Β-cell Subpopulations Research Articles

Garlic Extract Promotes Pancreatic Islet Neogenesis Through α-to-β-Cell Transdifferentiation and Normalizes Glucose Homeostasis in Diabetic Rats.

Garlic extract (GE) has been shown to ameliorate hyperglycemia in diabetic rats (DRs) by increasing insulin production. However, the mechanism through which it exerts its effects remains unclear. Here, it investigates the molecular process and the origin of regenerating β-cell in rats with streptozotocin (STZ)-induced diabetes in response to GE. In this study, quantitative RT-PCR (qRT-PCR), western blotting, and immunohistochemical analysis are carried out after pancreas isolation. These findings show that 1 week of GE treatment increases the expression of the endocrine progenitor cell markers Neurogenin3 (Neurog3), pancreatic and duodenal homeobox 1 (Pdx1), neurogenic differentiation factor 1 (Neurod1), paired box proteins (Pax)4, V-maf musculoaponeurotic fibrosarcoma oncogene homolog B(Mafb),and NK homeobox factors (Nkx)6-1 in STZ-induced DRs. Continuation with GE treatment for 8 weeks causes the expression of the mature β-cell markers insulin(Ins)2, urocortin3 (Ucn3), and glucose transporter 2 (Glut2) to peak. Comprehensive examination of the islet through immunohistochemical analysis reveals the presence of a heterogeneous cell population including INS+/GLUT2- and INS+/GLUT2+ β-cell subpopulations with few bihormonal INS+/GCG+ cells after 4 weeks. By week 8, islet architecture is reestablished, and glucose-stimulated insulin secretion was restored through the upregulation of Ucn3. GE induces β-cell neogenesis in DRs and restores islet architecture. The newly formed mature β-like cells could have originated through the differentiation of endocrine progenitor cells as well as α- to β-cell transdifferentiation.

Glucokinase activity controls subpopulations of β-cells that alternately lead islet Ca2+ oscillations.

Oscillations in insulin secretion, driven by islet Ca2+ waves, are crucial for glycemic control. Prior studies, performed with single-plane imaging, suggest that subpopulations of electrically coupled β-cells have privileged roles in leading and coordinating the propagation of Ca2+ waves. Here, we used 3D light-sheet imaging to analyze the location and Ca2+ activity of single β-cells within the entire islet at >2 Hz. In contrast with single-plane studies, 3D network analysis indicates that the most highly synchronized β-cells are located at the islet center, and remain regionally but not cellularly stable between oscillations. This subpopulation, which includes 'hub cells', is insensitive to changes in fuel metabolism induced by glucokinase and pyruvate kinase activation. β-cells that initiate the Ca2+ wave ('leaders') are located at the islet periphery, and strikingly, change their identity over time via rotations in the wave axis. Glucokinase activation, which increased oscillation period, reinforced leader cells and stabilized the wave axis. Pyruvate kinase activation, despite increasing oscillation frequency, had no effect on leader cells, indicating the wave origin is patterned by fuel input. These findings emphasize the stochastic nature of the β-cell subpopulations that control Ca2+ oscillations and identify a role for glucokinase in spatially patterning 'leader' β-cells.

Pancreatic β-Cell Identity Change through the Lens of Single-Cell Omics Research.

The main hallmark in the development of both type 1 and type 2 diabetes is a decline in functional β-cell mass. This decline is predominantly attributed to β-cell death, although recent findings suggest that the loss of β-cell identity may also contribute to β-cell dysfunction. This phenomenon is characterized by a reduced expression of key markers associated with β-cell identity. This review delves into the insights gained from single-cell omics research specifically focused on β-cell identity. It highlights how single-cell omics based studies have uncovered an unexpected level of heterogeneity among β-cells and have facilitated the identification of distinct β-cell subpopulations through the discovery of cell surface markers, transcriptional regulators, the upregulation of stress-related genes, and alterations in chromatin activity. Furthermore, specific subsets of β-cells have been identified in diabetes, such as displaying an immature, dedifferentiated gene signature, expressing significantly lower insulin mRNA levels, and expressing increased β-cell precursor markers. Additionally, single-cell omics has increased insight into the detrimental effects of diabetes-associated conditions, including endoplasmic reticulum stress, oxidative stress, and inflammation, on β-cell identity. Lastly, this review outlines the factors that may influence the identification of β-cell subpopulations when designing and performing a single-cell omics experiment.

