Robustness of evolution-informed treatments across the genomic diversity of Pseudomonas aeruginosa

Antibiotic resistance is a critical challenge in modern medicine. It causes 1.3 million deaths annually, and this number is rising. Addressing this evolution-based problem necessitates evolution-informed solutions. While various such strategies have shown promise in vitro, their effectiveness across a bacterial species remains largely unexplored, a crucial aspect for practical applications. In this thesis, I, therefore, approach the field of evolutionary medicine and evolution-informed treatment designs from a translational perspective to identify robust evolution-informed treatments across the species Pseudomonas aeruginosa, a critical and often multi-drug resistant human pathogen.

To ensure the robustness of treatments across the species P. aeruginosa, it is essential to use a panel that reflects its genomic diversity. This thesis evaluated the P. aeruginosa pangenome and provided a representative panel for functional analyses. With the help of newly developed high-throughput assays, this thesis elucidated the robustness of evolution-informed treatments utilizing physiological trade-offs and the rate of spontaneous antibiotic resistance.    

In summary, this thesis identified robust evolution-informed treatments and generated new ideas for treatment designs advancing the translation of evolution-informed treatments into the direction of clinical interventions.





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