Point-of-care detection of SARS-CoV-2 in nasopharyngeal swab samples using an integrated smartphone-based centrifugal microfluidic platform

Autor: Aman Russom, Gustaf Sandh, Donal Barrett, Noa Lapins, Soares Rrg, Ahmad Saleem Akhtar, Pelechano, Xiushan Yin, Inês F. Pinto
Rok vydání: 2020
Předmět:
DOI: 10.1101/2020.11.04.20225888
Popis: With its origin estimated around December 2019 in Wuhan, China, the ongoing 2020 SARS-CoV-2 pandemic is a major global health challenge, resulting in more than 45 million infections and 1.2 million deaths. The demand for scalable, rapid and sensitive viral diagnostics is thus particularly pressing at present to help contain the rapid spread of infection and prevent overwhelming the capacity of health systems. While high-income countries have managed to rapidly expand diagnostic capacities, such is not the case in resource-limited settings of low- to medium-income countries.Aiming at developing cost-effective viral load detection systems for point-of-care COVID-19 diagnostics in resource-limited and resource-rich settings alike, we report the development of an integrated modular centrifugal microfluidic platform to perform loop-mediated isothermal amplification (LAMP) of viral RNA directly from heat-inactivated nasopharyngeal swab samples. The discs were pre-packed with dried n-benzyl-n-methylethanolamine modified agarose beads used as a versatile post-nucleic acid amplification signal enhancement strategy, allowing fluorescence detection via a smartphone camera and simple optics. The platform provided sample-to-answer analysis within 1 hour from sample collection and a detection limit between 100 and 1000 RNA copies in 10 μL reaction volume. Furthermore, direct detection of non-extracted SARS-CoV-2 RNA in nasopharyngeal swab samples from patients with Ct values below 26 (n=25 plus 6 PCR negative samples) was achieved with ∼94% sensitivity and 100% specificity, thus being fit-for-purpose to diagnose patients with a high risk of viral transmission. These results show significant promise towards bringing routine point-of-care COVID-19 diagnostics closer to resource-limited settings.
Databáze: OpenAIRE