Functional Connectivity in Islets of Langerhans from Mouse Pancreas Tissue Slices

Many details of glucose-stimulated intracellular calcium changes in beta 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 shortened, and the sizes of simultaneously responding clusters increased with increasing glucose. Exactly the opposite characterized deactivation. The frequency of fast calcium oscillations during activity increased with increasing glucose up to 12 mM glucose, 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. 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 beta cell heterogeneity and an important baseline for future studies of stimulus-secretion and intercellular coupling.

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Glucose-dependent activation, activity, and deactivation of beta cell networks in acute mouse pancreas tissue slices

10.1101/2020.03.11.986893 ◽

2020 ◽

Author(s):

Jurij Dolenšek ◽

Maša Skelin Klemen ◽

Marko Gosak ◽

Lidija Križančić-Bombek ◽

Viljem Pohorec ◽

...

Keyword(s):

Beta Cell ◽

Beta Cells ◽

Insulin Release ◽

Glucose Concentration ◽

Calcium Oscillations ◽

Tissue Slices ◽

Mouse Pancreas ◽

Network Parameters ◽

Cell Networks ◽

Glucose Dependence

AbstractGlucose progressively stimulates insulin release over a wide range of concentrations. However, the nutrient coding underlying activation, activity, and deactivation of beta cells affecting insulin release remains only partially described. Experimental data indicate that nutrient sensing in coupled beta cells in islets is predominantly a collective trait, overriding to a large extent functional differences between cells. However, some degree of heterogeneity between coupled beta cells may play important roles. To further elucidate glucose-dependent modalities in coupled beta cells, the degree of functional heterogeneity, and uncover the emergent collective operations, we combined acute mouse pancreas tissue slices with functional multicellular calcium imaging. We recorded beta cell calcium responses from threshold (7 mM) to supraphysiological (16 mM) glucose concentrations with high spatial and temporal resolution. This enabled the analysis of both classical physiological parameters and complex network parameters, as well as their comparison at the level of individual cells. The activation profile displayed two major glucose concentration-dependent features, shortening of delays to initial activation, and shortening of delays until half activation with increasing glucose concentration. Inversely, during deactivation both delays to initial deactivation and until half deactivation were progressively longer with increasing glucose concentration. The plateau activity with fast calcium oscillations expressed two types of glucose-dependence. Physiological concentrations mostly affected the frequency of oscillations, whereas supraphysiological concentrations progressively prolonged the duration of oscillations. Most of the measured functional network parameters also showed clear glucose-dependence. In conclusion, we propose novel understanding for glucose-dependent coding properties in beta cell networks, and its deciphering may have repercussions for our understanding of the normal physiology of glucose homeostasis as well as of disturbances of metabolic homeostasis, such as diabetes mellitus.

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Assessing the origin and velocity of Ca2+ waves in three-dimensional tissue: Insights from a mathematical model and confocal imaging in mouse pancreas tissue slices

Communications in Nonlinear Science and Numerical Simulation ◽

10.1016/j.cnsns.2020.105495 ◽

2021 ◽

Vol 93 ◽

pp. 105495 ◽

Cited By ~ 1

Author(s):

Marko Šterk ◽

Jurij Dolenšek ◽

Lidija Križančić Bombek ◽

Rene Markovič ◽

Darko Zakelšek ◽

...

Keyword(s):

Mathematical Model ◽

Three Dimensional ◽

Confocal Imaging ◽

Tissue Slices ◽

Mouse Pancreas

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Automated 3-D cell population analysis in thick tissue sections using laser-scanning confocal-microscopy data

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100148642 ◽

1993 ◽

Vol 51 ◽

pp. 562-563

Author(s):

Hakan Ancin

Keyword(s):

Laser Scanning ◽

Population Analysis ◽

Three Dimensional ◽

Large Data ◽

Laser Scanning Confocal Microscopy ◽

Tissue Slices ◽

Scanning Confocal Microscopy ◽

Tissue Sections ◽

Spatially Adaptive ◽

Microscopy Data

This paper presents methods for performing detailed quantitative automated three dimensional (3-D) analysis of cell populations in thick tissue sections while preserving the relative 3-D locations of cells. Specifically, the method disambiguates overlapping clusters of cells, and accurately measures the volume, 3-D location, and shape parameters for each cell. Finally, the entire population of cells is analyzed to detect patterns and groupings with respect to various combinations of cell properties. All of the above is accomplished with zero subjective bias.In this method, a laser-scanning confocal light microscope (LSCM) is used to collect optical sections through the entire thickness (100 - 500μm) of fluorescently-labelled tissue slices. The acquired stack of optical slices is first subjected to axial deblurring using the expectation maximization (EM) algorithm. The resulting isotropic 3-D image is segmented using a spatially-adaptive Poisson based image segmentation algorithm with region-dependent smoothing parameters. Extracting the voxels that were labelled as "foreground" into an active voxel data structure results in a large data reduction.

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