Volume 7 Supplement 5
Large-scale analysis of antigenic diversity of T-cell epitopes in dengue virus
© Khan et al; licensee BioMed Central Ltd 2006
Published: 18 December 2006
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.
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 (~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 (~<100 aa) within viral antigens that are specific targets of immune responses (such as T-cell epitopes specific to particular human leukocyte antigen alleles).
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).
Dengue virus has four serotypes (DV1, DV2, DV3 and DV4) that show substantial genetic diversity both within and between serotypes. Sequence comparison studies showed 30–40% difference in amino acid sequences between serotypes [1, 2]. The amino acid differences within each serotype are lower but the observed intra-serotype diversity is sufficiently large to warrant the definition of clusters of dengue virus variants [3, 4]. Studies of genetic diversity have focused on clade diversity and replacement , mutation spectra , conserved regions  and implications for clinical manifestations . Several studies have focused on the analysis of antigenic diversity (diversity of targets of immune responses in protein sequences) of dengue virus; these studies focussed on experimental mapping of antibody recognition sites [7–11] and T-cell epitopes [2, 12–15] and subsequent analysis of their diversity. Recently, Simmons et al.  analyzed the T cell responses of individuals infected with DV2 by ELISpot assay and identified 34 peptides of several dengue proteins as potential novel T-cell epitopes.
Generally, there is a correspondence between genetic and antigenic evolution of viruses, but genetic changes may result in disproportionately large antigenic changes [16, 17]. While genetic and antigenic diversity in dengue virus strains had become evident , large-scale and detailed systematic analyses that explore their relationship have not been reported. Understanding this relationship is important for the study of vaccine development, especially in rapidly mutating viruses. In this paper, we will focus on protein sequence diversity, and thus consider only genetic variations that affect the protein sequences.
Biological studies of antigenic diversity require great experimental effort, even for a single viral protein. Consequently, most research groups focus on studying small number of viral sequences. Rapid accumulation of sequence data from both classical and genomic/proteomic approaches makes the experimental studying of antigenic diversity difficult and time-consuming. A bioinformatics approach is necessary to support large-scale antigenic analysis of viral diversity, which can complement laboratory experiments.
In this study, we have developed a bioinformatics method to analyze antigenic diversity in the context of T-cell mediated immune responses. We studied antigenic diversity of more than 9000 dengue virus protein sequences reported in the NCBI Entrez protein database . The study aimed to identify a minimal set of sequences that encodes the complete antigenic diversity of short peptides from all known sequences in dengue virus serotypes. Short peptides, principally 9-mers were studied because they represent the predominant length of binding cores of T-cell epitopes. We analysed the relationship between short-peptide antigenic diversity and protein sequence diversity of dengue virus; the analysis was performed at two time points to help understand the effects of the accumulation of sequence data to the relationship. We have also analyzed the effects of sequence determinants on antigenic diversity of short peptides. This study provides a framework for large-scale, systematic analysis of antigenic diversity for the protein sequences of any virus. We did not analyze B-cell epitope antigenic diversity because of their complex conformational nature. Although linear B-cell epitopes exist and our method can be used to study them, very often, they also show conformational preferences and dependence on the context of a protein antigen . Further, only approximately 10% of B-cell epitopes from native proteins are linear .
Dengue serotype protein datasets
Collected and unique protein sequences for each dengue serotype in 2004 and 2005 and the corresponding increase in data between the two time points.
Data retrieved in 2004 (#)
Data retrieved in 2005 (#)
Proteins of a representative dengue virus serotype 2 polyprotein entry (P14340 of 3391 amino acids) in the NCBI Entrez protein database.
Length (amino acids)
Precursor membrane (pM)
Nonstructural protein 1 (NS1)
Nonstructural protein 2a (NS2a)
Nonstructural protein 2b (NS2b)
Nonstructural protein 3 (NS3)
Nonstructural protein 4a (NS4a)
Nonstructural protein 4b (NS4b)
Nonstructural protein 5 (NS5)
Unique sequences for the proteins of the four serotypes in 2004 and 2005.
No. of unique sequences (all four serotypes)
Intra- and inter-serotype amino acid sequence identities of dengue proteins
Minimum and maximum percentage sequence identity range for each dengue protein, intra- and inter-serotype.
