An integrated lab-on-a-chip device for RNA extraction, amplification and CRISPR-Cas12a-assisted detection for COVID-19 screening in resource-limited settings

  1. Bongkot Ngamsom
  2. Alexander Iles
  3. Moses Kamita
  4. Racheal Kimani
  5. Pablo Rodriguez-Mateos
  6. Mary Mungai
  7. Charlotte E. Dyer
  8. Cheryl Walter
  9. Jesse Gitaka
  10. Nicole Pamme

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Abstract

In response to the ongoing COVID-19 pandemic and disparities of vaccination coverage in low- and middle-income countries, it is vital to adopt a widespread testing and screening programme, combined with contact tracing, to monitor and effectively control the infection dispersion in areas where medical resources are limited. This work presents a lab-on-a-chip platform, namely “IFAST-CRISPR”, as an affordable, rapid and high-precision molecular diagnostic means for SARS-CoV-2 detection. The herein proposed “sample-to-answer” platform integrates RNA extraction, amplification and CRISPR-Cas-based detection with lateral flow readout in one device. The microscale dimensions of the device containing immiscible liquids, coupled with the use of silica paramagnetic beads and GuHCl, streamline sample preparation, including RNA concentration, extraction and purification, in 15 min with minimal hands-on steps. By combining RT-LAMP with CRISPR-Cas12 assays targeting the nucleoprotein (N) gene, visual identification of ≥ 470 copies mL -1 genomic SARS-CoV-2 samples was achieved in 45 min, with no cross-reactivity towards HCoV-OC43 nor H1N1. On-chip assays showed the ability to isolate and detect SARS-CoV-2 from 1,000 genome copies mL -1 of replication-deficient viral particles in 1 h. This simple, affordable and integrated platform demonstrated a visual, faster, and yet specificity and sensitivity-comparable alternative to the costly gold-standard RT-PCR assay, requiring only a simple heating source. Further investigations on multiplexing and direct interfacing of the accessible Swan-brand cigarette filter for saliva sample collection could provide a complete work flow for COVID-19 diagnostics from saliva samples suitable for low-resource settings.

Article activity feed

  1. Rapid Reviews Infectious Diseases

    Mehmet Ozsoz, Abdullahi Umar Ibrahim, Fahreddin Palaz

    Review 2: "An integrated lab-on-a-chip device for RNA extraction, amplification and CRISPR-Cas12a-assisted detection for COVID-19 screening in resource-limited settings"

    This preprint presents a lab-on-a-chip platform for CRISPR-Cas-based SARS-CoV-2 viral detection. Reviewers found the strength of evidence as potentially informative for a proof-of-concept demonstration. Further work is needed to validate the device performance outside of the lab.

  2. Rapid Reviews Infectious Diseases

    Margaret Ip

    Review 1: "An integrated lab-on-a-chip device for RNA extraction, amplification and CRISPR-Cas12a-assisted detection for COVID-19 screening in resource-limited settings"

    This preprint presents a lab-on-a-chip platform for CRISPR-Cas-based SARS-CoV-2 viral detection. Reviewers found the strength of evidence as potentially informative for a proof-of-concept demonstration. Further work is needed to validate the device performance outside of the lab.

  3. Rapid Reviews Infectious Diseases

    Strength of evidence

    Reviewers: Margaret Ip (The Chinese University of Hong Kong) | 📒📒📒◻️◻️
    Mehmet Ozsoz (Near East University), Abdullahi Umar İbrahim (Near East University), Fahreddin Palaz (Hacettepe University) | 📗📗📗📗◻️

  4. ScreenIT

    SciScore for 10.1101/2022.01.06.22268835: (What is this?)

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

    Table 1: Rigor

    EthicsIACUC: Ethical Approval: This study was approved by the Mount Kenya University Independent Ethical Review Committee (
    Consent: Nasopharyngeal swab and saliva samples were collected from participants with their written informed consent after the nature and possible consequences of the study had been fully explained to them. Materials and reagents: Genomic SARS-CoV-2 RNA (2019-nCoV/USA-WA1/2020, ATCC VR-1986D), HCoV-OC43 (ATCC VR-1558D) and H1N1 (ATCC VR-1736D) RNAs were purchased from LGC standards, UK. SARS-CoV-2
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Nasopharyngeal swab and saliva samples were collected from participants with their written informed consent after the nature and possible consequences of the study had been fully explained to them. Materials and reagents: Genomic SARS-CoV-2 RNA (2019-nCoV/USA-WA1/2020, ATCC VR-1986D), HCoV-OC43 (ATCC VR-1558D) and H1N1 (ATCC VR-1736D) RNAs were purchased from LGC standards, UK. SARS-CoV-2
    HCoV-OC43
    suggested: None
    Software and Algorithms
    SentencesResources
    RT-LAMP products were identified via agarose gel electrophoresis (1 %w/v agarose, 1xTAE buffer, 80 V, 45 min) and the results analyzed using a molecular imager (Chemidoc XRS+, BioRAD).
    BioRAD
    suggested: None

    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.

    Results from scite Reference Check: We found no unreliable references.

    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.

  5. Version published to 10.1101/2022.01.06.22268835v1 on medRxiv