RORB and RORC associate with human islet dysfunction and inhibit insulin secretion in INS-1 cells

Liver kinase B1 (LKB1) regulates the epigenetic landscape of mouse pancreatic beta cells

Liver kinase B1 (LKB1/STK11) is an important regulator of pancreatic β-cell identity and function. Elimination of Lkb1 from the β-cell results in improved glucose-stimulated insulin secretion and is accompanied by profound changes in gene expression, including the upregulation of several neuronal genes. The mechanisms through which LKB1 controls gene expression are, at present, poorly understood. Here, we explore the impact of β cell-selective deletion of Lkb1 on chromatin accessibility in mouse pancreatic islets. To characterize the role of LKB1 in the regulation of gene expression at the transcriptional level, we combine these data with a map of islet active transcription start sites and histone marks. We demonstrate that LKB1 elimination from β-cells results in widespread changes in chromatin accessibility, correlating with changes in transcript levels. Changes occurred in hundreds of promoter and enhancer regions, many of which were close to neuronal genes. We reveal that dysregulated enhancers are enriched in binding motifs for transcription factors (TFs) important for β-cell identity, such as FOXA, MAFA or RFX6, and we identify microRNAs (miRNAs) that are regulated by LKB1 at the transcriptional level. Overall, our study provides important new insights into the epigenetic mechanisms by which LKB1 regulates β-cell identity and function.

Liver kinase B1 (LKB1) regulates the epigenetic landscape of mouse pancreatic beta cells

Liver kinase B1 (LKB1/STK11) is an important regulator of pancreatic β-cell identity and function. Elimination of Lkb1 from the β-cell results in improved glucose-stimulated insulin secretion and is accompanied by profound changes in gene expression, including the upregulation of several neuronal genes. The mechanisms through which LKB1 controls gene expression are, at present, poorly understood. Here, we explore the impact of β cell- selective deletion of Lkb1 on chromatin accessibility in mouse pancreatic islets. To characterize the role of LKB1 in the regulation of gene expression at the transcriptional level, we combine these data with a map of islet active transcription start sites and histone marks. We demonstrate that LKB1 elimination from β-cells results in widespread changes in chromatin accessibility, correlating with changes in transcript levels. Changes occurred in hundreds of promoter and enhancer regions, many of which were close to neuronal genes. We reveal that dysregulated enhancers are enriched in binding motifs for transcription factors important for β-cell identity, such as FOXA, MAFA or RFX6 and we identify microRNAs (miRNAs) that are regulated by LKB1 at the transcriptional level. Overall, our study provides important new insights into the epigenetic mechanisms by which LKB1 regulates β-cell identity and function.

Unraveling the significance of PPP1R1A gene in pancreatic β-cell function: A study in INS-1 cells and human pancreatic islets

BACKGROUND AND AIMS

The protein phosphatase 1 regulatory inhibitor subunit 1A (PPP1R1A) has been linked with insulin secretion and diabetes mellitus. Yet, its full significance in pancreatic β-cell function remains unclear. This study aims to elucidate the role of the PPP1R1A gene in β-cell biology using human pancreatic islets and rat INS-1 (832/13) cells.

RESULTS

Disruption of Ppp1r1a in INS-1 cells was associated with reduced insulin secretion and impaired glucose uptake; however, cell viability, ROS, apoptosis or proliferation were intact. A significant downregulation of crucial β-cell function genes such as Ins1, Ins2, Pcsk1, Cpe, Pdx1, Mafa, Isl1, Glut2, Snap25, Vamp2, Syt5, Cacna1a, Cacna1d and Cacnb3, was observed upon Ppp1r1a disruption. Furthermore, silencing Pdx1 in INS-1 cells altered PPP1R1A expression, indicating that PPP1R1A is a target gene for PDX1. Treatment with rosiglitazone increased Ppp1r1a expression, while metformin and insulin showed no effect. RNA-seq analysis of human islets revealed high PPP1R1A expression, with α-cells showing the highest levels compared to other endocrine cells. Muscle tissues exhibited greater PPP1R1A expression than pancreatic islets, liver, or adipose tissues. Co-expression analysis revealed significant correlations between PPP1R1A and genes associated with insulin biosynthesis, exocytosis machinery, and intracellular calcium transport. Overexpression of PPP1R1A in human islets augmented insulin secretion and upregulated protein expression of Insulin, MAFA, PDX1, and GLUT1, while silencing of PPP1R1A reduced Insulin, MAFA, and GLUT1 protein levels.

