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

The calcium pump PMCA4b promotes epithelial cell polarization and lumen formation

Loss of epithelial cell polarity and tissue disorganization are hallmarks of carcinogenesis, in which Ca2+ signaling plays a significant role. Here we demonstrate that the plasma membrane Ca2+ pump PMCA4 (ATP2B4) is downregulated in luminal breast cancer, and this is associated with shorter relapse-free survival in patients with luminal A and B1 subtype tumors. Using the MCF-7 breast cancer cell model we show that PMCA4 silencing results in the loss of cell polarity while a forced increase in PMCA4b expression induces cell polarization and promotes lumen formation. We identify Arf6 as a regulator of PMCA4b endocytic recycling essential for PMCA4-mediated lumen formation. Silencing of the single pmca gene in Drosophila melanogaster larval salivary gland destroys lumen morphology suggesting a conserved role of PMCAs in lumen morphogenesis. Our findings point to a role of PMCA4 in controlling epithelial cell polarity, and in the maintenance of normal glandular tissue architecture.

Hypertonicity during a rapid rise in D-glucose mediates first-phase insulin secretion

Introduction

Biphasic insulin secretion is an intrinsic characteristic of the pancreatic islet and has clinical relevance due to the loss of first-phase in patients with Type 2 diabetes. As it has long been shown that first-phase insulin secretion only occurs in response to rapid changes in glucose, we tested the hypothesis that islet response to an increase in glucose is a combination of metabolism plus an osmotic effect where hypertonicity is driving first-phase insulin secretion.

Methods

Experiments were performed using perifusion analysis of rat, mouse, and human islets. Insulin secretion rate (ISR) and other parameters associated with its regulation were measured in response to combinations of D-glucose and membrane-impermeable carbohydrates (L-glucose or mannitol) designed to dissect the effect of hypertonicity from that of glucose metabolism.

Results

Remarkably, the appearance of first-phase responses was wholly dependent on changes in tonicity: no first-phase in NAD(P)H, cytosolic calcium, cAMP secretion rate (cAMP SR), or ISR was observed when increased D-glucose concentration was counterbalanced by decreases in membrane-impermeable carbohydrates. When D-glucose was greater than 8 mM, rapid increases in L-glucose without any change in D-glucose resulted in first-phase responses in all measured parameters that were kinetically similar to D-glucose. First-phase ISR was completely abolished by H89 (a non-specific inhibitor of protein kinases) without affecting first-phase calcium response. Defining first-phase ISR as the difference between glucose-stimulated ISR with and without a change in hypertonicity, the peak of first-phase ISR occurred after second-phase ISR had reached steady state, consistent with the well-established glucose-dependency of mechanisms that potentiate glucose-stimulated ISR.

Discussion

The data collected in this study suggests a new model of glucose-stimulated biphasic ISR where first-phase ISR derives from (and after) a transitory amplification of second-phase ISR and driven by hypertonicity-induced rise in H89-inhibitable kinases likely driven by first-phase responses in cAMP, calcium, or a combination of both.

Unique features of β-cell metabolism are lost in type 2 diabetes

Pancreatic β cells play an essential role in the control of systemic glucose homeostasis as they sense blood glucose levels and respond by secreting insulin. Upon stimulating glucose uptake in insulin-sensitive tissues post-prandially, this anabolic hormone restores blood glucose levels to pre-prandial levels. Maintaining physiological glucose levels thus relies on proper β-cell function. To fulfill this highly specialized nutrient sensor role, β cells have evolved a unique genetic program that shapes its distinct cellular metabolism. In this review, the unique genetic and metabolic features of β cells will be outlined, including their alterations in type 2 diabetes (T2D). β cells selectively express a set of genes in a cell type-specific manner; for instance, the glucose activating hexokinase IV enzyme or Glucokinase (GCK), whereas other genes are selectively "disallowed", including lactate dehydrogenase A (LDHA) and monocarboxylate transporter 1 (MCT1). This selective gene program equips β cells with a unique metabolic apparatus to ensure that nutrient metabolism is coupled to appropriate insulin secretion, thereby avoiding hyperglycemia, as well as life-threatening hypoglycemia. Unlike most cell types, β cells exhibit specialized bioenergetic features, including supply-driven rather than demand-driven metabolism and a high basal mitochondrial proton leak respiration. The understanding of these unique genetically programmed metabolic features and their alterations that lead to β-cell dysfunction is crucial for a comprehensive understanding of T2D pathophysiology and the development of innovative therapeutic approaches for T2D patients.

