Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Doctor of Philosophy

Program

Mathematics

Supervisor

Wahl, Lindi M.

Abstract

This thesis explores how elevations in mutation rates, also known as the rise of mutators, can be affected by two main factors: mutational biases and harsh environmental challenges. We show here that shifts in mutational biases -especially reductions or reversals- increase an organism's access to previously under-sampled mutations, resulting in higher frequencies of beneficial de novo mutations. Through a discrete-time mathematical model and simulations, we demonstrate that this enhanced access facilitates the rise of mutator strains with larger fitness effects. We also consider how evolutionary rescue can promote mutator lineages under abrupt or gradual environmental stress. Using branching processes and deterministic models, supported by simulations, we show that de novo mutators are likely to hitchhike due to evolutionary rescue events when the wildtype mutation rate is intermediate, while pre-existing mutators in the populations have a significant advantage when mutation costs are minimal due to low wildtype mutation rates. Unsurprisingly, the stronger a mutator is, the more effective it is if the wildtype mutation rate is low, while its relative advantage decreases in populations where the wildtype itself is a mutator. Finally, by analyzing cancer mutational data, we show that our theoretical predictions apply to human cancer. We find that non-hypermutated tumors exhibit a reversal of germline mutation biases such that a similar mutation spectrum across tissues shows signs of positive selection in cancer genes, whereas hypermutated tumors potentially access cancer-driver mutations through their high mutation rates without the need for bias shifts. Altogether, these findings underscore the important role that mutational biases and severe environmental stresses have on mutator emergence in asexual organisms, point to mechanisms of adaptive evolution and drug resistance development, and suggest possible therapeutical implications for the treatment of cancer.

Summary for Lay Audience

This thesis explores how changes in an organism's DNA, called mutations, provide one source for evolution. In particular, increases in mutation rates can be stimulated by many factors, out of which we study the effect of environmental pressures and potential changes in certain mutational patterns organisms might have. We demonstrate here that when such patterns change —especially when they weaken or reverse previous biases— organisms gain access to beneficial mutations previously inaccessible to them. This increased access can then allow the emergence of mutator strains that have higher mutation rates and are more capable of surviving and flourishing. Additionally, we explore how environmental stress can help mutator strains succeed. Our research indicates that new mutators can benefit from severe changes in their environment, especially when the mutation rate is originally moderate. Pre-existing mutators, on the other hand, can gain significant advantages when mutation rates in the population are lower. By analyzing data from human cancers, we show that our findings apply to mutations that can cause cancer as well. We suggest two main distinct mechanisms contributing to cancer development; some cancers have relatively low mutation rates but they reverse previous mutational patterns, while others can acquire crucial mutations through their high mutation rates without the need for any changes in mutation patterns. Overall, our findings highlight the essential roles of mutation patterns and environmental pressures in the evolution of organisms, particularly in their ability to adapt and develop resistance to treatments. This research could lead to new insights into cancer therapies and enhance our understanding of how cancer evolves.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Download

Share

COinS