Network Properties of Electrically Coupled Bursting Pituitary Cells

Abstract

The endocrine cells of the anterior pituitary gland are electrically active when stimulated or, in some cases, when not inhibited. The activity pattern thought to be most effective in releasing hormones is bursting, which consists of depolarization with small spikes that are much longer than single spikes. Although a majority of the research on cellular activity patterns has been performed on dispersed cells, the environment in situ is characterized by networks of coupled cells of the same type, at least in the case of somatotrophs and lactotrophs. This produces some degree of synchronization of their activity, which can be greatly increased by hormones and changes in the physiological state. In this computational study, we examine how electrical coupling among model cells influences synchronization of bursting oscillations among the population. We focus primarily on weak electrical coupling, since strong coupling leads to complete synchronization that is not characteristic of pituitary cell networks. We first look at small networks to point out several unexpected behaviors of the coupled system, and then consider a larger random scale-free network to determine what features of the structural network formed through gap junctional coupling among cells produce a high degree of functional coupling, i.e., clusters of synchronized cells. We employ several network centrality measures, and find that cells that are closely related in terms of their closeness centrality are most likely to be synchronized. We also find that structural hubs (cells with extensive coupling to other cells) are typically not functional hubs (cells synchronized with many other cells). Overall, in the case of weak electrical coupling, it is hard to predict the functional network that arises from a structural network, or to use a functional network as a means for determining the structural network that gives rise to it.

Network representation of multicellular activity in pancreatic islets: Technical considerations for functional connectivity analysis

“…In conclusion, we would like to stress that the scope of network analyses has, in recent years, been extended to investigate intercellular interactions and functional connectivity patterns in different types of tissues. These encompass various kinds of neural assemblies [ 131 ], pituitary endocrine cells [ 132 , 133 ], astrocytes [ 134 ], yeast cells [ 135 ], distinct epithelial cell types [ 136 , 137 ], acinar cells [ 138 ], and hepatocytes [ 139 ]. As such, the insights we present herein hold relevance for comprehending the intricacies of collective cellular activity across diverse contexts, where the assessment of multicellular dynamics can be achieved through suitable imaging techniques.…”

Conversion of spikers to bursters in pituitary cell networks: Is it better to disperse for maximum exposure or circle the wagons?

“…For these reasons, the results from prior studies should not be expected to carry over to pituitary cell networks. The current study is a follow-up to a recent one from our group, which considered weak coupling of identical pituitary bursters and demonstrated the difficulty in predicting the functional network defined by cell synchronization from the structural network of cell coupling [ 10 ].…”

“…In Eq (10), N i represents the set of electrically-connected neighbors of cell i. The dimensionless secretion value is calculated using an increasing sigmoid function:…”

“…bursters and demonstrated the difficulty in predicting the functional network defined by cell synchronization from the structural network of cell coupling [10].…”

“…Whether the structural network, where the edges represent gap junctions, is also scale-free is not known. In a recent study, we showed that the relationship between the structural network of pituitary-type bursters and the resulting functional network is tenuous at best, at least in the case of weak coupling that we considered [ 10 ]. For example, the hubs of the functional network do not correspond to the hubs of the structural network.…”