Differential Proteomics Based on 18O Labeling to Determine the

Differential Proteomics Based on 18O Labeling to Determine the Cyclin Dependent Kinase 9 Interactome Karel Bezstarosti,†,‡ Alireza Ghamari,†,§ Frank G. Grosveld,§ and Jeroen A. A. Demmers*,‡ Proteomics Center and Department of Cell Biology, Erasmus University Medical Center, Dr. Molewaterplein 50, 3015 GE Rotterdam, The Netherlands Received March 9, 2010

Although enzyme catalyzed 18O labeling has been used as a tool in quantitative proteomics, this type of labeling has not yielded the same impact yet as alternative techniques for quantitation like SILAC or labeling with chemical mass tags. The practical difficulties involved in 18O labeling, most importantly the occurrence of incomplete labeling and, as a result, the difficulties in data analysis and interpretation have hampered its implementation in high-throughput comparative proteomics protocols. In this paper, we have optimized the 18O labeling procedure to such an extent that complete labeling can be achieved in a routine manner. We have implemented this approach into a protein-protein interaction analysis pipeline to differentiate between bona fide interaction partners of the low-level expressing cell cycle regulator cyclin-dependent kinase 9 (Cdk9) and nonspecifically binding or background proteins. Previously known as well as novel interaction partners of Cdk9 were found, among which most notably the Mediator complex and several other proteins involved in transcriptional regulation. We show here that a differential proteomics approach based on 18O labeling provides a valuable method for highconfidence determination of protein interaction partners and is easily implemented in protein network analysis workflows. Keywords: cyclin dependent kinase 9 • nanoflow LC-MS/MS • quantitative proteomics • interactome • protein-protein interactions

Introduction It is a widely accepted concept in biology that the great majority of proteins execute their function while being part of larger assemblies.1 As a result, characterization of the binding partners of a protein has become a critical part of analyzing its biological function. Unraveling protein complexes can be done by combining affinity purification of a tagged protein of interest from physiological fluids and subsequent analysis of the associated protein partners by mass spectrometry, a technique often referred to as “functional proteomics”.2 Different tags have been introduced of which polyhistidine (His), glutathione S-transferase (GST), FLAG, tandem affinity purification (TAP) and biotinylation tags are most widely used. For the in vivo biotinylation of an artificial 23-aa peptide tag, the bacterial BirA biotin ligase is coexpressed in the cell line together with the tagged protein of interest.3 The associated proteins are then isolated and resolved by SDS-PAGE before they are proteolytically cleaved and subsequently identified by tandem mass spectrometry (MS/MS). When the sample complexity is high, the combination of reversed-phase liquid chromatography for peptide fractionation and tandem mass * To whom correspondence should be addressed. Dr. Jeroen A.A. Demmers, Proteomics Center, Erasmus University Medical Center, Dr. Molewaterplein 50, 3015 GE Rotterdam, The Netherlands. E-mail: j.demmers@ erasmusmc.nl. Phone: +31 10 7038124. Fax: +31 10 7039468. † These authors contributed equally. ‡ Proteomics Center. § Department of Cell Biology.

4464 Journal of Proteome Research 2010, 9, 4464–4475 Published on Web 07/01/2010

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O labeling • differential proteomics •

spectrometry (LC-MS/MS) is used. Alternatively, protein mixtures are digested in-solution and then fractionated and analyzed by mass spectrometry. One important side effect of the analysis of protein-protein interactions by the isolation of proteins from complex mixtures like a cell lysates or a nuclear extracts is the presence of contaminating or background proteins. In particular for the investigation of weak protein-protein interactions, relatively mild affinity purification conditions should be used. In such cases, the presence of nonspecifically binding and sticky proteins may hamper data analysis to a large extent. Substantial amounts of proteins may be identified for which it is hard to assess whether they are real interactors or contaminating proteins. Usually, contaminating proteins are removed from protein data sets based on biological knowledge and common sense of the researcher. This however heavily undermines the in principle unbiased nature of the affinity-purification procedure. To assess whether a protein is a contaminant or a bona fide interaction partner, proteins found in both control and sample need to be relatively quantified. Incorporation of stable heavy isotopes into proteins or their proteolytic peptides has been used for a decade or so as a means of relative protein quantification by mass spectrometry in comparative proteomics experiments, see for example ref 4. There are basically two ways to achieve incorporation of heavy isotope labels into proteins or peptides. Labeling of proteins in cell culture (SILAC) 10.1021/pr100217d

 2010 American Chemical Society

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O Labeling and MS to Study Protein Interactions

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Figure 1. (A) Principle of trypsin catalyzed 18O labeling. Incorporation of two 18O labels at the C-terminus of a tryptic peptide takes place in a two-step reaction. (B) In a differential labeling experiment, proteins in a control sample are labeled with a heavy stable isotope label, whereas proteins in the experimental sample remain unlabeled. Incorporation of two 18O labels results in a peptide mass difference of 4 Da.

or metabolically in vivo occurs by growing cells or whole organisms in the presence of amino acids or nutrients carrying heavy stable isotopes (like leucine-d35 or 15N-labeled ammonium sulfate,6 respectively). In addition, isotopes can also be incorporated in vitro at a later stage of the sample treatment procedure, either chemically (isobaric tags and ICAT7,8) or enzymatically (18O labeling9). While ICAT labeling takes place at the protein level, labeling with isobaric tags occurs at the peptide level after proteolytic digestion of the proteins. Enzyme catalyzed 18O labeling of proteolytic peptides (Figure 1) has been used as a tool in quantitative proteomics for some time now10 but has not yet yielded the same impact as competitive quantitative techniques. The practical difficulties involved, most importantly the occurrence of incomplete incorporation of two 18O atoms into the proteolytic peptide and, as a consequence, the difficulties in data analysis and interpretation, are the most likely reasons for this. In many studies, mixtures of one 18O and two 18O atoms present in the proteolytic peptides, as a result of incomplete incorporation or by the occurrence of back-exchange from 18O to 16O, result in complex isotopic patterns that are difficult to interpret. Some studies have overcome these problems by developing and/or optimizing techniques in which only one 18O label gets incorporated.11 However, this is not advisible, as the difference in

m/z values between the “light” and “heavy” peptides becomes too small and the quantitative accuracy is likely to drop because of the larger influence of M+2 isotope peak of unlabeled peptide to the monoisotopic peak of 18O labeled peptide. As a consequence, isotopic correction has to be applied, which severely hampers the interpretation of the data. Accurate data analysis should therefore be more straightforward when the m/z differences between the “light” and “heavy” versions of the peptide are at least 4 Da (i.e., two 18O isotopes for the ‘heavy’ variant). To overcome inefficient labeling, algorithms for the correction of 18O labeling efficiencies have been developed,12 while other studies have focused on minimizing backexchange of 18O to 16O. It was found that this can be achieved either by decreasing the pH value for trypsin catalyzed incorporation reactions13-15 or by using immobilized trypsin for the exchange reaction.16-18 Here, we have overcome the obstacles mentioned above by combining several improvements and we can now routinely achieve complete 18O labeling and subsequent quantitative mass spectrometry analysis within several hours. It turns out to be essential for optimal heavy isotope incorporation to perform the actual 18O labeling step in the presence of immobilized trypsin under acidic conditions (pH 4.5) after proteins have been digested and dried completely. Journal of Proteome Research • Vol. 9, No. 9, 2010 4465

research articles We have applied this method to investigate novel interaction partners cyclin dependent kinase 9 (Cdk9) in murine erythroleukemia cells and show that both strong and weak or transient interaction partners can be identified in a reliable manner. Cdk9, together with its cyclin partner T1, T2a, T2b, or K,19-21 forms the positive transcription elongation factor b (P-TEFb), which is a DRB-sensitive kinase. P-TEFb phosphorylates a number of substrates, including the C-terminal domain of the largest subunit (Rpb1) of RNA polymerase II on Ser2 of its tandem heptad repeats,22,23 permitting the transition into productive elongation. P-TEFb can be recruited to target genes in specific as well as general ways. Brd4 is known as a factor which can recruit Cdk9 to the active regions of chromatin in a more general fashion.24,25 P-TEFb can also exist in inactive complexes with Hexim1 or Hexim2.26,27 It has been recently shown that poised polymerases in Drosophila and human occupy a considerable number of genes, which are highly enriched for developmentally regulated genes.28-31 Therefore, control of P-TEFb and subsequent active interaction with RNA Polymerase II at these genes appear to be critical to turn the poised RNA Polymerase II into its active form. The importance of Cdk9 in developmental pathways has been indicated by morpholino knock down assays in the zebra fish, causing severe defects in the development of definitive hematopoiesis.32 Using a unbiased comparative proteomics screen based on 18 O labeling, we have identified a substantial set of previously unknown interaction partners of Cdk9, among which most notably is the complete Mediator complex, revealing novel aspects of Cdk9 functioning.

