Skip to main content
SpringerLink
Log in

Comparison of Data Acquisition Strategies on Quadrupole Ion Trap Instrumentation for Shotgun Proteomics

  • Focus: Advancing High Performance Mass Spectrometry: Research Article
  • Published:
Journal of The American Society for Mass Spectrometry

Abstract

The most common data collection in shotgun proteomics is via data-dependent acquisition (DDA), a process driven by an automated instrument control routine that directs MS/MS acquisition from the highest abundant signals to the lowest. An alternative to DDA is data-independent acquisition (DIA), a process in which a specified range in m/z is fragmented without regard to prioritization of a precursor ion or its relative abundance in the mass spectrum, thus potentially offering a more comprehensive analysis of peptides than DDA. In this work, we evaluate both DDA and DIA on three different linear ion trap instruments: an LTQ, an LTQ modified with an electrodynamic ion funnel, and an LTQ Velos. These instruments represent both older (LTQ) and newer (LTQ Velos) ion trap designs (i.e., linear versus dual ion traps, respectively), and allow direct comparison of peptide identifications using both DDA and DIA analysis. Further, as the LTQ Velos has an enhanced “S-lens” ion guide to improve ion flux, we found it logical to determine if the former LTQ model could be leveraged by improving sensitivity by modifying with an electrodynamic ion guide of significantly different design to the S-lens. We find that the ion funnel enabled LTQ identifies more proteins in the insoluble fraction of a yeast lysate than the other two instruments in DIA mode, whereas the faster scanning LTQ Velos performs better in DDA mode. We explore reasons for these results, including differences in scan speed, source ion optics, and linear ion trap design.

ᅟ

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5

Similar content being viewed by others

References

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

    Article  CAS  Google Scholar 

  2. Stahl, D.C., Swiderek, K.M., Davis, M.T., Lee, T.D.: Data-controlled automation of liquid chromatography/tandem mass spectrometry analysis of peptide mixtures. J. Am. Soc. Mass Spectrom. 7, 532–540 (1996)

    Article  CAS  Google Scholar 

  3. Tabb, D.L., Vega-Montoto, L., Rudnick, P.A., Variyath, A.M., Ham, A.J., Bunk, D.M., Kilpatrick, L.E., Billheimer, D.D., Blackman, R.K., Cardasis, H.L., Carr, S.A., Clauser, K.R., Jaffe, J.D., Kowalski, K.A., Neubert, T.A., Regnier, F.E., Schilling, B., Tegeler, T.J., Wang, M., Wang, P., Whiteaker, J.R., Zimmerman, L.J., Fisher, S.J., Gibson, B.W., Kinsinger, C.R., Mesri, M., Rodriguez, H., Stein, S.E., Tempst, P., Paulovich, A.G., Liebler, D.C., Spiegelman, C.: Repeatability and reproducibility in proteomic identifications by liquid chromatography-tandem mass spectrometry. J. Proteome Res. 9, 761–776 (2010)

    Article  CAS  Google Scholar 

  4. Michalski, A., Cox, J., Mann, M.: More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC-MS/MS. J. Proteome Res. 10, 1785–1793 (2011)

    Article  CAS  Google Scholar 

  5. Zhao, J., Grant, S.F.: Advances in whole genome sequencing technology. Curr. Pharm. Biotechnol. 12, 293–305 (2011)

    Article  CAS  Google Scholar 

  6. Chapman, J.D., Goodlett, D.R., Masselon, C.D.: Multiplexed and data-independent tandem mass spectrometry for global proteome profiling. Mass Spectrom. Rev. (2013). doi:10.1002/mas.21400

  7. Venable, J.D., Dong, M.Q., Wohlschlegel, J., Dillin, A., Yates, J.R.: Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra. Nat. Methods 1, 39–45 (2004)

    Article  CAS  Google Scholar 

  8. Purvine, S., Eppel, J.T., Yi, E.C., Goodlett, D.R.: Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3, 847–850 (2003)

    Article  CAS  Google Scholar 

  9. Silva, J.C., Denny, R., Dorschel, C.A., Gorenstein, M., Kass, I.J., Li, G.Z., McKenna, T., Nold, M.J., Richardson, K., Young, P., Geromanos, S.: Quantitative proteomic analysis by accurate mass retention time pairs. Anal. Chem. 77, 2187–2200 (2005)

