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Rigshospitalet - a part of Copenhagen University Hospital
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Drug-Driven Phenotypic Convergence Supports Rational Treatment Strategies of Chronic Infections

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  • Lejla Imamovic
  • Mostafa Mostafa Hashim Ellabaan
  • Ana Manuel Dantas Machado
  • Linda Citterio
  • Tune Wulff
  • Soren Molin
  • Helle Krogh Johansen
  • Morten Otto Alexander Sommer
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Chronic Pseudomonas aeruginosa infections evade antibiotic therapy and are associated with mortality in cystic fibrosis (CF) patients. We find that in vitro resistance evolution of P. aeruginosa toward clinically relevant antibiotics leads to phenotypic convergence toward distinct states. These states are associated with collateral sensitivity toward several antibiotic classes and encoded by mutations in antibiotic resistance genes, including transcriptional regulator nfxB. Longitudinal analysis of isolates from CF patients reveals similar and defined phenotypic states, which are associated with extinction of specific sub-lineages in patients. In-depth investigation of chronic P. aeruginosa populations in a CF patient during antibiotic therapy revealed dramatic genotypic and phenotypic convergence. Notably, fluoroquinolone-resistant subpopulations harboring nfxB mutations were eradicated by antibiotic therapy as predicted by our in vitro data. This study supports the hypothesis that antibiotic treatment of chronic infections can be optimized by targeting phenotypic states associated with specific mutations to improve treatment success in chronic infections.

Original languageEnglish
JournalCell
Volume172
Issue number1-2
Pages (from-to)121-134.e14
ISSN0092-8674
DOIs
Publication statusPublished - 11 Jan 2018

    Research areas

  • Anti-Bacterial Agents/pharmacology, Bacterial Proteins/genetics, Cystic Fibrosis/complications, DNA-Binding Proteins/genetics, Drug Resistance, Bacterial, Evolution, Molecular, Humans, Male, Middle Aged, Mutation, Phenotype, Pseudomonas Infections/complications, Pseudomonas aeruginosa/drug effects, Selection, Genetic, Transcription Factors/genetics

ID: 56201679