Experimental Section Biotinylation tagging of proteins in murine erythroleukemia (MEL) cells and pull down of interacting partners by paramagnetic streptavidin beads have been described previously.3 Briefly, a MEL cell line that expresses the E. coli BirA biotin ligase was stably transfected with the murine Cdk9 cDNA under the control of the EF-1R promoter. The cDNA was linked to a sequence at its 3′ end that codes for a C-terminal tag in frame containing a minimal biotinylable 15-amino acid peptide and V5 peptide.33 Stable clones were selected by G418. Expression of the tagged version of Cdk9 was checked by Western blots probed with streptavidin and Cdk9 antibody. Five milligrams of nuclear extract was prepared, followed by streptavidin pull down. Protein Digestion and 18O Labeling. Proteins were digested with trypsin (Roche) while still bound to the beads. The resulting proteolytic peptides were collected by spinning down and subsequent removal of the remaining beads. Finally, the peptides were dried to completeness using a speedvac. Next, 10 µL of a suspension of immobilized trypsin beads (Pierce cat # 20230) were washed three times with a 50 mM ammonium acetate solution (pH 4.5) and diluted in 40 µL of this solution. The enzyme/substrate ratio was estimated to be 1:200. These beads were then added to the peptide pellet and the mixture was again dried to completeness in a speedvac for 2 h. The dried peptides plus trypsin beads were then dissolved/ resuspended in either H216O or H218O (97%, Sigma-Aldrich). The mixtures were incubated o/n at RT while shaking. The immobilized trypsin beads were separated from the peptides in solution by a manually manufactured filtering device consisting of a piece of Whatman GFC filter paper wrapped in a disposable pipet tip. The beads plus filter paper were washed three times with Buffer A solution (see below). Finally, “light” (16O) and 4466

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“heavy” ( O) samples were mixed in a 1:1 ratio and analyzed by mass spectrometry. For the incorporation test assay, 15 pmol of a protein standards mix (Dionex cat # 161088) was taken of which 200 fmol was analyzed by LC-MS. Mass Spectrometry. Nanoflow liquid chromatographytandem mass spectrometry was performed on an LTQ-Orbitrap mass spectrometer (Thermo) operating in positive mode and equipped with a nanospray source coupled to an 1100 series capillary liquid chromatography system (Agilent Technologies). Peptides were trapped on a ReproSil C18 reversed-phase column (column dimensions, 1.5 cm by 100 µm, packed inhouse; Dr Maisch GmbH) at a flow rate of 8 µL/min. Peptide separation was performed on a ReproSil C18 reversed-phase column (column dimensions, 15 cm by 50 µm, packed inhouse; Dr Maisch GmbH) using a linear gradient from 0 to 80% B buffer (A buffer is 0.1% formic acid, and B buffer is 80% (v/ v) acetonitrile-0.1% formic acid) for 120 min and at a constant flow rate of 200 nL/min using a splitter. The column eluent was directly sprayed into the electrospray ionization source of the mass spectrometer. Mass spectra were acquired in continuum mode; fragmentation of the peptides was performed in data-dependent mode. Peak lists were created from raw data files using Mascot Distiller software (version 2.0; MatrixScience). The Mascot search algorithm (version 2.0; MatrixScience) was used for searching against the NCBInr protein database (version 20080704; taxonomy, Mus musculus; total number of entries, 111 965). The peptide tolerance was set to 10 ppm and the fragment ion tolerance was set to 0.8 Da. A maximum number of two missed cleavages by trypsin were allowed. Carbamidomethylated cysteine was set as fixed modification, and oxidized methionine, C-terminal 18O(1) and C-terminal 18O(2) labels, phospho (ST) and phospho (Y) were set as variable modifications. The Mascot score cutoff value for a positive protein hit was set to 60. Individual peptide tandem mass spectra with Mascot scores below 40 were checked manually and either interpreted as being valid identifications or discarded. Data Analysis. Data analysis for the quantitative mass spectrometry experiments was performed using a version of the open source software package MSQuant (available from msquant.sourceforge.org) that was adapted for 18O labeling analysis. The quantification mode was set to 18O, while the type for quantification was set to “all MS spectra”. Only bold red peptides were included in the preselection of peptides. The left LC detection window was set to 60 s, the right window to 90 s. Preselected peptides were only validated when their individual Mascot score was >35. After running the automated quantitation procedure all quantified peptides were manually checked and requantified when needed.

Results To set up an unbiased differential proteomics screening method for the analysis of interaction partner of a protein of interest, first the incorporation efficiency of 18O into every proteolytic peptide that originates from interacting proteins had to be optimized. We developed a two-step approach in which the proteins were first digested with soluble trypsin. Subsequently, proteolytic peptides were incubated with H218O at pH 4.5 in the presence of immobilized trypsin. A mix of protein standards was digested with trypsin and the two C-terminal 16 O atoms of the resulting proteolytic peptides were exchanged for 18O. Complete labeling with two 18O could be achieved, as illustrated in Figure 2. Clearly, no singly 18O labeled variants could be observed in any of the peptide mass spectra, so no

18


Figure 2. Doubly charged tryptic peptide FLEQQNQVLQTK (A) in the absence of 18O label and (B) after incorporation of the label. The two-step labeling reaction in the presence of immobilized trypsin as described here ultimately results in the complete incorporation of two 18O labels, with no intermediary products present. The peptide isotope peaks in (B) at m/z 739.39 and 739.89 are due to impurities of commercial H218O, containing only 97% 18 O.

partial labeling occurred, nor did any back-exchange from 18O to 16O take place during sample treatment or analysis. Thus, complete incorporation of two 18O labels into each of the tryptic peptides in a mixture can be achieved routinely. “Light” (no label) and “heavy” (two 18O isotope labels) samples were then mixed in a 1:1 molar ratio and analyzed by nanoflow LC-MS/ MS. Figure 3 shows the resulting chromatogram and a typical mass spectrum as an example. The inset shows that a typical proteolytic peptidesFESNFNTQATNR peptide of lysozymeswas observed both as a light and as a heavy variant, and that these two variants are easily distinguishable from one another without substantial interference of the natural 13C isotopes of the light variant. The nanoflow LC-MS/MS profiles also show that the ionization and chromatographic properties of unlabeled versus 18O labeled peptides do not show significant differences. The open source software package MSQuant34,35 was used to analyze the mixed standard protein mix data set in a quantitative manner. The algorithm basically calculates the light-to-heavy ratios for each proteolytic peptide in the LC-MS/ MS run. Subsequently, the average light-to-heavy ratio for the protein with which the peptide has been associated based on analysis of MS/MS data by the Mascot search algorithm is calculated. The average light-to-heavy ratios for each of the proteins present in the set of standard proteins are given in Table 1. The results show that complete labeling of proteolytic peptides with two 18O atoms in a complex mixture is achievable and that both identification and relative quantitation of proteins can be performed in an automated manner. Although one-peptide hits are usually excluded from further analysis in the automated procedure, in the case of lysozyme, the peptide

