Simpler and faster Covid-19 testing: Strategies to streamline SARS-CoV-2 molecular assays
Nuttada Panpradist,
Qin Wang,
Parker S. Ruth,
Jack H. Kotnik,
Amy K. Oreskovic,
Abraham Miller,
Samuel W.A. Stewart,
Justin Vrana,
Peter D. Han,
Ingrid A. Beck,
Lea M. Starita,
Lisa M. Frenkel,
Barry R. Lutz
Affiliations
Nuttada Panpradist
Department of Bioengineering, University of Washington, Seattle, WA, United States; Global Health of Women, Adolescents, and Children (Global WACh), School of Public Health, University of Washington, Seattle, WA, United States
Qin Wang
Department of Bioengineering, University of Washington, Seattle, WA, United States
Parker S. Ruth
Department of Bioengineering, University of Washington, Seattle, WA, United States; Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, United States
Jack H. Kotnik
Department of Bioengineering, University of Washington, Seattle, WA, United States; Department of Family Medicine, University of Washington, Seattle, WA, United States
Amy K. Oreskovic
Department of Bioengineering, University of Washington, Seattle, WA, United States
Abraham Miller
Department of Bioengineering, University of Washington, Seattle, WA, United States
Samuel W.A. Stewart
Department of Bioengineering, University of Washington, Seattle, WA, United States; Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA, United States
Justin Vrana
Department of Bioengineering, University of Washington, Seattle, WA, United States
Peter D. Han
Department of Genome Sciences, Seattle, WA, United States; Brotman Baty Institute for Precision Medicine, Seattle, WA, United States
Ingrid A. Beck
Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA, United States
Lea M. Starita
Department of Genome Sciences, Seattle, WA, United States; Brotman Baty Institute for Precision Medicine, Seattle, WA, United States
Lisa M. Frenkel
Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA, United States; Departments of Global Health, Medicine, Paediatrics, and Laboratory Medicine, University of Washington, Seattle, WA, United States; Corresponding authors.
Barry R. Lutz
Department of Bioengineering, University of Washington, Seattle, WA, United States; Brotman Baty Institute for Precision Medicine, Seattle, WA, United States; Corresponding authors.
Background: Detection of SARS-CoV-2 infections is important for treatment, isolation of infected and exposed individuals, and contact tracing. RT-qPCR is the “gold-standard” method to sensitively detect SARS-CoV-2 RNA, but most laboratory-developed RT-qPCR assays involve complex steps. Here, we aimed to simplify RT-qPCR assays by streamlining reaction setup, eliminating RNA extraction, and proposing reduced-cost detection workflows that avoid the need for expensive qPCR instruments. Method: A low-cost RT-PCR based “kit” was developed for faster turnaround than the CDC developed protocol. We demonstrated three detection workflows: two that can be deployed in laboratories conducting assays of variable complexity, and one that could be simple enough for point-of-care. Analytical sensitivity was assessed using SARS-CoV-2 RNA spiked in simulated nasal matrix. Clinical performance was evaluated using contrived human nasal matrix (n = 41) and clinical nasal specimens collected from individuals with respiratory symptoms (n = 110). Finding: The analytical sensitivity of the lyophilised RT-PCR was 10 copies/reaction using purified SARS-CoV-2 RNA, and 20 copies/reaction when using direct lysate in simulated nasal matrix. Evaluation of assay performance on contrived human matrix showed 96.7–100% specificity and 100% sensitivity at ≥20 RNA copies. A head-to-head comparison with the standard CDC protocol on clinical specimens showed 83.8–94.6% sensitivity and 96.8–100% specificity. We found 3.6% indeterminate samples (undetected human control), lower than 8.1% with the standard protocol. Interpretation: This preliminary work should support laboratories or commercial entities to develop and expand access to Covid-19 testing. Software guidance development for this assay is ongoing to enable implementation in other settings. Fund: USA NIH R01AI140845 and Seattle Children's Research Institute
