Cited by 529SARS-CoV-2 and COVID-19 Researchvaccines and immunoinformatics approachesCOVID-19 Clinical Research Studies

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

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Abstract

Infection- or vaccination-induced SARS-CoV-2 S–specific CD4 + T cells are indifferent to the S mutations of variants of concern.

Overview

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Written from the paper’s full text.

TL;DR

In a prospective cohort of 121 BNT162b2-vaccinated health care workers, prior COVID-19 led to rapid recall after one dose, while COVID-19–naive donors required two doses for comparable humoral responses. B.1.351 partially escaped neutralizing and Fc-mediated antibody responses, but CD4+ T cell responses to WT, B.1.1.7, and B.1.351 S proteins were comparable.

Key findings

  • Among 121 HCWs (23 COVID-19–recovered, 98 naive), one vaccine dose boosted binding antibodies in all recovered donors; in naive donors, 92.5% had detectable anti-RBD Ig after one dose but only 53.2% had OD ratio >10, rising after dose two to all detectable and 93.3% with ratio >10. S1 IgG by MIA rose from geometric mean 252.6 ± 49.55 to 2088.5 ± 287.5 BAU/ml in naive donors after the second dose (P < 0.0001).
  • Neutralizing antibodies against WT were detected in all 13 recovered donors before vaccination; one dose boosted PRNT50 to a geometric mean plateau of 1:1874. Naive donors reached a lower peak after two doses (geometric mean titer 1:189, P < 0.0001 vs recovered). Against B.1.351, titers were consistently lower: 2.7-fold and 3.3-fold decreases post-vaccinations 1 and 2 in recovered donors, and a 3.1-fold decrease after dose two in naive donors; B.1.1.7 titers were higher (2.5-fold and 2.2-fold increases in recovered donors).
  • S-specific ADCC-mediating antibodies were induced by infection and vaccination, with comparable activity against WT and B.1.1.7 S, but significantly reduced activity against B.1.351 S at almost all time points in both naive and recovered donors.
  • CD4+ T cell responses did not differ between WT S and B.1.1.7 S or WT S and B.1.351 S. In naive donors, 5 of 7 were CD4+ T cell responders after one or two vaccinations; in recovered donors, 8 of 12 responded before vaccination and 10 of 12 after one or two vaccinations. CD8+ S-specific responses were difficult to detect and were not used to draw conclusions on VOC cross-reactivity.

Methods

  • Prospective cohort of 121 symptomatic HCWs in the Netherlands enrolled from April 2020; 98 classified COVID-19–naive and 23 COVID-19–recovered by RT-PCR and serology. All received two BNT162b2 mRNA doses 21 days apart. Binding antibody assays were performed on all 121; in-depth humoral analyses on 25 (13 recovered, 12 naive); T cell analyses on 20 (13 recovered, 7 naive).
  • Humoral assays included Wantai RBD total Ig ELISA, Luminex S1 IgG MIA, in-house N/S ELISA, and PRNT50 using infectious WT SARS-CoV-2 (D614G), B.1.1.7, and B.1.351. ADCC was measured by NK92.05-CD16 degranulation (CD107a) against WT N, WT S, B.1.1.7 S, and B.1.351 S.
  • T cell responses were measured by AIM flow cytometry (CD69/CD137 in CD4+ and CD8+ subsets) after stimulation with overlapping WT S peptide pools or peptide pools covering mutated regions of B.1.1.7 and B.1.351, with IFN-γ ELISA in a subset. Statistical analyses used GraphPad Prism 9.0.2.

Limitations

  • The paper states the study population was selected HCWs, relatively young, predominantly female, and with mild COVID-19 if previously infected; it was underpowered to compare age groups or comorbidities.
  • The paper states in-depth T cell profiling was limited to 20 donors, focused only on S-specific T cells, and could not further address CD8+ T cell responses to VOCs because of low SARS-CoV-2–specific CD8+ T cell frequency; peptide pools of 15-mers may have limited sensitivity, and some pre-exposure S-specific T cells were probably cross-reactive with seasonal human coronaviruses.
  • The paper states it did not analyze the P.1 VOC, and future studies are needed to assess whether neutralizing antibody differences correlate with breakthrough infection risk and whether ADCC should be measured with infectious virus and primary cells. Evident from the text: the study reports immune responses, not clinical protection or breakthrough infection outcomes.