CONCLUSION

This study provides valuable insights into the role of PPP1R1A in regulating β-cell function and glucose homeostasis. PPP1R1A presents a promising opportunity for future therapeutic interventions.

Disrupting of family with sequence similarity 105, member A (Fam105a) deteriorates pancreatic β-cell physiology and insulin secretion in INS-1 cells

The role of "Family with sequence similarity 105, member A" (FAM105A) in pancreatic β-cell function in relation to type 2 diabetes mellitus (T2D) is not fully understood. To address this issue, various molecular and functional experiments were conducted on primary human islets and INS-1 cells. RNA-seq expression analysis showed that FAM105A is highly expressed in human islets and its expression is reduced in diabetic islets compared to healthy islets. FAM105A expression correlated negatively with HbA1c levels and body mass index (BMI). Co-expression analysis showed a significant correlation between FAM105A with PDX1, GCK, GLUT1 and INSR, but not the INS gene. Silencing of Fam105a impaired insulin release, content, glucose uptake, and mitochondria ATP content but did not affect cell viability, reactive oxygen species (ROS) or apoptosis levels. Silencing of Fam105a was associated with reduced Pdx1 and Glut2 expression at mRNA and protein levels. RNA-seq analysis of dysregulated genes in Fam105a-silenced cells showed an overall downregulation of gene expression in β-cells and insulin secretion pathway. Disrupting Pdx1 did not affect Fam105a expression in INS-1 cells. Overall, the results suggest that FAM105A plays an important role in pancreatic β-cells biology and may be involved in the development of T2D.

Propensity scores as a novel method to guide sample allocation and minimize batch effects during the design of high throughput experiments

BACKGROUND

We developed a novel approach to minimize batch effects when assigning samples to batches. Our algorithm selects a batch allocation, among all possible ways of assigning samples to batches, that minimizes differences in average propensity score between batches. This strategy was compared to randomization and stratified randomization in a case-control study (30 per group) with a covariate (case vs control, represented as β1, set to be null) and two biologically relevant confounding variables (age, represented as β2, and hemoglobin A1c (HbA1c), represented as β3). Gene expression values were obtained from a publicly available dataset of expression data obtained from pancreas islet cells. Batch effects were simulated as twice the median biological variation across the gene expression dataset and were added to the publicly available dataset to simulate a batch effect condition. Bias was calculated as the absolute difference between observed betas under the batch allocation strategies and the true beta (no batch effects). Bias was also evaluated after adjustment for batch effects using ComBat as well as a linear regression model. In order to understand performance of our optimal allocation strategy under the alternative hypothesis, we also evaluated bias at a single gene associated with both age and HbA1c levels in the 'true' dataset (CAPN13 gene).

RESULTS

Pre-batch correction, under the null hypothesis (β1), maximum absolute bias and root mean square (RMS) of maximum absolute bias, were minimized using the optimal allocation strategy. Under the alternative hypothesis (β2 and β3 for the CAPN13 gene), maximum absolute bias and RMS of maximum absolute bias were also consistently lower using the optimal allocation strategy. ComBat and the regression batch adjustment methods performed well as the bias estimates moved towards the true values in all conditions under both the null and alternative hypotheses. Although the differences between methods were less pronounced following batch correction, estimates of bias (average and RMS) were consistently lower using the optimal allocation strategy under both the null and alternative hypotheses.

