mRNA vaccine-induced T cells respond identically to SARS-CoV-2 variants of concern but differ in longevity and homing properties depending on prior infection status
A year and a half since the December 2019 emergence of SARS-CoV-2 , the novel betacoronavirus had already infected almost 200 million people and taken the lives of over 4 million , nearly collapsed worldwide health systems , disrupted the global economy , and perturbed society and public health on a scale not experienced within the past 100 years . Fortunately , multiple highly efficacious vaccines , including the two-dose mRNA-based ones developed by Pfizer/BioNTech and Moderna , which confer ~90 % protection against disease , were approved for emergency use before the end of 2020 . Although the vaccines provide the most promising route for a rapid exit from the COVID-19 pandemic , concerns remain regarding the durability of the immunity elicited by these vaccines and the extent to which they will protect against the variants of SARS-CoV-2 now spreading rapidly around the world . The first variant observed to display a survival advantage was the D614G , which was more transmissible than the original strain and quickly became the dominant variant throughout the world Korber et al . , 2020 . This variant , fortunately , did not evade immunity and in fact appeared to be more sensitive than the original strain to antibody neutralization by convalescent sera Weissman et al . , 2021 . More worrisome , however , was the emergence at the end of 2020 of rapidly spreading variants in multiple parts of the world , including B . 1 . 1 . 7 , B . 1 . 351 , P . 1 , and B . 1 . 427/B . 1 . 429 ( originally identified in United Kingdom , South Africa , Brazil , and California , respectively ) Plante et al . , 2021 , followed by additional highly transmissible variants in 2021 including the B . 1 . 617 . 2 which was first detected in India Callaway , 2021 . Some variants , including B . 1 . 1 . 7 , may be more virulent Davies et al . , 2021 . While antibodies against the original strain elicited by either vaccination or infection generally remain potent against B . 1 . 1 . 7 , their activity against B . 1 . 351 and P . 1 is compromised Wang et al . , 2021; The CITIID-NIHR BioResource COVID-19 Collaboration et al . , 2021; Muik et al . , 2021; Garcia-Beltran et al . , 2021; Stamatatos et al . , 2021; Cele et al . , 2021; Hoffmann et al . , 2021; Planas et al . , 2021; Edara et al . , 2021; Kuzmina et al . , 2021 . Antibodies from vaccinees were 14-fold less effective against B . 1 . 351 than against the ancestral strain , and a subset of individuals completely lacked neutralizing antibody activity against B . 1 . 351 9 months or more after convalescence Planas et al . , 2021 . Reassuringly , early data suggest that relative to antibody responses , T-cell-mediated immunity appears to be less prone to evasion by the variants Skelly et al . , 2021; Tarke et al . , 2021; Redd et al . , 2021; Geers et al . , 2021; Woldemeskel et al . , 2021; Stankov et al . , 2021; Tauzin et al . , 2021 . Among 280 CD4+ and 523 CD8+ T cell epitopes from the original SARS-CoV-2 , an average of 91 . 5 % ( for CD4 ) and 98 . 1 % ( for CD8 ) mapped to regions not mutated in the B . 1 . 1 . 7 , B1 . 351 , P . 1 , and B . 1 . 427/B . 1 . 429 variants . Focusing on just the spike response , the sole SARS-CoV-2 antigen in the mRNA-based vaccines , then 89 . 7 % of the CD4+ epitopes and 96 . 4 % of the CD8+ epitopes are conserved Tarke et al . , 2021 . In line with this , the magnitude of the response of T cells from convalescent or vaccinated individuals was not markedly reduced when assessed against any of the variants Tarke et al . , 2021 . The relative resistance of T cells against SARS-CoV-2 immune evasion is important in light of the critical role these immune effectors play during COVID-19 . T cell numbers display a strong , inverse association with disease severity Chen et al . , 2020; Woodruff et al . , 2020 , and the frequency of SARS-CoV-2-specific T cells predicts recovery from severe disease Rydyznski Moderbacher et al . , 2020; Neidleman et al . , 2021 . SARS-CoV-2-specific T cells can also provide long-term , self-renewing immunological memory: these cells are detected more than half a year into convalescence and can proliferate in response to homeostatic signals Dan et al . , 2021; Neidleman et al . , 2020b . Furthermore , the ability of individuals with inborn deficiencies in B cell responses to recover from COVID-19 without intensive care suggests that the combination of T cells and innate immune mechanisms is sufficient for recovery when antibodies are lacking Soresina et al . , 2020 . Although T cells against the ancestral strain display a response of similar magnitude and breadth to the variants Tarke et al . , 2021 , to what extent these T cells’ phenotypes and effector functions differ during their response to variant detection is a different question . Small changes in the sequences of T cell epitopes , in the form of altered peptide ligands ( APLs ) , can theoretically alter how the T cells respond to stimulation . Indeed , change of a single residue can convert a proliferative , IL4-secreting effector response into one that continues to produce IL4 in the absence of proliferation Evavold and Allen , 1991 . Furthermore , APLs can activate Th1 cells without inducing either proliferation or cytokine production , shift Th1 responses into Th2-focused ones , and in some instances even render T cells anergic or immunoregulatory by eliciting TGFβ production Sloan-Lancaster