Chris Stark

The BioGRID Interaction Database: 2011 update

The Biological General Repository for Interaction Datasets (BioGRID) is a public database that archives and disseminates genetic and protein interaction data from model organisms and humans (http://www.thebiogrid.org). BioGRID currently holds 347 966 interactions (170 162 genetic, 177 804 protein) curated from both high-throughput data sets and individual focused studies, as derived from over 23 000 publications in the primary literature. Complete coverage of the entire literature is maintained for budding yeast (Saccharomyces cerevisiae), fission yeast (Schizosaccharomyces pombe) and thale cress (Arabidopsis thaliana), and efforts to expand curation across multiple metazoan species are underway. The BioGRID houses 48 831 human protein interactions that have been curated from 10 247 publications. Current curation drives are focused on particular areas of biology to enable insights into conserved networks and pathways that are relevant to human health. The BioGRID 3.0 web interface contains new search and display features that enable rapid queries across multiple data types and sources. An automated Interaction Management System (IMS) is used to prioritize, coordinate and track curation across international sites and projects. BioGRID provides interaction data to several model organism databases, resources such as Entrez-Gene and other interaction meta-databases. The entire BioGRID 3.0 data collection may be downloaded in multiple file formats, including PSI MI XML. Source code for BioGRID 3.0 is freely available without any restrictions.

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 . 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.

The BioGRID interaction database

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.

A Global Protein Kinase and Phosphatase Interaction Network in Yeast

Budding Yeast Kinome Revealed Covalent modification of proteins by phosphorylation is a primary means by which cells control the biochemical activities and functions of proteins. To better understand the full spectrum of cellular control mechanisms mediated by phosphorylation, Breitkreutz et al. (p. 1043; see the Perspective by Levy et al.) used mass spectrometry to identify proteins that interacted with the complete set of protein kinases from budding yeast and with other molecules, including phosphatases, which influence phosphorylation reactions. The results reveal a network of interacting protein kinases and phosphatases, and analysis of other interacting proteins suggests previously undiscovered roles for many of these enzymes. Phosphorylation reactions in budding yeast reveal the regulatory architecture of a fundamental cellular control system. 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.

Proteomic, functional, and domain-based analysis of in vivo 14-3-3 binding proteins involved in cytoskeletal regulation and cellular organization.

BACKGROUND 14-3-3 proteins are abundant and conserved polypeptides that mediate the cellular effects of basophilic protein kinases through their ability to bind specific peptide motifs phosphorylated on serine or threonine. RESULTS We have used mass spectrometry to analyze proteins that associate with 14-3-3 isoforms in HEK293 cells. This identified 170 unique 14-3-3-associated proteins, which show only modest overlap with previous 14-3-3 binding partners isolated by affinity chromatography. To explore this large set of proteins, we developed a domain-based hierarchical clustering technique that distinguishes structurally and functionally related subsets of 14-3-3 target proteins. This analysis revealed a large group of 14-3-3 binding partners that regulate cytoskeletal architecture. Inhibition of 14-3-3 phosphoprotein recognition in vivo indicates the general importance of such interactions in cellular morphology and membrane dynamics. Using tandem proteomic and biochemical approaches, we identify a phospho-dependent 14-3-3 binding site on the A kinase anchoring protein (AKAP)-Lbc, a guanine nucleotide exchange factor (GEF) for the Rho GTPase. 14-3-3 binding to AKAP-Lbc, induced by PKA, suppresses Rho activation in vivo. CONCLUSION 14-3-3 proteins can potentially engage around 0.6% of the human proteome. Domain-based clustering has identified specific subsets of 14-3-3 targets, including numerous proteins involved in the dynamic control of cell architecture. This notion has been validated by the broad inhibition of 14-3-3 phosphorylation-dependent binding in vivo and by the specific analysis of AKAP-Lbc, a RhoGEF that is controlled by its interaction with 14-3-3.

WW Domains Provide a Platform for the Assembly of Multiprotein Networks

ABSTRACT WW domains are protein modules that mediate protein-protein interactions through recognition of proline-rich peptide motifs and phosphorylated serine/threonine-proline sites. To pursue the functional properties of WW domains, we employed mass spectrometry to identify 148 proteins that associate with 10 human WW domains. Many of these proteins represent novel WW domain-binding partners and are components of multiprotein complexes involved in molecular processes, such as transcription, RNA processing, and cytoskeletal regulation. We validated one complex in detail, showing that WW domains of the AIP4 E3 protein-ubiquitin ligase bind directly to a PPXY motif in the p68 subunit of pre-mRNA cleavage and polyadenylation factor Im in a manner that promotes p68 ubiquitylation. The tested WW domains fall into three broad groups on the basis of hierarchical clustering with respect to their associated proteins; each such cluster of bound proteins displayed a distinct set of WW domain-binding motifs. We also found that separate WW domains from the same protein or closely related proteins can have different specificities for protein ligands and also demonstrated that a single polypeptide can bind multiple classes of WW domains through separate proline-rich motifs. These data suggest that WW domains provide a versatile platform to link individual proteins into physiologically important networks.