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Integrity signals

Registry

Crossref · 10.1126/sciimmunol.abj1750

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Figures

Fig. 1. HCW study design. N = 121 HCWs were enrolled in a prospective SARS-CoV-2 infection and vaccination study. Upon symptomatic presentation to occupational health services, a paired nasopharyngeal swab and EDTA blood sample was obtained (T0). A second EDTA blood sample was obtained 3 weeks after diagnostic RT-PCR (T3). On the basis of the diagnostic RT-PCR result at T0 and serology result at T3, 98 COVID-19–naive (yellow) and 23 COVID-19–recovered (blue) HCWs were enrolled in the vaccination study on average 50 days after inclusion. N = 13 COVID-19–recovered and N = 12 COVID-19–naive participants were randomly selected for in-depth analysis. Blood samples were collected after the first (Vx13) and second (Vx23) vaccination, processed, and subsequently used for downstream serological and cellular assays.
Fig. 1. HCW study design. N = 121 HCWs were enrolled in a prospective SARS-CoV-2 infection and vaccination study. Upon symptomatic presentation to occupational health services, a paired nasopharyngeal swab and EDTA blood sample was obtained (T0). A second EDTA blood sample was obtained 3 weeks after diagnostic RT-PCR (T3). On the basis of the diagnostic RT-PCR result at T0 and serology result at T3, 98 COVID-19–naive (yellow) and 23 COVID-19–recovered (blue) HCWs were enrolled in the vaccination study on average 50 days after inclusion. N = 13 COVID-19–recovered and N = 12 COVID-19–naive participants were randomly selected for in-depth analysis. Blood samples were collected after the first (Vx13) and second (Vx23) vaccination, processed, and subsequently used for downstream serological and cellular assays.CC BY · PubMed Central
Fig. 2. Detection of SARS-CoV-2–specific humoral responses. Total Ig levels were measured in COVID-19–naive (yellow) and –recovered (blue) donors at the acute, convalescent, post-vaccination 1, and post-vaccination 2 stage (T0, T3, Vx13, and Vx23) by an (A) ELISA against nucleocapsid (N) and (B) RBD. (C) Quantitative IgG against S1 was measured by a Luminex bead assay. (D) Antibody binding to WT SARS-CoV-2 and VOC B.1.1.7 and B.1.351 was determined by end point titration in ELISA. Virus neutralization was measured by PRNT50 against (E) WT SARS-CoV-2 (D614G) and (F) VOC. Analyses in (B) and (C) were performed on 121 participants, and in-depth analyses were performed in (A), (D), (E), and (F) on 25 participants. Time points in (A), (B), and (C) were compared by performing a nonparametric repeated measures Friedman test. End point titers between VOC in (D) were compared by RM one-way ANOVA or Friedman test. PRNT50 titers in (D) and (E) were compared by RM one-way ANOVA. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Symbol shapes indicate individual donors and are consistent throughout the figures. Lines in (A) and (B) show the means; lines in (C), (D), (E), and (F) show geometric means. Dotted lines represent cutoff values for positivity [3× background OD450 in (A), OD450 ratio = 1 in (B), and 10.08 BAU/ml in (C)]. NT: not tested.
