Diabetes Drug Discovery Research Articles

Directed differentiation of pancreatic δ cells from human pluripotent stem cells

Dysfunction of pancreatic δ cells contributes to the etiology of diabetes. Despite their important role, human δ cells are scarce, limiting physiological studies and drug discovery targeting δ cells. To date, no directed δ-cell differentiation method has been established. Here, we demonstrate that fibroblast growth factor (FGF) 7 promotes pancreatic endoderm/progenitor differentiation, whereas FGF2 biases cells towards the pancreatic δ-cell lineage via FGF receptor 1. We develop a differentiation method to generate δ cells from human stem cells by combining FGF2 with FGF7, which synergistically directs pancreatic lineage differentiation and modulates the expression of transcription factors and SST activators during endoderm/endocrine precursor induction. These δ cells display mature RNA profiles and fine secretory granules, secrete somatostatin in response to various stimuli, and suppress insulin secretion from in vitro co-cultured β cells and mouse β cells upon transplantation. The generation of human pancreatic δ cells from stem cells in vitro would provide an unprecedented cell source for drug discovery and cell transplantation studies in diabetes.

IP-GCN: A deep learning model for prediction of insulin using graph convolutional network for diabetes drug design

Insulin is a kind of protein that regulates the blood sugar levels is significant to prevent complications associated with diabetes, such as cancer, neurodegenerative disorders, cardiovascular disease, and kidney damage. Insulin protein (IP) plays an active role in drug discovery, medicine, and therapeutic methods. Unlike experimental protocols, computational predictors are fast and can predict IP accurately. This work introduces a model, called IP-GCN for IP prediction. The patterns from IP are extracted by K-spaced position specific scoring matrix (KS-PSSM) and the model training is accomplished using powerful deep learning tool, called Graph Convolutional Network (GCN). Additionally, we implemented Pseudo Amino Acid Composition (PseAAC) and Dipeptide Composition (DPC) for feature encoding to assess the predictive performance of GCN. To evaluate the efficacy of our novel approach, we compare its performance with well-known deep/machine learning algorithms such as Convolutional Neural Network (CNN), Extremely Randomized Tree (ERT), and Support Vector Machine (SVM). Predictive results demonstrate that the proposed predictor (IP-GCN) secured the best performance on both training and testing datasets. The novel computational would be fruitful in diabetes drug discovery and contributes to research for therapeutic interventions in various Insulin protein associated diseases.

High-Throughput Methods for the Discovery of Small Molecule Modulators of Pancreatic Beta-Cell Function and Regeneration.

The progression of type II diabetes (T2D) is characterized by a complex and highly variable loss of beta-cell mass, resulting in impaired insulin secretion. Many T2D drug discovery efforts aimed at discovering molecules that can protect or restore beta-cell mass and function have been developed using limited beta-cell lines and primary rodent/human pancreatic islets. Various high-throughput screening methods have been used in the context of drug discovery, including luciferase-based reporter assays, glucose-stimulated insulin secretion, and high-content screening. In this context, a cornerstone of small molecule discovery has been the use of immortalized rodent beta-cell lines. Although insightful, this usage has led to a more comprehensive understanding of rodent beta-cell proliferation pathways rather than their human counterparts. Advantages gained in enhanced physiological relevance are offered by three-dimensional (3D) primary islets and pseudoislets in contrast to monolayer cultures, but these approaches have been limited to use in low-throughput experiments. Emerging methods, such as high-throughput 3D islet imaging coupled with machine learning, aim to increase the feasibility of integrating 3D microtissue structures into high-throughput screening. This review explores the current methods used in high-throughput screening for small molecule modulators of beta-cell mass and function, a potentially pivotal strategy for diabetes drug discovery.

Revisiting the ethnomedicinal, ethnopharmacological, phytoconstituents and phytoremediation of the plant Solanum viarum Dunal.