Network representation of multicellular activity in pancreatic islets: Technical considerations for functional connectivity analysis

Within the islets of Langerhans, beta cells orchestrate synchronized insulin secretion, a pivotal aspect of metabolic homeostasis. Despite the inherent heterogeneity and multimodal activity of individual cells, intercellular coupling acts as a homogenizing force, enabling coordinated responses through the propagation of intercellular waves. Disruptions in this coordination are implicated in irregular insulin secretion, a hallmark of diabetes. Recently, innovative approaches, such as integrating multicellular calcium imaging with network analysis, have emerged for a quantitative assessment of the cellular activity in islets. However, different groups use distinct experimental preparations, microscopic techniques, apply different methods to process the measured signals and use various methods to derive functional connectivity patterns. This makes comparisons between findings and their integration into a bigger picture difficult and has led to disputes in functional connectivity interpretations. To address these issues, we present here a systematic analysis of how different approaches influence the network representation of islet activity. Our findings show that the choice of methods used to construct networks is not crucial, although care is needed when combining data from different islets. Conversely, the conclusions drawn from network analysis can be heavily affected by the pre-processing of the time series, the type of the oscillatory component in the signals, and by the experimental preparation. Our tutorial-like investigation aims to resolve interpretational issues, reconcile conflicting views, advance functional implications, and encourage researchers to adopt connectivity analysis. As we conclude, we outline challenges for future research, emphasizing the broader applicability of our conclusions to other tissues exhibiting complex multicellular dynamics.

Diabetes and vitamin D: The effect of insulin sensitivity and gut microbial health

Current global estimation suggests that about 10% of adults worldwide have diabetes, thus, various strategies are needed to address the issue, including dietary factors such as vitamin D. Various studies have suggested an inverse associations between vitamin D and the risks and pathogenesis of all forms of diabetes (type 1, type 2 and gestational diabetes). The underlying mechanism is not fully understood; however, the expression of vitamin D receptors in pancreatic beta cells suggests an important physiological role for vitamin D in beta cell function. Vitamin D deficiency may impair blood glucose control and decrease insulin sensitivity by reducing insulin secretion from beta cells. Many studies suggest that vitamin D intervention may be beneficial; however, there is inconclusive evidence of the effectiveness of vitamin D supplementation on reducing the risks or managing the pathogenesis of all forms of diabetes. Part of the pathogenesis of vitamin D for reducing diabetes is thought to be related to its impact on gut microbiota profile, via the suggested prebiotic properties of vitamin D.

Exendin-4 affects calcium signalling predominantly during activation and activity of beta cell networks in acute mouse pancreas tissue slices

Tight control of beta cell stimulus-secretion coupling is crucial for maintaining homeostasis of energy-rich nutrients. While glucose serves as a primary regulator of this process, incretins augment beta cell function, partly by enhancing cytosolic [Ca2+] dynamics. However, the details of how precisely they affect beta cell recruitment during activation, their active time, and functional connectivity during plateau activity, and how they influence beta cell deactivation remain to be described. Performing functional multicellular Ca2+ imaging in acute mouse pancreas tissue slices enabled us to systematically assess the effects of the GLP-1 receptor agonist exendin-4 (Ex-4) simultaneously in many coupled beta cells with high resolution. In otherwise substimulatory glucose, Ex-4 was able to recruit approximately a quarter of beta cells into an active state. Costimulation with Ex-4 and stimulatory glucose shortened the activation delays and accelerated beta cell activation dynamics. More specifically, active time increased faster, and the time required to reach half-maximal activation was effectively halved in the presence of Ex-4. Moreover, the active time and regularity of [Ca2+]IC oscillations increased, especially during the first part of beta cell response. In contrast, subsequent addition of Ex-4 to already active cells did not significantly enhance beta cell activity. Network analyses further confirmed increased connectivity during activation and activity in the presence of Ex-4, with hub cell roles remaining rather stable in both control experiments and experiments with Ex-4. Interestingly, Ex-4 demonstrated a biphasic effect on deactivation, slightly prolonging beta cell activity at physiological concentrations and shortening deactivation delays at supraphysiological concentrations. In sum, costimulation by Ex-4 and glucose increases [Ca2+]IC during beta cell activation and activity, indicating that the effect of incretins may, to an important extent, be explained by enhanced [Ca2+]IC signals. During deactivation, previous incretin stimulation does not critically prolong cellular activity, which corroborates their low risk of hypoglycemia.

