Identification of Ubiquitin Target Proteins Using Cell-Based Arrays

Sep 26, 2007 - Our results demonstrate that this large-scale application of cell-based arrays represents a novel global approach in identifying candid...
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Identification of Ubiquitin Target Proteins Using Cell-Based Arrays Tao Zhou,† Bing Liang,† Gui-Ying Su, Wei-Li Gong, Hui-Yan Li, Li-Feng Tian, Kun He, Jie Zhao, Jiang-Hong Man, Tao Li, Wei-Hua Li, Zhi-Yi Zhang, Chen-Hui Wang, Ai-Ling Li, Hui Liu, Xin Pan, Pei-Jing Zhang, Bao-Feng Jin, and Xue-Min Zhang* Institute of Basic Medical Sciences, National Center of Biomedical Analysis, Beijing 100850, China Received May 21, 2007

A global understanding of ubiquitinated proteins in vivo is key to unraveling the biological significance of ubiquitination. There are, however, a few effective screening methods for rapid analysis of ubiquitinated proteins. In the current study, we designed a cell-based cDNA expression array combined with cell imaging for the rapid identification of polyubiquitinated proteins, which normally accumulate to form the unique “dot” structure following inhibition of ubiquitin proteasomes. The array consisted of 112 cDNAs encoding key components of major cellular pathways and potential targets of polyubiquitination. Among them, 40 proteins formed accumulation dots in response to proteasome inhibitor, MG-132, treatment. More importantly, 24 of those 40 proteins, such as MAPKAPK3, NLK, and RhoGDI2, are previously not known as the targets of ubiquitin. We further validated our findings by examining the endogenous counterparts of some of these proteins and found that those endogenous proteins form a similar “dot” structure. Immunoprecipitation assays confirmed that these accumulated proteins are polyubiquitinated. Our results demonstrate that this large-scale application of cell-based arrays represents a novel global approach in identifying candidates of the polyubiquitinated proteins. Therefore, the technique utilized here will facilitate future research on ubiquitination-regulated cell signaling. Keywords: cell arrays • ubiquitin • localization • proteasome inhibitor

Introduction Recent research has implicated ubiquitination in the regulation of a variety of biological processes,13 although the molecular mechanisms involved are not fully understood. The identification of ubiquitinated substrates by ubiquitin-binding proteins in vivo is necessary for a greater understanding of how ubiquitin (Ub) modification facilitates protein function, activity, and localization, as well as how the Ub signal is propagated and translated to regulate downstream cellular events. Many ubiquitinated proteins with diverse cellular functions have been identified.3,6,9,16,31,32,34 Additionally, several recent proteomic studies utilizing mass spectrometry and affinity purification of tagged Ub have identified new Ub-targeted proteins in mammalian cells. Peng et al.28 reported that trypsin proteolysis of Ub-targeted proteins (His-Myc tagged) produced a signature peptide containing a two-residue remnant at the ubiquitination site, which was essential for Ub-targeted protein identification. Rosas-Acosta and co-workers29 utilized tandem affinity purification after stably transfected cell lines expressing a doubletagged (His and S) modifier were generated to increase the specificity of targeted proteins. Current methods utilized to systematically identify proteins in biological samples15,28 are limited by a variety of factors. First, generation of stable cell lines and sample preparation is a time-consuming process. * To whom correspondence should be addressed. Xuemin Zhang, National Center of Biomedical Analysis, 27 Tai-Ping Road, Beijing 100850, China. Tel., (8610) 86538178; Fax, (8610) 68246161; E-mail, [email protected]. † These authors contributed equally to this work. 10.1021/pr070299l CCC: $37.00

 2007 American Chemical Society

Second, research requires a large amount of starting material. A study by Kirkpartrick and co-workers pooled 80 plates (10 cm diameter) per condition, to yield approximately 150-200 mg total cellular protein.20 Third, it requires sophisticated manipulation of tandem mass spectrometry. Although advances in genomic research in vivo have resulted in the functional analysis of thousands of novel genes, the mechanisms regulating cellular processes on a global scale have not been fully elucidated. Functional analysis typically utilizes molecular and cell-based assays on a gene-by-gene basis, resulting in a bottleneck effect for the characterization of the huge numbers of targets arising from genomic and proteomic surveys. Ziauddin and Sabatini41 have recently described a novel cell-based microarray system to identify cellular functions of gene products, paving the way for high-throughput gene analysis in the field of functional genomics.35,38 Spots on arrays represent clusters of mammalian cells, expressing defined DNA constructs or small interfering RNAs (siRNAs), which direct the increase or decrease in specific gene product functions. Zanardi A et al. developed an “immunocell-array” based on this platform. By spotting specific antibodies, they detected the localization and state of hundreds of proteins involved in specific signaling pathways.40 Here, we introduced a cell-based platform for rapid identification of ubiquitinated proteins based on the findings that a unique “dot” structure is formed after inhibition of ubiquitin proteasomes. It has been demonstrated that proteins modified by Lys48-linked poly-Ub chains are targeted for proteasome-mediated degradation.13 Therefore, most of the proteins modified by Lys48-linked poly-Ub will Journal of Proteome Research 2007, 6, 4397-4406

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research articles accumulate, to a different extent, when proteasomes are inhibited.1 But if the protein expression level is very low, it will be difficult to detect the accumulation of the protein although its degradation by proteasome is inhibited. However, when the protein expression level is high, the ubiquitinated protein will accumulate or form the “dot” structure when proteasome is inhibited, which is easily recognized by fluorescent microscope on the transfected cell arrays. The high expression of the GFPtagged protein just served well for this purpose. Our study performed a rapid screen for the accumulation dots induced by proteasome inhibitors using cell-based arrays. In total, we identified 40 proteins that formed accumulation dots in response to the proteasome inhibitor MG-132. Of these, 24 proteins had not been previously associated with UP system. The variety of Ub-targeted proteins identified in the current study highlights the importance of ubiquitination in the regulation of cell growth and apoptosis. Our results demonstrate that cell-based arrays represent a novel approach to identify ubiquitinated proteins involved in diverse cellular processes.

