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Analysis of Mass Spectrometry Data in Proteomics

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Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 453))

Abstract

The systematic study of proteins and protein networks, that is, proteomics, calls for qualitative and quantitative analysis of proteins and peptides. Mass spectrometry (MS) is a key analytical technology in current proteomics and modern mass spectrometers generate large amounts of high-quality data that in turn allow protein identification, annotation of secondary modifications, and determination of the absolute or relative abundance of individual proteins. Advances in mass spectrometryûdriven proteomics rely on robust bioinformatics tools that enable large-scale data analysis. This chapter describes some of the basic concepts and current approaches to the analysis of MS and MS/MS data in proteomics.

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References

  1. Kozak, M. (2006) Rethinking some mechanisms invoked to explain translational regulation in eukaryotes.Gene Available online 22 June.

    Google Scholar 

  2. Seet, B. T., Dikic, I., Zhou, M. M., et al. (2006) Reading protein modifications with interaction domains.Nat Rev Mol Cell Biol 7, 473–483.

    Article  PubMed  CAS  Google Scholar 

  3. Jensen, O. N. (2006) Interpreting the protein language using proteomics.Nat Rev Mol Cell Biol 7, 391–403.

    Article  PubMed  CAS  Google Scholar 

  4. Aebersold, R., Mann, M. (2003) Mass spectrometry-based proteomics.Nature 422, 198–207.

    Article  PubMed  CAS  Google Scholar 

  5. Patterson, S. D., Aebersold, R. (1995) Mass spectrometric approaches for the identification of gel-separated proteins.Electrophoresis 16, 1791–1814.

    Article  PubMed  CAS  Google Scholar 

  6. Domon, B, Aebersold, R. (2006) Challenges and opportunities in proteomic data analysis.Mol Cell Proteomics. Available online 8 August.

    Google Scholar 

  7. Patterson S. D. (2003) Data analysis: the Achilles heel of proteomics.Nat Biotechnol 21, 221–222.

    Article  PubMed  CAS  Google Scholar 

  8. Steen, H., Mann, M. (2004) The ABC's (and XYZ's) of peptide sequencing.Nat Rev Mol Cell Biol 5, 699–711.

    Article  PubMed  CAS  Google Scholar 

  9. Fridriksson, E. K., Beavil, A., Holowka, D., et al. (2000) Heterogeneous glycosylation of immunoglobulin E constructs characterized by top-down high-resolution 2-D mass spectrometry.Biochemistry 39, 3369–3376.

    Article  PubMed  CAS  Google Scholar 

  10. Jensen, O. N., Larsen, M. R., Roepstorff, P. (1998) Mass spectrometric identification and microcharacterization of proteins from electrophoretic gels: strategies and applications.Proteins 2, 74–89.

    Article  PubMed  Google Scholar 

  11. Roepstorff, P., Fohlman, J. (1984) Proposal for a common nomenclature for sequence ions in mass spectra of peptides.Biomed Mass Spectrom 11, 601.

    Article  PubMed  CAS  Google Scholar 

  12. Wysocki, V. H., Tsaprailis, G., Smith, L. L., et al. (2000) Mobile and localized protons: a framework for understanding peptide dissociation.J Mass Spectrom 35, 1399–1406.

    Article  PubMed  CAS  Google Scholar 

  13. Laskin, J., Futrell, J. H. (2003) Collisional activation of peptide ions in FT-ICR.Mass Spectrom Rev 22, 158–181.

    Article  PubMed  CAS  Google Scholar 

  14. Pedrioli, P. G., Eng, J. K., Hubley, R., et al. (2004) A common open representation of mass spectrometry data and its application to proteomics research.Nat Biotechnol 22, 1459–1466.

    Article  PubMed  CAS  Google Scholar 

  15. Orchard, S., Kersey, P., Hermjakob, H., et al. (2003) The HUPO Proteomics Standards Initiative meeting: towards common standards for exchanging proteomics data.Comp Funct Genom 4, 16–19.

    Article  CAS  Google Scholar 

  16. Cottingham, K. (2006) CPAS: a proteom-ics data management system for the masses.J Proteome Res 5, 14.

    Article  PubMed  CAS  Google Scholar 

  17. Matthiesen, R., Trelle, M. B., Hϕjrup, P., et al. (2005) VEMS 3.0: Algorithms and computational tools for tandem mass spectrometry based identification of post-translational modifications in proteins.J Proteome Res 4, 2338–2347.

    Article  PubMed  CAS  Google Scholar 

  18. Fenyo, D., Qin, J., Chait, B.T. (1998) Protein identification using mass spectrometric information.Electrophoresis 19, 998–1005.

