OpenLB
Open Library of Bioscience
Advanced Search
Nature communications
05 10, 2021;12 (1): 2593.

Identification and characterization of a SARS-CoV-2 specific CD8 T cell response with immunodominant features.

Anastasia Gangaev, Steven L C Ketelaars, Olga I Isaeva, Sanne Patiwael, Anna Dopler, Kelly Hoefakker, Sara De Biasi, Lara Gibellini, Cristina Mussini, Giovanni Guaraldi, Massimo Girardis, Cami M P Talavera Ormeno, Paul J M Hekking, Neubury M Lardy, Mireille Toebes, Robert Balderas, Ton N Schumacher, Huib Ovaa, Andrea Cossarizza, Pia Kvistborg
Author Information
  1. Anastasia Gangaev: Division of Molecular Oncology and Immunology, The Netherlands Cancer Institute, Amsterdam, North Holland, The Netherlands. ORCID
  2. Steven L C Ketelaars: Division of Molecular Oncology and Immunology, The Netherlands Cancer Institute, Amsterdam, North Holland, The Netherlands.
  3. Olga I Isaeva: Division of Molecular Oncology and Immunology, The Netherlands Cancer Institute, Amsterdam, North Holland, The Netherlands. ORCID
  4. Sanne Patiwael: Division of Molecular Oncology and Immunology, The Netherlands Cancer Institute, Amsterdam, North Holland, The Netherlands.
  5. Anna Dopler: Division of Molecular Oncology and Immunology, The Netherlands Cancer Institute, Amsterdam, North Holland, The Netherlands. ORCID
  6. Kelly Hoefakker: Division of Molecular Oncology and Immunology, The Netherlands Cancer Institute, Amsterdam, North Holland, The Netherlands.
  7. Sara De Biasi: University of Modena and Reggio Emilia School of Medicine, Modena, Emilia Romagna, Italy. ORCID
  8. Lara Gibellini: University of Modena and Reggio Emilia School of Medicine, Modena, Emilia Romagna, Italy. ORCID
  9. Cristina Mussini: University of Modena and Reggio Emilia School of Medicine, Modena, Emilia Romagna, Italy.
  10. Giovanni Guaraldi: University of Modena and Reggio Emilia School of Medicine, Modena, Emilia Romagna, Italy. ORCID
  11. Massimo Girardis: University of Modena and Reggio Emilia School of Medicine, Modena, Emilia Romagna, Italy.
  12. Cami M P Talavera Ormeno: Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, South Holland, The Netherlands.
  13. Paul J M Hekking: Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, South Holland, The Netherlands.
  14. Neubury M Lardy: Department of Immunogenetics, Sanquin Diagnostics B.V., Amsterdam, North Holland, The Netherlands.
  15. Mireille Toebes: Division of Molecular Oncology and Immunology, The Netherlands Cancer Institute, Amsterdam, North Holland, The Netherlands.
  16. Robert Balderas: Department of Biological Sciences, BD Biosciences, San Jose, CA, USA. ORCID
  17. Ton N Schumacher: Division of Molecular Oncology and Immunology, The Netherlands Cancer Institute, Amsterdam, North Holland, The Netherlands. ORCID
  18. Huib Ovaa: Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, South Holland, The Netherlands. ORCID
  19. Andrea Cossarizza: University of Modena and Reggio Emilia School of Medicine, Modena, Emilia Romagna, Italy. ORCID
  20. Pia Kvistborg: Division of Molecular Oncology and Immunology, The Netherlands Cancer Institute, Amsterdam, North Holland, The Netherlands. p.kvistborg@nki.nl. ORCID
PMID: 33972535 DOI: 10.1038/s41467-021-22811-y

