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. 2021 Jan 15:327:128899.
doi: 10.1016/j.snb.2020.128899. Epub 2020 Sep 14.

Ultrasensitive supersandwich-type electrochemical sensor for SARS-CoV-2 from the infected COVID-19 patients using a smartphone

Affiliations

Ultrasensitive supersandwich-type electrochemical sensor for SARS-CoV-2 from the infected COVID-19 patients using a smartphone

Hui Zhao et al. Sens Actuators B Chem. .

Abstract

The recent pandemic outbreak of COVID-19 caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), poses a threat to public health globally. Thus, developing a rapid, accurate, and easy-to-implement diagnostic system for SARS-CoV-2 is crucial for controlling infection sources and monitoring illness progression. Here, we reported an ultrasensitive electrochemical detection technology using calixarene functionalized graphene oxide for targeting RNA of SARS-CoV-2. Based on a supersandwich-type recognition strategy, the technology was confirmed to practicably detect the RNA of SARS-CoV-2 without nucleic acid amplification and reverse-transcription by using a portable electrochemical smartphone. The biosensor showed high specificity and selectivity during in silico analysis and actual testing. A total of 88 RNA extracts from 25 SARS-CoV-2-confirmed patients and eight recovery patients were detected using the biosensor. The detectable ratios (85.5 % and 46.2 %) were higher than those obtained using RT-qPCR (56.5 % and 7.7 %). The limit of detection (LOD) of the clinical specimen was 200 copies/mL, which is the lowest LOD among the published RNA measurement of SARS-CoV-2 to date. Additionally, only two copies (10 μL) of SARS-CoV-2 were required for per assay. Therefore, we developed an ultrasensitive, accurate, and convenient assay for SARS-CoV-2 detection, providing a potential method for point-of-care testing.

Keywords: Calixarene; Electrochemical biosensor; SARS-CoV-2; Smartphone; Supersandwich-type biosensor.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

None
Graphical abstract
Scheme 1
Scheme 1
Schematic representation of SARS-CoV-2 detection using the electrochemical biosensor. (A) Prepare of premix A and B; (B) Process of electrochemical detection using a smartphone.
Fig. 1
Fig. 1
(A) SEM image of Au@Fe3O4; (B) XPS patterns of Au@Fe3O4; (C) XRD patterns of Fe3O4 and Au@Fe3O4; (D) EDS patterns of Au@Fe3O4; (E) Zeta Potential patterns of Au@Fe3O4; (F) The diameter of Au@Fe3O4.
Fig. 2
Fig. 2
(A) SEM image of RGO-SCX8-Au; (B) FT-IR spectra of SCX8, RGO and RGO-SCX8; (C) TGA curves of RGO and RGO-SCX8; (D) XPS patterns of RGO-SCX8-Au; (E) Zeta Potential patterns of RGO-SCX8-Au.
Fig. 3
Fig. 3
The feasibility of the proposed SARS-CoV-2 biosensor. (A) EIS characterization of modified electrodes of SARS-CoV-2 biosensor in 0.1 M PBS (pH 7.2) containing 2.0 mM [Fe(CN)6]3−/4− and 0.1 M KCl. (a) bare screen printing carbon electrode (SPCE); (b) Au@Fe3O4/SPCE; (c) CP/Au@Fe3O4/SPCE; (d) HT/CP/Au@Fe3O4/SPCE; (e) Target/HT/CP/Au@Fe3O4/SPCE; (f) Au@SCX8-TB-RGO-AP-LP-Target/HT/CP/ Au@Fe3O4. (B) DPV curves for the artificial target, one-mismatch target (1 M T) and two-mismatch target (2 M T) of 10-12 M. (C) DPV curves for different concentrations of artificial target for the SARS-CoV-2 biosensor. (D) The resulting calibration plot for log[C] vs. DPV response in the range of 10-17-10-12 M.

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