Development of RNA-Based Assay for Rapid Detection of SARS-CoV-2 in Clinical Samples

  1. Vinod Kumar
  2. Suman Mishra
  3. Rajni Sharma
  4. Jyotsna Agarwal
  5. Ujjala Ghoshal
  6. Tripti Khanna
  7. Lokendra K. Sharma
  8. Santosh Kumar Verma
  9. Prabhakar Mishra
  10. Swasti Tiwari

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Abstract

<b><i>Introduction:</i></b> The ongoing spread of pandemic coronavirus disease-19 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of growing concern. Rapid diagnosis and management of SARS-CoV-2 are crucial for controlling the outbreak in the community. Here, we report the development of a first rapid-colorimetric assay capable of detecting SARS-CoV-2 in the human nasopharyngeal RNA sample in less than 30 min. <b><i>Method:</i></b> We utilized a nanomaterial-based optical sensing platform to detect RNA-dependent RNA polymerase gene of SARS-CoV-2, where the formation of oligo probe-target hybrid led to salt-induced aggregation and change in gold-colloid color from pink to blue visibility range. Accordingly, we found a change in colloid color from pink to blue in assay containing nasopharyngeal RNA sample from the subject with clinically diagnosed COVID-19. The colloid retained pink color when the test includes samples from COVID-19 negative subjects or human papillomavirus-infected women. <b><i>Results:</i></b> The results were validated using nasopharyngeal RNA samples from positive COVID-19 subjects (<i>n</i> = 136). Using real-time polymerase chain reaction as gold standard, the assay was found to have 85.29% sensitivity and 94.12% specificity. The optimized method has detection limit as little as 0.5 ng of SARS-CoV-2 RNA. <b><i>Conclusion:</i></b> We found that the developed assay rapidly detects SARS-CoV-2 RNA in clinical samples in a cost-effective manner and would be useful in pandemic management by facilitating mass screening.

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  1. Version published to 10.1159/000522337
  2. Version published to 10.1101/2020.06.30.172833v4 on bioRxiv
  3. Version published to 10.1101/2020.06.30.172833v3 on bioRxiv
  4. Version published to 10.1101/2020.06.30.172833v2 on bioRxiv
  5. ScreenIT

    SciScore for 10.1101/2020.06.30.172833: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study protocol to use clinical samples was approved by Institutional Human Ethics Committee SGPGIMS, Lucknow (Ref N.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analyses were performed using software MedCalc for Windows (MedCalc Software, Ostend, Belgium).
    MedCalc
    suggested: (MedCalc, RRID:SCR_015044)

    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.

  6. Version published to 10.1101/2020.06.30.172833v1 on bioRxiv