Literature DB >> 12732507

Quantitative detection of methanotrophs in soil by novel pmoA-targeted real-time PCR assays.

Steffen Kolb1, Claudia Knief, Stephan Stubner, Ralf Conrad.   

Abstract

Methane oxidation in soils is mostly accomplished by methanotrophic bacteria. Little is known about the abundance of methanotrophs in soils, since quantification by cultivation and microscopic techniques is cumbersome. Comparison of 16S ribosomal DNA and pmoA (alpha subunit of the particulate methane monooxygenase) phylogenetic trees showed good correlation and revealed five distinct groups of methanotrophs within the alpha and gamma subclasses of Proteobacteria: the Methylococcus group, the Methylobacter/Methylosarcina group, the Methylosinus group, the Methylocapsa group, and the forest clones group (a cluster of pmoA sequences retrieved from forest soils). We developed quantitative real-time PCR assays with SybrGreen for each of these five groups and for all methanotrophic bacteria by targeting the pmoA gene. Detection limits were between 10(1) and 10(2) target molecules per reaction for all assays. Real-time PCR analysis of soil samples spiked with cells of Methylococcus capsulatus, Methylomicrobium album, and Methylosinus trichosporium recovered almost all the added bacteria. Only the Methylosinus-specific assay recovered only 20% of added cells, possibly due to a lower lysis efficiency of type II methanotrophs. Analysis of the methanotrophic community structure in a flooded rice field soil showed (5.0 +/- 1.4) x 10(6) pmoA molecules g(-1) for all methanotrophs. The Methylosinus group was predominant (2.7 x 10(6) +/- 1.1 x 10(6) target molecules g(-1)). In addition, bacteria of the Methylobacter/Methylosarcina group were abundant (2.0 x 10(6) +/- 0.9 x 10(6) target molecules g of soil(-1)). On the other hand, pmoA affiliated with the forest clones and the Methylocapsa group was below the detection limit of 1.9 x 10(4) target molecules g of soil(-1). Our results showed that pmoA-targeted real-time PCR allowed fast and sensitive quantification of the five major groups of methanotrophs in soil. This approach will thus be useful for quantitative analysis of the community structure of methanotrophs in nature.

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Year:  2003        PMID: 12732507      PMCID: PMC154495          DOI: 10.1128/AEM.69.5.2423-2429.2003

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  41 in total

1.  Quantification of ammonia-oxidizing bacteria in arable soil by real-time PCR.

Authors:  A Hermansson; P E Lindgren
Journal:  Appl Environ Microbiol       Date:  2001-02       Impact factor: 4.792

2.  Vertical distribution of the methanotrophic community after drainage of rice field soil.

Authors: 
Journal:  FEMS Microbiol Ecol       Date:  2001-01       Impact factor: 4.194

3.  PCR bias in ecological analysis: a case study for quantitative Taq nuclease assays in analyses of microbial communities.

Authors:  S Becker; P Böger; R Oehlmann; A Ernst
Journal:  Appl Environ Microbiol       Date:  2000-11       Impact factor: 4.792

4.  Evaluation of real-time quantitative PCR for identification and quantification of Chlamydia pneumoniae by comparison with immunohistochemistry.

Authors:  T Mygind; S Birkelund; E Falk; G Christiansen
Journal:  J Microbiol Methods       Date:  2001-09       Impact factor: 2.363

5.  Detection of methanotroph diversity on roots of submerged rice plants by molecular retrieval of pmoA, mmoX, mxaF, and 16S rRNA and ribosomal DNA, including pmoA-based terminal restriction fragment length polymorphism profiling.

Authors:  H P Horz; M T Yimga; W Liesack
Journal:  Appl Environ Microbiol       Date:  2001-09       Impact factor: 4.792

6.  Family- and genus-level 16S rRNA-targeted oligonucleotide probes for ecological studies of methanotrophic bacteria.

Authors:  J Gulledge; A Ahmad; P A Steudler; W J Pomerantz; C M Cavanaugh
Journal:  Appl Environ Microbiol       Date:  2001-10       Impact factor: 4.792

7.  Modeling amino acid replacement.

Authors:  T Müller; M Vingron
Journal:  J Comput Biol       Date:  2000       Impact factor: 1.479

