期刊
FRONTIERS IN MICROBIOLOGY
卷 10, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fmicb.2019.01381
关键词
microbiota compositions; selective enrichment; Campylobacter; 16S rRNA sequencing; bacterial isolation
类别
资金
- Ministry of Food and Drug Safety in Korea [16162MFDS029]
- BK21 Plus Program of the Department of Agricultural Biotechnology, Seoul National University, Seoul, Korea
Since contaminated poultry meat is the major source of transmitting Campylobacter jejuni to humans, the isolation of Campylobacter from poultry carcasses is frequently performed in many countries as a baseline survey to ensure food safety. However, existing isolation methods have technical limitations in isolating this fastidious bacterium, such as a growth competition with indigenous bacteria in food samples. In this study, we compared the differences in microbiota compositions between Bolton and Preston selective media, two most common selective media to isolate Campylobacter, and investigated how different microbiota compositions resulting from different enrichment methods may affect isolation frequencies. A next-generation sequencing (NGS) analysis of 16S rRNA demonstrated that Bolton and Preston-selective enrichments generated different microbiota structures that shared only 31.57% of Operating Taxonomic Unit (OTU) types. Particularly, Escherichia was highly prevalent in Bolton selective media, and the enrichment cultures that increase Escherichia negatively affected the efficacy of Campylobacter isolation. Furthermore, the combination of the selective media made a significant difference in the isolation frequency. The Bolton broth and Preston agar combination exhibited the highest (60.0%) frequencies of Campylobacter isolation, whereas the Bolton broth and Bolton agar combination showed the lowest (2.5%). These results show that each selective medium generates a unique microbiota structure and that the sequence of combining the selective media also critically affects the isolation frequency by altering microbiota compositions. In this study, we demonstrated how a microbiota analysis using NGS can be utilized to optimize a protocol for bacterial isolation from food samples.
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