The Biological General Repository for Interaction Datasets (BioGRID: https://thebiogrid.org) is an open access database dedicated to the annotation and archival of protein, genetic and chemical interactions for all major model organism species and humans. As of September 2016 (build 3.4.140), the BioGRID contains 1 072 173 genetic and protein interactions, and 38 559 post-translational modifications, as manually annotated from 48 114 publications. This dataset represents interaction records for 66 model organisms and represents a 30% increase compared to the previous 2015 BioGRID update. BioGRID curates the biomedical literature for major model organism species, including humans, with a recent emphasis on central biological processes and specific human diseases. To facilitate network-based approaches to drug discovery, BioGRID now incorporates 27 501 chemical–protein interactions for human drug targets, as drawn from the DrugBank database. A new dynamic interaction network viewer allows the easy navigation and filtering of all genetic and protein interaction data, as well as for bioactive compounds and their established targets. BioGRID data are directly downloadable without restriction in a variety of standardized formats and are freely distributed through partner model organism databases and meta-databases.

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 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.

Glycolysis is a metabolic pathway that is central to the assimilation of carbon for either respiration or fermentation and therefore is critical for the growth of all organisms. Consequently, glycolytic transcriptional regulation is important for the metabolic flexibility of pathogens in their attempts to colonize diverse niches. We investigated the transcriptional control of carbohydrate metabolism in the human fungal pathogen Candida albicans and identified two factors, Tye7p and Gal4p, as key regulators of glycolysis. When respiration was inhibited or oxygen was limited, a gal4tye7 C. albicans strain showed a severe growth defect when cultured on glucose, fructose or mannose as carbon sources. The gal4tye7 strain displayed attenuated virulence in both Galleria and mouse models as well, supporting the connection between pathogenicity and metabolism. Chromatin immunoprecipitation coupled with microarray analysis (ChIP-CHIP) and transcription profiling revealed that Tye7p bound the promoter sequences of the glycolytic genes and activated their expression during growth on either fermentable or non-fermentable carbon sources. Gal4p also bound the glycolytic promoter sequences and activated the genes although to a lesser extent than Tye7p. Intriguingly, binding and activation by Gal4p was carbon source-dependent and much stronger during growth on media containing fermentable sugars than on glycerol. Furthermore, Tye7p and Gal4p were responsible for the complete induction of the glycolytic genes under hypoxic growth conditions. Tye7p and Gal4p also regulated unique sets of carbohydrate metabolic genes; Tye7p bound and activated genes involved in trehalose, glycogen, and glycerol metabolism, while Gal4p regulated the pyruvate dehydrogenase complex. This suggests that Tye7p represents the key transcriptional regulator of carbohydrate metabolism in C. albicans and Gal4p provides a carbon source-dependent fine-tuning of gene expression while regulating the metabolic flux between respiration and fermentation pathways.

The dimorphic switch from a single-cell budding yeast to a filamentous form enables Saccharomyces cerevisiae to forage for nutrients and the opportunistic pathogen Candida albicans to invade human tissues and evade the immune system. We constructed a genome-wide set of targeted deletion alleles and introduced them into a filamentous S. cerevisiae strain, Σ1278b. We identified genes involved in morphologically distinct forms of filamentation: haploid invasive growth, biofilm formation, and diploid pseudohyphal growth. Unique genes appear to underlie each program, but we also found core genes with general roles in filamentous growth, including MFG1 (YDL233w), whose product binds two morphogenetic transcription factors, Flo8 and Mss11, and functions as a critical transcriptional regulator of filamentous growth in both S. cerevisiae and C. albicans.

A surprising level of evolutionary plasticity is revealed by analysis of differences between related yeasts in the mechanisms regulating the essential cellular process of ribosomal gene expression.

Coordinated ribosomal protein (RP) gene expression is crucial for cellular viability, but the transcriptional network controlling this regulon has only been well characterized in the yeast Saccharomyces cerevisiae. We have used whole-genome transcriptional and location profiling to establish that, in Candida albicans, the RP regulon is controlled by the Myb domain protein Tbf1 working in conjunction with Cbf1. These two factors bind both the promoters of RP genes and the rDNA locus; Tbf1 activates transcription at these loci and is essential. Orthologs of Tbf1 bind TTAGGG telomeric repeats in most eukaryotes, and TTAGGG cis-elements are present upstream of RP genes in plants and fungi, suggesting that Tbf1 was involved in both functions in ancestral eukaryotes. In all Hemiascomycetes, Rap1 substituted Tbf1 at telomeres and, in the S. cerevisiae lineage, this substitution also occurred independently at RP genes, illustrating the extreme adaptability and flexibility of transcriptional regulatory networks.

Thirty-eight isolates of Alternaria alternata from pistachio orchards with a history of Pristine (pyraclostrobin + boscalid) applications and displaying high levels of resistance to boscalid fungicide (mean EC(50) values >500 microg/ml) were identified following mycelial growth tests. A cross-resistance study revealed that the same isolates were also resistant to carboxin, a known inhibitor of succinate dehydrogenase (Sdh). To determine the genetic basis of boscalid resistance in A. alternata the entire iron sulphur gene (AaSdhB) was isolated from a fungicide-sensitive isolate. The deduced amino-acid sequence showed high similarity with iron sulphur proteins (Ip) from other organisms. Comparison of AaSdhB full sequences from sensitive and resistant isolates revealed that a highly conserved histidine residue (codon CAC in sensitive isolates) was converted to either tyrosine (codon TAC, type I mutants) or arginine (codon CGC, type II mutants) at position 277. In other fungal species this residue is involved in carboxamide resistance. In this study, 10 and 5 mutants were of type I and type II respectively, while 23 other resistant isolates (type III mutants) had no mutation in the histidine codon. The point mutation detected in type I mutants was used to design a pair of allele-specific polymerase chain reaction (PCR) primers to facilitate rapid detection. A PCR-restriction fragment length polymorphism (RFLP) assay in which amplified gene fragments were digested with AciI was successfully employed for the diagnosis of type II mutants. The relevance of these modifications in A. alternata AaSdhB sequence in conferring boscalid resistance is discussed.