Published online before print May 1, 2008, doi: 10.1161/ATVBAHA.107.161000
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© 2008 American Heart Association, Inc.
Cell Biology and Signaling |
Platelet Protein Interactions
Map, Signaling Components, and Phosphorylation Groundstate
From the Department of Bioinformatics (M.D., T.D.), Biocenter, University of Würzburg; the Institut fuer Klinische Biochemie & Pathobiochemie (M.D., I.B., S.M., U.W.), Würzburg; Rudolf Virchow Center (A.S.), Würzburg; and EMBL (T.D.), Heidelberg, Germany.
Correspondence to Thomas Dandekar, Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, Würzburg, D-97074 Germany. E-mail dandekar{at}biozentrum.uni-wuerzburg.de
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Abstract |
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Objectives— Assembly of a comprehensive proteome and transcriptome database of human platelets, derivation of a model of the platelet-specific interactome, and generation of a functional interaction map of platelet phosphorylations and kinases.
Methods and Results— Interactions are derived from literature-curated data from HPRD and yeast two hybrid (Y2H) and mapped to platelet-specific expression data (SAGE or proteome). From this a cell-type specific model of platelet proteins and protein–protein interactions is derived. The obtained inventory of platelet-specific proteins includes key domains, protein GO annotations, and receptors. Collected interactions point to new platelet signaling components, actin remodeling processes, and pharmacological targets and offer incentives for further studies (eg, on the IPP complex). Integration of platelet-specific phosphoproteins and the characterization of the platelet kinase repertoire sketch a first outline of kinase signaling in human platelets.
Conclusions— A first view of the platelet interactome, platelet phosphorylation, and platelet kinome is available from the in silico data.
Key Words: platelet • interactome • network • signaling pathway • phosphoproteome
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Introduction |
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The small anuclear platelets are central for hemostasis and involved in the pathophysiology of several cardiovascular diseases as well as inflammatory processes and metastasis. Data on the platelet and its proteome are accumulating at an unprecedented speed. This includes mass spectrometry techniques1–6 and census of the platelet transcriptome,7–9 protein–protein interactions based on literature mining,10 and systematic yeast two hybrid (Y2H) assays.11,12 This opens the attractive possibility to create a "virtual platelet:" an in silico model of the complete platelet and all its interactions. Such a "virtual platelet" would model the platelet and its interactions in more detail and allows to pinpoint biological functions, interactions, drug targets, and all pathophysiological processes mentioned above in molecular detail.13 As a first step toward this goal, we show that a cell-specific model of the human platelet interactome can be derived by mapping various platelet-specific protein expression data on interaction data sets available so far. Protein and mRNA expression data are platelet-specific, whereas interaction data has been inferred from various human cell types. These predict analogous interactions for the platelet, eg, for the assembly in the IPP (ILK, PINCH, Parvin) subnetwork as shown using immunoprecipitation and Western blot. Furthermore we extend our interactome model by incorporating data concerning the platelet phosphoproteome14 and complement this by the characterization of the platelet protein kinase repertoire (kinome). Additionally this integrated network model puts protein phosphorylations in the context of interacting protein kinases and thus generates a new perspective on the kinase signaling network in human platelets. We systematically analyze the collected platelet proteins and interactions including predicted key interactors, the resulting platelet kinase network, and known as well as predicted new receptors.
See accompanying article on page 1214
The complete data on the platelet proteome, interactome, and phosphorylation state used in this study is available online at the "PlateletWeb–Knowledgebase" (http://plateletweb.bioapps.biozentrum.uni-wuerzburg.de), where all interacting proteins are hyperlinked allowing an easy navigation through the platelet interactome network.
