Limited within-host diversity and tight transmission bottlenecks limit SARS-CoV-2 evolution in acutely infected individuals

  1. Katarina Braun
  2. Gage Moreno
  3. Cassia Wagner
  4. Molly A. Accola
  5. William M. Rehrauer
  6. David Baker
  7. Katia Koelle
  8. David H. O’Connor
  9. Trevor Bedford
  10. Thomas C. Friedrich
  11. Louise H. Moncla

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Abstract

The recent emergence of divergent SARS-CoV-2 lineages has raised concerns about the role of selection within individual hosts in propagating novel variants. Of particular concern are variants associated with immune escape and/or enhanced transmissibility. Though growing evidence suggests that novel variants can arise during prolonged infections, most infections are acute. Understanding the extent to which variants emerge and transmit among acutely infected hosts is therefore critical for predicting the pace at which variants resistant to vaccines or conferring increased transmissibility might emerge in the majority of SARS-CoV-2 infections. To characterize how within-host diversity is generated and propagated, we combine extensive laboratory and bioinformatic controls with metrics of within- and between-host diversity to 133 SARS-CoV-2 genomes from acutely infected individuals. We find that within-host diversity during acute infection is low and transmission bottlenecks are narrow, with very few viruses founding most infections. Within-host variants are rarely transmitted, even among individuals within the same household. Accordingly, we also find that within-host variants are rarely detected along phylogenetically linked infections in the broader community. Together, these findings suggest that efficient selection and transmission of novel SARS-CoV-2 variants is unlikely during typical, acute infection.

One Sentence Summary

Patterns of SARS-CoV-2 within hosts suggest efficient selection and transmission of novel variants is unlikely during typical, acute infection.

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  1. ScreenIT

    SciScore for 10.1101/2021.04.30.440988: (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
    Reads were paired and merged using BBMerge (https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/bbmerge-guide/) and mapped to the Wuhan-Hu-1/2019 reference (Genbank accession MN908947.3) using BBMap (https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/bbmap-guide/).
    https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/bbmerge-guide/
    suggested: (Bestus Bioinformaticus Merge, RRID:SCR_016970)
    BBMap
    suggested: (BBmap, RRID:SCR_016965)
    Mapped reads were imported into Geneious (https://www.geneious.com/) for visual inspection.
    Geneious
    suggested: (Geneious, RRID:SCR_010519)
    Variants were called using callvariants.sh (contained within BBMap) and annotated using SnpEff (https://pcingola.github.io/SnpEff/).
    SnpEff
    suggested: (SnpEff, RRID:SCR_005191)
    Briefly, reads were trimmed with Trimmomatic (http://www.usadellab.org/cms/?
    Trimmomatic
    suggested: (Trimmomatic, RRID:SCR_011848)
    Trimmed reads were mapped using Bowtie 2 (http://bowtie-bio.sourceforge.net/bowtie2/index.shtml) (52), and pileups were generated using samtools mpileup (http://www.htslib.org/doc/samtools-mpileup.html).
    samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    We used custom python scripts to filter and clean metadata.
    python
    suggested: (IPython, RRID:SCR_001658)
    Matlab code to replicate the combined bottleneck estimates can be found in the GitHub accompanying this paper (https://github.com/lmoncla/ncov-WI-within-host).
    Matlab
    suggested: (MATLAB, RRID:SCR_001622)

    Results from OddPub: Thank you for sharing your code and 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.

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  2. Version published to 10.1101/2021.04.30.440988 on bioRxiv