Materials and Methods Cells and Antibodies. HEK293, HeLa, MCF7, and T47D cells obtained from ATCC (Manassas, VA) were cultured in Dulbecco’s modified Eagle’s medium (DMEM, Life Technologies) and supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin, in 37 °C, 5% CO2 incubator. The polyclonal rabbit anti-GFP, anti-SOX4, and anti-Syntenin antibodies were prepared in-house, monoclonal anti-GFP, antiPRAK, anti-Myc and anti-Cytochorome c antibodies, polyclonal rabbit anti-IKKR, anti-IKKγ, anti-NF-κB, anti-IκBa, anti-PIAS3, anti-caspase3, anti-p15, anti-PKC, anti-E2F4, and anti-p21 antibodies were purchased from Santa Cruz Biotechnology, monoclonal anti-RIP, anti-PR and anti-p53 antibodies, polyclonal rabbit anti-CyclinD1, anti-Bcl-2, and anti-Bcl-xl antibodies from Cell Signal Technology, monoclonal anti-IKKβ antibody from BD biosciences, polyclonal anti-RhoGDI2 antibody from Sigma-Aldrich. The polyclonal rabbit anti-Pim-1, anti-SP1, and anti-MDM4 antibodies were gifts from Dr. Xu. Mouse IgG/ FITC and Rabbit IgG/FITC secondary antibodies were purchased from Molecular Probes Biotechnology. Cell-Based Arrays. The surfaces of glass slides were first treated with NaOH solution and washed, then soaked in polyL-lysine solution (0.1 mg/mL; Sigma) for 1 h and washed with deionized water. Then slides were dried at 37 °C and exposed to UV light for sterilization.4 All 112 genes were isolated by PCR from either human mammary or hepatic cDNA library and cloned in-frame into the pEGFP-N1 vectors (Clontech) separately. Each GFP fusion vector was mixed with adequate amounts of lipofectamine 2000 (Invitrogen) according to the manufacturer’s recommendation. We diluted the mixed plasmids in the gelatin (Sigma) solution to keep the gelatin concentration at 0.4% and plasmids concentration at 50 ng/ µL. The arrays were printed by a robotic arrayer (SmartArrayer 48, CapitalBio Corporation) under the sterile condition with 0.1 µL of the mixed solution for each spot, which can also be dispensed manually to spots for limited number of samples. The HEK293 cells were seeded at a density of 1 × 106 cells in the 10 cm dish, which contained the slides, and 24 h later, MG132 (10µM, Calbiochem) or equal amounts of DMSO as a control were added. Similarly, chemotherapeutic drugs doxorubicin (DOX, 0.4 µg/mL), cisplatin (10µM), camptothecin (CPT, 2 µM), and daunorubicin (DNR, 0.5 µg/mL) were added in other 4398

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experimental groups.39 After incubation for another 12 h, the slides were washed and subsequently fixed for 10 min in 4% paraformaldehyde solution and then were detected by Randiance 2100 laser-scanning confocal microscope (Bio-Bad, CA). Immunofluorescent Assay. Cells were grown on glass coverslips, which were treated as described on cell-based arrays. MG-132 (10 µM) or equal amounts of DMSO as a control were added. After 12 h of incubation, cells were washed and fixed, then permeabilized by 1% Triton X-100 for 10 min at 4 °C. The samples were saturated with PBS containing 1% goat serum albumin for 1 h and incubated for 1 h at room temperature with specific antibody. The samples were then washed three times with PBS and incubated for 1 h with a 1:100 dilution of the FITC marked secondary antibodies. The samples were then mounted for analysis on a confocal microscope. Two-Dimensional Electrophoresis and Two-Dimensional Western Blot. Mo7e cells with or without MG-132 treatment for 12 h were collected and lysed with lysis buffer (8 M urea, 4% CHAPS, 40 mM Tris) containing a protease inhibitor cocktail (Roche Diagnostic). Then, the lysates were aliquoted and stored at -70 °C until use. 2-D was performed as described by Gorg et al.12 Gels were stained with 0.1% (w/v) Coomassie Blue G-250 in 50% methanol and 10% acetic acid, or silver staining according to the protocol of Shevchenko et al.,30 and gel image analysis was processed using Adobe Photoshop software and the Diversity One program (Pharmacia). For MS identification, protein spots from the 2-DE gel stained by Coomassie Brilliant were excised and digested as described previously.10 Both PMF (Peptide Mass Fingerprint) study with MALDI-TOF-MS and sequence analysis by nanoESI-MS/MS were carried out for protein identification. For Western blot, unstained 2-DE gels were transferred onto a NC membrane (Amersham Pharmacia Biotech). The membrane was then blocked with 5% nonfat milk and probed with anti-RhoGDI antibody at a 1:500 dilution. After being washed, the membranes were incubated with a 1:5000diluted horseradish peroxidase-conjugated anti-rabbit immunoglobulin. Antibody-antigen complexes were detected using an ECL chemiluminescence kit according to the manufacturer’s instructions (Amersham Life Science). In vivo Ubiquitylation Assays. HEK293 cells were transfected with each of plasmids of GFP-tagged candidates (4.0 µg) and Myc-Ubiquitin (2.0 µg) for 24 h. Then the cells were treated with or without MG-132 (20 µM) for another 6 h and subsequently harvested and lysed with IP lysis buffer (20 mM TrisHCl pH 8.0, 150 mM NaCl, 1 mM EDTA, 0.1% NP-40, 10% glycerol, 1 mM DTT, 1× cocktail), in which 20 µM MG-132 were added. After brief sonication, whole cell extracts were centrifuged at 12 000 rpm for 20 min to remove cell debris. Supernatants were incubated with polyclonal anti-GFP antibody for 4 h at 4 °C and then protein A/G- Sepharose beads for 2 h at 4 °C. The immunocomplexes were washed 4 times with the same IP lysis buffer, and the immunoprecipitated proteins were subjected to SDS-PAGE, followed by Western blot with antiMyc and monoclonal anti-GFP antibody. Furthermore, p15 and PRAK were employed for endogenous protein ubiquitination assay. Cells were infected with pMSCV-IRES-GFP (as a negative control; a gift from Dr. Wang) or pMSCV-IRES-GFP-Ubiquitin (constructed by our lab), which expressed ubiquitin without the tag protein. The cell infection has been described previously.23 The infected cells were treated with 20 µM MG-132 for 6 h before harvested for immunoprecipitate. Endogenous p15

