The paper provides a review of the recent advances in the study of complex biological systems that were inspired and enabled by methods of network science. Specific focus is given to the extraction of functional connectivity patterns in multicellular systems, with emphasis on insulin secreting beta cell populations in islets of Langerhans. Describing the intercellular activity patterns by means of network language has not only revealed that beta cell networks share many architectural similarities with several other real-life networks, such as small-worldness, heterogeneity, and modularity, but also leads to important new insights into the relationship between cellular metabolic activity and the orchestration of collective behavior. Most importantly, the paper describes the emerging field of multilayer networks and highlights the potential offered by this framework in exploring the complex organization of tissues in both health and disease.
COBISS.SI-ID: 512746040
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 switch to supercritical calcium dynamics and loss of beta cell functionality.
COBISS.SI-ID: 512760376
SNAP-25 is a protein of the core SNARE complex mediating stimulus-dependent release of insulin from pancreatic β cells. The protein exists as two alternatively spliced isoforms, SNAP-25a and SNAP-25b, differing in 9 out of 206 amino acids, yet their specific roles in pancreatic β cells remain unclear. We explored the effect of SNAP-25b-deficiency on glucose-stimulated insulin release in islets and found increased secretion both in vivo and in vitro. However, slow photo-release of caged Ca2+ in β cells within pancreatic slices showed no significant differences in Ca2+-sensitivity, amplitude or rate of exocytosis between SNAP-25b-deficient and wild-type littermates. Therefore, we next investigated if Ca2+ handling was affected in glucose-stimulated β cells using intracellular Ca2+-imaging and found premature activation and delayed termination of [Ca2+] i elevations. These findings were accompanied by less synchronized Ca2+-oscillations and hence more segregated functional β cell networks in SNAP-25b-deficient mice. Islet gross morphology and architecture were maintained in mutant mice, although sex specific compensatory changes were observed. Thus, our study proposes that SNAP-25b in pancreatic β cells, except for participating in the core SNARE complex, is necessary for accurate regulation of Ca2+-dynamics.
COBISS.SI-ID: 512737080
In beta cells, stimulation by metabolic, hormonal, neuronal, and pharmacological factors is coupled to secretion of insulin through different intracellular signaling pathways. Our knowledge about the molecular machinery supporting these pathways and the patterns of signals it generates comes mostly from rodent models, especially the laboratory mouse. The increased availability of human islets for research during the last few decades has yielded new insights into the specifics in signaling pathways leading to insulin secretion in humans. In this review, we follow the most central triggering pathway to insulin secretion from its very beginning when glucose enters the beta cell to the calcium oscillations it produces to trigger fusion of insulin containing granules with the plasma membrane. Along the way, we describe the crucial building blocks that contribute to the flow of information and focus on their functional role in mice and humans and on their translational implications.
COBISS.SI-ID: 512726328
In the exocrine pancreas, the relationship between structure and function, as well as between normal and pathological functioning, can be easily understood if presented in a systematic and logical manner. In this chapter, we explain pancreas physiology. We start by explaining the embryological and ontogenetic development of the pancreas and describe the basic anatomical characteristics of the mature gland, i.e. the macro- and microscopic structure, its vascular supply and innervation. These form the foundation necessary to understand the mechanisms of acinar and ductal cell secretion and their regulation, which are covered in the middle part, with an emphasis on the ionic part of the pancreatic juice. In the last part, we focus on the enzymatic part of the pancreatic juice and its role in digestion of all main groups of energy-rich nutrients, i.e. carbohydrates, proteins and lipids. Two main sources of additional information will help the reader grasp the main concepts in pancreas physiology: figures summarize and combine various concepts encountered in the main text, and clinical boxes contain examples of how a given piece of knowledge can be relevant to understand some diseases.
COBISS.SI-ID: 512723000