Cell-Based Identification of Natural Substrates and Cleavage Sites for Extracellular Proteases by SILAC Proteomics

  • Magda Gioia
  • Leonard J. Foster
  • Christopher M. OverallEmail author
Part of the Methods in Molecular Biology™ book series (MIMB, volume 539)


Proteolysis is one of the most important post-translational modifications of the proteome with every protein undergoing proteolysis during its synthesis and maturation and then upon inactivation and degradation. Extracellular proteolysis can either activate or inactivate bioactive molecules regulating physiological and pathological processes. Therefore, it is important to develop non-biased high-content screens capable of identifying the substrates for a specific protease. This characterization can also be useful for identifying the nodes of intersection between a protease and cellular pathways and so aid in the detection of drug targets. Classically, biochemical methods for protease substrate screening only discover what can be cleaved but this is often not what is actually cleaved in vivo. We suggest that biologically relevant protease substrates can be best found by analysis of proteolysis in a living cellular context, starting with a proteome that has never been exposed to the activity of the examined protease. Therefore, protease knockout cells form a convenient and powerful system for these screens.

We describe a method for identification and quantification of shed and secreted cleaved substrates in cell cultures utilizing the cell metabolism as a labelling system. SILAC (stable isotope labelling by amino acids) utilises metabolic incorporation of stable isotope-labelled amino acids into living cells. As a model system to develop this approach, we chose the well-characterised matrix metalloproteinase, MMP-2, because of its importance in tumour metastasis and a large database of MMP substrates with which to benchmark this new approach. However, the concepts can be applied to any extracellular or cell membrane protease. Generating differential metabolically labelled proteomes is one key to the approach; the other is the use of a negative peptide selection procedure to select for cleaved N-termini in the N-terminome. Using proteomes exposed or not to a particular protease enables biologically relevant substrates and their cleavage sites to be identified and quantified by tandem mass spectrometry proteomics and database searching.

Key words

Protease Proteinases Matrix metalloproteinase MMP Degradomics Proteomics SILAC Shedding Protease substrate identification Quantitative proteomics Tandem mass spectrometry 



Funding for this work was from the National Cancer Institute of Canada (NCIC) and the Canadian Institutes of Health Research (CIHR).


