在两个口腔疾病群体中探索口腔细菌组成网络,使用NGS-分子诊断的融合方法
Jinuk Jeong1, Kung Ahn2, Kyeongeui Yun2,3
1Department of Bioconvergence Engineering, Dankook University, Yongin, 16890, Republic of Korea.
Genes & genomics
|June 7, 2024
概括
准确的细菌分类学分析对于了解口腔疾病至关重要. 这项研究将下一代测序与分子诊断结合起来,在口腔疾病患者中揭示物种级细菌网络,识别低酸盐减少细菌的频率.
科学领域:
- 微生物学 微生物学
- 口腔健康 口腔健康
- 基因组学就是基因组学.
背景情况:
- 口腔疾病与微生物社区不平衡有关.
- 与肠道微生物组相比,口腔微生物组数据有限.
- 标准的16S rRNA测序在物种层面面临着分类学错误分类的问题.
研究的目的:
- 探索口腔疾病患者的唾液中的物种级细菌组成网络.
- 将口腔微生物组数据与韩国特定的健康口腔微生物组数据进行比较.
- 为了解决目前口腔微生物组研究的局限性.
主要方法:
- 使用了全面的分子诊断 (qRT-PCR和桑格测序).
- 基于补充下一代测序 (NGS) 的16S V3-V4安普利康测序.
- 应用了NGS和分子诊断的融合方法.
主要成果:
- 与健康对照组相比,在口腔疾病组中观察到降酸盐细菌的频率明显较低.
- 准确的细菌分类学被确定为主要的殖民者,如链球菌和Actinomyces.
- 确定了一个细菌网络,病原体与与酸盐减少相关的核心物种形成联系.
结论:
- 引入了一种新的方法,可以在物种层面准确识别细菌组成网络.
- 融合NGS-分子诊断方法克服了分类学分类的挑战.
- 通过将口腔健康与细菌网络相关联,结果可以作为口腔疾病预防研究的参考材料.
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