research articles MS/MS spectrum was manually checked and found to be a valid match. Moreover, the heavy-to-light ratio for this peptide was found to be close to 1, in accordance with the ratios for the other proteins in the sample (see Table 1). Since the H:L ratios of different peptide peak pairs for the same protein, which differ several orders of magnitude in intensity, are still consistent, it is suggested that the method might also be suitable to assess specific interactions for lower abundant proteins in a mixture, for example, those found to be only weakly interacting with a protein of interest. Next, this differential labeling approach was applied to a functional proteomics assay in which we screen for interaction partners of Cyclin dependent kinase 9 (Cdk9). The rationale behind the use of differential labeling is to be able to differentiate between bona fide interacting proteins and nonspecifically binding proteins with high confidence. Generally, in a nonquantitative mass spectrometry experiment, proteins in a negative control sample and those identified in the sample containing the protein of interest and interacting partners are directly compared to assess which of the proteins interact in a specific manner. However, the mere presence or absence of a certain protein in protein data sets as a measure for either overlap or specificity is generally not sufficient, as this gives no information about the relative abundances of the present proteins. A more accurate and correct approach would therefore involve a comparative labeling strategy in which differences between sample and control can be assessed in a quantitative manner. To determine the identity of proteins associated with Cdk9, protein complexes were isolated from nuclear extracts of MEL cells transfected with a biotin tagged version of Cdk9 using streptavidin beads under mild conditions. The proteins that copurified with Cdk9 were washed and digested with trypsin while still bound to the beads and subsequently identified by tandem mass spectrometry. A control sample was taken following the same procedure from an equal number of cells, but using nontransfected MEL cells. Proteolytic peptides from the control sample were then labeled using H218O in the twostep approach mentioned earlier, while proteolytic peptides from the Cdk9 pulldown sample underwent the same procedure with unlabeled H2O. The peptide mixtures were dissolved in equal volumes of buffer and mixed in a 1:1 volume ratio. Peptides and proteins were identified by a 120-min nanoflow LC-MS/MS run and subsequent data analysis by the Mascot search algorithm. In addition to common contaminants like keratins and structural and housekeeping proteins, typical nonspecifically binding proteins that are usually identified in the analysis of nuclear extracts from BirA-expressing MEL cells include naturally biotinylated protein like acetyl CoA carboxylase and pyruvate carboxylase. It is clear from Figure 4A that acetyl CoA carboxylase is present in both sample and control, since both the “light” and “heavy” variants of a tryptic peptide of the protein are identified in the mass spectrum. In contrast, a tryptic peptide from cyclin T1 was found to be present only in its “light” form, indicating that this peptide is absent from the control sample and that it is therefore specific for the coimmunopurified Cdk9 sample (Figure 4B). Heavy-to-light ratios were calculated for all proteins identified from the mixed sample (Table 2). In line with the expectations are the relatively high values for typical background proteins, such as ribosomal, housekeeping, and structural proteins. In contrast, among the proteins that were Journal of Proteome Research • Vol. 9, No. 9, 2010 4467

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Figure 3. Nanoflow LC-MS/MS chromatogram and spectrum of a tryptic digest of a mixture of ten different protein standards. Half of the protein mixture was digested in the presence of H216O, the other half in H218O and the two parts were mixed in a 1:1 ratio. Tryptic peptides observed were present in a “light” and “heavy” form, as shown in the lower inset for one representative peptide (FESNFNTQATNR of lysozyme; m/z of the light form: 714.83, m/z of the heavy form 716.83). The extracted ion chromatograms and the respective peak areas for both the “light” and “heavy” forms of this peptide are shown in the upper inset. Table 1. Mascot and MSQuant Results of the LC-MS/MS Analysis As Described in Figure 3a protein

Beta-galactosidase Transferrin Lysozyme Alcohol dehydrogenase Albumin Cytochrome c Trypsin Glycerol kinase Serpin peptidase inhibitor

molecular mass

number of peptides

Mascot score

heavy:light ratio

131098 79856 14761 31954

7 15 9 5

629 1166 369 331

0.94 ( 0.10 1.0 ( 0.10 1.0 ( 0.15 0.84 ( 0.09

68083 11794 24662 56349 46289

15 2 2 2 2

745 184 176 147 111

0.86 ( 0.01 0.80 ( 0.20 1.1 ( 0.1 0.98 ( 0.00 0.80 ( 0.00

a The heavy-to-light ratio for a protein is an average of the individual heavy-to-light ratios over all peptides for each protein that was identified by Mascot.

quantitated with heavy-to-light scores close to 0, indicating specificity for the Cdk9 coimmunopurification sample, we identified in a single experiment the far majority of interacting proteins that have been described in different studies in the literature, as well as several novel interaction partners of diverse functionalities, suggesting putative additional roles for Cdk9 in various nuclear events such as transcription and cell cycle control (see Discussion section). To validate the differential labeling approach for comparative purposes, Western blot analysis was performed for several of 4468


the specific Cdk9 interactors identified in our screen with lower and higher Mascot score. This analysis confirms the obtained results: antibodies against AF4, Cdk7, Cyclin T1, Paf1, Med1 and Hexim1 were used to show the presence of these proteins in the Cdk9 coimmunoprecipitation sample and the absence in the control sample (Figure 5). As the interaction with a kinase suggests the possibility for interactors to be phosphorylated, we are currently investigating the modification status of these proteins. In Figure 6, all Cdk9 associated proteins were first grouped based on the gene ontology (GO) term “biological process” they are associated with in the GO database at www.geneontology.org and then plotted against the median of their heavy-tolight ratios, while the diameter of the circle indicates the number of identified proteins per group. From this representation, it is obvious that proteins associated with transcription or regulation of transcription in general show significantly lower heavy-to-light ratios.

Discussion Here, we show that complete 18O labeling of peptides in complex mixtures can be routinely achieved. Proteolytic peptides that are only partially labeled, as a result from either suboptimal labeling efficiency or back-exchange from 18O to 16 O during sample preparation and which are frequently observed in reports on 18O labeling in the literature, are absent from all mass spectra in the LC-MS/MS analysis. This greatly

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Figure 4. MS spectra of two tryptic peptides from a 1:1 mixture of a digest of a Cdk9 coimunoprecipitation experiment (H216O) and a control sample (in H218O). (A) Doubly charged peptide LGTPELSPTER of the well-known contaminant acetyl-CoA carboxylase3 shows both the “light” and “heavy” forms and is therefore marked as a nonspecific protein. (B) Triply charged peptide GPPEETGAAVFDHPAK of cyclin T1 is only present in the “light” form and is therefore specific for the Cdk9 sample.

