The evolution of antibiotic resistance is shaped by interactions between genes, the chemical environment, and an antibiotic's mechanism of action. This thesis explores these interactions with experiments, theory, and analysis, seeking a mechanistic understanding of how different interactions between genes and drugs can enhance or constrain the evolution of antibiotic resistance. Chapter 1 investigates the effects of the chemical decay of an antibiotic. Tetracycline resistant and sensitive bacteria were grown competitively in the presence of tetracycline and its decay products. Antibiotic decay did not only remove selection for resistance, but long-lived decay products favored tetracycline sensitivity by inducing costly drug efflux pumps in the resistant strain. Selection against resistance by antibiotic-related compounds may contribute to the coexistence of drug-sensitive and resistant bacteria in nature. Chapter 2 investigates how genetic interactions can favor particular combinations of resistance-conferring mutations. All possible combinations of a set of trimethoprim resistance-conferring mutations in the drug's target gene were constructed and phenotyped. Incompatibilities between mutations arose in a high-order, not pairwise, manner. One mutation was found to induce this ruggedness and create a multi-peaked adaptive landscape. Chapters 1 and 2 observed that non-optimal expression of a drug resistance gene or a drug's target could compromise antibiotic resistance. Chapter 3 broadly characterizes non-optimal gene expression under antibiotic treatment, using a functional genetic screen to identify over one hundred pathways to antibiotic resistance through positive and negative changes in gene expression. Genes with the potential to confer antibiotic resistance were found to often go unused during antibiotic stress. The optimization of gene expression for drug-free growth was found to cause non-optimal expression under drug treatment, creating a situation where regulatory mutations can confer resistance by correcting errors in gene expression. Chapter 4 investigates whether it is beneficial to up-regulate the genes encoding antibiotic targets when they are inhibited. Drug target genes were quantitatively over-expressed, and drug resistance was found to not always increase, but alternatively to remain unchanged or even decrease. These diverse effects were explained by simple models that consider toxicity arising from gene over-expression, and mechanisms of drug action in which drugs induce harmful enzymatic reactions.

A new era of malaria eradication programs relies on increased knowledge of the parasite through sequencing of the Plasmodium genome. Programs call for re-orientation at specific epidemiological markers as regions move from control towards pre- and total elimination. However, relatively little is known about the effects of intervention strategies on the parasite population or if the epidemiological cues correspond to effects on the parasite population. We hypothesized that genomic tools could be used to track population changes in Plasmodium falciparum to detect significant shifts as eradication programs apply interventions. Making use of new whole-genome sequencing data as well as GWAS and other studies, we used SNPs as biological markers for regions associated with drug resistance as well as a set of neutral SNPs to identify individual parasites. By utilizing tools developed as proxy for full genomic sequencing of the human pathogen Plasmodium falciparum, we characterized and tracked parasite populations to test for changes over time and between populations. When applied to markers under selection - those associated with reduced antimalarial drug sensitivity - we were able to track migration of resistance-associated mutations in the population and identify new mutations with potential implications for resistance. Using a population genetic analysis toolbox to study changes in neutral allele frequencies in samples from the field, we found significant population changes over time that included restricted effective population size, reduced complexity of infections, and evidence for both clonal and epidemic propagation of parasites.

Epistasis describes non-additive interactions which affect gene expression and phenotype. It can happen on multiple levels, including on a genomic level with interactions between genes or even chromosomes affecting global patterns of gene expression. It can also happen within a gene itself, with epistatic interactions between amino acids affecting gene expression and resultant phenotypes. I present three studies in two organisms to study this phenomenon on a global-genomic scale, and also on a local-genic scale.

Modern-day management of infectious diseases is critically linked to the use of mathematical models to understand and predict dynamics at many levels, from the mechanisms of pathogenesis to the patterns of population-wide transmission and evolution. This thesis describes the development and application of mathematical techniques for HIV infection and dynamics on social networks. Treatment of HIV infection has improved dramatically in the past few decades but is still limited by the development of drug resistance and the inability of current therapies to completely eradicate the virus from an individual. We begin with a synthesis of the important evolutionary principles governing the HIV epidemic, emphasizing the role of modeling. We then describe a modeling framework to study the emergence of drug-resistant HIV within a patient. Our model integrates laboratory data and patient behavior, with the goal of predicting outcomes of clinical trials. Current results demonstrate how pharmacologic properties of antiretroviral drugs affect selection for drug resistance, and can explain drug-class-specific resistance risks. Thirdly, we describe models for a new class of drugs that aim to eliminate cells with latent viral infection. We provide estimates for the required efficacy of these drugs and describe the potential challenges of future clinical trials. Finally, models and mechanisms for understanding viral dynamics are increasingly finding applications outside traditional virology. They can be used to study the dynamics of behaviors, to help predict and intervene in their spread. We describe techniques for applying infectious disease models to social contagion, drawing on techniques for network epidemiology. We use this framework to interpret data on the interpersonal spread of health-related behaviors.

