A Rapid Detection of COVID-19 Viral RNA in Human Saliva Using Electrical Double Layer-Gated Field-Effect Transistor-Based Biosensors

Autor: Akhil K. Paulose, Chih‐Cheng Huang, Po‐Hsuan Chen, Adarsh Tripathi, Pin‐Hsuan Chen, Yu‐Shan Huang, Yu‐Lin Wang
Rok vydání: 2021
Předmět:
Zdroj: Advanced Materials Technologies
ISSN: 2365-709X
Popis: In light of the swift outspread and considerable mortality, coronavirus disease 2019 (COVID‐19) necessitates a rapid screening tool and a precise diagnosis. Saliva is considered as an alternative specimen to detect the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) since the viral load is comparable to what are found in a throat and a nasal cavity. The electrical double layer (EDL)‐gated field‐effect transistor‐based biosensor (BioFET) emerges as a promising candidate for salivary COVID‐19 tests due to a high sensitivity, a portable configuration, a label‐free operation, and a matrix insensitivity. In this work, the authors utilize EDL‐gated BioFETs to detect complementary DNAs (cDNAs) and viral RNAs with various testing conditions such as switches of probes, temperature treatments, and matrices. The selectivity is confirmed with cDNA and noncomplementary DNA (ncDNA), exhibiting an eightfold difference in electrical signals. The matrix insensitivity is evaluated, and BioFETs successfully validate the detection of SARS‐CoV‐2 N‐gene RNA down to 1 fm in diluted human saliva with a 95°C‐ and a 25°C‐treatment, respectively. This proposed system has a high potential to be deployed for an on‐site COVID‐19 screening, improving the disease control and benefitting frontline healthcare system.
The electrical double layer‐gated field‐effect transistor‐based biosensors are utilized to detect the severe acute respiratory syndrome coronavirus 2 N‐gene cDNAs and viral RNAs in diluted human saliva, achieving detection limit of ≈1 fm. This proposed system has a high potential to be deployed for on‐site coronavirus disease 2019 screening, improving disease control and benefitting frontline healthcare system.
Databáze: OpenAIRE
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