and Allen , 1996 . Another important aspect that has not been explored is to what extent vaccine- vs . infection-induced T cell responses differ phenotypically and functionally , and to what extent convalescent individuals benefit from vaccination as they already harbor some form of immunity against the virus . Studies based on the antibody and B cell response suggest that for COVID-19 convalescents , a single dose of the mRNA vaccines is helpful while the additional booster is not necessary Stamatatos et al . , 2021; Goel et al . , 2021; Ebinger et al . , 2021; how this translates in the context of vaccine-elicited T cell immunity is not clear . To address these knowledge gaps , we conducted 39-parameter phenotyping by CyTOF on 33 longitudinal specimens from 11 mRNA-vaccinated individuals , six of whom had previously contracted and recovered from COVID-19 . For each participant , blood specimens were obtained prior to vaccination , two weeks following the first dose , and two weeks following the second . For every specimen , we assessed in depth the phenotypes and effector functions of total CD4+ and CD8+ T cells , and of CD4+ and CD8+ T cells responding to the original SARS-CoV-2 spike , to spike from variants B . 1 . 1 . 7 and B . 1 . 351 , and to nucleocapsid . By conducting analyses on the resulting 165 high-dimensional datasets generated , we find a reassuringly unaltered T cell response against the variants , an ability of the booster dose to alter the phenotypes of vaccine-elicited T cells , and a striking impact of prior infection on qualitative features of T cells elicited by vaccination .
To characterize the phenotypic features of mRNA vaccination-elicited SARS-CoV-2-specific T cells , we procured 33 longitudinal blood samples from the COVID-19 Host Immune Response and Pathogenesis ( CHIRP ) cohort . Four of the participants had received the Moderna ( mRNA-1273 ) vaccine , while the remaining seven had received the Pfizer/BioNTech ( BNT162b2 ) one . For all participants , longitudinal specimens were obtained at three timepoints: prior to vaccination , ~ 2 weeks ( range 13–18 days ) after the first vaccine dose , and ~2 weeks ( range 6–38 days ) after the second dose . Five of the participants were never infected with SARS-CoV-2 , while the remaining six had completely recovered from mild ( non-hospitalized ) COVID-19 disease ( Table 1 ) . These prior infections had all occurred in the San Francisco Bay Area between March and July of 2020 , when the dominant local strain was the original ancestral strain . Each specimen was phenotyped using a 39-parameter T cell-centric CyTOF panel ( see Materials and methods and Table 2 ) at baseline ( to establish the overall phenotypes of total CD4+ and CD8+ T cells ) , and following 6 hr of stimulation with overlapping 15-mer peptides spanning the entire original ( ancestral ) SARS-CoV-2-spike , B . 1 . 1 . 7 spike , B . 1 . 351 spike , or the original SARS-CoV-2 nucleocapsid ( the latter as a control for a SARS-CoV-2-specific response not boosted by vaccination ) . Including all the baseline and stimulation conditions , a total of 165 specimens from the 11 participants were analyzed by CyTOF . We first confirmed our ability to identify SARS-CoV-2-specific T cells by stimulating PBMCs from vaccinated individuals with spike peptides . In line with our prior studies implementing a 6 hr peptide stimulation Neidleman et al . , 2021; Neidleman et al . , 2020b , spike-specific CD4+ T cells could be specifically identified through intracellular cytokine staining for IFNγ , and a more robust response was observed among CD4+ than CD8+ T cells ( Figure 1 ) . No specific induction of IL4 or IL17 by CD4+ T cells were observed in response to peptide stimulation ( Figure 1—figure supplement 1 ) . In addition , activation-induced markers ( AIM ) such as Ox40 , 4-1BB , and CD69 could also be identified in T cells after spike peptide stimulation , but with a higher background in the baseline ( no peptide stimulation ) specimens relative to the intracellular cytokine staining approach ( Figure 1—figure supplement 1 ) . For these reasons , in this study we exclusively used IFNγ positivity in the peptide-stimulated samples as a marker of antigen-specific T cells . In the infection-naïve participants , the first vaccination dose primed a spike-specific CD4+ T cell response , which was further boosted with the second dose ( Figure 1B , top left ) . For each participant and time point , similar numbers of cells were stimulated by exposure to the ancestral or variant spikes . This finding suggests that vaccine-elicited spike-specific CD4+ T cells recognize ancestral and variant spike equally well , and is consistent with their recently reported ability to recognize variant strains Tarke et al . , 2021 . The response of vaccine-elicited CD8+ T cells to spike peptides was weaker , and mostly apparent only after the second dose ( Figure 1B , top right ) . As expected , vaccination did not elicit T cells able to respond to nucleocapsid peptides ( Figure 1C , top panels ) . In contrast to the infection-naïve individuals where spike-specific CD4+ T cells were clearly elicited and then boosted upon the second dose , spike-specific CD4+ T cell responses in convalescent individuals did not show a consistent upward trend . Convalescent donor PID4112 had a large frequency of pre-vaccination SARS-CoV-2-specific CD4+ T cells that increased to >1% of the total CD4+ T cell frequency after the first dose and then dampened after dose 2 ( Figure 1B , bottom left ) . PID4112 also exhibited an