8.  Evidence that particulate methane monooxygenase and ammonia monooxygenase may be evolutionarily related.

Authors:  A J Holmes; A Costello; M E Lidstrom; J C Murrell
Journal:  FEMS Microbiol Lett       Date:  1995-10-15       Impact factor: 2.742

9.  Expression of individual copies of Methylococcus capsulatus bath particulate methane monooxygenase genes.

Authors:  S Stolyar; M Franke; M E Lidstrom
Journal:  J Bacteriol       Date:  2001-03       Impact factor: 3.490

10.  Methane fluxes from differentially managed grassland study plots: the important role of CH4 oxidation in grassland with a high potential for CH4 production.

Authors:  C Kammann; L Grünhage; H J Jäger; G Wachinger
Journal:  Environ Pollut       Date:  2001       Impact factor: 8.071

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  94 in total

1.  Real-time quantitative PCR for assessment of abundance of Pseudoalteromonas species in marine samples.

Authors:  Torben L Skovhus; Niels B Ramsing; Carola Holmström; Staffan Kjelleberg; Ingela Dahllöf
Journal:  Appl Environ Microbiol       Date:  2004-04       Impact factor: 4.792

2.  Community structure, abundance, and activity of methanotrophs in the Zoige wetland of the Tibetan Plateau.

Authors:  Juanli Yun; Guoqiang Zhuang; Anzhou Ma; Hongguang Guo; Yanfen Wang; Hongxun Zhang
Journal:  Microb Ecol       Date:  2011-12-10       Impact factor: 4.552

3.  Composition of methane-oxidizing bacterial communities as a function of nutrient loading in the Florida everglades.

Authors:  Ashvini Chauhan; Ashish Pathak; Andrew Ogram
Journal:  Microb Ecol       Date:  2012-04-29       Impact factor: 4.552

4.  Molecular quantification of virulence gene-containing Aeromonas in water samples collected from different drinking water treatment processes.

Authors:  Chang-Ping Yu; Kung-Hui Chu
Journal:  Environ Monit Assess       Date:  2010-07-16       Impact factor: 2.513

5.  Recovery of methanotrophs from disturbance: population dynamics, evenness and functioning.

Authors:  Adrian Ho; Claudia Lüke; Peter Frenzel
Journal:  ISME J       Date:  2010-10-28       Impact factor: 10.302

6.  Impacts of inter- and intralaboratory variations on the reproducibility of microbial community analyses.

Authors:  Yao Pan; Levente Bodrossy; Peter Frenzel; Anne-Grethe Hestnes; Sascha Krause; Claudia Lüke; Marion Meima-Franke; Henri Siljanen; Mette M Svenning; Paul L E Bodelier
Journal:  Appl Environ Microbiol       Date:  2010-09-24       Impact factor: 4.792

7.  Landscape position influences microbial composition and function via redistribution of soil water across a watershed.

Authors:  Zhe Du; Diego A Riveros-Iregui; Ryan T Jones; Timothy R McDermott; John E Dore; Brian L McGlynn; Ryan E Emanuel; Xu Li
Journal:  Appl Environ Microbiol       Date:  2015-10-02       Impact factor: 4.792

8.  Effect of inhibition of acetoclastic methanogenesis on growth of archaeal populations in an anoxic model environment.

Authors:  Holger Penning; Ralf Conrad
Journal:  Appl Environ Microbiol       Date:  2006-01       Impact factor: 4.792

9.  Application of a newly developed ARB software-integrated tool for in silico terminal restriction fragment length polymorphism analysis reveals the dominance of a novel pmoA cluster in a forest soil.

Authors:  Peter Ricke; Steffen Kolb; Gesche Braker
Journal:  Appl Environ Microbiol       Date:  2005-03       Impact factor: 4.792

10.  Methanotrophic bacteria in oilsands tailings ponds of northern Alberta.

Authors:  Alireza Saidi-Mehrabad; Zhiguo He; Ivica Tamas; Christine E Sharp; Allyson L Brady; Fauziah F Rochman; Levente Bodrossy; Guy Cj Abell; Tara Penner; Xiaoli Dong; Christoph W Sensen; Peter F Dunfield
Journal:  ISME J       Date:  2012-12-20       Impact factor: 10.302

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