Dominant substitutions underlying the antigenic evolution of H5 influenza virus

Highly pathogenic avian influenza (HPAI) H5 viruses have recently been documented in mammals including humans, posing a major threat to global public health. To prevent a potential H5 pandemic, it is critical to elucidate the antigenic evolutionary pattern and identify key drivers underlying its evolution. In this work, we construct a comprehensive antigenic map of H5 influenza viruses spanning their evolutionary history and classified three antigenic clusters with no cross-neutralization. The first corresponds to ancestral clades, the second to 2.3.4.4* clades being predominant since 2010, and the third to 2.3.4.4 h clade. Despite the gradually increasing genetic distances from ancestral to 2.3.4.4* to 2.3.4.4 h, their antigenic evolution does not follow the same progressive pattern: the antigenic distance between 2.3.4.4 h and ancestral is smaller than that between 2.3.4.4* and ancestral. This divergence is associated with two distinct mutation patterns at six key amino acid positions: (1) persistent mutations at positions 88 (N > R > S), 199 (D > N > S), and 205 (K > N > D), and (2) reversible mutations at positions 131 (Q > L > Q), 139 (S > P > S), and 289 (N > H > N). These findings not only reveal the antigenic evolution mechanism of H5 influenza, but also provide important guidance for vaccine strain selection and broad-spectrum vaccine development.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2025-11-28
DOI
https://doi.org/10.1038/s41467-025-65730-y
Primary Topic
Influenza Virus Research Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dominant substitutions underlying the antigenic evolution of H5 influenza virus

Youchun Wang, Xiaofan Ding, Zichen Li, Aiping Wu et al.
Nature Communications
Influenza Virus Research Studies
article

Dominant substitutions underlying the antigenic evolution of H5 influenza virus

Youchun Wang, Xiaofan Ding, Zichen Li, Aiping Wu, Jincheng Tong, Qianjun He, Weijin Huang, Cheng Bian, Mingjie Zhang, Qianqian Li, Huan Li, Jiamin Chen, Luyao Qin, R. Bi, Jingze Liu, Yun Ma
article en

Abstract

Highly pathogenic avian influenza (HPAI) H5 viruses have recently been documented in mammals including humans, posing a major threat to global public health. To prevent a potential H5 pandemic, it is critical to elucidate the antigenic evolutionary pattern and identify key drivers underlying its evolution. In this work, we construct a comprehensive antigenic map of H5 influenza viruses spanning their evolutionary history and classified three antigenic clusters with no cross-neutralization. The first corresponds to ancestral clades, the second to 2.3.4.4* clades being predominant since 2010, and the third to 2.3.4.4 h clade. Despite the gradually increasing genetic distances from ancestral to 2.3.4.4* to 2.3.4.4 h, their antigenic evolution does not follow the same progressive pattern: the antigenic distance between 2.3.4.4 h and ancestral is smaller than that between 2.3.4.4* and ancestral. This divergence is associated with two distinct mutation patterns at six key amino acid positions: (1) persistent mutations at positions 88 (N > R > S), 199 (D > N > S), and 205 (K > N > D), and (2) reversible mutations at positions 131 (Q > L > Q), 139 (S > P > S), and 289 (N > H > N). These findings not only reveal the antigenic evolution mechanism of H5 influenza, but also provide important guidance for vaccine strain selection and broad-spectrum vaccine development.

Nature CommunicationsVol. 16(1)
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Ministry of Education (RO), Suzhou Institute of Systems Medicine (CN), National Institutes for Food and Drug Control (CN)
Chinese Academy of Medical Sciences
Openalex Percentile: Top 51%
Influenza Virus Research Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.