Abstract

The COVID-19 pandemic caused by SARS-CoV-2 is a continuous challenge worldwide, and there is an urgent need to map the landscape of immunogenic and immunodominant epitopes recognized by CD8 T cells. Here, we analyze samples from 31 patients with COVID-19 for CD8 T cell recognition of 500 peptide-HLA class I complexes, restricted by 10 common HLA alleles. We identify 18 CD8 T cell recognized SARS-CoV-2 epitopes, including an epitope with immunodominant features derived from ORF1ab and restricted by HLA-A*01:01. In-depth characterization of SARS-CoV-2-specific CD8 T cell responses of patients with acute critical and severe disease reveals high expression of NKG2A, lack of cytokine production and a gene expression profile inhibiting T cell re-activation and migration while sustaining survival. SARS-CoV-2-specific CD8 T cell responses are detectable up to 5 months after recovery from critical and severe disease, and these responses convert from dysfunctional effector to functional memory CD8 T cells during convalescence.

References

  1. Worldometer. https://www.worldometers.info/coronavirus (2020).
  2. Shomuradova, A. S. et al. SARS-CoV-2 epitopes are recognized by a public and diverse repertoire of human T cell receptors. Immunity 53, 1245–1257 (2020). [PMID: 33326767]
  3. Wajnberg, A. et al. Robust neutralizing antibodies to SARS-CoV-2 infection persist for months. Science 370, 1227–1230 (2020). [PMID: 33115920]
  4. Sekine, T. et al. Robust T cell immunity in convalescent individuals with asymptomatic or mild COVID-19. Cell 183, 158–168 (2020). [PMID: 32979941]
  5. Lau, E. H. Y. et al. Neutralizing antibody titres in SARS-CoV-2 infections. Nat. Commun. 12, 63 (2021). [PMID: 33397909]
  6. Ni, L. et al. Detection of SARS-CoV-2-specific humoral and cellular immunity in COVID-19 convalescent individuals. Immunity 52, 971–977 (2020). [PMID: 32413330]
  7. Ren, L. et al. The kinetics of humoral response and its relationship with the disease severity in COVID-19. Commun. Biol. 3, 780 (2020). [PMID: 33311543]
  8. Grifoni, A. et al. Targets of T cell responses to SARS-CoV-2 coronavirus in humans with COVID-19 disease and unexposed individuals. Cell 181, 1–13 (2020). [DOI: 10.1016/j.cell.2020.05.015]
  9. Weiskopf, D. et al. Phenotype and kinetics of SARS-CoV-2-specific T cells in COVID-19 patients with acute respiratory distress syndrome. Sci. Immunol. 5, eabd2071 (2020). [PMID: 32591408]
  10. Peng, Y. et al. Broad and strong memory CD4+and CD8+T cells induced by SARS-CoV-2 in UK convalescent individuals following COVID-19. Nat. Immunol. 21, 1336–1345 (2020). [DOI: 10.1038/s41590-020-0782-6]
  11. Thieme, C. J. et al. Robust T cell response toward spike, membrane, and nucleocapsid SARS-CoV-2 proteins is not associated with recovery in critical COVID-19 patients. Cell Rep. Med. 1, 100092 (2020). [PMID: 32904468]
  12. Schulien, I. et al. Characterization of pre-existing and induced SARS-CoV-2-specific CD8+T cells. Nat. Med. 27, 78–85 (2021). [PMID: 33184509]
  13. Oja, A. E. et al. Divergent SARS-CoV-2-specific T- and B-cell responses in severe but not mild COVID-19 patients. Eur. J. Immunol. 50, 1998–2012 (2020). [PMID: 33073359]
  14. Le Bert, N. et al. SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls. Nature 584, 457–462 (2020). [DOI: 10.1038/s41586-020-2550-z]
