Emergent Dynamics of Electrically Coupled Beta-cells: Implications for Physiopathology of the Endocrine Pancreas

More than 40 years of research studies on the endocrine beta-cells have enlightened most of the fundamental mechanisms involved in insulin secretion in rodents, with a vast published literature that confirms our knowledge of the electrophysiology of these cells, based on both experiments and mathematical models. Although, much more remains to be understood, with particular regards to the loss of beta-cell functionality in pathologies such as diabetes. Among the mechanisms involved in the normal regulation of insulin secretion in mouse islets, gap junction electrical coupling was shown to be an essential aspect in beta-cell endocrine function. Intercellular communications induced by such coupling represent in fact an efficient way through which cells can synchronise their intrinsically heterogeneous activity, homogenising pancreatic islets response to glucose stimuli, improving glucose responsiveness, and giving rise to a global pulsatile insulin release, which is more effective than a constant insulin supply. Therefore in this scenario, the pancreatic islet is a complex structure where beta-cells explicate their function through communication. It is also proven that the loss of direct electrical coupling in rodents leads to an altered beta-cells function, characterised by impaired glucose tolerance and insulin secretion. Interestingly, in this case, the resulting pattern of hormone release resembles those observed in diabetic patients, thus suggesting that the beneficial effect of electrical coupling may be compromised or lost in diabetic islets. In confirmation of that, recently published studies show altered expressions of the protein forming junctional channels in in-vitro environments resembling diabetic inflammatory condition, and an increase resistance to cytotoxic compounds in the case of electrically coupled beta-cells. Moreover such metabolic disorders can have dramatic effects on the islet architecture itself and alter intercellular communication by topological modification of the islet, which are very likely to occur especially in autoimmune forms of diabetes, where beta-cells are progressively killed by an intra-islet infiltrate of immune cells. Such evidence requires investigating deeply gap junction properties between beta-cells, extending the knowledge accumulated on rodents to the less studied human case. Concerning this, published literature have shown interesting aspects regarding the human islet. In fact, in common with rodents, also in humans are expressed proteins forming gap junctional channels, and moreover, functional tight junctions have been observed by histological studies. Furthermore, an even more intriguing fact is that human islet architecture is completely different compared to the mouse islet. Therefore, it is reasonable to think that gap junction channels not only have a role in homogenising and synchronising the response of human beta-cells, but it can also be hypothesised that such a different topology of the islet have a considerable effect on cells emergent activity and could imply significant functional differences respect to the rodent case. Unfortunately, the human beta-cell electrophysiology has been analysed only recently, and electrical coupling between human beta-cells remains a largely unexplored topic. Therefore, in this dissertation a mathematical modelling approach is adopted to investigate gap junction coupling effect on the emergent dynamics of beta-cell populations, trying to analyse the collective behaviour of coupled cell clusters in-silico. Different electrophysiological models are used in this framework to reproduce the dynamics of both mouse and human beta-cells. Specifically, based on a mouse electrophysiological model, two studies here presented are focused on the analysis of the emergent electrical activity of coupled cell populations, and its robustness upon operating conditions, such as the cluster topology, the stimulatory glucose concentration, and the intrinsic biological noise. Finally, a third study based on a mathematical model fine-tuned on human electrophysiology attempts to estimate and analyse gap junction coupling between human beta-cells, validating obtained results against the few available experimental studies. This dissertation contains new results outlined in the following. At first, a study of compact beta-cell clusters shows that a coherent dynamics characterises beta-cells in mouse islets. This robust dynamical state ensures a long-range correlated cellular activity, and it is strictly dependent on both glucose stimulation level and cluster size. The beta-cell cluster is able to switch from coherent to uncorrelated dynamics resembling phase transition and critical phenomena observed in other physical systems. It is worth noting that a similar regulation of the dynamics around a critical point is a feature of other biological networks, such as neuronal networks. At second, a study concerning the topological effects on the emergent dynamics shows that the beta-cells in mouse islets can be viewed as a fully coupled functional unit while the human islet seems to be characterised by functionally distinct modules of beta-cells. This substantial difference is mainly due to the percolated network architecture underlying beta-cells arrangement in human islets, which induces a complex pattern of intercellular synchronisations. It is important to note that such pattern shows scale-free similarity features characteristic of the percolated cluster resembling the human beta-cell arrangement, not observed in the compact mouse architectures. Finally, the third study represents to the best of our knowledge the first attempt to estimate gap junction conductance between human beta-cells. Results obtained are surprisingly in agreement with the reported values of the junctional conductance between mouse beta-cells. The analyses of small coupled populations of human beta-cells show moreover that the estimated strength of coupling can substantially alter the emergent dynamics, and consequently the insulin release.