key: cord-1036950-9uegfque
authors: Peng, Yanchun; Felce, Suet Ling; Dong, Danning; Penkava, Frank; Mentzer, Alexander J.; Yao, Xuan; Liu, Guihai; Yin, Zixi; Chen, Ji-Li; Lu, Yongxu; Wellington, Dannielle; Wing, Peter A. C.; Dominey-Foy, Delaney C. C.; Jin, Chen; Wang, Wenbo; Hamid, Megat Abd; Fernandes, Ricardo A.; Wang, Beibei; Fries, Anastasia; Zhuang, Xiaodong; Ashley, Neil; Rostron, Timothy; Waugh, Craig; Sopp, Paul; Hublitz, Philip; Beveridge, Ryan; Tan, Tiong Kit; Dold, Christina; Kwok, Andrew J.; Rich-Griffin, Charlotte; Dejnirattisa, Wanwisa; Liu, Chang; Kurupati, Prathiba; Nassiri, Isar; Watson, Robert A.; Tong, Orion; Taylor, Chelsea A.; Sharma, Piyush Kumar; Sun, Bo; Curion, Fabiola; Revale, Santiago; Garner, Lucy C.; Jansen, Kathrin; Ferreira, Ricardo C.; Attar, Moustafa; Fry, Jeremy W.; Russell, Rebecca A.; Stauss, Hans J.; James, William; Townsend, Alain; Ho, Ling-Pei; Klenerman, Paul; Mongkolsapaya, Juthathip; Screaton, Gavin R.; Dendrou, Calliope; Sansom, Stephen N.; Bashford-Rogers, Rachael; Chain, Benny; Smith, Geoffrey L; McKeating, Jane A.; Fairfax, Benjamin P.; Bowness, Paul; McMichael, Andrew J.; Ogg, Graham; Knight, Julian C.; Dong, Tao
title: An immunodominant NP(105-113)-B*07:02 cytotoxic T cell response controls viral replication and is associated with less severe COVID-19 disease
date: 2022-01-01
journal: Nat Immunol
DOI: 10.1038/s41590-021-01084-z
sha: b298164874c2248f4a760575921150f9551ba2ce
doc_id: 1036950
cord_uid: 9uegfque

NP(105-113)-B*07:02 specific CD8(+) T-cell responses are considered among the most dominant in SARS-CoV-2-infected individuals. We found strong association of this response with mild disease. Analysis of NP(105-113)-B*07:02 specific T-cell clones and single cell sequencing were performed concurrently, with functional avidity and anti-viral efficacy assessed using an in vitro SARS-CoV-2 infection system, and were correlated with T cell receptor usage, transcriptome signature, and disease severity (acute N=77, convalescent N=52). We demonstrated a beneficial association of NP(105-113)-B*07:02 specific T-cells in COVID-19 disease progression, linked with expansion of T-cell precursors, high functional avidity and anti-viral effector function. Broad immune memory pools were narrowed post-infection but NP(105-113)-B*07:02 specific T-cells were maintained 6 months after infection with preserved anti-viral efficacy to the SARS-CoV-2 Victoria strain, as well as Alpha, Beta, Gamma and Delta variants. Our data shows that NP(105-113)-B*07:02 specific T-cell responses associate with mild disease and high anti-viral efficacy, pointing to inclusion for future vaccine design.

CD8 + T cells play a well-documented role in clearing viral infections. Immunodominance is a central feature of CD8 + T cell responses in viral infections and understanding the nature of Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms this response for a given infection where they are shown to be protective will be critical for the design of vaccines aiming to elicit optimal CD8 + T cell responses 1, 2 .

The role of the immunodominant cytotoxic T cell immune response in protection and potential disease pathogenesis of SARS-CoV-2 infection is currently poorly defined. We and others have identified immunodominant T cell epitopes restricted by common HLA types 3, 4, 5, 6 ; in particular, we found multiple dominant epitopes in NP (nucleoprotein) restricted by HLA-B*07:02, B*27:05, B*40:01, A*03:01 and A*11:01. We also found that multi-functional NP and M (membrane) CD8 + T cell responses are associated with mild disease and NP is one of the most common targets for CD8 + dominant T cell responses in SARS-CoV-2 infection 3 .

Among the dominant epitopes identified to date, NP 105-113 -B*07:02 appears to be among the most dominant 3, 4, 6, 7 ; notably, no variants are found within this epitope from over 300k sequences in COG-UK global sequence data alignment 8 . This suggests that this epitope would be a good target for inclusion within an improved vaccine design, expanded to stimulate effective CD8 + T cell responses as well as neutralising antibodies, in order to protect against newly emergent viral strains that escape antibody responses to spike in some cases. 9 .

Biased TRBV27 gene usage, with long CDR3β loops preferentially expressed in NP 105-113 -B*07:02 specific-T cell receptor (TCRs) has been observed in both unexposed and COVID-19 recovered individuals 10 . This study suggested a role for cross-reactive responses in COVID-19 based on pre-existing immunity to seasonal coronaviruses or other pathogens. However, a subsequent study suggested that the immunodominant NP 105-113 -B*07:02 CD8 + T cell responses are unlikely to arise from pre-existing cross-reactive memory pools, but rather represent a high frequency of naive T cell precursors found across HLA-B*07:02expressing individuals 7 .

In this study, we present an in-depth analysis to explore correlations between NP 105-113 -B*07:02 specific T cell responses, T cell receptor (TCR) repertoires and disease severity. We saw stronger overall T cell responses in individuals recovered from severe COVID, which may be explained by high exposure to viral protein; however, we found an immunodominant epitope response (HLA-B*07:02 NP 105-113 specific CD8 + ) which significantly associated with mild cases. Importantly, this epitope is one of the most dominant CD8 + T cell epitopes reported so far by us and others. We examined potential mechanisms of protection using single cell transcriptome analysis, and functional evaluation of expanded T cell clones bearing the same TCRs as those identified in single cell analysis. We also assessed the ability of T cell lines and clones to mount effective effector function against cells infected with live SARS-CoV-2 virus and Vaccinia virus expressing SARS-CoV-2 proteins. We found that NP 105-113 -B*07:02 is the dominant NP response in HLA-B*07:02 positive patients with mild symptoms, with high frequency and higher magnitude when compared to severe cases. Single cell analysis revealed that preserved beneficial functional phenotypes are associated with protection from severe illness and have better overall anti-viral function. In addition, NP 105-113 -B*07:02 specific T cells can recognise the naturally processed epitope in live virus and recombinant Vaccinia virus infected cells, which correlates with anti-viral efficacy.

