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. 2021 Feb 16;2(2):100204.
doi: 10.1016/j.xcrm.2021.100204. Epub 2021 Jan 26.

Comprehensive analysis of T cell immunodominance and immunoprevalence of SARS-CoV-2 epitopes in COVID-19 cases

Alison Tarke  1   2 , John Sidney  1 , Conner K Kidd  1 , Jennifer M Dan  1   3 , Sydney I Ramirez  1   3 , Esther Dawen Yu  1 , Jose Mateus  1 , Ricardo da Silva Antunes  1 , Erin Moore  1 , Paul Rubiro  1 , Nils Methot  1 , Elizabeth Phillips  4 , Simon Mallal  4 , April Frazier  1 , Stephen A Rawlings  3 , Jason A Greenbaum  1 , Bjoern Peters  1   3 , Davey M Smith  3 , Shane Crotty  1   3 , Daniela Weiskopf  1 , Alba Grifoni  1 , Alessandro Sette  1   3
Affiliations

Comprehensive analysis of T cell immunodominance and immunoprevalence of SARS-CoV-2 epitopes in COVID-19 cases

Alison Tarke et al. Cell Rep Med. .

Abstract

T cells are involved in control of SARS-CoV-2 infection. To establish the patterns of immunodominance of different SARS-CoV-2 antigens and precisely measure virus-specific CD4+ and CD8+ T cells, we study epitope-specific T cell responses of 99 convalescent coronavirus disease 2019 (COVID-19) cases. The SARS-CoV-2 proteome is probed using 1,925 peptides spanning the entire genome, ensuring an unbiased coverage of human leukocyte antigen (HLA) alleles for class II responses. For HLA class I, we study an additional 5,600 predicted binding epitopes for 28 prominent HLA class I alleles, accounting for wide global coverage. We identify several hundred HLA-restricted SARS-CoV-2-derived epitopes. Distinct patterns of immunodominance are observed, which differ for CD4+ T cells, CD8+ T cells, and antibodies. The class I and class II epitopes are combined into epitope megapools to facilitate identification and quantification of SARS-CoV-2-specific CD4+ and CD8+ T cells.

Keywords: CD4+T cells; CD8+ T cells; COVID-19; HLA; SARS-CoV-2; T cells; epitopes.

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Conflict of interest statement

A.S. is a consultant for Gritstone, Flow Pharma, Merck, Epitogenesis, Gilead, and Avalia. S.C. is a consultant for Avalia. All other authors declare no competing interests. LJI has filed for patent protection for various aspects of vaccine design and identification of specific epitopes.