elevated nucleocapsid-specific CD4+ T cell response after the first vaccination dose ( Figure 1C , bottom left ) , which may have been due to bystander effects resulting from the concomitant large spike-specific response . In comparison , PID4112’s spike-specific CD8+ T cell response was low after dose 1 , and boosted after dose 2 ( Figure 1B , bottom right ) . In contrast to PID4112 , the remaining five convalescent donors exhibited an overall weak spike-specific T cell response . In fact , when comparing these five donors to the five infection-naïve donors , there was a significant decrease in the magnitude of the spike-specific CD4+ T cell response , while the spike-specific CD8+ T cell response was equivalent between the two groups ( Figure 1D ) . These results were unexpected and suggest that , when excluding outlier PID4112 , the magnitude of the vaccine-elicited spike-specific CD4+ T cell response ( after full vaccination ) was lower in convalescent individuals than in infection-naïve individuals . These assessments of the magnitude of the spike-specific T cell response together suggest that ( 1 ) in infection-naïve individuals the CD4+ T cell response is boosted by the second vaccination dose , ( 2 ) convalescent individuals exhibit a more disparate response , with most donors mounting a weaker response than infection-naïve individuals , and ( 3 ) the response is more robust among CD4+ than CD8+ T cells . As a higher number of SARS-CoV-2-specific CD4+ T cells were available for analysis , we focused on this subset for our subsequent analyses . Leveraging our ability to not only assess the magnitude but also the detailed ( 39-parameter ) phenotypic features of SARS-CoV-2-specific CD4+ T cells , we first determined whether the ancestral and variant spike epitopes stimulated different subsets of vaccine-elicited spike-specific CD4+ T cells . Such differences could theoretically result from the fact that ~5–10% of the spike epitopes differ between variants and ancestral strains Tarke et al . , 2021 , and may therefore act as APLs steering responding cells towards different fates . We isolated the datasets corresponding to both post-vaccination timepoints for all eleven donors , and then exported the data corresponding to spike-specific CD4+ T cells ( as defined by IFNγ production , Figure 1 ) . After reducing the multidimensional single-cell data for each individual specimen to a two-dimensional datapoint through multidimensional scaling ( MDS ) Ritchie et al . , 2015 , we observed the ancestral spike-stimulated samples to be interspersed among the B . 1 . 1 . 7- and B . 1 . 351-responding ones ( Figure 2A ) . We then visualized the spike-specific CD4+ T cells at the single-cell level . When visualized alongside total ( baseline ) CD4+ T cells , spike-specific cells occupied a distinct ‘island’ defined by high expression of IFNγ ( Figure 2B ) , suggesting unique phenotypic features of these cells . To better analyze these spike-responding CD4+ T cells , we visualized them in isolation within a new tSNE which clearly demonstrated complete mixing of the cells stimulated by the ancestral , B . 1 . 1 . 7 , and B . 1 . 351 spike proteins ( Figure 2C ) . Almost all the responding cells expressed high levels of CD45RO and low levels of CD45RA ( Figure 2D ) , suggesting them to be mostly memory cells . These memory CD4+ T cells included central memory T cells ( Tcm ) , T follicular helper cells ( Tfh ) , and those expressing multiple activation markers ( CD38 , HLADR , CD69 , CD25 ) and receptors known to direct cells to tissues including the respiratory tract ( CXCR4 , CCR5 , CCR6 , CD49d ) ( Figure 2E ) . The expression levels of these and all other antigens quantitated by CyTOF were not statistically different between CD4+ T cells responding to the three spike proteins ( Figure 2—figure supplement 1 ) . To confirm the identical phenotypes of the three groups of spike-responding cells , we implemented unbiased clustering by FlowSOM . Spike-stimulated cells were clustered into eight subsets , and no subset was preferentially enriched in any one of the three groups ( Figure 2F ) . Together , these data suggest that vaccine-elicited spike-specific CD4+ T cells respond in the same manner to spike epitopes from the ancestral or variant strains , and would probably mount similar responses in vivo to infection by all three virus types . We next took advantage of our longitudinal study design to assess for any changes in the differentiation of spike-specific T cell responses over the course of the 2-dose vaccination . As the data presented above suggested no phenotypic differences between CD4+ T cells responding to the ancestral , B . 1 . 1 . 7 , and B . 1 . 351 spike proteins , our subsequent analyses combined these datasets . We first assessed whether , among infection-naïve individuals , the phenotypes of spike-specific CD4+ T cells were different after the first and second doses . While MDS and tSNE visualizations of the data revealed that the cells from the two timepoints were somewhat interspersed ( Figure 3A-B ) , FlowSOM clustering suggested some differences in cluster distribution ( Figure 3C-D ) . Direct comparison of the cluster frequencies revealed a cluster ( B8 ) significantly enriched after the first dose , and a different cluster ( B5 ) significantly enriched after the second dose ( Figure 3E ) . As these two clusters differentially expressed the Tcm markers CD27 and CCR7 ( Figure 3F ) , we then assessed whether Tcm cells were differentially represented among spike-specific CD4+ T cells after