Novel Insights into the Global Proteome Responses of Insulin

Sep 14, 2010 - Insulin-Producing INS-1E Cells To Different Degrees of ... Sequence Analysis, Department of Systems Biology, Technical University of De...
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Novel Insights into the Global Proteome Responses of Insulin-Producing INS-1E Cells To Different Degrees of Endoplasmic Reticulum Stress Wannes D’Hertog,† Michael Maris,† Gabriela B. Ferreira,† Eefje Verdrengh,† Kasper Lage,‡,§,|,⊥ Daniel A. Hansen,‡ Alessandra K. Cardozo,# Christopher T. Workman,‡ Yves Moreau,∇ Decio L. Eizirik,# Etienne Waelkens,O,[ Lutgart Overbergh,*,†,+ and Chantal Mathieu†,+ Laboratory for Experimental Medicine and Endocrinology (LEGENDO), University Hospital Gasthuisberg, Catholic University of Leuven, Herestraat 49, box 902, B-3000 Leuven, Belgium, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Building 208, DK-2800 Kgs. Lyngby, Denmark, Pediatric Surgical Research Laboratories, MassGeneral Hospital for Children, Massachusetts General Hospital, Boston, Massachusetts 02114, Harvard Medical School, Boston, Massachusetts 02115, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, Laboratory for Experimental Medicine, Free University of Brussels, route de Lennik 808, box CP618, B-1070 Brussel, Belgium, ESAT-SDC, Department of Electrical Engineering, Catholic University of Leuven, Kasteelpark Arenberg 10, box 2446, B-3001 Heverlee, Belgium, ProMeta, University Hospital Gasthuisberg, Catholic University of Leuven, Herestraat 49, box 901, B-3000 Leuven, Belgium, and Laboratory of Biochemistry, University Hospital Gasthuisberg, Catholic University of Leuven, Herestraat 49, box 901, B-3000 Leuven, Belgium Received May 5, 2010

Exposure of insulin-secreting β-cells to inflammatory cytokines or high concentrations of free fatty acids, factors involved in the pathogenesis of type 1 and type 2 diabetes, leads to endoplasmic reticulum (ER) stress, β-cell dysfunction, and eventually apoptotic β-cell death. The aim of this study was to investigate the impact of ER stress on β-cells at the protein level to evaluate the contribution of posttranscriptional and post-translational changes in ER stress-induced β-cell damage. INS-1E cells were exposed in vitro to the ER-stress inducer cyclopiazonic acid (CPA) at two concentrations, and protein changes were evaluated using 2D-DIGE. CPA, 25 µM, led to massive apoptosis, accompanied by a near complete protein translation shut-down. CPA, 6.25 µM, led to adaptation of the β-cells to ER stress. Identification of the differentially expressed proteins in the two conditions led to the discovery of a clear pattern of defense pathways, with post-translational modifications playing a crucial role. Key alterations included inhibition of insulin translation and post-translational modifications in ER chaperones HYOU1 and HSPA5. Also, a central role for 14-3-3 proteins is suggested. In conclusion, INS-1E cells are highly sensitive to ER stress, leading to important post-transcriptional and posttranslational modifications that may contribute to β-cell dysfunction and death. Keywords: Type 1 diabetes • 2D-DIGE • INS-1E • endoplasmic reticulum stress

Introduction Pancreatic β-cells are responsible for synthesizing, processing, and secreting insulin into the circulation, thus maintaining normal blood glucose levels, a situation imbalanced in both * Corresponding author. E-mail: [email protected]. Tel.: 0032-16-34.61.63. Fax: 00-32-16-34.60.35. † Laboratory for Experimental Medicine and Endocrinology (LEGENDO), Catholic University of Leuven. ‡ Technical University of Denmark. § Massachusetts General Hospital. | Harvard Medical School. ⊥ Broad Institute of MIT and Harvard. # Free University of Brussels. ∇ Department of Electrical Engineering, Catholic University of Leuven. O ProMeta, Catholic University of Leuven. [ Laboratory of Biochemistry, Catholic University of Leuven. + These authors contributed equally to this work.

5142 Journal of Proteome Research 2010, 9, 5142–5152 Published on Web 09/14/2010

Type 1 and Type 2 diabetic patients. The amount of insulin to be produced in β-cells requires a highly developed endoplasmic reticulum (ER). Proper function of the ER is essential for β-cell survival. Perturbation of its function induces cellular damage, eventually resulting in apoptosis. Various conditions, like inhibition of protein glycosylation, impaired formation of disulfide bonds, and calcium depletion can disturb ER function. Accumulation of unfolded or misfolded proteins in the organelle is met by the unfolded protein response (UPR). The UPR is a protective pathway which decreases ER protein levels and restores ER function by different mechanisms, such as (1) attenuation of protein translation through activation of the PERKseukaryotictranslationinitiationfactor2alpha(eIF2alpha)s pathway; (2) upregulation of ER chaperones through activation of the ATF6sX-box binding protein 1 (XBP1)spathway; (3) degradation of misfolded proteins through activation of the ER 10.1021/pr1004086

 2010 American Chemical Society

Global Proteome Responses of Insulin-Producing INS-1E Cells degradation pathway (ERAD); and (4) halting new protein production via activation of IRE1R.1,2 In the case of prolonged or excessive ER stress, the different steps activated by the UPR response are not sufficient to restore ER homeostasis, and apoptotic pathways are triggered.3 Cyclopiazonic acid (CPA) is a highly selective and reversible inhibitor of the sarco-endoplasmic reticulum pump (SERCA pump), thereby depleting ER Ca2+-stores, and is recognized as an established model for the induction of ER stress in diabetic research4-8 as well as in other fields.9-11 In INS-1E cells, CPA leads to IRE1R-mediated splicing of xbp-1 mRNA and activation of ATF6, PERK, and ATF4.12 These effects were already observed at 6.25 µM CPA and were more pronounced in 25 µM CPA.5 Pro-inflammatory cytokines are also known to cause ER stress in β-cells, at least in part, through inhibition of the same SERCA pump. Other known modes of action act via activation of iNOS,4 JNK,13 and inositol 1,4,5-trisphosphate receptor type 2 (IPTR2),14 leading to depletion of ER Ca2+ stores. To clarify the molecular mechanisms involved in β-cell UPR, we used the differentiated rat INS-1E cell line.15 INS-1E cells have a wellpreserved insulin release in response to glucose15 and respond to cytokines and CPA in a way similar to primary β-cells.5,16,17 Taking into account the large amount of cells necessary for proteomic analysis, using a cell line opens the possibility to investigate different experimental conditions, i.e., different time points combined with different concentrations of CPA. In the present study, we investigated the global changes induced by CPA at the protein level. The results obtained point to two different patterns of responses when β-cells are exposed to moderate or severe ER stress. INS-1E cells under severe ER stress quickly undergo apoptosis. Major defects in insulin processing are observed, suggesting not only that insulin mRNA expression is decreased but also the conversion of pro-insulin to insulin. There is a marked decrease in the expression of ER chaperones, a phenomenon not observed at the mRNA level, indicating posttranscriptional effects. Under moderate ER stress, i.e., exposure to 6.25 µM CPA, the INS-1E cells adapt better, as suggested by the transient downregulation or inactivation of many proteins involved in cell fate, followed at later time points by upregulation or reactivation of key pathways involved in β-cell survival.

