Fast-slow analysis demonstrates mechanism for stochastic endocrine cell electrical bursts
Fast-slow analysis demonstrates mechanism for stochastic endocrine cell electrical bursts lead image
Endocrine cells rely on bursts of electrical impulses for secreting hormones. As in nerve cells, these impulses result from ion flux across the cell membrane through ion channels. However, because endocrine cells are smaller than neurons, they have fewer ion channels, increasing the influence of any single channel.
Fazli et al. demonstrate how the short-lived stochastic opening of ion channels in pituitary cells can yield longer responses by converting electrical impulses into much longer bursts of action potentials. Using a mathematical model of stress hormone-secreting corticotrophs, the group used fast-slow analysis to demonstrate that the stochastic opening of a single type of ion channel can push the cell across what is called a separating surface and lead to several additional electrical impulses.
The model points to an essential role of large-conductance voltage-gated BK-type potassium channels in hormone release.
“Almost all prior analyses of bursting, including our own, have focused on deterministic systems in which it is tacitly assumed that all ion channel types present in the model are present in large numbers,” said author Richard Bertram. “In contrast to neurons, the endocrine pituitary cells like corticotrophs are all small and noisy, and stochastic effects likely play a much greater role.”
Electrical bursting is often explained as a slow periodic passage across equilibrium structures of the model’s fast subsystem of variables, but such a framework failed to fully explain the bursting activity in corticotrophs.
The group is studying the effects of chronic stress on bursting electrical activity in corticotrophs, as well as how pituitary cell networks affect their bursting electrical activity and coordination.
Source: “Fast-slow analysis of a stochastic mechanism for electrical bursting,” by Mehran Fazli, Theodore Vo, and Richard Bertram, Chaos (2021). The article can be accessed at https://doi.org/10.1063/5.0059338 .
