Systematic Analysis of Human ProteinComplexes Identifies ChromosomeSegregation ProteinsJames R. A. Hutchins,1* Yusuke Toyoda,2* Björn Hegemann,1*† Ina Poser,2*Jean-Karim Hériché,3,4 Martina M. Sykora,1 Martina Augsburg,2 Otto Hudecz,1Bettina A. Buschhorn,1 Jutta Bulkescher,4 Christian Conrad,4 David Comartin,5,6Alexander Schleiffer,1 Mihail Sarov,2 Andrei Pozniakovsky,2 Mikolaj Michal Slabicki,2Siegfried Schloissnig,2,7 Ines Steinmacher,1 Marit Leuschner,2 Andrea Ssykor,2 Steffen Lawo,5,6Laurence Pelletier,5,6 Holger Stark,8 Kim Nasmyth,1‡ Jan Ellenberg,4 Richard Durbin,3Frank Buchholz,2 Karl Mechtler,1 Anthony A. Hyman,2§ Jan-Michael Peters1§

Chromosome segregation and cell division are essential, highly ordered processes that depend onnumerous protein complexes. Results from recent RNA interference screens indicate that theidentity and composition of these protein complexes is incompletely understood. Using genetagging on bacterial artificial chromosomes, protein localization, and tandem-affinity purification–mass spectrometry, the MitoCheck consortium has analyzed about 100 human protein complexes,many of which had not or had only incompletely been characterized. This work has led to thediscovery of previously unknown, evolutionarily conserved subunits of the anaphase-promotingcomplex and the g-tubulin ring complex—large complexes that are essential for spindle assemblyand chromosome segregation. The approaches we describe here are generally applicable tohigh-throughput follow-up analyses of phenotypic screens in mammalian cells.

Phenotypic screens using random mutagen-esis, systematic gene deletion, or RNA inter-ference (RNAi) are powerful techniques for

cataloguing gene function. To interpret the result-ing genotype-phenotype relationships, detailedmolecular analyses are required, among whichprotein localization and identification of proteininteractions are particularly informative. In yeast,the modification of most genes at their endoge-nous loci with tag-coding sequences has beenvaluable for systems-wide analyses of proteinfunction (1–4). In mammalian cells, however, large-scale localization and interaction studies of proteins

expressed under control of their own regulatorysequences have so far lagged behind phenotypicanalysis. The MitoCheck consortium (www.mitocheck.org) has therefore used recombineeringtechniques (5) to develop a fast and reliableprocedure for the introduction of genes tagged inbacterial artificial chromosomes (BACs) intohuman tissue culture cells. This technique allowsthe stable expression of genes under their ownpromoters at near-physiological levels (6). Wehave combined this “BAC TransgeneOmics”technology with large-scale protein localizationand interaction experiments to characterize about100 mitotic protein complexes (Fig. 1A). Byusing this combined approach, we discoveredpreviously unknown subunits of the g-tubulinring complex (g-TuRC) and the anaphase-promoting complex (APC/C), complexes thatare essential for spindle assembly and chromo-some segregation, respectively (7, 8).

Generation of a library of HeLa cell poolsstably expressing green fluorescent protein(GFP)–tagged BACs. We chose to characterizeproteins required for mitosis because this processis essential for eukaryotic life, is of relevancefor tumor biology, and is known to depend onnumerous protein complexes. Many of thesehad been characterized before, providing priorknowledge that we could use to control our ap-proaches and to draw hypotheses for unknowngenes. RNAi screens performed in C. elegans,Drosophila, and mammalian cells as well asproteomic studies have furthermore identifiednumerous uncharacterized proteins required for

mitosis (9–17). In addition, the MitoCheck con-sortium carried out a genome-wide RNAi screenby means of time-lapse imaging of chromosomesegregation in live cells that provided detailedphenotypic information for the majority of hu-man proteins (16).

From these screens and the literature, weselected 696 proteins (table S1) for C-terminaltagging with a combined localization affinity-purification (LAP) tag (18), using high-throughputBAC recombineering in Escherichia coli (6). Inmost cases, we tagged mouse genes and expressedthem in human cells because this allows func-tional testing of the tagged proteins throughRNAi-mediated depletion of their endogenouscounterparts (19). N-terminal tags were introducedif C-terminal tagging failed or in some casesto validate data obtained with the C-terminaltag. We were able to tag and stably express 591(89%) of the selected proteins in HeLa cells (fig.S1). For each gene, we obtained at least one non-clonal pool of stably expressing cells, resultingin a library of 657 pools. Using antibodies to theGFP moiety of the LAP tag, we could detect thetagged proteins in 559 pools (85%), correspond-ing to 504 unique proteins (77%), by means ofimmunofluorescence microscopy (IFM) (tableS1 and fig. S1C).

