Beta-cell hubs maintain Ca2+ oscillations in human and mouse islet simulations

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.

Kinetic modelling of glycolytic oscillations

Glycolytic oscillations have been studied for well over 60 years, but aspects of their function, and mechanisms of regulation and synchronisation remain unclear. Glycolysis is amenable to mechanistic mathematical modelling, as its components have been well characterised, and the system can be studied at many organisational levels: in vitro reconstituted enzymes, cell free extracts, individual cells, and cell populations. In recent years, the emergence of individual cell analysis has opened new ways of studying this intriguing system.

The Importance of Intra-Islet Communication in the Function and Plasticity of the Islets of Langerhans during Health and Diabetes

Islets of Langerhans are anatomically dispersed within the pancreas and exhibit regulatory coordination between islets in response to nutritional and inflammatory stimuli. However, within individual islets, there is also multi-faceted coordination of function between individual beta-cells, and between beta-cells and other endocrine and vascular cell types. This is mediated partly through circulatory feedback of the major secreted hormones, insulin and glucagon, but also by autocrine and paracrine actions within the islet by a range of other secreted products, including somatostatin, urocortin 3, serotonin, glucagon-like peptide-1, acetylcholine, and ghrelin. Their availability can be modulated within the islet by pericyte-mediated regulation of microvascular blood flow. Within the islet, both endocrine progenitor cells and the ability of endocrine cells to trans-differentiate between phenotypes can alter endocrine cell mass to adapt to changed metabolic circumstances, regulated by the within-islet trophic environment. Optimal islet function is precariously balanced due to the high metabolic rate required by beta-cells to synthesize and secrete insulin, and they are susceptible to oxidative and endoplasmic reticular stress in the face of high metabolic demand. Resulting changes in paracrine dynamics within the islets can contribute to the emergence of Types 1, 2 and gestational diabetes.

STIM1 regulates pancreatic β-cell behaviour: A modelling study

Pancreatic β-cells are equipped with the molecular machinery allowing them to respond to high glucose levels in the form of electrical activity and Ca2+ oscillations. These oscillations drive insulin secretion. Two key ionic mechanisms involved in this response are the Store-Operated Current and the current through ATP-dependent K+ channels. Both currents have been shown to be regulated by the protein STIM1, but this dual regulation by STIM1 has not been studied before. In this paper, we use mathematical modelling to gain insight into the role of STIM1 in the β-cell response. We extended a previous β-cell model to include the dynamics of STIM1 and described the dependence of the ATP-dependent K+ current on STIM1. Our simulations suggest that the total concentration of STIM1 modifies the bursting frequency, the burst duration and the intracellular Ca2+ levels. These results are in good agreement with experimental reports, and the contribution of the studied currents to electrical activity and Ca2+ dynamics is discussed. The model predicts that in the absence of STIM1 the excitability of the plasma membrane increases and that the glucose threshold for electrical activity is shifted to lower concentrations. These computational predictions may be related to impaired insulin secretion under conditions of reduced STIM1 in the diabetic state.

β-cell intrinsic dynamics rather than gap junction structure dictates subpopulations in the islet functional network

Diabetes is caused by the inability of electrically coupled, functionally heterogeneous β-cells within the pancreatic islet to provide adequate insulin secretion. Functional networks have been used to represent synchronized oscillatory [Ca2+] dynamics and to study β-cell subpopulations, which play an important role in driving islet function. The mechanism by which highly synchronized β-cell subpopulations drive islet function is unclear. We used experimental and computational techniques to investigate the relationship between functional networks, structural (gap junction) networks, and intrinsic β-cell dynamics in slow and fast oscillating islets. Highly synchronized subpopulations in the functional network were differentiated by intrinsic dynamics, including metabolic activity and KATP channel conductance, more than structural coupling. Consistent with this, intrinsic dynamics were more predictive of high synchronization in the islet functional network as compared to high levels of structural coupling. Finally, dysfunction of gap junctions, which can occur in diabetes, caused decreases in the efficiency and clustering of the functional network. These results indicate that intrinsic dynamics rather than structure drive connections in the functional network and highly synchronized subpopulations, but gap junctions are still essential for overall network efficiency. These findings deepen our interpretation of functional networks and the formation of functional subpopulations in dynamic tissues such as the islet.

