Gene microarray study corroborates proteomic findings in rodent islet cells

Reversal of diabetes following transplantation of an insulin-secreting human liver cell line: Melligen cells

As an alternative to the transplantation of islets, a human liver cell line has been genetically engineered to reverse type 1 diabetes (TID). The initial liver cell line (Huh7ins) commenced secretion of insulin in response to a glucose concentration of 2.5 mmol/l. After transfection of the Huh7ins cells with human islet glucokinase, the resultant Melligen cells secreted insulin in response to glucose within the physiological range; commencing at 4.25 mmol/l. Melligen cells exhibited increased glucokinase enzymatic activity in response to physiological glucose concentrations, as compared with Huh7ins cells. When transplanted into diabetic immunoincompetent mice, Melligen cells restored normoglycemia. Quantitative real-time polymerase chain reaction (qRT-PCR) revealed that both cell lines expressed a range of β-cell transcription factors and pancreatic hormones. Exposure of Melligen and Huh7ins cells to proinflammatory cytokines (TNF-α, IL-1β, and IFN-γ) affected neither their viability nor their ability to secrete insulin to glucose. Gene expression (microarray and qRT-PCR) analyses indicated the survival of Melligen cells in the presence of known β-cell cytotoxins was associated with the expression of NF-κB and antiapoptotic genes (such as BIRC3). This study describes the successful generation of an artificial β-cell line, which, if encapsulated to avoid allograft rejection, may offer a clinically applicable cure for T1D.

Nova1 is a master regulator of alternative splicing in pancreatic beta cells

Alternative splicing (AS) is a fundamental mechanism for the regulation of gene expression. It affects more than 90% of human genes but its role in the regulation of pancreatic beta cells, the producers of insulin, remains unknown. Our recently published data indicated that the ‘neuron-specific’ Nova1 splicing factor is expressed in pancreatic beta cells. We have presently coupled specific knockdown (KD) of Nova1 with RNA-sequencing to determine all splice variants and downstream pathways regulated by this protein in beta cells. Nova1 KD altered the splicing of nearly 5000 transcripts. Pathway analysis indicated that these genes are involved in exocytosis, apoptosis, insulin receptor signaling, splicing and transcription. In line with these findings, Nova1 silencing inhibited insulin secretion and induced apoptosis basally and after cytokine treatment in rodent and human beta cells. These observations identify a novel layer of regulation of beta cell function, namely AS controlled by key splicing regulators such as Nova1.

Modulation of the peroxiredoxin system by cytokines in insulin-producing RINm5F cells: down-regulation of PRDX6 increases susceptibility of beta cells to oxidative stress

Peroxiredoxins are a family of six antioxidant enzymes (PRDX1-6), and may be an alternative system for the pancreatic beta cells to cope with oxidative stress. This study investigated whether the main diabetogenic pro-inflammatory cytokines or the anti-inflammatory cytokine IL-4 modulate PRDXs levels and putative intracellular pathways important for this process in the insulin-producing RINm5F cells. RINm5F cells expressed significant amounts of PRDX1, PRDX3 and PRDX6 enzymes. Only PRDX6 was modulated by cytokines, showing both mRNA and protein down-regulation following incubation of RINm5F cells with TNF-alpha and IFN-gamma but not with IL-1beta. Separately IFN-gamma or TNF-alpha decreased PRDX6 protein but not mRNA levels. The blockage of the JNK signalling and of the calpains and proteasome proteolysis systems restored PRDX6 protein levels. IL-4 alone did not modulate PRDXs levels. However, pre/co-incubation with IL-4 substantially prevented the decrease in PRDX6 induced by pro-inflammatory cytokines. Knockdown of PRDX6 increased susceptibility of RINm5F cells to the deleterious effects of pro-inflammatory cytokines and to oxidative stress. These results show that, from the PRDXs significantly expressed in RINm5F cells, only PRDX6 is modulated by the diabetogenic cytokines IFN-gamma and TNF-alpha. This PRDX6 down-regulation depends on the calpain and proteasome systems and JNK signalling. PRDX6 is an important enzyme for protection against oxidative stress and the interaction between pro- and anti-inflammatory cytokines might be important to determine the antioxidant capacity of the cells.