Localization of mitotic proteins. First, weanalyzed all cell pools in which a GFP signalcould be detected for the intracellular local-ization of tagged proteins in interphase, meta-phase, and telophase, using fixed cells stainedwith antibodies to GFP and a-tubulin, and4′,6-diamidino-2-phenylindole (DAPI) to visu-alize DNA (Fig. 1B). In mitotic cells, we ob-served specific association with centrosomes,spindles, kinetochores, chromosomes, cleavagefurrows, midbodies, or cortical structures for180 proteins, of which 25 had not been char-acterized in mitosis and 54 not at all (fig. S1C).For 14 proteins, we confirmed our fixed-celldata by means of time-lapse imaging of livingcells (Fig. 1C and fig. S2).

To identify proteins with potential roles inspindle assembly, we localized in more detail102 proteins that showed mitotic centrosome orspindle association. Of these, 23 had not beencharacterized in mitosis and 9 not at all. Immu-nofluorescence images were classified into 87staining patterns at five different mitotic stages,resulting in specific localization trajectories (Fig.1B and fig. S3). The frequency distribution ofdifferent patterns was scored manually, and the102 proteins were clustered into 10 groups accord-ing to these scores (Fig. 2). Localization analysiswith this resolution allowed separation even ofcomplexes with very similar localization, suchas the kinetochore complex MIS12 and the mi-totic checkpoint complex (MCC), into separatelocalization trajectories (see fig. S3). In all cases,subunits of known complexes were recoveredin the same clusters [chromosomal passengercomplex (CPC), centralspindlin, MIS12, Aurora

RESEARCHARTICLE

1Research Institute of Molecular Pathology (IMP), Dr. Bohr-Gasse7, A-1030 Vienna, Austria. 2Max Planck Institute (MPI) for Mo-lecular Cell Biology and Genetics, Pfotenhauerstrasse 108,D-01307 Dresden, Germany. 3Wellcome Trust Sanger Institute,Wellcome Trust Genome Campus, Hinxton, Cambridge CB101HH, UK. 4Cell Biology and Biophysics Unit, European MolecularBiology Laboratory, Meyerhofstrasse 1, D-69117 Heidelberg,Germany. 5Samuel Lunenfeld Research Institute, Mount SinaiHospital, 600 University Avenue, Toronto, Ontario M5G 1X5,Canada. 6Department of Molecular Genetics, University ofToronto, Toronto, Ontario M5S 1A8, Canada. 7German CancerResearch Center, Im Neuenheimer Feld 280, 69120 Heidelberg,Germany. 8Max Planck Institute for Biophysical Chemistry, AmFassberg 11, D-37077 Göttingen, Germany.

*These authors contributed equally to this work.†Present address: Institute of Biochemistry, EidgenössischeTechnische Hochschule Zürich, Schafmattstrasse 18, CH-8093Zürich, Switzerland.‡Present address: Department of Biochemistry, Universityof Oxford, South Parks Road, Oxford OX1 3QU, UK.§To whom correspondence should be addressed. E-mail:hyman@mpi-cbg.de (A.A.H.); peters@imp.univie.ac.at(J.-M.P.)

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A-targeting protein for Xklp2 (TPX2), andg-TuRC], although prior knowledge about theexistence of these complexes had not been usedto “train” the cluster algorithm. This suggests thatclustering of localization trajectories can beused to formulate hypotheses about functionsand physical interactions of uncharacterizedproteins. For example, centrosomal protein of120 kD (CEP120) clustered with proteins re-quired for centriole duplication, suggesting thatCEP120 may have a role in this process. RNAiexperiments indicated that this is indeed thecase (fig. S4).

Identification of mitotic protein complexes.To characterize mitotic protein complexes, weisolated LAP-tagged proteins from cells ar-rested in mitosis using tandem-affinity purifica-tion (TAP) (fig. S5) (6). Samples were analyzedwith SDS–polyacrylamide gel electrophoresis(SDS-PAGE) followed by silver staining andwith in-solution trypsinization and tandem massspectrometry (MS). Initially, proteins were selectedon the basis of localization identified by meansof GFP imaging or on reported mitotic functions.Once interaction partners had been identified,interaction mapping was performed iteratively

by producing new LAP-tagged cell pools tovalidate a subset of the interactions throughreciprocal analyses. In total, cell pools containing254 different tagged genes were analyzed. In 239cases (94%), the “bait” proteins could be iden-tified. These interacted with a total of 936 “prey”proteins that were present in specific samples,corresponding to 2011 distinct pair-wise inter-actions (20). Other proteins, which were foundin more than 4.5% of all samples or in “mock”purifications, were excluded from further analysesbecause these proteins might represent contam-inants (tables S2 and S3). For a complete pre-

