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QUICK identification and SPR validation of signal transducersand activators of transcription 3 (Stat3) interacting proteins

Peng Zhenga, 1, Qiu Zhongb, 1, Qian Xionga, Mingkun Yanga, Jia Zhanga, c, Chongyang Lia,Li-Jun Bic,⁎, Feng Gea,⁎⁎aInstitute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, ChinabIBP-ARI Joint Center for Research on Tuberculosis, Antituberculosis Research Institute of Guangdong Province, Guangzhou 510630, ChinacNational Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China

A R T I C L E I N F O

⁎ Correspondence to: L.-J. Bi, Institute of Biop⁎⁎ Correspondence to: F. Ge, Institute of Hydro

E-mail addresses: blj@sun5.ibp.ac.cn (L.-J1 These authors contributed equally to this

1874-3919/$ – see front matter © 2011 Elseviedoi:10.1016/j.jprot.2011.10.020

A B S T R A C T

Article history:Received 18 July 2011Accepted 23 October 2011Available online 30 October 2011

Signal transducers and activators of transcription 3 (Stat3) has been reported to be involvedin the pathogenesis of various human diseases and is constitutively active in humanmultiple myeloma (MM) U266 cells. The Stat3-regulated mechanisms involved in theseprocesses, however, are not fully defined. To further understand the regulation of Stat3activity, we performed a systematic proteomic analysis of Stat3 interacting proteins inU266 cells. This analysis, termedquantitative immunoprecipitation combinedwith knockdown(QUICK), combines RNAi, stable isotope labeling with amino acids in cell culture (SILAC),immunoprecipitation, and quantitative MS. As a result, quantitative mass spectrometryanalysis allowed us to distinguish specific Stat3 interacting proteins from backgroundproteins and led to the identification of a total of 38 proteins. Three Stat3 interactingproteins — 14-3-3ζ, PRKCB and Hsp90 — were further confirmed by reciprocal co-immunoprecipitations and surface plasmon resonance (SPR) analysis. Our resultstherefore not only uncover a number of Stat3 interacting proteins that possess a varietyof cellular functions, but also provide new insight into the mechanisms that regulateStat3 activity and function in MM cells.

© 2011 Elsevier B.V. All rights reserved.

Keywords:Quantitative immunoprecipitationcombined with knockdown (QUICK)Stable isotope labeling with aminoacids in cell culture (SILAC)Stat314-3-3ζMultiple myelomaSurface plasmon resonance (SPR)

1. Introduction

Multiple myeloma (MM) is a B-cell malignancy characterizedby the accumulation of clonal plasma cells within the bonemarrow [1]. Although the pathogenesis of the disease stillremains unclear, it is well established that interleukin-6(IL-6) plays an essential role in the malignant progressionof MM [2–3]. Numerous reports suggest that IL-6 promotessurvival and proliferation of MM cells through the phosphory-lation of a cell signaling protein, Stat3 [4–5]. The Stat proteinsare a conserved family of transcription factors implicated in

hysics, Chinese Academybiology, Chinese Academ. Bi), gefeng@ihb.ac.cn (F.work.

r B.V. All rights reserved.

regulating processes such as inflammation, survival, prolifera-tion, metastasis, angiogenesis, and chemoresistance of tumorcells [6]. One of these members, namely Stat3, is ubiquitouslyexpressed and is functionally involved in regulating cellproliferation, differentiation and cell survival [7]. In manycancer cells, Stat3 signaling has been recognized as a pivotalpathway supporting survival and growth [8–10]. Stat3 is oftenconstitutively active in many human cancer cells includingMM, leukemia, lymphoma, and solid tumors [8, 11]. Stat3 canalso be activated by certain interleukins (e.g., IL-6) and growthfactors (e.g., epidermal growth factor). Upon activation, Stat3

of Sciences, China. Tel./fax: +86 10 64871293.y of Sciences, China. Tel./fax: +86 27 68780500.Ge).

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undergoes phosphorylation at serine 727 and at tyrosine 705,dimerization, nuclear translocation, and DNA binding, whichin turn leads to transcription of various genes, includingthose for apoptosis inhibitors (Bcl-xL, Mcl-1, and survivin),cell cycle regulators (cyclin D1 and c-myc), and inducers ofangiogenesis (VEGF) and metastasis (TWIST) [12].

The Stat3 signaling is modulated, both positively andnegatively, by its interaction with numerous other proteins,and cross-talk occurs with various other signaling cascades,including the NF-κB, AP-1 or PI-3K pathways [13]. Hence, akey step in understanding the physiological function ofStat3 and associated MM-pathology is placing Stat3 intobiochemical pathways by the identification of its interactingproteins. A systemic identification of Stat3 protein interactionsmay provide new clues about the molecular mechanism ofStat3 in MM pathogenesis. Therefore, in this study, we system-atically analyzed the Stat3 interacting proteins using the QUICK(quantitative immunoprecipitation combinedwith knockdown)assay developed by Selbach and Mann [14]. This methodwas used to identify interactions between proteins at theirendogenous levels and in their normal cellular environ-ment by a combination of stable isotope labeling withamino acids (SILAC) [15], RNAi-induced knockdown, co-immunoprecipitation, and quantitative MS. This highly sensi-tive and accurate approach for PPI analysis has been applied toidentify interaction partners of β-catenin and Cbl [14], 14-3-3ζinteracting proteins [16] and Lrrk2 interaction partners [17].

