key: cord-0885870-cnc2s0rh
authors: Tarke, Alison; Coelho, Camila H.; Zhang, Zeli; Dan, Jennifer M.; Yu, Esther Dawen; Methot, Nils; Bloom, Nathaniel I.; Goodwin, Benjamin; Phillips, Elizabeth; Mallal, Simon; Sidney, John; Filaci, Gilberto; Weiskopf, Daniela; da Silva Antunes, Ricardo; Crotty, Shane; Grifoni, Alba; Sette, Alessandro
title: SARS-CoV-2 vaccination induces immunological T cell memory able to cross-recognize variants from Alpha to Omicron
date: 2022-01-24
journal: Cell
DOI: 10.1016/j.cell.2022.01.015
sha: 20810e13e86e02fb07d5c29a396ca7538d68dba3
doc_id: 885870
cord_uid: cnc2s0rh

We address whether T cell responses induced by different vaccine platforms (mRNA-1273, BNT162b2, Ad26.COV2.S, NVX-CoV2373) cross-recognize early SARS-CoV-2 variants. T cell responses to early variants were preserved across vaccine platforms. By contrast, significant overall decreases were observed for memory B cells and neutralizing antibodies. In subjects ∼6 months post-vaccination, 90% (CD4+) and 87% (CD8+) of memory T cell responses were preserved against variants on average by AIM assay, and 84% (CD4+) and 85% (CD8+) preserved against Omicron. Omicron RBD memory B cell recognition was substantially reduced to 42% compared to other variants. T cell epitope repertoire analysis revealed a median of 11 and 10 spike epitopes recognized by CD4+ and CD8+ T cells, with average preservation > 80% for Omicron. Functional preservation of the majority of T cell responses may play an important role as second-level defenses against diverse variants.

and variant recognition ( Figure 2D) . Overall, the average fold-change values considering all variants was 1.00 (range 0.92 to 1.1) for CD4 + and 1.01 (range 0.76 to 1.2) for CD8 + T cells. The greatest decrease was to 0.76 for Delta by cytokine + CD8 + T cells. At the level of individual CD4 + T cell responses, decreases greater than 3-fold were observed for three donors: one Ad26.COV2.S donor for Beta and Lambda, one Ad26.COV2.S donor for Beta, and one mRNA-1273 donor for Delta (Figure 2A) . No decreases greater than 10-fold were observed. For CD8 + T cells, decreases greater than 10-fold were observed with one Ad26.COV2.S donor for Alpha and R.1 and one mRNA-1273 donor for Delta. Decreases in the 3-10 fold range were observed for four BNT162b2 donors (one for Beta, one for Gamma, one for Delta, and one for Lambda), one Ad26.COV2.S donor for lambda, and one mRNA-1273 donor with R.1 (Figure 2C) .

Considering the different assay readouts (AIM and ICS) and different donors analyzed, the foldchange was calculated in 171 instances for 8 different variants, for a total of 1,368 determinations. T cell responses with decreases greater than 3-fold were observed in 14 instances (1.02%) of variant/subject combinations tested, and decreases greater than 10-fold were observed in 3 instances (0.22%) of variant/subjects tested. Thus, in almost 99% of cases the differences in measured T cell recognition were less than 3-fold.

In the context of AIM + T cells responses measured at time point 1 (2 weeks post-1 st dose, Figure  S3 ), we found a very similar pattern to what was observed in time point 2, with no substantial decreases in each of the variants analyzed at both population and individual level, except for 3 out of 280 instances (1%) with AIM+ CD8 + T cells ( Figure S3B) . These results confirm, in a larger dataset, that T cell responses from vaccinated subjects are largely preserved against Alpha, Beta and Gamma (Tarke et al., 2021b) . Importantly, these results extend these observations to more VOI/VOCs, including the prominent Delta variant.

Alpha (P<0.0001), Beta (P<0.0001), Gamma (P<0.0001) and Delta (P<0.0001) variants ( Figure 3J ). The highest neutralization antibody titers were against D614G, and reductions in neutralizing titers of 2.4-fold, 4.5-fold, 3.8-fold and 3.4-fold against Alpha, Beta, Gamma and Delta variants were noted ( Figure 3J and Figure S4J ). A similar pattern was observed for COVID-19 convalescent subjects (Figure S4K-L) . Spike and RBD binding IgG titers in vaccinated subjects had similar trends to neutralizing antibodies but with smaller differences (Figure 3K -L, Figure S4M-N) . In conclusion, while no significant change in T cell recognition was noted, decreases in memory B cell and neutralizing antibody recognition of all variants analyzed were apparent.

With the recent emergence of the Omicron variant, studies were immediately expanded to include Omicron. We first predicted the impact of variant mutations for CD4 + and CD8 + T cell epitopes experimentally curated in the IEDB (www.IEDB.org) Vita et al., 2019) (Table S4 ). In addition to Omicron, we included a wider panel of early and late SARS-CoV-2 variants for comparison.

For CD4 + T cells, an average of 95% of the epitopes spanning the entire SARS-CoV-2 proteome were fully conserved (no mutations) across the variants ( Figure 4A ). The Delta variant was not associated with a significant decrease (Figure 4A) , while the fraction of fully conserved epitopes was reduced in Omicron (88%), compared to the other variants (p<0.0001) ( Figure 4A) . A similar result was observed for CD8 + T cell epitopes, with 98% overall conservation but 95% for Omicron (P<0.0001) ( Figure 4B ). Considering only spike epitopes, an average of 91% and 94% CD4 + and CD8 + T cell epitopes were conserved in the various variants. The Omicron variant was associated with the fewest fully conserved spike epitopes for both CD4 + and CD8 + T cells (CD4 + : 72%, P<0.0001; CD8 + : 86%, P<0.0001) (Figure 4C-D) .

We further found that 82% of 9-mers encompassing the entire spike protein are conserved in Omicron, as compared with 86% of the CD8 epitopes being conserved. Thus, mutations do not appear to occur more frequently in areas of Spike recognized as epitopes.

To address whether Omicron mutations preferentially impacted more dominant epitopes, we divided epitopes in dominant and subdominant based on the frequency of individual responses as previously described . This analysis indicated that the most dominant CD4 + epitopes tend to be more frequently conserved compared to subdominant epitopes (75% versus 64%), while a modest opposite trend was observed for CD8 + T cell epitopes (84% versus 88%)(data not shown).

