The BioGRID interaction database: 2015 update.

The Biological General Repository for Interaction Datasets (BioGRID: http://thebiogrid.org) is an open access database that houses genetic and protein interactions curated from the primary biomedical literature for all major model organism species and humans. As of September 2014, the BioGRID contains 749,912 interactions as drawn from 43,149 publications that represent 30 model organisms. This interaction count represents a 50% increase compared to our previous 2013 BioGRID update. BioGRID data are freely distributed through partner model organism databases and meta-databases and are directly downloadable in a variety of formats. In addition to general curation of the published literature for the major model species, BioGRID undertakes themed curation projects in areas of particular relevance for biomedical sciences, such as the ubiquitin-proteasome system and various human disease-associated interaction networks. BioGRID curation is coordinated through an Interaction Management System (IMS) that facilitates the compilation interaction records through structured evidence codes, phenotype ontologies, and gene annotation. The BioGRID architecture has been improved in order to support a broader range of interaction and post-translational modification types, to allow the representation of more complex multi-gene/protein interactions, to account for cellular phenotypes through structured ontologies, to expedite curation through semi-automated text-mining approaches, and to enhance curation quality control.

The BioGRID interaction database: 2013 update.

The Biological General Repository for Interaction Datasets (BioGRID: http//thebiogrid.org) is an open access archive of genetic and protein interactions that are curated from the primary biomedical literature for all major model organism species. As of September 2012, BioGRID houses more than 500 000 manually annotated interactions from more than 30 model organisms. BioGRID maintains complete curation coverage of the literature for the budding yeast Saccharomyces cerevisiae, the fission yeast Schizosaccharomyces pombe and the model plant Arabidopsis thaliana. A number of themed curation projects in areas of biomedical importance are also supported. BioGRID has established collaborations and/or shares data records for the annotation of interactions and phenotypes with most major model organism databases, including Saccharomyces Genome Database, PomBase, WormBase, FlyBase and The Arabidopsis Information Resource. BioGRID also actively engages with the text-mining community to benchmark and deploy automated tools to expedite curation workflows. BioGRID data are freely accessible through both a user-defined interactive interface and in batch downloads in a wide variety of formats, including PSI-MI2.5 and tab-delimited files. BioGRID records can also be interrogated and analyzed with a series of new bioinformatics tools, which include a post-translational modification viewer, a graphical viewer, a REST service and a Cytoscape plugin.

SAINT: probabilistic scoring of affinity purification-mass spectrometry data.

We present 'significance analysis of interactome' (SAINT), a computational tool that assigns confidence scores to protein-protein interaction data generated using affinity purification-mass spectrometry (AP-MS). The method uses label-free quantitative data and constructs separate distributions for true and false interactions to derive the probability of a bona fide protein-protein interaction. We show that SAINT is applicable to data of different scales and protein connectivity and allows transparent analysis of AP-MS data.

Global analysis of protein phosphorylation in yeast.

Protein phosphorylation is estimated to affect 30% of the proteome and is a major regulatory mechanism that controls many basic cellular processes. Until recently, our biochemical understanding of protein phosphorylation on a global scale has been extremely limited; only one half of the yeast kinases have known in vivo substrates and the phosphorylating kinase is known for less than 160 phosphoproteins. Here we describe, with the use of proteome chip technology, the in vitro substrates recognized by most yeast protein kinases: we identified over 4,000 phosphorylation events involving 1,325 different proteins. These substrates represent a broad spectrum of different biochemical functions and cellular roles. Distinct sets of substrates were recognized by each protein kinase, including closely related kinases of the protein kinase A family and four cyclin-dependent kinases that vary only in their cyclin subunits. Although many substrates reside in the same cellular compartment or belong to the same functional category as their phosphorylating kinase, many others do not, indicating possible new roles for several kinases. Furthermore, integration of the phosphorylation results with protein-protein interaction and transcription factor binding data revealed novel regulatory modules. Our phosphorylation results have been assembled into a first-generation phosphorylation map for yeast. Because many yeast proteins and pathways are conserved, these results will provide insights into the mechanisms and roles of protein phosphorylation in many eukaryotes.

The BioGRID Interaction Database: 2008 update.

