Dataset Information

Bertram2006_ATPproduction_Mitochondrial

ABSTRACT: This a model from the article: A simplified model for mitochondrial ATP production. Bertram R, Gram Pedersen M, Luciani DS, Sherman A. J Theor Biol 2006 Dec 21;243(4):575-86 16945388 , Abstract: Most of the adenosine triphosphate (ATP) synthesized during glucose metabolism is produced in the mitochondria through oxidative phosphorylation. This is a complex reaction powered by the proton gradient across the mitochondrial inner membrane, which is generated by mitochondrial respiration. A detailed model of this reaction, which includes dynamic equations for the key mitochondrial variables, was developed earlier by Magnus and Keizer. However, this model is extraordinarily complicated. We develop a simpler model that captures the behavior of the original model but is easier to use and to understand. We then use it to investigate the mitochondrial responses to glycolytic and calcium input. We use the model to explain experimental observations of the opposite effects of raising cytosolic Ca(2+)in low and high glucose, and to predict the effects of a mutation in the mitochondrial enzyme nicotinamide nucleotide transhydrogenase (Nnt) in pancreatic beta-cells. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Bertram R, Gram Pedersen M, Luciani DS, Sherman A. (2006) - version=1.0 The original CellML model was created by: Tessa Paris tpar054@aucklanduni.ac.nz The University of Auckland This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

SUBMITTER: Camille Laibe

PROVIDER: MODEL1006230114 | BioModels | 2005-01-01

REPOSITORIES: BioModels

ACCESS DATA

Publications

A simplified model for mitochondrial ATP production.

Bertram Richard R Gram Pedersen Morten M Luciani Dan S DS Sherman Arthur A

Journal of theoretical biology 20060725 4

Most of the adenosine triphosphate (ATP) synthesized during glucose metabolism is produced in the mitochondria through oxidative phosphorylation. This is a complex reaction powered by the proton gradient across the mitochondrial inner membrane, which is generated by mitochondrial respiration. A detailed model of this reaction, which includes dynamic equations for the key mitochondrial variables, was developed earlier by Magnus and Keizer. However, this model is extraordinarily complicated. We de ...[more]

