Broadband multispectral microscopy of insulin granule dynamics in live pancreatic islets

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Diabetes is a chronic disease characterized by a high blood sugar level over an extended period of time. As of 2019, it was estimated that 463 million people worldwide or almost 9% of the world adult population, had diabetes, with rates continuing to rise. The hallmark of diabetes is the failure of insulin secreting beta cells located in the pancreas. The beta cell is the only cell in the body that secretes insulin, which in turn is the only hormone able to lower plasma glucose levels. Given the importance of beta cells, numerous methods have been applied to study their physiology. Beta cells store insulin in small compartments called insulin granules and when blood sugar levels rise, these granules fuse with the cell membrane, allowing beta cells to release large quantities of insulin at once. Unfortunately, direct visualization of insulin granules is not straightforward, since current methods require external labels that can affect granule function and dynamics. The team of investigators has been developing a straightforward optical microscopic technique called Confocal Broadband Backscattering Microscopy (CBBM) that can visualize insulin granules without any labels and monitor their dynamics over the course of hours and even days, which could potentially lead to a new treatment for diabetes. Project outcomes and efforts will be integrated into a course on optical microscopy in biology; provide training opportunities for undergraduate, graduate, and post graduate students; and enhance research experiences for K-12 students. The overarching goal of this project is to develop a label-free microscopy system for functional imaging and continuous monitoring of insulin granules in live pancreatic islets in a custom islet-on-a-chip. The approach will combine novel confocal broadband backscattering microscopy (CBBM) with the existing confocal FRET and super-resolution STORM modalities, with all three sharing a major part of the optical train and having a common field of view. The CBBM technique will provide a functional image of a beta cell, resolve insulin granules, monitor the conversion of proinsulin into insulin inside the granules, and visualize granule-based insulin intercellular transport. The project will also develop a physical and mathematical model to describe light scattering from insulin granules within the confocal volume of the label-free microscopy system and an inverse algorithm to differentiate insulin and non-insulin granules label-free. These algorithms will be used to monitor temporal changes in granules and continuously visualize them in 3D during insulin intercellular transport and release. To better understand islet function and the optimal environments for transplantable islets, glucose exchanges will be combined with in vivo functional imaging in human pancreatic islets, allowing investigation of important feedback loops in glucose/insulin cycles. Experiments will also be performed to investigate critical differences between islets derived from diabetic and healthy subjects.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.