Evolutionary Trajectories of Ciprofloxacin Resistance in P. aeruginosa Lung Biofilms: Mutation Dynamics, Metabolomic Shifts, and Collateral Sensitivity
Higazy, D.; Wang, K. C.; Bay, L.; Poulsend, S. S.; Jensen, P. R.; Moser, C.; Ciofu, O.
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The evolution of antimicrobial resistance (AMR) in chronic biofilms is often viewed as a unidirectional path toward higher fitness, yet the metabolic constraints governing these trajectories remain poorly understood. We performed a four-passage evolution experiment using a murine lung biofilm model to assess the impact of prolonged ciprofloxacin (CIP) exposure on resistance and host response. This approach integrated population-level adaptive dynamics, whole-genome sequencing (WGS), and NMR-based metabolomics, alongside histopathology and cytokine analysis. Prolonged CIP treatment accelerated resistance, with isolates reaching MICs of 8-12 mg/L (a 32- to 48-fold increase) by the fourth passage. WGS revealed distinct evolutionary trajectories: control isolates accumulated metabolic and regulatory mutations without susceptibility changes, while CIP-treated isolates exhibited a stepwise progression from metabolic adaptation to high-level resistance, marked by early nfxB and late gyrA mutations. Metabolomic profiling revealed progressive divergence, with PCA identifying the nfxB genotype as the primary driver of variation (49.1% of variance). This resistant metabolic state was characterized by the depletion of central carbon metabolites, including glucose and tyrosine, alongside the accumulation of essential amino acids. Importantly, these changes were accompanied by a distinct trade-off; high-level CIP resistance triggered collateral sensitivity to tobramycin and aztreonam. While CIP treatment ultimately reduced neutrophilic inflammation (p = 0.011) and mucin production (p = 0.0496), early-passage lungs exhibited transient elevations in pro-inflammatory cytokines (CXCL2, MMP2, TNF-). In conclusion, the adaptive trajectory to CIP resistance involves metabolic rewiring and collateral sensitivity, offering a framework to exploit the evolutionary costs of resistance in chronic biofilm infections.
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