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

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.

Publication DOI: https://doi.org/10.1093/bioinformatics/btw399
Divisions: College of Health & Life Sciences > Aston Pharmacy School
College of Health & Life Sciences
College of Health & Life Sciences > Chronic and Communicable Conditions
Additional Information: © The Author(s) 2016. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Uncontrolled Keywords: Statistics and Probability,Medicine(all),Biochemistry,Molecular Biology,Computer Science Applications,Computational Theory and Mathematics,Computational Mathematics
Publication ISSN: 1367-4803
Last Modified: 08 Jan 2024 08:10
Date Deposited: 28 Jun 2016 11:05
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2016-11-01
Published Online Date: 2016-07-10
Accepted Date: 2016-06-18
Submitted Date: 2016-03-18
Authors: Sheikh, Qamar M.
Gatherer, Derek
Reche, Pedro A.
Flower, Darren R. (ORCID Profile 0000-0002-8542-7067)

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