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SILAC Yeast: From Labeling to Comprehensive Proteome Quantification

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Shotgun Proteomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1156))

Abstract

Mass spectrometry-based quantitative proteomics can identify and quantify thousands of proteins in complex mixtures, enabling characterization and comparison of cellular functional states in a proteome-wide scale. In this context, stable isotope labeling with amino acids in cell culture (SILAC) has emerged as a simple yet powerful approach, which has been applied to address different biological questions across a variety of systems, ranging from single cells to entire multicellular organisms. In this chapter, detailed instructions for SILAC labeling yeast are provided, including a series of quality checks for evaluating labeling efficiency and procedures for determining the optimal labeling parameters for a particular yeast strain. In addition, two different complete workflows for the comprehensive mass spectrometry-based SILAC quantification of close to the entire yeast proteome are described, which can be applied to assess any biological question of interest and, therefore, can be of broad use for the researchers in the field.

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References

  1. Aebersold R, Mann M (2003) Mass spectrometry-based proteomics. Nature 422(6928):198–207

    Article  CAS  PubMed  Google Scholar 

  2. Ong SE, Blagoev B, Kratchmarova I, Kristensen DB, 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. Mol Cell Proteomics 1(5):376–386

    Article  CAS  PubMed  Google Scholar 

  3. Ong SE, Kratchmarova I, Mann M (2003) Properties of 13C-substituted arginine in stable isotope labeling by amino acids in cell culture (SILAC). J Proteome Res 2(2):173–181

    Article  CAS  PubMed  Google Scholar 

  4. Ong SE (2012) The expanding field of SILAC. Anal Bioanal Chem 404(4):967–976

    Article  CAS  PubMed  Google Scholar 

  5. Gruhler A, Olsen JV, Mohammed S, Mortensen P, Faergeman NJ, Mann M et al (2005) Quantitative phosphoproteomics applied to the yeast pheromone signaling pathway. Mol Cell Proteomics 4(3):310–327

    Article  CAS  PubMed  Google Scholar 

  6. Fröhlich F, Christiano R, Walther TC (2013) Native SILAC: metabolic labeling of proteins in prototroph microorganisms based on lysine synthesis regulation. Mol Cell Proteomics 12(7):1995–2005

    Article  PubMed  Google Scholar 

  7. Olsen JV, 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(3):635–648

    Article  CAS  PubMed  Google Scholar 

  8. Geiger T, Cox J, Ostasiewicz P, Wisniewski JR, Mann M (2010) Super-SILAC mix for quantitative proteomics of human tumor tissue. Nat Methods 7(5):383–385

    Article  CAS  PubMed  Google Scholar 

  9. Krüger M, Moser M, Ussar S, Thievessen I, Luber CA, Forner F et al (2008) SILAC mouse for quantitative proteomics uncovers kindlin-3 as an essential factor for red blood cell function. Cell 134(2):353–364

    Article  PubMed  Google Scholar 

  10. Pratt JM, Petty J, Riba-Garcia I, Robertson DH, Gaskell SJ, Oliver SG et al (2002) Dynamics of protein turnover, a missing dimension in proteomics. Mol Cell Proteomics 1(8):579–591

    Article  CAS  PubMed  Google Scholar 

  11. Doherty MK, Whitehead C, McCormack H, Gaskell SJ, Beynon RJ (2005) Proteome dynamics in complex organisms: using stable isotopes to monitor individual protein turnover rates. Proteomics 5(2):522–533

    Article  CAS  PubMed  Google Scholar 

  12. Doherty MK, Hammond DE, Clague MJ, Gaskell SJ, Beynon RJ (2009) Turnover of the human proteome: determination of protein intracellular stability by dynamic SILAC. J Proteome Res 8(1):104–112

    Article  CAS  PubMed  Google Scholar 

  13. Selbach M, Schwanhäusser B, Thierfelder N, Fang Z, Khanin R, Rajewsky N (2008) Widespread changes in protein synthesis induced by microRNAs. Nature 455(7209): 58–63

    Article  CAS  PubMed  Google Scholar 

  14. Schwanhäusser B, Busse D, Li N, Dittmar G, Schuchhardt J, Wolf J et al (2011) Global quantification of mammalian gene expression control. Nature 473(7347):337–342

    Article  PubMed  Google Scholar 

  15. Schulze WX, Mann M (2004) A novel proteomic screen for peptide-protein interactions. J Biol Chem 279(11):10756–10764

    Article  CAS  PubMed  Google Scholar 

  16. Blagoev B, Kratchmarova I, Ong SE, Nielsen M, Foster LJ, Mann M (2003) A proteomics strategy to elucidate functional protein-protein interactions applied to EGF signaling. Nat Biotechnol 21(3):315–318

    Article  CAS  PubMed  Google Scholar 

  17. Mittler G, Butter F, Mann M (2009) A SILAC-based DNA protein interaction screen that identifies candidate binding proteins to functional DNA elements. Genome Res 19(2):284–293