Both electrical and metabolic coupling shape the collective multimodal activity and functional connectivity patterns in beta cell collectives: A computational model perspective

Pancreatic beta cells are coupled excitable oscillators that synchronize their activity via different communication pathways. Their oscillatory activity manifests itself on multiple timescales and consists of bursting electrical activity, subsequent oscillations in the intracellular Ca^{2+}, as well as oscillations in metabolism and exocytosis. The coordination of the intricate activity on the multicellular level plays a key role in the regulation of physiological pulsatile insulin secretion and is incompletely understood. In this paper, we investigate theoretically the principles that give rise to the synchronized activity of beta cell populations by building up a phenomenological multicellular model that incorporates the basic features of beta cell dynamics. Specifically, the model is composed of coupled slow and fast oscillatory units that reflect metabolic processes and electrical activity, respectively. Using a realistic description of the intercellular interactions, we study how the combination of electrical and metabolic coupling generates collective rhythmicity and shapes functional beta cell networks. It turns out that while electrical coupling solely can synchronize the responses, the addition of metabolic interactions further enhances coordination, the spatial range of interactions increases the number of connections in the functional beta cell networks, and ensures a better consistency with experimental findings. Moreover, our computational results provide additional insights into the relationship between beta cell heterogeneity, their activity profiles, and functional connectivity, supplementing thereby recent experimental results on endocrine networks.

The simplified Kirchhoff network model (SKNM): a cell-based reaction-diffusion model of excitable tissue

Cell-based models of excitable tissues offer the advantage of cell-level precision, which cannot be achieved using traditional homogenized electrophysiological models. However, this enhanced accuracy comes at the cost of increased computational demands, necessitating the development of efficient cell-based models. The widely-accepted bidomain model serves as the standard in computational cardiac electrophysiology, and under certain anisotropy ratio conditions, it is well known that it can be reduced to the simpler monodomain model. Recently, the Kirchhoff Network Model (KNM) was developed as a cell-based counterpart to the bidomain model. In this paper, we aim to demonstrate that KNM can be simplified using the same steps employed to derive the monodomain model from the bidomain model. We present the cell-based Simplified Kirchhoff Network Model (SKNM), which produces results closely aligned with those of KNM while requiring significantly less computational resources.

Determinants of collective failure in excitable networks

We study collective failures in biologically realistic networks that consist of coupled excitable units. The networks have broad-scale degree distribution, high modularity, and small-world properties, while the excitable dynamics is determined by the paradigmatic FitzHugh-Nagumo model. We consider different coupling strengths, bifurcation distances, and various aging scenarios as potential culprits of collective failure. We find that for intermediate coupling strengths, the network remains globally active the longest if the high-degree nodes are first targets for inactivation. This agrees well with previously published results, which showed that oscillatory networks can be highly fragile to the targeted inactivation of low-degree nodes, especially under weak coupling. However, we also show that the most efficient strategy to enact collective failure does not only non-monotonically depend on the coupling strength, but it also depends on the distance from the bifurcation point to the oscillatory behavior of individual excitable units. Altogether, we provide a comprehensive account of determinants of collective failure in excitable networks, and we hope this will prove useful for better understanding breakdowns in systems that are subject to such dynamics.

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.

Bioengineered Pancreas-Liver Crosstalk in a Microfluidic Coculture Chip Identifies Human Metabolic Response Signatures in Prediabetic Hyperglycemia

Aberrant glucose homeostasis is the most common metabolic disturbance affecting one in ten adults worldwide. Prediabetic hyperglycemia due to dysfunctional interactions between different human tissues, including pancreas and liver, constitutes the largest risk factor for the development of type 2 diabetes. However, this early stage of metabolic disease has received relatively little attention. Microphysiological tissue models that emulate tissue crosstalk offer emerging opportunities to study metabolic interactions. Here, a novel modular multitissue organ-on-a-chip device is presented that allows for integrated and reciprocal communication between different 3D primary human tissue cultures. Precisely controlled heterologous perfusion of each tissue chamber is achieved through a microfluidic single "synthetic heart" pneumatic actuation unit connected to multiple tissue chambers via specific configuration of microchannel resistances. On-chip coculture experiments of organotypic primary human liver spheroids and intact primary human islets demonstrate insulin secretion and hepatic insulin response dynamics at physiological timescales upon glucose challenge. Integration of transcriptomic analyses with promoter motif activity data of 503 transcription factors reveals tissue-specific interacting molecular networks that underlie β-cell stress in prediabetic hyperglycemia. Interestingly, liver and islet cultures show surprising counter-regulation of transcriptional programs, emphasizing the power of microphysiological coculture to elucidate the systems biology of metabolic crosstalk.