Solanum viarum, a perennial shrub, belongs to the family Solanaceae known for its therapeutic value worldwide. As a beneficial remedial plant, it is used for treating several disorders like dysentery, diabetes, inflammation, and respiratory disorders. Phytochemistry studies of this plant have shown the presence of steroidal glycoside alkaloids, including solasonine, solasodine, and solamargine. It also has flavonoids, saponins, minerals, and other substances. S. viarum extracts and compounds possess a variety of pharmacological effects, including antipyretic, antioxidant, antibacterial, insecticidal, analgesic, and anticancer activity. Most of the heavy metals accumulate in the aerial sections of the plant which is considered a potential phytoremediation, a highly effective method for the treatment of metal-polluted soils. We emphasize the forgoing outline of S. viarum, as well as its ethnomedicinal and ethnopharmacological applications, the chemistry of its secondary metabolites, and heavy metal toxicity. In addition to describing the antitumor activity of compounds and their mechanisms of action isolated from S. viarum, liabilities are also explained and illustrated, including any significant chemical or metabolic stability and toxicity risks. A comprehensive list of information was compiled from Science Direct, PubMed, Google Scholar, and Web of Science using different key phrases (traditional use, ethnomedicinal plants, western Himalaya, Himachal Pradesh, S viarum, and biological activity). According to the findings of this study, we hope that this review will inspire further studies along the drug discovery pathway of the chemicals extracted from the plant of S. viarum. Further, this review shows that ethnopharmacological information from ethnomedicinal plants can be a promising approach to drug discovery for cancer and diabetes.

A colorimetric sensing strategy based on chitosan-stabilized platinum nanoparticles for quick detection of α-glucosidase activity and inhibitor screening.

α-Glucosidase (α-Glu) is implicated in the progression and pathogenesis of type II diabetes (T2D). In this study, we developed a rapid colorimetric technique using platinum nanoparticles stabilized by chitosan (Ch-PtNPs) to detect α-Glu activity and its inhibitor. The Ch-PtNPs facilitate the conversion of 3,3',5,5'-tetramethylbenzidine (TMB) into oxidized TMB (oxTMB) in the presence of dissolved O2. The catalytic hydrolysis of 2-O-α-D-glucopyranosyl-L-ascorbic acid (AA-2G) by α-Glu produces ascorbic acid (AA), which reduces oxTMB to TMB, leading to the fading of the blue color. However, the presence of α-Glu inhibitors (AGIs) hinders the generation of AA, allowing Ch-PtNPs to re-oxidize colorless TMB back to blue oxTMB. This unique phenomenon enables the colorimetric detection of α-Glu activity and AGIs. The linear range for α-Glu was found to be 0.1-1.0 U mL-1 and the detection limit was 0.026 U mL-1. Additionally, the half-maximal inhibition value (IC50) for acarbose, an α-Glu inhibitor, was calculated to be 0.4769mM. Excitingly, this sensing platform successfully detected α-Glu activity in human serum samples and effectively screened AGIs. These promising findings highlight the potential application of the proposed strategy in clinical diabetes diagnosis and drug discovery.

Automated high-throughput, high-content 3D imaging of intact pancreatic islets.

Diabetes poses a global health crisis affecting individuals across age groups and backgrounds, with a prevalence estimate of 700 million people worldwide by 2045. Current therapeutic strategies primarily rely on insulin therapy or hypoglycemic agents, which fail to address the root cause of the disease - the loss of pancreatic insulin-producing beta-cells. Therefore, bioassays that recapitulate intact islets are needed to enable drug discovery for beta-cell replenishment, protection from beta-cell loss, and islet-cell interactions. Standard cancer insulinoma beta-cell lines MIN6 and INS-1 have been used to interrogate beta-cell metabolic pathways and function but are not suitable for studying proliferative effects. Screening using primary human/rodent intact islets offers a higher level of physiological relevance to enhance diabetes drug discovery and development. However, the 3-dimensionality of intact islets have presented challenges in developing robust, high-throughput assays to detect beta-cell proliferative effects. Established methods rely on either dissociated islet cells plated in 2D monolayer cultures for imaging or reconstituted pseudo-islets formed in round bottom plates to achieve homogeneity. These approaches have significant limitations due to the islet cell dispersion process. To address these limitations, we have developed a robust, intact ex vivo pancreatic islet bioassay in 384-well format that is capable of detecting diabetes-relevant endpoints including beta-cell proliferation, chemoprotection, and islet spatial morphometrics.

