The Journal of infection
August 22, 2026 · via Europe PMC
Clinical validation of an optimised metagenomic nanopore sequencing method for detecting viral respiratory pathogens.
Sanderson ND, Dingle KE, Hopkins KMV, +13 more, Young BC
AI summary — for doctors, generated from the abstract only
An optimized nanopore metagenomic workflow for respiratory viruses in nasopharyngeal swabs was highly specific but detected only about half of PCR-positive targets, performing best at higher viral loads.
What was studied
A diagnostic accuracy study validating a nanopore sequencing workflow (host depletion, SISPA amplification, ONT sequencing) on 344 prospectively collected upper respiratory samples against routine multiplex PCR covering 23 targets.
Key findings
- Sensitivity vs PCR was 51% (95% CI 45%-57%) with pre-defined criteria, ranging 19%-85% across common pathogens
- Specificity was 99.8% (95% CI 99.6%-99.9%)
- Sensitivity rose to 58% with post-hoc thresholds, 70% excluding rhinovirus/enterovirus, and 83% excluding samples with Ct of 35 or higher
- Read crossover from multiplexing caused 7 of 9 false positives; only 2 plausible additional pathogens were found
- 41 RSV, 13 influenza A and 10 rhinovirus/enterovirus were subtyped; cost was about 112 GBP per sample
Clinical relevance
Current metagenomic sequencing is not a replacement for multiplex PCR for routine respiratory virus detection in swabs, but may have niche uses, such as subtyping or higher viral load samples.
Who should care
Limitations
Single workflow evaluation with PCR as an imperfect reference; several sensitivity improvements were post-hoc.
Metagenomic sequencing of nasal swabs is specific but still too insensitive for routine respiratory virus diagnosis.
This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.
Abstract
BACKGROUND
Clinical metagenomics (CMg) offers high-throughput respiratory pathogen detection with a wider range than targeted, probe-dependent diagnostics. Sequencing cost and the challenges of high host biomass are barriers to the use of CMg in high-throughput respiratory pathogen detection in non-invasive samples such as nasopharyngeal swabs.
METHODS
We optimised a nanopore sequencing workflow to detect RNA viruses in nasopharyngeal swabs, employing pathogen enrichment, by background nucleic acid depletion and SISPA amplification, and Oxford Nanopore Technology (ONT) sequencing. As a pre-requisite for agnostic pathogen detection, we first derived quality control (QC) criteria and diagnostic thresholds against a gold-standard comprising 23 pathogen targets detected by routine multiplex PCR. In this diagnostic accuracy study we validated this workflow using 344 prospectively collected upper respiratory tract samples submitted for routine testing.
FINDINGS
Using pre-defined QC and positivity criteria, the workflow's sensitivity versus PCR was 51% (95%CI: 45%-57%) (133/260 positive targets detected) (ranging from 19%-85% across pathogens with >20 gold- standard detections), and specificity 99.8% (95%CI: 99.6%-99.9%) (3836/3845 negative targets not detected). Sensitivity improved to 58% (159/274) using post-hoc optimised thresholds, 61% (159/260) only considering RNA pathogens, 70% (144/207) excluding rhinovirus/enterovirus and 83% (140/169) excluding samples with post workflow qPCR Ct values ≥35. Read crossover from multiplex sequencing contributed most (7/9) false-positives. Only 2 plausible additional pathogens were identified (rhinovirus and coronavirus OC43). 41 respiratory syncytial virus (RSV), 13 influenza A and 10 rhinovirus/enterovirus were successfully sub-typed by sequencing. Multiplexed nanopore sequencing costs were £112/sample.
INTERPRETATION
Although CMg has substantial diagnostic potential, this validation study demonstrates the technical limitations of current metagenomic sequencing methods applied to viral detection in upper respiratory tract samples with high host and low pathogen biomass. Its greater sensitivity at higher viral loads demonstrates the importance of identifying the most appropriate use cases to maximise its utility and value.
DOI
10.1016/j.jinf.2026.106839
PMID
42632487
Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.
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