4.4 Article

Seasonal Changes in the Microbial Communities on Lettuce (Lactuca sativa L.) in Chungcheong-do, South Korea

期刊

JOURNAL OF MICROBIOLOGY AND BIOTECHNOLOGY
卷 33, 期 2, 页码 219-227

出版社

KOREAN SOC MICROBIOLOGY & BIOTECHNOLOGY
DOI: 10.4014/jmb.2210.10001

关键词

16S rRNA gene; lettuce; microbial community; metagenomics; potential pathogen

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In this study, the changes in bacterial community and prevalence of foodborne pathogens on lettuce in different seasons were investigated using 16S rRNA gene-based sequencing. The results revealed significant differences in microbial communities and relative abundance of potential pathogens among different seasons. In addition, seasonal biomarkers and microbial association networks of microbiota on lettuce samples were detected. These findings provide basic data for food safety management to predict and prevent future outbreaks.
Lettuce is one of the most consumed vegetables worldwide. However, it has potential risks associated with pathogenic bacterial contamination because it is usually consumed raw. In this study, we investigated the changes in the bacterial community on lettuce (Lactuca sativa L.) in Chungcheong-do, South Korea, and the prevalence of foodborne pathogens on lettuce in different seasons using 16S rRNA gene-based sequencing. Our data revealed that the Shannon diversity index showed the same tendency in term of the number of OTUs, with the index being greatest for summer samples in comparison to other seasons. Moreover, the microbial communities were significantly different between the four seasons. The relative abundance of Actinobacteriota varied according to the season. Family Micrococcaceae was most dominant in all samples except summer, and Rhizobiaceae was predominant in the microbiome of the summer sample. At the genus level, the relative abundance of Bacillus was greatest in spring samples, whereas Pseudomonas was greatest in winter samples. Potential pathogens, such as Staphylococcus and Clostridium, were detected with low relative abundance in all lettuce samples. We also performed metagenome shotgun sequencing analysis on the selected summer and winter samples, which were expected to be contaminated with foodborne pathogens, to support 16S rRNA gene-based sequencing dataset. Moreover, we could detect seasonal biomarkers and microbial association networks of microbiota on lettuce samples. Our results suggest that seasonal characteristics of lettuce microbial communities, which include diverse potential pathogens, can be used as basic data for food safety management to predict and prevent future outbreaks.

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