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Fig. 1. Use of BAC TransgeneOmics for identification and characterizationof mitotic protein complexes in human cells. (A) Schematic outline of theworkflow established for BAC tagging, GFP localization, and TAP-MS ofmitotic proteins. (B) Representative images of fixed HeLa cells, obtained bymeans of IFM with antibodies to GFP. Examples are shown of cells thatstably express LAP-tagged proteins that have different locations in in-terphase, metaphase, or telophase, as indicated in the images. Images areconnected by lines that represent a subset of the localization trajectoriesobserved for different proteins. The red and blue lines represent thetrajectories of MIS12 and MCC, respectively. Dotted lines represent allobserved trajectories that include centrosome localization in metaphase.Scale bar, 10 mm. (C) Time-lapse images of a mitotic HeLa cell stablyexpressing H2B-mCherry (red) and the CPC subunit INCENP-LAP (green).Numbers indicate time (minutes) before and after anaphase onset. Scalebar, 10 mm.

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CEP55 NME7 PRC1 CENPE PFDN2 NDE1 RACGAP1 KIF23 CDCA8 AURKC AURKB KCNK1 CCDC61 M6PR AZI1 CSNK1E CEP170L_human WDR8 WDR51B WDR67 CEP164 CEP110 CNTROB PLK1 CEP350 PPP2R3C TUBGCP3 CEP170 NEDD1 MOZART2B TUBGCP2 MOZART1 TUBGCP6 TUBG1 CEP76 ODF2 FGFR1OP WDR51A CEP290 CEP192_human CDK5RAP2 CENPJ_human CEP78 PLK4 CEP250 CETN2 CEP63 CEP152 CCDC52 CEP120 NEK2 CEP135 TUBA3 NACA TPX2 NUP160 CKAP5_human LRRCC1 AURKA DYNLL1 COMMD4_human FOLR1 CETN3 TACC3 DCTN1 ACTR1A HAUS3 HAUS8 HAUS2 HAUS6 KIFC3 HAUS1 HAUS4 TUBB TUBB2C KIF11 DYNC1LI1 DCTN2 DYNC1H1 SKA3_human SPAG5 DCTN3 NDC80 SKA1_human KIF2C DYNLL2 DYNC1I2 AKAP9 C5orf37 C15orf23 RCN1 CCDC15 CCBE1_human XPC TUBA1C SFI1 PNMA2_human VBP1 KIFC1 KIF2B PCMT1 FZD7

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Fig. 2. Heat map showing hierarchical clustering of the localization trajectoriesof 102 spindle and centrosome proteins. IFM images of fixed HeLa cells ex-pressing LAP-tagged proteins (listed on the y axis) in five mitotic phases wereclassified into 33 staining patterns (mouse ortholog proteins were imaged unlesssuffixed as “_human”). The frequency with which each staining pattern wasobserved for each protein in each phase is represented by a square, with colorranging from black (0% occurrence) to bright green (100% occurrence). Thenumber codes for the staining patterns are as follows: 1, centrosome (PCM-like);2, centrosome (fine dots); 3, dots near centrosome; 4, centrosome and partialmicrotubule (MT); 5, microtubule; 6, chromosome; 7, kinetochore; 8, cortex(whole); 9, cortex (partial); 10, dots in cytoplasm; 11, ER-like meshwork; 12,nuclear envelope; 13, nucleus; 14, dots in nucleus; 15, nucleolus; 16, whole cell;17, spindle MT (whole); 18, spindle MT (K-fiber); 19, spindle matrix-like; 20,chromosome (axis); 21, chromosome (periphery); 22, kinetochore (sisters);23, kinetochore (inner); 24, microtubule (whole); 25, microtubule (K-fiber);

26, spindle midzone; 27, cleavage furrow; 28, microtubule next to midbody;29, microtubule (unclear); 30, midbody; 31, midbody ring; 32, midbodynext to ring; and 33, Golgi-like. The “status” column shows the charac-terization status of each gene, as defined by literature searching in PubMed,according to the following color scheme: blue, reported to be involved inmitosis; yellow, some function reported but not in the context of mitosis;and red, functionally uncharacterized. The dendrogram on the left indi-cates the relative similarities of the trajectories of individual proteins tothe entire trajectory pattern. The clustered heat map was divided into 10subclusters on the basis of a visual inspection of clustered localizationpatterns (subclusters indicated by alternating green and yellow shading).The names of subunits of previously identified complexes are boxed indifferent colors (Centralspindlin, light blue; CPC, magenta; g-TuRC, darkblue; Aurora A-TPX2, bright green; chTOG-TACC3, orange; Augmin/HAUS,red; SKA, olive-green).