The human pancreatic islet transcriptome: expression of candidate genes for type 1 diabetes and the impact of pro-inflammatory cytokines

Type 1 diabetes (T1D) is an autoimmune disease in which pancreatic beta cells are killed by infiltrating immune cells and by cytokines released by these cells. Signaling events occurring in the pancreatic beta cells are decisive for their survival or death in diabetes. We have used RNA sequencing (RNA–seq) to identify transcripts, including splice variants, expressed in human islets of Langerhans under control conditions or following exposure to the pro-inflammatory cytokines interleukin-1β (IL-1β) and interferon-γ (IFN-γ). Based on this unique dataset, we examined whether putative candidate genes for T1D, previously identified by GWAS, are expressed in human islets. A total of 29,776 transcripts were identified as expressed in human islets. Expression of around 20% of these transcripts was modified by pro-inflammatory cytokines, including apoptosis- and inflammation-related genes. Chemokines were among the transcripts most modified by cytokines, a finding confirmed at the protein level by ELISA. Interestingly, 35% of the genes expressed in human islets undergo alternative splicing as annotated in RefSeq, and cytokines caused substantial changes in spliced transcripts. Nova1, previously considered a brain-specific regulator of mRNA splicing, is expressed in islets and its knockdown modified splicing. 25/41 of the candidate genes for T1D are expressed in islets, and cytokines modified expression of several of these transcripts. The present study doubles the number of known genes expressed in human islets and shows that cytokines modify alternative splicing in human islet cells. Importantly, it indicates that more than half of the known T1D candidate genes are expressed in human islets. This, and the production of a large number of chemokines and cytokines by cytokine-exposed islets, reinforces the concept of a dialog between pancreatic islets and the immune system in T1D. This dialog is modulated by candidate genes for the disease at both the immune system and beta cell level.

Pancreatic beta cells are destroyed by the immune system in type 1 diabetes mellitus, causing insulin dependence for life. Candidate genes for diabetes contribute to this process by acting both at the immune system and, as we suggest here, at the pancreatic beta cell level. We have utilized a novel technology, RNA sequencing, to define all transcripts expressed in human pancreatic islets under basal conditions and following exposure to cytokines, pro-inflammatory mediators that contribute to trigger diabetes. Our observations double the number of known genes present in human islets and indicate that >60% of the candidate genes for type 1 diabetes are expressed in beta cells. The data also show that pro-inflammatory cytokines modify alternative splicing in human islets, a process that may generate novel RNAs and proteins recognizable by the immune system. This, taken together with the findings that pancreatic beta cells themselves express and release many cytokines and chemokines (proteins that attract immune cells), indicates that early type 1 diabetes is characterized by a dialog between beta cells and the immune system. We suggest that candidate genes for diabetes function at least in part as “writers” for the beta cell words in this dialog.

In vitro phenotypic, genomic and proteomic characterization of a cytokine-resistant murine β-TC3 cell line

Type 1 diabetes mellitus (T1DM) is caused by the selective destruction of insulin-producing β-cells. This process is mediated by cells of the immune system through release of nitric oxide, free radicals and pro-inflammatory cytokines, which induce a complex network of intracellular signalling cascades, eventually affecting the expression of genes involved in β-cell survival.

The aim of our study was to investigate possible mechanisms of resistance to cytokine-induced β-cell death. To this purpose, we created a cytokine-resistant β-cell line (β-TC3R) by chronically treating the β-TC3 murine insulinoma cell line with IL-1β + IFN-γ. β-TC3R cells exhibited higher proliferation rate and resistance to cytokine-mediated cell death in comparison to the parental line. Interestingly, they maintained expression of β-cell specific markers, such as PDX1, NKX6.1, GLUT2 and insulin. The analysis of the secretory function showed that β-TC3R cells have impaired glucose-induced c-peptide release, which however was only moderately reduced after incubation with KCl and tolbutamide. Gene expression analysis showed that β-TC3R cells were characterized by downregulation of IL-1β and IFN-γ receptors and upregulation of SOCS3, the classical negative regulator of cytokines signaling. Comparative proteomic analysis showed specific upregulation of 35 proteins, mainly involved in cell death, stress response and folding. Among them, SUMO4, a negative feedback regulator in NF-kB and JAK/STAT signaling pathways, resulted hyper-expressed. Silencing of SUMO4 was able to restore sensitivity to cytokine-induced cell death in β-TC3R cells, suggesting it may play a key role in acquired cytokine resistance by blocking JAK/STAT and NF-kB lethal signaling.