A previous study has identified five dominant CD8 + epitopes targeting NP, including the most dominant epitope NP 105-113 (amino acid sequence SPRWYFYYL) restricted by HLA-B*07:02 3 . 52 individuals who recovered from COVID- 19 were included in this current study, comprising 30 mild cases and 22 severe cases (including 4 with critical illness; clinical features summarised in Supplementary Table 1 and Extended Data Fig. 1a-c) . All the patients were HLA typed and 19 (36.5%) were HLA-B*07:02 positive (10 mild and 9 severe cases, Extended Data Fig. 1d) . We proceeded to carry out ex vivo IFN-γ ELISpot assays using HLA-B*07:02 positive convalescent samples 1-3 months post infection. 79% (15/19) of HLA-B*07:02 individuals showed responses to this epitope which accounted for 29% individuals of overall cohort (15/52) (Fig. 1a) , including 90% (9/10) of individuals recovered from mild and 67% (6/9) from severe disease (Fig. 1b) . This further confirms the dominance of this NP 105-113 -B*07:02 T cell response in our cohort, in particular in individuals recovered from mild illness. In addition, individuals recovered from mild disease made significantly stronger responses to this epitope, compared to those who had recovered from severe disease (Fig. 1c, P=0 .04). We also observed that this NP 105-113 -B*07:02-specific response is dominant in mild cases and makes up 60% of overall NP responses of each individual, whereas in severe cases, the proportion is substantially lower, with an average of 19.5% (Fig. 1d, P=0 .015). In addition, we did not find HLA-B*07:02 association with disease outcome in our study cohorts (Fig. 1e , 77 acute and 52 convalescent patients). Our data highlights the association of the strength of this dominant epitope-induced T cell response with mild disease outcome and provides evidence that this link is epitope-specific rather than a wider allelic association with HLA-B*07:02.

To explore the mechanisms underlining this association, we sorted NP 105-113 -B*07:02specific T cells at a single cell level with peptide MHC-class I pentamers using flow cytometry. We performed single cell analysis using SmartSeq2 for PBMC samples from four convalescent patients, including two who recovered from mild COVID-19 infection (C-COV19-005, 56 years old and C-COV19-046, 76 years old) and two who recovered from severe disease in early infection (C-COV19-038, 44 years old and C-COV19-045, 72 years old). TCR sequences and transcriptomic profiles of each single cell were analysed.

Analysis of single cell RNA-Seq data with UMAP visualisation and unbiased clustering revealed a homogenous cell population; therefore we compared gene expression of CD8 + NP-specific sorted single cells isolated from mild (N=208 from two patients) and severe cases (N=140 from two patients) by scoring expression levels of manually defined gene sets (Supplementary Table 2 ). Gene signatures associated with T cell cytotoxicity and inhibitory receptors were analysed and compared between severity groups. We found that cells from patients who had recovered from severe COVID-19 have significantly higher cytotoxicity gene expression scores (Fig. 2a, P=0 .00032), with upregulation of GZMK (P=3.02E -05 ) and GNLY (P=1.41E -09 ) (encoding granzyme K and granulysin respectively, Fig. 2b ). These cells also displayed increased inhibitory receptor expression (Fig. 2c, P=0 .00072), such as TIGIT, CTLA4 and HAVCR2 (TIM3). This supports findings published by us and others 3, 11 where patients with severe COVID-19 disease are exposed to higher antigen loads, and that these cells are still present at 1 -3 months convalescence, rather than CD8 + central memory T cells. NP 10 5 -113 -B*07:02-specific T cells have a highly diverse TCR repertoire Consistent with findings by other studies 7, 10 , we found that NP 105-113 -B*07:02-specific T cells from our cohort show very broad TCR repertoires. Circos plots show paired TCR α and β chains (V and J gene usage) from the four individuals analysed with SmartSeq2 single cell RNA-Seq (Fig. 3a ) and the combined TCR repertoire of all four patients represented by TCR clonotype (defined separately for each patient combining V gene and CDR3 amino acid sequence) (Fig. 3b) . Although the NP 105-113 -specific TCR repertoire is diverse with unique pairings of Vα and Vβ genes, we observed that 15/45 (33.3%) of unique Vβ clonotypes were paired with several distinct Vα clonotypes. In contrast, there is only 1/55 (1.8%) Vα clonotype that pairs to multiple Vβ clonotypes; this highlights the importance of studying Vβ in the TCR repertoire. Further detailed TCR information can be found in Supplementary Table 3 .

Several studies have reported that pre-existing cross-reactive T cells to SARS-CoV-2 can be detected in unexposed individuals, and these T cells may have resulted from previous human seasonal coronavirus infection 7, 10, 12, 13 . These studies found TCRs specific to NP 105-113 -B*07:02 in SARS-CoV-2 unexposed and infected individuals. These cells were revealed as likely to be naïve 7 ; this is very different from the central/effector memory phenotype of SARS-CoV-2 specific T cells reported earlier. To investigate this further, we sought to determine what role these T cells might play in the early stages of SARS-CoV-2 infection and COVID-19 disease, and if these cells contribute to the association of mild disease due to their specificity for this NP dominant epitope.

To take advantage of the results from our SmartSeq2 single cell RNA-Seq, we first compared TCR sequences from our four convalescent COVID-19 patients to pre-pandemic TCR sequences from healthy donors published by Lineburg, Nguyen and another study cohort, COMBAT 14 . The COMBAT dataset represents a comprehensive multi-omic blood atlas encompassing acute patients with varying COVID-19 severity (41 mild and 36 severe), and 10 healthy volunteers (pre-pandemic), using bulk TCR sequencing and CITE-Seq, which combines single cell gene expression and cell surface protein expression. TCR sequences from the Lineburg and Nguyen datasets have been experimentally validated to be specific for the NP 105-113 epitope, however for the COMBAT dataset, we used GLIPH2 analysis 15 to extract TCRs with predicted specificity to this epitope based on convergence with known NP 105-113 -specific TCRs.

