Abstract
The ability to enumerate all of the proteins in a cell is quickly becoming a reality. Quantitative proteomics adds an extra dimension to proteome-wide discovery experiments by enabling differential measurements of protein concentrations, characterization of protein turnover, increased stringency of co-immunoprecipitation reactions, as well as many other intriguing applications. One of the most widely used techniques that enable relative protein quantitation is stable isotope labeling by amino acids in cell culture (SILAC) (Ong et al., Mol Cell Proteomics 1(5):376–386, 2002). Over the past decade, SILAC has become the preferred approach for proteome-wide quantitation by mass spectrometry. This approach relies on the metabolic incorporation of isotopically enriched amino acids into the proteome of cells—the proteome of “light” (1H, 12C, 14N) cells can then be compared to “heavy” (2H, 13C, 15N) cells as the isotopically labeled proteins and peptides are easily distinguished in a mass spectrometer. Since cellular uptake and response to isotopically different amino acid(s) is naïve, it is without impact on cell physiology. We provide a detailed step-by-step procedure for performing SILAC-based experiment for proteome-wide quantitation in this chapter.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ong SE, Blagoev B, Kratchmarova I, Kristensen DB, Steen H, Pandey A, 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(5):376–386
Beck S, Michalski A, Raether O, Lubeck M, Kaspar S, Goedecke N, Baessmann C, Hornburg D, Meier F, Paron I, Kulak NA, Cox J, Mann M (2015) The impact II, a very high-resolution quadrupole time-of-flight instrument (QTOF) for deep shotgun proteomics. Mol Cell Proteomics 14(7):2014–2029. doi:10.1074/mcp.M114.047407, M114.047407 [pii]
Zhang G, Fenyo D, Neubert TA (2009) Evaluation of the variation in sample preparation for comparative proteomics using stable isotope labeling by amino acids in cell culture. J Proteome Res 8(3):1285–1292. doi:10.1021/pr8006107
Bantscheff M, Schirle M, Sweetman G, Rick J, Kuster B (2007) Quantitative mass spectrometry in proteomics: a critical review. Anal Bioanal Chem 389(4):1017–1031. doi:10.1007/s00216-007-1486-6
Tzouros M, Golling S, Avila D, Lamerz J, Berrera M, Ebeling M, Langen H, Augustin A (2013) Development of a 5-plex SILAC method tuned for the quantitation of tyrosine phosphorylation dynamics. Mol Cell Proteomics 12(11):3339–3349. doi:10.1074/mcp.O113.027342, O113.027342 [pii]
Hilger M, Mann M (2012) Triple SILAC to determine stimulus specific interactions in the Wnt pathway. J Proteome Res 11(2):982–994. doi:10.1021/pr200740a
Van Hoof D, Pinkse MW, Oostwaard DW, Mummery CL, Heck AJ, Krijgsveld J (2007) An experimental correction for arginine-to-proline conversion artifacts in SILAC-based quantitative proteomics. Nat Methods 4(9):677–678. doi:10.1038/nmeth0907-677, nmeth0907-677 [pii]
Bendall SC, Hughes C, Stewart MH, Doble B, Bhatia M, Lajoie GA (2008) Prevention of amino acid conversion in SILAC experiments with embryonic stem cells. Mol Cell Proteomics 7(9):1587–1597. doi:10.1074/mcp.M800113-MCP200, M800113-MCP200 [pii]
de Godoy LM, Olsen JV, de Souza GA, Li G, Mortensen P, Mann M (2006) Status of complete proteome analysis by mass spectrometry: SILAC labeled yeast as a model system. Genome Biol 7(6):R50. doi:10.1186/gb-2006-7-6-r50, gb-2006-7-6-r50 [pii]
Gruhler A, Schulze WX, Matthiesen R, Mann M, Jensen ON (2005) Stable isotope labeling of Arabidopsis thaliana cells and quantitative proteomics by mass spectrometry. Mol Cell Proteomics 4(11):1697–1709. doi:10.1074/mcp.M500190-MCP200, M500190-MCP200 [pii]
Gruhler A, Olsen JV, Mohammed S, Mortensen P, Faergeman NJ, Mann M, Jensen ON (2005) Quantitative phosphoproteomics applied to the yeast pheromone signaling pathway. Mol Cell Proteomics 4(3):310–327. doi:10.1074/mcp.M400219-MCP200, M400219-MCP200 [pii]
Bose R, Molina H, Patterson AS, Bitok JK, Periaswamy B, Bader JS, Pandey A, Cole PA (2006) Phosphoproteomic analysis of Her2/neu signaling and inhibition. Proc Natl Acad Sci U S A 103(26):9773–9778. doi:10.1073/pnas.0603948103, 0603948103 [pii]
