Towards the knowledge-based design of universal influenza epitope ensemble vaccines

Sheikh, Qamar M. and Gatherer, Derek and Reche, Pedro A. and Flower, Darren R. (2016) Towards the knowledge-based design of universal influenza epitope ensemble vaccines. Bioinformatics, 32 (21). pp. 3233-3239. ISSN 1367-4803

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Abstract

MOTIVATION: Influenza A viral heterogeneity remains a significant threat due to unpredictable antigenic drift in seasonal influenza and antigenic shifts caused by the emergence of novel subtypes. Annual review of multivalent influenza vaccines targets strains of influenza A and B likely to be predominant in future influenza seasons. This does not induce broad, cross protective immunity against emergent subtypes. Better strategies are needed to prevent future pandemics. Cross-protection can be achieved by activating CD8+ and CD4+ T cells against highly-conserved regions of the influenza genome. We combine available experimental data with informatics-based immunological predictions to help design vaccines potentially able to induce cross-protective T-cells against multiple influenza subtypes. RESULTS: To exemplify our approach we designed two epitope ensemble vaccines comprising highly-conserved and experimentally-verified immunogenic influenza A epitopes as putative non-seasonal influenza vaccines; one specifically targets the US population and the other is a universal vaccine. The USA-specific vaccine comprised 6 CD8+ T cell epitopes (GILGFVFTL, FMYSDFHFI, GMDPRMCSL, SVKEKDMTK, FYIQMCTEL, DTVNRTHQY) and 3 CD4+ epitopes (KGILGFVFTLTVPSE, EYIMKGVYINTALLN, ILGFVFTLTVPSERG). The universal vaccine comprised 8 CD8+ epitopes: (FMYSDFHFI, GILGFVFTL, ILRGSVAHK, FYIQMCTEL, ILKGKFQTA, YYLEKANKI, VSDGGPNLY, YSHGTGTGY) and the same 3 CD4+ epitopes. Our USA-specific vaccine has a population protection coverage (portion of the population potentially responsive to one or more component epitopes of the vaccine, PPC) of over 96% and 95% coverage of observed influenza subtypes. The universal vaccine has a PPC value of over 97% and 88% coverage of observed subtypes. AVAILABILITY: http://imed.med.ucm.es/EPISOPT.html CONTACT: d.r.flower@aston.ac.uk SUPPLEMENTARY INFORMATION: none.

Item Type:
Journal Article
Journal or Publication Title:
Bioinformatics
Additional Information:
© The Author(s) 2016. Published by Oxford University Press.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1706
Subjects:
ID Code:
80880
Deposited By:
Deposited On:
15 Aug 2016 10:40
Refereed?:
Yes
Published?:
Published
Last Modified:
20 Sep 2020 03:44