Title
Co-evolution positions and rules for antigenic variants of human influenza A/H3N2 viruses.
Abstract
In pandemic and epidemic forms, avian and human influenza viruses often cause significant damage to human society and economics. Gradually accumulated mutations on hemagglutinin (HA) cause immunologically distinct circulating strains, which lead to the antigenic drift (named as antigenic variants). The "antigenic variants" often requires a new vaccine to be formulated before each annual epidemic. Mapping the genetic evolution to the antigenic drift of influenza viruses is an emergent issue to public health and vaccine developmentWe developed a method for identifying antigenic critical amino acid positions, rules, and co-mutated positions for antigenic variants. The information gain (IG) and the entropy are used to measure the score of an amino acid position on hemagglutinin (HA) for discriminating between antigenic variants and similar viruses. A position with high IG and entropy implied that this position is highly correlated to an antigenic drift. Nineteen positions with high IG and high genetic diversity are identified as antigenic critical positions on the HA proteins. Most of these antigenic critical positions are located on five epitopes or on the surface based on the HA structure. Based on IG values and entropies of these 19 positions on the HA, the decision tree was applied to create a rule-based model and to identify rules for predicting antigenic variants of a given two HA sequences which are often a vaccine strain and a circulating strain. The predicting accuracies of this model on two sets, which consist of a training set (181 hemagglutination inhibition (HI) assays) and an independent test set (31,878 HI assays), are 91.2% and 96.2% respectively.Our method is able to identify critical positions, rules, and co-mutated positions on HA for predicting the antigenic variants. The information gains and the entropies of HA positions provide insight to the antigenic drift and co-evolution positions for influenza seasons. We believe that our method is robust and is potential useful for studying influenza virus evolution and vaccine development.
Year
DOI
Venue
2009
10.1186/1471-2105-10-S1-S41
BMC Bioinformatics
Keywords
Field
DocType
seasonality,antigenic variation,information gain,microarrays,amino acid,bioinformatics,genetics,rule based,public health,genetic diversity,decision tree,hemagglutination inhibition,algorithms
Biology,Evolution of influenza,H5N1 genetic structure,Hemagglutinin (influenza),Antigenic drift,Antigenic shift,Genetics,Influenza A virus,Virology,Antigenic variation,Original antigenic sin
Journal
Volume
Issue
ISSN
10 Suppl 1
S-1
1471-2105
Citations 
PageRank 
References 
24
1.42
0
Authors
3
Name
Order
Citations
PageRank
Jhang-Wei Huang1362.54
Chwan-Chuen King2413.64
Jinn-moon Yang336435.89