Blood transfusions have long been the preferred treatment for severely anemic patients in medical practice, but recent studies show increased long-term mortality rates following a blood transfusion. Physical predictions of the effects of a blood transfusion show overall decreased oxygen delivery, in contradiction with the observed improved delivery in practice. To further explore this, Golden Syrian Hamsters were made anemic to 50% hematocrit deficiency and then transfused differing amounts of 70-72% pRBC blood units. The average percent change in physical parameters was calculated and compared between the normal baseline state, anemic state, and the post-transfusion state. Results suggest that increase in overall blood flow in response to hemodilution and blood transfusion is a major contributing factor in increasing oxygen delivery, in addition to increasing hematocrit levels. Further experimentation to confirm the effective degree of blood flow on increased oxygen delivery post-transfusion is a promising path to gaining deeper understanding of the physical effects of blood transfusion in anemic patients.

Evidence suggests that novel enzyme functions evolved from low-level promiscuous activities in ancestral enzymes. Yet, the evolutionary dynamics and physiological mechanisms of how such side activities contribute to systems-level adaptations are poorly understood. Furthermore, it remains untested whether knowledge of an organism's promiscuous reaction set ('underground metabolism') can aid in forecasting the genetic basis of metabolic adaptations. In this dissertation, novel approaches toward exploring promiscuity in the space of a metabolic network are described. The work leverages genome-scale models, which have been widely used for predicting growth phenotypes in various nutrient environments and following genetic perturbation in Escherichia coli. Failure modes of model predictions in relation to gene essentiality are explored as opportunities for targeting biological discovery, suggesting the presence of unknown underground pathways stemming from enzymatic cross-reactivity or suggesting limitations of experimental conditions stemming from short growth tests. Workflows are presented that couple constraint-based modeling and bioinformatic tools with knockout strain analysis and long-term growth experiments for the purpose of enhancing knowledge and predictability of enzyme promiscuity at the genome scale. Furthermore, a computational model of underground metabolism and laboratory evolution experiments are employed to examine the role of enzyme promiscuity in the acquisition and optimization of growth on predicted non-native substrates. Promiscuous enzyme activities played key roles in multiple phases of adaptation. Genes underlying the phenotypic innovations were accurately predicted by genome-scale model simulations of metabolism with enzyme promiscuity. Thus, it is shown that computational approaches will be essential to synthesize the complex role of promiscuous activities in models of evolutionary adaptation.

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