Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations

Article metrics


Researchers have several options when designing proteomics experiments. Primary among these are choices of experimental method, instrumentation and spectral interpretation software. To evaluate these choices on a proteome scale, we compared triplicate measurements of the yeast proteome by liquid chromatography tandem mass spectrometry (LC-MS/MS) using linear ion trap (LTQ) and hybrid quadrupole time-of-flight (QqTOF; QSTAR) mass spectrometers. Acquired MS/MS spectra were interpreted with Mascot and SEQUEST algorithms with and without the requirement that all returned peptides be tryptic. Using a composite target decoy database strategy, we selected scoring criteria yielding 1% estimated false positive identifications at maximum sensitivity for all data sets, allowing reasonable comparisons between them. These comparisons indicate that Mascot and SEQUEST yield similar results for LTQ-acquired spectra but less so for QSTAR spectra. Furthermore, low reproducibility between replicate data acquisitions made on one or both instrument platforms can be exploited to increase sensitivity and confidence in large-scale protein identifications.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Overview of experiment design.
Figure 2: Mascot and SEQUEST are complementary analysis tools for interpreting LTQ and QSTAR MS/MS.
Figure 3: Considerably more peptide and protein identifications can be achieved by analyzing a sample multiple times.
Figure 4: LTQ and QSTAR mass spectrometers exclusively identify many peptides and proteins.
Figure 5: Practical comparison of analytical options.


  1. 1

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

  2. 2

    Aebersold, R. & Goodlett, D.R. Mass spectrometry in proteomics. Chem. Rev. 101, 269–95 (2001).

  3. 3

    Florens, L. et al. A proteomic view of the Plasmodium falciparum life cycle. Nature 419, 520–526 (2002).

  4. 4

    Peng, J. et al. A proteomics approach to understanding protein ubiquitination. Nat. Biotechnol. 21, 921–926 (2003).

  5. 5

    Foster, L.J., De Hoog, C.L. & Mann, M. Unbiased quantitative proteomics of lipid rafts reveals high specificity for signaling factors. Proc. Natl. Acad. Sci. USA 100, 5813–5818 (2003).

  6. 6

    Louris, J. et al. Instrumentation, applications, and energy deposition in quadrupole ion-trap tandem mass spectrometry. Anal. Chem. 59, 1677–1685 (1987).

  7. 7

    Jonscher, K.R. & Yates, J.R., III. The quadrupole ion trap mass spectrometer–a small solution to a big challenge. Anal. Biochem. 244, 1–15 (1997).

  8. 8

    Chernushevich, I.V., Loboda, A.V. & Thomson, B.A. An introduction to quadrupole-time-of-flight mass spectrometry. J. Mass Spectrom. 36, 849–865 (2001).

  9. 9

    Schwartz, J.C., Senko, M.W. & Syka, J.A. Two-dimensional quadurpole ion trap mass spectrometer. J. Am. Soc. Mass Spectrom. 13, 659–669 (2002).

  10. 10

    Mayya, V., Rezaul, K., Cong, Y.S. & Han, D. Systematic comparison of a two-dimensional ion trap and a three-dimensional ion trap mass spectrometer in proteomics. Mol. Cell. Proteomics 4, 214–223 (2005).

  11. 11

    Perkins, D.N., Pappin, D.J., Creasy, D.M. & Cottrell, J.S. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20, 3551–3567 (1999).

  12. 12

    Eng, J.K., McCormack, A.L. & Yates, J.R., III. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom. 5, 976–989 (1994).

  13. 13

    Sadygov, R.G., Cociorva, D. & Yates, J.R., III. Large-scale database searching using tandem mass spectra: Looking up the answer in the back of the book. Nat. Methods 1, 195–202 (2004).

  14. 14

    Lasonder, E. et al. Analysis of the Plasmodium falciparum proteome by high-accuracy mass spectrometry. Nature 419, 537–542 (2002).

  15. 15

    Resing, K.A. et al. Improving reproducibility and sensitivity in identifying human proteins by shotgun proteomics. Anal. Chem. 76, 3556–3568 (2004).

  16. 16

    Fenyo, D. & Beavis, R.C. A method for assessing the statistical significance of mass spectrometry–based protein identifications using general scoring schemes. Anal. Chem. 75, 768–774 (2003).

  17. 17

    Keller, A., Nesvizhskii, A.I., Kolker, E. & Aebersold, R. Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal. Chem. 74, 5383–5392 (2002).

  18. 18

    Elias, J.E., Gibbons, F.D., King, O.D., Roth, F.P. & Gygi, S.P. Intensity-based protein identification by machine learning from a library of tandem mass spectra. Nat. Biotechnol. 22, 214–219 (2004).

  19. 19

    Moore, R.E., Young, M.K. & Lee, T.D. Qscore: an algorithm for evaluating SEQUEST database search results. J. Am. Soc. Mass Spectrom. 13, 378–386 (2002).

  20. 20

    Peng, J., Elias, J.E., Thoreen, C.C., Licklider, L.J. & Gygi, S.P. Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome. J. Proteome Res. 2, 43–50 (2003).