Figures

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Graphical abstract
Figure 1
Figure 1
SARS-CoV-2-specific T cell reactivity per protein PBMCs from convalescent COVID-19 donors (n = 99) were analyzed for reactivity against SARS-CoV-2 (A–F). Heatmaps of T cell reactivity across the entire SARS-CoV-2 proteome and as a function of the donor tested are shown for CD4+ (A) and CD8+ (B) T cells. The x axis shows individual donors’ responses to the indicated SARS-CoV-2 protein. Immunodominance at the ORF/antigen level and breath of T cell responses are shown for CD4+ (C) and CD8+ (E) T cells. Data are shown as geometric mean ± geometric SD. The numbers of donors recognizing one or more antigens with a response >10%, normalized per donor to account for the differences in magnitude based on days PSO, are shown for CD4+ (D) and CD8+ (F) T cells. Empty blue and red circles represent CD4+ and CD8+ T cell reactivity per protein, respectively. Filled blue and red circles highlight the immunodominant antigens recognized by CD4+ and CD8+ T cells, respectively.
Figure 2
Figure 2
SARS-CoV-2-specific CD4+ T cell reactivities and their correlations with antibody production and CD8+ T cell reactivity (A) RBD IgG serology is shown for all the convalescent COVID-19 donors (n = 99) of this cohort. (B–E) Serology data of (A) are correlated with CD4+ T cell reactivities specific against all combined proteins (B), structural proteins S, M, and N (C), non-structural proteins nsp3, nsp4, nsp12, and nsp13 (D), and ORF8 and ORF3a (E). (F–I) The total CD8+ T cell reactivity is correlated with the total CD4+ T cell reactivity (F) and the CD4+ T cell reactivity against structural proteins S, M, and N (G), non-structural proteins nsp3, nsp4, nsp12, and nsp13 (H), and ORF8 and ORF3a (I). Empty and filled circles represent correlation between CD4+ T cell reactivity and serology or CD8+ T cell reactivity, respectively. All analyses were performed using Spearman correlation, and the p values shown were not corrected for multiple hypothesis testing.
Figure 3
Figure 3
Heat maps of HLA predicted binding patterns in the 27 most frequent HLA class II alleles (A) SARS-CoV-2 CD4+ T cell epitopes as a function of the number of responding donors (n = 44 convalescent COVID-19 donors) recognized and strength of responses. (B and C) Predicted binding patterns for the top 49 most immunodominant SARS-CoV-2 CD4+ T cell epitopes (B) are compared with a set of matched non-epitopes (C). Predicted half maximal inhibitory concentration (IC50) was calculated using NetMHCIIpan and converted to log10 scale. Lower values indicate stronger predicted binding affinity and are highlighted at the red end of the spectrum. Predicted values with an IC50 < 1 000 nM (log10 scale < 3) are considered positive binders.
Figure 4
Figure 4
Distribution of SARS-CoV-2 CD8+ T cell responses by antigen and class I allele (A) The number of donors tested with their HLA-matched class I peptides for each of the 8 dominant proteins for CD8+ (n = 40 convalescent COVID-19 donors with a range of 4 to 35 donors tested per protein). (B and C) The distribution of allele-specific CD8+ responses for the 18 class I alleles that were tested in 3 or more donors is shown as function of protein composition (B) or the HLA class I alleles tested (C). Blue bars represent the total magnitude of AIM+ CD8+ T cells divided by the number of positive donors. Gray bars represent the frequency of positive tests. (D) The total number of epitopes identified for each class I allele is shown in panel.
Figure 5
Figure 5
Immunodominant regions for CD4+ T cells S, N, and M proteins. (A) S, (B) N, and (C) M proteins as a function of the frequency of positive response (red) and total magnitude (black) in the topmost panel. The dotted red line indicates the cutoff of 20% frequency of positivity used to define the immunodominant regions boxed in red and also shown in red in Figure 6. The x axis labels in this topmost panel indicate the middle position of the peptide. Binding promiscuity was calculated based on NetMHCIIpan predicted IC50 for the alleles present in the cohort of donors tested and is shown in gray on the upper middle panel. The lower middle panel shows the % homology of SARS-CoV-2 to the four most frequent CCC (229E in pink, NL63 in green, HKU1 in orange, and OC43 in black) and the max value (blue). The linear structure of each protein is drawn below the graph of homology. The magnitude of CD8+ responses to class I predicted epitopes is shown in the bottom panel, where black dots represent epitopes and red dots represent non-epitopes, each centered on the middle position of the peptide. PBMCs from convalescent COVID-19 donors (n = 44) were tested for reactivity to the peptides indicated in the topmost and bottommost panels (A)–(C).
Figure 6
Figure 6
Immunodominant regions for CD4+ T cells and B cells in relation to the 3D rendering of S, N, and M proteins 3D rendering of S (A), N (B), and M (C) proteins. The drawings show in gray the 3D structures, in red the CD4+ T cell immunodominant regions for each protein with frequency of positive responses >20% (also shown in red in Figure 5), and in yellow the B cell immunodominant regions for each protein based on the work of Shrock et al. Glycosylation sites for S are shown as gray dots and are based on information embedded in the original crystal structure shown to map the immunodominant regions (PDB: 6XR8). (A) The S protein is shown as monomer on the left and trimer in the middle and on the right (side and top views). (B) N protein 3D rendering was based on a model generated using Phyre2. Additional details about the N model are available in the STAR methods section. (C) The M protein is shown as a monomer according to a model previously described by Heo et al. All the 3D renderings have been performed using the free version of YASARA.
Figure 7
Figure 7
T cell responses to SARS-CoV-2 megapools as measured in AIM (empty circles) and FluoroSpot (filled in circles) assays (A–D) Twenty-five unexposed and 31 convalescent COVID-19 donors were tested in the AIM assays (A and C), and all donors were also tested in the FluoroSpot assays (B and D). (A and B) CD4+ T cell responses to CD4-R+S (previously described), CD4-E (280 class II epitopes identified in this study), and EC class II megapools were measured via AIM (A) and FluoroSpot (B). Bars represent geometric mean ± geometric SD, and p values were calculated by Mann-Whitney. (C and D) CD8+ T cell responses to CD8-A+B (previously described), CD8-E (454 class I epitopes identified in this study), and EC class I megapools were measured via AIM (C) and FluoroSpot (D). Bars represent geometric mean ± geometric SD, and p values were calculated by Mann-Whitney. (E–H) ROC analysis for CD4+ and CD8+ T cell response data in FluoroSpot (F–H) and AIM (E–G) assays. (I–L) Additionally, we further tested 17 of these COVID-19 convalescent donors in FluoroSpot with a titration of 200, 50, 25, and 12.5 × 103 cells per well with the indicated CD4-MPs (I and J) and CD8-MPs (K and L). (I and K) Bars represent geometric mean ± geometric SD, and p values were calculated by Mann-Whitney.
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