A Robust, Safe, and Scalable Magnetic Nanoparticle Workflow for RNA Extraction of Pathogens from Clinical and Wastewater Samples

  1. Gerardo Ramos‐Mandujano
  2. Rahul Salunke
  3. Sara Mfarrej
  4. Andri Taruna Rachmadi
  5. Sharif Hala
  6. Jinna Xu
  7. Fadwa S. Alofi
  8. Asim Khogeer
  9. Anwar M. Hashem
  10. Naif A. M. Almontashiri
  11. Afrah Alsomali
  12. Digambar B. Shinde
  13. Samir Hamdan
  14. Pei‐Ying Hong
  15. Arnab Pain
  16. Mo Li

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Abstract

Molecular diagnosis and surveillance of pathogens such as SARS‐CoV‐2 depend on nucleic acid isolation. Pandemics at the scale of COVID‐19 can cause a global shortage of proprietary commercial reagents and BSL‐2 laboratories to safely perform testing. Therefore, alternative solutions are urgently needed to address these challenges. An open‐source method, m agnetic‐nanoparticle‐ a ided v iral R NA i solation from c ontagious s amples (MAVRICS), built upon readily available reagents, and easily assembled in any basically equipped laboratory, is thus developed. The performance of MAVRICS is evaluated using validated pathogen detection assays and real‐world and contrived samples. Unlike conventional methods, MAVRICS works directly in samples inactivated in phenol‐chloroform (e.g., TRIzol), thus allowing infectious samples to be handled safely without biocontainment facilities. MAVRICS allows wastewater biomass immobilized on membranes to be directly inactivated and lysed in TRIzol followed by RNA extraction by magnetic nanoparticles, thereby greatly reducing biohazard risk and simplifying processing procedures. Using 39 COVID‐19 patient samples and two wastewater samples, it is shown that MAVRICS rivals commercial kits in detection of SARS‐CoV‐2, influenza viruses, and respiratory syncytial virus. Therefore, MAVRICS is safe, fast, and scalable. It is field‐deployable with minimal equipment requirements and could become an enabling technology for widespread testing and wastewater monitoring of diverse pathogens.

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  1. Version published to 10.1002/gch2.202000068
  2. Version published to 10.1101/2020.06.28.20141945v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2020.06.28.20141945: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The use of clinical samples in this study is approved by the institutional review board (IRB# H-02-K-076-0320-279) of MOH and KAUST Institutional Biosafety and Bioethics Committee (IBEC).
    IACUC: The use of clinical samples in this study is approved by the institutional review board (IRB# H-02-K-076-0320-279) of MOH and KAUST Institutional Biosafety and Bioethics Committee (IBEC).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Adjust pH with HCl (pH < 6.5) and adjust the volume with water to 50 ml.
    Adjust
    suggested: (ADJUST, RRID:SCR_009526)

    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.

  4. Version published to 10.1101/2020.06.28.20141945v1 on medRxiv