Article

Using a mutual information-based site transition network to map the genetic evolution of influenza A/H3N2 virus.

Institute of Bioinformatics, Zhejiang University, Hangzhou, PR China.
Bioinformatics (impact factor: 5.47). 09/2009; 25(18):2309-17. DOI:10.1093/bioinformatics/btp423 pp.2309-17
Source: PubMed

ABSTRACT 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.
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 approximately 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.
All code and data are available at http://ibi.zju.edu.cn/birdflu/.

0 0
 · 
0 Bookmarks
 · 
40 Views
  • Source
    Article: Inference of genotype-phenotype relationships in the antigenic evolution of human influenza A (H3N2) viruses.
    Lars Steinbrück, Alice Carolyn McHardy
    [show abstract] [hide abstract]
    ABSTRACT: Distinguishing mutations that determine an organism's phenotype from (near-) neutral 'hitchhikers' is a fundamental challenge in genome research, and is relevant for numerous medical and biotechnological applications. For human influenza viruses, recognizing changes in the antigenic phenotype and a strains' capability to evade pre-existing host immunity is important for the production of efficient vaccines. We have developed a method for inferring 'antigenic trees' for the major viral surface protein hemagglutinin. In the antigenic tree, antigenic weights are assigned to all tree branches, which allows us to resolve the antigenic impact of the associated amino acid changes. Our technique predicted antigenic distances with comparable accuracy to antigenic cartography. Additionally, it identified both known and novel sites, and amino acid changes with antigenic impact in the evolution of influenza A (H3N2) viruses from 1968 to 2003. The technique can also be applied for inference of 'phenotype trees' and genotype-phenotype relationships from other types of pairwise phenotype distances.
    PLoS Computational Biology 04/2012; 8(4):e1002492. · 5.22 Impact Factor
  • Source
    Article: Allele dynamics plots for the study of evolutionary dynamics in viral populations.
    Lars Steinbrück, Alice Carolyn McHardy
    [show abstract] [hide abstract]
    ABSTRACT: Phylodynamic techniques combine epidemiological and genetic information to analyze the evolutionary and spatiotemporal dynamics of rapidly evolving pathogens, such as influenza A or human immunodeficiency viruses. We introduce 'allele dynamics plots' (AD plots) as a method for visualizing the evolutionary dynamics of a gene in a population. Using AD plots, we propose how to identify the alleles that are likely to be subject to directional selection. We analyze the method's merits with a detailed study of the evolutionary dynamics of seasonal influenza A viruses. AD plots for the major surface protein of seasonal influenza A (H3N2) and the 2009 swine-origin influenza A (H1N1) viruses show the succession of substitutions that became fixed in the evolution of the two viral populations. They also allow the early identification of those viral strains that later rise to predominance, which is important for the problem of vaccine strain selection. In summary, we describe a technique that reveals the evolutionary dynamics of a rapidly evolving population and allows us to identify alleles and associated genetic changes that might be under directional selection. The method can be applied for the study of influenza A viruses and other rapidly evolving species or viruses.
    Nucleic Acids Research 10/2010; 39(1):e4. · 8.03 Impact Factor
  • Source
    Article: Mapping of H3N2 influenza antigenic evolution in China reveals a strategy for vaccine strain recommendation.
    Xiangjun Du, Libo Dong, Yu Lan, Yousong Peng, Aiping Wu, Ye Zhang, Weijuan Huang, Dayan Wang, Min Wang, Yuanji Guo, Yuelong Shu, Taijiao Jiang
    [show abstract] [hide abstract]
    ABSTRACT: One of the primary efforts in influenza vaccine strain recommendation is to monitor through gene sequencing the viral surface protein haemagglutinin (HA) variants that lead to viral antigenic changes. Here we have developed a computational method, denoted as PREDAC, to predict antigenic clusters of influenza A (H3N2) viruses with high accuracy from viral HA sequences. Application of PREDAC to large-scale HA sequence data of H3N2 viruses isolated from diverse regions of Mainland China identified 17 antigenic clusters that have dominated for at least one season between 1968 and 2010. By tracking the dynamics of the dominant antigenic clusters, we not only find that dominant antigenic clusters change more frequently in China than in the United States/Europe, but also characterize the antigenic patterns of seasonal H3N2 viruses within China. Furthermore, we demonstrate that the coupling of large-scale HA sequencing with PREDAC can significantly improve vaccine strain recommendation for China.
    Nature Communications 01/2012; 3:709. · 7.40 Impact Factor

Show more

Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.

Keywords

antigenic change
 
antigenic changes
 
antigenic sites
 
characteristic inner sites
 
connecting inter-subnetwork sites
 
critical importance
 
detailed view
 
drug design
 
evolutionary path
 
future potential drifts
 
genetic evolution pathways
 
multiple co-occurring mutations
 
mutation sites
 
next antigenic drift
 
novel five-step prediction algorithm
 
occasional large changes
 
possible mutations
 
site transition network
 
specific mutations
 
STN network