Systematic combinatorial optimization of three-phage cocktails against multidrug-resistant Pseudomonas aeruginosa

Microbiology Spectrum

卷:14

Research Article

Meshack Tweya Omwega^1,2  Moses Gachoya³  Justin Nyasinga^1,3  Martin Georges^1,3  Collins Kigen^1,3  Kevin Kamanyi⁴  Samuel Nyamweya⁵  Erick Odoyo^1,3  Lillian Musila³ 

[1] Department of Applied Health Sciences, Kisii University, Kisii, Kenya

[2] Department of Pathology, Egerton University, Nakuru, Kenya

[3] Department of Medical Biochemistry and Parasitology, Kisii University, Kisii, Kenya

[4] Kenya Medical Research Institute, Kericho, Kenya

[5] Microbiology Hub Kericho, Walter Reed Army Institute of Research–Africa, Kericho, Kenya

关键词: bacteriophage therapy;    Pseudomonas aeruginosa;    antimicrobial resistance;    phage cocktails;    phage interactions;    synergy;    biofilm;    Highest Single Agent independence model;    combinatorial optimization;    Galleria mellonella;    invertebrate infection model;    phage cocktail design;   

DOI  :  10.1128/spectrum.04096-25

 received in 2025-12-19, accepted in 2026-04-08,  发布年份 2026

来源: American Society for Microbiology

【 摘 要 】

ABSTRACTMultidrug-resistant (MDR) Pseudomonas aeruginosa poses a significant global health threat, necessitating alternative therapeutic strategies. Bacteriophage therapy shows promise, but single-phage use is prone to resistance. Bacteriophage cocktails can address this issue, but they are typically formulated empirically without a systematic evaluation of constituent phage interactions. We employed a comprehensive combinatorial approach to optimize three-phage cocktails against clinical P. aeruginosa isolates. From 25 candidate bacteriophages, 5 were selected based on a broad host range (≥60% of 51 MDR P. aeruginosa clinical isolates). Ten possible three-phage cocktail combinations were systematically generated and evaluated using real-time Omnilog phenotypic microarray analysis. Phage interactions were quantified using the Highest Single Agent independence model to classify synergistic (Δ > +5%), neutral (−5% ≤ Δ ≤ +5%), or antagonistic (Δ < −5%) effects. Individual phage inhibition efficiencies ranged from 35.4% to 75.4%. Cocktail performance varied dramatically (16.1%–84.1% inhibition). Only one cocktail exhibited synergy, achieving 84.1% inhibition, an 8.7% improvement over the best individual phage. Four cocktails (40%) showed neutral interactions, while five (50%) demonstrated antagonistic effects. The optimal cocktail (Phages 1 + 3 + 4) demonstrated efficacy across six of eight diverse clinical isolates in biofilm inhibition assays (29%–63% biomass reduction, 2.7–3.6 log10 colony-forming unit reduction) and achieved 80% survival in Galleria mellonella versus 10% in infected controls. These findings demonstrate that phage cocktail optimization requires rational validation, as antagonistic interactions can occur, establishing a critical validation step before committing resources to in vivo efficacy studies.IMPORTANCEBacteriophage cocktails are increasingly proposed as alternatives to antibiotics against multidrug-resistant bacteria, yet their development remains largely empirical. This study challenges the assumption that the combination of effective phages yields additive or synergistic benefits. Through systematic evaluation of all possible three-phage combinations from five phages, we discovered that antagonistic interactions (50%) predominated over synergistic effects (10%), with some cocktails performing worse than individual phages. Using the Highest Single Agent independence model, we established a quantitative framework for rational cocktail design that identified a therapeutically superior formulation. This approach is generalizable across bacterial pathogens and provides a critical validation step for phage therapy development. Our findings demonstrate that rational testing of phage interactions is essential before in vivo or clinical translation, potentially preventing costly failures and accelerating the development of effective phage-based therapeutics against multidrug-resistant infections.

【 授权许可】

CC BY   
Copyright © 2026 Omwega et al.

【 图 表 】

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