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.

  • Protocol
  • Published:

Measuring protein structural changes on a proteome-wide scale using limited proteolysis-coupled mass spectrometry

Nature Protocols volume 12, pages 2391–2410 (2017)Cite this article

Subjects

Abstract

Protein structural changes induced by external perturbations or internal cues can profoundly influence protein activity and thus modulate cellular physiology. A number of biophysical approaches are available to probe protein structural changes, but these are not applicable to a whole proteome in a biological extract. Limited proteolysis-coupled mass spectrometry (LiP-MS) is a recently developed proteomics approach that enables the identification of protein structural changes directly in their complex biological context on a proteome-wide scale. After perturbations of interest, proteome extracts are subjected to a double-protease digestion step with a nonspecific protease applied under native conditions, followed by complete digestion with the sequence-specific protease trypsin under denaturing conditions. This sequential treatment generates structure-specific peptides amenable to bottom-up MS analysis. Next, a proteomics workflow involving shotgun or targeted MS and label-free quantification is applied to measure structure-dependent proteolytic patterns directly in the proteome extract. Possible applications of LiP-MS include discovery of perturbation-induced protein structural alterations, identification of drug targets, detection of disease-associated protein structural states, and analysis of protein aggregates directly in biological samples. The approach also enables identification of the specific protein regions involved in the structural transition or affected by the binding event. Sample preparation takes approximately 2 d, followed by one to several days of MS and data analysis time, depending on the number of samples analyzed. Scientists with basic biochemistry training can implement the sample preparation steps. MS measurement and data analysis require a background in proteomics.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Experimental LiP-MS workflow.
Figure 2: Effect of different E/S ratios and choice of proteases.
Figure 3: Analysis of LiP-MS data.

Similar content being viewed by others

References

  1. Walther, T.C. & Mann, M. Mass spectrometry-based proteomics in cell biology. J. Cell Biol. 190, 491–500 (2010).

    Article  CAS  Google Scholar 

  2. Feng, Y. et al. Global analysis of protein structural changes in complex proteomes. Nat. Biotechnol. 32, 1036–1044 (2014).

    Article  CAS  Google Scholar 

  3. Leuenberger, P. et al. Cell-wide analysis of protein thermal unfolding reveals determinants of thermostability. Science 355, eaai7825 (2017).

    Article  Google Scholar 

  4. Stauffer, S. et al. Stepwise priming by acidic pH and a high K+ concentration is required for efficient uncoating of influenza A virus cores after penetration. J. Virol. 88, 13029–13046 (2014).

    Article  Google Scholar 

  5. Geiger, R. et al. L-arginine modulates T cell metabolism and enhances survival and anti-tumor activity. Cell 167, 829–842 (2016).

    Article  CAS  Google Scholar 

  6. Aceto, A. et al. Analysis by limited proteolysis of domain organization and GSH-site arrangement of bacterial glutathione transferase B1-1. Int. J. Biochem. Cell Biol. 27, 1033–1041 (1995).

    Article  CAS  Google Scholar 

  7. Dieckmann, R. et al. Probing the domain structure and ligand-induced conformational changes by limited proteolysis of tyrocidine synthetase 1. J. Mol. Biol. 288, 129–140 (1999).

    Article  CAS  Google Scholar 

  8. Nouwen, N. et al. Domain structure of secretin PulD revealed by limited proteolysis and electron microscopy. EMBO J. 19, 2229–2236 (2000).

    Article  CAS  Google Scholar 

  9. Pagnozzi, D. et al. Stoichiometry and topology of the complex of the endogenous ATP synthase inhibitor protein IF(1) with calmodulin. Biochemistry 49, 7542–7552 (2010).

    Article  CAS  Google Scholar 

  10. Peng, Z.Y. & Kim, P.S. A protein dissection study of a molten globule. Biochemistry 33, 2136–2141 (1994).

    Article  CAS  Google Scholar 

  11. Polverino de Laureto, P. et al. Protein aggregation and amyloid fibril formation by an SH3 domain probed by limited proteolysis. J. Mol. Biol. 334, 129–141 (2003).

