New Search

Export article
Open Access

Other versions available

Robotic RNA extraction for SARS-CoV-2 surveillance using saliva samples

Jennifer R. Hamilton, Elizabeth C. Stahl, Connor A. Tsuchida, Enrique Lin-Shiao, C. Kimberly Tsui, , , Lea B. Witkowsky, Erica A. Moehle, Shana L. McDevitt,
Show More
Published: 5 August 2021

Abstract: Saliva is an attractive specimen type for asymptomatic surveillance of COVID-19 in large populations due to its ease of collection and its demonstrated utility for detecting RNA from SARS-CoV-2. Multiple saliva-based viral detection protocols use a direct-to-RT-qPCR approach that eliminates nucleic acid extraction but can reduce viral RNA detection sensitivity. To improve test sensitivity while maintaining speed, we developed a robotic nucleic acid extraction method for detecting SARS-CoV-2 RNA in saliva samples with high throughput. Using this assay, the Free Asymptomatic Saliva Testing (IGI FAST) research study on the UC Berkeley campus conducted 11,971 tests on supervised self-collected saliva samples and identified rare positive specimens containing SARS-CoV-2 RNA during a time of low infection prevalence. In an attempt to increase testing capacity, we further adapted our robotic extraction assay to process pooled saliva samples. We also benchmarked our assay against nasopharyngeal swab specimens and found saliva methods require further optimization to match this gold standard. Finally, we designed and validated a RT-qPCR test suitable for saliva self-collection. These results establish a robotic extraction-based procedure for rapid PCR-based saliva testing that is suitable for samples from both symptomatic and asymptomatic individuals.
Keywords: Saliva / SARS CoV 2 / Virus testing / RNA extraction / Gene pool / Robotics / Nucleic acids / COVID 19
Other Versions

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

Share this article

Click here to see the statistics on "PLoS ONE" .
References (14)
    Cited by 4 articles
      Back to Top Top