Fig. 2. Detection of SARS-CoV-2–specific humoral responses. Total Ig levels were measured in COVID-19–naive (yellow) and –recovered (blue) donors at the acute, convalescent, post-vaccination 1, and post-vaccination 2 stage (T0, T3, Vx13, and Vx23) by an (A) ELISA against nucleocapsid (N) and (B) RBD. (C) Quantitative IgG against S1 was measured by a Luminex bead assay. (D) Antibody binding to WT SARS-CoV-2 and VOC B.1.1.7 and B.1.351 was determined by end point titration in ELISA. Virus neutralization was measured by PRNT50 against (E) WT SARS-CoV-2 (D614G) and (F) VOC. Analyses in (B) and (C) were performed on 121 participants, and in-depth analyses were performed in (A), (D), (E), and (F) on 25 participants. Time points in (A), (B), and (C) were compared by performing a nonparametric repeated measures Friedman test. End point titers between VOC in (D) were compared by RM one-way ANOVA or Friedman test. PRNT50 titers in (D) and (E) were compared by RM one-way ANOVA. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Symbol shapes indicate individual donors and are consistent throughout the figures. Lines in (A) and (B) show the means; lines in (C), (D), (E), and (F) show geometric means. Dotted lines represent cutoff values for positivity [3× background OD450 in (A), OD450 ratio = 1 in (B), and 10.08 BAU/ml in (C)]. NT: not tested.CC BY · PubMed Central
Fig. 3. Detection of ADCC-mediating antibodies by measuring NK92.05 degranulation. (A) Gating strategy for detection of degranulating NK cells: (i) NK92.05-CD16 cells are selected on the basis of size and granularity, (ii) exclusion of doublets, and (iii) selection of LIVE and CD56+ cells. Degranulation is measured as percentage CD107a+ cells within the NK fraction; PBS coating is included as background control. (B and C) ADCC-mediating antibodies were detected in COVID-19–naive (yellow) and –recovered (blue) donors at the acute, convalescent, post-vaccination 1, and post-vaccination 2 stage (T0, T3, Vx13, and Vx23) against the WT N (B) and S (C) protein. (D) ADCC-mediating antibody reactivity with WT SARS-CoV-2 and VOC B.1.1.7 and B.1.351. These analyses were performed on 25 participants. Time points in (B) and (C) were compared by performing a nonparametric repeated measures Friedman test. Differences between variants were assessed by mixed-effect models. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001. Symbol shapes indicate individual donors and are consistent throughout the figures. Lines indicate mean responses.
Fig. 3. Detection of ADCC-mediating antibodies by measuring NK92.05 degranulation. (A) Gating strategy for detection of degranulating NK cells: (i) NK92.05-CD16 cells are selected on the basis of size and granularity, (ii) exclusion of doublets, and (iii) selection of LIVE and CD56+ cells. Degranulation is measured as percentage CD107a+ cells within the NK fraction; PBS coating is included as background control. (B and C) ADCC-mediating antibodies were detected in COVID-19–naive (yellow) and –recovered (blue) donors at the acute, convalescent, post-vaccination 1, and post-vaccination 2 stage (T0, T3, Vx13, and Vx23) against the WT N (B) and S (C) protein. (D) ADCC-mediating antibody reactivity with WT SARS-CoV-2 and VOC B.1.1.7 and B.1.351. These analyses were performed on 25 participants. Time points in (B) and (C) were compared by performing a nonparametric repeated measures Friedman test. Differences between variants were assessed by mixed-effect models. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001. Symbol shapes indicate individual donors and are consistent throughout the figures. Lines indicate mean responses.CC BY · PubMed Central
