Capturing dynamic phage-pathogen coevolution by clinical surveillance
Bibliographic record
Abstract
Abstract Bacteria harness diverse defense systems that protect against phage predation 1 , many of which are encoded on horizontally transmitted mobile genetic elements (MGEs) 2 . In turn, phages evolve counter-defenses 3 , driving a dynamic arms race that remains underexplored in human disease contexts. For the diarrheal pathogen Vibrio cholerae , a higher burden of its lytic phage, ICP1, in patient stool correlates with reduced disease severity 4 . However, direct molecular evidence of phage-driven selection of epidemic V. cholerae has not been demonstrated. Here, through clinical surveillance in cholera-endemic Bangladesh, we capture the acquisition of a parasitic anti-phage MGE, PLE11, that initiated a selective sweep coinciding with the largest cholera outbreak in recent records. PLE11 exhibited potent anti-phage activity against co-circulating ICP1, explaining its rapid and dominating emergence. We identify PLE11-encoded Rta as the novel defense responsible and provide evidence that Rta restricts phage tail assembly. Using experimental evolution, we predict phage counteradaptations against PLE11 and document the eventual emergence and selection of ICP1 that achieves a convergent evolutionary outcome. By probing how PLEs hijack phage structural proteins to drive their horizontal transmission while simultaneously restricting phage tail assembly, we discover that PLEs manipulate tail assembly to construct chimeric tails comprised of MGE and phage-encoded proteins. Collectively, our findings reveal the molecular basis of the natural selection of a globally significant pathogen and its virus in a clinically relevant context.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".