Stimulus secretion coupling in pancreatic beta-cells

胰腺β细胞的刺激分泌耦合

• 批准号: 8349645
• 负责人: Arthur Sherman
• 金额: $ 24.06万
• 依托单位: NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8349645
• 关键词: Accounting; Action Potentials; Address; Appearance; Area; Arts; Autoantibodies; Avidity; B-Lymphocytes; Behavior; Beta Cell; Biological Assay; Biological Markers; Calcium; Calcium Oscillations; Cell model; Cell physiology; Cells; Chemicals; Collaborations; Communities; Coupled; Coupling; Cyclic AMP; Defect; Development; Disease; Endocrine; Equation; Evolution; Feedback; Glyburide; Human; Immune; Individual; Insulin; Insulin-Dependent Diabetes Mellitus; Ion Channel; Islets of Langerhans; Journals; Lead; Maps; Mathematics; Measurement; Membrane Potentials; Metabolic; Metabolism; Methods; Michigan; Modeling; Neurons; Non-Insulin-Dependent Diabetes Mellitus; Organ; Pancreas; Paper; Pharmaceutical Preparations; Phase; Phase Transition; Physiologic pulse; Physiological; Physiology; Pituitary Gland; Plasma; Postdoctoral Fellow; Potassium; Process; Protein Kinase C; Published Comment; Reading; Relative (related person); Reporting; Risk; Rodent; Signal Pathway; Stimulus; Structure of beta Cell of islet; Sulfonylurea Compounds; System; T-Lymphocyte; Testing; Time; Tolbutamide; Work; Writing; active control; cell fixing; glucose metabolism; insight; insulin secretion; interest; islet; killings; mathematical model; millisecond; research study; stem; tool; voltage

One of our main activities over the last few years has been the development of a comprehensive model for oscillations of membrane potential and calcium on time scales ranging from seconds to minutes. These lead to corresponding oscillations of insulin secretion. The basic hypothesis of the model is that the faster (tens of seconds) oscillations stem from feedback of calcium onto ion channels, likely calcium-activated potassium (K(Ca)) channels and ATP-dependent potassium (K(ATP)) channels, whereas the slower (five minutes) oscillations stem from oscillations in metabolism. The metabolic oscillations are transduced into electrical oscillations via the K(ATP) channels. The latter, notably, are a first-line target of insulin-stimulating drugs, such as the sulfonylureas (tolbutamide, glyburide) used in the treatment of Type 2 Diabetes. The model thus consists of an electrical oscillator (EO) and a metabolic (glycolytic) oscillator (G)) and is referred to as the Dual Oscillator Model (DOM). We are currently testing this model in several ways. Last year we reported that metabolic oscillations, assayed by NAD(P)H measurements, often persist in steady calcium, indicating that calcium oscillations are not required for metabolic oscillations. The two, however, are generally found in tandem, and the calcium oscillations, as well as mean calcium level, do influence the metabolic oscillations. We have now confirmed these findings with measurements of K(ATP) channel conductance and are preparing a paper on the subject. We have written a commentary (Ref. # 1)about dynamical systems methods in physiology in order to enhance the benefit for the physiology community of two recent papers by others presenting a new, more comprehensive model for (fast) beta-cell electrical activity. Whereas we have made our models as simple as possible for the phenemona addressed, the new model includes a much wider set of mechanisms. This raises issues of how to assess the relative importance of the different mechanisms and of how cells use redundancy. The complexity of the new model and others like it also poses a challenge for understanding how the model works and what its capabilities and limitations are. The commentary describes with a minimum of mathematics how bifurcation diagrams can still be applied effectively. Such diagrams are at one level maps of the parameter regimes in which the various behaviors of the model, including steady states, spiking and bursting, are found. They also provide a way to dissect the dynamics by exploiting the fact that different processes (here, spiking and bursting) operate on different time scales (< 1 sec vs. 10 - 60 sec) and can be considered as semi-independent. This reduces the collective behavior into the behavior of simpler sub-systems and greatly increases the power of analysis. Evolution may exploit such timescale separation as well, as it serves to make cell function modular - the individual subsystems can be altered with limited effect on the others. The review can be profitably read as a didactic guide to the work described in this report. A figure from the commentary was selected as the cover art for the journal's July issue. A particularly interesting application of the separation of timescales in models for bursting in beta cells is the phenomenon of resetting. An insight from the earliest beta-cell model (Chay-Keizer, 1983) is that the plateau from which spiking occurs is established by bi-stability. That is, if the slow variable calcium is fixed, the cell can sit at either a low-voltage (-60 mV) steady state or a high-voltage (-20 mV) spiking state. Consequently, brief electrical stimuli should be able to switch the cell from one state to the other. Moreover, the models predicted that the later in the low-voltage (silent) phase in which the perturbation is delivered, the shorter would be the induced high-voltage (active) phase. Experiments have confirmed that silent-active phase transitions can be induced as expected, but the duration of the induced phase does not seem to depend on when the perturbation is applied. In Ref. # 2 we show in collaboration with the Bertram group that more recent beta-cell models, with two slow variables controlling the active and silent phase durations can account for this heretofore puzzling experimental observation. Ref. # 4 addresses the issues of bistability, resettability and separation of timescales in models of bursting for both beta cells and closely related but different pituitary cells. It is discussed in detail in our report on Mathematical Modeling of Neurons and Endocrine Cells. In collaboration with Max Pietropaolo (U. Michigan) post-doctoral fellow Anmar Khadra and I began a new line of work for the lab on Type 1 Diabetes (T1D), characterized by auto-immune destruction of beta cells. Pietropaolo has a long-standing interest in use of islet autoantibodies as biomarkers of risk for progression to T1D. While differences in rate of progression have been correlated with the appearance of different autoantibodies or the number of autoantibody types, we sought to determine the underlying mechanism by developing a mathematical model for the interactions among beta cells, T cells and B cells. We identified two key parameters controlling the time to progression to T1D, the avidity of the T cells for beta cells and their killing efficiency. The model was also able to illuminate the phenomenon of avidity maturation, in which T-cell avidity increases over time, accelerating the disease process. See Ref. # 3.

在过去的几年里，我们的主要活动之一是在时间尺度上开发膜电位和钙振荡的综合模型，从秒到分钟不等。这些导致相应的胰岛素分泌振荡。该模型的基本假设是，更快（几十秒）的振荡源于钙对离子通道的反馈，可能是钙活化的钾（K(Ca)）通道和ATP依赖的钾（K(ATP)）通道，而较慢（5分钟）的振荡源于代谢的振荡。代谢振荡通过K（ATP）通道转导成电振荡。值得注意的是，后者是胰岛素刺激药物的一线靶点，如用于治疗2型糖尿病的磺脲类药物（甲磺丁酰胺、格列本脲）。因此，该模型由一个电子振荡器（EO）和一个代谢（糖酵解）振荡器(G)组成，被称为双振荡器模型（DOM）。我们目前正在用几种方法测试这个模型。去年我们报道了代谢振荡，通过NAD(P)H测量，通常在稳定的钙中持续存在，表明钙振荡不是代谢振荡所必需的。然而，这两者通常是串联发现的，钙的振荡，以及平均钙水平，确实影响代谢振荡。我们现在已经通过K（ATP）通道电导的测量证实了这些发现，并正在准备一篇关于这个主题的论文。