Coculture analysis of extracellular protein interactions affecting insulin secretion by pancreatic beta cells

共培养分析细胞外蛋白相互作用对胰岛β细胞胰岛素分泌的影响

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Abstract

Interactions between cell-surface proteins help coordinate the function of neighboring cells. Pancreatic beta cells are clustered together within pancreatic islets and act in a coordinated fashion to maintain glucose homeostasis. It is becoming increasingly clear that interactions between transmembrane proteins on the surfaces of adjacent beta cells are important determinants of beta-cell function. Elucidation of the roles of particular transcellular interactions by knockdown, knockout or overexpression studies in cultured beta cells or in vivo necessitates direct perturbation of mRNA and protein expression, potentially affecting beta-cell health and/or function in ways that could confound analyses of the effects of specific interactions. These approaches also alter levels of the intracellular domains of the targeted proteins and may prevent effects due to interactions between proteins within the same cell membrane to be distinguished from the effects of transcellular interactions. Here a method for determining the effect of specific transcellular interactions on the insulin secreting capacity and responsiveness of beta cells is presented. This method is applicable to beta-cell lines, such as INS-1 cells, and to dissociated primary beta cells. It is based on coculture models developed by neurobiologists, who found that exposure of cultured neurons to specific neuronal proteins expressed on HEK293 (or COS) cell layers identified proteins important for driving synapse formation. Given the parallels between the secretory machinery of neuronal synapses and of beta cells, we reasoned that beta-cell functional maturation might be driven by similar transcellular interactions. We developed a system where beta cells are cultured on a layer of HEK293 cells expressing a protein of interest. In this model, the beta-cell cytoplasm is untouched while extracellular protein-protein interactions are manipulated. Although we focus here primarily on studies of glucose-stimulated insulin secretion, other processes can be analyzed; for example, changes in gene expression as determined by immunoblotting or qPCR.

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