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

Causal interaction of metabolic oscillations in monolayers of Hela cervical cancer cells: emergence of complex networks

A novel global cooperative phenomenon was observed in monolayers of HeLa cervical cancer cells that exhibited glycolytic oscillations but did not exhibit synchronisation or partial synchronisation. The analysis of causality of the oscillations between cell pairs in the cell-monolayer sheet revealed a hidden causal interaction network. Furthermore, the network exhibits characteristics of a broad-scale network. This suggests that key cells perform a hub-like function in the network and that the population of HeLa cells forms metabolically connected functional network rather than randomly connected one. Unlike previous work that focused on the synchronisation of glycolytic oscillations in the HeLa cells, the present study analysed the causality between the oscillating cells by Convergent Cross Mapping (CCM), which is based on the phase-space reconstruction of time-series data and is used to find causality in weakly coupled components of nonlinear dynamical systems. We believe that the framework proposed in this study is useful for investigating the hidden state of a group of cells and can accelerate studies on cellular metabolic phenomena including metabolic oscillations in [Formula: see text] cells within islets of Langerhans. It would also be applicable to systems of weakly coupled oscillators that may include hidden cooperative phenomena.

Resolving Spatiotemporal Electrical Signaling Within the Islet via CMOS Microelectrode Arrays

Glucose-stimulated β-cells exhibit synchronized calcium dynamics across the islet that recruit β-cells to enhance insulin secretion. Compared with calcium dynamics, the formation and cell-to-cell propagation of electrical signals within the islet are poorly characterized. To determine factors that influence the propagation of electrical activity across the islet underlying calcium oscillations and β-cell synchronization, we used high-resolution complementary metal-oxide-semiconductor multielectrode arrays (CMOS-MEA) to measure voltage changes associated with the membrane potential of individual cells within intact C57BL6 mouse islets. We measured fast (milliseconds, spikes) and slow (seconds, waves) voltage dynamics. Single spike activity and wave signal velocity were both glucose-dependent, but only spike activity was influenced by N-methyl-d-aspartate receptor activation or inhibition. A repeated glucose stimulus revealed a highly responsive subset of cells in spike activity. When islets were pretreated for 72 h with glucolipotoxic medium, the wave velocity was significantly reduced. Network analysis confirmed that in response to glucolipotoxicity the synchrony of islet cells was affected due to slower propagating electrical waves and not due to altered spike activity. In summary, this approach provided novel insight regarding the propagation of electrical activity and the disruption of cell-to-cell communication due to excessive stimulation.

ARTICLE HIGHLIGHTS

The high-resolution complementary metal-oxide-semiconductor multielectrode array is suited to track the spatiotemporal propagation of electrical activity through the islet on a cellular scale. A highly responsive subpopulation of islet cells was identified by action potential-like spike activity and proved to be robust to glucolipotoxicity. Electrical waves revealed synchronized electrical activity and their propagation through the islet was slowed down by glucolipotoxicity. The N-methyl-d-aspartate receptor did not influence islet synchronization since modulation of the receptor only affected electrical spikes. The technique is a useful tool for exploring the pancreatic islet network in health and disease.

Glucokinase activity controls peripherally located subpopulations of β-cells that lead islet Ca2+ oscillations

Oscillations in insulin secretion, driven by islet Ca2+ waves, are crucial for glycemic control. Prior studies, performed with single-plane imaging, suggest that subpopulations of electrically coupled β-cells have privileged roles in leading and coordinating the propagation of Ca2+ waves. Here, we used three-dimensional (3D) light-sheet imaging to analyze the location and Ca2+ activity of single β-cells within the entire islet at >2 Hz. In contrast with single-plane studies, 3D network analysis indicates that the most highly synchronized β-cells are located at the islet center, and remain regionally but not cellularly stable between oscillations. This subpopulation, which includes 'hub cells', is insensitive to changes in fuel metabolism induced by glucokinase and pyruvate kinase activation. β-Cells that initiate the Ca2+ wave (leaders) are located at the islet periphery, and strikingly, change their identity over time via rotations in the wave axis. Glucokinase activation, which increased oscillation period, reinforced leader cells and stabilized the wave axis. Pyruvate kinase activation, despite increasing oscillation frequency, had no effect on leader cells, indicating the wave origin is patterned by fuel input. These findings emphasize the stochastic nature of the β-cell subpopulations that control Ca2+ oscillations and identify a role for glucokinase in spatially patterning 'leader' β-cells.

