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Swab-Seq: A high-throughput platform for massively scaled up SARS-CoV-2 testing.
Bloom, Joshua S; Sathe, Laila; Munugala, Chetan; Jones, Eric M; Gasperini, Molly; Lubock, Nathan B; Yarza, Fauna; Thompson, Erin M; Kovary, Kyle M; Park, Jimin; Marquette, Dawn; Kay, Stephania; Lucas, Mark; Love, TreQuan; Booeshaghi, A Sina; Brandenberg, Oliver F; Guo, Longhua; Boocock, James; Hochman, Myles; Simpkins, Scott W; Lin, Isabella; LaPierre, Nathan; Hong, Duke; Zhang, Yi; Oland, Gabriel; Choe, Bianca Judy; Chandrasekaran, Sukantha; Hilt, Evann E; Butte, Manish J; Damoiseaux, Robert; Kravit, Clifford; Cooper, Aaron R; Yin, Yi; Pachter, Lior; Garner, Omai B; Flint, Jonathan; Eskin, Eleazar; Luo, Chongyuan; Kosuri, Sriram; Kruglyak, Leonid; Arboleda, Valerie A.
Afiliación
  • Bloom JS; Department of Human Genetics, David Geffen School of Medicine, UCLA.
  • Sathe L; Howard Hughes Medical Institute, HHMI.
  • Munugala C; Octant, Inc.
  • Jones EM; Department of Pathology & Laboratory Medicine, David Geffen School of Medicine, UCLA.
  • Gasperini M; Department of Human Genetics, David Geffen School of Medicine, UCLA.
  • Lubock NB; Howard Hughes Medical Institute, HHMI.
  • Yarza F; Octant, Inc.
  • Thompson EM; Octant, Inc.
  • Kovary KM; Octant, Inc.
  • Park J; Octant, Inc.
  • Marquette D; Octant, Inc.
  • Kay S; Octant, Inc.
  • Lucas M; Octant, Inc.
  • Love T; Department of Computational Medicine, David Geffen School of Medicine, UCLA.
  • Booeshaghi AS; Department of Computational Medicine, David Geffen School of Medicine, UCLA.
  • Brandenberg OF; Department of Computational Medicine, David Geffen School of Medicine, UCLA.
  • Guo L; Department of Computational Medicine, David Geffen School of Medicine, UCLA.
  • Boocock J; Department of Mechanical Engineering, Caltech.
  • Hochman M; Department of Human Genetics, David Geffen School of Medicine, UCLA.
  • Simpkins SW; Howard Hughes Medical Institute, HHMI.
  • Lin I; Department of Biological Chemistry, David Geffen School of Medicine, UCLA.
  • LaPierre N; Department of Human Genetics, David Geffen School of Medicine, UCLA.
  • Hong D; Howard Hughes Medical Institute, HHMI.
  • Zhang Y; Department of Biological Chemistry, David Geffen School of Medicine, UCLA.
  • Oland G; Department of Human Genetics, David Geffen School of Medicine, UCLA.
  • Choe BJ; Howard Hughes Medical Institute, HHMI.
  • Chandrasekaran S; Department of Biological Chemistry, David Geffen School of Medicine, UCLA.
  • Hilt EE; Octant, Inc.
  • Butte MJ; Octant, Inc.
  • Damoiseaux R; Department of Human Genetics, David Geffen School of Medicine, UCLA.
  • Kravit C; Department of Pathology & Laboratory Medicine, David Geffen School of Medicine, UCLA.
  • Cooper AR; Department of Computer Science, Samueli School of Engineering, UCLA.
  • Yin Y; Department of Computational Medicine, David Geffen School of Medicine, UCLA.
  • Pachter L; Department of Human Genetics, David Geffen School of Medicine, UCLA.
  • Garner OB; Department of Surgery, David Geffen School of Medicine, UCLA.
  • Flint J; Department of Emergency Medicine, David Geffen School of Medicine, UCLA.
  • Eskin E; Department of Pathology & Laboratory Medicine, David Geffen School of Medicine, UCLA.
  • Luo C; Department of Pathology & Laboratory Medicine, David Geffen School of Medicine, UCLA.
  • Kosuri S; Department of Pediatrics, David Geffen School of Medicine, UCLA.
  • Kruglyak L; Department of Microbiology, Immunology & Molecular Genetics, David Geffen School of Medicine, UCLA.
  • Arboleda VA; California NanoSystems Institute, UCLA.
medRxiv ; 2021 Mar 09.
Article en En | MEDLINE | ID: mdl-32909008
The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is due to the high rates of transmission by individuals who are asymptomatic at the time of transmission1,2. Frequent, widespread testing of the asymptomatic population for SARS-CoV-2 is essential to suppress viral transmission. Despite increases in testing capacity, multiple challenges remain in deploying traditional reverse transcription and quantitative PCR (RT-qPCR) tests at the scale required for population screening of asymptomatic individuals. We have developed SwabSeq, a high-throughput testing platform for SARS-CoV-2 that uses next-generation sequencing as a readout. SwabSeq employs sample-specific molecular barcodes to enable thousands of samples to be combined and simultaneously analyzed for the presence or absence of SARS-CoV-2 in a single run. Importantly, SwabSeq incorporates an in vitro RNA standard that mimics the viral amplicon, but can be distinguished by sequencing. This standard allows for end-point rather than quantitative PCR, improves quantitation, reduces requirements for automation and sample-to-sample normalization, enables purification-free detection, and gives better ability to call true negatives. After setting up SwabSeq in a high-complexity CLIA laboratory, we performed more than 80,000 tests for COVID-19 in less than two months, confirming in a real world setting that SwabSeq inexpensively delivers highly sensitive and specific results at scale, with a turn-around of less than 24 hours. Our clinical laboratory uses SwabSeq to test both nasal and saliva samples without RNA extraction, while maintaining analytical sensitivity comparable to or better than traditional RT-qPCR tests. Moving forward, SwabSeq can rapidly scale up testing to mitigate devastating spread of novel pathogens.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: MedRxiv Año: 2021 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: MedRxiv Año: 2021 Tipo del documento: Article