simplifies the analysis of peak intensity ratios, since now only two components (i.e., ‘light’ and “heavy”) need to be considered and no correction algorithms have to be applied to convert peak intensities of intermediately labeled peptide species. Major advantages of the presented method over other heavy isotope labeling strategies that are used in proteomics research nowadays are (1) the ease of implementation and use, (2) the versatility, as it can be applied to sample material originating from noncell cultures, and (3) the cost effectiveness. In addition, there is no chemical labeling step involved and there is no need for adaptation of cell culturing conditions like those needed for SILAC approaches. This is a substantial advantage, especially when cell types are used that are more difficult to grow, like the one used in this study. The 18O labeling method provides a valuable alternative for the commercial labels that are used in a postdigestion way for quantitative purposes. Because of the high sensitivity of this approachsextremely mild affinity purification conditions combined with reliable picking of proteins that are unique to a samplesit is likely that besides direct or physical interactors of the bait protein, also indirect interactors via other proteins are identified. Although the analysis described here gives a lot of detailed information on protein-protein interaction networks and even interactions between complete complexes, indirect interactions cannot easily be distinguished from direct interactions. We have shown here that a comparative proteomics screen based on 18O labeling can be used to investigate protein-protein interactions in great detail. We have identified in a single analysis the far majority of the Cdk9 interactors that have been described previously in many different studies in the literature. In addition, several novel Cdk9 associated proteins were identified, of which the functional relevance is currently under investigation. Besides the Mediator subunits that have been described in the literature,24 16 additional Mediator subunits were identified to be interacting with Cdk9. The Mediator complex functions as a bridge between the activators and RNA Polymerase II and is required for the recruitment, assembly and regeneration of transcription complexes on core promoters during initiation and reinitiation of transcription.36-41 Since Cdk9 plays a critical role in activating poised RNA Polymerase II at developmentally regulated genes,31 we speculate that modulation of Cdk9 activity by the Mediator complex may be

involved in transcriptional control of a subset of developmental genes at the elongation step of transcription. Cyclin T1 and T2 are essential for the activity of Cdk919,20 as it is inactive in the absence of its cyclin partner. The association of P-TEFb with the bromodomain proteins Brd4 and Brdt has been described before and was found to be necessary to form the transcriptionally active P-TEFb, then recruits P-TEFb to a promoter, and enables P-TEFb to contact the Mediator complex.24,25 About half of the cellular P-TEFb exists as a complex with Brd4. Both Hexim1 and Hexim2 can inhibit P-TEFb when bound to the complex and thus serve as potent regulators of P-TEFb function.26,27 In addition, all of the factors that make up the human PAF complex were identified as specific interactors of Cdk9 in the MEL cell extract described here, suggesting the interaction of this complex with Cdk9. The human PAF (hPAF) complex shares four subunits with yPAF (Ctr9, Paf1, Leo1, and Cdc73), but in addition contains a novel higher eukaryoticspecific subunit, Ski8/Wdr61.42 The yeast PAF (yPAF) complex has been shown to interact with RNA polymerase II, regulates multiple steps in the expression of genes involved in the cell cycle and coordinates the setting of histone marks associated with active transcription. Both hPaf1 and the hPAF complex as key regulators of cell-cycle progression and mutation or loss of stoichiometry of at least one of the members may potentially lead to cancer development.43 The hPAF1 complex has been recently shown to be involved in transcription elongation.44 The interaction between the Paf complex and Cdk9 that we observe could be either directly or indirectly, e.g. via RNA polymerase II. BCDIN3 (Bin3) is the 7SK snRNA methylphosphate capping enzyme (MePCE) present in the snRNP complex containing both RNA processing and transcription factors, including the elongation factor P-TEFb.45 BCDIN3, as well as the other proteins that the 7SK snRNP complex can be associated with, for example, Cyclin T1, Hexim1, Hexim2, were also identified as specific Cdk9 interactors in this screen. Recently, it was demonstrated that AF4 functions as a positive regulator of P-TEFb and as a mediator of histone H3-K79 methylation by recruiting Dot1 to elongating RNA Polymerase II.46 AF4 was found here as a specific interactor of Cdk9, together with related proteins of the AF4/FMR2 family which are involved in human diseases such as acute lymphoblastic leukemia and mental retardation, that is, AFF3 and AFF4. The Journal of Proteome Research • Vol. 9, No. 9, 2010 4469

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Table 2. Heavy-to-Light Ratios for All Proteins Identified in the Mixture of the Cdk9 Coimmunoprecipitation Digest and the Control Sample #

UniProt Entry

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

MED7 MED31 MED21 FGF14 MED30 MED10 MED20 HEXI2 MED6 VIME ZN592 HEXI1 MED16 MAT1 MED23 RPB1 TF2H2 ELL2 NOP58 HNRPM LARP7 MED15 ILF3 MED26 AFF3 LEO1 MED4 SFRS3 MEPCE CDK9 PSD2 PAF1 MED1 PR40A

35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64

DDX55 CDC37 MED24 ATAD5 Q7TQK0 WDR61 PRP8 MED17 CTR9 CCNT1 RL23A TF2H1 CDC73 Q5RJI0 NUCL AFF4 ZCH18 AFF1 Q3TKZ9 MED14 RUNX1 TCOF TF2H4 REXO1 HS90A CV028 TAF7 BRD4 BRDT RL10

4470

UniProt Info

Mediator of RNA polymerase II transcription subunit 7 Mediator of RNA polymerase II transcription subunit 31 Mediator of RNA polymerase II transcription subunit 21 Fibroblast growth factor 14 Mediator of RNA polymerase II transcription subunit 30 Mediator of RNA polymerase II transcription subunit 10 Mediator of RNA polymerase II transcription subunit 20 Protein HEXIM2 Mediator of RNA polymerase II transcription subunit 6 Vimentin Zinc finger protein 592 Protein HEXIM1 Mediator of RNA polymerase II transcription subunit 16 CDK-activating kinase assembly factor MAT1 Mediator of RNA polymerase II transcription subunit 23 DNA-directed RNA polymerase II subunit RPB1 General transcription factor IIH subunit 2 RNA polymerase II elongation factor ELL2 Nucleolar protein 58 Heterogeneous nuclear ribonucleoprotein M La-related protein 7 Mediator of RNA polymerase II transcription subunit 15 Interleukin enhancer-binding factor 3 Mediator of RNA polymerase II transcription subunit 26 AF4/FMR2 family member 3 RNA polymerase-associated protein LEO1 Mediator of RNA polymerase II transcription subunit 4 Pre-mRNA-splicing factor SRP20 7SK snRNA methylphosphate capping enzyme (Bcdin3/Bin3) Cell division protein kinase 9 PH and SEC7 domain-containing protein 2 RNA polymerase II-associated factor 1 homologue Mediator of RNA polymerase II transcription subunit 1 Pre-mRNA-processing factor 40 homologue A, Formin-binding protein 3 ATP-dependent RNA helicase DDX55 Hsp90 cochaperone Cdc37 Mediator of RNA polymerase II transcription subunit 24 ATPase family AAA domain-containing protein 5 Cyclin T2 WD repeat-containing protein 61 Pre-mRNA-processing-splicing factor 8 Mediator of RNA polymerase II transcription subunit 17 RNA polymerase-associated protein CTR9 homologue Cyclin-T1 60S ribosomal protein L23a General transcription factor IIH subunit 1 Cell division cycle protein 73 homologue RNA binding motif protein 39 Nucleolin AF4/FMR2 family member 4 Zinc finger CCCH domain-containing protein 18 AF4/FMR2 family member 1 (AF4/MIIt2) Nolc1 Mediator of RNA polymerase II transcription subunit 14 Runt-related transcription factor 1 Treacle protein General transcription factor IIH subunit 4 RNA exonuclease 1 homologue Heat shock protein HSP 90-alpha UPF0027 protein C22orf28 homologue;] Transcription initiation factor TFIID subunit 7 Bromodomain-containing protein 4 Bromodomain testis-specific protein 60S ribosomal protein L10


Mascot score

% coverage

heavy:light ratio

SD

# unique peptides

65 37 110 45 129 167 68 103 101 189 60 225 189 178 324 195 74 135 73 206 770 192 46 307 271 107 281 63 354 441 45 529 229 574

8.6 5.3 9.7 10.5 11.8 16.3 5.2 8.2 9.7 8.4 1.5 22.8 3.9 10.7 5.4 2.4 6.3 15.3 2.7 6.3 22.1 4.5 3.7 10.2 4.9 3 18.5 11.3 15.9 19.9 2.3 17 3.3 10.7

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.00 0.00 0.00 0.01 0.01 0.01 0.02 0.01 0.02 0.03 0.01 0.01 0.00 0.02 0.01 0.01