CONCLUSIONS

Our algorithm provides an extremely flexible and effective method for assigning samples to batches by exploiting knowledge of covariates prior to sample allocation.

Utilizing Variants Identified with Multiple Genome-Wide Association Study Methods Optimizes Genomic Selection for Growth Traits in Pigs

Improving the prediction accuracies of economically important traits in genomic selection (GS) is a main objective for researchers and breeders in the livestock industry. This study aims at utilizing potentially functional SNPs and QTLs identified with various genome-wide association study (GWAS) models in GS of pig growth traits. We used three well-established GWAS methods, including the mixed linear model, Bayesian model and meta-analysis, as well as 60K SNP-chip and whole genome sequence (WGS) data from 1734 Yorkshire and 1123 Landrace pigs to detect SNPs related to four growth traits: average daily gain, backfat thickness, body weight and birth weight. A total of 1485 significant loci and 24 candidate genes which are involved in skeletal muscle development, fatty deposition, lipid metabolism and insulin resistance were identified. Compared with using all SNP-chip data, GS with the pre-selected functional SNPs in the standard genomic best linear unbiased prediction (GBLUP), and a two-kernel based GBLUP model yielded average gains in accuracy by 4 to 46% (from 0.19 ± 0.07 to 0.56 ± 0.07) and 5 to 27% (from 0.16 ± 0.06 to 0.57 ± 0.05) for the four traits, respectively, suggesting that the prioritization of preselected functional markers in GS models had the potential to improve prediction accuracies for certain traits in livestock breeding.

Gene expression analysis in endometriosis: Immunopathology insights, transcription factors and therapeutic targets

Background

Endometriosis is recognized as an estrogen-dependent inflammation disorder, estimated to affect 8%-15% of women of childbearing age. Currently, the etiology and pathogenesis of endometriosis are not completely clear. Underlying mechanism for endometriosis is still under debate and needs further exploration. The involvement of transcription factors and immune mediations may be involved in the pathophysiological process of endometriosis, but the specific mechanism remains to be explored. This study aims to investigate the underlying molecular mechanisms in endometriosis.

Methods

The gene expression profile of endometriosis was obtained from the gene expression omnibus (GEO) database. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were applied to the endometriosis GSE7305 datasets. Cibersort and MCP-counter were used to explore the immune response gene sets, immune response pathway, and immune environment. Differentially expressed genes (DEGs) were identified and screened. Common biological pathways were being investigated using the kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. Transcription factors were from The Human Transcription Factors. The least absolute shrinkage and selection operator (Lasso) model identified four differential expressions of transcription factors (AEBP1, HOXB6, KLF2, and RORB). Their diagnostic value was calculated by receiver operating characteristic (ROC) curve analysis and validated in the validation cohort (GSE11691, GSE23339). By constructing the interaction network of crucial transcription factors, weighted gene coexpression network analysis (WGCNA) was used to search for key module genes. Metascape was used for enrichment analysis of essential module genes and obtained HOXB6, KLF2. The HOXB6 and KLF2 were further verified as the only two intersection genes according to Support Vector Machine Recursive Feature Elimination (SVM-RFE) and random forest models. We constructed ceRNA (lncRNA-miRNA-mRNA) networks with four potential transcription factors. Finally, we performed molecular docking for goserelin and dienogest with four transcription factors (AEBP1, HOXB6, KLF2, and RORB) to screen potential drug targets.

