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Proteome-Wide Quantitation by SILAC

  • Kristoffer T.G. Rigbolt
  • Blagoy Blagoev
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 658)

Abstract

Ongoing improvements in instrumentation, fractionation techniques, and enrichment procedures have dramatically increased the coverage of the proteome achievable via LC-MS/MS-based methodologies, opening the call for approaches to quantitatively assess differences at a proteome-wide scale. Stable isotope labeling by amino acids in cell culture (SILAC) has emerged as a powerful and versatile approach for proteome-wide quantitation by mass spectrometry. SILAC utilizes the cells’ own metabolism to incorporate isotopically labeled amino acids into its proteome which can be mixed with the proteome of unlabeled cells and differences in protein expression can easily be read out by comparing the abundance of the labeled versus unlabeled proteins. SILAC has been applied to numerous different cell lines and the technique has been adapted for a wide range of experimental procedures. In this chapter we provide detailed procedure for performing SILAC-based experiment for proteome-wide quantitation, including a protocol for optimizing SILAC labeling. We also provide an update on the most recent developments of this technique.

Key words

SILAC quantitative proteomics mass spectrometry LC-MS/MS labeling isotope 

Notes

Acknowledgements

We would like to thank all members of the Center for Experimental BioInformatics (CEBI) for useful discussions, especially Dr. Irina Kratchmarova for the critical reading of the chapter. The research leading to these results has received funding from the European Commission’s 7th Framework Programme (grant agreement HEALTH-F4-2008-201648/PROSPECTS), the Danish Natural Science Research Council and the Lundbeck Foundation.