The intra-serotype percentage sequence identity was between 92% and 99%, except for C, pM, E and NS1 of DV2, which showed minimum sequence identities ranging from 79% to 89%. In contrast, the average inter-serotype percentage sequence identity was in the range of 60–79%, except for NS2a. The NS3, NS4b and NS5 proteins are highly conserved across the serotypes, with average sequence identities in the range of 77–79%, probably because of their involvement in forming the RNA replication complex . The NS2a protein is the most diverse across the serotypes (average PSI of 39%), although it is highly conserved within each serotype. The inter-serotype diversity observed for NS2a is comparable to the inter-Flavivirus diversity of the envelope protein, which shows approximately 40% amino acid identity .
Minimal sequence sets representing dengue virus antigenic diversity
Reduction of the number of unique dengue sequences by removal of antigenically redundant sequences.
Data retrieved in 2004
Data retrieved in 2005
Unique sequences (#)
Minimal antigenic set
Unique sequences (#)
Minimal antigenic set
Unique sequences (#)*
Percentage of unique sequences (%)**
Unique sequences (#)*
Percentage of unique sequences (%)**
Characterization and application of sequence variables that affect antigenic diversity
We examined the effects of sequence determinants, such as number and length of sequences, on the short-peptide antigenic diversity of dengue virus. These analyses were carried out using test datasets of different numbers of sequences (20, 40, 60, 80, 100, 120 and 140 sequences) and different lengths (23, 46, 128, 138, 276 and 460 aa) that were randomly selected from a set of DV2 envelope protein sequences with repeated sampling for 20 times. Antigenic diversity analysis of each test dataset was performed to identify a minimal set of sequences that represents the complete short-peptide antigenic diversity for each dataset. These minimal sets were used to analyze the effects of the sequence determinants on antigenic diversity.
Effects of number of sequences on short-peptide antigenic diversity
Effects of number of unique dengue virus serotype 2 (DV2) envelope sequences (N) on short-peptide (9-mer) antigenic diversity.
Number of unique sequences (N)
Length of sequences
Minimal number of unique sequences that represent complete short-peptide antigenic diversity (Mean ± SE)
18 ± 0.30
32 ± 0.54
46 ± 0.70
58 ± 0.87
70 ± 0.87
80 ± 0.87
90 ± 0.71
Percentage of unique sequences that represent complete short-peptide antigenic diversity (%) (Mean ± SE)
90 ± 1.5
80 ± 1.35
77 ± 1.17
73 ± 1.09
70 ± 0.87
67 ± 0.73
64 ± 0.51
Effects of length of sequences on short-peptide antigenic diversity
Effect of length of dengue virus serotype 2 (DV2) envelope protein sequences on short-peptide (9-mer) antigenic diversity.
Length of fragments
100% (460 aa)
60% (276 aa)
30% (138 aa)
20% (92 aa)
10% (46 aa)
5% (23 aa)
Number of fragments
Number of unique fragments
Minimal number of fragments that represent complete short-peptide antigenic diversity (Mean ± SE)
111 ± 0.11
74 ± 0.11
48 ± 0.17
38 ± 0.10
24 ± 0.10
14 ± 0.10
Percentage of fragments that represent complete short-peptide antigenic diversity (%) (Mean ± SE)
59 ± 0.06
40 ± 0.06
26 ± 0.09
20 ± 0.05
13 ± 0.05
7 ± 0.05
In this study, we applied a systematic bioinformatics approach to collect, clean, organize and analyze the antigenic diversity of short peptides in reported protein sequence data of dengue virus. We have developed a computational method for the analysis of antigenic diversity in the context of T-cell mediated immune responses. The method was applied for the analysis of short-peptide antigenic diversity of dengue virus to determine a minimal sequence set that encodes the complete antigenic diversity of linear epitopes within each dengue virus serotype. We studied the relationship between short-peptide antigenic diversity and protein sequence diversity of DV and also explored the effects of sequence determinants on viral antigenic diversity. Our analysis showed that the minimal number of unique sequences required to represent complete antigenic diversity of linear epitopes 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 sequences and linear relationship to the length of protein antigens.
It is clear that antigenic diversity in the reported dengue sequences is large. With many asymptomatic human and animal carriers of dengue viruses representing a huge reservoir for emergence of new strains [6, 24, 28], the diversity is expected to increase, although at a progressively slower pace. This is because antigenic redundancy increases when the number of sequences increases; we observed that when the dataset for a particular protein reaches approximately 200 sequences, the effect of addition of new sequences to increasing antigenic diversity is marginal.