  15. Braun, J. et al. SARS-CoV-2-reactive T cells in healthy donors and patients with COVID-19. Nature 587, 270–274 (2020). [DOI: 10.1038/s41586-020-2598-9]
  16. Neidleman, J. et al. SARS-CoV-2-specific T cells exhibit phenotypic features of helper function, lack of terminal differentiation, and high proliferation potential. Cell Rep. Med. 1, 100081 (2020). [PMID: 32839763]
  17. Nelde, A. et al. SARS-CoV-2-derived peptides define heterologous and COVID-19-induced T cell recognition. Nat. Immunol. 22, 74–85 (2020). [PMID: 32999467]
  18. Ferretti, A. P. et al. Unbiased screens show CD8+T cells of COVID-19 patients recognize shared epitopes in SARS-CoV-2 that largely reside outside the spike protein. Immunity 53, 1–13 (2020). [DOI: 10.1016/j.immuni.2020.10.006]
  19. Yewdell, J. W. Confronting complexity: real-world immunodominance in antiviral CD8+ T cell responses. Immunity 25, 533–543 (2006). [PMID: 17046682]
  20. Su, S., Du, L. & Jiang, S. Learning from the past: development of safe and effective COVID-19 vaccines. Nat. Rev. Microbiol. 368, 1–9 (2020).
  21. Diao, B. et al. Reduction and functional exhaustion of T cells in patients with coronavirus disease 2019 (COVID-19). Front. Immunol. 11, 827 (2020). [PMID: 32425950]
  22. Zheng, M. et al. Functional exhaustion of antiviral lymphocytes in COVID-19 patients. Cell. Mol. Immunol. 17, 533–535 (2020). [PMID: 32203188]
  23. Mathew, D. et al. Deep immune profiling of COVID-19 patients reveals distinct immunotypes with therapeutic implications. Science 369, eabc8511 (2020). [PMID: 32669297]
  24. Nielsen, M., Lundegaard, C., Lund, O. & Kesmir, C. The role of the proteasome in generating cytotoxic T-cell epitopes: insights obtained from improved predictions of proteasomal cleavage. Immunogenetics 57, 33–41 (2005). [PMID: 15744535]
  25. Jurtz, V. et al. NetMHCpan-4.0: improved peptide-MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data. J. Immunol. 199, 3360–3368 (2017). [PMID: 28978689]
  26. Kvistborg, P. et al. Anti-CTLA-4 therapy broadens the melanoma-reactive CD8+ T cell response. Sci. Transl. Med. 254, 254ra126 (2014).
  27. Kvistborg, P. et al. TIL therapy broadens the tumor-reactive CD8(+) T cell compartment in melanoma patients. Oncoimmunology 1, 409–418 (2012).
  28. Shu, Y. & McCauley, J. GISAID: Global Initiative on Sharing All Influenza Data - from vision to reality. Eurosurveillance 22, 30494 (2017). [PMID: 28382917]
  29. Frankild, S., De Boer, R. J., Lund, O., Nielsen, M. & Kesmir, C. Amino acid similarity accounts for T cell cross-reactivity and for ‘holes’ in the T cell repertoire. PLoS ONE 3, e1831 (2008). [PMID: 18350167]
  30. Rubio-Godoy, V. et al. Positional scanning-synthetic peptide library-based analysis of self- and pathogen-derived peptide cross-reactivity with tumor-reactive Melan-A-specific CTL. J. Immunol. 169, 5696–5707 (2002). [PMID: 12421949]
  31. Riley, T. P. et al. T cell receptor cross-reactivity expanded by dramatic peptide-MHC adaptability. Nat. Chem. Biol. 14, 934–942 (2018). [PMID: 30224695]
  32. De Boer, R. J., Homann, D. & Perelson, A. S. Different dynamics of CD4+ and CD8+ T cell responses during and after acute lymphocytic choriomeningitis virus infection. J. Immunol. 171, 3928–3935 (2003). [PMID: 14530309]
