Immunogenetics

, Volume 57, Issue 1–2, pp 33–41

The role of the proteasome in generating cytotoxic T-cell epitopes: insights obtained from improved predictions of proteasomal cleavage

  • Morten Nielsen
  • Claus Lundegaard
  • Ole Lund
  • Can Keşmir
Original Paper

Abstract

Cytotoxic T cells (CTLs) perceive the world through small peptides that are eight to ten amino acids long. These peptides (epitopes) are initially generated by the proteasome, a multi-subunit protease that is responsible for the majority of intra-cellular protein degradation. The proteasome generates the exact C-terminal of CTL epitopes, and the N-terminal with a possible extension. CTL responses may diminish if the epitopes are destroyed by the proteasomes. Therefore, the prediction of the proteasome cleavage sites is important to identify potential immunogenic regions in the proteomes of pathogenic microorganisms (or humans). We have recently shown that NetChop, a neural network-based prediction method, is the best method available at the moment to do such predictions; however, its performance is still lower than desired. Here, we use novel sequence encoding methods and show that the new version of NetChop predicts approximately 10% more of the cleavage sites correctly while lowering the number of false positives with close to 15%. With this more reliable prediction tool, we study two important questions concerning the function of the proteasome. First, we estimate the N-terminal extension of epitopes after proteasomal cleavage and find that the average extension is relatively short. However, more than 30% of the peptides have N-terminal extensions of three amino acids or more, and thus, N-terminal trimming might play an important role in the presentation of a substantial fraction of the epitopes. Second, we show that good TAP ligands have an increased chance of being cleaved by the proteasome, i.e., the specificity of TAP has evolved to fit the specificity of the proteasome. This evolutionary relationship allows for a more efficient antigen presentation.

Keywords

Proteasomal cleavage MHC class I epitope Neural networks Sequence encoding Hidden Markov models Evolution of TAP specificity N-terminal trimming 