each of the vaccination doses . Indeed , Tcm cells were significantly higher after the first dose ( Figure 3G ) , consistent with Cluster 8 ( enriched after the first dose ) expressing high levels of these two receptors . Assessment of other canonical CD4+ T cell subsets – in particular naïve ( Tn ) , stem cell memory ( Tscm ) , effector memory RA ( Temra ) , effector memory ( Tem ) , T transitional memory ( Ttm ) , Tfh , and regulatory T cells ( Treg ) – revealed Tn cells , like the Tcm subset , to be decreased after the second dose . By contrast , Ttm cells were found to be higher after the second dose , while the remaining subsets were not altered ( Figure 3G-H ) . Overall , Tcm and Tfh were the most abundant subsets among the spike-specific CD4+ T cells ( Figure 3G-H ) . These data together suggest that after receiving the second dose , infection-naïve individuals’ spike-specific CD4+ T cells increase in quantity ( Figure 1B ) , and alter their phenotypes as reflected by a decrease Tcm cells and an increase in Ttm cells . We then conducted a similar analysis in the convalescent individuals . As the pre-vaccination timepoint included spike-specific CD4+ T cells primed by prior SARS-CoV-2 infection , we included all three timepoints in this analysis . When the data were visualized by MDS , it was apparent that most of the pre-vaccination specimens localized away from the post-vaccination specimens , which were interspersed with each other ( Figure 4A ) . Similar distinctions between pre-and post-vaccination specimens were visualized at the single-cell level by tSNE , which was particularly apparent when visualized as contour heatmaps ( Figure 4B and C ) . Clustering of the cells by FlowSOM revealed that the cluster distribution was markedly skewed among the pre-vaccination cells ( Figure 4D and E ) , with one cluster being under-represented ( C2 ) and one over-represented ( C5 ) as compared to both post-vaccination timepoints ( Figure 4F ) . Cluster C3 was the only cluster that was significantly different after 1 vs 2 doses ( Figure 4F ) but as this cluster comprised only <5 % of the cells it was not analyzed further . To assess what may drive the differences between the phenotypes of the pre- vs . post-vaccination spike-specific CD4+ T cells , we assessed for markers differentially expressed between clusters C2 and C5 . Cluster C2 cells preferentially expressed the Tcm markers CD27 and CCR7 , the Tfh markers PD1 and CXCR5 , and the co-stimulatory receptors ICOS and Ox40 , while among these only CD27 was preferentially expressed in Cluster C5 ( Figure 4—figure supplement 1 ) . Manual gating confirmed Tcm , Tfh , and ICOS+ Ox40+ cells to be preferentially enriched in the post-vaccination specimens ( Figure 4G-I ) . None of the canonical subsets were differentially abundant after the first vs . second vaccination dose . Together , these results suggest that , in contrast to the infection-naïve individuals , convalescents’ spike-specific CD4+ T cells were similar after the first vs . second vaccination dose; however , in these individuals vaccination drastically altered the phenotypes of the pre-existing spike-specific CD4+ T cells ( presumably elicited from the original infection ) . We next determined whether there were any phenotypic differences between the vaccine-induced spike-specific CD4+ T cells from the infection-naïve vs . convalescent individuals . Removal of convalescent outlier PID4112 revealed the magnitude of the spike-specific CD4+ T cell response to be lower in the convalescents than in infection-naïve participants after full vaccination ( Figure 1D ) . But when all donors were included there was no statistically significant difference in response magnitude ( Figure 5A ) . However , the spike-specific CD4+ T cells from the convalescent and infection-naïve individuals exhibited clear phenotypic differences when assessed by both MDS ( Figure 5B ) and tSNE contours ( Figure 5C ) ; this was more apparent after the second vaccine dose , but could already be observed after the first . Since the cells after the second dose are more clinically relevant ( as they are the ones persisting in vaccinated individuals moving forward ) , we focused our subsequent analysis on just this timepoint . When visualized as a dot plot , it was apparent that the spike-specific CD4+ T cells from infection-naïve individuals segregated away from those from the convalescents ( Figure 5D ) . Clustering of the data also demonstrated differences between the two patient groups ( Figure 5E and F ) , which was confirmed by demonstration of a significant difference in Cluster A1 abundance ( Figure 5G ) . To identify these phenotypic differences , we first assessed the relative distributions of the main canonical CD4+ T cell subsets . Interestingly , the vaccinated convalescents harbored significantly more spike-specific Tcm and Tn , and less spike-specific Ttm ( Figure 6A ) . By contrast , Tfh and Treg frequencies were not different between infection-naïve and convalescent vaccinees ( Figure 6B ) . To broaden our analysis , we assessed for unique features of Cluster A1 , which was over-represented in the infection-naïve donors , and Cluster A3 , an abundant cluster which was over-represented in the convalescent donors albeit insignificantly ( Figure 5G ) . Interestingly , Cluster A1 expressed low levels of CD127 , CXCR4 , and CCR7 in contrast to Cluster A3 ( Figure 5—figure supplement 1A ) . As Cluster A1 is enriched among the infection-naïve individuals , these findings suggest that these three receptors may be expressed