In vitro and in silico inhibitory validation of Tapinanthus cordifolius leaf extract on alpha-glucosidase in the management of type 2 diabetes

The anti-diabetic properties of medicinal plants are becoming more widely recognized. To identify potential anti-diabetic agents for diabetes drug discovery, the current study used in vitro and in silico approaches to assess the alpha glucosidase inhibitory activities of Tapinanthus cordifolius (TC) leaf extracts and its bioactive components respectively. In vitro alpha glucosidase inhibitory assay was carried out on TC extract and fractions at various concentrations (50–1600 µg/mL), and the compounds with alpha glucosidase inhibitory potentials were identified using molecular docking, pharmacophore modelling, and molecular dynamics simulation. The crude extract exhibited the highest activity with an IC50 value of 248 μg/mL. Out of the 42 phytocompounds of the extract, α-Tocopherol-β-d-mannoside gave the lowest binding energy of −6.20 Kcal/mol followed by, 5-Ergosterol (−5.46 kcal/mol), Acetosyringone (−4.76 kcal/mol), and Benzaldehyde, 4-(Ethylthio)-2,5-Dimethoxy-(−4.67 kcal/mol). The selected compounds interacted with critical active site amino acid residues of alpha-glucosidase, just like the reference ligand. Molecular dynamics simulation revealed the formation of a stable complex between α-glucosidase and α-Tocopherol-β-d-mannoside, with ASP 564 sustaining two hydrogen bond connections for 99.9 and 75.0% of the simulation duration, respectively. Therefore, the selected TC compounds, especially α-Tocopherol-β-d-mannoside might be explored for future research and development as diabetic medicines. Communicated by Ramaswamy H. Sarma

Harnessing Human Pluripotent Stem Cell-Derived Pancreatic In Vitro Models for High-Throughput Toxicity Testing and Diabetes Drug Discovery.

The long-standing goals in diabetes research are to improve β-cell survival, functionality and increase β-cell mass. Current strategies to manage diabetes progression are still not ideal for sustained maintenance of normoglycemia, thereby increasing demand for the development of novel drugs. Available pancreatic cell lines, cadaveric islets, and their culture methods and formats, either 2D or 3D, allow for multiple avenues of experimental design to address diverse aims in the research setting. More specifically, these pancreatic cells have been employed in toxicity testing, diabetes drug screens, and with careful curation, can be optimized for use in efficient high-throughput screenings (HTS). This has since spearheaded the understanding of disease progression and related mechanisms, as well as the discovery of potential drug candidates which could be the cornerstone for diabetes treatment. This book chapter will touch on the pros and cons of the most widely used pancreatic cells, including the more recent human pluripotent stem cell-derived pancreatic cells, and HTS strategies (cell models, design, readouts) that can be used for the purpose of toxicity testing and diabetes drug discovery.

Comparative Study of The Effects of Confounding Factors on Improving Rat Pancreatic Islet Isolation Yield and Quality.

Objective Isolated pancreatic islets are valuable resources for a wide range of research, including cell replacement studies and cell-based platforms for diabetes drug discovery and disease modeling. Islet isolation is a complex and stepwise procedure aiming to obtain pure, viable, and functional islets for in vitro and in vivo studies. It should be noted that differences in rodent strains, gender, weight, and density gradients may affect the isolated islet’s properties. We evaluated the variables affecting the rat islet isolation procedure to reach the maximum islet yield and functionality, which would be critical for further studies on islet regenerative biology. Materials and Methods The present experimental study compared the yield and purity of isolated islets from non- diabetic rats of two different strains. Next, islet particle number (IPN) and islet equivalent (IEQ) were compared between males and females, and the weight range that yields the highest number of islets was investigated. Moreover, the influence of three different density gradients, namely Histopaque, Pancoll, and Lymphodex, on final isolated islets purity and yield were assessed. Finally, the viability and functionality of isolated islets were measured. Results The IEQ, IPN, and purity of isolated islets in 15 Lister hooded rats (LHRs) were significantly (P≤0.05) higher than those of the other strains. Male LHRs resulted in significantly higher IEQ compared to females (P≤0.05). Moreover, IPN and IEQ did not significantly vary among different weight groups. Also, the utilization of Histopaque and Pancoll leads to higher yield and purity. In vivo assessments of the isolated islets presented significantly reduced blood glucose percentage in the transplanted group on days 2-5 following transplantation. ConclusionBased on these results, an optimal protocol for isolating high-quality rat islets with a constant yield, purity, and function has been established as an essential platform for developing diabetes research.