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Materials and Methods |
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Proteome and Network Assembly
A comprehensive database of platelet proteins was compiled (2934 different gene products in total; Figure 1): We collected proteins from proteome studies on platelets1–6 as well as by extracting proteins, from the curated databases HPRD (Human Proteome Reference Database),10 UniProtKB/Swiss-Prot,15 and the Entrez Gene Database.16 Additionally protein predictions from 1964 transcripts identified in recent SAGE analysis of human platelets7 were integrated into the collection as well as a set of 297 proteins reported to be phosphorylated in resting platelets.14 Protein interaction data were acquired from NCBI EntrezGene database16 (based on literature curated HPRD dataset), and from 2 large scale Y2H screens on human proteins12,11 to derive a generic human interactome network. Platelet proteins from our database were mapped to this interactome map to construct a platelet-specific interactome model. Statistical analysis was performed using R (http://www.R-project.org) based on algorithms and data structures of the Bioconductor package.17
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Experimental Methods
This study was performed in accordance with the Declaration of Helsinki and was approved by our local medical ethics committee. Whole blood was collected from healthy donors who did not take any antiplatelet drugs during the two weeks prior to blood donation. Further details on Materials and Methods can be found in the online supplementary available at http://atvb.ahajournals.org.
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Results |
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Human Proteins Expressed in the Platelet
To establish a comprehensive database of the platelet proteome (Figure 1) we collected data from large scale proteome studies of platelets1–6 and combined them with protein data from well annotated databases10,15 as well as with protein predictions from 1964 different transcripts from a recent platelet transcriptome study.7 Although the expression of a protein in platelets cannot be inferred from the presence of its transcript alone, the SAGE data are still a good indicator for platelet proteins that have not been directly measured in the platelet so far. Inclusion of the transcriptome enhances the data basis. Together, these data allowed the detection of novel interaction partners in the platelet network derived from this data. The database obtained finally comprises 3093 different platelet-expressed gene products.
Analysis of this platelet-specific proteome database revealed only a small overlap of 419 (13.5%) gene products between the SAGE-derived and proteome-derived dataset, indicating the rather complementary nature of these 2 techniques. The complete EntrezGene inventory consists of 33 017 human genes, and according to our database at least 9.4% of all known gene products have been identified in the platelet so far. The coverage may be even higher, as there are lower estimates on the total of human protein coding genes (
22 000 according to the current Ensembl gene catalogue, release 43) and still an unknown number of platelet proteins that have not been detected yet.
Protein–Protein Interactions of the Platelet
Mapping the data of our platelet proteome database to the known human interaction data we derived a model for the platelet-specific interactome comprising 1932 protein nodes and 2851 interaction edges (Table). This platelet interactome map covers 23.4% of the human interactome (nodes) as given by the entire set of proteins in the interaction data. Comparing the derived platelet interactome with the complete human interactome, 11.3% of all known human protein–protein interactions (edges) are found in the platelet interactome so far. Altogether 85% of the interactions in the platelet interactome map are based on these literature-curated datasets, and only 15% are derived from Y2H screens.11,12 We find a highly connected central component in the platelet interactome and a topology similar to that of the entire human interactome including maximal path length (both networks 15), characteristic path length (platelet: 5.0; interactome: 4.6; Table). To assess the information contained in our data set we compared our platelet network to 10 000 random networks of equal size. None of these comes even close to the platelet network in terms of connectivity and size of the central component (supplemental Figure I, available online at http://atvb.ahajournals.org). Comparing the connectivity of each protein in the platelet network with that in the complete interactome network (supplemental Figure II) we find a significantly (P<0.05) higher connectivity in the platelet for proteins with functions in the reorganization of the cellular actin cytoskeleton such as Gelsolin, WASP, and integrin linked kinase (ILK), pointing to a rather central role in the platelet.
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The platelet interactome delineates the components of any subnetwork of interest and provides a basis for further experimental investigation of specific interaction modules.