Investigation of the motif activity of transcription regulators in pancreatic β-like cell subpopulations differentiated from human induced pluripotent stem cells.

Pancreatic β-cells are composed of different subtypes that play a key role in the control of insulin secretion and thereby control glucose homeostasis. In vitro differentiation of human induced pluripotent stem cells (hiPSCs) into 3D spheroids leads to the generation of β-cell subtypes and thus to the development of islet-like structures. Using this cutting-edge cell model, the aim of the study was to decipher the signaling signature that underlines β-cell subtypes, with a focus on the search for the activity of motifs of important transcription regulators (TRs). The investigation was performed using data from previous single-cell sequencing analysis introduced into the integrated system for motif activity response analysis (ISMARA) of transcription regulators. We extracted the matrix of important TRs activated in the β-cell subpopulation and bi-hormonal-like β-cells. Based on these TRs and their targets, we built specific regulatory networks for main cell subpopulations. Our data confirmed the transcriptomic heterogeneity of the β-cell subtype lineage and suggested a mechanism that could account for the differentiation of β-cell subtypes during pancreas development. We do believe that our findings could be instrumental for understanding the mechanisms that affect the balance of β-cell subtypes, leading to impaired insulin secretion in type 2 diabetes.

β-cell intrinsic dynamics rather than gap junction structure dictates subpopulations in the islet functional network.

Diabetes is caused by the inability of electrically coupled, functionally heterogeneous β-cells within the pancreatic islet to provide adequate insulin secretion. Functional networks have been used to represent synchronized oscillatory [Ca2+] dynamics and to study β-cell subpopulations, which play an important role in driving islet function. The mechanism by which highly synchronized β-cell subpopulations drive islet function is unclear. We used experimental and computational techniques to investigate the relationship between functional networks, structural (gap junction) networks, and intrinsic β-cell dynamics in slow and fast oscillating islets. Highly synchronized subpopulations in the functional network were differentiated by intrinsic dynamics, including metabolic activity and KATP channel conductance, more than structural coupling. Consistent with this, intrinsic dynamics were more predictive of high synchronization in the islet functional network as compared to high levels of structural coupling. Finally, dysfunction of gap junctions, which can occur in diabetes, caused decreases in the efficiency and clustering of the functional network. These results indicate that intrinsic dynamics rather than structure drive connections in the functional network and highly synchronized subpopulations, but gap junctions are still essential for overall network efficiency. These findings deepen our interpretation of functional networks and the formation of functional subpopulations in dynamic tissues such as the islet.

Pancreatic β-cell senescence in diabetes: mechanisms, markers and therapies.

Cellular senescence is a response to a wide variety of stressors, including DNA damage, oncogene activation and physiologic aging, and pathologically accelerated senescence contributes to human disease, including diabetes mellitus. Indeed, recent work in this field has demonstrated a role for pancreatic β-cell senescence in the pathogenesis of Type 1 Diabetes, Type 2 Diabetes and monogenic diabetes. Small molecule or genetic targeting of senescent β-cells has shown promise as a novel therapeutic approach for preventing and treating diabetes. Despite these advances, major questions remain around the molecular mechanisms driving senescence in the β-cell, identification of molecular markers that distinguish senescent from non-senescent β-cell subpopulations, and translation of proof-of-concept therapies into novel treatments for diabetes in humans. Here, we summarize the current state of the field of β-cell senescence, highlighting insights from mouse models as well as studies on human islets and β-cells. We identify markers that have been used to detect β-cell senescence to unify future research efforts in this field. We discuss emerging concepts of the natural history of senescence in β-cells, heterogeneity of senescent β-cells subpopulations, role of sex differences in senescent responses, and the consequences of senescence on integrated islet function and microenvironment. As a young and developing field, there remain many open research questions which need to be addressed to move senescence-targeted approaches towards clinical investigation.

