OBJECTIVES: To stepwise select tigecycline-resistant Escherichia coli mutants in vitro, determine the mutation rates, identify the resistance mechanisms, determine the resistance level and cross-resistance to other antibiotic classes, evaluate the fitness costs of tigecycline resistance mechanisms and investigate if the same in vitro-identified target genes were mutated in clinical isolates. METHODS: Spontaneous mutants with reduced susceptibility to tigecycline were selected on agar plates supplemented with tigecycline. Resistance levels and cross-resistance were evaluated by performing MIC assays and determining mutation rates using Luria-Delbruck fluctuation tests. Mutant fitness was estimated by measuring exponential growth rates, lag phase and total yield. Illumina whole-genome sequencing was used to identify mutations increasing MICs of tigecycline. RESULTS: Spontaneous mutants with reduced susceptibility to tigecycline were selected at a rate of ~10(-8) to 10(-6) per cell per generation; however, the clinical MIC breakpoint was not reached. The resistance level of tigecycline was low and some of the mutants had elevated MICs of hydrophobic drugs (chloramphenicol, erythromycin and novobiocin) or decreased MICs of SOS response inducers (ciprofloxacin and nitrofurantoin). Mutations were identified in efflux regulatory network genes (lon, acrR and marR) or lipopolysaccharide core biosynthesis pathway genes (lpcA, rfaE, rfaD, rfaC and rfaF). Mutations in the same target genes were found in clinical isolates. CONCLUSIONS: Tigecycline selects for low-level resistance mutations with relatively high mutation rates and the majority of them come with a substantial fitness cost. Further in vivo experiments are needed to evaluate how these mutations affect bacterial virulence and ability to establish a successful infection.
OBJECTIVES: To stepwise select tigecycline-resistant Escherichia coli mutants in vitro, determine the mutation rates, identify the resistance mechanisms, determine the resistance level and cross-resistance to other antibiotic classes, evaluate the fitness costs of tigecycline resistance mechanisms and investigate if the same in vitro-identified target genes were mutated in clinical isolates. METHODS: Spontaneous mutants with reduced susceptibility to tigecycline were selected on agar plates supplemented with tigecycline. Resistance levels and cross-resistance were evaluated by performing MIC assays and determining mutation rates using Luria-Delbruck fluctuation tests. Mutant fitness was estimated by measuring exponential growth rates, lag phase and total yield. Illumina whole-genome sequencing was used to identify mutations increasing MICs of tigecycline. RESULTS: Spontaneous mutants with reduced susceptibility to tigecycline were selected at a rate of ~10(-8) to 10(-6) per cell per generation; however, the clinical MIC breakpoint was not reached. The resistance level of tigecycline was low and some of the mutants had elevated MICs of hydrophobic drugs (chloramphenicol, erythromycin and novobiocin) or decreased MICs of SOS response inducers (ciprofloxacin and nitrofurantoin). Mutations were identified in efflux regulatory network genes (lon, acrR and marR) or lipopolysaccharide core biosynthesis pathway genes (lpcA, rfaE, rfaD, rfaC and rfaF). Mutations in the same target genes were found in clinical isolates. CONCLUSIONS:Tigecycline selects for low-level resistance mutations with relatively high mutation rates and the majority of them come with a substantial fitness cost. Further in vivo experiments are needed to evaluate how these mutations affect bacterial virulence and ability to establish a successful infection.
Authors: Lindsey E Nielsen; Erik C Snesrud; Fatma Onmus-Leone; Yoon I Kwak; Ricardo Avilés; Eric D Steele; Deena E Sutter; Paige E Waterman; Emil P Lesho Journal: Antimicrob Agents Chemother Date: 2014-08-04 Impact factor: 5.191