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sentation of all data, see www.mitocheck.org.Additional information on tagged BACs can befound at http://hymanlab.mpi-cbg.de/BACE.

We analyzed baits from 11 previously de-scribed reference complexes which, accordingto the literature, contain 74 subunits (fig. S6A).Our experiments identified 70 of these, indicatinga low false-negative detection rate (fig. S6B). In175 cases, our experiments revealed interac-tions between two proteins, both of which hadbeen tagged and used as baits. Of these inter-actions, 94 (54%) could be detected with bothbaits. This frequency of reciprocal interactionsis higher than in previous studies performed inyeast [15% in (3); 8% in (4)]. These results sug-gest that the number of false-positive interactionsin our data set is relatively low. However, we can-not exclude that some false-positive interactionswere detected.

To identify previously unknown complexes,we analyzed the data set of all interactions forthe presence of proteins that are densely con-

nected with each other (fig. S7) using a cluster-ing algorithm that we call spectral fuzzy C-means(SFCM). We identified 35 singletons (cases inwhich only the bait had been found), 107 clustersthat contain between two and 20 proteins, and13 clusters with more than 20 components (Fig.3, figs. S7 and S8, and table S4). The 13 largeclusters contain sets of loosely connected pro-teins, which presumably had been grouped to-gether because the density of the interactionnetwork was not high enough to separate theseproteins into smaller, more meaningful clusters.However, among the 107 small clusters 11matchedthe reference complexes with an average preci-sion of 59% (the fraction of cluster membersthat belong to the same reference complex) andan average recall of 89% (the fraction of thereference complex subunits assigned to thesame cluster). These values indicate that manyof the small clusters represent bona fide proteincomplexes or groups of closely related com-plexes (for example, different isoforms of co-

hesin complexes clustered together) (table S4).As an example, Fig. 3 shows a graphical rep-resentation of 10 of the 107 small clusters andhow they compare with reference complexesdescribed in the literature. The entire interactionnetwork can be seen in the supporting visual-ization S1 file.

Identification and characterization of mitoticprotein complexes by combined interaction andlocalization studies. To test whether co-purifyingproteins interact in vivo, we analyzed in howmany cases similar localization patterns had beenobtained for interacting proteins. We manuallyannotated a subset of 728 interactions and foundthat 49% of all pairwise interacting bait andprey proteins had similar localizations. This fre-quency was even higher (79%) when only recip-rocally confirmed interactions were considered(fig. S9). For example, we observed that CEP120both co-localized and physically interacted withcoiled coil domain–containing 52 (CCDC52),suggesting that these proteins form a complex

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Fig. 3. Combined interaction and localization map for a selection of 10out of 107 small clusters (cluster size, 2 to 20 proteins). Proteininteraction data obtained by means of TAP-MS were analyzed with SFCMclustering. The resulting clusters (enclosed by orange dashed lines) weremanually annotated according to literature knowledge (for compositionof reference complexes as described in the literature, see fig. S6) (29).The resulting curated clusters are shown as gray ellipses: Complexescontaining reciprocal interactions are enclosed by solid gray lines,whereas those without reciprocal interactions are denoted by dashedgray lines. Inter- and intra-cluster interactions are represented bydashed and solid blue lines, respectively, with the number of in-

teractions corresponding to the thickness of these lines. Localization asdetermined by use of GFP imaging is shown in the color codes asindicated. Cluster and protein complexes can have interactions withseveral other clusters/complexes. For example, MCC co-purified andtherefore co-clustered both with APC/C and with the MIS12/NDC80cluster. The former association reflects binding of MCC to APC/C inprometaphase cells (30), from which these proteins were purified,whereas MCC association with MIS12/NDC80 may reflect recruitment ofMCC components to unattached kinetochores in prometaphase (31). Foran expanded “master map,” integrating localization and interactiondata for more proteins, see fig. S8.

