Direct detection of SARS-CoV-2 using non-commercial RT-LAMP reagents on heat-inactivated samples

  1. Alisa Alekseenko
  2. Donal Barrett
  3. Yerma Pareja-Sanchez
  4. Rebecca J. Howard
  5. Emilia Strandback
  6. Henry Ampah-Korsah
  7. Urška Rovšnik
  8. Silvia Zuniga-Veliz
  9. Alexander Klenov
  10. Jayshna Malloo
  11. Shenglong Ye
  12. Xiyang Liu
  13. Björn Reinius
  14. Simon J. Elsässer
  15. Tomas Nyman
  16. Gustaf Sandh
  17. Xiushan Yin
  18. Vicent Pelechano

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Abstract

RT-LAMP detection of SARS-CoV-2 has been shown to be a valuable approach to scale up COVID-19 diagnostics and thus contribute to limiting the spread of the disease. Here we present the optimization of highly cost-effective in-house produced enzymes, and we benchmark their performance against commercial alternatives. We explore the compatibility between multiple DNA polymerases with high strand-displacement activity and thermostable reverse transcriptases required for RT-LAMP. We optimize reaction conditions and demonstrate their applicability using both synthetic RNA and clinical patient samples. Finally, we validate the optimized RT-LAMP assay for the detection of SARS-CoV-2 in unextracted heat-inactivated nasopharyngeal samples from 184 patients. We anticipate that optimized and affordable reagents for RT-LAMP will facilitate the expansion of SARS-CoV-2 testing globally, especially in sites and settings where the need for large scale testing cannot be met by commercial alternatives.

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  1. Version published to 10.1038/s41598-020-80352-8
  2. ScreenIT

    SciScore for 10.1101/2020.08.22.20179507: (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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2020.08.22.20179507v1 on medRxiv