Applied Microbiology and Biotechnology

, Volume 80, Issue 3, pp 365–380

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

  • Ursel M. E. Schütte
  • Zaid Abdo
  • Stephen J. Bent
  • Conrad Shyu
  • Christopher J. Williams
  • Jacob D. Pierson
  • Larry J. Forney
Mini-Review

DOI: 10.1007/s00253-008-1565-4

Cite this article as:
Schütte, U.M.E., Abdo, Z., Bent, S.J. et al. Appl Microbiol Biotechnol (2008) 80: 365. doi:10.1007/s00253-008-1565-4

Abstract

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.

Keywords

T-RFLP Microbial communities 16S rRNA genes Multivariate statistics 

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Ursel M. E. Schütte
    • 1
    • 5
  • Zaid Abdo
    • 2
    • 3
    • 5
  • Stephen J. Bent
    • 1
    • 5
  • Conrad Shyu
    • 4
  • Christopher J. Williams
    • 3
    • 5
  • Jacob D. Pierson
    • 1
    • 5
  • Larry J. Forney
    • 1
    • 5
  1. 1.Department of Biological SciencesUniversity of IdahoMoscowUSA
  2. 2.Department of MathematicsUniversity of IdahoMoscowUSA
  3. 3.Department of StatisticsUniversity of IdahoMoscowUSA
  4. 4.Department of PhysicsUniversity of IdahoMoscowUSA
  5. 5.Initiative for Bioinformatics and Evolutionary StudiesUniversity of IdahoMoscowUSA

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