Newcomer insulin secretory granules as a highly calcium-sensitive pool

A microrheological examination of insulin-secreting β-cells in healthy and diabetic-like conditions

Pancreatic β-cells regulate glucose homeostasis through glucose-stimulated insulin secretion, which is hindered in type-2 diabetes. Transport of the insulin vesicles is expected to be affected by changes in the viscoelastic and transport properties of the cytoplasm. These are evaluated in situ through particle-tracking measurements using a rat insulinoma β-cell line. The use of inert probes assists in decoupling the material properties of the cytoplasm from the active transport through cellular processes. The effect of glucose-stimulated insulin secretion is examined, and the subsequent remodeling of the cytoskeleton, at constant effects of cell activity, is shown to result in reduced mobility of the tracer particles. Induction of diabetic-like conditions is identified to alter the mean-squared displacement of the passive particles in the cytoplasm and diminish its reaction to glucose stimulation.

A hydrophobic groove in secretagogin allows for alternate interactions with SNAP-25 and syntaxin-4 in endocrine tissues

Vesicular release of neurotransmitters and hormones relies on the dynamic assembly of the exocytosis/trans-SNARE complex through sequential interactions of synaptobrevins, syntaxins, and SNAP-25. Despite SNARE-mediated release being fundamental for intercellular communication in all excitable tissues, the role of auxiliary proteins modulating the import of reserve vesicles to the active zone, and thus, scaling repetitive exocytosis remains less explored. Secretagogin is a Ca2+-sensor protein with SNAP-25 being its only known interacting partner. SNAP-25 anchors readily releasable vesicles within the active zone, thus being instrumental for 1st phase release. However, genetic deletion of secretagogin impedes 2nd phase release instead, calling for the existence of alternative protein-protein interactions. Here, we screened the secretagogin interactome in the brain and pancreas, and found syntaxin-4 grossly overrepresented. Ca2+-loaded secretagogin interacted with syntaxin-4 at nanomolar affinity and 1:1 stoichiometry. Crystal structures of the protein complexes revealed a hydrophobic groove in secretagogin for the binding of syntaxin-4. This groove was also used to bind SNAP-25. In mixtures of equimolar recombinant proteins, SNAP-25 was sequestered by secretagogin in competition with syntaxin-4. Kd differences suggested that secretagogin could shape unidirectional vesicle movement by sequential interactions, a hypothesis supported by in vitro biological data. This mechanism could facilitate the movement of transport vesicles toward release sites, particularly in the endocrine pancreas where secretagogin, SNAP-25, and syntaxin-4 coexist in both α- and β-cells. Thus, secretagogin could modulate the pace and fidelity of vesicular hormone release by differential protein interactions.

Disrupted glucose homeostasis and glucagon and insulin secretion defects in Robo βKO mice

The axon guidance proteins, Roundabout (Robo) receptors play a critical role in morphogenesis of the islets of Langerhans. Mice with a β cell-selective deletion of Robo (Robo βKO), show severely disrupted spatial architecture of their islets, without defects in β cell differentiation or maturity. We have recently shown that Robo βKO mice have reduced synchronous glucose-stimulated β cell calcium oscillations in their islets in vivo, likely disrupting their pulsatile insulin secretion. Here, we analyze whole-body metabolic regulation in Robo βKO mice. We show that Robo βKO mice have mild defects in glucose homeostasis, and altered glucagon and insulin secretion. However, we did not observe any severe whole-body glucoregulatory phenotype following the disruption of islet architecture in Robo βKO. Our data suggest that islet architecture plays only a mild role in overall glucoregulation.

Determinants and dynamics of pancreatic islet architecture

The islets of Langerhans are highly organized structures that have species-specific, three-dimensional tissue architecture. Islet architecture is critical for proper hormone secretion in response to nutritional stimuli. Islet architecture is disrupted in all types of diabetes mellitus and in cadaveric islets for transplantation during isolation, culture, and perfusion, limiting patient outcomes. Moreover, recapitulating native islet architecture remains a key challenge for in vitro generation of islets from stem cells. In this review, we discuss work that has led to the current understanding of determinants of pancreatic islet architecture, and how this architecture is maintained or disrupted during tissue remodeling in response to normal and pathological metabolic changes. We further discuss both empirical and modeling data that highlight the importance of islet architecture for islet function.

Machine learning provides insight into models of heterogeneous electrical activity in human beta-cells

Understanding how heterogeneous cellular responses emerge from cell-to-cell variations in expression and function of subcellular components is of general interest. Here, we focus on human insulin-secreting beta-cells, which are believed to constitute a population in which heterogeneity is of physiological importance. We exploit recent single-cell electrophysiological data that allow biologically realistic population modeling of human beta-cells that accounts for cellular heterogeneity and correlation between ion channel parameters. To investigate how ion channels influence the dynamics of our updated mathematical model of human pancreatic beta-cells, we explore several machine learning techniques to determine which model parameters are important for determining the qualitative patterns of electrical activity of the model cells. As expected, K^＋ channels promote absence of activity, but once a cell is active, they increase the likelihood of having action potential firing. HERG channels were of great importance for determining cell behavior in most of the investigated scenarios. Fast bursting is influenced by the time scales of ion channel activation and, interestingly, by the type of Ca^2＋ channels coupled to BK channels in BK-CaV complexes. Slow, metabolically driven oscillations are promoted mostly by K(ATP) channels. In summary, combining population modeling with machine learning analysis provides insight into the model and generates new hypotheses to be investigated both experimentally, via simulations and through mathematical analysis.

Minimal and Maximal Models to Quantitate Glucose Metabolism: Tools to Measure, to Simulate and to Run in Silico Clinical Trials

Several models have been proposed to describe the glucose system at whole-body, organ/tissue and cellular level, designed to measure non-accessible parameters (minimal models), to simulate system behavior and run in silico clinical trials (maximal models). Here, we will review the authors' work, by putting it into a concise historical background. We will discuss first the parametric portrait provided by the oral minimal models-building on the classical intravenous glucose tolerance test minimal models-to measure otherwise non-accessible key parameters like insulin sensitivity and beta-cell responsivity from a physiological oral test, the mixed meal or the oral glucose tolerance tests, and what can be gained by adding a tracer to the oral glucose dose. These models were used in various pathophysiological studies, which we will briefly review. A deeper understanding of insulin sensitivity can be gained by measuring insulin action in the skeletal muscle. This requires the use of isotopic tracers: both the classical multiple-tracer dilution and the positron emission tomography techniques are discussed, which quantitate the effect of insulin on the individual steps of glucose metabolism, that is, bidirectional transport plasma-interstitium, and phosphorylation. Finally, we will present a cellular model of insulin secretion that, using a multiscale modeling approach, highlights the relations between minimal model indices and subcellular secretory events. In terms of maximal models, we will move from a parametric to a flux portrait of the system by discussing the triple tracer meal protocol implemented with the tracer-to-tracee clamp technique. This allows to arrive at quasi-model independent measurement of glucose rate of appearance (Ra), endogenous glucose production (EGP), and glucose rate of disappearance (Rd). Both the fast absorbing simple carbs and the slow absorbing complex carbs are discussed. This rich data base has allowed us to build the UVA/Padova Type 1 diabetes and the Padova Type 2 diabetes large scale simulators. In particular, the UVA/Padova Type 1 simulator proved to be a very useful tool to safely and effectively test in silico closed-loop control algorithms for an artificial pancreas (AP). This was the first and unique simulator of the glucose system accepted by the U.S. Food and Drug Administration as a substitute to animal trials for in silico testing AP algorithms. Recent uses of the simulator have looked at glucose sensors for non-adjunctive use and new insulin molecules.

