The Influenza A(H1N1)pdm09 virus caused a global pandemic in 2009 and has circulated seasonally ever since.As the continual genetic evolution of hemagglutinin in this virus leads to antigenic drift,rapid identificatio...The Influenza A(H1N1)pdm09 virus caused a global pandemic in 2009 and has circulated seasonally ever since.As the continual genetic evolution of hemagglutinin in this virus leads to antigenic drift,rapid identification of antigenic variants and characterization of the antigenic evolution are needed.In this study,we developed PREDAC-H1pdm,a model to predict antigenic relationships between H1N1pdm viruses and identify antigenic clusters for post-2009 pandemic H1N1 strains.Our model performed well in predicting antigenic variants,which was helpful in influenza surveillance.By mapping the antigenic clusters for H1N1pdm,we found that substitutions on the Sa epitope were common for H1N1pdm,whereas for the former seasonal H1N1,substitutions on the Sb epitope were more common in antigenic evolution.Additionally,the localized epidemic pattern of H1N1pdm was more obvious than that of the former seasonal H1N1,which could make vaccine recommendation more sophisticated.Overall,the antigenic relationship prediction model we developed provides a rapid determination method for identifying antigenic variants,and the further analysis of evolutionary and epidemic characteristics can facilitate vaccine recommendations and influenza surveillance for H1N1pdm.展开更多
基金funded by the National Natural Science Foundation of China (32070678)the National Key Research and Development Program of China (2021YFC2302001).
文摘The Influenza A(H1N1)pdm09 virus caused a global pandemic in 2009 and has circulated seasonally ever since.As the continual genetic evolution of hemagglutinin in this virus leads to antigenic drift,rapid identification of antigenic variants and characterization of the antigenic evolution are needed.In this study,we developed PREDAC-H1pdm,a model to predict antigenic relationships between H1N1pdm viruses and identify antigenic clusters for post-2009 pandemic H1N1 strains.Our model performed well in predicting antigenic variants,which was helpful in influenza surveillance.By mapping the antigenic clusters for H1N1pdm,we found that substitutions on the Sa epitope were common for H1N1pdm,whereas for the former seasonal H1N1,substitutions on the Sb epitope were more common in antigenic evolution.Additionally,the localized epidemic pattern of H1N1pdm was more obvious than that of the former seasonal H1N1,which could make vaccine recommendation more sophisticated.Overall,the antigenic relationship prediction model we developed provides a rapid determination method for identifying antigenic variants,and the further analysis of evolutionary and epidemic characteristics can facilitate vaccine recommendations and influenza surveillance for H1N1pdm.
