Pancreatic Beta Cells Are Highly Susceptible to Oxidative and ER

Article pubs.acs.org/jpr

Pancreatic Beta Cells Are Highly Susceptible to Oxidative and ER Stresses during the Development of Diabetes Dhana G. Gorasia,†,‡ Nadine L. Dudek,†,‡,⊥ Paul D. Veith,‡,§ Renu Shankar,†,‡ Helena Safavi-Hemami,†,‡,# Nicholas A. Williamson,‡ Eric C. Reynolds,‡,§ Michael J. Hubbard,∥ and Anthony W. Purcell*,†,‡,⊥ †

Department of Biochemistry and Molecular Biology, ‡The Bio21 Molecular Science and Biotechnology Institute, §Oral Health Cooperative Research Centre, Melbourne Dental School, and Bio21 Institute, ∥Departments of Paediatrics and Pharmacology, The University of Melbourne, Parkville, Victoria 3010, Australia ⊥ Department of Biochemistry and Molecular Biology, School of Biomedical Sciences, Monash University, Clayton, Victoria 3800, Australia S Supporting Information *

ABSTRACT: The complex interplay of many cell types and the temporal heterogeneity of pancreatic islet composition obscure the direct role of resident alpha and beta cells in the development of Type 1 diabetes. Therefore, in addition to studying islets isolated from non-obese diabetic mice, we analyzed homogeneous cell populations of murine alpha (αTC-1) and beta (NIT-1) cell lines to understand the role and differential survival of these two predominant islet cell populations. A total of 56 proteins in NIT-1 cells and 50 in αTC-1 cells were differentially expressed when exposed to proinflammatory cytokines. The major difference in the protein expression between cytokine-treated NIT-1 and αTC-1 cells was free radical scavenging enzymes. A similar observation was made in cytokine-treated whole islets, where a comprehensive analysis of subcellular fractions revealed that 438 unique proteins were differentially expressed under inflammatory conditions. Our data indicate that beta cells are relatively susceptible to ER and oxidative stress and reveal key pathways that are dysregulated in beta cells during cytokine exposure. Additionally, in the islets, inflammation also leads to enhanced antigen presentation, which completes a three-way insult on beta cells, rendering them targets of infiltrating T lymphocytes. KEYWORDS: Diabetes, oxidative stress, ER stress, inflammation, 2D-DIGE, MALDI-TOF MS

■

INTRODUCTION In the pancreas, the Islets of Langerhans consist of two predominant cell types: alpha and beta cells. In Type 1 diabetes (T1D), insulin-producing beta cells are specifically destroyed by an autoimmune response. However, in the same inflammatory environment, alpha cells are not affected. Evidence from the nonobese diabetic (NOD) mouse model of diabetes has implicated various effector mechanisms, such as perforin1−3 and Fas signaling,4,5 in the killing of beta cells. However, genetic deficiency of perforin2,3 and blocking of the Fas signaling pathway6 only partially protect NOD mice from diabetes, suggesting the presence of other effector mechanisms in the destruction of pancreatic beta cells. Proinflammatory cytokines such as interferon gamma (IFN-γ), tumor necrosis factor alpha (TNF-α), and interleukin 1-beta (IL-1β), which are released by infiltrating immune cells, are important candidates for non-perforin-dependent killing mechanisms. Under in vitro conditions, IL-1β, in combination with IFN-γ and/or TNF-α, causes severe functional impairment and death by apoptosis in rodent pancreatic islets.7−11 The effect of cytokines is less deleterious in human islets; however, the exposure of human islets to multiple cytokines for longer periods also causes a similar functional impairment and cell death.12,13 Several studies have addressed the mechanisms involved in cytokine-mediated death of beta cells. Nuclear factor-kB © XXXX American Chemical Society

(NF-κB) and signal transducer and activator of transcription 1 (STAT 1) have been shown to be the central regulators of many cytokine-induced genes, including stress response genes and genes involved in beta cell function.14−16 Previous proteomics studies have been performed on isolated whole rat islets to better understand the mechanism of beta cell death using traditional two-dimensional gel electrophoresis (2DGE) and have focused mainly on the effect of IL-1β.17−19 Recently D’Hertog et al. utilized 2D fluorescent gel electrophoresis technique to examine the effect of multiple cytokines on INS-1E cells, a rat pancreatic beta cell line.20 The authors identified a total of 158 proteins that were cytokine-regulated and suggested that chaperones involved in protein folding and proteins involved in RNA metabolism played a central role in cytokine-induced beta cell death. The aim of this study was to further identify pancreatic proteins that are differentially expressed during exposure to cytokines using 2D difference gel electrophoresis (2D-DIGE) and to dissect the role of alpha and beta cells in the overall islet response to cytokine treatment, including beta cell death and alpha cell survival, by comparing effects observed in cell lines and isolated pancreatic islets from diabetes-prone NOD mice. Received: June 30, 2014

A

dx.doi.org/10.1021/pr500643h | J. Proteome Res. XXXX, XXX, XXX−XXX

Journal of Proteome Research

■

Article

EXPERIMENTAL PROCEDURES

focusing (IEF) was performed using Ettan IPHphor II (GE Healthcare). Following IEF, the proteins in the strips were reduced and alkylated with DTT and iodoacetamide, respectively, for 15 min. The strips were placed on top of 8−16% Criterion TrisHCL polyacrylamide gradient gels (Bio-Rad). Electrophoresis was carried out at 200 V in 25 mM Tris, 192 mM glycine, 0.1% SDS. The differentially labeled coresolved proteome maps within each DIGE gel were imaged at 100 μm resolutions on a Typhoon 9400 variable mode imager (GE Healthcare) using dye-specific excitation and emission wavelengths. Cropped image files were exported into the DeCyder v6.5 software (GE Healthcare) for analysis using biological variation analysis (BVA). Due to the presence of internal standard in all gels, the BVA module can match multiple DIGE gels. The quantitation is expressed as a spot ratio, comparing spot volumes on the secondary image with corresponding spot volumes of the internal standard. For islets, a cut off of 1.3-fold was chosen because ∼80% of the proteome remained unchanged at this cut off.

Cell Culture

NIT-1 insulinoma cell line21 was grown in tissue culture flasks using low-glucose DMEM (Invitrogen) supplemented with 10% FCS (Sigma), 2 mM glutamine, 100 units/mL benzyl-penicillin, 0.1 mg/mL streptomycin sulfate, 0.05 mM β-mercaptoethanol, 5 mM HEPES buffer, and 0.1 mM nonessential amino acids at 37 °C and 10% CO2. The SV40-transformed αTC-1 cell line from mouse22 was grown in DMEM supplemented as described above at 37 °C in a 10% CO2 atmosphere. Treatment of NIT-1 and αTC-1 Cell Lines with Cytokines

NIT-1 and αTC-1 cells were either left untreated or treated for 24 h with the following combinations of cytokines: IFN-γ (100 U/mL) + IL-1β (10 U/mL) (Peprotech) or IFN-γ (100 U/mL) + TNFα (1000 U/mL) (Peprotech). For each treatment condition, triplicate experiments were performed originating from three independent experiments. Following treatment, cells were lysed with DIGE lysis buffer (30 mM Tris, 7 M Urea, 2 M Thiourea, 4% (w/v) CHAPS) on ice for 30 min. The samples were then treated with 2D clean up kit (GE Healthcare) according to the manufacturer’s instructions.

