Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Mapping intact protein isoforms in discovery mode using top-down proteomics

This article has been updated

Abstract

A full description of the human proteome relies on the challenging task of detecting mature and changing forms of protein molecules in the body. Large-scale proteome analysis1 has routinely involved digesting intact proteins followed by inferred protein identification using mass spectrometry2. This ‘bottom-up’ process affords a high number of identifications (not always unique to a single gene). However, complications arise from incomplete or ambiguous2 characterization of alternative splice forms, diverse modifications (for example, acetylation and methylation) and endogenous protein cleavages, especially when combinations of these create complex patterns of intact protein isoforms and species3. ‘Top-down’ interrogation of whole proteins can overcome these problems for individual proteins4,5, but has not been achieved on a proteome scale owing to the lack of intact protein fractionation methods that are well integrated with tandem mass spectrometry. Here we show, using a new four-dimensional separation system, identification of 1,043 gene products from human cells that are dispersed into more than 3,000 protein species created by post-translational modification (PTM), RNA splicing and proteolysis. The overall system produced greater than 20-fold increases in both separation power and proteome coverage, enabling the identification of proteins up to 105 kDa and those with up to 11 transmembrane helices. Many previously undetected isoforms of endogenous human proteins were mapped, including changes in multiply modified species in response to accelerated cellular ageing (senescence) induced by DNA damage. Integrated with the latest version of the Swiss-Prot database6, the data provide precise correlations to individual genes and proof-of-concept for large-scale interrogation of whole protein molecules. The technology promises to improve the link between proteomics data and complex phenotypes in basic biology and disease research7.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: The four-dimensional platform for high-resolution fractionation of protein molecules.
Figure 2: Two visual representations of proteome-scale runs.
Figure 3: Proteome analysis metrics associated with this study.
Figure 4: Monitoring dynamics of HMGA1 isoforms during senescence in B16F10 and H1299 cells.

Change history

  • 07 December 2011

    Acknowledgements were corrected.

References

  1. 1

    Wisniewski, J. R., Zougman, A., Nagaraj, N. & Mann, M. Universal sample preparation method for proteome analysis. Nature Methods 6, 359–362 (2009)

    CAS  Article  Google Scholar 

  2. 2

    Nesvizhskii, A. I. & Aebersold, R. Interpretation of shotgun proteomic data: the protein inference problem. Mol. Cell. Proteomics 4, 1419–1440 (2005)

    CAS  Article  Google Scholar 

  3. 3

    Schluter, H., Apweiler, R., Holzhutter, H. G. & Jungblut, P. R. Finding one’s way in proteomics: a protein species nomenclature. Chem. Cent. J. 3, 11 (2009)

    Article  Google Scholar 

  4. 4

    Boyne, M. T., Pesavento, J. J., Mizzen, C. A. & Kelleher, N. L. Precise characterization of human histories in the H2A gene family by top down mass spectrometry. J. Proteome Res. 5, 248–253 (2006)

    CAS  Article  Google Scholar 

  5. 5

    Ge, Y., Rybakova, I. N., Xu, Q. G. & Moss, R. L. Top-down high-resolution mass spectrometry of cardiac myosin binding protein C revealed that truncation alters protein phosphorylation state. Proc. Natl Acad. Sci. USA 106, 12658–12663 (2009)

    CAS  ADS  Article  Google Scholar 

  6. 6

    Nilsson, T. et al. Mass spectrometry in high-throughput proteomics: ready for the big time. Nature Methods 7, 681–685 (2010)

    CAS  Article  Google Scholar 

  7. 7

    Mazur, M. T. et al. Quantitative analysis of intact apolipoproteins in human HDL by top-down differential mass spectrometry. Proc. Natl Acad. Sci. USA 107, 7728–7733 (2010)

    CAS  ADS  Article  Google Scholar 

  8. 8

    Righetti, P. G., Castagna, A., Antonioli, P. & Boschetti, E. Prefractionation techniques in proteome analysis: the mining tools of the third millennium. Electrophoresis 26, 297–319 (2005)