In conclusion, our study represents the first extensive proteomic characterization of a murine cytokine-resistant β-cell line, which might represent a useful tool for studying the mechanisms involved in resistance to cytokine-mediated β-cell death. This knowledge may be of potential benefit for patients with T1DM. In particular, SUMO4 could be used as a therapeutical target.

Hippocampal gene profiling: toward a systems biology of the hippocampus

Transcriptomics and proteomics approaches give a unique perspective for understanding brain and hippocampal functions but also pose unique challenges because of the singular complexity of the nervous system. The proliferation of genome-wide expression studies during the last decade has provided important insight into the molecular underpinnings of brain anatomy, neural plasticity, and neurological diseases. Microarray technology has dominated transcriptomics research, but this situation is rapidly changing with the recent technological advances in high-throughput sequencing. The full potential of transcriptomics in the neurosciences will be achieved as a result of its integration with other "-omics" disciplines as well as the development of novel analytical bioinformatics and systems biology tools for meta-analysis. Here, we review some of the most relevant advances in the gene profiling of the hippocampus, its relationship with proteomics approaches, and the promising perspectives for the future.

Calcineurin/nuclear factor of activated T cells and MAPK signaling induce TNF-{alpha} gene expression in pancreatic islet endocrine cells

Cytokines contribute to pancreatic islet inflammation, leading to impaired glucose homeostasis and diabetic diseases. A plethora of data shows that proinflammatory cytokines are produced in pancreatic islets by infiltrating mononuclear immune cells. Here, we show that pancreatic islet α cells and β cells express tumor necrosis factor-α (TNF-α) and other cytokines capable of promoting islet inflammation when exposed to interleukin-1β (IL-1β). Cytokine expression by β cells was dependent on calcineurin (CN)/nuclear factor of activated T cells (NFAT) and MAPK signaling. NFAT associated with the TNF-α promoter in response to stimuli and synergistically activated promoter activity with ATF2 and c-Jun. In contrast, the β-cell-specific transcriptional activator MafA could repress NFAT-mediated TNF-α gene expression whenever C/EBP-β was bound to the promoter. NFAT differentially regulated the TNF-α gene depending upon the expression and MAPK-dependent activation of interacting basic leucine zipper partners in β cells. Both p38 and JNK were required for induction of TNF-α mRNA and protein expression. Collectively, the data show that glucose and IL-1β can activate signaling pathways, which control induction and repression of cytokines in pancreatic endocrine cells. Thus, by these mechanisms, pancreatic β cells themselves may contribute to islet inflammation and their own immunological destruction in the pathogenesis of diabetes.

Islet protein profiling

Islet protein profiling is defined as generation of extended protein expression data sets from islets or islet cells. Islets from rodent control and animal models of type 1 and type 2 diabetes mellitus and healthy humans and insulin- and glucagon-producing cell lines have been used. Protein profiling entails separation, differential expression determination, identification and expression analysis. Protein/peptide separation is either gel-based or by chromatography. Differential expression is based on comparison of visualized spots/proteins between gels or by sample labelling in gel-free systems. Identification of proteins is made by tryptic fragmentation of proteins, fragment mass determination and mass comparison with protein databases. Analysis of expression data sets interprets the complex protein changes into cellular mechanisms to generate hypotheses. The importance of such protein expression sets to elucidate islet cellular events is evidenced by the observation that only about 50% of the differentially expressed proteins and transcripts showed concordance when measured in parallel. Using protein profiling, different areas related to islet dysfunction in type 1 and type 2 diabetes mellitus have been addressed, including dysfunction induced by elevated levels of glucose and fatty acids and cytokines. Because islets from individuals with type 1 or type 2 diabetes mellitus have not yet been protein profiled, islets from rat (BB-DP) and mouse (NOD, ob/ob, MKR) models of the disease have been used, and mechanisms responsible for islet dysfunction delineated offering avenues of intervention.

