American Journal of Medical and Biological Research. 2016, 4(5), 90-94
DOI: 10.12691/AJMBR-4-5-2
Original Research

Computational Design of Serotype Independent Vaccine against Streptococcus pneumoniae Based on B-Cell Epitopes of Pneumococcal Plasmid Stabilization Protein

Shirin Tarahomjoo1,

1Division of Genomics and Genetic Engineering, Department of Biotechnology and Central Laboratory, Razi Vaccine and Serum Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj 31975/148, Iran

Pub. Date: December 06, 2016

Cite this paper

Shirin Tarahomjoo. Computational Design of Serotype Independent Vaccine against Streptococcus pneumoniae Based on B-Cell Epitopes of Pneumococcal Plasmid Stabilization Protein. American Journal of Medical and Biological Research. 2016; 4(5):90-94. doi: 10.12691/AJMBR-4-5-2

Abstract

Pneumococcal conjugate vaccines (PCVs) were constructed through chemical conjugation of pneumococcal capsules to immunogenic carrier proteins. The PCVs implementation in developing countries was prevented by their high manufacturing costs. This issue can be overcome by development of protein based vaccines against pneumococci. Antibody responses are necessary for protection against S. pneumoniae. The plasmid stabilization protein (PSP) was already identified as a pneumococcal surface protein able to elicit protection against S. pneumoniae serotype 19F and its protective B-cell epitope regions were determined. Whole antigens are not as potent as epitope based vaccines and every epitope in a multi epitope based vaccine can individually induce a protective immune response against the pathogen. Thus better immunoprotection can be achieved by multi epitope based vaccines. In the present study, therefore, we aim to design a multi epitope vaccine against pneumococci based on the identified B-cell epitope regions of PSP using immunoinformatic tools. These regions were joined together using the (EAAAK) 4 linker. The resulting antigen (HPBE) showed much higher immunoprotective ability compared to PSP regarding the VaxiJen scores. The codon optimization was done for HPBE using OPTIMIZER. Analysis of the mRNA secondary structure using Mfold tool revealed no stable hairpin at the 5' end and thus the antigen can be expressed appropriately. The 3D model of the antigen resulted from I-TASSER indicated the presence of alpha helix, beta sheet, turn, coil, and 310 helix as the protein structural elements. Analyzing physicochemical properties of the antigen using ProtParam showed that it was stable and its half life in Escherichia coli was more than 10 h. Considering the GRAVY score, HPBE possessed a hydrophilic nature and it can be expressed in the soluble form in E. coli at 79.6% probability. Our results demonstrated that HPBE is a suitable vaccine candidate, which can elicit protection against common S. pneumoniae serotypes causing invasive pneumococcal disease in children less than 5 years of age.

Keywords

computational design, pneumococcal conjugate vaccines, protective epitope, protein based vaccines, Streptococcus pneumoniae

Copyright

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References

[1]  Mook-Kanamori, B.B., et al., Pathogenesis and pathophysiology of pneumococcal meningitis. Clinical microbiology reviews, 2011. 24(3): p. 557-591.
 
[2]  Johnson, H.L., et al., Systematic evaluation of serotypes causing invasive pneumococcal disease among children under five: the pneumococcal global serotype project. PLoS Med, 2010. 7(10): p. e1000348.
 
[3]  Publication, W., Pneumococcal vaccines WHO position paper–2012–recommendations. Vaccine, 2012. 30(32): p. 4717-4718.
 
[4]  Ginsburg, A.S., et al., Issues and challenges in the development of pneumococcal protein vaccines. Expert review of vaccines, 2012. 11(3): p. 279-285.
 
[5]  Foster, T.J., et al., Adhesion, invasion and evasion: the many functions of the surface proteins of Staphylococcus aureus. Nature Reviews Microbiology, 2014. 12(1): p. 49-62.
 
[6]  Bergmann, S. and S. Hammerschmidt, Versatility of pneumococcal surface proteins. Microbiology, 2006. 152(2): p. 295-303.
 
