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Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) for Quantitative Proteomics

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Advancements of Mass Spectrometry in Biomedical Research

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1140))

Abstract

Stable isotope labeling by amino acids in cell culture (SILAC) is a powerful approach for high-throughput quantitative proteomics. SILAC allows highly accurate protein quantitation through metabolic encoding of whole cell proteomes using stable isotope labeled amino acids. Since its introduction in 2002, SILAC has become increasingly popular. In this chapter we review the methodology and application of SILAC, with an emphasis on three research areas: dynamics of posttranslational modifications, protein-protein interactions, and protein turnover.

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References

  1. Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H., & Aebersold, R. (1999). Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nature Biotechnology, 17, 994–999.

    Article  CAS  PubMed  Google Scholar 

  2. Ross, P. L. (2004). Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Molecular and Cellular Proteomics, 3, 1154–1169.

    Article  CAS  PubMed  Google Scholar 

  3. Dayon, L., Hainard, A., Licker, V., Turck, N., Kuhn, K., Hochstrasser, D. F., et al. (2008). Relative quantification of proteins in human cerebrospinal fluids by MS/MS using 6-plex isobaric tags. Analytical Chemistry, 80, 2921–2931.

    Article  CAS  PubMed  Google Scholar 

  4. Stewart, I. I., Thomson, T., & Figeys, D. (2001). 18O Labeling: A tool for proteomics. Rapid Communications in Mass Spectrometry, 15, 2456–2465.

    Article  CAS  PubMed  Google Scholar 

  5. Ong, S., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., et al. (2002). Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Molecular & Cellular Proteomics, 1, 376–386.

    Article  CAS  Google Scholar 

  6. Ong, S., Foster, L. J., & Mann, M. (2003). Mass spectrometric-based approaches in quantitative proteomics. Methods, 29, 124–130.

    Article  CAS  PubMed  Google Scholar 

  7. Oda, Y., Huang, K., Cross, F. R., Cowburn, D., & Chait, B. T. (1999). Accurate quantitation of protein expression and site-specific phosphorylation. Proceedings of the National Academy of Sciences of the United States of America, 96, 6591–6596.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Bindschedler, L. V., & Cramer, R. (2011). Fully automated software solution for protein quantitation by global metabolic labeling with stable isotopes. Rapid Communications in Mass Spectrometry, 25, 1461–1471.

    Article  CAS  PubMed  Google Scholar 

  9. Manning, G., Plowman, G. D., Hunter, T., & Sudarsanam, S. (2002). Evolution of protein kinase signaling from yeast to man. Trends in Biochemical Sciences, 27, 514–520.

    Article  CAS  PubMed  Google Scholar 

  10. Ibarrola, N., Kalume, D. E., Gronborg, M., Iwahori, A., & Pandey, A. (2003). A proteomic approach for quantitation of phosphorylation using stable isotope labeling in cell culture. Analytical Chemistry, 75, 6043–6049.

    Article  CAS  PubMed  Google Scholar 

  11. Liang, X., Hajivandi, M., Veach, D., Wisniewski, D., Clarkson, B., Resh, M. D., et al. (2006). Quantification of change in phosphorylation of BCR-ABL kinase and its substrates in response to Imatinib treatment in human chronic myelogenous leukemia cells. Proteomics, 6, 4554–4564.

    Article  CAS  PubMed  Google Scholar 

  12. Park, K., Mohapatra, D. P., Misonou, H., & Trimmer, J. S. (2006). Graded regulation of the Kv2.1 potassium channel by variable phosphorylation. Science, 313, 976–979.

    Article  CAS  PubMed  Google Scholar 

  13. Wisniewski, J. R., Zougman, A., Krüger, S., Ziółkowski, P., Pudełko, M., Bebenek, M., et al. (2008). Constitutive and dynamic phosphorylation and acetylation sites on NUCKS, a hypermodified nuclear protein, studied by quantitative proteomics. Proteins, 73, 710–718.

    Article  CAS  PubMed  Google Scholar 

  14. Lu, X., Hamrahi, V. F., Tompkins, R. G., & Fischman, A. J. (2009). Effect of insulin levels on the phosphorylation of specific amino acid residues in IRS-1: Implications for burn-induced insulin resistance. International Journal of Molecular Medicine, 24, 531–538.

    Article  CAS  PubMed  Google Scholar 

  15. Olsen, J. V., Blagoev, B., Gnad, F., Macek, B., Kumar, C., Mortensen, P., et al. (2006). Global, in vivo, and site-specific phosphorylation dynamics in signaling networks. Cell, 127, 635–648.