Experimental Procedures Cell Culture Conditions. INS-1E cells, a kind gift from Prof. C. Wollheim (Centre Medical Universitaire, Geneva, Switzerland), were cultured as described previously.14 Cells used for experiments ranged from passage 62 to 66.15 INS-1E cells were treated with CPA (Sigma) dissolved in DMSO and used at a final concentration of 3.1, 6.25, 12.5, or 25 µM. Control cells were treated with DMSO alone. For cytokine treatment, 10 units/mL of recombinant human IL-1β (a kind gift from Dr. C. W. Reinolds, National Cancer Institute, National Institutes of Health, Bethesda, MD) and 500 units/mL of recombinant rat IFN-γ (R&D Systems) were used. Cell Death Analysis. The percentage of living, apoptotic, and necrotic cells was assessed by microscopic counting as described.18 INS-1E cells were cultured in 96-well plates (8000 cells/well). After 6, 12, and 24 h of exposure, cells were incubated for 15 min with propidium iodide (10 µg/mL) (Invitrogen) and Hoechst HO342 (20 µg/mL) (Invitrogen). A minimum of 500 cells were counted in each experimental condition by two researchers, one of them unaware of the sample identity, on an inverted fluorescent Ti-E microscope

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(Nikon). Viable or necrotic cells were identified by intact nuclei with, respectively, blue (Hoechst HO342) or yellow (Hoechst HO342 plus propidium iodide) fluorescence. Apoptotic cells were detected by their fragmented nuclei, which exhibited either a blue or yellow fluorescence depending on the stage in the process. Real-Time RT-PCR. Total RNA was extracted from 5 × 105 cells using the High Pure RNA Isolation Kit (Roche), and 0.5 µg was reverse transcribed using 100U Superscript II RT (Life Technologies) at 42 °C for 80 min, in the presence of 5 µM oligodT16. Real time PCR was performed for CHOP10, HSPA5, HYOU1, PDIA6, and hypoxanthine-guanine phosphoribosyltransferase (HPRT) using TaqGold (Eurogentec), TaqMan probes, or SYBR-Green and the MyiQ system (Bio-Rad) as described previously.19 The following primers were designed making use of the software program Primer3:20 CHOP10-FW: 5′-TCTCATCCCCAGGAAACGAA-3′;CHOP-RV:5′-ATCTGGAGAGCGAGGGCTTT3′; and CHOP-TP: 5′-ACCCTGCGTCCCTAGCTTGGCTG-3′. INS2FW:5′-GCTGGCCCTGCTCATCCT-3′.INS2-RV:5′-CCACCAAGTGAGAACCACAAAG-3′. HPRT-FW: 5′-TTATCAGACTGAAGAGCTACTGTAATGATC-3′; HPRT-RV: 5′-TTACCAGTGTCAATTATATCTTCAACAATC-3′; and HPRT-TP 5′-TGAGAGATCATCTCCACCAATAACTTTTATGTCCC-3′.HYOU1-FW:5′-CACATGGCACAGATTGAAGG-3′; and HYOU1-RV: 5′-CAGGCACTCGATCAAACAAA3′. PDIA6-FW: 5′-GCAGCAAGTGCACTGAAAGA-3′; and PDIA6RV: 5′-GGAAATCCCTGGACACCATAC-3′. HSPA5-FW: 5′-ACCTATTCCTGCGTCGGTGT-3′;HSPA5-RV:5′-AGGAGTGAAGGCCACATACGA-3′; and HSPA5-TP: 5′- AAGAACGGCCGCGTGGAGATCAT-3′. Normalization was performed using the housekeeping gene HPRT, whose expression is not modified by CPA (data not shown). Quantification was based on the ∆∆Ct method. Where necessary, a correction for differences in efficiency between the target and housekeeping gene was performed using the Pfaffl method.21 2D-DIGE Analysis. An amount of 8.5 × 106 INS-1E cells was incubated during 6, 12, or 24 h with 6.25 µM CPA or with 25 µM CPA during 6 or 12 h. Control cells were treated with DMSO alone. Quadruplicate experiments were performed, originating from four independent experiments. Sample collection and processing was performed as described earlier.14 Protein samples were separated in the first dimension using two pH ranges (pH 4-7 and pH 6-9) on 24 cm strips (GE Healthcare). First and second dimensions were performed as described earlier.14 Spot Digestion and Protein Identification by MALDI-TOF/ TOF Analysis. For spot picking, two preparative gels for each pH range were run (350 µg of protein lysate each). First- and second-dimension runs were performed as described,14 except that Cy Dye-labeling was omitted. Glass plates were pretreated with BindSilane, and two reference markers were applied to enable automatic picking. The gels were poststained using Krypton (Pierce). Matching with the analytical gels was performed using the BVA module of the DeCyder V7.0 software. A pick list was generated and exported into the Spot Picker V1.20 software which controls the Ettan Spot Picker (GE Healthcare). Spot digestion and peptide purification were performed as previously reported.14 MS/MS analyses were performed on a 4800 MALDI TOF/TOF (Applied Biosystems, CA, USA). The instrument was calibrated with the Applied Biosystems Calibration Mixture 1. Measurements were taken in the positive ion mode between 900 and 3000 m/z. Sequences were automatically acquired by scanning first in MS mode and selecting the 15 most intense ions for MS/MS using an exclusion list of Journal of Proteome Research • Vol. 9, No. 10, 2010 5143