    Article  CAS  Google Scholar 

  12. Eftink, M.R. Fluorescence techniques for studying protein structure. Methods Biochem. Anal. 35, 127–205 (1991).

    CAS  PubMed  Google Scholar 

  13. Ilari, A. & Savino, C. Protein structure determination by x-ray crystallography. Methods Mol. Biol. 452, 63–87 (2008).

    Article  CAS  Google Scholar 

  14. Pelton, J.T. & McLean, L.R. Spectroscopic methods for analysis of protein secondary structure. Anal. Biochem. 277, 167–176 (2000).

    Article  CAS  Google Scholar 

  15. Konermann, L., Pan, J. & Liu, Y.H. Hydrogen exchange mass spectrometry for studying protein structure and dynamics. Chem. Soc. Rev. 40, 1224–1234 (2011).

    Article  CAS  Google Scholar 

  16. Heyduk, T. Measuring protein conformational changes by FRET/LRET. Curr. Opin. Biotechnol. 13, 292–296 (2002).

    Article  CAS  Google Scholar 

  17. Sakakibara, D. et al. Protein structure determination in living cells by in-cell NMR spectroscopy. Nature 458, 102–105 (2009).

    Article  CAS  Google Scholar 

  18. Herzog, F. et al. Structural probing of a protein phosphatase 2A network by chemical cross-linking and mass spectrometry. Science 337, 1348–1352 (2012).

    Article  CAS  Google Scholar 

  19. Roeser, J. et al. Oxidative protein labeling in mass-spectrometry-based proteomics. Anal. Bioanal. Chem. 397, 3441–3455 (2010).

    Article  CAS  Google Scholar 

  20. Mendoza, V.L. & Vachet, R.W. Probing protein structure by amino acid-specific covalent labeling and mass spectrometry. Mass Spectrom. Rev. 28, 785–815 (2009).

    Article  CAS  Google Scholar 

  21. Picotti, P. & Aebersold, R. Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions. Nat. Methods 9, 555–566 (2012).

    Article  CAS  Google Scholar 

  22. Liu, F. et al. Proteome-wide profiling of protein assemblies by cross-linking mass spectrometry. Nat. Methods 12, 1179–1184 (2015).

    Article  CAS  Google Scholar 

  23. Kosinski, J. et al. Molecular architecture of the inner ring scaffold of the human nuclear pore complex. Science 352, 363–365 (2016).

    Article  CAS  Google Scholar 

  24. Leitner, A., Walzthoeni, T. & Aebersold, R. Lysine-specific chemical cross-linking of protein complexes and identification of cross-linking sites using LC-MS/MS and the xQuest/xProphet software pipeline. Nat. Protoc. 9, 120–137 (2014).

    Article  CAS  Google Scholar 

  25. Savitski, M.M. et al. Tracking cancer drugs in living cells by thermal profiling of the proteome. Science 346, 1255784 (2014).

    Article  Google Scholar 

  26. Fontana, A. et al. Probing protein structure by limited proteolysis. Acta Biochim. Pol. 51, 299–321 (2004).

    CAS  PubMed  Google Scholar 

  27. Monti, M. & Pucci, P. Limited proteolysis mass spectrometry of protein complexes. Mass Spectrometry of Protein Interactions (ed. Downard, K.) Ch. 4 (Wiley, 2007).

  28. Polverino de Laureto, P. et al. Probing the structure of human growth hormone by limited proteolysis. Int. J. Pept. Protein Res. 45, 200–208 (1995).

    Article  CAS  Google Scholar 

  29. Picotti, P. et al. Modulation of the structural integrity of helix F in apomyoglobin by single amino acid replacements. Protein Sci. 13, 1572–1585 (2004).

    Article  CAS  Google Scholar 

  30. Glatter, T. et al. Large-scale quantitative assessment of different in-solution protein digestion protocols reveals superior cleavage efficiency of tandem Lys-C/trypsin proteolysis over trypsin digestion. J. Proteome Res. 11, 5145–5156 (2012).

    Article  CAS  Google Scholar 

  31. Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).

