Weberviruses are gut-associated phages that infect <i>Klebsiella</i> spp
Bibliographic record
Abstract
Weberviruses are bacteriophages (phages) that can infect and lyse clinically relevant, multidrug-resistant (MDR) strains of Klebsiella. They are an attractive therapeutic option to tackle Klebsiella infections due to their high burst sizes, long shelf life, and associated depolymerases. In this study, we isolated and characterized seven new lytic phages and compared their genomes with those of their closest relatives. Gene-sharing network, ViPTree proteome, and terL gene-sequence-based analyses incorporating all publicly available webervirus genomes [n = 258 from isolates, n = 65 from metagenome-assembled genome (MAG) datasets] confirmed the seven phages as members of the genus Webervirus and identified a novel genus (Defiantjazzvirus) within the family Drexlerviridae. Using our curated database of 265 isolated phage genomes and 65 MAGs (n = 330 total), we found that weberviruses are distributed globally and primarily associated with samples originating from the gut: sewage (154/330, 47%), wastewater (83/330, 25%), and human faeces (66/330, 20%). We identified three distinct clusters of potential depolymerases encoded within the 330 genomes. Due to their global distribution, frequency of isolation and lytic activity against the MDR clinical Klebsiella strains used in this study, we conclude that weberviruses and their depolymerases show promise for development as therapeutic agents against Klebsiella spp.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".