SARS‐CoV‐2 infection activates dendritic cells via cytosolic receptors rather than extracellular TLRs

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Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) causes coronavirus disease 2019 (COVID‐19), an infectious disease characterized by strong induction of inflammatory cytokines, progressive lung inflammation, and potentially multiorgan dysfunction. It remains unclear how SARS‐CoV‐2 infection leads to immune activation. The Spike (S) protein of SARS‐CoV‐2 has been suggested to trigger TLR4 and thereby activate immunity. Here, we have investigated the role of TLR4 in SARS‐CoV‐2 infection and immunity. Neither exposure of isolated S protein, SARS‐CoV‐2 pseudovirus nor primary SARS‐CoV‐2 isolate induced TLR4 activation in a TLR4‐expressing cell line. Human monocyte‐derived DCs express TLR4 but not angiotensin converting enzyme 2 (ACE2), and DCs were not infected by SARS‐CoV‐2. Notably, neither S protein nor SARS‐CoV‐2 induced DC maturation or cytokines, indicating that both S protein and SARS‐CoV‐2 virus particles do not trigger extracellular TLRs including TLR4. Ectopic expression of ACE2 in DCs led to efficient infection by SARS‐CoV‐2 and, strikingly, efficient type I IFN and cytokine responses. These data strongly suggest that not extracellular TLRs but intracellular viral sensors are key players in sensing SARS‐CoV‐2. These data imply that SARS‐CoV‐2 escapes direct sensing by TLRs, which might underlie the lack of efficient immunity to SARS‐CoV‐2 early during infection.

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  1. SciScore for 10.1101/2021.09.02.458667: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Primary cells: This study was performed in accordance with the ethical principles set out in the declaration of Helsinki and was approved by the institutional review board of the Amsterdam University Medical Centers,
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The antibody clones used are: CD86 (2331 (FUN-1), BD Pharmingen),
    CD86
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Cell lines: The Simian kidney cell line VeroE6 (ATCC® CRL-1586™) was maintained in CO2 independent medium (Gibco Life Technologies, Gaithersburg, Md.) supplemented with 10% fetal calf serum (FCS), 2mM L-glutamine and penicillin/streptomycin.
    VeroE6
    suggested: None
    HEK293 cells stably transfected with TLR4 cDNA (HEK/TLR4) were a kind gift from D. T. Golenbock(15).
    HEK293
    suggested: CLS Cat# 300192/p777_HEK293, RRID:CVCL_0045)
    HEK293 and HEK/TLR4 cells were transiently transfected with pcDNA3.1(-)hACE2 (Addgene plasmid #1786) to generate HEK/ACE2 or HEK/TLR4/ACE2 cell lines.
    HEK/TLR4
    suggested: None
    For the pseudovirus infection assays, HEK293 or 293/TLR4 cell lines and DCs were exposed to 95ng/mL and 191.05ng/mL of SARS-CoV-2 pseudovirus, respectively.
    293/TLR4
    suggested: None
    Also, the HEK293/ACE2 and HEK/TLR4/ACE2 cell lines were exposed to the SARS-CoV-2 isolate (hCoV-19/Italy) at TCID 100 (MOI 0.0028) for 24 hours at 37°C.
    HEK/TLR4/ACE2
    suggested: None
    Recombinant DNA
    SentencesResources
    HEK293 and HEK/TLR4 cells were transiently transfected with pcDNA3.1(-)hACE2 (Addgene plasmid #1786) to generate HEK/ACE2 or HEK/TLR4/ACE2 cell lines.
    pcDNA3.1 ( -)hACE2
    suggested: None
    SARS-CoV-2 pseudovirus production: For production of single-round infection viruses, human embryonic kidney 293T/17 cells (ATCC, CRL-11268) were co-transfected with an adjusted HIV-1 backbone plasmid (pNL4-3.
    pNL4-3
    suggested: None
    Luc.R-S-) containing previously described stabilizing mutations in the capsid protein (PMID: 12547912) and firefly luciferase in the nef open reading frame (1.35ug) and pSARS-CoV-2 expressing SARS-CoV-2 S protein (0.6ug) (GenBank; MN908947.3)(22).
    pSARS-CoV-2
    suggested: None
    Software and Algorithms
    SentencesResources
    Single-cell measurements were performed on a FACS Canto flow cytometer (BD Biosciences) and FlowJo V10 software (TreeStar) was used to analyze the data.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Statistics: Graphpad Prism v8 (GraphPad Software) was used to generate all graphs and for statistical analyses.
    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: 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.