The values reported in Figure 4A -D were stringent estimates of the number of preserved epitopes, since conservative substitutions and changes not impacting HLA binding can still be crossreactively recognized. Accordingly, we examined the effect of the mutations on the predicted binding affinity of each CD8 epitope for which HLA restriction could be inferred ( Figure 4E-G) . Notably, in the majority of cases, the variant-associated mutations were predicted to not impair HLA binding capacity ( Figure 4E-G) . Importantly, 72% of the epitopes with Omicron variant mutations were predicted to retain similar HLA class I binding capabilities, which was not dissimilar to other SARS-CoV-2 variants (p=0.8625; Figure 4H ). In conclusion, bioinformatic analyses suggest that the majority of CD4 + and CD8 + T cell epitopes are unaffected by mutations, regardless of whether early or late variants were considered ( Figure 4A-D) . These data suggest that variant evolution was not driven by T cell escape. In the case of Omicron, the number of totally conserved spike epitopes was decreased. However, the majority of Omicron epitopes (full proteome or spike) were still 100% conserved, and the majority of mutated epitopes were predicted to still be recognized by T cells.

Considering that the Omicron variant contains 15 mutations in the RBD, we sought to investigate whether mRNA vaccination generated memory B cells that recognized Omicron spike and RBD. Memory B cells obtained from subjects receiving either mRNA-1273 or BNT162b2 (5-6 months post-vaccination) had significantly lower recognition of Omicron spike compared to the ancestral strain (P<0.0001) ( Figure  5A, Figure S5A ,C). Memory B cell recognition of Omicron RBD was significantly decreased, with 0.42 retained recognition (P<0.0001)( Figure 5B, Figure S5B ,D), substantially lower than Alpha, Beta or Delta RBD binding. In sum, memory B cell recognition of Omicron RBD, known to be important for most neutralizing antibodies, was substantially reduced compared to other variants.

Next, we experimentally determined the impact of Omicron mutations on T cell responses in comparison to other variants, in a cohort of individuals vaccinated 5-6 months before blood donation and also in parallel subsequently used for epitope mapping. The overall conservation of memory CD4 + T cell recognition of Omicron spike was 0.84 (84%) by AIM and 0.93 (93%) by ICS assay (Figure S5G) . A significant decrease was observed for Omicron by AIM, comparable in magnitude to that of Alpha or Beta variants ( Figure 5C ,E and Figure S5 ). No significant decrease was observed for CD4 + T cell recognition of Omicron by ICS; significant differences were only observed for Alpha and Beta ( Figure 5D ,F and Figure S5E -F). At the individual subject level, no AIM + or ICS + CD4 + T cell recognition decreases >3-fold were observed.

The preservation of memory CD8 + T cell recognition of Omicron spike was 0.85 (85%) by AIM and 1.1 (110%) by ICS (Figure 5E -F, and Figure S5J ), with neither change being statistically significant. Significant decreases were observed for Alpha, Beta and Delta by AIM (Figure 5E-F) . In the context of Omicron, 3 out of the 12 positive donors analyzed for CD8 + T cell responses showed a minimal decrease at the fold-change level that nevertheless placed the response below the AIM assay limit of sensitivity; thus the frequency of positive responders to Omicron was 75%, the lowest of all variants ( Figure S5H) . A loss of positive responders to Omicron was also observed by ICS (7 out of 8, 88%) ( Figure S5I ). For all timepoints analyzed in this study, we found a very weak inverse correlation between fold-change decrease and the magnitude of the spike-specific T cell responses ( Figure S5K -L), suggesting that overall weaker responses tend to be less frequently associated with decreases in the variants. This might simply reflect weaker responses being associated with a lesser dynamic range and therefore decreases less reliably measured. In any case, it did not support the notion that significant decreases are selectively associated with weak responses. We also examined the notion that weaker responses might be associated with individual HLA allele combinations, utilizing bioinformatic tools specifically designed to detect HLA associations (Paul et al., 2017) . No specific HLA class I or class II alleles were significantly correlated to reduced variant recognition in our cohort (data not shown), but the limited sample size was not powered to detect HLA associations, which usually required substantially larger numbers of observations. Overall, compared to other variants, no clear pattern of a loss of CD4 + or CD8 + T cell recognition of Omicron was observed by either T cell assay.

To further examine the molecular mechanism involved in the observed effects of T cell recognition of variant spike epitopes, we selected four donors for in depth spike epitope identification studies and variant analyses ( Figure 6A -D, Table S5 ). Each vaccinated donor recognized 5 to 42 (median 11) individual CD4 + T cell epitopes in spike ( Figure 6A ). Approximately 80% of the CD4 + T cell response was associated with epitopes fully conserved in Omicron, with the actual values per donor ranging from 65% to 100% ( Figure 6B ). Each vaccinated donor with a measurable CD8 + T cell response against the ancestral strain was found to recognize 6 to 19 (median 10) spike CD8 + T cell epitopes ( Figure 6C ). Approximately 80% of the CD8 + T cell response was associated with epitopes fully conserved in Omicron, with the values per donor ranging from 70% to 100% ( Figure 6D ). These results were in agreement with the bioinformatic analyses (Figure 4 ). In general, there was also good correspondence between the peptide pools, except with the CD8 + T cell response by donor 6276, where the sum of the response for the individual epitopes exceeded the one observed for the megapool, suggesting that perhaps some of the identified epitopes may not be generated efficiently from the originating 15-mers contained in the megapool ( Figure 6C ). In sum, these epitope mapping data showed how the wide epitope repertoire associated with vaccine-induced responses counterbalances the effect of variant mutations of observed spike epitopes.

Here we analyzed adaptive immunity in vaccinated individuals to a comprehensive panel of SARS-CoV-2 variants, including Delta and Omicron, for multiple vaccines. Our data demonstrate that the vast majority of T cell epitopes are fully conserved, not only in the "early" variants previously analyzed Geers et al., 2021; Keeton et al., 2021; Melo-Gonzalez et al., 2021; Riou et al., 2021; Tarke et al., 2021b) , but also in newer variants, suggesting that the continued evolution of variants has not been associated with increased escape from T cell responses at the population level.

At the level of the full proteome, which is relevant for natural infection, 95% of reported class II and 98% of class I epitopes were fully conserved by computational analysis based on IEDB data extracted on July 2021. In the case of Omicron, the fraction of epitopes that were fully conserved dropped to 88% for class II and 95% for class I epitopes in the whole proteome. Focused only on spike, relevant in the context of vaccination, 91% of class II and 94% of class I epitopes were still fully conserved. The fraction of totally conserved spike epitopes in Omicron dropped to 72% for class II and 86% for class I epitopes. The higher number of mutated T cell epitopes in spike was expected since many variant mutations are localized in the spike protein. Overall, the majority of T cell epitopes available in IEDB are conserved at the sequence level in all variants analyzed so far, including Omicron. It should be emphasized that an epitope mutation does not preclude cross-reactive recognition of the mutated sequence. To partially address this point, we calculated the fraction of class I epitope mutations predicted to be associated with a decrease in binding affinity to the relevant HLA. We found that, of the mutated epitopes, HLA binding was well conserved for the majority of the epitopes. The impact on HLA binding was not different for Omicron epitopes compared to other variants. These observations argue against a model that mutations accumulated in Omicron might be the result of T cell immune pressure at the population level.

