Large Freshwater Phages with the Potential to Augment Aerobic Methane Oxidation
Bibliographic record
Abstract
Abstract There is growing evidence that phages with unusually large genomes are common across various natural and human microbiomes, but little is known about their genetic inventories or potential ecosystem impacts. Here, we reconstructed large phage genomes from freshwater lakes known to contain bacteria that oxidize methane. Twenty-two manually curated genomes (18 are complete) ranging from 159 to 527 kbp in length were found to encode the pmoC gene, an enzymatically critical subunit of the particulate methane monooxygenase, the predominant methane oxidation catalyst in nature. The phage-associated PmoC show high similarity (> 90%) and affiliate phylogenetically with those of coexisting bacterial methanotrophs, and their abundance patterns correlate with the abundances of these bacteria, supporting host-phage relationships. We suggest that phage PmoC has similar functions to additional copies of PmoC encoded in bacterial genomes, thus contribute to growth on methane. Transcriptomics data from one system showed that the phage-associated pmoC genes are actively expressed in situ . Augmentation of bacterial methane oxidation by pmoC-phages during infection could modulate the efflux of this powerful greenhouse gas into the 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".