References

  1. Bairoch A, Apweiler R (2000) The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000. Nucleic Acids Res 28:45–48CrossRefPubMedGoogle Scholar
  2. Baldi P, Brunak S (2001) Bioinformatics: the machine learning approach, 2nd edn. MIT Press, CambridgeGoogle Scholar
  3. Cascio P, Hilton C, Kisselev AF, Rock KL, Goldberg AL (2001) 26S Proteasomes and immunoproteasomes produce mainly N-extended versions of an antigenic peptide. EMBO J 20:2357–2366Google Scholar
  4. Eggers M, Boes-Fabian B, Ruppert T, Kloetzel PM, Koszinowski UH (1995) The cleavage preference of the proteasome governs the yield of antigenic peptides. J Exp Med 182:1865–1870Google Scholar
  5. Goldberg AL, Cascio P, Saric T, Rock KL (2002) The importance of the proteasome and subsequent proteolytic steps in the generation of antigenic peptides. Mol Immunol 39:147–164Google Scholar
  6. Henikoff S, Henikoff JG (1992) Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci USA 89:10915–10919PubMedGoogle Scholar
  7. Holzhutter HG, Frommel C, Kloetzel PM (1999) A theoretical approach towards the identification of cleavage-determining amino acid motifs of the 20 S proteasome. J Mol Biol 286:1251–1265Google Scholar
  8. Kesmir C, Nussbaum AK, Schild H, Detours V, Brunak S (2002) Prediction of proteasome cleavage motifs by neural networks. Protein Eng 15:287–296CrossRefPubMedGoogle Scholar
  9. Kesmir C, Noort VV, Boer RJD, Hogeweg P (2003) Bioinformatic analysis of functional differences between the immunoproteasome and the constitutive proteasome. Immunogenetics 55:437–449CrossRefPubMedGoogle Scholar
  10. Kuttler C, Nussbaum AK, Dick TP, Rammensee HG, Schild H, Hadeler KP (2000) An algorithm for the prediction of proteasomal cleavages. J Mol Biol 298:417–429CrossRefPubMedGoogle Scholar
  11. Levy F, Burri L, Morel S, Peitrequin AL, Levy N, Bachi A, Hellman U, Van den Eynde BJ, Servis C (2002) The final N-terminal trimming of a subaminoterminal proline-containing HLA class I-restricted antigenic peptide in the cytosol is mediated by two peptidases. J Immunol 169:4161–4171Google Scholar
  12. Nielsen M, Lundegaard C, Worning P, Lauemoller SL, Lamberth K, Buus S, Brunak S, Lund O (2003) Reliable prediction of T-cell epitopes using neural networks with novel sequence representations. Protein Sci 12:1007–1017Google Scholar
  13. Nielsen M, Lundegaard C, Worning P, Hvid CS, Lamberth K, Buus S, Brunak S, Lund O (2004) Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach. Bioinformatics 20:1388–1397Google Scholar
  14. Nussbaum AK, Dick TP, Keilholz W, Schirle M, Stevanovic S, Dietz K, Heinemeyer W, Groll M, Wolf DH, Huber R, Rammensee HG, Schild H (1998) Cleavage motifs of the yeast 20S proteasome β subunits deduced from digests of enolase 1. Proc Natl Acad Sci USA 95:12504–12509CrossRefPubMedGoogle Scholar
  15. Peters B, Bulik S, Tampe R, Endert PMV, Holzhutter HG (2003) Identifying MHC class I epitopes by predicting the TAP transport efficiency of epitope precursors. J Immunol 171:1741–1749PubMedGoogle Scholar
  16. Press WH, Flannery BP, Teukolsky SA, Vetterling WT (1992) Numerical recipes in C: the art of scientific computing. Cambridge University Press, CambridgeGoogle Scholar
  17. Rammensee H, Bachmann J, Emmerich NP, Bachor OA, Stevanovic S (1999) SYFPEITHI: database for MHC ligands and peptide motifs. Immunogenetics 50:213–219CrossRefPubMedGoogle Scholar
  18. Reits E, Griekspoor A, Neijssen J, Groothuis T, Jalink K, Veelen PV, Janssen H, Calafat J, Drijfhout JW, Neefjes J (2003) Peptide diffusion, protection, and degradation in nuclear and cytoplasmic compartments before antigen presentation by MHC class I. Immunity 18:97–108Google Scholar
  19. Reits E, Neijssen J, Herberts C, Benckhuijsen W, Janssen L, Drijfhout JW, Neefjes J (2004) A major role for TPPII in trimming proteasomal degradation products for MHC class I antigen presentation. Immunity 20:495–506CrossRefPubMedGoogle Scholar
  20. Saric T, Chang SC, Hattori A, York IA, Markant S, Rock KL, Tsujimoto M, Goldberg AL (2002) An IFN-gamma-induced aminopeptidase in the ER, ERAP1, trims precursors to MHC class I-presented peptides. Nat Immunol 3:1169–1176Google Scholar
  21. Saxová P, Buus S, Brunak S, Kesmir C (2003) Predicting proteasomal cleavage sites: a comparison of available methods. Int Immunol 15:781–787CrossRefPubMedGoogle Scholar
  22. Schneider TD, Stephens RM (1990) Sequence logos: a new way to display consensus sequences. Nucleic Acids Res 18:6097–6100PubMedGoogle Scholar
  23. Serwold T, Gonzalez F, Kim J, Jacob R, Shastri N (2002) ERAAP customizes peptides for MHC class I molecules in the endoplasmic reticulum. Nature 419:480–483CrossRefPubMedGoogle Scholar
  24. Stoltze L, Nussbaum AK, Sijts A, Emmerich NP, Kloetzel PM, Schild H (2000) The function of the proteasome system in MHC class I antigen processing. Immunol Today 21:317–319Google Scholar
  25. Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–1293PubMedGoogle Scholar
  26. Tenzer S, Stoltze L, Schonfisch B, Dengjel J, Muller M, Stevanovic S, Rammensee HG, Schild H (2004) Quantitative analysis of prion-protein degradation by constitutive and immuno-20S proteasomes indicates differences correlated with disease susceptibility. J Immunol 172:1083–1091Google Scholar
  27. Thorne JL, Goldman N, Jones DT (1996) Combining protein evolution and secondary structure. Mol Biol Evol 13:666–673Google Scholar
  28. Toes RE, Nussbaum AK, Degermann S, Schirle M, Emmerich NP, Kraft M, Laplace C, Zwinderman A, Dick TP, Muller J, Schonfisch B, Schmid C, Fehling HJ, Stevanovic S, Rammensee HG, Schild H (2001) Discrete cleavage motifs of constitutive and immunoproteasomes revealed by quantitative analysis of cleavage products. J Exp Med 194:1–12CrossRefPubMedGoogle Scholar
  29. van Endert PM (1996) Peptide selection for presentation by HLA class I: a role for the human transporter associated with antigen processing? Immunol Res 15:265–279Google Scholar
  30. Yewdell JW (2001) Not such a dismal science: the economics of protein synthesis, folding, degradation and antigen processing. Trends Cell Biol 11:294–297Google Scholar
  31. York IA, Chang SC, Saric T, Keys JA, Favreau JM, Goldberg AL, Rock KL (2002) The ER aminopeptidase ERAP1 enhances or limits antigen presentation by trimming epitopes to 8–9 residues. Nat Immunol 3:1177–1184Google Scholar

Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • Morten Nielsen
    • 1
  • Claus Lundegaard
    • 1
  • Ole Lund
    • 1
  • Can Keşmir
    • 1
    • 2
  1. 1.Center for Biological Sequence AnalysisTechnical University of DenmarkLyngbyDenmark
  2. 2.Theoretical Biology/BioinformaticsUtrecht UniversityUtrechtThe Netherlands

Personalised recommendations