Dual lipid modification of the yeast ggamma subunit Ste18p determines membrane localization of Gbetagamma

The pheromone response in the yeast Saccharomyces cerevisiae is mediated by a heterotrimeric G protein. The Gbetagamma subunit (a complex of Ste4p and Ste18p) is associated with both internal and plasma membranes, and a portion is not stably associated with either membrane fraction. Like Ras, Ste18p contains a farnesyl-directing CaaX box motif (C-terminal residues 107 to 110) and a cysteine residue (Cys 106) that is a potential site for palmitoylation. Mutant Ste18p containing serine at position 106 (mutation ste18-C106S) migrated more rapidly than wild-type Ste18p during sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). The electrophoretic mobility of wild-type Ste18p (but not the mutant Ste18p) was sensitive to hydroxylamine treatment, consistent with palmitoyl modification at Cys 106. Furthermore, immunoprecipitation of the Gbetagamma complex from cells cultured in the presence of [(3)H]palmitic acid resulted in two radioactive species on nonreducing SDS-PAGE gels, with molecular weights corresponding to Ggamma and Gbetagamma. Substitution of serine for either Cys 107 or Cys 106 resulted in the failure of Gbetagamma to associate with membranes. The Cys 107 substitution also resulted in reduced steady-state accumulation of Ste18p, suggesting that the stability of Ste18p requires modification at Cys 107. All of the mutant forms of Ste18p formed complexes with Ste4p, as assessed by coimmunoprecipitation. We conclude that tight membrane attachment of the wild-type Gbetagamma depends on palmitoylation at Cys 106 and prenylation at Cys 107 of Ste18p

A MOD(ern) perspective on literature curation

Curation of biological data is a multi-faceted task whose goal is to create a structured, comprehensive, integrated, and accurate resource of current biological knowledge. These structured data facilitate the work of the scientific community by providing knowledge about genes or genomes and by generating validated connections between the data that yield new information and stimulate new research approaches. For the model organism databases (MODs), an important source of data is research publications. Every published paper containing experimental information about a particular model organism is a candidate for curation. All such papers are examined carefully by curators for relevant information. Here, four curators from different MODs describe the literature curation process and highlight approaches taken by the four MODs to address: (1) the decision process by which papers are selected, and (2) the identification and prioritization of the data contained in the paper. We will highlight some of the challenges that MOD biocurators face, and point to ways in which researchers and publishers can support the work of biocurators and the value of such support

Fungal BLAST and Model Organism BLASTP Best Hits: new comparison resources at the Saccharomyces Genome Database (SGD)

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) is a scientific database of gene, protein and genomic information for the yeast Saccharomyces cerevisiae. SGD has recently developed two new resources that facilitate nucleotide and protein sequence comparisons between S.cerevisiae and other organisms. The Fungal BLAST tool provides directed searches against all fungal nucleotide and protein sequences available from GenBank, divided into categories according to organism, status of completeness and annotation, and source. The Model Organism BLASTP Best Hits resource displays, for each S.cerevisiae protein, the single most similar protein from several model organisms and presents links to the database pages of those proteins, facilitating access to curated information about potential orthologs of yeast proteins

Expanded protein information at SGD: new pages and proteome browser

The recent explosion in protein data generated from both directed small-scale studies and large-scale proteomics efforts has greatly expanded the quantity of available protein information and has prompted the Saccharomyces Genome Database (SGD; ) to enhance the depth and accessibility of protein annotations. In particular, we have expanded ongoing efforts to improve the integration of experimental information and sequence-based predictions and have redesigned the protein information web pages. A key feature of this redesign is the development of a GBrowse-derived interactive Proteome Browser customized to improve the visualization of sequence-based protein information. This Proteome Browser has enabled SGD to unify the display of hidden Markov model (HMM) domains, protein family HMMs, motifs, transmembrane regions, signal peptides, hydropathy plots and profile hits using several popular prediction algorithms. In addition, a physico-chemical properties page has been introduced to provide easy access to basic protein information. Improvements to the layout of the Protein Information page and integration of the Proteome Browser will facilitate the ongoing expansion of sequence-specific experimental information captured in SGD, including post-translational modifications and other user-defined annotations. Finally, SGD continues to improve upon the availability of genetic and physical interaction data in an ongoing collaboration with BioGRID by providing direct access to more than 82 000 manually-curated interactions

