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Multiplexed MS/MS for improved data-independent acquisition

Abstract

In mass spectrometry–based proteomics, data-independent acquisition (DIA) strategies can acquire a single data set useful for both identification and quantification of detectable peptides in a complex mixture. However, DIA data are noisy owing to a typical five- to tenfold reduction in precursor selectivity compared to data obtained with data-dependent acquisition or selected reaction monitoring. We demonstrate a multiplexing strategy, MSX, for DIA analysis that increases precursor selectivity fivefold.

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Figure 1: Multiplexed data-independent acquisition with MSX.
Figure 2: Demultiplexing reduces chemical noise and improves selectivity.
Figure 3: Quantitation of the LVNELTEFAK peptide by MSX and MS1.

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References

  1. Stahl, D.C., Swiderek, K.M., Davis, M.T. & Lee, T.D. J. Am. Soc. Mass Spectrom. 7, 532–540 (1996).

    CAS  Article  Google Scholar 

  2. Liu, H., Sadygov, R.G. & Yates, J.R. Anal. Chem. 76, 4193–4201 (2004).

    CAS  Article  Google Scholar 

  3. Michalski, A., Cox, J. & Mann, M. J. Proteome Res. 10, 1785–1793 (2011).

    CAS  Article  Google Scholar 

  4. Wenner, B.R. & Lynn, B.C. J. Am. Soc. Mass Spectrom. 15, 150–157 (2004).

    CAS  Article  Google Scholar 

  5. Hoopmann, M.R., Finney, G.L. & MacCoss, M.J. Anal. Chem. 79, 5620–5632 (2007).

    CAS  Article  Google Scholar 

  6. Purvine, S., Eppel, J.T., Yi, E.C. & Goodlett, D.R. Proteomics 3, 847–850 (2003).

    CAS  Article  Google Scholar 

  7. Myung, S. et al. Anal. Chem. 75, 5137–5145 (2003).

    CAS  Article  Google Scholar 

  8. Venable, J.D., Dong, M.Q., Wohlschlegel, J., Dillin, A. & Yates, J.R. Nat. Methods 1, 39–45 (2004).

    CAS  Article  Google Scholar 

  9. Panchaud, A. et al. Anal. Chem. 81, 6481–6488 (2009).

    CAS  Article  Google Scholar 

  10. Weisbrod, C.R., Eng, J.K., Hoopmann, M.R., Baker, T. & Bruce, J.E. J. Proteome Res. 11, 1621–1632 (2012).

    CAS  Article  Google Scholar 

  11. Gillet, L.C. et al. Mol. Cell Proteomics 11, O111.016717 (2012).

    Article  Google Scholar 

  12. Williams, E.R., Loh, S.Y., McLafferty, F.W. & Cody, R.B. Anal. Chem. 62, 698–703 (1990).

    CAS  Article  Google Scholar 

  13. MacLean, B. et al. Bioinformatics 26, 966–968 (2010).

    CAS  Article  Google Scholar 

  14. US National Institute of Standards and Technology. NIST Peptide Tandem Mass Spectral Libraries (eds. Stein, S.E. & Rudnick, P.A.) 〈http://peptide.nist.gov/〉 (2009; 24 May 2011 builds).

  15. Yost, R.A. & Enke, C.G. Anal. Chem. 51, 1251–1264 (1979).

    CAS  Article  Google Scholar 

  16. Frahm, J.L., Howard, B.E., Heber, S. & Muddiman, D.C. J. Mass Spectrom. 41, 281–288 (2006).

    CAS  Article  Google Scholar 

  17. Gay, S., Binz, P.A., Hochstrasser, D.F. & Appel, R.D. Electrophoresis 20, 3527–3534 (1999).

    CAS  Article  Google Scholar 

  18. Frewen, B.E., Merrihew, G.E., Wu, C.C., Noble, W.S. & MacCoss, M.J. Anal. Chem. 78, 5678–5684 (2006).

    CAS  Article  Google Scholar 

  19. Lawson, C.L. & Hanson, R.J. Solving Least Squares Problems (Society for Industrial and Applied Mathematics, Philadelphia, 1995).

  20. Chambers, M.C. et al. Nat. Biotechnol. 30, 918–920 (2012).

    CAS  Article  Google Scholar 

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Acknowledgements

The authors acknowledge financial support from US National Institutes of Health grants R01 GM103551, P41 GM103533 and F31 AG037265.

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Authors and Affiliations

Authors

Contributions

A.K., C.C.W., J.D.C., J.D.E., M.J.M., M.K., V.Z. and Y.S.T. designed experiments. A.K., C.C.W., J.D.E., M.J.M., M.K., N.W.B. and V.Z. interpreted results. J.D.E. and M.J.M. wrote the manuscript. A.K. created a firmware modification for the Q-Exactive. A.K. and M.K. provided preliminary data. G.E.M., J.D.E. and N.W.B. performed experiments. B.X.M., D.M.M. and J.D.E. wrote software.

Corresponding author

Correspondence to Michael J MacCoss.

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Competing interests

All authors received financial support from Thermo Fisher Scientific. A.K., J.D.C., M.K. and V.Z. are employees of Thermo Fisher Scientific, the company that markets and sells the mass spectrometry instrumentation used in this manuscript. Thermo Fisher will make the methods described herein available to their customers in version 2.2 SP1 of the Q-Exactive software.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8, Supplementary Tables 1 and 2, Supplementary Data and Supplementary Note (PDF 3353 kb)

Supplementary Video 1

Demonstration of multiplexed data-independent acquisition (MSX) and demultiplexing (MOV 5308 kb)

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Egertson, J., Kuehn, A., Merrihew, G. et al. Multiplexed MS/MS for improved data-independent acquisition. Nat Methods 10, 744–746 (2013). https://doi.org/10.1038/nmeth.2528

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