Strain-level metagenomic analysis of the fermented dairy beverage nunu highlights potential food safety risks
| dc.contributor.author | Walsh, Aaron M. | |
| dc.contributor.author | Crispie, Fiona | |
| dc.contributor.author | Daari, Kareem | |
| dc.contributor.author | O'Sullivan, Orla | |
| dc.contributor.author | Martin, Jennifer C. | |
| dc.contributor.author | Arthur, Cornelius T. | |
| dc.contributor.author | Claesson, Marcus J. | |
| dc.contributor.author | Scott, Karen P. | |
| dc.contributor.author | Cotter, Paul D. | |
| dc.date.accessioned | 2017-06-23T13:46:39Z | |
| dc.date.available | 2017-06-23T13:46:39Z | |
| dc.date.issued | 2017-06-16 | |
| dc.date.updated | 2017-06-23T13:39:40Z | |
| dc.description.abstract | The rapid detection of pathogenic strains in food products is essential for the prevention of disease outbreaks. It has already been demonstrated that whole metagenome shotgun sequencing can be used to detect pathogens in food but, until recently, strain-level detection of pathogens has relied on whole metagenome assembly, which is a computationally demanding process. Here, we demonstrate that three short read alignment-based methods, MetaMLST, PanPhlAn, and StrainPhlAn, can accurately, and rapidly, identify pathogenic strains in spinach metagenomes which were intentionally spiked with Shiga toxin-producing Escherichia coli in a previous study. Subsequently, we employ the methods, in combination with other metagenomics approaches, to assess the safety of nunu, a traditional Ghanaian fermented milk product which is produced by the spontaneous fermentation of raw cow milk. We show that nunu samples are frequently contaminated with bacteria associated with the bovine gut, and worryingly, we detect putatively pathogenic E. coli and Klebsiella pneumoniae strains in a subset of nunu samples. Ultimately, our work establishes that short read alignment-based bioinformatics approaches are suitable food safety tools, and we describe a real-life example of their utilisation. Importance: Foodborne pathogens are responsible for millions of illnesses, annually. Here, we demonstrate that short read alignment-based bioinformatics tools can accurately, and rapidly, detect pathogenic strains in food products from shotgun metagenomics data. The methods used here are considerably faster than both traditional culturing methods and alternative bioinformatics approaches that rely on metagenome assembly, and thus they can potentially be used for more high-throughput food safety testing. Overall, our results suggest that whole metagenome sequencing can be used as a practical food safety tool to prevent diseases or link outbreaks to specific food products. | en |
| dc.description.status | Peer reviewed | en |
| dc.description.version | Accepted Version | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Walsh, A. M., Crispie, F., Daari, K., O'Sullivan, O., Martin, J. C., Arthur, C. T., Claesson, M. J., Scott, K. P. and Cotter, P. D. (2017) 'Strain-level metagenomic analysis of the fermented dairy beverage nunu highlights potential food safety risks', Applied and Environmental Microbiology. In Press, doi: 10.1128/aem.01144-17 | en |
| dc.identifier.doi | 10.1128/aem.01144-17 | |
| dc.identifier.issn | 0099-2240 | |
| dc.identifier.journaltitle | Applied and Environmental Microbiology | en |
| dc.identifier.uri | https://hdl.handle.net/10468/4188 | |
| dc.language.iso | en | en |
| dc.publisher | American Society for Microbiology | en |
| dc.rights | © 2017 American Society for Microbiology | en |
| dc.subject | Foodborne pathogens | en |
| dc.subject | Bioinformatics | en |
| dc.subject | Pathogenic strains | en |
| dc.subject | Food safety | en |
| dc.subject | Nunu | en |
| dc.subject | Escherichia coli | en |
| dc.title | Strain-level metagenomic analysis of the fermented dairy beverage nunu highlights potential food safety risks | en |
| dc.type | Article (peer-reviewed) | en |
