Phenol-chloroform-based RNA purification for detection of SARS-CoV-2 by RT-qPCR: Comparison with automated systems

  1. Henrik Dimke
  2. Sanne L. Larsen
  3. Marianne N. Skov
  4. Hanne Larsen
  5. Gitte N. Hartmeyer
  6. Jesper B. Moeller

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rapidly reached pandemic levels. Sufficient testing for SARS-CoV-2 has remained essential for tracking and containing the virus. SARS-CoV-2 testing capabilities are still limited in many countries. Here, we explore the use of conventional RNA purification as an alternative to automated systems for detection of SARS-CoV-2 by RT-qPCR. 87 clinical swab specimens were extracted by conventional phenol-chloroform RNA purification and compared to commercial platforms for RNA extraction and the fully integrated Cobas ® 6800 diagnostic system. Our results show that the conventional RNA extraction is fully comparable to modern automated systems regarding analytical sensitivity and specificity with respect to detection of SARS-CoV-2 as evaluated by RT-qPCR. Moreover, the method is easily scalable and implemented in conventional laboratories as a low cost and suitable alternative to automated systems for the detection of SARS-CoV-2.

Article activity feed

  1. Version published to 10.1371/journal.pone.0247524
  2. ScreenIT

    SciScore for 10.1101/2020.05.26.20099440: (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
    95% confidence intervals and Pearson correlation coefficients (r) were calculated using Prism 8.3 (Graphpad Software).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    Graphpad
    suggested: (GraphPad, RRID:SCR_000306)

    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:
    While there are numerous advantages to the AGPC method, there are also inherent limitations. In comparison to automated RNA extraction systems there is extensive hands-on time and inadvertently risks of human errors. Furthermore, there is a possibility for loss of the sample, if the pellet is lost during the isolation step or if the sample is inadvertently mixed when transferring the aqueous phase between tubes. However, well established workflows can minimize these risks to very low levels. By spiking the sample specimens with the Nobilis ND C2 vaccine against Newcastle Disease containing inactivated virus, we obtained a good measure of the extraction efficiency and presence of potential inhibitors of the PCR analysis. This allowed us to monitor the entire extraction process and in the rare case of sample loss or other failures, repeat the RNA extraction and analysis, as only 200 μl out of the 1ml EswabTM media was used for the initial analysis. RNA isolation using the AGPC method is favored among scientists for small scale RNA purification setups, due to its low cost, versatility and ease of use. Here we show that the AGPC method is easily scalable to volumes usable for clinical diagnostics as a supplement to conventional automated systems. The state-of-the-art Cobas®6800 system has a capacity of 384 samples per 8 hours, which is roughly equivalent to the throughput of our RNA isolation pipeline presented here. While the Cobas®6800 system is unsurpassed in ease, accuracy an...

    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.

  3. Version published to 10.1101/2020.05.26.20099440v1 on medRxiv