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Characterization of microbial communities in gas industry pipelines.

ABSTRACT: Culture-independent techniques, denaturing gradient gel electrophoresis (DGGE) analysis, and random cloning of 16S rRNA gene sequences amplified from community DNA were used to determine the diversity of microbial communities in gas industry pipelines. Samples obtained from natural gas pipelines were used directly for DNA extraction, inoculated into sulfate-reducing bacterium medium, or used to inoculate a reactor that simulated a natural gas pipeline environment. The variable V2-V3 (average size, 384 bp) and V3-V6 (average size, 648 bp) regions of bacterial and archaeal 16S rRNA genes, respectively, were amplified from genomic DNA isolated from nine natural gas pipeline samples and analyzed. A total of 106 bacterial 16S rDNA sequences were derived from DGGE bands, and these formed three major clusters: beta and gamma subdivisions of Proteobacteria and gram-positive bacteria. The most frequently encountered bacterial species was Comamonas denitrificans, which was not previously reported to be associated with microbial communities found in gas pipelines or with microbially influenced corrosion. The 31 archaeal 16S rDNA sequences obtained in this study were all related to those of methanogens and phylogenetically fall into three clusters: order I, Methanobacteriales; order III, Methanomicrobiales; and order IV, Methanosarcinales: Further microbial ecology studies are needed to better understand the relationship among bacterial and archaeal groups and the involvement of these groups in the process of microbially influenced corrosion in order to develop improved ways of monitoring and controlling microbially influenced corrosion.

SUBMITTER: Zhu XY

PROVIDER: S-EPMC194955 | biostudies-literature | 2003 Sep

REPOSITORIES: biostudies-literature

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Characterization of microbial communities in gas industry pipelines.

Zhu Xiang Y XY Lubeck John J Kilbane John J JJ

Applied and environmental microbiology 20030901 9

Culture-independent techniques, denaturing gradient gel electrophoresis (DGGE) analysis, and random cloning of 16S rRNA gene sequences amplified from community DNA were used to determine the diversity of microbial communities in gas industry pipelines. Samples obtained from natural gas pipelines were used directly for DNA extraction, inoculated into sulfate-reducing bacterium medium, or used to inoculate a reactor that simulated a natural gas pipeline environment. The variable V2-V3 (average siz ...[more]

PMID: 12957923

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Project description:This study provides a deep modern insight into the phylogenetic diversity among bacterial consortia found in working and nonworking high-methane natural gas pipelines located in Poland. The working pipeline was characterized by lower biodiversity (140-154 bacterial genera from 22 to 23 classes, depending on the source of the debris) in comparison to the off-gas pipeline (169 bacterial genera from 23 classes). The sediment recovered from the working pipeline contained mostly DNA identified as belonging to the phylum Firmicutes (66.4%-45.9% operational taxonomic units [OTUs]), predominantly Bacillus (41.4%-31.1% OTUs) followed by Lysinibacillus (2.6%-1.5% OTUs) and Clostridium (2.4%-1.8% OTUs). In the nonworking pipeline, Proteobacteria (46.8% OTUs) and Cyanobacteria (27.8% OTUs) were dominant. Over 30% of the Proteobacteria sequences showed homologies to Gammaproteobacteria, with Pseudomonas (7.1%), Enhydrobacter (2.1%), Stenotrophomonas (0.5%), and Haempohilus (0.4%) among the others. Differences were noted in terms of the chemical compositions of deposits originating from the working and nonworking gas pipelines. The deposits from the nonworking gas pipeline contained iron, as well as carbon (42.58%), sulphur (15.27%), and oxygen (15.32%). This composition can be linked to both the quantity and type of the resident microorganisms. The presence of a considerable amount of silicon (17.42%), and of aluminum, potassium, calcium, and magnesium at detectable levels, may likewise affect the metabolic activity of the resident consortia in the working gas pipeline. All the analyzed sediments included both bacteria known for causing and intensifying corrosion (e.g., Pseudomonas, Desulfovibrio, Shewanella, Serratia) and bacteria that can protect the surface of pipelines against deterioration (e.g., Bacillus). Biocorrosion is not related to a single mechanism or one species of microorganism, but results from the multidirectional activity of multiple microbial communities. The analysis presented here of the state of the microbiome in a gas pipeline during the real gas transport is a particularly valuable element of this work.