The changing view of insulin granule mobility: From conveyor belt to signaling hub

Before the advent of TIRF microscopy the fate of the insulin granule prior to secretion was deduced from biochemical investigations, electron microscopy and electrophysiological measurements. Since Calcium-triggered granule fusion is indisputably necessary to release insulin into the extracellular space, much effort was directed to the measure this event at the single granule level. This has also been the major application of the TIRF microscopy of the pancreatic beta cell when it became available about 20 years ago. To better understand the metabolic modulation of secretion, we were interested to characterize the entirety of the insulin granules which are localized in the vicinity of the plasma membrane to identify the characteristics which predispose to fusion. In this review we concentrate on how the description of granule mobility in the submembrane space has evolved as a result of progress in methodology. The granules are in a state of constant turnover with widely different periods of residence in this space. While granule fusion is associated +with prolonged residence and decreased lateral mobility, these characteristics may not only result from binding to the plasma membrane but also from binding to the cortical actin web, which is present in the immediate submembrane space. While granule age as such affects granule mobility and fusion probability, the preceding functional states of the beta cell leave their mark on these parameters, too. In summary, the submembrane granules form a highly dynamic heterogeneous population and contribute to the metabolic memory of the beta cells.

Targeting the insulin granule for modulation of insulin exocytosis

The pancreatic β-cells control insulin secretion in the body to regulate glucose homeostasis, and β-cell stress and dysfunction is characteristic of Type 2 Diabetes. Pharmacological targeting of the β-cell to increase insulin secretion is typically utilised, however, extended use of common drugs such as sulfonylureas are known to result in secondary failure. Moreover, there is evidence they may induce β-cell failure in the long term. Within β-cells, insulin secretory granules (ISG) serve as compartments to store, process and traffic insulin for exocytosis. There is now growing evidence that ISG exist in multiple populations, distinct in their protein composition, motility, age, and capacity for secretion. In this review, we discuss the implications of a heterogenous ISG population in β-cells and highlight the need for more understanding into how unique ISG populations may be targeted in anti-diabetic therapies.

Glucose-induced [Ca2+]i oscillations in β cells are composed of trains of spikes within a subplasmalemmal microdomain

Electrical activity and oscillations of cytosolic Ca²⁺ concentrations ([Ca²⁺]_i) that trigger insulin release in response to glucose are key functions of pancreatic β cells. Although oscillatory Ca²⁺ signals have been intensively studied in β cells, their lower frequency did not match that of electrical activity. In addition, the measured peak [Ca²⁺]_i did not reach levels that are typically required by synaptotagmins to elicit the release of insulin-containing vesicles in live-cell experiments. We therefore sought to resolve the Ca²⁺ dynamics in the subplasmalemmal microdomain that is critical for triggering fast exocytosis. Applying total internal reflection fluorescence (TIRF) microscopy in insulin-producing INS-1E and primary mouse β cells, we resolved extraordinary fast trains of Ca²⁺ spiking (frequency > 3 s^-1) in response to glucose exposure. Using a low-affinity [Ca²⁺]_i indicator dye, we provide experimental evidence that Ca²⁺ spikes reach low micromolar apparent concentrations in the vicinity of the plasma membrane_. Analysis of Ca²⁺ spikes evoked by repeated depolarization for 10 ms closely matched the Ca²⁺ dynamics observed upon glucose application. To our knowledge, this is the first study that experimentally demonstrates Ca²⁺ spikes in β cells with velocities that resemble those of bursting or continuously appearing trains of action potentials (APs) in non-patched cells.

Reduced synchroneity of intra-islet Ca2+ oscillations in vivo in Robo-deficient β cells

The spatial architecture of the islets of Langerhans is hypothesized to facilitate synchronized insulin secretion among β cells, yet testing this in vivo in the intact pancreas is challenging. Robo βKO mice, in which the genes Robo1 and Robo2 are deleted selectively in β cells, provide a unique model of altered islet spatial architecture without loss of β cell differentiation or islet damage from diabetes. Combining Robo βKO mice with intravital microscopy, we show here that Robo βKO islets have reduced synchronized intra-islet Ca2+ oscillations among β cells in vivo. We provide evidence that this loss is not due to a β cell-intrinsic function of Robo, mis-expression or mis-localization of Cx36 gap junctions, or changes in islet vascularization or innervation, suggesting that the islet architecture itself is required for synchronized Ca2+ oscillations. These results have implications for understanding structure-function relationships in the islets during progression to diabetes as well as engineering islets from stem cells.

Construction of a prognostic model with histone modification-related genes and identification of potential drugs in pancreatic cancer

Background

Pancreatic cancer (PC) is a highly fatal and aggressive disease with its incidence and mortality quite discouraging. An effective prediction model is urgently needed for the accurate assessment of patients’ prognosis to assist clinical decision-making.

Methods

Gene expression data and clinicopathological data of the samples were acquired from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases. Differential expressed genes (DEGs) analysis, univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, random forest screening and multivariate Cox regression analysis were applied to construct the risk signature. The effectiveness and independence of the model were validated by time-dependent receiver operating characteristic (ROC) curve, Kaplan–Meier (KM) survival analysis and survival point graph in training set, test set, TCGA entire set and GSE57495 set. The validity of the core gene was verified by immunohistochemistry and our own independent cohort. Meanwhile, functional enrichment analysis of DEGs between the high and low risk groups revealed the potential biological pathways. Finally, CMap database and drug sensitivity assay were utilized to identify potential small molecular drugs as the risk model-related treatments for PC patients.

Results

Four histone modification-related genes were identified to establish the risk signature, including CBX8, CENPT, DPY30 and PADI1. The predictive performance of risk signature was validated in training set, test set, TCGA entire set and GSE57495 set, with the areas under ROC curve (AUCs) for 3-year survival were 0.773, 0.729, 0.775 and 0.770 respectively. Furthermore, KM survival analysis, univariate and multivariate Cox regression analysis proved it as an independent prognostic factor. Mechanically, functional enrichment analysis showed that the poor prognosis of high-risk population was related to the metabolic disorders caused by inadequate insulin secretion, which was fueled by neuroendocrine aberration. Lastly, a cluster of small molecule drugs were identified with significant potentiality in treating PC patients.

Conclusions

Based on a histone modification-related gene signature, our model can serve as a reliable prognosis assessment tool and help to optimize the treatment for PC patients. Meanwhile, a cluster of small molecule drugs were also identified with significant potentiality in treating PC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01928-6.

Isolation and Proteomics of the Insulin Secretory Granule

Insulin, a vital hormone for glucose homeostasis is produced by pancreatic beta-cells and when secreted, stimulates the uptake and storage of glucose from the blood. In the pancreas, insulin is stored in vesicles termed insulin secretory granules (ISGs). In Type 2 diabetes (T2D), defects in insulin action results in peripheral insulin resistance and beta-cell compensation, ultimately leading to dysfunctional ISG production and secretion. ISGs are functionally dynamic and many proteins present either on the membrane or in the lumen of the ISG may modulate and affect different stages of ISG trafficking and secretion. Previously, studies have identified few ISG proteins and more recently, proteomics analyses of purified ISGs have uncovered potential novel ISG proteins. This review summarizes the proteins identified in the current ISG proteomes from rat insulinoma INS-1 and INS-1E cell lines. Here, we also discuss techniques of ISG isolation and purification, its challenges and potential future directions.

