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Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

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2018 Impact Factor: 3.883

Front Envir Sci Eng    2012, Vol. 6 Issue (1) : 82-97    https://doi.org/10.1007/s11783-011-0306-6
REVIEW ARTICLE
Current molecular biologic techniques for characterizing environmental microbial community
Dawen GAO(), Yu TAO
State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China
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Abstract

Microbes are vital to the earth because of their enormous numbers and instinct function maintaining the natural balance. Since the microbiology was applied in environmental science and engineering more than a century ago, researchers desire for more and more information concerning the microbial spatio-temporal variations in almost every fields from contaminated soil to wastewater treatment plant (WWTP). For the past 30 years, molecular biologic techniques explored for environmental microbial community (EMC) have spanned a broad range of approaches to facilitate the researches with the assistance of computer science: faster, more accurate and more sensitive. In this feature article, we outlined several current and emerging molecular biologic techniques applied in detection of EMC, and presented and assessed in detail the application of three promising tools.

Keywords molecular biological technique      microbial community      denaturing gradient gel electrophoresis (DGGE)      terminal restriction fragment length polymorphism (T-RFLP)      environmental applications     
Corresponding Author(s): GAO Dawen,Email:gaodw@hit.edu.cn   
Issue Date: 01 February 2012
 Cite this article:   
Dawen GAO,Yu TAO. Current molecular biologic techniques for characterizing environmental microbial community[J]. Front Envir Sci Eng, 2012, 6(1): 82-97.
 URL:  
https://academic.hep.com.cn/fese/EN/10.1007/s11783-011-0306-6
https://academic.hep.com.cn/fese/EN/Y2012/V6/I1/82
Fig.1  Summary of molecular methods used for detecting and quantifying environmental microbial community (EMC). Others include SSCP, RISA, CLSM, TGGE, FAME and ARDRA etc. Data were collected from 608 articles distributed in nine frontier environment-concerned journals published on ISI web of knowledge (Thomson Reuters) with environmental microbial community structure as title/keywords/abstract in the latest 10 years. The nine journals are: , , , , , , , ,
Fig.1  Summary of molecular methods used for detecting and quantifying environmental microbial community (EMC). Others include SSCP, RISA, CLSM, TGGE, FAME and ARDRA etc. Data were collected from 608 articles distributed in nine frontier environment-concerned journals published on ISI web of knowledge (Thomson Reuters) with environmental microbial community structure as title/keywords/abstract in the latest 10 years. The nine journals are: , , , , , , , ,
Fig.2  Comparison of bacterial 16S rDNA gene community fingerprints (DGGE profile and respective UPGMA dendrogram) derived from biocake and mixed liquor sampled at different DO concentrations. The scale bar indicates the percentage similarity at the nodes. LDO, low DO (0.5 mg·L); MDO, moderate DO (2.0 mg·L); HDO, high DO (4.0 mg·L); AS, mixed liquor; BF, Biocake
Fig.2  Comparison of bacterial 16S rDNA gene community fingerprints (DGGE profile and respective UPGMA dendrogram) derived from biocake and mixed liquor sampled at different DO concentrations. The scale bar indicates the percentage similarity at the nodes. LDO, low DO (0.5 mg·L); MDO, moderate DO (2.0 mg·L); HDO, high DO (4.0 mg·L); AS, mixed liquor; BF, Biocake
Fig.3  Relative abundance, measured as the percentage of the total peak height for of a given restriction fragment, for samples from different locations and days. Labels indicate bands for OP11 C 13 (white), OP11 C2 (orange), (dark orange) (pink), (LGC) bacteria (olive green), and (light blue) []
Fig.3  Relative abundance, measured as the percentage of the total peak height for of a given restriction fragment, for samples from different locations and days. Labels indicate bands for OP11 C 13 (white), OP11 C2 (orange), (dark orange) (pink), (LGC) bacteria (olive green), and (light blue) []
Fig.4  Comparison between DGGE and T-RFLP methods based on the same samples. The samples were from an anammox bacteria enrichment SBR [] at different times. For T-RFLP analyses, the T-RFs larger than 900 bp and smaller than 50 bp were not counted. The arrow showed in the DGGE result reflected the poor separation of gel bands from each other
Fig.4  Comparison between DGGE and T-RFLP methods based on the same samples. The samples were from an anammox bacteria enrichment SBR [] at different times. For T-RFLP analyses, the T-RFs larger than 900 bp and smaller than 50 bp were not counted. The arrow showed in the DGGE result reflected the poor separation of gel bands from each other
resolution and sensitivitya)quantitative abilityb)operationc)costd)reference
DGGEmedium specificitylimited sensitivitynot quantitative, but semiquantitative with the assistance of special softwaremedium labor intensivetime-consumingmedium costa) [31,132], b) [49], c) [133], d) [134]
T-RFLPmedium resolutionhigh sensitivitylow detection limitsemiquantitativemedium time-consuming automatableinternet mass data sharingmedium high costa) [135], b)-c) [136], d) [135]
LH-PCRlow specificitylimited resolutionhigh sensitivequantitativesimple and quick operationgood reproducibilitymedium costa) [137], b) [138], c) [139], d) [140]
ARISAhigh specificityhigh throughputhigh sensitivitynot quantitative, but quantitative combined with other toolsgood reproducibilityrapid operationlow costa) [48,130,141,142], b) [143,144], c) [45,48], d) [130,142]
MAR-FISHlimited specificity High sensitivityquantitativerapid, but need careful and professional operationhigh costa) [145], b) [146-148], c)-d) [149]
SIPlimited specificitylow sensitivitynot quantitative, but quantitative combined with other tools like PLFArapid operation for PLFA-SIP and RNA-SIP, but time-consuming for DNA-SIPmedium high costa) [70,72,73], b) [73], c) [70,72,73], d) [70,72,73]
microarrayshigh specificityhigh throughputlimited sensitivity but CGA not includedquantitative/potential quantitative, depending on probe specificityincomplete function gene databaselabor intensive Time-consuminghigh costa) [76,78,150,151],b) [76,152],c) [76,78,79],d) [153,154]
Tab.1  Summaries of current and emerging molecular biologic techniques used in detection of EMC
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