Abstract
Millions of foodborne infections are reported yearly worldwide due to a variety of pathogens. A promising approach to tackle this issue relies on Next Generation Sequencing (NGS). In this work a novel multi-foodborne pathogen detection was developed. The method combines a selective enrichment step in a novel broth, multiplex PCR with interlaboratory-validated primers, long-read Flongle MinION sequencing, and data analysis in three cloud-based pipelines to overcome complex, command line-based bioinformatic data analyses. The method, was evaluated in salmon samples spiked with fresh, heat and cold stressed, bacterial cultures of Salmonella spp., E. coli O157:H7 and L. monocytogenes, as well as with in-house, and commercial mock communities, doped with Y. enterocolitica and thermotolerant Campylobacter spp. No major deviations from the expected results were obtained, reaching a limit of detection <10 CFU/25 g for Salmonella spp., E. coli O157 and L. monocytogenes with sensitivity, specificity and accuracy values > 90% regardless the bioinformatic pipeline selected and concordance values between 0.9 to 1.0. Taken together, the proposed method allows for simple and reliable implementation of NGS as testing tool to streamline foodborne pathogen detection, and overcoming the typical limitations associated with this technology.