1 1 1 2 2 2 1 3 2 4 1 3 3 3 7 4 2 2 1 4 11 3 1 5 5 2 4 1 7 8 2 7 4 8

51 229 233 42 380 67 82 291 359 818 115 177 471 290 102 1047 46 308 256 341 73 44 165 57 530 48 82 302 162 108

1.5 11.3 4.4 0.4 10.4 3.3 2.1 10.2 4.6 23.8 14.1 6 14.1 11.9 4.3 20.7 1.8 8.2 10.7 6.1 3.1 0.8 5.4 3.9 12.8 2.2 3.5 7.1 4.1 6.1

0.02 0.02 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.04 0.04 0.05 0.05 0.05 0.05 0.06 0.06 0.06 0.06 0.06 0.07 0.08 0.08 0.08 0.08 0.08 0.09

0.02 0.01 0.02 0.01 0.03 0.01 0.01 0.02 0.00 0.03 0.02 0.01 0.00 0.02 0.04 0.06 0.06 0.00 0.00 0.06 0.04 0.00 -

1 3 3 1 5 1 3 5 5 12 2 3 7 4 2 17 1 8 5 7 1 1 2 1 8 1 1 6 3 1

18

research articles


Table 2. Continued #

UniProt Entry

UniProt Info

Mascot score

% coverage

heavy:light ratio

SD

# unique peptides

65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130

RBM25 SF3B5 Q71LX8 EWS CDK7 MED11 SRRM1 ILF2 RFC4 NOP56 LYAR FNBP4 RS26 FIP1 RS6 Q921K2 ERH GAR1 RL35A MBB1A TR150 ACTB RLA2 RS25 H2B1P BCLF1 Q6GTN8 RL6 RL17 GPTC4 PEBB PRP19 ZFR PRPF3 WDR82 SRRM2 MED22 ALBU DDX17 Q0VBG3 Q3TEZ1 TBL1R RL18 SF3B1 FBRL RL7A Q7TSF6 NOM1 RL24 SP16H RNPS1 PP1RA RUVB1 Q6P4T2 SR140 HSP7C RL11 RL14 DIDO1 O89072 Q80Y35 A2APB8 RBM39 RL27 U5S1 RS8

RNA-binding protein 25 Splicing factor 3B subunit 5 Heat shock protein 90 RNA-binding protein EWS Cell division protein kinase 7 Mediator of RNA polymerase II transcription subunit 11 Serine/arginine repetitive matrix protein 1 Interleukin enhancer-binding factor 2 Replication factor C subunit 4 Nucleolar protein 56 Cell growth-regulating nucleolar protein Formin-binding protein 4 40S ribosomal protein S26 Pre-mRNA 3′-end-processing factor FIP1 40S ribosomal protein S6 Poly (ADP-ribose) polymerase family, member 1 Enhancer of rudimentary homologue H/ACA ribonucleoprotein complex subunit 1 60S ribosomal protein L35a Myb-binding protein 1A Thyroid hormone receptor-associated protein 3 Actin, cytoplasmic 1 60S acidic ribosomal protein P2 40S ribosomal protein S25 Histone H2B type 1-P Bcl-2-associated transcription factor 1 Nuclear factor, erythroid derived 2,-like 1 60S ribosomal protein L6 60S ribosomal protein L17 G patch domain-containing protein 4 Core-binding factor subunit beta Pre-mRNA-processing factor 19 Zinc finger RNA-binding protein U4/U6 small nuclear ribonucleoprotein Prp3 WD repeat-containing protein 82 Serine/arginine repetitive matrix protein 2 Mediator of RNA polymerase II transcription subunit 22 Serum albumin Probable ATP-dependent RNA helicase DDX17 Putative uncharacterized protein Stratifin F-box-like/WD repeat-containing protein TBL1XR1 60S ribosomal protein L18 Splicing factor 3B subunit 1 rRNA 2′-O-methyltransferase fibrillarin 60S ribosomal protein L7a : SubName: Full)Mki67 protein;] Nucleolar MIF4G domain-containing protein 1 60S ribosomal protein L24 FACT complex subunit SPT16 RNA-binding protein with serine-rich domain 1 Serine/threonine-protein phosphatase 1 regulatory subunit 10 RuvB-like 1 Activating signal cointegrator 1 complex subunit 3-like 1 U2-associated protein SR140 Heat shock cognate 71 kDa protein 60S ribosomal protein L11 60S ribosomal protein L14 Death-inducer obliterator 1 Ribosomal protein S2 Nuclear mitotic apparatus protein 1 TPX2, microtubule-associated protein homologue RNA-binding protein 39 60S ribosomal protein L27 116 kDa U5 small nuclear ribonucleoprotein component 40S ribosomal protein S8

480 91 641 132 162 63 112 61 137 338 283 103 116 43 41 195 102 72 42 954 189 270 91 127 57 121 48 93 57 81 42 108 86 104 60 201 82 93 766 44 38 71 88 178 93 205 1493 146 51 254 79 329 98 112 85 66 41 84 85 43 178 82 290 156 110 195

14.8 17.4 16.9 3.5 9 16.2 3.6 6.2 5.5 14.8 16.8 1.9 26.1 3.5 4.8 4.5 25.2 3.9 8.2 10.8 5.3 20.9 11.3 14.4 13.4 4.7 1.5 6.3 5.4 7.1 30.8 4.2 1.5 3.2 2.3 1.7 7.9 3.1 22.5 8 4.4 4.5 11.7 4.2 9.8 12 10.3 1.9 11.9 5.3 4.1 8.2 4.8 0.9 1.2 2.5 5.1 5.3 1.4 5 2.5 3.7 11.9 27.9 1.8 14.9

0.09 0.09 0.09 0.10 0.12 0.14 0.14 0.14 0.15 0.15 0.16 0.17 0.17 0.19 0.19 0.20 0.20 0.21 0.21 0.22 0.23 0.23 0.23 0.24 0.24 0.24 0.25 0.25 0.25 0.25 0.27 0.27 0.27 0.27 0.29 0.30 0.30 0.30 0.31 0.32 0.33 0.33 0.34 0.34 0.35 0.35 0.35 0.37 0.37 0.38 0.39 0.39 0.39 0.40 0.40 0.40 0.41 0.41 0.42 0.45 0.45 0.45 0.45 0.47 0.47 0.47

0.03 0.07 0.04 0.00 0.00 0.15 0.10 0.04 0.00 0.14 0.09 0.09 0.00 0.11 0.04 0.03 0.05 0.00 0.00 0.03 0.00 0.14 0.00 0.13 0.02 0.00 0.04 0.07 0.08 0.22 0.06 0.00 0.02 0.00 0.24 0.32 0.35 0.00 0.07

8 1 10 2 3 1 2 1 2 5 5 2 2 1 1 4 2 1 1 13 4 6 1 2 2 3 1 2 1 1 1 2 1 2 1 3 1 1 13 1 1 1 2 4 3 3 22 1 1 4 1 6 2 2 1 1 1 1 2 1 4 2 4 3 2 3

Journal of Proteome Research • Vol. 9, No. 9, 2010 4471

research articles

Bezstarosti et al.

