Diversification of Pseudomonas aeruginosa Biofilm Populations under Repeated Phage Exposures Decreases the Efficacy of the Treatment
Bibliographic record
Abstract
Phage therapy has been proposed as a therapeutic alternative to antibiotics for the treatment of chronic, biofilm-related P. aeruginosa infections. To gain a deeper insight into the complex biofilm–phage interactions, we investigated in the present study the effect of three successive exposures to lytic phages of biofilms formed by the reference strains PAO1 and PA14 as well as of two sequential clinical P. aeruginosa isolates from the sputum of a patient with cystic fibrosis (CF). The Calgary device was employed as a biofilm model and the efficacy of phage treatment was evaluated by measurements of the biomass stained with crystal violet (CV) and of the cell density of the biofilm bacterial population (CFU/mL) after each of the three phage exposures. The genetic alterations of P. aeruginosa isolates from biofilms exposed to phages were investigated by whole-genome sequencing. We show here that the anti-biofilm efficacy of the phage treatment decreased rapidly with repeated applications of lytic phages on P. aeruginosa strains with different genetic backgrounds. Although we observed the maintenance of a small subpopulation of sensitive cells after repeated phage treatments, a fast recruitment of mechanisms involved in the persistence of biofilms to the phage attack occurred, mainly by mutations causing alterations of the phage receptors. However, mutations causing phage-tolerant phenotypes such as alginate-hyperproducing mutants were also observed. In conclusion, a decreased anti-biofilm effect occurred after repeated exposure to lytic phages of P. aeruginosa biofilms due to the recruitment of different resistance and tolerance mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".