Skip to main content

Advertisement

Log in

Clustering and Filtering Tandem Mass Spectra Acquired in Data-Independent Mode

  • Research Article
  • Published:
Journal of The American Society for Mass Spectrometry

Abstract

Data-independent mass spectrometry activates all ion species isolated within a given mass-to-charge window (m/z) regardless of their abundance. This acquisition strategy overcomes the traditional data-dependent ion selection boosting data reproducibility and sensitivity. However, several tandem mass (MS/MS) spectra of the same precursor ion are acquired during chromatographic elution resulting in large data redundancy. Also, the significant number of chimeric spectra and the absence of accurate precursor ion masses hamper peptide identification. Here, we describe an algorithm to preprocess data-independent MS/MS spectra by filtering out noise peaks and clustering the spectra according to both the chromatographic elution profiles and the spectral similarity. In addition, we developed an approach to estimate the m/z value of precursor ions from clustered MS/MS spectra in order to improve database search performance. Data acquired using a small 3 m/z units precursor mass window and multiple injections to cover a m/z range of 400–1400 was processed with our algorithm. It showed an improvement in the number of both peptide and protein identifications by 8 % while reducing the number of submitted spectra by 18 % and the number of peaks by 55 %. We conclude that our clustering method is a valid approach for data analysis of these data-independent fragmentation spectra. The software including the source code is available for the scientific community.

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

Access this article

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

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6

Similar content being viewed by others

References

  1. Gatlin, C.L., Eng, J.K., Cross, S.T., Detter, J.C., Yates, J.R.: Automated identification of amino acid sequence variations in proteins by HPLC/microspray tandem mass spectrometry. Anal. Chem. 72, 757–763 (2000)

    Article  CAS  Google Scholar 

  2. Washburn, M.P., Wolters, D., Yates III, J.R.: Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nat. Biotechnol. 19, 242–247 (2001)

    Article  CAS  Google Scholar 

  3. Chang, E.J., Archambault, V., McLachlin, D.T., Krutchinsky, A.N., Chait, B.T.: Analysis of protein phosphorylation by hypothesis-driven multiple-stage mass spectrometry. Anal. Chem. 76, 4472–4483 (2004)

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  5. 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 

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

    Article  CAS  Google Scholar 

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

    Google Scholar 

  9. 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)

    Google Scholar 

  10. Spahr, C.S., Davis, M.T., McGinley, M.D., Robinson, J.H., Bures, E.J., Beierle, J., Mort, J., Courchesne, P.L., Chen, K., Wahl, R.C., Yu, W., Luethy, R., Patterson, S.D.: Towards defining the urinary proteome using liquid chromatography-tandem mass spectrometry. I. Profiling an unfractionated tryptic digest. Proteomics 1, 93–107 (2001)

    Google Scholar 

  11. 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 

  12. Chen, S., Panchaud, A., Goodlett, D., Shaffer, S.: Making a case for data-independent tandem mass spectrometry workflows. J. Biomol. Tech. 21, S52–S53 (2010)

    Google Scholar 

  13. Hengel, S.M., Murray, E., Langdon, S., Hayward, L., O’Donoghue, J., Panchaud, A., Hupp, T., Goodlett, D.R.: Data-independent proteomic screen identifies novel tamoxifen agonist that mediates drug resistance. J. Proteome Res. 10, 4567–4578 (2011)

    Google Scholar 

  14. Gillet, L.C., Navarro, P., Tate, S., Röst, 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. Proteom. 11, (2012)

  15. Scherl, A., Tsai, Y.S., Shaffer, S.A., Goodlett, D.R.: Increasing information from shotgun proteomic data by accounting for misassigned precursor ion masses. Proteomics 8, 2791–2797 (2008)

    Article  CAS  Google Scholar 

  16. Ahrné, E., Ohta, Y., Nikitin, F., Scherl, A., Lisacek, F., Müller, M.: An improved method for the construction of decoy peptide MS/MS spectra suitable for the accurate estimation of false discovery rates. Proteomics 11, 4085–4095 (2011)

    Article  Google Scholar 

  17. Bern, M., Finney, G., Hoopmann, M.R., Merrihew, G., Toth, M.J., MacCoss, M.J.: Deconvolution of mixture spectra from ion-trap data-independent-acquisition tandem mass spectrometry. Anal. Chem. 82, 833 (2010)

    Article  CAS  Google Scholar 

  18. Venable, J.D., Xu, T., Cociorva, D., Yates III, J.R.: Cross-correlation algorithm for calculation of peptide molecular weight from tandem mass spectra. Anal. Chem. 78, 1921–1929 (2006)

    Article  CAS  Google Scholar 

  19. Carvalho, P.C., Han, X., Xu, T., Cociorva, D.: da G. Carvalho M., Barbosa, V.C., Yates, J.R., 3rd: XDIA: improving on the label-free data-independent analysis. Bioinformatics 26, 847–848 (2010)

  20. Prim, R.: Shortest connection networks and some generalizations. Bell Syst. Technical J. 36, 1389–1401 (1957)

    Article  Google Scholar 

  21. Gluck, F., Hoogland, C., Antinori, P., Robin, X., Nikitin, F., Zufferey, A., et al.: EasyProt—an easy-to-use graphical platform for proteomics data analysis. J. Proteom. 79, 146–160 (2013)

    Article  CAS  Google Scholar 

  22. Colinge, J., Masselot, A., Giron, M., Dessingy, T., Magnin, J.: OLAV: towards high-throughput tandem mass spectrometry data identification. Proteomics 3, 1454–1463 (2003)

    Article  CAS  Google Scholar 

  23. Elias, J.E., Gygi, S.P.: Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat. Methods 4, 207–214 (2007)

    Article  CAS  Google Scholar 

  24. Frank, A.M., Bandeira, N., Shen, Z., Tanner, S., Brigg, S.P., Smith, R.D., Pevzner, P.A.: Clustering millions of tandem mass spectra. J. Proteome Res. 7, 113–122 (2008)

    Google Scholar 

Download references

Acknowledgment

The authors thank the Swiss National Science Foundation (SNSF), grant 315230_130830, for support of this work. The authors declare no conflict of interest.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Markus Muller.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(DOCX 905 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pak, H., Nikitin, F., Gluck, F. et al. Clustering and Filtering Tandem Mass Spectra Acquired in Data-Independent Mode. J. Am. Soc. Mass Spectrom. 24, 1862–1871 (2013). https://doi.org/10.1007/s13361-013-0720-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13361-013-0720-z

Keywords

Navigation