The Biological General Repository for Interaction Datasets (BioGRID) database (http://www.thebiogrid.org) was developed to house and distribute collections of protein and genetic interactions from major model organism species. BioGRID currently contains over 198 000 interactions from six different species, as derived from both high-throughput studies and conventional focused studies. Through comprehensive curation efforts, BioGRID now includes a virtually complete set of interactions reported to date in the primary literature for both the budding yeast Saccharomyces cerevisiae and the fission yeast Schizosaccharomyces pombe. A number of new features have been added to the BioGRID including an improved user interface to display interactions based on different attributes, a mirror site and a dedicated interaction management system to coordinate curation across different locations. The BioGRID provides interaction data with monthly updates to Saccharomyces Genome Database, Flybase and Entrez Gene. Source code for the BioGRID and the linked Osprey network visualization system is now freely available without restriction.

MAPK signaling specificity: it takes two to tango.

A surprisingly limited repertoire of core signaling pathways generates an enormous diversity of responses, often in a cell type-specific manner. Even within one cell, a single pathway might yield two different responses depending on the input signal. In budding yeast, a mitogen-activated protein kinase (MAPK) module seems to transmit both mating pheromone and invasive growth signals in the same yeast cell. We discuss recent insights into mechanisms of differential MAPK activation in this system.

Stratus not altocumulus: a new view of the yeast protein interaction network.

Systems biology approaches can reveal intermediary levels of organization between genotype and phenotype that often underlie biological phenomena such as polygenic effects and protein dispensability. An important conceptualization is the module, which is loosely defined as a cohort of proteins that perform a dedicated cellular task. Based on a computational analysis of limited interaction datasets in the budding yeast Saccharomyces cerevisiae, it has been suggested that the global protein interaction network is segregated such that highly connected proteins, called hubs, tend not to link to each other. Moreover, it has been suggested that hubs fall into two distinct classes: "party" hubs are co-expressed and co-localized with their partners, whereas "date" hubs interact with incoherently expressed and diversely localized partners, and thereby cohere disparate parts of the global network. This structure may be compared with altocumulus clouds, i.e., cotton ball-like structures sparsely connected by thin wisps. However, this organization might reflect a small and/or biased sample set of interactions. In a multi-validated high-confidence (HC) interaction network, assembled from all extant S. cerevisiae interaction data, including recently available proteome-wide interaction data and a large set of reliable literature-derived interactions, we find that hub-hub interactions are not suppressed. In fact, the number of interactions a hub has with other hubs is a good predictor of whether a hub protein is essential or not. We find that date hubs are neither required for network tolerance to node deletion, nor do date hubs have distinct biological attributes compared to other hubs. Date and party hubs do not, for example, evolve at different rates. Our analysis suggests that the organization of global protein interaction network is highly interconnected and hence interdependent, more like the continuous dense aggregations of stratus clouds than the segregated configuration of altocumulus clouds. If the network is configured in a stratus format, cross-talk between proteins is potentially a major source of noise. In turn, control of the activity of the most highly connected proteins may be vital. Indeed, we find that a fluctuation in steady-state levels of the most connected proteins is minimized.

BioGRID: a general repository for interaction datasets.

Access to unified datasets of protein and genetic interactions is critical for interrogation of gene/protein function and analysis of global network properties. BioGRID is a freely accessible database of physical and genetic interactions available at http://www.thebiogrid.org. BioGRID release version 2.0 includes >116 000 interactions from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens. Over 30 000 interactions have recently been added from 5778 sources through exhaustive curation of the Saccharomyces cerevisiae primary literature. An internally hyper-linked web interface allows for rapid search and retrieval of interaction data. Full or user-defined datasets are freely downloadable as tab-delimited text files and PSI-MI XML. Pre-computed graphical layouts of interactions are available in a variety of file formats. User-customized graphs with embedded protein, gene and interaction attributes can be constructed with a visualization system called Osprey that is dynamically linked to the BioGRID.

Regulation of the yeast amphiphysin homologue Rvs167p by phosphorylation.

