4.5 Article

Coupling sensitive in vitro and in silico techniques to assess cross-reactive CD4+ T cells against the swine-origin H1N1 influenza virus

Journal

VACCINE
Volume 29, Issue 17, Pages 3299-3309

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.vaccine.2011.02.019

Keywords

Influenza; Pandemic; H1N1; Informatics; Human; T cells; Cross-reactive

Funding

  1. DARPA/DSO [BAA09-310, 70023]

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The outbreak of the novel swine-origin H1N1 influenza in the spring of 2009 took epidemiologists, immunologists, and vaccinologists by surprise and galvanized a massive worldwide effort to produce millions of vaccine doses to protect against this single virus strain. Of particular concern was the apparent lack of pre-existing antibody capable of eliciting cross-protective immunity against this novel virus, which fueled fears this strain would trigger a particularly far-reaching and lethal pandemic. Given that disease caused by the swine-origin virus was far less severe than expected, we hypothesized cellular immunity to cross-conserved T cell epitopes might have played a significant role in protecting against the pandemic H1N1 in the absence of cross-reactive humoral immunity. In a published study, we used an immunoinformatics approach to predict a number of CD4(+) T cell epitopes are conserved between the 2008-2009 seasonal H1NI vaccine strain and pandemic HI NI (A/California/04/2009) hemagglutinin proteins. Here, we provide results from biological studies using PBMCs from human donors not exposed to the pandemic virus to demonstrate that pre-existing CD4(+) T cells can elicit cross-reactive effector responses against the pandemic H1N1 virus. As well, we show our computational tools were 80-90% accurate in predicting CD4(+) T cell epitopes and their HLA-DRB1-dependent response profiles in donors that were chosen at random for HLA haplotype. Combined, these results confirm the power of coupling immunoinformatics to define broadly reactive CD4(+) T cell epitopes with highly sensitive in vitro biological assays to verify these in silico predictions as a means to understand human cellular immunity, including cross-protective responses, and to define CD4(+) T cell epitopes for potential vaccination efforts against future influenza viruses and other pathogens. (C) 2011 Elsevier Ltd. All rights reserved.

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