Aerosol-jet-printed graphene electrochemical immunosensors for rapid and label-free detection of SARS-CoV-2 in saliva.
Cícero C PolaSonal V RangnekarRobert SheetsBeata M SzydlowskaJulia R DowningKshama W ParateShay G WallaceDaphne TsaiMark C HersamCarmen L GomesJonathan C ClaussenPublished in: 2d materials (2022)
Rapid, inexpensive, and easy-to-use coronavirus disease 2019 (COVID-19) home tests are key tools in addition to vaccines in the world-wide fight to eliminate national and local shutdowns. However, currently available tests for SARS-CoV-2, the virus that causes COVID-19, are too expensive, painful, and irritating, or not sufficiently sensitive for routine, accurate home testing. Herein, we employ custom-formulated graphene inks and aerosol jet printing (AJP) to create a rapid electrochemical immunosensor for direct detection of SARS-CoV-2 Spike Receptor-Binding Domain (RBD) in saliva samples acquired non-invasively. This sensor demonstrated limits of detection that are considerably lower than most commercial SARS-CoV-2 antigen tests (22.91 ± 4.72 pg/mL for Spike RBD and 110.38 ± 9.00 pg/mL for Spike S1) as well as fast response time (~30 mins), which was facilitated by the functionalization of printed graphene electrodes in a single-step with SARS-CoV-2 polyclonal antibody through the carbodiimide reaction without the need for nanoparticle functionalization or secondary antibody or metallic nanoparticle labels. This immunosensor presents a wide linear sensing range from 1 to 1000 ng/mL and does not react with other coexisting influenza viruses such as H1N1 hemagglutinin. By combining high-yield graphene ink synthesis, automated printing, high antigen selectivity, and rapid testing capability, this work offers a promising alternative to current SARS-CoV-2 antigen tests.
Keyphrases
- sars cov
- label free
- loop mediated isothermal amplification
- respiratory syndrome coronavirus
- coronavirus disease
- sensitive detection
- carbon nanotubes
- healthcare
- room temperature
- high frequency
- machine learning
- walled carbon nanotubes
- deep learning
- clinical practice
- high throughput
- water soluble
- simultaneous determination