Schütte Ursel M E, Abdo Zaid, Bent Stephen J, Shyu Conrad, Williams Christopher J, Pierson Jacob D, Forney Larry J
Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA.
Appl Microbiol Biotechnol. 2008 Sep;80(3):365-80. doi: 10.1007/s00253-008-1565-4. Epub 2008 Jul 22.
Terminal restriction fragment length polymorphism (T-RFLP) analysis is a popular high-throughput fingerprinting technique used to monitor changes in the structure and composition of microbial communities. This approach is widely used because it offers a compromise between the information gained and labor intensity. In this review, we discuss the progress made in T-RFLP analysis of 16S rRNA genes and functional genes over the last 10 years and evaluate the performance of this technique when used in conjunction with different statistical methods. Web-based tools designed to perform virtual polymerase chain reaction and restriction enzyme digests greatly facilitate the choice of primers and restriction enzymes for T-RFLP analysis. Significant improvements have also been made in the statistical analysis of T-RFLP profiles such as the introduction of objective procedures to distinguish between signal and noise, the alignment of T-RFLP peaks between profiles, and the use of multivariate statistical methods to detect changes in the structure and composition of microbial communities due to spatial and temporal variation or treatment effects. The progress made in T-RFLP analysis of 16S rRNA and genes allows researchers to make methodological and statistical choices appropriate for the hypotheses of their studies.
末端限制性片段长度多态性(T-RFLP)分析是一种常用的高通量指纹识别技术,用于监测微生物群落结构和组成的变化。这种方法被广泛应用,因为它在获得的信息和劳动强度之间提供了一种折衷。在这篇综述中,我们讨论了过去10年中16S rRNA基因和功能基因的T-RFLP分析所取得的进展,并评估了该技术与不同统计方法结合使用时的性能。基于网络的工具可用于进行虚拟聚合酶链反应和限制性酶切,极大地便利了T-RFLP分析中引物和限制性酶的选择。T-RFLP图谱的统计分析也有了显著改进,例如引入了区分信号和噪声的客观程序、图谱间T-RFLP峰的比对,以及使用多元统计方法来检测由于空间和时间变化或处理效应导致的微生物群落结构和组成的变化。16S rRNA和基因的T-RFLP分析所取得的进展使研究人员能够做出适合其研究假设的方法学和统计选择。