Persistent Oxidative Stress and Inflammasome Activation in CD14highCD16− Monocytes From COVID-19 Patients

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Abstract

The poor outcome of the coronavirus disease-2019 (COVID-19), caused by SARS-CoV-2, is associated with systemic hyperinflammatory response and immunopathology. Although inflammasome and oxidative stress have independently been implicated in COVID-19, it is poorly understood whether these two pathways cooperatively contribute to disease severity. Herein, we found an enrichment of CD14 high CD16 monocytes displaying inflammasome activation evidenced by caspase-1/ASC-speck formation in severe COVID-19 patients when compared to mild ones and healthy controls, respectively. Those cells also showed aberrant levels of mitochondrial superoxide and lipid peroxidation, both hallmarks of the oxidative stress response, which strongly correlated with caspase-1 activity. In addition, we found that NLRP3 inflammasome-derived IL-1β secretion by SARS-CoV-2-exposed monocytes in vitro was partially dependent on lipid peroxidation. Importantly, altered inflammasome and stress responses persisted after short-term patient recovery. Collectively, our findings suggest oxidative stress/NLRP3 signaling pathway as a potential target for host-directed therapy to mitigate early COVID-19 hyperinflammation and also its long-term outcomes.

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  1. SciScore for 10.1101/2021.09.13.21263292: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Protocols in this study were reviewed and approved by the National Institutes of Health (NIH) Central Intramural Institutional Review Board (IRB).
    Consent: All participants provided written informed consent prior to any study procedures in accordance with the Declaration of Helsinki.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Cells were washed twice with the FLICA kit wash buffer and then incubated with LIVE/DEAD Fixable AQUA Dead Cells Stain (Thermo Fisher, USA) for 15 min at RT, followed by extracellular staining in PBS + 1% BSA with the following fluorochrome-conjugated antibodies for monocyte phenotyping: anti-CD14 BV605 (Clone:M5E2)
    anti-CD14
    suggested: None
    Cells were fixed and permeabilized with Cytofix/Cytoperm (BD Biosciences, USA) overnight at 4°C and stained for 1h at RT for intracellular ASC, with anti-ASC/TMS1 AF647 antibody from Novus Biologicals, Littleton, CO.
    anti-ASC/TMS1 AF647
    suggested: None
    Flow Cytometry: PBMCs were stained with the following list of fluorescently labeled antibodies against cell surface markers subsequently detected by flow cytometry: anti- CD14 BV605 (Clone:M5E2), anti-CD16 PE-Cy7/BV711 (Clone:3G8), and anti- CD3 PE (Clone:HIT3a) from BioLegend; anti-CD20 e450 (Clone:2H7)
    anti-CD16 PE-Cy7/BV711
    suggested: None
    anti- CD3
    suggested: None
    anti-CD20
    suggested: None
    GFP fluorescence was detected by staining cells with Alexa Fluor 647 anti- GFP antibody at 1:200 (Biolegend).
    GFP
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    To determine viral titers by TCID50 assay, cells were harvested, lysed by freeze/thawing and plated in triplicate onto Vero E6 cells using 10-fold serial dilutions.
    Vero E6
    suggested: None
    Software and Algorithms
    SentencesResources
    All compensation and gating analyses were performed using FlowJo 10.5.3 (TreeStar, Ashland, OR, USA)
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Statistical Analyses: Statistical analyses were performed using non-parametric Mann-Whitney or Kruskal-Wallis test in GraphPad Prism 8.0.1 software (GraphPad, USA).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    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: We detected the following sentences addressing limitations in the study:
    The limitations of the current study include lack of critically ill ventilated ICU patients (as participants had to be able to provide consent), lack of multiple longitudinal sampling and small sample size. Nevertheless, our findings collectively corroborate the hypothesis that early exposure of alveolar macrophages and endothelial cells to SARS-CoV-2 may induce oxidative stress dysregulation and aberrant cytokine secretion. This initial cell priming event may contribute to the enhanced recruitment to the site of infection of pre-activated circulating monocytes pre-committed to inflammasome activation and aberrant oxidative stress response, resulting in exacerbation of tissue immunopathology and ultimately organ failure. In this context, recent advances in targeting ROS by administration of glutathione or glutathione precursors (N-acetyl-cysteine, NAC), as well as IL-1 signaling by administrating Anakinra, a IL-1 Receptor antagonist (IL-1Ra), have been reported to prevent inflammation and/or worse clinical outcome in COVID-19 patients (Cauchois et al., 2020; Cavalli et al., 2020; Horowitz et al., 2020; Huet et al., 2020; Ibrahim et al., 2020; Kyriazopoulou et al., 2021a; Kyriazopoulou et al., 2021b). Thus, our findings suggest that early treatment with antioxidants and IL-1 signaling inhibitors may represent potential therapeutic intervention for COVID-19 by preventing deleterious effects downstream of the inflammasome pathway and consequently tissue immunopathology and that ...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04401436RecruitingCOVID-19 Associated Lymphopenia Pathogenesis Study in Blood


    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.