Prophages block cell surface receptors to ensure survival of their viral progeny
Bibliographic record
Abstract
Summary In microbial communities, viruses compete for host cells to infect, and thus evolved diverse ways to inhibit their competitors. One mechanism is Superinfection exclusion (Sie), whereby a virus that has established an infection prevents a secondary infection. We identified a Pseudomonas prophage Sie protein that alters pilus dynamics through the pilus assembly chaperone, PilZ. This protein, known as Zip for Pil Z i nteracting p rotein, does not abrogate pilus activity, but fine tunes it, providing strong phage resistance without a fitness cost. This tuning is modulated through quorum sensing, which coordinates Zip production in concert with bacterial cell density to ensure maximal protection when bacterial populations are at the highest risk of phage infection. Most notably, Zip activity prevents internalization and destruction of phage progeny. We refer to this as the “anti-Kronos effect” after the Greek god who devoured his own children and show that it is a conserved feature of diverse prophage-encoded Sie systems.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".