Cell Networks in Endocrine/Neuroendocrine Gland Function

Reproduction, growth, stress, and metabolism are determined by endocrine/neuroendocrine systems that regulate circulating hormone concentrations. All these systems generate rhythms and changes in hormone pulsatility observed in a variety of pathophysiological states. Thus, the output of endocrine/neuroendocrine systems must be regulated within a narrow window of effective hormone concentrations but must also maintain a capacity for plasticity to respond to changing physiological demands. Remarkably most endocrinologists still have a "textbook" view of endocrine gland organization which has emanated from 20^th century histological studies on thin 2D tissue sections. However, 21^st -century technological advances, including in-depth 3D imaging of specific cell types have vastly changed our knowledge. We now know that various levels of multicellular organization can be found across different glands, that organizational motifs can vary between species and can be modified to enhance or decrease hormonal release. This article focuses on how the organization of cells regulates hormone output using three endocrine/neuroendocrine glands that present different levels of organization and complexity: the adrenal medulla, with a single neuroendocrine cell type; the anterior pituitary, with multiple intermingled cell types; and the pancreas with multiple intermingled cell types organized into distinct functional units. We give an overview of recent methodologies that allow the study of the different components within endocrine systems, particularly their temporal and spatial relationships. We believe the emerging findings about network organization, and its impact on hormone secretion, are crucial to understanding how homeostatic regulation of endocrine axes is carried out within endocrine organs themselves. © 2022 American Physiological Society. Compr Physiol 12:3371-3415, 2022.

Gap junction coupling and islet delta-cell function in health and disease

The pancreatic islets contain beta-cells and alpha-cells, which are responsible for secreting two principal gluco-regulatory hormones; insulin and glucagon, respectively. However, they also contain delta-cells, a relatively sparse cell type that secretes somatostatin (SST). These cells have a complex morphology allowing them to establish an extensive communication network throughout the islet, despite their scarcity. Delta-cells are electrically excitable cells, and SST secretion is released in a glucose- and K_ATP-dependent manner. SST hyperpolarises the alpha-cell membrane and suppresses exocytosis. In this way, islet SST potently inhibits glucagon release. Recent studies investigating the activity of delta-cells have revealed they are electrically coupled to beta-cells via gap junctions, suggesting the delta-cell is more than just a paracrine inhibitor. In this Review, we summarize delta-cell morphology, function, and the role of SST signalling for regulating islet hormonal output. A distinguishing feature of this Review is that we attempt to use the discovery of this gap junction pathway, together with what is already known about delta-cells, to reframe the role of these cells in both health and disease. In particular, we argue that the discovery of gap junction communication between delta-cells and beta-cells provides new insights into the contribution of delta-cells to the islet hormonal defects observed in both type 1 and type 2 diabetes. This reappraisal of the delta-cell is important as it may offer novel insights into how the physiology of this cell can be utilised to restore islet function in diabetes.

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.

IsletLab: an application to reconstruct and analyze islet architectures

The continuous interaction between experimental and theoretical work has proven to be extremely useful for the study of pancreatic cells and, recently, of pancreatic islets. This prolific interaction relies on the capability of implementing computational models and methods to derive quantitative data for the analysis and interpretation of experimental observations. In this addendum I introduce Isletlab, a multiplatform application developed to provide the research community with a user-friendly interface for the implementation of computational algorithms for the characterization and simulation of pancreatic islets.

