Adaptive genomic plasticity in large-genome, broad-host–range vibrio phages
Bibliographic record
Abstract
The host range of a bacteriophage-the diversity of hosts it can infect-is central to understanding phage ecology and applications. Whereas most well-characterized phages have narrow host ranges, broad-host-range phages represent an intriguing component of marine ecosystems. The genetic and evolutionary mechanisms driving their generalism remain poorly understood. In this study, we analyzed Schizotequatroviruses and their Vibrio crassostreae hosts, collected from an oyster farm. Schizotequatroviruses exhibit broad host ranges, large genomes (~252 kbp) encoding 26 transfer ribonucleic acids, and conserved genomic organization interspersed with recombination hotspots. These recombination events, particularly in regions encoding receptor-binding proteins and antidefense systems, highlight their adaptability to host resistance. Some lineages demonstrated the ability of receptor-switching between OmpK and LamB. Despite their broad host range, Schizotequatroviruses were rare in the environment. Their scarcity could not be attributed to burst size, which was comparable to other phages in vitro, but may result from ecological constraints or fitness trade-offs, such as their preference for targeting generalist vibrios in seawater rather than the patho-phylotypes selected in oyster farms. Our findings clarify the genetic and ecological variables shaping Schizotequatrovirus generalism and provide a foundation for future phage applications in aquaculture and beyond.
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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 | 0.001 | 0.001 |
| 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".