Quantifying proteomes and their post-translational modifications by stable isotope label-based mass spectrometry

Current Opinion in Chemical Biology

Volumn 17, Issue 5, 2013, Pages 779-786

  Merrill, Anna E ^a   Coon, Joshua J ^a,b  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b UNIVERSITY OF WISCONSIN SCHOOL OF MEDICINE AND PUBLIC HEALTH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PHOSPHATASE; PROTEIN KINASE; PROTEOME; STABLE ISOTOPE;

AMINO ACID SEQUENCE; HUMAN; MASS SPECTROMETRY; NONHUMAN; PROTEIN ANALYSIS; PROTEIN PROCESSING; PROTEIN PROTEIN INTERACTION; PROTEIN SYNTHESIS; REVIEW;

ANIMALS; HUMANS; ISOTOPE LABELING; MASS SPECTROMETRY; PROTEIN BINDING; PROTEIN PROCESSING, POST-TRANSLATIONAL; PROTEOME; PROTEOMICS;

EID: 84887202097     PISSN: 13675931     EISSN: 18790402     Source Type: Journal    
DOI: 10.1016/j.cbpa.2013.06.011     Document Type: Review

References (55)

1. Gygi S.P., Rist B., Gerber S.A., Turecek F., Gelb M.H., Aebersold R. Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nat Biotechnol 1999, 17:994-999.
2. Thompson A., Schafer J., Kuhn K., Kienle S., Schwarz J., Schmidt G., Neumann T., Johnstone R., Mohammed A.K., Hamon C. Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal Chem 2003, 75:1895-1904.
3. Ross P.L., Huang Y.N., Marchese J.N., Williamson B., Parker K., Hattan S., Khainovski N., Pillai S., Dey S., Daniels S., et al. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol Cell Proteomics 2004, 3:1154-1169.
4. Ong S.E., Blagoev B., Kratchmarova I., Kristensen D.B., Steen H., Pandey A., Mann M. Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol Cell Proteomics 2002, 1:376-386.
5. Jiang H., English A.M. Quantitative analysis of the yeast proteome by incorporation of isotopically labeled leucine. J Proteome Res 2002, 1:345-350.
6. Choe L., D'Ascenzo M., Relkin N.R., Pappin D., Ross P., Williamson B., Guertin S., Pribil P., Lee K.H. 8-Plex quantitation of changes in cerebrospinal fluid protein expression in subjects undergoing intravenous immunoglobulin treatment for Alzheimer's disease. Proteomics 2007, 7:3651-3660.
7. McAlister G.C., Huttlin E.L., Haas W., Ting L., Jedrychowski M.P., Rogers J.C., Kuhn K., Pike I., Grothe R.A., Blethrow J.D., et al. Increasing the multiplexing capacity of TMTs using reporter ion isotopologues with isobaric masses. Anal Chem 2012, 84:7469-7478.
8. Werner T., Becher I., Sweetman G., Doce C., Savitski M.M., Bantscheff M. High-resolution enabled TMT 8-plexing. Anal Chem 2012, 84:7188-7194.
9. Dephoure N., Gygi S.P. Hyperplexing: a method for higher-order multiplexed quantitative proteomics provides a map of the dynamic response to rapamycin in yeast. Sci Signal 2012, 5:rs2.
10. Wenger C.D., Lee M.V., Hebert A.S., McAlister G.C., Phanstiel D.H., Westphall M.S., Coon J.J. Gas-phase purification enables accurate, multiplexed proteome quantification with isobaric tagging. Nat Methods 2011, 8:933-935.
11. Ting L., Rad R., Gygi S.P., Haas W. MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics. Nat Methods 2011, 8:937-940.
12. Olsen J.V., Vermeulen M., Santamaria A., Kumar C., Miller M.L., Jensen L.J., Gnad F., Cox J., Jensen T.S., Nigg E.A., et al. Quantitative phosphoproteomics reveals widespread full phosphorylation site occupancy during mitosis. Sci Signal 2010, 3:ra3.
13. Hebert A.S., Merrill A.E., Bailey D.J., Still A.J., Westphall M.S., Strieter E.R., Pagliarini D.J., Coon J.J. Neutron-encoded mass signatures for multiplexed proteome quantification. Nat Methods 2013, 10:332-334.
14. Sardiu M.E., Washburn M.P. Building protein-protein interaction networks with proteomics and informatics tools. J Biol Chem 2011, 286:23645-23651.
15. Jager S., Cimermancic P., Gulbahce N., Johnson J.R., McGovern K.E., Clarke S.C., Shales M., Mercenne G., Pache L., Li K., et al. Global landscape of HIV-human protein complexes. Nature 2012, 481:365-370.
16. Vermeulen M., Hubner N.C., Mann M. High confidence determination of specific protein-protein interactions using quantitative mass spectrometry. Curr Opin Biotechnol 2008, 19:331-337.