The physiological role of β-cell heterogeneity in pancreatic islet function

Endocrine cells within the pancreatic islets of Langerhans are heterogeneous in terms of transcriptional profile, protein expression and the regulation of hormone release. Even though this heterogeneity has long been appreciated, only within the past 5 years have detailed molecular analyses led to an improved understanding of its basis. Although we are beginning to recognize why some subpopulations of endocrine cells are phenotypically different to others, arguably the most important consideration is how this heterogeneity affects the regulation of hormone release to control the homeostasis of glucose and other energy-rich nutrients. The focus of this Review is the description of how endocrine cell heterogeneity (and principally that of insulin-secreting β-cells) affects the regulation of hormone secretion within the islets of Langerhans. This discussion includes an overview of the functional characteristics of the different islet cell subpopulations and describes how they can communicate to influence islet function under basal and glucose-stimulated conditions. We further discuss how changes to the specific islet cell subpopulations or their numbers might underlie islet dysfunction in type 2 diabetes mellitus. We conclude with a discussion of several key open questions regarding the physiological role of islet cell heterogeneity.

Microtubules regulate pancreatic β-cell heterogeneity via spatiotemporal control of insulin secretion hot spots

Heterogeneity of glucose-stimulated insulin secretion (GSIS) in pancreatic islets is physiologically important but poorly understood. Here, we utilize mouse islets to determine how microtubules (MTs) affect secretion toward the vascular extracellular matrix at single cell and subcellular levels. Our data indicate that MT stability in the β-cell population is heterogenous, and that GSIS is suppressed in cells with highly stable MTs. Consistently, MT hyper-stabilization prevents, and MT depolymerization promotes the capacity of single β-cell for GSIS. Analysis of spatiotemporal patterns of secretion events shows that MT depolymerization activates otherwise dormant β-cells via initiation of secretion clusters (hot spots). MT depolymerization also enhances secretion from individual cells, introducing both additional clusters and scattered events. Interestingly, without MTs, the timing of clustered secretion is dysregulated, extending the first phase of GSIS and causing oversecretion. In contrast, glucose-induced Ca²⁺ influx was not affected by MT depolymerization yet required for secretion under these conditions, indicating that MT-dependent regulation of secretion hot spots acts in parallel with Ca²⁺ signaling. Our findings uncover a novel MT function in tuning insulin secretion hot spots, which leads to accurately measured and timed response to glucose stimuli and promotes functional β-cell heterogeneity.

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.

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.

Machine Learning Algorithms, Applied to Intact Islets of Langerhans, Demonstrate Significantly Enhanced Insulin Staining at the Capillary Interface of Human Pancreatic β Cells

Pancreatic β cells secrete the hormone insulin into the bloodstream and are critical in the control of blood glucose concentrations. β cells are clustered in the micro-organs of the islets of Langerhans, which have a rich capillary network. Recent work has highlighted the intimate spatial connections between β cells and these capillaries, which lead to the targeting of insulin secretion to the region where the β cells contact the capillary basement membrane. In addition, β cells orientate with respect to the capillary contact point and many proteins are differentially distributed at the capillary interface compared with the rest of the cell. Here, we set out to develop an automated image analysis approach to identify individual β cells within intact islets and to determine if the distribution of insulin across the cells was polarised. Our results show that a U-Net machine learning algorithm correctly identified β cells and their orientation with respect to the capillaries. Using this information, we then quantified insulin distribution across the β cells to show enrichment at the capillary interface. We conclude that machine learning is a useful analytical tool to interrogate large image datasets and analyse sub-cellular organisation.

Hubs, diversity, and synchronization in FitzHugh-Nagumo oscillator networks: Resonance effects and biophysical implications

Using the FitzHugh-Nagumo equations to represent the oscillatory electrical behavior of β-cells, we develop a coupled oscillator network model with cubic lattice topology, showing that the emergence of pacemakers or hubs in the system can be viewed as a natural consequence of oscillator population diversity. The optimal hub to nonhub ratio is determined by the position of the diversity-induced resonance maximum for a given set of FitzHugh-Nagumo equation parameters and is predicted by the model to be in a range that is fully consistent with experimental observations. The model also suggests that hubs in a β-cell network should have the ability to "switch on" and "off" their pacemaker function. As a consequence, their relative amount in the population can vary in order to ensure an optimal oscillatory performance of the network in response to environmental changes, such as variations of an external stimulus.

