Novel Strategy May Improve Seasonal Flu Vaccine Effectiveness

Method Helps Predict Which Flu Strains Will Become Widespread

May 23, 2016

New findings describe a novel strategy for predicting how circulating influenza viruses will evolve, an approach that may help scientists create better seasonal influenza vaccines. The findings, which appear in the journal Nature Microbiology, were conducted by scientists affiliated with the Centers of Excellence for Influenza Research and Surveillance (CEIRS) program of the National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health (NIH).

The seasonal influenza vaccine must be updated each year because flu viruses mutate. The changes in globally circulating flu strains are monitored each season and these data are used to predict which strains will be most prevalent during the next flu season. The seasonal flu vaccine is designed to protect against the three or four predicted dominant strains. However, sometimes an unexpected or an entirely new strain predominates, or emerges too late to be included in the vaccine. This happened during the 2014-2015 flu season, and that season’s flu vaccine was less than 20 percent effective at protecting against influenza infection.

In a laboratory study led by CEIRS investigator Yoshihiro Kawaoka, Ph.D., and his colleagues at the University of Wisconsin-Madison School of Veterinary Medicine Influenza Research Institute, researchers developed a strategy to predict flu mutations before they occur in nature by simulating the changes in the lab. The scientists obtained samples of naturally occurring human H1N1 and H3N2 flu viruses from the 2009-2010 and the 2012-2013 flu seasons, respectively. They inserted random mutations in the viruses’ genetic material and then mixed the mutated viruses with antibodies against circulating flu viruses. Some of the strains had sufficiently mutated such that they replicated despite the presence of the antibodies, and continued replicated and mutating. If this occurred in natural infection, vaccinated individuals with antibodies to the vaccine strain could still be infected by the mutated strains.

The scientists then mapped the mutational patterns with a process called antigenic cartography. The mapping revealed clusters of viruses with unique mutations that matched how H1N1 viruses in the 2009-2010 and H3N2 in the 2014-2015 flu seasons actually evolved in nature. Studies in mice and ferrets immunized against naturally occurring H1N1 influenza confirmed that the mutated viruses developed in the lab avoided detection by the immune system and thus may have the potential to emerge as the next seasonal strain. This laboratory-based method of predicting how current influenza virus strains will mutate could be used to help choose the influenza strains in the seasonal flu vaccine, according to the researchers.

C Li et al. Selection of antigenically advanced variants of seasonal influenza viruses. Nature Microbiology DOI: 10.1038/NMICROBIOL.2016.58 (2016).

NIAID Director Anthony S. Fauci, M.D., and David Spiro, Ph.D., chief, Influenza, SARS, and Related Viral Respiratory Diseases Section, in NIAID’s Division of Microbiology and Infectious Diseases, are available for comment.


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