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
Introduction:Human influenza A/H3N2 imposes a substantial global disease burden.Beyond hemagglutinin(HA),neuraminidase(NA)also plays a critical role in the antigenic evolution of influenza viruses.However,a comprehens...Introduction:Human influenza A/H3N2 imposes a substantial global disease burden.Beyond hemagglutinin(HA),neuraminidase(NA)also plays a critical role in the antigenic evolution of influenza viruses.However,a comprehensive understanding of NA antigenic evolution remains lacking.Methods:NA inhibition(NAI)data were collected and structural epitopes for A/H3N2 NA were identified.A machine learning model was developed to accurately predict antigenic relationships by integrating four feature groups:epitopes,physicochemical properties,N-glycosylation,and catalytic sites.An antigenic correlation network(ACNet)was constructed and antigenic clusters were identified using the Markov clustering algorithm.Results:The best random forest model(PREDEC-N2)achieved an accuracy of 0.904 in crossvalidation and 0.867 in independent testing.Eight main antigenic clusters were identified on the ACNet.Spatiotemporal analysis revealed the continuous replacement and rapid global spread of new antigenic clusters for human influenza A/H3N2 NA.Conclusions:This study developed a timely and accurate computational model to map the antigenic landscape of A/H3N2 NA,revealing both its relative antigenic conservation and continuous evolution.These insights provide valuable guidance for improved antigenic surveillance,vaccine recommendations,and prevention and control strategies for human influenza viruses.展开更多
The human influenza A （H3N2） virus dominated the 2014-2015 winter season in many countries and caused massive morbid- ity and mortality because of its antigenic variation. So far, very little is known about the anti...The human influenza A （H3N2） virus dominated the 2014-2015 winter season in many countries and caused massive morbid- ity and mortality because of its antigenic variation. So far, very little is known about the antigenic patterns of the recent H3N2 virus. By systematically mapping the antigenic relationships of H3N2 strains isolated since 2010, we discovered that two groups with obvious antigenic divergence, named SW13 （A/Switzerland/9715293/2013-1ike strains） and HK14 （A/Hong Kong/5738/2014-1ike strains）, co-circulated during the 2014-2015 winter season. HK14 group co-circulated with SW13 in Europe and the United States during this season, while there were few strains of HK14 in China's Mainland, where SW13 has dominated since 2012. Furthermore, we found that substitutions near the receptor-binding site on hemagglutinin played an im- portant role in the antigenic variation of both the groups. These findings provide a comprehensive understanding of the recent antigenic evolution of H3N2 virus and will aid in the selection of vaccine strains.展开更多
Influenza virus can rapidly change its antigenicity, via mutation in the hemagglutinin(HA) protein, to evade host immunity. The emergence of the novel human-infecting avian H7N9 virus in China has caused widespread co...Influenza virus can rapidly change its antigenicity, via mutation in the hemagglutinin(HA) protein, to evade host immunity. The emergence of the novel human-infecting avian H7N9 virus in China has caused widespread concern. However, evolution of the antigenicity of this virus is not well understood. Here, we inferred the antigenic epitopes of the HA protein from all H7 viruses, based on the five well-characterized HA epitopes of the human H3N2 virus. By comparing the two major H7 phylogenetic lineages, i.e., the Eurasian lineage and the North American lineage, we found that epitopes A and B are more frequently mutated in the Eurasian lineage, while epitopes B and C are more frequently mutated in the North American lineage. Furthermore, we found that the novel H7N9 virus(derived from the Eurasian lineage) isolated in China in the year 2013, contains six frequently mutated sites on epitopes that include site 135, which is located in the receptor binding domain. This indicates that the novel H7N9 virus that infects human may already have been subjected to gradual immune pressure and receptor-binding variation. Our results not only provide insights into the antigenic evolution of the H7 virus but may also help in the selection of suitable vaccine strains.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.
基金Supported by the National Key Research and Development Program under grant 2022YFC2303800the Major Program of Guangzhou National Laboratory under grant GZNL2024A01002+2 种基金the National Natural Science Foundation of China under grant 81961128002the Science and Technology Planning Project of Guangdong Province,China under grant 2021B1212040017the Shenzhen Science and Technology Program under grant ZDSYS20230626091203007.
