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Quantitatively Modelling the Transition from Non-Genetic to Genetic Antimicrobial Resistance
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- Author / Creator
- Guthrie, Joshua D
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Antimicrobial resistance is a growing global health crisis that requires an interdisciplinary approach to better understand and combat. Physics-based modelling has provided valuable insights into the underlying mechanisms of antimicrobial resistance and the quantitative behaviour of resistant cell populations. Antimicrobial resistance can arise through genetic mutations and from non-genetic mechanisms that arise due to underlying stochastic physical processes which occur during gene expression. Non-genetic resistance results in phenotypic heterogeneity in genetically identical cell populations, which enables a fraction of the population to survive during drug treatment. Although genetic and non-genetic mechanisms have been investigated individually, it remains unclear how non-genetic resistance alters the evolution of antimicrobial resistance. In this thesis, physics-based methods are used to develop and analyze a phenomenological model of cell population dynamics to investigate the evolution of antimicrobial resistance during drug treatment. The model quantifies the transition from reversible non-genetic resistance to permanent genetic resistance and is used to make quantitative predictions about antimicrobial resistance evolution in cell populations. A deterministic framework that utilizes population growth equations is used to investigate regimes where stochastic fluctuations in population dynamics are negligible and standard numerical methods are used to solve these equations. In regimes where stochastic fluctuations play an important role in the population dynamics leading to antimicrobial resistance, the model is reformulated in a stochastic framework as a set of continuous-time stochastic processes and simulated using Monte Carlo methods. The structure and parameter values of the model are guided by experimental studies of non-genetic and genetic antimicrobial resistance in fungi, with parameter scans being used to investigate changes in subpopulation fitness and their effect on the survival and evolution of the population. The research presented in this thesis supports previous experimental and qualitative findings of antimicrobial resistance evolution by showing quantitatively that non-genetic resistance aids the survival of cell populations undergoing drug treatment and increases the probability of an antimicrobial resistance mutation appearing in the population. Additionally, a novel hypothesis about the evolution of antimicrobial resistance in cell populations is suggested, namely that increased survival due to non-genetically resistant cells results in intraspecific competition between subpopulations and hinders the evolution of antimicrobial resistance. The research presented in this thesis has advanced our understanding of antimicrobial resistance by providing a quantitative framework for investigating the transition from non-genetic to genetic resistance.
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- Graduation date
- Spring 2024
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- Type of Item
- Thesis
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- Degree
- Master of Science
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- License
- This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.