Inflammasome activation in infected macrophages drives COVID-19 pathology

  1. Esen Sefik
  2. Rihao Qu
  3. Caroline Junqueira
  4. Eleanna Kaffe
  5. Haris Mirza
  6. Jun Zhao
  7. J. Richard Brewer
  8. Ailin Han
  9. Holly R. Steach
  10. Benjamin Israelow
  11. Holly N. Blackburn
  12. Sofia E. Velazquez
  13. Y. Grace Chen
  14. Stephanie Halene
  15. Akiko Iwasaki
  16. Eric Meffre
  17. Michel Nussenzweig
  18. Judy Lieberman
  19. Craig B. Wilen
  20. Yuval Kluger
  21. Richard A. Flavell

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Abstract

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  1. Version published to 10.1038/s41586-022-04802-1
  2. Version published to 10.1101/2021.09.27.461948v2 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.09.27.461948: (What is this?)

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

    Table 1: Rigor

    EthicsIACUC: All animal experimentations were performed in compliance with Yale Institutional Animal Care and Use Committee protocols.
    Euthanasia Agents: Animals were anaesthetized using isoflurane.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    BlindingA pulmonary pathologist reviewed the slides blinded and identified immune cell infiltration and other related pathologies.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Mice were treated with anti-IFNAR2 antibody at 1.5mg/kg dosing on days 7 and 11 post infection.
    anti-IFNAR2
    suggested: None
    Antibodies: Antibodies against the following antigens were used: Mouse antigens: CD45 (Clone: 30-F11), F4/80(BM8), CD326 (G8.8); Human antigens: CD45 (HI30), CD3 (UCHT1), CD14 (HCD14), CD16 (3G8), CD19 (HIB19), CD206 (15-2), CD86 (BU63), CD68(Y1/82A), CD11B (M1/70), CD11C (3.9), HLA-DR(LN3), NKp46 (9E2), CD56(MEM-188), CD4(OKT4), CD8(SK1).
    antigens: CD45
    suggested: None
    F4/80
    suggested: None
    CD326
    suggested: None
    HI30
    suggested: None
    CD3
    suggested: (Nanostring Cat# 121300104, RRID:AB_2893077)
    UCHT1
    suggested: None
    CD14
    suggested: (Miltenyi Biotec Cat# 130-094-531, RRID:AB_2721154)
    HCD14
    suggested: None
    CD16
    suggested: (BD Biosciences Cat# 557939, RRID:AB_2802162)
    CD19
    suggested: (Miltenyi Biotec Cat# 130-094-531, RRID:AB_2721154)
    HIB19
    suggested: (BD Biosciences Cat# 557939, RRID:AB_2802162)
    CD206
    suggested: None
    CD86
    suggested: None
    BU63
    suggested: None
    CD68
    suggested: (Nanostring Cat# 121300104, RRID:AB_2893077)
    CD11B
    suggested: (Miltenyi Biotec Cat# 130-094-531, RRID:AB_2721154)
    CD11C
    suggested: (Nanostring Cat# 121300104, RRID:AB_2893077)
    NKp46
    suggested: None
    CD56
    suggested: None
    CD4
    suggested: None
    CD8
    suggested: None
    Anti-dsRNA antibody (J2) was purchased from Sigma.
    Anti-dsRNA
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Infectious titers of SARS-CoV-2 were determined by plaque assay in Vero E6 (standard) or Vero ACE2+TMPRSS2+ (sensitive) cells in DMEM 4% FBS, and 0.6% Avicel RC-58132.
    Vero E6
    suggested: None
    Vero ACE2+TMPRSS2+
    suggested: None
    Software and Algorithms
    SentencesResources
    Data were analyzed using FlowJo software.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Differential expression analysis was also performed with DESeq2.
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)
    For IFN-stimulated gene identification, http://www.interferome.org was used with parameters -In Vivo, -Mus musculus or Homo sapiens -fold change up 2 and down 2.
    http://www.interferome.org
    suggested: (Interferome, RRID:SCR_007743)

    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 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.

    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.

  4. Version published to 10.1101/2021.09.27.461948v1 on bioRxiv