RPA-Based Method For The Detection Of SARS-COV2

  1. Angus A. Nassir
  2. Mazarati Jean Baptiste
  3. Ivan Mwikarago
  4. Majidi R. Habimana
  5. Janvier Ndinkabandi
  6. Anthere Murangwa
  7. Thierry Nyatanyi
  8. Claude Mambo Muvunyi
  9. Sabin Nsanzimana
  10. Mutesa Leon
  11. Clarisse Musanabaganwa

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

Coronavirus disease 2019 (COVID-19) is a highly infectious disease with significant mortality, morbidity, and far-reaching economic and social disruptions. Testing is key in the fight against COVID-19 disease. The gold standard for COVID-19 testing is the reverse transcription polymerase chain reaction (RT-PCR) test. RT-PCR requires highly specialized, expensive, and advanced bulky equipment that is difficult to use in the field or in a point of care setting. There is need for a simpler, inexpensive, convenient, portable and accurate test. Our aims were to: (i) design primer-probe pairs for use in isothermal amplification of the S1, ORF3 and ORF8 regions of the SARS-CoV2 virus; (ii) optimize the recombinase polymerase amplification (RPA) assay for the isothermal amplification of the named SARS-COV2 regions; (iii) detect amplification products on a lateral flow device. and (ii) perform a pilot field validation of RPA on RNA extracted from nasopharyngeal swabs.

Results

Assay validation was done at the National Reference Lab (NRL) at the Rwanda Biomedical Center (RBC) in Rwanda. Results were compared to an established, WHO-approved rRT-PCR laboratory protocol. The assay provides a faster and cheaper alternative to rRT-PCR with 100% sensitivity, 93% specificity, and positive and negative predictive agreements of 100% and 93% respectively.

Conclusion

To the best of our knowledge, this is the first in-field and comparative laboratory validation of RPA for COVID-19 disease in low resource settings. Further standardization will be required for deployment of the RPA assay in field settings.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.09.17.20196402: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationPreviously collected, anonymized samples from current COVID-19 patients were randomly selected and used to validate the assay.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    To determine the best regions to target for efficient primer design, BLAST analysis was performed and the percent sequence identity between the SARS CoV2 sequences and other coronavirus sequences determined (table S 1).
    BLAST
    suggested: (BLASTX, RRID:SCR_001653)
    Primers were designed using Primer3 Plus software to flank the Orf3b and Orf8/8b regions since this exhibit the lowest homology between SARS CoV2 and other coronaviruses (Untergasser et al., 2012).
    Primer3 Plus
    suggested: None
    Visualization was done using the PCRD cassettes Statistical Tests: Graphpad QuickCalcs (https://www.graphpad.com/quickcalcs/ConfInterval1.cfm) was used to calculate confidence intervals (95% CI) for sensitivity and specificity comparisons of LightMix®Modular SARS-CoV2 RT-PCR and RPA.
    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:
    Study Limitations: Due to financial limitations, only 49 samples were tested, optimization of reaction temperatures and MgOAc concentrations was not done, ORF3a and ORF8a/b probes were not tested, and the absolute limit of detection of RNA extracted from nasopharyngeal swabs for RPA testing could not be determined.

    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 10.1101/2020.09.17.20196402v1 on medRxiv