A bioinformatics tool for epitope-based vaccine design that accounts for human ethnic diversity: Application to emerging infectious diseases.

Oyarzun, Patricio, Ellis, Jonathan J., Gonzalez-Galarza, Faviel F., Jones, Andrew R, Middleton, Derek, Boden, Mikael and Kobe, Bostjan (2015) A bioinformatics tool for epitope-based vaccine design that accounts for human ethnic diversity: Application to emerging infectious diseases.. Vaccine, 33 10: 1267-1273. doi:10.1016/j.vaccine.2015.01.040


Author Oyarzun, Patricio
Ellis, Jonathan J.
Gonzalez-Galarza, Faviel F.
Jones, Andrew R
Middleton, Derek
Boden, Mikael
Kobe, Bostjan
Title A bioinformatics tool for epitope-based vaccine design that accounts for human ethnic diversity: Application to emerging infectious diseases.
Journal name Vaccine   Check publisher's open access policy
ISSN 0264-410X
1873-2518
Publication date 2015-01
Year available 2015
Sub-type Article (original research)
DOI 10.1016/j.vaccine.2015.01.040
Open Access Status
Volume 33
Issue 10
Start page 1267
End page 1273
Total pages 7
Place of publication Camden, London, United Kingdom
Publisher Elsevier
Collection year 2016
Language eng
Formatted abstract
Background
Peptide vaccination based on multiple T-cell epitopes can be used to target well-defined ethnic populations. Because the response to T-cell epitopes is restricted by HLA proteins, the HLA specificity of T-cell epitopes becomes a major consideration for epitope-based vaccine design. We have previously shown that CD4+ T-cell epitopes restricted by 95% of human MHC class II proteins can be predicted with high-specificity.

Methods
We describe here the integration of epitope prediction with population coverage and epitope selection algorithms. The population coverage assessment makes use of the Allele Frequency Net Database. We present the computational platform Predivac-2.0 for HLA class II-restricted epitope-based vaccine design, which accounts comprehensively for human genetic diversity.

Results
We validated the performance of the tool on the identification of promiscuous and immunodominant CD4+ T-cell epitopes from the human immunodeficiency virus (HIV) protein Gag. We further describe an application for epitope-based vaccine design in the context of emerging infectious diseases associated with Lassa, Nipah and Hendra viruses. Putative CD4+ T-cell epitopes were mapped on the surface glycoproteins of these pathogens and are good candidates to be experimentally tested, as they hold potential to provide cognate help in vaccination settings in their respective target populations.

Conclusion
Predivac-2.0 is a novel approach in epitope-based vaccine design, particularly suited to be applied to virus-related emerging infectious diseases, because the geographic distributions of the viruses are well defined and ethnic populations in need of vaccination can be determined (“ethnicity-oriented approach”). 
Keyword Emerging infectious diseases
Immunodominance
Lassa, Nipah and Hendra viruses
MHC (HLA) class II proteins
Multi epitope peptide vaccination
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Fri, 06 Feb 2015, 09:25:44 EST by Mrs Louise Nimwegen on behalf of School of Chemistry & Molecular Biosciences