Deducing Insulin-Producing Cells from Goat Adipose Tissue-Derived Mesenchymal Stem Cells.

Mesenchymal stem cell is a potent tool for regenerative medicine against control of incurable diseases in human and animals. Diabetes mellitus is one such condition marked with the blood glucose is high due to lack of insulin (INS) hormone secreted by the pancreatic cells. Rare, but sporadic, cases of dysfunctional pancreatic cells in goat as well as the promises of stem cell therapy as an off-the-shelf medicine prompted us to explore the potential of adipose-derived goat mesenchymal stem cells (AD-MSCs) to transdifferentiate into pancreatic islet-like cells. We isolated, in vitro cultured, and characterized the AD-MSCs by expression of MSC-specific markers and differentiation into multiple mesodermal lineage cells. The characterized AD-MSCs were in vitro transdifferentiated into INS-producing islet-like cells using a cocktail of glucose, nicotinamide, activin-A, exendin-4, pentagastrin, retinoic acid, and mercaptoethanol in 3 weeks. The transdifferentiated islet-like cells demonstrated the expression of pancreatic endoderm-specific transcripts PDX1, NGN3, PAX6, PAX4, ISL1, and GLUT2 as well as protein expression of pancreatic and duodenal homeobox 1 (PDX1), INS, and Islets 1 (ISL1). The islet-like cells also demonstrated the significant glucose-dependent INS release with respect to the course of transdifferentiation regime. The study envisaged to create the building material for basic research into mechanism of glucose homeostasis, which may pave road for developments in diabetes drug discovery and regenerative therapies.

402.1: Towards a GMP-Compliant Protocol for the Differentiation of Human Pluripotent Stem Cells to Beta-like Cells for the Treatment of Type 1 Diabetes

Background: β-cell replacement therapy by allogeneic pancreas or islet transplantation is a promising approach for patients with type 1 diabetes. However, there is a scarcity of organ donors. The generation of insulin-producing pancreatic β-cells from human pluripotent stem cells (hPSC) in vitro would provide an unlimited cell source for drug discovery and cell replacement therapy for diabetes. Here we aim to generate β-cells under GMP (Good Manufacturing Practice)-compliant conditions that can be used for clinical application. Methods: We applied a modified seven-stage (30-day) differentiation protocol to generate hPSC-derived insulin-producing β-like cells in a 3D microwell culture system. Next, in order to scale up the production of hPSC-derived β-cells, we adapted the protocol to spinner flask culture. Differentiation was assessed by qPCR, immunocytochemistry and flowcytometry for stage-specific marker expression. β-cell function was evaluated in vitro by GSIS (Glucose-Stimulated Insulin Secretion), and in vivo by intraperitoneal glucose tolerance tests after transplantation of stage-7 cell clusters in immunodeficient mice and human C-peptide secretion was determined by ELISA. Results: In the microwell set-up, cells acquired a definitive endoderm phenotype at stage 1 (day 3), characterized by expression of SOX17 (87.2% ± 4.6; n=5), FOXA2 (82.8% ± 4.6; n=3), co-expression of c-KIT and CXCR4 (93.3% ± 5.6; n=4), and silencing of pluripotency marker OCT4 (2.8% ± 6; n=5). At the end of stage 4 (day 12), pancreatic progenitor cells were identified by the co-expression of PDX1/NKX6.1 (46.7% ± 3.5; n=3). Finally, at the end of stage 7 (day 30), C-peptide-positive β-like cells (49.5% ± 10.5; n=3) and glucagon-positive α-like cells (18.4%± 6.1; n=3) were present. The stimulation index upon exposure to glucose was 4.4 ± 3.1(n=5). Following transplantation of day-30 clusters into mice, stimulated human C-peptide levels reached 46 pmol/L (n=21), 70.5 pmol/L (n=19) and 327.4 pmol/L (n=11) at day 14, 28 and 60 respectively, indicating further maturation of the cells in vivo after transplantation. Next, we scaled up the cell culture in disposable spinner flasks, and obtained comparable differentiation efficiency. Conclusion: We can generate functional hPSCs-derived β-like cells in GMP-compliant conditions in vitro. We will apply these protocols on a clinical-grade PSC line that is currently in expansion (banking) in the GMP facility of our institute. hPSCs-derived β-like cells are a promising future alternative to donor islets for the treatment of type 1 diabetes.

