The impact of existing and theoretical mutations on SARS-CoV-2 CD8+ T cell targets

By Bhavana KunkalikarReviewed by Danielle Ellis, B.Sc.Oct 25 2022

In a recent study posted to the bioRxiv* preprint server, researchers evaluated the effect of mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) on CD8+ T cell responses.

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Background

The resolution of SARS-CoV-2 infections and the development of adaptive immunological memory have both been primarily attributed to T cell recognition of SARS-CoV-2 antigens following natural infection and/or vaccination. SARS-CoV-2-specific T cell responses can have varying clinical effects, and the processes driving T cell contact with target antigens are not entirely known. This is particularly true given the virus' quick evolution, which produces new variants capable of evading immune defenses.

About the study

In the present study, researchers assessed the effect of mutations on the immunogenicity of CD8+ T cells using the SARS-CoV-2 Omicron variant as the model organism.

The team assembled a pool of 1380 distinct SARS-CoV-2 peptides obtained from epitope databases to examine the impact of current mutations on SARS-CoV-2-specific CD8+ T cell epitopes. Among these, 9-mers and 10-mers were the most prevalent. The pool of 1380 peptides corresponding to each proteome was mapped to recognize immunogenic Wuhan Hu-1 epitopes mutated in the Omicron BA.1, BA.2, BA.4, and BA.5 sublineages. Additionally, modifications in both 9-mer and 10-mer peptides at various sequence locations were examined.

To systematically examine the effects of current mutations on their manifestation, Wuhan CD8+ T cell targets were used. The human leukocyte antigen (HLA)-binding metrics corresponding to each Wuhan-mutated peptide were predicted to 64 HLAs, which were chosen because they were previously used by the "TCoV" pipeline to assess the overall major histocompatibility complex (MHC) binding displayed by SARS-CoV-2 variants and due to their frequent presence in epitope databases. The antigen characteristics presented by Wuhan-mutated peptides as well as BA.1, BA.2, BA.4, or BA.5 peptides, were compared against the 64 HLA-I alleles.

The impact of Omicron VOC mutations on the immunogenicity potential of pMHC was also assessed. The team combined prediction scores for antigen presentation and T-cell recognition potential for each peptide-MHC. A Convolutional Neural Network (CNN) model called TRAP developed by the team provided more accurate predictions of the T cell recognition potential for HLA-I displayed by 9- and 10-mer peptides. The team trained a TRAP instantiation on coronavirus epitopes to estimate the potential of T cell recognition in Wuhan compared to the Omicron pMHC of interest.

Results

The team found out of 1,380 mutations of Wuhan Hu-1 CD8+ T cell targets, 90 were produced by BA4, 80 by BA.1, 76 by BA.5, and 70 by BA.2. Although epitopes having two or three mutations were also prevalent, single point mutations accounted for the majority of these changes for each variation. For each variant, spike glycoprotein was the source of the majority of CD8+ T cell epitopes that displayed alterations. All of the variants had PàL/H mutations at P2 among the 9-mers. In this location, BA.4 also carries a PàS mutation. Proline substitutions were observed for 10-mers as well, albeit they were less prevalent.

Omicron BA.1 mutants were estimated to be weaker binders to MHC-I alleles than their Wuhan Hu-1 counterparts. To ensure that these results are not the consequence of HLA biases in the dataset, netMHCpan rank scores were examined. Distinct HLAs bind with their ligands at diverse nM ranges. Following a comparison of CD8+ T cell targets corresponding to all SARS-CoV-2 proteins, the team observed a similar but weaker trend. Also, compared to Wuhan Hu-1, the BA.2, BA.4, and BA.5 mutants showed weaker expected binding to MHC-I.

By categorizing paired data according to the HLA supertype, the team discovered that Wuhan Hu-1 pMHC may have a greater binding affinity than BA1 spike-derived B07-pMHC; however, this difference was not statistically significant. Along with HLA-A02 for BA4, the team discovered that ligands coupled to HLA-A03 and HLA-B07 were severely impaired for BA2 and BA5. Since almost 25% to 35% of the world's population carries an A02, A03, or B07 supertype allele, the team noted that it was possible that binding detriments related to a specific pMHC may impede T cell reactivity for people bearing specific HLA, with variations between subvariants.

Compared to their Wuhan Hu-1 counterparts, BA1 epitopes exhibit a slight loss in immunogenicity, even though expected T cell immunogenicity globally was conserved after the Omicron infection. The T cell immunogenicity observed HLA-A02, -A03, -B07, and -C01 ligands showed severe reductions. This indicated that certain Omicron-based VOC mutations generate subtle impacts on T cell immunogenicity that seem to be HLA-dependent.

Conclusion

Overall, the study demonstrated a diverse and heterogeneous environment of impact with respect to the SARS-CoV-2 Omicron variant. The study put forth a paradigm that utilizes in-silico mutagenesis as well as immunogenicity modeling to predict the outcomes of theoretical SARS-CoV-2 mutations.

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources