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Identifying and quantifying proteolytic events and the natural N terminome by terminal amine isotopic labeling of substrates

Nature Protocols volume 6, pages 15781611 (2011) | Download Citation

Abstract

Analysis of the sequence and nature of protein N termini has many applications. Defining the termini of proteins for proteome annotation in the Human Proteome Project is of increasing importance. Terminomics analysis of protease cleavage sites in degradomics for substrate discovery is a key new application. Here we describe the step-by-step procedures for performing terminal amine isotopic labeling of substrates (TAILS), a 2- to 3-d (depending on method of labeling) high-throughput method to identify and distinguish protease-generated neo–N termini from mature protein N termini with all natural modifications with high confidence. TAILS uses negative selection to enrich for all N-terminal peptides and uses primary amine labeling-based quantification as the discriminating factor. Labeling is versatile and suited to many applications, including biochemical and cell culture analyses in vitro; in vivo analyses using tissue samples from animal and human sources can also be readily performed. At the protein level, N-terminal and lysine amines are blocked by dimethylation (formaldehyde/sodium cyanoborohydride) and isotopically labeled by incorporating heavy and light dimethylation reagents or stable isotope labeling with amino acids in cell culture labels. Alternatively, easy multiplex sample analysis can be achieved using amine blocking and labeling with isobaric tags for relative and absolute quantification, also known as iTRAQ. After tryptic digestion, N-terminal peptide separation is achieved using a high-molecular-weight dendritic polyglycerol aldehyde polymer that binds internal tryptic and C-terminal peptides that now have N-terminal alpha amines. The unbound naturally blocked (acetylation, cyclization, methylation and so on) or labeled mature N-terminal and neo-N-terminal peptides are recovered by ultrafiltration and analyzed by tandem mass spectrometry (MS/MS). Hierarchical substrate winnowing discriminates substrates from the background proteolysis products and non-cleaved proteins by peptide isotope quantification and bioinformatics search criteria.

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References

  1. 1.

    et al. Isotopic labeling of terminal amines in complex samples identifies protein N termini and protease cleavage products. Nat. Biotechnol. 28, 281–288 (2010).

  2. 2.

    , , & System-wide proteomic identification of protease cleavage products by terminal amine isotopic labeling of substrates. Protoc. Exchange published online, doi:10.1038/nprot.2010.30 (2010).

  3. 3.

    , , & Multiplex N terminome analysis of MMP-2 and MMP-9 substrate degradomes by iTRAQ-TAILS quantitative proteomics. Mol. Cell. Proteomics 9, 894–911 (2010).

  4. 4.

    , , , & A statistics-based platform for quantitative N terminome analysis and identification of protease cleavage products. Mol. Cell. Proteomics 9, 912–927 (2010).

  5. 5.

    & The surprising complexity of signal sequences. Trends Biochem. Sci. 31, 563–571 (2006).

  6. 6.

    et al. Inflammation dampened by gelatinase A cleavage of monocyte chemoattractant protein-3. Science 289, 1202–1206 (2000).

  7. 7.

    & Strategies for MMP inhibition in cancer: innovations for the post-trial era. Nat. Rev. Cancer 2, 657–672 (2002).

  8. 8.

    et al. Proteolytic processing of SDF-1alpha reveals a change in receptor specificity mediating HIV-associated neurodegeneration. Proc. Natl. Acad. Sci. USA 103, 19182–19187 (2006).

  9. 9.

    Molecular determinants of metalloproteinase substrate specificity: matrix metalloproteinase substrate binding domains, modules, and exosites. Mol. Biotechnol. 22, 51–86 (2002).

  10. 10.

    , & Impact of the N-terminal amino acid on targeted protein degradation. Biol. Chem. 387, 839–851 (2006).

  11. 11.

    et al. Exploring proteomes and analyzing protein processing by mass spectrometric identification of sorted N-terminal peptides. Nat. Biotechnol. 21, 566–569 (2003).

  12. 12.

    , , & Positional proteomics: selective recovery and analysis of N-terminal proteolytic peptides. Nat. Methods 2, 955–957 (2005).

  13. 13.

    et al. Isolation of N-terminal protein sequence tags from cyanogen bromide cleaved proteins as a novel approach to investigate hydrophobic proteins. J. Proteome Res. 2, 598–609 (2003).