ProHits: integrated software for mass spectrometry-based interaction proteomics

Affinity purification coupled with mass spectrometric identification (AP-MS) is now a method of choice for charting novel protein-protein interactions, and has been applied to a large number of both small scale and high-throughput studies1. However, general and intuitive computational tools for sample tracking, AP-MS data analysis, and annotation have not kept pace with rapid methodological and instrument improvements. To address this need, we developed the ProHits LIMS platform. ProHits is a complete open source software solution for MS-based interaction proteomics that manages the entire pipeline from raw MS data files to fully annotated protein-protein interaction datasets. ProHits was designed to provide an intuitive user interface from the biologists perspective, and can accommodate multiple instruments within a facility, multiple user groups, multiple laboratory locations, and any number of parallel projects. ProHits can manage all project scales, and supports common experimental pipelines, including those utilizing gel-based separation, gel-free analysis, and multi-dimensional protein or peptide separation. ProHits is a client-based HTML program written in PHP that runs a MySQL database on a dedicated server. The complete ProHits software solution consists of two main components: a Data Management module, and an Analyst module (Fig. 1a; see Supplementary Fig. 1 for data structure tables). These modules are supported by an Admin Office module, in which projects, instruments, user permissions and protein databases are managed (Supplementary Fig. 2). A simplified version of the software suite (“ProHits Lite”), consisting only of the Analyst module and Admin Office, is also available for users with pre-existing data management solutions or who receive pre-computed search results from analyses performed in a core MS facility (Supplementary Fig. 3). A step-by-step installation package, installation guide and user manual (see Supplementary Information) are available on the ProHits website (www.prohitsMS.com). Figure 1 Overview of ProHits. (a) Modular organisation of ProHits. The Data Management module backs up all raw mass spectrometry data from acquisition computers, and handles data conversion and database searches. The Analyst module organizes data by project, bait, ... In the Data Management module, raw data from all mass spectrometers in a facility or user group are copied to a single secure storage location in a scheduled manner. Data are organized in an instrument-specific manner, with folder and file organization mirroring the organization on the acquisition computer. ProHits also assigns unique identifiers to each folder and file. Log files and visual indicators of current connection status assist in monitoring the entire system. The Data Management module monitors the use of each instrument for reporting purposes (Supplementary Fig. 4–5). Raw MS files can be automatically converted to appropriate file formats using the open source ProteoWizard converters (http://proteowizard.sourceforge.net/). Converted files may be subjected to manual or automated database searches, followed by statistical analysis of the search results, according to any user-defined schedule; search engine parameters are also recorded to facilitate reporting and compliance with MIAPE guidelines2. Mascot3, X!Tandem4 and the TransProteomics Pipeline (TPP5) are fully integrated with ProHits via linked search engine servers (Supplementary Fig. 6–7). The Analyst module organizes data by project, bait, experiment and/or sample, for gel-based or gel-free approaches (Fig. 1a; for description of a gel-based project, see Supplementary Fig. 8). To create and analyze a gel-free affinity purification sample, the user specifies the bait gene name and species. ProHits automatically retrieves the amino acid sequence and other annotation from its associated database. Bait annotation may then be modified as necessary, for example to specify the presence of an epitope tag or mutation (Supplementary Fig. 9). A comprehensive annotation page tracks experimental details (Supplementary Fig. 10), including descriptions of the Sample, Affinity Purification protocol, Peptide Preparation methodology, and LC-MS/MS procedures. Controlled vocabulary lists for experimental descriptions can be added via drop-down menus to facilitate compliance with annotation guidelines such as MIAPE6 and MIMIx7, and to facilitate the organization and retrieval of data files. Free text notes for cross-referencing laboratory notebook pages, adding experimental details not captured in other sections, describing deviations from reference protocols and links to gel images or other file types may be added in the Experimental Detail page. Once an experiment is created, multiple samples may be linked to it, for example technical replicates of the same sample, or chromatographic fractions derived from the same preparation. All baits, experiments, samples and protocols are assigned unique identifiers. Once a sample is created, it is linked to both the relevant raw files and database search results. For multiple samples in HTP projects, automatic sample annotation may be established by using a standardized file naming system (Supplementary Fig. 11), or files may be manually linked. Alternatively, search results obtained outside of ProHits (with the X!Tandem or Mascot search engines) can be manually imported into the Analyst module (Supplementary Fig. 12). The ProHits Lite version enables uploading of external search results for users with an established MS data management system. In the Analyst module, mass spectrometry data can be explored in an intuitive manner, and results from individual samples, experiments or baits can be viewed and filtered (Supplementary Fig. 13–14). A user interface enables alignment of data from multiple baits or MS analyses using the Comparison tool. Data from individual MS runs, or derived from any user-defined sample group, are selected for visualization in a tabular format, for side-by-side comparisons (Fig. 1b; Supplementary Fig. 15–17). In the Comparison view, control groups and individual baits, experiments or samples are displayed by column. Proteins identified in each MS run or group of runs are displayed by row, and each cell corresponds to a putative protein hit, according to user-specified database search score cutoff. Cells display spectral count number, unique peptides, scores from search engines, and/or protein coverage information; a mouse-over function reveals all associated data for each cell in the table. For each protein displayed in the Comparison view, an associated Peptide link (Fig. 1b) may also be selected to reveal information such as sequence, location, spectral counts, and score, for each associated peptide. Importantly, all search results can be filtered. For example, ProHits allows for the removal of non-specific background proteins from the hit list, as defined by negative controls, search engine score thresholds, or contaminant lists. Links to the external NCBI and BioGRID8 databases are provided for each hit to facilitate data interpretation. Overlap with published interaction data housed in the BioGRID database8 can be displayed to allow immediate identification of new interaction partners. A flexible export function enables visualization in a graphical format with Cytoscape9, in which spectral counts, unique peptides, and search engine scores can be visualized as interaction edge attributes. The Analyst module also includes advanced search functions, bulk export functions for filtered or unfiltered data, and management of experimental protocols and background lists (e.g. Supplementary Fig. 18–20). Deposition of all mass spectrometry-associated data in public repositories is likely to become mandatory for publication of proteomics experiments2, 7, 10. Open access to raw files is essential for data reanalysis and cross-platform comparison; however, data submission to public repositories can be laborious due to strict formatting requirements. ProHits facilitates extraction of the necessary details in compliance with current standards, and generates Proteomic Standard Initiative (PSI) v2.5 compliant reports11, either in the MITAB format for BioGRID8 or in XML format for submission to IMEx consortium databases12, including IntAct13 (Supplementary Fig. 21). MS raw files associated with a given project can also be easily retrieved and grouped for submission to data repositories such as Tranche14. ProHits has developed to manage many large-scale in-house projects, including a systematic analysis of kinase and phosphatase interactions in yeast, consisting of 986 affinity purifications15. Smaller-scale projects from individual laboratories are readily handled in a similar manner. Examples of AP-MS data from both yeast and mammalian projects are provided in a demonstration version of ProHits at www.prohitsMS.com, and in Supplementary documents. The modular architecture of ProHits will accommodate additional new features, as dictated by future experimental and analytical needs. Although ProHits has been designed to handle protein interaction data, simple modifications of the open source code will enable straightforward adaptation to other proteomics workflows.