research articles peaks arising from tryptic autodigestion. Air was used as the collision gas, while the collision energy was adapted automatically. Data interpretation was carried out using the GPS Explorer software (V3.6), and database searching was carried out using the Mascot program (version 2.2.00). Since all experiments were performed on rat INS-1E cells, MS/MS searches were conducted in the following databases with the taxonomy set on Rattus: NCBI (1 999 711 entries) (release date February 15, 2010) and Swiss-Prot (5769 sequences) (version 51.6, release date February 6, 2007). MS/MS tolerance for precursor and fragment ions was set on 1 Da, methionine oxidation as variable modification, and carbamidomethylation of cysteine as fixed modification. As the enzyme, trypsin was selected, and a maximum of one missed cleavage was allowed. Using these parameters, the probability-based MOWSE scores greater than the given cutoff value for MS/MS fragmentation data were taken as significant (p < 0.05). For protein identifications where no hit was found in the rat databases, protein identity was based on comparison with the orthologous mouse sequence because the mouse genome is better annotated compared to the rat genome. For all identified proteins, each sequenced peptide was individually aligned using BLAST.22 For protein identifications where all the individual peptides completely matched to more than one UniProt database accession number/protein name, both protein sequences were aligned using BLAST.22 If this alignment resulted in 100% sequence identity, thus pointing to a single protein present in the database under different names/accession numbers, the UniProt accession number of the entry with the best description is consistently given to eliminate redundancy. For peptides matching to different isoforms or to multiple members of a protein family, the following criteria were used for selecting which one to report: (1) if at least one of the identified peptides matched exclusively to a specific isoform or protein member, this protein isoform/member could be identified unambiguously. (2) The experimental MW and pI obtained from the 2-DE gel was compared with the theoretical MW and pI of the different isoforms/protein members. In case no single protein could be ruled out based on these criteria, or possibly more than one member of the protein group could be present in a single spot, the different names/ accession numbers are reported. Interactome Network Analysis. Network analysis was performed as reported in a previous work14 based on refs 23 and 24. In short, data were downloaded from MINT 48, BIND 49, IntAct 50, KEGG, and Reactome. To increase the coverage of interactions, interolog data 53 (the transfer of protein interactions between orthologous protein pairs in different organisms) were included. Interactions were transferred from 17 eukaryotic organisms and added to the network. Orthology was assigned using the Inparanoid database 55 using stringent thresholds. The statistical significance of the networks was estimated using a randomization scheme in which networks were generated from random input sets of the same size as in the present experiment. We performed 10 000 randomizations from which we derived a probability distribution that was used to calculate the significance of the networks in this study. Western Blotting. An amount of 2.5 × 106 INS-1E cells was cultured as described above. The cells were then lysed in 150 mM NaCl, 1 mM CaCl2, 1 mM MgCl2, 10 mM NaF, 1% NP-40, 1 mM Na3VO4, 1 mM phenylmethylsulfonyl fluoride, and a protease inhibitor cocktail (Complete Protease Inhibitor, Roche Diagnostics). Protein concentrations were determined using the 5144

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D’Hertog et al. BCA Protein Assay Reagent Kit (Perbio Science). An amount of 10 µg of cell lysate was denatured using the NuPage Sample Buffer (4X) and NuPage 10X Reducing Agent and heated for 10 min at 70 °C, before loading on a 4-12% NuPage Bis-Tris gel. Proteins were transferred to an Amersham Hybond LFP lowfluorescent PVDF membrane (GE Healthcare). Protein electrophoresis and electroblotting were performed following the instructions of the manufacturer. Equal loading and transfer efficiency were tested by staining for β-actin, which did not change upon treatment with CPA. Previously blocked membranes were incubated overnight at 4 °C with one of the following antibodies: anti-CHOP (1/350, Santa Cruz Biotechnology, Santa Cruz, USA), anti-actin (1/12 000, Sigma), antiHYOU1 (1/5000, Abcam), anti-HSPA5 (1/500, Santa Cruz Biotechnology), and anti-PDIA6 (1/5000, Abcam). Imaging and quantification of the blots were done using the ECL-plex (GE Healthcare) goat-antimouse Cy2 and goat-antirabbit Cy5 secondary antibodies and subsequent scanning of the blots on the Typhoon scanner. Image analysis and quantification of the bands were performed using ImageQuant TL (v2003). Enzyme-Linked Immunosorbent Assay. Insulin release was measured upon stimulation with low (3 mM) or high (20 mM) glucose concentration. After incubation, INS-1E cells (1 × 105 cells in a 24-well plate) were washed twice with prewarmed glucose-free Krebs-Ringer HEPES bicarbonate (KRHB) (134 mM NaCl, 4.7 mM KCl, 1.2 mM NaH2PO4 · H2O, 1.2 mM MgSO4 · 7H2O, 1 mM CaCl2 · 2H2O, 5 mM NaHCO3, 10 mM HEPES, and 0.5% BSA) and equilibrated for 30 min at room temperature. The solution was replaced with KRHB with either 3 or 20 mM glucose and incubated for 1 h at 37 °C. For insulin content, 1 × 105 INS-1E cells were cultured in a 24-well plate and treated with 6.25 or 25 µM PA for 6, 12, and 24 h. Samples were sonicated (UP50H, Hielscher) in Milli-Q water 5 times for 10 s on ice, and insulin was extracted using acidic ethanol (95% ethanol, 5% 12 N HCl) overnight. Insulin release and content was determined using the rat insulin ELISA kit from Mercodia, according to the manufacturer’s guidelines. Statistical Analysis. For 2D-DIGE experiments, the independent Student’s t test was used. To analyze differences in protein levels, the Decyder V7.0 software was used, and a p-value of less than or equal to 0.05 was considered statistically significant. For all other tests, the independent Student’s t test was used, and p < 0.05 was considered statistically significant.

Results Effect of CPA on Apoptosis Susceptibility of INS-1E Cells. To investigate the susceptibility of INS-1E cells to CPA-induced apoptosis, cells were cultured for 6, 12, or 24 h in the presence of different concentrations of CPA, ranging from 3.1 to 25 µM. At the lowest concentration of CPA (3.1 µM), no apoptosis was induced at any of the time points investigated. When using higher concentrations of 6.25 and 12.5 µM CPA, the percentage of apoptotic cells increased in a dose-dependent manner. Using the highest concentration of 25 µM CPA, the proportion of apoptotic cells increased from 6 h of exposure, increasing further after 12 h, resulting in a major induction of apoptosis after 24 h treatment (Figure 1a). No significant increases in the level of necrosis were observed in any of the conditions analyzed (data not shown). This increase in apoptosis was paralleled by an increase in transcript levels for the proapoptotic transcription factor CHOP (Figure 1b). No increase in CHOP mRNA levels was observed using 3.1 or 6.25 µM CPA. Using the higher concentrations of 12.5 or 25 µM, a marked

Global Proteome Responses of Insulin-Producing INS-1E Cells

Figure 1. (a) Percentage of apoptosis induction in INS-1E cells upon exposure to a concentration range from 3.1 until 25 µM CPA. Black bars indicate 6 h, white bars 12 h, and striped bars 24 h of treatment. Error bars indicate SEM of three independent experiments. (b) Relative mRNA expression levels of CHOP in INS-1E cells upon treatment with a concentration range from 3.1 until 25 µM CPA. CHOP mRNA was quantified by Q-RT-PCR and normalized to the housekeeping gene HPRT. The mean ( SEM of four independent experiments is shown. * p < 0.05 ** p < 0.01 versus control.

induction of CHOP mRNA expression was observed, and this already from 6 h onward (17.5-, 4.8-, and 3.5-fold for 12.5 µM and 49.8-, 28.1-, and 23.1-fold for 25 µM at, respectively, 6, 12, and 24 h; p < 0.05 compared to control for all conditions). This was paralleled by an increase in CHOP protein expression, as measured upon 25 µM CPA stimulation (8.8-fold after 6 h (p < 0.05, n ) 3) and 7.3-fold after 12 h (p < 0.01, n ) 3) (Supporting Information, Figure 1), consistent with previous findings.7 Effects of High Concentration of CPA (25 µM) on INS-1E Cell Protein Expression. Alterations in Proteomic Profile: 2D-DIGE Analysis. Differential proteomic profiles of INS-1E cells were determined after 6 and 12 h exposure to 25 µM CPA (n ) 4, Supporting Information, Figure 2). 44 and 90 spots were differentially expressed after 6 h and 12 h respectively (Supporting Information, Table 1). These originated exclusively from the pH 4-7 range. We were able to unambiguously identify 35 (79.5%) and 49 (54.4%) spots at 6 and 12 h, respectively. This resulted in a total of 57 different proteins, due to the presence of post-translationally modified forms in 10 of the identified proteins. According to their subcellular localization, most of the identified proteins resided in the cytosol (37%), nucleus (18%), or ER (13%), indicating that besides the expected high amount of alterations observed in the ER also secondary effects outside the ER were picked up. This is in line with observations in yeast,

