Project description:The striatin-interacting phosphatases and kinases (STRIPAK) multi subunit complex is a highly conserved signaling complex that controls diverse developmental processes in higher and lower eukaryotes. In this perspective article, we summarize how STRIPAK controls diverse developmental processes in euascomycetes, such as fruiting body formation, cell fusion, sexual and vegetative development, pathogenicity, symbiosis, as well as secondary metabolism. Recent structural investigations revealed information about the assembly and stoichiometry of the complex enabling it to act as a signaling hub. Multiple organellar targeting of STRIPAK subunits suggests how this complex connects several signaling transduction pathways involved in diverse cellular developmental processes. Furthermore, recent phosphoproteomic analysis shows that STRIPAK controls the dephosphorylation of subunits from several signaling complexes. We also refer to recent findings in yeast, where the STRIPAK homologue connects conserved signaling pathways, and based on this we suggest how so far non-characterized proteins may functions as receptors connecting mitophagy with the STRIPAK signaling complex. Such lines of investigation should contribute to the overall mechanistic understanding of how STRIPAK controls development in euascomycetes and beyond.
Project description:Plant stress responses involve numerous changes at the molecular and cellular level and are regulated by highly complex signaling pathways. Studying protein-protein interactions (PPIs) and the resulting networks is therefore becoming increasingly important in understanding these responses. Crucial in PPI networks are the so-called hubs or hub proteins, commonly defined as the most highly connected central proteins in scale-free PPI networks. However, despite their importance, a growing amount of confusion and controversy seems to exist regarding hub protein identification, characterization and classification. In order to highlight these inconsistencies and stimulate further clarification, this review critically analyses the current knowledge on hub proteins in the plant interactome field. We focus on current hub protein definitions, including the properties generally seen as hub-defining, and the challenges and approaches associated with hub protein identification. Furthermore, we give an overview of the most important large-scale plant PPI studies of the last decade that identified hub proteins, pointing out the lack of overlap between different studies. As such, it appears that although major advances are being made in the plant interactome field, defining hub proteins is still heavily dependent on the quality, origin and interpretation of the acquired PPI data. Nevertheless, many hub proteins seem to have a reported role in the plant stress response, including transcription factors, protein kinases and phosphatases, ubiquitin proteasome system related proteins, (co-)chaperones and redox signaling proteins. A significant number of identified plant stress hubs are however still functionally uncharacterized, making them interesting targets for future research. This review clearly shows the ongoing improvements in the plant interactome field but also calls attention to the need for a more comprehensive and precise identification of hub proteins, allowing a more efficient systems biology driven unraveling of complex processes, including those involved in stress responses.
Project description:One major task in the post-genome era is to reconstruct proteomic and genomic interacting networks using high-throughput experiment data. To identify essential nodes/hubs in these interactomes is a way to decipher the critical keys inside biochemical pathways or complex networks. These essential nodes/hubs may serve as potential drug-targets for developing novel therapy of human diseases, such as cancer or infectious disease caused by emerging pathogens. Hub Objects Analyzer (Hubba) is a web-based service for exploring important nodes in an interactome network generated from specific small- or large-scale experimental methods based on graph theory. Two characteristic analysis algorithms, Maximum Neighborhood Component (MNC) and Density of Maximum Neighborhood Component (DMNC) are developed for exploring and identifying hubs/essential nodes from interactome networks. Users can submit their own interaction data in PSI format (Proteomics Standards Initiative, version 2.5 and 1.0), tab format and tab with weight values. User will get an email notification of the calculation complete in minutes or hours, depending on the size of submitted dataset. Hubba result includes a rank given by a composite index, a manifest graph of network to show the relationship amid these hubs, and links for retrieving output files. This proposed method (DMNC || MNC) can be applied to discover some unrecognized hubs from previous dataset. For example, most of the Hubba high-ranked hubs (80% in top 10 hub list, and >70% in top 40 hub list) from the yeast protein interactome data (Y2H experiment) are reported as essential proteins. Since the analysis methods of Hubba are based on topology, it can also be used on other kinds of networks to explore the essential nodes, like networks in yeast, rat, mouse and human. The website of Hubba is freely available at http://hub.iis.sinica.edu.tw/Hubba.
Project description:Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest.AvailabilityCHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).
Project description:We evaluated the effects of suppressing MAP4K4 on transcriptome and YAP1 pathway based on the observation that partial suppression of MAP4K4 leads to transformation through activation of YAP1. Mutations and deletions involving subunits of the serine-threonine phosphatase PP2A occur in a broad range of human cancers, and partial loss of PP2A function contributes to cell transformation. In particular, displacement of regulatory B subunits by the viral oncoprotein SV40 small-t antigen (ST) or mutation or deletion of PP2A subunits alters the abundance and types of PP2A complexes in cells and induces cell transformation in human cells. Here we show that ST not only displaces common PP2A B subunits but also promotes PP2A A-C subunit interactions with a set of alternative B subunits (B’’’, striatins) that are components of the Striatin-interacting phosphatase and kinase (STRIPAK) complex. We found that members of the STRIPAK complex are required for ST-PP2A induced cell transformation. PP2A interacts with and dephosphorylates the STRIPAK-associated kinase MAP4K4, which induces cell transformation in part through the regulation of the Hippo pathway effector YAP1. These observations identify an unanticipated role of MAP4K4 in transformation and show that the STRIPAK complex plays a key role in defining PP2A specificity and activity.
Project description:The MST-LATS kinase cascade is central to the Hippo pathway that controls tissue homeostasis, development, and organ size. The PP2A complex STRIPAKSLMAP blocks MST1/2 activation. The GCKIII family kinases associate with STRIPAK, but the functions of these phosphatase-associated kinases remain elusive. We previously showed that the scaffolding protein SAV1 promotes Hippo signaling by counteracting STRIPAK (Bae et al., 2017). Here, we show that the GCKIII kinase STK25 promotes STRIPAK-mediated inhibition of MST2 in human cells. Depletion of STK25 enhances MST2 activation without affecting the integrity of STRIPAKSLMAP. STK25 directly phosphorylates SAV1 and diminishes the ability of SAV1 to inhibit STRIPAK. Thus, STK25 as the kinase component of STRIPAK can inhibit the function of the STRIPAK inhibitor SAV1. This mutual antagonism between STRIPAK and SAV1 controls the initiation of Hippo signaling.
Project description:Hubs are ubiquitous network elements with high connectivity. One of the common observations about hub proteins is their preferential attachment leading to scale-free network topology. Here we examine the question: does rich protein always get richer, or can it get poor too? To answer this question, we compared similar and well-annotated hub proteins in six organisms, from prokaryotes to eukaryotes. Our findings indicate that hub proteins retain, gain or lose connectivity based on the context. Furthermore, the loss or gain of connectivity appears to correlate with the functional role of the protein in a given system.