    Article  CAS  PubMed  Google Scholar 

  16. Rogers, L. D., & Foster, L. J. (2009). Phosphoproteomics—Finally fulfilling the promise? Molecular BioSystems, 5, 1122–1129.

    Article  CAS  PubMed  Google Scholar 

  17. Nilsson, C. L. (2012). Advances in quantitative phosphoproteomics. Analytical Chemistry, 84, 735–746.

    Article  CAS  PubMed  Google Scholar 

  18. Bodenmiller, B., Mueller, L. N., Mueller, M., Domon, B., & Aebersold, R. (2007). Reproducible isolation of distinct, overlapping segments of the phosphoproteome. Nature Methods, 4, 231–237.

    Article  CAS  PubMed  Google Scholar 

  19. Stensballe, A., Andersen, S., & Jensen, O. N. (2001). Characterization of phosphoproteins from electrophoretic gels by nanoscale Fe(III) affinity chromatography with off-line mass spectrometry analysis. Proteomics, 1, 207–222.

    Article  CAS  PubMed  Google Scholar 

  20. Ficarro, S., Chertihin, O., Westbrook, V. A., White, F., Jayes, F., Kalab, P., et al. (2003). Phosphoproteome analysis of capacitated human sperm. Evidence of tyrosine phosphorylation of a kinase-anchoring protein 3 and valosin-containing protein/p97 during capacitation. Journal of Biological Chemistry, 278, 11579–11589.

    Article  CAS  Google Scholar 

  21. Larsen, M. R., Thingholm, T. E., Jensen, O. N., Roepstorff, P., & Jørgensen, T. J. D. (2005). Highly selective enrichment of phosphorylated peptides from peptide mixtures using titanium dioxide microcolumns. Molecular & Cellular Proteomics, 4, 873–886.

    Article  CAS  Google Scholar 

  22. Rush, J., Moritz, A., Lee, K. A., Guo, A., Goss, V. L., Spek, E. J., et al. (2005). Immunoaffinity profiling of tyrosine phosphorylation in cancer cells. Nature Biotechnology, 23, 94–101.

    Article  CAS  PubMed  Google Scholar 

  23. Zhang, G., & Neubert, T. A. (2011). Comparison of three quantitative phosphoproteomic strategies to study receptor tyrosine kinase signaling. Journal of Proteome Research, 10, 5454–5462.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Gruhler, A., Olsen, J. V., Mohammed, S., Mortensen, P., Faergeman, N. J., Mann, M., et al. (2005). Quantitative phosphoproteomics applied to the yeast pheromone signaling pathway. Molecular & Cellular Proteomics, 4, 310–327.

    Article  CAS  Google Scholar 

  25. Platt, M. D., Salicioni, A. M., Hunt, D. F., & Visconti, P. E. (2009). Use of differential isotopic labeling and mass spectrometry to analyze capacitation-associated changes in the phosphorylation status of mouse sperm proteins. Journal of Proteome Research, 8, 1431–1440.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Schreiber, T. B., Mäusbacher, N., Soroka, J., Wandinger, S. K., Buchner, J., & Daub, H. (2012). Global analysis of phosphoproteome regulation by the Ser/Thr phosphatase Ppt1 in Saccharomyces cerevisiae. Journal of Proteome Research, 11, 2397–2408.

    Article  CAS  PubMed  Google Scholar 

  27. Chen, C., Wu, D., Zhang, L., Zhao, Y., & Guo, L. (2012). Comparative phosphoproteomics studies of macrophage response to bacterial virulence effectors. Journal of Proteomics, 77, 251–261.

    Article  CAS  PubMed  Google Scholar 

  28. Xiao, K., Sun, J., Kim, J., Rajagopal, S., Zhai, B., Villén, J., et al. (2010). Global phosphorylation analysis of beta-arrestin-mediated signaling downstream of a seven transmembrane receptor (7TMR). Proceedings of the National Academy of Sciences, 107, 15299–15304.

