Ecological constraints foster both extreme viral-host lineage stability and mobile element diversity in a marine community
Bibliographic record
Abstract
ABSTRACT Phages are typically viewed as very rapidly evolving biological entities. Little is known, however, about whether and how phages can establish long-term genetic stability. We addressed this eco-evolutionary question in an open marine animal associated system, through two longitudinal samplings years apart in an oyster farm, obtaining >1,000 virulent phages and >600 Vibrio crassostreae strains. Surprisingly, lineages of phage and bacteria were very persistent, with some phages remaining strictly identical after four years. The phage-vibrio infection network remained modular with multiple lineages co-habitating within individual oysters for long periods of time. Seasonal restriction of V. crassostreae , overwintering in wild oysters, and limited viral decay may explain phage stability. Oysters also act as hotspots of activity of diverse mobile genetic element (MGE), hosting plasmids, prophages, phage-plasmids and entirely new classes of satellite-plasmids. Our findings demonstrate how nested ecological constraints can stabilize viral lineages: oysters house vibrio populations that escape host immunity, vibrios restrict phages via receptors and defenses, and satellites parasitize their cognate helper phages. We suggest that ecological context can favor the long-term maintenance of viral lineages and stabilize MGE persistence in the ocean, even amid ongoing mutation and antagonistic co-evolution.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".