Fig. 4. Detection of S-specific T cells by measuring up-regulation of AIM. (A) Gating strategy for virus-specific T cells that up-regulate AIM: (i) Lymphocytes are selected on the basis of size and granularity, (ii) exclusion of doublets, (iii) selection of LIVE and CD3+ cells, and (iv) division into CD4+ and CD8+ T cells. Activation is measured as percentage CD69+/CD137+ double-positive cells within the CD4 or CD8 fraction; DMSO stimulation is included as background control. (B to D) Antigen-specific activation of CD4+ and CD8+ T cells in COVID-19–naive (yellow) and COVID-19–recovered (blue) donors at the acute, convalescent, post-vaccination 1, and post-vaccination 2 stage (T0, T3, Vx13, and Vx23) by overlapping peptide pools covering the full WT S protein. Activation of SARS-CoV-2–specific CD4+ T cells is shown as percentage of AIM+ cells within the CD4+ subset after (B) subtraction of the DMSO background or (C) as an SI by dividing specific activation over background activation. (D) Activation of SARS-CoV-2–specific CD8+ T cells is shown as SI. An SI of 2 or higher is considered a positive T cell response. (E and F) Antigen-specific activation of CD4+ T cells by peptide pools exclusively covering mutational regions in VOC B.1.1.7 and B.1.351, compared against homologous WT peptide pools. Antigen-specific T cell responses are shown as SI. These analyses were performed in 20 participants. Time points in (B), (C), and (D) were compared by performing a Kruskall-Wallis test. Differences between variants were compared by performing Wilcoxon test. *P < 0.05 and **P < 0.01. Symbol shapes indicate individual donors and are consistent throughout the figures. Lines indicate mean (B) or geometric mean (C to F) responses. Low cell count samples (<10,000 or <5000 events within CD4+ or CD8+ gate, respectively) were excluded.
Fig. 4. Detection of S-specific T cells by measuring up-regulation of AIM. (A) Gating strategy for virus-specific T cells that up-regulate AIM: (i) Lymphocytes are selected on the basis of size and granularity, (ii) exclusion of doublets, (iii) selection of LIVE and CD3+ cells, and (iv) division into CD4+ and CD8+ T cells. Activation is measured as percentage CD69+/CD137+ double-positive cells within the CD4 or CD8 fraction; DMSO stimulation is included as background control. (B to D) Antigen-specific activation of CD4+ and CD8+ T cells in COVID-19–naive (yellow) and COVID-19–recovered (blue) donors at the acute, convalescent, post-vaccination 1, and post-vaccination 2 stage (T0, T3, Vx13, and Vx23) by overlapping peptide pools covering the full WT S protein. Activation of SARS-CoV-2–specific CD4+ T cells is shown as percentage of AIM+ cells within the CD4+ subset after (B) subtraction of the DMSO background or (C) as an SI by dividing specific activation over background activation. (D) Activation of SARS-CoV-2–specific CD8+ T cells is shown as SI. An SI of 2 or higher is considered a positive T cell response. (E and F) Antigen-specific activation of CD4+ T cells by peptide pools exclusively covering mutational regions in VOC B.1.1.7 and B.1.351, compared against homologous WT peptide pools. Antigen-specific T cell responses are shown as SI. These analyses were performed in 20 participants. Time points in (B), (C), and (D) were compared by performing a Kruskall-Wallis test. Differences between variants were compared by performing Wilcoxon test. *P < 0.05 and **P < 0.01. Symbol shapes indicate individual donors and are consistent throughout the figures. Lines indicate mean (B) or geometric mean (C to F) responses. Low cell count samples (<10,000 or <5000 events within CD4+ or CD8+ gate, respectively) were excluded.CC BY · PubMed Central