Mathematical Modeling for the Physiological and Clinical Investigation of Glucose Homeostasis and Diabetes

Mathematical modeling in the field of glucose metabolism has a longstanding tradition. The use of models is motivated by several reasons. Models have been used for calculating parameters of physiological interest from experimental data indirectly, to provide an unambiguous quantitative representation of pathophysiological mechanisms, to determine indices of clinical usefulness from simple experimental tests. With the growing societal impact of type 2 diabetes, which involves the disturbance of the glucose homeostasis system, development and use of models in this area have increased. Following the approaches of physiological and clinical investigation, the focus of the models has spanned from representations of whole body processes to those of cells, i.e., from in vivo to in vitro research. Model-based approaches for linking in vivo to in vitro research have been proposed, as well as multiscale models merging the two areas. The success and impact of models has been variable. Two kinds of models have received remarkable interest: those widely used in clinical applications, e.g., for the assessment of insulin sensitivity and β-cell function and some models representing specific aspects of the glucose homeostasis system, which have become iconic for their efficacy in describing clearly and compactly key physiological processes, such as insulin secretion from the pancreatic β cells. Models are inevitably simplified and approximate representations of a physiological system. Key to their success is an appropriate balance between adherence to reality, comprehensibility, interpretative value and practical usefulness. This has been achieved with a variety of approaches. Although many models concerning the glucose homeostasis system have been proposed, research in this area still needs to address numerous issues and tackle new opportunities. The mathematical representation of the glucose homeostasis processes is only partial, also because some mechanisms are still only partially understood. For in vitro research, mathematical models still need to develop their potential. This review illustrates the problems, approaches and contribution of mathematical modeling to the physiological and clinical investigation of glucose homeostasis and diabetes, focusing on the most relevant and stimulating models.

Insulin granule biogenesis and exocytosis

Insulin is produced by pancreatic β-cells, and once released to the blood, the hormone stimulates glucose uptake and suppresses glucose production. Defects in both the availability and action of insulin lead to elevated plasma glucose levels and are major hallmarks of type-2 diabetes. Insulin is stored in secretory granules that form at the trans-Golgi network. The granules undergo extensive modifications en route to their release sites at the plasma membrane, including changes in both protein and lipid composition of the granule membrane and lumen. In parallel, the insulin molecules also undergo extensive modifications that render the hormone biologically active. In this review, we summarize current understanding of insulin secretory granule biogenesis, maturation, transport, docking, priming and eventual fusion with the plasma membrane. We discuss how different pools of granules form and how these pools contribute to insulin secretion under different conditions. We also highlight the role of the β-cell in the development of type-2 diabetes and discuss how dysregulation of one or several steps in the insulin granule life cycle may contribute to disease development or progression.

A Cellular Automaton Model as a First Model-Based Assessment of Interacting Mechanisms for Insulin Granule Transport in Beta Cells

In this paper a first model is derived and applied which describes the transport of insulin granules through the cell interior and at the membrane of a beta cell. A special role is assigned to the actin network, which significantly influences the transport. For this purpose, microscopically measured actin networks are characterized and then further ones are artificially generated. In a Cellular Automaton model, phenomenological laws for granule movement are formulated and implemented. Simulation results are compared with experiments, primarily using TIRF images and secretion rates. In this respect, good similarities are already apparent. The model is a first useful approach to describe complex granule transport processes in beta cells, and offers great potential for future extensions. Furthermore, the model can be used as a tool to validate hypotheses and associated mechanisms regarding their effect on exocytosis or other processes. For this purpose, the source code for the model is provided online.

Altered β-Cell Calcium Dynamics via Electric Field Exposure

Electric field stimulation has long been investigated with results supporting its therapeutic potential; however, its effects on insulin secreting cells has yet to be fully elucidated. Herein we explored the effects of physiological direct current (DC) electric field stimulation on the intracellular calcium dynamics of mouse derived βTC-6 insulinoma cells. This electrical stimulation resulted in an elevation in intracellular calcium along with a rise in calcium spiking activity. Further investigation indicated that the rise in intracellular calcium was mediated by an influx of calcium via L-type voltage gated calcium channels. Additionally, the effects of the electric field stimulation were able to induce insulin secretion in the absence of glucose stimulation. Given these results, DC electric field stimulation could be used as a non-invasive tool to modulate intracellular calcium dynamics and insulin secretion of β-cells for therapeutic application.

Recent Insights into Beta-cell Exocytosis in Type 2 Diabetes

As one of the leading causes of morbidity and mortality worldwide, diabetes affects an estimated 422 million adults, and it is expected to continue expanding such that by 2050, 30% of the U.S. population will become diabetic within their lifetime. Out of the estimated 422 million people currently afflicted with diabetes worldwide, about 5% have type 1 diabetes (T1D), while the remaining ~95% of diabetics have type 2 diabetes (T2D). Type 1 diabetes results from the autoimmune-mediated destruction of functional β-cell mass, whereas T2D results from combinatorial defects in functional β-cell mass plus peripheral glucose uptake. Both types of diabetes are now believed to be preceded by β-cell dysfunction. T2D is increasingly associated with numerous reports of deficiencies in the exocytosis proteins that regulate insulin release from β-cells, specifically the soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins. SNARE protein's functionality is further regulated by a variety of accessory factors such as Sec1/Munc18 (SM), double C2-domain proteins (DOC2), and additional interacting proteins at the cell surface that influence the fidelity of insulin release. As new evidence emerges about the detailed mechanisms of exocytosis, new questions and controversies have come to light. This emerging information is also contributing to dialogue in the islet biology field focused on how to correct the defects in insulin exocytosis. Herein we present a balanced review of the role of exocytosis proteins in T2D, with thoughts on novel strategies to protect functional β-cell mass.

Reducing Glucokinase Activity to Enhance Insulin Secretion: A Counterintuitive Theory to Preserve Cellular Function and Glucose Homeostasis

Pancreatic beta-cells are the only cells in the body that can synthesize and secrete insulin. Through the process of glucose-stimulated insulin secretion, beta-cells release insulin into circulation, stimulating GLUT4-dependent glucose uptake into peripheral tissue. Insulin is normally secreted in pulses that promote signaling at the liver. Long before type 2 diabetes is diagnosed, beta-cells become oversensitive to glucose, causing impaired pulsatility and overstimulation in fasting levels of glucose. The resulting hypersecretion of insulin can cause poor insulin signaling and clearance at the liver, leading to hyperinsulinemia and insulin resistance. Continued overactivity can eventually lead to beta-cell exhaustion and failure at which point type 2 diabetes begins. To prevent or reverse the negative effects of overstimulation, beta-cell activity can be reduced. Clinical studies have revealed the potential of beta-cell rest to reverse new cases of diabetes, but treatments lack durable benefits. In this perspective, we propose an intervention that reduces overactive glucokinase activity in the beta-cell. Glucokinase is known as the glucose sensor of the beta-cell due to its high control over insulin secretion. Therefore, glycolytic overactivity may be responsible for hyperinsulinemia early in the disease and can be reduced to restore normal stimulus-secretion coupling. We have previously reported that reducing glucokinase activity in prediabetic mouse islets can restore pulsatility and enhance insulin secretion. Building on this counterintuitive finding, we review the importance of pulsatile insulin secretion and highlight how normalizing glucose sensing in the beta cell during prediabetic hyperinsulinemia may restore pulsatility and improve glucose homeostasis.

