Immunodominant B cell epitope in a hotspot mutation site and mechanism of immune escape for SARS-CoV-2

  1. Jamille Ramos Oliveira
  2. Rafael Rahal G. Machado
  3. Helen Andrade Arcuri
  4. Jhosiene Yukari Magawa
  5. Isabela Pazotti Daher
  6. Alysson Henrique Urbanski
  7. Gabriela Justamante Händel Schmitz
  8. Roberto Carlos Vieira Silva
  9. Edison Luiz Durigon
  10. Silvia Beatriz Boscardin
  11. Daniela Santoro Rosa
  12. Deborah Schechtman
  13. Helder I Nakaya
  14. Edecio Cunha-Neto
  15. Gabriele Gadermaier
  16. Verônica Coelho
  17. Keity Souza Santos
  18. Jorge Kalil

Reviewed by

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

Recent SARS-CoV-2 variants pose important concerns due to their higher transmissibility ( 1 ) and escape ( 2 ) from previous infections or vaccine-induced neutralizing antibodies (nAb). The receptor binding domain (RBD) of the Spike protein is a major nAb target ( 3 ), but data on its B cell epitopes are still lacking. Using a peptide microarray, we identified an immunodominant epitope (S 415-429 ) recognized by 68% of sera from 71 convalescent Brazilians infected with the ancestral variant. In contrast with previous studies, we have identified a linear IgG and IgA antibody binding epitope within the RBD. IgG and IgA antibody levels for this epitope positively correlated with nAb titers, suggesting a potential target of antibody neutralizing activity. Interestingly, this immunodominant RBD region harbors the mutation hotspot site K417 present in P.1 (K417T) and B.1.351 (K417N) variants. In silico simulation analyses indicate impaired RBD binding to nAb in both variants and that a glycosylation in the B.1.351 417N could further hinder antibody binding as compared to the K417T mutation in P.1. This is in line with published data showing that nAb from either convalescents or anti-CoV-2 vaccinees are less effective towards B.1.351 than for P.1. Our data support the occurrence of immune pressure and selection involving this immunodominant epitope that may have critically contributed to the recent COVID-19 marked rise in Brazil and South Africa, and pinpoint a potential additional immune escape mechanism for SARS-CoV-2.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.03.11.21253399: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power AnalysisThe statistical power (1-β) of 50 versus 21 individuals for P44 was calculated.
    Sex as a biological variableStudy population: Seventy-one COVID-19 convalescent individuals (52% Female, 48% Male, median age 42 years old) with RT-PCR diagnostic confirmation from March to April 2020 were included in this study.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    To ensure that the secondary antibodies do not interact with the antigen-derived peptides printed on the arrays, one copy of the array was pre-stained with goat anti-human IgG (H+L) DyLight680 (Invitrogen, USA) secondary antibody or goat anti-human IgA (chain alpha) DyLight800 (Rockland Immunochemicals Inc., USA) diluted 1:2000 in staining buffer (PBS with 10% blocking buffer) on an orbital shaker at room temperature for 45 min.
    anti-human IgG
    suggested: (Rockland Cat# 609-145-130, RRID:AB_2614820)
    anti-human IgA
    suggested: (Rockland Cat# 609-145-130, RRID:AB_2614820)
    After three washing steps of 1 min each with 200 µL of the standard buffer, the microarrays were incubated with previously titrated secondary antibodies, anti-IgG and anti-IgA at a dilution of 1:2000, on an orbital shaker at room temperature for 45 minutes.
    anti-IgG
    suggested: None
    anti-IgA
    suggested: (LSBio (LifeSpan Cat# LS-C68423-2000, RRID:AB_10634906)
    Structural analyses: Structural representations of RBD interacting with ACE2 (pdb: 6M0J) and the neutralizing antibody REGN10933 (pdb: 6XDG) were generated using UCSF Chimera (https://www.cgl.ucsf.edu/chimera/).
    ACE2
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Therefore, we used 96-well plates containing 5 ×104 cells/mL of Vero cells (ATCC CCL-81).
    Vero
    suggested: None
    Software and Algorithms
    SentencesResources
    The heatmap was generated using the pheatmap R package (v1.0.12).
    pheatmap
    suggested: (pheatmap, RRID:SCR_016418)
    The software PyMol (PyMOL Molecular Graphics System, Version 2.0 Schrödinger, LLC) was used for visualization, mutagenesis and computation of binding regions between molecules.
    PyMOL
    suggested: (PyMOL, RRID:SCR_000305)
    Statistical analyses: GraphPad Prism 9.0.1 was used for statistical analyses of individual peptide reactivity comparing sera of subjects with high and low neutralization capacity (Mann Whitney) and Spearman for correlation analysis, p values <0.05 were considered statistically significant.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.03.11.21253399 on medRxiv