    Article  CAS  Google Scholar 

  32. Rost, H.L. et al. OpenMS: a flexible open-source software platform for mass spectrometry data analysis. Nat. Methods 13, 741–748 (2016).

    Article  CAS  Google Scholar 

  33. Perez-Riverol, Y. et al. Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective. Biochim. Biophys. Acta 1844, 63–76 (2014).

    Article  CAS  Google Scholar 

  34. Feng, Y. & Picotti, P. Selected reaction monitoring to measure proteins of interest in complex samples: a practical guide. Methods Mol. Biol. 1394, 43–56 (2016).

    Article  CAS  Google Scholar 

  35. MacLean, B. et al. Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26, 966–968 (2010).

    Article  CAS  Google Scholar 

  36. Choi, M. et al. MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments. Bioinformatics 30, 2524–2526 (2014).

    Article  CAS  Google Scholar 

  37. Moulder, R., Goo, Y.A. & Goodlett, D.R. Label-free quantitation for clinical proteomics. Methods Mol. Biol. 1410, 65–76 (2016).

    Article  CAS  Google Scholar 

  38. Richards, A.L. et al. One-hour proteome analysis in yeast. Nat. Protoc. 10, 701–714 (2015).

    Article  CAS  Google Scholar 

  39. Surinova, S. et al. Automated selected reaction monitoring data analysis workflow for large-scale targeted proteomic studies. Nat. Protoc. 8, 1602–1619 (2013).

    Article  Google Scholar 

  40. Wyss, M. et al. Limited proteolysis of creatine kinase. Implications for three-dimensional structure and for conformational substrates. Biochemistry 32, 10727–10735 (1993).

    Article  CAS  Google Scholar 

  41. Vita, C., Dalzoppo, D. & Fontana, A. Limited proteolysis of thermolysin by subtilisin: isolation and characterization of a partially active enzyme derivative. Biochemistry 24, 1798–1806 (1985).

    Article  CAS  Google Scholar 

  42. Martini, F. et al. Investigation of intra-domain and inter-domain interactions of glutathione transferase P1-1 by limited chymotryptic cleavage. Eur. J. Biochem. 218, 845–851 (1993).

    Article  CAS  Google Scholar 

  43. Hatori, Y. et al. Domain organization and movements in heavy metal ion pumps: papain digestion of CopA, a Cu+-transporting ATPase. J. Biol. Chem. 282, 25213–25221 (2007).

    Article  CAS  Google Scholar 

  44. Griese, M. et al. Limited proteolysis of surfactant protein D causes a loss of its calcium-dependent lectin functions. Biochim. Biophys. Acta 1638, 157–163 (2003).

    Article  CAS  Google Scholar 

  45. Scolaro, L.A., Mersich, S.E. & Damonte, E.B. A mouse attenuated mutant of Junin virus with an altered envelope glycoprotein. Arch. Virol. 111, 257–362 (1990).

    Article  CAS  Google Scholar 

  46. Kordyukova, L.V. et al. Influenza A virus M1 protein structure probed by in situ limited proteolysis with bromelain. Protein Pept. Lett. 15, 922–930 (2008).

    Article  CAS  Google Scholar 

  47. Polverino de Laureto, P. et al. Limited proteolysis of bovine alpha-lactalbumin: isolation and characterization of protein domains. Protein Sci. 8, 2290–2303 (1999).

    Article  CAS  Google Scholar 

  48. Kim, J. et al. Characterization of a unique IgG1 mAb CEX profile by limited Lys-C proteolysis/CEX separation coupled with mass spectrometry and structural analysis. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 878, 1973–1981 (2010).

    Article  CAS  Google Scholar 

  49. Laganowsky, A. et al. Mass spectrometry of intact membrane protein complexes. Nat. Protoc. 8, 639–651 (2013).

    Article  CAS  Google Scholar 

  50. Becher, I. et al. Chemoproteomics reveals time-dependent binding of histone deacetylase inhibitors to endogenous repressor complexes. ACS Chem. Biol. 9, 1736–1746 (2014).

