Drivers of adaptive evolution during chronic SARS-CoV-2 infections

  1. Sheri Harari
  2. Maayan Tahor
  3. Natalie Rutsinsky
  4. Suzy Meijer
  5. Danielle Miller
  6. Oryan Henig
  7. Ora Halutz
  8. Katia Levytskyi
  9. Ronen Ben-Ami
  10. Amos Adler
  11. Yael Paran
  12. Adi Stern

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Abstract

In some immunocompromised patients with chronic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, considerable adaptive evolution occurs. Some substitutions found in chronic infections are lineage-defining mutations in variants of concern (VOCs), which has led to the hypothesis that VOCs emerged from chronic infections. In this study, we searched for drivers of VOC-like emergence by consolidating sequencing results from a set of 27 chronic infections. Most substitutions in this set reflected lineage-defining VOC mutations; however, a subset of mutations associated with successful global transmission was absent from chronic infections. We further tested the ability to associate antibody evasion mutations with patient-specific and virus-specific features and found that viral rebound is strongly correlated with the emergence of antibody evasion. We found evidence for dynamic polymorphic viral populations in most patients, suggesting that a compromised immune system selects for antibody evasion in particular niches in a patient’s body. We suggest that a tradeoff exists between antibody evasion and transmissibility and that extensive monitoring of chronic infections is necessary to further understanding of VOC emergence.

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  1. Version published to 10.1038/s41591-022-01882-4
  2. ScreenIT

    SciScore for 10.1101/2022.02.17.22270829: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: This study was approved by the TASMC Helsinki committee (approval No. 1042-20-TLV), and by the Tel Aviv University IRB (approval number 0004435-1), with an exemption from informed consent.
    Consent: This study was approved by the TASMC Helsinki committee (approval No. 1042-20-TLV), and by the Tel Aviv University IRB (approval number 0004435-1), with an exemption from informed consent.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Logistic regression: Logistic regression was performed twice to test for significant predictors of an antibody-evasion outcome.
    antibody-evasion outcome.
    suggested: None
    Severe B-cell depletion was defined as one of the following conditions: treatment with anti-B cell directed antibodies up to nine months prior to COVID-9 detection, or blood-test measurements of low B-cell markers.
    anti-B
    suggested: None
    Second, at the level of time-point sequenced, we tested whether ABT (convalescent plasma, hyperimmune plasma, or monoclonal antibody/ies) or viral rebound predicted an outcome of an antibody-evasion mutation.
    antibody-evasion mutation.
    suggested: None
    Software and Algorithms
    SentencesResources
    Mapping and variant calling was performed using our AccuNGS pipeline 41.
    AccuNGS
    suggested: None

    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.

    Results from scite Reference Check: We found no unreliable references.

    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.

  3. Version published to 10.1101/2022.02.17.22270829 on medRxiv