Here we analyze the subnetwork around the IPP complex (Figure 2A, supplemental Table IX). This complex forms an interface between the integrin signaling and the actin cytoskeleton18 and has been described recently as critical regulator in the heart.19 This predicted subnetwork around the IPP complex was next analyzed experimentally. First, we verified the presence of key components of the IPP complex in highly purified platelets by Western blot analysis20 (data not shown). Subsequently, using immunoprecipitation with both ILK and PINCH antibodies, we detected an endogenous interaction between those 2 proteins in nonstimulated as well as in TRAP- and ADP-stimulated platelets (Figure 2B). Functional integrity and capacity of platelet membrane receptors was analyzed by platelet receptor-regulated VASP phosphorylation21 (Figure 2C).
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Hub Proteins, Interaction Domains, and Platelet Receptors
Our platelet database allows a more complete characterization of the platelet proteome including transmembrane proteins, receptors and kinases (supplemental Tables I and IV through VII). The domain composition of the platelet proteome reveals an enrichment of proteins involved in reorganization of the cytoskeleton and signal transduction (supplemental Tables II and III), among them proteins with tyrosine kinase domains, reflecting the importance of kinases for platelet signaling. This is further supported by the analysis of platelet hub proteins (proteins with a high number of interaction partners; supplemental Table VIII). Apart from highly connected adaptor proteins (eg, Grb2) we find many nonreceptor tyrosine kinases (eg, Fyn, Src, Syk, Lyn) participating in the highly connected kinase signaling network. A more detailed description of these results can be found in the online data supplement.
Platelet Kinases and Phosphorylation Ground State
Our interactome model provides an extensible platform for the integration of further information on function or posttranslational protein modification such as phosphorylations. Using a recently published set of platelet phosphorylation sites14 we derive a set of 297 platelet phosphoproteins. 227 could be mapped on the platelet network; for the others no interaction partners in the platelet have been described so far. Furthermore, we used a comprehensive inventory of the human kinome22 (comprising a total of 518 kinases) to characterize a repertoire of 127 platelet kinases using sequence analysis, among them 90 serine-threonine kinases, 31 tyrosine kinases, 5 kinases of dual specificity, and 1 of undefined specificity (supplemental Table VII). Our in silico interactome now allows us to integrate the phosphorylated proteins and the kinases into a common interaction context. Figure 3 shows the distribution of kinases (red) and phosphoproteins (yellow) as well as phoshorylated kinases (blue) in the platelet interactome revealing that the ground state of the platelet14 already contains a considerable amount of phosphorylated proteins (data from nonactivated platelets). A clustering of kinases and phosphoproteins around the highly connected tyrosine kinases can be observed and underlines the strong regulatory potential of these kinases. We then dissected the network into a tyrosine-specific kinase-phosphorylation map containing only interacting tyrosine phosphoproteins and tyrosine kinases as well as a serine/threonine-specific map. Focusing on tyrosine phosphorylation we extract a densely connected subnetwork (Figure 3B, supplemental Table X). Although not all these interactions denote phosphorylation reactions the analysis of phosphorylations in the context of interacting kinases can help to obtain a better understanding of particular phosphorylations. For instance, the adhesion molecule CD226 (DNAM-1) is tyrosinephosphorylated in platelets on stimulation.23 Figure 3 shows tyrosine kinase Fyn with direct neighborhood to CD226. Indeed Fyn has been reported for this phosphorylation of CD226 at position Y322 in transfected cell lines.24 Prominent platelet tyrosine kinases like Fyn, Src, Syk, or Lyn emerge in central positions of this network because they are important hubs in the interactome network (supplemental Table VIII); most of them are already phosphorylated in resting platelets. This first map of platelet phosphorylations now allows the exploration of specific pathways in more detail. Data, predictions, and interactions are available online in our PlateletWeb knowledge base, which makes it possible to navigate through the platelet interactome.
