Najib Naamane

DNA methylation profiling identifies epigenetic dysregulation in pancreatic islets from type 2 diabetic patients

In addition to genetic predisposition, environmental and lifestyle factors contribute to the pathogenesis of type 2 diabetes (T2D). Epigenetic changes may provide the link for translating environmental exposures into pathological mechanisms. In this study, we performed the first comprehensive DNA methylation profiling in pancreatic islets from T2D and non‐diabetic donors. We uncovered 276 CpG loci affiliated to promoters of 254 genes displaying significant differential DNA methylation in diabetic islets. These methylation changes were not present in blood cells from T2D individuals nor were they experimentally induced in non‐diabetic islets by exposure to high glucose. For a subgroup of the differentially methylated genes, concordant transcriptional changes were present. Functional annotation of the aberrantly methylated genes and RNAi experiments highlighted pathways implicated in β‐cell survival and function; some are implicated in cellular dysfunction while others facilitate adaptation to stressors. Together, our findings offer new insights into the intricate mechanisms of T2D pathogenesis, underscore the important involvement of epigenetic dysregulation in diabetic islets and may advance our understanding of T2D aetiology.

Induction of nuclear factor-κB and its downstream genes by TNF-α and IL-1β has a pro-apoptotic role in pancreatic beta cells

Aims/hypothesisIL-1β and TNF-α contribute to pancreatic beta cell death in type 1 diabetes. Both cytokines activate the transcription factor nuclear factor-κB (NF-κB), but recent observations suggest that NF-κB blockade prevents IL-1β + IFN-γ- but not TNF-α + IFN-γ-induced beta cell apoptosis. The aim of the present study was to compare the effects of IL-1β and TNF-α on cell death and the pattern of NF-κB activation and global gene expression in beta cells.MethodsCell viability was measured after exposure to IL-1β or to TNF-α alone or in combination with IFN-γ, and blockade of NF-κB activation or protein synthesis. INS-1E cells exposed to IL-1β or TNF-α in time course experiments were used for IκB kinase (IKK) activation assay, detection of p65 NF-κB by immunocytochemistry, real-time RT-PCR and microarray analysis.ResultsBlocking NF-κB activation protected beta cells against IL-1β + IFNγ- or TNFα + IFNγ-induced apoptosis. Blocking de novo protein synthesis did not increase TNF-α- or IL-1β-induced beta cell death, in line with the observations that cytokines induced the expression of the anti-apoptotic genes A20, Iap-2 and Xiap to a similar extent. Microarray analysis of INS-1E cells treated with IL-1β or TNF-α showed similar patterns of gene expression. IL-1β, however, induced a higher rate of expression of NF-κB target genes putatively involved in beta cell dysfunction and death and a stronger activation of the IKK complex, leading to an earlier translocation of NF-κB to the nucleus.Conclusions/interpretationNF-κB activation in beta cells has a pro-apoptotic role following exposure not only to IL-1β but also to TNF-α. The more marked beta cell death induced by IL-1β is explained at least in part by higher intensity NF-κB activation, leading to increased transcription of key target genes.

STAT1 is a master regulator of pancreatic beta-cell apoptosis and islet inflammation.

Cytokines produced by islet-infiltrating immune cells induce β-cell apoptosis in type 1 diabetes. The IFN-γ-regulated transcription factors STAT1/IRF-1 have apparently divergent effects on β-cells. Thus, STAT1 promotes apoptosis and inflammation, whereas IRF-1 down-regulates inflammatory mediators. To understand the molecular basis for these differential outcomes within a single signal transduction pathway, we presently characterized the gene networks regulated by STAT1 and IRF-1 in β-cells. This was done by using siRNA approaches coupled to microarray analysis of insulin-producing cells exposed or not to IL-1β and IFN-γ. Relevant microarray findings were further studied in INS-1E cells and primary rat β-cells. STAT1, but not IRF-1, mediates the cytokine-induced loss of the differentiated β-cell phenotype, as indicated by decreased insulin, Pdx1, MafA, and Glut2. Furthermore, STAT1 regulates cytokine-induced apoptosis via up-regulation of the proapoptotic protein DP5. STAT1 and IRF-1 have opposite effects on cytokine-induced chemokine production, with IRF-1 exerting negative feedback inhibition on STAT1 and downstream chemokine expression. The present study elucidates the transcriptional networks through which the IFN-γ/STAT1/IRF-1 axis controls β-cell function/differentiation, demise, and islet inflammation.

