Validation of an Automated, End-to-End Metagenomic Sequencing Assay for Agnostic Detection of Respiratory Viruses.

Autor:	Gauthier NPG; Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada., Chan W; School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada., Locher K; Division of Medical Microbiology, Vancouver General Hospital, Vancouver, British Columbia, Canada.; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada., Smailus D; Canada's Michael Smith Genome Sciences Centre at BC Cancer, Vancouver, British Columbia, Canada., Coope R; Canada's Michael Smith Genome Sciences Centre at BC Cancer, Vancouver, British Columbia, Canada., Charles M; Division of Medical Microbiology, Vancouver General Hospital, Vancouver, British Columbia, Canada.; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada., Jassem A; British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada., Kopetzky J; British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada., Chorlton SD; BugSeq Bioinformatics Inc, Vancouver, British Columbia, Canada., Manges AR; School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada.; British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada.
Jazyk:	angličtina
Zdroj:	The Journal of infectious diseases [J Infect Dis] 2024 Dec 16; Vol. 230 (6), pp. e1245-e1253.
DOI:	10.1093/infdis/jiae226
Abstrakt:	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), which were reverse-transcription polymerase chain reaction positive, or negative for influenza, severe acute respiratory syndrome coronavirus 2, and respiratory syncytial virus. 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 and semiquantitative, with analytical limits of detection ranging from 103 to 104 copies/mL. Our assay is highly specific (100%) and sensitive (61.9% overall: 86.8%; reverse-transcription polymerase chain reaction cycle threshold < 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 report 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. Competing Interests: Potential conflicts of interest. S. D. C is a shareholder and employee of BugSeq Bioinformatics. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed. (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)
Databáze:	MEDLINE
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