    Article  CAS  Google Scholar 

  29. Hilger, M., Bonaldi, T., Gnad, F., & Mann, M. (2009). Systems-wide analysis of a phosphatase knock-down by quantitative proteomics and phosphoproteomics. Molecular and Cellular Proteomics, 8, 1908–1920.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Urbaniak, M. D., Martin, D. M. A., & Ferguson, M. A. J. (2013). Global quantitative SILAC phosphoproteomics reveals differential phosphorylation is widespread between the procyclic and bloodstream form lifecycle stages of Trypanosoma brucei. Journal of Proteome Research, 12, 2233–2244.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Pan, C., Olsen, J. V., Daub, H., & Mann, M. (2009). Global effects of kinase inhibitors on signaling networks revealed by quantitative phosphoproteomics. Molecular and Cellular Proteomics, 8, 2796–2808.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Liang, X., Fonnum, G., Hajivandi, M., Stene, T., Kjus, N. H., Ragnhildstveit, E., et al. (2007). Quantitative comparison of IMAC and TiO2 surfaces used in the study of regulated, dynamic protein phosphorylation. Journal of the American Society for Mass Spectrometry, 18, 1932–1944.

    Article  CAS  PubMed  Google Scholar 

  33. Blagoev, B., Ong, S., Kratchmarova, I., & Mann, M. (2004). Temporal analysis of phosphotyrosine-dependent signaling networks by quantitative proteomics. Nature Biotechnology, 22, 1139–1145.

    Article  CAS  PubMed  Google Scholar 

  34. Bose, R., Molina, H., Patterson, A. S., Bitok, J. K., Periaswamy, B., Bader, J. S., et al. (2006). Phosphoproteomic analysis of Her2/neu signaling and inhibition. Proceedings of the National Academy of Sciences of the United States of America, 103, 9773–9778.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Hinsby, A. M., Olsen, J. V., & Mann, M. (2004). Tyrosine phosphoproteomics of fibroblast growth factor signaling: A role for insulin receptor substrate-4. The Journal of Biological Chemistry, 279, 46438–46447.

    Article  CAS  PubMed  Google Scholar 

  36. Cunningham, D. L., Sweet, S. M. M., Cooper, H. J., & Heath, J. K. (2010). Differential phosphoproteomics of fibroblast growth factor signaling: Identification of Src family kinase-mediated phosphorylation events. Journal of Proteome Research, 9, 2317–2328.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Kratchmarova, I., Blagoev, B., Haack-Sorensen, M., Kassem, M., & Mann, M. (2005). Mechanism of divergent growth factor effects in mesenchymal stem cell differentiation. Science, 308, 1472–1477.

    Article  CAS  PubMed  Google Scholar 

  38. Zhang, G., Spellman, D. S., Skolnik, E. Y., & Neubert, T. A. (2006). Quantitative phosphotyrosine proteomics of EphB2 signaling by stable isotope labeling with amino acids in cell culture (SILAC). Journal of Proteome Research, 5, 581–588.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Krüger, M., Kratchmarova, I., Blagoev, B., Tseng, Y., Kahn, C. R., & Mann, M. (2008). Dissection of the insulin signaling pathway via quantitative phosphoproteomics. Proceedings of the National Academy of Sciences, 105, 2451–2456.

    Article  Google Scholar 

  40. Spellman, D. S., Deinhardt, K., Darie, C. C., Chao, M. V., & Neubert, T. A. (2008). Stable isotopic labeling by amino acids in cultured primary neurons: Application to brain-derived neurotrophic factor-dependent phosphotyrosine-associated signaling. Molecular and Cellular Proteomics, 7, 1067–1076.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Hammond, D. E., Hyde, R., Kratchmarova, I., Beynon, R. J., Blagoev, B., & Clague, M. J. (2010). Quantitative analysis of HGF and EGF-dependent phosphotyrosine signaling networks. Journal of Proteome Research, 9, 2734–2742.

    Article  CAS  PubMed  Google Scholar 

  42. Osinalde, N., Moss, H., Arrizabalaga, O., Omaetxebarria, M. J., Blagoev, B., Zubiaga, A. M., et al. (2011). Interleukin-2 signaling pathway analysis by quantitative phosphoproteomics. Journal of Proteomics, 75, 177–191.

    Article  CAS  PubMed  Google Scholar 

  43. Størvold, G. L., Landskron, J., Strozynski, M., Arntzen, M. Ø., Koehler, C. J., Kalland, M. E., et al. (2013). Quantitative profiling of tyrosine phosphorylation revealed changes in the activity of the T cell receptor signaling pathway upon cisplatin-induced apoptosis. Journal of Proteomics, 91, 344–357.

    Article  PubMed  CAS  Google Scholar 

  44. Zhang, Y., Wolf-Yadlin, A., Ross, P. L., Pappin, D. J., Rush, J., Lauffenburger, D. A., et al. (2005). Time-resolved mass spectrometry of tyrosine phosphorylation sites in the epidermal growth factor receptor signaling network reveals dynamic modules. Molecular & Cellular Proteomics, 4, 1240–1250.

