Validation of an automated, end-to-end metagenomic sequencing assay for agnostic detection of respiratory viruses

Abstract

Background Current molecular diagnostics are limited in the number and type of detectable pathogens. Metagenomic next generation sequencing (mNGS) is an emerging, and increasingly feasible, pathogen-agnostic diagnostic approach. Translational barriers prohibit the widespread adoption of this technology in clinical laboratories. We validate an end-to-end mNGS assay for detection of respiratory viruses. Our assay is optimized to reduce turnaround time, lower cost-per-sample, increase throughput, and deploy secure and actionable bioinformatic results. Methods We validated our assay using residual nasopharyngeal swab specimens from Vancouver General Hospital (n = 359), RT-PCR-positive, or negative for Influenza, SARS-CoV-2, and RSV. We quantified sample stability, assay precision, the effect of background nucleic acid levels, and analytical limits of detection. Diagnostic performance metrics were estimated. Results We report that our mNGS assay is highly precise, semi-quantitative, with analytical limits of detection ranging from 103-104 copies/mL. Our assay is highly specific (100%) and sensitive (61.9% Overall: 86.8%; RT-PCR Ct < 30). Multiplexing capabilities enable processing of up to 55-specimens simultaneously on an Oxford Nanopore GridION device, with results reported within 12-hours. Conclusions This study outlines the diagnostic performance and feasibility of mNGS for respiratory viral diagnostics, infection control, and public health surveillance. We addressed translational barriers to widespread mNGS adoption.