Genome sequence and functional genomic analysis of the oil-degrading bacterium Oleispira antarctica
Bibliographic record
Abstract
Ubiquitous bacteria from the genus Oleispira drive oil degradation in the largest environment on Earth, the cold and deep sea. Here we report the genome sequence of Oleispira antarctica and show that compared with Alcanivorax borkumensis—the paradigm of mesophilic hydrocarbonoclastic bacteria—O. antarctica has a larger genome that has witnessed massive gene-transfer events. We identify an array of alkane monooxygenases, osmoprotectants, siderophores and micronutrient-scavenging pathways. We also show that at low temperatures, the main protein-folding machine Cpn60 functions as a single heptameric barrel that uses larger proteins as substrates compared with the classical double-barrel structure observed at higher temperatures. With 11 protein crystal structures, we further report the largest set of structures from one psychrotolerant organism. The most common structural feature is an increased content of surface-exposed negatively charged residues compared to their mesophilic counterparts. Our findings are relevant in the context of microbial cold-adaptation mechanisms and the development of strategies for oil-spill mitigation in cold environments. Oleispira antarctica is an oil-degrading bacterium found in the cold and deep sea. Here Kube et al. report the genome sequence of O. antarcticaand provide a comprehensive functional genetic and protein structural analysis, revealing insights into how this organism has adapted to its cold 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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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 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".