Prediction of T-cell epitopes for designing a reverse vaccine against streptococcal bacteria

Document Type : Original article

Authors

Department of Biotechnology, Faculty of Advanced Sciences and Technologies, University of Isfahan, Isfahan, Iran

Abstract

Streptococcal bacteria are among dangerous human pathogens with major prevalence worldwide. A good vaccine against streptococcal bacteria should have epitopes that confer protection from infection by different streptococcal bacteria types. we aimed was to recognize the most immunogenic and conserved epitopes of streptococcal bacteria, which could be a potential candidate for vaccine development. Nineteen different M proteins of different streptococcal bacteria were chosen and analyzed. Nine-mer epitopes able to simulate both cells mediate and humoral immunity were predicted. Molecular docking was applied in order to measure free binding energy of selected epitopes. Final epitopes were analyzed if they were conserved among different streptococcal bacteria. The identified epitopes require experimental validation for their potential use in peptide vaccines.

Keywords


1. Ryan KJ, Ray CG. Medical microbiology. McGraw Hill. 2004;4:370.
2. Kreikemeyer B, Gámez G, Margarit I, Giard J-C, Hammerschmidt S, Hartke A, Podbielski A. Genomic organization, structure, regulation and pathogenic role of pilus constituents in major pathogenic Streptococci and Enterococci. Int J Med Microbiol 2011;301:240-251.
3. Carapetis JR, Steer AC, Mulholland EK, Weber M. The global burden of group A streptococcal diseases. Lancet Infect Dis 2005;5:685-694.
4. Maisey HC, Quach D, Hensler ME, Liu GY, Gallo RL, Nizet V, Doran KS. A group B streptococcal pilus protein promotes phagocyte resistance and systemic virulence. FASEB J 2008;22:1715-1724.
5. Oehmcke S, Shannon O, Mörgelin M, Herwald H. Streptococcal M proteins and their role as virulence determinants. Clin Chim Acta 2010;411:1172-1180.
6. Wei Z, Fu Q, Liu X, Xiao P, Lu Z, Chen Y. Identification of Streptococcus equi ssp. zooepidemicus surface associated proteins by enzymatic shaving. Vet Microbiol 2012;159:519-525.
7. Hamula CL, Peng H, Wang Z, Tyrrell GJ, Li XF, Le XC. An improved SELEX technique for selection of DNA aptamers binding to M-type 11 of Streptococcus pyogenes. Methods 2016;97:51-57.
8. Fischetti VA, Pancholi V, Schneewind O. Conservation of a hexapeptide sequence in the anchor region of surface proteins from gram‐positive cocci. Mol Microbiol 1990;4:1603-1605.
9. Su YF, Chuang WJ, Wang SM, Chen WY, Chiang-Ni C, Lin YS, Wu JJ, Liu CC. The deficient cleavage of M protein-bound IgG by IdeS: insight into the escape of Streptococcus pyogenes from antibody-mediated immunity. Mol Immunol 2011;49:134-142.
10. Berge A, Kihlberg B-M, Sjöholm AG, Björck L. Streptococcal protein H forms soluble complement-activating complexes with IgG, but inhibits complement activation by IgG-coated targets. J Biol Chem 1997;272:20774-20781.
11. Moreland NJ, Waddington CS, Williamson DA, Sriskandan S, Smeesters PR, Proft T, Steer AC, Walker MJ, Baker EN, Baker MG, Lennon D, Dunbar R, Carapetis J, Fraser JD. Working towards a group A streptococcal vaccine: report of a collaborative Trans-Tasman workshop. Vaccine 2014;32:3713-3720.
12. Burt FJ, Samudzi RR, Randall C, Pieters D, Vermeulen J, Knox CM. Human defined antigenic region on the nucleoprotein of Crimean-Congo hemorrhagic fever virus identified using truncated proteins and a bioinformatics approach. J Virol Methods 2013;193:706-712.
13. Gershoni JM, Roitburd-Berman A, Siman-Tov DD, Freund NT, Weiss Y. Epitope mapping. BioDrugs 2007;21:145-156.
14. Soria-Guerra RE, Nieto-Gomez R, Govea-Alonso DO, Rosales-Mendoza S. An overview of bioinformatics tools for epitope prediction: implications on vaccine development. J Biomed Inform 2015;53:405-414.
15. Hakenberg J, Nussbaum AK, Schild H, Rammensee H-G, Kuttler C, Holzhütter HG, Kloetzel PM, Kaufmann SH, Mollenkopf HJ. MAPPP: MHC class I antigenic peptide processing prediction. Appl Bioinformatics. 2003;2:155-158.
