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, Liliana Attisano, Rod Bremner, Benjamin J. Blencowe, Tony Mazzulli, Hong Han, Laurence Pelletier () and Jeffrey L. Wrana ()
Additional contact information
Marie-Ming Aynaud: Mount Sinai Hospital
J. Javier Hernandez: Mount Sinai Hospital
Seda Barutcu: Mount Sinai Hospital
Ulrich Braunschweig: University of Toronto
Kin Chan: Mount Sinai Hospital
Joel D. Pearson: Mount Sinai Hospital
Daniel Trcka: Mount Sinai Hospital
Suzanna L. Prosser: Mount Sinai Hospital
Jaeyoun Kim: Mount Sinai Hospital
Miriam Barrios-Rodiles: Mount Sinai Hospital
Mark Jen: Mount Sinai Hospital
Siyuan Song: University of Toronto
Jess Shen: Mount Sinai Hospital
Christine Bruce: Mount Sinai Hospital/University Health Network
Bryn Hazlett: Mount Sinai Hospital/University Health Network
Susan Poutanen: Mount Sinai Hospital/University Health Network
Liliana Attisano: University of Toronto
Rod Bremner: Mount Sinai Hospital
Benjamin J. Blencowe: University of Toronto
Tony Mazzulli: Mount Sinai Hospital/University Health Network
Hong Han: University of Toronto
Laurence Pelletier: Mount Sinai Hospital
Jeffrey L. Wrana: Mount Sinai Hospital

Nature Communications, 2021, vol. 12, issue 1, 1-10

Abstract: Abstract Population scale sweeps of viral pathogens, such as SARS-CoV-2, require high intensity testing for effective management. Here, we describe “Systematic Parallel Analysis of RNA coupled to Sequencing for Covid-19 screening” (C19-SPAR-Seq), a multiplexed, scalable, readily automated platform for SARS-CoV-2 detection that is capable of analyzing tens of thousands of patient samples in a single run. To address strict requirements for control of assay parameters and output demanded by clinical diagnostics, we employ a control-based Precision-Recall and Receiver Operator Characteristics (coPR) analysis to assign run-specific quality control metrics. C19-SPAR-Seq coupled to coPR on a trial cohort of several hundred patients performs 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. This study establishes the feasibility of employing C19-SPAR-Seq for the large-scale monitoring of SARS-CoV-2 and other pathogens.

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/s41467-021-21653-y Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21653-y

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-021-21653-y

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().