Simpler and faster Covid-19 testing: Strategies to streamline SARS-CoV-2 molecular assays.

EBioMedicine(2021)

引用 24|浏览6
暂无评分
摘要
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.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要