    CAS  Article  Google Scholar 

  9. 9

    Wang, H. et al. Intact-protein-based high-resolution three-dimensional quantitative analysis system for proteome profiling of biological fluids. Mol. Cell. Proteomics 4, 618–625 (2005)

    CAS  Article  Google Scholar 

  10. 10

    Capriotti, A. L., Cavaliere, C., Foglia, P., Samperi, R. & Laganà, A. Intact protein separation by chromatographic and/or electrophoretic techniques for top-down proteomics. J. Chromatogr. A (in the press)

  11. 11

    Gygi, S. P., Corthals, G. L., Zhang, Y., Rochon, Y. & Aebersold, R. Evaluation of two-dimensional gel electrophoresis-based proteome analysis technology. Proc. Natl Acad. Sci. USA 97, 9390–9395 (2000)

    CAS  ADS  Article  Google Scholar 

  12. 12

    Tran, J. C. & Doucette, A. A. Multiplexed size separation of intact proteins in solution phase for mass spectrometry. Anal. Chem. 81, 6201–6209 (2009)

    CAS  Article  Google Scholar 

  13. 13

    Tran, J. C. & Doucette, A. A. Gel-eluted liquid fraction entrapment electrophoresis: an electrophoretic method for broad molecular weight range proteome separation. Anal. Chem. 80, 1568–1573 (2008)

    CAS  Article  Google Scholar 

  14. 14

    Lee, J. E. et al. A robust two-dimensional separation for top-down tandem mass spectrometry of the low-mass proteome. J. Am. Soc. Mass Spectrom. 20, 2183–2191 (2009)

    CAS  Article  Google Scholar 

  15. 15

    Vellaichamy, A. et al. Size-sorting combined with improved nanocapillary liquid chromatography-mass spectrometry for identification of intact proteins up to 80 kDa. Anal. Chem. 82, 1234–1244 (2010)

    CAS  Article  Google Scholar 

  16. 16

    Roth, M. J. et al. Precise and parallel characterization of coding polymorphisms, alternative splicing, and modifications in human proteins by mass spectrometry. Mol. Cell. Proteomics 4, 1002–1008 (2005)

    CAS  Article  Google Scholar 

  17. 17

    Durbin, K. R. et al. Intact mass detection, interpretation, and visualization to automate top down proteomics on a large scale. Proteomics 10, 3589–3597 (2010)

    CAS  Article  Google Scholar 

  18. 18

    Duncan, M. W., Aebersold, R. & Caprioli, R. M. The pros and cons of peptide-centric proteomics. Nature Biotechnol. 28, 659–664 (2010)

    CAS  Article  Google Scholar 

  19. 19

    Bunger, M. K., Cargile, B. J., Ngunjiri, A., Bundy, J. L. & Stephenson, J. L. J. Automated proteomics of E. coli via top-down electron-transfer dissociation mass spectrometry. Anal. Chem. 80, 1459–1467 (2008)

    CAS  Article  Google Scholar 

  20. 20

    Parks, B. A. et al. Top-down proteomics on a chromatographic time scale using linear ion trap fourier transform hybrid mass spectrometers. Anal. Chem. 79, 7984–7991 (2007)

    CAS  Article  Google Scholar 

  21. 21

    Patrie, S. M. et al. Top down mass spectrometry of 60-kDa proteins from Methanosarcina acetivorans using quadrupole FTMS with automated octopole collisionally activated dissociation. Mol. Cell. Proteomics 5, 14–25 (2006)

    CAS  Article  Google Scholar 

  22. 22

    Roth, M. J., Parks, B. A., Ferguson, J. T., Boyne, M. T. I. & Kelleher, N. L. ‘Proteotyping’: Population proteomics of human leukocytes using top down mass spectrometry. Anal. Chem. 80, 2857–2866 (2008)