Protein Spot Excision and Identification by MALDI TOF/TOF

Preparative gels were used for excision of protein spots and loaded with 350 μg of protein and run under identical conditions as those for DIGE gels. Individual protein spots, detected using proteomeweaver software (Bio-Rad), were excised from Coomassie-stained 2D gels using a Proteineer SP spot picker (Bruker Daltonics). The cut gel spots were transferred to 96-well digest adaptors, and in-gel tryptic digestion performed as described.23 Three microliters of the digested peptides was carefully spotted on an Anchorchip target plate with prespotted matrix and calibration standards (Bruker Daltonics). After 10 min of adsorption, Anchorchips were washed by dipping in a reservoir of 0.1% TFA and allowed to dry prior to matrix assisted laser desorption ionization (MALDI)-time-of-flight (TOF) analysis. Identification by mass spectrometry was performed as described in ref 23. All searches were performed against the mouse IPI database (v3.37). The protein searches were considered to be correct if the MS/MS score was greater than 30 (identity threshold = 30) or if the MS score was greater than 70 (identity threshold = 60). Protein hits were also considered to be correct if the MS/MS score was >20 together with MS score > 50. Proteins identified by PMF only with a Mascot score between 70 and 75 were manually checked, taking the mass accuracy, partial cleavages, intensity coverage, and mixture mode analysis into consideration. Some of the protein spots resulted in more than one identification, and it was difficult to determine which protein had actually changed with cytokine treatment. Therefore, all proteins were listed in the tables. The false positive detection rate (FDR) was determined by combining all MS/MS data for each experiment into single mgf files and conducting Mascot decoy searches on each. The FDR was less than 3.5% for each of the five experiments, and the combined average FDR was 2.2%.

Isolation of Islets, Cytokine Treatments, and Subcellular Fractionation

NOD mice were purchased from the Animal Resource Centre (West Australia) and housed at the Bio21 Institute Animal Facility in Melbourne, Australia. Studies were carried out in accordance with accepted standards of humane animal care and were approved by the animal ethics committee, University of Melbourne. Islets of Langerhans were isolated from NOD mice at 4−6 weeks of age. The pelleted islets were resuspended in 3− 5 mL of CMRL (Invitrogen) supplemented with 10% FCS and 4 mM glutamine and handpicked into a fresh Petri dish. The islets were cultured for 24 h without or with cytokines (100 U/mL IFN-γ or 100 U/mL IFN-γ + 1000 U/mL TNF-α + 10 U/mL IL-1β). Subcellular fractionation of islet proteins was performed using the subcellular proteo extract kit (Merck) according to the manufacturer’s instructions. This experiment was not performed with biological replicate because, first, murine islets are difficult to obtain in large quantities and, second, a replicated cell-specific (NIT-1 and αTC-1) data set had already been obtained that could be utilized for comparison against islet cell data. Labeling of Protein Samples

Fluorescent dyes (CyDye, GE Healthcare) were reconstituted in dimethylformamide (Sigma) to give a CyDye concentration of 1 nmol/μL. Fifty micrograms of all protein samples was either labeled with 400 pmoles of Cy3 or Cy5 dye (see Supporting Information Tables 1 and 2 for labeling strategy). Fifty micrograms of internal standard was labeled with 400 pmoles of Cy2 dye. The internal standard was generated by pooling equal aliquots from all samples. The samples were left on ice for 30 min in dark for fluorescent labeling. Reactions were stopped by adding 1 μL of 10 mM L-lysine (Sigma) followed by incubation in the dark for 10 min.

Quantitative Western Blots

Protein lysates were separated on 12% SDS-PAGE gels (Invitrogen) using 3-(N-morpholino)propanesulfonic acid (Invitrogen) buffer at 200 V for 50 min. Proteins were transferred onto a nitrocellulose membrane (GE Healthcare) in the presence of 20 mM Tris, 0.15 M glycine, and 20% methanol at 100 V for 1 h. Membranes were blocked in 5% skim milk in phosphatebuffered saline with 0.05% Tween (PBST) and probed with primary and secondary antibodies, each for 1 h, with rocking. Primary antibodies used were PDI A6, BiP, SOD 2, Prdx 3, and HSP60. Proteins were visualized using Western Lighting

Isoelectric Focusing and SDS-PAGE

Immobiline DryStrip gels (3−11 nonlinear) (GE Healthcare) were rehydrated overnight at room temperature with Destreak rehydration solution (GE Healthcare) and 1% ampholytes. The pooled samples containing sample buffer were loaded on to the rehydrated strips using anodic cup loading, and isoelectric B



Article

Figure 1. Pie charts showing subcellular localization and biological processes of identified proteins in NIT-1 and αTC-1 cell lines. (A) Venn diagram showing the overlap of uniquely identified proteins between the NIT-1 and αTC-1 cell lines. Unique proteins from both cell lines were categorized on the basis of subcellular localization for (B) NIT-1 and (D) αTC-1 and on the basis of biological processes for (C) NIT-1 and (E) αTC-1 using STRAP software. Number of proteins and percentage are shown on the pie chart.

the role of resident alpha and beta cells in this disease directly in vivo. Therefore, in addition to studying islets isolated from NOD mice, we analyzed homogeneous cell populations of murine alpha (αTC-1) and beta (NIT-1) cell lines to understand the role and differential survival of the two predominant cell populations in islets when they are exposed to cytokines. The data set obtained in this study can be further utilized for analysis of beta cell death in isolated pancreatic islets derived from diabetes-prone NOD mice.

Chemiluminescence (PerkinElmer) and photographed using the Kodak IS4000 camera and Kodak Image Station software (Kodak, USA). The expression signal was calculated using a densitometer (Bio-Rad), and the expression levels were normalized against Coomassie blue-stained gels that were run in parallel with the immunoblotted SDS-PAGE gels.

■

RESULTS T1D is a complex disease involving the interplay of many cell types as the disease progresses. The temporal heterogeneity of pancreatic islet cellular composition makes it hard to understand

Proteomic Analysis of NIT-1 and αTC-1 Cell Lines

In order to characterize the NIT-1 and αTC-1 cell lines, the proteome of these two cell lines was interrogated by 2DGE, and C



Article

the resolved protein species were characterized by MALDI TOF/TOF MS. A total of 936 and 1013 protein spots were selected for in-gel tryptic digest for NIT-1 and αTC-1 cells, respectively (Supporting Information Table 3 and 4). The software was able to detect faintly stained protein spots that were not visible by eye. Of the identified proteins, 655 and 659 proteins were unique in NIT-1 and αTC-1 cells, respectively. A total of 310 proteins were present in both cell lines, whereas 345 and 349 identified proteins were exclusive to NIT-1 and αTC-1 cells, respectively (Figure 1A). Biological processes and subcellular localizations of all proteins were extracted from the gene ontology (GO) database using STRAP software.24,25 In both cell lines, the majority of identified proteins were found to be localized in the nucleus, cytoplasm, and mitochondria in roughly equivalent proportions (Figure 1B,D). The biological process analysis revealed that the identified proteins are involved in a variety of cellular functions, regulation, and metabolic processes, and, again, a similar distribution of biological processes for the identified proteins was observed between the two cell lines (Figure 1C,E). Identification of Differentially Expressed Proteins in Cytokine-Treated NIT-1 and αTC-1 Cell Lines

