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A rapid, low cost, and highly sensitive SARS-CoV-2 diagnostic based on whole genome sequencing
Preprint
in English
| bioRxiv
| ID: ppbiorxiv-061499
ABSTRACT
Early detection of infection with SARS-CoV-2 is key to managing the current global pandemic, as evidence shows the virus is most contagious on or before symptom onset. Here, we introduce a low-cost, high-throughput method for diagnosis of SARS-CoV-2 infection, dubbed Pathogen-Oriented Low-Cost Assembly & Re-Sequencing (POLAR), that enhances sensitivity by aiming to amplify the entire SARS-CoV-2 genome rather than targeting particular viral loci, as in typical RT-PCR assays. To achieve this goal, we combine a SARS-CoV-2 enrichment method developed by the ARTIC Network (https//artic.network/) with short-read DNA sequencing and de novo genome assembly. We are able to reliably (>95% accuracy) detect SARS-CoV-2 at concentrations of 84 genome equivalents per milliliter, better than the reported limits of detection of almost all diagnostic methods currently approved by the US Food and Drug Administration. At higher concentrations, we are able to reliably assemble the SARS-CoV-2 genome in the sample, often with no gaps and perfect accuracy. Such genome assemblies enable the spread of the disease to be analyzed much more effectively than would be possible with an ordinary yes/no diagnostic, and can help identify vaccine and drug targets. Finally, we show that POLAR diagnoses on 10 of 10 clinical nasopharyngeal swab samples (half positive, half negative) match those obtained in a CLIA-certified lab using the Center for Disease Controls 2019-Novel Coronavirus test. Using POLAR, a single person can process 192 samples over the course of an 8-hour experiment, at a cost of [~]$30/patient, enabling a 24-hour turnaround with sequencing and data analysis time included. Further testing and refinement will likely enable greater enhancements in the sensitivity of the above approach.
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Full text:
Available
Collection:
Preprints
Database:
bioRxiv
Type of study:
Diagnostic study
/
Prognostic study
Language:
English
Year:
2020
Document type:
Preprint