    Article  CAS  Google Scholar 

  45. Zhang, L., Yu, C., Vasquez, F. E., Galeva, N., Onyango, I., Swerdlow, R. H., et al. (2010). Hyperglycemia alters the Schwann cell mitochondrial proteome and decreases coupled respiration in the absence of superoxide production. Journal of Proteome Research, 9, 458–471.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Matsumura, T., Oyama, M., Kozuka-Hata, H., Ishikawa, K., Inoue, T., Muta, T., et al. (2010). Identification of BCAP-(L) as a negative regulator of the TLR signaling-induced production of IL-6 and IL-10 in macrophages by tyrosine phosphoproteomics. Biochemical and Biophysical Research Communications, 400, 265–270.

    Article  CAS  PubMed  Google Scholar 

  47. Brockmeyer, C., Paster, W., Pepper, D., Tan, C. P., Trudgian, D. C., McGowan, S., et al. (2011). T cell receptor (TCR)-induced tyrosine phosphorylation dynamics identifies THEMIS as a new TCR signalosome component. Journal of Biological Chemistry, 286, 7535–7547.

    Article  CAS  Google Scholar 

  48. Azimifar, S. B., Böttcher, R. T., Zanivan, S., Grashoff, C., Krüger, M., Legate, K. R., et al. (2012). Induction of membrane circular dorsal ruffles requires co-signalling of integrin-ILK-complex and EGF receptor. Journal of Cell Science, 125, 435–448.

    Article  CAS  PubMed  Google Scholar 

  49. Mäusbacher, N., Schreiber, T. B., Machatti, M., Schaab, C., & Daub, H. (2012). Proteome-wide analysis of temporal phosphorylation dynamics in lysophosphatidic acid-induced signaling. Proteomics, 12, 3485–3498.

    Article  PubMed  CAS  Google Scholar 

  50. Pan, X., Whitten, D. A., Wu, M., Chan, C., Wilkerson, C. G., & Pestka, J. J. (2013). Global protein phosphorylation dynamics during deoxynivalenol-induced ribotoxic stress response in the macrophage. Toxicology and Applied Pharmacology, 268, 201–211.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Zhou, Q., Chaerkady, R., Shaw, P. G., Kensler, T. W., Pandey, A., & Davidson, N. E. (2010). Screening for therapeutic targets of vorinostat by SILAC-based proteomic analysis in human breast cancer cells. Proteomics, 10, 1029–1039.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Bennetzen, M. V., Larsen, D. H., Dinant, C., Watanabe, S., Bartek, J., Lukas, J., et al. (2013). Acetylation dynamics of human nuclear proteins during the ionizing radiation-induced DNA damage response. Cell Cycle, 12, 1688–1695.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Wu, Q., Xu, W., Cao, L., Li, X., He, T., Wu, Z., et al. (2013). SAHA treatment reveals the link between histone lysine acetylation and proteome in nonsmall cell lung cancer A549 Cells. Journal of Proteome Research, 12, 4064–4073.

    Article  CAS  PubMed  Google Scholar 

  54. Meierhofer, D., Wang, X., Huang, L., & Kaiser, P. (2008). Quantitative analysis of global ubiquitination in HeLa cells by mass spectrometry. Journal of Proteome Research, 7, 4566–4576.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Akimov, V., Rigbolt, K. T. G., Nielsen, M. M., & Blagoev, B. (2011). Characterization of ubiquitination dependent dynamics in growth factor receptor signaling by quantitative proteomics. Molecular BioSystems, 7, 3223–3233.

    Article  CAS  PubMed  Google Scholar 

  56. Na, C. H., & Peng, J. (2012). Analysis of ubiquitinated proteome by quantitative mass spectrometry. Methods in Molecular Biology, 893, 417–429.

    Article  CAS  PubMed  Google Scholar 

  57. Udeshi, N. D., Mertins, P., Svinkina, T., & Carr, S. A. (2013). Large-scale identification of ubiquitination sites by mass spectrometry. Nature Protocols, 8, 1950–1960.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Anania, V. G., Pham, V. C., Huang, X., Masselot, A., Lill, J. R., & Kirkpatrick, D. S. (2014). Peptide level immunoaffinity enrichment enhances ubiquitination site identification on individual proteins. Molecular and Cellular Proteomics, 13(1), 145–156.

