Within-patient evolution of Pseudomonas aeruginosa populations during antimicrobial treatment

Multidrug-resistant (MDR) Pseudomonas aeruginosa infections pose a major challenge to effective treatment. Understanding genomic adaptations during antimicrobial therapy in patients infected with this pathogen is crucial for preventing therapeutic failure. Here, we investigated the population diversity and evolution of P. aeruginosa collected longitudinally from six patients who evolved multidrug-resistant infections. Serial clinical P. aeruginosa single-colony isolates (n = 63) and culture-enriched metagenomic population samples (n = 39) were collected and subjected to whole-genome sequencing. The resulting data were used to characterize and compare the species composition, multi-locus sequence types (STs), and resistance-associated mutations present within each sample type. Single-colony isolate sequencing showed that each patient was infected with a single P. aeruginosa strain that accumulated mutations and became increasingly more antibiotic-resistant over time. Mutations in genes associated with β-lactam resistance, including ampC, ftsI, and mexR, arose over time and corresponded with changes in antimicrobial susceptibility in single-colony isolates. Species profiling of culture-enriched metagenomic populations revealed that all samples contained P. aeruginosa, but also additional gram-negative pathogens. Metagenomic analysis of culture-enriched populations identified resistance-associated mutations at low frequency, many of which were not identified in single-colony isolates from the same sample. In some cases, resistance-associated mutations initially detected at low frequency rose to fixation after antimicrobial treatment. Overall, this study shows that population-based metagenomic sequencing effectively captures the within-patient genomic diversity of P. aeruginosa during antimicrobial therapy and could aid the detection and interpretation of resistance-associated mutations in this pathogen.

Pseudomonas aeruginosa infections are notoriously difficult to treat and are associated with high rates of morbidity and mortality. While the genetic basis of resistance in P. aeruginosa is well documented in vitro, less is known about how resistance evolves within patients during antibiotic therapy. Standard approaches based on analysis of clonal isolates may miss within-patient diversity, potentially overlooking low-frequency mutations that contribute to treatment failure. In this study, we compared single-colony isolate whole-genome sequencing with culture-enriched metagenomic sequencing to monitor the evolution of P. aeruginosa populations in patients receiving antibiotic therapy. The culture-enriched metagenomic approach enabled the detection of emerging resistance mutations, such as low-frequency variants in ampC and ftsI, before these variants rose to fixation. It also revealed genetically resistant subpopulations missed by isolate sequencing alone. Overall, our findings highlight the value of population-based metagenomic sequencing in capturing bacterial adaptation during infection and underscore its potential to improve resistance surveillance and guide personalized antimicrobial therapy.