Standalone nanopore sequencing for foodborne pathogen surveillance: a large-scale evaluation and quality control framework

Whole-genome sequencing (WGS) is central to foodborne pathogen surveillance and cross-border outbreak detection. Long-read sequencing using Oxford Nanopore Technologies (ONT) promises rapid, complete, and cost-effective genome assemblies in a single workflow. However, the adoption of standalone ONT sequencing of native DNA has been slowed by concerns that DNA modifications can compromise per-base sequencing accuracy and downstream genotyping. We evaluated ONT-only sequencing performance across 294 genetically diverse isolates representing ten major foodborne pathogens. At 50x coverage, 97.3% (286/294) of the ONT assemblies produced identical or near-identical cgMLST profiles ([≤]3 allelic differences) as Illumina-polished hybrid assemblies. Elevated error rates were observed in four Salmonella enterica serovar Kentucky and four Listeria monocytogenes isolates and were associated with the presence of specific DNA phosphorothioation or methylation systems. To enable rapid identification of unreliable assemblies, we developed alpaqa, a lightweight computational tool that detects systematic nanopore assembly errors without requiring supplemental short-read data or reference genomes. By flagging assemblies affected by systematic errors, alpaqa provides a quality safeguard for ONT-only workflows. Masking low-quality bases in assemblies flagged by alpaqa improved cgMLST accuracy, although this reduced the number of callable loci and therefore genotyping resolution. Our findings demonstrate that standalone ONT sequencing of native DNA is sufficiently accurate for routine foodborne pathogen surveillance with current chemistry, software, and appropriate quality control, supporting its use in harmonised genomic surveillance frameworks.