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indicating a key role for downstream signals in the response to ER stress.25 Some crucial proteins involved in insulin processing were downregulated, such as prohormone convertase 2 (PCSK2) (in four out of the five different isoforms identified). Also, heterogeneous nuclear ribonucleoprotein K (hnRPK), an RNA binding protein, was downregulated in the six different isoforms identified (see Supporting Information, Table 1). A second group of proteins that was altered in expression were molecular chaperones, involved in protein folding and clearing the ER from misfolded proteins. A decrease in expression was observed for the hypoxia upregulated protein 1 (HYOU1), 78 kDa glucose-regulated protein (HSPA5/BiP), heath shock 70 kDa protein 8 (HSPA8), and protein disulfide isomerase A3 (PDIA3). For HSPA8, an upregulation of one isoform, opposed to a downregulation of a second one, suggested a specific effect of CPA on post-translational modifications. For HSPA5, a downregulation was observed only in the third major isoform of the protein at 6 h. However, all three major isoforms showed the same tendency to be downregulated at 6 and 12 h (see Supporting Information, Table 1). The combined downregulation of these chaperones pointed toward a defective UPR response and the inability of the INS-1E cells to cope with severe ER stress, leading to apoptosis. Interactome Network. From the 23 unique proteins identified at 6 h, 15 were found to be in an interaction network (p < 1 × 10-6) (Figure 2a). hnRPK and HSPA5 were centrally located in this network, confirming their crucial role in altering the proteome profile at this early 6 h time point. At 12 h the picture is less clear, with only 22 out of the 45 unique proteins represented in the network (p < 1 × 10-6) (Figure 2b). This may point toward a deterioration of the cellular state of the cells upon treatment with 25 µM CPA, consistent with the finding that the majority of the protective proteins was downregulated and that the cells were already undergoing apoptosis. Confirmation of the Observed Alterations in Chaperone Levels: Western Blotting and Quantitative RT-PCR. To validate the data obtained from 2D-DIGE, as well as to compare with previously performed microarray data,6 Western blot analysis and quantitative RT-PCR were performed for key chaperones altered by CPA treatment. For this purpose, we chose to investigate expression of HYOU1, HSPA5 (altered in 2D-DIGE and induced in expression in microarray6), and PDIA6 (only induced in microarray analysis) upon treatment of INS-1E cells with 25 µM CPA. At the mRNA level, HSPA5 was induced from 6 h of incubation on (2.6-fold, p < 0.01, n ) 3) and stayed upregulated at 12 and 24 h (3.0-fold and 2.9-fold, respectively, p < 0.01, n ) 3). Similarly, HYOU1 mRNA was induced from 6 h of incubation on (1.5-fold, p < 0.05, n ) 3) and stayed upregulated at 12 and 24 h (2.0-fold and 2.3-fold, respectively, p < 0.01, n ) 3). Finally, a similar regulation was observed for PDIA6, with mRNA levels increasing 1.3-, 1.3-, and 1.6-fold after 6, 12, and 24 h of CPA exposure, respectively (p < 0.05 for 6 and 12 h, n ) 3, and p < 0.01 for 24 h) (Table 1 and Supporting Information Figure 3). No alterations in protein expression were observed for any of the three chaperones investigated at 6, 12, and 24 h of CPA exposure (p ) NS, n ) 3) as analyzed by Western blotting, suggesting post-transcriptional regulation. The absence of regulation at the total protein level was, at least for HSPA5 and HYOU1, not consistent with the differential regulation observed in 2D-DIGE, suggesting post-translational modification. This underscores the importance of gel-based proteomic studies, making the analysis Journal of Proteome Research • Vol. 9, No. 10, 2010 5145

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D’Hertog et al.

Figure 2. Network analysis of the identified differential expressed proteins after (a) 6 h of exposure to 25 µM CPA (p < 1 × 10-6) and (b) 12 h of exposure to 25 µM CPA (p < 1 × 10-6). Colored circles represent proteins that were identified in this study, and gray circles represent interconnecting proteins revealed by the network software program. A maximum of two interconnecting proteins is allowed. The identified proteins were colored according to their function: proteins involved in metabolism, blue; protein synthesis/modification, light pink; ionic channels and related proteins, light blue; processing of peptides, dark pink; cell adhesion and cytoskeleton, dark green; RNA synthesis/ turnover, yellow; cell cycle, brown; defense/repair mechanisms, orange; calcium binding, light green; and miscellaneous, purple. Table 1. Summarized Data for HYOU1, HSPA5, and PDIA6a protein nameb

6.25 µM CPA method

6h

12 h

24 h

HYOU1 2D-DIGE

+1.3 Western blot RT-PCR HSPA5

2D-DIGE +1.52 +3.3 +6.89 +3.07

PDIA6

25 µM CPA 6h

12 h

-1.33 -1.6 -1.36 -1.85 -1.67 N.A. N.A. +1.52 +2 -2.14

24 h

N.A. +2.32

-1.83 -2.02

+2.09 -1.52 +2.56 Western blot N.A. N.A. N.A. N.A. RT-PCR +2.39 +2.6 2D-DIGE +1.73 Western blot N.A. RT-PCR +1.32

N.A. +3

N.A. +2.9

N.A. N.A. +1.34 +1.62

a Significant results (p < 0.05) are indicated in bold, whereas nonsignificant data have been omitted from the table. N.A. ) not altered in expression. b Protein name according to UniProt.

of post-translational modified forms possible, as opposed to Western blotting. Alterations in Proteins Involved in Insulin Processing: Functional Implications. One of the major effects of high concentrations of CPA on INS-1E cells was on proteins involved in insulin processing, such as PCSK2. In line with this, there was a downregulation in PCSK2 mRNA expression (Figure 3a). In parallel, insulin 2 mRNA levels were decreased (Figure 3b). These changes led to a functional impairment in insulin release since 25 µM of CPA reduced glucose-induced insulin release in INS-1E cells at 6, 12, and 24 h upon stimulation with 20 mM glucose (Figure 4b). Effects of Low Concentration of CPA (6.25 µM) on INS-1E Cell Protein Expression. Alterations in Proteomic Profile: 2D-DIGE Analysis. In analogy to the exposure of INS1E to high concentrations of CPA, a quadruplicate proteomic 5146