Table 2. Continued #

UniProt Entry

UniProt Info

131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197

RBP2 SFRS7 Q8BTS0 K22E TOP1 HSP72 RBM10 Q61769 RL4 IF4A3 K1C10 RL36 CYTA K1C17 B2RUN6 RL13 TBA1B Q8VHM5 K1C42 RS13 ACTS Q3TVJ3 NPM RS16 HNRH2 RL22 TBB5 RL7 DDX46 PLAK H4 K2C75 NOP2 CHERP K1C28 RBM8A FUS MPPH1 Q6NZQ2 GATA1 K1C16 KHDR1 Q8BVY0 Q9CQ16 RLA0 URP2 ACACA HNRPF H2AV DKC1 K1C14 SSRP1 TOP2B Q3UVQ1 THOC4 PYC K2C5 Q5SZA3 H11 K2C73 K2C79 Q0VDM9 PTBP2 CERU K2C6A K2C1 K22O

E3 SUMO-protein ligase RanBP2 Splicing factor, arginine/serine-rich 7 DEAD (Asp-Glu-Ala-Asp) box polypeptide 5 Keratin, type II cytoskeletal 2 epidermal DNA topoisomerase 1 Heat shock-related 70 kDa protein 2 RNA-binding protein 10 Ki-67 protein 60S ribosomal protein L4 Eukaryotic initiation factor 4A-III Keratin, type I cytoskeletal 10 60S ribosomal protein L36 Cystatin-A Keratin, type I cytoskeletal 17 PRP4 pre-mRNA processing factor 4 homologue B 60S ribosomal protein L13 Tubulin alpha-1B chain Heterogeneous nuclear ribonucleoprotein R Keratin, type I cytoskeletal 42 40S ribosomal protein S13 Actin, alpha skeletal muscle DEAD (Asp-Glu-Ala-Asp) box polypeptide 21 Nucleophosmin 40S ribosomal protein S16 Heterogeneous nuclear ribonucleoprotein H2 60S ribosomal protein L22 Tubulin beta-5 chain 60S ribosomal protein L7 Probable ATP-dependent RNA helicase DDX46 Junction plakoglobin Histone H4 Keratin, type II cytoskeletal 75 Putative rRNA methyltransferase NOP2 Calcium homeostasis endoplasmic reticulum protein Keratin, type I cytoskeletal 28 RNA-binding protein 8A RNA-binding protein FUS M-phase phosphoprotein DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 31 Erythroid transcription factor GATA1 Keratin, type I cytoskeletal 16 p21 Ras GTPase-activating protein-associated p62 Putative uncharacterized protein Ribosomal protein L27a 60S acidic ribosomal protein P0 Kindlin-3 Acetyl-CoA carboxylase 1 Heterogeneous nuclear ribonucleoprotein F Histone H2A.V H/ACA ribonucleoprotein complex subunit 4 Keratin, type I cytoskeletal 14 FACT complex subunit SSRP1 DNA topoisomerase 2-beta Putative uncharacterized protein THO complex subunit 4 Pyruvate carboxylase Keratin, type II cytoskeletal 5 Histone 1, H1c Histone H1.1 Keratin, type II cytoskeletal 73 Keratin, type II cytoskeletal 79 Krt78 protein Polypyrimidine tract-binding protein 2 Ceruloplasmin Keratin, type II cytoskeletal 6A Keratin, type II cytoskeletal 1 Keratin-76

core binding factor-R Runx1 is a transcription factor thought to be involved in the development of normal hematopoiesis and it has also been associated with leukemia. Interactions between Runx1 and P-TEFb appose the silencer and enhancer in CD4-negative thymoma cells. In the absence of Runx1 on the silencer, P-TEFb interacts with the transcription complex.47 Also nucleolin, a protein with potential functions in transcrip4472


Mascot score

% coverage

79 63 649 60 395 67 129 2142 80 168 419 47 37 157 37 122 167 90 481

0.7 6.2 20.5 3.3 11.6 1.6 3.9 14 2.1 8.5 10 10.5 6.4 41.9 1.8 14.6 5.5 5.7 16.6

232 539 53 59 99 48 209 98 64 89 227 208 87 46 419 129 140 173 68 86 367 59 85 73 45 227 1834 134 114 40 560 108 227 168 43 353 564 72 116 266 310 82 79 108 355 213 118

18.5 11.4 6.5 6.8 5.1 10.2 8.8 7.8 1 1.9 29.1 8.1 3.4 1.5 5.7 16.2 4.4 2.5 1.4 6.5 12.2 3.2 3.9 7.4 2.8 6.6 14.8 6 14.7 4.7 17.6 3.4 3.5 4.9 3.9 7.6 14.5 92.3 9.4 5.5 7.3 1.5 2.8 2 10.1 4.7 2.7

heavy:light ratio

SD

0.47 0.47 0.47 0.48 0.48 0.49 0.50 0.50 0.50 0.50 0.50 0.51 0.51 0.51 0.51 0.54 0.54 0.56 0.56 0.58 0.58 0.59 0.60 0.60 0.61 0.65 0.66 0.67 0.67 0.69 0.71 0.72 0.73 0.73 0.74 0.75 0.77 0.78 0.78 0.82 0.85 0.86 0.86 0.94 0.97 0.98 1.00 1.02 1.05 1.05 1.07 1.13 1.16 1.18 1.27 1.27 1.37 1.37 1.38 1.45 1.47 1.49 1.51 1.52 1.55 1.93 2.17

0.19 0.57 0.10 0.21 0.01 0.07 0.20 0.22 0.00 0.00 0.20 0.00 0.42 0.35 0.00 0.14 0.00 0.54 0.16 0.00 0.28 0.00 0.00 0.00 0.17 0.00 0.08 0.40 0.00 0.10 0.52 0.84 0.12 0.00 0.86 0.33 0.25 0.53 0.40 0.00 0.60 0.41 0.20 0.02

# unique peptides

2 1 12 1 8 1 3 32 1 3 6 1 1 3 1 3 2 3 8 5 8 1 1 2 1 3 2 1 1 3 3 2 1 6 2 2 3 1 2 5 1 1 1 1 4 30 2 2 1 9 3 5 2 1 6 9 1 2 4 5 1 2 2 7 3 2

tion activation, has been described to interact with P-TEFb.48 The general transcription factor IIH subunits 1, 2, and 4 (TF2H1, TF2H2 and TF2H4) were also found. Other TFIIH members identified are Cdk7 and me´nage-a`-trois 1 (MAT1 or CDKactivating kinase assembly factor p36). Additional members like Cyclin H, TF2H3, and TF2H5 were not identified, possibly because their abundance was below the detection limit. An

18


Figure 5. Western blot analysis confirms the results for six of the interacting proteins that were found to be associates with Cdk9: Af4, Cdk7, Cyclin T1, Paf1, Med1, and Hexim1.

research articles pre-mRNA splicing. Also, the interaction of Cdk9 with Cdc37, a cochaperone that binds to numerous kinases and promotes their interaction with the Hsp90 complex, resulting in stabilization and promotion of their activity, has not been described before is. Nolc1 (Q3TKZ9) is a known interactor of RNA polymerase I and II and may therefore be an indirect partner of Cdk9, though the high Mascot identification score in our screen might suggest that the binding could be direct. Also, the zinc finger protein 592 (Zfp592), which belongs to the Krueppel C2H2-type zinc-finger protein family, was found to be associated with Cdk9, suggesting that it may be involved in transcriptional regulation. The functional relevance of the proteins with unknown functions that were found to be specifically associated with Cdk9 is the subject of current investigations. It should be noted that even in case of equal loading of sample and control, many of the heavy-to-light ratios for nonspecific interactors are less than 1.0, which you would expect when background proteins are present in both sample and control. Thus, there seems to be a higher abundance rate for background proteins in the sample than for the same proteins in the negative control. An explanation for this could be that, in addition to binding to the “empty” beads, nonspecific proteins may as well stick to the proteinaceous surface that is presented by both the bait protein and its interactors. As a consequence, the total surface area that background proteins can bind to in a nonspecific manner is much higher in the bait sample than in the control, which could explain the higher abundances of nonspecifically binding proteins as compared to the control situation. Another remarkable feature is the gradual increase, as opposed to a stepwise increase, of heavy-to-light ratios from 0 to 1 for the identified proteins, which might reflect different degrees in binding strengths or stabilities for interacting proteins. It also suggests that it is difficult to distinguish between core complex partners and more loosely interacting “second shell” proteins. Alternatively, indirect interactions, that is, proteins interacting to binding partners of Cdk9 but not to Cdk9 itself, could also account for this feature. Additional experiments, such as affinity purifications under more stringent conditions, should be performed to differentiate between strong and weak protein-protein interactions.