1747-P: Islet Ca2+ Dynamics, Heterogeneity, and Consistency in Three Dimensions with Activators of Pyruvate Kinase

Pancreatic β-cell heterogeneity is important for Ca2+ triggering and insulin secretion and is affected in diabetes. Organization and consistency of β-cell subpopulations are poorly understood despite being key in understanding how individual cells contribute to islet function and diabetes. Existing studies analyze single 2D planes of the islet. However, subpopulation organization cannot be fully understood without examining β cell dynamics throughout the entire islet in 3D. Here, we imaged islets from β cell specific GCaMP6s Ca2+ reporter mice using high-speed light-sheet microscopy to analyze the 3D organization and consistency in high glucose and with pharmacologic activators of pyruvate kinase (PK), a glycolytic enzyme that controls βcell excitability. Phase analysis revealed that cells which initiated islet depolarization (leaders) are not highly consistent across oscillations, but the 3D region where the calcium wave originates is consistent, according to a metric based upon the KL-divergence (P<0.0001 over 11 oscillations). Using functional network analysis, β-cell hubs which drive islet synchrony are more consistent over an islet region than across individual cells (P<0.0001). The wave origin was more regionally dependent than the β-cell hubs (P<0.0001). We also found that network analysis is similar (P=0.04) and phase analysis is different between 2D and 3D (P<0.0001). Following quantification of heterogeneity in the 3D islet, certain sub-populations of β cells are similar throughout the islet, while others are not. Acute PK activation decreased the consistency of wave initiators (P<0.0001), but not the consistency of hub cells in the functional network (P=0.15), shedding new light onto the mechanism behind these subpopulations. Islet regions, rather than individual cells, are more consistent and thus likely responsible for initiating Ca2+ triggering and insulin secretion. These mechanisms help render the islet robust to single β cell failures. Disclosure J.Briggs: None. E.Jin: None. M.J.Merrins: None. R.K.Benninger: None. Funding William S. Middleton Memorial Veterans Hospital; U.S. Department of Veterans Affairs Biomedical Laboratory Research and Development Service (I01B005113); National Institutes of Health (R01DK113103, R01DK127637, R01DK102950, R01DK106412); National Science

Single-nucleus RNA sequencing of human pancreatic islets identifies novel gene sets and distinguishes β-cell subpopulations with dynamic transcriptome profiles

BackgroundSingle-cell RNA sequencing (scRNA-seq) provides valuable insights into human islet cell types and their corresponding stable gene expression profiles. However, this approach requires cell dissociation that complicates its utility in vivo. On the other hand, single-nucleus RNA sequencing (snRNA-seq) has compatibility with frozen samples, elimination of dissociation-induced transcriptional stress responses, and affords enhanced information from intronic sequences that can be leveraged to identify pre-mRNA transcripts.MethodsWe obtained nuclear preparations from fresh human islet cells and generated snRNA-seq datasets. We compared these datasets to scRNA-seq output obtained from human islet cells from the same donor. We employed snRNA-seq to obtain the transcriptomic profile of human islets engrafted in immunodeficient mice. In both analyses, we included the intronic reads in the snRNA-seq data with the GRCh38-2020-A library.ResultsFirst, snRNA-seq analysis shows that the top four differentially and selectively expressed genes in human islet endocrine cells in vitro and in vivo are not the canonical genes but a new set of non-canonical gene markers including ZNF385D, TRPM3, LRFN2, PLUT (β-cells); PTPRT, FAP, PDK4, LOXL4 (α-cells); LRFN5, ADARB2, ERBB4, KCNT2 (δ-cells); and CACNA2D3, THSD7A, CNTNAP5, RBFOX3 (γ-cells). Second, by integrating information from scRNA-seq and snRNA-seq of human islet cells, we distinguish three β-cell sub-clusters: an INS pre-mRNA cluster (β3), an intermediate INS mRNA cluster (β2), and an INS mRNA-rich cluster (β1). These display distinct gene expression patterns representing different biological dynamic states both in vitro and in vivo. Interestingly, the INS mRNA-rich cluster (β1) becomes the predominant sub-cluster in vivo.ConclusionsIn summary, snRNA-seq and pre-mRNA analysis of human islet cells can accurately identify human islet cell populations, subpopulations, and their dynamic transcriptome profile in vivo.

