Every islet matters: improving the impact of human islet research

Illuminating the complete ß-cell mass of the human pancreas- signifying a new view on the islets of Langerhans

Pancreatic islets of Langerhans play a pivotal role in regulating blood glucose homeostasis, but critical information regarding their mass, distribution and composition is lacking within a whole organ context. Here, we apply a 3D imaging pipeline to generate a complete account of the insulin-producing islets throughout the human pancreas at a microscopic resolution and within a maintained spatial 3D context. These data show that human islets are far more heterogenous than previously accounted for with regards to their size distribution and cellular make up. By deep tissue 3D imaging, this in-depth study demonstrates that 50% of the human insulin-expressing islets are virtually devoid of glucagon-producing α-cells, an observation with significant implications for both experimental and clinical research.

Genetic risk converges on regulatory networks mediating early type 2 diabetes

Type 2 diabetes mellitus (T2D), a major cause of worldwide morbidity and mortality, is characterized by dysfunction of insulin-producing pancreatic islet β cells1,2. T2D genome-wide association studies (GWAS) have identified hundreds of signals in non-coding and β cell regulatory genomic regions, but deciphering their biological mechanisms remains challenging3-5. Here, to identify early disease-driving events, we performed traditional and multiplexed pancreatic tissue imaging, sorted-islet cell transcriptomics and islet functional analysis of early-stage T2D and control donors. By integrating diverse modalities, we show that early-stage T2D is characterized by β cell-intrinsic defects that can be proportioned into gene regulatory modules with enrichment in signals of genetic risk. After identifying the β cell hub gene and transcription factor RFX6 within one such module, we demonstrated multiple layers of genetic risk that converge on an RFX6-mediated network to reduce insulin secretion by β cells. RFX6 perturbation in primary human islet cells alters β cell chromatin architecture at regions enriched for T2D GWAS signals, and population-scale genetic analyses causally link genetically predicted reduced RFX6 expression with increased T2D risk. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs and individuals, and thus we anticipate that this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits using GWAS data.

TFEB and TFE3 control glucose homeostasis by regulating insulin gene expression

To fulfill their function, pancreatic beta cells require precise nutrient-sensing mechanisms that control insulin production. Transcription factor EB (TFEB) and its homolog TFE3 have emerged as crucial regulators of the adaptive response of cell metabolism to environmental cues. Here, we show that TFEB and TFE3 regulate beta-cell function and insulin gene expression in response to variations in nutrient availability. We found that nutrient deprivation in beta cells promoted TFEB/TFE3 activation, which resulted in suppression of insulin gene expression. TFEB overexpression was sufficient to inhibit insulin transcription, whereas beta cells depleted of both TFEB and TFE3 failed to suppress insulin gene expression in response to amino acid deprivation. Interestingly, ChIP-seq analysis showed binding of TFEB to super-enhancer regions that regulate insulin transcription. Conditional, beta-cell-specific, Tfeb-overexpressing, and Tfeb/Tfe3 double-KO mice showed severe alteration of insulin transcription, secretion, and glucose tolerance, indicating that TFEB and TFE3 are important physiological mediators of pancreatic function. Our findings reveal a nutrient-controlled transcriptional mechanism that regulates insulin production, thus playing a key role in glucose homeostasis at both cellular and organismal levels.

Reprogramming of pancreatic islet cells for regeneration and rejuvenation

The pancreatic β cell, which produces insulin, is a terminally differentiated cell type that divides rarely. Consequently, the regenerative ability of β cells is limited and irreversible diabetes occurs after severe loss of β-cell function. In view of such poor regenerative capacity, considerable research efforts have been made to promote the expansion of functional insulin-producing cells as a regenerative therapy for diabetes. Here, we discuss recent findings regarding the robust expansion of functional mature islet cells both in vivo and ex vivo through MYCL-mediated reprogramming. We also describe the potential prospects for the application of reprogramming technologies to regenerative therapy and rejuvenation of islet cells.

Beta cell dysfunction induced by bone morphogenetic protein (BMP)-2 is associated with histone modifications and decreased NeuroD1 chromatin binding

Insufficient insulin secretion is a hallmark of type 2 diabetes and has been attributed to beta cell identity loss characterized by decreased expression of several key beta cell genes. The pro-inflammatory factor BMP-2 is upregulated in islets of Langerhans from individuals with diabetes and acts as an inhibitor of beta cell function and proliferation. Exposure to BMP-2 induces expression of Id1-4, Hes-1, and Hey-1 which are transcriptional regulators associated with loss of differentiation. The aim of this study was to investigate the mechanism by which BMP-2 induces beta cell dysfunction and loss of cell maturity. Mouse islets exposed to BMP-2 for 10 days showed impaired glucose-stimulated insulin secretion and beta cell proliferation. BMP-2-induced beta cell dysfunction was associated with decreased expression of cell maturity and proliferation markers specific to the beta cell such as Ins1, Ucn3, and Ki67 and increased expression of Id1-4, Hes-1, and Hey-1. The top 30 most regulated proteins significantly correlated with corresponding mRNA expression. BMP-2-induced gene expression changes were associated with a predominant reduction in acetylation of H3K27 and a decrease in NeuroD1 chromatin binding activity. These results show that BMP-2 induces loss of beta cell maturity and suggest that remodeling of H3K27ac and decreased NeuroD1 DNA binding activity participate in the effect of BMP-2 on beta cell dysfunction.

Inflammatory and immune etiology of type 2 diabetes

Type 2 diabetes (T2D) represents a global threat affecting millions of patients worldwide. However, its causes remain incompletely dissected and we lack the tools to predict which individuals will develop T2D. Although there is a clear proven clinical association of T2D with metabolic disorders such as obesity and nonalcoholic fatty liver disease (NAFLD), the existence of a significant number of nondiabetic obese subjects suggests yet-uncovered features of such relationships. Here, we propose that a significant proportion of individuals may harbor an immune profile that renders them susceptible to developing T2D. We note the heterogeneity of circulating monocytes and tissue macrophages in organs that are key to metabolic disorders such as liver, white adipose tissue (WAT), and endocrine pancreas, as well as their contribution to T2D genesis.

Understanding islet dysfunction in type 2 diabetes through multidimensional pancreatic phenotyping: The Human Pancreas Analysis Program

In this perspective, we provide an overview of a recently established National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) initiative, the Human Pancreas Analysis Program for Type 2 Diabetes (HPAP-T2D). This program is designed to define the molecular pathogenesis of islet dysfunction by studying human pancreatic tissue samples from organ donors with T2D. HPAP-T2D generates detailed datasets of physiological, histological, transcriptomic, epigenomic, and genomic information. Importantly, all data collected, generated, and analyzed by HPAP-T2D are made immediately and freely available through a centralized database, PANC-DB, thus providing a comprehensive data resource for the diabetes research community.