Kim Jinshil, Shin Hakdong, Park Hyeeun, Jung Hayan, Kim Junhyung, Cho Seongbeom, Ryu Sangryeol, Jeon Byeonghwa
Department of Food and Animal Biotechnology, Department of Agricultural Biotechnology, Center for Food and Bioconvergence, Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul, South Korea.
Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, South Korea.
Front Microbiol. 2019 Jun 21;10:1381. doi: 10.3389/fmicb.2019.01381. eCollection 2019.
Since contaminated poultry meat is the major source of transmitting to humans, the isolation of 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 , and investigated how different microbiota compositions resulting from different enrichment methods may affect isolation frequencies. A next-generation sequencing (NGS) analysis of 16S demonstrated that Bolton and Preston-selective enrichments generated different microbiota structures that shared only 31.57% of Operating Taxonomic Unit (OTU) types. Particularly, was highly prevalent in Bolton selective media, and the enrichment cultures that increase negatively affected the efficacy of r 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 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.
由于受污染的禽肉是向人类传播的主要来源，在许多国家，从家禽屠体中分离该菌作为一项基线调查经常进行，以确保食品安全。然而，现有的分离方法在分离这种苛求菌方面存在技术限制，例如与食品样本中的本土细菌存在生长竞争。在本研究中，我们比较了博尔顿（Bolton）和普雷斯顿（Preston）选择性培养基（两种最常用于分离该菌的选择性培养基）之间微生物群组成的差异，并研究了不同富集方法产生的不同微生物群组成如何影响分离频率。对16S的下一代测序（NGS）分析表明，博尔顿和普雷斯顿选择性富集产生了不同微生物群结构，它们仅共享31.57%的操作分类单元（OTU）类型。特别是，该菌在博尔顿选择性培养基中高度普遍，增加该菌的富集培养对其分离效率产生负面影响。此外，选择性培养基的组合对分离频率有显著影响。博尔顿肉汤和普雷斯顿琼脂组合的该菌分离频率最高（60.0%），而博尔顿肉汤和博尔顿琼脂组合的分离频率最低（2.5%）。这些结果表明，每种选择性培养基都会产生独特的微生物群结构，并且选择性培养基组合的顺序也会通过改变微生物群组成而严重影响分离频率。在本研究中，我们展示了如何利用基于NGS的微生物群分析来优化从食品样本中分离细菌的方案。
