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Impact of T-RFLP data analysis choices on assessments of microbial community structure and dynamics

BACKGROUND: Terminal restriction fragment length polymorphism (T-RFLP) analysis is a common DNA-fingerprinting technique used for comparisons of complex microbial communities. Although the technique is well established there is no consensus on how to treat T-RFLP data to achieve the highest possible...

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Autores principales: Fredriksson, Nils Johan, Hermansson, Malte, Wilén, Britt-Marie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4232699/
https://www.ncbi.nlm.nih.gov/pubmed/25381552
http://dx.doi.org/10.1186/s12859-014-0360-8
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author Fredriksson, Nils Johan
Hermansson, Malte
Wilén, Britt-Marie
author_facet Fredriksson, Nils Johan
Hermansson, Malte
Wilén, Britt-Marie
author_sort Fredriksson, Nils Johan
collection PubMed
description BACKGROUND: Terminal restriction fragment length polymorphism (T-RFLP) analysis is a common DNA-fingerprinting technique used for comparisons of complex microbial communities. Although the technique is well established there is no consensus on how to treat T-RFLP data to achieve the highest possible accuracy and reproducibility. This study focused on two critical steps in the T-RFLP data treatment: the alignment of the terminal restriction fragments (T-RFs), which enables comparisons of samples, and the normalization of T-RF profiles, which adjusts for differences in signal strength, total fluorescence, between samples. RESULTS: Variations in the estimation of T-RF sizes were observed and these variations were found to affect the alignment of the T-RFs. A novel method was developed which improved the alignment by adjusting for systematic shifts in the T-RF size estimations between the T-RF profiles. Differences in total fluorescence were shown to be caused by differences in sample concentration and by the gel loading. Five normalization methods were evaluated and the total fluorescence normalization procedure based on peak height data was found to increase the similarity between replicate profiles the most. A high peak detection threshold, alignment correction, normalization and the use of consensus profiles instead of single profiles increased the similarity of replicate T-RF profiles, i.e. lead to an increased reproducibility. The impact of different treatment methods on the outcome of subsequent analyses of T-RFLP data was evaluated using a dataset from a longitudinal study of the bacterial community in an activated sludge wastewater treatment plant. Whether the alignment was corrected or not and if and how the T-RF profiles were normalized had a substantial impact on ordination analyses, assessments of bacterial dynamics and analyses of correlations with environmental parameters. CONCLUSIONS: A novel method for the evaluation and correction of the alignment of T-RF profiles was shown to reduce the uncertainty and ambiguity in alignments of T-RF profiles. Large differences in the outcome of assessments of bacterial community structure and dynamics were observed between different alignment and normalization methods. The results of this study can therefore be of value when considering what methods to use in the analysis of T-RFLP data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-014-0360-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-42326992014-11-16 Impact of T-RFLP data analysis choices on assessments of microbial community structure and dynamics Fredriksson, Nils Johan Hermansson, Malte Wilén, Britt-Marie BMC Bioinformatics Methodology Article BACKGROUND: Terminal restriction fragment length polymorphism (T-RFLP) analysis is a common DNA-fingerprinting technique used for comparisons of complex microbial communities. Although the technique is well established there is no consensus on how to treat T-RFLP data to achieve the highest possible accuracy and reproducibility. This study focused on two critical steps in the T-RFLP data treatment: the alignment of the terminal restriction fragments (T-RFs), which enables comparisons of samples, and the normalization of T-RF profiles, which adjusts for differences in signal strength, total fluorescence, between samples. RESULTS: Variations in the estimation of T-RF sizes were observed and these variations were found to affect the alignment of the T-RFs. A novel method was developed which improved the alignment by adjusting for systematic shifts in the T-RF size estimations between the T-RF profiles. Differences in total fluorescence were shown to be caused by differences in sample concentration and by the gel loading. Five normalization methods were evaluated and the total fluorescence normalization procedure based on peak height data was found to increase the similarity between replicate profiles the most. A high peak detection threshold, alignment correction, normalization and the use of consensus profiles instead of single profiles increased the similarity of replicate T-RF profiles, i.e. lead to an increased reproducibility. The impact of different treatment methods on the outcome of subsequent analyses of T-RFLP data was evaluated using a dataset from a longitudinal study of the bacterial community in an activated sludge wastewater treatment plant. Whether the alignment was corrected or not and if and how the T-RF profiles were normalized had a substantial impact on ordination analyses, assessments of bacterial dynamics and analyses of correlations with environmental parameters. CONCLUSIONS: A novel method for the evaluation and correction of the alignment of T-RF profiles was shown to reduce the uncertainty and ambiguity in alignments of T-RF profiles. Large differences in the outcome of assessments of bacterial community structure and dynamics were observed between different alignment and normalization methods. The results of this study can therefore be of value when considering what methods to use in the analysis of T-RFLP data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-014-0360-8) contains supplementary material, which is available to authorized users. BioMed Central 2014-11-08 /pmc/articles/PMC4232699/ /pubmed/25381552 http://dx.doi.org/10.1186/s12859-014-0360-8 Text en © Fredriksson et al.; licensee BioMed Central Ltd. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology Article
Fredriksson, Nils Johan
Hermansson, Malte
Wilén, Britt-Marie
Impact of T-RFLP data analysis choices on assessments of microbial community structure and dynamics
title Impact of T-RFLP data analysis choices on assessments of microbial community structure and dynamics
title_full Impact of T-RFLP data analysis choices on assessments of microbial community structure and dynamics
title_fullStr Impact of T-RFLP data analysis choices on assessments of microbial community structure and dynamics
title_full_unstemmed Impact of T-RFLP data analysis choices on assessments of microbial community structure and dynamics
title_short Impact of T-RFLP data analysis choices on assessments of microbial community structure and dynamics
title_sort impact of t-rflp data analysis choices on assessments of microbial community structure and dynamics
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4232699/
https://www.ncbi.nlm.nih.gov/pubmed/25381552
http://dx.doi.org/10.1186/s12859-014-0360-8
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