  21. 21

    Sadygov, R.G. & Yates, J.R., III. A hypergeometric probability model for protein identification and validation using tandem mass spectral data and protein sequence databases. Anal. Chem. 75, 3792–3798 (2003).

  22. 22

    Liu, H., Sadygov, R.G. & Yates, J.R., III. A model for random sampling and estimation of relative protein abundance in shotgun proteomics. Anal. Chem. 76, 4193–4201 (2004).

  23. 23

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

  24. 24

    Medzihradszky, K.F. et al. The characteristics of peptide collision-induced dissociation using a high-performance MALDI-TOF/TOF tandem mass spectrometer. Anal. Chem. 72, 552–558 (2000).

  25. 25

    Hager, J.W. A new linear ion trap mass spectrometer. Rapid Comm. Mass Spec. 16, 512–526 (2002).

  26. 26

    Lipton, M.S. et al. Global analysis of the Deinococcus radiodurans proteome by using accurate mass tags. Proc. Natl. Acad. Sci. USA 99, 11049–11054 (2002).

  27. 27

    Meng, F. et al. Molecular-level description of proteins from Saccharomyces cerevisiae using quadrupole FT hybrid mass spectrometry for top down proteomics. Anal. Chem. 76, 2852–2858 (2004).

  28. 28

    Zhang, N., Aebersold, R. & Schwikowski, B. ProbID: a probabilistic algorithm to identify peptides through sequence database searching using tandem mass spectral data. Proteomics 2, 1406–1412 (2002).

  29. 29

    Tabb, D.L., Saraf, A. & Yates, J.R., III. GutenTag: high-throughput sequence tagging via an empirically derived fragmentation model. Anal. Chem. 75, 6415–6421 (2003).

  30. 30

    LeDuc, R.D. et al. ProSight PTM: an integrated environment for protein identification and characterization by top-down mass spectrometry. Nucleic Acids Res. 32, W340–W345 (2004).

  31. 31

    Chamrad, D.C. et al. Evaluation of algorithms for protein identification from sequence databases using mass spectrometry data. Proteomics 4, 619–628 (2004).

  32. 32

    Nesvizhskii, A.I., Keller, A., Kolker, E. & Aebersold, R. A statistical model for identifying proteins by tandem mass spectrometry. Anal. Chem. 75, 4646–4658 (2003).

  33. 33

    Verdel, A. & Moazed, D. Labeling and characterization of small RNAs associated with the RNA interference effector complex RITS. Methods Enzymol. 392, 297–307 (2005).

  34. 34

    Beausoleil, S.A. et al. Large-scale characterization of HeLa cell nuclear phosphoproteins. Proc. Natl. Acad. Sci. USA 101, 12130–12135 (2004).

  35. 35

    Peng, J. & Gygi, S.P. Proteomics: the move to mixtures. J. Mass Spectrom. 36, 1083–1091 (2001).

Download references


This work was supported in part by US National Institutes of Health GM67945 and HG00041 (S.P.G.). We thank D. Moazed for yeast lysate and the Pathology Functional Proteomic Center at Harvard Medical School for allowing use of their Mascot server.

Author information

Correspondence to Steven P Gygi.

Ethics declarations

Competing interests

ThermoElectron holds the licensing rights for the distribution of the SEQUEST algorithm. The Gygi lab has an industry-sponsored research project with ThermoElectron. These funds, however, did not provide any support (materials, equipment or salary) for the research described in this manuscript.

Supplementary information

Supplementary Fig. 1

Mascot and SEQUEST score distributions for target (blue) and decoy (red) database hits. (PDF 3286 kb)

Supplementary Fig. 2

Examples of MS/MS acquired by LTQ or QSTAR mass spectrometers. (PDF 107 kb)

Supplementary Fig. 3

Representation of MS/MS quality on LTQ and QSTAR and its influence on Mascot and SEQUEST scoring. (PDF 913 kb)

Supplementary Fig. 4

Comparison of LTQ and QSTAR acquisitions from equal gradient analyses. (PDF 73 kb)

Supplementary Fig. 5

Proteins identified by just one instrument appear to be less abundant than those identified by both LTQ and QSTAR. (PDF 83 kb)

Supplementary Fig. 6

Differential preference for ions selected for MS/MS by LTQ and QSTAR mass spectrometers influences the length distribution of identified peptides. (PDF 338 kb)

Supplementary Table 1

Mascot and SEQUEST score filter criteria applied to MS/MS spectra acquired on the LTQ and QSTAR mass spectrometers to achieve ˜99% precision (1% false positive rate) at maximum estimated sensitivity. (PDF 61 kb)

Supplementary Methods (PDF 83 kb)

Supplementary Data (PDF 87 kb)

Supplementary Discussion (PDF 109 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Elias, J., Haas, W., Faherty, B. et al. Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations. Nat Methods 2, 667–675 (2005) doi:10.1038/nmeth785

Download citation

Further reading