A human MAP kinase interactome

Mitogen-activated protein kinase (MAPK) pathways form the backbone of signal transduction in the mammalian cell. Here we applied a systematic experimental and computational approach to map 2,269 interactions between human MAPK-related proteins and other cellular machinery and to assemble these data into functional modules. Multiple lines of evidence including conservation with yeast supported a core network of 641 interactions. Using small interfering RNA knockdowns, we observed that approximately one-third of MAPK-interacting proteins modulated MAPK-mediated signaling. We uncovered the Na-H exchanger NHE1 as a potential MAPK scaffold, found links between HSP90 chaperones and MAPK pathways and identified MUC12 as the human analog to the yeast signaling mucin Msb2. This study makes available a large resource of MAPK interactions and clone libraries, and it illustrates a methodology for probing signaling networks based on functional refinement of experimentally derived protein-interaction maps.     

A skeleton of the human protein interactome

In this issue of Cell, Wanker and colleagues (Stelzl et al., 2005) present a large-scale two-hybrid map of more than 3000 putative human protein-protein interactions. These new data will serve as an important source of information regarding individual protein partners and offer preliminary insight into the global molecular organization of human cells.     

Mapping the human protein interactome

Interactions are the essence of all biomolecules because they cannot fulfill their roles without interacting with other molecules. Hence, mapping the interactions of biomolecules can be useful for understanding their roles and functions. Furthermore, the development of molecular based systems biology requires an understanding of the biomolecular interactions. In recent years, the mapping of protein-protein interactions in different species has been reported, but few reports have focused on the large-scale mapping of protein-protein interactions in human. Here, we review the developments in protein interaction mapping and we discuss issues and strategies for the mapping of the human protein interactome.     

Bioinformatics in the human interactome project

‘In the early days of the Human Interactome Project, ameeting was organized...’. Perhaps, a few years from now,newspapers will describe in those terms how straightforwardit was to plan the large-scale mapping of protein interactionsin human and other model organisms. Scientists attending thesecond Cold Spring Harbor Laboratory/Wellcome Trust symposiumon ‘Interactome Networks’¹ know well that thingsare not that easy. Important scientific, technical and sociologicalissues remain before the ‘Human Interactome Project’can be considered on its way. But things     

A proteomic snapshot of the human heat shock protein 90 interactome

Heat shock protein 90 (Hsp90) is a molecular chaperone which modulates several signalling pathways within a cell. By applying co-immunoprecipitation with endogeneous Hsp90, we were able to identify 39 novel protein interaction partners of this chaperone in human embryonic kidney cells (HEK293). Interestingly, levels of DNA-activated protein kinase catalytic subunit, an Hsp90 interaction partner found in this study, were found to be sensitive to Hsp90 inhibitor treatment only in HeLa cells but not in HEK293 cells referring to the tumorgenicity of this chaperone.     

An atomic model for the human septin hexamer by cryo-EM

In order to form functional filaments, human septins must assemble into hetero-oligomeric rod-like particles which polymerize end-to-end. The rules governing the assembly of these particles and the subsequent filaments are incompletely understood. Although crystallographic approaches have been successful in studying the separate components of the system, there has been difficulty in obtaining high resolution structures of the full particle. Here we report a first cryo-EM structure for a hexameric rod composed of human septins 2, 6 and 7 with a global resolution of ~3.6 Å and a local resolution of between ~3.0 Å and ~5.0 Å. By fitting the previously determined high-resolution crystal structures of the component subunits into the cryo-EM map, we are able to provide an essentially complete model for the particle. This exposes SEPT2 NC-interfaces at the termini of the hexamer and leaves internal cavities between the SEPT6-SEPT7 pairs. The floor of the cavity is formed by the two α₀ helices including their polybasic regions. These are locked into place between the two subunits by interactions made with the α₅ and α₆ helices of the neighbouring monomer together with its polyacidic region. The cavity may serve to provide space allowing the subunits to move with respect to one another. The elongated particle shows a tendency to bend at its centre where two copies of SEPT7 form a homodimeric G-interface. Such bending is almost certainly related to the ability of septin filaments to recognize and even induce membrane curvature.     

Global topological features of cancer proteins in the human interactome

MOTIVATION: The study of interactomes, or networks of protein-protein interactions, is increasingly providing valuable information on biological systems. Here we report a study of cancer proteins in an extensive human protein-protein interaction network constructed by computational methods. RESULTS: We show that human proteins translated from known cancer genes exhibit a network topology that is different from that of proteins not documented as being mutated in cancer. In particular, cancer proteins show an increase in the number of proteins they interact with. They also appear to participate in central hubs rather than peripheral ones, mirroring their greater centrality and participation in networks that form the backbone of the proteome. Moreover, we show that cancer proteins contain a high ratio of highly promiscuous structural domains, i.e., domains with a high propensity for mediating protein interactions. These observations indicate an underlying evolutionary distinction between the two groups of proteins, reflecting the central roles of proteins, whose mutations lead to cancer. CONTACT: paul.bates@cancer.org.uk SUPPLEMENTARY INFORMATION: The interactome data are available though the PIP (Potential Interactions of Proteins) web server at http://bmm.cancerresearchuk.org/servers/pip. Further additional material is available at http://bmm.cancerresearchuk.org/servers/pip/bioinformatics/     

Inferring modules from human protein interactome classes

Background  

The integration of protein-protein interaction networks derived from high-throughput screening approaches and complementary sources is a key topic in systems biology. Although integration of protein interaction data is conventionally performed, the effects of this procedure on the result of network analyses has not been examined yet. In particular, in order to optimize the fusion of heterogeneous interaction datasets, it is crucial to consider not only their degree of coverage and accuracy, but also their mutual dependencies and additional salient features.     

