Rapid diversification of <i>Pseudomonas aeruginosa</i> in cystic fibrosis lung-like conditions
Bibliographic record
Abstract
Abstract Chronic infection of the cystic fibrosis (CF) airway by the opportunistic pathogen Pseudomonas aeruginosa is the leading cause of morbidity and mortality for adult CF patients. Prolonged infections are accompanied by adaptation of P. aeruginosa to the unique conditions of the CF lung environment as well as marked diversification of the pathogen into phenotypically and genetically distinct strains that can coexist for years within a patient. Little is known, however, about the causes of this diversification and its impact on patient health. Here, we show experimentally that, consistent with ecological theory of diversification, the nutritional conditions of the CF airway can cause rapid and extensive diversification of P. aeruginosa. The increased viscosity associated with the thick mucous layer in the CF airway had little impact on within-population diversification but did promote divergence among populations. Notably, in vitro evolution recapitulated patho-adaptive traits thought to be hallmarks of chronic infection, including reduced motility and increased biofilm formation, and the range of phenotypes observed in a collection of clinical isolates. Our results suggest that nutritional complexity and reduced dispersal can drive evolutionary diversification of P. aeruginosa independent of other features of the CF lung such as an active immune system or the presence of competing microbial species. They also underscore the need to obtain diverse samples of P. aeruginosa when developing treatment plans. We suggest that diversification, by generating extensive phenotypic and genetic variation on which selection can act, may be a key first step in the transition from transient to chronic infection. Significance Statement Chronic infection with the opportunistic pathogen Pseudomonas aeruginosa is the leading cause of lung transplant or death in cystic fibrosis patients. P. aeruginosa diversifies in the CF lung, although why this happens remains a mystery. We allowed P. aeruginosa to evolve in the laboratory under a range of conditions approximating the CF lung. The diversity of evolved populations was highest, and most closely resembled the range of phenotypes among clinical isolates, in environments resembling the spectrum of nutritional resources available in the CF lung. Our results point to the nutritional complexity of the CF lung as a major driver of diversification and they suggest that diversity could be important in the development of chronic infections.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".