Advances in the use of terminal restriction fragment length polymorphism (T-RFLP) analysis of 16S rRNA genes to characterize microbial communities

• Published in: Applied microbiology and biotechnology 2008-09, Vol.80 (3), p.365-380
• Main Authors: Schütte, Ursel M. E, Abdo, Zaid, Bent, Stephen J, Shyu, Conrad, Williams, Christopher J, Pierson, Jacob D, Forney, Larry J
• Format: Article
• Language: English
• Subjects: 16S rRNA genes; Archaea - genetics; Automation; Bacteria - classification; Bacteria - genetics; Biological and medical sciences; Biotechnology; Cloning; DNA Fingerprinting - methods; DNA Primers - genetics; DNA, Ribosomal - genetics; Environmental Microbiology; Enzymes; Fundamental and applied biological sciences. Psychology; Fungi - genetics; Genes; Life Sciences; Microbial activity; Microbial communities; Microbial Genetics and Genomics; Microbiological Techniques - methods; Microbiology; Mini-Review; Multivariate statistics; Noise; Polymerase chain reaction; Polymorphism; Polymorphism, Restriction Fragment Length; Ribonucleic acid; RNA; RNA, Ribosomal, 16S - genetics; Statistical analysis; Statistical methods; Studies; T-RFLP
• ISSN: 0175-7598; 1432-0614
• DOI: 10.1007/s00253-008-1565-4

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.