Advertisement

In Vivo Quantitative Proteomics: The SILAC Mouse

  • Sara Zanivan
  • Marcus Krueger
  • Matthias Mann
Protocol
First Online:
Part of the Methods in Molecular Biology book series (MIMB, volume 757)

Abstract

Mass spectrometry-based proteomics is a field that has been quickly developing, enabling increasingly giving in-depth characterization of the proteomes of cells and tissues. Current technology allows identifying thousands of proteins in a single experiment. Stable isotope labeling with amino acid in cell culture (SILAC) was originally developed for high accuracy quantitative proteomic studies in cell lines. We have shown that SILAC can be extended to in vivo animal model by fully labeling C57BL/6 mice with 13C6-Lysine (Lys6). We used SILAC mice technology to map quantitative proteomic changes in mice lacking the expression of β1 integrin, β-Parvin, or the integrin tail-binding protein Kindlin-3. This approach confirmed the absence of the proteins and revealed a role of Kindlin-3 in red blood cells. Here we describe a practical method to generate and maintain a colony of SILAC mice and optimal strategies to perform in vivo quantitative proteomic experiments.

Key words

SILAC mouse Mass spectrometry In vivo quantitative proteomics Integrins Cell adhesion 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgments

The authors would like to thank SILANTES for the development of Lys6-containing mouse diet and Marcus Moser for contributing to the application of the SILAC mouse technology.

References

  1. 1.
    Gumbiner, B. M. (1996) Cell adhesion: the molecular basis of tissue architecture and morphogenesis. Cell 84, 345–357.PubMedCrossRefGoogle Scholar
  2. 2.
    Hood, J. D., and Cheresh, D. A. (2002) Role of integrins in cell invasion and migration. Nat. Rev. Cancer. 2, 91–100.PubMedCrossRefGoogle Scholar
  3. 3.
    Hynes, R. O. (2002) Integrins: bidirectional, allosteric signaling machines. Cell 110, 673–687.PubMedCrossRefGoogle Scholar
  4. 4.
    Meves, A., Stremmel, C., Gottschalk, K., and Fassler, R. (2009) The Kindlin protein family: new members to the club of focal adhesion proteins. Trends. Cell Biol. 19, 504–513.PubMedCrossRefGoogle Scholar
  5. 5.
    Wisniewski, J. R., Zougman, A., Nagaraj, N., and Mann, M. (2009) Universal sample preparation method for proteome analysis. Nat. Methods 6, 359–362.PubMedCrossRefGoogle Scholar
  6. 6.
    Zanivan, S., Gnad, F., Wickstrom, S. A., Geiger, T., Macek, B., Cox, J., Fassler, R., and Mann, M. (2008) Solid tumor proteome and phosphoproteome analysis by high resolution mass spectrometry. J. Proteome Res. 7, 5314–5326.PubMedCrossRefGoogle Scholar
  7. 7.
    Ong, S. E., and Mann, M. (2007) Stable isotope labeling by amino acids in cell culture for quantitative proteomics. Methods Mol. Biol. 359, 37–52.PubMedCrossRefGoogle Scholar
  8. 8.
    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 quantification of haploid versus diploid yeast. Nature 455, 1251–1254.PubMedCrossRefGoogle Scholar
  9. 9.
    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
  10. 10.
    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
  11. 11.
    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
  12. 12.
    Benevenga, N. J., Calvert, C., Eckhert, C. D., Fahey, G. C., Greger, C. L., Keen, C. L., Knapka, J. J., Magalhaes, H., and Oftedal, O. T. (1995) Nutrient requirements of the mouse, National Academy Press, Washington, D.C.Google Scholar
  13. 13.
    Cox, J., and Mann, M. (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372.PubMedCrossRefGoogle Scholar
  14. 14.
    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
  15. 15.
    Wisniewski, J. R., Zougman, A., and Mann, M. (2009) Combination of FASP and StageTip-based fractionation allows in-depth analysis of the hippocampal membrane proteome. J Proteome Res. 8, 5674–5678.PubMedCrossRefGoogle Scholar
  16. 16.
    Brakebusch, C., Grose, R., Quondamatteo, F., Ramirez, A., Jorcano, J. L., Pirro, A., Svensson, M., Herken, R., Sasaki, T., Timpl, R., Werner, S., and Fassler, R. (2000) Skin and hair follicle integrity is crucially dependent on beta 1 integrin expression on keratinocytes. EMBO J. 19, 3990–4003.PubMedCrossRefGoogle Scholar
  17. 17.
    Kuhn, R., Schwenk, F., Aguet, M., and Rajewsky, K. (1995) Inducible gene targeting in mice. Science 269, 1427–1429.PubMedCrossRefGoogle Scholar
  18. 18.
    Nieswandt, B., Brakebusch, C., Bergmeier, W., Schulte, V., Bouvard, D., Mokhtari-Nejad, R., Lindhout, T., Heemskerk, J. W., Zirngibl, H., and Fassler, R. (2001) Glycoprotein VI but not alpha2beta1 integrin is essential for platelet interaction with collagen. EMBO J. 20, 2120–2130.PubMedCrossRefGoogle Scholar
  19. 19.
    Shevchenko, A., Tomas, H., Havlis, J., Olsen, J. V., and Mann, M. (2006) In-gel digestion for mass spectrometric characterization of proteins and proteomes. Nat. Protoc. 1, 2856–2860.PubMedCrossRefGoogle Scholar
  20. 20.
    Rappsilber, J., Mann, M., and Ishihama, Y. (2007) Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat. Protoc. 2, 1896–1906.PubMedCrossRefGoogle Scholar
  21. 21.
    Cox, J., Matic, I., Hilger, M., Nagaraj, N., Selbach, M., Olsen, J. V., and Mann, M. (2009) A practical guide to the MaxQuant computational platform for SILAC-based quantitative proteomics. Nat. Protoc. 4, 698–705.PubMedCrossRefGoogle Scholar
  22. 22.
    Forner, F., Kumar, C., Luber, C. A., Fromme, T., Klingenspor, M., and Mann, M. (2009) Proteome differences between brown and white fat mitochondria reveal specialized metabolic functions. Cell Metab. 10, 324–335.PubMedCrossRefGoogle Scholar
  23. 23.
    Macek, B., Mann, M., and Olsen, J. V. (2009) Global and site-specific quantitative phosphoproteomics: principles and applications. Annu. Rev. Pharmacol. Toxicol. 49, 199–221.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Vascular Proteomics GroupBeatson Institute for Cancer ResearchGlasgowUK
  2. 2.Department of Cardiac Development and RemodelingMax-Planck-Institute of Heart and Lung ResearchBad NauheimGermany
  3. 3.Department of Proteomics and Signal TransductionMax-Planck-Institute of Heart and Lung ResearchBad NauheimGermany

Personalised recommendations

Cite protocol

Buy options