Integrated multiscale mathematical modeling of insulin secretion reveals the role of islet network integrity for proper oscillatory glucose-dose response

The integrated multiscale mathematical model we present in this paper is built on two of our previous ones: a model of electrical oscillation in β-cells connected to neighboring cells within a three-dimensional (3D) network, and a model of glucose-induced β-cell intracellular insulin granule trafficking and insulin secretion. In order to couple these two models, we assume that the rate at which primed and release-ready insulin granules fuse at the cell membrane increases with the intracellular calcium concentration. Moreover, by assuming that the fraction of free K_ATP-channels decreases with increasing glucose concentration, we take into account the effect of glucose dose on membrane potential and, indirectly via the effect on the potential, on intracellular calcium. Numerical analysis of our new model shows that a single step increase in glucose concentration yields the experimentally observed characteristic biphasic insulin release. We find that the biphasic response is typically oscillatory in nature for low and moderate glucose concentrations. The plateau fraction (the time that the β-cells spend in their active firing phase) increases with increasing glucose dose, as does the total insulin secretion. At high glucose concentrations, the oscillations tend to vanish due to a constantly elevated membrane potential of the β-cells. Our results also demonstrate how insulin secretion characteristics in various glucose protocols depend on the degree of β-cell loss, highlighting the potential impact from disease. In particular, both the secretory capacity (average insulin secretion rate per β-cell) and the oscillatory response diminish as the islet cell network becomes compromised.

Mathematical modeling informs the impact of changes in circadian rhythms and meal patterns on insulin secretion

Disruption of circadian rhythms has been associated with metabolic syndromes, including obesity and diabetes. A variety of metabolic activities are under circadian modulation, as local and global clock gene knockouts result in glucose imbalance and increased risk of metabolic diseases. Insulin release from the pancreatic β cells exhibits daily variation, and recent studies have found that insulin secretion, not production, is under circadian modulation. As consideration of daily variation in insulin secretion is necessary to accurately describe glucose-stimulated insulin secretion, we describe a mathematical model that incorporates the circadian modulation via insulin granule trafficking. We use this model to understand the effect of oscillatory characteristics on insulin secretion at different times of the day. Furthermore, we integrate the dynamics of clock genes under the influence of competing environmental signals (light/dark cycle and feeding/fasting cycle) and demonstrate how circadian disruption and meal size distribution change the insulin secretion pattern over a 24-h day.

Calcium signaling and secretory granule pool dynamics underlie biphasic insulin secretion and its amplification by glucose: experiments and modeling

Glucose-stimulated insulin secretion from pancreatic β-cells is controlled by a triggering pathway that culminates in calcium influx and regulated exocytosis of secretory granules, and by a less understood amplifying pathway that augments calcium-induced exocytosis. In response to an abrupt increase in glucose concentration, insulin secretion exhibits a first peak followed by a lower sustained second phase. This biphasic secretion pattern is disturbed in diabetes. It has been attributed to depletion and subsequent refilling of a readily releasable pool of granules or to the phasic cytosolic calcium dynamics induced by glucose. Here, we apply mathematical modeling to experimental data from mouse islets to investigate how calcium and granule pool dynamics interact to control dynamic insulin secretion. Experimental calcium traces are used as inputs in three increasingly complex models of pool dynamics, which are fitted to insulin secretory patterns obtained using a set of protocols of glucose and tolbutamide stimulation. New calcium and secretion data for so-called staircase protocols, in which the glucose concentration is progressively increased, are presented. These data can be reproduced without assuming any heterogeneity in the model, in contrast to previous modeling, because of nontrivial calcium dynamics. We find that amplification by glucose can be explained by increased mobilization and priming of granules. Overall, our results indicate that calcium dynamics contribute substantially to shaping insulin secretion kinetics, which implies that better insight into the events creating phasic calcium changes in human β-cells is needed to understand the cellular mechanisms that disturb biphasic insulin secretion in diabetes.

Insulin secretory granules labelled with phogrin-fluorescent proteins show alterations in size, mobility and responsiveness to glucose stimulation in living β-cells

The intracellular life of insulin secretory granules (ISGs) from biogenesis to secretion depends on their structural (e.g. size) and dynamic (e.g. diffusivity, mode of motion) properties. Thus, it would be useful to have rapid and robust measurements of such parameters in living β-cells. To provide such measurements, we have developed a fast spatiotemporal fluctuation spectroscopy. We calculate an imaging-derived Mean Squared Displacement (iMSD), which simultaneously provides the size, average diffusivity, and anomalous coefficient of ISGs, without the need to extract individual trajectories. Clustering of structural and dynamic quantities in a multidimensional parametric space defines the ISGs' properties for different conditions. First, we create a reference using INS-1E cells expressing proinsulin fused to a fluorescent protein (FP) under basal culture conditions and validate our analysis by testing well-established stimuli, such as glucose intake, cytoskeleton disruption, or cholesterol overload. After, we investigate the effect of FP-tagged ISG protein markers on the structural and dynamic properties of the granule. While iMSD analysis produces similar results for most of the lumenal markers, the transmembrane marker phogrin-FP shows a clearly altered result. Phogrin overexpression induces a substantial granule enlargement and higher mobility, together with a partial de-polymerization of the actin cytoskeleton, and reduced cell responsiveness to glucose stimulation. Our data suggest a more careful interpretation of many previous ISG-based reports in living β-cells. The presented data pave the way to high-throughput cell-based screening of ISG structure and dynamics under various physiological and pathological conditions.

Defective Amplifying Pathway of β-Cell Secretory Response to Glucose in Type 2 Diabetes: Integrated Modeling of In Vitro and In Vivo Evidence

In vivo studies have investigated the role of β-cell dysfunction in type 2 diabetes (T2D), whereas in vitro research on islets has elucidated key mechanisms that control the insulin secretion rate. However, the relevance of the cellular mechanisms identified in vitro (i.e., the triggering and amplifying pathways) has not been established in vivo. Furthermore, the mechanisms underpinning β-cell dysfunction in T2D remain undetermined. We propose a unifying explanation of several characteristic features of insulin secretion both in vitro and in vivo by using a mathematical model. The model describes the triggering and amplifying pathways and reproduces a variety of in vitro and in vivo tests in subjects with and without T2D, identifies the mechanisms modulating first-phase insulin secretion rate in response to basal hyperglycemia or insulin resistance, and shows that β-cell dysfunction in T2D can be explained by an impaired amplifying pathway with no need to postulate defects in intracellular calcium handling.