  1. 1.
    Guo, L., Eisenman, J.R., Mahimkar, R.M., Peschon, J.J., Paxton R.J., Black, R.A. and Johnson, R.S. (2002) A proteomic approach for the identification of cell-surface proteins shed by metalloproteases. Mol. Cell Proteomics 1, 30–36.PubMedCrossRefGoogle Scholar
  2. 2.
    Butler, G.S., Dean, R.A., Smith, D. and Overall, C.M. (2008) Membrane protease degradomics: proteomic identification and quantification of cell surface protease substrates. In: Peirce, M. and Wait, R. (eds.). Proteomic Analysis of Membrane Proteins: Methods and Protocols, Humana, Ottowa, NJ, in press.Google Scholar
  3. 3.
    Dean, R.A., Smith D. and Overall, C.M. (2007) Proteomic identification of cellular protease substrates using isobaric tags for relative and absolute quantification (iTRAQ) Curr Protocols Protein Sci. Supplement 49 21.18.1 21.18.12Google Scholar
  4. 4.
    Butler, G.S., Dean, R.A., Morrison, C.J. and Overall, C.M. (2008). Identification of cellular MMP substrates using quantitative proteomics: isotope-coded affinity tags (ICAT) and isobaric tags for relative and absolute quantification (iTRAQ). In: Clark, I. (ed.). Methods in Molecular Biology, Humana, Totowa, NJ, in press.Google Scholar
  5. 5.
    Ong, S.E., Blagoev, B., Kratchmarova, I., Kristensen, D.B., Steen, H., Pandey, A. and Mann, M. (2002) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell Proteomics 1(5), 376–386.PubMedCrossRefGoogle Scholar
  6. 6.
    Sternlicht, M.D. and Werb, Z. (2001) How matrix metalloproteinases regulate cell behavior. Annu. Rev. Cell Dev. Biol. 17, 463–516.PubMedCrossRefGoogle Scholar
  7. 7.
    Yamaguchi, M., Nakazawa, T., Kuyama, H., Obama, T., Ando, E., Okamura, T., Ueyama, N. and Norioka, S. (2005) High-throughput method for N-terminal sequencing of proteins by MALDI mass spectrometry. Anal. Chem. 77, 645–651.PubMedCrossRefGoogle Scholar
  8. 8.
    Chelius, D. and Shaler, T.A. (2003) Capture of peptides with N-terminal serine and threonine: a sequence-specific chemical method for peptide mixture simplification. Bioconjg. Chem. 14, 205–211.CrossRefGoogle Scholar
  9. 9.
    Gevaert, K., Van Damme, P., Martens, L. and Vandekerckhove, J. (2005) Diagonal reverse-phase chromatography applications in peptide-centric proteomics: ahead of catalogue-omics? Anal. Biochem. 345, 18–29.PubMedCrossRefGoogle Scholar
  10. 10.
    Akiyama, T.H., Sasagawa, T., Suzuki, M. and Titani, K. (1994) A method for selective isolation of the amino-terminal peptide from alpha-amino-blocked proteins. Anal. Biochem. 222, 210–216.PubMedCrossRefGoogle Scholar
  11. 11.
    Washburn, M.P., Wolters, D. and Yates, J.R., III (2001) Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nat. Biotechnol. 19, 242–247.PubMedCrossRefGoogle Scholar
  12. 12.
    Peng, J., Elias, J.E., Thoreen, C.C., Licklider, L.J. and Gygi, S.P. (2003) Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome. J. Proteome Res. 2, 43–50.PubMedCrossRefGoogle Scholar
  13. 13.
    Resing, K.A., Meyer-Arendt, K., Mendoza, A.M., Aveline-Wolf, L.D., Jonscher, K.R.; Pierce, K.G., Old, W.M., Cheung, H.T., Russell, S., Wattawa, J.L., Goehle, G.R., Knight, R.D. and Ahn, N.G. (2004) Improving reproducibility and sensitivity in identifying human proteins by shotgun proteomics. Anal. Chem. 76, 3556–3568.PubMedCrossRefGoogle Scholar
  14. 14.
    Link, A.J., Eng, J., Schieltz, D.M., Carmack, E., Mize, G.J., Morris, D.R., Garvik, B.M. and Yates, J.R., III (1999) Direct analysis of protein complexes using mass spectrometry. Nat. Biotechnol. 17, 676–682.PubMedCrossRefGoogle Scholar
  15. 15.
    Cargile, B.J., Talley, D.L. and Stephenson, J.L., Jr. (2004) Immobilized pH gradients as a first dimension in shotgun proteomics and analysis of the accuracy of pI predictability of peptides. Electrophoresis 25, 936–945.PubMedCrossRefGoogle Scholar
  16. 16.
    Ishihama, Y., Rappsilber, J. and Mann, M. (2006) Modular stop and go extraction tips with stacked disks for parallel and multidimensional peptide fractionation in proteomics. J. Proteome Res. 5, 988–994PubMedCrossRefGoogle Scholar
  17. 17.
    Carr, S., Aebersold, R., Baldwin, M., Burl-ingame, A., Clauser, K. and Nesvizhskii, A. (2004) The need for guidelines in publication of peptide and protein identification data: Working Group on Publication Guidelines for Peptide and Protein Identification Data. Mol. Cell. Proteomics 3, 531–533.PubMedCrossRefGoogle Scholar

Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Magda Gioia
  • Leonard J. Foster
  • Christopher M. Overall
    • 1
    Email author
  1. 1.Departments of Oral Biological and Medical Sciences and Biochemistry and Molecular Biology and the Centre for Blood Research, Life Sciences Institute, Room 4.401, 2350 Health Sciences MallUniversity of British ColumbiaVancouverCanada

Personalised recommendations