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Figure 1. Protein localization on cell-based arrays: (A) Cell-based array protocol. A gelatin solution and transfection reagent were mixed with cDNA expression vectors and placed on a glass slide using a robotic arrayer. The slide was then overlaid with a monolayer of adherent mammalian cells in medium, every spots on the array represent a cluster of mammalian cells, expressing defined DNA constructs. (B) Microscopic examination of cell arrays. Cell clusters reverse transfected with vectors on the array were detected by laser scanning confocal microscope (LSCM). (Top) Intact picture of an array containing 112 cDNAs. For each cell cluster, both GFP fluorescent image (left bottom panel) and differential interference contrast (DIC) image (right bottom panel) were acquired simultaneously. (C) cDNA-GFP fusions express and localize to a wide variety of intracellular compartments in HEK 293 cells. (Cyt-Nuc, cytoplasm and nucleus; Cyt, cytoplasm; Cyt-Memb, cytoplasm and membrane-associated; Nuc, nucleus; Cyt-predo, cytoplasm predominantly; Nucpredo, nucleus predominantly; Memb-Nuc, membrane and nucleus; Memb-predo, membrane predominantly). (D) Summary of subcellular localization of tested proteins. (Bar ) 10 µm)

and PRAK were immunoprecipitated with anti-p15 and antiPRAK antibodies as described above and immunoblotted as indicated.

Results Protein Localization on Cell-Based Arrays. The cell-based array consisted of 112 GFP-tagged cDNA expression vectors constructed in our laboratory and encoding products involved

in major cellular pathways, such as cell cycle and transcription regulation, stress signaling, signal transduction, ligand-receptor, sorting and degradation, cell communication and cell motility, among others (Supplemental Table S1, Supporting Information). The characteristic of each cDNA was previously known, eliminating the need to identify the cDNAs responsible for phenotypes of interest, a process that often requires substantial work. Using slides printed with these cDNAs in expression Journal of Proteome Research • Vol. 6, No. 11, 2007 4399

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Figure 2. Screening of proteins displaying changed phenotype: The arrays were treated with 10 µM MG-132 or equal amount DMSO (12 h). (A) No accumulation dots of the proteins formed in HEK293 cells treated with MG-132. (B) Accumulation dots of the proteins were noted in cytoplasm of HEK293 cells treated with MG-132. (C) Accumulation dots of the proteins were noted in nucleus of HEK293 cells treated with MG-132. (D) Images of immunofluorescent assay representing the accumulation dots of endogenous proteins in the cells treated with MG-132 (top). (Bottom) Accumulation dots of GFP-fused proteins after MG-132 treatment. (E) TNF-R stimulation was required for both endogenous (top) and GFP-tagged (bottom) IκBR to form accumulation dots in the presence of MG-132, whereas IKK-β and IKK-γ showed no response to TNF-R stimulation. Cells were stimulated with 20 ng mL-1 TNF-R for 15 min after 12 h incubation with MG-132 at 37 °C prior to immunofluorescence. Arrows indicate cytoplasmic accumulation dots. (Bar ) 10 µm) 4400

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Identification of Ubiquitin Target Proteins Table 1. List of Proteins that Formed Accumulation Dots in Response to MG-132 abbr. name

NCBI ID no.

pathwaya

subcellular localizationb

location of dots formedc

FLIP Cycs Casp3 Casp6 Casp9 PAK2 E2F4 pim-1 STAT1 Cyclin D1 PKC CREB 2 Mdm4 p21 TRAF2 Smurf1 SP1 SHP1 SHP2 NLK PIG3 PSMB4 Calpain MEK2 ELK1 MAP3K8 PRAK MAPKAPK3 p15 Spred2 Arp2/3 PEBP RHoH ALDH6A1 TAB1 ACSL5 SPRY3 RhoGDI2 THAP3 MKNK2

