title: Functional verification of computationally predicted qnr genes.
abstract: BACKGROUND
  The quinolone resistance (qnr) genes are widely distributed among bacteria. We recently developed and applied probabilistic models to identify tentative novel qnr genes in large public collections of DNA sequence data including fragmented metagenomes.
  
  
  RESULTS
  By using inducible recombinant expressions systems the functionality of four identified qnr candidates were evaluated in Escherichia coli. Expression of several known qnr genes as well as two novel candidates provided fluoroquinolone resistance that increased with elevated inducer concentrations. The two novel, functionally verified qnr genes are termed Vfuqnr and assembled qnr 1. Co-expression of two qnr genes suggested non-synergistic action.
  
  
  CONCLUSIONS
  The combination of a computational model and recombinant expression systems provides opportunities to explore and identify novel antibiotic resistance genes in both genomic and metagenomic datasets.
authors.affiliation: Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden. joakim.larsson@fysiologi.gu.se.
authors.forename: Carl-Fredrik
authors.initials: CF
authors.lastname: Flach
authors.forename: Fredrik
authors.initials: F
authors.lastname: Boulund
authors.forename: Erik
authors.initials: E
authors.lastname: Kristiansson
authors.forename: Dg Joakim
authors.initials: DJ
authors.lastname: Larsson
mesh_terms: D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D019295:Computational Biology; D003198:Computer Simulation; D024881:Drug Resistance, Bacterial / Q000235:genetics*; D004926:Escherichia coli / Q000187:drug effects / Q000235:genetics* / Q000378:metabolism; D029968:Escherichia coli Proteins / Q000235:genetics*; D024841:Fluoroquinolones / Q000494:pharmacology*; D008826:Microbial Sensitivity Tests; D008969:Molecular Sequence Data
chemical_list: D000900:Anti-Bacterial Agents; D029968:Escherichia coli Proteins; D024841:Fluoroquinolones; C485384:Qnr protein, E coli