We sought to compare NP-specific TCRs from COVID patients and healthy individuals using two different methodologies. Firstly, we calculated similarity scores for CDR3β amino acid sequences between pairwise combinations of SmartSeq2 TCRs and pre-pandemic/ healthy TCRs. A similarity score of 1 indicates that the pair of CDR3β sequences are identical, while a score of 0 indicates complete dissimilarity. In our convalescent patient cohort, CDR3β from patients with mild disease are more similar to TCRs from pre-pandemic/healthy individuals, than those from severe patients (Fig. 4a, P<2 .20E -16 ).

Secondly, we looked at the proportion of TCR sequences from mild and severe patients (acute cases from COMBAT dataset and convalescent cases from previously described SmartSeq2 patients) that can be found in the same convergence groups as sequences from healthy donors, indicating high CDR3β similarity. Convergence groups containing TCRs from healthy donors appear to contain higher proportions of TCRs from mild cases rather than severe, signifying greater similarity between TCRs from pre-pandemic individuals and patients with mild disease (Fig. 4b, P<2 .2E -16 ).

We were able to link predicted NP 105-113 -B*07:02 TCRs with their corresponding single cell data from the COMBAT dataset (healthy and acute SARS-CoV-2 infected patients). In this way, we could extract single cell CITE-Seq information from the COMBAT dataset, subsetted specifically to cells with predicted NP 105-113 specificity. Cellular subtyping of these CD8 + NP 105-113 -B*07:02 T cells show a higher proportion of naïve T cells in one HLA-B*07:02 healthy individual compared to predominantly T effector memory subtypes in acute COVID-19 patients (N=17, Fig. 4C ). Overall, our data supports the report that T cells bearing TCRs specific to NP 105-113 -HLA-B*07:02 in SARS-CoV-2 unexposed individuals are unlikely to have resulted from previous seasonal coronavirus infection 7 . This reinforces the finding that only NP 105-113 -B*07:02 specific T cells from acute HLA-B*07:02 positive patients are exposed to antigen and undergo T cell differentiation, whereas NP 105-113 -specific T cells in pre-pandemic individuals are naïve precursors rather than memory cells from prior cross-reactive infection.

In parallel with single cell sorting for SmartSeq2, we also sorted, cloned and expanded NP 105-113 -B*07:02-specific T cells from the same convalescent COVID-19 patients in vitro 16, 17 to obtain pure clonal T cell populations 16, 17 . We sequenced TCRs from each T cell clone with paired TCR α chain and β chain of each clone listed in Supplementary Table 4 . When comparing the TCR sequences between T cell clones and ex vivo single cells, in vitro expanded T cell clones are a good representation for the T cells isolated for ex vivo single cell analysis, with expanded TCRs from ex vivo single cells present as dominant TCRs from the T cell clones (Extended Data Fig. 2a ).

To provide a link between T cell clones and single cell data by their respective TCR sequences, we divided all the T cells, including T cell clones and single cells from SmartSeq2, into 18 groups according to their unique TRBVβ gene usage and CDR3β sequence (Table 1) . T cell functional avidity was measured by IFN-γ ELISPOT and calculated by EC50 (Extended Data Fig. 2b , Supplementary Table 5 ). We found evidence for low and high functional avidity groups (Fig. 5a) based on the EC50 of T cell clones, with EC50 < 0.11 considered as high avidity, and those with EC50 > 0.11 are low avidity T cells. We then aggregated RNA counts from single cells (pseudobulk) to compare differences in gene expression between the two avidity groups. Although there were only 7 significantly differentially expressed genes (Fig. 5b) , possibly as a result of small samples sizes and patient variation, differentially expressed genes of note upregulated in high functional avidity cells include IL10RA, PARK7 and LTA4H. The interaction of IL-10 with IL10RA expressed on CD8 + T cells has been reported to directly decrease CD8 + T cell antigen sensitivity in patients with chronic hepatitis C (HCV) infection 18 , while PARK7 promotes survival and maintains cellular homeostasis in the setting of intracellular stress 19 . LTA4H is an enzyme with known potent anti-inflammatory activity, and functions as an aminopeptidase to degrade a neutrophil chemoattractant Pro-Gly-Pro (PGP) to facilitate the resolution of neutrophilic inflammation and prevent prolonged inflammation with exacerbated pathology and illness 20 . This supports the idea that high functional avidity T cells undergo stronger antigen stimulation and would therefore start expressing immune dampening molecules. We further found that patients with mild disease show an increased proportion of high functional avidity TCR clonotypes which are also more expanded than low functional avidity TCR clonotypes (Fig. 5c ), whereas TCR clonotypes from patients with severe disease show equal expansion between high and low functional avidity TCRs. Therefore, the preferential expansion of high functional avidity TCR clonotypes may contribute to mild disease after SARS-CoV-2 infection.

Numerous studies including our own have shown the importance of antigen-processing and presentation to T cell recognition of its antigen 21, 22 . Some T cell epitopes may not be processed and presented as efficiently as others, which will subsequently diminish the T cell response to the epitope. To investigate T cell responses to naturally processed and presented viral epitopes, we made Vaccinia virus expressing SARS-CoV-2 viral proteins. We infected autologous Epstein-Barr virus (EBV) transformed B cell lines (BCLs) with Vaccinia virus expressing NP and co-cultured with NP 105-113 -B*07:02-specific T cell clones. T cell degranulation and cytokine production (CD107a expression and MIP1β chemokine production respectively) was then assessed by intracellular staining after six hours of incubation (Fig. 6a ). Gating for CD107a and/or MIP1β producing cells were based on corresponding negative controls (Extended Data Fig. 3a) . When compared to the peptide-loaded targets, we found that the response to Vaccinia virus infected BCLs was much weaker, consistent with lower antigen loads. The loading of this naturally processed and presented epitope was equivalent to no more than 3nM peptide (Extended Data Fig.  3b ). Nevertheless, NP Vaccinia virus-incubated clones with high CD107a expression showed a negative correlation with their individual EC50 values (Fig. 6b , R=-0.6176, P=0.0212), consistent with higher functional avidity resulting in more effective T cell killing. A similar negative correlation was also observed with MIP1β producing cells (Fig. 6c , R=-0.6879, P=0.0082).