The malaria parasite, Plasmodium falciparum, has a demonstrated history of adaptation to antimalarials and host immune pressure. This ability unraveled global eradication programs fifty years ago and seriously threatens renewed efforts today. Despite the magnitude of the global health problem, little is known about the genetic mechanisms by which the parasite evades control efforts. Population genomic methods provide a new way to identify the mutations and genes responsible for drug resistance and other clinically important traits.

Malaria is a treatable communicable disease yet remains a common cause of death and disease especially among pregnant women and children. Most of malaria's worldwide burden disproportionately lies in Southeast Asia and Sub-Saharan Africa. Western medicine's 100+ year history of combating Plasmodium falciparum has taught us that the global population of malaria parasites has a unique and dangerous ability to rapidly evolve and spread drug resistance. Recently it was documented that resistance to the first-line antimalarial artemisinin may be developing in Southeast Asia.

published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

P-glycoprotein (Pgp, ABCB1) is a polyspecific efflux transporter implicated in multidrug resistance in human cancers. In this study, tetramethylrhodamine-5-carbonyl azide (AzTMR) was covalently crosslinked to the Pgp drug binding pocket with a stoichiometry of 1. The Pgp-AzTMR adduct was functionally equivalent to unlabelled Pgp and retained its ability to transport Hoechst 33342. The binding site of AzTMR in Pgp was nonpolar, with a similar environment to that of propanol. Pgp-AzTMR could bind a second drug molecule, with a higher affinity for H-site drugs and lower affinity for other R-site drugs. Unlabelled Pgp interacted with dimeric versions of known Pgp modulators, binding them with higher affinity than the monomer. These compounds were also found to either stimulate or inhibit Pgp ATPase activity depending on the concentration. Pgp-AzTMR was able to bind dimeric drugs, indicating that 3 substrate moieties can fit into the binding pocket. / The Canadian Cancer Society

Breast cancer is a major cause of cancer-related death among women throughout the world. Treatment of breast cancer often fails due to the development of resistance to both chemo- and radiotherapy. The aim of this study was to analyze and compare the response to radiation of MCF-7 breast adenocarcinoma cells and MCF-7 cells that are resistant to doxorubicin (MCF-7/DOX). The results presented in this thesis show that drug-resistant MCF-7/DOX cells survive high doses of radiation exposure better than MCF-7 cells. Moreover, the chemo- and radioresistance of MCF-7/DOX cells share common molecular mechanisms and loss of sensitivity to radiation in chemo-resistant cells may be explained by alterations in their DNA methylation profile. The results of experiments presented in this thesis may, therefore, serve as a first step for future analysis of tumour resistance to radio- and chemotherapy and for the development of novel epigenetic strategies for reversal of breast cancer resistance to cytotoxic treatment regimens. / xi, 98 leaves : ill. (some col.) ; 29 cm

Cytotoxic chemotherapy is extremely important in adjuvant treatment of breast cancer. Yet, tumours frequently acquire chemoresistance that correlates with increased aggressiveness and poor prognosis. Three theories exist describing how the resistance develops: genetic, epigenetic and karyotypic theory. The epigenetic theory is the least explored. Here we analyzed the role of the epigenetic phenomena in the acquisition of drug resistance. To do so, we employed genome wide screens of microRNA and gene expression, DNA methylation and complete genome hybridization. We identified three novel microRNA interactions involved in the chemoresistant phenotype. These three microRNAs displayed depressed expression in the resistant cell lines and we were able to re-establish some level of drug sensitivity through ectopic expression of these under expressed microRNAs. In addition, we described the role of DNA methylation in impacting expression of a wide range of genes, thus, contributing to the phenotype of chemoresistance. Furthermore, we revealed a distorted global DNA methylation pattern that coincides with massive instability of the resistant genome. Finally, our results present a striking similarity between gene expression, epigenetic profiles and chromosomal aberrations in two different drug resistant cell lines. Taken together, this project suggests that the acquisition of chemoresistant phenotype is epigenetic in nature and may arise with a predictable pattern. Elucidating the specifics of this pattern may in the future prove useful in developing treatment and prognostic chemoresistance biomarkers. / xiii, 116 leaves : ill. (some col.) ; 29 cm