Harnessing metabolic dependence-driven antibiotic synergy to eradicate tolerant Pseudomonas aeruginosa

Pseudomonas aeruginosa is a major nosocomial pathogen, and its antibiotic tolerance under low-metabolism conditions severely compromises clinical efficacy, presenting a significant therapeutic challenge.

A quantitative assessment of the metabolic dependence of clinically relevant antibiotics against P. aeruginosa was conducted, and a novel combination strategy capable of eradicating its low-metabolic populations was developed.

We established a gradient nutrient model (0%-100% LB) to simulate a continuum of metabolic states. Through linear regression analysis correlating ATP levels with bactericidal efficiency, we developed a Metabolic Dependence Index classification system. Leveraging this system, we designed a Strongly Metabolism-Dependent (SMD) + Weakly Metabolism-Dependent (WMD) synchronous combination strategy, which was subsequently validated using five clinical isolates.

Low-metabolism populations exhibited significantly reduced susceptibility to SMD agents but unaltered tolerance to WMD antibiotics. The SMD + WMD combination achieved enhanced killing of low-metabolism bacteria (>99.999% killing) with a marked dose reduction in vitro. This strategy also improved in vitro clearance efficacy compared to monotherapy. Collectively, our work provides a quantitative framework for targeting metabolic heterogeneity to overcome antibiotic tolerance.