The Drosophila Interactions Database: Integrating The Interactome And Transcriptome

In this thesis I describe the integration of heterogeneous interaction data for Drosophila into DroID, the Drosophilainteractions database, making it a one-stop public resource for interaction data. I have also made it possible to filter the interaction data using gene expression data to generate context-relevant networks making DroID a one-of-a kind resource for biologists. In the two years since the upgraded DroID has been available, several studies have used the heterogeneous interaction data in DroID to advance our understanding of Drosophila biology thus validating the need for such a resource for biologists. In addition to this, I have identified organizing principles of interaction networks based on genome-wide gene expression data in the tissues and the entire life cycle of Drosophila. I have shown that all tissues and stages have a core ubiquitously expressed PPI network to which tissue and stage specific proteins attach to potentially modulate specific functions. In view of these organizing principles, I developed a normalized expression filter for interaction networks. I have shown that networks generated by using this filter are context-relevant as evidenced by their enrichment for genes with relevant mutant phenotypes. This filter has been implemented in DroID and I anticipate that studies on interactome networks using this filter will further our understanding of biology

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

Identification of New Protein Interactions between Dengue Fever Virus and Its Hosts, Human and Mosquito

<div><p>The four divergent serotypes of dengue virus are the causative agents of dengue fever, dengue hemorrhagic fever and dengue shock syndrome. About two-fifths of the world's population live in areas where dengue is prevalent, and thousands of deaths are caused by the viruses every year. Dengue virus is transmitted from one person to another primarily by the yellow fever mosquito, <em>Aedes aegypti</em>. Recent studies have begun to define how the dengue viral proteins interact with host proteins to mediate viral replication and pathogenesis. A combined analysis of these studies, however, suggests that many virus-host protein interactions remain to be identified, especially for the mosquito host. In this study, we used high-throughput yeast two-hybrid screening to identify mosquito and human proteins that physically interact with dengue proteins. We tested each identified host protein against the proteins from all four serotypes of dengue to identify interactions that are conserved across serotypes. We further confirmed many of the interactions using co-affinity purification assays. As in other large-scale screens, we identified some previously detected interactions and many new ones, moving us closer to a complete host – dengue protein interactome. To help summarize and prioritize the data for further study, we combined our interactions with other published data and identified a subset of the host-dengue interactions that are now supported by multiple forms of evidence. These data should be useful for understanding the interplay between dengue and its hosts and may provide candidates for drug targets and vector control strategies.</p> </div

Pie charts showing the number of host proteins that interacted with the corresponding proteins from one, two, three, or all four dengue serotypes.

<p>(A) Mosquito proteins. (B) Human proteins.</p

Number of host interactors for each dengue protein identified in this study by yeast two-hybrid screens.

<p>Number of host interactors for each dengue protein identified in this study by yeast two-hybrid screens.</p

Dengue-host interactions supported by multiple forms of evidence.

<p>(A) Dengue-human interactome. (B) Dengue-mosquito interactome. Pink nodes represent host proteins. Green nodes represent dengue proteins. Red edges represent PPI with conserved interologs. Additional details are available in Cytoscape files in supplemental data (Data S1).</p

Dengue – host protein networks derived from two-hybrid screens and co-AP assays in this study.

<p>(A) Human-dengue interaction map. (B) Mosquito-dengue interaction map. Edges represent protein-protein interactions. Green nodes are dengue proteins, yellow nodes are host proteins, and blue nodes are host proteins found in both the human and mosquito maps. Red edges represent protein-protein interactions universally detected for all four serotypes. Blue edges represent protein-protein interactions confirmed by co-AP assays. Green edges represent the universal interactions that were confirmed by co-AP assays. Additional details are available in Cytoscape files in supplemental data (Data S1).</p

Dengue virus proteins.

<p>(A) The dengue polyprotein in the ER membrane prior to processing. (B) The coding regions for the fourteen dengue virus proteins and partial peptides shown were separately cloned into yeast two-hybrid plasmids.</p

Examples of co-AP results.

<p>Host proteins were fused to a myc-tag while dengue proteins were fused to an NTAP-tag. The fusion proteins were expressed in S2R+ cells. NTAP-dengue proteins were purified from cell lysates, and then host proteins were detected with α-myc. (A) An α-myc immunoblot of cell lysates shows expression of mosquito and human proteins. (B) An α-myc immunoblot of NTAP-tag affinity-purified samples. Additional co-AP results are in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053535#pone.0053535.s014" target="_blank">Figure S3</a>.</p