The yeast amphiphysin homologue Rvs167p plays a role in regulation of the actin cytoskeleton, endocytosis, and sporulation. Rvs167p is a phosphoprotein in vegetatively growing cells and shows increased phosphorylation upon treatment with mating pheromone. Previous work has shown that Rvs167p can be phosphorylated in vitro by the cyclin-dependent kinase Pho85p complexed with its cyclin Pcl2p. Using chymotryptic phosphopeptide mapping, we have identified the sites on which Rvs167p is phosphorylated in vitro by Pcl2p-Pho85p. We have shown that these same sites are phosphorylated in vivo during vegetative growth and that phosphorylation at two of these sites is Pcl-Pho85p dependent. In cells treated with mating pheromone, the MAP kinase Fus3p is needed for full phosphorylation of Rvs167p. Functional genomics and genetics experiments revealed that mutation of other actin cytoskeleton genes compromises growth of a strain in which phosphorylation of Rvs167p is blocked by mutation. Phosphorylation of Rvs167p inhibits its interaction in vitro with Las17p, an activator of the Arp2/3 complex, as well as with a novel protein, Ymr192p. Our results suggest that phosphorylation of Rvs167p by a cyclin-dependent kinase and by a MAP kinase is an important mechanism for regulating protein complexes involved in actin cytoskeleton function.

Use of the BioGRID Database for Analysis of Yeast Protein and Genetic Interactions.

The BioGRID database is an extensive repository of curated genetic and protein interactions for the budding yeast Saccharomyces cerevisiae, the fission yeast Schizosaccharomyces pombe, and the yeast Candida albicans SC5314, as well as for several other model organisms and humans. This protocol describes how to use the BioGRID website to query genetic or protein interactions for any gene of interest, how to visualize the associated interactions using an embedded interactive network viewer, and how to download data files for either selected interactions or the entire BioGRID interaction data set.

BioGRID: A Resource for Studying Biological Interactions in Yeast.

The Biological General Repository for Interaction Datasets (BioGRID) is a freely available public database that provides the biological and biomedical research communities with curated protein and genetic interaction data. Structured experimental evidence codes, an intuitive search interface, and visualization tools enable the discovery of individual gene, protein, or biological network function. BioGRID houses interaction data for the major model organism species--including yeast, nematode, fly, zebrafish, mouse, and human--with particular emphasis on the budding yeast Saccharomyces cerevisiae and the fission yeast Schizosaccharomyces pombe as pioneer eukaryotic models for network biology. BioGRID has achieved comprehensive curation coverage of the entire literature for these two major yeast models, which is actively maintained through monthly curation updates. As of September 2015, BioGRID houses approximately 335,400 biological interactions for budding yeast and approximately 67,800 interactions for fission yeast. BioGRID also supports an integrated posttranslational modification (PTM) viewer that incorporates more than 20,100 yeast phosphorylation sites curated through its sister database, the PhosphoGRID.

Phenotypic and transcriptional plasticity directed by a yeast mitogen-activated protein kinase network.

The yeast pheromone/filamentous growth MAPK pathway mediates both mating and invasive-growth responses. The interface between this MAPK module and the transcriptional machinery consists of a network of two MAPKs, Fus3 and Kss1; two regulators, Rst1 and Rst2 (a.k.a. Dig1 and Dig2); and two transcription factors, Ste12 and Tec1. Of 16 possible combinations of gene deletions in FUS3, KSS1, RST1, and RST2 in the sigma1278 background, 10 display constitutive invasive growth. Rst1 was the primary negative regulator of invasive growth, while other components either attenuated or enhanced invasive growth, depending on the genetic context. Despite activation of the invasive response by lesions at the same level in the MAPK pathway, transcriptional profiles of different invasive mutant combinations did not exhibit a unified program of gene expression. The distal MAPK regulatory network is thus capable of generating phenotypically similar invasive-growth states (an attractor) from different molecular architectures (trajectories) that can functionally compensate for one another. This systems-level robustness may also account for the observed diversity of signals that trigger invasive growth.

PhosphoGRID: a database of experimentally verified in vivo protein phosphorylation sites from the budding yeast Saccharomyces cerevisiae.