    CAS  Article  Google Scholar 

  23. 23

    Gomez, S. M., Nishio, J. N., Faull, K. F. & Whitelegge, J. P. The chloroplast grana proteome defined by intact mass measurements from liquid chromatography mass spectrometry. Mol. Cell. Proteomics 1, 46–59 (2002)

    CAS  Article  Google Scholar 

  24. 24

    Matsuoka, S. et al. ATM and ATR substrate analysis reveals extensive protein networks responsive to DNA damage. Science 316, 1160–1166 (2007)

    CAS  ADS  Article  Google Scholar 

  25. 25

    Roberson, R. S., Kussick, S. J., Vallieres, E., Chen, S. Y. & Wu, D. Y. Escape from therapy-induced accelerated cellular senescence in p53-null lung cancer cells and in human lung cancers. Cancer Res. 65, 2795–2803 (2005)

    CAS  Article  Google Scholar 

  26. 26

    Yawata, T. et al. Identification of a 600-kb region on human chromosome 1q42.3 inducing cellular senescence. Oncogene 22, 281–290 (2003)

    CAS  Article  Google Scholar 

  27. 27

    Sgarra, R. et al. During apoptosis of tumor cells HMGA1a protein undergoes methylation: identification of the modification site by mass spectrometry. Biochemistry 42, 3575–3585 (2003)

    CAS  Article  Google Scholar 

  28. 28

    Sgarra, R. et al. The AT-hook of the chromatin architectural transcription factor high mobility group A1a is arginine-methylated by protein arginine methyltransferase 6. J. Biol. Chem. 281, 3764–3772 (2006)

    CAS  Article  Google Scholar 

  29. 29

    Narita, M. et al. A novel role for high-mobility group A proteins in cellular senescence and heterochromatin formation. Cell 126, 503–514 (2006)

    CAS  Article  Google Scholar 

  30. 30

    Service, R. F. Proteomics ponders prime time. Science 321, 1758–1761 (2008)

    CAS  Article  Google Scholar 

  31. 31

    Soubeyrand, S., Pope, L. & Hache, R. J. G. Topoisomerase II α-dependent induction of a persistent DNA damage response in response to transient etoposide exposure. Mol. Oncol. 4, 38–51 (2010)

    CAS  Article  Google Scholar 

  32. 32

    Serrano, M., Lin, A. W., McCurrach, M. E., Beach, D. & Lowe, S. W. Oncogenic ras provokes premature cell senescence associated with accumulation of p53 and p16(INK4a). Cell 88, 593–602 (1997)

    CAS  Article  Google Scholar 

  33. 33

    Trinkle-Mulcahy, L. et al. Identifying specific protein interaction partners using quantitative mass spectrometry and bead proteomes. J. Cell Biol. 183, 223–239 (2008)

    CAS  Article  Google Scholar 

  34. 34

    Tran, J. C. & Doucette, A. A. Rapid and effective focusing in a carrier ampholyte solution isoelectric focusing system: a proteome prefractionation tool. J. Proteome Res. 7, 1761–1766 (2008)

    CAS  Article  Google Scholar 

  35. 35

    Laemmli, U. K. Cleavage of structural proteins during the assembly of the head of Bacteriopage T4. Nature 227, 680–685 (1970)

    CAS  ADS  Article  Google Scholar 

  36. 36

    Wessel, D. & Flugge, U. I. A Method for the Quantitative recovery of protein in dilute solution in the presence of detergents and lipids. Anal. Biochem. 138, 141–143 (1984)

    CAS  Article  Google Scholar 

  37. 37

    Cox, B. & Emili, A. Tissue subcellular fractionation and protein extraction for use in mass-spectrometry-based proteomics. Nature Protocols 1, 1872–1878 (2006)

    CAS  Article  Google Scholar 

  38. 38

    Horn, D. M., Zubarev, R. A. & McLafferty, F. W. Automated reduction and interpretation of high resolution electrospray mass spectra of large molecules. J. Am. Soc. Mass Spectrom. 11, 320–332 (2000)