PMID: 16945388

Similar Datasets

Project description:This is the model described in the article: Interaction of glycolysis and mitochondrial respiration in metabolic oscillations of pancreatic islets. Bertram R, Satin LS, Pedersen MG, Luciani DS, Sherman A. Biophys J. 2007 Mar 1;92(5):1544-55. Pubmed ID: 17172305, doi: 10.1529/biophysj.106.097154. Abstract: Insulin secretion from pancreatic beta-cells is oscillatory, with a typical period of 2-7 min, reflecting oscillations in membrane potential and the cytosolic Ca(2+) concentration. Our central hypothesis is that the slow 2-7 min oscillations are due to glycolytic oscillations, whereas faster oscillations that are superimposed are due to Ca(2+) feedback onto metabolism or ion channels. We extend a previous mathematical model based on this hypothesis to include a more detailed description of mitochondrial metabolism. We demonstrate that this model can account for typical oscillatory patterns of membrane potential and Ca(2+) concentration in islets. It also accounts for temporal data on oxygen consumption in islets. A recent challenge to the notion that glycolytic oscillations drive slow Ca(2+) oscillations in islets are data showing that oscillations in Ca(2+), mitochondrial oxygen consumption, and NAD(P)H levels are all terminated by membrane hyperpolarization. We demonstrate that these data are in fact compatible with a model in which glycolytic oscillations are the key player in rhythmic islet activity. Finally, we use the model to address the recent finding that the activity of islets from some mice is uniformly fast, whereas that from islets of other mice is slow. We propose a mechanism for this dichotomy. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Bertram, Satin, Pedersen, Luciani, Sherman, 2007 version 02 The original CellML model was created and curated by: Catherine May Lloyd c.lloyd(at)auckland.ac.nz The University of Auckland, Bioengineering Institute This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. For more information see the terms of use. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Project description:This a model from the article: Calcium and glycolysis mediate multiple bursting modes in pancreatic islets. Bertram R, Satin L, Zhang M, Smolen P, Sherman A. Biophys J2004 Nov;87(5):3074-87 15347584, Abstract: Pancreatic islets of Langerhans produce bursts of electrical activity when exposed to stimulatory glucose levels. These bursts often have a regular repeating pattern, with a period of 10-60 s. In some cases, however, the bursts are episodic, clustered into bursts of bursts, which we call compound bursting. Consistent with this are recordings of free Ca2+ concentration, oxygen consumption, mitochondrial membrane potential, and intraislet glucose levels that exhibit very slow oscillations, with faster oscillations superimposed. We describe a new mathematical model of the pancreatic beta-cell that can account for these multimodal patterns. The model includes the feedback of cytosolic Ca2+ onto ion channels that can account for bursting, and a metabolic subsystem that is capable of producing slow oscillations driven by oscillations in glycolysis. This slow rhythm is responsible for the slow mode of compound bursting in the model. We also show that it is possible for glycolytic oscillations alone to drive a very slow form of bursting, which we call "glycolytic bursting." Finally, the model predicts that there is bistability between stationary and oscillatory glycolysis for a range of parameter values. We provide experimental support for this model prediction. Overall, the model can account for a diversity of islet behaviors described in the literature over the past 20 years. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Bertram R, Satin L, Zhang M, Smolen P, Sherman A. (2004) - version=1.0 The original CellML model was created by: Catherine Lloyd c.lloyd@auckland.ac.nz The University of Auckland This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. For more information see the terms of use. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Project description:Persons with Down syndrome (DS) exhibit low muscle strength that significantly impairs their physical functioning. The Ts65Dn mouse model of DS also exhibits muscle weakness in vivo and may serve as a useful model to examine potential factors responsible for DS-associated muscle dysfunction. Therefore, the purpose of this experiment was to directly assess skeletal muscle function in the Ts65Dn mouse and to reveal potential mechanisms of DS-associated muscle weakness. Soleus muscles were harvested from anesthetized male Ts65Dn and wild-type (WT) colony controls. In vitro muscle contractile experiments revealed normal force generation of unfatigued Ts65Dn soleus, but a 12% reduction in force was observed in Ts65Dn muscle during recovery following fatiguing contractions compared to WT muscle (p<0.05). Oxidative stress may contribute to DS-related pathologies, including muscle weakness, which may be the result of overexpression of chromosome 21 genes (e.g., copper-zinc superoxide dismutase (SOD1)). SOD1 expression was 25% higher (p<0.05) in Ts65Dn soleus compared to WT muscle but levels of other antioxidant proteins were unchanged. Lipid peroxidation (4-hydroxynoneal) was unaltered in Ts65Dn muscle although protein carbonyls were 20% greater compared to muscle of WT animals (p<0.05). Cytochrome c oxidase expression was reduced 22% in Ts65Dn muscle, suggesting a limitation in mitochondrial function may contribute to post-fatigue muscle weakness. Microarray analysis of Ts65Dn soleus revealed alteration of numerous cellular pathways including: proteolysis, glucose and fat metabolism, neuromuscular transmission, and ATP biosynthesis. In summary, the Ts65Dn mouse displays evidence of muscle dysfunction, and the potential role of mitochondria and oxidative stress warrants further investigation. We used microarrays to gain insight into potential mechanisms of DS-associated skeletal muscle weakness. Soleus muscles were obtained from four male Ts65Dn (DS) mice and four male colony control mice. Animals were apparently healthy and approximately five months old. The muscles were harvested in the basal state under anesthesia induced by sodium pentobarbital at approximately the same time of the day.