    Article  CAS  Google Scholar 

  10. Silva, J.C., Gorenstein, M.V., Li, G.Z., Vissers, J.P., Geromanos, S.J.: Absolute quantification of proteins by LCMSE: a virtue of parallel MS acquisition. Mol. Cell. Proteomics 5, 144–156 (2006)

    Article  CAS  Google Scholar 

  11. Bond, N.J., Shliaha, P.V., Lilley, K.S., Gatto, L.: Improving qualitative and quantitative performance for MS(E)-based label-free proteomics. J. Proteome Res. 12, 2340–2353 (2013)

    Article  CAS  Google Scholar 

  12. Myung, S., Lee, Y.J., Moon, M.H., Taraszka, J., Sowell, R., Koeniger, S., Hilderbrand, A.E., Valentine, S.J., Cherbas, L., Cherbas, P., Kaufmann, T.C., Miller, D.F., Mechref, Y., Novotny, M.V., Ewing, M.A., Sporleder, C.R., Clemmer, D.E.: Development of high-sensitivity ion trap ion mobility spectrometry time-of-flight techniques: a high-throughput nano-LC-IMS-TOF separation of peptides arising from a Drosophila protein extract. Anal. Chem. 75, 5137–5145 (2003)

    Article  CAS  Google Scholar 

  13. Sowell, R.A., Hersberger, K.E., Kaufman, T.C., Clemmer, D.E.: Examining the proteome of Drosophila across organism lifespan. J. Proteome Res. 6, 3637–3647 (2007)

    Article  CAS  Google Scholar 

  14. Geiger, T., Cox, J., Mann, M.: Proteomics on an Orbitrap benchtop mass spectrometer using all-ion fragmentation. Mol. Cell. Proteomics 9, 2252–2261 (2010)

    Article  CAS  Google Scholar 

  15. Panchaud, A., Scherl, A., Shaffer, S.A., von Haller, P.D., Kulasekara, H.D., Miller, S.I., Goodlett, D.R.: Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Anal. Chem. 81, 6481–6488 (2009)

    Article  CAS  Google Scholar 

  16. Panchaud, A., Jung, S., Shaffer, S.A., Aitchison, J.D., Goodlett, D.R.: Faster, quantitative, and accurate precursor acquisition independent from ion count. Anal. Chem. 83, 2250–2257 (2011)

    Article  CAS  Google Scholar 

  17. Egertson, J.D., Kuehn, A., Merrihew, G.E., Bateman, N.W., MacLean, B.X., Ting, Y.S., Canterbury, J.D., Marsh, D.M., Kellmann, M., Zabrouskov, V., Wu, C.C., MacCoss, M.J.: Multiplexed MS/MS for improved data-independent acquisition. Nat. Methods 10, 744–746 (2013)

    Article  CAS  Google Scholar 

  18. Gillet, L.C., Navarro, P., Tate, S., Rost, H., Selevsek, N., Reiter, L., Bonner, R., Aebersold, R.: Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol. Cell. Proteomics 11, O111 016717 (2012)

    Article  Google Scholar 

  19. Weisbrod, C.R., Eng, J.K., Hoopmann, M.R., Baker, T., Bruce, J.E.: Accurate peptide fragment mass analysis: multiplexed peptide identification and quantification. J. Proteome Res. 11, 1621–1632 (2012)

    Article  CAS  Google Scholar 

  20. Kebarle, P., Tang, L.: From ions in solution to ions in the gas-phase—the mechanism of electrospray mass-spectrometry. Anal. Chem. 65, A972–A986 (1993)

    Google Scholar 

  21. Cech, N.B., Enke, C.G.: Practical implications of some recent studies in electrospray ionization fundamentals. Mass Spectrom. Rev. 20, 362–387 (2001)

    Article  CAS  Google Scholar 

  22. Page, J.S., Kelly, R.T., Tang, K., Smith, R.D.: Ionization and transmission efficiency in an electrospray ionization-mass spectrometry interface. J. Am. Soc. Mass Spectrom. 18, 1582–1590 (2007)