at lower levels on the cells from these individuals , relative to those from vaccinated convalescents . This was confirmed by our detection of higher expression of CD127 , CXCR4 , and CCR7 on spike-specific CD4+ T cells from the convalescents , although for CXCR4 the difference did not reach statistical significance ( Figure 5—figure supplement 1B ) . We then followed up on each of these three differentially expressed markers . CD127 , the alpha chain of the IL7 receptor , can drive IL7-mediated homeostatic proliferation of SARS-CoV-2-specific CD4+ T cells Neidleman et al . , 2020b , and serves as a marker of long-lived precursor memory cells Kaech et al . , 2003 . To assess the potential longevity of the spike-specific CD4+ T cells , we determined the percentage of CD127+ cells expressing low levels of the terminal differentiation marker CD57 . After the second dose of vaccination , convalescent individuals harbored more long-lived ( CD127+ CD57- ) spike-specific CD4+ T cells than infection-naïve individuals ( Figure 6C ) . CXCR4 , the second preferentially-expressed marker among the convalescents’ spike-specific CD4+ T cells , was recently suggested to direct bystander T cells to the lung during COVID-19 , and to be co-expressed with the T resident memory / activation marker CD69 Neidleman et al . , 2021 . Interestingly , spike-specific CD4+ T cells from convalescent donors harbored a highly significantly elevated proportion of CXCR4+ CD69+ cells ( Figure 6D ) , suggesting a potentially superior ability to migrate into pulmonary tissues . The last differentially expressed antigen , CCR7 , is a chemokine receptor that directs immune cells to lymph nodes . As CD62L , a selectin that also mediates lymph node homing , was also on our panel , we assessed whether CCR7+ CD62L+ cells were enriched among the spike-specific CD4+ T cells from the convalescent donors , and found this to be the case ( Figure 6E ) . Our finding that the convalescent donors’ spike-specific CD4+ T cells were preferentially CXCR4+ CD69+ and CCR7+ CD62L + suggested that they may preferentially migrate out of the blood into lymphoid tissues . Supporting this possibility was our observation that , after the second vaccine dose , the percentages of CCR7+ CD62L + spike-specific cells increased as the percentages of spike-specific CD4+ T cells decreased ( Figure 6F ) . This suggests that the low spike-specific CD4+ T cell response after the second dose of vaccination in some convalescent donors ( Figure 1D ) may have resulted from these cells preferentially leaving the blood compartment . This was further supported by our finding that the expression levels of CCR7 and CD62L on spike-specific CD4+ T cells inversely correlated with the magnitude of the spike-specific CD4+ T cell response ( Figure 6G ) . To assess whether the CCR7+ CD62L + and CXCR4+ CD69+ CD4+ T cells have the potential to migrate into the nasopharynx , the most common site of SARS-CoV-2 entry , we obtained paired blood and nasal swabs from one of the participants ( PID4101 ) and phenotyped total CD4+ T cells isolated from these specimens . There was a marked enrichment of both CCR7+ CD62L + and CXCR4+ CD69+ CD4+ T cells in the intranasal specimens ( Figure 6H ) , suggesting that CD4+ T cells expressing these markers preferentially exit the blood and enter the nasopharynx . Together , these data suggest that after vaccination , spike-specific CD4+ T cells from convalescent individuals differ from those in infection-naïve individuals in that they appear to be more long-lived , and may more readily migrate out of the blood to mucosal sites , thus explaining their overall lower frequencies measured from the blood . Finally , we assessed to what extent the main similarities and differences observed with spike-specific CD4+ T cells were also seen for spike-specific CD8+ T cells . Similar to the CD4+ T cells , spike-specific CD8+ T cells stimulated by the three different spike proteins ( ancestral , B . 1 . 1 . 7 , B . 1 . 351 ) did not differ in their phenotypic features ( Figure 6—figure supplement 1A-C ) . Also similar to the CD4+ T cells , spike-specific CD8+ T cells elicited by vaccination differed phenotypically in the infection-naïve vs . convalescent individuals ( Figure 6—figure supplement 1D-F ) . Unlike the CD4+ T cell data , however , these phenotypic differences could not be accounted for by distribution changes among the main canonical subsets Tn , Tscm , Temra , Tcm , Tem , and Ttm ( Figure 6—figure supplement 1G ) . Also unlike the CD4+ T cells , these differences were also not explained by differential abundance of the CD127+ CD57- , CXCR4+ CD69+ , or CCR7+ CD62L + subsets ( Figure 6—figure supplement 1H ) . Instead , the differences appear to be due to other phenotypic changes , including elevated frequencies of activated cells in the convalescent donors , in particular those co-expressing the Tcm marker CD27 and activation marker CD38 , and the checkpoint inhibitor molecule CTLA4 and activation marker 4-1BB ( Figure 6—figure supplement 1I ) . These results suggest that vaccine-elicited spike-specific CD8+ T cells , like their CD4+ counterparts , respond equivalently to the B . 1 . 1 . 7 and B . 1 . 351 variants , and exhibit qualitative differences in convalescent individuals but via different phenotypic alterations than their CD4+ counterparts .