NM_003879 NM_018947 NM_032991 NM_001226 NM_032996 NM_002577 NM_001950 NM_002648 NM_139266 NM_053056 NM_002737 NM_182810 NM_002393 NM_000389 NM_021138 NM_020429 NM_138473 NM_002831 NM_002834 NM_016231 AF010309 NM_002796 NM_005186 NM_030662 NM_005229 NM_005204 NM_003668 NM_004635 NM_004936 NM_181784 NM_005717 XM_497846 BC014261 NM_005589 BC050554 NM_016234 NM_005840 NM_001175 BC092427 NM_017572

apoptosis apoptosis apoptosis, MAPK apoptosis, MAPK apoptosis, MAPK MAPK, Actin TGF-beta STAT STAT cell cycle MAPK MAPK other other apoptosis TGF-beta TGF-beta STAT STAT MAPK other other apoptosis MAPK, actin MAPK MAPK MAPK MAPK TGF-beta STAT actin other other other MAPK other STAT other other MAPK

cytoplasm cytoplasm, nucleus cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm nucleus predominantly cytoplasm predominantly cytoplasm cytoplasm nucleus cytoplasm predominantly nucleus cytoplasm membrane, nucleus cytoplasm nucleus predominantly cytoplasm nucleus predominantly cytoplasm, nucleus cytoplasm cytoplasm cytoplasm nucleus cytoplasm, nucleus nucleus predominantly nucleus predominantly cytoplasm, nucleus cytoplasm, membrane nucleus predominantly nucleus predominantly nucleus predominantly cytoplasm cytoplasm, membrane membrane membrane, cytoplasm cytoplasm, nucleus nucleus nucleus

cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm nucleus nucleus nucleus cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm cytoplasm nucleus nucleus nucleus

correlation with UP pathwayd

substrate substrate substrate substrate substrate substrate substrate substrate substrate substrate substrate substrate substrate substrate E3 ligase E3 ligase unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown

a Pathways of KEGG database (http://www.genome.jp/kegg). b Localization of proteins on our cell arrays before MG-132 treatment. c Locations of accumulation dots formed after treatment with MG-132 (10µM) for 12 h. dSearch results in NCBI PubMed.

vectors, we created living arrays of cell clusters expressing the gene products. A gelatin solution and transfection reagent were mixed with cDNA expression vectors and placed on a glass slide using a robotic arrayer. The slide was then overlaid with a monolayer of adherent mammalian cells in medium (Figure 1A), eliminating the need to use individual wells for DNA sequestration and limiting cell transfection to those specifically growing on top of each spot. We observed approximately 60% transfection efficiency, as measured by the expression of GFP-tagged proteins (Figure 1B), suggesting the method was suitable for rapid localization analysis of large sets of cDNA products. The transfected cell-based array was then used to achieve a rapid localization analysis in human embryonic kidney (HEK293) cells. As shown in Figure 1C, subcellular features were clearly visible, at high magnification, within cells of each transfected cluster, and were categorized into eight different patterns of subcellular localization, including cytoplasm and nucleus (CytNuc), cytoplasm (Cyt), cytoplasm and membrane-associated (Cyt-Memb), nucleus (Nuc), cytoplasm predominantly (Cytpredo), nucleus predominantly (Nuc-predo), membrane and nucleus (Memb-Nuc), and membrane predominantly (Membpredo). The distribution of cDNA products is summarized in Figure 1D. Our data suggested 27.7% of the cDNA products were localized in a Cyt pattern, 19.6% in a Nuc pattern, and 24.1% in a Cyt-Nuc pattern. Effects of Protein Inhibitor on Protein Phenotype. Arrays were then used to screen proteins that formed accumulation

dots in response to proteasome inhibitors. Consistent with our previous studies,19 treatment with MG-132 induced a dosedependent apoptosis, as observed by nuclear fragmentation and chromatin condensation in cells following Acridine Orange staining. To observe the changes of protein localization upon inhibition of the proteasome, the cell arrays were observed after 12 h of MG-132 treatment in low dose, prior to the induction of apoptosis in the majority of cells (data not shown). Although no effects were noted in 72 of the proteins studied, such as DFF40, FADD, WASF2, and Pitx2 (Figure 2A), obvious dots were noted in 40 proteins in response to MG-132 treatment (Table 1, three independent experiments). These dots were formed in cytoplasm (34 proteins) or in nucleus (6 proteins). Examples with marked accumulation dots in cytoplasm included PKC, MAPKAPK3, SPRY3, and E2F4, whose normal localization was Cyt, Nuc-predo, Cyt-Memb, and Cyt-predo, respectively (Figure 2B). Examples with dots in nucleus were p21 and CREB2, whose normal localizations were in nucleus (Figure 2C). We tested two more inhibitors, ALLN and lactacysin. Both showed the similar effect on the proteins to that of MG-132 (Figure S1, Supporting Information). To further investigate whether similar structures were noted in endogenous protein resulting from MG-132 treatment, we performed immunofluorescent assay on 22 proteins randomly selected from the 112 cDNA products. Among them, 9 proteins, including PRAK, p15, and casp3, displayed “dot” structures in cytoplasm (Figure 2D), whereas the other 13 proteins did not form accumulate dots. As indicated in Table 2, all selected Journal of Proteome Research • Vol. 6, No. 11, 2007 4401