Critical and Supercritical Spatiotemporal Calcium Dynamics in Beta Cells

A coordinated functioning of beta cells within pancreatic islets is mediated by oscillatory membrane depolarization and subsequent changes in cytoplasmic calcium concentration. While gap junctions allow for intraislet information exchange, beta cells within islets form complex syncytia that are intrinsically nonlinear and highly heterogeneous. To study spatiotemporal calcium dynamics within these syncytia, we make use of computational modeling and confocal high-speed functional multicellular imaging. We show that model predictions are in good agreement with experimental data, especially if a high degree of heterogeneity in the intercellular coupling term is assumed. In particular, during the first few minutes after stimulation, the probability distribution of calcium wave sizes is characterized by a power law, thus indicating critical behavior. After this period, the dynamics changes qualitatively such that the number of global intercellular calcium events increases to the point where the behavior becomes supercritical. To better mimic normal in vivo conditions, we compare the described behavior during supraphysiological non-oscillatory stimulation with the behavior during exposure to a slightly lower and oscillatory glucose challenge. In the case of this protocol, we observe only critical behavior in both experiment and model. Our results indicate that the loss of oscillatory changes, along with the rise in plasma glucose observed in diabetes, could be associated with a switch to supercritical calcium dynamics and loss of beta cell functionality.

Recent new insights into the role of SNARE and associated proteins in insulin granule exocytosis

Initial work on the exocytotic machinery of predocked insulin secretory granules (SGs) in pancreatic β-cells mimicked the SNARE hypothesis work in neurons, which includes SM/SNARE complex and associated priming proteins, fusion clamps and Ca²⁺ sensors. However, β-cell SGs, unlike neuronal synaptic vesicles, exhibit a biphasic secretory response that requires additional distinct features in exocytosis including newcomer SGs that undergo minimal docking time at the plasma membrane (PM) before fusion and multi-SG (compound) fusion. These exocytotic events are mediated by Munc18/SNARE complexes distinct from that which mediates predocked SG fusion. We review some recent insights in SNARE complex assembly and the promiscuity in SM/SNARE complex formation, whereby both contribute to conferring different insulin SG fusion kinetics. Some SNARE and associated proteins play non-fusion roles, including tethering SGs to Ca²⁺ channels, SG recruitment from cell interior to PM, and inhibitory SNAREs that block the action of profusion SNAREs. We discuss new insights into how sub-PM cytoskeletal mesh gates SG access to the PM and the targeting of SG exocytosis to PM domains in functionally polarized β-cells within intact islets. These recent developments have major implications on devising clever SNARE replacement therapies that could restore the deficient insulin secretion in diabetic islet β-cells.

Regulation of insulin exocytosis by calcium-dependent protein kinase C in beta cells

The control of insulin release from pancreatic beta cells helps ensure proper blood glucose level, which is critical for human health. Protein kinase C has been shown to be one key control mechanism for this process. After glucose stimulation, calcium influx into beta cells triggers exocytosis of insulin-containing dense-core granules and activates protein kinase C via calcium-dependent phospholipase C-mediated generation of diacylglycerol. Activated protein kinase C potentiates insulin release by enhancing the calcium sensitivity of exocytosis, likely by affecting two main pathways that could be linked: (1) the reorganization of the cortical actin network, and (2) the direct phosphorylation of critical exocytotic proteins such as munc18, SNAP25, and synaptotagmin. Here, we review what is currently known about the molecular mechanisms of protein kinase C action on each of these pathways and how these effects relate to the control of insulin release by exocytosis. We identify remaining challenges in the field and suggest how these challenges might be addressed to advance our understanding of the regulation of insulin release in health and disease.

Statistical Frailty Modeling for Quantitative Analysis of Exocytotic Events Recorded by Live Cell Imaging: Rapid Release of Insulin-Containing Granules Is Impaired in Human Diabetic β-cells

Hormones and neurotransmitters are released when secretory granules or synaptic vesicles fuse with the cell membrane, a process denoted exocytosis. Modern imaging techniques, in particular total internal reflection fluorescence (TIRF) microscopy, allow the investigator to monitor secretory granules at the plasma membrane before and when they undergo exocytosis. However, rigorous statistical approaches for temporal analysis of such exocytosis data are still lacking. We propose here that statistical methods from time-to-event (also known as survival) analysis are well suited for the problem. These methods are typically used in clinical settings when individuals are followed over time to the occurrence of an event such as death, remission or conception. We model the rate of exocytosis in response to pulses of stimuli in insulin-secreting pancreatic β-cell from healthy and diabetic human donors using piecewise-constant hazard modeling. To study heterogeneity in the granule population we exploit frailty modeling, which describe unobserved differences in the propensity to exocytosis. In particular, we insert a discrete frailty in our statistical model to account for the higher rate of exocytosis in an immediately releasable pool (IRP) of insulin-containing granules. Estimates of parameters are obtained from maximum-likelihood methods. Since granules within the same cell are correlated, i.e., the data are clustered, a modified likelihood function is used for log-likelihood ratio tests in order to perform valid inference. Our approach allows us for example to estimate the size of the IRP in the cells, and we find that the IRP is deficient in diabetic cells. This novel application of time-to-event analysis and frailty modeling should be useful also for the study of other well-defined temporal events at the cellular level.

Recent advances in mathematical modeling and statistical analysis of exocytosis in endocrine cells

Most endocrine cells secrete hormones as a result of Ca²⁺-regulated exocytosis, i.e., fusion of the membranes of hormone-containing secretory granules with the cell membrane, which allows the hormone molecules to escape to the extracellular space. As in neurons, electrical activity and cell depolarization open voltage-sensitive Ca²⁺ channels, and the resulting Ca²⁺ influx elevate the intracellular Ca²⁺ concentration, which in turn causes exocytosis. Whereas the main molecular components involved in exocytosis are increasingly well understood, quantitative understanding of the dynamical aspects of exocytosis is still lacking. Due to the nontrivial spatiotemporal Ca²⁺ dynamics, which depends on the particular pattern of electrical activity as well as Ca²⁺ channel kinetics, exocytosis is dependent on the spatial arrangement of Ca²⁺ channels and secretory granules. For example, the creation of local Ca²⁺ microdomains, where the Ca²⁺ concentration reaches tens of µM, are believed to be important for triggering exocytosis. Spatiotemporal simulations of buffered Ca²⁺ diffusion have provided important insight into the interplay between electrical activity, Ca²⁺ channel kinetics, and the location of granules and Ca²⁺ channels. By confronting simulations with statistical time-to-event (or survival) regression analysis of single granule exocytosis monitored with TIRF microscopy, a direct connection between location and rate of exocytosis can be obtained at the local, single-granule level. To get insight into whole-cell secretion, simplifications of the full spatiotemporal dynamics have shown to be highly helpful. Here, we provide an overview of recent approaches and results for quantitative analysis of Ca²⁺ regulated exocytosis of hormone-containing granules.

