Evolutionary Sweeps of Subviral Parasites and Their Phage Host Bring Unique Parasite Variants and Disappearance of a Phage CRISPR-Cas System
Bibliographic record
Abstract
With 1 to 4 million estimated cases annually, cholera is a disease of serious global concern in regions where access to safe drinking water is limited by inadequate infrastructure, inequity, or natural disaster. The Global Task Force on Cholera Control (GTFCC.org) considers outbreak surveillance to be a primary pillar in the strategy to reduce mortality from cholera worldwide. Therefore, developing a better understanding of temporal evolutionary changes in the causative agent of cholera, Vibrio cholerae, could help in those efforts. The significance of our research is in tracking the genomic shifts that distinguish V. cholerae outbreaks, with specific attention paid to current and historical trends in the arms race between V. cholerae and a cooccurring viral (bacteriophage) predator. Here, we discover additional diversity of a specific phage defense system in epidemic V. cholerae and document the loss of a phage-encoded CRISPR-Cas system, underscoring the dynamic nature of microbial populations across cholera outbreaks.
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 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".