Integrated transcriptomics contrasts fatty acid metabolism with hypoxia response in β-cell subpopulations associated with glycemic control

BackgroundUnderstanding how heterogeneous β-cell function impacts diabetes is imperative for therapy development. Standard single-cell RNA sequencing analysis illuminates some factors driving heterogeneity, but new strategies are required to enhance information capture.ResultsWe integrate pancreatic islet single-cell and bulk RNA sequencing data to identify β-cell subpopulations based on gene expression and characterize genetic networks associated with β-cell function in obese SM/J mice. We identify β-cell subpopulations associated with basal insulin secretion, hypoxia response, cell polarity, and stress response. Network analysis associates fatty acid metabolism and basal insulin secretion with hyperglycemic-obesity, while expression of Pdyn and hypoxia response is associated with normoglycemic-obesity.ConclusionsBy integrating single-cell and bulk islet transcriptomes, our study explores β-cell heterogeneity and identifies novel subpopulations and genetic pathways associated with β-cell function in obesity.

The role of highly functional β-cell subpopulations in the multicellular islet

The pancreatic islet is a multicellular network comprised of a majority of excitable insulin-producing β-cells. Electrically active β-cells show oscillations in intracellular Ca2+ that lead to insulin release. β-cell electrical activity is coordinated by gap junction channels. β-cell Ca2+ activity is globally elevated at high glucose, whereas it is globally silenced at low glucose due to gap junction communication. Using multicellular computational models of mouse and human islet electrophysiology, we investigated the role highly functional β-cell subpopulations may play in driving islet Ca2+ dynamics.

180-OR: Single-Cell RNA Sequencing Reveals a Role for ROS Signaling in Nutrient-Induced ß-Cell Proliferation

In nondiabetic obese individuals, β-cell mass accretion maintains glucose homeostasis by balancing levels of circulating insulin and insulin resistance. Type 2 diabetes appears when these compensatory mechanisms fail. Deciphering the pathways controlling β-cell proliferation may help to identify therapeutic targets to expand β-cell mass and prevent or delay the onset of diabetes. Previously we demonstrated that the monounsaturated fatty-acid oleate potentiates glucose-induced rat β-cell proliferation. Aim: To identify the transcriptional mechanisms underlying oleate-induced rat β-cell proliferation. Methods: Rat islets were exposed to 16.7mM glucose (Glu) with or without 0.5 mM oleate (Glu+Ol) or palmitate (Glu+Pal) for 48h. Proliferation was assessed by flow cytometry (C-peptide staining and EdU incorporation). Single-cell cDNA libraries were generated using 10X Genomics technology and sequenced on the Illumina platform. Bioinformatic analyses were performed using Seurat package. Results: β-cell proliferation was potentiated by Ol, but not Pal. Following single-cell RNA sequencing, UMAP plots revealed several β-cell sub-populations, including proliferating β-cells. A number of differences in gene expression were identified between groups in non-proliferating sub-populations. Among these, gene sets involved in ER-stress and β-cell differentiation were significantly up- and down-regulated, respectively, in response to Pal, but not Ol. Gene set enrichment analyses comparing proliferative vs. non-proliferative β-cells revealed an up-regulation of reactive oxygen species (ROS) and oxidoreductase activity-related pathways in both Glu and Glu+Ol groups. The antioxidant N-acetyl cysteine or the peroxiredoxin inhibitor Conoidin A inhibited Glu+Ol-induced β-cell proliferation. Conclusion: Our results suggest the involvement of ROS signaling through a redox relay via peroxiredoxin activation in nutrient-induced β-cell proliferation. Disclosure A. Vivoli: None. J. Ghislain: None. A. Castell: None. A. Filali: None. R. M. Sladek: None. V. Poitout: None.