T cell recognition of several variants, including Delta and Omicron, was experimentally measured in donors vaccinated with mRNA-1273, BNT162b2 or Ad26.COV2.S. Variant recognition relative to the ancestral sequence was similar in the three different vaccine platforms tested, which is reassuring in terms of the potential implications for protective effects being similar regardless of the vaccine platform considered. A significant higher variability was detected with Ad26.COV2.S, possibly related to evidence that Ad26.COV2.S induces spike specific T cells mainly targeting the S1 region of Spike, while other vaccines appear to elicit a more broad spike-specific T cell response (Kim Huat et al., 2021) .

A majority of memory T cells were not impacted by variants' mutations, which is again reassuring in terms of the potential implications for T cell protective effects being similar regardless of the different vaccine cohorts considered. Significant fold-change decreases were noted in the 3.5 month memory time point for the Delta variant when utilizing cytokine production as a readout. While it is possible that this function is more impacted in mutated sequences, a consistent difference was not observed across variants.

Memory T cell responses to the various variants, including Omicron, were dissected in detail in a cohort of donors 6-7 months following vaccination. The results confirmed that the majority of both CD4 + and CD8 + T cell responses detected by the AIM assay were preserved at this late time point. CD8 + T cell response decreases were observed when utilizing the IFNγ production as a readout in certain cases. Of note, regardless of the assay, Omicron responses were largely preserved in both CD4 + and CD8 + T cells. Broadly speaking, it is plausible that any antigen-specific T cell loss smaller than 2-fold is of modest relevance, given that the T cells respond as a recall response with relatively short doubling times. From animal models, we are not aware of conditions where less than 2-fold changes in antigen-specific T cell frequencies resulted in a measurable difference in protective immunity. It is also important to note that individual decreases or lack of responses were noted in 25% or less of the individuals in the case of Omicron, suggesting that some selected HLA-class profile, may be more susceptible to the impact of Omicron. In depth epitope identification experiments revealed that both CD4 + and CD8 + T cell responses in vaccinated donors were broad, and the data further demonstrated that for each individual donor/variant combination the majority of responses identified were to epitopes that were fully conserved. These data provide a clear explanation for the limited impact of variant-associated mutations on T cell responses at the population level.

Adaptive immunity against SARS-CoV-2 consists of multiple branches ). Memory B cell recognition of variants' spikes was reduced in all cases, but the reductions were moderate J o u r n a l P r e -p r o o f against Delta spike and Beta RBD, demonstrating substantially retained memory B cell recognition of most variants Goel et al., 2021; Sokal et al., 2021a) . However, memory B cell recognition of Omicron RBD was substantially reduced. Memory B cell binding to Omicron RBD is likely to be detectable at affinities insufficient for virus neutralization in vitro. This is consistent with the observations that neutralizing antibody titers against Omicron are generally low in individuals after two doses of mRNA-1273 or BNT162b2. Nevertheless, Omicron neutralizing antibody titers rapidly increase after a third immunization Planas et al., 2021; Schmidt et al., 2021; Sokal et al., 2021b) , most likely due to the presence of memory B cells that recognized Omicron RBD, as observed here. Memory B cells may have important contributions in protective immunity by making anamnestic neutralizing antibody responses after infection (Cameroni et al., 2021; Carreño et al., 2021; Cele et al., 2021; Doria-Rose et al., 2021; Gagne et al., 2021; Garcia-Beltran et al., 2021; Zou et al., 2021) .

These data provide reason for optimism, as most vaccine-elicited T cell responses remain capable of recognizing all known SARS-CoV-2 variants. Nevertheless, the data also underline the need for continued surveillance and the potential danger posed by continued variant evolution that could result in further reduction of T cell responses. Incorporation of additional elements eliciting broader T cell responses directed towards more conserved targets into vaccine strategies may be considered as a means to increase vaccine effectiveness against future variants.

The present study has limitations. A caveat is that all experiments were performed with a robust concentration of peptides (1µg/mL) which might underestimate the impact of mutations on T cells. It is also currently unknown what level of epitope conservation is likely to preserve functional T cell responses in vivo, and currently no rigorous correlate of protection based on T cell responses has been generated so to understand the impact of T cell responses against various SARS-CoV-2 outcomes such as severe disease. Further, the assays used in our study are testing peptide-based responses, rather than the responses that will occur in vivo. A variant might change multiple features of epitope presentation, e.g. by mutations outside the epitope that change processing, or more globally by evolving additional immune evasion strategies. Finally, the current study has not investigated subjects following natural infection.

We worked to ensure sex balance in the selection of non-human subjects. While citing references scientifically relevant for this work, we also actively worked to promote gender balance in our reference list. Figure 1 . Impact of variant-associated mutations on spike-specific CD4 + and CD8 + T cell recognition. T cell responses from fully vaccinated COVID-19 vaccinees were assessed with variant spike MPs. The effect of mutations associated with each variant MP was expressed as relative (fold-change variation) to the T cell reactivity detected with the ancestral strain MP. Results from COVID-19 mRNA-1273 (n=20, circles), BNT162b2 (n=20, triangles) and Ad26.COV2.S (n=12, squares) vaccinees are presented combined together, and separately by vaccine platform. For fold-change calculations, only donors responding to the ancestral S MP were included. (A) Representative gating of CD4 + T cells of a mRNA-1273 vaccine recipient responding to different SARS-CoV-2 variants MPs is shown. (B) Fold-change is calculated for AIM + CD4 + T cells relative to the ancestral strain in COVID-19 vaccinees. (C) A representative gating example is shown for a mRNA-1273 vaccine recipient for CD8 + T cells against the SARS-CoV-2 variants in analysis. (D) Fold-change is calculated for AIM + CD8 + T cells relative to the ancestral strain in COVID-19 vaccinees. Coefficients of variation (CV) and the geometric mean foldchanges (FC) for the variants are listed in each graph. Significance of fold-change decreases for each variant was assessed by Wilcoxon Signed Rank T test compared to a hypothetical median of 1. See also Figures S1, S2 and S3 and Table S1.

