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Integrated human pseudoislet system and microfluidic platform demonstrate differences in GPCR signaling in islet cells
John T. Walker, … , Alvin C. Powers, Marcela Brissova
John T. Walker, … , Alvin C. Powers, Marcela Brissova
Published April 30, 2020
Citation Information: JCI Insight. 2020;5(10):e137017. https://doi.org/10.1172/jci.insight.137017.
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Resource and Technical Advance Endocrinology Metabolism

Integrated human pseudoislet system and microfluidic platform demonstrate differences in GPCR signaling in islet cells

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Abstract

Pancreatic islets secrete insulin from β cells and glucagon from α cells, and dysregulated secretion of these hormones is a central component of diabetes. Thus, an improved understanding of the pathways governing coordinated β and α cell hormone secretion will provide insight into islet dysfunction in diabetes. However, the 3D multicellular islet architecture, essential for coordinated islet function, presents experimental challenges for mechanistic studies of intracellular signaling pathways in primary islet cells. Here, we developed an integrated approach to study the function of primary human islet cells using genetically modified pseudoislets that resemble native islets across multiple parameters. Further, we developed a microperifusion system that allowed synchronous acquisition of GCaMP6f biosensor signal and hormone secretory profiles. We demonstrate the utility of this experimental approach by studying the effects of Gi and Gq GPCR pathways on insulin and glucagon secretion by expressing the designer receptors exclusively activated by designer drugs (DREADDs) hM4Di or hM3Dq. Activation of Gi signaling reduced insulin and glucagon secretion, while activation of Gq signaling stimulated glucagon secretion but had both stimulatory and inhibitory effects on insulin secretion, which occur through changes in intracellular Ca2+. The experimental approach of combining pseudoislets with a microfluidic system allowed the coregistration of intracellular signaling dynamics and hormone secretion and demonstrated differences in GPCR signaling pathways between human β and α cells.

Authors

John T. Walker, Rachana Haliyur, Heather A. Nelson, Matthew Ishahak, Gregory Poffenberger, Radhika Aramandla, Conrad Reihsmann, Joseph R. Luchsinger, Diane C. Saunders, Peng Wang, Adolfo Garcia-Ocaña, Rita Bottino, Ashutosh Agarwal, Alvin C. Powers, Marcela Brissova

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Figure 2

Pseudoislets resemble native human islets in proliferation, apoptosis, and architecture and express markers of α and β cell identity.

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Pseudoislets resemble native human islets in proliferation, apoptosis, a...
(A) Immunofluorescence visualization of labeling for insulin (INS; β cells) and glucagon (GCG; α cells) in combination with detection of proliferation (Ki67), apoptosis (TUNEL), extracellular matrix (collagen IV, COLIV), and endothelial cells (caveolin-1, CAV1). Scale bar: 100 μm. (B) Quantification of β and α cell proliferation in native islets and pseudoislets, expressed as a percentage of INS+ or GCG+ cells expressing Ki67; n = 3 donors; P > 0.05. (C) Quantification of β and α cell apoptosis by TUNEL assay; n = 3 donors; P > 0.05. (D) Quantification of COLIV-expressing extracellular matrix, expressed as percentage of COLIV+ area to INS+ and GCG+ cell area; n = 3 donors; P > 0.05. (E) Quantification of endothelial cell area, expressed as percentage of CAV1+ cell area to INS+ and GCG+ cell area; n = 3 donors; P > 0.05. (F) Expression of transcription factors (TF) important for β cell identity (NKX6.1 and PDX1), α cell identity (MAFB and ARX), and pan endocrine cell identity (PAX6 and NKX2.2). Scale bar: 50 μm. (G) Quantification β cell identity markers in β cells of native islets and pseudoislets (n = 3 donors/marker; P > 0.05). (H) Quantification of α cell identity markers in α cells of native islets and pseudoislets (n = 3–4 donors/marker; P > 0.05). (I and J) Quantification of pan-endocrine markers in β (I) and α (J) cells of native islets and pseudoislets (n = 3 donors/marker; P > 0.05). Wilcoxon matched-pairs signed-rank test was used to analyze statistical significance in B–E and G–J. Data are represented as mean ± SEM.

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