Small subpopulations of β-cells do not drive islet oscillatory [Ca2+] dynamics via gap junction communication

The islets of Langerhans exist as multicellular networks that regulate blood glucose levels. The majority of cells in the islet are excitable, insulin-producing β-cells that are electrically coupled via gap junction channels. β-cells are known to display heterogeneous functionality. However, due to gap junction coupling, β-cells show coordinated [Ca²⁺] oscillations when stimulated with glucose, and global quiescence when unstimulated. Small subpopulations of highly functional β-cells have been suggested to control [Ca²⁺] dynamics across the islet. When these populations were targeted by optogenetic silencing or photoablation, [Ca²⁺] dynamics across the islet were largely disrupted. In this study, we investigated the theoretical basis of these experiments and how small populations can disproportionality control islet [Ca²⁺] dynamics. Using a multicellular islet model, we generated normal, skewed or bimodal distributions of β-cell heterogeneity. We examined how islet [Ca²⁺] dynamics were disrupted when cells were targeted via hyperpolarization or populations were removed; to mimic optogenetic silencing or photoablation, respectively. Targeted cell populations were chosen based on characteristics linked to functional subpopulation, including metabolic rate of glucose oxidation or [Ca²⁺] oscillation frequency. Islets were susceptible to marked suppression of [Ca²⁺] when ~10% of cells with high metabolic activity were hyperpolarized; where hyperpolarizing cells with normal metabolic activity had little effect. However, when highly metabolic cells were removed from the model, [Ca²⁺] oscillations remained. Similarly, when ~10% of cells with either the highest frequency or earliest elevations in [Ca²⁺] were removed from the islet, the [Ca²⁺] oscillation frequency remained largely unchanged. Overall, these results indicate small populations of β-cells with either increased metabolic activity or increased frequency are unable to disproportionately control islet-wide [Ca²⁺] via gap junction coupling. Therefore, we need to reconsider the physiological basis for such small β-cell populations or the mechanism by which they may be acting to control normal islet function.

Many biological systems can be studied using network theory. How heterogeneous cell subpopulations come together to create complex multicellular behavior is of great value in understanding function and dysfunction in tissues. The pancreatic islet of Langerhans is a highly coupled structure that is important for maintaining blood glucose homeostasis. β-cell electrical activity is coordinated via gap junction communication. The function of the insulin-producing β-cell within the islet is disrupted in diabetes. As such, to understand the causes of islet dysfunction we need to understand how different cells within the islet contribute to its overall function via gap junction coupling. Using a computational model of β-cell electrophysiology, we investigated how small highly functional β-cell populations within the islet contribute to its function. We found that when small populations with greater functionality were introduced into the islet, they displayed signatures of this enhanced functionality. However, when these cells were removed, the islet, retained near-normal function. Thus, in a highly coupled system, such as an islet, the heterogeneity of cells allows small subpopulations to be dispensable, and thus their absence is unable to disrupt the larger cellular network. These findings can be applied to other electrical systems that have heterogeneous cell populations.

Flipping the switch on the hub cell: Islet desynchronization through cell silencing

Pancreatic β cells, responsible for secreting insulin into the bloodstream and maintaining glucose homeostasis, are organized in the islets of Langerhans as clusters of electrically coupled cells. Gap junctions, connecting neighboring cells, coordinate the behavior of the islet, leading to the synchronized oscillations in the intracellular calcium and insulin secretion in healthy islets. Recent experimental work has shown that silencing special hub cells can lead to a disruption in the coordinated behavior, calling into question the democratic paradigm of islet insulin secretion with more or less equal input from each β cell. Islets were shown to have scale-free functional connectivity and a hub cell whose silencing would lead to a loss of functional connectivity and activity in the islet. A mechanistic model representing the electrical and calcium dynamics of β cells during insulin secretion was applied to a network of cells connected by gap junctions to test the hypothesis of hub cells. Functional connectivity networks were built from the simulated calcium traces, with some networks classified as scale-free, confirming experimental results. Potential hub cells were identified using previously defined centrality measures, but silencing them was unable to desynchronize the islet. Instead, switch cells, which were able to turn off the activity of the islet but were not highly functionally connected, were found via systematically silencing each cell in the network.