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analysis was performed after exposure to 6.25 µM CPA for 6, 12, and 24 h. Opposed to the minor effects on apoptosis induction, this lower concentration of CPA exposure had a great impact on the proteomic profile. 131, 48, and 86 spots were differentially expressed at 6, 12, and 24 h, respectively (Supporting Information Table 1). Of these, 101 (77.1%), 34 (70.8%), and 54 (63.0%) were identified. Subcellular localization for these identified proteins revealed a majority of cytoplasmic proteins (40.1%), while true ER proteins were found to account only for 8.5% of the identified proteins. Exposure of INS-1E cells to 6.25 µM had a great impact on the metabolic proteins of the cell. Out of the 33 unique metabolic proteins identified at 6 h, 18 were related to the Krebs cycle or glycolysis. The majority of these were transiently downregulated at 6 h but returned to control values after 24 h (Figure 5). A second transient effect was observed on the regulation of elongation factor 2 (EF2). After 6 h of exposure, five different isoforms of EF2 decreased (ranging from 1.16until 1.78-fold). This downregulation was aborted at 12 and 24 h, with two different isoforms being upregulated (1.14- and 1.17-fold), pointing to a transient attenuation of protein translational elongation upon low levels of ER stress (see Supporting Information Table 1). As observed for the high 25 µM CPA concentration, effects of 6.25 µM CPA were observed on proteins involved in insulin processing. Different isoforms of PCSK2 were downregulated at 6 h and remained downregulated up to 24 h of CPA exposure. Chromogranins A, B, and C (CGA, CGB, and SCG2) were increased after 24 h of exposure to 6.25 µM CPA, an effect more pronounced then after high-dose CPA exposure (see Supporting Information Table 1). The upregulation of CGA and CGB combined with the decrease in PCSK2 levels pointed toward a defective insulin processing and release by the INS-1E cells upon mild ER stress. Because of the changes in proteins involved in insulin processing at 6.25 µM CPA, we tested if there was any functional impact on the glucose-regulated insulin release. A decrease of 41.0% in insulin release was observed, after 12 h of low-dose CPA exposure (p < 0.05) (Figure 4a).

Global Proteome Responses of Insulin-Producing INS-1E Cells

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Figure 3. Relative mRNA expression levels of (a) prohormone convertase 2 and (b) insulin 2. INS-1E cells were exposed to 25 µM CPA. mRNA was quantified by Q-RT-PCR and normalized to the housekeeping gene HPRT. Severe ER stress caused a decrease in mRNA levels of both insulin and PCSK2. Insulin 2 mRNA levels were significantly decreased, to 30%, 12%, and 16% of control levels after 6, 12, and 24 h, respectively. PCSK2 mRNA expression dropped until 36% and 40% of control levels at 12 and 24 h, respectively. Rectangular markers (0) indicate control, and circular markers (O) indicate CPA-treated INS-1E cells. Error bars indicate SEM of three independent experiments; * p < 0.05 ** p < 0.01 versus control.

Figure 4. (a) Insulin release after treatment of INS-1E cells with 6.25 µM CPA for 6, 12, and 24 h. Insulin release was measured upon stimulation with 20 mM glucose. Insulin release was normalized for insulin content, which did not significantly change upon treatment with 6.25 µM CPA (data not shown). Black bars show the results for the control condition, white bars for INS-1E cells treated with 6.25 µM CPA. (b) Insulin secretion of INS-1E cells, treated with 25 µM CPA for 6, 12, and 24 h. Insulin release was measured upon stimulation with 20 mM glucose. Black bars show the results for the control condition, white bars for INS-1E cells treated with 25 µM CPA. CPA (25 µM) reduced glucoseinduced insulin release in INS-1E cells at 6, 12, and 24 h (50%, 63%, and 62% reduction, respectively). Insulin release was normalized for insulin content, which did not significantly change, except for a 20% reduction in content at 24 h upon treatment with 25 µM CPA (data not shown). Error bars indicate SEM of three independent experiments; * p < 0.05 ** p < 0.01 versus control.

Alterations were observed in different ER chaperones, namely, HSPA5, HYOU1, PDIA6, ERP29, HSP60, HSPA8, and HSP74. The unmodified form of HSPA5 was downregulated, which was accompanied by an increase of different modified isoforms after 6 h of exposure. This was a transient regulation since levels were opposite after 24 h of exposure. Also, several isoforms of hnRPK, as well as another RNA binding protein, namely, hnRPA1, were downregulated (see Supporting Information Table 1). Interactome Network Analysis of Altered Proteins by CPA. From the 88, 34, and 39 unique proteins identified upon 6.25 µM CPA treatment at 6, 12, and 24 h, 58, 13, and 30, respectively, were found to be in an interaction network (p < 5 × 10-6 for all) (Figure 6). Both the networks obtained after 6 and 24 h of exposure showed a tight interaction with the majority of altered proteins, while after 12 h of exposure the network contained less proteins. This reflected the finding that 12 h was a time point in which many of the proteins were transiently normalized before going to an opposite regulation at 24 h of exposure. The network obtained at 6 h showed a central role for key chaperones and RNA binding proteins, being connected to many proteins of other functional classes such as metabolic proteins and cytoskeleton proteins. Of note was the upregulation of two antiapoptotic 14-3-3 proteins, the beta/alpha and the zeta/delta forms, exclusively at the early 6 h time point. Since these two proteins were linked to a large number of other proteins in the network, they were thought to play a central role in the ER

stress process. At 24 h, although the regulation of most of the chaperones was opposite as compared to 6 h of exposure, they were still centrally located in the network, again suggesting a crucial role for the modified chaperones in adaptation to ER stress. Alterations in Chaperone Levels: Confirmation by Western Blotting and Quantitative RT-PCR. To further strengthen the findings of the 2D-DIGE analysis, one of the essential ER chaperones, namely, HSPA5, was analyzed by Western blotting and real-time RT-PCR. Investigating total amounts of HSPA5 by Western blotting, no regulation whatsoever was observed (data not shown). In addition, only a minor effect on HSPA5 mRNA levels was observed, with a significant induction after 6 h of CPA exposure (p < 0.01, n ) 3) (Table 1 and Supporting Information Figure 4). In the 2D-DIGE analysis, however, we detected a shift in modification status of HSPA5, similar to previous results obtained with the cytokine-treated INS-1E cells.14 The major (first) isoform of HSPA5 was downregulated (1.52 times at 6 h (p < 0.05)), while more acidic isoforms were upregulated at the same time point, indicative of inactivation. This pattern of regulation at the post-translational level was reversed at 24 h, where the first (unmodified) isoform of HSPA5 was upregulated (2.56 times (p < 0.05)) and the more acidic isoforms were downregulated.

