Novel Vaccines against Streptococcus pneumoniae Based on the Immunoprotective B-cell Epitope Region of Pneumococcal Choline Binding Protein D and Salmonella Enteritidis Flagellin

Shirin Tarahomjoo^1, and Soheila Ghaderi²

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

²Division of Central Laboratory, Department of Biotechnology and Central Laboratory, Razi Vaccine and Serum Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj 31975/148, Iran

Cite this paper:
Shirin Tarahomjoo and Soheila Ghaderi. Novel Vaccines against Streptococcus pneumoniae Based on the Immunoprotective B-cell Epitope Region of Pneumococcal Choline Binding Protein D and Salmonella Enteritidis Flagellin. American Journal of Microbiological Research. 2017; 5(6):118-123. doi: 10.12691/ajmr-5-6-1

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. Choline binding protein D (CBPD) was already identified as a pneumococcal surface protein able to elicit protection against S. pneumoniae and its most protective B-cell epitope region (MIBR) was determined. MIBR was highly conserved in common pneumococcal serotypes. Whole antigens are not as potent as epitope based vaccines and B-cell epitope based vaccines are more effective than whole antigen based vaccines in the prevention of infections. Bacterial flagellins are effective adjuvants that signal via Toll like receptor 5 (TLR5). The TLR5 binding site of flagellin located in the D1 domain and its proper conformation is critical for TLR5 recognition of flagellin. In the present study, therefore, we aim to design effective chimeric vaccines against pneumococci based on MIBR and flagellin of Salmonella Enteritidis (FliC) using bioinformatics tools. FliC was joined to MIBR at N-terminus (CFH), C-terminus (FCH) and the D3 domain (D3Gly202, D3Thr275). All of the constructs were immunoprotective regarding the VaxiJen score (0.8). The codon optimization for constructs was done using OPTIMIZER. Analysis of the mRNA secondary structures using Mfold tool revealed no stable hairpins at 5' ends of constructs and thus the antigens can be expressed appropriately. SCRATCH results indicated that the antigens can be expressed in the soluble form in Escherichia coli at more than 80% probability. The 3D models of antigens resulted from I-TASSER indicated the presence of alpha helix, beta sheet, turn, coil, and 3₁₀ helix as the protein structural elements. Superimposing 3D models of D1 domains of antigens with the D1 domain of FliC using FATCAT indicated no change in the D1 conformation. Therefore, FliC can exert its adjuvant effects in these constructs through TLR5 signaling. Inserting MIBR in Gly202 of FliC enhanced the protein beta sheet content remarkably, which can result in appropriate thermostability of the antigen. Our results, therefore, demonstrated that D3Gly202 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 Flagellin Pneumococcal conjugate vaccines Protective epitope Protein based vaccines Streptococcus pneumoniae

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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., B‐cell epitopes of antigenic proteins in Leishmania infantum: an in silico analysis. Parasite immunology, 2014. 36(7): p. 313-323.
[16]	Tarahomjoo, S, In silico Analysis of Surface Proteins of Streptococcus pneumoniae Serotype 19F for Identification of Immunoprotective Epitopes. American Journal of Microbiological Research, 2015. 3 (6): p. 190-196.
[17]	Andersen – Nissen, E., K. D. Smith, K. L. Strobe, et al. Evasion of toll like receptor 5 by flagellated bacteria. Proceeding of National Academy of Science USA 2005. 102 (26): p. 9247-9252.
[18]	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.
[19]	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.
[20]	Zuker, M., Mfold web server for nucleic acid folding and hybridization prediction. Nucleic acids research, 2003. 31(13): p. 3406-3415.
[21]	Cheng J, A. Z. Randall, M. J. Sweredoski and P. Baldi, SCRATCH: a protein structure and structural feature prediction server. Nucleic acids research, 2005. 33 (suppl 2): p.W72-W76.
[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]	Wiederstein, M. and M. J. Sippl, ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic acids research, 2007. 35 (suppl 2): p. W407-W410.
[24]	Yuzhen Ye and A. Godzik. Flexible structure alignment by chaining aligned fragment pairs allowing twists. Bioinformatics, 2003. 19 (suppl 2): p. ii246-ii255.
[25]	Ponomarenko J.V., et al., ElliPro: a new structure-based tool for the prediction of antibody epitopes. BMC Bioinformatics, 2008. 9: p. 514.
[26]	Li, J., et al., GC-content of synonymous codons profoundly influences amino acid usage. G3: Genes| Genomes| Genetics, 2015. 5(10): p. 2027-2036.
[27]	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.
[28]	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.
[29]	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.