As this study was aimed at using in-depth phenotyping as a discovery tool , it focused on deeply interrogating many different conditions ( e . g . spike variants , longitudinal sampling ) rather than many donors . Therefore , although a total of 165 CyTOF specimens were run , only 11 donors were analyzed . The main findings reported here should be confirmed in larger cohorts using more cost-effective and high-throughput alternatives to CyTOF such as conventional flow cytometry . Such follow-up studies should also examine the functional outcomes of the discoveries made here ( e . g . effect of chemokine receptor expression on homing of infection- and vaccine-elicited SARS-CoV-2-specific T cells ) , including in animal models of SARS-CoV-2 infection . A second limitation of the study was the need to stimulate the specimens in order to identify and characterize the vaccine-elicited T cells , and our limiting our analyses of SARS-CoV-2-specific T cells to those inducing IFNγ , which may have restricted our ability to characterize subsets such as Tfh cells that are relatively poor producers of this cytokine . We note however that we limited peptide exposure to 6 hours to minimize phenotypic changes caused by the stimulation , similar to our prior studies Neidleman et al . , 2021; Neidleman et al . , 2020b . Our analysis focused on CD4+ T cells because the overall numbers of detectable spike-specific CD8+ T cells were low . Nonetheless , the main findings we made with the CD4+ T cells – that they recognize variants equivalently , and that the phenotypes of the responding cells differ by prior SARS-CoV-2 natural infection status – were recapitulated among CD8+ T cells . Future studies should assess the phenotypes of non-stimulated , vaccine-elicited SARS-CoV-2-specific T cells using peptide-MHC tetramers/multimers . Such studies , however , would be limited to analyzing responses against a small number of epitopes , although use of combinatorial tetramers in conjunction with high-parameter phenotyping Newell et al . , 2013 would increase the ability to characterize a larger breadth of the vaccine-elicited T cell response . Such studies however would be limited for the most part to CD8+ T cells as tetramer reagents for CD4+ T cells are less robust . A final limitation is that serological analyses were not performed in this study . As coordination between the humoral and cellular arms of immunity are likely key to effectively controlling viral replication , future studies should assess to what extent the breadth , isotypes , and functional features of spike-specific antibodies elicited by vaccination associate with the herein described phenotypic features of vaccine-elicited SARS-CoV-2-specific T cells .
Eleven participants from the COVID-19 Host Immune Pathogenesis ( CHIRP ) cohort were recruited for this study . Six were previously infected with SARS-CoV-2 as established by RT-PCR , and had fully recovered from a mild course of disease . Importantly , infections of these six individuals had all occurred in the San Francisco Bay Area between March and July of 2020 , when the dominant local strain was the original ancestral ( Wuhan ) strain . The remaining five participants were not previously infected with the virus . All eleven participants were vaccinated with both doses of either of the Moderna or Pfizer/BioNTech mRNA vaccines ( Table 1 ) . Blood was drawn from each of the eleven participants prior to vaccination , ~ 2 weeks after the first vaccine dose , and ~2 weeks after the second vaccine dose ( 33 specimens total ) . On the day of each blood draw , PBMCs were isolated from blood using Lymphoprep ( StemCell Technologies ) , and then cryopreserved in 90 % fetal bovine serum ( FBS ) and 10 % DMSO . For participant PID4101 , an additional blood-draw and intranasal swab specimens were obtained for immunophenotyping studies . This study was approved by the University of California , San Francisco , and all participants provided informed consent ( IRB # 20–30588 ) . Cryopreserved PBMCs were revived and cultured overnight to allow for antigen recovery . The cells were then counted , and then 2 million cells per treatment condition were stimulated with the co-stimulatory agents 0 . 5 μg/ml anti-CD49d clone L25 and 0 . 5 μg/ml anti-CD28 clone L293 ( both from BD Biosciences ) , in the presence of 0 . 5 μM of overlapping 15-mer SARS-CoV-2 spike peptides PepMix SARS-CoV-2 peptides from the original SARS-CoV-2 strain , B . 1 . 1 . 7 , or B . 1 . 351 , or overlapping 15-mer SARS-CoV-2 nucleocapsid peptides ( all from JPT Peptide Technologies ) . Stimulations were conducted for 6 hours in RP10 media ( RPMI 1640 medium ( Corning ) supplemented with 10 % FBS ( VWR ) , 1 % penicillin ( Gibco ) , and 1 % streptomycin ( Gibco ) ) , in the presence of 3 μg/ml Brefeldin A Solution ( eBioscience ) to enable detection of intracellular cytokines . To establish the phenotypes of total T cells in the absence of stimulation , 2 million cells were cultured in parallel with the stimulated samples , but in the presence of only 3 μg/ml Brefeldin A . After culture , the cells were treated with cisplatin ( Sigma-Aldrich ) as a live/dead marker and fixed with paraformaldehyde ( PFA ) as previously described Neidleman et al . , 2020b; Ma et al . , 2020 . Cisplatin treatment and fixation was performed as follows: first , cells were resuspended in 2 ml PBS ( Rockland ) with 2 ml EDTA ( Corning ) , followed by addition of 2 ml PBS/EDTA supplemented with 25 μM cisplatin ( Sigma-Aldrich ) for 60 s . Cisplatin staining was then quenched with 10 ml of CyFACS ( metal contaminant-free PBS ( Rockland ) supplemented with 0 . 1 % FBS and 0 . 