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Antigenic Maps of Influenza A(H3N2) Produced With Human Antisera Obtained After Primary Infection.


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Authors

Fonville, Judith M 
Fraaij, Pieter LA 
de Mutsert, Gerrie 
Wilks, Samuel H 
van Beek, Ruud 

Abstract

BACKGROUND: Antigenic characterization of influenza viruses is typically based on hemagglutination inhibition (HI) assay data for viral isolates tested against strain-specific postinfection ferret antisera. Here, similar virus characterizations were performed using serological data from humans with primary influenza A(H3N2) infection. METHODS: We screened sera collected between 1995 and 2011 from children between 9 and 24 months of age for influenza virus antibodies, performed HI tests for the positive sera against 23 influenza viruses isolated between 1989 and 2011, and measured HI titers of antisera against influenza A(H3N2) from 24 ferrets against the same panel of viruses. RESULTS: Of the 17 positive human sera, 6 had a high response, showing HI patterns that would be expected from primary infection antisera, while 11 sera had lower, more dispersed patterns of reactivity that are not easily explained. The antigenic map based on the high-response human HI data was similar to the map created using ferret data. CONCLUSIONS: Although the overall structure of the ferret and human antigenic maps is similar, local differences in virus positions indicate that the human and ferret immune system might see antigenic properties of viruses differently. Further studies are needed to establish the degree of similarity between serological patterns in ferret and human data.

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Keywords

antibody landscapes, antigenic cartography, human antisera, influenza, primary infection, Animals, Antibodies, Viral, Antigens, Viral, Disease Models, Animal, Ferrets, Hemagglutination Inhibition Tests, Humans, Infant, Influenza A Virus, H3N2 Subtype, Influenza, Human, Retrospective Studies

Journal Title

J Infect Dis

Conference Name

Journal ISSN

0022-1899
1537-6613

Volume Title

213

Publisher

Oxford University Press (OUP)
Sponsorship
Medical Research Council (MR/K021885/1)
National Institutes of Health (NIH) (via Mount Sinai School of Medicine (MSSM)) (HHSN272201400008C)
This work was supported by the award of a Fellowship in Biomedical Informatics from the Medical Research Council UK [grant number MR/K021885/1] and a Junior Research Fellowship from Homerton College Cambridge to J.M.F.; a Medical Research Council UK studentship [number MR/K50127X/1 to S.H.W.]; the EU FP7 project PREPARE [grant number 602525 to P.L.A.F.]; the National Institute of Allergy and Infectious Diseases, National Institutes of Health [contract number HHSN272201400008C to R.A.M.F and the Center for Pathogen Evolution]; and the EU grant FLUNIVAC [grant number 602604 to G.F.R.].