  14. 14.

    & Positional proteomics: preparation of amino-terminal peptides as a strategy for proteome simplification and characterization. Nat. Protoc. 1, 1790–1798 (2006).

  15. 15.

    et al. Global sequencing of proteolytic cleavage sites in apoptosis by specific labeling of protein N termini. Cell 134, 866–876 (2008).

  16. 16.

    , & Protein alpha-n-acetylation studied by N-terminomics. FEBS J. published online, doi:10.1111/j.1742-4658.2011.08230.x. (7 July 2011).

  17. 17.

    & In search of partners: linking extracellular proteases to substrates. Nat. Rev. Mol. Cell Biol. 8, 245–257 (2007).

  18. 18.

    , , , & Metadegradomics: toward in vivo quantitative degradomics of proteolytic post-translational modifications of the cancer proteome. Mol. Cell Proteomics 7, 1925–1951 (2008).

  19. 19.

    & Nalpha -terminal acetylation of eukaryotic proteins. J. Biol. Chem. 275, 36479–36482 (2000).

  20. 20.

    , , & Human and mouse proteases: a comparative genomic approach. Nat. Rev. Genet. 4, 544–558 (2003).

  21. 21.

    Targeting proteases: successes, failures and future prospects. Nat. Rev. Drug Discov. 5, 785–799 (2006).

  22. 22.

    & Protease degradomics: a new challenge for proteomics. Nat. Rev. Mol. Cell Biol. 3, 509–519 (2002).

  23. 23.

    , & Differential dimethyl labeling of N termini of peptides after guanidination for proteome analysis. J. Proteome Res. 4, 2099–2108 (2005).

  24. 24.

    , , , & Targeted analysis of protein termini. J. Proteome Res. 6, 4634–4645 (2007).

  25. 25.

    & Proteomic discovery of protease substrates. Curr. Opin. Chem. Biol. 11, 36–45 (2007).

  26. 26.

    et al. Profiling constitutive proteolytic events in vivo. Biochem. J. 407, 41–48 (2007).

  27. 27.

    et al. Identification of proteolytic cleavage sites by quantitative proteomics. J. Proteome Res. 6, 2850–2858 (2007).

  28. 28.

    et al. A proteomic approach for the identification of cell-surface proteins shed by metalloproteases. Mol. Cell Proteomics 1, 30–36 (2002).

  29. 29.

    , & Global mapping of the topography and magnitude of proteolytic events in apoptosis. Cell 134, 679–691 (2008).

  30. 30.

    et al. Improved recovery of proteome-informative, protein N-terminal peptides by combined fractional diagonal chromatography (COFRADIC). Proteomics 8, 1362–1370 (2008).

  31. 31.

    et al. Caspase-specific and nonspecific in vivo protein processing during Fas-induced apoptosis. Nat. Methods 2, 771–777 (2005).

  32. 32.

    et al. Analysis of protein processing by N-terminal proteomics reveals novel species-specific substrate determinants of granzyme B orthologs. Mol. Cell. Proteomics 8, 258–272 (2008).

  33. 33.

    et al. Proteome-wide identification of HtrA2/Omi substrates. J. Proteome Res. 6, 1006–1015 (2007).

  34. 34.

    In vivo chemical modification of proteins (post-translational modification). Annu. Rev. Biochem. 50, 783–814 (1981).

  35. 35.

    & Proteomics discovery of metalloproteinase substrates in the cellular context by iTRAQ labeling reveals a diverse MMP-2 substrate degradome. Mol. Cell. Proteomics 6, 611–623 (2007).

  36. 36.

    et al. Identification of candidate angiogenic inhibitors processed by matrix metalloproteinase 2 (MMP-2) in cell based proteomic screens: disruption of vascular endothelial growth factor (VEGF)/heparin Affin regulatory peptide (Pleiotrophin) and VEGF/connective tissue growth factor angiogenic inhibitory complexes by MMP-2 proteolysis. Mol. Cell Biol. 27, 8454–8465 (2007).

  37. 37.

    , , & Pharmacoproteomics of a metalloproteinase hydroxamate inhibitor in breast cancer cells: dynamics of matrix metalloproteinase-14 (MT1-MMP) mediated membrane protein shedding. Mol. Cell Biol. 28, 4896–4914 (2008).