[7]  Tarahomjoo, S., Recent approaches in vaccine development against Streptococcus pneumoniae. Journal of molecular microbiology and biotechnology, 2014. 24(4): p. 215-227.
 
[8]  Tarahomjoo, S., Bioinformatic analysis of surface proteins of Streptococcus pneumoniae serotype 19F for identification of vaccine candidates. American Journal of Microbiological Research, 2014. 2(6): p. 174-177.
 
[9]  Novotný, J.í., et al., Antigenic determinants in proteins coincide with surface regions accessible to large probes (antibody domains). Proceedings of the National Academy of Sciences, 1986. 83(2): p. 226-230.
 
[10]  Quijada, L., et al., Mapping of the linear antigenic determinants of the Leishmania infantum hsp70 recognized by leishmaniasis sera. Immunology letters, 1996. 52(2): p. 73-79.
 
[11]  Faria, A.R., et al., High-throughput analysis of synthetic peptides for the immunodiagnosis of canine visceral leishmaniasis. PLoS Negl Trop Dis, 2011. 5(9): p. e1310.
 
[12]  Zhao, Z., et al., Multiple B-cell epitope vaccine induces a Staphylococcus enterotoxin B-specific IgG1 protective response against MRSA infection. Scientific reports, 2015. 5.
 
[13]  Lu, Y., et al., A candidate vaccine against influenza virus intensively improved the immunogenicity of a neutralizing epitope. International archives of allergy and immunology, 2002. 127(3): p. 245-250.
 
[14]  Kelly, D.F. and R. Rappuoli, Reverse vaccinology and vaccines for serogroup B Neisseria meningitidis, in Hot Topics in Infection and Immunity in Children II. 2005, Springer. p. 217-223.
 
[15]  Assis, L., et al., Bcell epitopes of antigenic proteins in Leishmania infantum: an in silico analysis. Parasite immunology, 2014. 36(7): p. 313-323.
 
[16]  Tarahomjoo, S., Identification of B-cell Epitope Regions in Cell Surface Proteins of Streptococcus pneumoniae Serotype 19F Using Bioinformatic Tools. American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS), 2015. 14(3): p. 107-117.
 
[17]  Doytchinova, I.A. and D.R. Flower, Bioinformatic approach for identifying parasite and fungal candidate subunit vaccines. Open Vaccine J, 2008. 1(1): p. 4.
 
[18]  Puigbo, P., et al., OPTIMIZER: a web server for optimizing the codon usage of DNA sequences. Nucleic acids research, 2007. 35(suppl 2): p. W126-W131.
 
[19]  Zuker, M., Mfold web server for nucleic acid folding and hybridization prediction. Nucleic acids research, 2003. 31(13): p. 3406-3415.
 
[20]  Gasteiger, E., et al., Protein identification and analysis tools on the ExPASy server. 2005: Springer.
 
[21]  Smialowski, P., et al., PROSO II–a new method for protein solubility prediction. Febs Journal, 2012. 279(12): p. 2192-2200.
 
[22]  Roy, A., A. Kucukural, and Y. Zhang, I-TASSER: a unified platform for automated protein structure and function prediction. Nature protocols, 2010. 5(4): p. 725-738.
 
[23]  Li, J., et al., GC-content of synonymous codons profoundly influences amino acid usage. G3: Genes| Genomes| Genetics, 2015. 5(10): p. 2027-2036.
 
[24]  Seo, S.W., J. Yang, and G.Y. Jung, Quantitative correlation between mRNA secondary structure around the region downstream of the initiation codon and translational efficiency in Escherichia coli. Biotechnology and bioengineering, 2009. 104(3): p. 611-616.
 
[25]  Singh, S.M. and A.K. Panda, Solubilization and refolding of bacterial inclusion body proteins. Journal of bioscience and bioengineering, 2005. 99(4): p. 303-310.
 
[26]  Yin, J., et al., Select what you need: a comparative evaluation of the advantages and limitations of frequently used expression systems for foreign genes. Journal of Biotechnology, 2007. 127(3): p. 335-347.