Fully vaccinated COVID-19 vaccinees were assessed with variant spike MPs and the effect of mutations associated with each variant MP is expressed as relative (fold-change variation) to the T cell reactivity detected with the ancestral strain MP. Results from COVID-19 mRNA-1273 (n=20, circles), BNT162b2 (n=20, triangles) and Ad26.COV2.S (n=12, squares) vaccinees are presented combined together. (A) Fold-change values for cytokine + CD4 + T cells are calculated based on the sum of CD4 + T cells expressing CD40L in combination with IFNγ, TNFα, IL-2, or granzyme B. (B) The functionality of the spike-specific CD40L + CD4 + T cell is defined by the different combinations of IFNγ, TNFα, IL-2, or granzyme B. (C) Fold-change values for cytokine + CD8 + T cells are calculated based on the sum of CD8 + T cells producing IFNγ, TNFα, or IL-2 and (D) the functionality of the spike-specific CD8 + T cells is calculated by looking at the different combinations of IFNγ, TNFα, IL-2, or granzyme B, excluding single positive granzyme B. All data is shown is background subtracted with an SI>2. Coefficients of variation (CV) and the geometric mean fold-changes (FC) for the variants are listed in each graph. Significance of fold-change decreases for each variant was assessed by Wilcoxon Signed Rank T test compared to a hypothetical median of 1. See also Figures S1 and S2 and Table S1.

Fully vaccinated recipients of the COVID-19 mRNA-1273 (n=12, circles), BNT162b2 (n=15, triangles), Ad26.COV2.S (n=14, squares) and NVX-CoV2373 (n=8, diamonds) vaccines were assessed for T and B cell memory to variant spikes. Fold-change values were calculated based on the response to the ancestral spike, for subjects with a measurable response. CD4 + T cell fold-change values are shown for (A) AIM and (B) ICS assay. (C) The functional profile of spike-specific CD40L + CD4 + T cells was calculated as the percentage of cells with 1, 2, 3, or 4 functions defined by intracellular staining for IFNγ, TNFα, IL-2, or granzyme B. CD8 + T cell fold-change values are shown for the (D) AIM and (E) ICS assay. (F) The functional profile of cytokine producing CD8 + T cells was calculated as the percentage of cells with 1, 2, 3, or 4 functions defined by intracellular staining for IFNγ, TNFα, IL-2, or granzyme B, excluding granzyme B single positive cells. p values for the functional profile of CD4 + and CD8 + T cells were calculated by Mann-Whitney. (G) Spike-specific cTFH + CD4 + T cells were calculated based on CXCR5 + of AIM + CD4 + T cells. SARS-CoV-2-specific memory B cells are shown to (H) spike and (I) RBD. Variant/ancestral fold-change values are shown for the (J) antibody neutralization assay as well as (K) spike and (L) RBD IgG serology. The geometric mean of the fold-change values (FC) is listed at the bottom of each graph. Significance of fold-change decreases for each variant was assessed by Wilcoxon Signed Rank T test compared to a hypothetical median of 1. See also Figures S1 and S4 and Table S1.

The number of epitopes fully conserved, or having single or multiple mutations (including insertions/deletions) was computed across SARS-CoV-2 variants. The analysis shown represents the breakdown of conserved and mutated CD4 + (A, C) and CD8 + T cell epitopes (B, D) for all SARS-CoV-2 proteins (A-B) and spike protein only (C-D). The percentage of conserved epitopes was calculated for each variant separately. Average conservancy and standard deviations were calculated for all variants, and then separately for early variants, more recent SARS-CoV-2 variants, and Omicron. (E-H) Predicted HLA binding affinities of mutated versus ancestral sequences of CD8 + T cell epitopes, based on epitope/HLA combinations curated in the IEDB data as of July 2021. Predicted HLA binding values to the relevant HLA allelic variant were calculated using the IEDB recommended NetMHCpanEL 4.1 (Reynisson et al., 2020) algorithm. Points outside the dotted lines in each panel indicate instances where the predicted HLA binding capacity of the mutated peptide was increased (>3-fold) or decreased (<3-fold). (E) Early, (F) Late, and (G) Omicron SARS-CoV-2 variants are shown. (H) Percentage of mutated CD8 + T cell epitopes associated with a 3-fold decrease in predicted binding capacity. Comparisons of epitopes conservancy across early and current variants were performed by unpaired Mann-Whitney test. Comparison with the Omicron variant was performed by One sample T test. Large font bold numbers indicate average conservation in all variants (black), Delta (ochre) and Omicron (dark red). See also Table S3 and S4. Significance of fold-change decreases for each variant was assessed by Wilcoxon Signed Rank T test compared to a hypothetical median of 1. See also Figure S5 and Table S1.

The response to SARS-CoV-2 variants was assessed in individuals 5-6 months after full vaccination with mRNA-1273 (n=4, circles). (A) CD4 + T cell epitope repertoires were determined for four mRNA-1273 vaccinees, and (C) CD8 + T cell epitope repertoires were determined for three mRNA-1273 vaccinees (no CD8 + T cell response was measurable for donor 6263) by testing the inferred HLA-class I restricted epitopes based on the individual HLA-A, -B and -C typing and applying the NetMHCpan EL4.1 algorithm implemented in the IEDB with a 4%ile cutoff. The percent of T cell response associated with conserved epitopes for each individual donor for (B) CD4 + and (D) CD8 + T cells is shown for each variant assessed. Each graph shows the total response detected with the ancestral spike MP, and the summed total response detected against each of the individual epitopes identified. The histograms show the % of the total response accounted from each epitope where black bars indicate non-mutated epitopes, while mutated epitopes are represented by open bars, with color coding further indicating which variant mutations are associated with the epitope. Based on these data the fraction of the total response to each variant that can be accounted for by non-mutated epitopes can be calculated, as also shown in the graph. See also Table S1, S2, S3 and S5.

Gating strategy for T cell AIM, ICS, and AIM+ICS assays included in this study. These gates and antibodies are the same for all timepoints. Spike-specific responses are measured for both CD4 + and CD8 + T cells within the same donors using the indicated AIM markers or cytokines. (B-C) Validation of a combined AIM/ICS assay. The addition of a cocktail of Brefeldin and Monesin in the ICS assay significantly decreases the detection of AIM markers, while the inclusion of the CD137 antibody in culture concomitantly, repristinates the response (B) and does not impact the IFNγ detection (C). Data are shown after background subtraction and stimulation index > 2. Statistical analyses are performed using a paired Wilcoxon test. (D-G) Representative gating strategy for the memory B cell assays using spike-protein at time point 3 (D) or 4 (E) or RBD at time point 3 (F) or 4 (G).