In this study, QUICK method was undertaken to identifyproteins that bind to Stat3 at endogenous level. In total, 38proteins were identifiedand20of themwerenovel Stat3putativepartners. Furthermore, we confirm the association of Stat3 with14-3-3ζ (YWHAZ), protein kinase C beta (PRKCB) and heat shockprotein 90 (HSP90) by reciprocal co-immunoprecipitations andsurface plasmon resonance (SPR) analysis. Taken together, ourresults revealed the functional diversity of Stat3 interacting pro-teins and provided new insight into the mechanisms that regu-late Stat3 activity and function in MM cells.

2. Materials and methods

2.1. Cell culture and RNA interference

The human myeloma cell line U266 was purchased fromAmerican Type Culture Collections (Rockville, MD). All cellswere routinely maintained in RPMI 1640 supplemented with1% penicillin/streptomycin, 1 mmol/L L-glutamine, and 10%fetal bovine serum at 37°C, 5% CO2 in air.

Stable Stat3 knockdownwas achieved by transfecting U266cells with a plasmid using the siSTRIKE U6 Hairpin CloningSystem (Promega, Madison, WI). The siRNA which targetedthe Stat3 sequence corresponded to nucleotides 823 to 841 ofhuman Stat3 [18]. A negative control scrambled siRNA(TTCTCCGAACGTGTCACGT) was used as a control. Theresulting pSiStrike/Stat3 and pSiStrike/control vectors werepurified and used to transfect the U266 cells. The plasmidswere introduced into U266 cells using the Nucleofector X005(Amaxa, Cologne, Germany), according to the OptimizedProtocol for theU266B1 cell line. Transfected cellswere selectedfor puromicin resistance for 3 weeks. One clone was selected

from pSiStrike/Stat3 transfected U266 cells (designated asU266-Si) and one from pSiStrike/control transfected U266 cells(designated as U266-Ctr).

2.2. QUICK identification of Stat3 interacting proteins inU266 cells

Stat3 interacting proteins were identified from U266 cells byusing the QUICK approach. The assay and SILAC labelingwere done essentially as described earlier [16]. In brief, U266-Si and U266-Ctr cells were grown in SILAC RPMI 1640 Medium(Pierce) containing 10% v/v dialyzed FBS, and 0.1 mg/mL heavy[13C6] or Light [12C6] L-lysine. In the forward SILAC experiment,the U266-Si cells were cultured in light medium, whereas theU266-Ctr cells were cultured in heavy medium. ReverseSILAC experiments were also performed in which the U266-Si and U266-Ctr cells were cultured in the heavy and lightmedium, respectively. To ensure full incorporation of theheavy and light labeled amino acids, cells were grown forat least six cell doublings prior to harvest.

U266-Si or U266-Ctr cells were harvested, washedwith PBS,incubated in 1.0% w/v paraformaldehyde (PFA) in PBS for10 min at 37 °C. Cross-linking reaction, antibody couplingand immunoprecipitation were performed essentially asdescribed earlier [16]. Immunoprecipitated proteins wereeluted and separated on a 10% SDS-PAGE gel and visualizedwith silver staining.

2.3. Protein separation and in-gel digestion

Protein bands were excised from the SDS-PAGE gel and cutinto 20 sections for in-gel tryptic digestion. In-gel trypticdigestion was performed essentially as described earlier[16]. The peptide extract and the supernatant of the gelslice were combined and then finally concentrated to a volumeof as little as 20 μL to inject into the nanoLC system.

2.4. Mass spectrometry, protein identificationand quantification

Dried peptides were reconstituted in 5% acetonitrile/0.1%formic acid and analyzed essentially as described earlier[16]. All identified peptides were subjected to relative quantifi-cation analysis using the program Census [19]. Only proteinswith a minimum of 2 quantifiable peptides were included inour final dataset. The protein ratios were calculated from theaverage of all quantified peptides. The quantification wasbased on four independent SILAC and LC-MS/MS experiments,which included two forward and two reverse SILAC labelings.Grubbs test [14] was utilized to test whether the determined ra-tios were significantly different from the 1:1 ratios characteristicof background proteins and a p-value of 0.05 was selected asthreshold for significant enrichment of Stat3 interacting pro-teins. To reduce errors caused by possible interfering peaks,wemanually confirmedpeptide SILAC ratios for the proteins in-cluded in Table 1. Only those proteins with p<0.05 and quanti-fied in all four sets (including two forward and two reverse)of SILAC measurements were reported as Stat3-interactingproteins. The detailed description of the quantified peptidesand proteins is available in Tables S1 and S2.