Protein phosphorylation plays a central role in cellular regulation. Recent proteomics strategies for identifying phosphopeptides have been developed using the model organism Saccharomyces cerevisiae, and consequently, when combined with studies of individual gene products, the number of reported specific phosphorylation sites for this organism has expanded enormously. In order to systematically document and integrate these various data types, we have developed a database of experimentally verified in vivo phosphorylation sites curated from the S. cerevisiae primary literature. PhosphoGRID (www.phosphogrid.org) records the positions of over 5000 specific phosphorylated residues on 1495 gene products. Nearly 900 phosphorylated residues are reported from detailed studies of individual proteins; these in vivo phosphorylation sites are documented by a hierarchy of experimental evidence codes. Where available for specific sites, we have also noted the relevant protein kinases and/or phosphatases, the specific condition(s) under which phosphorylation occurs, and the effect(s) that phosphorylation has on protein function. The unique features of PhosphoGRID that assign both function and specific physiological conditions to each phosphorylated residue will provide a valuable benchmark for proteome-level studies and will facilitate bioinformatic analysis of cellular signal transduction networks. Database URL: http://phosphogrid.org/

A global protein kinase and phosphatase interaction network in yeast.

The interactions of protein kinases and phosphatases with their regulatory subunits and substrates underpin cellular regulation. We identified a kinase and phosphatase interaction (KPI) network of 1844 interactions in budding yeast by mass spectrometric analysis of protein complexes. The KPI network contained many dense local regions of interactions that suggested new functions. Notably, the cell cycle phosphatase Cdc14 associated with multiple kinases that revealed roles for Cdc14 in mitogen-activated protein kinase signaling, the DNA damage response, and metabolism, whereas interactions of the target of rapamycin complex 1 (TORC1) uncovered new effector kinases in nitrogen and carbon metabolism. An extensive backbone of kinase-kinase interactions cross-connects the proteome and may serve to coordinate diverse cellular responses.

Type III secretion effectors of the IpaH family are E3 ubiquitin ligases.

Many bacteria pathogenic for plants or animals, including Shigella spp., which is responsible for shigellosis in humans, use a type III secretion apparatus to inject effector proteins into host cells. Effectors alter cell signaling and host responses induced upon infection; however, their precise biochemical activities have been elucidated in very few cases. Utilizing Saccharomyces cerevisiae as a surrogate host, we show that the Shigella effector IpaH9.8 interrupts pheromone response signaling by promoting the proteasome-dependent destruction of the MAPKK Ste7. In vitro, IpaH9.8 displayed ubiquitin ligase activity toward ubiquitin and Ste7. Replacement of a Cys residue that is invariant among IpaH homologs of plant and animal pathogens abolished the ubiquitin ligase activity of IpaH9.8. We also present evidence that the IpaH homolog SspH1 from Salmonella enterica can ubiquitinate ubiquitin and PKN1, a previously identified SspH1 interaction partner. This study assigns a function for IpaH family members as E3 ubiquitin ligases.

Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae.

BACKGROUND: The study of complex biological networks and prediction of gene function has been enabled by high-throughput (HTP) methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may, however, distort network properties and confound predictions. Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference. RESULTS: We describe here a comprehensive database of genetic and protein interactions, and associated experimental evidence, for the budding yeast Saccharomyces cerevisiae, as manually curated from over 31,793 abstracts and online publications. This literature-curated (LC) dataset contains 33,311 interactions, on the order of all extant HTP datasets combined. Surprisingly, HTP protein-interaction datasets currently achieve only around 14% coverage of the interactions in the literature. The LC network nevertheless shares attributes with HTP networks, including scale-free connectivity and correlations between interactions, abundance, localization, and expression. We find that essential genes or proteins are enriched for interactions with other essential genes or proteins, suggesting that the global network may be functionally unified. This interconnectivity is supported by a substantial overlap of protein and genetic interactions in the LC dataset. We show that the LC dataset considerably improves the predictive power of network-analysis approaches. The full LC dataset is available at the BioGRID (http://www.thebiogrid.org) and SGD (http://www.yeastgenome.org/) databases. CONCLUSION: Comprehensive datasets of biological interactions derived from the primary literature provide critical benchmarks for HTP methods, augment functional prediction, and reveal system-level attributes of biological networks.