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 wholemetagenome 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-alignmentbased 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 wholemetagenome sequencing can be used as a practical food safety tool to prevent diseases or to link outbreaks to specific food products.KEYWORDS fermentation, food-borne pathogens, metagenomics I n recent years, high-throughput sequencing (HTS) has become an important tool in food microbiology (1). HTS enables in-depth characterization of food-related microbial isolates, via whole-genome sequencing (WGS), and it facilitates cultureindependent analysis of mixed microbial communities in foods, via metagenomic sequencing.WGS has provided invaluable insights into the genetics of starter cultures (2, 3), and it is routinely used in epidemiology to identify outbreak-associated foodborne pathogens isolated from clinical samples, through comparison of the single-nucleotide polymorphism (SNP) profiles of outbreak strain genomes versus nonoutbreak strain