    Article  CAS  Google Scholar 

  51. Cadene, M. & Chait, B.T. A robust, detergent-friendly method for mass spectrometric analysis of integral membrane proteins. Anal. Chem. 72, 5655–5658 (2000).

    Article  CAS  Google Scholar 

  52. Proc, J.L. et al. A quantitative study of the effects of chaotropic agents, surfactants, and solvents on the digestion efficiency of human plasma proteins by trypsin. J. Proteome Res. 9, 5422–5437 (2010).

    Article  CAS  Google Scholar 

  53. Stark, G.R., Stein, W.H. & Moore, S. Reactions of the cyanate present in aqueous urea with amino acids and proteins. J. Biol. Chem. 235, 3177–3181 (1960).

    CAS  Google Scholar 

  54. Kang, S.C. et al. Guanidine hydrochloride extraction and detection of prion proteins in mouse and hamster prion diseases by ELISA. J. Pathol. 199, 534–541 (2003).

    Article  CAS  Google Scholar 

  55. Barron, R.M. et al. High titers of transmissible spongiform encephalopathy infectivity associated with extremely low levels of PrPSc in vivo. J. Biol. Chem. 282, 35878–35886 (2007).

    Article  CAS  Google Scholar 

  56. Meyer, R.K. et al. Detection of bovine spongiform encephalopathy-specific PrP(Sc) by treatment with heat and guanidine thiocyanate. J. Virol. 73, 9386–9392 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Ren, D. et al. An improved trypsin digestion method minimizes digestion-induced modifications on proteins. Anal. Biochem. 392, 12–21 (2009).

    Article  CAS  Google Scholar 

  58. Rashid, F., Sharma, S. & Bano, B. Comparison of guanidine hydrochloride (GdnHCl) and urea denaturation on inactivation and unfolding of human placental cystatin (HPC). Protein J. 24, 283–292 (2005).

    Article  CAS  Google Scholar 

  59. 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 

  60. Biniossek, M.L. & Schilling, O. Enhanced identification of peptides lacking basic residues by LC-ESI-MS/MS analysis of singly charged peptides. Proteomics 12, 1303–1309 (2012).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

ACKNOWLEDGMENTS

We thank O. Schubert (UCLA) for insightful discussions. We also thank T. Lehmann for building the device to hold the sample tubes in the water bath and G. de Franceschi for contributing to the setup of the original LiP-MS protocol. P.P. is supported by an EU FP7-ERC Starting Grant (FP7-ERC-StG-337965), a 'Foerderungsprofessur' grant from the Swiss National Science Foundation (grant PP00P3_133670), and Promedica Stiftung (grant 2-70669-11). Y.F. is supported by an ETH Research Grant (grant no. 4412-1); I.P. is supported by an EMBO long-term fellowship (EMBO ALTF2014); and A.K. acknowledges SystemsX.ch for funding.

Author information

Author notes

  1. Simone Schopper & Yuehan Feng

    Present address: Present addresses: Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark (S.S.); Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA (Y.F.).,

Authors and Affiliations

  1. Department of Biology, Institute of Biochemistry, ETH Zurich, Zurich, Switzerland

    Simone Schopper, Pascal Leuenberger, Yuehan Feng, Ilaria Piazza, Oliver Müller, Paul J Boersema & Paola Picotti

  2. Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland

    Abdullah Kahraman

Authors
  1. Simone Schopper
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Abdullah Kahraman
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pascal Leuenberger
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuehan Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ilaria Piazza
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Oliver Müller
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Paul J Boersema
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Paola Picotti
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.S., A.K. and P.P. wrote the paper. Y.F. developed and optimized the original version of the protocol. S.S., P.L., O.M. and I.P. contributed to protocol optimization. I.P. and P.L. generated figures. P.J.B. contributed to editing of the manuscript and setup of the MS pipeline. A.K. developed and optimized algorithms and tools for protein structural analyses and prepared the user guide. P.P. supervised the project.

Corresponding author

Correspondence to Paola Picotti.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Effect of different chaotropes.