17. Pagliuca F.W., Collins M.O., Lichawska A., Zegerman P., Choudhary J.S., Pines J. Quantitative proteomics reveals the basis for the biochemical specificity of the cell-cycle machinery. Mol Cell 2011, 43:406-417.
18. Baker C.L., Kettenbach A.N., Loros J.J., Gerber S.A., Dunlap J.C. Quantitative proteomics reveals a dynamic interactome and phase-specific phosphorylation in the Neurospora circadian clock. Mol Cell 2009, 34:354-363.
19. Hilger M., Mann M. Triple SILAC to determine stimulus specific interactions in the Wnt pathway. J Proteome Res 2012, 11:982-994.
20. Hanke S., Mann M. The phosphotyrosine interactome of the insulin receptor family and its substrates IRS-1 and IRS-2. Mol Cell Proteomics 2009, 8:519-534.
21. Vermeulen M., Eberl H.C., Matarese F., Marks H., Denissov S., Butter F., Lee K.K., Olsen J.V., Hyman A.A., Stunnenberg H.G., et al. Quantitative interaction proteomics and genome-wide profiling of epigenetic histone marks and their readers. Cell 2010, 142:967-980.
22. Mittler G., Butter F., Mann M. A SILAC-based DNA protein interaction screen that identifies candidate binding proteins to functional DNA elements. Genome Res 2009, 19:284-293.
23. Butter F., Scheibe M., Morl M., Mann M. Unbiased RNA-protein interaction screen by quantitative proteomics. Proc Natl Acad Sci U S A 2009, 106:10626-10631.
24. Butter F., Davison L., Viturawong T., Scheibe M., Vermeulen M., Todd J.A., Mann M. Proteome-wide analysis of disease-associated SNPs that show allele-specific transcription factor binding. PLoS Genet 2012, 8:e1002982.
25. Hulce J.J., Cognetta A.B., Niphakis M.J., Tully S.E., Cravatt B.F. Proteome-wide mapping of cholesterol-interacting proteins in mammalian cells. Nat Methods 2013, 10:259-264.
26. Nita-Lazar A., Saito-Benz H., White F.M. Quantitative phosphoproteomics by mass spectrometry: past, present, and future. Proteomics 2008, 8:4433-4443.
27. Macek B., Mann M., Olsen J.V. Global and site-specific quantitative phosphoproteomics: principles and applications. Annu Rev Pharmacol Toxicol 2009, 49:199-221.
28. Yu Y., Yoon S.O., Poulogiannis G., Yang Q., Ma X.M., Villen J., Kubica N., Hoffman G.R., Cantley L.C., Gygi S.P., et al. Phosphoproteomic analysis identifies Grb10 as an mTORC1 substrate that negatively regulates insulin signaling. Science 2011, 332:1322-1326.
29. Robitaille A.M., Christen S., Shimobayashi M., Cornu M., Fava L.L., Moes S., Prescianotto-Baschong C., Sauer U., Jenoe P., Hall M.N. Quantitative phosphoproteomics reveal mTORC1 activates de novo pyrimidine synthesis. Science 2013, 339:1320-1323.
30. Daub H., Olsen J.V., Bairlein M., Gnad F., Oppermann F.S., Korner R., Greff Z., Keri G., Stemmann O., Mann M. Kinase-selective enrichment enables quantitative phosphoproteomics of the kinome across the cell cycle. Mol Cell 2008, 31:438-448.
31. Wu R., Dephoure N., Haas W., Huttlin E.L., Zhai B., Sowa M.E., Gygi S.P. Correct interpretation of comprehensive phosphorylation dynamics requires normalization by protein expression changes. Mol Cell Proteomics 2011, 10. M111 009654.
32. Wu R., Haas W., Dephoure N., Huttlin E.L., Zhai B., Sowa M.E., Gygi S.P. A large-scale method to measure absolute protein phosphorylation stoichiometries. Nat Methods 2011, 8:677-683.
33. Cox J., Mann M. Quantitative, high-resolution proteomics for data-driven systems biology. Annu Rev Biochem 2011, 80:273-299.
34. Bensimon A., Heck A.J., Aebersold R. Mass spectrometry-based proteomics and network biology. Annu Rev Biochem 2012, 81:379-405.
35. Geiger T., Cox J., Mann M. Proteomic changes resulting from gene copy number variations in cancer cells. PLoS Genet 2010, 6.
36. Tolonen A.C., Haas W., Chilaka A.C., Aach J., Gygi S.P., Church G.M. Proteome-wide systems analysis of a cellulosic biofuel-producing microbe. Mol Syst Biol 2011, 7:461.
