Point-of-care real-time DNA detection device for SARS-CoV-2 from clinical samples

Author:

Presti Damián1ORCID,Bergier Julián1,Ripoll Lucas1,Borio Cristina1,Torchia Gustavo A.2,Bilen Marcos1

Affiliation:

1. Universidad Nacional de Quilmes

2. Centro de Investigaciones Ópticas CONICET—CIC BA - UNLP

Abstract

Since the global pandemic of SARS-CoV-2, people’s health and the economic support of their countries have been seriously affected. It was necessary to develop a low-cost and faster diagnostic tool that allows the evaluation of symptomatic patients. Point-of-care testing and point-of-need testing systems have been recently developed to solve these drawbacks, providing accurate and rapid diagnostics at field level or at the site of outbreaks. In this work, a bio-photonic device has been developed for the diagnosis of COVID-19. The device is used with an isothermal system (Easy Loop Amplification based) for the detection of SARS-CoV-2. The performance of the device was evaluated in the detection of a SARS-CoV-2 RNA sample panel, showing an analytical sensitivity comparable to the reference method of quantitative reverse transcription polymerase chain reaction used commercially. In addition, the device was mainly built with simple and low-cost components; therefore, it is possible to obtain a high-efficiency and low-cost instrument. The device excites the sample to be analyzed with a semiconductor laser with a specific wavelength, thus triggering spontaneous emission of the fluorophore bound to the specific probe. The emitted fluorescence is suitably managed by using interferential filters. Under these conditions, a signal is registered and, depending on this level, defines the case as positive or negative. All the analysis is done autonomously inside the developed device through an integrated control system, and it is connected to a portable device to show the results wirelessly.

Funder

Universidad Nacional de Quilmes

Agencia Nacional de Promoción Científica y Tecnológica

Publisher

Optica Publishing Group

Subject

Computer Vision and Pattern Recognition,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

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