Small subpopulations of β-cells do not drive islet oscillatory [Ca2+] dynamics via gap junction communication.

The islets of Langerhans exist as multicellular networks that regulate blood glucose levels. The majority of cells in the islet are excitable, insulin-producing β-cells that are electrically coupled via gap junction channels. β-cells are known to display heterogeneous functionality. However, due to gap junction coupling, β-cells show coordinated [Ca2+] oscillations when stimulated with glucose, and global quiescence when unstimulated. Small subpopulations of highly functional β-cells have been suggested to control [Ca2+] dynamics across the islet. When these populations were targeted by optogenetic silencing or photoablation, [Ca2+] dynamics across the islet were largely disrupted. In this study, we investigated the theoretical basis of these experiments and how small populations can disproportionality control islet [Ca2+] dynamics. Using a multicellular islet model, we generated normal, skewed or bimodal distributions of β-cell heterogeneity. We examined how islet [Ca2+] dynamics were disrupted when cells were targeted via hyperpolarization or populations were removed; to mimic optogenetic silencing or photoablation, respectively. Targeted cell populations were chosen based on characteristics linked to functional subpopulation, including metabolic rate of glucose oxidation or [Ca2+] oscillation frequency. Islets were susceptible to marked suppression of [Ca2+] when ~10% of cells with high metabolic activity were hyperpolarized; where hyperpolarizing cells with normal metabolic activity had little effect. However, when highly metabolic cells were removed from the model, [Ca2+] oscillations remained. Similarly, when ~10% of cells with either the highest frequency or earliest elevations in [Ca2+] were removed from the islet, the [Ca2+] oscillation frequency remained largely unchanged. Overall, these results indicate small populations of β-cells with either increased metabolic activity or increased frequency are unable to disproportionately control islet-wide [Ca2+] via gap junction coupling. Therefore, we need to reconsider the physiological basis for such small β-cell populations or the mechanism by which they may be acting to control normal islet function.

Harnessing the Endogenous Plasticity of Pancreatic Islets: A Feasible Regenerative Medicine Therapy for Diabetes?

Diabetes is a chronic metabolic disease caused by an absolute or relative deficiency in functional pancreatic β-cells that leads to defective control of blood glucose. Current treatments for diabetes, despite their great beneficial effects on clinical symptoms, are not curative treatments, leading to a chronic dependence on insulin throughout life that does not prevent the secondary complications associated with diabetes. The overwhelming increase in DM incidence has led to a search for novel antidiabetic therapies aiming at the regeneration of the lost functional β-cells to allow the re-establishment of the endogenous glucose homeostasis. Here we review several aspects that must be considered for the development of novel and successful regenerative therapies for diabetes: first, the need to maintain the heterogeneity of islet β-cells with several subpopulations of β-cells characterized by different transcriptomic profiles correlating with differences in functionality and in resistance/behavior under stress conditions; second, the existence of an intrinsic islet plasticity that allows stimulus-mediated transcriptome alterations that trigger the transdifferentiation of islet non-β-cells into β-cells; and finally, the possibility of using agents that promote a fully functional/mature β-cell phenotype to reduce and reverse the process of dedifferentiation of β-cells during diabetes.

Unique Human and Mouse β-Cell Senescence-Associated Secretory Phenotype (SASP) Reveal Conserved Signaling Pathways and Heterogeneous Factors.

The aging of pancreatic β-cells may undermine their ability to compensate for insulin resistance, leading to the development of type 2 diabetes (T2D). Aging β-cells acquire markers of cellular senescence and develop a senescence-associated secretory phenotype (SASP) that can lead to senescence and dysfunction of neighboring cells through paracrine actions, contributing to β-cell failure. In this study, we defined the β-cell SASP signature based on unbiased proteomic analysis of conditioned media of cells obtained from mouse and human senescent β-cells and a chemically induced mouse model of DNA damage capable of inducing SASP. These experiments revealed that the β-cell SASP is enriched for factors associated with inflammation, cellular stress response, and extracellular matrix remodeling across species. Multiple SASP factors were transcriptionally upregulated in models of β-cell senescence, aging, insulin resistance, and T2D. Single-cell transcriptomic analysis of islets from an invivo mouse model of reversible insulin resistance indicated unique and partly reversible changes in β-cell subpopulations associated with senescence. Collectively, these results demonstrate the unique secretory profile of senescent β-cells and its potential implication in health and disease.