16. Lata S, Bhasin M, Raghava GPS. Application of machine learning techniques in predicting MHC binders. Methods Mol Biol 2007;409:201-215.
17. Larsen ME, Kloverpris H, Stryhn A, Koofhethile CK, Sims S, Ndung’u T, Goulder P, Buus S, Nielsen M. HLArestrictor--a tool for patient-specific predictions of HLA restriction elements and optimal epitopes within peptides. Immunogenetics 2011;63:43-55.
18. Guan P, Doytchinova IA, Zygouri C, Flower DR. MHCPred: a server for quantitative prediction of peptide–MHC binding. Nucleic Acids Res. Oxford Univ Press; 2003;31:3621-3624.
19. Lundegaard C, Lamberth K, Harndahl M, Buus S, Lund O, Nielsen M. NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8-11. Nucleic Acids Res 2008;36:W509-512.
20. Singh H, Raghava GPS. ProPred1: prediction of promiscuous MHC Class-I binding sites. Bioinformatics 2003;19:1009-1014.
21. Reche PA, Glutting J-P, Zhang H, Reinherz EL. Enhancement to the RANKPEP resource for the prediction of peptide binding to MHC molecules using profiles. Immunogenetics 2004;56:405-419.
22. Dönnes P, Kohlbacher O. SVMHC: a server for prediction of MHC-binding peptides. Nucleic Acids Res 2006;34:W194-197.
23. Xiang Z, He Y. Vaxign: a web-based vaccine target design program for reverse vaccinology. Procedia Vaccinol 2009;1:23-29.
24. Vita R, Overton JA, Greenbaum JA, Ponomarenko J, Clark JD, Cantrell JR, Wheeler DK, Gabbard JL, Hix D, Sette A, Peters B. The immune epitope database (IEDB) 3.0. Nucleic Acids Res 2014;43:D405-412.
25. Saha S, Raghava GPS. Prediction of continuous B‐cell epitopes in an antigen using recurrent neural network. Proteins Struct Funct Bioinforma 2006;65:40-48.
26. Doytchinova IA, Flower DR. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics. Bio Med Central 2007;8:4.
27. Kaur H, Garg A, Raghava GPS. PEPstr: a de novo method for tertiary structure prediction of small bioactive peptides. Protein Pept Lett 2007;14:626-631.
28. Comeau SR, Gatchell DW, Vajda S, Camacho CJ. ClusPro: an automated docking and discrimination method for the prediction of protein complexes. Bioinformatics 2004;20:45-50.
29. Singh H, Raghava GPS. ProPred: prediction of HLA-DR binding sites. Bioinformatics 2001;17:1236-1237.
30. Capecchi B, Serruto D, Adu-Bobie J, Rappuoli R, Pizza M. The genome revolution in vaccine research. Curr Issues Mol Biol 2004;6:17-28.
31. Yu NY, Wagner JR, Laird MR, Melli G, Rey S, Lo R, Dao P, Sahinalp SC, Ester M, Foster LJ, Brinkman FS. PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes. Bioinformatics 2010;26:1608-1615.
32. Talay SR. Gram-Positive Adhesins. In: Concepts in bacterial virulence. Karger Publishers; 2005.p.90-113.
33. Saraav I, Pandey K, Sharma M, Singh S, Dutta P, Bhardwaj A, et al. Predicting promiscuous antigenic T cell epitopes of Mycobacterium tuberculosis mymA operon proteins binding to MHC Class I and Class II molecules. Infect Genet Evol 2016;44:182-189.
34. Perez-Casal J, Caparon MG, Scott JR. Introduction of the emm6 gene into an emm-deleted strain of Streptococcus pyogenes restores its ability to resist phagocytosis. Res Microbiol 1992;143:549-558.
35. Batzloff MR, Hayman WA, Davies MR, Zeng M, Pruksakorn S, Brandt ER, Good MF. Protection against group A streptococcus by immunization with J8-diphtheria toxoid: contribution of J8-and diphtheria toxoid-specific antibodies to protection. J Infect Dis 2003; 187:1598-1608.
36. Massell BF, Honikman LH, Amezcua J. Rheumatic fever following streptococcal vaccination: report of three cases. JAMA 1969;207:1115-1119.
37. Hu MC, Walls MA, Stroop SD, Reddish MA, Beall B, Dale JB. Immunogenicity of a 26-valent group A streptococcal vaccine. Infect Immun 2002;70:2171-2177.
38. Guilherme L, Faé KC, Higa F, Chaves L, Oshiro SE, Freschi de Barros S, Puschel C, Juliano MA, Tanaka AC, Spina G, Kalil J. Towards a vaccine against rheumatic fever. Clin Dev Immunol 2006;13:125-132.