Functional identification of islet cell types by electrophysiological fingerprinting

• The alpha-, beta- and delta-cells of the pancreatic islet exhibit different electrophysiological features. We used a large dataset of whole- cell patch- clamp recordings from cells in intactmouse islets (N = 288 recordings) to investigatewhether it is possible to reliably identify cell type (alpha,beta or gamma) based on their electrophysiological characteristics. We quantified 15 electrophysiological variables in each recorded cell. Individually, none of the variables could reliably distinguish the cell types. We therefore constructed a logistic regressionmodel that included all quantified variables, to determine whether they could together identify cell type. The model identified cell typewith 94% accuracy. Thismodelwas applied to a dataset of cells recorded from hyperglycaemic bV59M mice; it correctly identified cell type in all cells and was able to distinguish cells that co-expressed insulin and glucagon. Based on this revised functional identification, we were able to improve conductance-based models of the electrical activity in alpha-cells and generate a model of gamma-cell electrical activity. These new models could faithfully emulate alpha- and gamma-cell electrical activity recorded experimentally.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine (hsv//eng)

Nyckelord

islet electrophysiology

logistic regression

alpha-cell

beta-cell

gamma-cell

conductance-based

pancreatic alpha-cells

k-atp channels

inhibits glucagon-secretion

gated ion channels

beta-cells

insulin-secretion

delta-cells

potassium channels

endocrine pancreas

b-cells

ci l

1982

diabetes

v31

p538

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