Browsing by Subject "Tetrahydrofolate Dehydrogenase"
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Item Exploiting Evolutionary Tradeoffs to Fight Evolution of Antibiotic Resistance(2019-08-02) Tamer, Yusuf Talha; Reynolds, Kimberly A.; Rosen, Michael K.; Koh, Andrew Y.; Toprak, ErdalEvolution of antibiotic resistance is a growing public health problem around the world, and the identification of novel antimicrobials is no longer a viable approach to tackling this problem. To design smart technologies that take the evolutionary dimension into account, it is essential to understand the evolutionary process underlying the development of resistance. In nature, a single organism cannot be the most fit under all possible conditions, implying that bacterial populations that evolve resistance to antimicrobials should be less fit under other conditions. In this thesis, we report two examples of two tradeoffs in antibiotic-resistant bacterial populations. First, by studying biophysical and biochemical properties of the dihydrofolate reductase (DHFR) enzyme in Escherichia coli, we found that some mutations that conferred resistance to trimethoprim, a DHFR inhibitor, decreased drug affinity while substantially increasing substrate affinity. In addition, many of the epistatic interactions between such mutations were due to changes in the catalytic activities of DHFR mutants, rather than changes in trimethoprim affinity. We found that the high-order epistasis in catalytic power of DHFR (kcat and Km) created a rugged fitness landscape under trimethoprim selection. Taken together, these data provide a concrete illustration of how epistatic coupling at the level of biochemical parameters can give rise to complex fitness landscapes, suggesting new strategies for developing mutant specific inhibitors. In the second part of the thesis, we report that E. coli cells that evolved resistance against aminoglycosides pleiotropically evolved hypersensitivity against non-aminoglycoside antibiotics. A point mutation in a the potassium channel called TrkH decreases antibiotic efflux by altering the bacterial membrane potential. To mimic this phenotype, we designed and successfully used peptide-conjugated phosphorodiamidate morpholino oligomers (PPMOs) to silence efflux genes. Specifically, by silencing the acrA gene, we transiently induced antibiotic hypersensitivity in E. coli. This sequence-specific perturbation decreased the minimum lethal dose of several antibiotics. Moreover, this approach enables combination therapies using several pairs of antagonistic drugs with non-overlapping resistance mechanisms.Item The Structural Distribution of Epistasis in a Pair of Essential Metabolic Enzymes(December 2021) Nguyen, Thuy Ngoc-Thi; Hibbs, Ryan E.; Reynolds, Kimberly A.; Rice, Luke M.; Yu, HongtaoInteractions between proteins provide the basis for cells to perform metabolism, grow, divide, move, and appropriately respond to external stimuli. Because proteins do not act as independent entities, the genetic background influences the effect of a mutation in unexpected ways. This context-dependence of mutational effects is epistasis. Extensive progress has been made in our ability to identify epistasis between proteins. However, how the epistasis between a pair of proteins is distributed across the amino acid sequence is less clear. Previous work characterized this sequence-level epistasis between proteins that bind to form a physical complex. Until now, the structural pattern and magnitude of epistasis between pairs of mutations spanning interacting metabolic enzymes remained uncharacterized. In my dissertation work, I deeply examined the context dependence of mutations for two essential enzymes in the bacterial folate metabolic pathway, Dihydrofolate Reductase (DHFR) and Thymidylate Synthase (TYMS). To achieve this goal, I used deep mutational scanning assays on DHFR in the context of varying activities of TYMS. The result is a rigorous dataset with epistasis measurements over the entire amino acid sequence of DHFR. I found that the positions with the greatest magnitude of epistasis within the structure of DHFR lied at the active site. However, the sign of epistasis at the DHFR active site was dependent on whether TYMS was active. Beyond the active site, the distribution of positive epistasis among the positions of DHFR was also context- dependent on the state of TYMS. Therefore, we can think of the active site as a non-physical "interface" between protein pairs that do not form a physical complex but share an intermediate. The potential consequences of this dataset on the epistasis between DHFR and TYMS are profound. This dataset is fundamental towards our understanding of how epistasis mechanistically emerges in nonlinearities between catalytic activity in enzymes, protein abundance, and cellular growth rate. This experimental dataset is also necessary to credibly validate predictions of epistasis from models of statistical co-evolution.Item Using Evolutionary Statistics to Understand Cellular Systems(2019-11-18) Schober, Andrew Frank, Jr.; Lin, Milo; Reynolds, Kimberly A.; Reese, Michael L.; Tu, BenjaminMetabolic enzyme function is dependent on the larger context of a biochemical pathway. Despite detailed characterization of the requisite molecular "parts," it remains difficult to predict the adaptive response to a simple perturbation. That is: if the activity or expression of a single enzyme is changed, what other proteins (if any) require compensatory mutation? Comparative genomics and experimental evolution provide two powerful approaches to begin addressing these questions. In my thesis work, I examined adaptive interactions with the essential enzyme dihydrofolate reductase (DHFR). Analyses of gene synteny and co-occurrence across 1445 bacterial genomes indicated that DHFR coevolves with thymidylate synthase (TYMS), but is relatively decoupled from the rest of the folate metabolic pathway (and genome). Through directed evolution of E. coli, I demonstrated that these two enzymes adapt cooperatively in response to antibiotic stress. An allele replacement experiment confirmed that a pair of mutations to DHFR and TYMS were sufficient to reconstitute the entire trimethoprim resistance phenotype, establishing that the two enzymes are capable of independently driving adaptation. In the final component of my thesis, I drew on the 'mirror-tree' method to define a new measure of residue-residue coevolution which corrects for the phylogenetic relationship among species. In summary, my results verify that small groups of genes within larger metabolic pathways can form adaptive modules that evolve as a unit in response to environmental or mutational stress. Moreover, my mirror-tree inspired analysis provides a path forward for understanding how coupled adaptation between genes manifests at the resolution of site specific constraints on the protein sequence.