Synergy between ciprofloxacin and temperate phages overcomes therapeutic limitations caused by lysogen formation
Bibliographic record
Abstract
Bacteriophages have proven invaluable in combatting drug-resistant bacteria. Bias towards exclusive use of obligately lytic phages has restricted the range of phage therapy, however, since at least half of all Caudovirecetes are temperate, and such phages remain the only option available for many problematic pathogens - including the notorious members of the Burkholderia cepacia complex (Bcc). Temperate phage-antibiotic synergy (tPAS), a unique strategy that leverages lysogen-forming phages as adjuvants to traditional antibiotics, has been validated for phages infecting E. coli and P. aeruginosa and is a major step towards normalization of temperate phages in therapeutics. In this report, we extend tPAS to Burkholderia phages and show that combining these phages with subinhibitory doses of ciprofloxacin overcomes natural limitations in antibacterial activity caused by lysogen formation. We further demonstrate that the magnitude of this effect correlates with the lysogenization frequencies of utilized phages, meaning tPAS is tailored specifically to otherwise ineffective, highly lysogenic phages. Finally, we observed heterogeneity in lysogen depletion rates among synergizing phages, suggesting 'complete' lysogen depletion is not required for antibacterial synergy. Our results support the use of temperate phages as synergizing adjuvants against Bcc species, thereby substantially expanding the limited arsenal of tools available for combating these pathogens.
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 | 0.000 |
| 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) | 0.001 | 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".