T-RFLP-based differences in oral microbial communities as risk factor for development of oral diseases under stress
T-RFLP-based differences in oral microbial communities as risk factor for development of oral diseases under stress
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DOI：
10.1111/j.1758-2229.2012.00340.x
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发表时间：
2012-08-01
影响因子：
3.3
通讯作者：
Conrads, G.
中科院分区：
文献类型：
--
作者：
Horz, H. -P.;Ten Haaf, A.;Conrads, G.
人类口腔微生物组由大约800种不同的细菌物种组成，其中许多尚未培养。对它们与健康和疾病有关的动态和可变性仍然知之甚少。在这里，我们测试了一个假设，即压力引起的牙周病的出现是可预测的基础上的组成的初始微生物群。作为一个模型，我们分析了58个人执行一个具有挑战性的探险（暴露于各种压力因素，由于饮食，卫生，温度，身体和精神压力的变化）在喜马拉雅山脉（Annapurna Hessert）的偏远地区。在开始（Bhulbule）和七天后（马南）的目的地（海拔3000米的差异）采集斑块样品。28人保持无牙龈炎（第一组），而30名参与者出现牙周问题，主要是牙龈炎（第二组）。通过直接来自菌斑样品的扩增的16 S rRNA基因的T-RFLP分析来监测微生物群。基于使用T-Rex软件的加性-主-微生物-乘法-相互作用模型（AMMI），T-RF主效应的变异至少为95%，表明大多数变异是由于个体之间微生物群落的固有差异。然而，无论选择的分析参数如何，在组I和组II之间始终观察到高达3%的相互作用信号，但在两个采样时间点之间未观察到。异质性，多样性和相似性指数支持的数据表明，组I和II之间的显着差异已经出现临床症状之前。这些差异可能为使用口腔微生物群落的生态参数作为口腔疾病和感染发病的早期诊断标志物提供了基础。
The human oral microbiome is comprised of approximately 800 different bacterial species many of which are as yet uncultivated. Their dynamics and variability in relation to health and disease are still poorly understood. Here we tested the hypothesis that the emergence of stress-induced periodontal diseases is predictable based on the composition of the initial microbiota. As a model, we analysed 58 individuals performing a challenging expedition (exposure to various stress-factors due to changes in diet, hygiene, temperature, physical and mental stress) in remote regions of the Himalayans (Annapurna Himal). Plaque samples were taken at start (Bhulbule) and destination (3000 meter difference in altitude) seven days later (Manang). Twenty-eight individuals remained symptom-free (Group I) while 30 participants developed periodontal problems, mostly gingivitis (Group II). The microbiota was monitored via T-RFLP-analysis of amplified 16S rRNA genes directly from the plaque samples. Based on the Additive-Main-Effects-Multiplicative-Interactions-model (AMMI) using the T-Rex software variation from T-RF main effects was at least 95%, indicating that most variation was due to inherent differences in microbial communities among individuals. However, an interaction signal up to 3% was consistently observed between groups I and II but not between the two time points of sampling regardless of selected analytical parameters. The data, supported by heterogeneity, diversity and similarity indices indicated marked differences between groups I and II already prior the onset of clinical symptoms. These differences may provide the basis for using ecological parameters of oral microbial communities as early diagnostic marker for the onset of oral disorders and infections.