Amino acid-stimulated insulin secretion: a path forward in type 2 diabetes

Qualitative and quantitatively appropriate insulin secretion is essential for optimal control of blood glucose. Beta-cells of the pancreas produce and secrete insulin in response to glucose and non-glucose stimuli including amino acids. In this manuscript, we review the literature on amino acid-stimulated insulin secretion in oral and intravenous in vivo studies, in addition to the in vitro literature, and describe areas of consensus and gaps in understanding. We find promising evidence that the synergism of amino acid-stimulated insulin secretion could be exploited to develop novel therapeutics, but that a systematic approach to investigating these lines of evidence is lacking. We highlight evidence that supports the relative preservation of amino acid-stimulated insulin secretion compared to glucose-stimulated insulin secretion in type 2 diabetes, and make the case for the therapeutic potential of amino acids. Finally, we make recommendations for research and describe the potential clinical utility of nutrient-based treatments for type 2 diabetes including remission services.

Rapid Quantification of First and Second Phase Insulin Secretion Dynamics using an In vitro Platform for Improving Insulin Therapy

High-throughput quantification of the first- and second-phase insulin secretion dynamics is intractable with current methods. The fact that independent secretion phases play distinct roles in metabolism necessitates partitioning them separately and performing high-throughput compound screening to target them individually. We developed an insulin-nanoluc luciferase reporter system to dissect the molecular and cellular pathways involved in the separate phases of insulin secretion. We validated this method through genetic studies, including knockdown and overexpression, as well as small-molecule screening and their effects on insulin secretion. Furthermore, we demonstrated that the results of this method are well correlated with those of single-vesicle exocytosis experiments conducted on live cells, providing a quantitative reference for the approach. Thus, we have developed a robust methodology for screening small molecules and cellular pathways that target specific phases of insulin secretion, resulting in a better understanding of insulin secretion, which in turn will result in a more effective insulin therapy through the stimulation of endogenous glucose-stimulated insulin secretion.

Noncanonical Regulation of cAMP-Dependent Insulin Secretion and Its Implications in Type 2 Diabetes

Impaired glucose tolerance (IGT) and β-cell dysfunction in insulin resistance associated with obesity lead to type 2 diabetes (T2D). Glucose-stimulated insulin secretion (GSIS) from β-cells occurs via a canonical pathway that involves glucose metabolism, ATP generation, inactivation of K ATP channels, plasma membrane depolarization, and increases in cytosolic concentrations of [Ca 2+ ] c . However, optimal insulin secretion requires amplification of GSIS by increases in cyclic adenosine monophosphate (cAMP) signaling. The cAMP effectors protein kinase A (PKA) and exchange factor activated by cyclic-AMP (Epac) regulate membrane depolarization, gene expression, and trafficking and fusion of insulin granules to the plasma membrane for amplifying GSIS. The widely recognized lipid signaling generated within β-cells by the β-isoform of Ca 2+ -independent phospholipase A 2 enzyme (iPLA 2 β) participates in cAMP-stimulated insulin secretion (cSIS). Recent work has identified the role of a G-protein coupled receptor (GPCR) activated signaling by the complement 1q like-3 (C1ql3) secreted protein in inhibiting cSIS. In the IGT state, cSIS is attenuated, and the β-cell function is reduced. Interestingly, while β-cell-specific deletion of iPLA 2 β reduces cAMP-mediated amplification of GSIS, the loss of iPLA 2 β in macrophages (MØ) confers protection against the development of glucose intolerance associated with diet-induced obesity (DIO). In this article, we discuss canonical (glucose and cAMP) and novel noncanonical (iPLA 2 β and C1ql3) pathways and how they may affect β-cell (dys)function in the context of impaired glucose intolerance associated with obesity and T2D. In conclusion, we provide a perspective that in IGT states, targeting noncanonical pathways along with canonical pathways could be a more comprehensive approach for restoring β-cell function in T2D. © 2023 American Physiological Society. Compr Physiol 13:5023-5049, 2023.

