A Genotypic Analysis of Five P. aeruginosa Strains after Biofilm Infection by Phages Targeting Different Cell Surface Receptors
Bibliographic record
Abstract
Antibiotic resistance constitutes one of the most serious threats to the global public health and urgently requires new and effective solutions. Bacteriophages are bacterial viruses increasingly recognized as being good alternatives to traditional antibiotic therapies. In this study, the efficacy of phages, targeting different cell receptors, against Pseudomonas aeruginosa PAO1 biofilm and planktonic cell cultures was evaluated over the course of 48h. Although significant reductions in the number of viable cells were achieved for both cases, the high level of adaptability of the bacteria in response to the selective pressure caused by phage treatment resulted in the emergence of phage-resistant variants. To further investigate the genetic makeup of phage-resistant variants isolated from biofilm infection experiments, some of these bacteria were selected for phenotypic and genotypic characterization. Whole genome sequencing was performed on five phage-resistant variants and all of them carried mutations affecting the galU gene as well as one of pil genes. The sequencing analysis further revealed that three of the P. aeruginosa PAO1 variants carry large deletions (> 200 kbp) in their genomes. Complementation of the galU mutants with wild-type galU in trans restored LPS expression on the bacterial cell surface of these bacterial strains and rendered the complemented strains to be sensitive to phages. This provides unequivocal evidence that inactivation of galU function was associated with resistance to the phages that uses LPS as primary receptors. Overall, this work demonstrates that P. aeruginosa biofilms can survive phage attack and develop phage-resistant variants exhibiting defective LPS production and loss of type IV pili that are well adapted to the biofilm mode of growth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".