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.

PDX1LOW MAFALOW β-cells contribute to islet function and insulin release

Transcriptionally mature and immature β-cells co-exist within the adult islet. How such diversity contributes to insulin release remains poorly understood. Here we show that subtle differences in β-cell maturity, defined using PDX1 and MAFA expression, contribute to islet operation. Functional mapping of rodent and human islets containing proportionally more PDX1^HIGH and MAFA^HIGH β-cells reveals defects in metabolism, ionic fluxes and insulin secretion. At the transcriptomic level, the presence of increased numbers of PDX1^HIGH and MAFA^HIGH β-cells leads to dysregulation of gene pathways involved in metabolic processes. Using a chemogenetic disruption strategy, differences in PDX1 and MAFA expression are shown to depend on islet Ca²⁺ signaling patterns. During metabolic stress, islet function can be restored by redressing the balance between PDX1 and MAFA levels across the β-cell population. Thus, preserving heterogeneity in PDX1 and MAFA expression, and more widely in β-cell maturity, might be important for the maintenance of islet function.

Isolation and Assessment of Pancreatic Islets Versus Dispersed Beta Cells: A Straightforward Approach to Examine Cell-Cell Communication

Islets of Langerhans, found in the pancreas, are microorgans essential for glucose homeostasis within the body. Many cells are found with an islet, such as beta cells (~70%), alpha cells (~20%), delta cells (~5%), F cells (~4%), and epsilon cells (1%), each with its own unique function. To better understand the roles of these cells and how cell communication alters their function, several techniques have been established such as islet isolation and beta cell dispersion. Here we describe how to isolate primary rodent islets, disperse pancreatic islets, measure intracellular calcium, and use immunofluorescent staining to distinguish beta cells and alpha cells.

Mata A, Godínez-Fernández JR. Reconstructing human pancreatic islet architectures using computational optimization

We outline a general methodology based on computational optimization and experimental data to reconstruct human pancreatic islet architectures. By using the nuclei coordinates of islet cells obtained through DAPI staining, cell types identified by immunostaining, and cell size distributions estimated from capacitance measurements, reconstructed islets composed of non-overlapping spherical cells were obtained through an iterative optimization procedure. In all cases, the reconstructed architectures included >99% of the experimental identified cells, each of them having a radius within the experimentally reported ranges. Given the wide use of mathematical modeling for the study of pancreatic cells, and recently, of cell-cell interactions within the pancreatic islets, the methodology here proposed, also capable of identifying cell-to-cell contacts, is aimed to provide with a framework for modeling and analyzing experimentally-based pancreatic islet architectures.

Integrated Pancreatic Blood Flow: Bidirectional Microcirculation Between Endocrine and Exocrine Pancreas

The pancreatic islet is a highly vascularized endocrine micro-organ. The unique architecture of rodent islets, a so-called core-mantle arrangement seen in two-dimensional images, led researchers to seek functional implications for islet hormone secretion. Three models of islet blood flow were previously proposed, all based on the assumption that islet microcirculation occurs in an enclosed structure. Recent electrophysiological and molecular biological studies using isolated islets also presumed unidirectional flow. Using intravital analysis of the islet microcirculation in mice, we found that islet capillaries were continuously integrated to those in the exocrine pancreas, which made the islet circulation rather open, not self-contained. Similarly in human islets, the capillary structure was integrated with pancreatic microvasculature in its entirety. Thus, islet microcirculation has no relation to islet cytoarchitecture, which explains its well-known variability throughout species. Furthermore, tracking fluorescent-labeled red blood cells at the endocrine-exocrine interface revealed bidirectional blood flow, with similar variability in blood flow speed in both the intra- and extra-islet vasculature. To date, the endocrine and exocrine pancreas have been studied separately by different fields of investigators. We propose that the open circulation model physically links both endocrine and exocrine parts of the pancreas as a single organ through the integrated vascular network.

Heterogeneity of human pancreatic β-cells

Background

Human pancreatic β-cells are heterogeneous. This has been known for a long time and is based on various functional and morphological readouts. β-Cell heterogeneity could reflect fixed subpopulations with distinct functions. However, recent pseudotime analysis of large-scale RNA sequencing data suggest that human β-cell subpopulations may rather reflect dynamic interchangeable states characterized by low expression of genes involved in the unfolded protein response (UPR) and low insulin gene expression, low UPR and high insulin expression or high UPR and low insulin expression.