Discussion Endoplasmic reticulum stress has been put forward as a crucial mechanism involved in apoptotic β-cell death due to Journal of Proteome Research • Vol. 9, No. 10, 2010 5147

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Figure 5. Overview of glycolysis and Krebs cycle pathways with enzymes identified as being differentially expressed upon exposure of INS-1E cells with 6.25 µM CPA for (a) 6 h and (b) 12 h. The identified enzymes are depicted in bold next to the reaction they effect. Up- or downregulation of the enzymes is depicted with block arrows.

inflammatory cytokines or metabolic stressors like free fatty acids and glucose.26,14,27,28 We presently investigated the global 5148

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changes induced by moderate to severe ER stress on the β-cell proteome using CPA as a chemical ER stressor.

Global Proteome Responses of Insulin-Producing INS-1E Cells

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Figure 6. Network analysis of the identified differential expressed proteins after (a) 6 h of exposure to 6.25 µM CPA and (b) 12 h of exposure to 6.25 µM CPA and (c) 24 h of exposure to 6.25 µM CPA (all p < 5 × 10-6). Colored circles represent proteins that were identified in this study, and gray circles represent interconnecting proteins revealed by the network software program. A maximum of two interconnecting proteins is allowed. The identified proteins were colored according to their function: proteins involved in metabolism, blue; protein synthesis/modification, light pink; ionic channels and related proteins, light blue; processing of peptides, dark pink; cell adhesion and cytoskeleton, dark green; RNA synthesis/turnover, yellow; cell cycle, brown; defense/repair mechanisms, orange; calcium binding, light green; and miscellaneous, purple.

The present results show that INS-1E cells are particularly susceptible to ER stress. Levels of ER stress (25 µM CPA) that are not or only mildly toxic to other cells induced apoptosis in nearly half of the INS-1E cells.4 The present proteomics analysis yields a picture that explains discrepancies between the observed upregulation of chaperone and other protective gene mRNAs and this apoptotic evolution. Indeed, we demonstrate that the changes in mRNA that would be predicted to initiate protective pathways are not translated into protein changes. As an example, central chaperones like HSPA5, HYOU1, and PDIA6 are all upregulated at the mRNA level but not at the protein level, pointing to a shut-down of the post-transcriptional machinery, recently confirmed by the observation that IRE1R involved in ER stress is a crucial

player in mRNA decay.29 At low ER stress, IRE1R seems to be primarily responsible for XBP1 splicing (not associated to apoptosis), while at high ER stress, IRE1R is also actively involved in mRNA decay, and this specifically for secretory pathway cargo (SPC) proteins, possibly reducing protective proteins such as HSPA5 to insufficiently low levels.29 Of note, CHOP protein levels did rise in follow-up of increased mRNA levels, thus inducing an imbalance in the levels of HSPA5 versus CHOP, known to be pro-apoptotic.30 The present findings may be one of the underlying mechanisms of the high susceptibility of INS-1E cells to apoptosis. At low concentrations of CPA (6.25 µM), no apoptosis was induced in INS-1E cells suggesting that the global alterations in protein profile reflect an adaptation to stress. Two waves of Journal of Proteome Research • Vol. 9, No. 10, 2010 5149

research articles alterations can be observed: within the early time points, downregulation of many important proteins, and at later time points, a pickup in translation. Early on, multiple metabolicrelated proteins were downregulated, pointing to a deterioration of the metabolic state of the cell. Functionally, this was accompanied by a decrease in glucose-stimulated insulin secretion. These findings were also observed at high CPA concentrations and were in line with previously performed microarray data,6 showing a major decrease in insulin 1 and 2 mRNA expression. This early insulin mRNA decay fits with the findings of Han et al. in 2009, identifying insulin mRNA as a direct extra-XBP1 endonucleolytic substrate of IRE1R, thereby leading to β-cell dysfunction.29 Also, cytokines had an effect on insulin mRNA levels, by affecting the expression of PCSK2, mediated by IL-1β and exacerbated by addition of IFN-γ.14 This fits with the assumption that IL-1β alone causes β-cell dysfunction but not β-cell death, possibly through inhibition of the SERCA pump and induction of ER stress.4 Another protein downregulated in the early phases by CPA is hnRPK. This protein is involved in various processes, among which are mRNA stabilization and translation, RNA splicing, and chromatin remodeling.31,32 hnRPK has a stabilizing function for the prepro-insulin mRNA through binding at the pyrimidine-rich 3′ untranslated region.33,34 The downregulation of hnRPK could have a further detrimental effect for the correct processing of insulin, here at the mRNA level. Related to this, another group of proteins that was increased early on was the chromogranins (CGA, SCG1, and SCG2). The appearance of chromogranins in their high molecular weight unprocessed isoform may be a direct consequence of PCSK2 downregulation. Chromogranins are processed into different active peptides by PCSK2.35 The CGA-derived peptide pancreastatin inhibits glucose-stimulated insulin release.36 Similar inhibitory functions have been shown for SCG1,37 and this latter protein may take part in the regulation of insulin secretion in the same way as CGA. The upregulation of CGA and SCG1 combined with the decrease in PCSK2 levels supported a defective insulin processing and release by the INS-1E cell upon mild or severe ER stress. At later time points after 6.25 µM CPA, the protein profile reversed. The most striking example of this was HSPA5, for which total mRNA amounts were slightly induced and total protein levels were not altered. However, an inactivation at the protein level at 6 h was observed, due to a shift toward inactive post-translationally modified forms. At 24 h, the reverse was observed, resulting in activation of HSPA5. The exact nature of the CPA-induced post-translational modification remains to be clarified, but the changes observed are consistent with either phosphorylation or ribosylation. Both these modifications have been described for HSPA5 upon glucose starvation and hypoxia38,39 and function as a rapid mechanism of reversible inactivation.40 A similar shift toward inactive post-translational modified forms of HSPA5 has also been reported upon cytokine stimulation of INS-1E cells.14 The reversal of early inhibitory effects of 6.25 µM CPA was also observed for proteins from other functional classes, such as metabolic proteins, elongation factor 2 (EF2), and Bcl-2 inhibitor of transcription (PTRH2). These findings suggest that after several hours of moderate CPA-induced ER stress INS-1E cells trigger successful adaptation/survival mechanisms. Two centrally located proteins in the interactome network analysis, namely, the 14-3-3 protein beta/alpha (YWHAB) and the 14-3-3 5150

