Defining the Innate Immune Responses for SARS-CoV-2-Human Macrophage Interactions

  1. Mai M. Abdelmoaty
  2. Pravin Yeapuri
  3. Jatin Machhi
  4. Katherine E. Olson
  5. Farah Shahjin
  6. Vikas Kumar
  7. You Zhou
  8. Jingjing Liang
  9. Kabita Pandey
  10. Arpan Acharya
  11. Siddappa N. Byrareddy
  12. R. Lee Mosley
  13. Howard E. Gendelman

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Abstract

Host innate immune response follows severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and it is the driver of the acute respiratory distress syndrome (ARDS) amongst other inflammatory end-organ morbidities. Such life-threatening coronavirus disease 2019 (COVID-19) is heralded by virus-induced activation of mononuclear phagocytes (MPs; monocytes, macrophages, and dendritic cells). MPs play substantial roles in aberrant immune secretory activities affecting profound systemic inflammation and end-organ malfunctions. All follow the presence of persistent viral components and virions without evidence of viral replication. To elucidate SARS-CoV-2-MP interactions we investigated transcriptomic and proteomic profiles of human monocyte-derived macrophages. While expression of the SARS-CoV-2 receptor, the angiotensin-converting enzyme 2, paralleled monocyte-macrophage differentiation, it failed to affect productive viral infection. In contrast, simple macrophage viral exposure led to robust pro-inflammatory cytokine and chemokine expression but attenuated type I interferon (IFN) activity. Both paralleled dysregulation of innate immune signaling pathways, specifically those linked to IFN. We conclude that the SARS-CoV-2-infected host mounts a robust innate immune response characterized by a pro-inflammatory storm heralding end-organ tissue damage.

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  1. Version published to 10.3389/fimmu.2021.741502
  2. Version published to 10.1101/2021.07.07.449660v3 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.07.07.449660: (What is this?)

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

    Table 1: Rigor

    EthicsIACUC: SARS-CoV-2 infection: Experiments involving SARS-CoV-2 were performed in the University of Nebraska Medical Center (UNMC) biosafety level 3 (BSL-3) core facility and approved by UNMC Institutional Biosafety Committee (IBC) (protocol number 20-05-027-BL3).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    On days 0, 1, 3, 5, and 7 during differentiation, monocytes-macrophages were stained with fluorescently-conjugated antibodies to detect human ACE2 (APC, LSBio, LS-C275129, polyclonal), CD14 (Alexa Fluor 488, eBioscience, clone 61D3), and CD16 (PE, eBioscience, eBioCB16, clone CB16), and with isotype-matched antibodies serving as negative controls.
    ACE2
    suggested: None
    LS-C275129
    suggested: None
    CD14
    suggested: None
    CD16
    suggested: None
    Membranes were blocked in 5% nonfat milk in TBST buffer at room temperature for 1 hour, followed by incubation with primary antibodies to IFN-α (1:500, Thermo Fisher Scientific, MA5-37518)
    IFN-α
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    The virus was passaged on Vero.STAT1 knockout (KO) cells (ATCC, CCL-81-VHG) and titer was determined by plaque assay in Vero E6 cells (ATCC, CRL-1586) (Mendoza et al, 2020).
    Vero E6
    suggested: None
    Vero.STAT1 KO cells were maintained for study based on their high susceptibility to virus infection due to lack of Signal Transducer and Activator of Transcription 1 (STAT1) protein required for cellular antiviral responses (Durbin et al, 1996).
    Vero.STAT1 KO
    suggested: ATCC Cat# CCL-81-VHG, RRID:CVCL_YZ45)
    Vesicular stomatitis virus (VSV Indiana laboratory strain) (V-520-001-522, ATCC, VR-1238) was passaged on Vero cells (ATCC, CCL-81), and viral titer was determined using the plaque assay in Vero cells.
    Vero
    suggested: None
    Software and Algorithms
    SentencesResources
    Stained cells were examined with an LSR II flow cytometer (BD Biosciences) and analyzed using BD FACSDiva software.
    BD FACSDiva
    suggested: (BD FACSDiva Software, RRID:SCR_001456)
    Forward primer: 5’ GACCCCAAAATCAGCGAAAT 3’, Reverse primer: 5’ TCTGGTTACTGCCAGTTGAATCTG 3’, and Probe: 5’ FAM-ACCCCGCATTACGTTTGGTGGACC-BHQ-1 3’.
    Probe
    suggested: (UniPROBE, RRID:SCR_005803)
    Ingenuity Pathway Analysis (IPA) (Qiagen) was used to identify the pathways and networks affected post-viral exposure.
    Ingenuity Pathway Analysis
    suggested: (Ingenuity Pathway Analysis, RRID:SCR_008653)
    The Reactome gene set enrichment analysis (GSEA) was conducted using ReactomeFIViz (https://reactome.org/tools/reactome-fiviz) (Wu et al, 2014), a Cytoscape application for pathway and network-based data analysis.
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) local network cluster enrichment analysis was conducted using STRING database (http://string-db.org), which provides a critical assessment and integration of protein-protein interaction (PPI), including direct (physical) and indirect (functional) associations in a given organism (Szklarczyk et al, 2019).
    STRING
    suggested: (STRING, RRID:SCR_005223)
    Immunoblots were quantified using ImageJ software (NIH) relative to β-actin expression.
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    GO annotation, KEGG, Reactome GSEA, and STRING analyses were conducted using GO Resource, DAVID, ReactomeFIViz, and STRING databases, respectively.
    KEGG
    suggested: (KEGG, RRID:SCR_012773)
    DAVID
    suggested: (DAVID, RRID:SCR_001881)
    Statistical analysis was performed using GraphPad Prism 9.1.0 software (GraphPad Software, San Diego, CA).
    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 did not find any issues relating to the usage of bar graphs.

    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 10.1101/2021.07.07.449660v2 on bioRxiv
  5. Version published to 10.1101/2021.07.07.449660v1 on bioRxiv