A hallmark of diabetes is the selective destruction of the insulinproducing beta cells following an inflammatory lesion. We therefore sought to examine cytokine-induced changes in protein expression in beta and alpha cell-derived cell lines in order to further understand the differential responsiveness of these two cell types in the pancreas. NIT-1 and αTC-1 cells were treated with either IFN-γ + IL-1β or IFN-γ + TNF-α for 24 h, as these combinations of cytokines were observed to induce maximal cell death and changes in protein expression in NIT-1 cells.26 Approximately 900 protein spots were detected and matched in all of the gels in NIT-1 cells, and approximately 1000 protein spots were detected and matched in the αTC-1 cell line. Supporting Information Figure 1 shows the overlay of Typhoon scanned gels. The number of protein spots that were differentially expressed at a p value < 0.05 in beta cells was 27 and 31 for the IFN-γ + IL-1β and IFN-γ + TNF-α treated cells, respectively. Of these, 45 protein spots were identified by MS (Supporting Information Table 5). Similarly, in alpha cells, 23 and 32 protein spots were differentially expressed in IFN-γ + IL-1β and IFN-γ + TNF-α treated cells, respectively, and 42 protein spots were identified by MS (Supporting Information Table 6). In both NIT-1 and αTC-1 cell lines, cytokine treatment altered the expression levels of proteins involved in glucose (Krebs cycle) and lipid metabolism, such as succinate dehydrogenase and dihydrolipoyl dehydrogenase. Treatment with cytokines also altered proteins involved in RNA and protein synthesis, protein degradation, and cytoskeletal rearrangement. Since most proteins work together in networks, the interactions of the altered proteome were analyzed by Ingenuity Pathway Analysis (IPA) software (www.ingenuity.com). A network of interaction was obtained that suggests cross-talk between the differentially expressed proteins (Figure 2). As expected, following cytokine stimulation, NF-κB was placed in the center of the network for both NIT-1 and αTC-1 cells; however, the interactions of proteins with NF-κB differed between the two cell lines. In NIT-1 cells, HSP 90 and proteasome associated proteins were interacting partners, indicating that they are the central players in cytokine-induced pathways in these cells. Conversely, in αTC-1 network analysis, superoxide dismutase 2 (SOD2) was placed at the center of the

Figure 2. Protein interaction network of differentially expressed proteins in cytokine-treated NIT-1 and αTC-1 cells. Network analysis was performed using Ingenuity Pathway Analysis software. Interaction networks of differentially expressed proteins in (A) NIT-1 cells and (B) αTC-1 cells. Differentially expressed proteins that were identified in this study are colored in gray. White shapes are proteins that were added to the network by IPA based on their connectivity with dysregulated proteins. Solid arrows represent direct interactions that have been documented in the Ingenuity Knowledgebase. Dotted arrows represent indirect interactions, and the same shape symbolizes a different set of proteins classified under the same group. The data represents the consensus from biological triplicate experiments.

interactome, and proteasome associated proteins were also noted to be interacting partners. Notably, the major difference between cytokine-treated NIT-1 and αTC-1 cells was observed for the category of defense against reactive oxygen species (ROS). D



Article

Figure 3. Validation of 2D-DIGE results by quantitative immunoblotting. Total cell lysates from NIT-1 and αTC-1 cells, untreated and IFN-γ + TNF-α treated, were loaded with two different loadings and separated on SDS-PAGE gels. Immunoblot was performed using one gel, and the membrane was probed with HSP 60, SOD2, and peroxiredoxin 3 antibodies (A). Immunofluorescence levels were normalized against total protein in a Coomassiestained duplicate gel with identical loadings (B). Densitometry analysis was performed to analyze the fold difference, which is reported below each blot.

Increased Proteome Coverage by Subcellular Fractionation

These two cell types appear to respond differently towards scavenging ROS, with a significant increase in the levels of SOD2 only observed in αTC-1 cells, suggesting that NIT-1 cells have poor defence response against ROS rendering them susceptible to oxidative stress. This finding is consistent with previous observations that showed that beta cells have low expression levels of antioxidant species.27−31 Additionally, a greater fold increase in proteasome activator complex subunit 1 (upregulated by 2.39-fold) and 26S proteasome (upregulated by 2.32-fold) was observed in cytokine-treated NIT-1 cells compared to that in αTC-1 cells. This is consistent with our previous findings that antigen processing is upregulated in beta cells following cytokine treatment.32

After investigating the effects of cytokine treatments on beta and alpha cell lines, the effects of cytokine exposure was investigated in mouse islets. Because islets are composed of a mixture of endocrine cells, we were concerned that the combined proteome may mask the effects of individual cell types and thus sought to enhance the number of protein species that we could observe by using subcellular fractionation. This process produced three fractions (cytosol, membrane/organelle, and nucleus). 2DGE analysis of the subcellular fractions demonstrated enrichment of proteins in each fraction with different spotting patterns compared to that of the whole cell lysate (Supporting Information Figure 2). Approximately three times more proteins spots were visible after subcellular fractionation.

Validation of Selected Differentially Expressed Proteins by Quantitative Western Blot

To validate 2D-DIGE results, quantitative western blots were performed on a number of selected proteins on untreated and a combination of IFN-γ + TNF-α treated beta and alpha cell lines. In particular, proteins involved in oxidative stress response such as SOD2 and peroxiredoxins were investigated. The samples were loaded onto replicate SDS-PAGE gels. One gel was stained with Coomassie blue, whereas the proteins in the second gel were transferred onto nitrocellulose membranes and probed with antibodies against SOD2 and peroxiredoxin 3. Densitometric analysis was performed on the Coomassie-stained gel and on bands western blot membranes. Graphs of sample loadings versus densitometric intensity were plotted to ensure that chemiluminescence signals were within the linear range (r > 0.9). Total protein levels were normalized using the Coomassiestained gel, as described.33,34 Immunoblots and Coomassiestained gels are depicted in Figure 3, panels A and B, respectively. Densitometric evaluation performed on immunoblots showed a 1.3- and 3-fold increase in peroxiredoxin 3 and SOD2 levels, respectively, in IFN-γ + TNF-α treated αTC-1 cells. Negligible changes were observed in SOD2 levels in IFN-γ + TNF-α treated NIT-1 cells. The changes observed with quantitative immunoblots were consistent with DIGE results.

Proteomic Analysis of Isolated Mouse Islets

The proteome of islets from young NOD mice was surveyed to obtain a data set on the protein composition of the islets relative to the cell lines studied earlier. 2DGE and mass spectrometric analysis were performed on subcellular fractions from islets that were isolated from 6 week old NOD mice. Each gel contained approximately 1000 protein spots. Approximately 86−88% of excised protein spots were identified in the cytosol and membrane/organelle fraction, and 77% of proteins were identified in the nuclear fraction (Supporting Information Tables 7−9). A total of 1202 unique proteins were identified by MS. The biological process and subcellular localization of proteins are depicted in Figure 4. As anticipated, the majority of identified proteins were found to be localized in the mitochondria, cytoplasm, and nucleus (Figure 4A). Biological process analysis revealed that most proteins were involved in cellular functions, regulation, and metabolic processes (Figure 4B). Proteome analysis of NIT-1 and αTC-1 cells and islets showed that approximately 65 and 61% of the NIT-1 and αTC-1 detectable proteome was detected within islets, respectively (Figure 4C). E



Article

Figure 4. Pie charts showing subcellular localization and biological processes of identified proteins in isolated mouse islets. Identified proteins from all subcellular fractions were pooled together, and unique proteins were categorized on the basis of (A) subcellular localization and (B) biological process using STRAP software. (C) Venn diagram showing overlap of the proteome among NIT-1 cells, islets, and αTC-1 cells.

