title: Large-scale analysis of antigenic diversity of T-cell epitopes in dengue virus.
abstract: BACKGROUND
  Antigenic diversity in dengue virus strains has been studied, but large-scale and detailed systematic analyses have not been reported. In this study, we report a bioinformatics method for analyzing viral antigenic diversity in the context of T-cell mediated immune responses. We applied this method to study the relationship between short-peptide antigenic diversity and protein sequence diversity of dengue virus. We also studied the effects of sequence determinants on viral antigenic diversity. Short peptides, principally 9-mers were studied because they represent the predominant length of binding cores of T-cell epitopes, which are important for formulation of vaccines.
  
  
  RESULTS
  Our analysis showed that the number of unique protein sequences required to represent complete antigenic diversity of short peptides in dengue virus is significantly smaller than that required to represent complete protein sequence diversity. Short-peptide antigenic diversity shows an asymptotic relationship to the number of unique protein sequences, indicating that for large sequence sets (approximately 200) the addition of new protein sequences has marginal effect to increasing antigenic diversity. A near-linear relationship was observed between the extent of antigenic diversity and the length of protein sequences, suggesting that, for the practical purpose of vaccine development, antigenic diversity of short peptides from dengue virus can be represented by short regions of sequences (approximately <100 aa) within viral antigens that are specific targets of immune responses (such as T-cell epitopes specific to particular human leukocyte antigen alleles).
  
  
  CONCLUSIONS
  This study provides evidence that there are limited numbers of antigenic combinations in protein sequence variants of a viral species and that short regions of the viral protein are sufficient to capture antigenic diversity of T-cell epitopes. The approach described herein has direct application to the analysis of other viruses, in particular those that show high diversity and/or rapid evolution, such as influenza A virus and human immunodeficiency virus (HIV).
authors.affiliation: The Division of Biomedical Sciences, Johns Hopkins Singapore, 31 Biopolis Way, #02-01 The Nanos, Singapore 138669, Singapore. g0501159@nus.edu.sg
authors.forename: Asif M
authors.initials: AM
authors.lastname: Khan
authors.forename: A T
authors.initials: AT
authors.lastname: Heiny
authors.forename: Kenneth X
authors.initials: KX
authors.lastname: Lee
authors.forename: K N
authors.initials: KN
authors.lastname: Srinivasan
authors.forename: Tin Wee
authors.initials: TW
authors.lastname: Tan
authors.forename: J Thomas
authors.initials: JT
authors.lastname: August
authors.forename: Vladimir
authors.initials: V
authors.lastname: Brusic
mesh_terms: D000595:Amino Acid Sequence; D000940:Antigenic Variation; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D003716:Dengue Virus / Q000276:immunology*; D018984:Epitopes, T-Lymphocyte / Q000032:analysis*; D008969:Molecular Sequence Data; D010446:Peptide Fragments / Q000276:immunology; D017386:Sequence Homology, Amino Acid; D012703:Serotyping; D014764:Viral Proteins / Q000276:immunology
chemical_list: D018984:Epitopes, T-Lymphocyte; D010446:Peptide Fragments; D014764:Viral Proteins