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Shiga toxin-producing Escherichia coli (STEC) is an important public health pathogen, capable of causing hemorrhagic diarrhea and life-threatening kidney failure, particularly in children (1). STEC is primarily transmitted through the [...]

Nontyphoidal serovars of Salmonella enterica subsp. enterica, which cause salmonellosis, are responsible for an estimated 93.8 million illnesses and 155,000 deaths among humans worldwide each year (1). In New Zealand, [...]

A diverse array of micro-organisms can be found on food, including those that are pathogenic or resistant to antimicrobial drugs. Metagenomics involves extracting and sequencing the DNA of all micro-organisms on a sample, and here, we used a combination of culture and culture-independent approaches to investigate the microbial ecology of food to assess the potential application of metagenomics for the microbial surveillance of food. We cultured common foodborne pathogens and other organisms including Escherichia coli , Klebsiella/Raoultella spp., Salmonella spp. and Vibrio spp. from five different food commodities and compared their genomes to the microbial communities obtained by metagenomic sequencing following host (food) DNA depletion. The microbial populations of retail food were found to be predominated by psychrotrophic bacteria, driven by the cool temperatures in which the food products are stored. Pathogens accounted for a small percentage of the food metagenome compared to the psychrotrophic bacteria, and cultured pathogens were inconsistently identified in the metagenome data. The microbial composition of food varied amongst different commodities, and metagenomics was able to classify the taxonomic origin of 59% of antimicrobial resistance genes (ARGs) found on food to the genus level, but it was unclear what percentage of ARGs were associated with mobile genetic elements and thus transferable to other bacteria. Metagenomics may be used to survey the ARG burden, composition and carriage on foods to which consumers are exposed. However, food metagenomics, even after depleting host DNA, inconsistently identifies pathogens without enrichment or further bait capture.

Campylobacter spp. are leading bacterial gastroenteritis pathogens. Infections are largely underreported, and the burden of outbreaks may be underestimated. Current strategies of testing as few as one isolate per sample can affect attribution of cases to epidemiologically important sources with high Campylobacter diversity, such as chicken meat. Multiple culture method combinations were utilized to recover and sequence Campylobacter from 45 retail chicken samples purchased across Norwich, UK, selecting up to 48 isolates per sample. Simulations based on resampling were used to assess the impact of Campylobacter sequence type (ST) diversity on outbreak detection. Campylobacter was recovered from 39 samples (87%), although only one sample was positive through all broth, temperature, and plate combinations. Three species were identified ( Campylobacter jejuni , Campylobacter coli , and Campylobacter lari ), and 33% of samples contained two species. Positive samples contained 1-8 STs. Simulation revealed that up to 87 isolates per sample would be required to detect 95% of the observed ST diversity, and 26 isolates would be required for the average probability of detecting a random theoretical outbreak ST to reach 95%. An optimized culture approach and selecting multiple isolates per sample are essential for more complete Campylobacter recovery to support outbreak investigation and source attribution.