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Discussion |
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A View of Proteins in the Context of Their Interactions
A recent study presented a functional atlas of the integrin adhesome by constructing a generic interaction network of integrin associated proteins.25 Here, we establish for the first time a comprehensive platelet proteome database and a model of the platelet interactome (Figure 1; Materials and Methods). Evidence for protein expression relies on data from a number of published proteome studies,1–6 as well as a SAGE analysis of the platelet transcriptome recently performed by our group.7 We integrated protein–protein interaction data from a wide range of cell types as obtained from the literature-curated database HPRD10 and 2 recent large-scale Y2H screens of the human proteome.11,12
Because our platelet database assembles data from multiple studies a combined analysis in the broader sense of a meta-analysis becomes possible as shown here for the data aggregation on the basis GO-terms and domain frequencies. Furthermore this allows us to collate more comprehensive inventories of various interesting protein classes such as transmembrane proteins and established as well as predicted receptors. Analysis of subnetworks around candidate proteins can reveal new cross-links between classical pathways.
It must be kept in mind that the data has been combined from a variety of heterogeneous data sources. Concerning evidence for platelet expression, different mass spectrometry technologies and methods of sample preparation (eg, 2-DE, high-performance liquid chromatography [HPLC]) or prefractionation surely will have an influence on the data quality and the resulting protein spectrum detected in each study.5 For instance the generation of a virtual leukocyte-free platelet preparation is an important prerequisite not only for transcriptome but also for proteome analyses.20 Our SAGE data used in this study included specific precautions against contamination,7 whereas not all proteome studies measure and report the number of residual white blood cells in the sample. However, the impact of leukocyte contamination on proteome studies is less severe.20
The combination of data acquired by a broad spectrum of diverse technologies also has advantages, because they see and provide complementary information on the proteome expressed in platelets. This specifically relates to the integration of proteomic and transcriptomic data—a detailed analysis shows that these very different approaches overlap only little (13% of platelet proteins). This effect may be attributed to the different technologies and their different resolutions and also to the variable and still not fully understood effect of protein synthesis in platelets.7
In contrast to the proteome and transcriptome data which directly evidence platelet expression, interaction data are not platelet-specific, but has been inferred from observed interactions in a variety of human cell types. We assess the expert-curated HPRD10 interactions (80% of the interactions) to be of higher quality than the Y2H data (15% of the interactions) and therefore explicitly indicate interactions derived from the Y2H data in our web resource. A general scoring in terms of reliability or functional relevance, however, is difficult because of the heterogeneity of the included studies and will always depend on the particular question of research. Therefore, the user is advised to judge and weigh specific information provided by our resource, as all interactions provided are documented in the literature. As always the case with bioinformatical data they help to target experimental research as ultimate proof of predicted interactions and functions.
The obtained model can be viewed as a first draft of the platelet interactome. Our primary aim has been to maximize the data basis and integrate as much useful information as available to date. However, the coverage of the platelet proteome and human interactome26 is not yet complete and new proteomic studies are collecting more data.27 Thus the current version of our resource is work in progress and future efforts will incorporate novel interaction data and platelet proteins.
An Interactome for Signaling and Reshaping the Platelet
The importance of actin organization and intracellular signaling is stressed by the fact that proteins with a particular high connectivity (platelet-specific "hubs") are often involved in the remodeling of the actin cytoskeleton (supplemental Figure I). Similarly, the importance of certain signaling pathways is reflected by the overrepresentation of domains participating in Ca2+-signaling (EF-Hand domain), G-protein signaling (G-alpha domain), and tyrosine phosphorylation (tyrosine kinase domain) in the platelet proteome (supplemental Tables II and III). Nevertheless, it must be kept in mind that the spectrum of platelet domain frequencies has been compared against the complete set of proteins in the UniProt database. Comparing the platelet proteome to that of other specific cell types would certainly be of interest because it could reveal platelet specific differences. However, because of the large variety of the data sources that contribute to the platelet proteome database, no comparable dataset of other cells types is available to date and a comparison of heterogeneous data sources will probably not accurately reflect biological differences.
