Genome-Wide Patterns of Recombination in the Opportunistic Human Pathogen Pseudomonas aeruginosa
Bibliographic record
Abstract
The bacterium Pseudomonas aeruginosa is a significant cause of acute nosocomial infections as well as chronic respiratory infections in patients with cystic fibrosis (CF). Recent reports of the intercontinental spread of a CF-specific epidemic strain, combined with high intrinsic levels of antibiotic resistance, have made this opportunistic pathogen an important public health concern. Strain-specific differences correlate with variation in clinical outcomes of infected CF patients, increasing the urgency to understand the evolutionary origin of genetic factors conferring important phenotypes that enable infection, virulence, or resistance. Here, we describe the genome-wide patterns of homologous and nonhomologous recombination in P. aeruginosa, and the extent to which the genomes are affected by these diversity-generating processes. Based on whole-genome sequence data from 32 clinical isolates of P. aeruginosa, we examined the rate and distribution of recombination along the genome, and its effect on the reconstruction of phylogenetic relationships. Multiple lines of evidence suggested that recombination was common and usually involves short stretches of DNA (200-300 bp). Although mutation was the main source of nucleotide diversity, the import of polymorphisms by homologous recombination contributed nearly as much. We also identified the genomic regions with frequent recombination, and the specific sequences of recombinant origin within epidemic strains. The functional characteristics of the genes contained therein were examined for potential associations with a pathogenic lifestyle or adaptation to the CF lung environment. A common link between many of the high-recombination genes was their functional affiliation with the cell wall, suggesting that the products of recombination may be maintained by selection for variation in cell-surface molecules that allows for evasion of the host immune system.
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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 | 0.001 | 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".