Results

Immune and metabolic pathways were enriched in GSVA and GSEA. In single sample gene set enrichment analysis (ssGSEA), most immune infiltrating cells, immune response gene sets, and immune response pathways are differentially expressed between endometriosis and non-endometriosis. Twenty-seven transcription factors were screened from differentially expressed genes. Most of the twenty-seven transcription factors were correlated with immune infiltrating cells, immune response gene sets and immune response pathways. Furthermore, Adipocyte enhancer binding protein 1 (AEBP1), Homeobox B6 (HOXB6), Kruppel Like Factor 2 (KLF2) and RAR Related Orphan Receptor B (RORB) were selected out from twenty-seven transcription factors. ROC analysis showed that the four genes had a high diagnostic value for endometriosis. In addition, KLF2 and HOXB6 were found to play particularly important roles in multiple modules (String, WGCNA, SVM-RFE, random forest) on the gene interaction network. Using the ceRNA network, we found that NEAT1 may regulate the expressions of AEBP1, HOXB6 and RORB, while X Inactive Specific Transcript (XIST) may control the expressions of HOXB6, RORB and KLF2. Finally, we found that goserelin and dienogest may be potential drugs to regulate AEBP1, HOXB6, KLF2 and RORB through molecular docking.

Conclusions

AEBP1, HOXB6, KLF2, and RORB may be potential biomarkers for endometriosis. Two of them, KLF2 and HOXB6, are critical molecules in the gene interaction network of endometriosis. Discovered by molecular docking, AEBP1, HOXB6, KLF2, and RORB are targets for goserelin and dienogest.

Reduced Retinoic Acid Receptor Beta (Rarβ) Affects Pancreatic β-Cell Physiology

Various studies have suggested a link between vitamin A (VA), all-trans-retinol, and type 2 diabetes (T2D). However, the functional role/expression of vitamin A receptors (Rarα, β, and γ) in pancreatic β-cells is not clear yet. Accordingly, we performed a series of bioinformatics, molecular and functional experiments in human islet and INS-1 cells to evaluate the role of Rarβ on insulin secretion and pancreatic β-cell function. Microarray and RNA-sequencing (RAN-seq) expression analysis showed that RARα, β, and γ are expressed in human pancreatic islets. RNA-seq expression of RARβ in diabetic/hyperglycemic human islets (HbA1c ≥ 6.3%) revealed a significant reduction (p = 0.004) compared to nondiabetic/normoglycemic cells (HbA1c < 6%). The expression of RARβ with INS and PDX1 showed inverse association, while positive correlations were observed with INSR and HbA1c levels. Exploration of the T2D knowledge portal (T2DKP) revealed that several genetic variants in RARβ are associated with BMI. The most associated variant is rs6804842 (p = 1.2 × 10−25). Silencing of Rarβ in INS-1 cells impaired insulin secretion without affecting cell viability or apoptosis. Interestingly, reactive oxygen species (ROS) production levels were elevated and glucose uptake was reduced in Rarβ-silenced cells. mRNA expression of Ins1, Pdx1, NeuroD1, Mafa, Snap25, Vamp2, and Gck were significantly (p < 0.05) downregulated in Rarβ-silenced cells. For protein levels, Pro/Insulin, PDX1, GLUT2, GCK, pAKT/AKT, and INSR expression were downregulated considerably (p < 0.05). The expression of NEUROD and VAMP2 were not affected. In conclusion, our results indicate that Rarβ is an important molecule for β-cell function. Hence, our data further support the potential role of VA receptors in the development of T2D.

Adapting Physiology in Functional Human Islet Organogenesis

Generation of three-dimensional (3D)-structured functional human islets is expected to be an alternative cell source for cadaveric human islet transplantation for the treatment of insulin-dependent diabetes. Human pluripotent stem cells (hPSCs), such as human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs), offer infinite resources for newly synthesized human islets. Recent advancements in hPSCs technology have enabled direct differentiation to human islet-like clusters, which can sense glucose and secrete insulin, and those islet clusters can ameliorate diabetes when transplanted into rodents or non-human primates (NHPs). However, the generated hPSC-derived human islet-like clusters are functionally immature compared with primary human islets. There remains a challenge to establish a technology to create fully functional human islets in vitro, which are functionally and transcriptionally indistinguishable from cadaveric human islets. Understanding the complex differentiation and maturation pathway is necessary to generate fully functional human islets for a tremendous supply of high-quality human islets with less batch-to-batch difference for millions of patients. In this review, I summarized the current progress in the generation of 3D-structured human islets from pluripotent stem cells and discussed the importance of adapting physiology for in vitro functional human islet organogenesis and possible improvements with environmental cues.

