Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Sequence Characteristics of Coronavirus Disease 2019 (COVID-19) Persistence and Reinfection

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Abstract

Background

Both severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection and persistent infection have been reported, but sequence characteristics in these scenarios have not been described. We assessed published cases of SARS-CoV-2 reinfection and persistence, characterizing the hallmarks of reinfecting sequences and the rate of viral evolution in persistent infection.

Methods

A systematic review of PubMed was conducted to identify cases of SARS-CoV-2 reinfection and persistence with available sequences. Nucleotide and amino acid changes in the reinfecting sequence were compared with both the initial and contemporaneous community variants. Time-measured phylogenetic reconstruction was performed to compare intrahost viral evolution in persistent SARS-CoV-2 to community-driven evolution.

Results

Twenty reinfection and 9 persistent infection cases were identified. Reports of reinfection cases spanned a broad distribution of ages, baseline health status, reinfection severity, and occurred as early as 1.5 months or >8 months after the initial infection. The reinfecting viral sequences had a median of 17.5 nucleotide changes with enrichment in the ORF8 and N genes. The number of changes did not differ by the severity of reinfection and reinfecting variants were similar to the contemporaneous sequences circulating in the community. Patients with persistent coronavirus disease 2019 (COVID-19) demonstrated more rapid accumulation of sequence changes than seen with community-driven evolution with continued evolution during convalescent plasma or monoclonal antibody treatment.

Conclusions

Reinfecting SARS-CoV-2 viral genomes largely mirror contemporaneous circulating sequences in that geographic region, while persistent COVID-19 has been largely described in immunosuppressed individuals and is associated with accelerated viral evolution.

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  1. SciScore for 10.1101/2021.03.02.21252750: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data search and selection criteria: We conducted a systematic literature review in Pubmed through February 5, 2021 for cases of persistent COVID-19 using the search term “((covid or sars-CoV-2) AND (persistent or persistence or prolonged)) AND (sequence or evolution)”.
    Pubmed
    suggested: (PubMed, RRID:SCR_004846)
    Nucleotide sequence alignment was performed using MAFFT (Multiple Alignment using Fast Fourier Transform) [13].
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Best-fit nucleotide substitution was calculated using model selection followed by maximum likelihood (ML) phylogenetic tree construction using IQ-Tree with 1000-bootstrap replicates [13].
    IQ-Tree
    suggested: (IQ-TREE, RRID:SCR_017254)
    Mutation locations are graphically represented in Circos plots [14].
    Circos
    suggested: (Circos, RRID:SCR_011798)
    Time-measured phylogenetic analysis: The temporal signal of the ML tree was examined in TempEst [15] regressing on root-to-tip divergence, and outliers were inspected in the distribution of residuals.
    TempEst
    suggested: (TempEst, RRID:SCR_017304)
    To ensure a sufficient effective sample size ESS > 200, the convergence of three runs was diagnosed in Tracer v 1.7.1 (http://tree.bio.ed.ac.uk/software/tracer/) for all parameters.
    Tracer
    suggested: (Tracer, RRID:SCR_019121)
    LogCombiner v1.10.4 as part of the BEAST software package was used to combine the multiple runs to generate log and tree files after appropriate removal of the burn-in from each MCMC chain.
    BEAST
    suggested: (BEAST, RRID:SCR_010228)
    The comparison of the evolutionary rates from the combined log file is analyzed and visualized in R v4.0.2 (https://www.r-project.org/).
    https://www.r-project.org/
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)
    Statistical analyses were performed using GraphPad Prism 9 (GraphPad Software, San Diego, CA).
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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: 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.