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  18. Ong SE, Li X, Schenone M, Schreiber SL, Carr SA (2012) Identifying cellular targets of small-molecule probes and drugs with biochemical enrichment and SILAC. Methods Mol Biol 803:129–140

    Article  CAS  PubMed  Google Scholar 

  19. Wagner SA, Beli P, Weinert BT, Nielsen ML, Cox J, Mann M et al (2011) A proteome-wide, quantitative survey of in vivo ubiquitylation sites reveals widespread regulatory roles. Mol Cell Proteomics 10(10): M111.013284

    Article  PubMed Central  PubMed  Google Scholar 

  20. Choudhary C, Kumar C, Gnad F, Nielsen ML, Rehman M, Walther TC et al (2009) Lysine acetylation targets protein complexes and co-regulates major cellular functions. Science 325(5942):834–840

    Article  CAS  PubMed  Google Scholar 

  21. Martin BR, Wang C, Adibekian A, Tully SE, Cravatt BF (2012) Global profiling of dynamic protein palmitoylation. Nat Methods 9(1): 84–89

    Article  CAS  Google Scholar 

  22. 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

    Article  CAS  PubMed  Google Scholar 

  23. Wiśniewski JR, Zougman A, Nagaraj N, Mann M (2009) Universal sample preparation method for proteome analysis. Nat Methods 6(5):359–362

    Article  PubMed  Google Scholar 

  24. Hubner NC, Ren S, Mann M (2008) Peptide separation with immobilized pI strips is an attractive alternative to in-gel protein digestion for proteome analysis. Proteomics 8(23–24):4862–4872

    Article  CAS  PubMed  Google Scholar 

  25. Rappsilber J, Ishihama Y, Mann M (2003) Stop and go extraction tips for matrix-assisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics. Anal Chem 75(3):663–670

    Article  CAS  PubMed  Google Scholar 

  26. Rappsilber J, Mann M, Ishihama Y (2007) Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat Protoc 2(8):1896–1906

    Article  CAS  PubMed  Google Scholar 

  27. Nesvizhskii AI (2010) A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics. J Proteomics 73(11):2092–2123

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  28. Ishihama Y, Rappsilber J, Andersen JS, Mann M (2002) Microcolumns with self-assembled particle frits for proteomics. J Chromatogr A 979(1–2):233–239

    Article  CAS  PubMed  Google Scholar 

  29. Olsen JV, de Godoy LM, Li G, Macek B, Mortensen P, Pesch R et al (2005) Parts per million mass accuracy on an Orbitrap mass spectrometer via lock mass injection into a C-trap. Mol Cell Proteomics 4(12):2010–2021

    Article  CAS  PubMed  Google Scholar 

  30. Olsen JV, Macek B, Lange O, Makarov A, Horning S, Mann M (2007) Higher-energy C-trap dissociation for peptide modification analysis. Nat Methods 4(9):709–712

    Article  CAS  PubMed  Google Scholar 

  31. 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

    Article  CAS  PubMed  Google Scholar 

  32. Cox J, Matic I, Hilger M, Nagaraj N, Selbach M, Olsen JV et al (2009) A practical guide to the MaxQuant computational platform for SILAC-based quantitative proteomics. Nat Protoc 4(5):698–705

    Article  CAS  PubMed  Google Scholar 

  33. de Godoy LM, Olsen JV, Cox J, Nielsen ML, Hubner NC, Fröhlich F et al (2008) Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast. Nature 455(7217):1251–1254

    Article  PubMed  Google Scholar 

  34. Nagaraj N, Kulak NA, Cox J, Neuhauser N, Mayr K, Hoerning O et al (2012) System-wide perturbation analysis with nearly complete coverage of the yeast proteome by single-shot ultra HPLC runs on a bench top Orbitrap. Mol Cell Proteomics 11(3): M111.013722

    Article  PubMed Central  PubMed  Google Scholar 

  35. Thakur SS, Geiger T, Chatterjee B, Bandilla P, Fröhlich F, Cox J et al (2011) Deep and highly sensitive proteome coverage by LC-MS/MS without prefractionation. Mol Cell Proteomics 10(8):M110.003699

    Article  PubMed Central  PubMed  Google Scholar 

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Authors and Affiliations

  1. Instituto Carlos Chagas, Fiocruz Parana, Rua Prof. Algacyr Munhoz Mader 3775, 81350-010, Curitiba, PR, Brazil

    Lyris M. F. de Godoy

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  1. Lyris M. F. de Godoy
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Correspondence to Lyris M. F. de Godoy .

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Editors and Affiliations

  1. Ludwig-Maximilians-University, Munich, Germany

    Daniel Martins-de-Souza

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de Godoy, L.M.F. (2014). SILAC Yeast: From Labeling to Comprehensive Proteome Quantification. In: Martins-de-Souza, D. (eds) Shotgun Proteomics. Methods in Molecular Biology, vol 1156. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-0685-7_6

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  • DOI: https://doi.org/10.1007/978-1-4939-0685-7_6

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-0684-0

  • Online ISBN: 978-1-4939-0685-7

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