AIM + and cytokine + T cell reactivities against MPs spanning the entire sequence of different SARS-CoV-2 variants are shown for PBMCs from fully vaccinated COVID-19 mRNA-1273 (n=20, circles), BNT162b2 (n=20, triangles) and Ad26.COV2.S (n=12, squares) vaccinees analyzed by vaccine platform or combined together. Data for (A) AIM + CD4 + and (B) AIM + CD8 + T cells is shown. (C) The total cytokine response of all vaccinees combined was quantified by summing spike-specific CD40L expressing CD4 + T cells also expressing (D) IFNγ, (E) TNFα, (F) IL-2, or (G) Granzyme B. For CD8 + T cells, the total cytokine response is shown (H) as calculated by the total IFNγ (I), TNFα (J), or IL-2 (K) CD8 + T cells. The frequency of response is based on the LOS (dotted line) for the ancestral response and SI>2, while the frequency of responses across different variants is based on the number of donors responding to the ancestral spike pool. All data shown is background subtracted. 

Please refer to the Lead Contact (Alessandro Sette, alex@lji.org) for further information pertaining to availability of resources and reagents.

Upon specific request and execution of a material transfer agreement (MTA) to the Lead Contact or to A.G., aliquots of the peptide pools utilized in this study will be made available. Limitations will be applied on the availability of peptide reagents due to cost, quantity, demand and availability.

All the data generated in this study are available in the published article and summarized in the corresponding tables, figures and supplemental materials. Supplementary Table S4 is available at the current link: https://data.mendeley.com/datasets/4dxbxkf5ct/1.

The La Jolla Institute for Immunology (LJI) Clinical Core recruited healthy adults who had received the first and, when applicable, second dose of a COVID-19 vaccination among the mRNA-1273, BNT162b2, Ad26.COV2.S or NVX-CoV2373 available vaccinations. At the time of enrollment in the study, all donors gave informed consent. The LJI Clinical Core facility has collected blood draws under IRB approved protocols (LJI; VD-214) when possible two weeks after each vaccine dose administered (timepoint 1 and timepoint 2), 3.5 months after the last dose received (timepoint 3) and/or 5-6 months after the last dose (timepoint 4). All donors had their SARS-CoV-2 antibody titers measured by ELISA, as described below. Additional information on gender, ethnicity, age and timepoint of collection of the vaccinee cohorts are summarized in Table S1 . Pheresis blood donations from an additional cohort of mRNA vaccinees were provided by the contact research organization (CRO) BioIVT and collected under the same IRB approval (VD-214) at LJI.

Recombinant SARS-CoV-2-spike pseudotyped VSV-ΔG-GFP were generated with the specific amino acid mutations listed: 

The genome sequences for the B.1.1.7, B.1.351, P.1. and B.1.427/429 variants were selected as previously described (Tarke et al., 2021b) . For the additional variants selected, the sequence variations in the variant viruses were derived by comparison with Wuhan-1 (NC_045512.2). All mutated amino acids in the different variants are outlined in Table S3 . To determine the impact of the selected variants on T cell epitopes, CD4 and CD8 T cell epitopes were extracted from the IEDB database (www.IEDB.org)(Vita et al., 2019) on July 8 th 2021 using the following query: Organism: SARS-CoV2 (ID:2697049, SARS2), Include positive assays only, No B cells, No MHC assays, Host: Homo sapiens (human) and either MHC restriction type: Class I for CD8 epitopes or Class II for CD4 epitopes. Additional manual filtering was performed on the extracted datasets allowing only epitopes of 9-14 residues in size for class I and 13-25 residues for class II. This resulted in a total of 446 and 1092 epitopes for CD4 and CD8, respectively. The binding capacity of SARS-CoV-2 T cell epitopes, and their corresponding variant-derived peptides, was determined for their putative HLA class I restricting allele(s) in a smaller epitope subset (n=833) where information regarding allele restriction was available. Prediction analyses for class I were determined utilizing the NetMHCpan EL4.1 algorithm (Reynisson et al., 2020) implemented by the IEDB's analysis resource (Dhanda et al., 2019; Vita et al., 2019) . Predicted binding for class I analyses are expressed in terms of percentile. For each epitope-variant pair a fold-change (FC) of affinities (variant /WT) was determined, corresponding values FC >3, indicating a 3-fold or greater decrease in affinity due to the mutation, were accordingly categorized as a decrease in binding capacity, and a FC <0.3 as an increase; FCs between 0.3 and 3 were designated as neutral.

All the peptides used in this study were synthesized as crude material ( 1.1.529) ]. The Megapools (MP) for each variant were created by pooling aliquots of the corresponding individual peptides and then performing a sequential lyophilization. The resulting lyocake was subsequently resuspended in DMSO at 1 mg/mL as previously described Tarke et al., 2021a; Tarke et al., 2021b) .

The LJI Clinical Core performed blood collection and sample processing based on SOPs previously established and described (Dan et al., 2021; Tarke et al., 2021a) .

Whole blood was collected in heparin coated blood bags, and the cellular fraction was separated from plasma by a centrifugation at 1850 rpm for 15 minutes. The plasma was consequently collected and stored at -20°C for serology assays, while the cellular fraction underwent density-gradient sedimentation to obtain the PBMCs using Ficoll-Paque (Lymphoprep, Nycomed Pharma, Oslo, Norway) . Isolated PBMCs were stored in liquid nitrogen in cryopreserved cell recovery media containing 90% heat-inactivated fetal bovine serum (FBS; Hyclone Laboratories, Logan UT) and 10% DMSO (Gibco) until cellular assays were performed. HLA typing was performed by an ASHI-accredited laboratory at Murdoch University (Western Australia) for Class I (HLA A; B; C) and Class II (DRB1, DRB3/4/5, DQA1/DQB1, DPB1), as previously described(Tarke et al., 2021a) ( Table S2) .

SARS-CoV-2 serology was performed for all plasma samples collected as previously described (Rydyznski Moderbacher et al., 2020) . Briefly, 1 ug/mL SARS-CoV-2 spike (S) Receptor Binding Domain (RBD) was used to coat 96-well half-area plates (ThermoFisher Cat#3690), which were then incubated at 4°C overnight. After blocking the plates the next day at room temperature for 2 hours with 3% milk in phosphate buffered saline (PBS) and 0.05% Tween-20, the heat-inactivated plasma was added for an additional 90-minute incubation at room temperature, followed by incubation with the conjugated secondary antibody. Plates were read on the Spectramax Plate Reader at 450 nm using the SoftMax Pro. For data analysis of SARS-CoV-2 serology, the limit of detection (LOD) was defined as 1:3 while the limit of sensitivity (LOS) was established based on uninfected subjects, using plasma from normal healthy donors that did not receive COVID-19 vaccination.