Identification of Differentially Expressed Proteins in Cytokine-Treated Mouse Islets

identified peptides. Sequence coverage information is provided in Supporting Information Tables 7−9. As expected, some of the identified protein spots were represented in more than one spot, reflecting post-translational modifications or alternative splicing. A total of 22 proteins were present in both cytokinetreated NIT-1 cells and islets, and a total of 19 proteins were present in both cytokine-treated αTC-1 cells and islets (Figure 5A). Proteins involved in the metabolism of glucose (Krebs cycle and glycolysis) and lipids were changed in islets treated with cytokines. This was also observed in both cytokine-treated NIT-1 and αTC-1 cells. Cytokine treatment also altered expression levels of proteins involved in RNA and protein synthesis and degradation, a pathway that was also observed to be altered in the cytokine-treated NIT-1 and αTC-1 cells. In addition to this, islet precursor hormone (proinsulin and proglucagon) levels increased with cytokine treatment, perhaps due to decreased conversion of proinsulin to insulin. Previous studies have shown that cytokine treatment causes an increase in the amount of proinsulin in islets.35−37 Chaperones/foldases that are involved in protein folding, such as PDI isoforms and ERO1Lβ, were also altered. Analysis of the differentially expressed proteins in islets following cytokine treatment revealed two interactome networks

To identify proteins that are altered with cytokine treatment in islets, 2D-DIGE was performed. Briefly, ∼10 000 islets were isolated from 6 week old NOD mice and incubated with either IFN-γ alone, a combination of IFN-γ, TNF-α, and IL-1β, or left untreated for 24 h. Protein labeling was performed as described in Supporting Information Table 2. A total of 438 unique proteins were found to be differentially expressed in the cytosol, membrane/organelle, and nuclear fractions at a protein abundance change cut off of 1.3-fold. The Venn diagrams (Supporting Information Figure 3) show the number of proteins that were changed in islets when treated with IFN-γ alone and with the combination of the 3 cytokines, IFN-γ + TNF-α + IL-1β. In the cytosol fraction, nearly the same number of proteins changed in both treatments; however, in the membrane/organelle and nuclear fractions, the majority of changes occurred only with the triple cytokine treatment. The identified proteins were classified in the same groups as mentioned above, with islet hormones as an additional group. Supporting Information Table 10 shows the full list of identified proteins with spot number, full protein name, IPI accession number, MS score, MS/MS score, and number of unique F



Article

(Figure 5). In the first interactome (Figure 5B), the central players were TAR DNA-binding protein 43 (TARDBP) and heterogeneous nuclear ribonucleoprotein (hnRNP). Both proteins are involved in regulation of transcription and alternative splicing of mRNA. hnRNP has also been shown to play a role in regulation of apoptosis.38 Proteins involved in the second interactome (Figure 5C) were NFκB, SOD 1 and 2, and different isoforms of peroxiredoxins. This network interactome is indicative of involvement of reactive oxygen species and oxidative stress triggered by cytokine treatment. Network interactome analysis revealed that proteins involved in cellular stress response and defense against reactive oxygen species played a central role in cytokine-treated islets. Of note, NF-κB was placed in the center of the interactome network of cytokine-treated islets. NF-κB was also placed in the center for both the NIT-1 and αTC-1 interactome networks. However, there were differences in the other proteins that were interacting with NF-κB in NIT-1 and αTC-1 cells. In NIT-1 cells, the surrounding proteins were heat shock proteins and proteasome associated proteins, as opposed to αTC-1 cells in which free radical scavenging enzymes such as SOD2 and peroxiredoxins predominated. In islets, heat shock proteins were altered; most of them showed lower expression levels in islets exposed to cytokines. An exception was a protein spot identified as HSP60 and HSP1, which exhibited a 10-fold increased expression. The majority of the proteins assigned to the defense group were antioxidants involved in the elimination of free radicals. SOD1 and 2 were increased only in the combined cytokine treatment, no change was observed in catalase levels, and glutathione peroxidase was increased only with IFN-γ treatment alone in the cytosol and membrane fractions. There was an increase in glutathione peroxidase in the nuclear fraction in the presence of all cytokines. Peroxiredoxins were decreased with cytokine treatment except for peroxiredoxin 5 and 6, which were increased with IFN-γ treatment, and no further increase was observed upon exposure to the combination of the three cytokines in the cytosol and membrane/organelle fractions. Presumably, the highest production of free radicals in islets is under this condition. Together, these data suggest that cytokine treatment leads to an accumulation of ROS, particularly hydrogen peroxide, in the mitochondria of islets due to lack of antioxidant scavenging molecules such as peroxiredoxin 3. Furthermore, the altered levels of heat shock proteins are suggestive of cellular stress in islets. Validation of Selected Differentially Expressed Proteins by Quantitative Western Blot

Proteins involved in oxidative and ER stress, such as SOD2, peroxiredoxin 3, immunoglobulin binding protein (BiP), and protein disulfide isomerize A6 (PDI A6), were selected for further validation by quantitative immunoblots. BiP, which is a molecular chaperone, has been shown to play a crucial role in cell survival during ER stress. PDI A6 is an ER resident protein that catalyzes formation, reduction, and isomerization of disulfide bonds and therefore may be involved in the folding of proinsulin. Quantitative immunoblots were performed on untreated islets, islets treated with IFN-γ alone, and islets treated with a combination of IFN-γ, IL-1β, and TNF-α. Immunoblots were probed with antibodies raised against SOD2, peroxiredoxin 3, PDI A6, HSP60, and BiP. Immunoblots and Coomassie-stained gels are depicted in Figure 6, panels A and B, respectively. Densitometric evaluation showed a 1.9-fold increase in SOD2 levels in islets treated with a combination of three cytokines.

Figure 5. Network analysis of altered proteome with cytokine treatment of isolated mouse islets. (A) Venn diagram showing the overlap of uniquely identified proteins in cytokine-treated NIT-1 and αTC-1 cells and islets. Differentially expressed proteins in cytokine-treated islets were analyzed by IPA software to investigate the cross-talk between proteins. Network analysis showing (B) TARDBP and hnRNP and (C) SOD and peroxiredoxins as central players in cytokine-mediated death of beta cells. Differentially expressed proteins that were identified in this study are colored in gray. White shapes are proteins that were added to the network by IPA based on their connectivity with dysregulated proteins. Solid arrows represent direct interactions that have been documented in the Ingenuity Knowledgebase. Dotted arrows represent indirect interactions, and the same shape symbolizes a different set of proteins classified under the same group. G



Article

Figure 6. Validation of selected protein changes by quantitative immunoblots. Whole cell lysates from untreated islets, islets treated with IFN-γ alone, and islets treated with a combination of three cytokines, IFN-γ, TNF-α, and IL-1β, were loaded with three different loadings and separated on SDSPAGE gels. Immunoblots were performed using antibodies raised against HSP 60, SOD2, peroxiredoxin 3, PDIA6, and BiP (A). The chemiluminescence signal was normalized against total protein determined by Coomassie staining of a duplicate gel (B). Densitometry analysis was performed to calculate fold difference.

This finding is consistent with the DIGE results. A 1.8-fold increase in PDI A6 levels in islets treated with IFN-γ was also apparent; however, no substantial change was observed in islets treated with a combination of three cytokines. This is inconsistent with the DIGE results, where a 1.75-fold increase was observed in islets treated with a combination of three cytokines. The reason behind this discrepancy remains to be determined. Consistent with DIGE results, quantitative immunoblots showed no change in BiP and peroxiredoxin 3 levels in cytokine-treated islets. DIGE analysis also showed one protein spot identified as HSP60 and HSP1 to be upregulated by 10-fold. Quantitative immunoblotting revealed that there was no change in HSP60. Therefore, the 10-fold increase in the protein would most likely be associated with HSP 1 or a nonreactive isoform of HSP60.

