Model of 2,3-bisphosphoglycerate metabolism in the human erythrocyte based on detailed enzyme kinetic equations: equations and parameter refinement

Abstract

Over the last 25 years, several mathematical models of erythrocyte metabolism have been developed. Although these models have identified the key features in the regulation and control of erythrocyte metabolism, many important aspects remain unexplained. In particular, none of these models have satisfactorily accounted for 2,3-bisphosphoglycerate (2,3-BPG) metabolism. 2,3-BPG is an important modulator of haemoglobin oxygen affinity, and hence an understanding of the regulation of 2,3-BPG concentration is important for understanding blood oxygen transport. A detailed, comprehensive, and hence realistic mathematical model of erythrocyte metabolism is presented that can explain the regulation and control of 2,3-BPG concentration and turnover. The model is restricted to the core metabolic pathways, namely glycolysis, the 2,3-BPG shunt and the pentose phosphate pathway (PPP), and includes membrane transport of metabolites, the binding of metabolites to haemoglobin and Mg# + , as well as pH effects on key enzymic reactions and binding processes. The

Metabolic homeostasis in the human erythrocyte: In silico analysis

“…These are those of the stable steady state that corresponds to the exper- Three types of steady state solutions were found: stable steady state that corresponded to the experimental data used to refine the model of Mulquiney and Kuchel (1999) (solid line); unstable steady state (long-dashed line) and a third solution, which corresponds to the trivial solution (Rapoport and Heinrich, 1975 imental data used to refine the model of Mulquiney and Kuchel (1999). The ATP, ADP and 2,3-BPG concentrations refer to the total concentrations, including also the complexes with Mg 2+ , haemoglobin and 2,3-BPG synthase/phosphatase (Mulquiney and Kuchel, 1999). (2) indicates the decay of PK activity.…”

“…A Mathematica package developed by Mulquiney and Kuchel (2003) was used for the simulations in PC Windows-based computers. ATP consumption and a number of spontaneous and enzyme-catalyzed reactions that oxidize GSH were simulated (Mulquiney and Kuchel, 1999) by using the first order rate constants k ATPase and k ox , respectively. The rate constants represent a measure of the whole energy (k ATPase ) or oxidative (k ox ) load on the cell (Schuster and Holzhutter, 1995).…”

“…The computer simulations were done using the model of human RBC metabolism described by Mulquiney and Kuchel (1999). The model had been developed primarily to study the regulation and control of 2,3-BPG concentrations; it includes equations that describe the energy status and redox metabolism in the cell.…”

“…A number of hypotheses based on previous in silico analyses (Schuster and Holzhutter, 1995;Martinov et al, 2000;Ç akir et al, 2004) and on experimental observations (Beutler, 1988;Piomelli and Seaman, 1991;Magnani et al, 1991;Samaja et al, 1991;Chiarantini et al, 1994;Fiorani et al, 2000Fiorani et al, , 1997 have been proposed. In the present work, we performed in silico simulations using the model of human RBC metabolism that was based on NMR data and developed by Mulquiney and Kuchel (1999); it was used to explore metabolic collapse, and the crucial events that precede this collapse when enzyme activities decline. Our attention was focused on HK, although the effects on this enzyme were contrasted with those of other enzymes of glycolysis and the pentose phosphate pathway.…”

Cellular signaling identifiability analysis: A case study

“…This tends to be the case, for example, with models of membrane electrodynamics such as those describing the sinoatrial node action potential and ventricular contraction (Dokos et al, 1996;Kurata et al, 2002;Luo and Rudy, 1994a, b). Other examples include metabolic (Lambeth and Kushmerick, 2002;Mulquiney and Kuchel, 1999) and signaling systems (Huang and Ferrell, 1996;Kholodenko et al, 1999;Orton et al, 2005;Sedaghat et al, 2002). Often, these models are used for simulation and hypothesis generation, but their parameters need to be determined and tested for reliability before the model can be used for predictive purposes.…”