Evolutionary genomics of epidemic and nonepidemic strains of <i>Pseudomonas aeruginosa</i>
Bibliographic record
Abstract
Pseudomonas aeruginosa is an opportunistic pathogen of humans and is a major cause of morbidity and mortality in patients with cystic fibrosis (CF). Prolonged infection of the respiratory tract can lead to adaptation of the pathogen to the CF lung environment. To examine the general patterns of adaptation associated with chronic infection, we obtained genome sequences from a collection of P. aeruginosa isolated from airways of patients with CF. Our analyses support a nonclonal epidemic population structure, with a background of unique, recombining genotypes, and the rare occurrence of successful epidemic clones. We present unique genome sequence evidence for the intercontinental spread of an epidemic strain shared between CF clinics in the United Kingdom and North America. Analyses of core and accessory genomes identified candidate genes and important functional pathways associated with adaptive evolution. Many genes of interest were involved in biological functions with obvious roles in this pathosystem, such as biofilm formation, antibiotic metabolism, pathogenesis, transport, reduction/oxidation, and secretion. Key factors driving the adaptive evolution of this pathogen within the host appear to be the presence of oxidative stressors and antibiotics. Regions of the accessory genome unique to the epidemic strain were enriched for genes in transporter families that efflux heavy metals and antibiotics. The epidemic strain was significantly more resistant than nonepidemic strains to three different antibiotics. Multiple lines of evidence suggest that selection imposed by the CF lung environment has a major influence on genomic evolution and the genetic characteristics of P. aeruginosa isolates causing contemporary infection.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 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".