Our study of factors that affect antigenic diversity provided insight into dealing with the increasing T-cell epitope antigenic diversity in the context of vaccine development. Length of sequences had the largest effect on short-peptide antigenic diversity. The asymptotic behaviour of antigenic diversity increase was observed for the increase in the number of sequence variants. For practical purposes of vaccine formulation, antigenic diversity cannot be represented by whole protein sequences because it is not feasible to use these sequences for systematic experimental analysis: they are long and their number is increasing rapidly. The implication is that conventional vaccination strategies, which utilize whole attenuated pathogen with little knowledge of the specificity of immune responses they elicit, may not be suitable for providing protection from multiple variants of viruses. Furthermore, it may be difficult to optimize such vaccine according to the human leukocyte antigen (HLA) profile of the population receiving the vaccine [29, 30], as neither the identities of the HLA molecules that bind T-cell epitopes, nor the epitopes themselves are known.
The more effective vaccine strategy that we propose is to focus on short segments of proteins (~<100 aa) that are known to be specific targets of immune responses (such as T-cell epitopes specific to particular HLA alleles), particularly those that have high concentration of T-cell epitopes . By combining selected sets of short antigen fragments that represent T-cell epitope antigenic diversity, complete sets of viral targets can be covered in a "divide-and-conquer" approach. This may provide a promising basis for multivalent peptide-based vaccines against dengue virus. However, this strategy does not address the dengue virus-specific problem of protection versus immunopathology during secondary infections with a different serotype .
Several caveats need to be considered in a study such as this. First, it is well-known that not all HLA-restricted epitopes are 9-mers . This may impact the interpretation of our results, which were based only on 9-mers, and hence may not give a true representation of dengue T-cell epitope antigenic diversity. We selected 9-mers because they represent the typical size of HLA class I T-cell epitopes, as well as the binding core of HLA class II T-cell epitopes . We performed the same analysis with peptides of 8-mers and 10-mers. The results showed no significant difference as compared to the analysis of 9-mers (data not shown).
The second caveat is the sampling bias in dengue virus sequences reported to the public databases. Only dengue sequences that have been studied are reported, and viruses collected in accessible locations, associated with notable disease outbreaks or of known immunological properties are preferentially studied. Consequently, certain dengue proteins have been studied intensively, while the others remained largely unstudied. For example, sequences of the envelope protein, known to be important for immunological activity and viral entry into host [26, 33], were the most abundant in our dataset (3183 sequences for all four serotypes), while that of NS4a, which is relatively unknown for immunological activity, was under-represented. In addition, for majority of the proteins, a large portion of the reported sequences were incomplete in length. For example, 95% of DV2 NS5 collected sequences were incomplete in length (data not shown). However, the data used in this study was the most representative available and the large sample size for majority of the proteins helps to decrease the margin of error due to sampling bias. In addition, the reported sequences represent highly pathogenic strains isolated during dengue outbreaks.
There has been no significant increase in the number of unique sequences for dengue virus since the last analysis (December 2005). The September 2006 data set contained a total of 2661 (793 DV1, 784 DV2, 759 DV3 and 325 DV4) dengue unique sequences. This was an increase of 242 unique sequences from the 2005 data set. The increase, approximately 10%, was not expected to significantly affect the results observed for 2005 data set. Therefore, we did not perform the analysis of antigenic diversity on the 2006 data set because of the small increase in the number of unique sequence.
This study has provided evidence that there are limited numbers of antigenic combinations in variant protein sequences of a viral species and that short regions of the viral proteins 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).
All dengue virus protein sequence entries present in the NCBI Entrez protein database  were collected in June 2004 and then again in December 2005. Data retrieval was performed through the NCBI taxonomy browser  and the respective taxonomy ID for each of the dengue serotypes (DV1-4) are 11053, 11060, 11069 and 11070. The collected entries for both time points were processed separately using identical procedures.
Data processing: cleaning and grouping
The dengue virus RNA genome is translated into a single polyprotein (~3390 aa) that is cleaved by proteases to yield 10 dengue proteins: the C protein; the M protein, which is synthesized as a larger precursor protein pM; the major E glycoprotein; and seven nonstructural (NS) proteins, NS1, NS2a, NS2b, NS3, NS4a, NS4b and NS5 (Table 2). Individual protein sequences were extracted from collected entries for each DV serotype and grouped according to the 10 dengue proteins for analysis. The protein sequence extraction was done by sequence alignments and identification of known cleavage sites for dengue proteins. The cleavage sites were obtained from the annotation of the GenPept  reference polyprotein sequence for each dengue serotype (DV1: AAF59976; DV2: P14340; DV3: AAM51537; DV4: AAG45437) and the literature . The grouping of the extracted sequences for proteins of each serotype was facilitated by local sequence alignment using the BLAST algorithm  (parameters: filter – no; expect – 100; descriptions & alignments – 1000), followed by multiple sequence alignment using ClustalX 1.83  with default parameters, followed by manual inspection. Duplicate or identical sequences for proteins within each serotype were removed, and the unique sequences were retained for further analysis. Both full-length and partial unique sequences of each dengue serotype protein were used for the analysis, unless indicated otherwise. Data compiled from public databases are prone to errors and discrepancies , which may affect the analysis. Therefore, we inspected the collected DV entries and corrected errors and discrepancies (see additional file 1: Table S1.pdf).