Cytokines Interleukin-1β and Tumor Necrosis Factor-α Regulate Different Transcriptional and Alternative Splicing Networks in Primary β-Cells

OBJECTIVE Cytokines contribute to pancreatic β-cell death in type 1 diabetes. This effect is mediated by complex gene networks that remain to be characterized. We presently utilized array analysis to define the global expression pattern of genes, including spliced variants, modified by the cytokines interleukin (IL)-1β + interferon (IFN)-γ and tumor necrosis factor (TNF)-α + IFN-γ in primary rat β-cells. RESEARCH DESIGN AND METHODS Fluorescence-activated cell sorter–purified rat β-cells were exposed to IL-1β + IFN-γ or TNF-α + IFN-γ for 6 or 24 h, and global gene expression was analyzed by microarray. Key results were confirmed by RT-PCR, and small-interfering RNAs were used to investigate the mechanistic role of novel and relevant transcription factors identified by pathway analysis. RESULTS Nearly 16,000 transcripts were detected as present in β-cells, with temporal differences in the number of genes modulated by IL-1β + IFNγ or TNF-α + IFN-γ. These cytokine combinations induced differential expression of inflammatory response genes, which is related to differential induction of IFN regulatory factor-7. Both treatments decreased the expression of genes involved in the maintenance of β-cell phenotype and growth/regeneration. Cytokines induced hypoxia-inducible factor-α, which in this context has a proapoptotic role. Cytokines also modified the expression of >20 genes involved in RNA splicing, and exon array analysis showed cytokine-induced changes in alternative splicing of >50% of the cytokine-modified genes. CONCLUSIONS The present study doubles the number of known genes expressed in primary β-cells, modified or not by cytokines, and indicates the biological role for several novel cytokine-modified pathways in β-cells. It also shows that cytokines modify alternative splicing in β-cells, opening a new avenue of research for the field.

Death Protein 5 and p53-Upregulated Modulator of Apoptosis Mediate the Endoplasmic Reticulum Stress–Mitochondrial Dialog Triggering Lipotoxic Rodent and Human β-Cell Apoptosis

Environmental factors such as diets rich in saturated fats contribute to dysfunction and death of pancreatic β-cells in diabetes. Endoplasmic reticulum (ER) stress is elicited in β-cells by saturated fatty acids. Here we show that palmitate-induced β-cell apoptosis is mediated by the intrinsic mitochondrial pathway. By microarray analysis, we identified a palmitate-triggered ER stress gene expression signature and the induction of the BH3-only proteins death protein 5 (DP5) and p53-upregulated modulator of apoptosis (PUMA). Knockdown of either protein reduced cytochrome c release, caspase-3 activation, and apoptosis in rat and human β-cells. DP5 induction depends on inositol-requiring enzyme 1 (IRE1)–dependent c-Jun NH2-terminal kinase and PKR–like ER kinase (PERK)–induced activating transcription factor (ATF3) binding to its promoter. PUMA expression is also PERK/ATF3-dependent, through tribbles 3 (TRB3)–regulated AKT inhibition and FoxO3a activation. DP5−/− mice are protected from high fat diet–induced loss of glucose tolerance and have twofold greater pancreatic β-cell mass. This study elucidates the crosstalk between lipotoxic ER stress and the mitochondrial pathway of apoptosis that causes β-cell death in diabetes.