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(Figs. 2 and 3). Similarly, we observed that eightproteins, which had not been characterized whenwe performed our experiments, interacted re-ciprocally with each other and were all locatedon mitotic spindles (fig. S10). These proteins aresubunits of the Augmin/HAUS complex, whichhas recently been shown to be essential for spin-dle function (21–23). Combining localization andinteraction data can also identify unknown in-teractions between well-characterized proteinsand complexes, as is illustrated by our findingthat Polo-like kinase 1-interacting checkpointhelicase [PICH, also known as excision repaircross-complementing rodent repair deficiency,complementation group 6-like (ERCC6L)] inter-acts and co-localizes on chromosome bridges

with subunits of the RTR complex [RecQhelicase (BLM)-topoisomerase III (TOP3A)–RecQ mediated genome instability 1 (RMI1)complex] (fig. S11) (24).

Identification of C10orf104 as a subunit ofthe APC/C. We further characterized chromo-some 10 open reading frame 104 (C10orf104)because this 11.7-kD protein co-purified withseven different APC/C subunits (fig. S12A), butnot with any other bait, and thus co-clustered withthe APC/C in our SFCM analysis (Fig. 3). TheAPC/C is a 1.5-MD ubiquitin ligase complex thatis essential for chromosome segregation andmitotic exit (8). Because APC/C has been char-acterized in detail, it was surprising that a pre-viously uncharacterized protein co-purified with

APC/C subunits. However, when C10orf104 alsowas used as bait several APC/C subunits weredetected (fig. S12A), and antibodies raised againstC10orf104 immunoprecipitated the entire APC/Cand its associated cyclin B ubiquitylation activ-ity (Fig. 4, A and B). Immunoblot experimentsshowed that C10orf104 is present throughoutthe cell cycle (fig. S12, B and C), and densitygradient centrifugation experiments indicatedthat most of C10orf104 is associated with theAPC/C (Fig. 4C). These observations indicatethat C10orf104 is a constitutive subunit of theAPC/C and not a substrate or a transiently asso-ciating regulatory protein. Electron microscopicanalysis of APC/C labeled with antibodies toC10orf104 suggested that C10orf104 is locatedat the top of APC/C’s “arc lamp” domain, in thevicinity of the subunit CDC27 (Fig. 4D and fig.S12, D to F). The amino acid sequence ofC10orf104 is highly conserved among verte-brates (95% identical between human andzebrafish), suggesting that despite its small size,this protein performs an important functionwithin the APC/C. Related sequences also existin invertebrates (fig. S12G), although we couldnot yet identify homologous sequences in yeast.These observations indicate that C10orf104 isan evolutionarily conserved APC/C subunit,which we propose to call APC16 (gene symbolANAPC16). We suspect that APC16 has pre-viously escaped detection in protein gels orthrough MS because of its small size.

Identification of proteins interacting withthe g-TuRC. We also characterized chromosome13 open reading frame 37 (C13orf37) and twoclosely related proteins, called family with se-quence similarity 128 member A and memberB (FAM128A and FAM128B), because theseproteins co-purified with three different subunitsof the g-TuRC. This complex is located at centro-somes and mediates the formation of bipolar spin-dles inmitosis (7).WhenC13orf37 and FAM128Bwere used as baits, all six known g-TuRC sub-units were identified (Fig. 3 and Fig. 5, A and B).Sucrose density gradient centrifugation experi-ments confirmed that C13orf37 and FAM128Bare associated with the g-TuRC component tu-bulin gamma 1 (TUBG1) (fig S13A). Similar tog-TuRC subunits, C13orf37 and FAM128Bwerelocated on centrosomes throughout the cell cycleand to a lesser extent on mitotic spindles (Fig. 2,Fig. 5, C and D, and fig. S13B). Proteins homol-ogous to C13orf37 and FAM128A/B are pre-dicted to exist in many eukaryotes, including inthe case of C13orf37 the fission yeast Schizosac-charomyces pombe (fig. S13, C and D). How-ever, the corresponding genomic sequences havenot been annotated as genes in all organisms,possibly because C13orf37 and FAM128A/B aresmall proteins of 8.5 and 16.2 kD, respectively.C13orf37 and FAM128A/B may thus be evolu-tionarily conserved g-TuRC subunits that previ-ously may not have been detected because oftheir small size. However, unlike the knownsubunits of g-TuRC [tubulin, gamma complex–