    Article  CAS  PubMed  Google Scholar 

  59. Udeshi, N. D., Mani, D. R., Eisenhaure, T., Mertins, P., Jaffe, J. D., Clauser, K. R., et al. (2012). Methods for quantification of in vivo changes in protein ubiquitination following proteasome and deubiquitinase inhibition. Molecular and Cellular Proteomics, 11, 148–159.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Ong, S., Mittler, G., & Mann, M. (2004). Identifying and quantifying in vivo methylation sites by heavy methyl SILAC. Nature Methods, 1, 119–126.

    Article  CAS  PubMed  Google Scholar 

  61. Ong, S., & Mann, M. (2006). A practical recipe for stable isotope labeling by amino acids in cell culture (SILAC). Nature Protocols, 1, 2650–2660.

    Article  CAS  PubMed  Google Scholar 

  62. Zee, B. M., Levin, R. S., Xu, B., LeRoy, G., Wingreen, N. S., & Garcia, B. A. (2010). In vivo residue-specific histone methylation dynamics. Journal of Biological Chemistry, 285, 3341–3350.

    Article  CAS  Google Scholar 

  63. Bartke, T., Vermeulen, M., Xhemalce, B., Robson, S. C., Mann, M., & Kouzarides, T. (2010). Nucleosome-interacting proteins regulated by DNA and histone methylation. Cell, 143, 470–484.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Cao, X., Zee, B. M., & Garcia, B. A. (2013). Heavy methyl-SILAC labeling coupled with liquid chromatography and high-resolution mass spectrometry to study the dynamics of site-specific histone methylation. Methods in Molecular Biology, 977, 299–313.

    Article  CAS  PubMed  Google Scholar 

  65. Wang, Z., Pandey, A., & Hart, G. W. (2007). Dynamic interplay between O-linked N-acetylglucosaminylation and glycogen synthase kinase-3-dependent phosphorylation. Molecular & Cellular Proteomics, 6, 1365–1379.

    Article  CAS  Google Scholar 

  66. Ostasiewicz, P., Zielinska, D. F., Mann, M., & Wisniewski, J. R. (2010). Proteome, phosphoproteome, and N-glycoproteome are quantitatively preserved in formalin-fixed paraffin-embedded tissue and analyzable by high-resolution mass spectrometry. Journal of Proteome Research, 9, 3688–3700.

    Article  CAS  PubMed  Google Scholar 

  67. Palmisano, G., Lendal, S. E., & Larsen, M. R. (2011). Titanium dioxide enrichment of sialic acid-containing glycopeptides. Methods in Molecular Biology, 753, 309–322.

    Article  CAS  PubMed  Google Scholar 

  68. Boersema, P. J., Geiger, T., Wisniewski, J. R., & Mann, M. (2013). Quantification of the N-glycosylated secretome by super-SILAC during breast cancer progression and in human blood samples. Molecular and Cellular Proteomics, 12, 158–171.

    Article  PubMed  CAS  Google Scholar 

  69. Taga, Y., Kusubata, M., Ogawa-Goto, K., & Hattori, S. (2013). Site-specific quantitative analysis of overglycosylation of collagen in osteogenesis imperfecta using hydrazide chemistry and SILAC. Journal of Proteome Research, 12, 2225–2232.

    Article  CAS  PubMed  Google Scholar 

  70. Bonenfant, D., Towbin, H., Coulot, M., Schindler, P., Mueller, D. R., & van Oostrum, J. (2007). Analysis of dynamic changes in post-translational modifications of human histones during cell cycle by mass spectrometry. Molecular & Cellular Proteomics, 6, 1917–1932.

    Article  CAS  Google Scholar 

  71. Cuomo, A., Moretti, S., Minucci, S., & Bonaldi, T. (2011). SILAC-based proteomic analysis to dissect the “histone modification signature” of human breast cancer cells. Amino Acids, 41, 387–399.

    Article  CAS  PubMed  Google Scholar 

  72. Guan, X., Rastogi, N., Parthun, M. R., & Freitas, M. A. (2013). Discovery of histone modification crosstalk networks by stable isotope labeling of amino acids in cell culture mass spectrometry (SILAC MS). Molecular and Cellular Proteomics, 12, 2048–2059.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Tackett, A. J., DeGrasse, J. A., Sekedat, M. D., Oeffinger, M., Rout, M. P., & Chait, B. T. (2005). I-DIRT, a general method for distinguishing between specific and nonspecific protein interactions. Journal of Proteome Research, 4, 1752–1756.

