C-MEMS-derived glassy carbon electrochemical biosensors for rapid detection of SARS-CoV-2 spike protein

According to a World Health Organization (WHO) report, the world has experienced more than 766 million cases of positive SARS-CoV-2 infection and more than 6.9 million deaths due to COVID through May 2023. The WHO declared a pandemic due to the rapid spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, and the fight against this pandemic is not over yet. Important reasons for virus spread include the lack of detection kits, appropriate detection techniques, delay in detection, asymptomatic cases and failure in mass screening. In the last 3 years, several researchers and medical companies have introduced successful test kits to detect the infection of symptomatic patients in real time, which was necessary to monitor the spread. However, it is also important to have information on asymptomatic cases, which can be obtained by antibody testing for the SARS-CoV-2 virus. In this work, we developed a simple, advantageous immobilization procedure for rapidly detecting the SARS-CoV-2 spike protein. Carbon-MEMS-derived glassy carbon (GC) is used as the sensor electrode, and the detection is based on covalently linking the SARS-CoV-2 antibody to the GC surface. Glutaraldehyde was used as a cross-linker between the antibody and glassy carbon electrode (GCE). The binding was investigated using Fourier transform infrared spectroscopy (FTIR) characterization and cyclic voltammetric (CV) analysis. Electrochemical impedance spectroscopy (EIS) was utilized to measure the change in total impedance before and after incubation of the SARS-CoV-2 antibody with various concentrations of SARS-CoV-2 spike protein. The developed sensor can sense 1 fg/ml to 1 µg/ml SARS-CoV-2 spike protein. This detection is label-free, and the chances of false positives are minimal. The calculated LOD was ~31 copies of viral RNA/mL. The coefficient of variation (CV) number is calculated from EIS data at 100 Hz, which is found to be 0.398%. The developed sensor may be used for mass screening because it is cost-effective.