Functional characteristics of hub and wave-initiator cells in β cell networks

Islets of Langerhans operate as multicellular networks in which several hundred β cells work in synchrony to produce secretory pulses of insulin, a hormone crucial for controlling metabolic homeostasis. Their collective rhythmic activity is facilitated by gap junctional coupling and affected by their functional heterogeneity, but the details of this robust and coordinated behavior are still not fully understood. Recent advances in multicellular imaging and optogenetic and photopharmacological strategies, as well as in network science, have led to the discovery of specialized β cell subpopulations that were suggested to critically determine the collective dynamics in the islets. In particular hubs, i.e., β cells with many functional connections, are believed to significantly enhance communication capacities of the intercellular network and facilitate an efficient spreading of intercellular Ca2+ waves, whereas wave-initiator cells trigger intercellular signals in their cohorts. Here, we determined Ca2+ signaling characteristics of these two β cell subpopulations and the relationship between them by means of functional multicellular Ca2+ imaging in mouse pancreatic tissue slices in combination with methods of complex network theory. We constructed network layers based on individual Ca2+ waves to identify wave initiators, and functional correlation-based networks to detect hubs. We found that both cell types exhibit a higher-than-average active time under both physiological and supraphysiological glucose concentrations, but also that they differ significantly in many other functional characteristics. Specifically, Ca2+ oscillations in hubs are more regular, and their role appears to be much more stable over time than for initiator cells. Moreover, in contrast to wave initiators, hubs transmit intercellular signals faster than other cells, which implies a stronger intercellular coupling. Our research indicates that hubs and wave-initiator cell subpopulations are both natural features of healthy pancreatic islets, but their functional roles in principle do not overlap and should thus not be considered equal.

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.

The characteristics of postprandial glycemic response patterns to white rice and glucose in healthy adults: Identifying subgroups by clustering analysis

OBJECTIVES

Large interpersonal variability in postprandial glycemic response (PGR) to white rice has been reported, and differences in the PGR patterns during the oral glucose tolerance test (OGTT) have been documented. However, there is scant study on the PGR patterns of white rice. We examined the typical PGR patterns of white rice and glucose and the association between them.

MATERIALS AND METHODS

We analyzed the data of 3-h PGRs to white rice (WR) and glucose (G) of 114 normoglycemic female subjects of similar age, weight status, and same ethnic group. Diverse glycemic parameters, based on the discrete blood glucose values, were calculated over 120 and 180 min. K-means clustering based on glycemic parameters calculated over 180 min was applied to identify subgroups and representative PGR patterns. Principal factor analysis based on the parameters used in the cluster analysis was applied to characterize PGR patterns. Simple correspondence analysis was performed on the clustering categories of WR and G.

RESULTS

More distinct differences were found in glycemic parameters calculated over 180 min compared with that calculated over 120 min, especially in the negative area under the curve and Nadir. We identified four distinct PGR patterns to WR (WR1, WR2, WR3, and WR4) and G (G1, G2, G3, and G4), respectively. There were significant differences among the patterns regard to postprandial hyperglycemia, hypoglycemic, and glycemic variability. The WR1 clusters had significantly lower glycemic index (59 ± 19), while no difference was found among the glycemic index based on the other three clusters. Each given G subgroup presented multiple patterns of PGR to WR, especially in the largest G subgroup (G1), and in subgroup with the greatest glycemic variability (G3).

CONCLUSION

Multiple subgroups could be classified based on the PGR patterns to white rice and glucose even in seemingly homogeneous subjects. Extending the monitoring time to 180 min was conducive to more effective discrimination of PGR patterns. It may not be reliable to extrapolate the patterns of PGR to rice from that to glucose, suggesting a need of combining OGTT and meal tolerance test for individualized glycemic management.

Mitoribosome insufficiency in β cells is associated with type 2 diabetes-like islet failure

Genetic variations in mitoribosomal subunits and mitochondrial transcription factors are related to type 2 diabetes. However, the role of islet mitoribosomes in the development of type 2 diabetes has not been determined. We investigated the effects of the mitoribosomal gene on β-cell function and glucose homeostasis. Mitoribosomal gene expression was analyzed in datasets from the NCBI GEO website (GSE25724, GSE76894, and GSE76895) and the European Nucleotide Archive (ERP017126), which contain the transcriptomes of type 2 diabetic and nondiabetic organ donors. We found deregulation of most mitoribosomal genes in islets from individuals with type 2 diabetes, including partial downregulation of CRIF1. The phenotypes of haploinsufficiency in a single mitoribosomal gene were examined using β-cell-specific Crif1 (Mrpl59) heterozygous-deficient mice. Crif1^beta+/− mice had normal glucose tolerance, but their islets showed a loss of first-phase glucose-stimulated insulin secretion. They also showed increased β-cell mass associated with higher expression of Reg family genes. However, Crif1^beta+/− mice showed earlier islet failure in response to high-fat feeding, which was exacerbated by aging. Haploinsufficiency of a single mitoribosomal gene predisposes rodents to glucose intolerance, which resembles the early stages of type 2 diabetes in humans.