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D’Hertog et al. protein zeta/delta (YWHAZ), are interesting candidates for this late adaptive response. 14-3-3 proteins play a role in the regulation of diverse biological processes, among which are survival/apoptotic signaling.41 They inhibit apoptosis through interaction with the Bad complex formation, resulting in inhibition of Bad:Bcl-XL-mediated apoptosis42-47 and consequently promoting cell survival.48,49 Proteins of the Bcl2 family, which are activated by the IRE1R-JNK- and IRE1RCHOP pathway, play a major role in controlling cell death upon ER stress triggered by Ca2+ depletion, by modulating Ca2+ homeostasis.50 Another protein of this family, Bcl-2 inhibitor of transcription (PTRH2), was downregulated at 6 h, while being induced after 24 h, again promoting cell survival. The initial upregulation of these two 14-3-3 family members at 6 h upon low CPA stimulation could point to an inhibition of apoptosis by altering Bcl2 family members, leading to the observed survival of the cells. Compared to our previous performed proteomic analysis on cytokine-treated INS-1E cells,14 CPA induced a similar defect in insulin processing as well as a similar posttranslational regulation of HSPA5 suggesting that cytokines act, at least in part, through induction of ER stress. A more detailed view was recently introduced by Gurzov et al. in 2009, who showed a role for ER stress in cytokine-mediated apoptosis, with DP5sa BH3-only family membersbeing crucial in this pathway.3 DP5 seems to converge from different pathways, including JNK and NF-κB. Gurzov et al. showed a central role for DP5 in ER-stress-mediated apoptosis, but this time DP5 is acting downstream of ER stress. Unfortunately we were unable to confirm a possible role for DP5 in the present study because of its low molecular weight (10 kDa) and extreme basic pH (11.85), falling outside the detection range of our 2D-DIGE approach. In conclusion, the present study provides novel information on the global responses of insulin-producing cells, at the protein level, to different degrees of ER stress. In the presence of severe ER stress, normal protective mechanisms, such as upregulation of chaperones, are initiated at the mRNA level but fail to be translated in proteins, hampering cell survival. At moderate levels of ER stress, on the other hand, successful adaptive changes are triggered at the mRNA and protein level, enabling survival and partial preservation of insulin release. Underlying processes involved in this adaptation have been identified, suggesting a role for 14-3-3 proteins. An important role for post-translational modifications was also observed, with a temporal inactivation of HSPA5 as the most striking example. The present study underscores the importance of proteomic analysis to obtain a clearer understanding on the impact of ER stress on β-cell function and survival. The present study identified key proteins and processes involved in the impact of ER stress on β-cell function and survival.

Acknowledgment. This work was supported by the Catholic University of Leuven (GOA 2004/10 and 2009/10), the Flemish Research Foundation (FWO G.0552.06 G.0649.08), the Belgium Program on Interuniversity Poles of Attraction initiated by the Belgian State (IUAP P5/17 and P6/40), the Centre of Excellence SymBioSys (Research Council K.U.Leuven EF/05/007), the Juvenile Diabetes Research Foundation International (1-2008-536), and the European Union (projects Savebeta, in the Framework Program 6 of the European Community, and NAIMIT, in the Framework Program 7 of the European Community). K.L. is supported by a grant from

Global Proteome Responses of Insulin-Producing INS-1E Cells ‘Forskningsra˚det for Sundhed og Sygdom’ and by NICHD RO1 grant HD055150-03. G.B.F. is supported by a doctoral fellowship (Alban, no. E06D100904BR), A.K.C. by a Research Associate of the Fonds National de la Recherche Scientifique, and C.M. by a clinical research fellowship (FWO). We gratefully acknowledge the technical assistance of Karin Schildermans, Sandy Vandoninck, Nursen Gol, Jos Depovere, and Jos Laureys.

Supporting Information Available: Supporting Figures 1-4 and Table 1. Additional data on MS/MS analysis of proteins identified on single peptides. This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Eizirik, D. L.; Cardozo, A. K.; Cnop, M. The role for endoplasmic reticulum stress in diabetes mellitus. Endocr. Rev. 2008, 29, 42– 61. (2) Rutkowski, D. T.; Kaufman, R. J. A trip to the ER: coping with stress. Trends Cell Biol. 2004, 14, 20–28. (3) Gurzov, E. N.; Ortis, F.; Cunha, D. A.; Gosset, G.; et al. Signaling by IL-1beta+IFN-gamma and ER stress converge on DP5/Hrk activation: a novel mechanism for pancreatic beta-cell apoptosis. Cell Death Differ. 2009, 16, 1539–1550. (4) Cardozo, A. K.; Ortis, F.; Storling, J.; Feng, Y. M.; et al. 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, 452–461. (5) Pirot, P.; Eizirik, D. L.; Cardozo, A. K. Interferon-gamma potentiates endoplasmic reticulum stress-induced death by reducing pancreatic beta cell defence mechanisms. Diabetologia 2006, 49, 1229– 1236. (6) Pirot, P.; Naamane, N.; Libert, F.; Magnusson, N. E.; et al. Global profiling of genes modified by endoplasmic reticulum stress in pancreatic beta cells reveals the early degradation of insulin mRNAs. Diabetologia 2007, 50, 1006–1014. (7) Pirot, P.; Ortis, F.; Cnop, M.; Ma, Y.; et al. Transcriptional regulation of the endoplasmic reticulum stress gene chop in pancreatic insulin-producing cells. Diabetes 2007, 56, 1069–1077. (8) Mokhtari, D.; Kerblom, B.; Mehmeti, I.; Wang, X.; et al. Increased Hsp70 expression attenuates cytokine-induced cell death in islets of Langerhans from Shb knockout mice. Biochem. Biophys. Res. Commun. 2009, 387, 553–557. (9) Cheng, T. C.; Benton, H. P. The intracellular Ca(2+)-pump inhibitors thapsigargin and cyclopiazonic acid induce stress proteins in mammalian chondrocytes. Biochem. J. 1994, 301 (Pt 2), 563–568. (10) Doutheil, J.; Gissel, C.; Oschlies, U.; Hossmann, K. A.; et al. Relation of neuronal endoplasmic reticulum calcium homeostasis to ribosomal aggregation and protein synthesis: implications for stressinduced suppression of protein synthesis. Brain Res. 1997, 775, 43–51. (11) Zuppini, A.; Navazio, L.; Mariani, P. Endoplasmic reticulum stressinduced programmed cell death in soybean cells. J. Cell Sci. 2004, 117, 2591–2598. (12) Harding, H. P.; Novoa, I.; Zhang, Y.; Zeng, H.; et al. Regulated translation initiation controls stress-induced gene expression in mammalian cells. Mol. Cell 2000, 6, 1099–1108. (13) Wang, Q.; Zhang, H.; Zhao, B.; Fei, H. IL-1beta caused pancreatic beta-cells apoptosis is mediated in part by endoplasmic reticulum stress via the induction of endoplasmic reticulum Ca2+ release through the c-Jun N-terminal kinase pathway. Mol. Cell. Biochem. 2009, 324, 183–190. (14) D’Hertog, W.; Overbergh, L.; Lage, K.; Ferreira, G. B.; et al. 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, 2180–2199. (15) Merglen, A.; Theander, S.; Rubi, B.; Chaffard, G.; et al. Glucose sensitivity and metabolism-secretion coupling studied during twoyear continuous culture in INS-1E insulinoma cells. Endocrinology 2004, 145, 667–678. (16) Cardozo, A. K.; Heimberg, H.; Heremans, Y.; Leeman, R.; et al. A comprehensive analysis of cytokine-induced and nuclear factorkappa B-dependent genes in primary rat pancreatic beta-cells. J. Biol. Chem. 2001, 276, 48879–48886.