Boersema PJ, Geiger T, Wisniewski JR, Mann M (2013) Quantification of the N-glycosylated secretome by super-SILAC during breast cancer progression and in human blood samples. Mol Cell Proteomics 12(1):158–171. doi:10.1074/mcp.M112.023614, M112.023614 [pii]
Dhungana S, Merrick BA, Tomer KB, Fessler MB (2009) Quantitative proteomics analysis of macrophage rafts reveals compartmentalized activation of the proteasome and of proteasome-mediated ERK activation in response to lipopolysaccharide. Mol Cell Proteomics 8(1):201–213. doi:10.1074/mcp.M800286-MCP200, M800286-MCP200 [pii]
Ong SE, Mittler G, Mann M (2004) Identifying and quantifying in vivo methylation sites by heavy methyl SILAC. Nat Methods 1(2):119–126. doi:10.1038/nmeth715, nmeth715 [pii]
Zhang K, Li L, Zhu M, Wang G, Xie J, Zhao Y, Fan E, Xu L, Li E (2015) Comparative analysis of histone H3 and H4 post-translational modifications of esophageal squamous cell carcinoma with different invasive capabilities. J Proteomics 112:180–189. doi:10.1016/j.jprot.2014.09.004, S1874-3919(14)00419-9 [pii]
Kruger M, Moser M, Ussar S, Thievessen I, Luber CA, Forner F, Schmidt S, Zanivan S, Fassler R, Mann M (2008) SILAC mouse for quantitative proteomics uncovers kindlin-3 as an essential factor for red blood cell function. Cell 134(2):353–364. doi:10.1016/j.cell.2008.05.033, S0092-8674(08)00695-8 [pii]
Schwanhausser B, Gossen M, Dittmar G, Selbach M (2009) Global analysis of cellular protein translation by pulsed SILAC. Proteomics 9(1):205–209. doi:10.1002/pmic.200800275
Hanke S, Besir H, Oesterhelt D, Mann M (2008) Absolute SILAC for accurate quantitation of proteins in complex mixtures down to the attomole level. J Proteome Res 7(3):1118–1130. doi:10.1021/pr7007175
Rees JS, Lilley KS, Jackson AP (2015) SILAC-iPAC: a quantitative method for distinguishing genuine from non-specific components of protein complexes by parallel affinity capture. J Proteomics 115:143–156. doi:10.1016/j.jprot.2014.12.006, S1874-3919(14)00559-4 [pii]
Tackett AJ, DeGrasse JA, Sekedat MD, Oeffinger M, Rout MP, Chait BT (2005) I-DIRT, a general method for distinguishing between specific and nonspecific protein interactions. J Proteome Res 4(5):1752–1756. doi:10.1021/pr050225e
Kessner D, Chambers M, Burke R, Agus D, Mallick P (2008) ProteoWizard: open source software for rapid proteomics tools development. Bioinformatics 24(21):2534–2536. doi:10.1093/bioinformatics/btn323, btn323 [pii]
Mortensen P, Gouw JW, Olsen JV, Ong SE, Rigbolt KT, Bunkenborg J, Cox J, Foster LJ, Heck AJ, Blagoev B, Andersen JS, Mann M (2010) MSQuant, an open source platform for mass spectrometry-based quantitative proteomics. J Proteome Res 9(1):393–403. doi:10.1021/pr900721e
Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26(12):1367–1372. doi:10.1038/nbt.1511, nbt.1511 [pii]
Cox J, Matic I, Hilger M, Nagaraj N, Selbach M, Olsen JV, Mann M (2009) A practical guide to the MaxQuant computational platform for SILAC-based quantitative proteomics. Nat Protoc 4(5):698–705. doi:10.1038/nprot.2009.36, nprot.2009.36 [pii]
Moore RE, Young MK, Lee TD (2002) Qscore: an algorithm for evaluating SEQUEST database search results. J Am Soc Mass Spectrom 13(4):378–386. doi:10.1016/S1044-0305(02)00352-5
Qiao Y, Zhang H, Bu D, Sun S (2011) PI: an open-source software package for validation of the SEQUEST result and visualization of mass spectrum. BMC Bioinformatics 12:234. doi:10.1186/1471-2105-12-234, 1471-2105-12-234 [pii]
Ma J, Li W, Lv Y, Chang C, Wu S, Song L, Ding C, Wei H, He F, Jiang Y, Zhu Y (2013) A new insight into the impact of different proteases on SILAC quantitative proteome of the mouse liver. Proteomics. 13(15):2238–2242
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Science+Business Media LLC
About this protocol
Cite this protocol
Kani, K. (2017). Quantitative Proteomics Using SILAC. In: Comai, L., Katz, J., Mallick, P. (eds) Proteomics. Methods in Molecular Biology, vol 1550. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6747-6_13
Download citation
DOI: https://doi.org/10.1007/978-1-4939-6747-6_13
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-6745-2
Online ISBN: 978-1-4939-6747-6
eBook Packages: Springer Protocols