Persistent organic pollutants and β-cell toxicity: a comprehensive review

Persistent organic pollutants (POPs) are a diverse family of contaminants that show widespread global dispersion and bioaccumulation. Humans are continuously exposed to POPs through diet, air particles, and household and commercial products; POPs are consistently detected in human tissues, including the pancreas. Epidemiological studies show a modest but consistent correlation between exposure to POPs and increased diabetes risk. The goal of this review is to provide an overview of epidemiological evidence and an in-depth evaluation of the in vivo and in vitro evidence that POPs cause β-cell toxicity. We review evidence for six classes of POPs: dioxins, polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), organophosphate pesticides (OPPs), flame retardants, and per- and polyfluoroalkyl substances (PFAS). The available data provide convincing evidence implicating POPs as a contributing factor driving impaired glucose homeostasis, β-cell dysfunction, and altered metabolic and oxidative stress pathways in islets. These findings support epidemiological data showing that POPs increase diabetes risk and emphasize the need to consider the endocrine pancreas in toxicity assessments. Our review also highlights significant gaps in the literature assessing islet-specific endpoints after both in vivo and in vitro POP exposure. In addition, most rodent studies do not consider the impact of biological sex or secondary metabolic stressors in mediating the effects of POPs on glucose homeostasis and β-cell function. We discuss key gaps and limitations that should be assessed in future studies.

Heme Oxygenase-1 (HMOX-1) and inhibitor of differentiation proteins (ID1, ID3) are key response mechanisms against iron-overload in pancreatic β-cells

Iron overload promotes the generation of reactive oxygen species (ROS). Pancreatic β-cells can counter oxidative stress through multiple anti-oxidant responses. Herein, RNA-sequencing was used to describe the expression profile of iron regulatory genes in human islets with or without diabetes. Functional experiments including siRNA silencing, qPCR, western blotting, cell viability, ELISA and RNA-sequencing were performed as means of identifying the genetic signature of the protective response following iron overload-induced stress in human islets and INS-1. FTH1 and FTL genes were highly expressed in human islets and INS-1 cells, while hepcidin (HAMP) was low. FXN, DMT1 and FTHL1 genes were differentially expressed in diabetic islets compared to control. Silencing of Hamp in INS-1 cells impaired insulin secretion and influenced the expression of β-cell key genes. RNA-sequencing analysis in iron overloaded INS-1 cells identified Id1 and Id3 as the top down-regulated genes, while Hmox1 was the top upregulated. Expression of ID1, ID3 and HMOX1 was validated at the protein level in INS-1 cells and human islets. Differentially expressed genes (DEGs) were enriched for TGF-β, regulating stem cells, ferroptosis, and HIF-1 signaling. Hmox1-silenced cells treated with FAC elevated the expression of Id1 and Id3 expression than untreated cells. Our findings suggest that HMOX1, ID1 and ID3 define the response mechanism against iron-overload-induced stress in β-cells.

Prolonged Low-Dose Dioxin Exposure Impairs Metabolic Adaptability to High-Fat Diet Feeding in Female but Not Male Mice

CONTEXT

Human studies consistently show an association between exposure to persistent organic pollutants, including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD, aka "dioxin"), and increased diabetes risk. We previously showed that a single high-dose TCDD exposure (20 µg/kg) decreased plasma insulin levels in male and female mice in vivo, but effects on glucose homeostasis were sex-dependent.

OBJECTIVE

The current study assessed whether prolonged exposure to a physiologically relevant low-dose of TCDD impacts glucose homeostasis and/or the islet phenotype in a sex-dependent manner in chow-fed or high-fat diet (HFD)-fed mice.

