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Monitoring Influenza Virus Survival Outside the Host Using Real-Time Cell Analysis
Published on: February 20, 2021
Networks of genomic co-occurrence capture characteristics of human influenza A (H3N2) evolution
Xiangjun Du1, Zhuo Wang, Aiping Wu
1National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.
Abstract:
The recent availability of full genomic sequence data for a large number of human influenza A (H3N2) virus isolates over many years provides us an opportunity to analyze human influenza virus evolution by considering all gene segments simultaneously. However, such analysis requires development of new computational models that can capture the complex evolutionary features over the entire genome. By analyzing nucleotide co-occurrence over the entire genome of human H3N2 viruses, we have developed a network model to describe H3N2 virus evolutionary patterns and dynamics. The network model effectively captures the evolutionary antigenic features of H3N2 virus at the whole-genome level and accurately describes the complex evolutionary patterns between individual gene segments. Our analyses show that the co-occurring nucleotide modules apparently underpin the dynamics of human H3N2 evolution and that amino acid substitutions corresponding to nucleotide co-changes cluster preferentially in known antigenic regions of the viral HA. Therefore, our study demonstrates that nucleotide co-occurrence networks represent a powerful method for tracking influenza A virus evolution and that cooperative genomic interaction is a major force underlying influenza virus evolution.
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