■

identification of insulin and glucagon in these cell lines was anticipated because they are not resolved on 2DGE due to their low molecular weight. Another limitation of 2DGE is the under representation of membrane proteins, as they are hydrophobic and therefore not soluble. In the present study, the proteome of mouse islets was also characterized. Due to subcellular fractionation of islets, approximately 3000 protein spots were visualized on 2DGE, and 1241 unique proteins were identified by mass spectrometric analysis. Earlier characterization of mouse islets using 2DGE led to the identification of 144 proteins.40−42 The identification of proteins in this study adds a total of 1058 new proteins to the list of 2DGE resolved and identified species in the pancreatic proteome. In comparison, using a LC−MS/MS strategy, Waanders et al. identified around 7000 proteins from mouse pancreatic islets,43 which encompasses all of the identified proteins in this study. The point of differentiation was that their study examined the effect of glucose concentration on around 2000 proteins in single islets using the LC−MS/MS strategy. This is in line with the number of proteins assessed for differential expression in our cytokine treatment regime using 2D-DIGE. Exposure of islets to high glucose caused an increase in the levels of SOD2,43 which was also increased in our study of cytokine treatment. This suggests that oxidative stress is involved in both treatment conditions and therefore suggests a link between hyperglycemia and inflammatory stress.

DISCUSSION

Proteome of Beta Cells, Alpha Cells, and Islets

In the current study, the proteomes of pancreatic beta (NIT-1) and alpha (αTC-1) cell lines as well as mouse islets were characterized. A comprehensive understanding of beta cell biology and how the proteome is affected under various experimental conditions can provide valuable insights into the mechanisms involved in the development of both type 1 and type 2 diabetes. The total proteome of NIT-1 cells has not been studied before. However, Lee et al. studied the proteome of vesicles secreted from NIT-1 cells.39 The authors identified 270 proteins, and this is the most proteins identified from NIT-1 cells to date. In the current work, 655 unique proteins were identified in NIT-1 cells using 2DGE and mass spectrometry. All of the proteins that were identified in the vesicle proteome were also identified in the current NIT-1 proteome study. The proteome of αTC-1 cells was unexplored before now. In this study, 659 unique proteins were successfully identified. Although insulin itself was not identified in the NIT-1 proteome, proteins involved in the secretion and processing of insulin were identified, such as secretagogin and neuroendocrine convertase 2. Similarly, glucagon was not identified in αTC-1 cells. The lack of

Cytokine-Responsive Proteins in Cell Lines and Islets

In addition to whole proteome analysis, 2D-DIGE was utilized to unveil the global pattern of proteins altered in NIT-1 and αTC-1 cell lines as well as in whole islets treated with proinflammatory cytokines (IFN-γ, TNF-α, and IL-1β). Treatment with different combinations of cytokines for 24 h resulted in expression level changes in a total of 56 proteins in NIT-1 cells and 50 proteins in αTC-1 cells at p < 0.05. Previous proteomics studies investigating the effect of cytokine treatment used whole islets and focused on single cytokine (IL-1β) stimulation.44,45 Subcellular fractionation was utilized to increase the proteome coverage to account for the more complex cellular composition of islets. After performing H



Article

This result is in line with a study performed by Ortis et al.,46 where microarray analysis was performed on cytokine-treated beta cells from rat islets. They observed no change in peroxiredoxin 3. A lack of increase in peroxiredoxin 3 levels would potentially result in a high local production of hydrogen peroxide, which, in turn, could lead to mitochondrial dysfunction and affect oxidative phosphorylation. Studies aiming at scavenging free radicals, by overexpressing antioxidant enzymes such as SOD2, catalase, or peroxiredoxins,50,51 have been successful in preventing cytokine-induced apoptosis in beta cell lines. However, there are controversial results in the protection of islets and NOD mice depending on the antioxidant used. A study by Chen et al. showed that islets overexpressing SOD2 and catalase provided no protection against cytokine-induced death.52 One possible reason that these islets were not protected could be because catalase was shown to be localized to the cytoplasm and thus it would be effective in scavenging cytoplasmic but not mitochondrial hydrogen peroxide. It has been shown by Gurgul et al. that overexpression of mitochondrial catalase, as opposed to cytoplasmic catalase, preferentially protected against cytokineinduced death.53 Overall, these observations suggest that the mitochondrial redox state is important for the survival of beta cells. From the current proteomics study, it was found that peroxiredoxin 3 expression was not upregulated in the cytokine-treated islets. This suggests that islets lack the full defense response against oxidative stress, making them vulnerable to this stress. As detoxification of ROS in mitochondria requires both SOD2 and peroxiredoxin 3, it can be speculated that overexpression of both SOD2 and peroxiredoxin 3 would provide maximum protection against mitochondrial reactive oxygen species and probably protect beta cells from oxidative stress.

subcellular fractionation on islets, expression changes were observed in a total of 438 unique proteins in islets with a combined cytokine treatment for 24 h. Proteins that were altered in islets were also observed to be changed in the expression levels in the NIT-1 cells. This is expected, as 80% of cells in islets are beta cells. Furthermore, it also suggests that NIT-1 and αTC-1 cell lines are useful tools to understand changes in islets. The dysregulated pathways with cytokine treatment were similar in cell lines and islets. However, understanding the pathways first in the cell lines helped us to differentiate which pathways were operational in alpha or beta cells in islets. Under inflammatory conditions, it appears that beta cells are affected the most and that both beta and alpha cells act independently in response to cytokine exposure. Increase in Oxidative Defense Proteins in αTC-1 Cells but Not in NIT-1 Cells

Oxidative stress has been shown to play a major role in cytokineinduced beta cell death. Comparison of cytokine-treated NIT-1 and αTC-1 cells revealed that αTC-1 cells responded to cytokine treatment by increasing the levels of antioxidant enzymes such as SOD2 and peroxiredoxin 3. Conversely, in NIT-1 cells, only thioredoxin domain-containing protein 12 was observed to increase in response to cytokine treatment. These data suggests that free radicals were generated upon treatment with cytokines in both NIT-1 and αTC-1 cells. However, NIT-1 cells appear to be less capable of scavenging the free radicals, as the expression levels of antioxidant enzymes, which are able to inactivate ROS and prevent oxidative stress, remained unchanged, thus rendering them susceptible to oxidative stress. Previous studies have reported a low content of antioxidant enzymes in beta cells. However, in the current study, the basal expression levels of antioxidant enzymes such as SOD2 in NIT-1 cells appeared to be of a similar amount to that in αTC-1 cells from quantitative western blots. The defect in NIT-1 cells appeared to be in the induction of the expression of SOD2 and other antioxidant molecules such as peroxiredoxin 3. In contrast, the expression levels of the antioxidant enzymes SOD2 and peroxiredoxin 3 increased in αTC-1 cells, thus preventing oxidative stress in these cells. Together, these data suggest that NIT-1 cells have a lack of defense response against free radicals when compared to that in αTC-1 cells.