To further investigate the anti-viral activity of NP 105-113 -B*07:02 specific T cells, we established an in vitro SARS-CoV-2 infection system. Briefly, the ACE2 gene was delivered into autologous EBV-transformed BCLs by lentiviral transduction to enable SARS-CoV-2 infection via ACE2 protein expressed on the cell surface. ACE2 + BCLs were purified by flow sorting and maintained by antibiotic selection, after which cells were subsequently used for SARS-CoV-2 virus infection (Victoria strain). After 48 hours incubation, intracellular viral copies were quantified by quantitative PCR, where the reduction of virus replication is calculated as percentage of virus suppression by T cells (Fig. 6d) . We found that the percentage of virus suppression was strongly correlated with their functional avidity (Fig.  6e , R=-0.7699, P=0.0075). Therefore, high functional avidity T cells can efficiently inhibit viral replication.

In order to examine whether the memory T cells established post-natural infection could provide sufficient protection against secondary viral infection, we collected PBMCs from three patients (C-COV19-005, C-COV19-045, C-COV19-046) six months after infection and sequenced sorted CD8 + NP 105-113 -B*07:02-specific T cells. We discovered that six months after infection, the TCR repertoire of NP 105-113 -B*07:02-specific T cells narrows (independent of cell numbers), and the T cell memory pool contains both high and low functional avidity T cells (Fig. 7a) . We then isolated and expanded further NP 105-113 -B*07:02-specific T cell bulk lines from PBMC samples taken six months after infection. We assessed the anti-viral efficacy of these bulk T cell lines in our in vitro SARS-CoV-2 infection assays. All three T cell lines showed increased MIP1β and CD107a protein expression after incubation with NP-expressing Vaccinia virus (Extended Data Fig. 4) , increased TNF and CD107a expression after incubation with BCLs infected with SARS-CoV-2 virus (Victoria strain) and current variants of concerns (VOCs) including the Delta variant (Fig. 7b, Extended Data Fig. 5 ). In addition, we found that these antigen-specific bulk cell lines are capable of suppressing SARS-CoV-2 replication (Fig. 7c) and showed strong inhibition against VOCs, including the recently emerged Alpha, Beta, Gamma and Delta SARS-CoV-2 variants (Fig. 7d-e) . This is consistent with the evidence of conservation of this NP 105-113 -B*07:02 epitope, and indicates the protective role of NP 105-113 -specific T cells in secondary infection against different SARS-CoV-2 variants.

Our observation of strong and dominant NP 105-113 -B*07:02 specific T cell responses in mild cases highlights the possible protective role of this unique and most dominant response found so far in SARS-CoV-2 infection 3, 4, 5, 6 . We found high similarity and convergence of TCRs in HLA-B*07:02 positive healthy and recovered individuals, with naive precursors identified in pre-pandemic samples supporting previous reports 7, 10 . In addition, T cells from convalescent patients with mild disease show higher functional avidity as well as better effector and anti-viral function compared with convalescent severe COVID-19. Interestingly, the immune memory pools post-infection (six months convalescence) are narrowed but remain proportional; we found no bias towards high or low functional avidity TCRs during immune memory contraction. Moreover, this dominant NP 105-113-specific response restricted by HLA-B*07:02 is associated with protection against severe disease but does not associate with HLA-B*07:02 when analysed alone.

The highly diverse T cell receptor repertoire of NP 105-113 -B*07:02 specific T cells in recovered individuals is of particular interest; whether this is a common phenomenon of acute primary virus infection, or if these responses are unique, with high frequency and broader choice of TCR precursors available would merit future investigation. The latter is supported by our finding that TCRs in COVID-19 recovered individuals can be similar to those found in pre-pandemic individuals, in particular patients with mild symptoms. We hypothesise that NP 105-113 -B*07:02 specific T cell responses play an important role in protecting individuals from severe illness, which is likely due to early priming and expansion of high frequency naive TCRs specific to this epitope.

We further provided evidence to support our hypothesis by studying a cohort of patients with acute SARS-CoV-2 infection, by analysing the TCR repertoire in HLA-B*07:02 positive patients. We first found high frequencies of TCR precursors with naïve phenotype in HLA-B*07:02 positive healthy donors; this further supports the recent findings from Nguyen et al., that these T cell precursors bearing NP-specific TCRs are not due to pre-existing memory from seasonal coronaviruses. We observed that strong cytotoxicity and inhibitory receptor expression is associated with disease severity, where NP 105-113 -B*07:02 specific T cells are more activated and well differentiated in individuals recovered from severe illness. This is likely as the result of stronger antigen stimulation and expansion during the acute phase of viral infection.

We found overall high functional avidity T cell expansion in mild cases, and that high functional avidity is associated with expression of immune damping molecules such as IL10RA, PARK7 and LTA4H, which could potentially act to prevent prolonged inflammation with exacerbated pathology and illness 18, 20, 23, 24 In particular, LTA4H has a known function as an aminopeptidase to degrade a neutrophil chemoattractant PGP, facilitating the resolution of neutrophilic inflammation, which is known to be associated with immunopathology in respiratory virus infections such as COVID-19 25 . This further provides evidence that expansion of high avidity precursors in mild cases contributes to the overall protective immunity from severe illness.

We show that NP 105-113 -B*07:02 specific T cells can respond to cells infected with live SARS-CoV-2 virus as well as emerging viral variants, and most importantly suppress virus replication in infected cells. The magnitude and strength of response to naturally processed epitopes presented by infected cells is correlated with their functional avidity. The proportional expansion with both high and low functional avidity T cells was maintained in CD8 + T cell memory pools after immune memory contraction (at six months post-infection), and these cells could suppress virus replication efficiently for all viral variant strains. This is not surprising due to the conservation of this epitope across viral strains, and provides some reassurance that memory T cells generated from natural infection could respond to newly emerged variants and still provide protective immunity. Taken together, we have demonstrated that, firstly, we found strong association of NP 105-113 -HLA-B*07:02 specific T cell response with mild disease; secondly, the protective effect of NP 105-113 -HLA-B*07:02 specific TCRs from severe illness may be due to early expansion of high frequency naïve T cell precursors bearing these TCRs. Moreover, we found that the TCR repertoire is not disturbed following virus infection and immune memory contraction, and that these memory T cells are able to suppress the original SARS-CoV-2 viral strain (contracted by the patient) as well as newly emerged viral strains.

