The BIophysical Basis for Adaptation: Predicting Evolutionary Outcomes from Physicochemical Properties
Benitez Cardenas, Andres
Doctor of Philosophy
Experimental evolution can be used in conjunction with biophysical characterization of enzymes to determine the link between cellular fitness and physicochemical properties of enzymes. Sequencing of ancestral and evolved populations can be used to compare the outcomes of experimental evolution with measurements of fitness, using growth rate assays to correlate fitness outcomes to specific mutations. Combined with enzyme assays of kinetic properties that can provide a direct link between genotypic and phenotypic changes of adaptive mutants, we can model the complex relationship between genotypic changes and evolutionary outcomes. Two experimental evolution systems were used to explore the link between enzyme properties and fitness outcomes. In the first series of studies, a “weak link” evolution experiment was used to explore the effect of reducing selection strength on altering accessible pathways for adaptation. In the weak link method the essential gene for adenylate kinase (AK) was replaced in the chromosome of the thermophile Geobacillus stearothermophilus with a homolog from Bacillus subtilis. Replacement with the maladapted gene confers a high fitness cost, and therefore mutations that restore function of AK are strongly favored. Two triple mutants of AK containing a new combination of single point mutants identified under strong selection, AKQ199R/A193V/Q16L and AKQ199R/T179I/Q16L were discovered through an adaptation experiment using a weak temperature ramp; suggesting that the adaptive landscape for AK thermostability is highly constrained. A thermostable coupled assay was developed for measuring adenylate kinase activity using LDHTTHERMOPHILUS and PKGSTEAROTHERMOPHILUS at high temperatures. The triple mutants had increased function compared with the double mutant ancestors, but the triple mutants displayed diminishing returns epistasis on fitness. In the second experimental evolution system, a mathematical model was developed to investigate the role of adaptive mutations, in the tetracycline inactivation enzyme TetX2, on antibiotic resistance to minocycline (MCN). Growth rates measurements, enzyme kinetics, and flux balance equations were used to develop a model to predict the effect on growth rates of TetX2 and seven adaptive TetX2 variants at different MCN concentrations. Population histogram measurements for the experimental evolution study were measured using a high throughput Illumina sequencing method (FREQ-SEQ). We found that the model was able to accurately predict the fitness outcomes for the wild type and the seven single mutants of TetX2 that were originally isolated, as well as for a double mutant that was not used in the development of the original model. The mathematical model accurately predicts that the two mutants TetX2T280A and TetX2N371I provide the largest fitness benefits, in agreement with the results of in vitro experiments on adaptation to MCN. The model was also able to accurately predict enzyme parameters from growth rates values, with a specific emphasis on predicting the ratio of Vmax/KM(MCN). The model allows us to make predictions about the fitness benefits of physicochemical changes to enzymes, and can be used as a high throughput method for determining enzyme kinetic parameters without requiring protein purification. Understanding how physicochemical changes of enzymes relate to phenotypic changes, and ultimately to fitness, requires knowledge of both the molecular basis for determining enzyme properties, and how selection acts on fitness differences to determine evolutionary outcomes. This research provides direct links between physicochemical changes and adaptive phenotypes, as well providing observations of how adaptive landscapes and fitness changes affect evolutionary outcomes.