Evolution of a globally unique SARS-CoV-2 Spike E484T monoclonal antibody escape mutation in a persistently infected, immunocompromised individual

  1. Peter J Halfmann
  2. Nicholas R Minor
  3. Luis A Haddock III
  4. Robert Maddox
  5. Gage K Moreno
  6. Katarina M Braun
  7. David A Baker
  8. Kasen K Riemersa
  9. Ankur Prasad
  10. Kirsten J Alman
  11. Matthew C Lambert
  12. Kelsey Florek
  13. Allen Bateman
  14. Ryan Westergaard
  15. Nasia Safdar
  16. David R Andes
  17. Yoshihiro Kawaoka
  18. Madiha Fida
  19. Joseph D Yao
  20. Thomas C Friedrich
  21. David H O’Connor

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Abstract

Prolonged infections in immunocompromised individuals may be a source for novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants, particularly when both the immune system and antiviral therapy fail to clear the infection and enable within-host evolution. Here we describe a 486-day case of SARS-CoV-2 infection in an immunocompromised individual. Following monotherapy with the monoclonal antibody Bamlanivimab, the individual’s virus acquired resistance, likely via the earliest known occurrence of Spike amino acid variant E484T. Recently, E484T has arisen again as a derivative of E484A in the Omicron Variant of Concern, supporting the hypothesis that prolonged infections can give rise to novel variants long before they become prevalent in the human population.

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  1. Version published to 10.1093/ve/veac104
  2. Version published to 10.1101/2022.04.11.22272784v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2022.04.11.22272784: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Ethics statement: Collection and testing of biological specimens and protected health information were performed in concordance with the University of Wisconsin IRB # 2021-0076 following informed consent from the patient.
    Sex as a biological variablenot detected.
    RandomizationRoot-to-tip analysis: To examine the rate at which the patient’s virus accumulated mutations, and compare that rate with SARS-CoV-2 globally, we randomly subsampled approximately 5,000 SARS-CoV-2 sequences 33 from the GISAID global dataset using scripts made available in the Nextstrain command line interface 34.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    The immunocompromised individual’s virus was isolated from the ∼10-months post-diagnosis nasopharyngeal swab sample cultured on Vero E6/TMPRSS2 cells.
    Vero E6/TMPRSS2
    suggested: None
    Software and Algorithms
    SentencesResources
    For those samples being sequenced with ARTIC on an ONT minION (see Supplemental Table 1), we mixed 12 μl of the purified DNA library, 37.5 μl of the ONT Sequencing Buffer II, and 25.5 μl of ONT Loading Solution, and loaded the mixture onto the MinION for sequencing.
    MinION
    suggested: (MinION, RRID:SCR_017985)
    SARS-CoV-2 sequence analysis: Processing raw sequence data for consensus sequence analyses: The majority of analyses described here use consensus sequences, which we assembled for each sample using a workflow customized to run remotely with compute resources from the UW-Madison Center For High Throughput Computing (https://chtc.cs.wisc.edu/), and using the workload manager HTC Condor.
    Condor
    suggested: (Condor, RRID:SCR_017664)
    First, we mapped the reads to MN908947.3 using minimap2’s ‘map-ont’ preset, clipped reads down to MIDNIGHT amplicon pileups using SAMtools, and then used covtobed to produce BED-format tables of regions where read depth-of-coverage was below 20 28–30.
    SAMtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    We then annotated protein effects onto these VCFs using snpEff 32.
    snpEff
    suggested: (SnpEff, RRID:SCR_005191)

    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.

  4. Version published to 10.1101/2022.04.11.22272784v1 on medRxiv