. doi: 10.1016/j.virs.2023.05.008
Citation: Mi Liu, Jingze Liu, Wenjun Song, Yousong Peng, Xiao Ding, Lizong Deng, Taijiao Jiang. Development of PREDAC-H1pdm to model the antigenic evolution of influenza A/(H1N1) pdm09 viruses .VIROLOGICA SINICA, 2023, 38(4) : 541-548.  http://dx.doi.org/10.1016/j.virs.2023.05.008

开发PREDAC-H1pdm模型以模拟流感A/H1N1 pdm09病毒的抗原进化

  • 流感A(H1N1)pdm09病毒在2009年引发了全球性大流行,此后一直在季节性流行。由于该病毒血凝素的持续基因进化导致抗原漂移,迫切需要快速识别抗原变异体并对抗原演化进行表征。在本研究中,我们开发了PREDAC-H1pdm模型,用于预测H1N1pdm病毒之间的抗原关系,并识别2009年后流行的H1N1株系的抗原簇。我们的模型在预测抗原变异体方面表现良好,有助于流感监测。通过绘制H1N1pdm的抗原簇,我们发现Sa抗原表位上的替代常见于H1N1pdm,而对于之前的季节性H1N1,Sb抗原表位上的替代更常见。此外,H1N1pdm的局部流行模式比之前的季节性H1N1更明显,这可能使疫苗推荐更加复杂。总的来说,我们开发的抗原关系预测模型为快速确定抗原变异体提供了一种方法,并进一步地分析了进化和流行特征,可以促进H1N1pdm的疫苗推荐和流感监测。

Development of PREDAC-H1pdm to model the antigenic evolution of influenza A/(H1N1) pdm09 viruses

  • 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.

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    Development of PREDAC-H1pdm to model the antigenic evolution of influenza A/(H1N1) pdm09 viruses

      Corresponding author: Taijiao Jiang, jiang_taijiao@gzlab.ac.cn
    • a. Jiangsu Institute of Clinical Immunology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China;
    • b. Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China;
    • c. Suzhou Institute of Systems Medicine, Suzhou, 215123, China;
    • d. Guangzhou Laboratory, Guangzhou, 510005, China;
    • e. Bioinformatics Center, College of Biology, Hunan Provincial Key Laboratory of Medical Virology, Hunan University, Changsha, 410082, China;
    • f. State Key Laboratory of Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, 510120, China

    Abstract: 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.

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