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Table 2. Validation of Accumulation Dots in 22 Proteinsa at Endogenous Level abbr. name

GFP-tagged protein dots

endogenous protein dots

correlation with UP pathwayb

IKKR IKKβ IKKγ PIAS3 SOX4 Syntenin Bcl-xl NF-κB PRB Bcl-2 p53 RIP p15 PRAK Pim1 IKBr Casp3 CyclinD1 p21 Cycs PKC E2F4

+ + + + + + + + + +

+ + + + + + + + + -

unknown unknown unknown unknown unknown unknown unknown unknown substrate substrate substrate substrate unknown unknown unknown substrate substrate substrate substrate substrate substrate substrate

a Randomly selected from the 112 proteins list. b Search results in NCBI PubMed.

proteins except E2F4 showed the same response to MG-132 treatment with their GFP-tagged proteins. These data clearly demonstrated that a majority of GFP-tagged proteins and their endogenous counterparts behave similarly when the proteasome was inhibited. To further evaluate the specificity of the array identifying ubiquitin-targeted proteins, we examined six elements in NFκB pathway in the presence of TNF-R stimulation. As shown in Figure 2E, both GFP-tagged and endogenous IκBR were observed to form accumulation dots after the pathway being activated by TNF-R, whereas there were no changes for IKK-β, IKK-γ (Figure 2E), RIP, IKK-R, and NF-κB (p65) (Data not shown). Previous studies indicated that TNF-R stimulation resulted in the phosphorylation and polyubiquitination of IκBR, consequently targeting it for rapid degradation by the 26S proteasome.1,5,7,8 Our result was consistent with these conclusions.

Protein Clustering in Response to Localization Changes. Among 112 cDNA products, 38 are already known to be UP substrates (33 cDNAs) or E3 ligases (5 cDNAs) (Supplemental Table S1), including 10 proteins whose ubiquitination requires additional stimulation by cytokine or hormone. Of these, 16 substrates including E3 ligase (42.4% efficiency) displayed obviously accumulation dots in response to MG-132 treatment. Of the other 74 proteins, accumulation dots were noted in 24 cDNA products, including 21 cytoplasmic and 3 nuclear accumulation dots. They functionally belonged to the signal elements of the pathways of MAPK, STAT, TGF-β, apoptosis, and others. We also treated the arrays with chemotherapeutic drugs, and no changes were noted following treatment with them, suggesting the effects were specific to UP inhibitors (Figure 3). Accumulation dots of RhoGDI2 protein were also noted in HEK293 cells in response to MG-132 stimulation (Figure 4A). Previous research has demonstrated that RhoGDI2, endogenously and specifically expressed in blood cells, was localized predominantly to the cytoplasm and translocated to the nucleus in response to certain stimulation.21 In the current study, MG-132 treatment (12 h) resulted in RhoGDI2 nuclear accumulation and accumulation dots in cytoplasm. We further demonstrated that endogenous RhoGDI2 protein also accumulated in Mo7e leukemia cells by 2-D gel mass spectrometry and Western blot. Interestingly, the effects of MG-132 treatment were not similar for all spots identified as RhoGDI2 isoforms, with increases noted in spots b, c, and d and decrease noted in spot a. Increased accumulation was confirmed by 2-D gel Western blot (Figure 4C). Immunoprecipitation Validation. To demonstrate that the accumulation dots correlate well with the ubiquitination status of the proteins, we performed immunoprecipitation (IP) assay on Rho-GDI2, MAPKAPK3, PRAK, and NLK proteins (Figure 5A), which were randomly selected from 24 cDNA products that formed accumulation dots upon MG-132 and newly identified as ubiquitin target proteins on the array. HEK293 cells were cotransfected with the Myc-ubiquitin and each of the selected cDNAs, and then treated with 20 µM MG-132 for an additional 6 h. Immunoprecipitated samples were resolved by SDS-PAGE and subjected to Western blot analyses with monoclonal antiMyc antibody. Our results demonstrated that ubiquitination really occurred to the four proteins, with Smurf1 protein (an

Figure 3. MG-132-specific changes in the phenotype of proteins: 293 cells transfected with PKC-GFP (top row), CREB2-GFP (middle row), and MAPKAPK3 (bottom row) were treated with MG-132 (line b), Adriamycin (line c), cisplatin (line d), CPT (line e) and DNR (line f). 4402

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Figure 4. MG-132 induced change of RhoGDI2 protein: (A) RhoGDI2 formed accumulation dots with MG-132 treatment. (B) 2-D patterns of Mo7e cells with or without MG-132 (10 mM) treatment (12 h), with changes noted in different isoforms (a, b, c, d) of RhoGDI2 protein. (C) Increased and decreased expression levels of different isoforms following MG-132 treatment (12 h). (Bar ) 10um).

E3 ligase) used as the positive control (Figure 5A), and the Mdm2 mutant, without ubiquitin-binding ability, was used as the negative control (data not shown). We also demonstrate that accumulation dots correlated well with ubiquitination status of endogenous p15 and PRAK proteins (Figure 5B).