Glucokinase activity controls peripherally-located subpopulations of β-cells that lead islet Ca2+ oscillations

Oscillations in insulin secretion, driven by islet Ca2+ waves, are crucial for glycemic control. Prior studies, performed with single-plane imaging, suggest that subpopulations of electrically coupled β-cells have privileged roles in leading and coordinating the propagation of Ca2+ waves. Here, we used 3D light-sheet imaging to analyze the location and Ca2+ activity of single β-cells within the entire islet at >2 Hz. In contrast with single-plane studies, 3D network analysis indicates that the most highly synchronized β-cells are located at the islet center, and remain regionally but not cellularly stable between oscillations. This subpopulation, which includes 'hub cells', is insensitive to changes in fuel metabolism induced by glucokinase and pyruvate kinase activation. β-cells that initiate the Ca2+ wave ('leaders') are located at the islet periphery, and strikingly, change their identity over time via rotations in the wave axis. Glucokinase activation, which increased oscillation period, reinforced leader cells and stabilized the wave axis. Pyruvate kinase activation, despite increasing oscillation frequency, had no effect on leader cells, indicating the wave origin is patterned by fuel input. These findings emphasize the stochastic nature of the β-cell subpopulations that control Ca2+ oscillations and identify a role for glucokinase in spatially patterning 'leader' β-cells.

Exploring pancreatic beta-cell subgroups and their connectivity

Functional pancreatic islet beta cells are essential to ensure glucose homeostasis across species from zebrafish to humans. These cells show significant heterogeneity, and emerging studies have revealed that connectivity across a hierarchical network is required for normal insulin release. Here, we discuss current thinking and areas of debate around intra-islet connectivity, cellular hierarchies and potential "controlling" beta-cell populations. We focus on methodologies, including comparisons of different cell preparations as well as in vitro and in vivo approaches to imaging and controlling the activity of human and rodent islet preparations. We also discuss the analytical approaches that can be applied to live-cell data to identify and study critical subgroups of cells with a disproportionate role in control Ca2+ dynamics and thus insulin secretion (such as "first responders", "leaders" and "hubs", as defined by Ca2+ responses to glucose stimulation). Possible mechanisms by which this hierarchy is achieved, its physiological relevance and how its loss may contribute to islet failure in diabetes mellitus are also considered. A glossary of terms and links to computational resources are provided.

CRISP: Correlation-Refined Image Segmentation Process

Calcium imaging enables real-time recording of cellular activity across various biological contexts. To assess the activity of individual cells, scientists typically manually outline the cells based on visual inspection. This manual cell masking introduces potential user error. To ameliorate this error, we developed the Correlation-Refined Image Segmentation Process (CRISP), a two-part automated algorithm designed to both enhance the accuracy of user-drawn cell masks and to automatically identify cell masks. We developed and tested CRISP on calcium images of densely packed β-cells within the islet of Langerhans. Because these β-cells are densely packed within the islet, traditional clustering-based image segmentation methods struggle to identify individual cell outlines. Using β-cells isolated from two different mouse phenotypes and imaged on two different confocal microscopes, we show that CRISP is generalizable and accurate. To test the benefit of using CRISP in functional biological analyses, we show that CRISP improves accuracy of functional network analysis and utilize CRISP to characterize the distribution of β-cell size.

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.

Synchronizing beta cells in the pancreas

The secretion of insulin from the pancreas relies on both gap junctions and subpopulations of beta cells with specific intrinsic properties.