Identification, source tracking, and surveillance of food pathogens is a
crucial factor for the food-producing industry. Over the last decade,
the techniques used for this have moved from conventional enrichment
methods, through species-specific detection by PCR to sequencing-based
methods, whole-genome sequencing (WGS) being the ultimate method.
However, using WGS requires the right infrastructure, high computational
power, and bioinformatics expertise. Therefore, there is a need for
faster, more cost-effective, and more user-friendly methods. A newly
developed method, ON-rep-seq, combines the classical rep-PCR method with
nanopore sequencing, resulting in a highly discriminating set of
sequences that can be used for species identification and also strain
discrimination. This study is essentially a real industry case from a
salmon processing plant. Twenty Listeria monocytogenes isolates were
analyzed both by ON-rep-seq and WGS to identify and differentiate
putative L. monocytogenes from a routine sampling of processing
equipment and products, and finally, compare the strain-level
discriminatory power of ON-rep-seq to different analyzing levels
delivered from the WGS data. The analyses revealed that among the
isolates tested there were three different strains. The isolates of the
most frequently detected strain (n=15) were all detected in the
problematic area in the processing plant. The strain level
discrimination done by ON-rep-seq was in full accordance with the
interpretation of WGS data. Our findings also demonstrate that
ON-rep-seq may serve as a primary screening method alternative to WGS
for identification and strain-level differentiation for surveillance of
potential pathogens in a food-producing environment.
ON‐rep‐seq as a rapid and cost‐effective alternative to whole‐genome sequencing for species‐level identification and strain‐level discrimination of
Listeria monocytogenes
contamination in a salmon processing plant