Discussion Previous research in our laboratory investigated the effects of UP system inhibitors on leukemia cell proteome, with 2-D

mass spectrometry data identifying a total of 39 protein spots affected by UP inhibitors.19 In the current study, of the 112 proteins investigated, 40 displayed significant changes in localization, as a result of treatment with UP system inhibitors. However, we were unable to identify the majority of the changed proteins by 2-D gel proteomics. Additionally, we found that alterations in protein localization were not always accompanied by changes in protein expression, although these findings may have been due to the limited sensitivity of the Journal of Proteome Research • Vol. 6, No. 11, 2007 4403

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Figure 5. MG-132 increased protein ubiquitination by blocking the UP system: (A) HEK293 cells were cotransfected with plasmids of GFP-tagged candidates (4.0 µg) and Myc-Ubiquitin (2.0 µg). Cells were incubated, 24 h after transfection, with MG-132 (20µM) for an additional 6 h of treatment. GFP-tagged candidates were immunoprecipitated with anti-GFP antibody and subjected to Western blot analysis with anti-Myc antibody. The bracket represents ubiquitinated proteins. (B) Validation of ubiquitination by immunoprecipitation of endogenous p15 and PRAK. After the infection with pMSCV-IRES-Ubiquitin for 30 h and the treatment with MG-132 (20µM) for an additional 6 h, the cells were immunoprecipitated with anti-p15 and anti-PRAK antibodies and immunoblotted with anti-p15 or antiPRAK, respectively, as indicated. Lane 1 was IP with mouse IgG, which was as the control of anti-p15 and anti-PRAK monoclonal antibodies. Arrows indicate the position of unmodified p15 or PRAK in the cell lysate.

2-D gel-based assay. Therefore, the array provides an additional approach to reveal important information of UP system. Multiple types of Ub modification have been described, including mono-, multi-, and polyubiquitination. The changes noted in the localization of 40 proteins in response to MG-132 treatment suggested that they were closely related to the UP system. Previous research suggested that seven Lys residues of Ub were possibly involved in chain formation in vivo, whereas poly-Ub chains linked via Lys48 or Lys63 are, to date, the best characterized.28 Lys48-linked poly-Ub chains have been implicated as signals for proteasomal degradation of modified substrates.13 Our data suggested proteins identified in the current study were polyubiquitinated, and targeted for proteasomal destruction, given that MG-132 inhibits Ub-mediated proteolysis by binding to and inactivating proteasomes, without affecting the ubiquitination of substrates.14 IP data analysis further confirmed the polyubiquitination of proteins studied. Our data identified a variety of proteins that had not previously been reported to be regulated by Ub-mediated degradation. For example, nemo-like kinase (NLK), a MAPK-related kinase that functions downstream of TAK1 and inhibits Wnt signaling,18,27 binds to and phosphorylates TCF/LEF transcription factors, preventing them from binding to their DNA targets. MAPKAPK3 functions as a modulator of polycomb-mediated repression, which can be activated either by ERK, p38, or JNK,26 and has been shown to phosphorylate HSPB1, PCGF4, and TCF3 in vitro.25 RhoGDI2 belongs to a family of proteins that 4404

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inhibit the dissociation of GDP from Rho GTPases, which are in turn involved in the regulation of such cellular processes as cell adhesion, motility, contraction, and cytokinesis.22 It was also shown to be a metastasis suppressor gene in models of bladder cancer.33 In our previous work, we reported the MG132-induced alterations of RhoGDI2. Here we demonstrated that these proteins could be polyubiquitinated (Figure 5). Cell microarrays are a recent addition to the set of tools available for functional genomic and proteomics studies. The use of cell microarray is mainly focused on the loss- and gainof-function studies. Due to the advantages over traditional approaches, cell arrays have many other potential uses, such as high-throughput identification of genes of biological interest and investigation of cellular phenomena diversity.38 The present study demonstrated that cell-based arrays could be used for rapid identification of polyubiquitinated proteins, which are characterized by the formation of protein accumulation dots following exposure to UP system inhibitors. A total of 42.4% of known substrates on the cell arrays formed protein accumulation dots, suggesting that these proteins were regulated by Ubmediated degradation. The absence of accumulation dots, however, does not exclude the possibility of Ub-dependent regulation of the other known substrates, as they may simply require additional stimulation than what was utilized in our study. For example, IκB is degraded in an Ub-dependent manner but requires TNF-R-stimulated phosphorylation signals (Figure 2E). Additionally, we could not exclude the effects of

