Temperate phage-antibiotic synergy is widespread—extending to <i>Pseudomonas</i> —but varies by phage, host strain, and antibiotic pairing
Bibliographic record
Abstract
ABSTRACT Bacteriophages (phages) are bacterial-specific viruses that can be used alone or with antibiotics to reduce bacterial load. Most phages are unsuitable for therapy because they are “temperate” and can integrate into the host genome, forming a lysogen that is protected from subsequent phage infections. However, integrated phages can be awakened by stressors such as antibiotics. Supported by this interaction, here we explore the potential use of combined temperate phage and antibiotic against the multi-drug-resistant pathogen, Pseudomonas aeruginosa . In all, thirty-nine temperate phages were isolated from clinical strains, and a subset was screened for synergy with six antibiotics (ciprofloxacin, levofloxacin, meropenem, piperacillin, tobramycin, and polymyxin B), using checkerboard assays. Interestingly, our screen identified phages that can synergize with each antibiotic, despite their widely differing targets; however, these are highly phage-antibiotic and phage-host pairing specific. Screening across multiple clinical strains reveals that temperate phages can reduce the antibiotic minimum inhibitory concentration up to 32-fold, even in a resistant isolate, functionally re-sensitizing the bacterium to the antibiotic. Meropenem and tobramycin did not reduce the frequency of lysogens, suggesting a mechanism of action independent of the temperate nature of the phages. By contrast, ciprofloxacin and piperacillin were able to reduce the frequency of lysogeny, the former by inducing phages—as previously reported in E. coli . Curiously, synergy with piperacillin reduced lysogen survivors, but not by inducing the phages, suggesting an alternative mechanism for biasing the phage lysis-lysogeny equilibrium. Overall, our findings indicate that temperate phages can act as adjuvants in clinically relevant pathogens, even in the presence of antibiotic resistance, thereby drastically expanding their therapeutic potential. IMPORTANCE The recent discovery that otherwise therapeutically unusable temperate phages can potentiate the activity of antibiotics, resulting in a potent synergy, has only been tested in E. coli , and with a single model phage. Here, working with clinical isolates of Pseudomonas and phages from these isolates, we highlight the broad applicability of this synergy—across a variety of mechanisms but also highlight the limitations of predicting the phage, host, and antibiotic combinations that will synergize.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".