Protein sequence and antigenic diversity analysis of dengue virus
In the context of this study, protein sequence diversity of a dengue protein was defined as the total number of unique sequences reported in the database for the protein. Sequences having at least a single amino acid difference between them were considered as unique. We calculated the pairwise percentage amino acid identity of the full-length unique sequences of each dengue protein, intra- and inter-serotype, by use of ClustalW 1.83  with default parameters, followed by manual inspection. This was done to survey the extent of amino acid variation and conservation in the latest, comprehensive dengue data of 2005.
Antigenic diversity of a dengue protein was defined in this study as the minimal set of unique sequences required to represent the complete set of overlapping 9-mer peptides encoded by all unique sequences reported in the database for the protein. We developed a bioinformatics method that performs exhaustive search to determine the minimal set for a given protein. The method comprises two steps: (a) generation of a set of overlapping 9-mers from the entire length of all unique sequences reported in the database for the protein, followed by (b) identification of a minimal set of unique sequences that represents all the unique 9-mers. The union of such sets for all the ten proteins of a dengue serotype represents the antigenic diversity of the proteins for the serotype as defined in this study. The computer program for the method was written in Perl and C language.
In the first step of the method, we generated overlapping 9-mers from the entire length of each unique sequence because the whole length was assumed to contain potential targets of T-cell mediated immune responses (T-cell epitopes) . This assumption was based, firstly, on the estimate that from a complete set of overlapping peptides (9 or 10-mers) spanning a protein, on average, 0.1–5% of the peptides will bind to any particular HLA molecule . Secondly, given the large number of HLA molecules (more than 2532 known as of September 2006; ), the vast majority of the complete set of overlapping peptides are highly likely to bind at least one molecule from the total HLA pool. Thus, each overlapping peptide is a potential T-cell epitope. This assumption ensures the capture of all possible candidate 9-mer T-cell epitopes that can be present across the entire length of the unique sequence. We focused our antigenic diversity study on 9-mers because they represent the predominant length of HLA class I T-cell epitopes, as well as the binding core of HLA class II T-cell epitopes [32, 40]. Furthermore, our preliminary analysis using 8-mers and 10-mers did not produce notably different results compared to the analysis of 9-mers (data not shown). A small number of 9-mers derived from the unique sequences contained unknown residues (denoted by "X") and, hence, were excluded from the analysis because they were antigenically non-informative.
Determining the effects of sequence determinants on antigenic diversity
The effects on antigenic diversity of two sequence determinants, the number of viral sequences in the studied set and the length of protein antigens were studied. The study was performed on unique sequences from the DV2 envelope protein (retrieved in 2005) because it provided a sufficiently large and well-defined dataset (198 full-length sequences). Test datasets with different numbers of sequences (20, 40, 60, 80, 100, 120 and 140 sequences) and different lengths (23, 46, 128, 138, 276 and 460 aa) were randomly derived from the envelope dataset with repeated sampling (20 repeats). Any duplicate sequences were removed from the test datasets. The minimal set of sequences that represents the complete short-peptide antigenic diversity was determined for each dataset. These minimal sets were used to analyze the effects of the sequence determinants on antigenic diversity.
List of abbreviations used
Dengue Virus Serotype 1
Dengue Virus Serotype 2
Dengue Virus Serotype 3
Dengue Virus Serotype 4
National Center for Biotechnology Information
Human Immunodeficiency Virus
Human Leukocyte Antigen.
The authors thank Seng Hong Seah, Zhang Guanglan, Judice Koh and Olivo Miotto for their help and valuable suggestions. We also thank Dr. Deborah McClellan for editorial review of the manuscript. This project has been funded in part with Federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, USA, under Grant No. 5 U19 AI56541 and Contract No. HHSN2662-00400085C.
This article has been published as part of BMC Bioinformatics Volume 7, Supplement 5, 2006: APBioNet – Fifth International Conference on Bioinformatics (InCoB2006). The full contents of the supplement are available online at http://www.biomedcentral.com/1471-2105/7?issue=S5.
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