Preexisting human antibodies neutralize recently emerged H7N9 influenza strains

Carole J.Henry Dunand, Paul E. Leon, Kaval Kaur, Gene S. Tan, Nai Ying Zheng, Sarah Andrews, Min Huang, Xinyan Qu, Yunping Huang, Marlene Salgado-Ferrer, Irvin Y. Ho, William Taylor, Rong Hai, Jens Wrammert, Rafi Ahmed, Adolfo García-Sastre, Peter Palese, Florian Krammer, Patrick C. Wilson

Research output: Contribution to journalArticlepeer-review

109 Scopus citations

Abstract

The emergence and seasonal persistence of pathogenic H7N9 influenza viruses in China have raised concerns about the pandemic potential of this strain, which, if realized, would have a substantial effect on global health and economies. H7N9 viruses are able to bind to human sialic acid receptors and are also able to develop resistance to neuraminidase inhibitors without a loss in fitness. It is not clear whether prior exposure to circulating human influenza viruses or influenza vaccination confers immunity to H7N9 strains. Here, we demonstrate that 3 of 83 H3 HA-reactive monoclonal antibodies generated by individuals that had previously undergone influenza A virus vaccination were able to neutralize H7N9 viruses and protect mice against homologous challenge. The H7N9-neutralizing antibodies bound to the HA stalk domain but exhibited a difference in their breadth of reactivity to different H7 influenza subtypes. Mapping viral escape mutations suggested that these antibodies bind at least two different epitopes on the stalk region. Together, these results indicate that these broadly neutralizing antibodies may contribute to the development of therapies against H7N9 strains and may also be effective against pathogenic H7 strains that emerge in the future.

Original languageEnglish
Pages (from-to)1255-1268
Number of pages14
JournalJournal of Clinical Investigation
Volume125
Issue number3
DOIs
StatePublished - 2 Mar 2015

Fingerprint

Dive into the research topics of 'Preexisting human antibodies neutralize recently emerged H7N9 influenza strains'. Together they form a unique fingerprint.

Cite this