    Article  CAS  Google Scholar 

  23. Shaffer, S.A., Tang, K.Q., Anderson, G.A., Prior, D.C., Udseth, H.R., Smith, R.D.: A novel ion funnel for focusing ions at elevated pressure using electrospray ionization mass spectrometry. Rapid Commun. Mass Spectrom. 11, 1813–1817 (1997)

    Article  CAS  Google Scholar 

  24. Shaffer, S.A., Prior, D.C., Anderson, G.A., Udseth, H.R., Smith, R.D.: An ion funnel interface for improved ion focusing and sensitivity using electrospray ionization mass spectrometry. Anal. Chem. 70, 4111–4119 (1998)

    Article  CAS  Google Scholar 

  25. Shaffer, S.A., Tolmachev, A., Prior, D.C., Anderson, G.A., Udseth, H.R., Smith, R.D.: Characterization of an improved electrodynamic ion funnel interface for electrospray ionization mass spectrometry. Anal. Chem. 71, 2957–2964 (1999)

    Article  CAS  Google Scholar 

  26. Kelly, R.T., Tolmachev, A.V., Page, J.S., Tang, K., Smith, R.D.: The ion funnel: theory, implementations, and applications. Mass Spectrom. Rev. 29, 294–312 (2010)

    Google Scholar 

  27. Schwartz, J.C., Zhou, X-G., Bier, M.E.: Method and apparatus of increasing dynamic range and sensitivity of a mass spectrometer. US Patent 5,572,022 (1996)

  28. Page, J.S., Tang, K., Smith, R.D.: An electrodynamic ion funnel interface for greater sensitivity and higher throughput with linear ion trap mass spectrometers. Int. J. Mass Spectrom. 265, 244–250 (2007)

    Article  CAS  Google Scholar 

  29. Olsen, J.V., Schwartz, J.C., Griep-Raming, J., Nielsen, M.L., Damoc, E., Denisov, E., Lange, O., Remes, P., Taylor, D., Splendore, M., Wouters, E.R., Senko, M., Makarov, A., Mann, M., Horning, S.: A dual pressure linear ion trap Orbitrap instrument with very high sequencing speed. Mol. Cell. Proteomics 8, 2759–2769 (2009)

    Article  CAS  Google Scholar 

  30. Second, T.P., Blethrow, J.D., Schwartz, J.C., Merrihew, G.E., MacCoss, M.J., Swaney, D.L., Russell, J.D., Coon, J.J., Zabrouskov, V.: Dual-pressure linear ion trap mass spectrometer improving the analysis of complex protein mixtures. Anal. Chem. 81, 7757–7765 (2009)

    Article  Google Scholar 

  31. McDonald, W.H., Tabb, D.L., Sadygov, R.G., MacCoss, M.J., Venable, J., Graumann, J., Johnson, J.R., Cociorva, D., Yates III, J.R.: MS1, MS2, and SQT-three unified, compact, and easily parsed file formats for the storage of shotgun proteomic spectra and identifications. Rapid Commun. Mass Spectrom. 18, 2162–2168 (2004)

    Article  CAS  Google Scholar 

  32. Yates III, J.R., Eng, J.K., McCormack, A.L., Schieltz, D.: Method to correlate tandem mass spectra of modified peptides to amino acid sequences in the protein database. Anal. Chem. 67, 1426–1436 (1995)

    Article  CAS  Google Scholar 

  33. Kall, L., Canterbury, J.D., Weston, J., Noble, W.S., MacCoss, M.J.: Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nat. Methods 4, 923–925 (2007)

    Article  Google Scholar 

  34. Sharma, V., Eng, J.K., Maccoss, M.J., Riffle, M.: A mass spectrometry proteomics data management platform. Mol. Cell. Proteomics 11, 824–831 (2012)

    Article  CAS  Google Scholar 

  35. Zhang, B., Chambers, M.C., Tabb, D.L.: Proteomic parsimony through bipartite graph analysis improves accuracy and transparency. J. Proteome Res. 6, 3549–3557 (2007)

    Article  CAS  Google Scholar 

  36. Tang, K.Q., Tolmachev, A.V., Nikolaev, E., Zhang, R., Belov, M.E., Udseth, H.R., Smith, R.D.: Independent control of ion transmission in a jet disrupter dual-channel ion funnel electrospray ionization MS interface. Anal. Chem. 74, 5431–5437 (2002)