Characteristics of the New Insulin-Resistant Zebrafish Model.

Insulin resistance, which occurs when insulin levels are sufficiently high over a prolonged period, causing the cells to fail to respond normally to the hormone. As a system for insulin resistance and diabetes drug development, insulin-resistant rodent models have been clearly established, but there is a limitation to high-throughput drug screening. Recently, zebrafish have been identified as an excellent system for drug discovery and identification of therapeutic targets, but studies on insulin resistance models have not been extensively performed. Therefore, we aimed to make a rapid insulin-resistant zebrafish model that complements the existing rodent models. To establish this model, zebrafish were treated with 10 μM insulin for 48 h. This model showed characteristics of insulin-resistant disease such as damaged pancreatic islets. Then we confirmed the recovery of the pancreatic islets after pioglitazone treatment. In addition, it was found that insulin-resistant drugs have as significant an effect in zebrafish as in humans, and these results proved the value of the zebrafish insulin resistance model for drug selection. In addition, RNA sequencing was performed to elucidate the mechanism involved. KEGG pathway enrichment analysis of differentially expressed genes showed that insulin resistance altered gene expression due to the MAPK signaling and calcium signaling pathways. This model demonstrates the utility of the zebrafish model for drug testing and drug discovery in insulin resistance and diabetes.

Live-cell imaging of glucose-induced metabolic coupling of \u03b2 and \u03b1\xa0cell metabolism in health and type\xa02 diabetes

Type 2 diabetes is characterized by β and α cell dysfunction. We used phasor-FLIM (Fluorescence Lifetime Imaging Microscopy) to monitor oxidative phosphorylation and glycolysis in living islet cells before and after glucose stimulation. In healthy cells, glucose enhanced oxidative phosphorylation in β cells and suppressed oxidative phosphorylation in α cells. In Type 2 diabetes, glucose increased glycolysis in β cells, and only partially suppressed oxidative phosphorylation in α cells. FLIM uncovers key perturbations in glucose induced metabolism in living islet cells and provides a sensitive tool for drug discovery in diabetes.

Pinocembrin and its linolenoyl ester derivative induce wound healing activity in HaCaT cell line potentially involving a GPR120/FFA4 mediated pathway

Wound healing represents an urgent need from the clinical point of view. Several diseases result in wound conditions which are difficult to treat, such as in the case of diabetic foot ulcer. Starting from there, the medicinal research has focused on various targets over the years, including GPCRs as new wound healing drug targets. In line with this, GPR120, known to be an attractive target in type 2 diabetes drug discovery, was studied to finalize the development of new wound healing agents. Pinocembrin (HW0) was evaluated as a suitable compound for interacting with GPR120, and was hybridized with fatty acids, which are known endogenous GPR120 ligands, to enhance the wound healing potential and GPR120 interactions. HW0 and its 7-linolenoyl derivative (HW3) were found to be innovative wound healing agents. Immunofluorescence and functional assays suggested that their activity was mediated by GPR120, and docking simulations showed that the compounds could share the same pocket occupied by the known GPR120 agonist, TUG-891.

Therapeutic Potential of Peptides Derived from Animal Venoms: Current Views and Emerging Drugs for Diabetes.

The therapeutic potential of venom-derived drugs is evident today. Currently, several significant drugs are FDA approved for human use that descend directly from animal venom products, with others having undergone, or progressing through, clinical trials. In addition, there is growing awareness of the important cosmeceutical application of venom-derived products. The success of venom-derived compounds is linked to their increased bioactivity, specificity and stability when compared to synthetically engineered compounds. This review highlights advancements in venom-derived compounds for the treatment of diabetes and related disorders. Exendin-4, originating from the saliva of Gila monster lizard, represents proof-of-concept for this drug discovery pathway in diabetes. More recent evidence emphasises the potential of venom-derived compounds from bees, cone snails, sea anemones, scorpions, snakes and spiders to effectively manage glycaemic control. Such compounds could represent exciting exploitable scaffolds for future drug discovery in diabetes, as well as providing tools to allow for a better understanding of cell signalling pathways linked to insulin secretion and metabolism.

Recent Advances in the Generation of β-Cells from Induced Pluripotent Stem Cells as a Potential Cure for Diabetes Mellitus.