1 % sodium azide ( Sigma-Aldrich ) ) , centrifuged , and resuspended in 2 % PFA in CyFACS . Fixation was allowed to proceed for 10 minutes at room temperature , after which cells were washed twice with CyFACS , and then resuspended in CyFACS containing 10 % DMSO . Fixed cells were stored at –80 °C until analysis by CyTOF . For paired blood/swab specimens from PID4101 , cells were immediately cisplatin-treated and fixed , without prior cryopreservation . CyTOF staining was conducted in a fashion similar to recently described methods Neidleman et al . , 2021; Neidleman et al . , 2020b; Ma et al . , 2020; Cavrois et al . , 2017; Neidleman et al . , 2020a; Xie et al . , 2021 . Cisplatin-treated cells were thawed , counted , and each treatment condition was barcoded using the Cell-ID 20-Plex Pd Barcoding Kit ( Fluidigm ) . After the cells were barcoded and washed , the barcoded samples were combined and diluted to 6 × 106 cells / 800 μl CyFACS per well in Nunc 96 DeepWell polystyrene plates ( Thermo Fisher ) . Cells were blocked with mouse ( Thermo Fisher ) , rat ( Thermo Fisher ) , and human AB ( Sigma-Aldrich ) sera for 15 min at 4 °C , and then washed twice in CyFACS . Surface CyTOF antibody staining ( Table 2 ) was conducted for 45 min at 4 °C , in a volume of 100 μl / sample . Cells were then washed three times with CyFACS and fixed overnight at 4 °C in 100 μl of 2 % PFA in PBS . The next day , samples were washed twice with Intracellular Fixation & Permeabilization Buffer ( eBioscience ) , and incubated for 45 minutes at 4 °C . After two additional washes with Permeabilization Buffer ( eBioscience ) , samples were blocked for 15 min at 4 °C in 100 μl of Permeabilization Buffer containing mouse and rat sera . After one additional wash with Permeabilization Buffer , samples were stained with the intracellular CyTOF antibodies ( Table 2 ) at 4 °C for 45 min in a volume of 100 μl / sample . Cells were then washed once with CyFACS , and stained for 20 min at room temperature with 250 nM of Cell-ID Intercalator-IR ( Fluidigm ) . Immediately prior to sample acquisition , cells were washed twice with CyFACS buffer , once with MaxPar cell staining buffer ( Fluidigm ) , and once with Cell acquisition solution ( CAS , Fluidigm ) . Cells were resuspended in EQ Four Element Calibration Beads ( Fluidigm ) diluted in CAS immediately prior to acquisition on a Helios-upgraded CyTOF2 instrument ( Fluidigm ) at the UCSF Parnassus flow core facility . CyTOF datasets , exported as flow cytometry standard ( FCS ) files , were de-barcoded and normalized according to manufacturer’s instructions ( Fluidigm ) . FlowJo software ( BD Biosciences ) was used to identify CD4+ T cells ( live , singlet CD3+ CD19 CD4+ CD8- ) and CD8+ T cells ( live , singlet CD3+ CD19 CD4-CD8+ ) among all analyzed samples . IFNγ+ in the stimulated samples were considered to be the SARS-CoV-2-responsive cells . For high-dimensional analyses of SARS-CoV-2-specific T cells among the stimulated samples , we excluded samples with an insufficient number of events ( ≤ 3 ) to limit skewing of the data . Manual gating analysis was initially performed using FlowJo , and then select populations were exported as FCS files and then imported into R software as GatingSet objects . Using the CytoExploreR package , 2D-gates were manually drawn on the imported samples . The 2D dot plots and statistical results were exported for data visualization , bar-graph generation , and statistical comparisons as previously described ( https://github . com/DillonHammill/CytoExploreR; Hammill , 2021 ) . High-dimensional analyses ( MDS , tSNE , and FlowSOM ) were performed using R software by implementing a CyTOF workflow recently described Nowicka et al . , 2017 . For MDS plot generation , we used the plotMDS function from the limma package with default settings . Euclidean distances between all samples were calculated using the arcsinh-transformed median expression levels with cofactor 5 , of the lineage and functional markers listed below . The first ( MDS1 ) and second ( MDS2 ) MDS dimensions were plotted to show the dissimilarities between samples from the indicated conditions as described Ritchie et al . , 2015 . tSNE was performed using the Trsne function from the Rtsne package using arcsinh-transformed expression of lineage markers ( no PCA step , iterations = 1000 , , perplexity = 30 , theta = 0 . 5 ) . Events corresponding to unstimulated T cells were down-sampled to 1000 cells per sample , and SARS-CoV-2-specific cells ( cell numbers ranging from 4 to 229 per sample ) were all included in the tSNE analyses without down-sampling . Each cell was displayed in a tSNE plot for dimension reduction visualization and colored with arcsinh-transformed cell marker expression as heatmaps , or pseudo-colored by the appropriate group . Unsupervised cell subset clustering was performed using FlowSOM Van Gassen et al . , 2015 and ConsensusClusterPlus packages using arcsinh-transformed expression levels of the lineage markers indicated above Wilkerson and Hayes , 2010 . For clustering of SARS-CoV-2-specific T cells , we set the meta-cluster number to eight and cluster number to 40 . The frequency of each cluster within each sample was calculated using the following equation: ( Frequency of cluster in specified sample ) = ( Cell count of cluster / Total cell count of specified sample ) . This was then converted to a percentage by multiplying by 100 . The percentages of each cluster from the selected samples were plotted as box plots with jittered points , followed by statistical analysis between the groups . To compare the abundance distribution of clusters between groups , frequencies of clusters in samples from each group were normalized using the equation below: ( Normalized frequency of cluster in specified sample ) = ( Frequency of cluster in specified sample/ Total number of samples in each group ) . This was then converted to a percentage by multiplying by 100 , and plotted as stacked bar charts . The statistical tests used in comparison of groups are indicated within the figure legends . For 2-group comparisons , student’s t-tests were performed and p-values were adjusted for multiple testing using the Holm-Sidak method where applicable . For comparisons of three or more groups , significance between groups was first evaluated by one-way ANOVA , and then the p-values were adjusted for multiple testing using the Holm-Sidak method where applicable . For datasets with significant ANOVA-adjusted p-values ( ≤ 0 . 