Scope of review

This review discusses findings obtained by single-cell RNA sequencing combined with pseudotime analysis that human β-cell heterogeneity represents dynamic interchangeable functional states. The physiological significance and potential implications of β-cell heterogeneity in the development and progression of diabetes is highlighted.

Major conclusions

The existence of dynamic functional states allow β-cells to transition between periods of high insulin production and UPR-mediated stress recovery. The recovery state is important since proinsulin is a misfolding-prone protein, making its biosynthesis in the endoplasmic reticulum a stressful event. The transition of β-cells between dynamic states is likely controlled at multiple levels and influenced by the microenvironment within the pancreatic islets. Disturbances in the ability of the β-cells to transition between periods of high insulin biosynthesis and UPR-mediated stress recovery may contribute to diabetes development. Diabetes medications that restore the ability of the β-cells to transition between the functional states should be considered.

Calcium Signaling in ß-cell Physiology and Pathology: A Revisit

Pancreatic beta (β) cell dysfunction results in compromised insulin release and, thus, failed regulation of blood glucose levels. This forms the backbone of the development of diabetes mellitus (DM), a disease that affects a significant portion of the global adult population. Physiological calcium (Ca²⁺) signaling has been found to be vital for the proper insulin-releasing function of β-cells. Calcium dysregulation events can have a dramatic effect on the proper functioning of the pancreatic β-cells. The current review discusses the role of calcium signaling in health and disease in pancreatic β-cells and provides an in-depth look into the potential role of alterations in β-cell Ca²⁺ homeostasis and signaling in the development of diabetes and highlights recent work that introduced the current theories on the connection between calcium and the onset of diabetes.

β-Cell Maturation and Identity in Health and Disease

The exponential increase of patients with diabetes mellitus urges for novel therapeutic strategies to reduce the socioeconomic burden of this disease. The loss or dysfunction of insulin-producing β-cells, in patients with type 1 and type 2 diabetes respectively, put these cells at the center of the disease initiation and progression. Therefore, major efforts have been taken to restore the β-cell mass by cell-replacement or regeneration approaches. Implementing novel therapies requires deciphering the developmental mechanisms that generate β-cells and determine the acquisition of their physiological phenotype. In this review, we summarize the current understanding of the mechanisms that coordinate the postnatal maturation of β-cells and define their functional identity. Furthermore, we discuss different routes by which β-cells lose their features and functionality in type 1 and 2 diabetic conditions. We then focus on potential mechanisms to restore the functionality of those β-cell populations that have lost their functional phenotype. Finally, we discuss the recent progress and remaining challenges facing the generation of functional mature β-cells from stem cells for cell-replacement therapy for diabetes treatment.

Random Matrix Analysis of Ca2+ Signals in β-Cell Collectives

Even within small organs like pancreatic islets, different endocrine cell types and subtypes form a heterogeneous collective to sense the chemical composition of the extracellular solution and compute an adequate hormonal output. Erroneous cellular processing and hormonal output due to challenged heterogeneity result in various disorders with diabetes mellitus as a flagship metabolic disease. Here we attempt to address the aforementioned functional heterogeneity with comparing pairwise cell-cell cross-correlations obtained from simultaneous measurements of cytosolic calcium responses in hundreds of islet cells in an optical plane to statistical properties of correlations predicted by the random matrix theory (RMT). We find that the bulk of the empirical eigenvalue spectrum is almost completely described by RMT prediction, however, the deviating eigenvalues that exist below and above RMT spectral edges suggest that there are local and extended modes driving the correlations. We also show that empirical nearest neighbor spacing of eigenvalues follows universal RMT properties regardless of glucose stimulation, but that number variance displays clear separation from RMT prediction and can differentiate between empirical spectra obtained under non-stimulated and stimulated conditions. We suggest that RMT approach provides a sensitive tool to assess the functional cell heterogeneity and its effects on the spatio-temporal dynamics of a collective of beta cells in pancreatic islets in physiological resting and stimulatory conditions, beyond the current limitations of molecular and cellular biology.

