16S rRNA gene and rpoB Nanopore Sequencing for Bacterial Detection and Identification in Clinical Samples

Broad-range amplification and sequencing of the 16S ribosomal RNA (rRNA) gene directly from clinical samples can improve diagnosis of bacterial infections. Recent advances in the Oxford Nanopore Technologies (ONT) third-generation sequencing platform, delivering sequencing accuracy exceeding 99%, makes it a possible option for this approach. However, even full-length 16S rRNA sequencing may lack resolution to distinguish closely related species, a problem exacerbated by the remaining ONT error rate. Here, we propose a strategy combining ONT sequencing of the 16S rRNA gene with a segment of the rpoB gene. We further developed a novel bioinformatics tool mitigating issues related to the ONT error rate, and also providing homology scores allowing for implementation of CLSI interpretive criteria. Using this approach, we investigated 25 abdominal abscess samples, with Illumina sequencing of the same genes as the comparator method. Our results showed that rpoB ONT sequencing provided species-level identification in 91.5% of detections, as compared to 68.9% with 16S rRNA ONT sequencing. However, 16S rRNA ONT sequencing showed the highest sensitivity detecting 84.0% of the total identifications as compared to 74.2% for rpoB. Together, 16S rRNA and rpoB ONT sequencing achieved a detection rate of 94.0%, with species-level identification in 87.7%. For both gene targets, ONT sequencing paralleled Illumina sequencing. Combining ONT sequencing with optimized bioinformatics processing, alongside the high sensitivity of 16S rRNA broad-range amplification and the improved taxonomic resolution of rpoB, enable accurate detection and identification of bacteria directly from clinical samples.