References

  1. 1.
    Cox, J., and Mann, M. (2007) Is proteomics the new genomics? Cell 130, 395–398.PubMedCrossRefGoogle Scholar
  2. 2.
    de Godoy, L. M., Olsen, J. V., Cox, J., Nielsen, M. L., Hubner, N. C., Frohlich, F., Walther, T. C., and Mann, M. (2008) Comprehensive mass-spectrometry-based proteome quantitation of haploid versus diploid yeast. Nature 455, 1251–1254.PubMedCrossRefGoogle Scholar
  3. 3.
    Ong, S. E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., and Mann, M. (2002) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell. Proteomics 1, 376–386.PubMedCrossRefGoogle Scholar
  4. 4.
    Graumann, J., Hubner, N. C., Kim, J. B., Ko, K., Moser, M., Kumar, C., Cox, J., Scholer, H., and Mann, M. (2008) Stable isotope labeling by amino acids in cell culture (SILAC) and proteome quantitation of mouse embryonic stem cells to a depth of 5,111 proteins. Mol. Cell. Proteomics 7, 672–683.PubMedGoogle Scholar
  5. 5.
    Prokhorova, T. A., Rigbolt, K. T., Johansen, P. T., Henningsen, J., Kratchmarova, I., Kassem, M., and Blagoev, B. (2009) SILAC-labeling and quantitative comparison of the membrane proteomes of self-renewing and differentiating human embryonic stem cells. Mol. Cell. Proteomics 8, 959–970.Google Scholar
  6. 6.
    Bendall, S. C., Hughes, C., Stewart, M. H., Doble, B., Bhatia, M., and Lajoie, G. A. (2008) Prevention of amino acid conversion in SILAC experiments with embryonic stem cells. Mol. Cell. Proteomics 7, 1587–1597.PubMedCrossRefGoogle Scholar
  7. 7.
    Kratchmarova, I., Blagoev, B., Haack-Sorensen, M., Kassem, M., and Mann, M. (2005) Mechanism of divergent growth factor effects in mesenchymal stem cell differentiation. Science 308, 1472–1477.PubMedCrossRefGoogle Scholar
  8. 8.
    Van Hoof, D., Pinkse, M. W., Oostwaard, D. W., Mummery, C. L., Heck, A. J., and Krijgsveld, J. (2007) An experimental correction for arginine-to-proline conversion artifacts in SILAC-based quantitative proteomics. Nat. Methods 4, 677–678.PubMedCrossRefGoogle Scholar
  9. 9.
    Mann, M. (2006) Functional and quantitative proteomics using SILAC. Nat. Rev. Mol. Cell. Biol. 7, 952–958.PubMedCrossRefGoogle Scholar
  10. 10.
    Blagoev, B., and Mann, M. (2006) Quantitative proteomics to study mitogen-activated protein kinases. Methods 40, 243–250.PubMedCrossRefGoogle Scholar
  11. 11.
    Blagoev, B., Ong, S. E., Kratchmarova, I., and Mann, M. (2004) Temporal analysis of phosphotyrosine-dependent signaling networks by quantitative proteomics. Nat. Biotechnol. 22, 1139–1145.PubMedCrossRefGoogle Scholar
  12. 12.
    Olsen, J. V., Blagoev, B., Gnad, F., Macek, B., Kumar, C., Mortensen, P., and Mann, M. (2006) Global, in vivo, and site-specific phosphorylation dynamics in signaling networks. Cell 127, 635–648.PubMedCrossRefGoogle Scholar
  13. 13.
    Dengjel, J., Akimov, V., Olsen, J. V., Bunkenborg, J., Mann, M., Blagoev, B., and Andersen, J. S. (2007) Quantitative proteomic assessment of very early cellular signaling events. Nat. Biotechnol 25, 566–568.PubMedCrossRefGoogle Scholar
  14. 14.
    Blagoev, B., Kratchmarova, I., Ong, S. E., Nielsen, M., Foster, L. J., and Mann, M. (2003) A proteomics strategy to elucidate functional protein-protein interactions applied to EGF signaling. Nat. Biotechnol. 21, 315–318.PubMedCrossRefGoogle Scholar
  15. 15.
    Vermeulen, M., Mulder, K. W., Denissov, S., Pijnappel, W. W., van Schaik, F. M., Varier, R. A., Baltissen, M. P., Stunnenberg, H. G., Mann, M., and Timmers, H. T. (2007) Selective anchoring of TFIID to nucleosomes by trimethylation of histone H3 lysine 4. Cell 131, 58–69.PubMedCrossRefGoogle Scholar
  16. 16.
    Ishihama, Y., Sato, T., Tabata, T., Miyamoto, N., Sagane, K., Nagasu, T., and Oda, Y. (2005) Quantitative mouse brain proteomics using culture-derived isotope tags as internal standards. Nat. Biotechnol. 23, 617–621.PubMedCrossRefGoogle Scholar
  17. 17.
    Kruger, M., Moser, M., Ussar, S., Thievessen, I., Luber, C. A., Forner, F., Schmidt, S., Zanivan, S., Fassler, R., and Mann, M. (2008) SILAC mouse for quantitative proteomics uncovers kindlin-3 as an essential factor for red blood cell function. Cell 134, 353–364.PubMedCrossRefGoogle Scholar