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the half-life of proteins, given that a greater number of proteins appeared in accumulation dots following MG-132 treatment for longer time, albeit with significant increases in apoptosis. As well, MG-132 could not be responsible for all protein degradation. For example, previous research has suggested that degradation of the progesterone receptor was not inhibited by MG-132 but by ALLN, another proteasome inhibitor.22 For many years, it has been thought that UP system activity was limited mostly to the cytoplasm,13 which is in agreement with our data. Interestingly, some proteins originally localized to the nucleus displayed cytoplasmic accumulation dots (Figure 2B), suggesting that cytoplasm was the main site of UP system function. We hypothesized that these proteins might be translocated in a retrograde manner into the cytoplasm. Some nuclear accumulation dots were also observed following MG132 treatment, such as CREB2 (Figure 2C), a known UP system substrate, suggesting a role for the UP system in the nucleus. Polyubiquitin chains, in which ubiquitin is linked to itself through Lys 48, are recognized by proteasomes and the modified proteins degraded. In contrast, modification with Lys 63-linked polyubiquitin has been associated with intracellular signaling. NF-κB is a principal transcriptional regulator that plays a pivotal part in cell proliferation and apoptosis. In response to various stimulation (such as TNF-R, IL-1), RIP functions upstream of IKK (IκB kinase) and activates IKK through forming a complex with IKK.17 IκBs are phosphorylated by IKK and are rapidly degraded by proteasome after polyubiquitination.2 Given that TNF-R stimulation prompted IκBR modification with Lys48-linked polyubiquitin, whereas RIP is modified with Lys63-linked polyubiquitin,36,37 whether the approach is robust to discriminate between Lys 48 and Lys 63 linkages was examined. Whereas IκBR formed accumulation dots, we did not observed the similar structure in RIP protein. In addition, NF-κB and IKK are not involved in TNF-Rstimulated degradation through proteasomes, and were also not accumulated. These results were further validated by the examination at endogenous protein level (Figure 2E). The development of GFP as molecular tag has revolutionized research over the past decade by allowing complex biochemical processes to be correlated with protein function in living cells.24 GFP can be covalently fused to the protein of interest, so that targeting is precise, the key advantage of genetically encoded GFP. Although GFP tags have unique applications, they are still limited by a variety of factors, such as the need for ectopic expression, the significant size of GFP, and the possibility that the fusion may interfere with the function of the protein of interest.11 Consequently, the use of multiple analysis methods is needed to confirm GFP-tagged data. It is necessary to point out that the highly expressed GFP-tagged proteins seldom form accumulation dots without the inhibition of proteasome and only one-third of the proteins on the array did so when proteasome is inhibited, most of which are ubiquitin target proteins as demonstrated in our study. Therefore, our method is a valid one for identifying potential ubiquitin target proteins. The identification of a pool of Ub-targeted proteins, in the current study, highlighted important functions of ubiquitination in the regulation of cell growth and apoptosis. This cellbased array combined with cell-imaging technique, as well as other proteomics approaches utilized to study the dynamics of signal stimulation and to visualize Ub signaling networks in vivo, will facilitate a more comprehensive understanding of cellular signaling events governed by ubiquitination and dra-

matically increase our knowledge of the physiology and regulation of the UP system in the cell. Abbreviations: Ub, ubiquitin; UP, ubiquitin-proteasome; GFP, green fluorescence protein; IP, immunoprecipitation; MG132, Z-Leu-Leu-Leu-CHO.

Acknowledgment. We are thankful to Dr. Zhenggang Liu for his contribution to the manuscript. This work was supported by the National Natural Science foundation of China (30500583, and 30525021) and grants from National 973 Project (2006CB500700 and 2006CB910802). Supporting Information Available: Supplemental Table S1 and Figure S1. This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Alkalay, I.; Yaron, A.; Hatzubai, A.; Jung, S.; Avraham, A.; Gerlitz, O.; Lavon, I. P.; Neriah, Y. B. Mol. Cell. Biol. 1995, 15, 12941301. (2) Baeuerle, P. A.; Baltimore, D. Cell. 1996, 87, 13-20. (3) Campanero, M. R.; Flemington, E. K. Proc. Natl. Acad. Sci. U.S.A. 1997, 94, 2221-2226. (4) Chang, F. H.; Lee, C. H.; Chen, M. T.; Kuo, C. C.; Chiang, Y. L.; Hang, C. Y.; Roffler, S. Nucleic Acids Res. 2004, 32, e33. (5) Chen, Z. J.; Hagler, J.; Palombella, V. J.; Melandri, F.; Scherer, D.; Ballard, D.; Maniatis, T. Genes Dev. 1995, 9, 1586-1597. (6) De Graaf, P.; Little, N. A.; Ramos, Y. F.; Meulmeester, E.; Letteboer, S. J.; Jochemsen, A. G. J. Biol. Chem. 2003, 278, 38315-38324. (7) DiDonato, J. A.; Mercurio, F.; Karin, M. Mol. Cell. Biol. 1995, 15, 1302-1311. (8) DiDonato, J. A.; Mercurio, F.; Rosette, C.; Wu-Li, J.; Suyang, H.; Ghosh, S.; Karin, M. Mol. Cell. Biol. 1996, 16, 1295-1304. (9) Fang, S.; Jensen, J. P.; Ludwig, R. L.; Vousden, K. H.; Weissman, A. M. J. Biol. Chem. 2000, 275, 8945-8951. (10) Gharahdaghi, F.; Weinberg, C. R.; Meagher, D. A.; Imai, B. S.; Mische, S. M. Electrophoresis 1999, 20, 601-605. (11) Giepmans, B. N. G.; Adams, S. R.; Ellisman, M. H.; Tsien, R. Y. Science 2006, 312, 217-224. (12) Gorg, A.; Postel, W.; Gunther, S. Electrophoresis 1988, 9, 531546. (13) Haglund, K.; Dikic, I. EMBO J. 2005, 24, 3353-3359. (14) He, Q.; Huang, Y.; Sheikh, M. S. Oncogene 2004, 23, 2554-2558. (15) Hodges, E.; Redelius, J. S.; Wu, W.; Hoog, C. Mol. Cell. Proteomics 2005, 4, 1319-1327. (16) Honda, R.; Tanaka, H.; Yasuda, H. FEBS Lett. 1997, 420, 25-27. (17) Hur, G. M.; Lewis, J.; Yang, Q. F.; Lin, Y.; Nakano, H.; Nedospasov, S.; Liu, Z. G. Genes Dev. 2003, 17, 873-882. (18) Ishitani, T.; Ninomiya-Tsuji, J.; Nagai, S.; Nishita, M.; Meneghini, M.; Barker, N.; Waterman, M.; Bowerman, B.; Clevers, H.; Shibuya, H.; Matsumoto, K. Nature 1999, 399, 798-802. (19) Jin, B. F.; He, K.; Wang, H. X.; Wang, J.; Zhou, T.; Lan, Y.; Hu, M. R.; Wei, K. H.; Yang, S. C.; Shen, B. F.; Zhang, X. M. Oncogene. 2003, 22, 4819-4830. (20) Kirkpatrick, D. S.; Weldon, S. F.; Tsaprailis, G.; Liebler, D. C.; Jay, A. Gandolfi. Proteomics. 2005, 5, 2104-2111. (21) Krieser, R. J.; Eastman, A. Cell Death Differ. 1999, 6, 412-419. (22) Lange, C. A.; Shen, T. J.; Horwitz, K. B. PNAS 2000, 97(3), 10321037. (23) Li, Z. P.; Wang, C. G.; Jiao, X. M.; Lu, Y. N.; Fu, M. F.; Quong, A. A.; Dye, C.; Yang, J. G.; Dai, M. Z.; Ju, X. M.; Zhang, X. P.; Li, A. P.; Burbelo, P.; Stanley, E. R.; Pestell1, R. G. Mol. Cell. Biol. 2006, 26(11), 4240-4256. (24) Lippincott-Schwartz, J.; Patterson, G. H. Science 2003, 300, 8791. (25) Ludwig, S.; Engel, K.; Hoffmeyer, A.; Sithanandam, G.; Neufeld, B.; Palm, D.; Gaestel, M.; Rapp, U. R. Mol. Cell. Biol. 1996, 16, 6687-6697. (26) McLaughlin, M. M.; Kumar, S.; McDonnell, P. C.; Van Horn, S.; Lee, J. C.; Livi, G. P.; Young, P. R. J. Biol. Chem. 1996, 271, 84888492. (27) Meneghini, M. D.; Ishitani, T.; Carter, J. C.; Hisamoto, N.; Ninomiya-Tsuji, J.; Thorpe, C. J.; Hamill, D. R.; Matsumoto, K.; Bowerman, B. Nature 1999, 399, 793-797. (28) Peng, J.; Schwartz, D.; Elias, J. E.; Thoreen, C. C.; Cheng, D.; Marsischky, G.; Roelofs, J.; Finley, D.; and Gygi, S. P. Nat. Biotechnol. 2003, 21, 921-926.