ER Stress and BiP

Apart from oxidative stress, ER stress has also been implicated in the death of beta cells.54 ER stress triggers the unfolded protein response (UPR), which involves decreasing the influx of proteins to ER, increasing the amount of ER chaperones, and degrading misfolded protein.55 An increase in the expression levels of chaperones/folding enzymes, such as PDI A6/P5, ERp29, PDIA3, and ERO1 beta, was observed in islets treated with cytokines. Presumably, the increase in chaperone levels is part of the UPR that assists misfolded protein in achieving their correct conformation. This indicates that beta cells experience ER stress when exposed to cytokines; however, upregulation of BiP is considered to be crucial for cell survival during ER stress.55 In the current study, no change was observed in BiP, and this observation is in concordance with a study performed by Cardozo et al.56 Therefore, it is possible that the failure to induce increased BiP expression deprives beta cells from an important mechanism for cell survival during ER stress.55 To explore the role of BiP in cytokine-induced ER stress, Wang et al. overexpressed BiP in NIT-1 cells.57 These cells were partially protected from apoptosis induced by cytokines.57 Together, these data suggest that beta cells experience ER stress under inflammatory conditions. However, they lack a crucial BiPmediated mechanism for cell survival during ER stress and therefore undergo apoptosis. In conclusion, this study characterized the proteomes of NIT-1 cells, αTC-1 cells, and islets and examined the effect of proinflammatory cytokines on protein expression. DIGE results, which were validated by quantitative immunoblot,

Increased Levels of SOD2 in Islets Exposed to Cytokines

In addition to understanding the proteins that were differentially expressed in alpha and beta cell lines, the global protein expression pattern was also investigated in cytokine-treated islets. An increase in SOD2 expression levels were observed in the cytokine-treated islets, and this observation is in agreement with published findings from microarray46 and western blot15 analysis. The increase in SOD2 points toward a protective response of the islets against cytokine-induced ROS formation. However, it has been shown that longer exposure of beta cells to cytokines results in downregulation of SOD2, further aggravating beta cell death.15 SOD2 is expressed in mitochondria, where it converts superoxide anion radicals, which can react with nitric oxide to form reactive peroxynitrite and hydrogen peroxide.47 Hydrogen peroxide is toxic, and it can lead to production of extremely reactive hydroxyl radicals,48,49 if they are not converted to water by catalase, glutathione peroxidase, or peroxiredoxins. In this study, no change was observed in catalase levels, and glutathione peroxidase levels were seen to increase only in the nuclear fraction. Furthermore, DIGE results and quantitative immunoblot showed no increase in a mitochondrial specific peroxiredoxin 3. I



Article

(2) Kagi, D.; Odermatt, B.; Seiler, P.; Zinkernagel, R. M.; Mak, T. W.; Hengartner, H. Reduced incidence and delayed onset of diabetes in perforin-deficient nonobese diabetic mice. J. Exp. Med. 1997, 186, 989− 97. (3) Amrani, A.; Verdaguer, J.; Anderson, B.; Utsugi, T.; Bou, S.; Santamaria, P. Perforin-independent beta-cell destruction by diabetogenic CD8+ T lymphocytes in transgenic nonobese diabetic mice. J. Clin. Invest. 1999, 103, 1201−9. (4) Savinov, A. Y.; Tcherepanov, A.; Green, E. A.; Flavell, R. A.; Chervonsky, A. V. Contribution of Fas to diabetes development. Proc. Natl. Acad. Sci. U.S.A. 2003, 100, 628−32. (5) Allison, J.; Thomas, H. E.; Catterall, T.; Kay, T. W.; Strasser, A. Transgenic expression of dominant-negative Fas-associated death domain protein in beta cells protects against Fas ligand-induced apoptosis and reduces spontaneous diabetes in nonobese diabetic mice. J. Immunol. 2005, 175, 293−301. (6) Angstetra, E.; Graham, K. L.; Emmett, S.; Dudek, N. L.; Darwiche, R.; Ayala-Perez, R.; Allison, J.; Santamaria, P.; Kay, T. W.; Thomas, H. E. In vivo effects of cytokines on pancreatic beta-cells in models of type I diabetes dependent on CD4+ T lymphocytes. Immunol. Cell Biol. 2009, 87, 178−85. (7) Mandrup-Poulsen, T. The role of interleukin-1 in the pathogenesis of IDDM. Diabetologia 1996, 39, 1005−29. (8) Hoorens, A.; Pipeleers, D. Nicotinamide protects human beta cells against chemically-induced necrosis, but not against cytokine-induced apoptosis. Diabetologia 1999, 42, 55−9. (9) Pavlovic, D.; Chen, M. C.; Gysemans, C. A.; Mathieu, C.; Eizirik, D. L. The role of interferon regulatory factor-1 in cytokine-induced mRNA expression and cell death in murine pancreatic beta-cells. Eur. Cytokine Network 1999, 10, 403−12. (10) Nerup, J.; Mandrup-Poulsen, T.; Helqvist, S.; Andersen, H. U.; Pociot, F.; Reimers, J. I.; Cuartero, B. G.; Karlsen, A. E.; Bjerre, U.; Lorenzen, T. On the pathogenesis of IDDM. Diabetologia 1994, 37, S82−9. (11) Rabinovitch, A. An update on cytokines in the pathogenesis of insulin-dependent diabetes mellitus. Diabetes/Metab. Rev. 1998, 14, 129−51. (12) Eizirik, D. L.; Pavlovic, D. Is there a role for nitric oxide in beta-cell dysfunction and damage in IDDM? Diabetes/Metab. Rev. 1997, 13, 293−307. (13) Delaney, C. A.; Pavlovic, D.; Hoorens, A.; Pipeleers, D. G.; Eizirik, D. L. Cytokines induce deoxyribonucleic acid strand breaks and apoptosis in human pancreatic islet cells. Endocrinology 1997, 138, 2610−4. (14) Cardozo, A. K.; Heimberg, H.; Heremans, Y.; Leeman, R.; Kutlu, B.; Kruhoffer, M.; Orntoft, T.; Eizirik, D. L. A comprehensive analysis of cytokine-induced and nuclear factor-kappa B-dependent genes in primary rat pancreatic beta-cells. J. Biol. Chem. 2001, 276, 48879−86. (15) Papaccio, G.; Graziano, A.; D’Aquino, R.; Valiante, S.; Naro, F. A biphasic role of nuclear transcription factor (NF)-kappaB in the islet beta-cell apoptosis induced by interleukin (IL)-1beta. J. Cell. Physiol. 2005, 204, 124−30. (16) Gysemans, C. A.; Ladriere, L.; Callewaert, H.; Rasschaert, J.; Flamez, D.; Levy, D. E.; Matthys, P.; Eizirik, D. L.; Mathieu, C. Disruption of the gamma-interferon signaling pathway at the level of signal transducer and activator of transcription-1 prevents immune destruction of beta-cells. Diabetes 2005, 54, 2396−403. (17) Sparre, T.; Christensen, U. B.; Gotfredsen, C. F.; Larsen, P. M.; Fey, S. J.; Hjerno, K.; Roepstorff, P.; Pociot, F.; Karlsen, A. E.; Nerup, J. Changes in expression of IL-1 beta influenced proteins in transplanted islets during development of diabetes in diabetes-prone BB rats. Diabetologia 2004, 47, 892−908. (18) Sparre, T.; Christensen, U. B.; Mose Larsen, P.; Fey, S. J.; Wrzesinski, K.; Roepstorff, P.; Mandrup-Poulsen, T.; Pociot, F.; Karlsen, A. E.; Nerup, J. IL-1beta induced protein changes in diabetes prone BB rat islets of Langerhans identified by proteome analysis. Diabetologia 2002, 45, 1550−61. (19) Sparre, T.; Larsen, M. R.; Heding, P. E.; Karlsen, A. E.; Jensen, O. N.; Pociot, F. Unraveling the pathogenesis of type 1 diabetes with