Table 1 – Summary of Stat3 interacting proteins identified by QUICK method. Proteins are categorized according to theirmolecular function with gene names, protein names, average ratios and S.D. listed.

Gene name a) Protein name b) UniPort ID c) Average ratio(H/L)

S.D. p-value

ChaperoneHSP90B1 Heat shock protein 90 kDa beta P14625 4.08 0.47 <0.01YWHAQ 14-3-3 protein theta P27348 2.32 0.55 <0.01YWHAB 14-3-3 protein beta/alpha P31946 2.58 0.34 <0.01YWHAG 14-3-3 protein gamma P61981 2.46 0.36 <0.01YWHAE 14-3-3 protein epsilon P62258 2.35 0.51 <0.01YWHAZ 14-3-3 protein zeta/delta P63104 4.02 0.26 <0.01HSPH1 Heat shock protein 105 kDa Q92598 1.79 0.15 0.002

KinasePGK1 Phosphoglycerate kinase 1 P00558 2.4 0.2 <0.01MAP3K4 Mitogen-activated protein kinase kinase kinase 4 Q9Y6R4 3.26 0.3 <0.01MAPK1 Mitogen-activated protein kinase 1 P28482 6.01 0.22 <0.01MAPK14 Mitogen-activated protein kinase 14 Q16539 4.92 0.29 <0.01MAPK3 Mitogen-activated protein kinase 3 P27361 5.08 0.2 <0.01PRKCB Protein kinase C beta type P05771 3.89 0.39 <0.01PRKCA Protein kinase C alpha type P17252 3.69 0.66 <0.01PRKDC DNA-dependent protein kinase catalytic subunit P78527 4.24 0.41 <0.01PTK2 Focal adhesion kinase 1 Q05397 2.5 0.34 <0.01SRPK1 Serine/threonine–protein kinase Q96SB4 2.57 0.76 <0.01

PhosphatasePPP2R1A Serine/threonine–protein phosphatase 2A 65 kDa

regulatory subunit A alpha isoformP30153 4.11 0.68 <0.01

PPP2R1B Serine/threonine–protein phosphatase 2A 65 kDaregulatory subunit A beta isoform

P30154 4.14 0.45 <0.01

PPP2CA Serine/threonine–protein phosphatase 2A catalyticsubunit alpha isoform

P67775 2.9 0.89 <0.01

PPP2R5D Serine/threonine–protein phosphatase 2A 56 kDaregulatory subunit delta isoform

Q14738 3.9 0.58 <0.01

Enzyme modulatorCDC37 Hsp90 co-chaperone Cdc37 Q16543 3.19 0.26 <0.01

IsomeraseFKBP4 FK506-binding protein 4 Q02790 5.05 0.4 <0.01

Nucleic acid bindingHNRNPK Heterogeneous nuclear ribonucleoprotein K P61978 3.02 0.19 <0.01HNRNPH1 Heterogeneous nuclear ribonucleoprotein H P31943 6.11 0.24 <0.01HNRNPU Heterogeneous nuclear ribonucleoprotein U Q00839 3.25 0.44 <0.01EIF4G1 Eukaryotic translation initiation factor 4 gamma 1 Q04637 3.76 0.63 <0.01NCL Nucleolin P19338 4.96 0.71 <0.01ANXA1 Annexin A1 P04083 3.19 0.19 <0.01PTPRC Leukocyte common antigen P08575 3.19 0.48 <0.01EEF2 Elongation factor 2 P13639 4.25 0.38 <0.01

OxidoreductaseHDAC1 Histone deacetylase 1 Q13547 3.72 0.53 <0.01HDAC2 Histone deacetylase 2 Q92769 2.83 0.3 <0.01

Transcription factorSTAT3 Signal transducer and activator of transcription 3 P40763 5.06 0.57 <0.01STAT5A Signal transducer and activator of transcription 5A P42229 5.13 0.3 <0.01STAT5B Signal transducer and activator of transcription 5B P51692 4.7 0.38 <0.01CAND1 Cullin-associated NEDD8-dissociated protein 1 Q86VP6 2.15 0.25 <0.01ILF2 Interleukin enhancer-binding factor 2 Q12905 2.3 0.32 <0.01

a) Name of the corresponding gene according to the IPI database.b) Name of identified proteins according to the IPI database.c) Accession numbers are derived from the UniProt database.

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2.5. Bioinformatics analysis of the Stat3 interacting proteins

All identified Stat3-interacting proteins were classified basedon the PANTHER (Protein ANalysis THrough EvolutionaryRelationships) system (http://www.pantherdb.org), whichis a unique resource that classifies genes and proteins bytheir functions [20]. Some proteins were annotated manuallybased on literature searches and closely related homologues.

The differentially expressed protein interaction networkwas built automatically by the STRING (Search Tool for theRetrieval of Interacting Genes/Proteins) system with defaultsetting except that organism, confidence (score), and interactorsshownwere set to “human”, “0.40”, and “nomore than 10 inter-actors”, respectively [21]. The gene name list of these proteinswas input to search against the database which containsknown and predicted protein–protein interactions. The retrieveincluded a detailed network which highlights several hubproteins.

