ABSTRACT
Perilla (Perilla frutescens) is a commonly consumed herb with various health benefits in Asia. However, the risks of food-borne illness owing to the presence of pathogens on perilla leaves have not been evaluated. In this study, we evaluated the microbiota of perilla leaves harvested in South Korea using Illumina MiSeq sequencing of the 16S rRNA gene. In total, 2,743,003 sequencing reads were obtained, and 92-437 operational taxonomic units were observed in all samples. Bacterial loads were quantified, and the diversity indices were compared. Differences in the microbiota among sampling times and regions were also investigated. Proteobacteria and Firmicutes were predominant phyla at both times. At the class level, the bacterial communities were composed primarily of Alphaproteobacteria, Bacilli, and Gammaproteobacteria. Diverse bacterial taxa, such as Bacillus, uncultured family Enterobacteriaceae, and Sphingomonas were detected, and the representative pathogenic species (i.e., Acinetobacter lwoffii, Klebsiella pneumoniae, and Staphylococcus aureus) were quantified by qRT-PCR. The results of the co-occurrence network analysis showed characteristics of bacterial taxa in the microbiome on perilla leaves and provided insights into the roles of correlations among diverse microbes, including potential pathogens. Based on these results, the potential risk of food-borne illness from consumption of perilla leaves may be higher in July than in April. In summary, the microbial compositions determined in this study can be used as a base data for food-safety management for prediction and prevention of future outbreaks.
Subject(s)
Microbiota/genetics , Perilla frutescens/microbiology , Plant Leaves/microbiology , Foodborne Diseases/microbiology , Foodborne Diseases/prevention & control , Humans , Metagenome/genetics , Metagenomics , Republic of KoreaABSTRACT
Lettuce (Lactuca sativa L.) is a major ingredient used in many food recipes in South Korea. Lettuce samples were collected during their maximum production period between April and July in order to investigate the microbiota of lettuce during different seasons. 16S rRNA gene-based sequencing was conducted using Illumina MiSeq, and real-time PCR was performed for quantification. The number of total bacterial was greater in lettuce collected in July than in that collected in April, albeit with reduced diversity. The bacterial compositions varied according to the site and season of sample collection. Potential pathogenic species such as Bacillus spp., Enterococcus casseliflavus, Klebsiella pneumoniae, and Pseudomonas aeruginosa showed season-specific differences. Results of the network co-occurrence analysis with core genera correlations showed characteristics of bacterial species in lettuce, and provided clues regarding the role of different microbes, including potential pathogens, in this microbiota. Although further studies are needed to determine the specific effects of regional and seasonal characteristics on the lettuce microbiota, our results imply that the 16S rRNA gene-based sequencing approach can be used to detect pathogenic bacteria in lettuce.