突变
抗原漂移
系统发育树
生物
计算生物学
血凝素(流感)
甲型流感病毒
遗传学
突变率
表位
病毒
基因
抗原
作者
Zhen Xia,Gulei Jin,Jun Zhu,Ruhong Zhou
出处
期刊:Bioinformatics
[Oxford University Press]
日期:2009-08-25
卷期号:25 (18): 2309-2317
被引量:31
标识
DOI:10.1093/bioinformatics/btp423
摘要
Abstract Motivation: Mapping the antigenic and genetic evolution pathways of influenza A is of critical importance in the vaccine development and drug design of influenza virus. In this article, we have analyzed more than 4000 A/H3N2 hemagglutinin (HA) sequences from 1968 to 2008 to model the evolutionary path of the influenza virus, which allows us to predict its future potential drifts with specific mutations. Results: The mutual information (MI) method was used to design a site transition network (STN) for each amino acid site in the A/H3N2 HA sequence. The STN network indicates that most of the dynamic interactions are positioned around the epitopes and the receptor binding domain regions, with strong preferences in both the mutation sites and amino acid types being mutated to. The network also shows that antigenic changes accumulate over time, with occasional large changes due to multiple co-occurring mutations at antigenic sites. Furthermore, the cluster analysis by subdividing the STN into several subnetworks reveals a more detailed view about the features of the antigenic change: the characteristic inner sites and the connecting inter-subnetwork sites are both responsible for the drifts. A novel five-step prediction algorithm based on the STN shows a reasonable accuracy in reproducing historical HA mutations. For example, our method can reproduce the 2003–2004 A/H3N2 mutations with ∼70% accuracy. The method also predicts seven possible mutations for the next antigenic drift in the coming 2009–2010 season. The STN approach also agrees well with the phylogenetic tree and antigenic maps based on HA inhibition assays. Availability: All code and data are available at http://ibi.zju.edu.cn/birdflu/ Contact: ruhongz@us.ibm.com Supplementary information: Supplementary data are available at Bioinformatics online.
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