research articles

(17) Cardozo, A. K.; Kruhoffer, M.; Leeman, R.; Orntoft, T.; et al. Identification of novel cytokine-induced genes in pancreatic betacells by high-density oligonucleotide arrays. Diabetes 2001, 50, 909–920. (18) Hoorens, A.; Van de, C. M.; Kloppel, G.; Pipeleers, D. Glucose promotes survival of rat pancreatic beta cells by activating synthesis of proteins which suppress a constitutive apoptotic program. J. Clin. Invest. 1996, 98, 1568–1574. (19) Overbergh, L.; Giulietti, A.; Valckx, D.; Decallonne, R.; et al. The use of real-time reverse transcriptase PCR for the quantification of cytokine gene expression. J. Biomol. Tech. 2003, 14, 33–43. (20) Rozen, S.; Skaletsky, H. Primer3 on the WWW for general users and for biologist programmers. Methods Mol. Biol. 2000, 132, 365– 386. (21) Pfaffl, M. W. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res. 2001, 29, e45. (22) Altschul, S. F.; Madden, T. L.; Schaffer, A. A.; Zhang, J.; et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997, 25, 3389–3402. (23) Lage, K.; Karlberg, E. O.; Storling, Z. M.; Olason, P. I.; et al. A human phenome-interactome network of protein complexes implicated in genetic disorders. Nat. Biotechnol. 2007, 25, 309–316. (24) Lage, K.; Hansen, N. T.; Karlberg, E. O.; Eklund, A. C.; et al. A largescale analysis of tissue-specific pathology and gene expression of human disease genes and complexes. Proc. Natl. Acad. Sci. U.S.A. 2008, 105, 20870–20875. (25) Jonikas, M. C.; Collins, S. R.; Denic, V.; Oh, E.; et al. Comprehensive characterization of genes required for protein folding in the endoplasmic reticulum. Science 2009, 323, 1693–1697. (26) Cnop, M.; Igoillo-Esteve, M.; Cunha, D. A.; Ladriere, L.; et al. An update on lipotoxic endoplasmic reticulum stress in pancreatic beta-cells. Biochem. Soc. Trans. 2008, 36, 909–915. (27) Cunha, D. A.; Hekerman, P.; Ladriere, L.; Bazarra-Castro, A.; et al. Initiation and execution of lipotoxic ER stress in pancreatic betacells. J. Cell Sci. 2008, 121, 2308–2318. (28) Brunner, Y.; Schvartz, D.; Priego-Capote, F.; Coute, Y.; et al. Glucotoxicity and pancreatic proteomics. J. Proteomics 2009, 71, 576–591. (29) Han, D.; Lerner, A. G.; Vande, W. L.; Upton, J. P.; et al. IRE1alpha kinase activation modes control alternate endoribonuclease outputs to determine divergent cell fates. Cell 2009, 138, 562–575. (30) Rutkowski, D. T.; Arnold, S. M.; Miller, C. N.; Wu, J.; et al. Adaptation to ER stress is mediated by differential stabilities of pro-survival and pro-apoptotic mRNAs and proteins. PLoS Biol. 2006, 4, e374. (31) Bomsztyk, K.; Denisenko, O.; Ostrowski, J.; hnRNP, K. one protein multiple processes. Bioessays 2004, 26, 629–638. (32) Mikula, M.; Dzwonek, A.; Karczmarski, J.; Rubel, T.; et al. Landscape of the hnRNP K protein-protein interactome. Proteomics 2006, 6, 2395–2406. (33) Fred, R. G.; Welsh, N. The importance of RNA binding proteins in preproinsulin mRNA stability. Mol. Cell. Endocrinol. 2009, 297, 28– 33. (34) Fred, R. G.; Adams, C. M.; Welsh, N. Affinity binding analysis shows that hnRNP K and hnRNP E, in cytosolic extracts from human islets, binds specifically to the stabilizing segment of insulin mRNA. Diabetologia 2007, 50, S 207. (35) Laslop, A.; Becker, A.; Lindberg, I.; Fischer-Colbrie, R. Proteolytic processing of chromogranins is modified in brains of transgenic mice. Ann. N.Y. Acad. Sci. 2002, 971, 49–52. (36) Schmid, G. M.; Meda, P.; Caille, D.; Wargent, E.; et al. Inhibition of insulin secretion by betagranin, an N-terminal chromogranin A fragment. J. Biol. Chem. 2007, 282, 12717–12724. (37) Karlsson, E.; Stridsberg, M.; Sandler, S. Chromogranin-B regulation of IAPP and insulin secretion. Regul. Pept. 2000, 87, 33–39. (38) Ledford, B. E.; Leno, G. H. ADP-ribosylation of the molecular chaperone GRP78/BiP. Mol. Cell. Biochem. 1994, 138, 141–148. (39) Freiden, P. J.; Gaut, J. R.; Hendershot, L. M. Interconversion of three differentially modified and assembled forms of BiP. EMBO J. 1992, 11, 63–70. (40) Hendershot, L. M. The ER function BiP is a master regulator of ER function. Mt. Sinai J. Med. 2004, 71, 289–297. (41) Morrison, D. K. The 14-3-3 proteins: integrators of diverse signaling cues that impact cell fate and cancer development. Trends Cell Biol. 2009, 19, 16–23. (42) Datta, S. R.; Katsov, A.; Hu, L.; Petros, A.; et al. 14-3-3 proteins and survival kinases cooperate to inactivate BAD by BH3 domain phosphorylation. Mol. Cell 2000, 6, 41–51. (43) Masters, S. C.; Yang, H.; Datta, S. R.; Greenberg, M. E.; et al. 143-3 inhibits Bad-induced cell death through interaction with serine-136. Mol. Pharmacol. 2001, 60, 1325–1331.

Journal of Proteome Research • Vol. 9, No. 10, 2010 5151

research articles (44) Goldman, E. H.; Chen, L.; Fu, H. Activation of apoptosis signalregulating kinase 1 by reactive oxygen species through dephosphorylation at serine 967 and 14-3-3 dissociation. J. Biol. Chem. 2004, 279, 10442–10449. (45) Rosenquist, M. 14-3-3 proteins in apoptosis. Braz. J. Med. Biol. Res. 2003, 36, 403–408. (46) Masters, S. C.; Fu, H. 14-3-3 proteins mediate an essential antiapoptotic signal. J. Biol. Chem. 2001, 276, 45193–45200. (47) Zha, J.; Harada, H.; Yang, E.; Jockel, J.; et al. Serine phosphorylation of death agonist BAD in response to survival factor results in binding to 14-3-3 not BCL-X(L). Cell. 1996, 87, 619–628.

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D’Hertog et al. (48) Yang, E.; Zha, J.; Jockel, J.; Boise, L. H.; et al. Bad, a heterodimeric partner for Bcl-XL and Bcl-2, displaces Bax and promotes cell death. Cell. 1995, 80, 285–291. (49) Jiang, P.; Du, W.; Wu, M. p53 and Bad: remote strangers become close friends. Cell Res. 2007, 17, 283–285. (50) Kim, I.; Xu, W.; Reed, J. C. Cell death and endoplasmic reticulum stress: disease relevance and therapeutic opportunities. Nat. Rev. Drug Discovery 2008, 7, 1013–1030.

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