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Repeated mRNA vaccination sequentially boosts SARS-CoV-2-specific CD8+ T cells in persons with previous COVID-19

Nature Immunology volume 25, pages 166–177 (2024)Cite this article

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Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) hybrid immunity is more protective than vaccination or previous infection alone. To investigate the kinetics of spike-reactive T (TS) cells from SARS-CoV-2 infection through messenger RNA vaccination in persons with hybrid immunity, we identified the T cell receptor (TCR) sequences of thousands of index TS cells and tracked their frequency in bulk TCRβ repertoires sampled longitudinally from the peripheral blood of persons who had recovered from coronavirus disease 2019 (COVID-19). Vaccinations led to large expansions in memory TS cell clonotypes, most of which were CD8+ T cells, while also eliciting diverse TS cell clonotypes not observed before vaccination. TCR sequence similarity clustering identified public CD8+ and CD4+ TCR motifs associated with spike (S) specificity. Synthesis of longitudinal bulk ex vivo single-chain TCRβ repertoires and paired-chain TCRɑβ sequences from droplet sequencing of TS cells provides a roadmap for the rapid assessment of T cell responses to vaccines and emerging pathogens.

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Fig. 1: Vaccines expand previously detected and low-abundance clonotypes.
Fig. 2: Longitudinal kinetics of S-reactive clonotypes defined by AIM-scTCRαβ-seq from after infection to before vaccination.
Fig. 3: Trajectories of S-reactive clonotypes defined by AIM-scTCRαβ-seq differentiate CD4+ and CD8+ T cells.
Fig. 4: TCRαβ sequence similarity network shows public CD8+ T cell responses among sequences recovered by AIM-scTCRαβ-seq.
Fig. 5: Transgenic CD8+ T cell-origin TCRs from five public clusters are activated in the context of HLA-A*03:01 and the KCY epitope.
Fig. 6: TRB sequence-defined metrics and nAbs are associated with disease severity before and after mRNA vaccination.

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Data availability

The whole PBMC and nasal TRB repertoires are available at https://doi.org/10.5281/zenodo.7698787. Sorted naive and memory PBMC T cell subset TRB repertoires from the time point E00, sorted total CD4+ T cells and AIM-sorted CD4+ T cell subsets from the time point E03 are available at https://doi.org/10.5281/zenodo.7686500. Processed single-cell CD69+CD137+ AIM-scTCRɑβ-seq and feature barcode oligonucleotide-labeled mAb data are available at https://zenodo.org/record/6909380. The flow cytometry results from the intracellular cytokine staining of CD4+ and CD8+ S-reactive T cells are available at https://doi.org/10.5281/zenodo.8088178. The sequences of CD8+ and CD4+ T cell-origin TCRs expressed in reporter cells are available from GenBank (OP245920-OP245935 and OR239787-OR239798, respectively). The reference dataset for Cell Ranger used was GRCh-Alts-ensembl-5.0.0 and is available at 10xgenomics.com/support/software/cell-ranger/downloads. Source data are provided with this paper.

Code availability

The code used to analyze and present the data is based on Python v.3.8 or R v.4.1.2 and is available at https://github.com/kmayerb/NIA34780B. The availability of the tool used to classify PBMC TRB repertoires for evidence of CMV infection is discussed at https://www.immunoseq.com/cmv-classifier/.

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Acknowledgements

We thank: the participants; the Virology Research Clinic, University of Washington for collecting the specimens and data; D. Geraghty and C.-W. Pyo at the Fred Hutchinson Cancer Center (FHCC) for HLA typing; L. Stamatatos, FHCC, for the SARS-CoV-2 S protein with stabilizing proline substitutions used in the antibody assays; J. Bloom, FHCC, for the expression plasmids encoding the SARS-CoV-2 S protein from strain Wu-1, or Omicron BA.1, BA.2 and BA.4, with 21-amino-acid C-terminal deletions. D.M.K. received support from a National Institutes of Health (NIH) National Institute of Allergy and Infectious Diseases (NIAID) contract no. 75N93019C00063 (D.M.K.). The study has received support from NIH grant nos. AI163999 (D.M.K.), K08 AI148588 (E.S.F.), R01 AI136514 (K.M.-B. and A.F.-G.), F30 CA254168 (T.H.P.), T32 CA080416 (S.J.), P01 CA225517 (A.G.C., D.M.K., L.J., T.H.P. and S.J.), R01 AI134878 (A.M.S., E.L.B. and R.S.G.) and UM1 AI068614 (A.M.S., E.L.B. and R.S.G.). The scientific computing infrastructure at the FHCC was funded by an NIH Office of Research Infrastructure Programs grant no. S10 OD028685 (K.M.-B., A.F.-G. and E.S.F.). The Bill and Melinda Gates Foundation provided support via grant no. INV-027499 (A.F.-G. and K.M.-B.). This study was funded in part with Federal funds from the NIAID, NIH and Department of Health and Human Services under NIH contract no. HHSN272201800013C.