Intact pancreatic islets and dispersed beta-cells both generate intracellular calcium oscillations but differ in their responsiveness to glucose

Pancreatic islets produce pulses of insulin and other hormones that maintain normal glucose homeostasis. These micro-organs possess exquisite glucose-sensing capabilities, allowing for precise changes in pulsatile insulin secretion in response to small changes in glucose. When communication among these cells is disrupted, precision glucose sensing falters. We measured intracellular calcium patterns in 6-mM-steps between 0 and 16 mM glucose, and also more finely in 2-mM-steps from 8 to 12 mM glucose, to compare glucose sensing systematically among intact islets and dispersed islet cells derived from the same mouse pancreas in vitro. The calcium activity of intact islets was uniformly low (quiescent) below 4 mM glucose and active above 8 mM glucose, whereas dispersed beta-cells displayed a broader activation range (2-to-10 mM). Intact islets exhibited calcium oscillations with 2-to-5-min periods, yet beta-cells exhibited longer 7-10 min periods. In every case, intact islets showed changes in activity with each 6-mM-glucose step, whereas dispersed islet cells displayed a continuum of calcium responses ranging from islet-like patterns to stable oscillations unaffected by changes in glucose concentration. These differences were also observed for 2-mM-glucose steps. Despite the diversity of dispersed beta-cell responses to glucose, the sum of all activity produced a glucose dose-response curve that was surprisingly similar to the curve for intact islets, arguing against the importance of "hub cells" for function. Beta-cells thus retain many of the features of islets, but some are more islet-like than others. Determining the molecular underpinnings of these variations could be valuable for future studies of stem-cell-derived beta-cell therapies.

Informing β-cell regeneration strategies using studies of heterogeneity

BACKGROUND

Current therapeutic strategies for type 1 (T1DM) and type 2 diabetes mellitus (T2DM) rely on increasing or substituting endogenous insulin secretion in combination with lifestyle changes. β-cell regeneration, a process whereby new β-cells arise from progenitors, self-renewal or transdifferentiation, has the potential to become a viable route to insulin self-sufficiency. Current regeneration strategies capture many of the transcriptomic and protein features of native β-cells, generating cells capable of glucose-dependent insulin secretion in vitro and alleviation of hyperglycemia in vivo. However, whether novel β-cells display appreciable heterogeneity remains poorly understood, with potential consequences for long-term functional robustness.

SCOPE OF REVIEW

The review brings together crucial discoveries in the β-cell regeneration field with state-of-the-art knowledge regarding β-cell heterogeneity. Aspects that might aid production of longer-lasting and more plastic regenerated β-cells are highlighted and discussed.

MAJOR CONCLUSIONS

Different β-cell regeneration approaches result in a similar outcome: glucose-sensitive, insulin-positive cells that mimic the native β-cell phenotype but which lack normal plasticity. The β-cell subpopulations identified to date expand our understanding of β-cell survival, proliferation and function, signposting the direction for future regeneration strategies. Therefore, regenerated β-cells should exhibit stimulus-dependent differences in gene and protein expression, as well as establish a functional network with different β-cells, all while coexisting with other cell types on a three-dimensional platform.

Biophysical modeling of β-cells networks: Realistic architectures and heterogeneity effects

The β-cells dynamics is the regulator of insulin secretion in the pancreas, and its investigation is a central aspect in designing effective treatment strategies for diabetes. Despite great efforts, much is still unknown about the complex organization of such endocrine cells and realistic mathematical modeling represents a useful tool to elucidate key aspects of glucose control in humans. In this contribution, we study the human β-cells collective behaviour, by modeling their electric and metabolic coupling in a cluster, of size and architecture similar to human islets of Langerhans. We focus on the effect of coupling on various dynamics regimes observed in the islets, that are spiking and bursting on multiple timescales. In particular, we test the effect of hubs, that are highly glucose-sensitive β-cells, on the overall network dynamics, observing different modulation depending on the timescale of the dynamics. By properly taking into account the role of cells heterogeneity, recently emerged, our model effectively describes the effect of hubs on the synchronization of the islet response and the correlation of β-cells activity.