Dataset Information

Strain-Level Metagenomic Analysis of the Fermented Dairy Beverage Nunu Highlights Potential Food Safety Risks.

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 demonstrated that three short-read-alignment-based methods, i.e., MetaMLST, PanPhlAn, and StrainPhlAn, could accurately and rapidly identify pathogenic strains in spinach metagenomes that had been intentionally spiked with Shiga toxin-producing Escherichia coli in a previous study. Subsequently, we employed the methods, in combination with other metagenomics approaches, to assess the safety of nunu, a traditional Ghanaian fermented milk product that is produced by the spontaneous fermentation of raw cow milk. We showed that nunu samples were frequently contaminated with bacteria associated with the bovine gut and, worryingly, we detected 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 utilization.IMPORTANCE Foodborne pathogens are responsible for millions of illnesses each year. Here we demonstrate that short-read-alignment-based bioinformatics tools can accurately and rapidly detect pathogenic strains in food products by using shotgun metagenomics data. The methods used here are considerably faster than both traditional culturing methods and alternative bioinformatics approaches that rely on metagenome assembly; therefore, 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 to link outbreaks to specific food products.

SUBMITTER: Walsh AM

PROVIDER: S-EPMC5541208 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Strain-Level Metagenomic Analysis of the Fermented Dairy Beverage Nunu Highlights Potential Food Safety Risks.

Walsh Aaron M AM Crispie Fiona F Daari Kareem K O'Sullivan Orla O Martin Jennifer C JC Arthur Cornelius T CT Claesson Marcus J MJ Scott Karen P KP Cotter Paul D PD

Applied and environmental microbiology 20170801 16

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 demonstrated that three short-read-alignment-based methods, i.e., MetaMLST, PanPhlAn, and StrainPhlAn, could accurately a ...[more]

PMID: 28625983

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Project description:Kefir is a putatively health-promoting dairy beverage that is produced when a kefir grain, consisting of a consortium of microorganisms, is added to milk to initiate a natural fermentation. Here, a detailed analysis was carried out to determine how the microbial population, gene content, and flavor of three kefirs from distinct geographic locations change over the course of 24-h fermentations. Metagenomic sequencing revealed that Lactobacillus kefiranofaciens was the dominant bacterial species in kefir during early stages of fermentations but that Leuconostoc mesenteroides became more prevalent in later stages. This pattern is consistent with an observation that genes involved in aromatic amino acid biosynthesis were absent from L. kefiranofaciens but were present in L. mesenteroides. Additionally, these shifts in the microbial community structure, and associated pathways, corresponded to changes in the levels of volatile compounds. Specifically, Acetobacter spp. correlated with acetic acid; Lactobacillus spp. correlated with carboxylic acids, esters and ketones; Leuconostoc spp. correlated with acetic acid and 2,3-butanedione; and Saccharomyces spp. correlated with esters. The correlation data suggest a causal relationship between microbial taxa and flavor that is supported by observations that addition of L. kefiranofaciens NCFB 2797 increased the levels of esters and ketones whereas addition of L. mesenteroides 213M0 increased the levels of acetic acid and 2,3-butanedione. Finally, we detected genes associated with probiotic functionalities in the kefir microbiome. Our results illustrate the dynamic nature of kefir fermentations and microbial succession patterns therein and can be applied to optimize the fermentation processes, flavors, and health-related attributes of this and other fermented foods. IMPORTANCE Traditional fermented foods represent relatively low-complexity microbial environments that can be used as model microbial communities to understand how microbes interact in natural environments. Our results illustrate the dynamic nature of kefir fermentations and microbial succession patterns therein. In the process, the link between individual species, and associated pathways, with flavor compounds is revealed and several genes that could be responsible for the purported gut health-associated benefits of consuming kefir are identified. Ultimately, in addition to providing an important fundamental insight into microbial interactions, this information can be applied to optimize the fermentation processes, flavors, and health-related attributes of this and other fermented foods.

Dataset Information

Strain-Level Metagenomic Analysis of the Fermented Dairy Beverage Nunu Highlights Potential Food Safety Risks.

Publications

Strain-Level Metagenomic Analysis of the Fermented Dairy Beverage Nunu Highlights Potential Food Safety Risks.

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