    CAS  Article  Google Scholar 

  39. 39

    Boyne, M. T. et al. Tandem mass spectrometry with ultrahigh mass accuracy clarifies peptide identification by database retrieval. J. Proteome Res. 8, 374–379 (2009)

    CAS  Article  Google Scholar 

  40. 40

    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)

    CAS  Article  Google Scholar 

  41. 41

    Zamdborg, L. et al. ProSight PTM 2.0: improved protein identification and characterization for top down mass spectrometry. Nucleic Acids Res. 35, W701–W706 (2007)

    Article  Google Scholar 

  42. 42

    Papadopoulos, P. M., Katz, M. J. & Bruno, G. in Proc. 3rd IEEE Int. Conf.. Cluster Computing 258 〈http://www.computer.org/portal/web/csdl/doi/10.1109/CLUSTR.2001.959986〉 (2001)

  43. 43

    Meng, F. Y. et al. Informatics and multiplexing of intact protein identification in bacteria and the archaea. Nature Biotechnol. 19, 952–957 (2001)

    CAS  Article  Google Scholar 

  44. 44

    Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate – a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995)

    MathSciNet  MATH  Google Scholar 

  45. 45

    Storey, J. D. & Tibshirani, R. Statistical significance for genomewide studies. Proc. Natl Acad. Sci. USA 100, 9440–9445 (2003)

    CAS  ADS  MathSciNet  Article  Google Scholar 

  46. 46

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

    CAS  Article  Google Scholar 

  47. 47

    Reiter, L. et al. Protein identification false discovery rates for very large proteomics data sets generated by tandem mass spectrometry. Mol. Cell. Proteomics 8, 2405–2417 (2009)

    CAS  Article  Google Scholar 

Download references

Acknowledgements

We thank all members of the group who contributed to development of top-down mass spectrometry over the years along with several private foundations: The Searle Scholars Program, The Burroughs Wellcome Fund, The David and Lucile Packard Foundation, The Richard and Camille Dreyfus Foundation, and The Chicago Biomedical Consortium with support from The Searle Funds at The Chicago Community Trust. We further acknowledge the Department of Chemistry at the University of Illinois, the Neuroproteomics Center on Cell to Cell Signaling supported through the National Institute on Drug Abuse (P30DA 018310), the National Institute for General Medical Sciences (GM 067193-08) and the National Science Foundation (DMS 0800631), whose combined investment in basic research over the past decade made this work possible. We dedicate this work in memory of Jonathan Widom.

Author information

Affiliations

Authors

Contributions

Project design: J.C.T., L.Z., P.M.T., N.L.K. Cell culture and biology: J.C.T., J.E.L., A.D.C., D.R.A., M.L., C.W., S.M.M.S., N.S. Separations: J.C.T., J.E.L., A.D.C., D.R.A. Mass spectrometry: J.C.T., J.E.L., A.D.C., D.R.A., J.D.T., A.V., J.F.K., P.D.C. Data analysis and statistics: J.C.T., L.Z., K.R.D., B.P.E., R.D.L., P.M.T., N.L.K. Writing: J.C.T., N.L.K.

Corresponding author

Correspondence to Neil L. Kelleher.

Ethics declarations

Competing interests

Some components of the separations and software (ProSight) are available commercially.

Supplementary information

Supplementary Information

The file contains Supplementary Text, Supplementary References and Supplementary Figures 1-14 with legends. (PDF 1536 kb)

Supplementary Tables

This file contains Supplementary Tables 1-8 with detailed reports on protein identifications. (XLS 1653 kb)

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Tran, J., Zamdborg, L., Ahlf, D. et al. Mapping intact protein isoforms in discovery mode using top-down proteomics. Nature 480, 254–258 (2011). https://doi.org/10.1038/nature10575

Download citation

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links