Progress and potential of Drosophila protein interaction maps

DroID 2011: a comprehensive, integrated resource for protein, transcription factor, RNA and gene interactions for Drosophila

DroID (http://droidb.org/), the Drosophila Interactions Database, is a comprehensive public resource for Drosophila gene and protein interactions. DroID contains genetic interactions and experimentally detected protein–protein interactions curated from the literature and from external databases, and predicted protein interactions based on experiments in other species. Protein interactions are annotated with experimental details and periodically updated confidence scores. Data in DroID is accessible through user-friendly, intuitive interfaces that allow simple or advanced searches and graphical visualization of interaction networks. DroID has been expanded to include interaction types that enable more complete analyses of the genetic networks that underlie biological processes. In addition to protein–protein and genetic interactions, the database now includes transcription factor–gene and regulatory RNA–gene interactions. In addition, DroID now has more gene expression data that can be used to search and filter interaction networks. Orthologous gene mappings of Drosophila genes to other organisms are also available to facilitate finding interactions based on gene names and identifiers for a number of common model organisms and humans. Improvements have been made to the web and graphical interfaces to help biologists gain a comprehensive view of the interaction networks relevant to the genes and systems that they study.

DroID: the Drosophila Interactions Database, a comprehensive resource for annotated gene and protein interactions

BACKGROUND

Charting the interactions among genes and among their protein products is essential for understanding biological systems. A flood of interaction data is emerging from high throughput technologies, computational approaches, and literature mining methods. Quick and efficient access to this data has become a critical issue for biologists. Several excellent multi-organism databases for gene and protein interactions are available, yet most of these have understandable difficulty maintaining comprehensive information for any one organism. No single database, for example, includes all available interactions, integrated gene expression data, and comprehensive and searchable gene information for the important model organism, Drosophila melanogaster.

DESCRIPTION

DroID, the Drosophila Interactions Database, is a comprehensive interactions database designed specifically for Drosophila. DroID houses published physical protein interactions, genetic interactions, and computationally predicted interactions, including interologs based on data for other model organisms and humans. All interactions are annotated with original experimental data and source information. DroID can be searched and filtered based on interaction information or a comprehensive set of gene attributes from Flybase. DroID also contains gene expression and expression correlation data that can be searched and used to filter datasets, for example, to focus a study on sub-networks of co-expressed genes. To address the inherent noise in interaction data, DroID employs an updatable confidence scoring system that assigns a score to each physical interaction based on the likelihood that it represents a biologically significant link.

CONCLUSION

DroID is the most comprehensive interactions database available for Drosophila. To facilitate downstream analyses, interactions are annotated with original experimental information, gene expression data, and confidence scores. All data in DroID are freely available and can be searched, explored, and downloaded through three different interfaces, including a text based web site, a Java applet with dynamic graphing capabilities (IM Browser), and a Cytoscape plug-in. DroID is available at http://www.droidb.org.

Systematic identification of factors involved in post-transcriptional processes in wheat grain

Post-transcriptional processing of primary transcripts can significantly affect both the quantity and the structure of mature mRNAs and the corresponding protein products. It is an important mechanism of gene regulation in animals, yeast and plants. Here we have investigated the interactive networks of pre-mRNA processing factors in the developing grain of wheat (Triticum aestivum), one of the world's major food staples. As a first step we isolated a homologue of the plant specific AtRSZ33 splicing factor, which has been shown to be involved in the early stages of embryo development in Arabidopsis. Real-time PCR showed that the wheat gene, designated TaRSZ38, is expressed mainly in young, developing organs (flowers, root, stem), and expression peaks in immature grain. In situ hybridization and immunodetection revealed preferential abundance of TaRSZ38 in mitotically active tissues of the major storage organ of the grain, the endosperm. The protein encoded by TaRSZ38 was subsequently used as a starting bait in a two-hybrid screen to identify additional factors in grain that are involved in pre-mRNA processing. Most of the identified proteins showed high homology to known splicing factors and splicing related proteins, supporting a role for TaRSZ38 in spliceosome formation and 5' site selection. Several clones were selected as baits in further yeast two-hybrid screens. In total, cDNAs for 16 proteins were isolated. Among these proteins, TaRSZ22, TaSRp30, TaU1-70K, and the large and small subunits of TaU2AF, are wheat homologues of known plant splicing factors. Several, additional proteins are novel for plants and show homology to known pre-mRNA splicing, splicing related and mRNA export factors from yeast and mammals.

Illuminating drug discovery with biological pathways

Systems biology promises to impact significantly on the drug discovery process. One of its ultimate goals is to provide an understanding of the complete set of molecular mechanisms describing an organism. Although this goal is a long way off, many useful insights can already come from currently available information and technology. One of the biggest challenges in drug discovery today is the high attrition rate: many promising candidates prove ineffective or toxic owing to a poor understanding of the molecular mechanisms of biological systems they target. A "systems" approach can help identify pathways related to a disease and can suggest secondary effects of drugs that might cause these problems and thus ultimately improve the drug discovery pipeline.

Model systems in drug discovery: chemical genetics meets genomics

Animal model systems are an intricate part of the discovery and development of new medicines. The sequencing of not only the human genome but also those of the various pathogenic bacteria, the nematode Caenorhabditis elegans, the fruitfly Drosophila, and the mouse has enabled the discovery of new drug targets to push forward at an unprecedented pace. The knowledge and tools in these "model" systems are allowing researchers to carry out experiments more efficiently and are uncovering previously hidden biological connections. While the history of bacteria, yeast, and mice in drug discovery are long, their roles are ever evolving. In contrast, the history of Drosophila and C. elegans at pharmaceutical companies is short. We will briefly review the historic role of each model organism in drug discovery and then update the readers as to the abilities and liabilities of each model within the context of drug development.

Two-hybrid arrays

The two-hybrid system is a genetic method for detecting protein-protein interactions. The assay can be applied to random libraries or arrays of colonies that express defined pairs of proteins. Arrays enable the testing of all possible protein pairs for interactions in a systematic fashion. The array format makes a large number of individual assays comparable and thus greatly simplifies the identification of false positives. Two-hybrid arrays have been used to study interactions among the proteins of yeast, hepatitis C virus, vaccinia virus, Drosophila, Caenorhabditis elegans, mouse and other species, and have already identified thousands of interactions.

Mapping protein-protein interactions with combinatorial biology methods

Extremely diverse, DNA-encoded libraries of peptides and proteins have been constructed that include a linkage between each polypeptide and the encoding DNA. Library members can be selected by virtue of a particular binding specificity, and their protein sequence can be deduced from the sequence of the cognate DNA. Such combinatorial biology methods have proven invaluable in both identifying natural protein-protein interactions and also in mapping the specificities and energetics of these interactions in fine detail.