Oxford Nanopore Technologies R10 sequencing enables accurate cgMLST-based bacterial outbreak investigation of and when accounting for methylation-related errors.

Core-genome multi-locus sequence typing (cgMLST) is a well-established and standardized method for genomics-based cluster detection and phylogenomic analysis of bacteria. The reduced error rate of Oxford Nanopore Technologies (ONT) R10 sequencing has prompted many laboratories to explore incorporating this technology into their activities. However, conflicting reports exist on the performance of ONT R10 sequencing for cgMLST analysis. This study evaluates the suitability of ONT R10 data for cgMLST allele calling and cluster detection for bacterial outbreak investigation. ONT and Illumina sequencing data were generated for 24 and 24 isolates. For ONT, both the rapid barcoding kit (RBK) and the rapid PCR barcoding kit (RPB) were used. The percentage of loci called in the ONT-only assemblies was very high for both species. However, the proportion of mismatched alleles to the hybrid assemblies was substantially higher for the ONT-only assemblies with the RBK kit, resulting in incorrect cluster assignments. The large majority of these mismatched alleles were due to incorrect base calls at methylated positions, which did not affect the ONT data generated using the RPB kit or any of the ONT-only assemblies. In conclusion, ONT R10 sequencing shows great potential as a viable method for cgMLST analysis, but methylation-related errors can affect performance for certain species and strains. When properly corrected for, ONT R10 had the same performance for cgMLST analysis as Illumina, and both could be used interchangeably. These results support the integration of ONT R10 sequencing into routine public health and clinical workflows.

IMPORTANCE: This study evaluates the suitability of Oxford Nanopore Technologies R10 sequencing for core-genome multi-locus sequence typing (cgMLST), a widely used method in (clinical) outbreak investigation and bacterial strain tracking. We have sequenced 24 and 24 strains, including confirmed outbreak cases, using Illumina and ONT R10 sequencing to evaluate the performance for cgMLST analysis. We used a PCR-based and native barcoding protocol for the ONT sequencing, which enabled us to demonstrate a substantial species-dependent impact of methylation-related errors on the performance. However, we demonstrate that when these errors are properly addressed, ONT R10 can be used for accurate cgMLST-based clustering, including integration with strains sequenced using Illumina. Our findings support the use of ONT R10 as an alternative to Illumina sequencing for cgMLST analysis in routine public health practice.