Evaluation Of SYBR Green Real Time PCR For Detecting SARS-CoV-2 From Clinical Samples

  1. Álvaro Fajardo
  2. Marianoel Pereira-Gómez
  3. Natalia Echeverría
  4. Fernando López-Tort
  5. Paula Perbolianachis
  6. Fabián Aldunate
  7. Pilar Moreno
  8. Gonzalo Moratorio

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Abstract

The pandemic caused by SARS-CoV-2 has triggered an extraordinary collapse of healthcare systems and hundred thousand of deaths worldwide. Following the declaration of the outbreak as a Public Health Emergency of International Concern by the World Health Organization (WHO) on January 30 th , 2020, it has become imperative to develop diagnostic tools to reliably detect the virus in infected patients. Several methods based on real time reverse transcription polymerase chain reaction (RT-qPCR) for the detection of SARS-CoV-2 genomic RNA have been developed. In addition, these methods have been recommended by the WHO for laboratory diagnosis. Since all these protocols are based on the use of fluorogenic probes and one-step reagents (cDNA synthesis followed by PCR amplification in the same tube), these techniques can be difficult to perform given the limited supply of reagents in low and middle income countries. In the interest of economy, time and availability of chemicals and consumables, the SYBR Green-based detection was implemented to establish a convenient assay. Therefore, we adapted one of WHO recommended Taqman-based one-step real time PCR protocols (from the University of Hong Kong) to SYBR Green. Our results suggest that SYBR-Green detection represents a reliable cost-effective alternative to increase the testing capacity.

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    SciScore for 10.1101/2020.05.13.093609: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    : Ab1 files from Sanger sequencing were analyzed using the Staden package v1.7.0 (http://staden.sourceforge.net).
    http://staden.sourceforge.net
    suggested: (Staden Package, RRID:SCR_005629)

    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.

    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 10.1101/2020.05.13.093609 on bioRxiv