Effect of antibiotic therapy on human fecal microbiota and the relation to the development of Clostridium difficile
Effect of antibiotic therapy on human fecal microbiota and the relation to the development of Clostridium difficile
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DOI：
10.1007/s00248-007-9356-5
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发表时间：
2008-10-01
影响因子：
3.6
通讯作者：
Beaugerie, L.
中科院分区：
文献类型：
--
作者：
De La Cochetiere, M. F.;Durand, T.;Beaugerie, L.
胃肠道是一个复杂的生态系统。最近的研究表明，人类粪便微生物群是由一个微生物联合体组成的。众所周知，抗生素治疗改变了微生物群，促进了机会主义者的增殖，这些机会主义者可能占据以前无法获得的生态位。因此，重要的是表征常驻微生物群，以评估其潜在的能力，允许病原体的发展，如艰难梭菌。我们使用了260名受试者的样本，这些受试者参加了一项先前发表的抗生素相关性腹泻临床研究，我们调查了粪便显性常驻微生物群与艰难梭菌随后发展之间的可能关系。我们使用细菌16S rDNA分子谱结合偏最小二乘（PLS）回归分析。在抗生素治疗前第0天（D-0）和治疗开始后第14天（D-14）采集粪便样本。分离粪便DNA，用普通引物聚合酶链反应扩增16S rDNA的v6 ~ v8区，用时间温度梯度凝胶电泳（TTGE）分析。根据相似度（Pearson相关系数）对主要菌谱进行比较。采用PLS判别分析模型确定菌群特征。分析了D-0上87个TTGE剖面。所有病例的带型都很复杂。艰难梭菌随后的发病没有被TTGE谱的任何聚类所揭示，但被相应的PLS模型解释了高达46%。此外，该软件从TTGE档案中分派的438个区域中有6个恰好是针对获得艰难梭菌的患者组的。第一种方法在分子系统发育分析中显示出与未培养克隆相关的序列。对于D-14上的87个TTGE谱，也没有发现聚类，但对应的PLS模型解释了艰难梭菌的后续发病高达74.5%，从而证实了D-0上的结果。我们发现的微生物群的非详尽数据应作为评估容许菌群假设的第一步。PLS模型成功地用于预测艰难梭菌的发育。我们发现，在主要细菌方面的重要标准可以明显地被认为是艰难梭菌发展的易感因素。然而，抗生素相关性腹泻病例的常驻微生物群仍有待分析。此外，这些发现表明，加强粪便微生物群抵抗修饰能力的策略将具有临床意义。
The gastrointestinal tract is a complex ecosystem. Recent studies have shown that the human fecal microbiota is composed of a consortium of microorganism. It is known that antibiotic treatment alters the microbiota, facilitating the proliferation of opportunists that may occupy ecological niches previously unavailable to them. It is therefore important to characterize resident microbiota to evaluate its latent ability to permit the development of pathogens such as Clostridium difficile. Using samples from 260 subjects enrolled in a previously published clinical study on antibiotic-associated diarrhea, we investigated the possible relationship between the fecal dominant resident microbiota and the subsequent development of C. difficile. We used molecular profiling of bacterial 16S rDNA coupled with partial least square (PLS) regression analysis. Fecal samples were collected on day 0 (D-0) before antibiotic treatment and on day 14 (D-14) after the beginning of the treatment. Fecal DNA was isolated, and V6-to-V8 regions of the 16S rDNA were amplified by polymerase chain reaction with general primers and analyzed by temporal temperature gradient gel electrophoresis (TTGE). Main bacteria profiles were compared on the basis of similarity (Pearson correlation coefficient). The characteristics of the microbiota were determined using PLS discriminant analysis model. Eighty-seven TTGE profiles on D-0 have been analyzed. The banding pattern was complex in all cases. The subsequent onset of C. difficile was not revealed by any clustering of TTGE profiles, but was explained up to 46% by the corresponding PLS model. Furthermore, 6 zones out of the 438 dispatched from the TTGE profiles by the software happened to be specific for the group of patients who acquired C. difficile. The first approach in the molecular phylogenetic analysis showed related sequences to uncultured clones. As for the 87 TTGE profiles on D-14, no clustering could be found either, but the subsequent onset of C. difficile was explained up to 74.5% by the corresponding PLS model, thus corroborating the results found on D-0. The non exhaustive data of the microbiota we found should be taken as the first step to assess the hypothesis of permissive microbiota. The PLS model was used successfully to predict C. difficile development. We found that important criteria in terms of main bacteria could be markedly considered as predisposing factors for C. difficile development. Yet, the resident microbiota in case of antibiotic-associated diarrhea has still to be analyzed. Furthermore, these findings suggest that strategies reinforcing the ability of the fecal microbiota to resist to modifications would be of clinical relevance.