A comparison of the accuracy of iTRAQ quantification by nLC-ESI MSMS and nLC-MALDI MSMS methods

Journal of Proteomics

Volumn 73, Issue 7, 2010, Pages 1391-1403

  Shirran, Sally L ^a   Botting, Catherine H ^a  

^a UNIVERSITY OF ST ANDREWS   (United Kingdom)

Author keywords

iTRAQ quantification; Mascot; nLC ESI MSMS; nLC MALDI MSMS; ProteinPilot

Indexed keywords

ION; PROTEIN;

ACCURACY; ARTICLE; ELECTROSPRAY MASS SPECTROMETRY; INTERMETHOD COMPARISON; LIQUID CHROMATOGRAPHY; MATRIX ASSISTED LASER DESORPTION IONIZATION TIME OF FLIGHT MASS SPECTROMETRY; PRIORITY JOURNAL; PROTEIN ANALYSIS; QUANTITATIVE ANALYSIS;

GENE EXPRESSION PROFILING; PEPTIDE MAPPING; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SPECTROMETRY, MASS, ELECTROSPRAY IONIZATION; SPECTROMETRY, MASS, MATRIX-ASSISTED LASER DESORPTION-IONIZATION;

EID: 77951022016     PISSN: 18743919     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jprot.2010.03.003     Document Type: Article

References (26)

1. Shiio Y., and Aebersold R. Quantitative proteome analysis using isotope-coded affinity tags and mass spectrometry. Nat Protoc 1 (2006) 139-145
2. Ross P.L., Huang Y.N., Marchese J.N., Williamson B., Parker K., Hattan S., et al. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol Cell Proteomics 3 (2004) 1154-1169
3. Rudella A., Friso G., Alonso J.M., Ecker J.R., and van Wijk K.J. Downregulation of ClpR2 leads to reduced accumulation of the ClpPRS protease complex and defects in chloroplast biogenensis in Arabidopsis. Plant Cell 18 (2006) 1704-1721
4. Glen A., Gan C.S., Hamdy F.C., Eaton C.L., Cross S.C., Catto J.W.F., et al. iTRAQ-facilitated proteomic analysis of human prostate cancer cells identifies proteins associated with progression. J Proteome Res 7 (2008) 897-907
5. Radosevich T.J., Reinhardt T.A., Lippolis J.D., Bannantine J.P., and Stabel J.R. Proteome and differential analysis of membrane cytosolic proteins from mycobacterium avium subsp. paratuberculosis. J Bacteriol 189 (2007) 1109-1117
6. Yang Y., Zhang S., Howe K., Wilson D.B., Moser F., Irwin D., et al. comparison of nLC-ESI-MS/MS and nLC-MALDI-MS/MS for GeLC-based protein identification and iTRAQ-based shotgun quantitative proteomics. J Biomol Tech 18 (2007) 226-230
7. Kuzyk M.A., Ohlund L.B., Elliot M.H., Smith D., Qian H., Delany A., et al. A comparison of MS/MS-based, stable isotope labelled, quantitation performance on ESI-quadrupole TOF and MALDI-TOF/TOF mass spectrometers. Proteomics 9 (2009) 3328-3340
8. Stabels M.D., Cho J.-C., Giovannoni S.J., and Barofsky D.F. Proteomic Analysis of Novel Marine Bacteria Using MALDI and ESI Mass Spectrometry. J Biomol Tech 15 (2004) 191-198
9. Bodnar W.M., Blackburn R.K., Krise J.M., and Moseley M.A. Exploiting the complementary nature of LC/MALDI/MS/MS and LC/ESI/MS/MS for increased proteome coverage. J Am Soc Mass Spectrom 14 (2003) 971-979
10. Scheri R.C., Lee J., Curtis L.R., and Barofsky D.F.A. comparison of relative quantification with isobaric tags on a subset of the murine hepatic proteome using electrospray ionisation quadrupole time of flight and matrix assisted laser desorption ionisation tandem time of flight. Rapid Commum Mass Spectrom 22 (2008) 3137-3146
11. Wiese S., Reidergeld K.A., Meyer H.E., and Warscheid B. Protein labelling by iTRAQ: A new tool for quantitative mass spectrometry in proteome research. Proteomics 7 (2007) 340-350
12. http://www.abrf.org/ResearchGroups/Proteomics/Studies/ABRF-PRG07Presenta tion.ppt.
13. DeSouza L.V., Taylor A.M., Li W., Minkoff M.S., Romaschin A.D., Colgan T.J., et al. Absolute Quantification of endogenous levels of a potential cancer marker in cancerous and normal endometrial tissues. J Proteome Res 7 (2008) 3525-3534
14. Anderson L., and Hunter C.L. Quantitive mass spectrometric multiple reaction monitoring assays for major plasma proteins. Mol Cell Proteomics 5 (2006) 573-588
15. Patel V.J., Thalassinos K., Slade S.E., Connolly J.B., Crombie A., Murrell J.C., et al. A comparison of labelling and label free mass spectrometry-based proteomic approaches. J Prot Res 8 (2009) 3752-3759
16. Pierce A., Unwin R.D., Evans C.A., Griffith S., Carney L., Zhang L., et al. Eight-channel iTRAQ enables comparison of the activity of six leukemogenic tyrosine kinases. Mol Cell Proteomics 7 (2008) 853-863
17. Ow S.Y., Salim M., Noirel J., Evans C., Rehman I., and Wright P.C. iTRAQ underestimation in simple and complex mixtures: the good, the bad and the ugly. J Proteome Res 8 (2009) 5347-5355
18. Farinazzo A., Restuccia U., Bachi A., Guerrier L., Fortis F., Boschetti E., et al. Temporal quantitative proteomics by iTRAQ 2D-LC-MS/MS and corresponding mRNA expression analysis identify post-transcriptional modulation of actin-cytoskeleton regulators during TGF-β-Induced Epithelial-Mesenchymal transition. J Proteome Res 8 (2009) 35-47
19. Lacerda C.M.R., Xin L., Rogers I., Reardon K.F., Analysis of iTRAQ data using Mascot and Peaks quantification algorithms. Brief Func Genomics Proteomics 2008;7:119-126.
20. Shilov I.V., Seymour S.L., Patel A.A., Loboda A., Tang W.H., Keating S.P., et al. The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra. Mol Cell Proteomics 6 (2007) 1638-1655
21. Perkins D.N., Pappin D.J.C., Creasy D.M., and Cotrell J.S. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20 (1999) 3551-3567
22. Hu J., Qian J., Borisov O., Pan S., Li Y., Liu T., et al. Optimized oroteomic analysis of a mouse model of cerebellar dysfunction using amine-specific isobaric tags. Proteomics 6 (2006) 4321-4334
23. Pan C., Kora G., Pelletier D.A., McDonald W.H., Hurst G.B., Hettish R.L., et al. Robust estimation of peptide abundance ratios and rigorous scoring of their variability and bias in quantitative shotgun proteomics. Anal Chem 78 (2006) 7110-7120
24. Ong S.E., Blagoev B., Kratchmarova I., Kristensen D.B., Steen H., Pandy A., et al. Stable isotope labelling by amino aicds in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol Cell Proteomics 1 (2002) 376-386
25. Gygi S.P., Rist B., Gerber S.A., Turecek F., Gelb M.H., and Aebersold R. Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nat Biotechnol 17 (1999) 994-999
26. MacCoss M.J., Wu C.C., Liu H., Sadygov R., and Yates J.R. A correlation algorithm for the automated analysis of quantitative 'shotgun' proteomics data. Anal Chem 75 (2003) 6912-6921