2098-P: Transcriptomic Changes Associated with Oleate-Induced ß-Cell Proliferation in Rat Islets

Background: In nondiabetic obese individuals, β-cell mass accretion maintains glucose homeostasis by balancing levels of circulating insulin and insulin resistance. Type 2 diabetes appears when these compensatory mechanisms fail. Deciphering the pathways controlling β-cell proliferation has thus become a major research goal in the hope to identify therapeutic targets to expand β-cell mass and prevent or delay the onset of diabetes. Previously we demonstrated that fatty acids potentiate glucose induced β-cell proliferation in response to nutrient surfeit in rats. In recent studies we identified the mono-unsaturated fatty-acid oleate as a major fatty acid driving β-cell proliferation in rat islets ex vivo. Aim: To identify the transcriptional mechanisms underlying oleate-induced β-cell proliferation in rats. Method: Rat islets were exposed to 16.7mM glucose +/- oleate (0.5mM) for 48h. Proliferation was assessed by flow cytometry using c-peptide antibodies and EdU. Single cell cDNA libraries were generated using 10X Genomics technology and sequenced on the Illumina platform. Bioinformatic analyses were performed using the Cell Ranger pipeline, Seurat and Monocle. Results: Oleate induced a 3.1+/-0.4 fold increase (p<0.01; n=4) in β-cell proliferation. Following single-cell RNA sequencing, t-SNE plots revealed several β-cell sub-populations, including proliferating β-cells. Comparison between proliferative and non-proliferative β-cells identified more than 300 differentially expressed genes. Gene ontology suggested an increase in mitochondrial activity and reactive oxygen species (ROS) in proliferating β-cells. Pseudotime ordering of β cells revealed that ER-stress related genes are up-regulated prior to proliferation in response to oleate. Conclusion: Our study suggests an involvement of ROS and ER-stress in oleate-induced β-cells proliferation. Further functional analyses will substantiate the importance of these stress responses. Disclosure A. Vivoli: None. A. Castell: None. A. Pacis: None. R.M. Sladek: None. J. Ghislain: None. V. Poitout: None.

319-OR: First Responder Beta-Cell Subpopulation Affects Islet Response to Glucose

Glucose-stimulated insulin secretion from the pancreatic β-cells is driven by calcium (Ca2+) uptake. In mice Ca2+ is disproportionally controlled by functional subpopulations of β-cells, identified in affecting 2nd phase oscillatory Ca2+ response. Yet, the “1st-responder” cells that lead the 1st Ca2+phase disrupted in early diabetes were overlooked. It is unknown whether 1st responders are a distinct subpopulation, and if so, which factors underlie this distinction, and what is their role. We hypothesized that 1st responder metabolic and electrical parameters are distinct from the known β-cell subpopulations, and they play an important role in the 1st Ca2+phase of the islet response. We simultaneously measured Ca2+ dynamics and electrical coupling in intact islets using β-cells specific expression of the Ca2+ sensor GCaMP6s. We performed repeated glucose and Kapt channel blocker stimulation of the islet. We used femtosecond laser ablation of specific cells. This was complimented by multicellular islet electrophysiology model where we could remove specific cells from the islet and evaluate glucokinase rate, Katp and coupling conductance of the cells. We found no overlap of 1st responder with either “wave-initiator”, leading Ca2+ wave, or highly connected “hub” cell subpopulations, based on the oscillatory 2nd phase Ca2+ wave coordination. Interestingly 1st responders were less electrically coupled (p=0.0157), supported by simulations. 1st responders were consistent under repeatable glucose stimulation and remained 1st responders under the Katp channel blocker, supported by computational results of lower than average Katp channel conductance (p<0.0001). Removing 1st responder from the islet resulted in delayed 1st phase islet response compared to the random cell removal, both in experiment and simulation (p=.0428). In conclusion, 1st responders are distinct β-cell sub-population, which influences the islet 1st phase Ca2+response. Disclosure V. Kravets: None. J.M. Dwulet: None. W. Schleicher: None. R.K. Benninger: None. Funding JDRF (63012150); National Institutes of Health (R0163012150)

