Single‐cell analyses reveal SARS‐CoV‐2 interference with intrinsic immune response in the human gut

  1. Sergio Triana
  2. Camila Metz‐Zumaran
  3. Carlos Ramirez
  4. Carmon Kee
  5. Patricio Doldan
  6. Mohammed Shahraz
  7. Daniel Schraivogel
  8. Andreas R Gschwind
  9. Ashwini K Sharma
  10. Lars M Steinmetz
  11. Carl Herrmann
  12. Theodore Alexandrov
  13. Steeve Boulant
  14. Megan L Stanifer

Reviewed by

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

No abstract available

Article activity feed

  1. Version published to 10.15252/msb.202110232
  2. ScreenIT

    SciScore for 10.1101/2020.10.21.348854: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: This study was carried out in accordance with the recommendations of the University Hospital Heidelberg with informed written consent from all subjects in accordance with the Declaration of Helsinki.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Mouse monoclonal antibody against SARS-CoV NP (Sino biologicals MM05) and mouse monoclonal against J2 (scions) were diluted in phosphate-buffered saline (PBS) at 1/1000 dilution and incubated for 1h at RT.
    SARS-CoV NP
    suggested: (Sino Biological Cat# 40143-MM05, RRID:AB_2827977)
    J2
    suggested: (US Biological Cat# U1000-87M, RRID:AB_2210756)
    Secondary antibody (anti-mouse CW800) and DNA dye Draq5 (Abcam) were diluted 1/10,000 in blocking buffer and incubated for 1 h at RT.
    anti-mouse CW800
    suggested: None
    Draq5
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Viral infections: Media was removed from cells and 106 pfu of SARS-CoV-2 (as determined in Vero cells) was added to cells for 1 hour at 37°C.
    Vero
    suggested: None
    In-cell western: 20,000 Vero E6 cells were seeded per well into a 96-well dish 24 hours prior to infection.
    Vero E6
    suggested: None
    Software and Algorithms
    SentencesResources
    Targeted single-cell RNA-sequencing: For targeted scRNAseq, outer and inner primers for targeted amplification were designed using an R package for primer design described in [24] and available through Bioconductor (http://bioconductor.org/packages/release/bioc/html/TAPseq.html).
    Bioconductor
    suggested: (Bioconductor, RRID:SCR_006442)
    In summary, following demultiplexing by sample, sequencing data were processed following the workflow provided by Drop-seq tools (v. 1.13, http://mccarrolllab.org/dropseq/) with STAR (v.
    STAR
    suggested: (STAR, RRID:SCR_015899)
    A custom script (Python v. 3.6.6) was used to filter for chimeric reads with a transcripts-per-transcript (TPT) cutoff of 0.25, and UMI observations were converted to transcript counts.
    Python
    suggested: (IPython, RRID:SCR_001658)
    Differential expression tests were performed using MAST [47].
    MAST
    suggested: (MAST, RRID:SCR_016340)
    Subsequently, genes whose mRNAs were found to be differentially expressed were subjected to a gene set overrepresentation analysis using the EnrichR package in R.
    EnrichR
    suggested: (Enrichr, RRID:SCR_001575)
    Furthermore signalling pathways enrichment was calculated using PROGENy.
    PROGENy
    suggested: (PROGENY, RRID:SCR_006647)
    Further brightness and contrast adjustments were performed using Fiji.
    Fiji
    suggested: (Fiji, RRID:SCR_002285)
    To measure the single cell fluorescent intensity for the ACE2, ISG15 and SARS-CoV-2 probes, a pipeline using CellProfiler 3.1.9 was developed.
    CellProfiler
    suggested: None
    Finally, the SARS-CoV2 mean intensity signal was plotted against the normalized ACE mean intensity signal or the ISG15 mean intensity signal using GraphPad Prism Version 6.0
    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 did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on page 20. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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 10.1101/2020.10.21.348854 on bioRxiv