Diabetes mellitus (DM) is a group of metabolic disorders characterized by high blood glucose levels due to insufficient insulin secretion, insulin action, or both. The present-day solution to diabetes mellitus includes regular administration of insulin, which brings about many medical complications in diabetic patients. Although islet transplantation from cadaveric subjects was proposed to be a permanent cure, the increased risk of infections, the need for immunosuppressive drugs, and their unavailability had restricted its use. To overcome this, the generation of renewable and transplantable β-cells derived from autologous induced pluripotent stem cells (iPSCs) has gained enormous interest as a potential therapeutic strategy to treat diabetes mellitus permanently. To date, extensive research has been undertaken to derive transplantable insulin-producing β-cells (iβ-cells) from iPSCs in vitro by recapitulating the in vivo developmental process of the pancreas. This in vivo developmental process relies on transcription factors, signaling molecules, growth factors, and culture microenvironment. This review highlights the various factors facilitating the generation of mature β-cells from iPSCs. Moreover, this review also describes the generation of pancreatic progenitors and β-cells from diabetic patient-specific iPSCs, exploring the potential of the diabetes disease model and drug discovery. In addition, the applications of genome editing strategies have also been discussed to achieve patient-specific diabetes cell therapy. Last, we have discussed the current challenges and prospects of iPSC-derived β-cells to improve the relative efficacy of the available treatment of diabetes mellitus.

3D quantification of changes in pancreatic islets in mouse models of diabetes type I and II.

ABSTRACTDiabetes is characterized by rising levels of blood glucose and is often associated with a progressive loss of insulin-producing beta cells. Recent studies have demonstrated that it is possible to regenerate new beta cells through proliferation of existing beta cells or trans-differentiation of other cell types into beta cells, raising hope that diabetes can be cured through restoration of functional beta cell mass. Efficient quantification of beta cell mass and islet characteristics is needed to enhance drug discovery for diabetes. Here, we report a 3D quantitative imaging platform for unbiased evaluation of changes in islets in mouse models of type I and II diabetes. To determine whether the method can detect pharmacologically induced changes in beta cell volume, mice were treated for 14 days with either vehicle or the insulin receptor antagonist S961 (2.4 nmol/day) using osmotic minipumps. Mice treated with S961 displayed increased blood glucose and insulin levels. Light-sheet imaging of insulin and Ki67 (also known as Mki67)-immunostained pancreata revealed a 43% increase in beta cell volume and 21% increase in islet number. S961 treatment resulted in an increase in islets positive for the cell proliferation marker Ki67, suggesting that proliferation of existing beta cells underlies the expansion of total beta cell volume. Using light-sheet imaging of a non-obese diabetic mouse model of type I diabetes, we also characterized the infiltration of CD45 (also known as PTPRC)-labeled leukocytes in islets. At 14 weeks, 40% of the small islets, but more than 80% of large islets, showed leukocyte infiltration. These results demonstrate how quantitative light-sheet imaging can capture changes in individual islets to help pharmacological research in diabetes.

Enhanced differentiation of human pluripotent stem cells into pancreatic endocrine cells in 3D culture by inhibition of focal adhesion kinase

