Large freshwater phages with the potential to augment aerobic methane oxidation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There is growing evidence that phages with unusually large genomes are common across various microbiomes, but little is known about their genetic inventories or potential ecosystem impacts. In the present study, we reconstructed large phage genomes from freshwater lakes known to contain bacteria that oxidize methane. Of manually curated genomes, 22 (18 are complete), ranging from 159 kilobase (kb) to 527 kb 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 sequences show high similarity to (>90%), and affiliate phylogenetically with, those of coexisting bacterial methanotrophs, including members of Methyloparacoccus, Methylocystis and Methylobacter spp. In addition, pmoC-phage abundance patterns correlate with those of the coexisting bacterial methanotrophs, supporting host-phage relationships. Future work is needed to determine whether phage-associated PmoC has similar functions to additional copies of PmoC encoded in bacterial genomes, thus contributing to growth on methane. Transcriptomics data from Lake Rotsee (Switzerland) showed that some phage-associated pmoC genes were highly expressed in situ and, of interest, that the most rapidly growing methanotroph was infected by three pmoC-phages. Thus, augmentation of bacterial methane oxidation by pmoC-phages during infection could modulate the efflux of this potent greenhouse gas into the environment.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 it