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Systems biology looks for emergent system effects from large scale assemblies of molecules and data, for instance in the human platelets. However, the computational efforts in all steps before such insights are possible can hardly be under estimated. In practice this involves numerous programming tasks, the establishment of new database systems but as well their maintenance, curation and data validation. Furthermore, network insights are only possible if strong algorithms decipher the interactions, decoding the hidden system effects. This thesis and my work are all about these challenges. To answer this requirement, an integrated platelet network, PlateletWeb, was assembled from different sources and further analyzed for signaling in a systems biological manner including multilevel data integration and visualization. PlateletWeb is an integrated network database and was established by combining the data from recent platelet proteome and transcriptome (SAGE) studies. The information on protein-protein interactions and kinase-substrate relationships extracted from bioinformatical databases as well as published literature were added to this resource. Moreover, the mass spectrometry-based platelet phosphoproteome was combined with site-specific phosphorylation/ dephosphorylation information and then enhanced with data from Phosphosite and complemented by bioinformatical sequence analysis for site-specific kinase predictions. The number of catalogued platelet proteins was increased by over 80% as compared to the previous version. The integration of annotations on kinases, protein domains, transmembrane regions, Gene Ontology, disease associations and drug targets provides ample functional tools for platelet signaling analysis. The PlateletWeb resource provides a novel systems biological workbench for the analysis of platelet signaling in the functional context of protein networks. By comprehensive exploration, over 15000 phosphorylation sites were found, out of which 2500 have the corresponding kinase associations. The network motifs were also investigated in this anucleate cell and characterize signaling modules based on integrated information on phosphorylation and protein-protein interactions. Furthermore, many algorithmic approaches have been introduced, including an exact approach (heinz) based on integer linear programming. At the same time, the concept of semantic similarities between two genes using Gene Ontology (GO) annotations has become an important basis for many analytical approaches in bioinformatics. Assuming that a higher number of semantically similar gene functional annotations reflect biologically more relevant interactions, an edge score was devised for functional network analysis. Bringing these two approaches together, the edge score, based on the GO similarity, and the node score, based on the expression of the proteins in the analyzed cell type (e.g. data from proteomic studies), the functional module as a maximum-scoring sub network in large protein-protein interaction networks was identified. This method was applied to various proteome datasets (different types of blood cells, embryonic stem cells) to identify protein modules that functionally characterize the respective cell type. This scalable method allows a smooth integration of data from various sources and retrieves biologically relevant signaling modules.
Platelets are crucial to inhibit extensive blood loss at sites of vascular injury. However, under pathological conditions such as rupture of an atherosclerotic plaque, activated platelets form aggregates that may occlude the vessel. This can lead to heart attack and stroke. Various and complex signaling pathways in the cell are involved in the steps of platelet adhesion, activation and aggregation. Single aspects of these processes were studied in three different subprojects in this work. The Glycoprotein (GP) Ib-V-IX complex is responsible for the first contact of platelets with the vessel wall. Subsequently, GPVI can bind to collagen of the subendothelium, which initiates a signaling cascade leading to platelet activation, aggregation, characterized by integrin activation and granule secretion and platelet procoagulant activity. The latter is characterized by exposed phosphatidylserine (PS) on the platelet surface, which enhances thrombin generation and thereby the coagulation cascade. A controlled regulation of GP receptors on the platelet surface is vital for an intact response of the cell to platelet agonists. In the first subproject described here the regulation of GPV and GPVI on mouse platelets was investigated and it was found that both receptors are shed from the platelet surface in a metalloproteinase dependent manner. However, GPVI is shed upon mitochondrial injury, while GPV cleavage could be observed upon platelet stimulation. The metalloproteinase responsible for GPVI shedding remains unknown whereas the metallproteinase that sheds GPV was identified in this work as being ADAM17. This shows that the expression of both receptors underlies a controlled mechanism regulated through distinct metalloproteinases. In the second subproject the role of protein kinase C (PKC) in platelet activation and procoagulant response was investigated using PKC specific inhibitors. It was found that PKC blockage reduced platelet activation but enhanced platelet procoagulant activity. This is the first time that a dual role in platelet activation and procoagulant activity is defined for PKC. In the third project the role of the small GTPase Rac1 in platelet signaling was studied using conditional Rac1 knock out mice. It is reported here that Rac1 lies downstream of GPVI and is involved in integrin activation and cytsolic Ca2+ changes in vitro and platelet adhesion and thrombus formation in vivo. This is the first time that Rac1 is demonstrated to have a pivotal role in GPVI signaling and furthermore points to a novel, unknown pathway downstream of GPVI.