A New Framework to Accurately Quantify Soil Bacterial Community Diversity from DGGE
Identifieur interne : 001961 ( Istex/Corpus ); précédent : 001960; suivant : 001962A New Framework to Accurately Quantify Soil Bacterial Community Diversity from DGGE
Auteurs : Jonathan Lalande ; Richard Villemur ; Louise DeschênesSource :
- Microbial Ecology [ 0095-3628 ] ; 2013-10-01.
Abstract
Abstract: Denaturing gradient gel electrophoresis (DGGE) has been and remains extensively used to assess and monitor the effects of various treatments on soil bacterial communities. Considering only abundant phylotypes, the diversity estimates produced by this technique have been proven to be uncorrelated to true community diversity. The aim of this paper was to develop a framework to estimate a community’s true diversity from DGGE. Developed using in silico DGGE profiles generated from published pyrosequencing datasets, this framework elongates the rank-abundance distributions (RADs) drawn by band quantification using the peak-to-signal ratio (PSR) parameter, which was proven to be related to bacterial richness. The ability to compare DGGE-based diversity estimates to the true diversity of communities led to a unique opportunity to identify potential pitfalls when analyzing DGGE gels with commercial analysis software programs and gain insight into the process of DNA band clustering in the profiles. Bacterial diversity was compared through richness, Shannon, and Simpson’s 1/D indices. Intermediate results demonstrated that, even though commercial gel analysis software programs were unable to produce consistent results throughout all samples, a newly developed Matlab-based framework unraveled the dominance profiles of communities from band quantification. Elongating these partial RADs using the PSRs extracted from the DGGE profiles chiefly made it possible to accurately estimate the true diversity of communities. For all the samples analyzed, the estimated Shannon and Simpson’s 1/D were accurate at ±10 %. Richness estimations were less accurate, ranging from −11 to 31 % of the expected values. The framework showed great potential to study the structure and diversity of soil bacterial communities.
Url:
DOI: 10.1007/s00248-013-0230-3
Links to Exploration step
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<Para>Denaturing gradient gel electrophoresis (DGGE) has been and remains extensively used to assess and monitor the effects of various treatments on soil bacterial communities. Considering only abundant phylotypes, the diversity estimates produced by this technique have been proven to be uncorrelated to true community diversity. The aim of this paper was to develop a framework to estimate a community’s true diversity from DGGE. Developed using in silico DGGE profiles generated from published pyrosequencing datasets, this framework elongates the rank-abundance distributions (RADs) drawn by band quantification using the peak-to-signal ratio (PSR) parameter, which was proven to be related to bacterial richness. The ability to compare DGGE-based diversity estimates to the true diversity of communities led to a unique opportunity to identify potential pitfalls when analyzing DGGE gels with commercial analysis software programs and gain insight into the process of DNA band clustering in the profiles. Bacterial diversity was compared through richness, Shannon, and Simpson’s 1/<Emphasis Type="Italic">D</Emphasis>
indices. Intermediate results demonstrated that, even though commercial gel analysis software programs were unable to produce consistent results throughout all samples, a newly developed Matlab-based framework unraveled the dominance profiles of communities from band quantification. Elongating these partial RADs using the PSRs extracted from the DGGE profiles chiefly made it possible to accurately estimate the true diversity of communities. For all the samples analyzed, the estimated Shannon and Simpson’s 1/<Emphasis Type="Italic">D</Emphasis>
were accurate at ±10 %. Richness estimations were less accurate, ranging from −11 to 31 % of the expected values. The framework showed great potential to study the structure and diversity of soil bacterial communities.</Para>
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<name type="personal" displayLabel="corresp"><namePart type="given">Jonathan</namePart>
<namePart type="family">Lalande</namePart>
<affiliation>École Polytechnique de Montréal, Chemical Engineering Department, CIRAIG, 2500 chemin de Polytechnique, H3T 1J4, Montréal, QC, Canada</affiliation>
<affiliation>E-mail: jonathan.lalande@polymtl.ca</affiliation>
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<name type="personal"><namePart type="given">Richard</namePart>
<namePart type="family">Villemur</namePart>
<affiliation>Environmental Microbiology Research Group, INRS–Institut Armand-Frappier Research Center, 531 boul. des Prairies, H7V 1B7, Laval, QC, Canada</affiliation>
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<name type="personal"><namePart type="given">Louise</namePart>
<namePart type="family">Deschênes</namePart>
<affiliation>École Polytechnique de Montréal, Chemical Engineering Department, CIRAIG, 2500 chemin de Polytechnique, H3T 1J4, Montréal, QC, Canada</affiliation>
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<abstract lang="en">Abstract: Denaturing gradient gel electrophoresis (DGGE) has been and remains extensively used to assess and monitor the effects of various treatments on soil bacterial communities. Considering only abundant phylotypes, the diversity estimates produced by this technique have been proven to be uncorrelated to true community diversity. The aim of this paper was to develop a framework to estimate a community’s true diversity from DGGE. Developed using in silico DGGE profiles generated from published pyrosequencing datasets, this framework elongates the rank-abundance distributions (RADs) drawn by band quantification using the peak-to-signal ratio (PSR) parameter, which was proven to be related to bacterial richness. The ability to compare DGGE-based diversity estimates to the true diversity of communities led to a unique opportunity to identify potential pitfalls when analyzing DGGE gels with commercial analysis software programs and gain insight into the process of DNA band clustering in the profiles. Bacterial diversity was compared through richness, Shannon, and Simpson’s 1/D indices. Intermediate results demonstrated that, even though commercial gel analysis software programs were unable to produce consistent results throughout all samples, a newly developed Matlab-based framework unraveled the dominance profiles of communities from band quantification. Elongating these partial RADs using the PSRs extracted from the DGGE profiles chiefly made it possible to accurately estimate the true diversity of communities. For all the samples analyzed, the estimated Shannon and Simpson’s 1/D were accurate at ±10 %. Richness estimations were less accurate, ranging from −11 to 31 % of the expected values. The framework showed great potential to study the structure and diversity of soil bacterial communities.</abstract>
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