Abstract
Mass spectrometry (MS)-based quantitative proteomics is an increasingly popular approach to study changes in protein abundances in biological samples. Stable isotope labeling by amino acids in cell culture (SILAC), one of the more widely used methods for quantitative proteomics, is a metabolic-labeling strategy that encodes whole cellular proteomes. Cells are grown in a culture medium where the natural form of an amino acid is replaced with a stable isotope form, such as arginine bearing six 13C atoms. Incorporation of the “heavy” amino acid occurs through cell growth, protein synthesis, and turnover. SILAC allows “light” and “heavy” proteomes to be distinguished by MS while avoiding any chemical derivatization and associated purification. In this chapter, we provide detailed SILAC protocols and explain how to incorporate SILAC into any experiment.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ong, S. E. and Mann, M. (2005) Mass spectrometry-based proteomics turns quantitative. Nat. Chem. Biol. 1, 252–262.
Ong, S. E., Blagoev, B., Kratchmarova, I., et al. (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.
Zhu, H., Pan, S., Gu, S., Bradbury, E. M., and Chen, X. (2002) Amino acid residue specific stable isotope labeling for quantitative proteomics. Rapid Commun. Mass Spectrom. 16, 2115–2123.
Jiang, H. and English, A. M. (2002) Quantitative analysis of the yeast proteome by incorporation of isotopically labeled leucine. J. Proteome Res. 1, 345–350.
Everley, P. A., Krijgsveld, J., Zetter, B. R., and Gygi, S. P. (2004) Quantitative cancer proteomics: stable isotope labeling with amino acids in cell culture (SILAC) as a tool for prostate cancer research. Mol. Cell Proteomics 3, 729–735.
Gu, S., Du, Y., Chen, J., et al. (2004) Large-scale quantitative proteomic study of PUMA-induced apoptosis using two-dimensional liquid chromatography-mass spectrometry coupled with amino acid-coded mass tagging. J. Proteome Res. 3, 1191–1200.
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.
de Hoog, C. L., Foster, L. J., and Mann, M. (2004) RNA and RNA binding proteins participate in early stages of cell spreading through spreading initiation centers. Cell 117, 649–662.
Foster, L. J., De Hoog, C. L., and Mann, M. (2003) Unbiased quantitative proteomics of lipid rafts reveals high specificity for signaling factors. Proc. Natl. Acad. Sci. USA 100, 5813–5818.
Andersen, J. S., Lam, Y. W., Leung, A. K., et al. (2005) Nucleolar proteome dynamics. Nature 433, 77–83.
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.
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.
Pratt, J. M., Petty, J., Riba-Garcia, I., et al. (2002) Dynamics of protein turnover, a missing dimension in proteomics. Mol. Cell Proteomics 1, 579–591.
Doherty, M. K., Whitehead, C., McCormack, H., Gaskell, S. J., and Beynon, R. J. (2005) Proteome dynamics in complex organisms: using stable isotopes to monitor individual protein turnover rates. Proteomics 5, 522–533.
Ibarrola, N., Molina, H., Iwahori, A., and Pandey, A. (2004) A novel proteomic approach for specific identification of tyrosine kinase substrates using [13C]tyrosine. J. Biol. Chem. 279, 15,805–15,813.
Ong, S. E., Mittler, G., and Mann, M. (2004) Identifying and quantifying in vivo methylation sites by heavy methyl SILAC. Nat. Methods 1, 119–126.
Ibarrola, N., Kalume, D. E., Gronborg, M., Iwahori, A., and Pandey, A. (2003) A proteomic approach for quantitation of phosphorylation using stable isotope labeling in cell culture. Anal. Chem. 75, 6043–6049.
Ballif, B. A., Roux, P. P., Gerber, S. A., MacKeigan, J. P., Blenis, J., and Gygi, S. P. (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. USA 102, 667–672.
Ishihama, Y., Sato, T., Tabata, T., et al. (2005) Quantitative mouse brain proteomics using culture-derived isotope tags as internal standards. Nat. Biotechnol. 23, 617–621.
Schulze, W. X. and Mann, M. (2004) A novel proteomic screen for peptide-protein interactions. J. Biol. Chem. 279, 10,756–10,764.
Gruhler, A., Olsen, J. V., Mohammed, S., et al. (2005) Quantitative phosphoproteomics applied to the yeast pheromone signaling pathway. Mol. Cell Proteomics 4, 310–327.
Gruhler, A., Schulze, W. X., Matthiesen, R., Mann, M., and Jensen, O. N. (2005) Stable isotope labeling of Arabidopsis thaliana cells and quantitative proteomics by mass spectrometry. Mol. Cell Proteomics 4, 1697–1709.
MacCoss, M. J. and Matthews, D. E. (2005) Quantitative MS for proteomics: teaching a new dog old tricks. Anal. Chem. 77, 294A–302A.
Olsen, J. V., Ong, S. E., and Mann, M. (2004) Trypsin cleaves exclusively C-terminal to arginine and lysine residues. Mol. Cell Proteomics 3, 608–614.
Zhang, R. and Regnier, F. E. (2002) Minimizing resolution of isotopically coded peptides in comparative proteomics. J. Proteome Res. 1, 139–147.
Gehrmann, M. L., Hathout, Y., and Fenselau, C. (2004) Evaluation of metabolic labeling for comparative proteomics in breast cancer cells. J. Proteome Res. 3, 1063–1068.
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.
Ishihama, Y. (2005) Proteomic LC-MS systems using nanoscale liquid chromatography with tandem mass spectrometry. J. Chromatogr. A. 1067, 73–83.
Meng, F., Forbes, A. J., Miller, L. M., and Kelleher, N. L. (2005) Detection and localization of protein modifications by high resolution tandem mass spectrometry. Mass Spectrom. Rev. 24, 126–134.
MacCoss, M. J., Wu, C. C., Liu, H., Sadygov, R., and Yates, J. R., 3rd (2003) A correlation algorithm for the automated quantitative analysis of shotgun proteomics data. Anal. Chem. 75, 6912–6921.
Li, X. J., Zhang, H., Ranish, J. A., and Aebersold, R. (2003) Automated statistical analysis of protein abundance ratios from data generated by stable-isotope dilution and tandem mass spectrometry. Anal. Chem. 75, 6648–6657.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Humana Press Inc.
About this protocol
Cite this protocol
Ong, SE., Mann, M. (2007). Stable Isotope Labeling by Amino Acids in Cell Culture for Quantitative Proteomics. In: Sechi, S. (eds) Quantitative Proteomics by Mass Spectrometry. Methods in Molecular Biology, vol 359. Humana Press. https://doi.org/10.1007/978-1-59745-255-7_3
Download citation
DOI: https://doi.org/10.1007/978-1-59745-255-7_3
Publisher Name: Humana Press
Print ISBN: 978-1-58829-571-2
Online ISBN: 978-1-59745-255-7
eBook Packages: Springer Protocols