An internet of things-based point-of-care device for direct reverse-transcription-loop mediated isothermal amplification to identify SARS-CoV-2.
Biosens Bioelectron
; 195: 113655, 2022 Jan 01.
Article
in English
| MEDLINE | ID: covidwho-1432989
ABSTRACT
Rapid and accurate testing tools for SARS-CoV-2 detection are urgently needed to prevent the spreading of the virus and to take timely governmental actions. Internet of things (IoT)-based diagnostic devices would be an ideal platform for point-of-care (POC) screening of COVID-19 and ubiquitous healthcare monitoring for patients. Herein, we present an advanced IoT-based POC device for real-time direct reverse-transcription-loop mediated isothermal amplification assay to detect SARS-CoV-2. The diagnostic system is miniaturized (10 cm [height] × 9 cm [width] × 5.5 cm [length]) and lightweight (320 g), which can be operated with a portable battery and a smartphone. Once a liquid sample was loaded into an integrated microfluidic chip, a series of sample lysis, nucleic amplification, and real-time monitoring of the fluorescent signals of amplicons were automatically performed. Four reaction chambers were patterned on the chip, targeting As1e, N, E genes and a negative control, so multiple genes of SARS-CoV-2 could be simultaneously analyzed. The fluorescence intensities in each chamber were measured by a CMOS camera upon excitation with a 488 nm LED light source. The recorded data were processed by a microprocessor inside the IoT-based POC device and transferred and displayed on the wirelessly connected smartphone in real-time. The positive results could be obtained using three primer sets of SARS-CoV-2 with a limit of detection of 2 × 101 genome copies/µL, and the clinical sample of SARS-CoV-2 was successfully analyzed with high sensitivity and accuracy. Our platform could provide an advanced molecular diagnostic tool to test SARS-CoV-2 anytime and anywhere.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Biosensing Techniques
/
Internet of Things
/
COVID-19
Type of study:
Diagnostic study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Biosens Bioelectron
Journal subject:
Biotechnology
Year:
2022
Document Type:
Article
Affiliation country:
J.bios.2021.113655
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