Mouse pancreatic endocrine cell transcriptome defined in the embryonic Ngn3-null mouse

OBJECTIVE

To document the transcriptome of the pancreatic islet during the early and late development of the mouse pancreas and highlight the qualitative and quantitative features of gene expression that contribute to the specification, growth, and differentiation of the major endocrine cell types. A further objective was to identify endocrine cell biomarkers, targets of diabetic autoimmunity, and regulatory pathways underlying islet responses to physiological and pathological stimuli.

RESEARCH DESIGN AND METHODS

mRNA expression profiling was performed by microarray analysis of e12.5-18.5 embryonic pancreas from neurogenin 3 (Ngn3)-null mice, a background that abrogates endocrine pancreatic differentiation. The intersection of this data with mRNA expression in isolated adult pancreatic islets and pancreatic endocrine tumor cell lines was determined to compile lists of genes that are specifically expressed in endocrine cells.

RESULTS

The data provided insight into the transcriptional and morphogenetic factors that may play major roles in patterning and differentiation of the endocrine lineage before and during the secondary transition of endocrine development, as well as genes that control the glucose responsiveness of the beta-cells and candidate diabetes autoantigens, such as insulin, IA-2 and Slc30a8 (ZnT8). The results are presented as downloadable gene lists, available at https://www.cbil.upenn.edu/RADQuerier/php/displayStudy.php?study_id=1330, stratified by predictive scores of relative cell-type specificity.

CONCLUSIONS

The deposited data provide a rich resource that can be used to address diverse questions related to islet developmental and cell biology and the pathogenesis of type 1 and 2 diabetes.

A protein interaction network associated with asthma

Identifying candidate genes related to complex diseases or traits and mapping their relationships require a system-level analysis at a cellular scale. The objective of the present study is to systematically analyze the complex effects of interrelated genes and provide a framework for revealing their relationships in association with a specific disease (asthma in this case). We observed that protein-protein interaction (PPI) networks associated with asthma have a power-law connectivity distribution as many other biological networks have. The hub nodes and skeleton substructure of the result network are consistent with the prior knowledge about asthma pathways, and also suggest unknown candidate target genes associated with asthma, including GNB2L1, BRCA1, CBL, and VAV1. In particular, GNB2L1 appears to play a very important role in the asthma network through frequent interactions with key proteins in cellular signaling. This network-based approach represents an alternative method for analyzing the complex effects of candidate genes associated with complex diseases and suggesting a list of gene drug targets. The full list of genes and the analysis details are available in the following online supplementary materials: http://biosoft.kaist.ac.kr:8080/resources/asthma_ppi.

Network activity-independent coordinated gene expression program for synapse assembly

Global biological datasets generated by genomics, transcriptomics, and proteomics provide new approaches to understanding the relationship between the genome and the synapse. Combined transcriptome analysis and multielectrode recordings of neuronal network activity were used in mouse embryonic primary neuronal cultures to examine synapse formation and activity-dependent gene regulation. Evidence for a coordinated gene expression program for assembly of synapses was observed in the expression of 642 genes encoding postsynaptic and plasticity proteins. This synaptogenesis gene expression program preceded protein expression of synapse markers and onset of spiking activity. Continued expression was followed by maturation of morphology and electrical neuronal networks, which was then followed by the expression of activity-dependent genes. Thus, two distinct sequentially active gene expression programs underlie the genomic programs of synapse function.