Project description:This a model from the article: Evidence that calcium release-activated current mediates the biphasic electrical activity of mouse pancreatic beta-cells. Mears D, Sheppard NF Jr, Atwater I, Rojas E, Bertram R, Sherman A. J Membr Biol1997 Jan 1;155(1):47-59 9002424, Abstract: The electrical response of pancreatic beta-cells to step increases in glucose concentration is biphasic, consisting of a prolonged depolarization with action potentials (Phase 1) followed by membrane potential oscillations known as bursts. We have proposed that the Phase 1 response results from the combined depolarizing influences of potassium channel closure and an inward, nonselective cation current (ICRAN) that activates as intracellular calcium stores empty during exposure to basal glucose (Bertram et al., 1995). The stores refill during Phase 1, deactivating ICRAN and allowing steady-state bursting to commence. We support this hypothesis with additional simulations and experimental results indicating that Phase 1 duration is sensitive to the filling state of intracellular calcium stores. First, the duration of the Phase 1 transient increases with duration of prior exposure to basal (2.8 mM) glucose, reflecting the increased time required to fill calcium stores that have been emptying for longer periods. Second, Phase 1 duration is reduced when islets are exposed to elevated K+ to refill calcium stores in the presence of basal glucose. Third, when extracellular calcium is removed during the basal glucose exposure to reduce calcium influx into the stores, Phase 1 duration increases. Finally, no Phase 1 is observed following hyperpolarization of the beta-cell membrane with diazoxide in the continued presence of 11 mm glucose, a condition in which intracellular calcium stores remain full. Application of carbachol to empty calcium stores during basal glucose exposure did not increase Phase 1 duration as the model predicts. Despite this discrepancy, the good agreement between most of the experimental results and the model predictions provides evidence that a calcium release-activated current mediates the Phase 1 electrical response of the pancreatic beta-cell. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Mears D, Sheppard NF Jr, Atwater I, Rojas E, Bertram R, Sherman A. (1997) - version=1.0 The original CellML model was created by: Tessa Paris tpar054@aucklanduni.ac.uk The University of Auckland This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. For more information see the terms of use. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Project description:This a model from the article: Calcium and glycolysis mediate multiple bursting modes in pancreatic islets. Bertram R, Satin L, Zhang M, Smolen P, Sherman A. Biophys J 2004 Nov;87(5):3074-87 15347584 , Abstract: Pancreatic islets of Langerhans produce bursts of electrical activity when exposed to stimulatory glucose levels. These bursts often have a regular repeating pattern, with a period of 10-60 s. In some cases, however, the bursts are episodic, clustered into bursts of bursts, which we call compound bursting. Consistent with this are recordings of free Ca2+ concentration, oxygen consumption, mitochondrial membrane potential, and intraislet glucose levels that exhibit very slow oscillations, with faster oscillations superimposed. We describe a new mathematical model of the pancreatic beta-cell that can account for these multimodal patterns. The model includes the feedback of cytosolic Ca2+ onto ion channels that can account for bursting, and a metabolic subsystem that is capable of producing slow oscillations driven by oscillations in glycolysis. This slow rhythm is responsible for the slow mode of compound bursting in the model. We also show that it is possible for glycolytic oscillations alone to drive a very slow form of bursting, which we call "glycolytic bursting." Finally, the model predicts that there is bistability between stationary and oscillatory glycolysis for a range of parameter values. We provide experimental support for this model prediction. Overall, the model can account for a diversity of islet behaviors described in the literature over the past 20 years. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Bertram R, Satin L, Zhang M, Smolen P, Sherman A. (2004) - version=1.0 The original CellML model was created by: Catherine Lloyd c.lloyd@auckland.ac.nz The University of Auckland This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Project description:This a model from the article: A role for calcium release-activated current (CRAC) in cholinergic modulation of electrical activity in pancreatic beta-cells. Bertram R, Smolen P, Sherman A, Mears D, Atwater I, Martin F, Soria B. Biophys J1995 Jun;68(6):2323-32 7647236, Abstract: S. Bordin and colleagues have proposed that the depolarizing effects of acetylcholine and other muscarinic agonists on pancreatic beta-cells are mediated by a calcium release-activated current (CRAC). We support this hypothesis with additional data, and present a theoretical model which accounts for most known data on muscarinic effects. Additional phenomena, such as the biphasic responses of beta-cells to changes in glucose concentration and the depolarizing effects of the sarco-endoplasmic reticulum calcium ATPase pump poison thapsigargin, are also accounted for by our model. The ability of this single hypothesis, that CRAC is present in beta-cells, to explain so many phenomena motivates a more complete characterization of this current. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Bertram R, Smolen P, Sherman A, Mears D, Atwater I, Martin F, Soria B. (1995) - version=1.0 The original CellML model was created by: Catherine Lloyd c.lloyd@auckland.ac.nz The University of Auckland This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. For more information see the terms of use. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Dataset Information

Bertram2006_ATPproduction_Mitochondrial

Publications

A simplified model for mitochondrial ATP production.

Similar Datasets

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