Author information

Author notes

  1. Rachel M. Gittelman

    Present address: Guardant Health, Redwood City, CA, USA

  2. Matyas Ecsedi

    Present address: Takeda Oncology, Cambridge, MA, USA

  3. These authors contributed equally: Emily S. Ford, Koshlan Mayer-Blackwell, Lichen Jing.

Authors and Affiliations

  1. Department of Medicine, University of Washington, Seattle, WA, USA

    Emily S. Ford, Lichen Jing, Kerry J. Laing, Thomas H. Pulliam, Saumya Jani, Carlissa J. Burrow, Christopher L. McClurkan, Anna Wald, Aude G. Chapuis & David M. Koelle

  2. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA

    Emily S. Ford, Koshlan Mayer-Blackwell, Anton M. Sholukh, Russell St. Germain, Emily L. Bossard, Anna Wald, Alexander L. Greninger, Andrew Fiore-Gartland & David M. Koelle

  3. Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA

    Hong Xie, Saumya Jani, Stacy Selke, Anna Wald, Alexander L. Greninger & David M. Koelle

  4. Department of Epidemiology, University of Washington, Seattle, WA, USA

    Anna Wald

  5. Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, MD, USA

    Michael R. Holbrook, Brett Eaton, Elizabeth Eudy, Michael Murphy & Elena Postnikova

  6. Adaptive Biotechnologies, Seattle, WA, USA

    Harlan S. Robins, Rebecca Elyanow & Rachel M. Gittelman

  7. Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA, USA

    Matyas Ecsedi, Elise Wilcox & Aude G. Chapuis

  8. Department of Global Health, University of Washington, Seattle, WA, USA

    David M. Koelle

  9. Department of Translational Research, Benaroya Research Institute, Seattle, WA, USA

    David M. Koelle

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  1. Emily S. Ford
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D.M.K., E.S.F., K.M.-B., A.F.-G., L.J. and K.J.L. conceptualized the study. A.M.S., E.L.B., R.S.G., M.R.H., B.E., E.E., M.M. and E.P. designed and performed the serological assays. L.J., C.J.B., H.X., T.H.P., K.J.L., H.S.R., R.M.G., R.E. and A.L.G. designed and performed the cellular immunity and sequencing assays. A.G.C., E.W. and M.E. provided the specialty reagents enabling the TCR functional assays. S.S. and C.L.M. processed and managed the specimen and demographic data. A.W. organized the clinical cohort. K.M.-B., E.S.F., K.J.L, L.J., S.J. and A.F.-G. carried out the bioinformatic and statistical analyses. E.S.F., K.M.-B., K.J.L., A.F.-G., L.J. and D.M.K. wrote the manuscript. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Corresponding author

Correspondence to David M. Koelle.

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Competing interests

H.S.R. and R.E. are employees of Adaptive Biotechnologies. B.E., E.E. and M.R.H. performed this work as employees of Laulima Government Solutions. M.M. and E.P. are subcontractors to Laulima Government Solutions; they performed this work as employees of Tunnell Government Services. The other authors declare no competing interests.

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Nature Immunology thanks Tao Dong and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. Primary Handling Editor: Ioana Visan in collaboration with the Nature Immunology editorial team.

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Extended data

Extended Data Fig. 1 Schedule of infection, vaccination, and sample collection.