To determine if any types of proteins are overrepresented,enrichment analysis of Gene Ontology (GO) terms [22] andKyoto Encyclopedia of Genes and Genomes (KEGG) pathways[23] was performedusing theweb-accessible programDatabasefor Annotation, Visualization and IntegratedDiscovery (DAVID )6.7 [24–25]. The default human proteome was used as thebackground list. The significance of the enrichmentswas statis-tically evaluated with a modified Fisher's exact test, and ap-value for each term was calculated by applying a Benjamini–Hochberg false discovery rate correction [24–25]. For GO termsenrichments, the GO fat annotation available in DAVID wasused. TheGO fat is a subset of theGO termset createdby filteringout the broadest ontology terms in order to do not overshadowmore specific ones. GO slims are cut-down versions of the GOontologies containing a subset of the terms in the whole GO.They give a broad overview of the ontology content withoutthe detail of the specific fine grained terms. The enrichmentof GO biological process terms was also analyzed using theCytoscape and its Plugin the Biological Networks Gene Ontologytool (BiNGO) 2.3 [26], using the complete GO term set and ahypergeometric statistical test with Benjamini–Hochberg falsediscovery rate correction. The GO categories, the distribution ofcellular components, molecular functions and biological pro-cesses of the Stat3 interacting proteins were analyzed.

2.6. Co-immunoprecipitation and Western blot analysis

Co-immunoprecipitation and Western blot analysis was per-formed essentially as described earlier [16]. The antibodiesand sources of the antibodiesused in this studywere as follows:14-3-3ζ, GAPDH antibodies (Santa Cruz Biotechnology, SantaCruz, CA), Stat1, Stat2, Stat5, Stat3, pY705-Stat3, pS727-Stat3antibodies (Cell Signaling, Danvers, MA), PRKCB antibody(BD Biosciences, San Jose, CA), Hsp90 antibody (Abcam, Inc.,Cambridge, MA).

2.7. Surface plasmon resonance (SPR) analysis

SPR experiments were carried out at 25 °C using a BIAcore3000 instrument (BIAcore AB, Uppsala, Sweden). SPR buffers,regeneration solutions and sensor chips were purchasedfrom GE Healthcare (Uppsala, Sweden). Chemicals unless

otherwise stated were from Sigma (St. Louis, MO, USA).Purchased proteins were: Stat3, 14-3-3γ (YWHAG), 14-3-3ζ(YWHAZ), protein phosphatase 2 catalytic subunit (PPP2CA),protein kinase C beta (PRKCB), heat shock protein 90 kDabeta (HSP90B1) and enolase 2 (ENO2) (OriGene Technologies,Rockville, MD). The surface of CM5 chipwas activated followinga standard 1-ethyl-3 (3-dimethylaminopropyl)-carbodiimidehydrochloride/N-hydroxysuccinimide amine coupling Biacoreprotocol. For immobilization of proteins, the Stat3 protein wasinjected in 100 μL of 10mM sodium acetate (flow rate: 10 μL/min). After immobilization, each surface was blocked by 1 Methanolamine at pH 8.5 for 6 min. For interaction measure-ments, recombinant human proteins (YWHAZ, PPP2CA,PRKCB, HSP90B1 and ENO2) were dissolved according to theinstructions of the manufacturer (OriGene Technologies).Various concentrations of proteins were injected over thisinteraction surface for 5 min in a buffer containing 150 mMNaCl, 5 mM CaCl2, 0.005% (v/v) Tween 20, 20 mM Hepes(pH7.4) with a flow rate of 5 μL/min. The sensor surface wasregenerated between sample injections by washing with 6 Mguanidine-HCl for 0.5 min at the flow rate of 50 μL/min. Anequivalent volume of each protein sample (analyte) wasinjected over a chip surface with no protein immobilized toserve as a blank phase for the background subtraction.ENO2, which was identified as a background protein by ourQUICK method, was injected as a negative control in thesame condition. All experiments were repeated at leastthree times. The kinetic parameters (ka: association rate con-stant; kd: dissociation rate constant; KD=kd/ka: equilibriumdissociation constant) for each interaction were determinedby globally fitting the experimental data with BIAevaluationsoftware 4.1 (GE Healthcare).

2.8. Statistical analysis

Data are expressed as the mean±standard error of the meanfromat least three separate experiments performed in triplicate,unless otherwise noted. Statistical analysis was performedusing a two-tailed Student's t-test. Results were consideredsignificant if p-values were less than 0.05.

