Glucokinase (GK) has been shown to play the role of the glucose sensor in the pancreatic b-cell, by virtue of its role as the rate controlling step in glycolysis. GK also has a very high control strength on glucose induced insulin secretion. The approach that led up to these important discoveries was quantitative and mathematical modeling of GK kinetics. Glucose must be metabolized before insulin secretion is stimulated, and the coupling factor between its metabolism and the ionic events which lead to the exocytosis of insulin containing granules is the energy state of the cell, [ATP]/[ADP]. Dukes [1994] and MacDonald [1990] have proposed that the major source of ATP production serving as a stimulus for insulin release is that generated by glycolytically-derived NADH, which is shuttled into the mitochondria and oxidized. This suggests that the rate of ATP production from the Krebs cycle is approximately constant, so that when a greater amount of pyruvate enters the Krebs cycle after a rise in glucose levels, this is counterbalanced by a diminution of the entry of acetyl CoA derived from fatty acids. Further, the factors governing the entry of pyruvate into the Krebs cycle (pyruvate dehydrogenase activity; PDH) and fatty acid oxidation, although important to the proper functioning of the cell, are not mechanisms by which the cell regulates the amount of insulin to be released. We propose to apply the quantitative approach taken in elucidating the relation between GK and glycolysis, to that of PDH and the rate of entry of pyruvate into the Krebs cycle. The experimental approach utilizes a mass spectrometer with a specialized inlet system that can monitor with a response time of 7 seconds the concentrations of dissolved O2, 12CO2, and 13CO2 in response to 13C labeled substrates. By using O2 consumption as a measure of ATP production, and production of 13CO2 in the presence of [1-13C]pyruvate as a measure of PDH, the basic hypothesis that ATP production from the Krebs c ycle is constant despite an increase in flux thrugh PDH can be tested. Both the measurements and their interpretation need to be quantitative to allow for rigorous conclusions to be made, so mathematical modeling analysis will be used for hypothesis testing, parameter estimation, flux estimations and control strength analysis. Understanding the regulatory mechanisms of the Krebs cycle in the functioning of the b-cell is prerequisite for understanding the pathology of both Type I and II diabetes mellitus.
| Bassingthwaighte, James B; Butterworth, Erik; Jardine, Bartholomew et al. (2012) Compartmental modeling in the analysis of biological systems. Methods Mol Biol 929:391-438 |
| Dash, Ranjan K; Bassingthwaighte, James B (2010) Erratum to: Blood HbO2 and HbCO2 dissociation curves at varied O2, CO2, pH, 2,3-DPG and temperature levels. Ann Biomed Eng 38:1683-701 |
| Bassingthwaighte, James B; Raymond, Gary M; Butterworth, Erik et al. (2010) Multiscale modeling of metabolism, flows, and exchanges in heterogeneous organs. Ann N Y Acad Sci 1188:111-20 |
| Dash, Ranjan K; Bassingthwaighte, James B (2006) Simultaneous blood-tissue exchange of oxygen, carbon dioxide, bicarbonate, and hydrogen ion. Ann Biomed Eng 34:1129-48 |
| Dash, Ranjan K; Bassingthwaighte, James B (2004) Blood HbO2 and HbCO2 dissociation curves at varied O2, CO2, pH, 2,3-DPG and temperature levels. Ann Biomed Eng 32:1676-93 |
| Kellen, Michael R; Bassingthwaighte, James B (2003) Transient transcapillary exchange of water driven by osmotic forces in the heart. Am J Physiol Heart Circ Physiol 285:H1317-31 |
| Kellen, Michael R; Bassingthwaighte, James B (2003) An integrative model of coupled water and solute exchange in the heart. Am J Physiol Heart Circ Physiol 285:H1303-16 |
| Wang, C Y; Bassingthwaighte, J B (2001) Capillary supply regions. Math Biosci 173:103-14 |
| Swanson, K R; True, L D; Lin, D W et al. (2001) A quantitative model for the dynamics of serum prostate-specific antigen as a marker for cancerous growth: an explanation for a medical anomaly. Am J Pathol 158:2195-9 |
| Swanson, K R; Alvord Jr, E C; Murray, J D (2000) A quantitative model for differential motility of gliomas in grey and white matter. Cell Prolif 33:317-29 |
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