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Fig. 4. Characterization of APC16, a previously unknown subunit of the APC/C. (A) Silver-stainedSDS-PAGE gel showing proteins immunoprecipitated by using antibodies to APC16 or CDC27 fromextracts of HeLa cells, cultured under logarithmic growth conditions (L), or arrested in S phase bymeans of treatment for 18 hours with hydroxyurea (HU) or arrested in prometaphase by treatmentfor 18 hours with nocodazole (N). Numbers on the left indicate the molecular masses of referenceproteins. (B) Phosphorimage showing the ubiquitylation of Cyclin B1 (CCNB1), catalyzed by CDC27and APC16 immunoprecipitates. [125I]-labeled human CCNB1 fragment (amino acids 1 to 84) wasincubated with CDC27 or APC16 immunoprecipitates from logarithmically growing HeLa cells, plusE1 and E2 enzymes, ubiquitin, and adenosine 5´-triphosphate (ATP), with or without therecombinant co-activator protein CDH1, for the times indicated and then analyzed with SDS-PAGEand phosphorimaging. CON indicates empty protein-A beads (left) and a condensin antibodyimmunoprecipitate (right). The asterisk marks a contaminating band present in the CCNB1 sample.(C) Immunoblots showing the co-sedimentation of APC16 with core APC/C subunits CDC16 andAPC10, after density gradient centrifugation. An extract of logarithmically growing HeLa cells wassubjected to centrifugation through a 10 to 30% sucrose density gradient. Twenty-eight fractionswere collected and analyzed with SDS-PAGE and immunoblotting with the antibodies indicated. (D)Three-dimensional model of the human APC/C obtained with electron microscopy (30) showing thelocation of APC16, as determined by means of antibody labeling.

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Fig. 5. Characterizationof the g-TuRC interactingproteins MOZART1 andMOZART2B. (A) Silver-stained SDS-PAGE gelof LAP-purified TUBG1,TUBGCP3, TUBGCP6,MOZART2B, and MOZART1.Numbers on the left indi-cate themolecularmassesof reference proteins. Pro-teins annotated accordingto expected electrophoreticmobility are listed on theright. CCT, chaperonin-containing T-complex.(B) MS results obtainedfrom the samples in (A),showing identificationof g-TuRC subunits plusMOZART1, MOZART2A,and MOZART2B. Entrieshighlighted in orange arebait proteins, yellow indi-cates proteins whose in-teraction with the bait haspreviously been reported,and a white backgroundindicates that the interac-tion was previously un-known. Asterisks indicateproteins identified by asingle peptide. (C) IFM im-ages showing centrosomallocalization of TUBG1,MOZART2B,andMOZART1through the cell cycle [G1phase, G2 phase, prophase(Pro), or prometaphase(PM)]. HeLa cells express-ing the indicated proteinswere fixed and stainedwith antibodies to GFP(green) and with DAPI(red). (D) IFM imagesshowing localization ofTUBG1, MOZART2B,and MOZART1 to centro-somes and the mitoticspindle in metaphase infixed LAP cells stainedwith antibodies to GFPand PLK1. All images inthis figure are maximum-intensity projections ofDeltaVision stacks. Scalebar, 10 mm. (E) IFM im-ages of HeLa cells treatedfor 72 hours with 100 nMsiRNA specific to either TUBG1 or MOZART1. Cells were fixed and stained withDAPI (blue) and TUBA1A antibodies (red). Scale bar, 10 mm. (F) IFM images ofTUBG1-LAP HeLa cells treated for 72 hours with 100 nM siRNA against TUBG1 soas to deplete the endogenous TUBG1 and, simultaneously, transfected either withluciferase siRNA (control siRNA) or MOZART1 siRNA. Cells were fixed and stainedwith DAPI, GFP antibodies (to visualize TUBG1-LAP), and CEP135 (to staincentrioles). Two distinct phenotypes were observed: CEP135 foci in close proximityto each other that colocalize with faint TUBG1-GFP foci (middle row) and CEP135foci dispersed randomly dispersed throughout the cell with no detectable TUBG1-

GFP foci (bottom row). Insets in the third column are magnified fivefold to showone centrosome. Scale bar, 10 mm. (G) Histogram showing quantification of theexperiment described in (E). In addition, cells containing themouse TUBG1-LAP orthe mouse MOZART1-LAP (BAC +) were treated with 100 nM siRNA specific forTUBG1 or MOZART1, respectively, and fixed and stained as in (E). C, control; TG,TUBG1 siRNA; M1, MOZART1 siRNA. (H) Histogram showing quantification of theexperiment described in (F). The number of cells with GFP-positive (TUBG1 +) or-negative (TUBG1 –) centrosomes was counted. The GFP-negative cells are acombination of both MOZART1-depletion phenotypes shown in (F).