Disruptions in the mitochondrial protein synthesis machinery give rise to metabolic disturbances that lay the foundation for type 2 diabetes. As physiological glucose levels rise, the energy-generating machinery of the mitochondria responds with increased activity, which stimulates insulin secretion. Many proteins responsible for mitochondrial metabolism are produced by ribosomes within this cellular organelle. Researchers led by Hyun Jin Kim and Minho Shong at Chungnam National University, Daejon, South Korea, have determined that mutations affecting a mitochondrial ribosomal protein called CRIF1 can lead to impaired insulin release. Mice with reduced CRIF1 were initially healthy, but as they aged, exhibited signs of impaired pancreatic function similar to those seen in patients with early-stage diabetes. This process was accelerated by consumption of a high-fat diet, and the researchers propose that this mechanism may be directly relevant to human disease.

The highly expressed calcium-insensitive synaptotagmin-11 and synaptotagmin-13 modulate insulin secretion

AIM

SYT11 and SYT13, two calcium-insensitive synaptotagmins, are downregulated in islets from type-2 diabetic donors, but their function in insulin secretion is unknown. To address this, we investigated the physiological role of these two synaptotagmins in insulin secreting cells.

METHODS

Correlations between gene expression levels were performed using previously described RNA-seq data on islets from 188 human donors. SiRNA knockdown was performed in EndoC-βH1 and INS-1 832/13 cells. Insulin secretion was measured with ELISA. Patch clamp was used for single cell electrophysiology. Confocal microscopy was used to determine intra-cellular localization.

RESULTS

Human islet expression of the transcription factor PDX-1 was positively correlated with SYT11 (p = 2.4e^-10 ) and SYT13 (p<2.2 e^-16 ). Syt11 and Syt13 both co-localized with insulin, indicating their localization in insulin granules. Downregulation of Syt11 in INS-1 832/13 cells (siSYT11) resulted in increased basal and glucose-induced insulin secretion. Downregulation of Syt13 (siSYT13) decreased insulin secretion induced by glucose and K⁺ .Interestingly, the cAMP raising agent forskolin was unable to enhance insulin secretion in siSYT13 cells. There was no difference in insulin content, exocytosis, or voltage-gated Ca²⁺ currents in the two models. Double knockdown of Syt11 and Syt13 (DKD) resembled the results in siSYT13 cells.

CONCLUSION

SYT11 and SYT13 have similar localization and transcriptional regulation but they regulate insulin secretion differentially. While downregulation of SYT11 might be a compensatory mechanism in type-2 diabetes, downregulation of SYT13 reduces the insulin secretory response and overrules the compensatory regulation of SYT11 in a way that could aggravate the disease.

From Isles of Königsberg to Islets of Langerhans: Examining the Function of the Endocrine Pancreas Through Network Science

Islets of Langerhans are multicellular microorgans located in the pancreas that play a central role in whole-body energy homeostasis. Through secretion of insulin and other hormones they regulate postprandial storage and interprandial usage of energy-rich nutrients. In these clusters of hormone-secreting endocrine cells, intricate cell-cell communication is essential for proper function. Electrical coupling between the insulin-secreting beta cells through gap junctions composed of connexin36 is particularly important, as it provides the required, most important, basis for coordinated responses of the beta cell population. The increasing evidence that gap-junctional communication and its modulation are vital to well-regulated secretion of insulin has stimulated immense interest in how subpopulations of heterogeneous beta cells are functionally arranged throughout the islets and how they mediate intercellular signals. In the last decade, several novel techniques have been proposed to assess cooperation between cells in islets, including the prosperous combination of multicellular imaging and network science. In the present contribution, we review recent advances related to the application of complex network approaches to uncover the functional connectivity patterns among cells within the islets. We first provide an accessible introduction to the basic principles of network theory, enumerating the measures characterizing the intercellular interactions and quantifying the functional integration and segregation of a multicellular system. Then we describe methodological approaches to construct functional beta cell networks, point out possible pitfalls, and specify the functional implications of beta cell network examinations. We continue by highlighting the recent findings obtained through advanced multicellular imaging techniques supported by network-based analyses, giving special emphasis to the current developments in both mouse and human islets, as well as outlining challenges offered by the multilayer network formalism in exploring the collective activity of islet cell populations. Finally, we emphasize that the combination of these imaging techniques and network-based analyses does not only represent an innovative concept that can be used to describe and interpret the physiology of islets, but also provides fertile ground for delineating normal from pathological function and for quantifying the changes in islet communication networks associated with the development of diabetes mellitus.