The SARS-CoV-2 pseudovirus (PSV) neutralization assay was performed for timepoint 3 samples as previously described (Mateus et al., 2021) . A monolayer of VERO cells (ATCC, Cat# CCL-81) was generated by seeding 2.5x10 4 cells in flat clear-bottom black 96-well plates (Corning, Cat# 3904). Pretitrated recombinant virus for each variant were incubated with serially diluted human heat-inactivated plasma at 37°C for 1-1.5 hours. Confluent VERO cell monolayers were added and incubated for 16 hours at 37°C in 5% CO2 then fixed in 4% paraformaldehyde in PBS pH 7.4 (Santa Cruz, Cat# sc-281692) with 10 μg/ml Hoechst (Thermo Scientific, Cat#62249). Cells were imaged using a Cell Insight CX5 imager to quantify the total number of cells and infected GFP expressing cells to determine the percentage of infection. Neutralization titers (inhibition dose 50-ID50) were calculated using the One-Site Fit Log IC50 model in Prism 8.0 (GraphPad), and calibrated to WHO international standard (20/268). Samples that did not reach 50% inhibition at the lowest serum dilution of 1:20 were considered as non-neutralizing and were calibrated as 10.73 IU/mL.

Activation Induced Marker (AIM) and Intra Cellular Staining (ICS) assays have been separately described in detail previously Mateus et al., 2021; Tarke et al., 2021b) . In this study, we performed both assays separately at timepoint 3, while we combined them for timepoints 1, 2, and 4. To assess the best protocol for AIM+ICS assay, we carried out the three assays in parallel in the same samples ( Figure S1 ). The best assay configuration to retain AIM marker expression and simultaneously detect cytokines required the addition of CD137 antibody to culture as described in detail below. Figure  S1 shows also the comparison of this AIM+ICS protocol with the classical AIM or ICS assays; no significant differences are observed amongst protocols, suggesting that the combined assay can be used to simultaneously detect AIM + cells and the cytokine profile.

In all T cell assays, PBMCs were cultured in the presence of SARS-CoV-2-specific (ancestral or variant) MPs [1 μg/ml] in 96-well U-bottom plates at a concentration of 1x10 6 PBMC per well. As a negative control, an equimolar amount of DMSO was used to stimulate the cells in triplicate wells and phytohemagglutinin (PHA, Roche, 1μg/ml) stimulated cells were used as positive controls. After incubation for 24 hours at 37°C in 5% CO2, cells were either stained for AIM markers only or an additional incubation of 4 hours was carried out by adding Golgi-Plug containing brefeldin A, Golgi-Stop containing monensin (BD Biosciences, San Diego, CA), and in the case of the AIM+ICS assay combined CD137 APC antibody was additionally added in culture (2:100; Biolegend Cat# 309810). In all assays, cells were stained on their surface for 30 min at 4°C in the dark. For AIM assays, cells were then acquired directly, while for both ICS and AIM+ICS assays, cells were additionally fixed with 1% of paraformaldehyde (Sigma-Aldrich, St. Louis, MO), permeabilized, and blocked for 15 minutes followed by intracellular staining for 30 min at room temperature.

All samples were acquired on a ZE5 5-laser cell analyzer (Bio-Rad laboratories) and analyzed with FlowJo software (Tree Star Inc.). The gates for AIM or cytokine positive cells were drawn relative to the negative and positive controls for each donor. A representative example of the gating strategy for AIM, ICS or AIM+ICS assays is depicted in Figure S1 . Specifically, lymphocytes were gated, followed by single cells determination. T cells were gated for being positive to CD3 and negative for a Dump channel including in the same colors CD14, CD19 and Live/Dead staining. The CD3 + CD4 + and CD3 + CD8 + were further gated based on OX40 + CD137 + and CD69 + CD137 + AIM markers, respectively. For ICS, CD3 + CD4 + and CD3 + CD8 + cells were further gated based on a combination of each cytokine (IFNγ, TNFα, IL-2, Granzyme B) with CD40L or FSC-A, respectively ( Figure S1 ). To the total cytokine response and T cell functionality was calculated from Boolean gating of single cytokines or Granzyme B that was applied to CD3 + CD4 + or CD3 + CD8 cells. In the resulting data generated from the AIM and ICS T cell assays, the background was removed from the data by subtracting the average of the % of AIM + or Cytokine + cells plated in triplicate wells stimulated with DMSO. The Stimulation Index (SI) was calculated by dividing the % of AIM + cells after SARS-CoV-2 stimulation with the average % of AIM + cells in the negative DMSO control. An SI greater than 2 and a LOS of 0.03% or 0.04 % AIM + CD4 + or CD8 + cells, respectively, after background subtraction was considered to be a positive response based on the median twofold standard deviation of T cell reactivity in negative DMSO controls. For ICS, CD4 + T cell responses were based on the expression of CD40L in combination with IFNγ, TNFα, IL-2 or Granzyme B, the sum of the double positive represents the overall CD4 + Cytokine + . CD8 + T cell responses were based on expression of IFNγ, TNFα, IL-2 or Granzyme B. In both cases, each single and multiple positive cytokines were background subtracted individually and found positive only if fulfilling the criteria of an SI greater than 2 and a LOS of 0.005% ICS + CD4 + T cells (all timepoints) or and a LOS of 0.02% or 0.01% ICS + CD8 + cells, for timepoints 2 and 3 or 4, respectively, after background subtraction. The LOS for ICS was considered to be a positive response based on the median twofold standard deviation of T cell reactivity in negative DMSO controls for all timepoints calculated on IFNγ. The multifunctional analyses for T cells were based on the sum of the multiple responses. To note, granzyme B was considered only if in combination with either CD40L or any other cytokine, while single positive granzyme B positive T cells were not considered in this analysis.