3. Results

3.1. QUICK identification of specific Stat3 interacting proteins

To identify Stat3 interacting proteins we conducted the QUICKapproach which is a SILAC-based quantitative strategy to cap-ture endogenous protein–protein interactions with very highconfidence [14]. The strategy for purification and identifica-tion of interacting proteins associated with Stat3 by QUICKmethod was illustrated in Fig. 1A. A prerequisite for theQUICK assay is the availability of RNAi cells exhibitingreduced expression of the protein of interest. Stat3 genesilencing was achieved by transfecting U266 cells with theStat3 shRNA plasmids as described earlier [27]. Stat3 knock-down efficiency was monitored by western blot analysis usingthe Stat3-specific antibody. As shown in Fig. 1B, Stat3 knock-down U266 cells (U266-Si) showed diminished Stat3 proteinlevels comparing with the parental U266 and U266 transfected

Fig. 1 – QUICK identification of STAT3 interacting proteins in U266 cells. (A) Schematic showing application of forward andreverse SILAC coupledwith in vivo cross-linking and RNAi to identify specific STAT3-interacting proteins. U266-Si and U266-CtrCells were differentially labeled by growing them in medium containing light or heavy amino acids (SILAC). Cells were lysed,combined, immunoprecipitated and analyzed by quantitative proteomics (LC-MS/MS). (B) Expression of STAT isoforms in U266parental (U266) and control cells (U266-Ctr) and U266/STAT3 shRNA cells (U266-Si). Compared with the parental U266 andU266-Ctr cells, U266-Si cells showed diminished STAT3 protein levels. Depletion of STAT3 showed no obvious effect on theexpression of other STAT isoforms. GAPDH blotting was performed to ensure equal loading. (C) Functional distribution ofidentified STAT3 interacting proteins. Categorizations were based on information provided by the online resource PANTHERclassification system.

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with negative control shRNA (U266-Ctr). Depletion of intra-cellular Stat3 showed no obvious effect on the expression ofother Stat isoforms and internal control GAPDH (Fig. 1B). Theimmunoprecipitated complex was eluted, separated on SDS-PAGE and visualized with silver staining (Fig. S1). Stained gelwas cut into 20 sections andsubjected to in-gel trypsindigestion(Fig. S1). The resulting peptidemixtureswere extracted from thegel and analyzed by LC-MS/MS analysis. As expected, Stat3 wassignificantly enriched 5.06-fold in the wt compared to theknockdown condition (Table 1). According to the criteriadescribed in Materials and methods, a total of 38 proteinswe identified as potential Stat3 interaction partners (Table 1).Moreover, we found 33 proteins being equally abundant in

both conditions and therefore considered as backgroundproteins (Table S2). The detailed information of all quantifiedproteins is shown in Tables S1 and S2.

Comparison of our data set with 799 known and pre-dicted interacting proteins of Stat3 (http://www.genecards.org/cgi-bin/carddisp.pl?gene=STAT3&search=stat3&rf=/home/genecards/current/website/carddisp.pl&interactions=799#int) re-vealed overlap but also differences (Table S3). About 17 (46%)of the proteins identified in this study have been reported inprevious studies as putative Stat3 binding partners and 21 pro-teins were newly identified Stat3 interacting partners (TableS3). It is worthmentioning that six previously reported putativeStat3 binding partners, COPB1, DDB1, HSPA8, IQGAP1, PDIA3,

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and PSMD1, had SILAC ratio close to 1, indicating that under ourexperimental conditions they are likely nonspecific interactingproteins (Tables S2 and S3). The novel proteins identified inour experiment might be a result of differences in cell lines,cell culture conditions, purification strategies, and mass spec-trometry platforms used.

3.2. Functional categories and protein association networkof identified proteins

To understand the biological relevance of the Stat3 interactingproteins, PANTHER classification system was used to classifythese interactors according to their functions. The PANTHERclassification system revealed that the interactors can be clas-sified into 8 groups according to their functions (Fig. 1C). Thelargest group of Stat3-interacting proteins is kinase (26%). Sig-nificant numbers of Stat3 targets are also implicated in nucleicacid binding (22%), chaperone (16%), and phosphatase (11%), in-dicating the functional diversity of Stat3 interacting proteins.

Fig. 2 – The protein–protein interaction network of the identifiedmapped using the STRING system (http://string.embl.de/) basedlinks betweenproteins represent possible interactions. Different lwhich are shown in the legend. Neighborhood stands for runs of gCo-occurrence: the presence of linked proteins across species. Co-other species (transferred by homology). Experiments: the prprotein–protein interaction databases. Databases: the protein inTextmining: the protein interaction informationwas extracted findividual gene fusion events per species.

Among the 38 identified proteins, 34 of them can be linkedthrough direct interaction into a protein–protein interactionnetwork based on the prediction results of STRING system(Fig. 2). Notably, several 14-3-3 proteins were hubs in this net-work and have the greatest number of connections. Bycomparing with 427 known and predicted interacting pro-teins of 14-3-3ζ (http://www.genecards.org/cgi-bin/carddisp.pl?gene=YWHAZ&rf=/home/genecards/current/website/carddisp.pl&interactions=446#int), 16 out of the 37 proteins are known14-3-3ζ interactors. In our previous study, we also found thatStat3 is one of the novel 14-3-3ζ interacting proteins [16]. Theseresults suggested that 14-3-3ζ can interact with Stat3 in vivoand may play an important role in regulating Stat3 activity inMM cells.

