Robust and sensitive detection of SARS-CoV-2 using PCR based methods

  1. Changwoo Park
  2. Jina Lee
  3. Zohaib ul Hassan
  4. Keun Bon Ku
  5. Seong Jun Kim
  6. Hong Gi Kim
  7. Edmond Changkyun Park
  8. Gun-Soo Park
  9. Daeui Park
  10. Seung-Hwa Baek
  11. Dongju Park
  12. Jihye Lee
  13. Sangeun Jeon
  14. Seungtaek Kim
  15. Chang-Seop Lee
  16. Hee Min Yoo
  17. Seil Kim

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Abstract

The World Health Organization (WHO) has declared the Coronavirus disease 2019 (COVID-19) as an international health emergency. Current diagnostic tests are based on the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) method, the gold standard test that involves the amplification of viral RNA. However, the RT-qPCR assay has limitations in terms of sensitivity and quantification. In this study, we tested both qPCR and droplet digital PCR (ddPCR) to detect low amounts of viral RNA. The cycle threshold (CT) of viral RNA by RT-PCR significantly varied according to the sequence of primer and probe sets with in vitro transcript (IVT) RNA or viral RNA as templates, whereas the copy number of viral RNA by ddPCR was effectively quantified with IVT RNA, cultured viral RNA, and RNA from clinical samples. Furthermore, the clinical samples were assayed via both methods, and the sensitivity of the ddPCR was determined to be significantly higher than RT-qPCR. These findings suggest that ddPCR could be used as a highly sensitive and compatible diagnostic method for viral RNA detection.

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    SciScore for 10.1101/2020.07.03.186304: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Clinical samples and RNA preparation: The clinical samples used in this study were collected from subjects according to registered protocols approved by the Institutional Review Board (IRB) of Jeonbuk National University Hospital, with all patients having signed written informed consent forms (IRB registration number: CUH 2020-02-050-008).
    Consent: Clinical samples and RNA preparation: The clinical samples used in this study were collected from subjects according to registered protocols approved by the Institutional Review Board (IRB) of Jeonbuk National University Hospital, with all patients having signed written informed consent forms (IRB registration number: CUH 2020-02-050-008).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Vero E6 cells (ATCC CRL-1586) were purchased from the American Type Culture Collection (ATCC) and were maintained in Dulbecco’s modified Eagle medium (DMEM) supplemented with 2% (v/v
    Vero E6
    suggested: None
    Human hepatoma Huh-7 were obtained from the Japan Cell Research Bank (National Institutes of Biomedical Innovation, Health and Nutrition, Japan).
    Huh-7
    suggested: CLS Cat# 300156/p7178_HuH7, RRID:CVCL_0336)
    Human lung fibroblast MRC-5 cells were obtained from the American Type Culture Collection (ATCC).
    MRC-5
    suggested: ICLC Cat# HL95001, RRID:CVCL_0440)
    Software and Algorithms
    SentencesResources
    Raw data (i.e., the fluorescence values for the droplets) were exported from the QuantaSoft software to Microsoft Excel 2016.
    QuantaSoft
    suggested: None
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    Results from OddPub: Thank you for sharing your data.

    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.

    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 10.1101/2020.07.03.186304v1 on bioRxiv