Figure 6. All identified proteins were grouped on basis of the GO terms they are associated with and then plotted against the median of their heavy-to-light ratios. The diameter of the circle indicates the number of identified proteins per group. It is obvious that proteins associated with transcription or regulation of transcription in general show significantly lower heavy-to-light ratios. The H:L ratio thresholds used to distinguish between primary interactors (0.3) are indicated in red.

indirect interaction of Cdk9 with Cdk7 has been described before,49 playing a role in the release of the Notch receptor intracellular domain during Notch signaling. Taf7, known to interact with both TFIIH and P-TEFb,50 was identified as well. Several other novel Cdk9 interactors that were identified in our screen have not been described before, among others Formin binding protein 3 (Pr40A) and several other factors involved in

In conclusion, this differential mass spectrometric method allows for an unbiased, sensitive, and high-throughput screening for protein interaction partners and thus enables the construction of reliable protein-protein interaction networks. It is an extremely cost-effective method and can be used for any protein sample type. We have shown here that such a screen for Cdk9 binding partners results in the identification of most of the previously known and several novel interacting proteins.

Acknowledgment. We are grateful to Dr. Joost Gouw for making the MSQuant software version that includes the 18 O quantitation option available to us. This work was supported by the European Framework 6 Integrated Projects EuTRACC and Cells into Organs and the Center for Biomedical Genetics (The Netherlands). Supporting Information Available: MS/MS spectra for all single peptide-based identifications, including peptide sequence, modifications, precursor mass, charge and mass error and Mascot score, and all sequences and MS spectra for Journal of Proteome Research • Vol. 9, No. 9, 2010 4473

research articles the peptides listed in Table 1.This material is available free of charge via the Internet at http://pubs.acs.org.

References (1) Alberts, B. The cell as a collection of protein machines: preparing the next generation of molecular biologists. Cell 1998, 92 (3), 291–4. (2) Kocher, T.; Superti-Furga, G. Mass spectrometry-based functional proteomics: from molecular machines to protein networks. Nat. Methods 2007, 4 (10), 807–15. (3) de Boer, E.; Rodriguez, P.; Bonte, E.; Krijgsveld, J.; Katsantoni, E.; Heck, A.; Grosveld, F.; Strouboulis, J. Efficient biotinylation and single-step purification of tagged transcription factors in mammalian cells and transgenic mice. Proc. Natl. Acad. Sci. U.S.A. 2003, 100 (13), 7480–5. (4) Tian, G.; Zhou, Y.; Hajkova, D.; Miyagi, M.; Dinculescu, A.; Hauswirth, W. W.; Palczewski, K.; Geng, R.; Alagramam, K. N.; Isosomppi, J.; Sankila, E. M.; Flannery, J. G.; Imanishi, Y. Clarin-1, encoded by the Usher Syndrome III causative gene, forms a membranous microdomain: possible role of clarin-1 in organizing the actin cytoskeleton. J. Biol. Chem. 2009, 284 (28), 18980–93. (5) Ong, S. E.; Blagoev, B.; Kratchmarova, I.; Kristensen, D. B.; Steen, H.; Pandey, A.; Mann, M.; Stable isotope labeling by amino acids in cell culture, SILAC. as a simple and accurate approach to expression proteomics. Mol. Cell. Proteomics 2002, 1 (5), 376–86. (6) Krijgsveld, J.; Ketting, R. F.; Mahmoudi, T.; Johansen, J.; Artal-Sanz, M.; Verrijzer, C. P.; Plasterk, R. H.; Heck, A. J. Metabolic labeling of C. elegans and D. melanogaster for quantitative proteomics. Nat. Biotechnol. 2003, 21 (8), 927–31. (7) Gygi, S. P.; Rist, B.; Gerber, S. A.; Turecek, F.; Gelb, M. H.; Aebersold, R. Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nat. Biotechnol. 1999, 17 (10), 994–9. (8) Yi, E. C.; Li, X. J.; Cooke, K.; Lee, H.; Raught, B.; Page, A.; Aneliunas, V.; Hieter, P.; Goodlett, D. R.; Aebersold, R. Increased quantitative proteome coverage with (13)C/(12)C-based, acid-cleavable isotopecoded affinity tag reagent and modified data acquisition scheme. Proteomics 2005, 5 (2), 380–7. (9) Desiderio, D. M.; Kai, M. Preparation of stable isotope-incorporated peptide internal standards for field desorption mass spectrometry quantification of peptides in biologic tissue. Biomed. Mass Spectrom. 1983, 10 (8), 471–9. (10) Mirgorodskaya, O. A.; Kozmin, Y. P.; Titov, M. I.; Korner, R.; Sonksen, C. P.; Roepstorff, P. Quantitation of peptides and proteins by matrix-assisted laser desorption/ionization mass spectrometry using (18)O-labeled internal standards. Rapid Commun. Mass Spectrom. 2000, 14 (14), 1226–32. (11) Rao, K. C.; Carruth, R. T.; Miyagi, M. Proteolytic 18O labeling by peptidyl-Lys metalloendopeptidase for comparative proteomics. J. Proteome Res. 2005, 4 (2), 507–14. (12) Ramos-Fernandez, A.; Lopez-Ferrer, D.; Vazquez, J. Improved method for differential expression proteomics using trypsincatalyzed 18O labeling with a correction for labeling efficiency. Mol. Cell. Proteomics 2007, 6 (7), 1274–86. (13) Zang, L.; Palmer Toy, D.; Hancock, W. S.; Sgroi, D. C.; Karger, B. L. Proteomic analysis of ductal carcinoma of the breast using laser capture microdissection LC-MS and 16O/18O isotopic labeling. J. Proteome Res. 2004, 3 (3), 604–12. (14) Staes, A.; Demol, H.; Van Damme, J.; Martens, L.; Vandekerckhove, J.; Gevaert, K. Global differential non-gel proteomics by quantitative and stable labeling of tryptic peptides with oxygen-18. J. Proteome Res. 2004, 3 (4), 786–91. (15) Hajkova, D.; Rao, K. C.; Miyagi, M. pH dependency of the carboxyl oxygen exchange reaction catalyzed by lysyl endopeptidase and trypsin. J. Proteome Res. 2006, 5 (7), 1667–73. (16) Chen, X.; Cushman, S. W.; Pannell, L. K.; Hess, S. Quantitative proteomic analysis of the secretory proteins from rat adipose cells using a 2D liquid chromatography-MS/MS approach. J. Proteome Res. 2005, 4 (2), 570–7. (17) Sevinsky, J. R.; Brown, K. J.; Cargile, B. J.; Bundy, J. L.; Stephenson, J. L., Jr. Minimizing back exchange in 18O/16O quantitative proteomics experiments by incorporation of immobilized trypsin into the initial digestion step. Anal. Chem. 2007, 79 (5), 2158–62. (18) Fenselau, C.; Yao, X. Proteolytic labeling with 18O for comparative proteomics studies: preparation of 18O-labeled peptides and the 18O/16O peptide mixture. Methods Mol. Biol. 2007, 359, 135–42. (19) Peng, J.; Zhu, Y.; Milton, J. T.; Price, D. H. Identification of multiple cyclin subunits of human P-TEFb. Genes Dev. 1998, 12 (5), 755– 62.