37. Phanstiel D.H., Brumbaugh J., Wenger C.D., Tian S., Probasco M.D., Bailey D.J., Swaney D.L., Tervo M.A., Bolin J.M., Ruotti V., et al. Proteomic and phosphoproteomic comparison of human ES and iPS cells. Nat Methods 2011, 8:821-827.
38. Lee M.V., Topper S.E., Hubler S.L., Hose J., Wenger C.D., Coon J.J., Gasch A.P. A dynamic model of proteome changes reveals new roles for transcript alteration in yeast. Mol Syst Biol 2011, 7:514.
39. Schwanhausser B., Busse D., Li N., Dittmar G., Schuchhardt J., Wolf J., Chen W., Selbach M. Global quantification of mammalian gene expression control. Nature 2011, 473:337-342.
40. Huttlin E.L., Jedrychowski M.P., Elias J.E., Goswami T., Rad R., Beausoleil S.A., Villen J., Haas W., Sowa M.E., Gygi S.P. A tissue-specific atlas of mouse protein phosphorylation and expression. Cell 2010, 143:1174-1189.
41. Lundby A., Lage K., Weinert B.T., Bekker-Jensen D.B., Secher A., Skovgaard T., Kelstrup C.D., Dmytriyev A., Choudhary C., Lundby C., et al. Proteomic analysis of lysine acetylation sites in rat tissues reveals organ specificity and subcellular patterns. Cell Rep 2012, 2:419-431.
42. Lundby A., Secher A., Lage K., Nordsborg N.B., Dmytriyev A., Lundby C., Olsen J.V. Quantitative maps of protein phosphorylation sites across 14 different rat organs and tissues. Nat Commun 2012, 3:876.
43. Grimsrud P.A., Carson J.J., Hebert A.S., Hubler S.L., Niemi N.M., Bailey D.J., Jochem A., Stapleton D.S., Keller M.P., Westphall M.S., et al. A quantitative map of the liver mitochondrial phosphoproteome reveals posttranslational control of ketogenesis. Cell Metab 2012, 16:672-683.
44. Hebert A.S., Dittenhafer-Reed K.E., Yu W., Bailey D.J., Selen E.S., Boersma M.D., Carson J.J., Tonelli M., Balloon A.J., Higbee A.J., et al. Calorie Restriction and SIRT3 Trigger Global Reprogramming of the Mitochondrial Protein Acetylome. Mol Cell 2013, 49:186-199.
45. Gouw J.W., Krijgsveld J., Heck A.J. Quantitative proteomics by metabolic labeling of model organisms. Mol Cell Proteomics 2010, 9:11-24.
46. Kruger M., Moser M., Ussar S., Thievessen I., Luber C.A., Forner F., Schmidt S., Zanivan S., Fassler R., Mann M. SILAC mouse for quantitative proteomics uncovers kindlin-3 as an essential factor for red blood cell function. Cell 2008, 134:353-364.
47. Walther D.M., Mann M. Accurate quantification of more than 4000 mouse tissue proteins reveals minimal proteome changes during aging. Mol Cell Proteomics 2011, 10:M110004523.
48. Scholten A., Mohammed S., Low T.Y., Zanivan S., van Veen T.A., Delanghe B., Heck A.J. In-depth quantitative cardiac proteomics combining electron transfer dissociation and the metalloendopeptidase Lys-N with the SILAC mouse. Mol Cell Proteomics 2011, 10. O111 008474.
49. Geiger T., Cox J., Ostasiewicz P., Wisniewski J.R., Mann M. Super-SILAC mix for quantitative proteomics of human tumor tissue. Nat Methods 2010, 7:383-385.
50. Deeb S.J., D'Souza R.C., Cox J., Schmidt-Supprian M., Mann M. Super-SILAC allows classification of diffuse large B-cell lymphoma subtypes by their protein expression profiles. Mol Cell Proteomics 2012, 11:77-89.
51. Monetti M., Nagaraj N., Sharma K., Mann M. Large-scale phosphosite quantification in tissues by a spike-in SILAC method. Nat Methods 2011, 8:655-658.
52. Altelaar A.F., Munoz J., Heck A.J. Next-generation proteomics: towards an integrative view of proteome dynamics. Nat Rev Genet 2013, 14:35-48.
53. Bailey D.J., Rose C.M., McAlister G.C., Brumbaugh J., Yu P., Wenger C.D., Westphall M.S., Thomson J.A., Coon J.J. Instant spectral assignment for advanced decision tree-driven mass spectrometry. Proc Natl Acad Sci U S A 2012, 109:8411-8416.
54. Kim W., Bennett E.J., Huttlin E.L., Guo A., Li J., Possemato A., Sowa M.E., Rad R., Rush J., Comb M.J., et al. Systematic and quantitative assessment of the ubiquitin-modified proteome. Mol Cell 2011, 44:325-340.
55. Wagner S.A., Beli P., Weinert B.T., Nielsen M.L., Cox J., Mann M., Choudhary C. A proteome-wide, quantitative survey of in vivo ubiquitylation sites reveals widespread regulatory roles. Mol Cell Proteomics 2011, 10. M111013284.