In silico and ex vivo approaches indicate immune pressure on capsid and non-capsid regions of coxsackie B viruses in the human system

Abstract

Coxsackie B Virus (CBV) infection has been linked to the aetiology of type 1 diabetes (T1D) and vaccination has been proposed as prophylaxis for disease prevention. Serum neutralising antibodies and the presence of viral protein and RNA in tissues have been common tools to examine this potential disease relationship, whilst the role of anti-CBV cytotoxic T cell responses and their targets have not been studied. To address this knowledge gap, we augmented conventional HLA-binding predictive algorithm-based epitope discovery by cross-referencing epitopes with sites of positive natural selection within the CBV3 viral genome, identified using mixed effects models of evolution. Eight epitopes for the common MHC class I allele HLA-A*0201 occur at sites that appear to be positively selected. Furthermore, such epitopes span the viral genome, indicating that effective anti-viral responses may not be restricted to the capsid region. To assess the spectrum of IFNy responses in non-diabetic subjects and recently diagnosed type 1 diabetes (T1D) patients, we stimulated PBMC ex vivo with pools of synthetic peptides based on component-restricted sequences identified in silico. We found responders were more likely to recognize multiple rather than a single CBV peptide pool, indicating that the natural course of infection results in multiple targets for effector memory responses, rather than immunodominant epitopes or viral components. The finding that anti-CBV CD8 T cell immunity is broadly targeted has implications for vaccination strategies and studies on the pathogenesis of CBV-linked diseases.

Fig 1. Phylogenetic analysis of available CBV sequences.

Polyprotein sequences returned from Genbank for the terms “coxsackievirus B”; “coxsackie B virus”; “CBV”; “CVB”, listed in Table 1, were aligned using ClustalW pairwise alignment in Mega6. Genetic similarity between sequences and serotype clades in this alignment was assessed by generation of a maximum-likelihood phylogenetic tree. Sequences for CBV1 (10- highlighted in blue), CBV2 (7- light blue), CBV3 (29- red), CBV4 (25-purple), CBV5 (15-orange) and CBV6 (6- green) all clustered together with sequences for the same serotype, as would be expected from their labelling on Genbank.

Fig 2. Conformation of viral component amino acid sequences to Pan-CBV and serotype-specific consensus sequences.

To identify the protein components accounting for the greatest variance between sequences and serotypes used in our analyses, a pan-CBV consensus sequence was generated using Python Bio.Align package (using a threshold of 0.7) for all sequences for all serotypes, and the proportion of sequences conforming to this consensus sequence was determined for each amino acid site (A). Consensus sequences were also generated for each serotype, and the proportion of sequences within each specific serotype conforming to their consensus sequence was determined for each amino acid site for each viral protein (B).

Fig 3. IFNy responses can be detected against epitopes at VP3 positions 538–548 in serotypes CBV1, 2, 3, 4 and 6.

(A) Consensus sequences for CBV serotypes 1–6 were submitted to HLA-restrictor and returned putative HLA-A*0201 binding epitopes. The prevalence of these epitopes was assessed manually and serotype-unique sequences were presented in a radial plot. The radial tracks represent CBV serotypes 1–6, the outermost track of red histograms represents CBV1, blue CBV2, purple CBV3, green CBV4, rust CBV5 and aqua CBV6. The height of the histograms indicates the percentage of sequences within the indicated serotype that contain the epitope of interest at that site. The outer green tiles highlight the viral component. All serotypes of CBV had a putative HLA-A*0201 epitope at positions 538–548 within the VP3 region, which is highlighted in the alignment of consensus sequences presented in (B). (C) Cryopreserved PBMCs from non-diabetic controls (grey circles) and recently diagnosed T1D patients (blue squares) were thawed and pre-cultured at high density for 48 hours before stimulation with synthetic peptides (each at a final concentration of 5ug/ml) for the 538–548 epitopes in an IFNγ ELISpot. The results are normalised to DMSO controls and expressed as mean stimulation index (SI) per 3.3 x 10⁵ cells. We used a short-term ELISPot stimulation of 24 hours to ensure we did not prime naïve precursors and to minimise potential false positives from TCR promiscuity.

Fig 4. MEME analysis of CBV1 VP1 sequences reveal putative immunogenic regions across serotypes of CBV.

(A) Trimmed and edited CBV1 VP1 sequences from Table 4 were aligned by Bio.Align in Python and submitted to Datamonkey to identify sites of positive selection by mixed effects model of evolution. The p-value for the significance of which the amino acid site is evolving under positive selection within the model is represented. (B) Epitopes present at VP1 684–692 are highlighted within an alignment of serotype consensus sequences. (C) The predicted affinity for all potential sequences at VP1 684–692 are plotted against the amino acid identity for positions 2 and 4 in the 8-mer. (D) Prevalence of each sequence present at sites 682–694 for all serotypes was determined and plotted against their predicted binding affinity for HLA-A*0201, determined by HLA-restrictor.

Fig 5. Circos plot indicating the prevalence of viral protein component epitopes across CBV serotypes.

(A) Trimmed and edited CBV3 sequences from Table 1 were aligned by Bio.Align in Python and submitted to Datamonkey to identify sites of positive selection by mixed effects model of evolution. The p-value for the significance of which the amino acid site is evolving under positive selection is represented. (B) The percentage of sequences for each serotype containing each epitope was calculated manually and presented as histograms in a Circos plot. The radial tracks represent CBV serotypes 1–6, the outermost track of red histograms represents CBV1, blue CBV2, purple CBV3, green CBV4, rust CBV5 and aqua CBV6. The height of the histograms indicates the percentage of sequences within the indicated serotype that contain the epitope of interest at that site. The outer green tiles highlight the viral component. The outermost purple highlights indicate the presence of a site of positive selection within the CBV3 genome.

Fig 6. IFNγ responses to CBV viral component peptide pools in non-diabetic controls and recently-diagnosed T1D patients.

PBMC from non-diabetic and recently diagnosed -T1D patients were pre-cultured at high density for 48 hours before stimulation with pools of CBV and control peptides for 18 hours in an IFNγ ELISpot assay. Spots are reported as mean stimulation index normalised to DMSO control for 3.3 x 10⁵cells. (A) Stimulation indices for cohort responses to viral component CBV pools and serotype specific CBV pools (B) are presented. (C) The number of individuals demonstrating positive IFNγ ELISpot responses to any CBV derived peptide pool for ND-T1Ds and non-diabetic controls. (D) The number of positive hits for CBV peptide pools in responders is plotted for control and recently-diagnosed T1D cases.