    Article  CAS  PubMed  Google Scholar 

  74. Zhong, J., Chaerkady, R., Kandasamy, K., Gucek, M., Cole, R. N., & Pandey, A. (2011). The interactome of a PTB domain-containing adapter protein, Odin, revealed by SILAC. Journal of Proteomics, 74, 294–303.

    Article  CAS  PubMed  Google Scholar 

  75. Foster, L. J., Rudich, A., Talior, I., Patel, N., Huang, X., Furtado, L. M., et al. (2006). Insulin-dependent interactions of proteins with GLUT4 revealed through stable isotope labeling by amino acids in cell culture (SILAC). Journal of Proteome Research, 5, 64–75.

    Article  CAS  PubMed  Google Scholar 

  76. Hanke, S., & Mann, M. (2009). The phosphotyrosine interactome of the insulin receptor family and its substrates IRS-1 and IRS-2. Molecular and Cellular Proteomics, 8, 519–534.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Dobreva, I., Fielding, A., Foster, L. J., & Dedhar, S. (2008). Mapping the integrin-linked kinase interactome using SILAC. Journal of Proteome Research, 7, 1740–1749.

    Article  CAS  PubMed  Google Scholar 

  78. Sharma, K., Kumar, C., Kéri, G., Breitkopf, S. B., Oppermann, F. S., & Daub, H. (2010). Quantitative analysis of kinase-proximal signaling in lipopolysaccharide-induced innate immune response. Journal of Proteome Research, 9, 2539–2549.

    Article  CAS  PubMed  Google Scholar 

  79. Ranish, J. A., Yi, E. C., Leslie, D. M., Purvine, S. O., Goodlett, D. R., Eng, J., et al. (2003). The study of macromolecular complexes by quantitative proteomics. Nature Genetics, 33, 349–355.

    Article  CAS  PubMed  Google Scholar 

  80. Kito, K., Kawaguchi, N., Okada, S., & Ito, T. (2008). Discrimination between stable and dynamic components of protein complexes by means of quantitative proteomics. Proteomics, 8, 2366–2370.

    Article  CAS  PubMed  Google Scholar 

  81. Synowsky, S. A., van Wijk, M., Raijmakers, R., & Heck, A. J. R. (2009). Comparative multiplexed mass spectrometric analyses of endogenously expressed yeast nuclear and cytoplasmic exosomes. Journal of Molecular Biology, 385, 1300–1313.

    Article  CAS  PubMed  Google Scholar 

  82. Chao, J. T., Foster, L. J., & Loewen, C. J. R. (2009). Identification of protein complexes with quantitative proteomics in S. cerevisiae. Journal of Visualized Experiments, 25, 1225.

    Google Scholar 

  83. Bard-Chapeau, E. A., Gunaratne, J., Kumar, P., Chua, B. Q., Muller, J., Bard, F. A., et al. (2013). EVI1 oncoprotein interacts with a large and complex network of proteins and integrates signals through protein phosphorylation. Proceedings of the National Academy of Sciences, 110, E2885–E2894.

    Article  CAS  Google Scholar 

  84. Selbach, M., & Mann, M. (2006). Protein interaction screening by quantitative immunoprecipitation combined with knockdown (QUICK). Nature Methods, 3, 981–983.

    Article  CAS  PubMed  Google Scholar 

  85. Ge, F., Li, W., Bi, L., Tao, S., Zhang, Z., & Zhang, X. (2010). Identification of novel 14-3-3ζ interacting proteins by quantitative immunoprecipitation combined with knockdown (QUICK). Journal of Proteome Research, 9, 5848–5858.

    Article  CAS  PubMed  Google Scholar 

  86. Meixner, A., Boldt, K., Van Troys, M., Askenazi, M., Gloeckner, C. J., Bauer, M., et al. (2011). A QUICK screen for Lrrk2 interaction partners—Leucine-rich repeat kinase 2 is involved in actin cytoskeleton dynamics. Molecular and Cellular Proteomics, 10, M110.001172.

    Article  PubMed  CAS  Google Scholar 

  87. Hah, N., Kolkman, A., Ruhl, D. D., Pijnappel, W. W. M. P., Heck, A. J. R., Timmers, H. T. M., et al. (2010). A role for BAF57 in cell cycle-dependent transcriptional regulation by the SWI/SNF chromatin remodeling complex. Cancer Research, 70, 4402–4411.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Zheng, P., Zhong, Q., Xiong, Q., Yang, M., Zhang, J., Li, C., et al. (2012). QUICK identification and SPR validation of signal transducers and activators of transcription 3 (Stat3) interacting proteins. Journal of Proteomics, 75, 1055–1066.

