Bacteriophages with the Ability to Degrade Uropathogenic Escherichia Coli Biofilms
Bibliographic record
Abstract
Escherichia coli-associated urinary tract infections (UTIs) are among the most common bacterial infections in humans. UTIs are usually managed with antibiotic therapy, but over the years, antibiotic-resistant strains of uropathogenic E. coli (UPEC) have emerged. The formation of biofilms further complicates the treatment of these infections by making them resistant to killing by the host immune system as well as by antibiotics. This has encouraged research into therapy using bacteriophages (phages) as a supplement or substitute for antibiotics. In this study we characterized 253 UPEC in terms of their biofilm-forming capabilities, serotype, and antimicrobial resistance. Three phages were then isolated (vB_EcoP_ACG-C91, vB_EcoM_ACG-C40 and vB_EcoS_ACG-M12) which were able to lyse 80.5% of a subset (42) of the UPEC strains able to form biofilms. Correlation was established between phage sensitivity and specific serotypes of the UPEC strains. The phages' genome sequences were determined and resulted in classification of vB_EcoP_ACG-C91 as a SP6likevirus, vB_EcoM_ACG-C40 as a T4likevirus and vB_EcoS_ACG-M12 as T1likevirus. We assessed the ability of the three phages to eradicate the established biofilm of one of the UPEC strains used in the study. All phages significantly reduced the biofilm within 2-12 h of incubation.
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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 | 0.000 |
| 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 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".