Sensitive detection and quantification of SARS-CoV-2 in saliva

Autor: Evgeny Izumchenko, Ping Wu, Nishant Agrawal, Jonathan A. Trujillo, Sherin J. Rouhani, Thomas F. Gajewski, Peng Wang, Mustafa Fatih Abasiyanik, Andrew Wang, Bekim Ameti, Kathleen G. Beavis, Cindy Bethel, Bulent Aydogan, Stephen Jumic, Blake Flood, Savaş Tay, Athalia Rachel Pyzer, Rachael Niemiec, Jeremy P. Segal, Jing Lin, Chaojie Zhen, Peter A. Savage, Marian S. Fernando, Vasudha Mishra, Scott Matushek, Sefika Ozcan, Madeline Hartley
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Scientific Reports
medRxiv
ISSN: 2045-2322
Popis: Saliva has significant advantages as a test medium for detection of SARS-CoV-2 infection in patients, such as ease of collection, minimal requirement of supplies and trained personnel, and safety. Comprehensive validation in a large cohort of prospectively collected specimens with unknown SARS-CoV-2 status should be performed to evaluate the potential and limitations of saliva-based testing. We developed a saliva-based testing pipeline for detection of SARS-CoV-2 nucleic acids using real-time reverse transcription PCR (RT-PCR) and droplet digital PCR (ddPCR) readouts, and measured samples from 137 outpatients tested at a curbside testing facility and 29 inpatients hospitalized for COVID-19. These measurements were compared to the nasal swab results for each patient performed by a certified microbiology laboratory. We found that our saliva testing positively detects 100% (RT-PCR) and 93.75% (ddPCR) of curbside patients that were identified as SARS-CoV-2 positive by the Emergency Use Authorization (EUA) certified nasal swab testing assay. Quantification of viral loads by ddPCR revealed an extremely wide range, with 1 million-fold difference between individual patients. Our results demonstrate for both community screening and hospital settings that saliva testing reliability is on par with that of the nasal swabs in detecting infected cases, and has potential for higher sensitivity when combined with ddPCR in detecting low-abundance viral loads that evade traditional testing methods.
Databáze: OpenAIRE