05 ) , we performed Tukey’s honestly significant difference ( HSD ) post-hoc test to determine the p-values between individual groups . For this study , a total of 120 specimens were analyzed by CyTOF . Each specimen included both CD4+ and CD8+ T cells . For each specimen , we gated separately on events corresponding to CD4+ T cells ( live , singlet CD3+ CD19- CD4+ CD8- ) and CD8+ T cells ( live , singlet CD3+ CD19- CD4 CD8+ ) , and exported the files as 240 individual FCS files . These 240 raw CyTOF datasets are available for download through the public repository Dryad via the following link: https://doi . org/10 . 7272/Q60R9MMK .
While mRNA vaccines are proving highly efficacious against SARS-CoV-2 , it is important to determine how booster doses and prior infection influence the immune defense they elicit , and whether they protect against variants . Focusing on the T cell response , we conducted a longitudinal study of infection-naïve and COVID-19 convalescent donors before vaccination and after their first and second vaccine doses , using a high-parameter CyTOF analysis to phenotype their SARS-CoV-2-specific T cells . Vaccine-elicited spike-specific T cells responded similarly to stimulation by spike epitopes from the ancestral , B . 1 . 1 . 7 and B . 1 . 351 variant strains , both in terms of cell numbers and phenotypes . In infection-naïve individuals , the second dose boosted the quantity and altered the phenotypic properties of SARS-CoV-2-specific T cells , while in convalescents the second dose changed neither . Spike-specific T cells from convalescent vaccinees differed strikingly from those of infection-naïve vaccinees , with phenotypic features suggesting superior long-term persistence and ability to home to the respiratory tract including the nasopharynx . These results provide reassurance that vaccine-elicited T cells respond robustly to emerging viral variants , confirm that convalescents may not need a second vaccine dose , and suggest that vaccinated convalescents may have more persistent nasopharynx-homing SARS-CoV-2-specific T cells compared to their infection-naïve counterparts .
Vaccination is one of the best ways to prevent severe COVID-19 . Two doses of mRNA vaccine protect against serious illness caused by the coronavirus SARS-CoV-2 . They do this , in part , by encouraging the immune system to make specialised proteins known as antibodies that recognise the virus . Most of the vaccine research so far has focussed on these antibodies , but they are only one part of the immune response . Vaccines also activate immune cells called T cells . These cells have two main roles , coordinating the immune response and killing cells infected with viruses . It is likely that they play a key role in preventing severe COVID-19 . There are many kinds of T cells , each with a different role . Currently , the identity and characteristics of the T cells that protect against COVID-19 is unclear . Different types of T cells have unique proteins on their surface . Examining these proteins can reveal details about how the T cells work , which part of the virus they recognise , and which part of the body they protect . A tool called cytometry by time of flight allows researchers to measure these proteins , one cell at a time . Using this technique , Neidleman , Luo et al . investigated T cells from 11 people before vaccination and after their first and second doses . Five people had never had COVID-19 before , and six had already recovered from COVID-19 . Neidleman , Luo et al . found that the T cells recognizing SARS-CoV-2 in the two groups differed . In people who had never had COVID-19 before , the second dose of vaccine improved the quality and quantity of the T cells . The same was not true for people who had already recovered from COVID-19 . However , although their T cells did not improve further after a second vaccine dose , they did show signs that they might offer more protection overall . The proteins on the cells suggest that they might last longer , and that they might specifically protect the nose , throat and lungs . Neidleman , Luo et al . also found that , for both groups , T cells activated by vaccination responded in the same way to different variants of the virus . This work highlights the importance of getting both vaccine doses for people who have never had COVID-19 . It also suggests that vaccination in people who have had COVID-19 may generate better T cells . Larger studies could show whether these patterns remain true across the wider population . If so , it is possible that delivering vaccines to the nose or throat could boost immunity by mimicking natural infection . This might encourage T cells to make the surface proteins that allow them to home to these areas .