Rational Design of Resistance-Suppressing Phage-Antibiotic Cocktails via Receptor Tradeoffs

Bacteriophages (phages) are promising antibiotic alternatives, yet their utility is limited by rapid resistance evolution. Current phage-antibiotic combination strategies rely on empirical screening for efficacy in killing, which often fails to prevent resistance. Here, we establish a mechanistic framework to rationally design phage–antibiotic cotreatments that specifically suppress resistance by leveraging evolutionary tradeoffs. We show that traditional killing efficacy metrics do not predict resistance suppression. Instead, we identify predictable evolutionary trade-offs, including species-specific targets like TolC ( Escherichia coli ) and Type IV pili ( Pseudomonas aeruginosa ). We also identify a universal vulnerability for Gram-negative bacteria, lipopolysaccharide (LPS). We find that LPS-targeting phages are ubiquitous and that phage-steered LPS perturbation creates a predictable hypersensitivity to lipophilic antibiotics. This mechanistic trade-off, governed by physicochemical rules rather than drug-specific targets, directly correlates with resistance suppression. This framework shifts combination therapy from empirical screening to the a priori design of evolutionarily stable cocktails.