Antibiotic resistance has become a serious threat to human health (WHO Antibacterial Agents in Clinical Development: an Analysis of the Antibacterial Clinical Development Pipeline, Including Tuberculosis. Geneva: World Health Organization; 2017), and the ability to predict antibiotic resistance from genome sequencing has become a focal point for the medical community. With this genocentric prediction in mind, we were intrigued about two particular findings for a collection of clinical Pseudomonas aeruginosa isolates (Marvig et al. Nature Genetics 2015;47:57-64; Frimodt-Møller et al. Scientific Reports 2018;8:12512; Bartell et al. Nature Communications 2019;10:629): (i) 15 out of 52 genes found to be frequently targeted by adaptive mutations during the initial infection stage of cystic fibrosis airways ('candidate pathoadaptive genes') (Marvig et al. Nature Genetics 2015;47:57-64) were associated with antibiotic resistance (López-Causapé et al. Fronters in Microbiology 2018;9:685; López-Causapé et al. Antimicrobal Agents and Chemotherapy 2018;62:e02583-17); (ii) there was a parallel lack of resistance development and linkage to the genetic changes in these antibiotic-resistance-associated genes (Frimodt-Møller et al. Scientific Reports 2018;8:12512; Bartell et al. Nature Communications 2019;10:629). In this review, we highlight alternative selective forces that potentially enhance the infection success of P. aeruginosa and focus on the linkage to the 15 pathoadaptive antibiotic-resistance-associated genes, thereby showing the problems we may face when using only genomic information to predict and inform about relevant antibiotic treatment.
Keywords: Pseudomonas aeruginosa; antibiotic resistance; bacterial pathogens; genomics; persistent bacterial infections; phenomics.