Beta cells within the pancreatic islets of Langerhans respond to stimulation with coherent oscillations of membrane potential and intracellular calcium concentration that presumably drive the pulsatile exocytosis of insulin. Their rhythmic activity is multimodal, resulting from networked feedback interactions of various oscillatory subsystems, such as the glycolytic, mitochondrial, and electrical/calcium components. How these oscillatory modules interact and affect the collective cellular activity, which is a prerequisite for proper hormone release, is incompletely understood. In the present work, we combined advanced confocal Ca²⁺ imaging in fresh mouse pancreas tissue slices with time series analysis and network science approaches to unveil the glucose-dependent characteristics of different oscillatory components on both the intra- and inter-cellular level. Our results reveal an interrelationship between the metabolically driven low-frequency component and the electrically driven high-frequency component, with the latter exhibiting the highest bursting rates around the peaks of the slow component and the lowest around the nadirs. Moreover, the activity, as well as the average synchronicity of the fast component, considerably increased with increasing stimulatory glucose concentration, whereas the stimulation level did not affect any of these parameters in the slow component domain. Remarkably, in both dynamical components, the average correlation decreased similarly with intercellular distance, which implies that intercellular communication affects the synchronicity of both types of oscillations. To explore the intra-islet synchronization patterns in more detail, we constructed functional connectivity maps. The subsequent comparison of network characteristics of different oscillatory components showed more locally clustered and segregated networks of fast oscillatory activity, while the slow oscillations were more global, resulting in several long-range connections and a more cohesive structure. Besides the structural differences, we found a relatively weak relationship between the fast and slow network layer, which suggests that different synchronization mechanisms shape the collective cellular activity in islets, a finding which has to be kept in mind in future studies employing different oscillations for constructing networks.

Type 2 diabetes mellitus is a complex multifactorial disease of epidemic proportions. It involves genetic and lifestyle factors that lead to dysregulations in hormone secretion and metabolic homeostasis. Accumulating evidence indicates that altered mitochondrial structure, function, and particularly bioenergetics of cells in different tissues have a central role in the pathogenesis of type 2 diabetes mellitus. In the present study, we explore how mitochondrial dysfunction impairs the coupling between metabolism and exocytosis in the pancreatic alpha and beta cells. We demonstrate that reduced mitochondrial ATP production is linked with the observed defects in insulin and glucagon secretion by utilizing computational modeling approach. Specifically, a 30–40% reduction in alpha cells’ mitochondrial function leads to a pathological shift of glucagon secretion, characterized by oversecretion at high glucose concentrations and insufficient secretion in hypoglycemia. In beta cells, the impaired mitochondrial energy metabolism is accompanied by reduced insulin secretion at all glucose levels, but the differences, compared to a normal beta cell, are the most pronounced in hyperglycemia. These findings improve our understanding of metabolic pathways and mitochondrial bioenergetics in the pathology of type 2 diabetes mellitus and might help drive the development of innovative therapies to treat various metabolic diseases.

Pancreatic beta cells regulate insulin secretion in response to glucose by generating ATP, which modulates ATP-sensitive potassium channels (K_ATP) channel activity and Ca²⁺ dynamics. We present a model of ATP production in pancreatic beta cells, focusing on ATP dynamics within the bulk cytosol, submembrane region, and microdomains near K_ATP channels. ATP is generated through glycolysis, mitochondrial oxidative phosphorylation (OxPhos), and glycolytic pyruvate kinase-mediated phosphoenolpyruvate (PEP) production, supported by PEP cycling between mitochondria and the cytosol. The model examines ATP production in relation to Ca²⁺ oscillations, elucidating their interdependent dynamics. Our findings demonstrate that both mitochondrial OxPhos and PEP-mediated ATP production contribute substantially to cellular ATP levels. Specifically, glycolysis and mitochondrial OxPhos are crucial for the initial (first-phase) increase in bulk and subplasmalemmal ATP, effectively “filling up” the ATP pool in beta cells. In the second phase, coordinated cycling between OxPhos and PEP pathways enables cost-effective fine-tuning of ATP levels, with localized effects in the K_ATP channel microdomains. This model addresses and clarifies the recent debate regarding the mechanisms by which sufficient ATP concentrations are achieved to close K_ATP channels in glucose-stimulated beta cells, offering novel insights into the regulation of energy production and K_ATP channel activity.

We propose a detailed computational beta cell model that emphasizes the role of anaplerotic metabolism under glucose and glucose-glutamine stimulation. This model goes beyond the traditional focus on mitochondrial oxidative phosphorylation and ATP-sensitive K+ channels, highlighting the predominant generation of ATP from phosphoenolpyruvate in the vicinity of KATP channels. It also underlines the modulatory role of H2O2 as a signaling molecule in the first phase of glucose-stimulated insulin secretion. In the second phase, the model emphasizes the critical role of anaplerotic pathways, activated by glucose stimulation via pyruvate carboxylase and by glutamine via glutamate dehydrogenase. It particularly focuses on the production of NADPH and glutamate as key enhancers of insulin secretion. The predictions of the model are consistent with empirical data, highlighting the complex interplay of metabolic pathways and emphasizing the primary role of glucose and the facilitating role of glutamine in insulin secretion. By delineating these crucial metabolic pathways, the model provides valuable insights into potential therapeutic targets for diabetes.

Hyperlipidemia is a common metabolic disorder in modern society and may precede hyperglycemia and diabetes by several years. Exactly how disorders of lipid and glucose metabolism are related is still a mystery in many respects. We analyze the effects of hyperlipidemia, particularly free fatty acids, on pancreatic beta cells and insulin secretion. We have developed a computational model to quantitatively estimate the effects of specific metabolic pathways on insulin secretion and to assess the effects of short- and long-term exposure of beta cells to elevated concentrations of free fatty acids. We show that the major trigger for insulin secretion is the anaplerotic pathway via the phosphoenolpyruvate cycle, which is affected by free fatty acids via uncoupling protein 2 and proton leak and is particularly destructive in long-term chronic exposure to free fatty acids, leading to increased insulin secretion at low blood glucose and inadequate insulin secretion at high blood glucose. This results in beta cells remaining highly active in the “resting” state at low glucose and being unable to respond to anaplerotic signals at high pyruvate levels, as is the case with high blood glucose. The observed fatty-acid-induced disruption of anaplerotic pathways makes sense in the context of the physiological role of insulin as one of the major anabolic hormones.