Verification

Claims the paper makes

55 Own result · 18 Not checked yet · 12 Own method · 12 Own interpretation · 2 No basis given · 1 Partly supported · accuracy not yet measured

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56 of 56
  • The paper relies on this without support.

    Little is known about T cell cross-reactivity with SARS-CoV-2 variants of concern.

    “Although several studies have demonstrated that some VOCs may be capable of evading infection or vaccination-induced neutralizing antibodies, little is known about T cell cross-reactivity with VOCs.”
  • The paper relies on this without support.

    The B.1.1.7 and B.1.351 variants both contain the N501Y mutation.

    “The B.1.1.7 and B.1.351 variants both contain the signature mutation N501Y”
  • The paper relies on this without support.

    The N501Y mutation is associated with increased affinity for the ACE2 receptor.

    “associated with increased affinity for the ACE2 (angiotensin converting enzyme 2) receptor.”
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Citations

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  1. N. Zucman, F. Uhel, D. Descamps, D. Roux, J. D. Ricard, Severe reinfection with South African SARS-CoV-2 variant 501Y.V2: A case report. Clin. Infect. Dis. 2021, ciab014 (2021).
  2. X. Xie, J. Zou, C. R. Fontes-Garfias, H. Xia, K. A. Swanson, M. Cutler, D. Cooper, V. D. Menachery, S. Weaver, P. R. Dormitzer, P. Y. Shi, Neutralization of N501Y mutant SARS-CoV-2 by BNT162b2 vaccine-elicited sera. bioRxiv 10.1101/2021.01.07.425740 (2021). · DOI · Paper page
  3. M. McCallum, J. Bassi, A. Marco, A. Chen, A. C. Walls, J. D. Iulio, M. A. Tortorici, M. J. Navarro, C. Silacci-Fregni, C. Saliba, M. Agostini, D. Pinto, K. Culap, S. Bianchi, S. Jaconi, E. Cameroni, J. E. Bowen, S. W. Tilles, M. S. Pizzuto, S. B. Guastalla, G. Bona, A. F. Pellanda, C. Garzoni, W. C. Van Voorhis, L. E. Rosen, G. Snell, A. Telenti, H. W. Virgin, L. Piccoli, D. Corti, D. Veesler, SARS-CoV-2 immune evasion by variant B.1.427/B.1.429. bioRxiv 10.1101/2021.03.31.437925 (2021). · DOI

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Metadata

Authors
Geers, D., Shamier, M. C., Bogers, S., den Hartog, G., Gommers, L., Nieuwkoop, N. N., Schmitz, K. S., Rijsbergen, L. C., van Osch, J. A. T., Dijkhuizen, E., Smits, G., Comvalius, A., van Mourik, D., Caniels, T. G., van Gils, M. J., Sanders, R. W., Oude Munnink, B. B., Molenkamp, R., de Jager, H. J., Haagmans, B. L., de Swart, R. L., Koopmans, M. P. G., van Binnendijk, R. S., de Vries, R. D., & GeurtsvanKessel, C. H.
Affiliations
  • Erasmus MC (NL)
  • National Institute for Public Health and the Environment (NL)
  • Amsterdam University Medical Centers (NL)
  • Cornell University (US)
  • Department of Viroscience, Erasmus MC, Rotterdam, Netherlands.
  • Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment, Bilthoven, Netherlands.
Corresponding author
  • Geers, Daryl
  • Shamier, Marc C.
  • de Vries, Rory D.
  • GeurtsvanKessel, Corine H.
Venue
Science Immunology
Published
2021-05-28
Volume
6
Issue
59
ISSN
2470-9468 (ISSN-L)
OpenAlex
W3165367963
Cited by
529
References
83
Citations by year
2026: 15 · 2025: 40 · 2024: 75 · 2023: 94 · 2022: 204 · 2021: 101
FWCI
37.69
Type
journal article
Language
en
Open access
Locations
  • Science Immunology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, cc-by)
  • Pure Amsterdam UMC (submittedVersion, cc-by)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, cc-by)
  • Rivm Repository (Netherlands National Institute for Public Health and the Environment) (submittedVersion)
  • Rivm (National Institute for Public Health and the Environment) (submittedVersion)
Funders
  • Bill and Melinda Gates Foundation (INV-002022)
  • Netherlands Organization for Scientific Research (VICI)
  • ZonMW (10150062010005)
  • Amsterdam UMC (AMC Fellowship)
  • Top Sector Life Sciences Health; Health~Holland (EMCLHS20017)
  • European Union’s Horizon 2020 RECoVER (101003589)
Topics
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
Keywords
SARS-CoV-2, variants of concern, spike protein mutations, CD4+ T cells, humoral immunity, T cell response, vaccine recipients, immune evasion, SARS-CoV-2 spike protein
MeSH terms
COVID-19, SARS-CoV-2, COVID-19 Vaccines, Antibodies, Viral, Cell Line, Cross Reactions, Humans, Immunologic Memory, Vaccination, CD4-Positive T-Lymphocytes, CD8-Positive T-Lymphocytes, Spike Glycoprotein, Coronavirus

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