3.3. GO analysis of the Stat3 interacting proteins

To gain insights into functional roles of Stat3, the over-representation (enrichment) of ontology termsand components

proteins. The network containing 37 identified proteins wason evidence with different types. In the evidence view, theine colors represent the types of evidence for the associations,enes that occur repeatedly in close neighborhood in genomes.expression: the genes that are co-expressed in the same or inotein interaction information was gathered from otherteraction information was gathered from curated databases.rom the abstracts of scientific literature. Fusion stands for the

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of molecular pathways in the Stat3 interacting proteins wasanalyzed in comparison to their occurrence in the human pro-teome. First, a GO slimGeneric assignment gave us an overviewof the GO distribution. The GO terms can also be visualized as agraph where directed links describe the hierarchy and relation-ships between terms. Fig. 3 shows the graphical representationof the results. The colored nodes are those determined to beoverrepresented with statistical significance. We found that bylooking at the closest branch points of the overrepresented GOterms, protein modification process, protein binding functionand cytosol proteins strongly enriched in the Stat3 interactingproteins (Fig. 3). Next, we performed a GO biological processanalysis, and a molecular function and cellular componentanalysis (Table 2 and Tables S4–S6). GO biological process analy-sis provides a comprehensive picture of the Stat3 interactingproteins inwhich protein kinase cascade, regulation of apopto-sis, regulation of programmed cell death, regulation of celldeath and regulation of phosphate metabolic process were alloverrepresented (Table 2). In the GO molecular functions cate-gory, we found that the most overrepresented functions in theGO molecular functions category were involved in regulatingbinding activity, such as phosphoprotein binding, ATP binding,

Fig. 3 – Overview of the GO slim generic distribution of the identCytoscape. The GO terms enriched in the Stat3 interacting proteindicate hierarchies and relationships between terms. Node sizbelonging to the functional category. Node color indicates the cothe legend. Information on all annotations is provided in Table

adenyl ribonucleotide binding and nucleotide binding. In theGO cellular component category, we found that most of theStat3 interactingproteins identifiedwere localized in thenuclearlumen (p-value=1.01×10−7), cytosol (p-value=7.75×10−5) andintracellular organelle lumen (p-value=1.25×10−4).

3.4. Signaling pathway analysis

To validate some of the proteins identified by QUICK, co-immunoprecipitation experiments and Western blot analysiswere performed. We first examined the phosphorylationstatus of Stat3 in U266 cells by using phospho-tyrosineand phospho-serine specific Stat3 antibodies. Consistentwith previous report [8], Stat3 is constitutively activated inU266 cells (Fig. S2). Based on howwell their biological functionsand importance are known, we selected three putative Stat3binding proteins for validation. As shown in Fig. 4A, Stat3,14-3-3ζ, PRKCB and Hsp90 were detected in the Stat3 immunecomplex (Stat3) and the U266 cell lysate (Input) but not inthe non-immune IgG control (IgG). Furthermore, reverseimmunoprecipitation assay using specific antibodies forthese proteins followed by Western blotting with 14-3-3ζ

ified Stat3 interacting proteins using BINGO 2.3, a plugin ofins are shown as nodes connected by directed edges thate is proportional to the number of Stat3 interacting proteinsrrected p-value for the enrichment of the term according tos S4–S6.

Table 2 – GO biological process terms enriched in the Stat3 interacting proteins. The top 5 GO biological process, molecularfunction and cellular component terms enriched in the Stat3 interacting proteins are listed. A complete list can be found inTables S4–S6.

Term Description Count a) % b) P-value c)

GO:0007243 Protein kinase cascade 11 29.72 1.52E−08GO:0042981 Regulation of apoptosis 14 37.83 3.03E−08GO:0043067 Regulation of programmed cell death 14 37.83 3.41E−08GO:0010941 Regulation of cell death 14 37.83 3.56E−08GO:0007242 Intracellular signaling cascade 16 43.24 1.03E−07GO:0051219 Phosphoprotein binding 4 10.81 5.47E−05GO:0005524 ATP binding 14 37.83 9.40E−05GO:0032559 Adenyl ribonucleotide binding 14 37.83 1.08E−04GO:0000166 Nucleotide binding 17 45.94 1.34E−04GO:0004674 Protein serine/threonine kinase activity 8 21.62 1.51E−04GO:0005829 Cytosol 16 43.24 1.01E−07GO:0031981 Nuclear lumen 13 35.13 7.75E−05GO:0070013 Intracellular organelle lumen 14 37.83 1.25E−04GO:0043233 Organelle lumen 14 37.83 1.59E−04GO:0005654 Nucleoplasm 10 27.02 1.72E−04

a) The number of Stat3 interacting proteins.b) The percentage of mapped proteins associated with each term.c) The statistical significance of the difference between the fraction of Stat3 interacting proteins assigned to this GO term and the fraction of allproteins within the human protein set assigned to this GO term.

