Newly introduced genomic prophage islands are critical determinants of in vivo competitiveness in the Liverpool Epidemic Strain of <i>Pseudomonas aeruginosa</i>
Bibliographic record
Abstract
Pseudomonas aeruginosa isolates have a highly conserved core genome representing up to 90% of the total genomic sequence with additional variable accessory genes, many of which are found in genomic islands or islets. The identification of the Liverpool Epidemic Strain (LES) in a children's cystic fibrosis (CF) unit in 1996 and its subsequent observation in several centers in the United Kingdom challenged the previous widespread assumption that CF patients acquire only unique strains of P. aeruginosa from the environment. To learn about the forces that shaped the development of this important epidemic strain, the genome of the earliest archived LES isolate, LESB58, was sequenced. The sequence revealed the presence of many large genomic islands, including five prophage clusters, one defective (pyocin) prophage cluster, and five non-phage islands. To determine the role of these clusters, an unbiased signature tagged mutagenesis study was performed, followed by selection in the chronic rat lung infection model. Forty-seven mutants were identified by sequencing, including mutants in several genes known to be involved in Pseudomonas infection. Furthermore, genes from four prophage clusters and one genomic island were identified and in direct competition studies with the parent isolate; four were demonstrated to strongly impact on competitiveness in the chronic rat lung infection model. This strongly indicates that enhanced in vivo competitiveness is a major driver for maintenance and diversifying selection of these genomic prophage genes.
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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) | 0.001 | 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".