  33. Kotturi, M. F. et al. Naive precursor frequencies and MHC binding rather than the degree of epitope diversity shape CD8+ T cell immunodominance. J. Immunol. 181, 2124–2133 (2008). [PMID: 18641351]
  34. Grifoni, A. et al. A sequence homology and bioinformatic approach can predict candidate targets for immune responses to SARS-CoV-2. Cell Host Microbe 27, 671–680 (2020). [PMID: 32183941]
  35. Miles, J. J., Douek, D. C. & Price, D. A. Bias in the αβ T-cell repertoire: implications for disease pathogenesis and vaccination. Immunol. Cell Biol. 89, 375–387 (2011). [PMID: 21301479]
  36. Turner, S. J., Doherty, P. C., McCluskey, J. & Rossjohn, J. Structural determinants of T-cell receptor bias in immunity. Nat. Rev. Immunol. 6, 883–894 (2006). [PMID: 17110956]
  37. Amanat, F. & Krammer, F. SARS-CoV-2 vaccines: status report. Immunity 52, 583–589 (2020). [PMID: 32259480]
  38. Thanh, Le,T. et al. The COVID-19 vaccine development landscape. Nat. Rev. Drug Discov. 19, 305–306 (2020). [DOI: 10.1038/d41573-020-00073-5]
  39. Wang, W., Zhang, W., Zhang, J., He, J. & Zhu, F. Distribution of HLA allele frequencies in 82 Chinese individuals with coronavirus disease-2019 (COVID-19). HLA 96, 194–196 (2020). [PMID: 32424945]
  40. Pisanti, S. et al. Correlation of the two most frequent HLA haplotypes in the Italian population to the differential regional incidence of Covid-19. J. Transl. Med. 18, 352 (2020). [PMID: 32933522]
  41. Shkurnikov, M. et al. Association of HLA Class I Genotypes With Severity of Coronavirus Disease-19. Front Immunol 12, 641900 (2021).
  42. Flores-Villanueva, P. O. et al. Control of HIV-1 viremia and protection from AIDS are associated with HLA-Bw4 homozygosity. Proc. Natl Acad. Sci. USA 98, 5140–5145 (2001). [PMID: 11309482]
  43. Rydyznski Moderbacher, C. et al. Antigen-specific adaptive immunity to SARS-CoV-2 in acute COVID-19 and associations with age and disease severity. Cell 183, 996–1012 (2020). [PMID: 33010815]
  44. Tan, A. T. et al. Early induction of functional SARS-CoV-2-specific T cells associates with rapid viral clearance and mild disease in COVID-19 patients. Cell Rep. 34, 108728 (2021). [PMID: 33516277]
  45. Zhou, J., Matsuoka, M., Cantor, H., Homer, R. & Enelow, R. I. Cutting edge: engagement of NKG2A on CD8+ effector T cells limits immunopathology in influenza pneumonia. J. Immunol. 180, 25–29 (2008). [PMID: 18096998]
  46. De Biasi, S. et al. Marked T cell activation, senescence, exhaustion and skewing towards TH17 in patients with COVID-19 pneumonia. Nat. Commun. 11, 3434 (2020). [PMID: 32632085]
  47. Giamarellos-Bourboulis, E. J. et al. Complex immune dysregulation in COVID-19 patients with severe respiratory failure. Cell Host Microbe 27, 992–1000 (2020). [PMID: 32320677]
  48. Mazzoni, A. et al. Impaired immune cell cytotoxicity in severe COVID-19 is IL-6 dependent. J. Clin. Investig. 130, 4694–4703 (2020). [PMID: 32463803]
  49. Morandi, F., Airoldi, I. & Pistoia, V. IL-27 driven upregulation of surface HLA-E expression on monocytes inhibits IFN-γ release by autologous NK cells. J. Immunol. Res. 2014, 938561 (2014). [PMID: 24741633]
  50. Pereira, B. I. et al. Senescent cells evade immune clearance via HLA-E-mediated NK and CD8+T cell inhibition. Nat. Commun. 10, 2387 (2019). [PMID: 31160572]
  51. Chen, Z. & John Wherry, E. T cell responses in patients with COVID-19. Nat. Rev. Immunol. 20, 529–536 (2020). [PMID: 32728222]