We recognise that there are a number of limitations of this study, for example: the number of convalescent patients analysed by single cell gene expression and TCR sequencing (N=4) is small. Also, the number of NP 105-113 -B*07:02-specific cells from pre-pandemic donors and acute COVID-19 patients is low; this is partly because these cells were not pentamer-sorted before analysis. In this study we focus on CD8 + T cell responses to a single epitope, however it may be useful in the future to see if there are any shared or distinct features with other dominant responses. Although our data supports that high frequency naive T cell precursors are likely to contribute to mild disease outcome, it is also possible as the consequence of high viral load and overstimulation caused by high functional avidity T cells (with higher proportion of precursor TCRs) leading to exhaustion and depletion during the acute virus infection, which merits further investigation including larger cohorts sizes. We find that a higher proportion of TCR sequences from mild cases converge with those from pre-pandemic individuals; however it may be possible that this observation has arisen from higher numbers of TCRs from mild patients used as input for this convergence analysis. The specifics of antigen loading of this particular epitope compared with other NP epitopes, as well as variation in levels of protein expression and localisation is also unknown, and warrants further investigation.

Patients were recruited from John Radcliffe Hospital in Oxford, UK, between March 2020 -April 2021 by identification of patients hospitalised during the SARS-CoV-2 pandemic. Patients were recruited into the Sepsis Immunomics study and had samples collected during acute disease and convalescence. Patients were sampled at least 28 days symptom onset. Written informed consent was obtained from all patients. Ethical approval was given by the South Central-Oxford C Research Ethics Committee in England (Ref 19/SC/0296). Clinical definitions were defined as previously described 3 .

Epstein-Barr virus (EBV)-transformed B cell lines (BCLs) were generated as described previously 26 . The cDNA for the human Angiotensin Converting Enzyme 2 (ACE2) gene (ENSG00000130234) was cloned into a lentiviral vector that allows co-expression of eGFP and a Puromycin resistance marker (Addgene, Plasmid 17488). The plasmids were co-transfected with packaging plasmids pMD2.G and psPAX2 into HEK293-TLA using PEIpro (Polyplus). Lentiviral supernatant was collected 48h and 72h post-transfection and concentrated by ultracentrifugation. EBV-transformed BCLs were infected by ACE2-lentivirus at MOI 0.1 with 8μg/ml polybrene (Sigma-Aldrich) overnight, then washed, and cultured for 3-5 days. ACE2-expressing B cells were stained using primary goat anti-human ACE2 antibody (R&D, 1:20) and donkey anti-goat AF647 secondary antibody (Abcam, 1:1000) followed by cell sorting by flow cytometry. B cells with stable expression of ACE2 were maintained with 0.5μg/ml puromycin (ThermoFisher). Mycoplasma testing was carried out every four weeks with all cell lines using MycoAlert detection kit (Lonza).

Short-term SARS-CoV-2-specific T cell lines were established as previously described 17 .

Briefly, 3x10 6 to 5x10 6 PBMCs were pulsed for 1h at 37°C with 10μM peptides containing T cell epitope regions and cultured in R10 (RPMI 1640 medium with 10% foetal calf serum (FCS), 2mM glutamine and 100mg/ml pen/strep) at 2x10 6 cells/well in a 24-well Costar plate. IL-2 was added to a final concentration of 100U/mL on day 3 and cultured for a further 10-14 days. T cell clones were generated by sorting HLA-B*07:02 NP 105-113 Pentamer + CD8 + T cells at a single cell level from thawed PBMCs or short-term cell lines. T cell clones were then expanded and maintained as described previously 27 .

University, Shandong, China 28 ) were first digested with KpnI and SacII. The resulting fragment was cloned into VACV expression vector pSC11, which was inserted with a DNA segment encoding KpnI and SacII digestion sites (GGTACCGCGGCCGCCCGCGG).

The SARS-CoV-2 NP-expressing recombinant Vaccinia virus (rVACV) was produced as described previously. 29, 30, 31 . In brief, HEK293T cells (ATCC, CRL-11268) were transfected with 3μg of pSC11 containing NP with polyethylenimine. At 24h post transfection, cells were infected with the Lister strain of VACV at MOI 1 for 48h. Infected cells were collected for recombinant virus purification using TK143B cells (ATCC, CRL-8303) in 25μg/ml bromodeoxyuridine. The NP-expressing rVACV was selected through β-galactosidase staining by supplementing 25μg/ml X-gal to an agarose overlay. Master stocks of rVACV were prepared by infection on rabbit RK13 (ATCC, CCL37) and titrated on African green monkey BS-C-1 (ATCC, CCL26) cells. 

Ex vivo IFN-γ ELISpot assays were performed using either freshly isolated, cryopreserved PBMCs or antigen-specific T cell clones as described previously 3 . For ex vivo ELISpots, peptides were added to 2x10 5 PBMCs/test at 2μg/mL for 16-18 h. When using T cell clones, autologous EBV-transformed B cell lines were first loaded with peptides at 3-fold titrated concentrations and subsequently co-cultured with T cells at an effector: target (E:T) ratio of 1:50 for at least 6h. To quantify antigen-specific responses, data were collected with AID ELISpot 7.0, mean spots of the control wells were subtracted from the positive wells (PHA stimulation), and the results expressed as spot forming units (SFU)/10 6 PBMCs. Responses were considered positive if results were at least three times the mean of the negative control wells and >25SFU/10 6 PBMCs. If negative control wells had >30SFU/10 6 PBMCs or positive control wells were negative, the results were excluded from further analysis. 