Toward a comprehensive quantitative proteome database: protein expression map of lymphoid neoplasms by 2-D DIGE and MS

Using 2-D DIGE, we constructed a quantitative 2-D database including 309 proteins corresponding to 389 protein spots across 42 lymphoid neoplasm cell lines. The proteins separated by 2-D PAGE were identified by MS and assigned to the expression data obtained by 2-D DIGE. The cell lines were categorized into four groups: those from Hodgkin's lymphoma (HL) (4 cell lines), B cell malignancies (19 cell lines), T cell malignancies (16 cell lines), and natural killer (NK) cell malignancies (3 cell lines). We characterized the proteins in the database by classifying them according to their expression level. We found 28 proteins with more than a 2-fold difference between the cell line groups. We also noted the proteins that allowed multidimensional separation to be achieved (1) between HL cells and other cells, (2) between the cells derived from B cells, T cells and NK cells, and (3) between HL cells and anaplastic large cell lymphoma cells. Decision tree classification identified five proteins that could be used to classify the 42 cell lines according to differentiation. These results suggest that the quantitative 2-D database using 2-D DIGE will be a useful resource for studying the mechanisms underlying the differentiation phenotypes of lymphoid neoplasms.

The biological limitations of transcriptomics in elucidating stress and stress responses

Global analysis of mRNA abundance via genomic arrays (i.e. transcriptomics or transcriptional profiling) is one approach to finding the genes that matter to organisms undergoing environmental stress. In evolutionary analyses of stress, mRNA abundance is often invoked as a proxy for the protein activity that may underlie variation in fitness. To provoke discussion of the utility and sensible application of this valuable approach, this manuscript examines the adequacy of mRNA abundance as a proxy for protein activity, fitness and stress. Published work to date suggests that mRNA abundance typically provides little information on protein activity and fitness and cannot substitute for detailed functional and ecological analyses of candidate genes. While the transcriptional profile can be an exquisitely sensitive indicator of stress, simpler indicators will often suffice. In view of this outcome, transcriptomics should undergo careful cost-benefit analysis before investigators deploy it in studies of stress responses and their evolution.

Identification of coexpressed gene clusters in a comparative analysis of transcriptome and proteome in mouse tissues

A major advantage of the mouse model lies in the increasing information on its genome, transcriptome, and proteome, as well as in the availability of a fast growing number of targeted and induced mutant alleles. However, data from comparative transcriptome and proteome analyses in this model organism are very limited. We use DNA chip-based RNA expression profiling and 2D gel electrophoresis, combined with peptide mass fingerprinting of liver and kidney, to explore the feasibility of such comprehensive gene expression analyses. Although protein analyses mostly identify known metabolic enzymes and structural proteins, transcriptome analyses reveal the differential expression of functionally diverse and not yet described genes. The comparative analysis suggests correlation between transcriptional and translational expression for the majority of genes. Significant exceptions from this correlation confirm the complementarities of both approaches. Based on RNA expression data from the 200 most differentially expressed genes, we identify chromosomal colocalization of known, as well as not yet described, gene clusters. The determination of 29 such clusters may suggest that coexpression of colocalizing genes is probably rather common.

Toxin-based selection of insulin-producing cells with improved defense properties for islet cell transplantation

Insulin-producing pancreatic beta-cells are known to be extremely susceptible to destruction, primarily by autoimmune mechanisms, infectious agents, and by chemical toxins that cause overt type I diabetes. As development of highly protected insulin-producing cells would be important for successful cell therapy of diabetic patients, gene transfection technique was utilized by several investigators in order to improve the defense properties of transplanted cells. In this article, we summarize other approaches based on a selection strategy that has been developed in our laboratory and by other research groups that engineer pancreatic beta-cells to provide protection against diabetogenic toxins (streptozotocin and alloxan), oxidative stress and cytokines. Selection strategies based on acute repeated or long-term continuous treatment of cell lines with cytotoxic agents have resulted in the selection of highly resistant cell subpopulations. We discuss possible involvement of different expression of cytoprotective genes in the selection of cell subpopulations, which demonstrate a broad spectrum of resistance. Importantly, toxin-based selection did not impair functional activity of the cells as it was shown in vitro. In addition, selected cells preserved their improved metabolic characteristics following encapsulation in alginate and subsequent implantation in diabetic animals. Identifying the mechanisms through which cell defense properties act will help clarify the process responsible for beta-cell regeneration in type I diabetes patients. Such knowledge might be useful in developing strategies focusing on the regeneration of beta-cell resistant populations.