Decreases in Gap Junction Coupling Recovers Ca2+ and Insulin Secretion in Neonatal Diabetes Mellitus, Dependent on Beta Cell Heterogeneity and Noise

Diabetes is caused by dysfunction to β-cells in the islets of Langerhans, disrupting insulin secretion and glucose homeostasis. Gap junction-mediated electrical coupling between β-cells in the islet plays a major role in coordinating a pulsatile secretory response at elevated glucose and suppressing insulin secretion at basal glucose. Previously, we demonstrated that a critical number of inexcitable cells can rapidly suppress the overall islet response, as a result of gap junction coupling. This was demonstrated in a murine model of Neonatal Diabetes Mellitus (NDM) involving expression of ATP-insensitive K_ATP channels, and by a multi-cellular computational model of islet electrical activity. Here we examined the mechanisms by which gap junction coupling contributes to islet dysfunction in NDM. We first verified the computational model against [Ca²⁺] and insulin secretion measurements in islets expressing ATP-insensitive K_ATP channels under different levels of gap junction coupling. We then applied this model to predict how different K_ATP channel mutations found in NDM suppress [Ca²⁺], and the role of gap junction coupling in this suppression. We further extended the model to account for stochastic noise and insulin secretion dynamics. We found experimentally and in the islet model that reductions in gap junction coupling allow progressively greater glucose-stimulated [Ca²⁺] and insulin secretion following expression of ATP-insensitive K_ATP channels. The model demonstrated good correspondence between suppression of [Ca²⁺] and clinical presentation of different NDM mutations. Significant recoveries in [Ca²⁺] and insulin secretion were predicted for many mutations upon reductions in gap junction coupling, where stochastic noise played a significant role in the recoveries. These findings provide new understanding how the islet functions as a multicellular system and for the role of gap junction channels in exacerbating the effects of decreased cellular excitability. They further suggest novel therapeutic options for NDM and other monogenic forms of diabetes.

Diabetes is a disease reaching a global epidemic, which results from dysfunction to the islets of Langerhans in the pancreas and their ability to secrete the hormone insulin to regulate glucose homeostasis. Islets are multicellular structures that show extensive coupling between heterogeneous cellular units; and central to the causes of diabetes is a dysfunction to these cellular units and their interactions. Understanding the inter-relationship between structure and function is challenging in biological systems, but is crucial to the cause of disease and discovering therapeutic targets. With the goal of further characterizing the islet of Langerhans and its excitable behavior, we examined the role of important channels in the islet where dysfunction is linked to or causes diabetes. Advances in our ability to computationally model perturbations in physiological systems has allowed for the testing of hypothesis quickly, in systems that are not experimentally accessible. Using an experimentally validated model and modeling human mutations, we discover that monogenic forms of diabetes may be remedied by a reduction in electrical coupling between cells; either alone or in conjunction with pharmacological intervention. Knowledge of biological systems in general is also helped by these findings, in that small changes to cellular elements may lead to major disruptions in the overall system. This may then be overcome by allowing the system components to function independently in the presence of dysfunction to individual cells.

Synaptotagmin-7 Functions to Replenish Insulin Granules for Exocytosis in Human Islet β-Cells

Synaptotagmin (Syt)-7, a major component of the exocytotic machinery in neurons, is also the major Syt in rodent pancreatic β-cells shown to mediate glucose-stimulated insulin secretion (GSIS). However, Syt-7's precise exocytotic actions in β-cells remain unknown. We show that Syt-7 is abundant in human β-cells. Adenovirus-short hairpin RNA knockdown (KD) of Syt-7 in human islets reduced first- and second-phase GSIS attributed to the reduction of exocytosis of predocked and newcomer insulin secretory granules (SGs). Glucose stimulation expectedly induced Syt-7 association in a Ca(2+)-dependent manner with syntaxin-3 and syntaxin-1A soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complexes known to mediate exocytosis of newcomer and predocked SGs, respectively. However, Syt-7-KD did not disrupt SNARE complex assembly. Instead, electron microscopy analysis showed that Syt-7-KD reduced the recruitment of SGs to the plasma membrane after glucose-stimulated depletion, which could not be rescued by glucagon-like peptide 1 pretreatment. To assess the possibility that this new action of Syt-7 on SG recruitment may involve calmodulin (CaM), pretreatment of islets with CaM blocker calmidazolium showed effects very similar to those of Syt-7-KD. Syt-7 therefore plays a novel more dominant function in the replenishment of releasable SG pools in human β-cells than its previously purported role in exocytotic fusion per se.

Paracrine regulation of glucagon secretion: the β/α/δ model

The regulation of glucagon secretion in the pancreatic α-cell is not well understood. It has been proposed that glucose suppresses glucagon secretion either directly through an intrinsic mechanism within the α-cell or indirectly through an extrinsic mechanism. Previously, we described a mathematical model for isolated pancreatic α-cells and used it to investigate possible intrinsic mechanisms of regulating glucagon secretion. We demonstrated that glucose can suppress glucagon secretion through both ATP-dependent potassium channels (K_ATP) and a store-operated current (SOC). We have now developed an islet model that combines previously published mathematical models of α- and β-cells with a new model of δ-cells and use it to explore the effects of insulin and somatostatin on glucagon secretion. We show that the model can reproduce experimental observations that the inhibitory effect of glucose remains even when paracrine modulators are no longer acting on the α-cell. We demonstrate how paracrine interactions can either synchronize α- and δ-cells to produce pulsatile oscillations in glucagon and somatostatin secretion or fail to do so. The model can also account for the paradoxical observation that glucagon can be out of phase with insulin, whereas α-cell calcium is in phase with insulin. We conclude that both paracrine interactions and the α-cell's intrinsic mechanisms are needed to explain the response of glucagon secretion to glucose.

Syntaxin-3 Binds and Regulates Both R- and L-Type Calcium Channels in Insulin-Secreting INS-1 832/13 Cells

Syntaxin (Syn)-1A mediates exocytosis of predocked insulin-containing secretory granules (SGs) during first-phase glucose-stimulated insulin secretion (GSIS) in part via its interaction with plasma membrane (PM)-bound L-type voltage-gated calcium channels (Cav). In contrast, Syn-3 mediates exocytosis of newcomer SGs that accounts for second-phase GSIS. We now hypothesize that the newcomer SG Syn-3 preferentially binds and modulates R-type Cav opening, which was postulated to mediate second-phase GSIS. Indeed, glucose-stimulation of pancreatic islet β-cell line INS-1 induced a predominant increase in interaction between Syn-3 and Cavα1 pore-forming subunits of R-type Cav2.3 and to lesser extent L-type Cavs, while confirming the preferential interactions between Syn-1A with L-type (Cav1.2, Cav1.3) Cavs. Consistently, direct binding studies employing heterologous HEK cells confirmed that Syn-3 preferentially binds Cav2.3, whereas Syn-1A prefers L-type Cavs. We then used siRNA knockdown (KD) of Syn-3 in INS-1 to study the endogenous modulatory actions of Syn-3 on Cav channels. Syn-3 KD enhanced Ca2+ currents by 46% attributed mostly to R- and L-type Cavs. Interestingly, while the transmembrane domain of Syn-1A is the putative functional domain modulating Cav activity, it is the cytoplasmic domain of Syn-3 that appears to modulate Cav activity. We conclude that Syn-3 may mimic Syn-1A in the ability to bind and modulate Cavs, but preferring Cav2.3 to perhaps participate in triggering fusion of newcomer insulin SGs during second-phase GSIS.

