ArticleGenome biology and evolution2022
Genomics of Diversification of Pseudomonas aeruginosa in Cystic Fibrosis Lung-like Conditions.
Article in Genome biology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Prioritization of Critical Factors for Surveillance of the Dissemination of Antibiotic Resistance inInternational journal of molecular sciences · 2023Pooled it
- Toward a Functional Genetics of Adaptation: Insights From Microbial Experimental Evolution.Genome biology and evolution · 2026Review
- Contribution of two-component regulatory systems to the acute-to-chronic infection transition ofJournal of bacteriology · 2026Review
- Article
- Attenuated Strains of Pseudomonas aeruginosa: A Promising Cell Factory for Rhamnolipid Production.Microbial biotechnology · 2025Review
- Article
- High-riskHeliyon · 2025Article
- Therapeutic Interventions forJournal of clinical medicine · 2024Review
- Article
- Co-occurring microflora and mucin driveISME communications · 2024Article
- Biofilm antimicrobial susceptibility through an experimental evolutionary lens.NPJ biofilms and microbiomes · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pseudomonas aeruginosa is among the most problematic opportunistic pathogens for adults with cystic fibrosis (CF), causing repeated and resilient infections in the lung and surrounding airways. Evidence suggests that long-term infections are associated with diversification into specialized types but the underlying cause of that diversification and the effect it has on the persistence of infections remains poorly understood. Here, we use evolve-and-resequence experiments to investigate the genetic changes accompanying rapid, de novo phenotypic diversification in lab environments designed to mimic two aspects of human lung ecology: spatial structure and complex nutritional content. After ∼220 generations of evolution, we find extensive genetic variation present in all environments, including those that most closely resemble the CF lung. We use the abundance and frequency of nonsynonymous and synonymous mutations to estimate the ratio of mutations that are selectively neutral (hitchhikers) to those that are under positive selection (drivers). A significantly lower proportion of driver mutations in spatially structured populations suggests that reduced dispersal generates subpopulations with reduced effective population size, decreasing the supply of beneficial mutations and causing more divergent evolutionary trajectories. In addition, we find mutations in a handful of genes typically associated with chronic infection in the CF lung, including one gene associated with antibiotic resistance. This demonstrates that many of the genetic changes considered to be hallmarks of CF lung adaptation can arise as a result of adaptation to a novel environment and do not necessarily require antimicrobial treatment, immune system suppression, or competition from other microbial species to occur.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.