TUBG1

TUBGCP3

TUBGCP6

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220TUBGCP6

A B

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11697

76 66

53

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TUBGCP5TUBGCP2/3

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TUBG1

Protein Other Massname (kDa) TUBG1 TUBGCP3 TUBGCP6 MOZART1 MOZART2B

TUBG1 γ-Tubulin 51.2 33.7% 85.6% 10.9% 11.8% 18.0%TUBGCP2 GCP-2 102.5 28.8% 56.9% 23.2% 26.8% 51.7%TUBGCP3 GCP-3 103.6 25.8% 55.4% 20.7% 21.6% 34.1%TUBGCP4 GCP-4 76.1 15.2% 31.1% 9.5% 12.3% 30.5%TUBGCP5 GCP-5 118.3 17.5% 20.8% 15.2% 18.1% 30.9%TUBGCP6 GCP-6 200.5 12.0% 7.0% 18.1% 7.6% 16.1%MOZART1 C13orf37 8.5 32.9% 52.4% 32.9% 34.6% 32.9%MOZART2A FAM128A 16.2 10.1% * - 10.1% * 24.1% 24.1%MOZART2B FAM128B 16.2 - 51.9% - - 22.0%

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associated proteins (TUBGCP2 to -6)], C13orf37and FAM128A/B do not contain the conserved“Spc97_Spc98”GCP domain (25). The TUBGCPnomenclature can therefore not be applied toC13orf37, FAM128A, or FAM128B. Instead, wepropose to call these proteins mitotic-spindle or-ganizing proteins associatedwith a ring of g-tubulin(MOZART1, MOZART2A and MOZART2B,respectively).

MOZART1, an evolutionarily conserved pro-tein essential for g-TuRC function. To testwhether the MOZARTs are important for g-TuRC function, we performed RNAi experimentsin HeLa cells. Transfection of MOZART2A/Bsmall interfering RNA (siRNA) did not result indetectable mitotic phenotypes, but we cannotexclude that this was due to incomplete de-pletion of these proteins. In contrast, depletionof either MOZART1 or TUBG1 led to the accu-mulation of prometaphase cells with monopolarspindles and closely spaced centrosome pairs(Fig. 5, E to G). These phenotypes were fullyreverted through stable integration of the cor-responding LAP-tagged mouse genes on BACs(Fig. 5G), ruling out off-target RNAi effectsand showing that the LAP-tagged proteins usedfor localization and interaction mapping arefunctional.

Monopolar spindle phenotypes have beenobserved after depletion of g-TuRC, but alsoafter inactivation of PLK1 (26) or Aurora A ki-nase (27).We therefore tested whetherMOZART1depletion could interfere with spindle assemblydirectly by preventing g-tubulin recruitmentto centrosomes, or indirectly by decreasingPLK1 or Aurora A activity. In IFM experiments,MOZART1-depleted cells were stained equallywell as control cells with antibodies specific forphospho-epitopes generated by PLK1 or AuroraA (fig S13, E and F), suggesting that MOZART1is not required for the activation of these kinases.However, depletion of MOZART1 did stronglyreduce TUBG1-LAP–staining at centrosomesin 70% of the cells (Fig. 5, F and H). Theseobservations indicate that MOZART1 is requiredfor g-TuRC recruitment to centrosomes. Becauseorthologs of MOZART1 exist in lower eukary-otes, including fission yeast, it is possible that thisfunction has been highly conserved duringevolution.

A human functional-genomics database.The data obtained in this study have enabled us toidentify previously unknown protein complexes(CEP120-CCDC52 and Augmin/HAUS), newsubunits of well-studied protein complexes suchas the APC/C (APC16) and g-TuRC (theMOZARTs),and unknown interactions between known pro-teins and complexes (PICH-RTR). However, themajority of our data has not yet been used forfollow-up experiments. We suspect that such ex-periments will lead to additional important dis-coveries about the functions of human proteincomplexes in mitosis (28). This notion is sup-ported by the observation that most of the protein

interactions detected in our experiments have notbeen previously reported. For example, for 60of the 107 small SFCM clusters none of theinteractions have been reported in seven majorpublic-interaction databases (fig. S7A). Manyof these clusters may therefore represent un-characterized protein complexes. To enable theexploitation of these data by the scientific com-munity, we have generated a human genome-wide database (www.mitocheck.org) thatcontains all data generated by the MitoCheckconsortium (fig. S14). These include infor-mation on tagged BACs, immunofluorescenceimages obtained through GFP localization,silver-stained SDS-PAGE gels of all proteinsamples obtained through TAP, and all proteininteraction lists obtained through in-solutiontrypsinization-tandem MS. In addition, thisdatabase contains movies from the MitoCheckRNAi screen, in which mitosis has been ana-lyzed by means of live imaging of cells inwhich all human proteins have been targetedby siRNAs (16). The database also providesinformation about gene synonyms used in theliterature, orthologs in other species, and pro-tein interactions reported in public databases.This collection of localization, interaction, andphenotypic data will be a useful resource forunderstanding the functions of human proteins.