4474


Bezstarosti et al. (20) Peng, J.; Marshall, N. F.; Price, D. H. Identification of a cyclin subunit required for the function of Drosophila P-TEFb. J. Biol. Chem. 1998, 273 (22), 13855–60. (21) Marshall, N. F.; Peng, J.; Xie, Z.; Price, D. H. Control of RNA polymerase II elongation potential by a novel carboxyl-terminal domain kinase. J. Biol. Chem. 1996, 271 (43), 27176–83. (22) Price, D. H. P-TEFb, a cyclin-dependent kinase controlling elongation by RNA polymerase II. Mol. Cell. Biol. 2000, 20 (8), 2629–34. (23) Garriga, J.; Grana, X. Cellular control of gene expression by T-type cyclin/CDK9 complexes. Gene 2004, 337, 15–23. (24) Jang, M. K.; Mochizuki, K.; Zhou, M.; Jeong, H. S.; Brady, J. N.; Ozato, K. The bromodomain protein Brd4 is a positive regulatory component of P-TEFb and stimulates RNA polymerase II-dependent transcription. Mol. Cell 2005, 19 (4), 523–34. (25) Yang, Z.; Yik, J. H.; Chen, R.; He, N.; Jang, M. K.; Ozato, K.; Zhou, Q. Recruitment of P-TEFb for stimulation of transcriptional elongation by the bromodomain protein Brd4. Mol. Cell 2005, 19 (4), 535–45. (26) Michels, A. A.; Fraldi, A.; Li, Q.; Adamson, T. E.; Bonnet, F.; Nguyen, V. T.; Sedore, S. C.; Price, J. P.; Price, D. H.; Lania, L.; Bensaude, O. Binding of the 7SK snRNA turns the HEXIM1 protein into a P-TEFb (CDK9/cyclin T) inhibitor. Embo J. 2004, 23 (13), 2608– 19. (27) Byers, S. A.; Price, J. P.; Cooper, J. J.; Li, Q.; Price, D. H. HEXIM2, a HEXIM1-related protein, regulates positive transcription elongation factor b through association with 7SK. J. Biol. Chem. 2005, 280 (16), 16360–7. (28) Guenther, M. G.; Levine, S. S.; Boyer, L. A.; Jaenisch, R.; Young, R. A. A chromatin landmark and transcription initiation at most promoters in human cells. Cell 2007, 130 (1), 77–88. (29) Muse, G. W.; Gilchrist, D. A.; Nechaev, S.; Shah, R.; Parker, J. S.; Grissom, S. F.; Zeitlinger, J.; Adelman, K. RNA polymerase is poised for activation across the genome. Nat. Genet. 2007, 39 (12), 1507– 11. (30) Zeitlinger, J.; Stark, A.; Kellis, M.; Hong, J. W.; Nechaev, S.; Adelman, K.; Levine, M.; Young, R. A. RNA polymerase stalling at developmental control genes in the Drosophila melanogaster embryo. Nat. Genet. 2007, 39 (12), 1512–6. (31) Price, D. H. Poised polymerases: on your mark. .get set. .go! Mol. Cell 2008, 30 (1), 7–10. (32) Meier, N.; Krpic, S.; Rodriguez, P.; Strouboulis, J.; Monti, M.; Krijgsveld, J.; Gering, M.; Patient, R.; Hostert, A.; Grosveld, F. Novel binding partners of Ldb1 are required for haematopoietic development. Development 2006, 133 (24), 4913–23. (33) Kolodziej, K. E.; Pourfarzad, F.; de Boer, E.; Krpic, S.; Grosveld, F.; Strouboulis, J. Optimal use of tandem biotin and V5 tags in ChIP assays. BMC Mol. Biol. 2009, 10, 6. (34) Schulze, W. X.; Mann, M. A novel proteomic screen for peptideprotein interactions. J. Biol. Chem. 2004, 279 (11), 10756–64. (35) Mortensen, P.; Gouw, J. W.; Olsen, J. V.; Ong, S. E.; Rigbolt, K. T.; Bunkenborg, J.; Cox, J.; Foster, L. J.; Heck, A. J.; Blagoev, B.; Andersen, J. S.; Mann, M. MSQuant, an open source platform for mass spectrometry-based quantitative proteomics. J. Proteome Res. 2010, 9 (1), 393–403. (36) Kuras, L.; Struhl, K. Binding of TBP to promoters in vivo is stimulated by activators and requires Pol II holoenzyme. Nature 1999, 399 (6736), 609–13. (37) Li, X. Y.; Virbasius, A.; Zhu, X.; Green, M. R. Enhancement of TBP binding by activators and general transcription factors. Nature 1999, 399 (6736), 605–9. (38) Ranish, J. A.; Yudkovsky, N.; Hahn, S. Intermediates in formation and activity of the RNA polymerase II preinitiation complex: holoenzyme recruitment and a postrecruitment role for the TATA box and TFIIB. Genes Dev. 1999, 13 (1), 49–63. (39) Cantin, G. T.; Stevens, J. L.; Berk, A. J. Activation domain-mediator interactions promote transcription preinitiation complex assembly on promoter DNA. Proc. Natl. Acad. Sci. U.S.A. 2003, 100 (21), 12003–8. (40) Kornberg, R. D. Mediator and the mechanism of transcriptional activation. Trends Biochem. Sci. 2005, 30 (5), 235–9. (41) Malik, S.; Roeder, R. G. Dynamic regulation of pol II transcription by the mammalian Mediator complex. Trends Biochem. Sci. 2005, 30 (5), 256–63. (42) Zhu, B.; Mandal, S. S.; Pham, A. D.; Zheng, Y.; Erdjument-Bromage, H.; Batra, S. K.; Tempst, P.; Reinberg, D. The human PAF complex coordinates transcription with events downstream of RNA synthesis. Genes Dev. 2005, 19 (14), 1668–73. (43) Moniaux, N.; Nemos, C.; Deb, S.; Zhu, B.; Dornreiter, I.; Hollingsworth, M. A.; Batra, S. K. The human RNA polymerase IIassociated factor 1 (hPaf1): a new regulator of cell-cycle progression. PLoS One 2009, 4 (9), e7077.

18

research articles


(44) Kim, J.; Guermah, M.; Roeder, R. G. The human PAF1 complex acts in chromatin transcription elongation both independently and cooperatively with SII/TFIIS. Cell 2010, 140 (4), 491–503. (45) Jeronimo, C.; Forget, D.; Bouchard, A.; Li, Q.; Chua, G.; Poitras, C.; Therien, C.; Bergeron, D.; Bourassa, S.; Greenblatt, J.; Chabot, B.; Poirier, G. G.; Hughes, T. R.; Blanchette, M.; Price, D. H.; Coulombe, B. Systematic analysis of the protein interaction network for the human transcription machinery reveals the identity of the 7SK capping enzyme. Mol. Cell 2007, 27 (2), 262– 74. (46) Bitoun, E.; Oliver, P. L.; Davies, K. E. The mixed-lineage leukemia fusion partner AF4 stimulates RNA polymerase II transcriptional elongation and mediates coordinated chromatin remodeling. Hum. Mol. Genet. 2007, 16 (1), 92–106.

(47) Jiang, H.; Peterlin, B. M. Differential chromatin looping regulates CD4 expression in immature thymocytes. Mol. Cell. Biol. 2008, 28 (3), 907–12. (48) Parada, C. A.; Roeder, R. G. A novel RNA polymerase II-containing complex potentiates Tat-enhanced HIV-1 transcription. Embo J. 1999, 18 (13), 3688–701. (49) Fryer, C. J.; White, J. B.; Jones, K. A. Mastermind recruits CycC: CDK8 to phosphorylate the Notch ICD and coordinate activation with turnover. Mol. Cell 2004, 16 (4), 509–20. (50) Gegonne, A.; Weissman, J. D.; Lu, H.; Zhou, M.; Dasgupta, A.; Ribble, R.; Brady, J. N.; Singer, D. S. TFIID component TAF7 functionally interacts with both TFIIH and P-TEFb. Proc. Natl. Acad. Sci. U.S.A. 2008, 105 (14), 5367–72.

PR100217D

Journal of Proteome Research • Vol. 9, No. 9, 2010 4475

Differential Proteomics Based on 18O Labeling to Determine the

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