Fig. 4 – Western blot analysis after co-immunoprecipitation. Immunoprecipitation assays of Stat3, 14-3-3ζ, PRKCB and Hsp90proteins were carried out in U266 cells as described in theMaterials andmethods section. (A) Immunoblot analysis demonstratedthat Stat3 protein bindswith 14-3-3ζ, PRKCB andHsp90proteins.No bandof Stat3was observed in the negative control (IgG). Inputstands for the total cell lysate extracted from U266 cells. Similarly, reverse immunoprecipitation assays confirmed the binding of(B) 14-3-3ζ, (C) PRKCB and (C) Hsp90 protein with Stat3.

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(Fig. 4B), PRKCB (Fig. 4C) and Hsp90 (Fig. 4D) confirmed theirbinding to Stat3. Thus, compelling evidence shows that Stat3interacts with 14-3-3ζ, PRKCB and Hsp90 proteins in U266 cells.

3.6. SPR analysis

The kinetic parameters for the binding of several Stat3 inter-acting proteins to Stat3 were analyzed using SPR method.We first test the phosphorylation status of the purified Stat3protein by using phospho-serine or -tyrosine specific Stat3antibodies. As shown in Fig. S3, purified Stat3 protein wasphosphorylated at both tyrosine 705 and serine 727. Then, we

Fig. 5 – Characterization of the interaction of YWHAG, YWHAZ, PSPR analysis was carried out as described in the Materials andme(25, 50, 100, 200, 400 nM) with Stat3; (B) YWHAZ (25, 50, 100, 200,Stat3; (D) PPP2CA (5, 10, 50, 100, 150 μM) with Stat3; (E) PRKCB (5200 μM) with Stat3.

selected five putative Stat3 interacting proteins for SPR analysis.These includedYWHAG, HSP90B1, YWHAZ, PPP2CAand PRKCB.We also included ENO2, which was identified as a backgroundprotein by QUICK method as a negative control for these SPRexperiments. Injection of solutions of individual proteins inthe runningbuffer into a chip containing covalently immobilizedStat3 resulted in the appearance of a characteristic response(Fig. 5). Response unit (RU) values were proportional to sampleconcentrations within certain ranges (Fig. 5). This in vitro assaysystem clearly demonstrated that YWHAG, YWHAZ, PPP2CA,PRKCB and HSP90B1 have affinity for immobilized Stat3,whereas no interaction between ENO2 and Stat3 occurred

PP2CA, PRKCB, HSP90B1 and ENO2 with Stat3 by SPR assays.thods section. Sensorgrams of the interactions of (A) YWHAG400 nM) with Stat3; (C) HSP90B1 (5, 10, 50, 100, 150 μM) with, 10, 50, 100, 200 μM) with Stat3; (F) ENO2 (5, 10, 50, 100,

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under the same conditions (Fig. 5). Evaluation of the sensor-grams has shown that the equilibrium dissociation con-stants (KD) for the interaction of YWHAG, YWHAZ, PPP2CA,PRKCB and HSP90B1 with immobilized Stat3 were: YWHAG,KD=700 nM; YWHAZ, KD=56 nM; PPP2CA, KD=110 nM; PRKCB,KD=610 nM; HSP90B1, KD=390 nM, respectively (Table 3). Fur-thermore, subsequent injection of the running buffer causedrapid dissociation of YWHAG and YWHAZ, whereas in thecase of PPP2CA, PRKCB and HSP90B1 their dissociation occurredmuch slower. This suggests different affinity of the proteinstested towards Stat3. Especially, the relatively high affinitybetween YWHAZ and Stat3 raised the possibility thatYWHAZ may have biological importance in Stat3 pathway.

4. Discussion

Stat3 activity is tightly regulated by its interacting proteinsand multiple signaling cascades and its prolonged activationis associated with various malignancies, including MM [8, 28].To further understand the regulation of Stat3 activity in MMcells, we have performed a comprehensive analysis of theinteractome of Stat3 inmyeloma cells using the QUICKmethod.As a result, a total of 38 Stat3 interacting proteins were identi-fied with very high confidence. Importantly, the current studyrevealed anumber of novel Stat3 bindingpartners. Furthermore,the interaction of Stat3 with 14-3-3ζ, PRKCB and Hsp90 wasconfirmed by co-immunoprecipitation/Western blot analysisand SPR study.

In this study, five 14-3-3 proteins, e.g. 14-3-3θ (YWHAQ), 14-3-3β (YWHAB), 14-3-3γ (YWHAG), 14-3-3ε (YWHAE), 14-3-3ζ(YWHAZ), were identified as Stat3 interacting proteins(Table 1). In particular, as suggested by bioinformational analysis(Fig. 2), 14-3-3 proteins may play an important role in regulatingStat3 activity in MM cells. The 14-3-3 proteins are a family ofubiquitously expressed regulatory molecules and sevenisoforms, designated δ, η, γ, ε, θ, β and ζ, have been describedpreviously [29–30]. The 14-3-3 proteins have raised to a positionof integrators of diverse signaling cues that impact cell fate andcancer development [31]. Through regulated interactions withcrucial signaling mediators, such as PKC [32–33], MAPK [34–36],or AKT [37–39], 14-3-3 controls diverse cellular responsesranging from signal transduction, cell cycle, metabolism, andapoptosis [31]. Among seven 14-3-3 proteins, 14-3-3ζ, alsotermed as YWHAZ (tyrosine 3-monooxygenase/tryptophan 5-

Table 3 – Kinetic parameters of proteins binding to Stat3.ka: association rate, kd: dissociation rate, and KD: kd/ka,dissociation constant; ND: not determined due to lowinteraction signal.