Conclusion. The widespread application ofRNAi for phenotypic screens has not been ac-companied by the development of approaches torapidly study protein function. This means thatit is difficult to characterize the results of suchscreens. Similar problems apply to the results ofhuman genetic and genomic studies, which oftenidentify many uncharacterized proteins potential-ly associated with disease. The combined use ofBAC tagging, protein localization, and interactionmapping techniques that we describe here formitotic proteins helps to overcome this limitationby allowing systems-scale approaches to study-ing protein function. These systematic nonge-netic approaches represent a valuable counterpartto RNAi screens, in which limited penetranceand off-target effects can result in ambiguity inthe identification of gene function. Rather thanrelying on phenotypic screens, hypotheses canbe generated and tested from analysis of theprotein complexes and localization of unchar-acterized proteins.

References and Notes1. S. Ghaemmaghami et al., Nature 425, 737

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379 (2007).32. We are grateful to the following colleagues for

their excellent assistance: E. Kreidl, M. Mazanek,M. Madalinski, G. Mitulović, M. Novatchkova,C. Stingl, Y. Sun (IMP and Institute of MolecularBiotechnology of the Austrian Academy of Sciences,Vienna); A. Bird, K. Kozak, D. Krastev, Z. Maliga,D. Richter, M. Theis, M. Toyoda (MPI, Dresden);P. Dube (MPI, Göttingen); and N. Kraut (BoehringerIngelheim, Vienna). This work was funded in themost part by the European Commission via the SixthFramework Programme Integrated Project MitoCheck(LSHG-CT-2004-503464). Work in the laboratoriesof J.-M.P. and K.M. received support from BoehringerIngelheim, the Vienna Spots of Excellence Programme,the Austrian Science Fund Special ResearchProgramme “Chromosome Dynamics,” and theGenome Research in Austria Programme. Work in thelaboratories of A.A.H. and F.B. received support fromthe Max Planck Society and from Bundesministeriumfür Bildung und Forschung grants NGFN-2 SMP-RNAi(01GR0402) and NGFN-Plus (01GS0859). Workin the laboratory of L.P. was supported by operatinggrants from the Natural Science and EngineeringResearch Council of Canada (RGPIN-355644-2008),the National Cancer Institute of Canada (019562),and the Human Frontier Science Program(CDA0044/200). L.P. holds a Canada ResearchChair in Centrosome Biogenesis and Function. Y.T.was supported by a Postdoctoral Fellowship forResearch Abroad from the Japan Society for thePromotion of Science.

Supporting Online Materialwww.sciencemag.org/cgi/content/full/science.1181348/DC1Materials and MethodsFigs. S1 to S14Tables S1 to S4ReferencesSupporting Visualization S1

31 August 2009; accepted 22 March 2010Published online 1 April 2010;10.1126/science.1181348Include this information when citing this paper.

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ProteinsSystematic Analysis of Human Protein Complexes Identifies Chromosome Segregation

Mechtler, Anthony A. Hyman and Jan-Michael PetersSsykor, Steffen Lawo, Laurence Pelletier, Holger Stark, Kim Nasmyth, Jan Ellenberg, Richard Durbin, Frank Buchholz, Karl Mihail Sarov, Andrei Pozniakovsky, Mikolaj Michal Slabicki, Siegfried Schloissnig, Ines Steinmacher, Marit Leuschner, AndreaAugsburg, Otto Hudecz, Bettina A. Buschhorn, Jutta Bulkescher, Christian Conrad, David Comartin, Alexander Schleiffer, James R. A. Hutchins, Yusuke Toyoda, Björn Hegemann, Ina Poser, Jean-Karim Hériché, Martina M. Sykora, Martina

originally published online April 1, 2010DOI: 10.1126/science.1181348 (5978), 593-599.328Science 

about 100 protein machines required for mitosis.binding partners by mass spectrometry. Applying the technology to proteins implicated in control of cell division revealedmonitor localization of tagged proteins by microscopy or to isolate interacting proteins and subsequently identify the

(p. 593, published online 1 April) were able toet al.Hutchins harbored in mammalian cells. Depending on the tag used, function of mammalian proteins by expressing a tagged version of proteins from bacterial artificial chromosomes

An international consortium of labs has been testing the feasibility of large-scale screening for insights into theDivision Machinery Tagged

ARTICLE TOOLS http://science.sciencemag.org/content/328/5978/593

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