  52. Cao, X. COVID-19: immunopathology and its implications for therapy. Nat. Rev. Immunol. 20, 269–270 (2020). [PMID: 32273594]
  53. Channappanavar, R., Fett, C., Zhao, J., Meyerholz, D. K. & Perlman, S. Virus-specific memory CD8 T cells provide substantial protection from lethal severe acute respiratory syndrome coronavirus infection. J. Virol. 88, 11034–11044 (2014). [PMID: 25056892]
  54. World Health Organization. Clinical Management of COVID-19: Interim Guidance, 27 May 2020 (World Health Organization, 2020).
  55. Poran, A. et al. Sequence-based prediction of SARS-CoV-2 vaccine targets using a mass spectrometry-based bioinformatics predictor identifies immunogenic T cell epitopes. Genome Med. 13, 70 (2020). [DOI: 10.1186/s13073-020-00767-w]
  56. Campbell, K. M., Steiner, G., Wells, D. K., Ribas, A. & Kalbasi, A. Prediction of SARS-CoV-2 epitopes across 9360 HLA class I alleles. Preprint at bioRxiv http://biorxiv.org/lookup/doi/10.1101/2020.03.30.016931 (2020).
  57. Prachar, M. et al. Identification and validation of 174 COVID-19 vaccine candidate epitopes reveals low performance of common epitope prediction tools. Sci. Rep. 10, 20465 (2020). [PMID: 33235258]
  58. Garboczi, D. N., Hung, D. T. & Wiley, D. C. HLA-A2-peptide complexes: refolding and crystallization of molecules expressed in Escherichia coli and complexed with single antigenic peptides. Proc. Natl Acad. Sci. USA 89, 3429–3433 (1992). [DOI: 10.1073/pnas.89.8.3429]
  59. Toebes, M. et al. Design and use of conditional MHC class I ligands. Nat. Med. 12, 246–251 (2006). [PMID: 16462803]
  60. Rodenko, B. et al. Generation of peptide-MHC class I complexes through UV-mediated ligand exchange. Nat. Protoc. 1, 1120–1132 (2006). [PMID: 17406393]
  61. Hadrup, S. R. et al. Parallel detection of antigen-specific T-cell responses by multidimensional encoding of MHC multimers. Nat. Methods 6, 520–526 (2009). [PMID: 19543285]
  62. Wolf, F. A., Angerer, P. & Theis, F. J. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 19, 15 (2018). [PMID: 29409532]
  63. Van Rossum, G. & Drake F. L. Python 3 Reference Manual (CreateSpace, 2009).
  64. McKinney, W. Data structures for statistical computing in Python. In Proc. 9th Python in Science Conference 56–61 (SCIPY, 2010).
  65. Oliphant, T. E. A Guide to NumPy (Trelgol Publishing USA, 2006).
  66. Waskom, M. et al. Mwaskom/Seaborn: V0.8.1 (September 2017). Zenodo https://doi.org/10.5281/zenodo.883859 (2017).
  67. Hunter, J. D. Matplotlib: a 2D graphics environment. Comput. Sci. Eng. 9, 90–95 (2007). [DOI: 10.1109/MCSE.2007.55]
  68. Sturm, G. et al. Scirpy: a Scanpy extension for analyzing single-cell T-cell receptor-sequencing data. Bioinformatics 36, 4817–4818 (2020). [PMID: 32614448]

MeSH Term

Adult
Aged
Aged, 80 and over
Alleles
CD8-Positive T-Lymphocytes
COVID-19
Epitopes, T-Lymphocyte
Female
Histocompatibility Antigens Class I
Humans
Immunodominant Epitopes
Immunologic Memory
Lymphocyte Activation
Male
Middle Aged
Polyproteins
SARS-CoV-2
Viral Proteins

Chemicals

Epitopes, T-Lymphocyte
Histocompatibility Antigens Class I
Immunodominant Epitopes
ORF1ab polyprotein, SARS-CoV-2
Polyproteins
Viral Proteins
Journal Article Research Support, Non-U.S. Gov't

Word Cloud

Similar Articles

Cited By