At the Intersection Between SARS-CoV-2, Macrophages and the Adaptive Immune Response: A Key Role for Antibody-Dependent Pathogenesis But Not Enhancement of Infection in COVID-19

  1. Jennifer K. DeMarco
  2. Wiliam E. Severson
  3. Daniel R. DeMarco
  4. Gregory Pogue
  5. Jon Gabbard
  6. Kenneth E. Palmer

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Abstract

Since entering the world stage in December of 2019, SARS-CoV-2 has impacted every corner of the globe with over 1.48 million deaths and caused untold economic damage. Infections in humans range from asymptomatic to severe disease associated with dysregulation of the immune system leading to the development of acute respiratory distress syndrome (ARDs).

The distinct shift in peripheral monocyte activation and infiltration of these cells into the respiratory tract in ARDs patients suggests severe COVID-19 may largely result from damage to the respiratory epithelia by improperly activated macrophages. Here, we present evidence that dysregulation of the immune response in COVID-19 begins with activation of macrophages by non-neutralizing antibodies and induction of ACE2 expression, rendering these cells susceptible to killing by SARS-CoV-2. Death of macrophages occurs independently of viral replication and leads to the release of inflammatory mediators and modulation of the susceptibility of downstream epithelial cells to SARS-CoV-2.

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  1. ScreenIT

    SciScore for 10.1101/2021.02.22.432407: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Prior to the addition of virus, serial dilutions of antibodies against either the nucleocapsid (Genetex GTX632269) or spike proteins (polyclonal anti-spike, Abcam ab272504; anti-RBD, AcroBiosystems SAD-S35-100ug) of SARS-CoV-2 in a total volume of 60ul of VIM were made in a separate 96 well dilution plate to which 60 pfu/well of SARS-CoV-2 (USA-WA1/2020) was added for a final MOI of 0.05.
    anti-spike ,
    suggested: None
    anti-RBD
    suggested: None
    Following incubation, samples were washed three times with 1XPBS+0.2% Triton-X100 for 5 minutes, prior to incubation with 1:1,000 anti-rabbit IgG secondary antibody (Rockland 611-141-122) for 1 hour.
    anti-rabbit IgG
    suggested: (Rockland Cat# 611-141-122, RRID:AB_1057564)
    Experimental Models: Cell Lines
    SentencesResources
    Determination of Viral Load: Raw 264.7 cells were seeded at a density of 2×106 cells/well in a 6-well plate (Geiner Bio-One 657165) and allowed to settle overnight at 37°C, 5% CO2.
    Raw 264.7
    suggested: None
    Impact of MP Supernatants on Vero E6 Susceptibility to SARS-CoV-2: Vero E6 cells (ATCC VERO C1008) were cultured in DMEM containing, 4 mM L-glutamine, sodium pyruvate (Hyclone SH30243),
    Vero E6
    suggested: RRID:CVCL_XD71)
    Software and Algorithms
    SentencesResources
    Prior to the addition of virus, serial dilutions of antibodies against either the nucleocapsid (Genetex GTX632269) or spike proteins (polyclonal anti-spike, Abcam ab272504; anti-RBD, AcroBiosystems SAD-S35-100ug) of SARS-CoV-2 in a total volume of 60ul of VIM were made in a separate 96 well dilution plate to which 60 pfu/well of SARS-CoV-2 (USA-WA1/2020) was added for a final MOI of 0.05.
    AcroBiosystems
    suggested: (ACRObiosystems, RRID:SCR_012550)
    Images were captured using a Zeiss LSM 710 confocal microscope and receptor expression quantitated using ImageJ.
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    Statistical Analysis: All graphical presentations of data and ANOVA analysis was conducted in GraphPad Prism 9.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.

    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.

  2. Version published to 10.1101/2021.02.22.432407 on bioRxiv