Clinical Accuracy and Operational Evaluation of a Novel Nanopore Based 16S Diagnostic Pathogen Detection Workflow

Culture-based methods remain standard practice for pathogenic bacterial detection in routine diagnostic laboratories but frequently fail to identify pathogens, particularly in low bacterial burden or antibiotic-exposed samples. While full-length 16S rRNA sequencing improves detection and taxonomic resolution, its adoption is hindered by bioinformatic complexity and operational feasibility. We developed an in-house Oxford Nanopore Technologies (ONT)-based full-length 16S assay coupled with an open-access, automated analysis pipeline designed for non-specialist staff. In this pilot study, 116 culture-negative clinical samples underwent sequencing, with 86 tested in parallel against outsourced standard-of-care 16S or species-specific PCR. Medical microbiologists, blinded to comparative results, independently assessed clinical relevance. Turnaround time, workflow integration, and cost requirements were also evaluated. Compared to outsourced 16S testing, the in-house workflow demonstrated a 100% positive percent agreement (12/12; 95% CI: 75.7%-100.0%). It significantly expanded clinical diagnostic yield from 14.0% (12/86) to 37.2% (32/86) (p<0.0001), identifying clinically relevant organisms in an additional 20 samples reported as negative by outsourced testing. It enhanced species-level resolution and identified polymicrobial infections (n=8). The NanoPATH pipeline generated clinically interpretable outputs via a single-command workflow and implementation modelling demonstrated that twice-weekly runs would achieve comparable turnaround times to outsourced testing, with cost-neutrality reached at 9 samples per run. An open-access ONT-based 16S workflow which is feasible for routine diagnostic laboratory implementation and operated without specialist bioinformaticians significantly improves pathogen detection from clinical samples. By overcoming analytical and operational barriers, this approach provides a practical framework for integrating sequencing-based diagnostics into standard clinical workflows and improving patient care.