Experimental Investigation of Structures and Interactions in Subnetworks
The IPP complex and its network (Figure 2a) are involved in cytoskeleton organization18 and play an important role in heart and smooth muscle cells.19,28 Our in silico network predicts the presence of diverse signaling proteins in the direct neighborhood of the core complex in human platelets (Figure 2a). In human platelets the activation-dependent association of ILK with β3-integrin has been reported29,30 whereas β-Parvin interacts with ILK also in unstimulated platelets.30 Consistent with these data, we find an association of PINCH with ILK in resting as well as in activated platelets. It is much more difficult to understand the specific contribution of this complex to integrin function in platelets as opposed to other cells. Nevertheless, our data suggest the existence of a preassembled ternary IPP-complex in resting platelets, translocating to the site of integrin activation on stimulation. Our observations indicate that ADP-receptor and Gi/Gq protein–mediated pathways have no effect on the assembly of the IPP complex. However, the role of other platelet activating pathways and in particular protein tyrosine kinase pathways in platelet IPP signaling should be investigated in future studies.
Platelet Phosphoproteome and Kinome
Platelet signaling is a key to understand and control platelet activation under clinical conditions. Our in silico model now shows phosphorylations of unstimulated platelets and kinases together in a protein–protein interaction network. Literature search often reveals that for a specific interaction a phosphorylation reaction has been described in other cells, suggesting and predicting that the same mechanism may be responsible for the observed platelet phosphorylation. The interactome map can therefore serve as an outline to detect novel platelet-specific signaling events that can subsequently be investigated experimentally. For instance Src and Syk (Figure 3), as effectors in ITAM-associated (immunoreceptor tyrosine-based activation motif) signaling has come into the focus of platelet research.31 ITAMs are short protein sequence motifs with 2 tyrosine residues that are phosphorylated by Src-family kinases32 leading to the recruitment and activation of Syk. ITAMs were initially identified as integral parts of classical immunoreceptors but meanwhile several ITAMs-containing and ITAM-coupled receptors (GPVI-FcRg, GPIb-IX-V, FcgRIIa) have been described in platelets31 including the induction of integrin 
IIbβ3 via collagen-GPVI-FcRg33,34 or via vWFGPIb-IX-V.35 All platelet-predicted interactions of Src and Syk as effectors in ITAM-associated platelet signaling can now be examined in detail including further downstream signaling. This includes for instance ADAP (Fyb; see Figure 3B), a substrate of Src which provides an important link between von Willebrand factor (vWF) signaling and IIbβ3 activation.35
Conclusions
We present here for the first time a comprehensive compilation and analysis of the platelet-specific interactome, integrating data from a large number of sources and evidence types. As an application we complement this analysis by experimentally investigating specific interactions in the IPP subnetwork. Integration of phosphoproteome data of resting platelets and characterization of the platelet kinome derives a first draft of the platelet kinase signaling map on a large-scale basis. A comprehensive internet-based resource makes this information available to all platelet researchers. Our network lays the foundation for the construction of more complex models by integration of novel data.36 We expect intriguing new insights from the investigation of specifically activated or inhibited platelets. This would allow the investigation of specific phosphorylation subnetworks and differential regulation of signaling cascades in human platelets. The PlateletWeb resource is intended to be further developed into a comprehensive knowledge base ("virtual platelet") for platelet systems biology.
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Acknowledgments |
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The authors thank Dr T. Jarchau for critical discussion of the manuscript and N. Günther for technical assistance.
Sources of Funding
This study was supported by the German Research Foundation (SFB 688, TPA2). A fellowship support (to M.D.) by the Würzburg University (IZKF) and the Scherer foundation is gratefully acknowledged.
Disclosures
None.
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Footnotes |
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M.D. and I.B. contributed equally to this study.
Original received December 12, 2007; final version accepted April 18, 2008.
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