A Unifying Organ Model of Pancreatic Insulin Secretion

The secretion of insulin by the pancreas has been the object of much attention over the past several decades. Insulin is known to be secreted by pancreatic β-cells in response to hyperglycemia: its blood concentrations however exhibit both high-frequency (period approx. 10 minutes) and low-frequency oscillations (period approx. 1.5 hours). Furthermore, characteristic insulin secretory response to challenge maneuvers have been described, such as frequency entrainment upon sinusoidal glycemic stimulation; substantial insulin peaks following minimal glucose administration; progressively strengthened insulin secretion response after repeated administration of the same amount of glucose; insulin and glucose characteristic curves after Intra-Venous administration of glucose boli in healthy and pre-diabetic subjects as well as in Type 2 Diabetes Mellitus. Previous modeling of β-cell physiology has been mainly directed to the intracellular chain of events giving rise to single-cell or cell-cluster hormone release oscillations, but the large size, long period and complex morphology of the diverse responses to whole-body glucose stimuli has not yet been coherently explained. Starting with the seminal work of Grodsky it was hypothesized that the population of pancreatic β-cells, possibly functionally aggregated in islets of Langerhans, could be viewed as a set of independent, similar, but not identical controllers (firing units) with distributed functional parameters. The present work shows how a single model based on a population of independent islet controllers can reproduce very closely a diverse array of actually observed experimental results, with the same set of working parameters. The model's success in reproducing a diverse array of experiments implies that, in order to understand the macroscopic behaviour of the endocrine pancreas in regulating glycemia, there is no need to hypothesize intrapancreatic pacemakers, influences between different islets of Langerhans, glycolitic-induced oscillations or β-cell sensitivity to the rate of change of glycemia.

Mathematical modelling of local calcium and regulated exocytosis during inhibition and stimulation of glucagon secretion from pancreatic alpha-cells

Glucagon secretion from pancreatic alpha-cells is dysregulated in diabetes. Despite decades of investigations of the control of glucagon release by glucose and hormones, the underlying mechanisms are still debated. Recently, mathematical models have been applied to investigate the modification of electrical activity in alpha-cells as a result of glucose application. However, recent studies have shown that paracrine effects such as inhibition of glucagon secretion by glucagon-like peptide 1 (GLP-1) or stimulation of release by adrenaline involve cAMP-mediated effects downstream of electrical activity. In particular, depending of the intracellular cAMP concentration, specific types of Ca(2+) channels are inhibited or activated, which interacts with mobilization of secretory granules. To investigate these aspects of alpha-cell function theoretically, we carefully developed a mathematical model of Ca(2+) levels near open or closed Ca(2+) channels of various types, which was linked to a description of Ca(2+) below the plasma membrane, in the bulk cytosol and in the endoplasmic reticulum. We investigated how the various subcellular Ca(2+) compartments contribute to control of glucagon-exocytosis in response to glucose, GLP-1 or adrenaline. Our studies refine previous modelling studies of alpha-cell function, and provide deeper insight into the control of glucagon secretion.

Granule mobility, fusion frequency and insulin secretion are differentially affected by insulinotropic stimuli

The pre-exocytotic behavior of insulin granules was studied against the background of the entirety of submembrane granules in MIN6 cells, and the characteristics were compared with the macroscopic secretion pattern and the cytosolic Ca(2+) concentration of MIN6 pseudo-islets at 22°C, 32°C and 37°C. The mobility of granules labeled by insulin-EGFP and the fusion events were assessed by TIRF microscopy utilizing an observer-independent algorithm. In the z-dimension, 40 mm K(+) or 30 mm glucose increased the granule turnover. The effect of high K(+) was quickly reversible. The increase by glucose was more sustained and modified the efficacy of a subsequent K(+) stimulus. The effect size of glucose increased with physiological temperature whereas that of high K(+) did not. The mobility in the x/y-dimension and the fusion rates were little affected by the stimuli, in contrast to secretion. Fusion and secretion, however, had the same temperature dependence. Granules that appeared and fused within one image sequence had significantly larger caging diameters than pre-existent granules that underwent fusion. These in turn had a different mobility than residence-matched non-fusing granules. In conclusion, delivery to the membrane, tethering and fusion of granules are differently affected by insulinotropic stimuli. Fusion rates and secretion do not appear to be tightly coupled.

Pulsatile insulin secretion, impaired glucose tolerance and type 2 diabetes

Type 2 diabetes (T2DM) results when increases in beta cell function and/or mass cannot compensate for rising insulin resistance. Numerous studies have documented the longitudinal changes in metabolism that occur during the development of glucose intolerance and lead to T2DM. However, the role of changes in insulin secretion, both amount and temporal pattern, has been understudied. Most of the insulin secreted from pancreatic beta cells of the pancreas is released in a pulsatile pattern, which is disrupted in T2DM. Here we review the evidence that changes in beta cell pulsatility occur during the progression from glucose intolerance to T2DM in humans, and contribute significantly to the etiology of the disease. We review the evidence that insulin pulsatility improves the efficacy of secreted insulin on its targets, particularly hepatic glucose production, but also examine evidence that pulsatility alters or is altered by changes in peripheral glucose uptake. Finally, we summarize our current understanding of the biophysical mechanisms responsible for oscillatory insulin secretion. Understanding how insulin pulsatility contributes to normal glucose homeostasis and is altered in metabolic disease states may help improve the treatment of T2DM.

Advancing our understanding of the glucose system via modeling: a perspective

The glucose story begins with Claude Bernard's discovery of glycogen and milieu interieur, continued with Banting's and Best's discovery of insulin and with Rudolf Schoenheimer's paradigm of dynamic body constituents. Tracers and compartmental models allowed moving to the first quantitative pictures of the system and stimulated important developments in terms of modeling methodology. Three classes of multiscale models, models to measure, models to simulate, and models to control the glucose system, are reviewed in their historical development with an eye to the future.

Detection of insulin granule exocytosis by an electrophysiology method with high temporal resolution reveals enlarged insulin granule pool in BIG3-knockout mice

We recently identified BIG3 as a negative regulator of insulin granule biogenesis and reported increased insulin secretion in BIG3-knockout (BKO) mice. To pinpoint the site of action for BIG3, we investigated whether BIG3 regulates quantal insulin granule exocytosis. We established an assay to detect insulin granule exocytosis by recording ATP-elicited currents at high temporal resolution by patch clamp. Similarly to insulin, ATP release was increased in BKO β-cells. Although the frequency of insulin granule exocytosis was increased in BKO β-cells, quantal size or release kinetics remained unchanged. Electron microscopy studies showed that the number of insulin granules was increased by >60% in BKO β-cells. However, the number of morphologically docked granules was unaltered. The number of insulin granules having significant distances away from plasma membrane was greatly increased in BKO β-cells. Thus, BIG3 negatively regulates insulin granule exocytosis by restricting insulin granule biogenesis without the release kinetics of individual granules at the final exocytotic steps being affected. Depletion of BIG3 leads to an enlarged releasable pool of insulin granules, which accounts for increased release frequency and consequently increased insulin secretion.

Modeling the pancreatic α-cell: dual mechanisms of glucose suppression of glucagon secretion

The mechanism by which glucose induces insulin secretion in β-cells is fairly well understood. Despite years of research, however, the mechanism of glucagon secretion in α-cells is still not well established. It has been proposed that glucose regulates glucagon secretion by decreasing the conductance of either outward ATP-dependent potassium channels (K(ATP)) or an inward store-operated current (SOC). We have developed a mathematical model based on mouse data to test these hypotheses and found that both mechanisms are possible. Glucose metabolism closes K(ATP) channels, which depolarizes the cell but paradoxically reduces calcium influx by inactivating voltage-dependent calcium and sodium channels and decreases secretion. Glucose metabolism also activates SERCA pumps, which fills the endoplasmic reticulum and hyperpolarizes the cells by reducing the inward current through SOC channels and again suppresses glucagon secretion. We find further that the two mechanisms can combine to account for the nonmonotonic dependence of secretion on glucose observed in some studies, an effect that cannot be obtained with either mechanism alone.

