ArticleMicrobiologyOpen2019
High-throughput sequencing approach in analysis of microbial communities colonizing natural gas pipelines.
Article in MicrobiologyOpen, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 11 citations in OpenAlex.
- Gas pipelines, highways for hydrogenotrophic spore-forming bacteria.ISME communications · 2026Article
- Microbially induced corrosion impacts on the oil industry.Archives of microbiology · 2022Review
- High-throughput sequencing approach in analysis of microbial communities colonizing natural gas pipelines.MicrobiologyOpen · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.