2077-P: Can Small ß-Cell Subpopulations Control Islet Dynamics? A Theoretical Study

Electrical activity of a pancreatic islet is globally activated under high glucose conditions and globally suppressed under low glucose conditions. This homogeneous behavior occurs due to the highly-coupled nature of the islet, despite heterogeneity of individual β-cells. Using hyperpolarization to silence β-cell activity, studies have shown that small subpopulations of highly functional β-cells can disproportionately control whole islet dynamics. Using a computational model of islet electrophysiology, we studied the theoretical basis of how small highly functional subpopulations of β-cells may regulate the global activity of islets. We modeled metabolic activity of β-cells as a continuous distribution and as a bimodal distribution. Then, in each case, we silenced the highest metabolically active cells and quantified the response of the islet. These highly metabolic cells (GKHigh) were silenced by hyperpolarization, similarly to experimental data. Only under a bimodal distribution, did a small (10%) population of GKHigh cells dramatically reduce islet activity, as experimentally demonstrated. Next, a simulation was run without GKHigh cells present in the islet. When GKHigh cells were absent, the islet remained globally active and had near normal duty cycle, suggesting that these cells are unnecessary for maintaining islet dynamics. Similarly, we investigated another functional subpopulation, β-cells with higher Ca2+ oscillation frequencies which could potentially act as pacemaker cells. When simulating the absence of 10% of these higher frequency cells, the global frequency of the islet was not significantly altered. These results indicate that small highly functional subpopulations are unable to drive islet function under normal conditions, but when targeted under hyperpolarizing conditions may cause dysfunction. Disclosure J.M. Dwulet: None. R.K. Benninger: None. Funding National Institutes of Health (R01DK106412, R01DK102950)

How Heterogeneity in Glucokinase and Gap-Junction Coupling Determines the Islet [Ca2+] Response

Understanding how cell subpopulations in a tissue impact overall system function is challenging. There is extensive heterogeneity among insulin-secreting β-cells within islets of Langerhans, including their insulin secretory response and gene expression profile, and this heterogeneity can be altered in diabetes. Several studies have identified variations in nutrient sensing between β-cells, including glucokinase (GK) levels, mitochondrial function, or expression of genes important for glucose metabolism. Subpopulations of β-cells with defined electrical properties can disproportionately influence islet-wide free-calcium activity ([Ca2+]) and insulin secretion via gap-junction electrical coupling. However, it is poorly understood how subpopulations of β-cells with altered glucose metabolism may impact islet function. To address this, we utilized a multicellular computational model of the islet in which a population of cells deficient in GK activity and glucose metabolism was imposed on the islet or in which β-cells were heterogeneous in glucose metabolism and GK kinetics were altered. This included simulating GK gene (GCK) mutations that cause monogenic diabetes. We combined these approaches with experimental models in which gck was genetically deleted in a population of cells or GK was pharmacologically inhibited. In each case, we modulated gap-junction electrical coupling. Both the simulated islet and the experimental system required 30–50% of the cells to have near-normal glucose metabolism, fewer than cells with normal KATP conductance. Below this number, the islet lacked any glucose-stimulated [Ca2+] elevations. In the absence of electrical coupling, the change in [Ca2+] was more gradual. As such, electrical coupling allows a large minority of cells with normal glucose metabolism to promote glucose-stimulated [Ca2+]. If insufficient numbers of cells are present, which we predict can be caused by a subset of GCK mutations that cause monogenic diabetes, electrical coupling exacerbates [Ca2+] suppression. This demonstrates precisely how metabolically heterogeneous β-cell populations interact to impact islet function.

