Evaluation of SARS-CoV-2 entry, inflammation and new therapeutics in human lung tissue cells

  1. Judith Grau-Expósito
  2. David Perea
  3. Marina Suppi
  4. Núria Massana
  5. Ander Vergara
  6. Maria José Soler
  7. Benjamin Trinite
  8. Julià Blanco
  9. Javier García-Pérez
  10. José Alcamí
  11. Anna Serrano-Mollar
  12. Joel Rosado
  13. Vicenç Falcó
  14. Meritxell Genescà
  15. Maria J. Buzon

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

The development of physiological models that reproduce SARS-CoV-2 infection in primary human cells will be instrumental to identify host-pathogen interactions and potential therapeutics. Here, using cell suspensions directly from primary human lung tissues (HLT), we have developed a rapid platform for the identification of viral targets and the expression of viral entry factors, as well as for the screening of viral entry inhibitors and anti-inflammatory compounds. The direct use of HLT cells, without long-term cell culture and in vitro differentiation approaches, preserves main immune and structural cell populations, including the most susceptible cell targets for SARS-CoV-2; alveolar type II (AT-II) cells, while maintaining the expression of proteins involved in viral infection, such as ACE2, TMPRSS2, CD147 and AXL. Further, antiviral testing of 39 drug candidates reveals a highly reproducible method, suitable for different SARS-CoV-2 variants, and provides the identification of new compounds missed by conventional systems, such as VeroE6. Using this method, we also show that interferons do not modulate ACE2 expression, and that stimulation of local inflammatory responses can be modulated by different compounds with antiviral activity. Overall, we present a relevant and rapid method for the study of SARS-CoV-2.