METHODS

Male and female mice were exposed to 20 ng/kg/d TCDD 2×/week for 12 weeks and simultaneously fed standard chow or a 45% HFD. Glucose homeostasis was assessed by glucose and insulin tolerance tests, and glucose-induced plasma insulin levels were measured in vivo. Histological analysis was performed on pancreas from male and female mice, and islets were isolated from females for TempO-Seq transcriptomic analysis.

RESULTS

Low-dose TCDD exposure did not lead to adverse metabolic consequences in chow-fed male or female mice, or in HFD-fed males. However, TCDD accelerated the onset of HFD-induced hyperglycemia and impaired glucose-induced plasma insulin levels in females. TCDD caused a modest increase in islet area in males but reduced the percent beta cell area within islets in females. TempO-Seq analysis suggested abnormal changes to endocrine and metabolic pathways in female TCDDHFD islets.

CONCLUSION

Our data suggest that prolonged low-dose TCDD exposure has minimal effects on glucose homeostasis and islet morphology in chow-fed male and female mice but promotes maladaptive metabolic responses in HFD-fed females.

Comprehensive Analysis of Differentially Expressed lncRNA, circRNA and mRNA and Their ceRNA Networks in Mice With Severe Acute Pancreatitis

Severe acute pancreatitis (SAP) is an acute digestive system disease with high morbidity mortality and hospitalization rate worldwide, due to various causes and unknown pathogenesis. In recent years, a large number of studies have confirmed that non-coding RNAs (ncRNAs) play an important role in many cellular processes and disease occurrence. However, the underlying mechanisms based on the function of ncRNAs, including long noncoding RNA (lncRNA) and circular RNA (circRNA), in SAP remain unclear. In this study, we performed high-throughput sequencing on the pancreatic tissues of three normal mice and three SAP mice for the first time to describe and analyze the expression profiles of ncRNAs, including lncRNA and circRNA. Our results identified that 49 lncRNAs, 56 circRNAs and 1,194 mRNAs were differentially expressed in the SAP group, compared with the control group. Furthermore, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of differentially expressed lncRNAs and circRNAs, and found that the functions of the parental genes are enriched in the calcium-regulated signaling pathway, NF-κB signaling pathway, autophagy and protein digestion and absorption processes, which are closely related to the central events in pathogenesis of SAP. We also constructed lncRNA/circRNA-miRNA-mRNA networks to further explore their underlying mechanism and possible relationships in SAP. We found that in the competitive endogenous RNA (ceRNA) networks, differentially expressed lncRNAs and circRNAs are mainly involved in the apoptosis pathway and calcium signal transduction pathway. In conclusion, we found that lncRNAs and circRNAs play an important role in the pathogenesis of SAP, which may provide new insights in further exploring the pathogenesis of SAP and seek new targets for SAP.

Integrative transcriptomic analysis of pancreatic islets from patients with prediabetes/type 2 diabetes

AIM

To identify new transcriptomic alterations in pancreatic islets associated with metabolic dysfunctions in people with prediabetes (PD)/type 2 diabetes (T2D).

MATERIALS AND METHODS

We collected information from public data repositories T2D related microarray datasets from pancreatic islets. We identified Differential Expressed Genes (DEGs) in non-diabetic (ND) vs people with T2D in each study. To identify relevant DEGs in T2D, we selected those that varied consistently in the different studies for further meta-analysis and functional enrichment analysis. DEGs were also evaluated at the PD stage.

RESULTS

A total of seven microarray datasets were collected and analysed to find the DEGs in each study and meta-analysis was performed with 245 ND and 96 T2D cases. We identified 55 transcriptional alterations potentially associated with specific metabolic dysfunctions in T2D. Meta-analysis showed that 87% of transcripts identified as DEGs (48 out of 55) were confirmed as having statistically significant up- or down-modulation in T2D compared to ND. Notably, nine of these DEGs have not been previously reported as dysregulated in pancreatic islets from people with T2D. Consistently, the most significantly enriched pathways were related to the metabolism and/or development/maintenance of β-cells. Eighteen of the 48 selected DEGs (38%) showed an altered expression in islets from people with PD.

