A Novel Approach to Anticipating Seasonal Flu Strains

A team of researchers led by University of Wisconsin-Madison School of Veterinary Medicine virologist Yoshihiro Kawaoka has described a novel strategy that could soon augment the current process for forecasting the naturally occurring mutations that help seasonal flu virus dodge the vaccine with a more precise approach.

Writing in Nature Microbiology, the researchers said the approach can help predict the antigenic evolution of circulating influenza viruses and give scientists the ability to more precisely anticipate seasonal flu strains, while fostering a closer match for the “vaccine viruses” that are used to create the global vaccine supply.

Although the 2016 influenza vaccine is a substantially stronger match to the circulating seasonal strains of influenza than was achieved during the 2014-2015 flu season—when the poor match between the virus used to make vaccine stocks and the circulating seasonal virus led to a vaccine that was less than 20% effective—the virus has a shifty nature, and picking the viruses used to make global vaccine stocks must be done well before the onset of the flu season. These factors have made vaccine strain selection a shot in the dark.

Using techniques that have been commonly employed in virology for the past three decades enabled Kawaoka, a professor of pathobiological sciences at the University of Wisconsin-Madison and faculty member at the University of Tokyo, and colleagues to assemble the 2014 virus before the onset of the epidemic.

“This is the first demonstration that one can accurately anticipate in the lab future seasonal influenza strains,” explained Kawaoka. “We can identify the mutations that will occur in nature and make those viruses available at the time of vaccine (virus) candidate selection… Influenza viruses randomly mutate. The only way the virus can continue to circulate in humans is by (accumulating) mutations in the hemagglutinin.”

In order to get ahead of the ongoing mutations in circulating flu viruses and provide approaches that may complement the current vaccine strain selection process, Kawaoka and colleagues capitalized on previous pilot studies with past influenza viruses that identified escape mutants that were antigenically similar to variants emerging in nature.

For the current study, they “selected antigenic variants from human H1N1 and H3N2 influenza virus libraries possessing random mutations in the globular head of the haemagglutinin protein (which includes the antigenic sites) by incubating them with human and/or ferret convalescent sera to human H1N1 and H3N2 viruses,” they wrote in Nature Microbiology. The team also “selected antigenic escape variants from human viruses treated with convalescent sera and from mice that had been previously immunized against human influenza viruses.”

The mapping approach used in the study identifies clusters of viruses that feature novel mutations that can effectively predict the molecular characteristics of the upcoming seasonal influenza virus. According to Kawaoka, this prediction could be used to develop more effective vaccine virus stockpiles needed each flu season throughout the world.

“Our method may therefore improve the current WHO influenza vaccine selection process,” Kawaoka and his group concluded. “These in vitro selection studies are highly predictive of the antigenic evolution of H1N1 and H3N2 viruses in human populations.”