Interactingproteins

ka (M−1S−1) kd (S−1) KD (M) (kd/ka)

Stat3/YWHAG (3.3±0.3)×104 (2.3±0.6)×10−2 (7.0±1.4)×10−7

Stat3/YWHAZ (1.2±0.4)×106 (6.7±1.6)×10−2 (5.6±1.1)×10−8

Stat3/HSP90B1 (1.2±0.2)×103 (4.7±1.3)×10−4 (3.9±1.7)×10−7

Stat3/PPP2CA (1.5±0.7)×103 (1.6±0.1)×10−4 (1.1±0.6)×10−7

Stat3/PRKCB (4.4±1.2)×102 (2.7±0.3)×10−4 (6.1±0.5)×10−7

Stat3/ENO2 ND ND ND

monooxygenase activation protein, zeta polypeptide), hasbeen shown to play a central role regulating multiple path-ways responsible for cancer initiation and progression [40].Involvement of 14-3-3ζ in multiple signaling pathways hasbeen reported and activities of various signaling mediators aredifferentially regulated by 14-3-3ζ viadirect physical association[40]. However, whether 14-3-3ζ also regulates the Stat familywas unknown. In this study, both co-immunoprecipitationandSPR results clearly showed that 14-3-3ζ is a Stat3 interactingprotein. Therefore, it is tempting to suggest that 14-3-3ζ mayplay an important role in regulating Stat3 activity in MM cells.Experiments testing this hypothesis are ongoing in ourlaboratory.

Our proteomic studies also identified several PKC isoformsandPP2Asubunits as Stat3 interacting proteins (Table 1). Proteinkinase C (PKC) comprises a family of Ser/Thr kinases and isdivided into three subfamilies termed conventional (cPKC:α, βI, βII, and γ), novel (nPKC: δ, ε, η and θ) and atypical(aPKC: ζ and ι) [41]. The PKCs play a crucial role in manyintracellular signal-transducingpathways [42]. Thesepathwaysare involved in various vital functions, including regulation ofcell proliferation and differentiation, cell-to-cell interactions,secretion, gene transcription, apoptosis and drug resistance[42]. PKC pathways have been implicated in MM cell prolifera-tion, apoptosis and migration and tumor induced angiogenesis[43–46]. Recently, evidence indicated that PKC interacts withStat3, phosphorylates Stat3 Ser727, and increases both DNAbinding and transcriptional activity of Stat3 [47].

Protein phosphatase 2A (PP2A) refers to a large family ofheterotrimeric serine–threonine phosphatases that accountfor the majority of serine–threonine phosphatase activity inmost cells and tissues [48]. PP2A have been implicated in cellcycle regulation, cell morphology and development [49] andis an essential factor for survival and growth of myelomacells [50]. PP2A also plays a prominent role in the regulationof Stat3 phosphorylation, subcellular distribution, and DNAbinding activity [51].

Consistent with these reports, both QUICK and SPR resultsclearly showed that protein phosphatase 2 catalytic subunit(PPP2CA) and protein kinase C beta (PRKCB) are Stat3-associated proteins. These data, along with the results onStat3/14-3-3ζ interaction, support the hypothesis that multi-ple signaling proteins, including PKC and PP2A, impinge onStat3 and that 14-3-3ζ serves as a coordinator for differentpathways to regulate Stat3 activity inMMcells. This speculativeidea, however, is not yet supported by experimental data, andfurther experimentswill be required to determine the functionalimplication of 14-3-3ζ/Stat3 interaction.

In conclusion, we demonstrated QUICK as a powerful andunambiguous method for quantitative analysis of protein in-teractions. By using this approach, we systematically profiledproteins interacting with Stat3 in MM cells. Many reliableStat3 interacting proteins were identified and some interestingclues were given. In addition to those previously described, wehave identified many novel proteins that are involved invarious biological processes, many of which have not beenpreviously described in association with Stat3. It is now im-portant to further characterize the interactions between theStat3 and individual target proteins and to define the signaltransduction pathways that control binding of Stat3 to their

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multiple binding partners in response to changing physio-logical and pathological conditions.

Supplementary materials related to this article can befound online at doi:10.1016/j.jprot.2011.10.020.

Acknowledgements

This work was supported by the Hundred Talents Program ofthe Chinese Academy of Sciences, National Basic ResearchProgram of China (973 Program, 2012CB518700), and the OpenResearch Fund of National Laboratory of Biomacromolecules.

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