    Article  PubMed  CAS  Google Scholar 

  19. Matthiesen, R., Bunkenborg, J., Stensballe, A., et al. (2004) Database-independent, data-base-dependent, and extended interpretation of peptide mass spectra in VEMS V2.0.Proteomics 4, 2583–2593.

    Article  PubMed  CAS  Google Scholar 

  20. Fermin, D., Allen, B. B., Blackwell, T. W., et al. (2006) Novel gene and gene model detection using a whole genome open reading frame analysis in proteomics.Genome Biol 7, R35.

    Article  PubMed  Google Scholar 

  21. Fenyö, D., Beavis, R. C. (2003) A method for assessing the statistical significance of mass spectrometry-based protein identifications using general scoring schemes.Anal Chem 75, 768–774.

    Article  PubMed  Google Scholar 

  22. Creasy, D. M., Cottrell, J. S. (2002) Error tolerant searching of tandem mass spec-trometry data not yet interpreted.Proteomics 2, 1426–1434.

    Article  PubMed  CAS  Google Scholar 

  23. Craig, R., Beavis, R. C. (2004) TANDEM: matching proteins with tandem mass spectra,Bioinformatics 20, 1466–1467.

    Article  PubMed  CAS  Google Scholar 

  24. Woodsmall, R. M., Benson, D. A., (1993) Information resources at the National Center for Biotechnology Information.Bull Med Libr Assoc 81, 282–284.

    PubMed  CAS  Google Scholar 

  25. LinksKersey, P. J., Duarte, J., Williams, A., Karavidopoulou, Y., Birney, E., Apweiler, R. (2004) The International Protein Index: an integrated database for proteomics experiment.Proteomics 4, 1985–1988.

    Article  Google Scholar 

  26. LinksBairoach, A., Apweiler, R. (1998) The SWISS-PROT protein sequence data bank and its supplement TrEMBL in 1998.Nucleic Acids Res 26, 38–42.

    Article  Google Scholar 

  27. Colinge, J., Masselot, A., Cusin, I., et al. (2004) High-performance peptide identification by tandem mass spectrometry allows reliable automatic data processing in pro-teomics.Proteomics 4, 1977–1984.

    Article  PubMed  CAS  Google Scholar 

  28. López-Ferrer, D., Martínez-Bartolomé, S., Villar, M., et al. (2004) Statistical model for large-scale peptide identification in databases from tandem mass spectra using SEQUEST.Anal Chem 76, 6853–6860.

    Article  Google Scholar 

  29. Dancik, V., Addona, T., Clauser, K., et al. (1999) De novo peptide sequencing via tandem mass spectrometry.J Comput Biol 6, 327–342.

    Article  PubMed  CAS  Google Scholar 

  30. Frank, A., Pevzner, P. (2005) PepNovo: de novo peptide sequencing via probabilistic network modeling.Anal Chem 77, 964–973.

    Article  PubMed  CAS  Google Scholar 

  31. Johnson, R. S., Taylor, J. A. (2002) Searching sequence databases via de novo peptide sequencing by tandem mass spectrometry.Mol Biotechnol 22, 301–315.

    Article  PubMed  CAS  Google Scholar 

  32. Shevchenko, A., Sunyaev, S., Loboba, A., et al. (2001) Charting the proteomes of organisms with unsequenced genomes by MALDI-Quadrupole time-of flight mass spectrometry and BLAST homologuey searching.Anal Chem 73, 1917–1926.

    Article  PubMed  CAS  Google Scholar 

  33. Andersen, J. S., Wilkinson, C. J., Mayor, T., Mortensen, P., Nigg, E. A., Mann, M. (2003) Proteomic characterization of the human centrosome by protein correlation profiling.Nature 426, 570–574.

    Article  PubMed  CAS  Google Scholar 

  34. MacCoss, M. J., Wu, C. C., Liu, H., et al. (2003) A correlation algorithm for the automated quantitative analysis of shotgun proteomics data.Anal Chem 75, 6912–6921.

    Article  PubMed  CAS  Google Scholar 

  35. Venable, J. D., Dong, M. Q., Wohlsch-legel, J., et al. (2004) Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra.Nat Methods 1, 39–45.

    Article  PubMed  CAS  Google Scholar 

  36. Listgarten, J., Emili, A. (2005) Statistical and computational methods for comparative proteomic profiling using liquid chro-matography-tandem mass spectrometry.Mol Cell Proteomics 4, 419–434.