  38. 38.

    , , & Stable-isotope dimethyl labeling for quantitative proteomics. Anal. Chem. 75, 6843–6852 (2003).

  39. 39.

    et al. Identification of formaldehyde-induced modifications in proteins: reactions with model peptides. J. Biol. Chem. 279, 6235–6243 (2004).

  40. 40.

    , , , & Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics. Nat. Protoc. 4, 484–494 (2009).

  41. 41.

    et al. Peptide labeling with isobaric tags yields higher identification rates using iTRAQ 4-plex compared to TMT 6-plex and iTRAQ 8-plex on LTQ Orbitrap. Anal. Chem. 82, 6549–6558 (2010).

  42. 42.

    et al. Characterization of protein phosphorylation by mass spectrometry using immobilized metal ion affinity chromatography with on-resin beta-elimination and Michael addition. Anal. Chem. 75, 3232–3243 (2003).

  43. 43.

    et al. Temporal profiling of the adipocyte proteome during differentiation using a five-plex SILAC based strategy. J. Proteome Res. 8, 48–58 (2009).

  44. 44.

    , & Cell-based identification of natural substrates and cleavage sites for extracellular proteases by SILAC proteomics. Methods Mol. Biol. 539, 131–153 (2009).

  45. 45.

    , , & PepC: proteomics software for identifying differentially expressed proteins based on spectral counting. Bioinformatics 26, 1574–1575 (2010).

  46. 46.

    , , , & Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation. Nat. Biotechnol. 25, 117–124 (2007).

  47. 47.

    & Proteome-derived, database-searchable peptide libraries for identifying protease cleavage sites. Nat. Biotechnol. 26, 685–694 (2008).

  48. 48.

    & Minimizing resolution of isotopically coded peptides in comparative proteomics. J. Proteome Res. 1, 139–147 (2002).

  49. 49.

    , & Stable-isotope dimethylation labeling combined with LC-ESI MS for quantification of amine-containing metabolites in biological samples. Anal. Chem. 79, 8631–8638 (2007).

  50. 50.

    & A predictive model for identifying proteins by a single peptide match. Bioinformatics 23, 277–280 (2007).

  51. 51.

    , , , & A uniform proteomics MS/MS analysis platform using open XML file formats. Mol. Syst. Biol. 1, 2005.0017 (2005).

  52. 52.

    , , & Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20, 3551–3567 (1999).

  53. 53.

    & TANDEM: matching proteins with tandem mass spectra. Bioinformatics 20, 1466–1467 (2004).

  54. 54.

    , , & Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations. Nat. Methods 2, 667–675 (2005).

  55. 55.

    , & Improving sensitivity by probabilistically combining results from multiple MS/MS search methodologies. J. Proteome Res. 7, 245–253 (2008).

  56. 56.

    et al. iProphet: Multi-level integrative analysis of shotgun proteomic data improves peptide and protein identification rates and error estimates. Mol. Cell. Proteomics. published online, doi:10.1074/mcp.M111.007690 (2011).

  57. 57.

    & Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat. Methods 4, 207–214 (2007).

  58. 58.

    & Semisupervised model-based validation of peptide identifications in mass spectrometry-based proteomics. J. Proteome Res. 7, 254–265 (2008).

  59. 59.

    VENNY. An interactive tool for comparing lists with Venn Diagrams. (2007).

  60. 60.

    & Proteomic identification of multitasking proteins in unexpected locations complicates drug targeting. Nat. Rev. Drug Discov. 8, 935–948 (2009).

  61. 61.

    & Updated biological roles for matrix metalloproteinases and new 'intracellular' substrates revealed by degradomics. Biochemistry 48, 10830–10845 (2009).

  62. 62.

    & TopFIND, a knowledgebase linking protein termini with function. Nat. Meth. 8, 703–704 (2011).

  63. 63.

    , & Silver staining of proteins in polyacrylamide gels. Nat. Protoc. 1, 1852–1858 (2006).

  64. 64.

    , & Stop and go extraction tips for matrix-assisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics. Anal. Chem. 75, 663–670 (2003).

  65. 65.

    , & Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat. Protoc. 2, 1896–1906 (2007).

  66. 66.

    & Overalkylation of a protein digest with iodoacetamide. Anal. Chem. 73, 3576–3582 (2001).

  67. 67.

    et al. Iodoacetamide-induced artifact mimics ubiquitination in mass spectrometry. Nat. Methods 5, 459–460 (2008).

  68. 68.

    & Reductive methylation of proteins with sodium cyanoborohydride. Identification, suppression and possible uses of N-cyanomethyl by-products. Biochem. J. 203, 331–334 (1982).

  69. 69.

    & Labeling of proteins by reductive methylation using sodium cyanoborohydride. J. Biol. Chem. 254, 4359–4365 (1979).

  70. 70.

    et al. Direct cancer tissue proteomics: a method to identify candidate cancer biomarkers from formalin-fixed paraffin-embedded archival tissues. Oncogene 26, 65–76 (2007).

  71. 71.

    & De novo sequencing of neuropeptides using reductive isotopic methylation and investigation of ESI QTOF MS/MS fragmentation pattern of neuropeptides with N-terminal dimethylation. Anal. Chem. 77, 7783–7795 (2005).

  72. 72.

    , & Adaptive discriminant function analysis and reranking of MS/MS database search results for improved peptide identification in shotgun proteomics. J. Proteome Res. 7, 4878–4889 (2008).

  73. 73.

    Free Statistics Software, Office for Research Development and Education, version 1.1.23-r6, (2010).

  74. 74.

    , , , & In-gel digestion for mass spectrometric characterization of proteins and proteomes. Nat. Protoc. 1, 2856–2860 (2006).

  75. 75.

    & A practical recipe for stable isotope labeling by amino acids in cell culture (SILAC). Nat. Protoc. 1, 2650–2660 (2006).

  76. 76.

    , & Modular stop and go extraction tips with stacked disks for parallel and multidimensional Peptide fractionation in proteomics. J. Proteome Res. 5, 988–994 (2006).

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Author information

Author notes

    • Oded Kleifeld
    • , Ulrich auf dem Keller
    •  & Magda Gioia

    Present addresses: Department of Biochemistry and Molecular Biology, Monash University, Clayton, Melbourne, Australia (O.K.); Ottawa Institute of Systems Biology, Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario, Canada (A.D); Institute of Cell Biology ETH Zurich, Zurich, Switzerland (U.a.d.K.); Department of Experimental Medicine and Biochemical Sciences, Università di Roma Tor Vergata, Roma, Italy (M.G.).

    • Oded Kleifeld
    • , Alain Doucet
    • , Anna Prudova
    • , Ulrich auf dem Keller
    •  & Magda Gioia

    These authors contributed equally to this work.

Affiliations

  1. Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, British Columbia, Canada.

    • Oded Kleifeld
    • , Alain Doucet
    • , Anna Prudova
    • , Ulrich auf dem Keller
    • , Magda Gioia
    •  & Christopher M Overall
  2. Department of Oral Biological and Medical Sciences, University of British Columbia, Vancouver, British Columbia, Canada.

    • Oded Kleifeld
    • , Alain Doucet
    • , Anna Prudova
    • , Ulrich auf dem Keller
    • , Magda Gioia
    •  & Christopher M Overall
  3. Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.

    • Jayachandran N Kizhakkedathu
  4. Department of Chemistry, University of British Columbia, Vancouver, British Columbia, Canada.

    • Jayachandran N Kizhakkedathu

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Contributions

O.K. developed dimethylation-TAILS and drafted the manuscript. A.D. participated in the development and optimization of dimethylation-TAILS and participated in the manuscript writing. A.P. developed iTRAQ-TAILS and revised the manuscript. U.a.d.K. participated in the development of analysis tools of iTRAQ-TAILS, wrote TAILS-ANNOTATOR and revised the manuscript. M.G. developed SILAC-TAILS and revised the manuscript. J.N.K. engineered the HPG-ALD polymer series and participated in methods development and manuscript writing. C.M.O. conceived the TAILS concept, projects and design, and was responsible for project supervision, data interpretation, manuscript writing and providing grant support.

Competing interests

The authors declare no competing financial interests.

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https://doi.org/10.1038/nprot.2011.382

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