文摘Introduction:Human influenza A/H3N2 imposes a substantial global disease burden.Beyond hemagglutinin(HA),neuraminidase(NA)also plays a critical role in the antigenic evolution of influenza viruses.However,a comprehensive understanding of NA antigenic evolution remains lacking.Methods:NA inhibition(NAI)data were collected and structural epitopes for A/H3N2 NA were identified.A machine learning model was developed to accurately predict antigenic relationships by integrating four feature groups:epitopes,physicochemical properties,N-glycosylation,and catalytic sites.An antigenic correlation network(ACNet)was constructed and antigenic clusters were identified using the Markov clustering algorithm.Results:The best random forest model(PREDEC-N2)achieved an accuracy of 0.904 in crossvalidation and 0.867 in independent testing.Eight main antigenic clusters were identified on the ACNet.Spatiotemporal analysis revealed the continuous replacement and rapid global spread of new antigenic clusters for human influenza A/H3N2 NA.Conclusions:This study developed a timely and accurate computational model to map the antigenic landscape of A/H3N2 NA,revealing both its relative antigenic conservation and continuous evolution.These insights provide valuable guidance for improved antigenic surveillance,vaccine recommendations,and prevention and control strategies for human influenza viruses.
基金supported by the National Basic Research Program of China(2015CB910501)the Major National Earmark Project for Infectious Diseases(2014ZX10004002-001)+1 种基金the Key Research Program of the Chinese Academy of Sciences(KJZD-EW-L09-1-2)to Jiang Tai Jiaothe National Natural Science Foundation of China(31470273)to Wu Ai Ping
文摘The human influenza A （H3N2） virus dominated the 2014-2015 winter season in many countries and caused massive morbid- ity and mortality because of its antigenic variation. So far, very little is known about the antigenic patterns of the recent H3N2 virus. By systematically mapping the antigenic relationships of H3N2 strains isolated since 2010, we discovered that two groups with obvious antigenic divergence, named SW13 （A/Switzerland/9715293/2013-1ike strains） and HK14 （A/Hong Kong/5738/2014-1ike strains）, co-circulated during the 2014-2015 winter season. HK14 group co-circulated with SW13 in Europe and the United States during this season, while there were few strains of HK14 in China's Mainland, where SW13 has dominated since 2012. Furthermore, we found that substitutions near the receptor-binding site on hemagglutinin played an im- portant role in the antigenic variation of both the groups. These findings provide a comprehensive understanding of the recent antigenic evolution of H3N2 virus and will aid in the selection of vaccine strains.
基金supported by the National Basic Research Program of China(2015CB910501)the Major National Earmark Project for Infectious Diseases(2014ZX10004002-001)+1 种基金the Key Research Program of the Chinese Academy of Sciences(KJZD-EW-L09-1-2)to Jiang Tai Jiaothe National Natural Science Foundation of China(31470273)to Wu Ai Ping
文摘Influenza virus can rapidly change its antigenicity, via mutation in the hemagglutinin(HA) protein, to evade host immunity. The emergence of the novel human-infecting avian H7N9 virus in China has caused widespread concern. However, evolution of the antigenicity of this virus is not well understood. Here, we inferred the antigenic epitopes of the HA protein from all H7 viruses, based on the five well-characterized HA epitopes of the human H3N2 virus. By comparing the two major H7 phylogenetic lineages, i.e., the Eurasian lineage and the North American lineage, we found that epitopes A and B are more frequently mutated in the Eurasian lineage, while epitopes B and C are more frequently mutated in the North American lineage. Furthermore, we found that the novel H7N9 virus(derived from the Eurasian lineage) isolated in China in the year 2013, contains six frequently mutated sites on epitopes that include site 135, which is located in the receptor binding domain. This indicates that the novel H7N9 virus that infects human may already have been subjected to gradual immune pressure and receptor-binding variation. Our results not only provide insights into the antigenic evolution of the H7 virus but may also help in the selection of suitable vaccine strains.
