Evidence map›Paper›PMID 25227464›Full record

ArticlemBio2014

Environmental heterogeneity drives within-host diversification and evolution of Pseudomonas aeruginosa.

Trine Markussen, Rasmus Lykke Marvig, María Gómez-Lozano, Kasper Aanæs, Alexandra E Burleigh, Niels Høiby, Helle Krogh Johansen, Søren Molin, Lars Jelsbak

Abstract read
In one paragraph

Article in mBio, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 papers.

0numbers the graph read from it
0cells of the map it votes in
114citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

114 citing papers in PubMed.

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  12. bioRxiv : the preprint server for biology · 2025
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  13. Review
  14. Therapeutic Interventions forJournal of clinical medicine · 2024
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  19. Article
  20. Demographic fluctuations in bloodstreamnpj antimicrobials and resistance · 2024
    Article

54 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Trine MarkussenDepartment of Systems Biology, Technical University of Denmark, Lyngby, Denmark.
Rasmus Lykke MarvigDepartment of Systems Biology, Technical University of Denmark, Lyngby, Denmark.
María Gómez-LozanoDepartment of Systems Biology, Technical University of Denmark, Lyngby, Denmark.
Kasper AanæsDepartment of Otorhinolaryngology, Head and Neck Surgery, Rigshospitalet and Faculty of Health Sciences, Copenhagen, Denmark.
Alexandra E BurleighDepartment of Systems Biology, Technical University of Denmark, Lyngby, Denmark.
Niels Høiby
Helle Krogh JohansenDepartment of Clinical Microbiology, University Hospital, Rigshospitalet, Copenhagen, Denmark.
Søren MolinDepartment of Systems Biology, Technical University of Denmark, Lyngby, Denmark lj@bio.dtu.dk sm@bio.dtu.dk.
Lars JelsbakDepartment of Systems Biology, Technical University of Denmark, Lyngby, Denmark lj@bio.dtu.dk sm@bio.dtu.dk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

unlabelledMicrobial population polymorphisms are commonly observed in natural environments, including long-term infected hosts. However, the underlying processes promoting and stabilizing diversity are difficult to unravel and are not well understood. Here, we use chronic infection of cystic fibrosis airways by the opportunistic pathogen Pseudomonas aeruginosa as a system for investigating bacterial diversification processes during the course of infection. We analyze clonal bacterial isolates sampled during a 32-year period and map temporal and spatial variations in population diversity to different infection sites within the infected host. We show that the ancestral infecting strain diverged into distinct sublineages, each with their own functional and genomic signatures and rates of adaptation, immediately after initial colonization. The sublineages coexisted in the host for decades, suggesting rapid evolution of stable population polymorphisms. Critically, the observed generation and maintenance of population diversity was the result of partitioning of the sublineages into physically separated niches in the CF airway. The results reveal a complex within-host population structure not previously realized and provide evidence that the heterogeneity of the highly structured and complex host environment promotes the evolution and long-term stability of pathogen population diversity during infection. IMPORTANCE: Within-host pathogen evolution and diversification during the course of chronic infections is of importance in relation to therapeutic intervention strategies, yet our understanding of these processes is limited. Here, we investigate intraclonal population diversity in P. aeruginosa during chronic airway infections in cystic fibrosis patients. We show the evolution of a diverse population structure immediately after initial colonization, with divergence into multiple distinct sublineages that coexisted for decades and occupied distinct niches. Our results suggest that the spatial heterogeneity in CF airways plays a major role in relation to the generation and maintenance of population diversity and emphasize that a single isolate in sputum may not represent the entire pathogen population in the infected individual. A more complete understanding of the evolution of distinct clonal variants and their distribution in different niches could have positive implications for efficient therapy.

Indexed as

Evolution, MolecularAdaptation, PhysiologicalCloning, MolecularCystic FibrosisEnvironmentGenes, BacterialGenetics, PopulationGenomicsHost-Pathogen InteractionsHumansPhenotypePhylogenyPolymorphism, Single NucleotidePseudomonas aeruginosaPseudomonas InfectionsQuorum Sensing

Identifiers

PMID25227464
PMCPMC4172072

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

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.