SARS-CoV-2 spike protein as a bacterial lipopolysaccharide delivery system in an overzealous inflammatory cascade

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Abstract

Accumulating evidence indicates a potential role for bacterial lipopolysaccharide (LPS) in the overactivation of the immune response during SARS-CoV-2 infection. LPS is recognised by Toll-like receptor 4 (TLR4) in innate immunity. Here, we showed that LPS binds to multiple hydrophobic pockets spanning both the S1 and S2 subunits of the SARS-CoV-2 spike (S) protein. LPS binds to the S2 pocket with a lower affinity compared to S1, suggesting its possible role as an intermediate in the TLR4 cascade. Congruently, nuclear factor-kappa B (NF-κB) activation in vitro is strongly boosted by S2. In vivo , however, a boosting effect is observed for both S1 and S2, with the former potentially facilitated by proteolysis. Collectively, our study suggests the S protein may act as a delivery system for LPS in host innate immune pathways. The LPS binding pockets are highly conserved across different SARS-CoV-2 variants and therefore represent potential therapeutic targets.

Article activity feed

  1. Peter A Ward

    Review 2: "SARS-CoV-2 spike protein as a bacterial lipopolysaccharide delivery system in an overzealous inflammatory cascade"

    This preprint explores binding of SARS-CoV-2 spike protein with lipopolysaccharide (LPS), and its role in increased inflammatory response. Reviewers find presented evidence reliable, while exercising caution with presented generalizations regarding use of drugs blocking TLR4-LPS.

  2. Chiranjib Chakraborty

    Review 1: "SARS-CoV-2 spike protein as a bacterial lipopolysaccharide delivery system in an overzealous inflammatory cascade"

    This preprint explores binding of SARS-CoV-2 spike protein with lipopolysaccharide (LPS), and its role in increased inflammatory response. Reviewers find presented evidence reliable, while exercising caution with presented generalizations regarding use of drugs blocking TLR4-LPS.

  3. SciScore for 10.1101/2021.10.29.466401: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    Primary antibodies against the His-tag (1:2000, Invitrogen) were followed by secondary HRP conjugated antibodies (1:2000, Dako, Denmark), for detection of both proteins.
    His-tag
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Sf9 cells transfected by following were used to express the S protein by following bac-to-bac baculovirus expression system (Thermo Fisher, SG).
    Sf9
    suggested: CLS Cat# 604328/p700_Sf9, RRID:CVCL_0549)
    SARS-CoV-2 S, SARS-CoV-2 S1 and two variants of SARS-CoV-2 S2 proteins, produced by ACROBiosystems (USA), were used for BN-PAGE, MST and to stimulate THP-1 cells and for in vivo experiments.
    THP-1
    suggested: CLS Cat# 300356/p804_THP-1, RRID:CVCL_0006)
    Experimental Models: Organisms/Strains
    SentencesResources
    Mouse inflammation model and in vivo imaging: BALB/c tg (NF-B-RE-Luc)-Xen reporter mice (Taconic Biosciences, Albany, NY, USA, 10– 12 weeks old) were used to study the immunomodulatory effects of SARS-CoV-2 S protein subunits alone or in combination with LPS.
    BALB/c
    suggested: RRID:IMSR_ORNL:BALB/cRl)
    Software and Algorithms
    SentencesResources
    The image was obtained using a Gel Doc Imager (Bio-Rad Laboratories,
    Bio-Rad Laboratories
    suggested: (Bio-Rad Laboratories, RRID:SCR_008426)
    The initial coordinates of E. coli lipid A and LPS were obtained from CHARMM-GUI LPS modeller,62 while the initial coordinates of the S protein were extracted from the cryo-EM structure of S ECD in the closed state (PDB: 6XR8)23 with missing loops constructed using Modeller version 9.21.63 Protein and lipid were parameterized using the CHARMM36 forcefield.
    Modeller
    suggested: (MODELLER, RRID:SCR_008395)
    70 All simulations were performed using GROMACS 201871 and the trajectories visualised in VMD.
    GROMACS
    suggested: (GROMACS, RRID:SCR_014565)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on page 31. 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.

    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.