Field-deployable, rapid diagnostic testing of saliva for SARS-CoV-2

  1. Shan Wei
  2. Hemant Suryawanshi
  3. Alexandre Djandji
  4. Esther Kohl
  5. Stephanie Morgan
  6. Eldad A. Hod
  7. Susan Whittier
  8. Kevin Roth
  9. Raymond Yeh
  10. Juan Carlos Alejaldre
  11. Elaine Fleck
  12. Stephen Ferrara
  13. Daniel Hercz
  14. David Andrews
  15. Lilly Lee
  16. Kristopher A. Hendershot
  17. Joshua Goldstein
  18. Yousin Suh
  19. Mahesh Mansukhani
  20. Zev Williams

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Abstract

To safely re-open economies and prevent future outbreaks, rapid, frequent, point-of-need, SARS-CoV-2 diagnostic testing is necessary. However, existing field-deployable COVID-19 testing methods require the use of uncomfortable swabs and trained providers in PPE, while saliva-based methods must be transported to high complexity laboratories for testing. Here, we report the development and clinical validation of H igh- P erformance L oop-mediated isothermal Amp lification (HP-LAMP), a rapid, saliva-based, SARS-CoV-2 test with a limit of detection of 1.4 copies of virus per µl of saliva and a sensitivity and specificity with clinical samples of > 96%, on par with traditional RT-PCR based methods using swabs, but can deliver results using only a single fluid transfer step and simple heat block. Testing of 120 patient samples in 40 pools comprised of 5 patient samples each with either all negative or a single positive patient sample was 100% accurate. Thus, HP-LAMP may enable rapid and accurate results in the field using saliva, without need of a high-complexity laboratory.

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  1. Version published to 10.1038/s41598-021-84792-8
  2. ScreenIT

    SciScore for 10.1101/2020.06.13.20129841: (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

    No key resources detected.

    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.

  3. ScreenIT

    SciScore for 10.1101/2020.06.13.20129841: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementThis portion of our study was reviewed and approved by the Columbia University IRB ( #AAAS9893 ) and all methods were carried out in accordance with relevant guidelines and regulations All study subjects signed informed consent prior to participating .RandomizationWe then tested saliva from the 4 positive , 2 indeterminate and 12 randomly selected negative samples using HP-LAMP as well as undergoing RNA extraction and RT-PCR .Blindingnot detected.Power Analysisnot detected.Sex as a biological variablenot detected.Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    HCoV-NL63 , HCoV-OC43 and HCoV-229E ) to ensure no cross-reactivity .
    HCoV-NL63
    suggested: CVCL_RW88

    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 OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2020.06.13.20129841v1 on medRxiv