Membrane Potential and Calcium Dynamics in Beta Cells from Mouse Pancreas Tissue Slices: Theory, Experimentation, and Analysis

Due to the lower sensitivity of the MP probes compared with [Ca2+]i indicators and to the smaller excitable area (thin membrane), high frequency confocal imaging of MP yields data that are even more noisy. Figure 6 depicts a typical result from confocal imaging of MP in beta cells during stimulation with 10 mM glucose. The plasmalemma is hardly distinguishable on individual frames, but becomes clearly visible when images are averaged within the temporal domain (Figure 6A,B, respectively). The MP signal from area covering few cells or a small part of plasmalemma (square, Figure 6A,B) is exceedingly noisy in the time domain (Figure 6E,G). Upon denoising, three oscillatory deflections clearly emerge (Figure 6F,H). Comparing this result with the one we obtained with the patch clamp technique (Figure 2), one can notice that bursts lack the superimposed spikes, most probably due to the sampling frequency used during the optical sampling of the MP. Importantly, this denoising protocol allows us to visualize the MP deflections in the spatial domain (Figure 6C,D). Such a visualization is very helpful in analyzing the spreading of the depolarization over many beta cells [86].

Since its advent, confocal imaging has helped us a lot in elucidating the normal and pathological responses to various stimuli in beta cells as well as in other cells in the islets of Langerhans and many other cell types. Two issues have longed remained unaddressed due to our inability to record simultaneously from many cells at a time and due to our inability to simultaneously capture signals at different steps along the stimulus-secretion response: first, what are the in situ properties of the beta cell response at a population level and second, what is the exact relationship between the various signals along the stimulus-secretion response. Recent advances in indicator and detector sensitivity, together with the tissue slice method and the analytical tools to filter and denoise experimentally obtained data and to understand them within the realm of complex network theory have enabled us to start addressing these issues. To be precise, the proposed methodology facilitates the exact extraction of the interaction patterns among beta cells thereby providing a firm description of the functional organization within the islets of Langerhans. Most importantly, by this means not only the physiology of beta cells can be assessed at a higher organizational level, but also fertile ground is provided for drawing a line between normal and pathological function and predict or detect the development of diabetes mellitus. Namely, recent studies put forward the idea of impaired cell-to-cell pathways in both type-1 and type-2 diabetes [71,83,170,171,172], and even suggest that modulations of gap-junctional communication might lead to the development of novel diabetes therapies [71,84]. To make a step further in our understanding of beta cell physiology, in the future the above approaches need to be applied and validated on human tissue.

Moreover, some new approaches need to be developed, for instance approaches to track the exocytotic process simultaneously with the more upstream changes in MCFs, MP and [Ca2+]i.