Single cell RNA-Seq with ex vivo sorted CD8 + Pentamer + T cells was performed using SmartSeq2 35 with following modifications. Reverse-transcription and PCR amplification were performed as described 35 with the exception of using ISPCR primer with biotintagged at 5' and increasing the number of cycles to 25. Sequencing libraries were prepared using the Nextera XT Library Preparation Kit (Illumina) and sequencing was performed on Illumina NextSeq sequencing platform with NextSeq Control Software v4. 

Intracellular cytokine staining was performed as described previously 3 . Briefly, T cells were co-cultured with peptide-loaded or virus-infected BCLs at an appropriate E:T ratio for a 6h incubation with GolgiPlug and GolgiStop, and surface stained with PE-anti- CD107a (1:20) . Dead cells were labelled using Live/Dead Fixable Aqua dye (Invitrogen); after staining with BV421-anti-CD8 (1:40), cells were then washed, fixed with Cytofix/Cytoperm and stained with AF488-anti-IFNγ (1:33), APC-anti-TNFα (eBioscience, 1:500)) and APC-H7anti-MIP1ß(1:33). Negative controls without peptide-stimulation or virus infection were run for each sample. All reagents were from BD Bioscience unless otherwise stated. All samples were acquired on Attune™ NxT Flow Cytometer (software V3.2.1) and analyzed using FlowJo™ v.10 software (FlowJo LLC).

EBV transformed BCLs were infected with Lister strain Vaccinia virus at MOI 3 for 90-120 mins at 37°C. Cells were washed to remove virus and incubated overnight in R10 at 37°C. Cells were counted and co-cultured with T cells at an E:T ratio of 1:1. Degranulation (CD107a expression) and cytokine production of T cells were evaluated by ICS as described above.

EBV transformed BCLs expressing ACE2 were infected with SARS-CoV-2 viruses at MOI 1 for 120 mins at 37°C. Cells were washed and incubated in R10 at 37°C. After 24h, cells were counted and co-cultured with T cells at E:T ratio of 1:1. Degranulation (CD107a expression) and cytokine production of T cells were evaluated by ICS as described above.

EBV transformed BCLs expressing ACE2 were infected with SARS-CoV-2 viruses at MOI 0.1 for 120 mins at 37°C. Cells were washed and co-cultured with T cells at E:T ratio of 4:1. Control wells containing virus-infected targets without T cells were also included. After 48hrs incubation, cells were washed with PBS and lysed with Buffer RLT (Qiagen). RNA was extracted using RNeasy 96 kit (Qiagen). Virus copies were quantified with Takyon™ Dry one-step RT-qPCR (Eurogentec) using SARS-CoV-2 (2019-nCoV) CDC qPCR Probe Assay (IDT, ISO 13485:2016) and human B2M (Beta-2-Microglobulin) as an endogenous control (Applied Biosystems). Suppression rate was calculated by the percentage of reduction of virus replication by T cells.

BCL files were converted to FASTQ format using bcl2fastq v2.20.0.422 (Illumina). FASTQ files were aligned to human genome hg19 using STAR v2.6.1d 36 . Reads were counted using featureCounts (subread v2.0.0 37 ). The resulting counts matrix was analysed in R v4.0.1 using Seurat v3.9.9.9010 38 .

Cells were filtered using the following criteria: minimum number of cells expressing specific gene = 3, minimum number of genes expressed by cell = 200 and maximum number of genes expressed by cell = 4000. Cells were excluded if they expressed more than 5% mitochondrial genes. Patient-specific cells were integrated using Harmony v1.0 to remove batch effects. The AddModuleScore function (Seurat) was used to look at expression of specific gene sets (Supplementary Table 2 ). The average expression of a gene set was calculated, and the average expression levels of control gene sets were subtracted to generate a score for each cell relating to that particular gene set. Higher scores indicate that that specific signature is expressed more highly in a particular cell compared to the rest of the population. Module scores were plotted using ggplot2 v3.3.2 39 .

TCR sequences were reconstructed from scRNA-Seq FASTQ files using MiXCR v3.0.13 40, 41 to produce separate TRA and TRB output files for analysis. The output files were parsed into R using tcR v2.3.2. For paired αβ TCRs, cells were filtered to retain 1α1β or 2α1β cells. Circos plots showing paired αβ TCRs were created using circlize v0.4.12 42 .

Lists were generated for all 1β cells (regardless of number of α) to use for downstream analysis.

Input data for clustering was all 1β from scRNA-Seq cells and 1β from bulk sequencing T cell clones. Single cells and clones were grouped by Vβ usage first; TCRs from either single cells or clones with unique Vβ gene usage were excluded. Each Vβ group was broken down into subgroups based on CDR3β sequence; any TCRs from either single cells or clones that contained unique CDR3β sequences were excluded. Only TRBV27, TRBV28, TRBV5-1 showed multiple CDR3β sequences with the same gene usage. After plotting EC50 values of T cell clones, groups were classified as low or high functional avidity based on a manually defined cut-off (EC50 0.11). This led to a list of 18 groups with unique Vβ gene usage and CDR3β sequences shared among the TCRs from single cell sequencing and bulk T cell clone sequencing.

To group as many single cells into one of these 18 groups, the stringsim function was used (stringdist v0.9.6 43 ) to compare the similarity between all SmartSeq2 CDR3β sequences and each of the 18 CDR3β from the single cell/clone grouping. A minimum similarity score of 0.7 was used to decide if a TCR from a single cell should belong to one of the 18 groups. Once allocated, the single cell was annotated as being high or low functional avidity based on its group number.

BCL files were converted to FASTQ files as before. TCRs were extracted using MiXCR and the resulting output files (TRA and TRB) were parsed into R using tcR as before. TCRs were filtered to retain 1α1β for each clone. TCR clonotypes (defined as Vβ gene usage and CDR3β sequence) were compared between single TCR and bulk TCR sequencing using ggalluvial v0.12.2 44 . The predicted functional avidity annotation was overlayed onto the plots using the stringsim function as previously described to classify TCRs into high or low functional avidity groups (minimum score 0.5).

