The Clinical Utility of Two High-Throughput 16S rRNA Gene Sequencing Workflows for Taxonomic Assignment of Unidentifiable Bacterial Pathogens in Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

Bacterial pathogens that cannot be identified using matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) are occasionally encountered in clinical laboratories. The 16S rRNA gene is often used for sequence-based analysis to identify these bacterial species. Nevertheless, traditional Sanger sequencing is laborious, time-consuming, and low throughput. Here, we compared two commercially available 16S rRNA gene sequencing tests that are based on Illumina and Nanopore sequencing technologies, respectively, in their ability to identify the species of 172 clinical isolates that failed to be identified by MALDI-TOF MS. Sequencing data were analyzed by the respective built-in programs (MiSeq Reporter software of Illumina and Epi2me of Nanopore) and BLAST+ (v2.11.0). Their agreement with Sanger sequencing on species-level identification was determined. Discrepancies were resolved by whole-genome sequencing. The diagnostic accuracy of each workflow was determined using the composite sequencing result as the reference standard. Despite the high base-calling accuracy of Illumina sequencing, we demonstrated that the Nanopore workflow had a higher taxonomic resolution at the species level. Using built-in analysis algorithms, the concordance of Sanger 16S with the Illumina and Nanopore workflows was 33.14% and 87.79%, respectively. The agreement was 65.70% and 83.14%, respectively, when BLAST+ was used for analysis. Compared with the reference standard, the diagnostic accuracy of Nanopore 16S was 96.36%, which was identical to that of Sanger 16S and better than that of Illumina 16S (69.07%). The turnaround time of the Illumina workflow and the Nanopore workflow was 78 h and 8.25 h, respectively. The per-sample cost of the Illumina and Nanopore workflows was US$28.5 and US$17.7, respectively.