ, Segal MR, Ganz P. Improving assessment of drug safety through proteomics: early detection and mechanistic characterization of the unforeseen harmful effects of Torcetrapib. Circulation. 2018;137(10):999–1010. https://doi.org/10.1161/CIRCULATIONAHA.117.028213.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Wilm M, Shevchenko A, Houthaeve T, Breit S, Schweigerer L, Fotsis T, Mann M. Femtomole sequencing of proteins from polyacrylamide gels by nano-electrospray mass spectrometry. Nature. 1996;379(6564):466–9. https://doi.org/10.1038/379466a0.

    Article  CAS  PubMed  Google Scholar 

  62. Winkler W, Zellner M, Diestinger M, Babeluk R, Marchetti M, Goll A, Zehetmayer S, Bauer P, Rappold E, Miller I, Roth E, Allmaier G, Oehler R. Biological variation of the platelet proteome in the elderly population and its implication for biomarker research. Mol Cell Proteomics. 2008;7(1):193–203. https://doi.org/10.1074/mcp.M700137-MCP200.

    Article  CAS  PubMed  Google Scholar 

  63. Wongsurawat T, Woo CC, Giannakakis A, Lin XY, Cheow ESH, Lee CN, Richards M, Sze SK, Nookaew I, Kuznetsov VA, Sorokin V. Distinctive molecular signature and activated signaling pathways in aortic smooth muscle cells of patients with myocardial infarction. Atherosclerosis. 2018;271:237–44. https://doi.org/10.1016/j.atherosclerosis.2018.01.024.

    Article  CAS  PubMed  Google Scholar 

  64. Yang H, Wahlmuller FC, Uhrin P, Baumgartner R, Mitulovic G, Sarg B, Geiger M, Zellner M. Proteome analysis of testis from infertile protein C inhibitor-deficient mice reveals novel changes in serpin processing and prostaglandin metabolism. Electrophoresis. 2015;36(21–22):2837–40. https://doi.org/10.1002/elps.201500218.

    Article  CAS  PubMed  Google Scholar 

  65. Yin X, Subramanian S, Hwang SJ, O’Donnell CJ, Fox CS, Courchesne P, Muntendam P, Gordon N, Adourian A, Juhasz P, Larson MG, Levy D. Protein biomarkers of new-onset cardiovascular disease: prospective study from the systems approach to biomarker research in cardiovascular disease initiative. Arterioscler Thromb Vasc Biol. 2014;34(4):939–45. https://doi.org/10.1161/atvbaha.113.302918.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Zellner M, Gerner C, Munk Eliasen M, Wurm S, Pollheimer J, Spittler A, Brostjan C, Roth E, Oehler R. Glutamine starvation of monocytes inhibits the ubiquitin-proteasome proteolytic pathway. Biochim Biophys Acta. 2003;1638(2):138–48.

    Article  CAS  PubMed  Google Scholar 

  67. Zellner M, Winkler W, Hayden H, Diestinger M, Eliasen M, Gesslbauer B, Miller I, Chang M, Kungl A, Roth E, Oehler R. Quantitative validation of different protein precipitation methods in proteome analysis of blood platelets. Electrophoresis. 2005;26(12):2481–9. https://doi.org/10.1002/elps.200410262.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Maria Zellner .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Zellner, M., Umlauf, E. (2019). Proteomics in Vascular Biology. In: Geiger, M. (eds) Fundamentals of Vascular Biology. Learning Materials in Biosciences. Springer, Cham. https://doi.org/10.1007/978-3-030-12270-6_17

Download citation

Publish with us

Policies and ethics