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变性高效液相色谱在微生物生态学中的应用:发酵罐污泥、堆肥及土壤群落分析

Application of denaturing high-performance liquid chromatography in microbial ecology: fermentor sludge, compost, and soil community profiling.

作者信息

Wagner Andreas Otto, Malin Cornelia, Illmer Paul

机构信息

Institute of Microbiology, University of Innsbruck, Technikerstrasse 25, A-6020 Innsbruck, Austria.

出版信息

Appl Environ Microbiol. 2009 Feb;75(4):956-64. doi: 10.1128/AEM.01411-08. Epub 2008 Dec 16.

Abstract

Genetic fingerprinting methods, such as denaturing gradient gel electrophoresis (DGGE), are used in microbial ecology for the analysis of mixed microbial communities but are associated with various problems. In the present study we used a new alternative method: denaturing high-performance liquid chromatography (dHPLC). This method was previously shown to work with samples from water and gut flora but had not yet been applied to complex environmental samples. In contrast to other publications dealing with dHPLC, we used a commonly available HPLC system. Samples from different origins (fermentor sludge, compost, and soil), all ecologically significant, were tested, and the 16S rRNA gene was amplified via PCR. After optimization of the HPLC elution conditions, amplicons of pure cultures and mixed microbial populations could be separated successfully. Systematic differentiation was carried out by a cloning approach, since fraction collection of the peaks did not result in satisfactory fragment separation. dHPLC was evaluated as a tool for microbial community analysis on a genetic level and demonstrated major improvements compared to gel-based fingerprinting methods, such as DGGE, that are commonly used in microbial ecology.

摘要

基因指纹分析方法,如变性梯度凝胶电泳(DGGE),在微生物生态学中用于分析混合微生物群落,但存在各种问题。在本研究中,我们使用了一种新的替代方法:变性高效液相色谱法(dHPLC)。该方法先前已证明可用于水和肠道菌群的样本,但尚未应用于复杂的环境样本。与其他涉及dHPLC的出版物不同,我们使用了一种常用的高效液相色谱系统。对来自不同来源(发酵罐污泥、堆肥和土壤)且均具有生态意义的样本进行了测试,并通过PCR扩增了16S rRNA基因。在优化了高效液相色谱洗脱条件后,纯培养物和混合微生物群体的扩增子能够成功分离。由于对峰进行馏分收集未能实现令人满意的片段分离,因此通过克隆方法进行了系统区分。dHPLC作为一种在基因水平上分析微生物群落的工具进行了评估,结果表明与微生物生态学中常用的基于凝胶的指纹分析方法(如DGGE)相比有了重大改进。

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