Genome Snapshot: a new resource at the Saccharomyces Genome Database (SGD) presenting an overview of the Saccharomyces cerevisiae genome

Sequencing and annotation of the entire Saccharomyces cerevisiae genome has made it possible to gain a genome-wide perspective on yeast genes and gene products. To make this information available on an ongoing basis, the Saccharomyces Genome Database (SGD) () has created the Genome Snapshot (). The Genome Snapshot summarizes the current state of knowledge about the genes and chromosomal features of S.cerevisiae. The information is organized into two categories: (i) number of each type of chromosomal feature annotated in the genome and (ii) number and distribution of genes annotated to Gene Ontology terms. Detailed lists are accessible through SGD's Advanced Search tool (), and all the data presented on this page are available from the SGD ftp site ()

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

The Gene Ontology in 2010: extensions and refinements

The Gene Ontology (GO) Consortium (http://www.geneontology.org) (GOC) continues to develop, maintain and use a set of structured, controlled vocabularies for the annotation of genes, gene products and sequences. The GO ontologies are expanding both in content and in structure. Several new relationship types have been introduced and used, along with existing relationships, to create links between and within the GO domains. These improve the representation of biology, facilitate querying, and allow GO developers to systematically check for and correct inconsistencies within the GO. Gene product annotation using GO continues to increase both in the number of total annotations and in species coverage. GO tools, such as OBO-Edit, an ontology-editing tool, and AmiGO, the GOC ontology browser, have seen major improvements in functionality, speed and ease of use.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Oxford University Press. The published article can be found at: http://nar.oxfordjournals.org/

The G beta gamma complex of the yeast pheromone response pathway. Subcellular fractionation and protein-protein interactions

Genetic evidence suggests that the yeast STE4 and STE18 genes encode G beta and G gamma subunits, respectively, that the G betagamma complex plays a positive role in the pheromone response pathway, and that its activity is subject to negative regulation by the G alpha subunit (product of the GPA1 gene) and to positive regulation by cell-surface pheromone receptors. However, as yet there is no direct biochemical evidence for a G betagamma protein complex associated with the plasma membrane. We found that the products of the STE4 and STE18 genes are stably associated with plasma membrane as well as with internal membranes and that 30% of the protein pool is not tightly associated with either membrane fraction. A slower-migrating, presumably phosphorylated, form of Ste4p is enriched in the non-membrane fraction. The Ste4p and Ste18p proteins that had been extracted from plasma membranes with detergent were found to co-sediment as an 8 S particle under low salt conditions and as a 6 S particle in the presence of 0.25 M NaCl; the Ste18p in these fractions was precipitated with anti-Ste4p antiserum. Under the conditions of our assay, Gpa1p was not associated with either particle. The levels of Ste4p and Ste18p accumulation in mutant cells provided additional evidence for a G betagamma complex. Ste18p failed to accumulate in ste4 mutant cells, and Ste4p showed reduced levels of accumulation and an increased rate of turnover in ste18 mutant cells. The gpa1 mutant blocked stable association of Ste4p with the plasma membrane, and the ste18 mutant blocked stable association of Ste4p with both plasma membranes and internal membranes. The membrane distribution of Ste4p was unaffected by the ste2 mutation or by down-regulation of the cell-surface receptors. These results indicate that at least 40% of Ste4p and Ste18p are part of a G betagamma complex at the plasma membrane and that stable association of this complex with the plasma membrane requires the presence of G alpha