To identify SARS-CoV-2-specific T cell epitopes, two different strategies for peptide testing were applied mirroring what was previously described (Tarke et al., 2021a). In both cases, epitopes were identified by AIM assay. In the context of the CD4 + T cell responses, 15-mer peptides overlapping by 10 amino acids spanning entire SARS-CoV-2 ancestral spike protein were synthesized. All peptides were synthesized as crude material (TC Peptide Lab, San Diego, CA, San Diego, CA) and individually resuspended in dimethyl sulfoxide (DMSO) at a concentration of 20 mg/mL. A portion of the 15-mer peptides were pooled into smaller mesopools of ten peptides each. All pools were resuspended at 1 mg/mL in DMSO. Each donor was tested first with the smaller mesopools to reach the single positive 15 mer. In the context of the CD8 + T cell responses, predicted spike peptides based on the individual HLA-A,-B and C typing were synthetized applying a cutoff of 4%ile using the NetMHCpan EL4.1 algorithm (Reynisson et al., 2020) implemented by the IEDB's analysis resource (Dhanda et al., 2019; Vita et al., 2019) . The predicted peptides were tested in the corresponding donors to identify the CD8 spike-specific epitopes. Hence, HLA restriction was inferred based on the HLA molecules expressed in the donor tested, and predicted HLA binding capacity to the allelic variant in question.

Detection of antigen-specific B cells by flow cytometry was performed using B cell probes consisting of SARS-CoV-2 viral proteins conjugated with fluorescent streptavidin, as previously described by our group (Dan et al., 2021) . Spike and RBD recombinant proteins used in this study are described in the Key Resource Table. Initially, two separate flow cytometry panels were used to identify Spike or RBD variants among recipients of the four vaccine platforms studied here. A third and a fourth panel were used to compare Omicron-specific B cell responses with the other VOCs, in PBMCs from mRNA vaccines (mRNA-1273 and BNT162b2) recipients. To enhance specificity, identification of both WT spike and WT RBD B cells was performed using two fluorochromes for each protein, prior to gating on variant B cells. For that, biotinylated WT SARS-CoV-2 spike was incubated with Streptavidin in either BV711 (BioLegend, Cat# 405241) or BV421 (BioLegend, Cat# 405225) at a 20:1 ratio (~6:1 molar ratio) for 1 hour at 4°C. In a separate panel, biotinylated WT RBD was also conjugated with streptavidin BV711 ( For the additional two panels employed to identify Omicron-specific B cells, the colors used for the variants for both RBD and Spike were: B.1.351 BUV615, B.1.1.529 BUV737, RBD.617.2. For the RBD panel, RBD B.1.1.7 labelled with BV785 was also included in the analysis.

Streptavidin PE-Cy5.5 (Thermo Fisher Scientific, Cat# SA1018) was used as a decoy probe to minimize background by eliminating SARS-CoV-2 nonspecific streptavidin-binding B cells. Seven million PBMCs were placed in U-bottom 96 well plates and stained with a solution consisting in 5µ of biotin (Avidity, catalog no. Bir500A) to avoid cross reactivity among probes, 20 ng of decoy probe, 416 ng of spike and 20.1 ng of RBD per sample, diluted in Brilliant Buffer (BD Biosciences, Cat# 566349) and incubated for 1 hour at 4°C, protected from light. After washing with PBS, cells from both spike and RBD panels were incubated with surface antibodies diluted in Brilliant Buffer, for 30 at 4°C, protected from light. Viability staining was performed using Live/Dead Fixable Blue Stain Kit (Thermo Fisher, Cat# L34962) diluted 1:200 in PBS and incubation at 4°C for 30 minutes. Acquisition was performed on Cytek Aurora and analyses were made using Flow Jo v. 10.7.1 (BD Biosciences). The frequency of Variantsspecific memory B cells was expressed as a percentage of WT spike or RBD memory B cells (Singlets, Lymphocytes, Live, CD3-CD14-CD16-CD56-CD19+ CD20+ CD38int/-, IgD-and/or CD27+ spike or RBD BV711+, spike or RBD BV421+). PBMCs from a known positive control (COVID-19 convalescent subject) and an unexposed subject were included to ensure consistent sensitivity and specificity of the assay.

Data and statistical analyses were performed in FlowJo 10 and GraphPad Prism 8.4, unless otherwise stated. Statistical details of the experiments are provided in the respective figure legends and in each methods section pertaining to the specific technique applied. Data plotted in logarithmic scales are expressed as geometric mean. In all assays, fold-change (FC) was calculated as the ratio of the variant pool/ ancestral pool for samples with a positive ancestral pool response. Significance of fold-change decreases for each variant was assessed by Wilcoxon Signed Rank T test compared to a hypothetical median of 1. Stamatatos, L., Czartoski, J., Wan, Y.H., Homad, L.J., Rubin, V., Glantz, H., Neradilek, M., Seydoux, E., Jennewein, M.F., MacCamy, A.J., et al. (2021) . mRNA vaccination boosts crossvariant neutralizing antibodies elicited by SARS-CoV-2 infection. Science.

Tan, A.T., Linster, M., Tan, C.W., Le Bert, N., Chia, W.N., Kunasegaran, K., Zhuang, Y., Tham, C.Y.L., Chia, A., Smith, G.J.D., et al. (2021) . Early induction of functional SARS-CoV-2-specific T cells associates with rapid viral clearance and mild disease in COVID-19 patients. Cell reports, 108728.

Tarke, A., Sidney, J., Kidd, C.K., Dan, J.M., Ramirez, S.I., Yu, E.D., Mateus, J., da Silva Antunes, R., Moore, E., Rubiro, P., et al. (2021a) . Comprehensive analysis of T cell immunodominance and immunoprevalence of SARS-CoV-2 epitopes in COVID-19 cases. Cell reports Medicine 2, 100204.

Tarke, A., Sidney, J., Methot, N., Yu, E.D., Zhang, Y., Dan, J.M., Goodwin, B., Rubiro, P., Sutherland, A., Wang, E., et al. (2021b) . Impact of SARS-CoV-2 variants on the total CD4(+) and CD8(+) T cell reactivity in infected or vaccinated individuals. Cell reports Medicine 2, 100355.