37-OR: Distinct Functional Beta-Cell Subpopulations in Intact Islets of Langerhans

Glucose-stimulated insulin secretion is driven by the coordinated Ca2+ response in pancreatic islets following glucose elevation. In mouse islets, spatial and temporal Ca2+ dynamics are disproportionally controlled by subpopulations of β-cells, as identified by optogenetics. It is unknown which factors underlie this functional heterogeneity of β-cells in intact islets. Here, we tested if distinct β-cell subpopulations may be identified based on Ca2+ response to glucose elevation, and if their Ca2+ uptake efficiency, metabolic activity and electrical coupling are significantly different. We used MIP-CreER GCaMP6s mouse model which expresses Ca2+-sensitive GFP specifically in β-cells. We performed simultaneous Ca2+ dynamics and metabolic activity (NADH) response to [2-11] mM glucose elevation, along with gap junction permeability measurements in individual islets. We observed three functional subpopulations of β-cells distinct from an islet average: cells with 1) the fastest response to glucose elevation (1st responders); 2) the fastest 2nd phase oscillatory Ca2+ response (wave-initiators); and 3) the non-coordinated Ca2+ oscillations (un-coordinated). While 1st responders and wave-initiators were in different sub-regions of the islet, both subpopulations accumulated more Ca2+ during initial Ca2+ elevation (p=0.0403, p=0.0101) compared to the islet-average. Wave-initiators were more metabolically active (p=0.0223). The un-coordinated cells accumulated less Ca2+ (p<0.001) and were less metabolically active (p=0.0296). Gap junction permeability was not significantly different between subpopulations. In conclusion, the 1st phase Ca2+ uptake and 2nd phase Ca2+ oscillations emerge in spatially- and metabolically-distinct subregions of the islet. This is likely due to increased metabolic activity of the β-cells in these regions which leads to greater membrane depolarization and thus, disproportionately enhances the islet Ca2+response. (NIH R01 DK102950 R01 DK106412) Disclosure V. Kravets: None. R.A. Piscopio: None. W. Schleicher: None. R.K. Benninger: None. Funding National Institutes of Health

1772-P: Insulin Granule Biogenesis at the Golgi Requires a Metabolically-Regulated, Non-centrosomal Subpopulation of Microtubules

Insulin undergoes biogenesis through the ER and Golgi, ultimately leading to packaging into vesicles that are secreted in response to glucose. The movement between these membranes and the process of budding from the Golgi are vital steps. Previous work has found a role for microtubules (MTs) in these processes in both pancreatic β-cells and other cell types. Here, we show that the last stages of this process are regulated by a specific subpopulation of MTs that are non-centrosomal. Their formation, or nucleation, at the Golgi membrane is regulated by a glucose signal-transduction pathway through cAMP and its effector EPAC2. This effect is especially pronounced during the first, rapid phase of insulin secretion, during which EPAC2 levels increase at the sites of their nucleation. Preventing new nucleation of this specific population dramatically affects the pipeline of insulin production, storage and release. There is an overall reduction of β-cell insulin content, and the remaining insulin becomes retained within the Golgi, likely because of stalling of insulin-granule budding. This diminished granule availability substantially effects the level of both basal and stimulated insulin secretion, though not the ratio between these levels during the first wave. Constant dynamic maintenance of this network is therefore critical for normal β-cell physiology. This is the first demonstration that the biogenesis of post-Golgi carriers, particularly large secretory granules, requires ongoing nucleation/replenishment of this network. We are further looking at the role of MTs in β-cell secretory activity in intact islets. We have observed that MTs promote β-cell heterogeneity by restricting secretion from a specific β-cell sub-population, where insulin release can be activated upon disruption of the entire MT network by the drug nocodazole. Disclosure K. Trogden: None. C.V. Wright: None. G. Gu: None. I. Kaverina: None. Funding National Institutes of Health (1F32DK117529-01A1)