Mechanisms of Antibiotic Resistance Evolution

Abstract: The continuing emergence and spread of antibiotic resistant bacteria are a threat to various applications in modern medicine and impose a strong economic burden on health systems. The development of new antibiotics is slow and cannot counterbalance the dissemination of resistant bacteria. Thus, we need to find ways to reduce the rate of antibiotic resistance development. For this, we need to acquire a deeper understanding of the mechanisms underlying the evolution of antibiotic resistance.Here, we investigate the factors that govern how antibiotic resistance mechanisms affect bacterial fitness and the overall level of resistance. Using porin-deficient mutants of Escherichia coli, we show that upregulation of alternative porins provides compensatory mechanisms that can ameliorate the fitness costs associated with resistance. Furthermore, we demonstrate that the phenotypic effects of antibiotic resistance mutations are largely predictable, both in combination with each other as well as in different bacterial strains. However, outliers from this trend exemplify the limitations of solely relying on laboratory strains for the characterization of antibiotic resistance mechanisms. In contrast, strong epistatic interactions were observed in mutants evolved at sub-lethal concentrations of streptomycin. Despite these low concentrations and weak selective pressure, strains of Salmonella Typhimurium evolved high-level resistance, which followed completely different mutational pathways compared to high-level selection. Finally, we show that aminoglycoside resistance genes can be selected de novo from the expression of completely randomized nucleotide sequences. This demonstrates that new genes can arise from pools of non-coding sequences and that this process is relatively common.The studies presented in this thesis provide insights into the mechanistic basis of resistance evolution, including the mutational spectrum causing antibiotic resistance, compensatory pathways for growth-restoration and the influence of epistatic interactions on the phenotypic expression of resistance mutations. Understanding these factors in detail will enable us to better predict and prevent the emergence of antibiotic resistance development, through improvements in surveillance, treatment regimens and drug development.