suggest that beta cells are susceptible to reactive oxygen species generated by beta cells themselves or by islet-infiltrating immune cells. Beta cells do not appear to have an effective free radical scavenging mechanism; in particular, the mitochondrial defense mechanisms, such as SOD2 and peroxiredoxin 3, fail to be induced upon cytokine treatment. In addition to oxidative stress, changes in ER chaperones, leading to misfolded protein and ER stress, appears to be playing a role in cytokine-mediated death of beta cells. The complex cellular response to inflammation in the islets also leads to enhanced antigen presentation, which completes a three-way insult on the beta cells, rendering these already fragile cells targets of infiltrating T lymphocytes. From this study, the cell source of proteins that were differentially expressed in the islets was inferred from changes in pathways observed in alpha and beta cell lines. Therefore, in the future, immunohistochemistry or confocal microscopy on isolated islets can be used to identify the source of differentially expressed proteins in islets.

■

ASSOCIATED CONTENT

* Supporting Information S

Table 1: CyDye labeling of protein samples from NIT-1 and αTC-1. Table 2: CyDye labeling of protein samples from subcellular fractionation of islets. Table 3: NIT-1 proteome. Table 4: αTC-1 proteome. Table 5: Differentially expressed proteins in cytokine-treated NIT-1. Table 6: Differentially expressed proteins in cytokine-treated αTC-1. Table 7: Islets proteome (cytosol). Table 8: Islets proteome (membrane/ organelle). Table 9: Islets proteome (nuclear). Tables 10−12: Differentially expressed proteins in cytokine treated islets (cytosol, membrane, and nuclear, respectively). Figure 1: Overlay of DIGE gel images. Figure 2: 2D gels of NIT-1 subcellular fractions. Figure 3: Number of proteins changed in islets subjected to different cytokine treatments. This material is available free of charge via the Internet at http://pubs.acs.org.

■

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: +613 9902 9265. Fax: +613 9902 9500. Present Address #

(H.S.-H.) Department of Biology, University of Utah, Salt Lake City, Utah 84112, United States. Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS This work was supported by a grant from the Juvenile Diabetes Research Foundation International (17-2012-134). A.W.P. acknowledges fellowship support from the Australian National Health and Medical Research Council. H.S.-H. is supported by a Marie Curie Fellowship from the European Union (CONBIOS 330486). M.J.H. acknowledges fellowship support from Melbourne Research Unit for Facial Disorders.

■

REFERENCES

(1) Kagi, D.; Odermatt, B.; Ohashi, P. S.; Zinkernagel, R. M.; Hengartner, H. Development of insulitis without diabetes in transgenic mice lacking perforin-dependent cytotoxicity. J. Exp. Med. 1996, 183, 2143−52. J



Article

proteomics: present and future directions. Mol. Cell. Proteomics 2005, 4, 441−57. (20) D’Hertog, W.; Overbergh, L.; Lage, K.; Ferreira, G. B.; Maris, M.; Gysemans, C.; Flamez, D.; Cardozo, A. K.; Van den Bergh, G.; Schoofs, L.; Arckens, L.; Moreau, Y.; Hansen, D. A.; Eizirik, D. L.; Waelkens, E.; Mathieu, C. Proteomics analysis of cytokine-induced dysfunction and death in insulin-producing INS-1E cells: new insights into the pathways involved. Mol. Cell. Proteomics 2007, 6, 2180−99. (21) Hamaguchi, K.; Gaskins, H. R.; Leiter, E. H. NIT-1, a pancreatic beta-cell line established from a transgenic NOD/Lt mouse. Diabetes 1991, 40, 842−9. (22) Powers, A. C.; Efrat, S.; Mojsov, S.; Spector, D.; Habener, J. F.; Hanahan, D. Proglucagon processing similar to normal islets in pancreatic alpha-like cell line derived from transgenic mouse tumor. Diabetes 1990, 39, 406−14. (23) Veith, P. D.; O’Brien-Simpson, N. M.; Tan, Y.; Djatmiko, D. C.; Dashper, S. G.; Reynolds, E. C. Outer membrane proteome and antigens of Tannerella forsythia. J. Proteome Res. 2009, 8, 4279−92. (24) Ashburner, M.; Ball, C. A.; Blake, J. A.; Botstein, D.; Butler, H.; Cherry, J. M.; Davis, A. P.; Dolinski, K.; Dwight, S. S.; Eppig, J. T.; Harris, M. A.; Hill, D. P.; Issel-Tarver, L.; Kasarskis, A.; Lewis, S.; Matese, J. C.; Richardson, J. E.; Ringwald, M.; Rubin, G. M.; Sherlock, G. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 2000, 25, 25−9. (25) Bhatia, V. N.; Perlman, D. H.; Costello, C. E.; McComb, M. E. Software tool for researching annotations of proteins: open-source protein annotation software with data visualization. Anal. Chem. 2009, 81, 9819−23. (26) Eizirik, D. L.; Mandrup-Poulsen, T. A choice of deaththe signaltransduction of immune-mediated beta-cell apoptosis. Diabetologia 2001, 44, 2115−33. (27) Eizirik, D. L.; Pipeleers, D. G.; Ling, Z.; Welsh, N.; Hellerstrom, C.; Andersson, A. Major species differences between humans and rodents in the susceptibility to pancreatic beta-cell injury. Proc. Natl. Acad. Sci. U.S.A. 1994, 91, 9253−6. (28) Grankvist, K.; Marklund, S. L.; Taljedal, I. B. CuZn-superoxide dismutase, Mn-superoxide dismutase, catalase and glutathione peroxidase in pancreatic islets and other tissues in the mouse. Biochem. J. 1981, 199, 393−8. (29) Lenzen, S.; Drinkgern, J.; Tiedge, M. Low antioxidant enzyme gene expression in pancreatic islets compared with various other mouse tissues. Free Radical Biol. Med. 1996, 20, 463−6. (30) Tiedge, M.; Lortz, S.; Drinkgern, J.; Lenzen, S. Relation between antioxidant enzyme gene expression and antioxidative defense status of insulin-producing cells. Diabetes 1997, 46, 1733−42. (31) Welsh, N.; Margulis, B.; Borg, L. A.; Wiklund, H. J.; Saldeen, J.; Flodstrom, M.; Mello, M. A.; Andersson, A.; Pipeleers, D. G.; Hellerstrom, C.; et al. Differences in the expression of heat-shock proteins and antioxidant enzymes between human and rodent pancreatic islets: implications for the pathogenesis of insulin-dependent diabetes mellitus. Mol. Med. 1995, 1, 806−20. (32) Dudek, N. L.; Tan, C. T.; Gorasia, D. G.; Croft, N. P.; Illing, P. T.; Purcell, A. W. Constitutive and inflammatory immunopeptidome of pancreatic beta-cells. Diabetes 2012, 61, 3018−25. (33) Pham, H.; Doerrbecker, J.; Ramp, A. A.; D’Souza, C. S.; Gorasia, D. G.; Purcell, A. W.; Ayers, M. M.; Orian, J. M. Experimental autoimmune encephalomyelitis (EAE) IN C57Bl/6 mice is not associated with astrogliosis. J. Neuroimmunol. 2011, 232, 51−62. (34) Shnyder, S. D.; Mangum, J. E.; Hubbard, M. J. Triplex profiling of functionally distinct chaperones (ERp29/PDI/BiP) reveals marked heterogeneity of the endoplasmic reticulum proteome in cancer. J. Proteome Res. 2008, 7, 3364−72. (35) Hostens, K.; Pavlovic, D.; Zambre, Y.; Ling, Z.; Van Schravendijk, C.; Eizirik, D. L.; Pipeleers, D. G. Exposure of human islets to cytokines can result in disproportionately elevated proinsulin release. J. Clin. Invest. 1999, 104, 67−72. (36) Borjesson, A.; Carlsson, C. Altered proinsulin conversion in rat pancreatic islets exposed long-term to various glucose concentrations or interleukin-1beta. J. Endocrinol. 2007, 192, 381−7.

