A Discrete-Event Simulation Approach for Modeling Human Body Glucose Metabolism

This dissertation describes CarbMetSim (Carbohydrate Metabolism Simulator), a discrete-event simulator that tracks the blood glucose level of a person in response to a timed sequence of diet and exercise activities. CarbMetSim implements broader aspects of carbohydrate metabolism in human beings with the objective of capturing the average impact of various diet/exercise activities on the blood glucose level. Key organs (stomach, intestine, portal vein, liver, kidney, muscles, adipose tissue, brain and heart) are implemented to the extent necessary to capture their impact on the production and consumption of glucose. Key metabolic pathways (glucose oxidation, glycolysis and gluconeogenesis) are accounted for by using the published values of the average flux along these pathways in the operation of different organs. CarbMetSim has the ability to model different levels of insulin resistance and insulin production ability. The impact of insulin and insulin resistance on the operation of various organs and pathways is captured in accordance with published research. The protein and lipid metabolism are implemented only to the extent that they affect carbohydrate metabolism

The Exploration of Nanotoxicological Copper and Interspecific Saccharomyces Hybrids

Nanotechnology takes advantage of cellular biology’s natural nanoscale operations by interacting with biomolecules differently than soluble or bulk materials, often altering normal cellular processes such as metabolism or growth. To gain a better understanding of how copper nanoparticles hybridized on cellulose fibers called carboxymethyl cellulose (CMC) affected growth of Saccharomyces cerevisiae, the mechanisms of toxicity were explored. Multiple methodologies covering genetics, proteomics, metallomics, and metabolomics were used during this investigation. The work that lead to this dissertation discovered that these cellulosic copper nanoparticles had a unique toxicity compared to copper. Further investigation suggested a possible ionic or molecular mimicry scenario with zinc, likely involving the Zrt family of zinc transporters and involving arrestin mediated endocytosis. Reactive oxygen species were generated by copper nanoparticles that induced lipid peroxidation, altering the phosphatidylcholine and phosphatidylethanolamine membrane composition, resulting in a disfigured cell surface. Following this study, I designed experiments aimed at furthering this dissertation\u27s focus on metabolism by describing the metabolism of a novel species, Saccharomyces arboricola, thus filling a gap in knowledge in the industrial fermentation field. Low levels of endogenous amino/organic acids separated S. arboricola from the S. cerevisiae industrial strains and their interspecific hybrids showed a mosaic metabolic profile of parental strains. Overall, my dissertation research identified mechanisms of cellulosic copper nanotoxicity that included transport, metal homeostasis, reactive oxygen species, and the cellular membrane composition. Perturbations of Saccharomyces yeast by exogenous exposure to nanocopper or by interspecific hybridization had effects on the cellular metabolism

A RBA model for the chemostat modeling

A RBA model for the chemostat modeling. 58. Conference on Decision and Contro

An in Silico Liver: Model of Gluconeogenesis

An in silico liver was developed in attempt to represent the in vivo state of the fasted liver. It featured two conceptual models. The first one represented carbohydrate metabolism of the human liver, which included the heterogeneous nature of the liver by incorporating spatial variation of key enzyme activities. This model was able to predict the overall fluxes in tissue and the effect of high intensity exercise on the various hepatic fluxes. A second model of hepatic metabolism was developed to represent the complex interplay between gluconeogenesis, lipid metabolism, and alcohol metabolism in the fasted rat liver. Biochemical pathways are represented by key kinetic reactions that include allosteric and substrates effectors, and phosphorylation/dephosphorylation enzymes regulation. The model also incorporates the compartmentation and intercompartmental transports between the cytosol and the mitochondria, and transport of metabolites between blood compartment and the tissue. The model is based on the experimental set-up of fasted perfused rat livers. The model was used to simulate the effects of the two main gluconeogenic substrates available during the fasting state-- lactate and pyruvate--along with the addition of fatty acids and/or ethanol. The model predicts successfully the rates of glucose and ketone production, substrate uptake, and citric acid cycle. Parameter estimations were performed in order to obtain a set of physiological parameters capable of representing the liver under various combinations of nutrients. Parameter sensitivity analysis was generated to quantify the contribution of each parameter to the model output. The model was validated with data available in the published literature from ex vivo studies. The in silico liver constitutes a tool that can be used to predict the effect of physiological stimuli on flux and concentration distributions. This will provide an increase in the understanding of such effects and to determine what parameters, enzymes, and fluxes are responsible