Fifty-three study participants with prior SARS-CoV-2 infection as documented by seropositivity to S and N proteins and participant P845 who was seronegative prior to vaccination received either BNT162 or mRNA-1273 1st dose (closed circle), 2nd dose (closed triangle), and booster (3rd) dose (closed square) on the days after symptom onset as shown. Persons with mild or moderate COVID-19 are shown in magenta, persons with severe COVID-19 in black. Duration of hospitalization in persons with severe COVID-19 is shown in purple. PBMC were obtained at exam visits convalescence (E00, n = 54), late convalescence (E00.5, n = 16), pre-dose 1 (E01, n = 34), post-dose 1 (E02, n = 52), post-dose 2 (E03, n = 53), pre-boost (E04, n = 7), and post-boost (E05, n = 44). 33 persons had samples at E00, E01 and E03, 31 had samples at E00, E01, E02, and E03, and 26 had samples at all of E00, E01, E02, E03, and E05. Three participants were observed to have breakthrough COVID-19 infection based on boosting of anti-nucleocapsid antibody levels at visit E05 (P545, P664, P669), indicated in orange. All participants received primary vaccination but not all received a booster dose.

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Extended Data Fig. 2 Primary vaccination led to expansion in specific TCR clonotypes in vaccinated persons.

Frequency (% of bulk TRB repertoire) of individual clonotypes in E01 vs. E03 in 32 persons with both samples. Expanded (red) (or contracted, purple) clonotypes were defined as log2(fold change) > 2 (or < 0.5) and Fisher’s exact test FDR-adjusted p value < 0.05. Dotted line indicates y = x. Participant ID at top of each graph. ND = not detected. Serologically-naive Participant P845 is not shown.

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Extended Data Fig. 3 Frequency of E01-E03 expanded clonotypes from E00 through E05.

(a) E01-E03 expanded clonotype frequency (abundance) over the course of the study. Each line is an individual clonotype. TRB-PI are shown in black, TRB-PV are in orange (n = 30). ND = not detected. (b) Boxplot at lower right shows the percent of TRB-PI and TRB-PV for each participant that were detectable after a 3rd vaccine dose (E05) (n = 26). Median, IQR and whiskers (1.5*IQR) are noted. Comparison between groups is by two-sided Wilcoxon rank sum test, p = 0.0023. Participants P742 and P758 were not sampled at E02 and trajectories are not shown. Participant P665 had no expanded clonotypes and is not shown. Participant P845 was serologically naive at E00. Participants P545 and P669 experienced breakthrough infection between the E03 and the E05 timepoints and so repertoires at E05 represent both repeat natural infection as well as mRNA booster vaccine dose.

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Extended Data Fig. 4 AIM-scTCRαβ-seq enriches a complex set of clonotypes from PBMC after mRNA vaccination of previously SARS-CoV-2 infected persons.

(a) Frequency of clonotypes detected by CD69+CD137+ AIM-scTCRαβ-seq plotted against the productive frequency of TRB-matched templates in bulk TRB sequencing at E03. Cell types defined by oligonucleotide-labeled mAbs are shown as CD4+ (green), CD8+ (blue), or phenotype not defined (purple) T cells. Clonotype enrichment in CD69+CD137+ AIM-scTCRαβ-seq was determined by cumulative distribution function (CDF) with false discovery rate (FDR) correction (Methods). Clonotypes that were detected, but not enriched, in CD69+CD137+ AIM-scTCRɑβ-seq are shown in red (n = 180) and were omitted from CDR3 motif discovery analysis. ND indicates clonotypes that could not be assigned a TRB unambiguously. (b,c) Productive frequency of CD69+CD137+ AIM-scTCRɑβ-seq detected clonotypes in relation to change in productive frequency from E01 to E03 in bulk TCR-β-seq is shown for 2 representative participants, including one with a lower proportion of representation in CD69+CD137+ AIM-scTCRαβ-seq of their significantly expanded clonotypes (P525, b) and another with a higher proportion of significantly expanded clonotypes also seen by CD69+CD137+ AIM-scTCRαβ-seq (P581, c). (d, e) Density plots show proportion of unique, expanded clonotypes by frequency at E03 (d) or fold change from E01 to E03 (primary vaccination) (e) by detection in CD69+CD137+ AIM-scTCRαβ-seq at E03 amongst 12 participants with both paired E01/E03 bulk TCR-β-seq and CD69+CD137+ AIM-scTCRαβ-seq.

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Extended Data Fig. 5 TS from CD69+CD137+ AIM-scTCRαβ-seq matching TRB clonotypes from nasal swabs in 14 participants at E05.