(37) Hansen, B. S.; Nielsen, J. H.; Linde, S.; Spinas, G. A.; Welinder, B. S.; Mandrup-Poulsen, T.; Nerup, J. Effect of interleukin-1 on the biosynthesis of proinsulin and insulin in isolated rat pancreatic islets. Biomed. Biochim. Acta 1988, 47, 305−9. (38) Thiede, B.; Siejak, F.; Dimmler, C.; Rudel, T. Prediction of translocation and cleavage of heterogeneous ribonuclear proteins and Rho guanine nucleotide dissociation inhibitor 2 during apoptosis by subcellular proteome analysis. Proteomics 2002, 2, 996−1006. (39) Lee, H. S.; Jeong, J.; Lee, K. J. Characterization of vesicles secreted from insulinoma NIT-1 cells. J. Proteome Res. 2009, 8, 2851−62. (40) Sanchez, J. C.; Chiappe, D.; Converset, V.; Hoogland, C.; Binz, P. A.; Paesano, S.; Appel, R. D.; Wang, S.; Sennitt, M.; Nolan, A.; Cawthorne, M. A.; Hochstrasser, D. F. The mouse SWISS-2D PAGE database: a tool for proteomics study of diabetes and obesity. Proteomics 2001, 1, 136−63. (41) Nicolls, M. R.; D’Antonio, J. M.; Hutton, J. C.; Gill, R. G.; Czwornog, J. L.; Duncan, M. W. Proteomics as a tool for discovery: proteins implicated in Alzheimer’s disease are highly expressed in normal pancreatic islets. J. Proteome Res. 2003, 2, 199−205. (42) Ahmed, M.; Bergsten, P. Glucose-induced changes of multiple mouse islet proteins analysed by two-dimensional gel electrophoresis and mass spectrometry. Diabetologia 2005, 48, 477−85. (43) Waanders, L. F.; Chwalek, K.; Monetti, M.; Kumar, C.; Lammert, E.; Mann, M. Quantitative proteomic analysis of single pancreatic islets. Proc. Natl. Acad. Sci. U.S.A. 2009, 106, 18902−7. (44) John, N. E.; Andersen, H. U.; Fey, S. J.; Larsen, P. M.; Roepstorff, P.; Larsen, M. R.; Pociot, F.; Karlsen, A. E.; Nerup, J.; Green, I. C.; Mandrup-Poulsen, T. Cytokine- or chemically derived nitric oxide alters the expression of proteins detected by two-dimensional gel electrophoresis in neonatal rat islets of Langerhans. Diabetes 2000, 49, 1819− 29. (45) Larsen, P. M.; Fey, S. J.; Larsen, M. R.; Nawrocki, A.; Andersen, H. U.; Kahler, H.; Heilmann, C.; Voss, M. C.; Roepstorff, P.; Pociot, F.; Karlsen, A. E.; Nerup, J. Proteome analysis of interleukin-1beta-induced changes in protein expression in rat islets of Langerhans. Diabetes 2001, 50, 1056−63. (46) Ortis, F.; Naamane, N.; Flamez, D.; Ladriere, L.; Moore, F.; Cunha, D. A.; Colli, M. L.; Thykjaer, T.; Thorsen, K.; Orntoft, T. F.; Eizirik, D. L. Cytokines interleukin-1beta and tumor necrosis factoralpha regulate different transcriptional and alternative splicing networks in primary beta-cells. Diabetes 2010, 59, 358−74. (47) Maritim, A. C.; Sanders, R. A.; Watkins, J. B., III Diabetes, oxidative stress, and antioxidants: a review. J. Biochem. Mol. Toxicol. 2003, 17, 24−38. (48) Jiang, Z. Y.; Woollard, A. C.; Wolff, S. P. Hydrogen peroxide production during experimental protein glycation. FEBS Lett. 1990, 268, 69−71. (49) Wolff, S. P.; Dean, R. T. Glucose autoxidation and protein modification. The potential role of ‘autoxidative glycosylation’ in diabetes. Biochem. J. 1987, 245, 243−50. (50) Azevedo-Martins, A. K.; Lortz, S.; Lenzen, S.; Curi, R.; Eizirik, D. L.; Tiedge, M. Improvement of the mitochondrial antioxidant defense status prevents cytokine-induced nuclear factor-kappaB activation in insulin-producing cells. Diabetes 2003, 52, 93−101. (51) Wolf, G.; Aumann, N.; Michalska, M.; Bast, A.; Sonnemann, J.; Beck, J. F.; Lendeckel, U.; Newsholme, P.; Walther, R. Peroxiredoxin III protects pancreatic ss cells from apoptosis. J. Endocrinol. 2010, 207, 163−75. (52) Chen, H.; Li, X.; Epstein, P. N. MnSOD and catalase transgenes demonstrate that protection of islets from oxidative stress does not alter cytokine toxicity. Diabetes 2005, 54, 1437−46. (53) Gurgul, E.; Lortz, S.; Tiedge, M.; Jorns, A.; Lenzen, S. Mitochondrial catalase overexpression protects insulin-producing cells against toxicity of reactive oxygen species and proinflammatory cytokines. Diabetes 2004, 53, 2271−80. (54) Cnop, M.; Welsh, N.; Jonas, J. C.; Jorns, A.; Lenzen, S.; Eizirik, D. L. Mechanisms of pancreatic beta-cell death in type 1 and type 2 diabetes: many differences, few similarities. Diabetes 2005, 54, S97−107. K



Article

(55) Eizirik, D. L.; Cardozo, A. K.; Cnop, M. The role for endoplasmic reticulum stress in diabetes mellitus. Endocr. Rev. 2008, 29, 42−61. (56) Cardozo, A. K.; Ortis, F.; Storling, J.; Feng, Y. M.; Rasschaert, J.; Tonnesen, M.; Van Eylen, F.; Mandrup-Poulsen, T.; Herchuelz, A.; Eizirik, D. L. Cytokines downregulate the sarcoendoplasmic reticulum pump Ca2+ ATPase 2b and deplete endoplasmic reticulum Ca2+, leading to induction of endoplasmic reticulum stress in pancreatic beta-cells. Diabetes 2005, 54, 452−61. (57) Wang, M.; Zhao, X. R.; Wang, P.; Li, L.; Dai, Y.; Huang, H.; Lei, P.; Zhu, H. F.; Shen, G. X. Glucose regulated proteins 78 protects insulinoma cells (NIT-1) from death induced by streptozotocin, cytokines or cytotoxic T lymphocytes. Int. J. Biochem. Cell Biol. 2007, 39, 2076−82.

L


Pancreatic Beta Cells Are Highly Susceptible to Oxidative and ER

Recommend Documents