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A Multiplexed, Next Generation Sequencing Platform for High-Throughput Detection of SARS-CoV-2
Marie-Ming Aynaud; J. Javier Hernandez; Seda Barutcu; Ulrich Braunschweig; Kin Chan; Joel D Pearson; Daniel Trcka; Suzanna L Prosser; Jaeyoun Kim; Miriam Barrios-Rodiles; Mark Jen; Siyuan Song; Jess Shen; Christine Bruce; Bryn Hazlett; Susan Poutanen; Lilliana Attisano; Rod Bremner; Benjamin Blencowe; Tony Mazzulli; Hong Han; Laurence Pelletier; Jeffrey L Wrana.
Afiliação
  • Marie-Ming Aynaud; Lunenfeld Tanenbaum Research Institute - Mount Sinai Hospital
  • J. Javier Hernandez; Lunenfeld Tanenbaum Research Institute - Mount Sinai Hospital
  • Seda Barutcu; Lunenfeld Tanenbaum Research Institute - Mount Sinai Hospital
  • Ulrich Braunschweig; Donnelly Centre for Cellular and Biomolecular Research, University of Toronto
  • Kin Chan; Lunenfeld Tanenbaum Research Institute - Mount Sinai Hospital
  • Joel D Pearson; Lunenfeld Tanenbaum Research Institute - Mount Sinai Hospital
  • Daniel Trcka; Lunenfeld Tanenbaum Research Institute - Mount Sinai Hospital
  • Suzanna L Prosser; Lunenfeld Tanenbaum Research Institute - Mount Sinai Hospital
  • Jaeyoun Kim; Lunenfeld Tanenbaum Research Institute - Mount Sinai Hospital
  • Miriam Barrios-Rodiles; Lunenfeld Tanenbaum Research Institute - Mount Sinai Hospital
  • Mark Jen; Lunenfeld Tanenbaum Research Institute - Mount Sinai Hospital
  • Siyuan Song; Donnelly Centre for Cellular and Biomolecular Research, University of Toronto
  • Jess Shen; Lunenfeld Tanenbaum Research Institute - Mount Sinai Hospital
  • Christine Bruce; Mount Sinai Hospital
  • Bryn Hazlett; Mount Sinai Hospital
  • Susan Poutanen; Mount Sinai Hospital
  • Lilliana Attisano; Donnelly Centre for Cellular and Biomolecular Research, University of Toronto
  • Rod Bremner; Lunefeld Tanenbaum Research Institute - Mount Sinai Hospital
  • Benjamin Blencowe; Donnelly Centre for Cellular and Biomolecular Research, University of Toronto
  • Tony Mazzulli; Mount Sinai Hospital
  • Hong Han; Donnelly Centre for Cellular and Biomolecular Research, University of Toronto
  • Laurence Pelletier; Lunenfeld Tanenbaum Research Institute - Mount Sinai Hospital
  • Jeffrey L Wrana; Lunenfeld Tanenbaum Research Institute - Mount Sinai Hospital
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20212712
Artigo de periódico
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ABSTRACT
Population scale sweeps of viral pathogens, such as SARS-CoV-2, that incorporate large numbers of asymptomatic or mild symptom patients present unique challenges for public health agencies trying to manage both travel and local spread. Physical distancing is the current major strategy to suppress spread of the disease, but with enormous socio-economic costs. However, modelling and studies in isolated jurisdictions suggest that active population surveillance through systematic molecular diagnostics, combined with contact tracing and focused quarantining can significantly suppress disease spread1-3 and has significantly impacted disease transmission rates, the number of infected people, and prevented saturation of the healthcare system4-7. However, reliable systems allowing for parallel testing of 10-100,000s of patients in larger urban environments have not yet been employed. Here we describe "COVID-19 screening using Systematic Parallel Analysis of RNA coupled to Sequencing" (C19-SPAR-Seq), a scalable, multiplexed, readily automated next generation sequencing (NGS) platform8 that is capable of analyzing tens of thousands of COVID-19 patient samples in a single instrument run. To address the strict requirements in clinical diagnostics for control of assay parameters and output, we employed a control-based Precision-Recall and predictive Receiver Operator Characteristics (coPR) analysis to assign run-specific quality control metrics. C19-SPAR-Seq coupled to coPR on a trial cohort of over 600 patients performed with a specificity of 100% and sensitivity of 91% on samples with low viral loads and a sensitivity of > 95% on high viral loads associated with disease onset and peak transmissibility. Our study thus establishes the feasibility of employing C19-SPAR-Seq for the large-scale monitoring of SARS-CoV-2 and other pathogens.
Licença
cc_by_nc_nd
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Cohort_studies / Estudo diagnóstico / Estudo observacional / Estudo prognóstico / Rct / Revisão sistemática Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Cohort_studies / Estudo diagnóstico / Estudo observacional / Estudo prognóstico / Rct / Revisão sistemática Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
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