Calcium current inactivation rather than pool depletion explains reduced exocytotic rate with prolonged stimulation in insulin-secreting INS-1 832/13 cells

Impairment in beta-cell exocytosis is associated with reduced insulin secretion and diabetes. Here we aimed to investigate the dynamics of Ca2+-dependent insulin exocytosis with respect to pool depletion and Ca2+-current inactivation. We studied exocytosis, measured as increase in membrane capacitance (ΔCm), as a function of calcium entry (Q) in insulin secreting INS-1 832/13 cells using patch clamp and mixed-effects statistical analysis. The observed linear relationship between ΔCm and Q suggests that Ca2+-channel inactivation rather than granule pool restrictions is responsible for the decline in exocytosis observed at longer depolarizations. INS-1 832/13 cells possess an immediately releasable pool (IRP) of ∼10 granules and most exocytosis of granules occurs from a large pool. The latter is attenuated by the calcium-buffer EGTA, while IRP is unaffected. These findings suggest that most insulin release occurs away from Ca2+-channels, and that pool depletion plays a minor role in the decline of exocytosis upon prolonged stimulation.

Here come the newcomer granules, better late than never

Exocytosis in pancreatic β-cells employs Munc18/soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complexes that mediate the priming and docking onto the plasma membrane (PM) of insulin granules, called predocked granules, that sit on the PM until Ca(2+) influx evokes fusion. This accounts for most of the initial peak secretory response. However, the subsequent sustained phase of glucose-stimulated insulin secretion arises from newcomer granules that have a minimal residence time at the PM before fusion. In this Opinion I discuss recent work that has begun to decipher the components of the exocytotic machinery of newcomer granules, including a Munc18/SNARE complex that is different from that mediating the fusion of predocked granules and which can potentially rescue defective insulin secretion in diabetes. These insights are applicable to other neuroendocrine cells that exhibit sustained secretion.

BIG3 inhibits insulin granule biogenesis and insulin secretion

While molecular regulation of insulin granule exocytosis is relatively well understood, insulin granule biogenesis and maturation and its influence on glucose homeostasis are relatively unclear. Here, we identify a novel protein highly expressed in insulin-secreting cells and name it BIG3 due to its similarity to BIG/GBF of the Arf-GTP exchange factor (GEF) family. BIG3 is predominantly localized to insulin- and clathrin-positive trans-Golgi network (TGN) compartments. BIG3-deficient insulin-secreting cells display increased insulin content and granule number and elevated insulin secretion upon stimulation. Moreover, BIG3 deficiency results in faster processing of proinsulin to insulin and chromogranin A to β-granin in β-cells. BIG3-knockout mice exhibit postprandial hyperinsulinemia, hyperglycemia, impaired glucose tolerance, and insulin resistance. Collectively, these results demonstrate that BIG3 negatively modulates insulin granule biogenesis and insulin secretion and participates in the regulation of systemic glucose homeostasis.

Minimal modeling of insulin secretion in the perfused rat pancreas: a drug effect case study

The experimental protocol of the perfused rat pancreas is commonly used to evaluate β-cell function. In this context, mathematical models become useful tools through the determination of indexes that allow the assessment of β-cell function in different experimental groups and the quantification of the effects of antidiabetic drugs, secretagogues, or treatments. However, a minimal model applicable to the isolated perfused rat pancreas has so far been unavailable. In this work, we adapt the C-peptide minimal model applied previously to the intravenous glucose tolerance test to obtain a specific model for the experimental settings of the perfused pancreas. Using the model, it is possible to estimate indexes describing β-cell responsivity for first (ΦD) and second phase (ΦS, T) of insulin secretion. The model was initially applied to untreated pancreata and afterward used for the assessment of pharmacologically relevant agents (the gut hormone GLP-1, the potent GLP-1 receptor agonist lixisenatide, and a GPR40/FFAR1 agonist, SAR1) to quantify and differentiate their effect on insulin secretion. Model fit was satisfactory, and parameters were estimated with good precision for both untreated and treated pancreata. Model application showed that lixisenatide reaches improvement of β-cell function similarly to GLP-1 (11.7- vs. 13.1-fold increase in ΦD and 2.3- vs. 2.8-fold increase in ΦS) and demonstrated that SAR1 leads to an additional improvement of β-cell function in the presence of postprandial GLP-1 levels.

Observer-independent quantification of insulin granule exocytosis and pre-exocytotic mobility by TIRF microscopy

Total internal reflection fluorescence microscopy of fluorescently labeled secretory granules permits monitoring of exocytosis and the preceding granule behavior in one experiment. While observer-dependent evaluation may be sufficient to quantify exocytosis, most of the other information contained in the video files cannot be accessed this way. The present program performs observer-independent detection of exocytosis and tracking of the entire submembrane population of insulin granules. A precondition is the exact localization of the peak of the granule fluorescence. Tracking is based on the peak base radius, peak intensity, and the precrossing itineraries. Robustness of the tracking was shown by simulated tracks of original granule patterns. Mobility in the X-Y dimension is described by the caging diameter which in contrast to the widely used mean square displacement has an inherent time resolution. Observer-independent detection of exocytosis in MIN6 cells labeled with insulin-EGFP is based on the maximal decrease in fluorescence intensity and position of the centroid of the dissipating cloud of released material. Combining the quantification of KCl-induced insulin exocytosis with the analysis of prefusion mobility showed that during the last 3 s pre-exocytotic granules had a smaller caging diameter than control granules and that it increased significantly immediately before fusion.

Multiscale modelling of insulin secretion during an intravenous glucose tolerance test

Dysfunctional insulin secretion from pancreatic β-cells plays a major role in the development of diabetes. The intravenous glucose tolerance test (IVGTT) is a widely used clinical test to assess β-cell function. The analysis of IVGTT data is conveniently performed using mathematical models, which need to be fairly simple to enable parameter identifiability (minimal models), but should at the same time have sound biological foundation at the cellular level. Using mathematical analysis and model reduction, we show here that our recent mathematical model of insulin secretory granule dynamics in β-cells provides mechanistic underpinning for our minimal model of pancreatic insulin secretion during an IVGTT.

Insulin biosynthetic interaction network component, TMEM24, facilitates insulin reserve pool release

Insulin homeostasis in pancreatic β cells is now recognized as a critical element in the progression of obesity and type II diabetes (T2D). Proteins that interact with insulin to direct its sequential synthesis, folding, trafficking, and packaging into reserve granules in order to manage release in response to elevated glucose remain largely unknown. Using a conformation-based approach combined with mass spectrometry, we have generated the insulin biosynthetic interaction network (insulin BIN), a proteomic roadmap in the β cell that describes the sequential interacting partners of insulin along the secretory axis. The insulin BIN revealed an abundant C2 domain-containing transmembrane protein 24 (TMEM24) that manages glucose-stimulated insulin secretion from a reserve pool of granules, a critical event impaired in patients with T2D. The identification of TMEM24 in the context of a comprehensive set of sequential insulin-binding partners provides a molecular description of the insulin secretory pathway in β cells.