Pancreatic β-cells activate a JunB/ATF3-dependent survival pathway during inflammation.

Destruction of insulin-producing pancreatic β-cells by local autoimmune inflammation is a hallmark of type 1 diabetes. Histochemical analysis of pancreases from non-obese diabetic mice indicated activation of the transcription factor JunB/AP-1 (activator protein-1) after autoimmune infiltration of the islets. In vitro studies demonstrated that the cytokines tumor necrosis factor (TNF)-α and interferon (IFN)-γ induce JunB expression as a protective mechanism against apoptosis in both human and rodent β-cells. The gene network affected was studied by microarray analysis showing that JunB regulates nearly 20% of the cytokine-modified β-cell genes, including the transcription factor ATF3. Direct transcriptional induction of ATF3 by JunB is a key event for β-cell survival after TNF-α+IFN-γ treatment. Moreover, pharmacological upregulation of JunB/ATF3 via increased cAMP protected rodent primary β-cells and human islet cells against pro-inflammatory mediators. These results were confirmed in genetically modified islets derived from Ubi-JunB transgenic mice. Our findings identify ATF3 as a novel downstream target of JunB in the survival mechanism of β-cells under inflammatory stress.

JunB protects β-cells from lipotoxicity via the XBP1-AKT pathway.

Diets rich in saturated fats may contribute to the loss of pancreatic β-cells in type 2 diabetes. JunB, a member of the activating protein 1 (AP-1) transcription factor family, promotes β-cell survival and mediates part of the beneficial effects of GLP-1 agonists. In this study we interrogated the molecular mechanisms involved in JunB-mediated β-cell protection from lipotoxicity. The saturated fatty acid palmitate decreased JunB expression, and this loss may contribute to β-cell apoptosis, as overexpression of JunB protected cells from lipotoxicity. Array analysis of JunB-deficient β-cells identified a gene expression signature of a downregulated endoplasmic reticulum (ER) stress response and inhibited AKT signaling. JunB stimulates XBP1 expression via the transcription factor c/EBPδ during ER stress, and forced expression of XBP1s rescued the viability of JunB-deficient cells, constituting an important antiapoptotic mechanism. JunB silencing inhibited AKT activation and activated the proapoptotic Bcl-2 protein BAD via its dephosphorylation. BAD knockdown reversed lipotoxic β-cell death potentiated by JunB siRNA. Interestingly, XBP1s links JunB and AKT signaling as XBP1 knockdown also reduced AKT phosphorylation. GLP-1 agonists induced cAMP-dependent AKT phosphorylation leading to β-cell protection against palmitate-induced apoptosis. JunB and XBP1 knockdown or IRE1 inhibition decreased AKT activation by cAMP, leading to β-cell apoptosis. In conclusion, JunB modulates the β-cell ER stress response and AKT signaling via the induction of XBP1s. The activation of the JunB gene network and the crosstalk between the ER stress and AKT pathway constitute a crucial defense mechanism by which GLP-1 agonists protect against lipotoxic β-cell death. These findings elucidate novel β-cell-protective signal transduction in type 2 diabetes.