(A-D) Protein extracts from S. cerevisiae cells were subjected to the LiP-MS protocol with PK. LiP was conducted for one minute at a E/S of 1/100. After the LiP step, sodium deoxycholate (DOC) or urea were added to denature protein fragments (see conditions in Box 1) and complete digestion was obtained by the sequential addition of Lys-C and trypsin. The resulting peptides from LiP-treated and control samples were analyzed by LC-MS/MS. (A) The total number of proteins and (B) peptides, (C) the percent of missed-cleavage (MC) and (D) of half-tryptic (HT) peptides out of the total number of peptides identified are reported for the different treatments.

Supplementary Figure 2 Effect of protease incubation times in the LiP step.

(A-D) Protein extracts from S. cerevisiae cells were subjected to the LiP-MS protocol with PK. LiP was conducted at an E/S of 1/100, using different incubation times as indicated. After the LiP step, sodium deoxycholate (DOC) was added to denature protein fragments as indicated in the protocol and complete digestion was obtained by the sequential addition of Lys-C and trypsin. The resulting peptides from LiP-treated and control samples were analyzed by LC-MS/MS. (A) The total number of proteins and (B) peptides, (C) the percent of missed-cleavage (MC) and (D) of half-tryptic (HT) peptides out of the total number of peptides identified are reported for the different treatments.

Supplementary Figure 3 Devices to stabilize sample tubes in a boiling water bath.

Crucial to the proper quenching of PK is obtaining consistent and maximal heat throughout the water bath. We recommend using a metallic water bath for optimal heat transfer. To hold sample tubes inside the water bath, we recommend using a homebuilt device such as the one shown in (A). Alternatively, floating racks such as the ones shown in B) can be used. Depending on their material, floating racks such as those shown in (B) may deteriorate with heat. We recommend measuring the temperature of the boiling water bath and ensuring that it is above 95°C to achieve complete inactivation of PK after the first proteolysis step. Water levels should be sufficient to submerge sample tubes above the sample level, but floating of tubes should be avoided. Note that the water level in the water bath will decrease over prolonged use with serial quenching of multiple samples or sample batches.

Supplementary Figure 4 Examples of data visualization at the protein and pathway level.

(A) Three-dimensional structure of horse myoglobin (Protein Data Bank entry 2frf) shown in a grey cartoon representation, which highlights its mainly alpha-helical secondary structure. Protein regions for which LiP peptides were identified after LiP of a sample containing apomyoglobin are displayed in yellow, while half-tryptic peptide ends are coloured in red. The bound heme molecule is represented as a multicolored ball and stick model. Note the two half-tryptic peptide ends embedded in the helix F next to the heme molecule. The two half-tryptic peptides are increasing in abundance or become detectable in samples containing apomyoglobin, relative to samples containing holomyoglobin, since in apomyoglobin the F helix is replaced by a locally unfolded segment, easily cleaved by PK (see also Feng et al., 2014). (B) LiP-MS analysis of core carbon metabolism upon a shift from glycolytic to gluconeogenic growth, adapted from Feng et al., 2014. A schematic representation of core carbon metabolism in S. cerevisiae, comprising the glycolytic pathway, the TCA and glyoxylate cycles, and the ethanol production branch is shown. Proteins are colored according to the results of LiP-MS and protein abundance measurements by LC-MS. Abundance changes are differences between levels in gluconeogenic relative to glycolytic growth. Only significant abundance changes are reported. Protein abundance changes were determined based on measurements conducted on the trypsin control sample. Changes in the LiP pattern were calculated from data obtained on the LiP-treated sample and after normalization for protein abundance changes. Reproduced with permission from Feng et al., Global analysis of protein structural changes in complex proteomes. Nat. Biotechnol. 32, 1036–1044 (2014), Nature Publishing Group.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–4. (PDF 597 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schopper, S., Kahraman, A., Leuenberger, P. et al. Measuring protein structural changes on a proteome-wide scale using limited proteolysis-coupled mass spectrometry. Nat Protoc 12, 2391–2410 (2017). https://doi.org/10.1038/nprot.2017.100

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nprot.2017.100

This article is cited by

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

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research