Cross-reactive antibody responses against SARS-CoV-2 and seasonal common cold coronaviruses

  1. Shelley Klompus
  2. Sigal Leviatan
  3. Thomas Vogl
  4. Iris N. Kalka
  5. Anastasia Godneva
  6. Eilat Shinar
  7. Adina Weinberger
  8. Eran Segal

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Abstract

Beyond SARS-CoV-2, six more coronaviruses infect humans (hCoVs), four of which cause only mild symptoms (seasonal/common cold hCoVs) 12 . Previous exposures to seasonal hCoVs may elicit immunological memory that could benefit the course of SARS-CoV-2 infections 3 . While cross-reactive T cells epitopes of SARS-CoV-2 and seasonal hCoVs have been reported in individuals unexposed to SARS-CoV-2 4-6 , potential antibody-based cross-reactivity is incompletely understood.

Here, we have probed for high resolution antibody binding against all hCoVs represented as 1,539 peptides with a phage-displayed 7 antigen library. We detected broad serum antibody responses against peptides of seasonal hCoVs in up to 75% of individuals. Recovered COVID-19 patients exhibited distinct antibody repertoires targeting variable SARS-CoV-2 epitopes, and could be accurately classified from unexposed individuals (AUC=0.96). Up to 50% of recovered patients also mounted antibody responses against unique epitopes of seasonal hCoV-OC43, that were not detectable in unexposed individuals.

These results indicate substantial interindividual variability and antibody cross-reactivity between hCoVs from the direction of SARS-CoV-2 infections towards seasonal hCoVs. Our accurate high throughput assay allows profiling preexisting antibody responses against seasonal hCoVs cost-effectively and could inform on their protective nature against SARS-CoV-2.

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  1. ScreenIT

    SciScore for 10.1101/2020.09.01.20182220: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Research with the COVID-19 serum samples has been approved by the Weizmann Institute of Science’s institutional review board (#1030-4), and by the Tel Aviv Sourasky Medical Center for the samples of unexposed individuals (#0658-12-TLV).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Seropositivity of these samples had been confirmed by MDA with a commercial antibody test (Abbot, SARS-CoV-2 IgG, ref. 6R86-22/6R86-32).
    SARS-CoV-2 IgG
    suggested: None
    6R86-22/6R86-32
    suggested: None
    Experimental Models: Organisms/Strains
    SentencesResources
    . hCoV antigen library design: Reference genomes of the seven hCoVs were downloaded from NCBI directly using amino acid sequences of the translated ORFs with the follow RefSeq accession numbers: SARS-CoV-2 - NC_045512.2, SARS-CoV-1 - NC_004718.3, MERS-CoV - NC_019843.3, hCoV-OC43 - NC_006213.1, hCoV-229E - NC_002645.1, hCoV-HKU1 - NC_006577.2, and hCoV-NL63 - NC_005831.2 For each strain the nonstructural proteins (NSPs) part of the large polyprotein 1ab (polyprotein 1a was discarded if annotated) were separated.
    hCoV-NL63 - NC_005831.2
    suggested: None
    Software and Algorithms
    SentencesResources
    Specifically for SARS-CoV-2, four additional ORFs reported in the literature 1 (but not annotated in RefSeq NC_045512.2) were added.
    RefSeq
    suggested: (RefSeq, RRID:SCR_003496)
    All oligo creation code, and analysis code was written in Python, using the libraries scikit-learn 44, scipy, statsmodels, pandas, numpy and matplotlib.
    Python
    suggested: (IPython, RRID:SCR_001658)
    scipy
    suggested: (SciPy, RRID:SCR_008058)
    matplotlib
    suggested: (MatPlotLib, RRID:SCR_008624)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    From a technical perspective, our study shares general limitations of PhIP-Seq, most notable length constraints of presented peptides (64 aa in this study) by underlying oligo synthesis and lack of eukaryotic post translational modifications such as glycosylation. Opposed to neutralization assays carried out with live viruses and cell cultures 31, our data does not inform on the neutralizing capacity of the observed binding events. While linear epitopes should be adequately covered, discontinuous, conformational epitopes relying on the correct folding of domains could be missed. We did not frequently detect binding to peptides of the RBD (with one adjacent peptide bound in 25% of COVID-19 and 0% of unexposed individuals’ sera, Fig. 2a), although other work and diagnostic tests relying on the full length RBD had reported common antibody responses in COVID-19 patients 14,16,17,21. This discrepancy may be due antibody responses against conformational epitopes in the RBD and/or a lack of S protein glycans 33 in the phage displayed peptides. While current oligo lengths employed in PhIP-Seq may underestimate conformational epitopes, it provides a unique layer of information unobtainable from working with full length antigens or isolated domains: Given the high resolution of the peptide approach, we pinpoint the exact bound regions revealing crucial targets of cross-reactivities. Our hCoV antigen library can be leveraged to study extended cohorts of patients with mild/severe disease...

    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

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  2. Version published to 10.1101/2020.09.01.20182220v2 on medRxiv
  3. Version published to 10.1101/2020.09.01.20182220v1 on medRxiv