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Grouping of large populations into few CTL immune 'response-types' from influenza H1N1 genome analysis.

Mukherjee S, Chandra N - Clin Transl Immunology (2014)

Bottom Line: Extent of CTL responses varies significantly across different populations and increases with increase in genetic heterogeneity.We also obtain lists of top-ranking epitopes and proteins, ranked on the basis of conservation, antigenic cross-reactivity and population coverage, which provide ready short-lists for rational vaccine design.Our method is fairly generic and has the potential to be applied for studying other viruses.

View Article: PubMed Central - PubMed

Affiliation: IISc Mathematics Initiative, Indian Institute of Science , Bangalore, India.

ABSTRACT
Despite extensive work on influenza, a number of questions still remain open about why individuals are differently susceptible to the disease and why only some strains lead to epidemics. Here we study the effect of human leukocyte antigen (HLA) genotype heterogeneity on possible cytotoxic T-lymphocyte (CTL) response to 186 influenza H1N1 genomes. To enable such analysis, we reconstruct HLA genotypes in different populations using a probabilistic method. We find that epidemic strains in general correlate with poor CTL response in populations. Our analysis shows that large populations can be classified into a small number of groups called response-types, specific to a given viral strain. Individuals of a response-type are expected to exhibit similar CTL responses. Extent of CTL responses varies significantly across different populations and increases with increase in genetic heterogeneity. Overall, our analysis presents a conceptual advance towards understanding how genetic heterogeneity influences disease susceptibility in individuals and in populations. We also obtain lists of top-ranking epitopes and proteins, ranked on the basis of conservation, antigenic cross-reactivity and population coverage, which provide ready short-lists for rational vaccine design. Our method is fairly generic and has the potential to be applied for studying other viruses.

No MeSH data available.


Related in: MedlinePlus

(a) Representation of the set of CD8+ epitopes on the IFV genome from consensus predictions. The innermost pie chart reflects the relative ratios of the different HLA alleles that are theoretically capable of recognizing the given strain of the IFV. The outer doughnut represents the number of epitopes for a pool of HLA alleles for each of the eight protein in the genome (size of the segments proportional to the number of epitopes). The histograms shown outside the doughnut reflects the corresponding HLA cognate alleles for epitopes of that protein. Proteins are labelled while the HLA alleles are as indicated in the colour key. (b) A biclustering diagram with columns representing different proteins in the viral genome and rows representing different HLA alleles that recognize the set of epitopes in each protein. The colour in each cell indicates the predicted recognition strength, as a factor of the number of epitopes in that protein for a given allele. Clustering patterns indicate similarity in responses both from an allele's perspective as well as from a protein's. The total antigenicity in terms of the number of epitopes is indicated for each protein. Also indicated is the recognition strength of each HLA in terms of the number of epitopes it can bind.
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fig2: (a) Representation of the set of CD8+ epitopes on the IFV genome from consensus predictions. The innermost pie chart reflects the relative ratios of the different HLA alleles that are theoretically capable of recognizing the given strain of the IFV. The outer doughnut represents the number of epitopes for a pool of HLA alleles for each of the eight protein in the genome (size of the segments proportional to the number of epitopes). The histograms shown outside the doughnut reflects the corresponding HLA cognate alleles for epitopes of that protein. Proteins are labelled while the HLA alleles are as indicated in the colour key. (b) A biclustering diagram with columns representing different proteins in the viral genome and rows representing different HLA alleles that recognize the set of epitopes in each protein. The colour in each cell indicates the predicted recognition strength, as a factor of the number of epitopes in that protein for a given allele. Clustering patterns indicate similarity in responses both from an allele's perspective as well as from a protein's. The total antigenicity in terms of the number of epitopes is indicated for each protein. Also indicated is the recognition strength of each HLA in terms of the number of epitopes it can bind.

Mentions: Epitope pools vary in size in different strains (distribution in Supplementary Figure 1a), despite retaining similar overall length of each protein. Figure 2a illustrates the relative number of epitopes from each protein along with the major alleles that they recognize for one example strain. Similar figures for all 186 strains are in FluTope. It is seen that the major alleles that recognize IFV epitopes vary in the range of 10–12 for different strains. Biclustering performed to capture cross-reactivity between epitopes and the alleles is shown in Figure 2b for one example strain, indicating a relative ranking of the theoretical potential of different alleles and pool of epitopes from different proteins in generating a CTL response. A dendrogram of 186 IFV strains, based on the extent of similarities in their epitope sets for each protein (Supplementary Table 4a) is seen to be different from those constructed based on sequence similarities in whole proteins (Supplementary Table 4b). These branching patterns, with higher number of branches in epitope trees, indicate that even subtle variations in the genome can give rise to significant differences in the CD8+ immunomes.