    Article  CAS  PubMed  Google Scholar 

  89. Blagoev, B., Kratchmarova, I., Ong, S., Nielsen, M., Foster, L. J., & Mann, M. (2003). A proteomics strategy to elucidate functional protein-protein interactions applied to EGF signaling. Nature Biotechnology, 21, 315–318.

    Article  CAS  PubMed  Google Scholar 

  90. Belle, A., Tanay, A., Bitincka, L., Shamir, R., & O'Shea, E. K. (2006). Quantification of protein half-lives in the budding yeast proteome. Proceedings of the National Academy of Sciences of the United States of America, 103, 13004–13009.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Doherty, M. K., Whitehead, C., McCormack, H., Gaskell, S. J., & Beynon, R. J. (2005). Proteome dynamics in complex organisms: Using stable isotopes to monitor individual protein turnover rates. Proteomics, 5, 522–533.

    Article  CAS  PubMed  Google Scholar 

  92. Doherty, M. K., Hammond, D. E., Clague, M. J., Gaskell, S. J., & Beynon, R. J. (2009). Turnover of the human proteome: Determination of protein intracellular stability by dynamic SILAC. Journal of Proteome Research, 8, 104–112.

    Article  CAS  PubMed  Google Scholar 

  93. Milner, E., Barnea, E., Beer, I., & Admon, A. (2006). The turnover kinetics of major histocompatibility complex peptides of human cancer cells. Molecular & Cellular Proteomics, 5, 357–365.

    Article  CAS  Google Scholar 

  94. Cohen, L. D., Zuchman, R., Sorokina, O., Müller, A., Dieterich, D. C., Armstrong, J. D., et al. (2013). Metabolic turnover of synaptic proteins: Kinetics, interdependencies and implications for synaptic maintenance. PLoS One, 8, e63191.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Pratt, J. M., Robertson, D. H. L., Gaskell, S. J., Riba-Garcia, I., Hubbard, S. J., Sidhu, K., et al. (2002). Stable isotope labelling in vivo as an aid to protein identification in peptide mass fingerprinting. Proteomics, 2, 157–163.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Cargile, B. J., Bundy, J. L., Grunden, A. M., & Stephenson, J. L. (2004). Synthesis/degradation ratio mass spectrometry for measuring relative dynamic protein turnover. Analytical Chemistry, 76, 86–97.

    Article  CAS  PubMed  Google Scholar 

  97. Andersen, J. S., Lam, Y. W., Leung, A. K. L., Ong, S., Lyon, C. E., Lamond, A. I., et al. (2005). Nucleolar proteome dynamics. Nature, 433, 77–83.

    Article  CAS  PubMed  Google Scholar 

  98. Cambridge, S. B., Gnad, F., Nguyen, C., Bermejo, J. L., Krüger, M., & Mann, M. (2011). Systems-wide proteomic analysis in mammalian cells reveals conserved, functional protein turnover. Journal of Proteome Research, 10, 5275–5284.

    Article  CAS  PubMed  Google Scholar 

  99. Boisvert, F., Ahmad, Y., Gierliński, M., Charrière, F., Lamont, D., Scott, M., et al. (2012). A quantitative spatial proteomics analysis of proteome turnover in human cells. Molecular and Cellular Proteomics, 11, M111.011429.

    Article  PubMed  CAS  Google Scholar 

  100. Tilghman, R. W., Blais, E. M., Cowan, C. R., Sherman, N. E., Grigera, P. R., Jeffery, E. D., et al. (2012). Matrix rigidity regulates cancer cell growth by modulating cellular metabolism and protein synthesis. PLoS One, 7, e37231.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Kristensen, L. P., Chen, L., Nielsen, M. O., Qanie, D. W., Kratchmarova, I., Kassem, M., et al. (2012). Temporal profiling and pulsed SILAC labeling identify novel secreted proteins during ex vivo osteoblast differentiation of human stromal stem cells. Molecular and Cellular Proteomics, 11, 989–1007.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., et al. (2011). Global quantification of mammalian gene expression control. Nature, 473, 337–342.

    Article  PubMed  CAS  Google Scholar 

  103. Schwanhäusser, B., Gossen, M., Dittmar, G., & Selbach, M. (2009). Global analysis of cellular protein translation by pulsed SILAC. Proteomics, 9, 205–209.

    Article  PubMed  CAS  Google Scholar 

  104. Jayapal, K. P., Sui, S., Philp, R. J., Kok, Y., Yap, M. G. S., Griffin, T. J., et al. (2010). Multitagging proteomic strategy to estimate protein turnover rates in dynamic systems. Journal of Proteome Research, 9, 2087–2097.