Uriu, K., Kimura, I., Shirakawa, K., Takaori-Kondo, A., Nakada, T.A., Kaneda, A., Nakagawa, S., Sato, K., and Genotype to Phenotype Japan, C. 1 1.1 1.1 1.1 1.0 1.0 1.0 1 1 1.1 1.1 1.1 1.0 1.0 1.0 1 **** **** in v a ri a n ts in v a ri a n ts in v a ri a n ts in v a ri a n ts in v a ri a n ts T cells   P26S  P26S  Q25R  H69-; V70-; A67V  D138Y; G142D;  V143-145del   R190S  L241-, L242-, A243-S371L, S373P, S375F  N440K  T547K  H655Y  T547K  Q677H; N679K  A701V  T716I   N764K   G769V; 88 100 100 100 100 100 100 100 100 19 19 19 19 19 19 19 19 19 100 100 100 100 100 100 100 100 100 16 16 16 16 16 16 16 16 16 80 100 100 100 100 100 100 100 100 10 10 10 10 10 10 10 10 10 83 100 100 100 100 100 100 100 17 17 17 17 17 17 17 17 17 17 17 Frequency 89 100 100 100 100 100 100 100 100 100 J o u r n a l P r e -p r o o f

Beyond Omicron: what's next for COVID's viral evolution

Broadly neutralizing antibodies overcome SARS-CoV-2 Omicron antigenic shift. bioRxiv

Activity of convalescent and vaccine serum against a B.1.1.529 variant SARS-CoV-2 isolate. medRxiv

SARS-CoV-2 Omicron has extensive but incomplete escape of Pfizer BNT162b2 elicited neutralization and requires ACE2 for infection

Mode of Transmission, and Mutational Landscape of Newly Emerging SARS-CoV-2 Variants

Anti-SARS-CoV-2 receptor-binding domain antibody evolution after mRNA vaccination

Immune Responses in Fully Vaccinated Individuals Following Breakthrough Infection with the SARS-CoV-2 Delta Variant in

Immunological memory to SARS-CoV-2 assessed for up to 8 months after infection

IEDB-AR: immune epitope database-analysis resource in 2019

Protection from SARS-CoV-2 Delta one year after mRNA-1273 vaccination in rhesus macaques coincides with anamnestic antibody response in the lung

mRNA-based COVID-19 vaccine boosters induce neutralizing immunity against SARS-CoV-2 Omicron variant

SARS-CoV-2 variants of concern partially escape humoral but not T-cell responses in COVID-19 convalescent donors and vaccinees

mRNA Vaccination Induces Durable Immune Memory to SARS-CoV-2 with Continued Evolution to Variants of Concern

SARS-CoV-2 human T cell epitopes: Adaptive immune response against COVID-19

Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals

SARS-CoV-2 variants, spike mutations and immune escape

Omicron SARS-CoV-2 variant: a new chapter in the COVID-19 pandemic

Prior infection with SARS-CoV-2 boosts and broadens Ad26.COV2.S immunogenicity in a variant-dependent manner

Differential immunogenicity of homologous versus heterologous boost in Ad26.COV2.S vaccine recipients. medRxiv

Striking Antibody Evasion Manifested by the Omicron Variant of SARS-CoV-2. bioRxiv

Omicron-specific cytotoxic T-cell responses are boosted following a third dose of mRNA COVID-19 vaccine in anti-CD20-treated multiple sclerosis patients. medRxiv

Recognition of Variants of Concern by Antibodies and T Cells Induced by a SARS-CoV-2 Inactivated Vaccine

SARS-CoV-2 B.1.617.2 Delta variant replication and immune evasion

The origins and potential future of SARS-CoV-2 variants of concern in the evolving COVID-19 pandemic

Experimental validation of the RATE tool for inferring HLA restrictions of T cell epitopes

Considerable escape of SARS-CoV-2 variant Omicron to antibody neutralization. bioRxiv

NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data

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Plasma neutralization properties of the SARS-CoV-2 Omicron variant. medRxiv

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mRNA vaccination of naive and COVID-19-recovered individuals elicits potent memory B cells that recognize SARS-CoV-2 variants

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Mouse anti-human CD3 BUV805 (clone UCHT1) BD Biosciences Cat# 612895

Mouse anti-human TNF alpha eFluor450 (clone MAb11) Life Tech Cat#

RRID:AB_2043889 Mouse anti-human CD14 V500 (clone M5E2) BD

Mouse anti-human CD19 V500 (clone HIB19) BD

Mouse anti-human CD4 BV605 (clone RPA-T4) BD

Mouse anti-human IFN gamma FITC (clone 4S.B3) Invitrogen

RRID:AB_465415 Rat anti-human IL-2 BB700 (clone MQ1-17H12) BD Biosciences Cat# 566405

RRID:AB_2744488 Mouse anti-human CD69 PE (clone FN50) BD Biosciences Cat# 555531

RRID:AB_395916 Mouse anti-human CD134 (OX40) PE-Cy7 (clone Ber-ACT35

Mouse anti-human CD4 BV605 (clone RPA-T4) BD

RRID:AB_2744420 Rat anti-human CXCR5 (CD185) BB700 (clone RF8B2) BD Biosciences Cat# 566469

RRID:AB_2869769 Mouse anti-human CD279 (PD-1) PE-Dazzle594 (clone EH12.2H7) BioLegend Cat# 329940

Mouse anti-human CD19 BUV563 (clone SJ25C1) BD

Mouse anti-human IgD Pacific Blue (clone IA6-2) BioLegend Cat# 348224

RRID:AB_2561597 Mouse anti-human CD20 BV510 (clone 2H7) BioLegend Cat# 302340

Mouse anti-human IgM BV570 (clone MHM-88) BioLegend Cat# 314517

Mouse anti-human CD27 BB515 (clone M-T271

Mouse anti-human IgA Vio Bright FITC (clone IS11-8E10) Miltenyi Biotec Cat#

BioLegend Cat# 344814

Mouse anti-human CD14 PerCP (clone 63D3) BioLegend Cat# 367152

RRID:AB_2876693 Mouse anti-human CD16 PerCP (clone 3G8) BioLegend Cat# 302030

RRID:AB_940380 Mouse anti-human CD56 PerCP (clone 3G8) BioLegend Cat# 318342

RRID:AB_2561865 Mouse anti-human IgG PerCP/Cyanine5.5 (clone M1310G05) BioLegend Cat#

Chemicals, peptides, and recombinant proteins Brilliant Staining Buffer Plus BD Biosciences Cat# 566385

Live/Dead Viability Dye eFluor506

Live/Dead Fixable Blue Stain Kit Thermo Fisher Scientific Cat# L34962 Synthetic peptides TC Peptide Lab

This project has been funded in whole or in part with Federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under Contract No. 75N93021C00016 to A.S. and Contract No. 75N9301900065 to A.S, D.W. A.T. was supported by a PhD student fellowship through the Clinical and Experimental Immunology Course at the University of Genoa, Italy. We thank Gina Levi and the LJI clinical core for assistance in sample coordination and blood processing. We gratefully thank the authors from the originating laboratories responsible for obtaining the specimens, as well as the submitting laboratories where the genome data were generated and shared via GISAID, and on which this research is based. We would like to thank Vamseedhar Rayaprolu and Erica Ollmann Saphire for providing the recombinant SARS-CoV-2 Receptor Binding Domain (RBD) protein used in the ELISA assay.