Raw BCL files were processed using 10x Genomics Cellranger v5.0.0 45 . For donor deconvolution from multiplexed single cell data, cellSNP v0.3.2 46 was used to generate a list of SNPs from Cellranger output (BAM file). Vireo v0.5.6 47 was used to demultiplex the sequencing data into individual patients from the pooled sequenced libraries, based on previously generated SNPs list TCRs from 10X sequencing represent six months convalescence and were compared to one month convalescence TCRs (SmartSeq2) from the same patient using ggalluvial. The predicted functional avidity annotation was overlayed onto the plots using the stringsim function as previously described to classify TCRs into high or low functional avidity groups (minimum score 0.5).

Normalised single cell gene expression data for T cells from the COMBAT dataset (level 2 subsets a and b) 14 was annotated with specific T cell subtypes according to COMBAT multimodal analysis, COMBAT TCR chain information and patient metadata. Any cells without both a CD8 + multimodal major cell type classification and TCR chain information were excluded from further analysis. A simplified severity grouping based on the WHO ordinal scale which ranges from 0 to 8 (https://www.who.int/blueprint/priority-diseases/key-action/ COVID-19_Treatment_Trial_Design_Master_Protocol_synopsis_Final_18022020.pdf) was used to classify participants into either Uninfected (0), Mild (1-4), Severe (5-7) or Death (8) .

A GLIPH2 CD8 + TCR input file was created from the following datasets: COMBAT 10x paired chain single cell and bulk TCR from all available participants 14 ; pentamer sorted NP 105-113 -B*07:02 specific TCR sequences and clonally expanded cells used to test functional avidity processed using MiXCR (as described previously); and NP 105-113 -B*07:02 specific TCR sequences from Lineburg and Nguyen datasets 7, 10 . Clonotypes were defined as having a unique combination of CDR3β amino acid sequence, TRBV gene, TRBJ gene and CDR3α amino acid sequence. Where no or multiple CDR3α sequences were available for a cell, an NA value was used for the CDR3α field in accordance with GLIPH2 input guidelines. For each clonotype, additional information indicating dataset origin was appended as part of the "condition" field. For the 10x COMBAT dataset, CD8 + clonotypes were distinguished from CD4 + clonotypes based on the multimodal classification of cells within each clone.

A matching GLIPH2 participant HLA input file was created using COMBAT formal HLA typing data and where no formal typing was available from imputed HLA typing 3, 14 , in addition to published HLA data relating to the Lineburg and Nguyen datasets 7, 10 .

The GLIPH2 irtools.centos v0.01 15 was run on a CentOS Linux platform (release 8.3.2011) using the CD8 + TCR and HLA input files above, together with CD8 + specific V-gene usage, CDR3 length and TCR reference files from the GLIPH2 repository and using the following parameters: local_min_pvalue=0.001; p_depth = 1000; global_convergence_cutoff = 1; simulation_depth=1000; kmer_min_depth=3; local_min_OVE=10; algorithm=GLIPH2; all_aa_interchangeable=1; number_of_hla_field=1; hla_association_cutoff=0.050000. A GLIPH score summary file was then programmatically curated, identifying convergence groups containing TCRs known to be NP 105-113 -B*07:02 specific as described previously, with associated GLIPH2 scoring and HLA prediction.

Convergence groups from this file were further categorized as being associated with or lacking association with HLA-B*07:02 based on having a GLIPH2 HLA score of <0.05 or >=0.05 respectively. Only clonotypes belonging to a HLA-B*07 associated convergence group which were from participants known to have a HLA-B*07:02 allele were deemed HLA-B*07:02 positive TCRs. Any clonotypes from convergence groups lacking HLA-B*07:02 association but belonging to patients having a HLA-B*07:02 allele were deemed ambiguous and excluded from the HLA-B*07:02 negative clonotype set.

NP 105-113 specific TCRs from pre-pandemic individuals (predicted from COMBAT dataset or experimentally defined from Lineburg and Nguyen datasets) were compiled to form a single list of sequences (237 TCRs). Similarity scores were calculated from pairwise comparisons between each CDR3β sequence from the pre-pandemic/healthy list and each CDR3β sequence from 85 unique clonotypes from four convalescent COVID-19 patients (clonotype defined per patient, TRBV gene usage and CDR3β sequence). A score of 1 indicates total similarity while a score of 0 is total dissimilarity. Each score was plotted on a box plot using ggplot2.

RNA counts from SmartSeq2 single cells were aggregated into groups based on patient origin and high/low functional avidity, and converted to a Single Cell Experiment (v1.10.1) object 48 . Differential gene expression was conducted using DESeq2 v1.28.1 on aggregated (pseudobulk) counts. Significant genes were visualised on a heatmap using pheatmap v1.0.12.

Mann Whitney non-parametric test to compare two groups (R); other statistical tests carried out using GraphPad Prism. Nonlinear regression with variable slope (four parameters) in dose-response-stimulation model was used for calculating the EC50 of T cell clones. Spearman's rank correlation coefficient was used for correlation analysis. ns not significant, * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001, S.D standard deviation.

Extended Data Fig. 1 on the left shows grouped TCRs from patients with mild disease, panel on the right for patients with severe disease. (B) Upper panel: IFN-γ ELISPOT assay for representative high and low functional avidity clones for each patient in blue and red respectively (C-COV19-038 only has low functional avidity clone shown). Lower panels: high functional avidity clone from C-COV19-45 and low functional avidity clone from C-COV-038 with example of EC50 derivation. TCM: T central memory, TEFF: T  effector, TEM: T effector memory, TEMRA: T effector memory re-expressing CD45RA. For all box plots, the lower and upper hinge represent 25-75th percentiles, the central line represents the median and whiskers extend to maximum and minimum values that are no greater than 1.5x interquartile range. Mann-Whitney test was used for analysis and two-tailed P value was calculated. **** P<0.0001. Peng Nat Immunol. Author manuscript; available in PMC 2022 January 04.

