Many tissues are gap-junction-coupled syncytia that support cell-to-cell communication via propagating calcium waves. This also holds true for pancreatic islets of Langerhans, where several thousand beta cells work in synchrony to ensure proper insulin secretion. Two emerging functional parameters of islet function are the location of wave initiator re- gions and the velocity of spreading calcium waves. High-frequency confocal laser-scanning imaging in tissue slices is one of the best available methods to determine these mark- ers, but it is limited to two-dimensional cross-sections of an otherwise three-dimensional islet. Here we show how mathematical modeling can significantly improve this limita- tion. Firstly, we analytically determine the shape of velocity profiles of spherical excitation waves in the focal plane of a homogeneous three-dimensional space. Secondly, we intro- duce a mathematical model consisting of coupled excitable cells that considers cellular heterogeneities to approach more realistic conditions by means of numerical simulations. We demonstrate the effectiveness of our approach on experimentally recorded waves from an islet that was stimulated with 9 mM glucose. Furthermore, we show that calcium waves were primarily triggered by a specific region located 30 µm bellow the focal plane at the periphery of the islet. Additionally, we show that the velocity of the calcium wave was around 80 µm/s. We discuss the importance of our approach for the correct determination of the origin and velocity of calcium waves from experimental data, as well as the pitfalls that are due to improper procedural simplifications.
COBISS.SI-ID: 26793987
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 Ca2C imaging in fresh mouse pancreas tissue slices with time series analysis and network science approaches to unveil the lucose 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 clu stered 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.
COBISS.SI-ID: 56986115
Residing in the islets of Langerhans in the pancreas, [beta]-cells contribute to glucose homeostasis by managing the body's insulin supply. Although it has been acknowledged that healthy [beta]-cells engage in heavy cell-to-cell communication to perform their homeostatic function, the exact role and effects of such communication remain partly understood. We offer a novel perspective on the subject in the form of (i) a dynamical network model that faithfully mimics fast calcium oscillations in response to above-threshold glucose stimulation and (ii) empirical data analysis that reveals a qualitative shift in the cross-correlation structure of measured signals below and above the threshold glucose concentration. Combined together, these results point to a glucose-induced transition in [beta]-cell activity thanks to increasing coordination through gap-junctional signaling and paracrine interactions. Our data and the model further suggest how the conservation of entire cell-cell conductance, observed in coupled but not uncoupled [beta]-cells, emerges as a collective phenomenon. An overall implication is that improving the ability to monitor [beta]-cell signaling should offer means to better understand the pathogenesis of diabetes mellitus.
COBISS.SI-ID: 512974648
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...
COBISS.SI-ID: 512903480
A coordinated functioning of beta cells within pancreatic islets is mediated by oscillatory membrane depolarization and subsequent changes in cytoplasmic calcium concentration. While gap junctions allow for intraislet information exchange, beta cells within islets form complex syncytia that are intrinsically nonlinear and highly heterogeneous. To study spatiotemporal calcium dynamics within these syncytia, we make use of computational modeling and confocal high-speed functional multicellular imaging. We show that model predictions are in good agreement with experimental data, especially if a high degree of heterogeneity in the intercellular coupling term is assumed. In particular, during the first few minutes after stimulation, the probability distribution of calcium wave sizes is characterized by a power law, thus indicating critical behavior. After this period, the dynamics changes qualitatively such that the number of global intercellular calcium events increases to the point where the behavior becomes supercritical. To better mimic normal in vivo conditions, we compare the described behavior during supraphysiological non-oscillatory stimulation with the behavior during exposure to a slightly lower and oscillatory glucose challenge. In the case of this protocol, we observe only critical behavior in both experiment and model. Our results indicate that the loss of oscillatory changes, along with the rise in plasma glucose observed in diabetes, could be associated with a...
COBISS.SI-ID: 512760376