Grouping of large populations into few CTL immune 'response-types' from influenza H1N1 genome analysis.

Mukherjee S, Chandra N - Clin Transl Immunology (2014)

(a) Representation of the set of CD8+ epitopes on the IFV genome from consensus predictions. The innermost pie chart reflects the relative ratios of the different HLA alleles that are theoretically capable of recognizing the given strain of the IFV. The outer doughnut represents the number of epitopes for a pool of HLA alleles for each of the eight protein in the genome (size of the segments proportional to the number of epitopes). The histograms shown outside the doughnut reflects the corresponding HLA cognate alleles for epitopes of that protein. Proteins are labelled while the HLA alleles are as indicated in the colour key. (b) A biclustering diagram with columns representing different proteins in the viral genome and rows representing different HLA alleles that recognize the set of epitopes in each protein. The colour in each cell indicates the predicted recognition strength, as a factor of the number of epitopes in that protein for a given allele. Clustering patterns indicate similarity in responses both from an allele's perspective as well as from a protein's. The total antigenicity in terms of the number of epitopes is indicated for each protein. Also indicated is the recognition strength of each HLA in terms of the number of epitopes it can bind.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4232073&req=5

fig2: (a) Representation of the set of CD8+ epitopes on the IFV genome from consensus predictions. The innermost pie chart reflects the relative ratios of the different HLA alleles that are theoretically capable of recognizing the given strain of the IFV. The outer doughnut represents the number of epitopes for a pool of HLA alleles for each of the eight protein in the genome (size of the segments proportional to the number of epitopes). The histograms shown outside the doughnut reflects the corresponding HLA cognate alleles for epitopes of that protein. Proteins are labelled while the HLA alleles are as indicated in the colour key. (b) A biclustering diagram with columns representing different proteins in the viral genome and rows representing different HLA alleles that recognize the set of epitopes in each protein. The colour in each cell indicates the predicted recognition strength, as a factor of the number of epitopes in that protein for a given allele. Clustering patterns indicate similarity in responses both from an allele's perspective as well as from a protein's. The total antigenicity in terms of the number of epitopes is indicated for each protein. Also indicated is the recognition strength of each HLA in terms of the number of epitopes it can bind.
Mentions: Epitope pools vary in size in different strains (distribution in Supplementary Figure 1a), despite retaining similar overall length of each protein. Figure 2a illustrates the relative number of epitopes from each protein along with the major alleles that they recognize for one example strain. Similar figures for all 186 strains are in FluTope. It is seen that the major alleles that recognize IFV epitopes vary in the range of 10–12 for different strains. Biclustering performed to capture cross-reactivity between epitopes and the alleles is shown in Figure 2b for one example strain, indicating a relative ranking of the theoretical potential of different alleles and pool of epitopes from different proteins in generating a CTL response. A dendrogram of 186 IFV strains, based on the extent of similarities in their epitope sets for each protein (Supplementary Table 4a) is seen to be different from those constructed based on sequence similarities in whole proteins (Supplementary Table 4b). These branching patterns, with higher number of branches in epitope trees, indicate that even subtle variations in the genome can give rise to significant differences in the CD8+ immunomes.

Bottom Line: Extent of CTL responses varies significantly across different populations and increases with increase in genetic heterogeneity.We also obtain lists of top-ranking epitopes and proteins, ranked on the basis of conservation, antigenic cross-reactivity and population coverage, which provide ready short-lists for rational vaccine design.Our method is fairly generic and has the potential to be applied for studying other viruses.

View Article: PubMed Central - PubMed

Affiliation: IISc Mathematics Initiative, Indian Institute of Science , Bangalore, India.

ABSTRACT
Despite extensive work on influenza, a number of questions still remain open about why individuals are differently susceptible to the disease and why only some strains lead to epidemics. Here we study the effect of human leukocyte antigen (HLA) genotype heterogeneity on possible cytotoxic T-lymphocyte (CTL) response to 186 influenza H1N1 genomes. To enable such analysis, we reconstruct HLA genotypes in different populations using a probabilistic method. We find that epidemic strains in general correlate with poor CTL response in populations. Our analysis shows that large populations can be classified into a small number of groups called response-types, specific to a given viral strain. Individuals of a response-type are expected to exhibit similar CTL responses. Extent of CTL responses varies significantly across different populations and increases with increase in genetic heterogeneity. Overall, our analysis presents a conceptual advance towards understanding how genetic heterogeneity influences disease susceptibility in individuals and in populations. We also obtain lists of top-ranking epitopes and proteins, ranked on the basis of conservation, antigenic cross-reactivity and population coverage, which provide ready short-lists for rational vaccine design. Our method is fairly generic and has the potential to be applied for studying other viruses.

No MeSH data available.


Related in: MedlinePlus