Eukaryotic Protein Domains as Functional Units of Cellular Evolution

Clustering proteins into groups on the basis of their domain compositions provides insight into protein evolution. Domains for Change Protein domains endow proteins with specific activities and the ability to interact with specific partners. Most protein domains occur in many proteins and most proteins have multiple domains, but the combinations of domains are far fewer than would be predicted, suggesting that there is evolutionary pressure that preserves certain domain combinations. Jin et al. use a proteome-wide clustering method to identify eukaryotic protein domain combinations that correlate with evolutionary change. Their analysis suggests that reciprocal interactions between a protein and its microenvironment constrain the repertoire of domains that control specific cellular functions. They analyzed the proteins in seven eukaryotic species and organized the domains into 1245 “domain clubs,” with the majority of clubs containing proteins with multiple distinct domains and proteins with rich interrelationships among members of different clubs. They grouped proteins on the basis of their domain clubs into functional trees and were able to place domains of unknown function into functional groups, as well as make predictions about the role domain evolution contributes to the evolution of protein function within a molecular environment, as well as to the evolution of molecular environments. Modular protein domains are functional units that can be modified through the acquisition of new intrinsic activities or by the formation of novel domain combinations, thereby contributing to the evolution of proteins with new biological properties. Here, we assign proteins to groups with related domain compositions and functional properties, termed “domain clubs,” which we use to compare multiple eukaryotic proteomes. This analysis shows that different domain types can take distinct evolutionary trajectories, which correlate with the conservation, gain, expansion, or decay of particular biological processes. Evolutionary jumps are associated with a domain that coordinately acquires a new intrinsic function and enters new domain clubs, thereby providing the modified domain with access to a new cellular microenvironment. We also coordinately analyzed the covalent and noncovalent interactions of different domain types to assess the molecular compartment occupied by each domain. This reveals that specific subsets of domains demarcate particular cellular processes, such as growth factor signaling, chromatin remodeling, apoptotic and inflammatory responses, or vesicular trafficking. We suggest that domains, and the proteins in which they reside, are selected during evolution through reciprocal interactions with protein domains in their local microenvironment. Based on this scheme, we propose a mechanism by which Tudor domains may have evolved to support different modes of epigenetic regulation and suggest a role for the germline group of mammalian Tudor domains in Piwi-regulated RNA biology.

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.

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.