Application of MSB selective enrichment followed by amplicon MinION sequencing for multipathogen detection in smoked salmon

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.

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Publication Details

Journal
npj Science of Food
Published
2025-10-28
DOI
https://doi.org/10.1038/s41538-025-00452-5
Primary Topic
Identification and Quantification in Food
Type
article
Field-Weighted Citation Impact
0.00

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article

Application of MSB selective enrichment followed by amplicon MinION sequencing for multipathogen detection in smoked salmon

Ana Costa-Ribeiro, Alexandre Lamas, Marta Prado, Alejandro Garrido‐Maestu
npj Science of Food
Identification and Quantification in Food
article

Application of MSB selective enrichment followed by amplicon MinION sequencing for multipathogen detection in smoked salmon

Ana Costa-Ribeiro, Alexandre Lamas, Marta Prado, Alejandro Garrido‐Maestu
article en

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.

npj Science of FoodVol. 9(1)
Universidade de Santiago de Compostela (ES), Instituto de Investigacións Mariñas (ES), International Iberian Nanotechnology Laboratory (PT), Universidade de Vigo (ES)
Ministerio de Ciencia, Innovación y Universidades, Fundação para a Ciência e a Tecnologia
Openalex Percentile: Top 72%
Identification and Quantification in Food
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Application of MSB selective enrichment followed by amplicon MinION sequencing for multipathogen detection in smoked salmon — Ana Costa-Ribeiro, Alexandre Lamas, et al. · npj Science of Food (2025) | TGRS Research Map | TGRS