    Article  CAS  PubMed  Google Scholar 

  105. Zhang, G., Deinhardt, K., Chao, M. V., & Neubert, T. A. (2011). Study of neurotrophin-3 signaling in primary cultured neurons using multiplex stable isotope labeling with amino acids in cell culture. Journal of Proteome Research, 10, 2546–2554.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Krijgsveld, J., Ketting, R. F., Mahmoudi, T., Johansen, J., Artal-Sanz, M., Verrijzer, C. P., et al. (2003). Metabolic labeling of C. elegans and D. melanogaster for quantitative proteomics. Nature Biotechnology, 21, 927–931.

    Article  CAS  PubMed  Google Scholar 

  107. Larance, M., Bailly, A. P., Pourkarimi, E., Hay, R. T., Buchanan, G., Coulthurst, S., et al. (2011). Stable-isotope labeling with amino acids in nematodes. Nature Methods, 8, 849–851.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Sury, M. D., Chen, J., & Selbach, M. (2010). The SILAC fly allows for accurate protein quantification in vivo. Molecular and Cellular Proteomics, 9, 2173–2183.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Xu, P., Tan, H., Duong, D. M., Yang, Y., Kupsco, J., Moberg, K. H., et al. (2012). Stable isotope labeling with amino acids in Drosophila for quantifying proteins and modifications. Journal of Proteome Research, 11, 4403–4412.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Krüger, M., Moser, M., Ussar, S., Thievessen, I., Luber, C. A., Forner, F., et al. (2008). SILAC mouse for quantitative proteomics uncovers kindlin-3 as an essential factor for red blood cell function. Cell, 134, 353–364.

    Article  PubMed  CAS  Google Scholar 

  111. Wu, C. C., MacCoss, M. J., Howell, K. E., Matthews, D. E., & Yates, J. R. (2004). Metabolic labeling of mammalian organisms with stable isotopes for quantitative proteomic analysis. Analytical Chemistry, 76, 4951–4959.

    Article  CAS  PubMed  Google Scholar 

  112. McClatchy, D. B., Dong, M., Wu, C. C., Venable, J. D., & Yates, J. R. (2007). 15N metabolic labeling of mammalian tissue with slow protein turnover. Journal of Proteome Research, 6, 2005–2010.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Ishihama, Y., Sato, T., Tabata, T., Miyamoto, N., Sagane, K., Nagasu, T., et al. (2005). Quantitative mouse brain proteomics using culture-derived isotope tags as internal standards. Nature Biotechnology, 23, 617–621.

    Article  CAS  PubMed  Google Scholar 

  114. Geiger, T., Cox, J., Ostasiewicz, P., Wisniewski, J. R., & Mann, M. (2010). Super-SILAC mix for quantitative proteomics of human tumor tissue. Nature Methods, 7, 383–385.

    Article  CAS  PubMed  Google Scholar 

  115. Deeb, S. J., D’Souza, R. C. J., Cox, J., Schmidt-Supprian, M., & Mann, M. (2012). Super-SILAC allows classification of diffuse large B-cell lymphoma subtypes by their protein expression profiles. Molecular and Cellular Proteomics, 11, 77–89.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Monetti, M., Nagaraj, N., Sharma, K., & Mann, M. (2011). Large-scale phosphosite quantification in tissues by a spike-in SILAC method. Nature Methods, 8, 655–658.

    Article  CAS  PubMed  Google Scholar 

  117. Tzouros, M., Golling, S., Avila, D., Lamerz, J., Berrera, M., Ebeling, M., et al. (2013). Development of a 5-plex SILAC method tuned for the quantitation of tyrosine phosphorylation dynamics. Molecular and Cellular Proteomics, 12(11), 3339–3349.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Hebert, A. S., Merrill, A. E., Stefely, J. A., Bailey, D. J., Wenger, C. D., Westphall, M. S., et al. (2013). Amine-reactive neutron-encoded labels for highly plexed proteomic quantitation. Molecular and Cellular Proteomics, 12, 3360–3369.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Hoedt, E., Zhang, G., Neubert, T.A. (2019). Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) for Quantitative Proteomics. In: Woods, A., Darie, C. (eds) Advancements of Mass Spectrometry in Biomedical Research. Advances in Experimental Medicine and Biology, vol 1140. Springer, Cham. https://doi.org/10.1007/978-3-030-15950-4_31

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