Stable Isotope Probing Analysis of the Diversity and Activity of Methanotrophic Bacteria in Soils from the Canadian High Arctic
Bibliographic record
Abstract
The melting of permafrost and its potential impact on CH(4) emissions are major concerns in the context of global warming. Methanotrophic bacteria have the capacity to mitigate CH(4) emissions from melting permafrost. Here, we used quantitative PCR (qPCR), stable isotope probing (SIP) of DNA, denaturing gradient gel electrophoresis (DGGE) fingerprinting, and sequencing of the 16S rRNA and pmoA genes to study the activity and diversity of methanotrophic bacteria in active-layer soils from Ellesmere Island in the Canadian high Arctic. Results showed that most of the soils had the capacity to oxidize CH(4) at 4 degrees C and at room temperature (RT), but the oxidation rates were greater at RT than at 4 degrees C and were significantly enhanced by nutrient amendment. The DGGE banding patterns associated with active methanotrophic bacterial populations were also different depending on the temperature of incubation and the addition of nutrients. Sequencing of the 16S rRNA and pmoA genes indicated a low diversity of the active methanotrophic bacteria, with all methanotroph 16S rRNA and pmoA gene sequences being related to type I methanotrophs from Methylobacter and Methylosarcina. The dominance of type I methanotrophs over type II methanotrophs in the native soil samples was confirmed by qPCR of the 16S rRNA gene with primers specific for these two groups of bacteria. The 16S rRNA and pmoA gene sequences related to those of Methylobacter tundripaludum were found in all soils, regardless of the incubation conditions, and they might therefore play a role in CH(4) degradation in situ. This work is providing new information supporting the potential importance of Methylobacter spp. in Arctic soils found in previous studies and contributes to the limited body of knowledge on methanotrophic activity and diversity in this extreme environment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".