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Single-strand RPA for rapid and sensitive detection of SARS-CoV-2 RNA.
Kim, Youngeun; Yaseen, Adam B; Kishi, Jocelyn Y; Hong, Fan; Saka, Sinem K; Sheng, Kuanwei; Gopalkrishnan, Nikhil; Schaus, Thomas E; Yin, Peng.
Afiliação
  • Kim Y; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115.
  • Yaseen AB; Department of Systems Biology, Harvard Medical School, Boston, MA 02115.
  • Kishi JY; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115.
  • Hong F; Department of Systems Biology, Harvard Medical School, Boston, MA 02115.
  • Saka SK; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115.
  • Sheng K; Department of Systems Biology, Harvard Medical School, Boston, MA 02115.
  • Gopalkrishnan N; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115.
  • Schaus TE; Department of Systems Biology, Harvard Medical School, Boston, MA 02115.
  • Yin P; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115.
medRxiv ; 2020 Oct 25.
Article em En | MEDLINE | ID: mdl-32839783
ABSTRACT
We report the single-strand Recombinase Polymerase Amplification (ssRPA) method, which merges the fast, isothermal amplification of RPA with subsequent rapid conversion of the double-strand DNA amplicon to single strands, and hence enables facile hybridization-based, high-specificity readout. We demonstrate the utility of ssRPA for sensitive and rapid (4 copies per 50 µL reaction within 10 min, or 8 copies within 8 min) visual detection of SARS-CoV-2 RNA spiked samples, as well as clinical saliva and nasopharyngeal swabs in VTM or water, on lateral flow devices. The ssRPA method promises rapid, sensitive, and accessible RNA detection to facilitate mass testing in the COVID-19 pandemic.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article