Examination of metabolism in diabetic offspring

The purpose of this study was to categorize aberrant metabolic function in diabetic offspring (FH+). This study examined metabolic flexibility (MF), and changes in fasting blood-glucose concentrations and markers of lipotoxicity with resistance training in college age FH+ and FH-. Results are significant at p = 0.05. MF testing indicate no baseline differences in RMR, VO2, REE, fat or CHO use were noted between T2D, FH+, or FH-. Passive stretching caused increased metabolism overall, however the T2D group temporarily displayed increased CHO use during passive stretching, which quickly returned to pre-stretched levels during recovery as compared with FH-. Both T2D and FH+ display impaired MF as compared with FH- via indirect calorimetry as noted by the change in RER. With training, changes in glucose: lactate ratios were no different between groups, but increased immediately after exercise with training, and decreased at five and ten minutes post-exercise with training. Lastly, there were no differences between FH- and FH+ in pre-training strength, BMI, or in markers measured in plasma before or after exercise. Strength increased from pre to post training similarly. However, changes in NEFA and insulin were noted in weight loss subjects vs non-weight loss. Negative correlations exist between weight loss and: TG, NEFA, insulin and HOMA, and strength, and positive correlations with blood glucose AUC. Though there are differences metabolic flexibility and recovery kinetics between groups with and without a family history of diabetes, this study does not reveal any such differences in glucoregulatory function, or markers of lipotoxicity. Resistance training did not affect FH+ differently than FH-, however there were differences in these markers when groups were re-categorized by weight loss. We were unable to isolate specific factors likely to contribute to the development of IR or T2D within the confines of the current study. However, further research, such as lipid tracers and MRI studies are needed to determine factors leading to more aberrant metabolic function in order to better understand what factors lead to the development of IR and T2D

Evolution of Yeast Respiro-Fermentative Lifestyle and the Underlying Mechanisms Behind Aerobic Fermentation

Under aerobic conditions, most yeasts such as Kluyveromyces lactis, prefer the respiratory pathway and some, such as Saccharomyces cerevisiae prefer less energy efficient fermentative pathway for their energy metabolism. These two metabolic strategies are also known as Crabtree negative and Crabtree positive respectively, and the evolution of the latter has lately been explained by the “make-accumulate-consume” life strategy. Scientists have for more than a century tried to elucidate the mechanism behind the physiology and the evolution of the peculiar respiro-fermentation trait. During the last decades, comparative genomics approaches have enabled the reconstruction of the evolutionary history of yeast, and several evolutionary events have been identified and postulated to have contributed to the development of the respiro-fermentative lifestyle in the Saccharomyces lineage. However, many of these inspiring studies have been verified with reference species only. Therefore, as parts of my thesis I conducted large-scale physiology studies of more than 40 yeast species and their central carbon metabolism under controlled conditions, in bioreactors. This was done in order to map the evolution of aerobic fermentation in yeast belonging to the Saccharomyces lineage that span over 200 million years of yeast evolution. This evolutionary blueprint, which most likely will be an invaluable information source of primary data for future in silico studies on the evolution of Crabtree effect, has already verified the importance of evolutionary events, such as promoter rewiring, chromatin relaxation, whole genome duplication, gene duplication and lateral gene-transfers. I further propose a mechanism that provides an explanation for the origin of the respiro-fermentative lifestyle in yeast, and how this was subsequently, through a multistep process developed into the Crabtree effect as we know it in the modern yeasts today, such as S. cerevisiae and its sister species

Thermodynamically-Constrained Computational Modeling of Lung Tissue Bioenergetics and the Effect of Hyperoxia-Induced Acute Lung Injury

Altered lung tissue bioenergetics is an important and early step in the pathogenesis of acute lung injury (ALI), one of the most common causes of admission to medical ICUs. A wealth of information exists regarding the effect of ALI on specific mitochondrial and cytosolic processes in isolated mitochondria, cultured endothelial cell, and intact lungs. However, the interdependence of lung cellular processes makes it difficult to quantify the impact of a change in a single or multiple cellular process(es) on overall lung tissue bioenergetics. Integrating bioenergetics data from isolated mitochondria and intact lung is necessary for determining the functional significance of targeting a specific cellular process for prognostic and/or therapeutic purposes. Thus, the main objective of my dissertation was to develop and validate comprehensive, thermodynamically-constrained models of mitochondrial and lung tissue bioenergetics, and to use these models to predict the impact of ALI-induced changes in mitochondrial and cytosolic processes on lung tissue bioenergetics. For Aim 1, I developed an integrated model of the bioenergetics of mitochondria isolated from rat lungs, which incorporates the major biochemical reactions and transport processes in lung mitochondria. The model was validated by assessing its ability to predict experimental data not used for parameter estimation. The model provides important insights into the bioenergetics of lung mitochondria and how they differ from those of mitochondria from other organs. For Aim 2, I developed and validated an integrated computational model of lung tissue bioenergetics. The model expanded the computational model developed under Aim 1 by accounting for glucose uptake and phosphorylation, glycolysis, and the pentose phosphate pathway. The model was then used to gain novel insights into how lung tissue glycolytic rate is regulated by exogenous substrates, and assess differences in the bioenergetics of isolated mitochondria isolated from lung tissue and those of mitochondria in intact lungs. For Aim 3, the models developed under Aims 1 and 2 were used to quantify the impact of previously measured changes in specific mitochondrial processes in a rat model of clinical ALI on lung mitochondrial and tissue bioenergetics. To the best of our knowledge, the two computational models are the first for lung mitochondrial and tissue bioenergetics. These models provide a mechanistic and quantitative framework for integrating available lung tissue bioenergetics data, for testing novel hypotheses regarding the role of different cytosolic and mitochondrial processes in lung tissue bioenergetics and the pathogenesis of ALI, and for identifying potential therapeutic targets for ALI