  18. 18.
    Mueller, L. N., Brusniak, M. Y., Mani, D. R., and Aebersold, R (2008). An assessment of software solutions for the analysis of mass spectrometry based quantitative proteomics data. J. Proteome Res. 7, 51–61.PubMedCrossRefGoogle Scholar
  19. 19.
    Ong, S. E., Foster, L. J., and Mann, M. (2003) Mass spectrometric-based approaches in quantitative proteomics. Methods 29, 124–130.PubMedCrossRefGoogle Scholar
  20. 20.
    Bantscheff, M., Schirle, M., Sweetman, G., Rick, J., and Kuster, B. (2007) Quantitative mass spectrometry in proteomics: a critical review. Anal. Bioanal. Chem. 389, 1017–1031.PubMedCrossRefGoogle Scholar
  21. 21.
    Nesvizhskii, A. I., and Aebersold, R. (2005) Interpretation of shotgun proteomic data: the protein inference problem. Mol. Cell Proteomics 4, 1419–1440.PubMedCrossRefGoogle Scholar
  22. 22.
    Cox, J., and Mann, M. (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantitation. Nat. Biotechnol. 26, 1367–1372.PubMedCrossRefGoogle Scholar
  23. 23.
    Ong, S. E., Kratchmarova, I., and Mann, M. (2003) Properties of 13C-substituted arginine in stable isotope labeling by amino acids in cell culture (SILAC). J. Proteome Res. 2, 173–181.PubMedCrossRefGoogle Scholar
  24. 24.
    Nielsen, M. L., Vermeulen, M., Bonaldi, T., Cox, J., Moroder, L., and Mann, M. (2008) Iodoacetamide-induced artifact mimics ubiquitination in mass spectrometry. Nat. Methods 5, 459–460.PubMedCrossRefGoogle Scholar
  25. 25.
    Andersen, J. S., Lam, Y. W., Leung, A. K., Ong, S. E., Lyon, C. E., Lamond, A. I., and Mann, M. (2005) Nucleolar proteome dynamics. Nature 433, 77–83.PubMedCrossRefGoogle Scholar
  26. 26.
    Kruger, M., Kratchmarova, I., Blagoev, B., Tseng, Y. H., Kahn, C. R., and Mann, M. (2008) Dissection of the insulin signaling pathway via quantitative phosphoproteomics. Proc. Natl. Acad. Sci. USA 105, 2451–2456.PubMedCrossRefGoogle Scholar
  27. 27.
    Molina, H., Yang, Y., Ruch, T., Kim, J. W., Mortensen, P., Otto, T., Nalli, A., Tang, Q. Q., Lane, M. D., Chaerkady, R., and Pandey, A. (2009) Temporal profiling of the adipocyte proteome during differentiation using a five-plex SILAC based strategy. J. Proteome Re s. 8, 48–58.Google Scholar
  28. 28.
    Hubner, N. C., Ren, S., and Mann, M. (2008) Peptide separation with immobilized pI strips is an attractive alternative to in-gel protein digestion for proteome analysis. Proteomics 8, 4862–4872.PubMedCrossRefGoogle Scholar
  29. 29.
    Park, S. K., Venable, J. D., Xu, T., and Yates, J. R., 3rd. (2008) A quantitative analysis software tool for mass spectrometry-based proteomics. Nat. Methods 5, 319–322.PubMedGoogle Scholar
  30. 30.
    Dobreva, I., Fielding, A., Foster, L. J., and Dedhar, S. (2008) Mapping the integrin-linked kinase interactome using SILAC. J. Proteome Res. 7, 1740–1749.PubMedCrossRefGoogle Scholar
  31. 31.
    Kristensen, A. R., Schandorff, S., Hoyer-Hansen, M., Nielsen, M. O., Jaattela, M., Dengjel, J., and Andersen, J. S. (2008) Ordered organelle degradation during starvation-induced autophagy. Mol. Cell. Proteomics 7, 2419–2428.PubMedCrossRefGoogle Scholar
  32. 32.
    Dengjel, J., Kratchmarova, I., and Blagoev, B. (2009) Receptor tyrosine kinase signaling: a view from quantitative proteomics. Mol. Biosyst. 5, 1112–1121.Google Scholar
  33. 33.
    Mortensen, P., Gouw, J. W., Olsen, J. V., Ong, S. E., Rigbolt, K. T., Bunkenborg, J., Cox, J., Foster, L. J., Heck, A. J., Blagoev, B., Andersen, J. S., and Mann, M. (2010) MSQuant, an open source platform for mass spectrometry-based quantitative proteomics. J. Proteome Res. 9, 393–403.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Kristoffer T.G. Rigbolt
    • 1
  • Blagoy Blagoev
    • 1
  1. 1.Center for Experimental BioInformatics, Department of Biochemistry and Molecular BiologyUniversity of Southern DenmarkOdenseDenmark

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