Trace gas oxidation genes and metabolism in bacterial communities from a high Arctic mineral cryosol over 13 years
Bibliographic record
Abstract
The trace gases carbon monoxide, hydrogen, and methane are important substrates for microbial growth in extreme environments.Evidence has emerged that bacteria in Antarctica and tropical deserts can function as chemoautotrophs by utilizing the energy gained by oxidizing these gases to fix carbon.Trace gas oxidizing bacteria are thought to be important primary producers in polar desert soils and may contribute to nutrient and greenhouse gas cycling, but it is not known how climate change will affect their abundance or activity.In this study, we aimed to determine how trace gas consumption by bacteria has changed over time.We compared metagenomes from high Arctic mineral cryosols obtained in 2011 from Axel Heiberg Island in Nunavut to metagenomes collected from the same site in summer 2024.Using culture-independent approaches, we discovered that the relative abundances of marker genes of trace gas oxidation were predicted with negative effects by soil moisture, which changed significantly over 13 years.In-situ soil gas flux experiments demonstrated that these mineral cryosols acted as sinks for atmospheric methane and hydrogen, but not for carbon monoxide, even though we observed transcripts for carbon monoxide dehydrogenases.We also obtained metagenome-assembled-genomes (MAGs) from the candidate class Ca.Dormibacteria, along with several MAGs capable of both trace gas oxidation and anaerobic respiration, making these organisms interesting candidates for astrobiology and extremophile studies.Our findings uncover metabolic flexibility of trace gas consuming bacteria and indicate that the relative abundance of some Arctic trace gas oxidizing bacteria could be altered by climate-driven changes in moisture.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".