BackgroundGeneration of insulin-producing cells from human pluripotent stem cells (hPSCs) in vitro would be useful for drug discovery and cell therapy in diabetes. Three-dimensional (3D) culture is important for the acquisition of mature insulin-producing cells from hPSCs, but the mechanism by which it promotes β cell maturation is poorly understood.MethodsWe established a stepwise method to induce high-efficiency differentiation of human embryonic stem cells (hESCs) into mature monohormonal pancreatic endocrine cells (PECs), with the last maturation stage in 3D culture. To comprehensively compare two-dimensional (2D) and 3D cultures, we examined gene expression, pancreas-specific markers, and functional characteristics in 2D culture-induced PECs and 3D culture-induced PECs. The mechanisms were considered from the perspectives of cell–cell and cell–extracellular matrix interactions which are fundamentally different between 2D and 3D cultures.ResultsThe expression of the pancreatic endocrine-specific transcription factors PDX1, NKX6.1, NGN3, ISL1, and PAX6 and the hormones INS, GCG, and SST was significantly increased in 3D culture-induced PECs. 3D culture yielded monohormonal endocrine cells, while 2D culture-induced PECs co-expressed INS and GCG or INS and SST or even expressed all three hormones. We found that focal adhesion kinase (FAK) phosphorylation was significantly downregulated in 3D culture-induced PECs, and treatment with the selective FAK inhibitor PF-228 improved the expression of β cell-specific transcription factors in 2D culture-induced PECs. We further demonstrated that 3D culture may promote endocrine commitment by limiting FAK-dependent activation of the SMAD2/3 pathway. Moreover, the expression of the gap junction protein Connexin 36 was much higher in 3D culture-induced PECs than in 2D culture-induced PECs, and inhibition of the FAK pathway in 2D culture increased Connexin 36 expression.ConclusionWe developed a strategy to induce differentiation of monohormonal mature PECs from hPSCs and found limited FAK-dependent activation of the SMAD2/3 pathway and unregulated expression of Connexin 36 in 3D culture-induced PECs. This study has important implications for the generation of mature, functional β cells for drug discovery and cell transplantation therapy for diabetes and sheds new light on the signaling events that regulate endocrine specification.

2107-P: A Human Pancreatic Spheroid Platform for Toxicology and Diabetes Research

Diabetes mellitus (DM) is a prevalent and chronic metabolic disorder that affects more than 300 million patients in the world. One of the major obstacles in DM is the lack of in vitro models that can capture the physiological features of the in vivo environment. Therefore, to identify new treatments for DM there is an increasing demand for functional in vitro pancreatic islet models in which the cellular microenvironment, consistency and long-term culture is more fully preserved. More recently, functional beta-cells derived from human induced pluripotent stem cells (hiPSCs) have gained prominence as an enticing system for the study of DM as a human, tissue-specific model to model the disease and identify potential therapeutic intervention. Here we describe and characterize a novel micro-engineered 384 well plate platform in which each well contains a single size-controlled hiPSC-pancreatic islet equivalent spheroid that emulates key characteristics of adult human pancreas. Gene expression and immunofluorescence analysis indicated that these islet-equivalents express key markers of pancreas cellular identity such as the master pancreatic transcription factor PDX-1, glucose-sensing and insulin-secreting genes such as GLUT2, ABCC8 and SYT4, and importantly, secreted proteins produced in mature humans islets, like Insulin, glucagon and somatostatin. RNAseq data indicated larger transcriptional consistency from different batches of microPancreas production than traditional cadaveric islet samples. In addition, cells show glucose dependent stimulated insulin secretion (GSIS), highlighting the functionality of the platform. Altogether, we describe a novel human pancreatic platform applicable to gene-expression, imaging and insulin-secretion studies as a reliable research source for diabetes drug discovery, disease modeling and toxicology applications. Disclosure S. Mora-Castilla: Employee; Self; StemoniX. B. Gaertner: Employee; Self; StemoniX. I. Barbosa-Farias: Employee; Self; StemoniX. W. Si: Employee; Self; StemoniX. F. Zanella: Employee; Self; StemoniX.

Lead Optimization Resources in Drug Discovery for Diabetes.

Diabetes, defined as a chronic metabolic syndrome, exhibits global prevalence and phenomenal rise worldwide. The rising incidence accounts for a global health crisis, demonstrating a profound effect on low and middle-income countries, particularly people with limited healthcare facilities. Highlighting the prevalence of diabetes and its socio-economic implications on the population across the globe, the article aimed to address the emerging significance of computational biology in drug designing and development, pertaining to identification and validation of lead molecules for diabetes treatment. The drug discovery programs have shifted the focus on in silico prediction strategies minimizing prolonged clinical trials and expenses. Despite technological advances and effective drug therapies, the fight against life-threatening, disabling disease has witnessed multiple challenges. The lead optimization resources in computational biology have transformed the research on the identification and optimization of anti-diabetic lead molecules in drug discovery studies. The QSAR approaches and ADMET/Toxicity parameters provide significant evaluation of prospective "drug-like" molecules from natural sources. The science of computational biology has facilitated the drug discovery and development studies and the available data may be utilized in a rational construction of a drug 'blueprint' for a particular individual based on the genetic organization. The identification of natural products possessing bioactive properties as well as their scientific validation is an emerging prospective approach in antidiabetic drug discovery.