GTP binding and hydrolysis kinetics of human septin 2

Septins are a family of conserved proteins that are essential for cytokinesis in a wide range of organisms including fungi, Drosophila and mammals. In budding yeast, where they were first discovered, they are thought to form a filamentous ring at the bridge between the mother and bud cells. What regulates the assembly and function of septins, however, has remained obscure. All septins share a highly conserved domain related to those found in small GTPases, and septins have been shown to bind and hydrolyze GTP, although the properties of this domain and the relationship between polymerization and GTP binding/hydrolysis is unclear. Here we show that human septin 2 is phosphorylated in vivo at Ser218 by casein kinase II. In addition, we show that recombinant septin 2 binds guanine nucleotides with a Kd of 0.28 microm for GTPgammaS and 1.75 microm for GDP. It has a slow exchange rate of 7 x 10(-5) s(-1) for GTPgammaS and 5 x 10(-4) s(-1) for GDP, and an apparent kcat value of 2.7 x 10(-4) s(-1), similar to those of the Ras superfamily of GTPases. Interestingly, the nucleotide binding affinity appears to be altered by phosphorylation at Ser218. Finally, we show that a single septin protein can form homotypic filaments in vitro, whether bound to GDP or GTP.     

Self assembly of human septin 2 into amyloid filaments

Septins are a conserved group of GTP-binding proteins that form hetero-oligomeric complexes which assemble into filaments. These are essential for septin function, including their role in cytokinesis, cell division, exocytosis and membrane trafficking. Septin 2 (SEPT2) is a member of the septin family and has been associated with neurofibrillary tangles and other pathological features of senile plaques in Alzheimer's disease. An in silico analysis of the amino acid sequence of SEPT2 identified regions with a significant tendency to aggregate and/or form amyloid. These were all observed within the GTP-binding domain. This was consistent with the experimental identification of a structure rich in β-sheet during temperature induced unfolding transitions observed for both the full length protein and the GTP-binding domain alone. This intermediate state is characterized by irreversible aggregation and has the ability to bind Thioflavin-T, suggesting its amyloid nature. Under electron microscopy, fibers extending for several micrometers in length could be visualized. The results shown in this study support the hypothesis that single septins, when present in excess or with unbalanced stoichiometries, may be unstable and assemble into amyloid-like structures.     

Integration,visualization and analysis of human interactome

Data integration and visualization are crucial to obtain meaningful hypotheses from the diversity of ‘omics’ fields and the large volume of heterogeneous and distributed data sets. In this review we focus on network analysis as a key technique to integrate, visualize and extrapolate relevant information from diverse data. We first describe challenges in integrating different types of data and then focus on systematically exploring network properties to gain insight into network function. We also describe the relationship between network structures and function of elements that form it. Next, we highlight the role of the interactome in connecting data derived from different experiments, and we stress the importance of network analysis to recognize interaction context-specific features. Finally, we present an example integration to demonstrate the value of the network approach in cancer research, and highlight the importance of dynamic data in the specific context of signaling pathways.     

A predicted interactome for Arabidopsis

The complex cellular functions of an organism frequently rely on physical interactions between proteins. A map of all protein-protein interactions, an interactome, is thus an invaluable tool. We present an interactome for Arabidopsis (Arabidopsis thaliana) predicted from interacting orthologs in yeast (Saccharomyces cerevisiae), nematode worm (Caenorhabditis elegans), fruitfly (Drosophila melanogaster), and human (Homo sapiens). As an internal quality control, a confidence value was generated based on the amount of supporting evidence for each interaction. A total of 1,159 high confidence, 5,913 medium confidence, and 12,907 low confidence interactions were identified for 3,617 conserved Arabidopsis proteins. There was significant coexpression of genes whose proteins were predicted to interact, even among low confidence interactions. Interacting proteins were also significantly more likely to be found within the same subcellular location, and significantly less likely to be found in conflicting localizations than randomly paired proteins. A notable exception was that proteins located in the Golgi were more likely to interact with Golgi, vacuolar, or endoplasmic reticulum sorted proteins, indicating possible docking or trafficking interactions. These predictions can aid researchers by extending known complexes and pathways with candidate proteins. In addition we have predicted interactions for many previously unknown proteins in known pathways and complexes. We present this interactome, and an online Web interface the Arabidopsis Interactions Viewer, as a first step toward understanding global signaling in Arabidopsis, and to whet the appetite for those who are awaiting results from high-throughput experimental approaches.     

Functional integrative levels in the human interactome recapitulate organ organization

Interactome networks represent sets of possible physical interactions between proteins. They lack spatio-temporal information by construction. However, the specialized functions of the differentiated cell types which are assembled into tissues or organs depend on the combinatorial arrangements of proteins and their physical interactions. Is tissue-specificity, therefore, encoded within the interactome? In order to address this question, we combined protein-protein interactions, expression data, functional annotations and interactome topology. We first identified a subnetwork formed exclusively of proteins whose interactions were observed in all tested tissues. These are mainly involved in housekeeping functions and are located at the topological center of the interactome. This ‘Largest Common Interactome Network’ represents a ‘functional interactome core’. Interestingly, two types of tissue-specific interactions are distinguished when considering function and network topology: tissue-specific interactions involved in regulatory and developmental functions are central whereas tissue-specific interactions involved in organ physiological functions are peripheral. Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery. This gradient of functions recapitulates the organization of organs, from cells to organs. Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization.