- Email: [email protected]
Toward a comprehensive characterization of the phosphotyrosine proteome
Cellular Signalling 23 (2011) 1387–1395
Contents lists available at ScienceDirect
Cellular Signalling j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / c e l l s i g
Toward a comprehensive characterization of the phosphotyrosine proteome Sara Bergström Lind a,⁎, Konstantin A. Artemenko b, Lioudmila Elfineh a, Corina Mayrhofer c,1, Roman A. Zubarev c,2, Jonas Bergquist b, Ulf Pettersson a a b c
Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, SE-751 85 Uppsala, Sweden Department of Physical and Analytical Chemistry, Uppsala University, SE-751 24 Uppsala, Sweden Division of Molecular Biometry, Department of Cell and Molecular Biology, Uppsala University, SE-751 24 Uppsala, Sweden
a r t i c l e
i n f o
Article history: Received 30 November 2010 Received in revised form 3 March 2011 Accepted 21 March 2011 Available online 5 April 2011 Keywords: Protein tyrosine phosphorylation Phosphotyrosine signaling Mass spectrometry Proteomics
a b s t r a c t Tyrosine phosphorylation (pTyr) regulates important cell functions and plays a key role in carcinogenesis. The purpose of this study was to perform a comprehensive study of the phosphotyrosine proteome. Immunoaffinity enriched pTyr proteins and peptides from K562 leukemia cells were analyzed with highresolving liquid chromatography mass spectrometry. Two different antibodies selective for the pTyr modification were used in repeated enrichments to identify as many pTyr peptides as possible. Stringent verification of putative pTyr sites was performed to assure high reliability in the subsequent biological interpretation of the data. Identified pTyr proteins were subjected to pathway analysis by using different analytical tools. In total, 294 pTyr peptides belonging to 217 pTyr proteins were identified, 15 of which had not previously been reported to be modified by pTyr. The pTyr proteins were clustered in six major groups based on the biological functions “cellular signaling”, “cell motility and shape”, “cell cycle process”, “transport”, “RNA processing” and “protein processing”. The pTyr proteins were mainly positioned in the following cellular compartments: cytoplasm, cytoskeleton, nucleus and ribonucleoprotein complexes. An interesting finding was that many proteins were related to RNA processing and were found to be heterogeneous nuclear ribonucleoproteins. Also, more than half of the novel pTyr proteins were localized to the nucleus, of which three (PBX2, TEAD1 and DIDO1) were classified as transcription factors and two (CENPC1 and MAD2L1) are associated with cell division control. © 2011 Elsevier Inc. All rights reserved.
1. Introduction Phosphorylation is one of the most important posttranslational modifications due to its involvement in many essential regulatory functions. Tyrosine phosphorylation (pTyr) is particularly interesting to study since many characteristics of cancer cells [1], e.g. growth, differentiation and apoptosis are regulated by this kind of modification and defective pTyr often plays a role in carcinogenesis [2,3]. pTyr signaling is regulated by tyrosine kinases and phosphatases as reviewed by Schlessinger [4]. The analysis of signaling pathways is complicated by the existence of redundancies. However, well-known
Abbreviations: pTyr, tyrosine phosphorylation (or tyrosine phosphorylated or phosphotyrosine). ⁎ Corresponding author at: Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University SE-751 85 Uppsala, Sweden. Tel.: +46 70 6042322; fax: +46 18 4714808. E-mail address: [email protected] (S. Bergström Lind). 1 Present address: Department of Animal Breeding and Genetics, University of Veterinary Medicine, AT-1210 Vienna, Austria. 2 Present address: Division of Molecular Biometry, Department of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden. 0898-6568/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.cellsig.2011.03.021
pathways that involve pTyr signaling, are the receptor tyrosine kinase pathways that mobilize the RAS/MAP kinase cascade, the phosphoinositol metabolism, and the JAK/STAT signaling pathways [4]. Compared to serine and threonine phosphorylation, pTyr is rare and seems to constitute less than one percent of all phosphorylations [5,6]. This makes a study like ours challenging. Clearly, investigations of pTyr proteins require enrichments by immunoaffinity-based methods using anti-pTyr-antibodies and selective tandem mass spectrometry (MS) to identify and verify pTyr sites [7–9]. In the present study, we have used K562 leukemia cells to acquire in-depth knowledge about pTyr proteins. This cell line was chosen because it is easy to cultivate, has successfully been used in other studies [7,9,10], and is relatively rich in pTyr. It contains the translocated oncogene BCR-ABL1 on the Philadelphia chromosome and expresses the BCR-ABL1 fusion protein with constitutive kinase activity. The dysregulation of the ABL1 tyrosine kinase is the primary cause of chronic myeloid leukemia (CML) [11]. Although the proteome of K562 is aberrant, it is a rich source of pTyr proteins and therefore a useful tool for studies of protein phosphorylation. The literature on protein phosphorylation is extensive. Many studies of pTyr have focused on specific pathways where pTyr plays a critical role like in Src signaling [12,13], EGF stimulation [14,15], or bidirectional EphR-ephrin signaling [16]. In other studies aimed at a
1388
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
comprehensive characterization of the pTyr proteome chemicals like pervanadate, which block tyrosine phosphatases have been used to enhance the level of phosphorylation. The aim of the present study was to perform a comprehensive characterization of the pTyr proteome in cells unperturbed by chemicals. By the use of optimized MS detection and enrichment methods [10,17] identification of a large number of validated pTyr proteins and phosphorylation sites was possible, some of which were novel. In addition we have used state-of-the-art software to assign the pTyr containing proteins to biological functions and pathways.
[18], PhosphoELM [19] (version 8.2, April 2009, http://phospho.elm. eu.org/), Phosida [20] (http://www.phosida.de, April 2010) and Phosphosite [21] (www.phosphosite.org, April 2010) databases. Sites were considered previously known if the amino acid sequence surrounding the pTyr site matched with the reference material. Protein identity was, however, not always matching, since a pTyr peptide sometimes could be matched to more than one protein identity (e.g. different isoforms or homologs in protein families). We also considered if the protein to which the site belongs had a previously identified other pTyr site reported in order to designate the protein as a new pTyr protein or not.
2. Material and methods 2.3. Sorting of tyrosine phosphorylated proteins 2.1. Identification of tyrosine phosphorylated peptides A detailed description of the procedures used are given by Artemenko et al. [17]. Briefly, K562 cells were grown to a density of 1–2 × 106 cells/mL before harvest. Cells were lysed for immunoaffinity enrichment of pTyr peptides or proteins. For each immunoaffinity enrichment, 2 × 108 cells were used. For peptide enrichment, the lysate was digested with trypsin and lyophilized before incubation with antibody. For protein enrichment, the lysate was incubated with antibody followed by tryptic digestion. For both peptide and protein enrichments, the 4G10 (Millipore) and the PYKD1 (Sloan Kettering Institute for Cancer Research) anti-phosphotyrosine antibodies were used. In total ten billion (1010) cells were used for enrichment, resulting in 52 preparations that were analyzed with a nano liquid chromatography system coupled on-line with a 7-tesla LTQ-FT Ultra mass spectrometer, either as single preparations or as pool of eight preparations. In total, 30 LC–MS/MS runs were performed. 2.2. Data evaluation RAW files from the MS instrument were converted to mgf files using an in-house written program. The mgf files were submitted to Mascot search (version 2.1.3, Matrix science, London, UK) in the International Protein Index (IPI) human database (74049 sequences), using the following settings: trypsin specificity, up to two missed cleavages were allowed, mass deviation for precursor ions and fragment ions were 0.02 and 0.9 Da, respectively, carbamidomethylation was chosen as fixed modification while deamidation (N,Q), oxidation (M), phosphorylation (S,T) and phosphorylation (Y) were set as variable modifications, instrument setting was ESI-FTICR and peptide/protein identifications were performed using MudPIT scoring. pTyr peptides with a Mascot score higher than 30 were extracted from Mascot to XML files. All pTyr sites suggested by Mascot were then searched in the Swiss-Prot database (http://www.expasy.org/ sprot), and sites that were not previously reported were subjected to manual verification. To pass the verification a pTyr peptide required to provide fragment ions revealing the phosphate group positioning at given tyrosine residue with a signal-to-noise ratio of ~ 3. Also, all other sequences suggested to match the MS/MS spectra were to have lower scores than that of the highest scoring pTyr peptide. A list of all identified pTyr peptides and sites, i.e. sites previously reported in Swiss-Prot and sites, that were accepted after manual verification by inspection of the corresponding MS/MS spectrum, is given in Supplementary Table 1. This list was complemented with a few pTyr proteins previously published by our group [10], but not detected in these new experiments. The corresponding MS/MS spectra of manually verified pTyr peptides are given in Supplemental data. Protein information extracted e.g. peptides assigned to a specific protein and sequence coverage for each of the 30 LC–MS analyses is given in Supplementary material, while methodological settings for each run can be found in Artemenko et al. [17]. To investigate if a pTyr site was new we have used the following sources: Goss et al. [9], Swiss-Prot (http://www.expasy.org/sprot/)
An open source tool, David GO [22] (http://david.abcc.ncifcrf.gov, version 6.7) was used for clustering of genes and proteins. Files with IPI accession numbers of all detected pTyr proteins (207 of 218 IPI accessions could be converted to David IDs) and proteins found to be new pTyr proteins (14 of 16 IPI accessions could be converted to David IDs) were loaded and subjected to gene ontology analysis for biological process (homo sapiens taxonomy, BP_3, BP_4 and BP_5 settings) and cell compartment (using CC_4 and CC_5 settings). Functional annotation clustering with medium stringency was performed using default background settings. Proteins classified into different categories of biological process by David GO were also subjected to pathway analysis using MetaCore™ (www.genego.com, GeneGo, St. Joseph, MI, USA). As datasets, proteins in the different categories in Table 2 were loaded separately and subjected sorted into “pathway maps” and “map folders” at p b 0.05 significance level based on enrichment analysis compared to a background of general protein expression. Proteins were also classified manually into groups based on information from the Swiss-Prot database. Finally, analysis of the frequencies of amino acids surrounding the pTyr sites was performed using the WebLogo tool (http://weblogo.berkeley.edu/logo.cgi) [23]. 3. Results 3.1. Aim of study The aim of our study was to comprehensively investigate the pTyr proteome. Extraction of pTyr proteins and peptides was performed by selective immunoaffinity enrichment using the complementary antibodies 4G10 and PYKD1 [17]. A flow chart is presented in Fig. 1 and our strategy included both enrichments at the protein and at the peptide levels. In total 52 immunoaffinity enrichments were combined into 30 LC–MS/MS analyses. A data base search identified 480 non-redundant pTyr peptides. Approximately 25% of the detected sites were already reported in the Swiss-Prot database. The other 75% were subjected to manual verification by inspection of the corresponding MS/MS spectra. Of the inspected pTyr sites 115 sites (30%) were accepted (assigned MS/MS spectra are supplied in Supplemental data) and considered together with the sites already reported in Swiss-Prot. In total, 294 pTyr sites belonging to 217 proteins were considered for biological pathway studies (Supplementary Table 1). 3.2. Protein sorting/clustering/pathway analysis As a first step the pTyr proteins were manually classified into categories based upon information from the Swiss-Prot database. The categories of molecular function that dominated were “kinases/ phosphatases” (23%), “adaptor/scaffold proteins” (15%), “RNA related proteins” (15%) and “structural proteins” (15%); see Fig. 2. Thereafter, the pTyr proteins were sorted by David GO into functional annotation clusters of cell compartments (Table 1). The pTyr proteins were mainly located in the cytoplasm, the cytoskeleton and in the nucleus. When sorting the pTyr proteins by David GO for biological process
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
1389
Table 1 Annotation clusters from David GO analysis of cell compartments of the studied pTyr proteins. Annotation cluster
Enrichment scorea
1. Cytoplasm Cytoplasm Cytosolic part
14.5 2.3
2. Cytoskeleton Intracellular non-membrane-bounded organelle/cytoskeleton 11.0 Cytoskeleton 5.6 Microtubule 3.8 Microtubule cytoskeleton 2.4 Actin filament 2.4 3. Nucleus Intracellular organelle/nucleus Nucleus Spindle Chromosome
6.8 4.6 2.7 2.0
4. Ribonucleoprotein complex Ribonucleoprotein complex
4.0
5. Junctions Junctions
3.1
a
Enrichment score annotates geometric mean of the p-value of each category in that cluster in minus log scale; enrichment score N2 corresponds to p b 0.01. p-value is the Fischer exact p-value of the degree of enrichment of the annotation term in the gene list compared to a background list.
Fig. 1. Flow chart of the principle for analysis and characterization of the phosphotyrosine proteome in K562 cells.
(Table 2), the highest enrichment scores were obtained for clusters related to “cellular signaling”, “cell motility and shape”, “cell cycle processes” and “RNA processing”. Proteins present in each cluster are shown in Table 2. Approximately 60% of the studied proteins were represented in a significant annotation cluster. To gain a deeper insight, proteins in each cluster group were also subjected to pathway analysis by GeneGO (Table 2 is extended with the detailed pathways from GeneGO in Supplementary Table 2). The cluster
“cellular signaling” was dominated by pathways involved in development and in immune response regulation, while the cluster of “cell motility and shape” included a number of pathways related to cell adhesion and cytoskeleton remodeling. As expected, the “cell cycle” cluster mainly contained pathways involved in cell cycle regulation. 3.3. New pTyr proteins When considering if a pTyr site had been previously identified or not, additional databases and references than Swiss-Prot were employed (see Section 2.2). When our sites were compared with databases of
Fig. 2. Distribution of identified tyrosine phosphorylated proteins within categories describing molecular function.
1390
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
phosphorylations, a pTyr site was accepted as previously known if the amino acid sequences surrounding the pTyr site matched (even though protein name not always matched).We identified 28 new pTyr sites and 15 new pTyr proteins (Table 3). Functional annotation clustering of these proteins by David GO indicated two clusters of proteins; “regulation of transcription/RNA metabolic processes” (including the PBX2, TEAD, ZIMZ2, DIDO1 and PER3 proteins) and “cellular protein metabolic processes” (including the FBXO9, MAD2L1 and VBP1 proteins). The enrichment scores for these clusters were, however, not significant (0.8 and 0.2, respectively) which was due to the low number of proteins submitted to analysis. Cellular functions of the new pTyr proteins are described in Discussion. 3.4. Frequently detected pTyr sites Table 4 describes the most frequently detected pTyr peptides and to what proteins they belong. The most frequently detected site was Y15 in CDK2/CDK3/CDC2 proteins (the sequence is matching all three proteins and from this analysis it cannot be established to which protein it actually belonged). Other commonly detected sites were Y216 in GSK3B, Y29 in EEF1A1, Y361 in HIPK2, Y182 in MAPK14 and Y438/Y426 in LCK/Yes, Y1135 in INPPL1, Y644 in BCR, Y393 in ABL1/ ABL2 and Y39 in VASP. 3.5. WebLogo analysis of amino acids flanking the pTyr sites To investigate if there is a preference for certain amino acids in regions that flank the pTyr sites, WebLogo analysis was performed. The six amino acids up- and downstream of the pTyr sites were included in the analysis. As presented in Fig. 3 no major dominance for a certain amino acid residue at a certain position was seen. A preference for a neutral amino acid, e.g. leucine (L), isoleucine (I), valine (V) or alanine (A) at the position just upstream of the pTyr site, an acidic region of glutamic acid residues (E) 3–5 amino acids residues upstream of the pTyr sites and a basic region of arginines (R) 4–6 amino acid residues downstream of the pTyr sites was indicated. 4. Discussion Studies of pTyr are important for understanding its role in pathological processes. This work is an attempt to provide a comprehensive list of validated pTyr sites and proteins in human cells and to relate the findings to processes previously associated with the pTyr modification in order to find new proteins, sites and functional categories of pTyr proteins. Our data rely on a series of analyses of immunoaffinity enriched pTyr proteins and peptides [10,17]. It is unfortunately not possible to extract a list of all known pTyr proteins from the Swiss-Prot data base for a comparison, but a measure of the comprehensiveness of this study is the cumulative number of detected pTyr peptides as a function of the number of performed LC–MS analyses as described by Artemenko et al. ([17]; see Fig. 2 in this reference). From this figure it is possible to identify important steps in the method development. Replicate runs and runs of pooled enrichments were identified as steps that improved the number of detected pTyr peptides. The fact that the number of pTyr peptides finally reached a plateau in the plot indicated that further analyses would not improve the results significantly and that this study could be considered reasonably comprehensive. After reaching this plateau we further added 14 pTyr sites, detected in our previous study of K562 cells [10]. The reason for not detecting these additional sites in the more comprehensive study by Artemenko et al. [17] might be the use of different procedures for the immunoaffinity enrichment in the two studies, providing slightly complementary results. Compared to previously published studies of pTyr in the K562 cell lines where 29 [7] and 86 [9] pTyr sites were reported, this is the most extensive study performed so far. In studies of pTyr in other cell lines as many as 400–600 sites were identified [12,14].
However, in these studies stimulations by Src-oncogene transformation or growth factors were used to enhance the level of pTyr. Enrichments are needed for detection of low abundant pTyr peptides. To separate them from competing unphosphorylated peptides in a cell lysate is required. This often leads to selection of only one peptide belonging to a specific protein. Manual validation is therefore crucial to assure quality and accuracy of the data generated by MS, e.g. accurate peptide and phosphorylation site assignment in MS/MS spectra [24]. Unfortunately, the extent of manual validation in many previous publications is often uncertain, which limits the use of such data for biological interpretation. To provide trustworthy data, we applied high-resolving MS analysis (resolution 100,000) of the peptides in the survey scans of precursor ions which provided high accuracy in the first step of the sequencing. Further, the true pTyr site was preferentially identified by an additional +79.966 Da difference in the MS/MS spectra for the tyrosine residue. Due to our stringent criteria for identification of a pTyr site (see Section 2.2), only 30% of the candidate MS/MS spectra were accepted. It is very likely that several of the inspected but not accepted pTyr sites are real. However, since the aim of our study was to provide a list of stringently validated pTyr sites we report on sites where the phosphorylation is explicitly positioned on a specific tyrosine residue. In this study, all reported pTyr sites were manually verified if not reported before in the SwissProt database. Thus the results presented here are unique. For pTyr peptides that were suggested to belong to several different proteins the multiple annotations were considered in further processing of the data. pTyr proteins are generally involved in signal transduction that most notably involves regulation of cell proliferation and differentiation, but also processes like cell metabolism, growth, mobility and survival are of importance. pTyr proteins crucial for signal initiation often possess kinase, phosphatase, phospholipase or Ras-GAP activity or belong to the adaptor protein family. These proteins facilitate the downstream interaction with other proteins, phospholipids or nucleic acids, to transfer the signals [4]. It was therefore expected that the results of the manual sorting of pTyr proteins based on the information in Swiss-Prot database (see Supplementary Table 1 and Fig. 2) revealed categories like “kinases/phosphatases” (tyrosine, serine/threonine, lipid kinases/phosphatases) and “adaptor/scaffold” proteins. On the other hand, two other categories, “RNA related” and “structural” proteins, made up a considerable part of the identified pTyr proteins. These results were unexpected. It would thus be interesting to look further into the regulation of these processes since RNA processing and structural changes are necessary to take place in fast growing cancer cells. The pTyr proteins studied were clustered by David GO analysis based on cellular localization into three dominating compartments; the cytoplasm, the cytoskeleton and the nucleus (Table 1). A fourth category, ribonucleoprotein complex, was also identified. Few pTyr proteins were assigned to the cell membrane. This was surprising since tyrosine autophosphorylation of many membrane bound tyrosine receptor kinases is a well-known phenomenon. An explanation might be that the recovery of membrane proteins was low. It is noteworthy that previous studies of pTyr proteins in K562 cells have failed to detect many of the known membrane-bound pTyr proteins [7,9]. Clustering of pTyr proteins by David GO, based on biological process (Table 2) highlighted “cellular signaling”, which can be explained by abundance of “kinases/phosphatases” and “adaptor/ scaffold” proteins as identified in the Swiss-Prot data base (Fig. 2). Other clusters with high scores were “cell motility and shape”, “cell cycle processes” and “RNA processes” and this finding agreed well with the rough sorting into categories from Swiss-Prot. “Structural” and “adaptor/scaffold” proteins were abundant in the cluster named “cell motility and shape”. This agreed with studies of mouse fibroblasts [12], where high frequencies of pTyr sites were
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
1391
Table 2 Annotation clusters from David GO analysis of biological process of the studied pTyr proteins. Annotation cluster
Enrichment scorea
Representative proteins
1. Cellular signaling Phosphorylation and intracellular signal transduction Insulin receptor signaling Cell surface receptor linked signal transduction Protein kinase cascade Growth hormone receptor signaling pathway Negative regulation of biological processes Regulation of immune response
7.8 4.3 4.2 1.9 1.8 2.1 1.5
Tyrosine protein kinases ABL1 BTK DDR1 EPHA4 FER JAK2 LCK LYN PTK2/FAK SYK TYK2 YES Tyrosine protein phosphatases PTPRA PTPN11 Serine/threonine protein kinases BCR CKDs DYRKs GSK3B HIPKs LATS MAPKs PRKCD RIPK1 Lipid kinases PI3Ks Adaptor proteins ABI1 APC CALM CD2AP CRKL DOK1
SHC1 GAB1 HGS ITGB1 NCK1 BCAR1 SORBS1 Transcription factors STAT5A Structural proteins ACTN4 CFL1 LASP1 MAP1B RNA-related proteins DDX5 EEF1A2 RBM3 GTP-ase related proteins GRLF1 ARAP1 Ubiquitin related protein PSMA2 PSMC2 TSG101 DNA-related proteins MAD2L1 SETD8 HIST1H4A
2. Cell motility and shape Cytoskeleton organization Regulation of cellular component organization Microtubule cytoskeleton organization Protein complex assembly Cell motility Regulation of cell motion Regulation of cell shape
5.8 1.9 1.8 1.7 2.4 2.0 1.4
DNA-related proteins MAD2L1 PRC1 Tyrosine protein kinases ABL1/2 EPHA4 PTK2/FAK JAK2 LYN SYK Serine/threonine protein kinases CDK5 GSK3B MAPK1 MAPK14 LATS1 Adaptor proteins ANK1 APC BCAR1 CBL CD2AP ERBB2IP GAB1/2 ITGB1 NCK1 SORBS1 Lipid kinases PIK3R1 Chaperones and heat shock related proteins HSPA4 Transcription factors AHCTF1
GTPase-related proteins ARAP1 GRLF1 RAN Structural proteins ACTB ACTG1 ACTN4 CFL1 EPB41 FLNB KRT8 LASP1 MAP1B MYH9 MYH10 PFN1 PXN TUBA1A TUBA1C VIM WASL Endosulfine family/cAMP-regulated phosphoprotein (ARPP) CAP1 RNA-related proteins UPF1 Miscellaneous proteins CALU DCTN2 PALMD PLA2G4A
3. Cell cycle process Cell cycle process
4.6
DNA related proteins MAD2L1
GTPase-related proteins ARAP1 (continued on next page)
1392
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
Table 2 (continued) Annotation cluster
Enrichment scorea
Representative proteins
3. Cell cycle process PRC1 SETD8 Adaptor proteins APC CD2AP ITGB1 Tyrosine protein kinase ABL1 TEC Serine/threonine protein kinases CDC2 CDK2 CDK3 GSK3B LATS1 MAPK12
RAN Ubiquitin related protein PSMA2 PSMC2 TSG101 Structural proteins MYH9 MYH10 Antigens MKI67 Endosulfine family/cAMP-regulated phosphoprotein (ARPP) AKAP8 Miscellaneous CALU DCTN2
4. Transport Regulation of intracellular transport Intracellular transport of proteins Regulation of glucose transport
1.4 1.4 1.3
Tyrosine protein kinases JAK2 LYN SYK Tyrosine protein phosphatases PTPN11 Serine/Threonine protein kinases CDK5 GSK3B MAPK1 Adaptor proteins CALM CBL CD2AP ERBB2IP HGS SORBS1 STAM2 Structural proteins ACTN4 CLTC KRT18 MYH9 MYH10
Lipid kinases PIK3R1 Miscellaneous PLA2G4A PTTG1IP CALU Chaperones and heat shock related proteins HSPA1 HSPA8 Ubiq CACYBP RNA-related proteins HNRNPA1 UPF1 GTPase-related proteins RAN
5. RNA processing RNA processing
2.5
RNA-related proteins CPSF6 CPSF7 DDX5 ELAVL1 HNRNPA0 HNRNPA1 HNRNPH3 HNRNPK NHP2L1
PABPC1 RBM4 RBMX SRRM2 UPF1 WBP11 Serine/threonine protein kinases PRPF4B Chaperones and heat shock related proteins HSPA1
6. Protein processing Protein folding
1.9
Chaperones and heat shock related proteins DNAJB4 HSPA4 HSPA8 VBP1 Adaptor proteins CD2AP Structural proteins ACTR10
Tyrosine protein kinases LYN RNA-related proteins CIRBP RBM3 Miscellaneous PLA2G4A
Response to heat
1.7
7. Miscellaneous Response to inorganic substance
1.5
RNA-related proteins EEF1A2 Structural proteins ACTB ACTG1 MAP1B PXN
Miscellaneous GART PLA2G4A Adaptor proteins CALM Ubiquitin related protein TFRC
a Enrichment score annotates geometric mean of the p-value of each category in that cluster in minus log scale; enrichment score N2 corresponds to p b 0.01; enrichment score N 1.3 corresponds to p b 0.05. p-value is the Fischer exact p-value of the degree of enrichment of the annotation term in the gene list compared to a background list.
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
1393
Table 3 Novel pTyr sites and pTyr proteins. Gene name
IPI accession
Protein name
Site
Peptide sequence
Other pTyr site
CALU CENPC1 CHST1 DIDO1 FBXO9 MAD2L1 PBX2 PER3 SAMD4B TEAD1 TROAP TUBA1Ba UNG VBP1 ZMIZ2 AKAP8 APC DCTN2 EEF2 HEMGN OTUD4 PPP1R13L PTPN18
IPI00014537 (IPI00789155) IPI00304885 IPI00021119 IPI00619921 IPI00296788 IPI00012369 IPI00028416 IPI00010692 IPI00470771 IPI00002901 IPI00029680 IPI00387144 IPI00011069 IPI00334159 IPI00289799 IPI00014474 IPI00012391 IPI00220503 IPI00186290 IPI00464963 IPI00399254 IPI00439948 IPI00152019
Y114 Y541 Y55 Y1700 Y111 Y199 Y316 Y1119 Y166 Y76 Y172 Y342 Y8 Y112 Y109 Y311 Y2645 Y313 Y443 Y479 Y460 Y126 Y207
WIyEDVER SEESPVySNSSVR LCEESPTFAyNLSRK ALGSAQyEDPR AVEEEQNGALyEAIK VNSMVAyKIPVND FQEEANIyAVK ILMTyQVPER SRPEPSyHSR NELIARyIK ASAyLAPR IHFPLATyAPVISAEK TLySFFSPSPAR FLLADNLyCK GYVQQGVySR QFQLyEEPDTK TLIyQMAPAVSK VHQLyETIQR EDLyLKPIQR EKPKEEPGIPAILNESHPENDVySYVLF LLyEIQNR TPLyLQPDAYGSLDR ENCAPLyDDALFLR
No No No No No No No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes
RBMXL1
IPI00061178
Y335
SDLySSCDR
Yes
RDBP SETD8 TUBA1Cb USP42
IPI00000858 IPI00288890 IPI00218343 IPI00375124
Isoform 1 of calumenin precursor Centromere protein C 1 Carbohydrate sulfotransferase 1 Isoform 4 of death-inducer obliterator 1 Isoform 1 of F-box only protein 9 Mitotic spindle assembly checkpoint protein MAD2A Pre-B-cell leukemia transcription factor 2 Period circadian protein homolog 3 SAMD4B protein Transcriptional enhancer factor TEF-1 Trophinin-associated protein Tubulin alpha-1B chain Isoform 2 of uracil-DNA glycosylase Von Hippel–Lindau binding protein 1 Isoform 2 of zinc finger MIZ domain-containing protein 2 A-kinase anchor protein 8 Isoform Long of adenomatous polyposis coli protein Dynactin 2 Elongation factor 2 Hemogen Isoform 1 of OTU domain-containing protein 4 Isoform 1 of RelA-associated inhibitor PTPN18 protein (cDNA FLJ51446, highly similar to tyrosine-protein phosphatase non-receptor type 18) RNA binding motif protein, X-linked-like 1 (kynurenine aminotransferase III isoform 3) Isoform 1 of negative elongation factor E Histone-lysine N-methyltransferase SETD8 Tubulin alpha-6 chain Ubiquitin carboxyl-terminal hydrolase 42
Y140 Y96 Y399 Y1069
SLyESFVSSSDR IySYMSPNK FDLmyAK YALyAAR
Yes Yes Yes Yes
a b
Site is previously known in the TUBA1A protein, Y272. Site previously reported for TUBA1B.
observed not only for proteins classified in the “signaling” group but also for proteins in the “adhesion/cytoskeleton” category. Goss et al. [9] showed pTyr modifications in several cytoskeleton proteins as well. As reviewed by Turner et al. [25], adaptor/scaffolding proteins are important bridging proteins for transferring growth signals into mechanisms that rearrange the cytoskeleton and alter the cell motility and shape. In the cluster “cell cycle process” the cell division kinases together with other serine/threonine kinases were predominant. Additionally, pTyr proteins implicated in e.g. structural conformation changes, like myosins, and in DNA control, MAD2L, PRC1 and SETD8, during cytokinesis were grouped to this cluster. As described in a review by Shields and Tiganis [26], previously pTyr-dependent signaling was primarily considered to be associated with the cellular response to mitogens in the G1 phase. From our results, pTyr proteins are obviously also involved in other cell cycle checkpoints. G2 progression and mitotic entry, spindle orientation and cytokinesis, are considered to be regulated by phosphotyrosine kinases and phosphatases which agrees with our findings [26]. The “RNA processing” cluster, almost exclusively containing RNArelated proteins, was especially interesting. Even though previous studies have reported on pTyr modification of DNA and RNA related proteins [13,14], this specific group of pTyr proteins has largely been overlooked. The pathway analysis from GeneGO (Supplementary Table 2) indicated that these proteins are involved in transcription and translation. In the study by Lou et al. [12], pTyr peptides from RNA related proteins were more frequent in Src-transformed cells compared to non-transformed cells. This indicates that these proteins are likely to be involved in processes related to cancer. Of the proteins found to be “RNA-related” (Supplementary Table 1), six were hnRNPs (heterogeneous nuclear ribonucleoproteins) known to complex with hnRNA and known to influence pre-mRNA processing. For the HNRNPK protein, the role of the pTyr modification has been shown to influence the protein–protein and protein–RNA interactions and
that tyrosine kinases could regulate HNRNPK upon extracellular stimuli [27]. Additional studies are needed to clarify the role of pTyr in the hnRNPs. For all functional annotation clusters, the tyrosine protein kinases ABL1, JAK2, LYN and PTK2 (or FAK), as well as the serine/threonine protein kinases MAPKs, GSK3B and CDKs appeared frequently, showing their involvement in many cellular processes. Also the transcription factor STAT5A is frequent in these clusters. As reviewed by Schlessinger, pTyr in STATs is of importance for signal transductions into the nucleus where a transcriptional program is initiated which can lead to oncogenic transformation [4]. Notably, only 60% of the identified pTyr proteins could be assigned to a annotation cluster after David GO analysis. Groups of pTyr proteins that had a high percentage of their pTyr proteins nonclustered by David GO analysis were “DNA and RNA-related proteins” and the heterogeneous group of “miscellaneous” proteins. One explanation why the residual 40% were not clustered can be that these proteins have not been considered to be involved in signaling processes and still remain to be assigned to clusters and pathways. For example, only three of the novel pTyr proteins (Table 3) were assigned to clusters when the whole list of pTyr proteins was taken into account (see Table 2). Pathway analysis by GeneGO was found to be a valuable tool to further study the pTyr proteins in different way than by David GO (see Supplementary Table 2). In general, the dominating pathway categories agreed well with the annotation clusters suggested for the same group of pTyr proteins. This was most strikingly observed for the “cell cycle process” and for the “cell motility and shape” clusters, which were dominated by pathways related to cell cycle and cell adhesion/cytoskeleton remodeling, respectively. After manual inspection of the pathways seen in the categories development, immune response, cytoskeleton remodeling, signal transduction and cell cycle it was obvious that several well-known signaling cascades and key signaling proteins were common for many pathways.
1394
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
Table 4 The most commonly identified pTyr peptides. Gene name
IPI accession
Protein name
Site
Peptide sequence
No of runsa
Comparisonb
CDK2/CDK3/CDC2
IGEGTyGVVYK
24
1, 3
Y1135 Y216 Y644 Y393/Y439
TLSEVDyAPAGPAR GEPNVSyICSR NSLETLLyKPVDR LMTGDTyTAHAGAK
21 16 16 14
4 1, 3 4 4
CDC2 CDK2/CDK3
IPI00026689 IPI00023503
Y15 Y15
IEKIGEGTyGVVYK VEKIGEGTyGVVYK
13 10
1 1, 3
EEF1A1/EEF1A2
IPI00396485/IPI00014424
Y29
STTTGHLIyK
10
2
VASP HIPK2
IPI00301058 IPI00215949
Y39 Y361
VQIyHNPTANSFR AVCSTyLQSR
10 9
4 3
MAPK14 TAGLN2 VIM VIM DOK1 LCK/YES1
IPI00002857 IPI00550363 IPI00418471 IPI00418471 IPI00015287 IPI00394952/IPI00013981
Y182 Y192 Y61 Y53 Y449 Y438/Y426
HTDDEmTGyVATR GASQAGMTGyGMPR SLYASSPGGVyATR SLyASSPGGVYATR SHNSALySQVQK LIEDNEyTAR
9 9 9 8 7 7
1, 3
CDC2 BCR HNRNPA0 ARFGAP2 HCK/LYN
IPI00026689 IPI00004497 IPI00011913 IPI00297322 IPI00029769/IPI00298625
Cell division protein kinase 2/Cell division protein kinase 3/Hypothetical protein DKFZp686L20222 Inositol polyphosphate phosphatase-like 1 Glycogen synthase kinase-3 beta Breakpoint cluster region protein Isoform IA of proto-oncogene tyrosine-protein kinase ABL1/Isoform IB of tyrosine-protein kinase ABL2 Hypothetical protein DKFZp686L20222 Cell division protein kinase 2/cell division protein kinase 3 Elongation factor 1-alpha 1/elongation factor 1-alpha 2 Vasodilator-stimulated phosphoprotein Isoform 2 of homeodomain-interacting protein kinase 2 Mitogen-activated protein kinase 14 isoform 2 Transgelin-2 Vimentin Vimentin Isoform 1 of docking protein 1 Lymphocyte-specific protein tyrosine kinase precursor (cDNA FLJ56184, highly similar to proto-oncogene tyrosine-protein kinase LCK)/proto-oncogene tyrosine-protein kinase Yes Hypothetical protein DKFZp686L20222 Breakpoint cluster region protein Heterogeneous nuclear ribonucleoprotein A0 ADP-rybosylation factor GTPase-activating protein 2. Isoform p59-HCK of Tyrosine-protein kinase HCK/LYN protein
Y15
INPPL1 GSK3B BCR ABL1/ABL2
IPI00031681/IPI00023503/ IPI00026689 IPI00016932 IPI00028570 IPI00004497 IPI00216969/IPI00329488
Y15 Y644 Y180 Y445 Y411/Y397
IGEGTyGVVYKGR NSLETLLyKPVDRVTR EDIySGGGGGGSR EVDAEyEAR VIEDNEyTAR
7 6 6 6 6
2
1 4
a
Number of LC–MS/MS run in which a specific pTyr peptide was identified. Comparisons with references; 1-pTyr peptide among the ten most frequently identified sites in non-transformed mouse fibroblast cells (Luo et al. [12]); 2-pTyr peptide among sites detected frequently in both nontransformed and Src-transformed cell populations (Luo et al. [12]); 3-pTyr peptide identified in control cell line U937 (Goss et al. [9]). 4-pTyr peptide identified only in Bcr-Abl expressing cell lines (Goss et al. [9]). b
About 10% of the identified pTyr sites were not previously reported in the literature or the phosphorylation databases. Among these, some sites belonged to proteins not previously reported to have a pTyr site, resulting in 15 pTyr proteins that were considered as novel. As mentioned before, only three of the new pTyr proteins, the CALU, MAD2L1 and VBP1 proteins, could be annotated to clusters when the whole list of pTyr proteins was considered (see Table 2). The remaining newly discovered pTyr proteins were found among the 40% of pTyr proteins that could not be assigned to clusters by David GO analysis. Notably, nine of the 15 new pTyr proteins had their location completely or partly in the cell nucleus; CENPC1, DIDO1, MAD2L1, PBX2, PER3, TEAD1, UNG, VBP1 and ZIMZ2 (full names are given in Table 3). These nuclear pTyr proteins are likely to be very scarce, but by pushing the limit of detection for pTyr peptides by repeated analyses of immunoaffinity enriched pools, they were now possible to identify. Three of the nuclear proteins were found to be transcription factors; PBX2, TEAD1 and DIDO1. The pTyr modification in these proteins might regulate their function, although it remains to be demonstrated if the modification leads to up-or downregulation. TEAD1 is known to be involved in the Hippo signaling pathway for
control of cell proliferation in mammals [28], while DIDO1 is involved in apoptosis and regarded as a tumor suppressor [29]. In 293T cells, Garcia-Domingo et al. [29] found that DIDO1 when phosphorylated on serine/threonine was predominantly localized to the cytoplasm. Upon induction of apoptosis, DIDO1 translocates to the nucleus where it appears unphosphorylated. In the same study, DIDO1 was shown by Western blotting to be tyrosine phosphorylated. However, no pTyr site was reported. PBX2 is a transcriptional activator that belongs to a family of PBX (Pre-B-cell leukemia transcription factor) proteins encoded by homeobox genes that have a generalized function in most cell types [30]. Two of the nuclear proteins are associated with cell division, i.e. CENPC1 and MAD2L1. The CENPC1 protein is important for chromosome segregation in the mitotic progression [31], while MAD2L1 prevents the transition into anaphase before all chromosomes are aligned [32,33]. Remaining novel nuclear pTyr proteins could not be grouped together. Instead they have various functions, e.g. the PER3 protein takes part in the circadian clock mechanism, the UNG protein prevents mutagenesis by eliminating uracil from DNA molecules, VPB1 functions as a chaperone and the ZIMZ2 protein interacts with nuclear hormone receptors. Left to mention are the
Fig. 3. WebLogo analysis of frequencies of amino acid surrounding the identified tyrosine phosphorylated sites. The frequency of each amino acid residue present in data set of identified tyrosine phosphorylated sites is proportional to its height.
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
new pTyr proteins that were localized outside the nucleus, i.e. CALU (Ca-binding protein), CHST1 (a sulfotransferase), FBXO9 (ubiquitin related protein), SAMD4B (transcription signaling protein [34]), TROAP (cell adhesion complex protein) and TUBA1B (structural protein; tubulin, microtubule) which all had heterogeneous functions. Tubulin proteins with other annotations are, however, previously reported to be tyrosine phosphorylated. As discussed by Lou et al. [12], the site identification frequency cannot be used as an absolute quantitative measure but can be taken as an indicator of the relative peptide abundance in a pTyr-enriched sample. Thus, a frequently detected site can be considered to have a high abundance, since it is likely that such pTyr sites occupy a large portion of the binding sites available on the antibodies and are therefore easier to detect. According to Table 4 the most frequently detected pTyr sites were found in cell division protein kinases, and in the INPPL1, GSK3B, BCR and ABL proteins. Detection of a high number of pTyr sites in the BCR-ABL1 fusion protein kinase was expected since this fusion protein functions as a constitutively active tyrosine kinase and possesses several important docking sites for recruitment of downstream signaling actors [35]. This activity of the Bcr-Abl protein gives rise to the carcinogenic properties and functions of the K562 cells, and many of the most frequently detected pTyr sites belonged to proteins previously related to Bcr-Abl signaling, e.g. BCR, ABL1/ABL2, INPPL1 and VASP [9]. Other pTyr proteins with highly abundant sites have been found in non-transformed mouse fibroblasts [12] and in U937 cells [9], which do not express the BCR-ABL fusion protein kinase, e.g. VIM, MAPK14, HIPK2, EEF1A1, GSK3B and the cell division protein kinases. Both in this study of K562 cells and in the study by Lou et al. [12], the most frequently detected pTyr site was Y15 in the CDK2/CDK3/CDC2/CDK1 proteins (not distinguishable). This pTyr site is important for fine tuning of the cell cycle [36–38]. Also our third most commonly identified pTyr site, Y216 in GSK3B, was ranked as number two in their study [12], indicating good agreement of data. The WebLogo analysis of amino acid residues surrounding the pTyr sites failed to show a clear overrepresentation of a certain amino acid at a certain position. This agreed with the findings observed by Beausoleil et al. [39] who performed WebLogo analysis of pTyr sites in pervanadate treated Jurkat cells. The tendency for an acidic region upstream of the pTyr sites indicated in this study agrees, however, with previous observations [8,39]. The surroundings of pTyr sites seem to be less constricted compared to serine and threonine phosphorylation sites [39,40]. 5. Conclusions To conclude, the aim of this study, to perform a comprehensive characterization of pTyr proteins, was fulfilled by categorizing and analyzing a stringently verified set of proteins with pTyr modification by different bioinformatic tools. In this way, new categories, e.g. RNA related pTyr proteins, new pTyr proteins, of which many were found in the nucleus and new sites of this posttranslational modification could be identified. Overall, this study provides an overview of groups of pTyr proteins that can be of importance for future functional studies. Our long term aim is to use knowledge of the pTyr proteome to search for “signatures” of tyrosine phosphorylation in different tumor cells. Such signatures ought to reflect differences among the perturbed signaling pathways and thus facility subclassification of tumors. Supplementary materials related to this article can be found online at doi:10.1016/j.cellsig.2011.03.021.
1395
Acknowledgments The Sloan Kettering Institute for Cancer Research is acknowledged as the provider of the PYKD1 antibody. We would also like to thank docent Jonas Åström and M.Sc. Martin Dahlö for valuable assistance. This work was supported by the Kjell and Märta Beijer Foundation (U.P.) and the Swedish Research Council (U.P. and J.B.). S.B.L. has a post-doc position from the Swedish Cancer Society. References [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] [35] [36] [37] [38] [39] [40]
D. Hanahan, R.A. Weinberg, Cell 100 (2000) 57–70. K.S. Kolibaba, B.J. Druker, Biochim. Biophys. Acta 1333 (1997) F217–F248. A. Levitzki, Pharmacol. Ther. 82 (1999) 231–239. J. Schlessinger, Cell 103 (2000) 211–225. T. Hunter, B.M. Sefton, Proc. Natl Acad. Sci. U.S.A. 77 (1980) 1311–1315. J.V. Olsen, B. Blagoev, F. Gnad, B. Macek, C. Kumar, P. Mortensen, M. Mann, Cell 127 (2006) 635–648. A.R. Salomon, S.B. Ficarro, L.M. Brill, A. Brinker, Q.T. Phung, C. Ericson, K. Sauer, A. Brock, D.M. Horn, P.G. Schultz, E.C. Peters, Proc. Natl Acad. Sci. U.S.A. 100 (2003) 443–448. J. Rush, A. Moritz, K.A. Lee, A. Guo, V.L. Goss, E.J. Spek, H. Zhang, X.M. Zha, R.D. Polakiewicz, M.J. Comb, Nat. Biotechnol. 23 (2005) 94–101. V.L. Goss, K.A. Lee, A. Moritz, J. Nardone, E.J. Spek, J. MacNeill, J. Rush, M.J. Comb, R.D. Polakiewicz, Blood 107 (2006) 4888–4897. S. Bergstrom Lind, M. Molin, M.M. Savitski, L. Emilsson, J. Astrom, L. Hedberg, C. Adams, M.L. Nielsen, A. Engstrom, L. Elfineh, E. Andersson, R.A. Zubarev, U. Pettersson, J. Proteome Res. 7 (2008) 2897–2910. R. Chopra, Q.Q. Pu, A.G. Elefanty, Blood Rev. 13 (1999) 211–229. W. Luo, R.J. Slebos, S. Hill, M. Li, J. Brabek, R. Amanchy, R. Chaerkady, A. Pandey, A.J. Ham, S.K. Hanks, J. Proteome Res. 7 (2008) 3447–3460. R. Amanchy, J. Zhong, H. Molina, R. Chaerkady, A. Iwahori, D.E. Kalume, M. Gronborg, J. Joore, L. Cope, A. Pandey, J. Proteome Res. 7 (2008) 3900–3910. T.H. Heibeck, S.J. Ding, L.K. Opresko, R. Zhao, A.A. Schepmoes, F. Yang, A.V. Tolmachev, M.E. Monroe, D.G. Camp II, R.D. Smith, H.S. Wiley, W.J. Qian, J. Proteome Res. 8 (2009) 3852–3861. P.J. Boersema, L.Y. Foong, V.M. Ding, S. Lemeer, B. van Breukelen, R. Philp, J. Boekhorst, B. Snel, J. den Hertog, A.B. Choo, A.J. Heck, Mol. Cell. Proteomics 9 (2010) 84–99. C. Jorgensen, A. Sherman, G.I. Chen, A. Pasculescu, A. Poliakov, M. Hsiung, B. Larsen, D.G. Wilkinson, R. Linding, T. Pawson, Science 326 (2009) 1502–1509. K. Artemenko, S. Bergstrom Lind, L. Elfineh, C. Mayrhofer, R.A. Zubarev, J. Bergquist, U. Pettersson, Analyst 136 (2011) 1971–1978. N. Farriol-Mathis, J.S. Garavelli, B. Boeckmann, S. Duvaud, E. Gasteiger, A. Gateau, A.L. Veuthey, A. Bairoch, Proteomics 4 (2004) 1537–1550. F. Diella, C.M. Gould, C. Chica, A. Via, T.J. Gibson, Nucleic Acids Res. 36 (2008) D240–D2448 (Database issue). F. Gnad, S. Ren, J. Cox, J.V. Olsen, B. Macek, M. Oroshi, M. Mann, Genome Biol. 8 (2007) R250. P.V. Hornbeck, I. Chabra, J.M. Kornhauser, E. Skrzypek, B. Zhang, Proteomics 4 (2004) 1551–1561. W. Huang da, B.T. Sherman, R.A. Lempicki, Nat. Protoc. 4 (2009) 44–57. G.E. Crooks, G. Hon, J.M. Chandonia, S.E. Brenner, Genome Res. 14 (2004) 1188–1190. A.M. Nichols, F.M. White, Methods Mol. Biol. 492 (2009) 143–160. C.E. Turner, Nat. Cell Biol. 2 (2000) E231–E236. B.J. Shields, T. Tiganis, Cell Cycle 8 (2009) 223–230. J. Ostrowski, D.S. Schullery, O.N. Denisenko, Y. Higaki, J. Watts, R. Aebersold, L. Stempka, M. Gschwendt, K. Bomsztyk, J. Biol. Chem. 275 (2000) 3619–3628. M. Ota, H. Sasaki, Development 135 (2008) 4059–4069. D. Garcia-Domingo, D. Ramirez, G. Gonzalez de Buitrago, A.C. Martinez, Mol. Cell. Biol. 23 (2003) 3216–3225. K. Monica, N. Galili, J. Nourse, D. Saltman, M.L. Cleary, Mol. Cell. Biol. 11 (1991) 6149–6157. Y. Xie, H.H. Heng, Cytogenet. Cell Genet. 74 (3) (1996) 192–193. X. Li, R.B. Nicklas, Nature 373 (1995) 630–632. Y. Li, R. Benezra, Science 274 (1996) 246–248. N. Luo, G. Li, Y. Li, X. Fan, Y. Wang, X. Ye, X. Mo, J. Zhou, W. Yuan, M. Tan, H. Xie, K. Ocorr, R. Bodmer, Y. Deng, X. Wu, BMB Rep. 43 (2010) 355–361. A. Quintas-Cardama, J. Cortes, Blood 113 (2009) 1619–1630. K.L. Gould, P. Nurse, Nature 342 (1989) 39–45. T.A. Potapova, J.R. Daum, K.S. Byrd, G.J. Gorbsky, Mol. Biol. Cell 20 (2009) 1737–1748. V.T. George, G. Brooks, T.C. Humphrey, Mol. Biol. Cell 18 (2007) 4168–4179. S.A. Beausoleil, J. Villen, S.A. Gerber, J. Rush, S.P. Gygi, Nat. Biotechnol. 24 (2006) 1285–1292. M. Salvi, L. Cesaro, L.A. Pinna, BioMol. Concepts 1 (2010) 185–196.
Contents lists available at ScienceDirect
Cellular Signalling j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / c e l l s i g
Toward a comprehensive characterization of the phosphotyrosine proteome Sara Bergström Lind a,⁎, Konstantin A. Artemenko b, Lioudmila Elfineh a, Corina Mayrhofer c,1, Roman A. Zubarev c,2, Jonas Bergquist b, Ulf Pettersson a a b c
Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, SE-751 85 Uppsala, Sweden Department of Physical and Analytical Chemistry, Uppsala University, SE-751 24 Uppsala, Sweden Division of Molecular Biometry, Department of Cell and Molecular Biology, Uppsala University, SE-751 24 Uppsala, Sweden
a r t i c l e
i n f o
Article history: Received 30 November 2010 Received in revised form 3 March 2011 Accepted 21 March 2011 Available online 5 April 2011 Keywords: Protein tyrosine phosphorylation Phosphotyrosine signaling Mass spectrometry Proteomics
a b s t r a c t Tyrosine phosphorylation (pTyr) regulates important cell functions and plays a key role in carcinogenesis. The purpose of this study was to perform a comprehensive study of the phosphotyrosine proteome. Immunoaffinity enriched pTyr proteins and peptides from K562 leukemia cells were analyzed with highresolving liquid chromatography mass spectrometry. Two different antibodies selective for the pTyr modification were used in repeated enrichments to identify as many pTyr peptides as possible. Stringent verification of putative pTyr sites was performed to assure high reliability in the subsequent biological interpretation of the data. Identified pTyr proteins were subjected to pathway analysis by using different analytical tools. In total, 294 pTyr peptides belonging to 217 pTyr proteins were identified, 15 of which had not previously been reported to be modified by pTyr. The pTyr proteins were clustered in six major groups based on the biological functions “cellular signaling”, “cell motility and shape”, “cell cycle process”, “transport”, “RNA processing” and “protein processing”. The pTyr proteins were mainly positioned in the following cellular compartments: cytoplasm, cytoskeleton, nucleus and ribonucleoprotein complexes. An interesting finding was that many proteins were related to RNA processing and were found to be heterogeneous nuclear ribonucleoproteins. Also, more than half of the novel pTyr proteins were localized to the nucleus, of which three (PBX2, TEAD1 and DIDO1) were classified as transcription factors and two (CENPC1 and MAD2L1) are associated with cell division control. © 2011 Elsevier Inc. All rights reserved.
1. Introduction Phosphorylation is one of the most important posttranslational modifications due to its involvement in many essential regulatory functions. Tyrosine phosphorylation (pTyr) is particularly interesting to study since many characteristics of cancer cells [1], e.g. growth, differentiation and apoptosis are regulated by this kind of modification and defective pTyr often plays a role in carcinogenesis [2,3]. pTyr signaling is regulated by tyrosine kinases and phosphatases as reviewed by Schlessinger [4]. The analysis of signaling pathways is complicated by the existence of redundancies. However, well-known
Abbreviations: pTyr, tyrosine phosphorylation (or tyrosine phosphorylated or phosphotyrosine). ⁎ Corresponding author at: Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University SE-751 85 Uppsala, Sweden. Tel.: +46 70 6042322; fax: +46 18 4714808. E-mail address: [email protected] (S. Bergström Lind). 1 Present address: Department of Animal Breeding and Genetics, University of Veterinary Medicine, AT-1210 Vienna, Austria. 2 Present address: Division of Molecular Biometry, Department of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden. 0898-6568/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.cellsig.2011.03.021
pathways that involve pTyr signaling, are the receptor tyrosine kinase pathways that mobilize the RAS/MAP kinase cascade, the phosphoinositol metabolism, and the JAK/STAT signaling pathways [4]. Compared to serine and threonine phosphorylation, pTyr is rare and seems to constitute less than one percent of all phosphorylations [5,6]. This makes a study like ours challenging. Clearly, investigations of pTyr proteins require enrichments by immunoaffinity-based methods using anti-pTyr-antibodies and selective tandem mass spectrometry (MS) to identify and verify pTyr sites [7–9]. In the present study, we have used K562 leukemia cells to acquire in-depth knowledge about pTyr proteins. This cell line was chosen because it is easy to cultivate, has successfully been used in other studies [7,9,10], and is relatively rich in pTyr. It contains the translocated oncogene BCR-ABL1 on the Philadelphia chromosome and expresses the BCR-ABL1 fusion protein with constitutive kinase activity. The dysregulation of the ABL1 tyrosine kinase is the primary cause of chronic myeloid leukemia (CML) [11]. Although the proteome of K562 is aberrant, it is a rich source of pTyr proteins and therefore a useful tool for studies of protein phosphorylation. The literature on protein phosphorylation is extensive. Many studies of pTyr have focused on specific pathways where pTyr plays a critical role like in Src signaling [12,13], EGF stimulation [14,15], or bidirectional EphR-ephrin signaling [16]. In other studies aimed at a
1388
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
comprehensive characterization of the pTyr proteome chemicals like pervanadate, which block tyrosine phosphatases have been used to enhance the level of phosphorylation. The aim of the present study was to perform a comprehensive characterization of the pTyr proteome in cells unperturbed by chemicals. By the use of optimized MS detection and enrichment methods [10,17] identification of a large number of validated pTyr proteins and phosphorylation sites was possible, some of which were novel. In addition we have used state-of-the-art software to assign the pTyr containing proteins to biological functions and pathways.
[18], PhosphoELM [19] (version 8.2, April 2009, http://phospho.elm. eu.org/), Phosida [20] (http://www.phosida.de, April 2010) and Phosphosite [21] (www.phosphosite.org, April 2010) databases. Sites were considered previously known if the amino acid sequence surrounding the pTyr site matched with the reference material. Protein identity was, however, not always matching, since a pTyr peptide sometimes could be matched to more than one protein identity (e.g. different isoforms or homologs in protein families). We also considered if the protein to which the site belongs had a previously identified other pTyr site reported in order to designate the protein as a new pTyr protein or not.
2. Material and methods 2.3. Sorting of tyrosine phosphorylated proteins 2.1. Identification of tyrosine phosphorylated peptides A detailed description of the procedures used are given by Artemenko et al. [17]. Briefly, K562 cells were grown to a density of 1–2 × 106 cells/mL before harvest. Cells were lysed for immunoaffinity enrichment of pTyr peptides or proteins. For each immunoaffinity enrichment, 2 × 108 cells were used. For peptide enrichment, the lysate was digested with trypsin and lyophilized before incubation with antibody. For protein enrichment, the lysate was incubated with antibody followed by tryptic digestion. For both peptide and protein enrichments, the 4G10 (Millipore) and the PYKD1 (Sloan Kettering Institute for Cancer Research) anti-phosphotyrosine antibodies were used. In total ten billion (1010) cells were used for enrichment, resulting in 52 preparations that were analyzed with a nano liquid chromatography system coupled on-line with a 7-tesla LTQ-FT Ultra mass spectrometer, either as single preparations or as pool of eight preparations. In total, 30 LC–MS/MS runs were performed. 2.2. Data evaluation RAW files from the MS instrument were converted to mgf files using an in-house written program. The mgf files were submitted to Mascot search (version 2.1.3, Matrix science, London, UK) in the International Protein Index (IPI) human database (74049 sequences), using the following settings: trypsin specificity, up to two missed cleavages were allowed, mass deviation for precursor ions and fragment ions were 0.02 and 0.9 Da, respectively, carbamidomethylation was chosen as fixed modification while deamidation (N,Q), oxidation (M), phosphorylation (S,T) and phosphorylation (Y) were set as variable modifications, instrument setting was ESI-FTICR and peptide/protein identifications were performed using MudPIT scoring. pTyr peptides with a Mascot score higher than 30 were extracted from Mascot to XML files. All pTyr sites suggested by Mascot were then searched in the Swiss-Prot database (http://www.expasy.org/ sprot), and sites that were not previously reported were subjected to manual verification. To pass the verification a pTyr peptide required to provide fragment ions revealing the phosphate group positioning at given tyrosine residue with a signal-to-noise ratio of ~ 3. Also, all other sequences suggested to match the MS/MS spectra were to have lower scores than that of the highest scoring pTyr peptide. A list of all identified pTyr peptides and sites, i.e. sites previously reported in Swiss-Prot and sites, that were accepted after manual verification by inspection of the corresponding MS/MS spectrum, is given in Supplementary Table 1. This list was complemented with a few pTyr proteins previously published by our group [10], but not detected in these new experiments. The corresponding MS/MS spectra of manually verified pTyr peptides are given in Supplemental data. Protein information extracted e.g. peptides assigned to a specific protein and sequence coverage for each of the 30 LC–MS analyses is given in Supplementary material, while methodological settings for each run can be found in Artemenko et al. [17]. To investigate if a pTyr site was new we have used the following sources: Goss et al. [9], Swiss-Prot (http://www.expasy.org/sprot/)
An open source tool, David GO [22] (http://david.abcc.ncifcrf.gov, version 6.7) was used for clustering of genes and proteins. Files with IPI accession numbers of all detected pTyr proteins (207 of 218 IPI accessions could be converted to David IDs) and proteins found to be new pTyr proteins (14 of 16 IPI accessions could be converted to David IDs) were loaded and subjected to gene ontology analysis for biological process (homo sapiens taxonomy, BP_3, BP_4 and BP_5 settings) and cell compartment (using CC_4 and CC_5 settings). Functional annotation clustering with medium stringency was performed using default background settings. Proteins classified into different categories of biological process by David GO were also subjected to pathway analysis using MetaCore™ (www.genego.com, GeneGo, St. Joseph, MI, USA). As datasets, proteins in the different categories in Table 2 were loaded separately and subjected sorted into “pathway maps” and “map folders” at p b 0.05 significance level based on enrichment analysis compared to a background of general protein expression. Proteins were also classified manually into groups based on information from the Swiss-Prot database. Finally, analysis of the frequencies of amino acids surrounding the pTyr sites was performed using the WebLogo tool (http://weblogo.berkeley.edu/logo.cgi) [23]. 3. Results 3.1. Aim of study The aim of our study was to comprehensively investigate the pTyr proteome. Extraction of pTyr proteins and peptides was performed by selective immunoaffinity enrichment using the complementary antibodies 4G10 and PYKD1 [17]. A flow chart is presented in Fig. 1 and our strategy included both enrichments at the protein and at the peptide levels. In total 52 immunoaffinity enrichments were combined into 30 LC–MS/MS analyses. A data base search identified 480 non-redundant pTyr peptides. Approximately 25% of the detected sites were already reported in the Swiss-Prot database. The other 75% were subjected to manual verification by inspection of the corresponding MS/MS spectra. Of the inspected pTyr sites 115 sites (30%) were accepted (assigned MS/MS spectra are supplied in Supplemental data) and considered together with the sites already reported in Swiss-Prot. In total, 294 pTyr sites belonging to 217 proteins were considered for biological pathway studies (Supplementary Table 1). 3.2. Protein sorting/clustering/pathway analysis As a first step the pTyr proteins were manually classified into categories based upon information from the Swiss-Prot database. The categories of molecular function that dominated were “kinases/ phosphatases” (23%), “adaptor/scaffold proteins” (15%), “RNA related proteins” (15%) and “structural proteins” (15%); see Fig. 2. Thereafter, the pTyr proteins were sorted by David GO into functional annotation clusters of cell compartments (Table 1). The pTyr proteins were mainly located in the cytoplasm, the cytoskeleton and in the nucleus. When sorting the pTyr proteins by David GO for biological process
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
1389
Table 1 Annotation clusters from David GO analysis of cell compartments of the studied pTyr proteins. Annotation cluster
Enrichment scorea
1. Cytoplasm Cytoplasm Cytosolic part
14.5 2.3
2. Cytoskeleton Intracellular non-membrane-bounded organelle/cytoskeleton 11.0 Cytoskeleton 5.6 Microtubule 3.8 Microtubule cytoskeleton 2.4 Actin filament 2.4 3. Nucleus Intracellular organelle/nucleus Nucleus Spindle Chromosome
6.8 4.6 2.7 2.0
4. Ribonucleoprotein complex Ribonucleoprotein complex
4.0
5. Junctions Junctions
3.1
a
Enrichment score annotates geometric mean of the p-value of each category in that cluster in minus log scale; enrichment score N2 corresponds to p b 0.01. p-value is the Fischer exact p-value of the degree of enrichment of the annotation term in the gene list compared to a background list.
Fig. 1. Flow chart of the principle for analysis and characterization of the phosphotyrosine proteome in K562 cells.
(Table 2), the highest enrichment scores were obtained for clusters related to “cellular signaling”, “cell motility and shape”, “cell cycle processes” and “RNA processing”. Proteins present in each cluster are shown in Table 2. Approximately 60% of the studied proteins were represented in a significant annotation cluster. To gain a deeper insight, proteins in each cluster group were also subjected to pathway analysis by GeneGO (Table 2 is extended with the detailed pathways from GeneGO in Supplementary Table 2). The cluster
“cellular signaling” was dominated by pathways involved in development and in immune response regulation, while the cluster of “cell motility and shape” included a number of pathways related to cell adhesion and cytoskeleton remodeling. As expected, the “cell cycle” cluster mainly contained pathways involved in cell cycle regulation. 3.3. New pTyr proteins When considering if a pTyr site had been previously identified or not, additional databases and references than Swiss-Prot were employed (see Section 2.2). When our sites were compared with databases of
Fig. 2. Distribution of identified tyrosine phosphorylated proteins within categories describing molecular function.
1390
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
phosphorylations, a pTyr site was accepted as previously known if the amino acid sequences surrounding the pTyr site matched (even though protein name not always matched).We identified 28 new pTyr sites and 15 new pTyr proteins (Table 3). Functional annotation clustering of these proteins by David GO indicated two clusters of proteins; “regulation of transcription/RNA metabolic processes” (including the PBX2, TEAD, ZIMZ2, DIDO1 and PER3 proteins) and “cellular protein metabolic processes” (including the FBXO9, MAD2L1 and VBP1 proteins). The enrichment scores for these clusters were, however, not significant (0.8 and 0.2, respectively) which was due to the low number of proteins submitted to analysis. Cellular functions of the new pTyr proteins are described in Discussion. 3.4. Frequently detected pTyr sites Table 4 describes the most frequently detected pTyr peptides and to what proteins they belong. The most frequently detected site was Y15 in CDK2/CDK3/CDC2 proteins (the sequence is matching all three proteins and from this analysis it cannot be established to which protein it actually belonged). Other commonly detected sites were Y216 in GSK3B, Y29 in EEF1A1, Y361 in HIPK2, Y182 in MAPK14 and Y438/Y426 in LCK/Yes, Y1135 in INPPL1, Y644 in BCR, Y393 in ABL1/ ABL2 and Y39 in VASP. 3.5. WebLogo analysis of amino acids flanking the pTyr sites To investigate if there is a preference for certain amino acids in regions that flank the pTyr sites, WebLogo analysis was performed. The six amino acids up- and downstream of the pTyr sites were included in the analysis. As presented in Fig. 3 no major dominance for a certain amino acid residue at a certain position was seen. A preference for a neutral amino acid, e.g. leucine (L), isoleucine (I), valine (V) or alanine (A) at the position just upstream of the pTyr site, an acidic region of glutamic acid residues (E) 3–5 amino acids residues upstream of the pTyr sites and a basic region of arginines (R) 4–6 amino acid residues downstream of the pTyr sites was indicated. 4. Discussion Studies of pTyr are important for understanding its role in pathological processes. This work is an attempt to provide a comprehensive list of validated pTyr sites and proteins in human cells and to relate the findings to processes previously associated with the pTyr modification in order to find new proteins, sites and functional categories of pTyr proteins. Our data rely on a series of analyses of immunoaffinity enriched pTyr proteins and peptides [10,17]. It is unfortunately not possible to extract a list of all known pTyr proteins from the Swiss-Prot data base for a comparison, but a measure of the comprehensiveness of this study is the cumulative number of detected pTyr peptides as a function of the number of performed LC–MS analyses as described by Artemenko et al. ([17]; see Fig. 2 in this reference). From this figure it is possible to identify important steps in the method development. Replicate runs and runs of pooled enrichments were identified as steps that improved the number of detected pTyr peptides. The fact that the number of pTyr peptides finally reached a plateau in the plot indicated that further analyses would not improve the results significantly and that this study could be considered reasonably comprehensive. After reaching this plateau we further added 14 pTyr sites, detected in our previous study of K562 cells [10]. The reason for not detecting these additional sites in the more comprehensive study by Artemenko et al. [17] might be the use of different procedures for the immunoaffinity enrichment in the two studies, providing slightly complementary results. Compared to previously published studies of pTyr in the K562 cell lines where 29 [7] and 86 [9] pTyr sites were reported, this is the most extensive study performed so far. In studies of pTyr in other cell lines as many as 400–600 sites were identified [12,14].
However, in these studies stimulations by Src-oncogene transformation or growth factors were used to enhance the level of pTyr. Enrichments are needed for detection of low abundant pTyr peptides. To separate them from competing unphosphorylated peptides in a cell lysate is required. This often leads to selection of only one peptide belonging to a specific protein. Manual validation is therefore crucial to assure quality and accuracy of the data generated by MS, e.g. accurate peptide and phosphorylation site assignment in MS/MS spectra [24]. Unfortunately, the extent of manual validation in many previous publications is often uncertain, which limits the use of such data for biological interpretation. To provide trustworthy data, we applied high-resolving MS analysis (resolution 100,000) of the peptides in the survey scans of precursor ions which provided high accuracy in the first step of the sequencing. Further, the true pTyr site was preferentially identified by an additional +79.966 Da difference in the MS/MS spectra for the tyrosine residue. Due to our stringent criteria for identification of a pTyr site (see Section 2.2), only 30% of the candidate MS/MS spectra were accepted. It is very likely that several of the inspected but not accepted pTyr sites are real. However, since the aim of our study was to provide a list of stringently validated pTyr sites we report on sites where the phosphorylation is explicitly positioned on a specific tyrosine residue. In this study, all reported pTyr sites were manually verified if not reported before in the SwissProt database. Thus the results presented here are unique. For pTyr peptides that were suggested to belong to several different proteins the multiple annotations were considered in further processing of the data. pTyr proteins are generally involved in signal transduction that most notably involves regulation of cell proliferation and differentiation, but also processes like cell metabolism, growth, mobility and survival are of importance. pTyr proteins crucial for signal initiation often possess kinase, phosphatase, phospholipase or Ras-GAP activity or belong to the adaptor protein family. These proteins facilitate the downstream interaction with other proteins, phospholipids or nucleic acids, to transfer the signals [4]. It was therefore expected that the results of the manual sorting of pTyr proteins based on the information in Swiss-Prot database (see Supplementary Table 1 and Fig. 2) revealed categories like “kinases/phosphatases” (tyrosine, serine/threonine, lipid kinases/phosphatases) and “adaptor/scaffold” proteins. On the other hand, two other categories, “RNA related” and “structural” proteins, made up a considerable part of the identified pTyr proteins. These results were unexpected. It would thus be interesting to look further into the regulation of these processes since RNA processing and structural changes are necessary to take place in fast growing cancer cells. The pTyr proteins studied were clustered by David GO analysis based on cellular localization into three dominating compartments; the cytoplasm, the cytoskeleton and the nucleus (Table 1). A fourth category, ribonucleoprotein complex, was also identified. Few pTyr proteins were assigned to the cell membrane. This was surprising since tyrosine autophosphorylation of many membrane bound tyrosine receptor kinases is a well-known phenomenon. An explanation might be that the recovery of membrane proteins was low. It is noteworthy that previous studies of pTyr proteins in K562 cells have failed to detect many of the known membrane-bound pTyr proteins [7,9]. Clustering of pTyr proteins by David GO, based on biological process (Table 2) highlighted “cellular signaling”, which can be explained by abundance of “kinases/phosphatases” and “adaptor/ scaffold” proteins as identified in the Swiss-Prot data base (Fig. 2). Other clusters with high scores were “cell motility and shape”, “cell cycle processes” and “RNA processes” and this finding agreed well with the rough sorting into categories from Swiss-Prot. “Structural” and “adaptor/scaffold” proteins were abundant in the cluster named “cell motility and shape”. This agreed with studies of mouse fibroblasts [12], where high frequencies of pTyr sites were
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
1391
Table 2 Annotation clusters from David GO analysis of biological process of the studied pTyr proteins. Annotation cluster
Enrichment scorea
Representative proteins
1. Cellular signaling Phosphorylation and intracellular signal transduction Insulin receptor signaling Cell surface receptor linked signal transduction Protein kinase cascade Growth hormone receptor signaling pathway Negative regulation of biological processes Regulation of immune response
7.8 4.3 4.2 1.9 1.8 2.1 1.5
Tyrosine protein kinases ABL1 BTK DDR1 EPHA4 FER JAK2 LCK LYN PTK2/FAK SYK TYK2 YES Tyrosine protein phosphatases PTPRA PTPN11 Serine/threonine protein kinases BCR CKDs DYRKs GSK3B HIPKs LATS MAPKs PRKCD RIPK1 Lipid kinases PI3Ks Adaptor proteins ABI1 APC CALM CD2AP CRKL DOK1
SHC1 GAB1 HGS ITGB1 NCK1 BCAR1 SORBS1 Transcription factors STAT5A Structural proteins ACTN4 CFL1 LASP1 MAP1B RNA-related proteins DDX5 EEF1A2 RBM3 GTP-ase related proteins GRLF1 ARAP1 Ubiquitin related protein PSMA2 PSMC2 TSG101 DNA-related proteins MAD2L1 SETD8 HIST1H4A
2. Cell motility and shape Cytoskeleton organization Regulation of cellular component organization Microtubule cytoskeleton organization Protein complex assembly Cell motility Regulation of cell motion Regulation of cell shape
5.8 1.9 1.8 1.7 2.4 2.0 1.4
DNA-related proteins MAD2L1 PRC1 Tyrosine protein kinases ABL1/2 EPHA4 PTK2/FAK JAK2 LYN SYK Serine/threonine protein kinases CDK5 GSK3B MAPK1 MAPK14 LATS1 Adaptor proteins ANK1 APC BCAR1 CBL CD2AP ERBB2IP GAB1/2 ITGB1 NCK1 SORBS1 Lipid kinases PIK3R1 Chaperones and heat shock related proteins HSPA4 Transcription factors AHCTF1
GTPase-related proteins ARAP1 GRLF1 RAN Structural proteins ACTB ACTG1 ACTN4 CFL1 EPB41 FLNB KRT8 LASP1 MAP1B MYH9 MYH10 PFN1 PXN TUBA1A TUBA1C VIM WASL Endosulfine family/cAMP-regulated phosphoprotein (ARPP) CAP1 RNA-related proteins UPF1 Miscellaneous proteins CALU DCTN2 PALMD PLA2G4A
3. Cell cycle process Cell cycle process
4.6
DNA related proteins MAD2L1
GTPase-related proteins ARAP1 (continued on next page)
1392
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
Table 2 (continued) Annotation cluster
Enrichment scorea
Representative proteins
3. Cell cycle process PRC1 SETD8 Adaptor proteins APC CD2AP ITGB1 Tyrosine protein kinase ABL1 TEC Serine/threonine protein kinases CDC2 CDK2 CDK3 GSK3B LATS1 MAPK12
RAN Ubiquitin related protein PSMA2 PSMC2 TSG101 Structural proteins MYH9 MYH10 Antigens MKI67 Endosulfine family/cAMP-regulated phosphoprotein (ARPP) AKAP8 Miscellaneous CALU DCTN2
4. Transport Regulation of intracellular transport Intracellular transport of proteins Regulation of glucose transport
1.4 1.4 1.3
Tyrosine protein kinases JAK2 LYN SYK Tyrosine protein phosphatases PTPN11 Serine/Threonine protein kinases CDK5 GSK3B MAPK1 Adaptor proteins CALM CBL CD2AP ERBB2IP HGS SORBS1 STAM2 Structural proteins ACTN4 CLTC KRT18 MYH9 MYH10
Lipid kinases PIK3R1 Miscellaneous PLA2G4A PTTG1IP CALU Chaperones and heat shock related proteins HSPA1 HSPA8 Ubiq CACYBP RNA-related proteins HNRNPA1 UPF1 GTPase-related proteins RAN
5. RNA processing RNA processing
2.5
RNA-related proteins CPSF6 CPSF7 DDX5 ELAVL1 HNRNPA0 HNRNPA1 HNRNPH3 HNRNPK NHP2L1
PABPC1 RBM4 RBMX SRRM2 UPF1 WBP11 Serine/threonine protein kinases PRPF4B Chaperones and heat shock related proteins HSPA1
6. Protein processing Protein folding
1.9
Chaperones and heat shock related proteins DNAJB4 HSPA4 HSPA8 VBP1 Adaptor proteins CD2AP Structural proteins ACTR10
Tyrosine protein kinases LYN RNA-related proteins CIRBP RBM3 Miscellaneous PLA2G4A
Response to heat
1.7
7. Miscellaneous Response to inorganic substance
1.5
RNA-related proteins EEF1A2 Structural proteins ACTB ACTG1 MAP1B PXN
Miscellaneous GART PLA2G4A Adaptor proteins CALM Ubiquitin related protein TFRC
a Enrichment score annotates geometric mean of the p-value of each category in that cluster in minus log scale; enrichment score N2 corresponds to p b 0.01; enrichment score N 1.3 corresponds to p b 0.05. p-value is the Fischer exact p-value of the degree of enrichment of the annotation term in the gene list compared to a background list.
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
1393
Table 3 Novel pTyr sites and pTyr proteins. Gene name
IPI accession
Protein name
Site
Peptide sequence
Other pTyr site
CALU CENPC1 CHST1 DIDO1 FBXO9 MAD2L1 PBX2 PER3 SAMD4B TEAD1 TROAP TUBA1Ba UNG VBP1 ZMIZ2 AKAP8 APC DCTN2 EEF2 HEMGN OTUD4 PPP1R13L PTPN18
IPI00014537 (IPI00789155) IPI00304885 IPI00021119 IPI00619921 IPI00296788 IPI00012369 IPI00028416 IPI00010692 IPI00470771 IPI00002901 IPI00029680 IPI00387144 IPI00011069 IPI00334159 IPI00289799 IPI00014474 IPI00012391 IPI00220503 IPI00186290 IPI00464963 IPI00399254 IPI00439948 IPI00152019
Y114 Y541 Y55 Y1700 Y111 Y199 Y316 Y1119 Y166 Y76 Y172 Y342 Y8 Y112 Y109 Y311 Y2645 Y313 Y443 Y479 Y460 Y126 Y207
WIyEDVER SEESPVySNSSVR LCEESPTFAyNLSRK ALGSAQyEDPR AVEEEQNGALyEAIK VNSMVAyKIPVND FQEEANIyAVK ILMTyQVPER SRPEPSyHSR NELIARyIK ASAyLAPR IHFPLATyAPVISAEK TLySFFSPSPAR FLLADNLyCK GYVQQGVySR QFQLyEEPDTK TLIyQMAPAVSK VHQLyETIQR EDLyLKPIQR EKPKEEPGIPAILNESHPENDVySYVLF LLyEIQNR TPLyLQPDAYGSLDR ENCAPLyDDALFLR
No No No No No No No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes
RBMXL1
IPI00061178
Y335
SDLySSCDR
Yes
RDBP SETD8 TUBA1Cb USP42
IPI00000858 IPI00288890 IPI00218343 IPI00375124
Isoform 1 of calumenin precursor Centromere protein C 1 Carbohydrate sulfotransferase 1 Isoform 4 of death-inducer obliterator 1 Isoform 1 of F-box only protein 9 Mitotic spindle assembly checkpoint protein MAD2A Pre-B-cell leukemia transcription factor 2 Period circadian protein homolog 3 SAMD4B protein Transcriptional enhancer factor TEF-1 Trophinin-associated protein Tubulin alpha-1B chain Isoform 2 of uracil-DNA glycosylase Von Hippel–Lindau binding protein 1 Isoform 2 of zinc finger MIZ domain-containing protein 2 A-kinase anchor protein 8 Isoform Long of adenomatous polyposis coli protein Dynactin 2 Elongation factor 2 Hemogen Isoform 1 of OTU domain-containing protein 4 Isoform 1 of RelA-associated inhibitor PTPN18 protein (cDNA FLJ51446, highly similar to tyrosine-protein phosphatase non-receptor type 18) RNA binding motif protein, X-linked-like 1 (kynurenine aminotransferase III isoform 3) Isoform 1 of negative elongation factor E Histone-lysine N-methyltransferase SETD8 Tubulin alpha-6 chain Ubiquitin carboxyl-terminal hydrolase 42
Y140 Y96 Y399 Y1069
SLyESFVSSSDR IySYMSPNK FDLmyAK YALyAAR
Yes Yes Yes Yes
a b
Site is previously known in the TUBA1A protein, Y272. Site previously reported for TUBA1B.
observed not only for proteins classified in the “signaling” group but also for proteins in the “adhesion/cytoskeleton” category. Goss et al. [9] showed pTyr modifications in several cytoskeleton proteins as well. As reviewed by Turner et al. [25], adaptor/scaffolding proteins are important bridging proteins for transferring growth signals into mechanisms that rearrange the cytoskeleton and alter the cell motility and shape. In the cluster “cell cycle process” the cell division kinases together with other serine/threonine kinases were predominant. Additionally, pTyr proteins implicated in e.g. structural conformation changes, like myosins, and in DNA control, MAD2L, PRC1 and SETD8, during cytokinesis were grouped to this cluster. As described in a review by Shields and Tiganis [26], previously pTyr-dependent signaling was primarily considered to be associated with the cellular response to mitogens in the G1 phase. From our results, pTyr proteins are obviously also involved in other cell cycle checkpoints. G2 progression and mitotic entry, spindle orientation and cytokinesis, are considered to be regulated by phosphotyrosine kinases and phosphatases which agrees with our findings [26]. The “RNA processing” cluster, almost exclusively containing RNArelated proteins, was especially interesting. Even though previous studies have reported on pTyr modification of DNA and RNA related proteins [13,14], this specific group of pTyr proteins has largely been overlooked. The pathway analysis from GeneGO (Supplementary Table 2) indicated that these proteins are involved in transcription and translation. In the study by Lou et al. [12], pTyr peptides from RNA related proteins were more frequent in Src-transformed cells compared to non-transformed cells. This indicates that these proteins are likely to be involved in processes related to cancer. Of the proteins found to be “RNA-related” (Supplementary Table 1), six were hnRNPs (heterogeneous nuclear ribonucleoproteins) known to complex with hnRNA and known to influence pre-mRNA processing. For the HNRNPK protein, the role of the pTyr modification has been shown to influence the protein–protein and protein–RNA interactions and
that tyrosine kinases could regulate HNRNPK upon extracellular stimuli [27]. Additional studies are needed to clarify the role of pTyr in the hnRNPs. For all functional annotation clusters, the tyrosine protein kinases ABL1, JAK2, LYN and PTK2 (or FAK), as well as the serine/threonine protein kinases MAPKs, GSK3B and CDKs appeared frequently, showing their involvement in many cellular processes. Also the transcription factor STAT5A is frequent in these clusters. As reviewed by Schlessinger, pTyr in STATs is of importance for signal transductions into the nucleus where a transcriptional program is initiated which can lead to oncogenic transformation [4]. Notably, only 60% of the identified pTyr proteins could be assigned to a annotation cluster after David GO analysis. Groups of pTyr proteins that had a high percentage of their pTyr proteins nonclustered by David GO analysis were “DNA and RNA-related proteins” and the heterogeneous group of “miscellaneous” proteins. One explanation why the residual 40% were not clustered can be that these proteins have not been considered to be involved in signaling processes and still remain to be assigned to clusters and pathways. For example, only three of the novel pTyr proteins (Table 3) were assigned to clusters when the whole list of pTyr proteins was taken into account (see Table 2). Pathway analysis by GeneGO was found to be a valuable tool to further study the pTyr proteins in different way than by David GO (see Supplementary Table 2). In general, the dominating pathway categories agreed well with the annotation clusters suggested for the same group of pTyr proteins. This was most strikingly observed for the “cell cycle process” and for the “cell motility and shape” clusters, which were dominated by pathways related to cell cycle and cell adhesion/cytoskeleton remodeling, respectively. After manual inspection of the pathways seen in the categories development, immune response, cytoskeleton remodeling, signal transduction and cell cycle it was obvious that several well-known signaling cascades and key signaling proteins were common for many pathways.
1394
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
Table 4 The most commonly identified pTyr peptides. Gene name
IPI accession
Protein name
Site
Peptide sequence
No of runsa
Comparisonb
CDK2/CDK3/CDC2
IGEGTyGVVYK
24
1, 3
Y1135 Y216 Y644 Y393/Y439
TLSEVDyAPAGPAR GEPNVSyICSR NSLETLLyKPVDR LMTGDTyTAHAGAK
21 16 16 14
4 1, 3 4 4
CDC2 CDK2/CDK3
IPI00026689 IPI00023503
Y15 Y15
IEKIGEGTyGVVYK VEKIGEGTyGVVYK
13 10
1 1, 3
EEF1A1/EEF1A2
IPI00396485/IPI00014424
Y29
STTTGHLIyK
10
2
VASP HIPK2
IPI00301058 IPI00215949
Y39 Y361
VQIyHNPTANSFR AVCSTyLQSR
10 9
4 3
MAPK14 TAGLN2 VIM VIM DOK1 LCK/YES1
IPI00002857 IPI00550363 IPI00418471 IPI00418471 IPI00015287 IPI00394952/IPI00013981
Y182 Y192 Y61 Y53 Y449 Y438/Y426
HTDDEmTGyVATR GASQAGMTGyGMPR SLYASSPGGVyATR SLyASSPGGVYATR SHNSALySQVQK LIEDNEyTAR
9 9 9 8 7 7
1, 3
CDC2 BCR HNRNPA0 ARFGAP2 HCK/LYN
IPI00026689 IPI00004497 IPI00011913 IPI00297322 IPI00029769/IPI00298625
Cell division protein kinase 2/Cell division protein kinase 3/Hypothetical protein DKFZp686L20222 Inositol polyphosphate phosphatase-like 1 Glycogen synthase kinase-3 beta Breakpoint cluster region protein Isoform IA of proto-oncogene tyrosine-protein kinase ABL1/Isoform IB of tyrosine-protein kinase ABL2 Hypothetical protein DKFZp686L20222 Cell division protein kinase 2/cell division protein kinase 3 Elongation factor 1-alpha 1/elongation factor 1-alpha 2 Vasodilator-stimulated phosphoprotein Isoform 2 of homeodomain-interacting protein kinase 2 Mitogen-activated protein kinase 14 isoform 2 Transgelin-2 Vimentin Vimentin Isoform 1 of docking protein 1 Lymphocyte-specific protein tyrosine kinase precursor (cDNA FLJ56184, highly similar to proto-oncogene tyrosine-protein kinase LCK)/proto-oncogene tyrosine-protein kinase Yes Hypothetical protein DKFZp686L20222 Breakpoint cluster region protein Heterogeneous nuclear ribonucleoprotein A0 ADP-rybosylation factor GTPase-activating protein 2. Isoform p59-HCK of Tyrosine-protein kinase HCK/LYN protein
Y15
INPPL1 GSK3B BCR ABL1/ABL2
IPI00031681/IPI00023503/ IPI00026689 IPI00016932 IPI00028570 IPI00004497 IPI00216969/IPI00329488
Y15 Y644 Y180 Y445 Y411/Y397
IGEGTyGVVYKGR NSLETLLyKPVDRVTR EDIySGGGGGGSR EVDAEyEAR VIEDNEyTAR
7 6 6 6 6
2
1 4
a
Number of LC–MS/MS run in which a specific pTyr peptide was identified. Comparisons with references; 1-pTyr peptide among the ten most frequently identified sites in non-transformed mouse fibroblast cells (Luo et al. [12]); 2-pTyr peptide among sites detected frequently in both nontransformed and Src-transformed cell populations (Luo et al. [12]); 3-pTyr peptide identified in control cell line U937 (Goss et al. [9]). 4-pTyr peptide identified only in Bcr-Abl expressing cell lines (Goss et al. [9]). b
About 10% of the identified pTyr sites were not previously reported in the literature or the phosphorylation databases. Among these, some sites belonged to proteins not previously reported to have a pTyr site, resulting in 15 pTyr proteins that were considered as novel. As mentioned before, only three of the new pTyr proteins, the CALU, MAD2L1 and VBP1 proteins, could be annotated to clusters when the whole list of pTyr proteins was considered (see Table 2). The remaining newly discovered pTyr proteins were found among the 40% of pTyr proteins that could not be assigned to clusters by David GO analysis. Notably, nine of the 15 new pTyr proteins had their location completely or partly in the cell nucleus; CENPC1, DIDO1, MAD2L1, PBX2, PER3, TEAD1, UNG, VBP1 and ZIMZ2 (full names are given in Table 3). These nuclear pTyr proteins are likely to be very scarce, but by pushing the limit of detection for pTyr peptides by repeated analyses of immunoaffinity enriched pools, they were now possible to identify. Three of the nuclear proteins were found to be transcription factors; PBX2, TEAD1 and DIDO1. The pTyr modification in these proteins might regulate their function, although it remains to be demonstrated if the modification leads to up-or downregulation. TEAD1 is known to be involved in the Hippo signaling pathway for
control of cell proliferation in mammals [28], while DIDO1 is involved in apoptosis and regarded as a tumor suppressor [29]. In 293T cells, Garcia-Domingo et al. [29] found that DIDO1 when phosphorylated on serine/threonine was predominantly localized to the cytoplasm. Upon induction of apoptosis, DIDO1 translocates to the nucleus where it appears unphosphorylated. In the same study, DIDO1 was shown by Western blotting to be tyrosine phosphorylated. However, no pTyr site was reported. PBX2 is a transcriptional activator that belongs to a family of PBX (Pre-B-cell leukemia transcription factor) proteins encoded by homeobox genes that have a generalized function in most cell types [30]. Two of the nuclear proteins are associated with cell division, i.e. CENPC1 and MAD2L1. The CENPC1 protein is important for chromosome segregation in the mitotic progression [31], while MAD2L1 prevents the transition into anaphase before all chromosomes are aligned [32,33]. Remaining novel nuclear pTyr proteins could not be grouped together. Instead they have various functions, e.g. the PER3 protein takes part in the circadian clock mechanism, the UNG protein prevents mutagenesis by eliminating uracil from DNA molecules, VPB1 functions as a chaperone and the ZIMZ2 protein interacts with nuclear hormone receptors. Left to mention are the
Fig. 3. WebLogo analysis of frequencies of amino acid surrounding the identified tyrosine phosphorylated sites. The frequency of each amino acid residue present in data set of identified tyrosine phosphorylated sites is proportional to its height.
S. Bergström Lind et al. / Cellular Signalling 23 (2011) 1387–1395
new pTyr proteins that were localized outside the nucleus, i.e. CALU (Ca-binding protein), CHST1 (a sulfotransferase), FBXO9 (ubiquitin related protein), SAMD4B (transcription signaling protein [34]), TROAP (cell adhesion complex protein) and TUBA1B (structural protein; tubulin, microtubule) which all had heterogeneous functions. Tubulin proteins with other annotations are, however, previously reported to be tyrosine phosphorylated. As discussed by Lou et al. [12], the site identification frequency cannot be used as an absolute quantitative measure but can be taken as an indicator of the relative peptide abundance in a pTyr-enriched sample. Thus, a frequently detected site can be considered to have a high abundance, since it is likely that such pTyr sites occupy a large portion of the binding sites available on the antibodies and are therefore easier to detect. According to Table 4 the most frequently detected pTyr sites were found in cell division protein kinases, and in the INPPL1, GSK3B, BCR and ABL proteins. Detection of a high number of pTyr sites in the BCR-ABL1 fusion protein kinase was expected since this fusion protein functions as a constitutively active tyrosine kinase and possesses several important docking sites for recruitment of downstream signaling actors [35]. This activity of the Bcr-Abl protein gives rise to the carcinogenic properties and functions of the K562 cells, and many of the most frequently detected pTyr sites belonged to proteins previously related to Bcr-Abl signaling, e.g. BCR, ABL1/ABL2, INPPL1 and VASP [9]. Other pTyr proteins with highly abundant sites have been found in non-transformed mouse fibroblasts [12] and in U937 cells [9], which do not express the BCR-ABL fusion protein kinase, e.g. VIM, MAPK14, HIPK2, EEF1A1, GSK3B and the cell division protein kinases. Both in this study of K562 cells and in the study by Lou et al. [12], the most frequently detected pTyr site was Y15 in the CDK2/CDK3/CDC2/CDK1 proteins (not distinguishable). This pTyr site is important for fine tuning of the cell cycle [36–38]. Also our third most commonly identified pTyr site, Y216 in GSK3B, was ranked as number two in their study [12], indicating good agreement of data. The WebLogo analysis of amino acid residues surrounding the pTyr sites failed to show a clear overrepresentation of a certain amino acid at a certain position. This agreed with the findings observed by Beausoleil et al. [39] who performed WebLogo analysis of pTyr sites in pervanadate treated Jurkat cells. The tendency for an acidic region upstream of the pTyr sites indicated in this study agrees, however, with previous observations [8,39]. The surroundings of pTyr sites seem to be less constricted compared to serine and threonine phosphorylation sites [39,40]. 5. Conclusions To conclude, the aim of this study, to perform a comprehensive characterization of pTyr proteins, was fulfilled by categorizing and analyzing a stringently verified set of proteins with pTyr modification by different bioinformatic tools. In this way, new categories, e.g. RNA related pTyr proteins, new pTyr proteins, of which many were found in the nucleus and new sites of this posttranslational modification could be identified. Overall, this study provides an overview of groups of pTyr proteins that can be of importance for future functional studies. Our long term aim is to use knowledge of the pTyr proteome to search for “signatures” of tyrosine phosphorylation in different tumor cells. Such signatures ought to reflect differences among the perturbed signaling pathways and thus facility subclassification of tumors. Supplementary materials related to this article can be found online at doi:10.1016/j.cellsig.2011.03.021.
1395
Acknowledgments The Sloan Kettering Institute for Cancer Research is acknowledged as the provider of the PYKD1 antibody. We would also like to thank docent Jonas Åström and M.Sc. Martin Dahlö for valuable assistance. This work was supported by the Kjell and Märta Beijer Foundation (U.P.) and the Swedish Research Council (U.P. and J.B.). S.B.L. has a post-doc position from the Swedish Cancer Society. References [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] [35] [36] [37] [38] [39] [40]
D. Hanahan, R.A. Weinberg, Cell 100 (2000) 57–70. K.S. Kolibaba, B.J. Druker, Biochim. Biophys. Acta 1333 (1997) F217–F248. A. Levitzki, Pharmacol. Ther. 82 (1999) 231–239. J. Schlessinger, Cell 103 (2000) 211–225. T. Hunter, B.M. Sefton, Proc. Natl Acad. Sci. U.S.A. 77 (1980) 1311–1315. J.V. Olsen, B. Blagoev, F. Gnad, B. Macek, C. Kumar, P. Mortensen, M. Mann, Cell 127 (2006) 635–648. A.R. Salomon, S.B. Ficarro, L.M. Brill, A. Brinker, Q.T. Phung, C. Ericson, K. Sauer, A. Brock, D.M. Horn, P.G. Schultz, E.C. Peters, Proc. Natl Acad. Sci. U.S.A. 100 (2003) 443–448. J. Rush, A. Moritz, K.A. Lee, A. Guo, V.L. Goss, E.J. Spek, H. Zhang, X.M. Zha, R.D. Polakiewicz, M.J. Comb, Nat. Biotechnol. 23 (2005) 94–101. V.L. Goss, K.A. Lee, A. Moritz, J. Nardone, E.J. Spek, J. MacNeill, J. Rush, M.J. Comb, R.D. Polakiewicz, Blood 107 (2006) 4888–4897. S. Bergstrom Lind, M. Molin, M.M. Savitski, L. Emilsson, J. Astrom, L. Hedberg, C. Adams, M.L. Nielsen, A. Engstrom, L. Elfineh, E. Andersson, R.A. Zubarev, U. Pettersson, J. Proteome Res. 7 (2008) 2897–2910. R. Chopra, Q.Q. Pu, A.G. Elefanty, Blood Rev. 13 (1999) 211–229. W. Luo, R.J. Slebos, S. Hill, M. Li, J. Brabek, R. Amanchy, R. Chaerkady, A. Pandey, A.J. Ham, S.K. Hanks, J. Proteome Res. 7 (2008) 3447–3460. R. Amanchy, J. Zhong, H. Molina, R. Chaerkady, A. Iwahori, D.E. Kalume, M. Gronborg, J. Joore, L. Cope, A. Pandey, J. Proteome Res. 7 (2008) 3900–3910. T.H. Heibeck, S.J. Ding, L.K. Opresko, R. Zhao, A.A. Schepmoes, F. Yang, A.V. Tolmachev, M.E. Monroe, D.G. Camp II, R.D. Smith, H.S. Wiley, W.J. Qian, J. Proteome Res. 8 (2009) 3852–3861. P.J. Boersema, L.Y. Foong, V.M. Ding, S. Lemeer, B. van Breukelen, R. Philp, J. Boekhorst, B. Snel, J. den Hertog, A.B. Choo, A.J. Heck, Mol. Cell. Proteomics 9 (2010) 84–99. C. Jorgensen, A. Sherman, G.I. Chen, A. Pasculescu, A. Poliakov, M. Hsiung, B. Larsen, D.G. Wilkinson, R. Linding, T. Pawson, Science 326 (2009) 1502–1509. K. Artemenko, S. Bergstrom Lind, L. Elfineh, C. Mayrhofer, R.A. Zubarev, J. Bergquist, U. Pettersson, Analyst 136 (2011) 1971–1978. N. Farriol-Mathis, J.S. Garavelli, B. Boeckmann, S. Duvaud, E. Gasteiger, A. Gateau, A.L. Veuthey, A. Bairoch, Proteomics 4 (2004) 1537–1550. F. Diella, C.M. Gould, C. Chica, A. Via, T.J. Gibson, Nucleic Acids Res. 36 (2008) D240–D2448 (Database issue). F. Gnad, S. Ren, J. Cox, J.V. Olsen, B. Macek, M. Oroshi, M. Mann, Genome Biol. 8 (2007) R250. P.V. Hornbeck, I. Chabra, J.M. Kornhauser, E. Skrzypek, B. Zhang, Proteomics 4 (2004) 1551–1561. W. Huang da, B.T. Sherman, R.A. Lempicki, Nat. Protoc. 4 (2009) 44–57. G.E. Crooks, G. Hon, J.M. Chandonia, S.E. Brenner, Genome Res. 14 (2004) 1188–1190. A.M. Nichols, F.M. White, Methods Mol. Biol. 492 (2009) 143–160. C.E. Turner, Nat. Cell Biol. 2 (2000) E231–E236. B.J. Shields, T. Tiganis, Cell Cycle 8 (2009) 223–230. J. Ostrowski, D.S. Schullery, O.N. Denisenko, Y. Higaki, J. Watts, R. Aebersold, L. Stempka, M. Gschwendt, K. Bomsztyk, J. Biol. Chem. 275 (2000) 3619–3628. M. Ota, H. Sasaki, Development 135 (2008) 4059–4069. D. Garcia-Domingo, D. Ramirez, G. Gonzalez de Buitrago, A.C. Martinez, Mol. Cell. Biol. 23 (2003) 3216–3225. K. Monica, N. Galili, J. Nourse, D. Saltman, M.L. Cleary, Mol. Cell. Biol. 11 (1991) 6149–6157. Y. Xie, H.H. Heng, Cytogenet. Cell Genet. 74 (3) (1996) 192–193. X. Li, R.B. Nicklas, Nature 373 (1995) 630–632. Y. Li, R. Benezra, Science 274 (1996) 246–248. N. Luo, G. Li, Y. Li, X. Fan, Y. Wang, X. Ye, X. Mo, J. Zhou, W. Yuan, M. Tan, H. Xie, K. Ocorr, R. Bodmer, Y. Deng, X. Wu, BMB Rep. 43 (2010) 355–361. A. Quintas-Cardama, J. Cortes, Blood 113 (2009) 1619–1630. K.L. Gould, P. Nurse, Nature 342 (1989) 39–45. T.A. Potapova, J.R. Daum, K.S. Byrd, G.J. Gorbsky, Mol. Biol. Cell 20 (2009) 1737–1748. V.T. George, G. Brooks, T.C. Humphrey, Mol. Biol. Cell 18 (2007) 4168–4179. S.A. Beausoleil, J. Villen, S.A. Gerber, J. Rush, S.P. Gygi, Nat. Biotechnol. 24 (2006) 1285–1292. M. Salvi, L. Cesaro, L.A. Pinna, BioMol. Concepts 1 (2010) 185–196.