Gene losses in the common vampire bat illuminate molecular adaptations to blood feeding

Vampire bats are the only mammals that feed exclusively on blood. To uncover genomic changes associated with this dietary adaptation, we generated a haplotype-resolved genome of the common vampire bat and screened 27 bat species for genes that were specifically lost in the vampire bat lineage. We found previously unknown gene losses that relate to reduced insulin secretion (FFAR1 and SLC30A8), limited glycogen stores (PPP1R3E), and a unique gastric physiology (CTSE). Other gene losses likely reflect the biased nutrient composition (ERN2 and CTRL) and distinct pathogen diversity of blood (RNASE7) and predict the complete lack of cone-based vision in these strictly nocturnal bats (PDE6H and PDE6C). Notably, REP15 loss likely helped vampire bats adapt to high dietary iron levels by enhancing iron excretion, and the loss of CYP39A1 could have contributed to their exceptional cognitive abilities. These findings enhance our understanding of vampire bat biology and the genomic underpinnings of adaptations to blood feeding.

Early Cytokine-Induced Transient NOX2 Activity Is ER Stress-Dependent and Impacts β-Cell Function and Survival

In type 1 diabetes (T1D) development, proinflammatory cytokines (PIC) released by immune cells lead to increased reactive oxygen species (ROS) production in β-cells. Nonetheless, the temporality of the events triggered and the role of different ROS sources remain unclear. Isolated islets from C57BL/6J wild-type (WT), NOX1 KO and NOX2 KO mice were exposed to a PIC combination. We show that cytokines increase O₂^•− production after 2 h in WT and NOX1 KO but not in NOX2 KO islets. Using transgenic mice constitutively expressing a genetically encoded compartment specific H₂O₂ sensor, we show, for the first time, a transient increase of cytosolic/nuclear H₂O₂ in islet cells between 4 and 5 h during cytokine exposure. The H₂O₂ increase coincides with the intracellular NAD(P)H decrease and is absent in NOX2 KO islets. NOX2 KO confers better glucose tolerance and protects against cytokine-induced islet secretory dysfunction and death. However, NOX2 absence does not counteract the cytokine effects in ER Ca²⁺ depletion, Store-Operated Calcium Entry (SOCE) increase and ER stress. Instead, the activation of ER stress precedes H₂O₂ production. As early NOX2-driven ROS production impacts β-cells’ function and survival during insulitis, NOX2 might be a potential target for designing therapies against early β-cell dysfunction in the context of T1D onset.

Glucose-dependent activation, activity, and deactivation of beta cell networks in acute mouse pancreas tissue slices

Many details of glucose-stimulated intracellular calcium changes in β cells during activation, activity, and deactivation, as well as their concentration-dependence, remain to be analyzed. Classical physiological experiments indicated that in islets, functional differences between individual cells are largely attenuated, but recent findings suggest considerable intercellular heterogeneity, with some cells possibly coordinating the collective responses. To address the above with an emphasis on heterogeneity and describing the relations between classical physiological and functional network properties, we performed functional multicellular calcium imaging in mouse pancreas tissue slices over a wide range of glucose concentrations. During activation, delays to activation of cells and any-cell-to-first-responder delays are shortened, and the sizes of simultaneously responding clusters increased with increasing glucose concentrations. Exactly the opposite characterized deactivation. The frequency of fast calcium oscillations during activity increased with increasing glucose up to 12 mM glucose concentration, beyond which oscillation duration became longer, resulting in a homogenous increase in active time. In terms of functional connectivity, islets progressed from a very segregated network to a single large functional unit with increasing glucose concentration. A comparison between classical physiological and network parameters revealed that the first-responders during activation had longer active times during plateau and the most active cells during the plateau tended to deactivate later. Cells with the most functional connections tended to activate sooner, have longer active times, and deactivate later. Our findings provide a common ground for recent differing views on β cell heterogeneity and an important baseline for future studies of stimulus-secretion and intercellular coupling.NEW & NOTEWORTHY We assessed concentration-dependence in coupled β cells, degree of functional heterogeneity, and uncovered possible specialized subpopulations during the different phases of the response to glucose at the level of many individual cells. To this aim, we combined acute mouse pancreas tissue slices with functional multicellular calcium imaging over a wide range from threshold (7 mM) and physiological (8 and 9 mM) to supraphysiological (12 and 16 mM) glucose concentrations, classical physiological, and advanced network analyses.

