Ca2+ dynamics in the pancreatic islet

Functional networks in pancreatic islets 

In biological systems, complex behavior can be described by networks, including brain neural networks, or the networks of interacting proteins. Recently it has been shown that network properties emerge in the islets of Langerhans. Within the networks there are cells which have disproportionately large number of functional links to other cells, and which control the dynamics of the rest of the cells. Network theory, combined with quantitative imaging techniques offer a powerful approach to interrogate connections between structure and function of complex systems. We apply network theory analysis to Ca2+ traces generated both from computational modeling and from multi-scale quantitative microscopy to understand and predict structural-functional connectivity in the pancreatic islets and disease pathogenesis.

Simulated 3D islet of beta cells

Computational modeling of the islet function

Cell electrophysiology or the coupled β-cell model we use was adapted from the published Cha–Noma single-cell model where the change of the membrane potential with time for each β-cell is related to the sum of individual ion currents through that cell's membrane. This model modified with addition of the coupling current between the cells to form the coupled islet allows to predict Ca2+ and insulin secretion dynamics of the β-cell islet in-silico. We use the model to test how removal of specific cell subpopulations effects the function of the rest of the sells, to predict functional changes under diabetic conditions (reduced cell-cell coupling) and more.

Zebrafish image obtained with confocal microscopy

Paracrine and neural inputs in islets of Langerhans

We study to which extent paracrine (alpha-beta and delta-beta cell communication) forms the beta cell network. We are using pancreatic slices from human donors and mice in healthy and diabetic conditions. 

Role of innervation in the formation of networks is studied in vivo in zebrafish models.