    Article  PubMed  CAS  Google Scholar 

  37. Beck, H. C., Nielsen, E. C., Matthiesen, R., et al. (2006) Quantitative proteomic analysis of post-translational modifications of human histones.Mol Cell Proteomics 5, 1314–1325.

    Article  PubMed  CAS  Google Scholar 

  38. Zar, J. H. (1999)Biostatistical Analysis. Prentice-Hall, Upper Saddle River, NJ.

    Google Scholar 

  39. Tusher, V. G., Tibshirani, R., Chu, G., et al. (2001) Significance analysis of microarrays applied to the ionizing radiation response.PNAS 98, 5116–5121.

    Article  PubMed  CAS  Google Scholar 

  40. Gerber, S. A., Rush, J., Stemman, O., et al. (2003) Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS.Proc Natl Acad Sci U S A 100, 6940–6945.

    Article  PubMed  CAS  Google Scholar 

  41. Turecek, F. (2002) Mass spectrometry in coupling with affinity capture-release and isotope-coded affinity tags for quantitative protein analysis.J Mass Spectrom 37, 1–14.

    Article  PubMed  CAS  Google Scholar 

  42. Ong, S. E., Blagoev, B., Kratchmarova, I., et al. (2002) Stable istotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.Mol Cell Proteom 1, 376–386.

    Article  CAS  Google Scholar 

  43. Yang, W. C., Mirzaei, H., Liu, X., et al. (2006) Enhancement of amino Acid detection and quantification by electrospray ionization mass spectrometry.Anal Chem 78, 4702–4708.

    Article  PubMed  CAS  Google Scholar 

  44. Gruhler, A., Schulze, W. X., Matthiesen, R., et al. (2005) Stable isotope labeling ofArabidopsis thaliana cells and quantitative proteomics by mass spectrometry.Mol Cell Proteom 4, 1697–709.

    Article  CAS  Google Scholar 

  45. Ballif, B. A., Roux, P. P., Gerber, S. A., et al. (2005) Quantitative phosphorylation profiling of the ERK/p90 ribosomal S6 kinase-signaling cassette and its targets, the tuberous sclerosis tumor suppressors.Proc Natl Acad Sci U S A 102, 667–672.

    Article  PubMed  CAS  Google Scholar 

  46. Fierro-Monti, I., Mohammed, S., Matthiesen, R., et al. (2005) Quantitative proteom-ics identifies Gemin5, a scaffolding protein involved in ribonucleoprotein assembly, as a novel partner for eukaryotic initiation factor 4.J Proteome Res 5, 1367–1378.

    Article  Google Scholar 

  47. Romijn, E. P., Christis, C., Wieffer, M., et al. (2006) Expression clustering reveals detailed co-expression patterns of functionally related proteins during B cell differentiation.Molecular & Cellular Proteomics 4, 1297–1310.

    Article  Google Scholar 

  48. Blagoev, B., Kratchmarova, I., Ong, S. E., et al. (2003) A proteomics strategy to elucidate functional protein-protein interactions applied to EGF signaling.Nat Biotechnol 21, 315–318.

    Article  PubMed  CAS  Google Scholar 

  49. http://www.yass.sdu.dk/yassdb/

  50. Craig, R., Cortens, J. P., Beavis, R. C. (2004) Open source system for analyzing, validating, and storing protein identification data.J Proteome Res 3, 1234–1242.

    Article  PubMed  CAS  Google Scholar 

  51. Jones, P., Cote, R. G., Martens, L., et al. (2006) PRIDE: a public repository of protein and peptide identifications for the pro-teomics community.Nucleic Acids Res 34, D659–663.

    Article  PubMed  CAS  Google Scholar 

  52. Gärdén, P., Alm, R., Häkkinen, J. (2005) Proteios: an open source proteomics initiative.Bioinformatics 21, 2085–2087.

    Article  PubMed  Google Scholar 

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Acknowledgments

R.M was supported by the EU TEMBLOR (IntAct) project and by a Carlsberg Foundation Fellowship. O.N.J. is a Lundbeck Foundation Research Professor and the recipient of a Young Investigator Award from the Danish Natural Science Research Council.

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© 2008 Humana Press, a part of Springer Science+Business Media, LLC

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Matthiesen, R., Jensen, O.N. (2008). Analysis of Mass Spectrometry Data in Proteomics. In: Keith, J.M. (eds) Bioinformatics. Methods in Molecular Biology™, vol 453. Humana Press. https://doi.org/10.1007/978-1-60327-429-6_4

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  • DOI: https://doi.org/10.1007/978-1-60327-429-6_4

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-60327-428-9

  • Online ISBN: 978-1-60327-429-6

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