Assessing Different Temporal Scales of Calcium Dynamics in Networks of Beta Cell Populations

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.

Glucose-induced insulin secretion in isolated human islets: Does it truly reflect β-cell function in vivo?

BACKGROUND

Diabetes always involves variable degrees of β-cell demise and malfunction leading to insufficient insulin secretion. Besides clinical investigations, many research projects used rodent islets to study various facets of β-cell pathophysiology. Their important contributions laid the foundations of steadily increasing numbers of experimental studies resorting to isolated human islets.

SCOPE OF REVIEW

This review, based on an analysis of data published over 60 years of clinical investigations and results of more recent studies in isolated islets, addresses a question of translational nature. Does the information obtained in vitro with human islets fit with our knowledge of insulin secretion in man? The aims are not to discuss specificities of pathways controlling secretion but to compare qualitative and quantitative features of glucose-induced insulin secretion in isolated human islets and in living human subjects.

MAJOR CONCLUSIONS

Much of the information gathered in vitro can reliably be translated to the in vivo situation. There is a fairly good, though not complete, qualitative and quantitative coherence between insulin secretion rates measured in vivo and in vitro during stimulation with physiological glucose concentrations, but the concordance fades out under extreme conditions. Perplexing discrepancies also exist between insulin secretion in subjects with Type 2 diabetes and their islets studied in vitro, in particular concerning the kinetics. Future projects should ascertain that the experimental conditions are close to physiological and do not alter the function of normal and diabetic islets.

The Pancreatic β-Cell: The Perfect Redox System

Pancreatic β-cell insulin secretion, which responds to various secretagogues and hormonal regulations, is reviewed here, emphasizing the fundamental redox signaling by NADPH oxidase 4- (NOX4-) mediated H₂O₂ production for glucose-stimulated insulin secretion (GSIS). There is a logical summation that integrates both metabolic plus redox homeostasis because the ATP-sensitive K⁺ channel (K_ATP) can only be closed when both ATP and H₂O₂ are elevated. Otherwise ATP would block K_ATP, while H₂O₂ would activate any of the redox-sensitive nonspecific calcium channels (NSCCs), such as TRPM2. Notably, a 100%-closed K_ATP ensemble is insufficient to reach the -50 mV threshold plasma membrane depolarization required for the activation of voltage-dependent Ca²⁺ channels. Open synergic NSCCs or Cl^- channels have to act simultaneously to reach this threshold. The resulting intermittent cytosolic Ca²⁺-increases lead to the pulsatile exocytosis of insulin granule vesicles (IGVs). The incretin (e.g., GLP-1) amplification of GSIS stems from receptor signaling leading to activating the phosphorylation of TRPM channels and effects on other channels to intensify integral Ca²⁺-influx (fortified by endoplasmic reticulum Ca²⁺). ATP plus H₂O₂ are also required for branched-chain ketoacids (BCKAs); and partly for fatty acids (FAs) to secrete insulin, while BCKA or FA β-oxidation provide redox signaling from mitochondria, which proceeds by H₂O₂ diffusion or hypothetical SH relay via peroxiredoxin "redox kiss" to target proteins.

Patterns of Insulin Secretion During First-Phase Insulin Secretion in Normal Chinese Adults

BACKGROUND

The increase in diabetes worldwide is alarming. Decreased acute insulin response to intravenous glucose tolerance test (IVGTT) during first-phase insulin secretion (FPIS) is a characteristic of diabetes. However, knowledge of the insulin secretion characteristics identified by different time to glucose peak in subjects with different metabolic state is sparse.

