GLPwatch

In Vitro Platform for Studying Human Insulin Release Dynamics of Single Pancreatic Islet Microtissues at High Resolution.

Adv Biosyst · 2020

Last updated 2026-05-28

Researchers created a lab system to study how human pancreatic islets release insulin in response to sugar. The system uses single islets in tiny drops and measures insulin release in real time, showing two clear phases of insulin release. Single islets produced stronger and more distinct insulin pulses than groups of islets, and the system could test how different compounds affect insulin release.

AI summary of the abstract below.

JournalAdv Biosyst, 2020
Citations48
Relative citation ratio2.51
NIH percentile80
Molecules
Conditions studied Type 2 Diabetes

Abstract

Insulin is released from pancreatic islets in a biphasic and pulsatile manner in response to elevated glucose levels. This highly dynamic insulin release can be studied in vitro with islet perifusion assays. Herein, a novel platform to perform glucose-stimulated insulin secretion (GSIS) assays with single islets is presented for studying the dynamics of insulin release at high temporal resolution. A standardized human islet model is developed and a microfluidic hanging-drop-based perifusion system is engineered, which facilitates rapid glucose switching, minimal sample dilution, low analyte dispersion, and short sampling intervals. Human islet microtissues feature robust and long-term glucose responsiveness and demonstrate reproducible dynamic GSIS with a prominent first phase and a sustained, pulsatile second phase. Perifusion of single islet microtissues produces a higher peak secretion rate, higher secretion during the first and second phases of insulin release, as well as more defined pulsations during the second phase in comparison to perifusion of pooled islets. The developed platform enables to study compound effects on both phases of insulin secretion as shown with two classes of insulin secretagogs. It provides a new tool for studying physiologically relevant dynamic insulin secretion at comparably low sample-to-sample variation and high temporal resolution.

Verbatim abstract via PubMed 32293140 ↗