ArticleMicroorganisms2016
Metagenomic Analyses Reveal That Energy Transfer Gene Abundances Can Predict the Syntrophic Potential of Environmental Microbial Communities.
Article in Microorganisms, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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
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Who cites it
4 citing papers in PubMed.
- Syntrophic Hydrocarbon Degradation in a Decommissioned Off-Shore Subsea Oil Storage Structure.Microorganisms · 2021Article
- Metagenomic Profiling and Microbial Metabolic Potential of Perdido Fold Belt (NW) and Campeche Knolls (SE) in the Gulf of Mexico.Frontiers in microbiology · 2020Article
- New Frontiers of Anaerobic Hydrocarbon Biodegradation in the Multi-Omics Era.Frontiers in microbiology · 2020Review
- Membrane Complexes ofFrontiers in microbiology · 2016Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hydrocarbon compounds can be biodegraded by anaerobic microorganisms to form methane through an energetically interdependent metabolic process known as syntrophy. The microorganisms that perform this process as well as the energy transfer mechanisms involved are difficult to study and thus are still poorly understood, especially on an environmental scale. Here, metagenomic data was analyzed for specific clusters of orthologous groups (COGs) related to key energy transfer genes thus far identified in syntrophic bacteria, and principal component analysis was used in order to determine whether potentially syntrophic environments could be distinguished using these syntroph related COGs as opposed to universally present COGs. We found that COGs related to hydrogenase and formate dehydrogenase genes were able to distinguish known syntrophic consortia and environments with the potential for syntrophy from non-syntrophic environments, indicating that these COGs could be used as a tool to identify syntrophic hydrocarbon biodegrading environments using metagenomic data.
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Registered trials
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