Project description:BackgroundMicrobiome studies commonly use 16S rRNA gene amplicon sequencing to characterize microbial communities. Errors introduced at multiple steps in this process can affect the interpretation of the data. Here we evaluate the accuracy of operational taxonomic unit (OTU) generation, taxonomic classification, alpha- and beta-diversity measures for different settings in QIIME, MOTHUR and a pplacer-based classification pipeline, using a novel software package: DECARD.ResultsIn-silico we generated 100 synthetic bacterial communities approximating human stool microbiomes to be used as a gold-standard for evaluating the colligative performance of microbiome analysis software. Our synthetic data closely matched the composition and complexity of actual healthy human stool microbiomes. Genus-level taxonomic classification was correctly done for only 50.4-74.8% of the source organisms. Miscall rates varied from 11.9 to 23.5%. Species-level classification was less successful, (6.9-18.9% correct); miscall rates were comparable to those of genus-level targets (12.5-26.2%). The degree of miscall varied by clade of organism, pipeline and specific settings used. OTU generation accuracy varied by strategy (closed, de novo or subsampling), reference database, algorithm and software implementation. Shannon diversity estimation accuracy correlated generally with OTU-generation accuracy. Beta-diversity estimates with Double Principle Coordinate Analysis (DPCoA) were more robust against errors introduced in processing than Weighted UniFrac. The settings suggested in the tutorials were among the worst performing in all outcomes tested.ConclusionsEven when using the same classification pipeline, the specific OTU-generation strategy, reference database and downstream analysis methods selection can have a dramatic effect on the accuracy of taxonomic classification, and alpha- and beta-diversity estimation. Even minor changes in settings adversely affected the accuracy of the results, bringing them far from the best-observed result. Thus, specific details of how a pipeline is used (including OTU generation strategy, reference sets, clustering algorithm and specific software implementation) should be specified in the methods section of all microbiome studies. Researchers should evaluate their chosen pipeline and settings to confirm it can adequately answer the research question rather than assuming the tutorial or standard-operating-procedure settings will be adequate or optimal.

Project description:Buried petroleum pipeline corrosion and leaks cause inevitable changes in the microbial communities of the surrounding soils. In addition, soils with different microbial communities can make different contributions to buried pipeline corrosion. Three kinds of soil samples of buried petroleum pipelines under different corrosion and petroleum contamination conditions were collected from the Shengli Oilfield of China to investigate the mutual influence between corrosion and the microbial communities of the surrounding soil. The 16S rRNA gene high-throughput Illumina MiSeq sequencing was used to analyze the microbial communities of different surrounding soils. Electrochemical tests were performed for steel corrosion investigation. The results showed that the microbial diversity of the surrounding soils of corroded pipelines with/without petroleum contamination (O-soil and C-soil, respectively) decreased significantly as compared with that of the non-corroded and non-contaminated ones (NC-soil). The C-soil contained more abundant Balneolaceae (Balneola, KSA1), Flavobacteriaceae (Muricauda, Gramella) and Desulfuromonadaceae (Pelobacter, Geoalkalibacter). The O-soil possessed a greater abundance of Halomonas, Pseudoalteromonas, Psychrobacter and Dietzia, which were reported to have a capacity for hydrocarbon degradation. Moreover, electrochemical measurements indicated that the microcosm of the C-soil and NC-soil promoted steel corrosion, while the C-soil community showed a slightly higher corrosion rate. However, the O-soil community mitigated the steel corrosion. These observations suggested that pipeline corrosion increased proportions of microorganisms, which are likely related to fermentation, sulfur respiration, iron respiration and manganese respiration in surrounding soils and enhanced the soil corrosivity, while petroleum contamination weakened the corrosion ability and promoted the growth of hydrocarbon-degrading organisms in the microbial community.

Dataset Information

Characterization of microbial communities in gas industry pipelines.

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Characterization of microbial communities in gas industry pipelines.

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