SARS-CoV-2 Viral Replication in a High Throughput Human Primary Epithelial Airway Organ Model

  1. Christine R. Fisher
  2. Felix Mba Medie
  3. Rebeccah J. Luu
  4. Robert Gaibler
  5. Caitlin R. Miller
  6. Thomas J. Mulhern
  7. Vidhya Vijayakumar
  8. Elizabeth Marr
  9. Jehan Alladina
  10. Benjamin Medoff
  11. Jeffrey T. Borenstein
  12. Ashley L. Gard

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Abstract

COVID-19 emerged as a worldwide pandemic early in 2020, and at this writing has caused over 170 million cases and 3.7 million deaths worldwide, and almost 600,000 deaths in the United States. The rapid development of several safe and highly efficacious vaccines stands as one of the most extraordinary achievements in modern medicine, but the identification and administration of efficacious therapeutics to treat patients suffering from COVID-19 has been far less successful. A major factor limiting progress in the development of effective treatments has been a lack of suitable preclinical models for the disease, currently reliant upon various animal models and in vitro culture of immortalized cell lines. Here we report the first successful demonstration of SARS-CoV-2 infection and viral replication in a human primary cell-based organ-on-chip, leveraging a recently developed tissue culture platform known as PREDICT96. This successful demonstration of SARS-CoV-2 infection in human primary airway epithelial cells derived from a living donor represents a powerful new pathway for disease modeling and an avenue for screening therapeutic candidates in a high throughput platform.

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  1. ScreenIT

    SciScore for 10.1101/2021.06.15.448611: (What is this?)

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

    Table 1: Rigor

    EthicsField Sample Permit: Bronchoscopy brushings were collected into collection media (RMPI (ThermoFisher) + 2% human serum albumin (ThermoFisher) + 5 μM ROCKi (Tocris)) and transported on ice to Draper (Cambridge, MA)19.
    IRB: All research involving human subjects was approved by the MGH and Partners Healthcare System Institutional Review Board, and adhered to all applicable institutional and sponsor ethical guidelines, including but not limited to anonymization of donors for personal identity.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Primary antibodies were used to stain basal cells (CK5, Thermo Fisher), goblet cells (Muc5A, Thermo Fisher), ciliated cells (acetylated-tubulin, Abcam) and SARS-CoV-2 (Spike and Nucleocapsid proteins, GeneTex).
    CK5
    suggested: None
    acetylated-tubulin, Abcam
    suggested: None
    SARS-CoV-2 (Spike and Nucleocapsid proteins, GeneTex).
    suggested: None
    The SARS-CoV-2 Spike and Nucleocapsid protein antibodies were combined when added to the PREDICT96-ALI airway tissues during primary antibody incubation steps.
    Nucleocapsid protein
    suggested: None
    Secondary antibodies used were Alexa Fluor 488 goat anti-mouse IgG (Thermo Fisher) and Alexa Fluor 555 goat anti-rabbit IgG (Thermo Fisher).
    anti-mouse IgG
    suggested: None
    anti-rabbit IgG
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    DH01 cells were thawed and plated at 15,000 cells per device in a 3 μL volume directly onto the membrane.
    DH01
    suggested: None
    Briefly, Vero E6 cells (ATCC) were plated in 6-well plates and incubated at 37°C and 5% CO2 until confluent.
    Vero E6
    suggested: None
    Software and Algorithms
    SentencesResources
    Mean Fluorescence Intensity Quantification: 10x tile scans of the middle of each PREDICT96-ALI tissue device were captured on a Zeiss LSM700 laser scanning confocal microscope with Zen Black software (Zeiss).
    Zen Black
    suggested: (Black Zen software, RRID:SCR_018163)
    The MFI of the signal from the red channel, or the Nucleocapsid and Spike protein expression, of these regions was measured via ImageJ Fiji.
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    Statistical analysis: Data are presented as mean ± standard deviation or standard error of the mean (indicated in figure legends) and were analyzed using Graphpad Prism version 9.0.0 for Windows (GraphPad Software).
    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:
    Organ-on-chip technologies have the potential to overcome these limitations by offering human-relevant physiological fidelity in infection-based assays. However, these platforms have historically been challenged by excessive complexity and difficulty in direct application in pharmaceutical laboratory environments. Further, in the case of SARS-CoV-2 research, these models have so far been limited to the study of pseudovirus entry into cells rather than direct investigations of infection by the live virus. Here, we report the first SARS-CoV-2 infection study in a human primary cell-based airway-on-a-chip model. Further, we utilize human airway epithelial cells isolated from living donors via research bronchoscopies, a capability that provides the opportunity for evaluating mechanisms of infection for specific patient subpopulations. Our high throughput PREDICT96-ALI platform was successfully adapted to operation in a BSL-3 environment while retaining key biological attributes of functional respiratory tissue. Importantly, PREDICT96-ALI has the demonstrated capacity for use in high-throughput assays, a critical capability for practical drug discovery and therapeutic screening applications. Further development of this platform technology can enable the study of respiratory infections across large numbers of independent human cell donors, spanning a wide-range of demographics and co-morbidities in order to capture natural variability in the population. Leveraging all of its featur...

    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.

  2. Version published to 10.1101/2021.06.15.448611v1 on bioRxiv