Rapid Detection of SARS-CoV-2 Antibodies Using Electrochemical Impedance-Based Detector

  1. Mohamed Z. Rashed
  2. Jonathan A. Kopechek
  3. Mariah C. Priddy
  4. Krystal T. Hamorsky
  5. Kenneth E. Palmer
  6. Nikhil Mittal
  7. Joseph Valdez
  8. Joseph Flynn
  9. Stuart J. Williams

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Abstract

Emerging novel human contagious viruses and pathogens put humans at risk of hospitalization and possibly death due to the unavailability of vaccines and drugs which may take years to develop. Coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was classified as a pandemic by theWorld Health Organization and has caused over 550,000 deaths worldwide as of July 2020. Accurate and scalable point-of-care devices would increase screening, diagnosis, and monitoringof COVID-19 patients. Here, we demonstrate rapid label-free electrochemical detection of SARS-CoV-2 antibodies using a commercially available impedance sensing platform. A 16-well plate containing sensing electrodes was pre-coated with receptor binding domain (RBD) of SARS-CoV-2 spike protein, and subsequently tested with samples of anti-SARS-CoV-2 monoclonal antibody CR3022 (0.1 μg/ml, 1.0 μg/ml, 10 μg/ml). Subsequent blinded testing was performed on six serum specimens taken from COVID-19 and non-COVID-19 patients (1:100 dilution factor). The platformwas able to differentiate spikes in impedance measurements from a negative control (1~ milk solution) for all CR3022 samples. Further, successful differentiation and detection of all positive clinical samples from negative control was achieved. Measured impedance values were consistent when compared to standard ELISA test results showing a strong correlation between them (R2 = 0:9). Detection occurs in less than five minutes and the well-based platform provides a simplified and familiar testing interface that can be readily adaptable for use in clinical settings.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.10.20171652: (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

    Antibodies
    SentencesResources
    To initially validate our approach, a monoclonal anti-SARS-CoV-2 antibody (CR3022, Abcam, Cambridge, MA, USA) was tested.
    CR3022
    suggested: None
    Tests with six human serological samples were provided (Serum samples were collected following protocols approved by the University of Louisville Institutional Review Board) and the impedance team was blinded to clinical information about the samples (i.e., whether they were positive or negative for anti-SARS-CoV-2 antibodies as validated by ELISA).
    anti-SARS-CoV-2
    suggested: None
    ELISA was performed by coating immunoplates with of SARS-CoV-2 spike RBD protein overnight, washing three times in PBS-T, blocking for 1 hr, incubating for 30 min with human serological samples diluted 1:100, washing 3 times in PBS-T, and incubating 1 hr with HRP-labeled secondary anti-human IgG antibody.
    anti-human IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    Impedance measurements were exported and analyzed further in MATLAB.
    MATLAB
    suggested: (MATLAB, RRID:SCR_001622)

    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: We detected the following sentences addressing limitations in the study:
    Further, a limitation in applying FET-based sensors is that their performance may be critically obstructed by the presence of multiple ligands and proteins in serum samples. Moreover, in terms of electrical detection, the detection of biomolecules is severely hindered by ionic screening effect caused by high ionic strength of physiological environment (Vu and Chen (2019)). Antibodies against SARS-CoV-2 are generally detected using either the recombinant spike protein or the smaller RBD portion of the spike protein. This study only tested detected binding of antibodies to RBD but similar results would be expected with the recombinant spike protein as well (Premkumar et al. (2020)). Coating the wells with anti-SARS-CoV-2 antibodies instead of spike RBD antigen may enable rapid EIS detection of viral particles in patient samples, although further testing is needed to determine the limit of detection for that approach. There is a need for rapid patient testing due to the highly contagious nature of SARS-CoV-2 particularly when compared to viruses from the same family including, Middle East respiratory syndrome coron-avirus (MERS-CoV) (fatality rate 34%) and severe acute respiratory syndrome coronavirus (SARS-CoV) (mortality rate 11%). This study demonstrated the feasibility of using a quantitative EIS technique with commercially available equipment for rapid and accurate detection of SARS-CoV-2 antibodies at clinically relevant concentrations. This approach could enable rapid scr...

    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.

    About SciScore

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  2. Version published to 10.1101/2020.08.10.20171652v1 on medRxiv