Evaluating the physical capture method of terminal restriction fragment length polymorphism for comparison of soil microbial communities

2007 ◽  
Vol 39 (2) ◽  
pp. 590-599 ◽  
Author(s):  
Christopher B. Blackwood ◽  
Jeffrey S. Buyer
Keyword(s):  
Restriction Fragment Length Polymorphism ◽  
Microbial Communities ◽  
Restriction Fragment ◽  
Length Polymorphism ◽  
Fragment Length ◽  
Fragment Length Polymorphism ◽  
Soil Microbial Communities ◽  
Soil Microbial ◽  
Capture Method ◽  
Restriction Fragment Length

scholarly journals Use of Multiplex Terminal Restriction Fragment Length Polymorphism for Rapid and Simultaneous Analysis of Different Components of the Soil Microbial Community▿

2006 ◽  
Vol 72 (11) ◽  
pp. 7278-7285 ◽  
Author(s):  
Brajesh K. Singh ◽  
Loic Nazaries ◽  
Stacey Munro ◽  
Ian C. Anderson ◽  
Colin D. Campbell
Keyword(s):  
Restriction Fragment Length Polymorphism ◽  
Microbial Communities ◽  
Restriction Fragment ◽  
Length Polymorphism ◽  
Fragment Length ◽  
Fragment Length Polymorphism ◽  
Soil Samples ◽  
Pine Forest ◽  
Pcr Products ◽  
Restriction Fragment Length

ABSTRACT A multiplex terminal restriction fragment length polymorphism (M-TRFLP) fingerprinting method was developed and validated for simultaneous analysis of the diversity and community structure of two or more microbial taxa (up to four taxa). The reproducibility and robustness of the method were examined using soil samples collected from different habitats. DNA was PCR amplified separately from soil samples using individual taxon-specific primers for bacteria, archaea, and fungi. The same samples were also subjected to a multiplex PCR with the primers for all three taxa. The terminal restriction fragment length polymorphism profiles generated for the two sets of PCR products were almost identical not only in terms of the presence of peaks but also in terms of the relative peak intensity. The M-TRFLP method was then used to investigate rhizosphere bacterial, fungal, and rhizobial/agrobacterial communities associated with the dwarf shrub Calluna vulgaris growing in either open moorland, a mature pine forest, or a transition zone between these two habitats containing naturally regenerating pine trees. Rhizosphere microbial communities associated with Vaccinium myrtillus collected from the native pine forest were also investigated. In this study, individual PCR products from the three taxa were also pooled before restriction digestion and fragment size analysis. The terminal restriction fragment length polymorphism profiles obtained with PCR products amplified individually and with multiplexed and pooled PCR products were found to be consistent with each other in terms of the number, position, and relative intensity of peaks. The results presented here confirm that M-TRFLP analysis is a highly reproducible and robust molecular tool for simultaneous investigation of multiple taxa, which allows more complete and higher resolution of microbial communities to be obtained more rapidly and economically.

scholarly journals Methodological Aspects of Multiplex Terminal Restriction Fragment Length Polymorphism-Technique to Describe the Genetic Diversity of Soil Bacteria, Archaea and Fungi

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3292 ◽  
Author(s):  
Agata Gryta ◽  
Magdalena Frąc
Keyword(s):  
Restriction Fragment Length Polymorphism ◽  
Microbial Diversity ◽  
Restriction Fragment ◽  
Length Polymorphism ◽  
Fragment Length ◽  
Fragment Length Polymorphism ◽  
Soil Microbial Diversity ◽  
Soil Dna ◽  
Soil Microbial ◽  
Restriction Fragment Length

The molecular fingerprinting methods used to evaluate soil microbial diversity could also be used as effective biosensors for the purposes of monitoring ecological soil status. The biodiversity of microorganisms is a relevant index of soil activity and there is a necessity to develop tools to generate reliable results for an emerging approach in the field of environmental control using microbial diversity biosensors. This work reports a method under development for determining soil microbial diversity using high efficiency Multiplex PCR-Terminal Restriction Fragment Length Polymorphism (M-T-RFLP) for the simultaneous detection of bacteria, archaea and fungi. Three different primer sets were used in the reaction and the analytical conditions were optimized. Optimal analytical conditions were achieved using 0.5 µM of primer for bacteria and 1 µM for archaea and fungi, 4 ng of soil DNA template, and HaeIII restriction enzyme. Comparative tests using the proposed analytical approach and a single analysis of each microorganism group were carried out to indicate that both genetic profiles were similar. The Jaccard similarity coefficient between single and multiplexing approach ranged from 0.773 to 0.850 for bacteria and fungi, and 0.208 to 0.905 for archaea. In conclusion, the multiplexing and pooling approaches significantly reduced the costs and time required to perform the analyses, while maintaining a proper effectiveness.

T-BAPS: A Bayesian Statistical Tool for Comparison of Microbial Communities Using Terminal-restriction Fragment Length Polymorphism (T-RFLP) Data

2007 ◽  
Vol 6 (1) ◽  
Author(s):  
Jing Tang ◽  
Jinglun Tao ◽  
Hidetoshi Urakawa ◽  
Jukka Corander
Keyword(s):  
Restriction Fragment Length Polymorphism ◽  
Microbial Communities ◽  
Restriction Fragment ◽  
Length Polymorphism ◽  
Fragment Length ◽  
Bayesian Model ◽  
Missing Values ◽  
Latent Class ◽  
Fragment Length Polymorphism ◽  
Restriction Fragment Length

The investigation of microbial communities is an essential part of the study of the biosphere. Flexible molecular fingerprinting tools such as terminal-restriction fragment length polymorphism (T-RFLP) analysis are often applied in the studies to enable the characterization of the microbial population. However, such data have so far been primarily analyzed using conventional clustering methods. Here we introduce a Bayesian model-based method for the purpose of comparing microbial communities using T-RFLP data. Such datasets have in general several challenging features, e.g. sparseness, missing values and structurally zero-valued observations. These features are taken into account by developing a Bayesian latent class mixture model for the observations in our framework. To make inferences under the model we use a recent Markov chain Monte Carlo (MCMC) -based method for the Bayesian model selection. To assess the introduced method we analyze both simulated and real datasets. The simulations show that our approach compares preferably to standard statistical clustering tools, such as k-means, hierarchical clustering, and Autoclass. The developed tool is freely available as a software package T-BAPS at http://www.abo.fi/fak/mnf/mate/jc/software/t-baps.html.

Sign in / Sign up

Export Citation Format

Share Document