Danning Dong #1,2,5 , Frank Penkava #6

Wanwisa Dejnirattisa 3,4 , Chang Liu 2,3,4 , Prathiba Kurupati 1 , Isar Nassiri 3,15,16 , Robert A. Watson 15

Confronting complexity: real-world immunodominance in antiviral CD8+ T cell responses

Mechanisms of viral interference with MHC class I antigen processing and presentation

Broad and strong memory CD4(+) and CD8(+) T cells induced by SARS-CoV-2 in UK convalescent individuals following COVID-19

Unbiased Screens Show CD8(+) T Cells of COVID-19 Patients Recognize Shared Epitopes in SARS-CoV-2 that Largely Reside outside the Spike Protein

Suboptimal SARS-CoV-2-specific CD8(+) T cell response associated with the prominent HLA-A*02:01 phenotype

Characterization of pre-existing and induced SARS-CoV-2-specific CD8(+) T cells

CD8(+) T cells specific for an immunodominant SARS-CoV-2 nucleocapsid epitope display high naive precursor frequency and TCR promiscuity

The impact of viral mutations on recognition by SARS-CoV-2 specific T-cells. bioRxiv

Evidence of escape of SARS-CoV-2 variant B.1.351 from natural and vaccineinduced sera

CD8(+) T cells specific for an immunodominant SARS-CoV-2 nucleocapsid epitope cross-react with selective seasonal coronaviruses

Robust T Cell Immunity in Convalescent Individuals with Asymptomatic or Mild COVID-19

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

SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity. medRxiv

Analyzing the Mycobacterium tuberculosis immune response by T-cell receptor clustering with GLIPH2 and genome-wide antigen screening

Enriched HLA-E and CD94/NKG2A Interaction Limits Antitumor CD8(+) Tumor-Infiltrating T Lymphocyte Responses

Boosted Influenza-Specific T Cell Responses after H5N1 Pandemic Live Attenuated Influenza Virus Vaccination

Interleukin-10 Directly Inhibits CD8(+) T Cell Function by Enhancing N-Glycan Branching to

Parkinsonism-associated protein DJ-1/Park7 is a major protein deglycase that repairs methylglyoxal-and glyoxal-glycated cysteine, arginine, and lysine residues

Matrikines are key regulators in modulating the amplitude of lung inflammation in acute pulmonary infection

HLA-B may be more protective against HIV-1 than HLA-A because it resists negative regulatory factor (Nef) mediated down-regulation

The antiviral efficacy of HIV-specific CD8(+) T-cells to a conserved epitope is heavily dependent on the infecting HIV-1 isolate

Differential effect of DJ-1/PARK7 on development of natural and induced regulatory T cells

PARK7/DJ-1 promotes pyruvate dehydrogenase activity and maintains Treg homeostasis. bioRxiv

Neutrophils in respiratory viral infections

HIV-specific cytotoxic T cells from long-term survivors select a unique T cell receptor

Self-Maintaining CD103<sup>+</sup> Cancer-Specific T Cells Are Highly Energetic with Rapid Cytotoxic and Effector Responses

A systemic and molecular study of subcellular localization of SARS-CoV-2 proteins

General method for production and selection of infectious vaccinia virus recombinants expressing foreign genes

Construction and characterization of an infectious vaccinia virus recombinant that expresses the influenza hemagglutinin gene and induces resistance to influenza virus infection in hamsters

Vaccinia virus expression vector: coexpression of betagalactosidase provides visual screening of recombinant virus plaques

Hypoxic and pharmacological activation of HIF inhibits SARS-CoV-2 infection of lung epithelial cells

Antibody evasion by the P. 1 strain of SARS-CoV-2

Reduced neutralization of SARS-CoV-2 B.1.617 by vaccine and convalescent serum

Full-length RNA-seq from single cells using Smart-seq2

STAR: ultrafast universal RNA-seq aligner

featureCounts: an efficient general purpose program for assigning sequence reads to genomic features

Comprehensive Integration of Single-Cell Data

Elegant Graphics for Data Analysis Use R!. 2nd

Antigen receptor repertoire profiling from RNA-seq data

MiXCR: software for comprehensive adaptive immunity profiling

circlize Implements and enhances circular visualization in R

The stringdist Package for Approximate String Matching

Layered Grammar for Alluvial Plots

Massively parallel digital transcriptional profiling of single cells

an efficient tool for genotyping single cells

Bayesian demultiplexing of pooled single-cell RNA-seq data without genotype reference

Orchestrating single-cell analysis with Bioconductor

T cell clones with different EC50 values and differing functional avidity (N=11)

Correlation plot between percentage of viral suppression by specific T cell clone and its corresponding EC50 value (N=11, R=-0.7699, P=0.0075). Spearman's rank correlation coefficient was used for correlation analysis with two-tailed P value

Author manuscript; available in PMC

Characterisation of NP 105-113 -B*07:02 specific T cell responses at six months convalescence

TRBV gene usage of common and expanded TCR clonotypes (defined as TRBV and TRBJ gene usage) are labelled for clarity. TCR clonotypes coloured pink are low functional avidity, blue depict high functional avidity; clonotypes coloured grey do not have similar TCRs to T cell clones. C-COV19-46 six months cells were sequenced by 10x single cell sequencing

Author manuscript; available in PMC

Gamma or Delta variant infected B cell lines. (C) Inhibition of SARS-CoV-2 viral replication (Victoria strain) by C-COV19-046 bulk NP 105-113 -specific T cell lines from one month (grey bars) and six months (red bars) convalescent samples, N=2 biological replicates. Data shown as means ± S.D representing three independent experiments with similar results. E:Teffector: target ratio. (D) Anti-viral activity of NP 105-113 -specific bulk T cells from six months convalescence against SARS-CoV-2 variants of concern: Alpha (purple bars), Beta (blue bars) and Gamma (green bars), N=3 biological replicates. Data shown as means ± S.D representing three independent experiments with similar results. (E) Anti-viral activity of NP 105-113 -specific bulk T cells from six months convalescence against SARS-CoV-2 variants of concern: Victoria strain (grey bars) and Delta variant (orange bars)

Author manuscript; available in PMC

We are grateful to all the participants for donating their samples and data for these analyses, and the research teams involved in the consenting, recruitment, and sampling of these participants. We would like to thank Kevin Clark and Sally-Ann Clark from WIMM flow cytometry facility for their help with cell sorting. The B.1.617.2 (Delta) variant was kindly provided by Wendy Barclay and Thushan De Silva from the UKRI funded Genotype to Phenotype Consortium (G2P-UK). This work uses data provided by patients and collected by the NHS as part of their care and support #DataSavesLives.