Characterizing and exploiting genetic trajectories towards antibiotic resistance
Abstract
Bacteria have an enormous genetic plasticity and adaptive potential that enables them toinhabit almost every ecological niche on this planet and respond to drastic environmental changes. While this bacterial diversity and flexibility is highly fascinating and provides us with immense resources, it can also put human health at risk, e.g. when pathogenic bacteria adapt to antibiotics and become resistant. As antibiotic resistant bacteria increase human morbidity and mortality it is crucial to take action. The antibiotic resistance crisis is addressed on multiple levels including governmental and non-governmental programs, education, public health campaigns as well as academic and industrial research in epidemiology, medicine, pharmacology,biology and chemistry. The work conductedin this thesis contributes to the antibiotic resistance research by providing novel tools to studyde novo antibiotic resistance evolution in a more systematic and high-throughput fashion. Moreover, these tools were utilized to characterize the genetic trajectories of de novo antibiotic resistance evolution,predominantly in the model organism Escherichiacoli. Genetic constrains were identified, like negative epistatic interactions between different resistance modes or collateral sensitivity, and subsequently exploited by creating a framework to rationally design drug combinations inorder to limit de novo resistance evolution. Finally, limitations in efficiency and geneticresponses to novel CRISPR-based antimicrobials were studied and based on the findings factors crucial to optimize killing efficiency were identified. In short, this thesis contributes to our understanding of antibiotic resistance evolution, providing suggestions for novel and improved treatment options that likely contribute to limiting resistance evolution and treatment of resistant bacteria
Info
Thesis PhD, 2019
UN SDG Classification
DK Main Research Area
Science/Technology