Journal of Proteome Research • Vol. 6, No. 11, 2007 4405

research articles (29) Rosas-Acosta, G.; Russell, W. K.; Deyrieux, A.; Russell, D. H.; Wilson, V. G. Mol. Cell. Proteomics 2005, 4(1), 56-72. (30) Shevchenko, A.; Wilm, M.; Vorm, O.; Mann, M. Anal. Chem. 1996, 68, 850-858. (31) Suzuki, H.; Chiba, T.; Kobayashi, M.; Takeuchi, M.; Suzuki, T.; Ichiyama, A.; Ikenoue, T.; Omata, M.; Furuichi, K.; Tanaka, K. Biochem. Biophys. Res. Commun. 1999, 256, 127-132. (32) Suzuki, Y.; Nakabayashi, Y.; Takahashi, R. Proc. Natl. Acad. Sci. U.S.A. 2001, 98, 8662-8667. (33) Theodorescu, D.; Sapinoso, L. M.; Conaway, M. R.; Oxford, G.; Hampton, G. M.; Frierson, H. F., Jr. Clin. Cancer Res. 2004, 10, 3800-3806. (34) Uchida, C.; Miwa, S.; Kitagawa, K.; Hattori, T.; Isobe, T.; Otani, S.; Oda, T.; Sugimura, H.; Kamijo, T.; Ookawa, K.; Yasuda, H.; Kitagawa, M. EMBO J. 2005, 24, 160-169. (35) Vanhecke, D.; Janitz, M. Oncogene 2004, 23, 8353-8358.

4406

Journal of Proteome Research • Vol. 6, No. 11, 2007

Zhou et al. (36) Wertz, I. E.; O’Rourke, K. M.; Zhou, H. L.; Eby, M.; Aravind, L.; Seshagiri, S.; Wu, P.; Wiesmann, C.; Baker, R.; Boone, D. L.; Ma, A.; Koonin, E. V.; Dixit, V. M. Nature 2004, 430, 694-699. (37) Wu, C. J.; Conze1, D. B.; Li, T.; Srinivasula1, S. M.; Ashwell, J. D. Nature Cell Biol. 2006, 8, 398-406. (38) Wu, R. Z.; Bailey, S. N.; Sabatini, D. M. Trends Cell Biol. 2002, 12, 485-488. (39) Yan, C.; Lu, D.; Hai, T.; Boyd, D. D. EMBO J. 2005, 24, 24252435. (40) Zanardi, A.; Giorgetti, L.; Botrugno, O. A.; Minucci, S.; Milani, P.; Pelicci, P. G.; Carbone, R. Mol. Cell Proteomics. 2007, 6(5), 939947. (41) Ziauddin, J.; Sabatini, D. M. Nature 2001, 411, 107-110.

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