Unified platform for genetic and serological detection of COVID-19 with single-molecule technology

  1. Noa Furth
  2. Shay Shilo
  3. Niv Cohen
  4. Nir Erez
  5. Vadim Fedyuk
  6. Alexander M. Schrager
  7. Adina Weinberger
  8. Amiel A. Dror
  9. Asaf Zigron
  10. Mona Shehadeh
  11. Eyal Sela
  12. Samer Srouji
  13. Sharon Amit
  14. Itzchak Levy
  15. Eran Segal
  16. Rony Dahan
  17. Dan Jones
  18. Daniel C. Douek
  19. Efrat Shema

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Abstract

The COVID-19 pandemic raises the need for diverse diagnostic approaches to rapidly detect different stages of viral infection. The flexible and quantitative nature of single-molecule imaging technology renders it optimal for development of new diagnostic tools. Here we present a proof-of-concept for a single-molecule based, enzyme-free assay for detection of SARS-CoV-2. The unified platform we developed allows direct detection of the viral genetic material from patients’ samples, as well as their immune response consisting of IgG and IgM antibodies. Thus, it establishes a platform for diagnostics of COVID-19, which could also be adjusted to diagnose additional pathogens.

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  1. Version published to 10.1101/2021.05.25.21257501v2 on medRxiv
  2. Version published to 10.1371/journal.pone.0255096
  3. ScreenIT

    SciScore for 10.1101/2021.05.25.21257501: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: This study was granted exemption from Institutional Review Boards (IRB) approval for utilizing discarded pooled RNA samples, anonymized and de-identified, for single-molecule detection of SARS-CoV-2 RNA with a multiplex approach.
    Consent: All samples were coded and de-identified as specified in the informed consent and the NIH investigator attestation addressing the protection of human subjects and approved by the NIH Office of Human Subjects Research Protections (OHSRP).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Seropositivity of these samples had been confirmed by MDA with a commercial antibody test (Abbot, SARS-CoV-2 IgG, ref. 6R86-22/6R86-32).
    SARS-CoV-2 IgG
    suggested: None
    6R86-22/6R86-32
    suggested: None
    Secondary anti-human IgG1 and IgM labeled antibodies (Rabbit monoclonal [H26-10] Anti-Human IgG1 H&L, Alexa Fluor® 647, Abcam, AB-ab200623 and Rabbit Anti-Human IgM mu chain (Alexa Fluor® 488), Abcam, AB-ab150189) were diluted 1:10,000 and added on the surface for 30 minutes incubation..
    anti-human IgG1
    suggested: (Abcam Cat# ab28056, RRID:AB_2040942)
    IgM labeled antibodies
    suggested: None
    Anti-Human IgM
    suggested: None
    After 2 hours incubation at room temperature, the plate was washed (X3, 5 minutes incubation for each wash) with Tween 0.05% in PBS. 20ul goat anti-human-HRP (Jackson 109-035-088) secondary antibody, diluted 1:2,500 in 2% FCS, was added to each well.
    X3
    suggested: None
    anti-human-HRP
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    For synthetic COVID-19 DNA, cellular RNA extracted from HEK293 cells were added in a final concentration of 0.1ng/ul.
    HEK293
    suggested: CLS Cat# 300192/p777_HEK293, RRID:CVCL_0045)
    Software and Algorithms
    SentencesResources
    Those parameters were coded to a MATLAB script that scanned the reverse complement sequence of the SARS-CoV-2 genome (NC_045512.2) in sliding windows of 25-40 nt.
    MATLAB
    suggested: (MATLAB, RRID:SCR_001622)
    The probe pair dataset attributes every probe in the pair with its coordinates, length, Tm, and BLAST hits.
    BLAST
    suggested: (BLASTX, RRID:SCR_001653)
    Genetic test sample preparation: Synthetic COVID-19 DNA in different concentrations or 10ul RNA extracted from swab samples were mixed with 1nM capture probes, 0.5nM detection probes, 0.3ul Rnase inhibitor (SUPERaseIn RNase Inhibitor, AM2694, ThermoFisher), and 2X SSC buffer in a final volume of 14.8ul.
    ThermoFisher
    suggested: (ThermoFisher; SL 8; Centrifuge, RRID:SCR_020809)

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.

  4. Version published to 10.1101/2021.05.25.21257501v1 on medRxiv