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Oil Immersed Lossless Total Analysis System (OIL-TAS): Integrated RNA Extraction and Detection for SARS-CoV-2 Testing
Duane S Juang; Terry D Juang; Dawn M Dudley; Christina M Newman; Thomas C Friedrich; David H O'Connor; David J Beebe.
Affiliation
  • Duane S Juang; University of Wisconsin-Madison
  • Terry D Juang; University of Wisconsin-Madison
  • Dawn M Dudley; University of Wisconsin-Madison
  • Christina M Newman; University of Wisconsin-Madison
  • Thomas C Friedrich; University of Wisconsin-Madison
  • David H O'Connor; University of Wisconsin-Madison
  • David J Beebe; University of Wisconsin-Madison
Preprint in English | medRxiv | ID: ppmedrxiv-20204842
ABSTRACT
The coronavirus disease 2019 (COVID-19) pandemic exposed difficulties in scaling current quantitative PCR (qPCR)-based diagnostic methodologies for large-scale infectious disease testing. Bottlenecks include the lengthy multi-step process of nucleic acid extraction followed by qPCR readouts, which require costly instrumentation and infrastructure, as well as reagent and plastic consumable shortages stemming from supply chain constraints. Here we report a novel Oil Immersed Lossless Total Analysis System (OIL-TAS), which integrates RNA extraction and detection onto a single device that is simple, rapid, cost effective, uses minimal supplies and requires reduced infrastructure to perform. We validated the performance of OIL-TAS using contrived samples containing inactivated SARS-CoV-2 viral particles, which show that the assay can reliably detect an input concentration of 10 copies/L and sporadically detect down to 1 copy/L. The OIL-TAS method can serve as a faster, cheaper, and easier-to-deploy alternative to current qPCR-based methods for infectious disease testing.
License
cc_by_nc_nd
Full text: Available Collection: Preprints Database: medRxiv Type of study: Diagnostic study / Prognostic study Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Diagnostic study / Prognostic study Language: English Year: 2020 Document type: Preprint
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