Research Project
10326565
Pancreatic islets rely on spatiotemporally orchestrated interactions between heterogenous cells to maintain blood glucose homeostasis. In type 1 diabetes, an islet-directed autoimmune attack leads to loss of functional ? cells, which is accompanied by defects in the other islet cell types. Diabetics suffer complications from chronic glucose misregulation, which ultimately reduce life expectancy. Administering insulin itself can treat type 1 diabetes. However, daily insulin injection is expensive, onerous, and carries side effects including risk of ketoacidosis and coma. Human stem cell-derived islet organoids (SC-islets) offer a chance to generate a limitless human islet supply as potential therapeutics through transplantation. However, SC-islets lack the precision, kinetics, and magnitude of insulin/glucagon secretion that natural islets show during adult life. Whether these limitations reflect poor spatiotemporal coordination between (or within) populations of SC-islet cell types, or intrinsic three-dimensional (3D) heterogeneity in development and maturation, is still unknown. Here, we propose to address these fundamental questions by experimentally capturing the trajectories of cellular activity and interaction across the 3D volume of developing SC-islets through the integration of novel technologies from stem cell biology, soft thin-film nanoelectronics, tissue clearing and single-cell spatial transcriptomics, and computational and system biology. Specifically, we have (1) exploited scalable cell differentiation and purification methods to build ?designer? SC-islets with custom ? and ? composition; (2) globally embedded soft stretchable sensor arrays within SC-islets, building ?cyborg islets? for chronically-stable tracing of islet-wide ?- and ?-cell type specific electrical activities at single-cell resolution in vitro and in vivo; (3) implemented 3D tissue clearing, staining, imaging, and in situ single-cell RNA sequencing to spatially map hormones, biomarkers, gene expression, and cell types in the intact SC-islets at subcellular resolution; and (4) used fluorescently-labeled electronic barcodes to identify sensor positions within cleared SC-islets and computationally integrate chronic electrical recording with hormones, biomarker and gene expression data at the single-cell level. We propose to integrate and use these inventions to address major challenges in SC-islet maturation. Specifically, we aim to employ such multimodal characterization of SC-islet development to address (1) the role of Dec1 in islet maturation mediated by circadian entrainment; (2) the 3D heterogeneity in SC-islet maturation; and (3) the role of nerve innervation and vascularization in the maturation of transplanted SC-islets. The success of this proposal will result in a platform that can monitor the in situ single-cell activity of SC-islets in a chronically stable manner, provide an understanding of the 3D heterogeneity during SC-islet development and maturation. We envision that it will ultimately enable us to build functionally specialized and mature SC-islets for human therapeutics.