In silico identification of NF-kappaB-regulated genes in pancreatic beta-cells

BackgroundPancreatic beta-cells are the target of an autoimmune attack in type 1 diabetes mellitus (T1DM). This is mediated in part by cytokines, such as interleukin (IL)-1β and interferon (IFN)-γ. These cytokines modify the expression of hundreds of genes, leading to beta-cell dysfunction and death by apoptosis. Several of these cytokine-induced genes are potentially regulated by the IL-1β-activated transcription factor (TF) nuclear factor (NF)-κB, and previous studies by our group have shown that cytokine-induced NF-κB activation is pro-apoptotic in beta-cells. To identify NF-κB-regulated gene networks in beta-cells we presently used a discriminant analysis-based approach to predict NF-κB responding genes on the basis of putative regulatory elements.ResultsThe performance of linear and quadratic discriminant analysis (LDA, QDA) in identifying NF-κB-responding genes was examined on a dataset of 240 positive and negative examples of NF-κB regulation, using stratified cross-validation with an internal leave-one-out cross-validation (LOOCV) loop for automated feature selection and noise reduction. LDA performed slightly better than QDA, achieving 61% sensitivity, 91% specificity and 87% positive predictive value, and allowing the identification of 231, 251 and 580 NF-κB putative target genes in insulin-producing INS-1E cells, primary rat beta-cells and human pancreatic islets, respectively. Predicted NF-κB targets had a significant enrichment in genes regulated by cytokines (IL-1β or IL-1β + IFN-γ) and double stranded RNA (dsRNA), as compared to genes not regulated by these NF-κB-dependent stimuli. We increased the confidence of the predictions by selecting only evolutionary stable genes, i.e. genes with homologs predicted as NF-κB targets in rat, mouse, human and chimpanzee.ConclusionThe present in silico analysis allowed us to identify novel regulatory targets of NF-κB using a supervised classification method based on putative binding motifs. This provides new insights into the gene networks regulating cytokine-induced beta-cell dysfunction and death.

New Approaches for in Silico Identification of Cytokine‐Modified β Cell Gene Networks

Abstract: Beta cell dysfunction and death in type 1 diabetes mellitus (T1DM) is caused by direct contact with activated macrophages and T lymphocytes and by exposure to soluble mediators secreted by these cells, such as cytokines and nitric oxide. Cytokine‐induced apoptosis depends on the expression of pro‐ and anti‐apoptotic genes that remain to be characterized. Using microarray analyses, we identified several transcription factor and “effector” gene networks regulated by interleukin‐1β and/or interferon‐γ in β cells. This suggests that β cell fate following exposure to cytokines is a complex and highly regulated process, depending on the duration and severity of perturbation of key gene networks. In order to draw correct conclusions from these massive amounts of data, we need to utilize novel bioinformatics and statistical tools. Thus, we are presently performing in silico analysis for the localization of binding sites for the transcription factor NF‐κB (previously shown to be pivotal for β cell apoptosis) in 15 temporally related gene clusters, identified by time‐course microarray analysis. In silico analysis is based on a broad range of computational techniques used to detect motifs in a DNA sequence corresponding to the binding site of a transcription factor. These computer‐based findings must be validated by use of positive and negative controls, and by “ChIP on chip” analysis. Moreover, new statistical approaches are required to decrease false positive findings. These novel approaches will constitute a “proof of principle” for the integrated use of bioinformatics and functional genomics in the characterization of relevant cytokine‐regulated β cell gene networks leading to β cell apoptosis in T1DM.

EuroDia: a beta-cell gene expression resource

Type 2 diabetes mellitus (T2DM) is a major disease affecting nearly 280 million people worldwide. Whilst the pathophysiological mechanisms leading to disease are poorly understood, dysfunction of the insulin-producing pancreatic beta-cells is key event for disease development. Monitoring the gene expression profiles of pancreatic beta-cells under several genetic or chemical perturbations has shed light on genes and pathways involved in T2DM. The EuroDia database has been established to build a unique collection of gene expression measurements performed on beta-cells of three organisms, namely human, mouse and rat. The Gene Expression Data Analysis Interface (GEDAI) has been developed to support this database. The quality of each dataset is assessed by a series of quality control procedures to detect putative hybridization outliers. The system integrates a web interface to several standard analysis functions from R/Bioconductor to identify differentially expressed genes and pathways. It also allows the combination of multiple experiments performed on different array platforms of the same technology. The design of this system enables each user to rapidly design a custom analysis pipeline and thus produce their own list of genes and pathways. Raw and normalized data can be downloaded for each experiment. The flexible engine of this database (GEDAI) is currently used to handle gene expression data from several laboratory-run projects dealing with different organisms and platforms. Database URL: http://eurodia.vital-it.ch