Modeling SARS-CoV-2 infection and its individual differences with ACE2-expressing human iPS cells

  1. Emi Sano
  2. Sayaka Deguchi
  3. Ayaka Sakamoto
  4. Natsumi Mimura
  5. Ai Hirabayashi
  6. Yukiko Muramoto
  7. Takeshi Noda
  8. Takuya Yamamoto
  9. Kazuo Takayama

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Abstract

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  1. Version published to 10.1016/j.isci.2021.102428
  2. ScreenIT

    SciScore for 10.1101/2021.02.22.432218: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Human ES cells were used following the Guidelines for Derivation and Utilization of Human Embryonic Stem Cells of the Ministry of Education, Culture, Sports, Science and Technology of Japan, and the study was approved by an independent ethics committee.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    The virus was plaque-purified and propagated in Vero cells and stored at −80°C.
    Vero
    suggested: CLS Cat# 605372/p622_VERO, RRID:CVCL_0059)
    The ACE2- and TMPRSS2-expressing Ad vectors (Ad-ACE2 and Ad-TMPRSS2, respectively) were propagated in HEK293 cells (JCRB9068, JCRB Cell Bank).
    HEK293
    suggested: None
    At day 2 (Vero cells) or day 4 (ACE2-iPS cells) after the infection, the viral RNA copy number in the cell culture supernatant was measured by qPCR.
    ACE2-iPS
    suggested: None
    Dilutions were placed onto the TMPRSS2/Vero cells in triplicate and incubated at 37°C for 96 hr.
    TMPRSS2/Vero
    suggested: None
    Software and Algorithms
    SentencesResources
    Standard curves were prepared using SARS-CoV-2 RNA (105 copies/μL) purchased from Nihon Gene Research Laboratories.
    Nihon Gene Research Laboratories
    suggested: (University of Southern California; Los Angeles; USA, RRID:SCR_008093)
    Adapter sequences and low-quality bases were trimmed from the raw reads by Cutadapt ver 1.14 (Martin, 2011).
    Cutadapt
    suggested: (cutadapt, RRID:SCR_011841)
    The trimmed reads were mapped to the human reference genome sequences (hg38) using STAR ver 2.5.3a (Dobin et al., 2013) with the GENCODE (release 36, GRCh38.p13) (Frankish et al., 2019) gtf file.
    STAR
    suggested: (STAR, RRID:SCR_015899)
    The raw counts for protein-coding genes were calculated using htseq-count ver 0.12.4 (Anders et al., 2015) with the GENCODE gtf file.
    GENCODE
    suggested: (GENCODE, RRID:SCR_014966)
    Gene expression levels were determined as transcripts per million (TPM) with DEseq2 (Love et al., 2014).
    DEseq2
    suggested: (DESeq2, RRID:SCR_015687)
    Raw data concerning this study were submitted under Gene Expression Omnibus (GEO) accession number GSE166990.
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    Statistical analyses were performed using GraphPad Prism8 and 9.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.

  3. Version published to 10.1101/2021.02.22.432218v1 on bioRxiv