Relative infectivity of the SARS-CoV-2 Omicron variant in human alveolar cells

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Abstract

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  1. SciScore for 10.1101/2022.04.13.486321: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Human tissues and alveolar organoid establishment: Human normal lung tissues were acquired from lung cancer patients with lobectomy surgery at SNUH with informed consent (IRB approval no. C-1809-137-975).
    Sex as a biological variablenot detected.
    RandomizationStatistical Analysis: To calculate the Omicron’s dominancy of the observed value against the expected value, for single and total infected cells, we adopted the proportion test with a random expectation of 0.25.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Virus particle preparation for the competition assay: For the virus stock preparation, Vero cells were infected with a 0.01 MOI and grown in DMEM with 2% FBS and 1% P/S for 48 hours at 37 00B0;C with 5% CO2 as previously described (Youk et al., 2020).
    Vero
    suggested: None
    Software and Algorithms
    SentencesResources
    Then, the adapter-removed fastq files were aligned to the SARS-CoV-2 reference genome sequence, wuhCor1.fa (NC_045512v2) with BWA-MEM (Heng Li. arXiv:1303.3997).
    BWA-MEM
    suggested: (Sniffles, RRID:SCR_017619)
    Any human contamination reads were removed by Kraken (Wood et al., 2019).
    Kraken
    suggested: (Kraken, RRID:SCR_005484)
    Then, the mutation sites were called using VarScan (Koboldt et al., 2012) and GATK HaplotypeCaller (Poplin et al., 2018).
    VarScan
    suggested: (VARSCAN, RRID:SCR_006849)
    GATK
    suggested: (GATK, RRID:SCR_001876)
    Data processing of the full-length single-cell transcriptome sequencings: From the pooled fastq file, we counted reads and UMIs of gene expression using zUMIs (Parekh1 et al., 2018).
    zUMIs
    suggested: (zUMIs, RRID:SCR_016139)
    Virus transcripts average depth: The read-depth of deduplicated bam files was analyzed by SAMtools (Li et al., 2009) for each cell and averaged.
    SAMtools
    suggested: (SAMTOOLS, RRID:SCR_002105)

    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:
    The limitation of our method is the lack of immune cells, which have a role in viral progression in vivo. Furthermore, our assay is able to decompose multiple viruses infecting a cell due to full-length single-cell RNA sequencing. To be specific, 10X Chromium cannot capture most of the viral genomic mutations. Technically, the manual picking of the infected single-cells is the rate limiting step in our assay. However, the process can be readily scalable by using a fluorescence-activated cell sorter (Hagemann-Jensen et al., 2021). Although this study mainly focused on the RNA transcripts from the virus, future studies may explore transcriptome changes of human genes at the single-cell resolution. To do so, infected cells should be incubated for a longer time, ideally for at least 24 h, as such a duration is necessary for alveolar cells to reprogram its transcription against viral infection (D. Kim et al., 2020; Youk et al., 2020). To summarize, we demonstrated a new method that can be used to yield the relative infectivity of viral variants systematically and quickly. Our assay suggested that the Omicron variant is 3-5 times more infectious than the other SARS-CoV-2 variants against human alveolar cells. Together with other complementary approaches, our method will help to reveal the functional characteristics of emerging viral variants, especially for comparison among variants, in the future. Supplementary Table 1: A full list of genomic mutations of the Alpha, Delta, Omicron...

    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.