CONCLUSIONS

These results provide new evidence to interpret the pathogenesis of T2D and the transition from PD to T2D. Further studies are necessary to validate its potential use for the development/implementation of efficient new strategies for the prevention, diagnosis/prognosis and treatment of T2D.

Characterizing pancreatic β-cell heterogeneity in the streptozotocin model by single-cell transcriptomic analysis

OBJECTIVES

The streptozotocin (STZ) model is widely used in diabetes research. However, the cellular and molecular states of pancreatic endocrine cells in this model remain unclear. This study explored the molecular characteristics of islet cells treated with STZ and re-evaluated β-cell dysfunction and regeneration in the STZ model.

METHODS

We performed single-cell RNA sequencing of pancreatic endocrine cells from STZ-treated mice. High-quality sequencing data from 2,999 cells were used to identify clusters via Louvain clustering analysis. Principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), uniform manifold approximation and projection (UMAP), force-directed layout (FDL), and differential expression analysis were used to define the heterogeneity and transcriptomic changes in islet cells. In addition, qPCR and immunofluorescence staining were used to confirm findings from the sequencing data.

RESULTS

Untreated β-cells were divided into two populations at the transcriptomic level, a large high-Glut2 expression (Glut2high) population and a small low-Glut2 expression (Glut2low) population. At the transcriptomic level, Glut2low β-cells in adult mice did not represent a developmentally immature state, although a fraction of genes associated with β-cell maturation and function were downregulated in Glut2low cells. After a single high-dose STZ treatment, most Glut2high cells were killed, but Glut2low cells survived and over time changed to a distinct cell state. We did not observe conversion of Glut2low to Glut2high β-cells up to 9 months after STZ treatment. In addition, we did not detect transcriptomic changes in the non-β endocrine cells or a direct trans-differentiation pathway from the α-cell lineage to the β-cell lineage in the STZ model.

CONCLUSIONS

We identified the heterogeneity of β-cells in both physiological and pathological conditions. However, we did not observe conversion of Glut2low to Glut2high β-cells, transcriptomic changes in the non-β endocrine cells, or direct trans-differentiation from the α-cell lineage to the β-cell lineage in the STZ model. Our results clearly define the states of islet cells treated with STZ and allow us to re-evaluate the STZ model widely used in diabetes studies.

Reduced Expression of PLCXD3 Associates With Disruption of Glucose Sensing and Insulin Signaling in Pancreatic β-Cells

Previous work has shown that reduced expression of PLCXD3, a member of the phosphoinositide-specific phospholipases (PI-PLC) family, impaired insulin secretion with an unclear mechanism. In the current study, we aim to investigate the mechanism underlying this effect using human islets and rat INS-1 (832/13) cells. Microarray and RNA sequencing data showed that PLCXD3 is among the highly expressed PI-PLCs in human islets and INS-1 (832/13) cells. Expression of PLCXD3 was reduced in human diabetic islets, correlated positively with Insulin and GLP1R expression and inversely with the donor's body mass index (BMI) and glycated hemoglobin (HbA_1c). Expression silencing of PLCXD3 in INS-1 (832/13) cells was found to reduce glucose-stimulated insulin secretion (GSIS) and insulin content. In addition, the expression of Insulin, NEUROD1, GLUT2, GCK, INSR, IRS2, and AKT was downregulated. Cell viability and apoptosis rate were unaffected. In conclusion, our data suggest that low expression of PLCXD3 in pancreatic β-cells associates with downregulation of the key insulin signaling and insulin biosynthesis genes as well as reduction in glucose sensing.