(a) Rank abundance plots of TRB clonotypes in nasal samples in 14 participants, where blue (CD8+) and green (CD4+) dashes indicate rank of clones identified in the same participant’s blood by CD69+CD137+ AIM-scTCRαβ-seq at E03. (b) In participant P673, rank abundance plot of TRB clonotypes in nasal samples collected at E05. Clones labeled TCR1, TCR2, TCR3, TCR4, TCR8.1 and TCR8.2 indicate TRB clonotypes with exact sequence match to experimentally-confirmed receptors shown to recognize HLA-A*03:01 S epitopes.

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Extended Data Fig. 6 TS and vaccine-expanded clonotypes.

Overlay of TRB sequences from CD69+CD137+ AIM-scTCRɑβ-seq of TS cells onto bulk TRB clonotype frequency at E01 and E03 in two representative participants. E01-to-E03 expanded (Ex) or contracted (Con), TRB clonotypes are shown, with TRB matching a CD69+CD137+ AIM-scTCRɑβ-seq (TS) shown in color and unmatched TRB are shown in gray (Und). Among clonotypes that neither expanded nor contracted (Non-Ex), only CD69+CD137+ AIM-scTCRɑβ-seq TRB-matched clonotypes are shown between red dashed lines. Frequencies of TRB clonotypes pre- and post-vaccine are as resolved by bulk TCR-β-seq. ND = not detected.

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Extended Data Fig. 7 Abundance of TS clonotypes by TCRβ-seq over time.

Longitudinal tracking of abundance of CD69+CD137+ AIM-scTCRαβ-seq-identified CD4+ and CD8+ TS TRB clonotypes in PBMC by TCRβ-seq in all participants with AIM-scTCRαβ-seq. Numbers in top rows indicate the number of unique CD69+CD137+ AIM-scTCRαβ-seq TRB clonotypes from E03 detected at each time point. Percentages refer to the fraction of CD69+CD137+ AIM-scTCRαβ-seq clonotypes detected at the E02 and E03 timepoints, respectively, detected only post-vaccination. Percentages in gray are the fraction of unique clones detected at E03 that are below the level of detection at E02. Not all participants had samples at each time point, indicated by absence of dot symbols at those samples. Participant P669 had SARS-CoV-2 infection between E03 and E05 timepoints and so this E05 repertoire reflects repeat SARS-Co-2 infection and mRNA booster vaccine.

Source data

Extended Data Fig. 8 Selection of AIM-scTCRαβ-seq T cells using CD69, CD137, and CD134/ CD154 marker sets compared to bulk TCRβ-seq and sorted CD4 TCRβ-seq from PBMCs over primary vaccination.

Frequency (% of bulk TRB repertoire) of individual clonotypes in E01 vs. E03 in 7 persons studied by CD69+CD137+ AIM-scTCRαβ-seq and (CD69/CD137)+(CD134/CD154)+ CD4+ AIM-TCRβ-seq. Dotted line indicates y = x. Participant ID at top of each pair of graphs. ND = not detected. All PBMC are shown. Clonotypes found in the total CD4+ sorted fraction are shown in black. Clonotypes present in the total CD4+ sorted fraction and also enriched in sequential sorting of CD4+CD69+CD137+ (green) cells are overlaid with CD4+CD69+(CD134/CD154)+ and CD4+CD137+(CD134/CD154)+ (pink) cells in the left and right panels, respectively, for seven participants. Clonotypes in all three fractions (total CD4+, CD4+CD69+CD137+, and CD4+CD69+(CD134/CD154)+ and CD4+CD137+(CD134/CD154)+) are shown in orange. Gray shaded clonotypes were not identified as CD4+ by any of these methods.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–12.

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Supplementary Tables 1–17

All supplementary tables (combined into a single workbook with one tab per table). The first row of each table is the table title.

Supplementary Data

Statistical/bar plot data for Supplementary Figs. 3a,b, 5b,c, 9 and 11.

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Ford, E.S., Mayer-Blackwell, K., Jing, L. et al. Repeated mRNA vaccination sequentially boosts SARS-CoV-2-specific CD8+ T cells in persons with previous COVID-19. Nat Immunol 25, 166–177 (2024). https://doi.org/10.1038/s41590-023-01692-x

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