Unraveling the Pathogenesis of Type 1 Diabetes with Proteomics: Present And Future Directions

Type 1 diabetes (T1D) is the result of selective destruction of the insulin-producing beta-cells in the pancreatic islets of Langerhans. T1D is due to a complex interplay between the beta-cell, the immune system, and the environment in genetically susceptible individuals. The initiating mechanism(s) behind the development of T1D are largely unknown, and no genes or proteins are specific for most T1D cases. Different pro-apoptotic cytokines, IL-1 beta in particular, are present in the islets during beta-cell destruction and are able to modulate beta-cell function and induce beta-cell death. In beta-cells exposed to IL-1 beta, a race between destructive and protective events are initiated and in susceptible individuals the deleterious events prevail. Proteins are involved in most cellular processes, and it is thus expected that their cumulative expression profile reflects the specific activity of cells. Proteomics may be useful in describing the protein expression profile and thus the diabetic phenotype. Relatively few studies using proteomics technologies to investigate the T1D pathogenesis have been published to date despite the defined target organ, the beta-cell. Proteomics has been applied in studies of differentiating beta-cells, cytokine exposed islets, dietary manipulated islets, and in transplanted islets. Although that the studies have revealed a complex and detailed picture of the protein expression profiles many functional implications remain to be answered. In conclusion, a rather detailed picture of protein expression in beta-cell lines, islets, and transplanted islets both in vitro and in vivo have been described. The data indicate that the beta-cell is an active participant in its own destruction during diabetes development. No single protein alone seems to be responsible for the development of diabetes. Rather the cumulative pattern of changes seems to be what favors a transition from dynamic stability in the unperturbed beta-cell to dynamic instability and eventually to beta-cell destruction.

Integrating global proteomic and genomic expression profiles generated from islet alpha cells: opportunities and challenges to deriving reliable biological inferences

Systematic profiling of expressed gene products represents a promising research strategy for elucidating the molecular phenotypes of islet cells. To this end, we have combined complementary genomic and proteomic methods to better assess the molecular composition of murine pancreatic islet glucagon-producing alphaTC-1 cells as a model system, with the expectation of bypassing limitations inherent to either technology alone. Gene expression was measured with an Affymetrix MG_U74Av2 oligonucleotide array, while protein expression was examined by performing high-resolution gel-free shotgun MS/MS on a nuclear-enriched cell extract. Both analyses were carried out in triplicate to control for experimental variability. Using a stringent detection p value cutoff of 0.04, 48% of all potential mRNA transcripts were predicted to be expressed (probes classified as present in at least two of three replicates), while 1,651 proteins were identified with high-confidence using rigorous database searching. Although 762 of 888 cross-referenced cognate mRNA-protein pairs were jointly detected by both platforms, a sizeable number (126) of gene products was detected exclusively by MS alone. Conversely, marginal protein identifications often had convincing microarray support. Based on these findings, we present an operational framework for both interpreting and integrating dual genomic and proteomic datasets so as to obtain a more reliable perspective into islet alpha cell function.

Identification of tissue-restricted transcripts in human islets

The purpose of our study was to identify transcripts specific for tissue-restricted, membrane-associated proteins in human islets that, in turn, might serve as markers of healthy or diseased islet cell masses. Using oligonucleotide chips, we obtained gene expression profiles of human islets for comparison with the profiles of exocrine pancreas, liver, and kidney tissue. As periislet presence of type 1 interferon is associated with the development of type 1 diabetes, the expression profile of human islets treated ex vivo with interferon-alpha2beta (IFNalpha2beta) was also determined. A set of genes encoding transmembrane- or membrane-associated proteins with novel islet-restricted expression was resolved by determining the intersection of the islet set with the complement of datasets obtained from other tissues. Under the influence of IFNalpha2beta, the expression levels of transcripts for several of the identified gene products were up- or down-regulated. One of the islet-restricted gene products identified in this study, vesicular monoamine transporter type 2, was shown to bind [3H]dihydrotetrabenazine, a ligand with derivatives suitable for positron emission tomography imaging. We report here the first comparison of gene expression profiles of human islets with other tissues and the identification of a target molecule with possible use in determining islet cell masses.