AIMS

This study aimed to find different patterns of FPIS in subjects with normal glucose tolerance (NGT) and analyzed the relationship between insulin secretion patterns and the risk for development of type 2 diabetes mellitus (T2DM).

METHODS

A total of 126 subjects were divided into three groups during a 10-min IVGTT, including NGT with time to glucose peak after 3 min (G1, n = 21), NGT with time to glucose peak at 3 min (G2, n = 95), and prediabetes or diabetes with time to glucose peak at 3 min (G3, n = 10). Glucose, insulin, and C-peptide concentrations at 0, 3, 5, 7, and 10 min during the IVGTT were tested. IVGTT-based indices were calculated to evaluate the insulin secretion and insulin sensitivity.

RESULTS

Age, body mass index (BMI), waist-to-hip ratio, triglyceride (TG), and hemoglobin A1c (HbA1c) of subjects were gradually higher, while high-density lipoprotein cholesterol (HDL-C) was gradually lower from G1 to G3 (p for linear trend <0.05), and the differences between G1 and G2 were also statistically significant (p < 0.05). Glucose peak of most participants in G1 converged at 5 min, and the curves shape of insulin and C-peptide in G2 were the sharpest among three groups. There was no significant difference in all IVGTT-based indices between G1 and G2, but AUC_Ins, AUC_Ins/AUC_Glu, and △Ins₃/△Glu₃ in G2 were the highest, and the p-value for linear trend of those indices among three groups were statistically significant (p < 0.05).

CONCLUSIONS

Two patterns of FPIS were in subjects with NGT, while subjects with later time to glucose peak during FPIS might be less likely to develop T2DM in the future.

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.

A direct look at the dysfunction and pathology of the β cells in human type 2 diabetes

β cells uniquely produce and secrete insulin under the control of several, integrated signals, to maintain blood glucose concentrations within a narrow physiological interval. β cell failure is key to the onset and progression of type 2 diabetes, due to impaired function and reduced mass. In this review we focus on several features of human β cell dysfunction and pathology in type 2 diabetes, as revealed by direct assessment of isolated islet traits and examination of pancreatic tissue from organ donors, surgical samples or autoptic specimens. Insulin secretion defects and pathology findings are discussed in relation to some of the major underlying mechanisms, to also provide clues for conceiving better prevention and treatment of type 2 diabetes by targeting the pancreatic β cells.

Heterogeneity and Delayed Activation as Hallmarks of Self-Organization and Criticality in Excitable Tissue

Self-organized critical dynamics is assumed to be an attractive mode of functioning for several real-life systems and entails an emergent activity in which the extent of observables follows a power-law distribution. The hallmarks of criticality have recently been observed in a plethora of biological systems, including beta cell populations within pancreatic islets of Langerhans. In the present study, we systematically explored the mechanisms that drive the critical and supercritical behavior in networks of coupled beta cells under different circumstances by means of experimental and computational approaches. Experimentally, we employed high-speed functional multicellular calcium imaging of fluorescently labeled acute mouse pancreas tissue slices to record calcium signals in a large number of beta cells simultaneously, and with a high spatiotemporal resolution. Our experimental results revealed that the cellular responses to stimulation with glucose are biphasic and glucose-dependent. Under physiological as well as under supraphysiological levels of stimulation, an initial activation phase was followed by a supercritical plateau phase with a high number of global intercellular calcium waves. However, the activation phase displayed fingerprints of critical behavior under lower stimulation levels, with a progressive recruitment of cells and a power-law distribution of calcium wave sizes. On the other hand, the activation phase provoked by pathophysiologically high glucose concentrations, differed considerably and was more rapid, less continuous, and supercritical. To gain a deeper insight into the experimentally observed complex dynamical patterns, we built up a phenomenological model of coupled excitable cells and explored empirically the model’s necessities that ensured a good overlap between computational and experimental results. It turned out that such a good agreement between experimental and computational findings was attained when both heterogeneous and stimulus-dependent time lags, variability in excitability levels, as well as a heterogeneous cell-cell coupling were included into the model. Most importantly, since our phenomenological approach involved only a few parameters, it naturally lends itself not only for determining key mechanisms of self-organized criticality at the tissue level, but also points out various features for comprehensive and realistic modeling of different excitable systems in nature.