    Article  CAS  Google Scholar 

  37. Page, J.S., Bogdanov, B., Vilkov, A.N., Prior, D.C., Buschbach, M.A., Tang, K., Smith, R.D.: Automatic gain control in mass spectrometry using a jet disrupter electrode in an electrodynamic ion funnel. J. Am. Soc. Mass Spectrom. 16, 244–253 (2005)

    Article  CAS  Google Scholar 

  38. Yi, E.C., Marelli, M., Lee, H., Purvine, S.O., Aebersold, R., Aitchison, J.D., Goodlett, D.R.: Approaching complete peroxisome characterization by gas-phase fractionation. Electrophoresis 23, 3205–3216 (2002)

    Article  CAS  Google Scholar 

  39. Scherl, A., Shaffer, S.A., Taylor, G.K., Kulasekara, H.D., Miller, S.I., Goodlett, D.R.: Genome-specific gas-phase fractionation strategy for improved shotgun proteomic profiling of proteotypic peptides. Anal. Chem. 80, 1182–1191 (2008)

    Article  CAS  Google Scholar 

  40. Ghaemmaghami, S., Huh, W., Bower, K., Howson, R.W., Belle, A., Dephoure, N., O'Shea, E.K., Weissman, J.S.: Global analysis of protein expression in yeast. Nature 425, 737–741 (2003)

    Article  CAS  Google Scholar 

  41. Kaur, P., O'Connor, P.B.: Use of statistical methods for estimation of total number of charges in a mass spectrometry experiment. Anal. Chem. 76, 2756–2762 (2004)

    Article  CAS  Google Scholar 

  42. Schwartz, J.C.: Measuring ion number and detector gain. US Patent 7,109,474 (2006)

  43. MacCoss, M.J., Toth, M.J., Matthews, D.E.: Evaluation and optimization of ion-current ratio measurements by selected-ion-monitoring mass spectrometry. Anal. Chem. 73, 2976–2984 (2001)

    Article  CAS  Google Scholar 

  44. Bevington, P.R., Robinson, D.K.: Data Reduction and Error Analysis for the Physical Sciences, 2nd edn. McGraw-Hill, New York (1992)

    Google Scholar 

Download references

Acknowledgments

We thank Jason Page, Keqi Tang, and Richard D. Smith at PNNL for assistance with the ion funnel designs. We thank Jae Schwartz, Michael Senko, Jean-Jacques Dunyach, and Philip Remes of Thermo Scientific for helpful discussions. We acknowledge Larry Stark and Jim Greenwell in the Department of Physics Machine Shop and Jim Gladden, Lon Buck, and Roy Olund in the Department of Chemistry Electronics Shop at the University of Washington. We thank Vagisha Sharma and Mike Riffle at the Proteomics Resource at the University of Washington for help with the yeast proteome analysis. This work was supported by NIH R01 DK069386 and the Yeast Resource Center at the University of Washington.

Author information

Author notes

  1. Jesse D. Canterbury

    Present address: Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, CA, 95134, USA

  2. David R. Goodlett

    Present address: University of Maryland School of Pharmacy, 20 North Pine Street, Baltimore, MD, 21201, USA

  3. Scott A. Shaffer

    Present address: Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, 364 Plantation St, Worcester, MA, 01605, USA

Authors and Affiliations

  1. Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA

    Jesse D. Canterbury, Gennifer E. Merrihew & Michael J. MacCoss

  2. Department of Medicinal Chemistry, University of Washington, Seattle, WA, 98195, USA

    David R. Goodlett & Scott A. Shaffer

Authors
  1. Jesse D. Canterbury
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gennifer E. Merrihew
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michael J. MacCoss
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. David R. Goodlett
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Scott A. Shaffer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Scott A. Shaffer.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Canterbury, J.D., Merrihew, G.E., MacCoss, M.J. et al. Comparison of Data Acquisition Strategies on Quadrupole Ion Trap Instrumentation for Shotgun Proteomics. J. Am. Soc. Mass Spectrom. 25, 2048–2059 (2014). https://doi.org/10.1007/s13361-014-0981-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13361-014-0981-1

Key words

Search

Navigation