Article activity feed

  1. Version published to 10.1371/journal.ppat.1010171
  2. Version published to 10.1101/2021.04.21.440731v2 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.04.21.440731: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Study protocol was approved by the Ethical Committee (Institutional Review Board number PR(AG)212/2020).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    For cell phenotyping the following antibodies were used: anti-CD31 (PerCP-Cy5.5, BioLegend), anti-CD11b (FITC, BioLegend), anti-CD11c (Pe-Cy7, BD Biosciences), anti-E-cadherin (Pe-CF594, BD Biosciences), primary goat anti-ACE2 (R&D systems), anti-CD14 (APC-H7, BD Biosciences), anti-CD45 (AF700, BioLegend), anti-EpCAM (APC, BioLegend), anti-CD3 (BV650, BD Biosciences), anti-CD15 (BV605, BD Biosciences) and anti-HLA-DR (BV421, BioLegend).
    anti-CD31
    suggested: (BioLegend Cat# 303122, RRID:AB_2562149)
    anti-CD11c
    suggested: (BD Biosciences Cat# 563403, RRID:AB_2732048)
    anti-E-cadherin
    suggested: None
    anti-CD14
    suggested: (BD Biosciences Cat# 564054, RRID:AB_2687593)
    anti-CD15
    suggested: (BD Biosciences Cat# 562979, RRID:AB_2744292)
    anti-HLA-DR (BV421
    suggested: (BioLegend Cat# 307636, RRID:AB_2561831)
    For TMPRSS2 detection, after ACE2 staining with the appropriate secondary antibody, cells were washed twice with PBS 1% NMS (normal mouse serum) and then stained with a secondary goat anti-rabbit IgG (AF488, Thermofisher) for 30 min at 4°C.
    anti-rabbit IgG
    suggested: (ChromoTek Cat# srbAF488-1-10, RRID:AB_2827585)
    The sections were then blocked in bovine serum albumin (5%), incubated with anti-ACE2 antibody (R&D Systems cat. n° AF933, dilution 1:100) and with biotinylated secondary antibody against goat IgGs (Vector Laboratories cat. n° BA-9500, dilution 1:250).
    goat IgGs
    suggested: (Vector Laboratories Cat# BA-9500, RRID:AB_2336123)
    A Fluorescent Minus One control (FMO) without primary anti-ACE2 antibody was used as a control.
    anti-ACE2
    suggested: None
    Next day, cellular suspensions were stained with the following antibodies: anti-CD11b (FITC, BioLegend), anti-CD69 (PE-CF594, BD Biosciences), anti-CD14 (APC-H7, BD Biosciences), anti-EpCAM (APC, BioLegend), anti-CD3 (BV650, BD Biosciences), anti-CD45 (BV605, BioLegend), and anti-HLA-DR (BV421, BioLegend).
    anti-CD11b
    suggested: (BioLegend Cat# 101239, RRID:AB_11125575)
    anti-CD69
    suggested: (BD Biosciences Cat# 740460, RRID:AB_2740186)
    anti-EpCAM (APC
    suggested: None
    anti-CD3
    suggested: None
    anti-CD45
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Briefly, 293T cells were transfected with 3µg of the plasmid encoding the SARS-CoV-2 spike.
    293T
    suggested: CCLV Cat# CCLV-RIE 1018, RRID:CVCL_0063)
    VeroE6 cells were added at a density of 30.000 cells/well and incubated with the drug for at least 1 h before infection.
    VeroE6
    suggested: JCRB Cat# JCRB1819, RRID:CVCL_YQ49)
    Recombinant DNA
    SentencesResources
    The spike of the SARS-CoV-2 virus was generated (GeneArt Gene Synthesis, ThermoFisher Scientific) from the codon-optimized sequence obtained by Ou et al.[35] and inserted into pcDNA3.1D/V5-His-TOPO (pcDNA3.1-S-CoV2Δ19-G614).
    pcDNA3.1D/V5-His-TOPO
    suggested: None
    pcDNA3.1-S-CoV2Δ19-G614
    suggested: None
    Software and Algorithms
    SentencesResources
    For cell phenotyping the following antibodies were used: anti-CD31 (PerCP-Cy5.5, BioLegend), anti-CD11b (FITC, BioLegend), anti-CD11c (Pe-Cy7, BD Biosciences), anti-E-cadherin (Pe-CF594, BD Biosciences), primary goat anti-ACE2 (R&D systems), anti-CD14 (APC-H7, BD Biosciences), anti-CD45 (AF700, BioLegend), anti-EpCAM (APC, BioLegend), anti-CD3 (BV650, BD Biosciences), anti-CD15 (BV605, BD Biosciences) and anti-HLA-DR (BV421, BioLegend).
    BD Biosciences
    suggested: (BD Biosciences, RRID:SCR_013311)
    After fixation with PBS 2% PFA, cells were acquired in an LSR Fortessa (BD Biosciences) and analyzed using the FlowJo v10.6.1 software (TreeStar).
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Statistical analyses: Statistical analyses were performed with Prism software, version 6.0 (GraphPad).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    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:
    Finally, it is also important to note the potential limitations of the model, including the limited availability of human lung samples, inter-patient variation (age, smoking, etc.), the effects on lung biology of the medical condition instigating surgery, and the location of the sample resection which may affect the proportion of cell subsets such as AT-II. However, this variability is what shapes the HLT into a highly physiological and relevant model in comparison to current methods based on immortalized cell cultures. Besides the interest of the model proposed here, our results highlight drugs with antiviral activity in HLT cells together with immunomodulatory properties, which could increase the benefit of this treatment during COVID-19 disease progression. For instance, camostat, cepharantine and ergoloid were three of the most potent drugs inhibiting SARS-CoV-2 entry, and remarkably, also exerted a significant anti-inflammatory effect on myeloid cells. Clinical trials with camostat, currently ongoing, ergoloid and cepharatine, will shed light on their use as both antivirals and anti-inflammatory compounds.

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

    IdentifierStatusTitle
    NCT04625114RecruitingThe Potential of Oral Camostat in Early COVID-19 Disease in …

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on page 29. 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:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • 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.

  4. Version published to 10.1101/2021.04.21.440731v1 on bioRxiv