InnateDB: facilitating systems-level analyses of the mammalian innate immune response

Abstract

Although considerable progress has been made in dissecting the signaling pathways involved in the innate immune response, it is now apparent that this response can no longer be productively thought of in terms of simple linear pathways. InnateDB (www.innatedb.ca) has been developed to facilitate systems-level analyses that will provide better insight into the complex networks of pathways and interactions that govern the innate immune response. InnateDB is a publicly available, manually curated, integrative biology database of the human and mouse molecules, experimentally verified interactions and pathways involved in innate immunity, along with centralized annotation on the broader human and mouse interactomes. To date, more than 3500 innate immunity-relevant interactions have been contextually annotated through the review of 1000 plus publications. Integrated into InnateDB are novel bioinformatics resources, including network visualization software, pathway analysis, orthologous interaction network construction and the ability to overlay user-supplied gene expression data in an intuitively displayed molecular interaction network and pathway context, which will enable biologists without a computational background to explore their data in a more systems-oriented manner.

Figure 1

Integration of publicly available resources as a foundation for InnateDB. More than 100 000 interactions were integrated into InnateDB from the Molecular Interaction (MINT) database (Chatr-aryamontri et al, 2007); the IntAct database (Kerrien et al, 2007); the Database of Interacting Proteins (DIP) (Salwinski et al, 2004); the General Repository for Interaction Datasets (BioGRID) (Breitkreutz et al, 2007) and the Biomolecular Interaction Network Database (BIND) (Alfarano et al, 2005). Cross-references to more than 2500 pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database (Kanehisa et al, 2007), the NCI-Nature Pathway Interaction Database (PID) (http://pid.nci.nih.gov), Integrating Network Objects with Hierarchies (INOH) pathway database (http://www.inoh.org/), NetPath (http://www.netpath.org) and the Reactome database (Joshi-Tope et al, 2005) were also incorporated. Up-to-date versions of Ensembl (www.ensembl.org) provide details of human and mouse genes, transcripts and proteins along with rich protein and gene annotation from the Universal Protein Resource (UniProt) (The UniProt Consortium, 2007), Gene Ontology (Ashburner et al, 2000) and Entrez Gene (http://www.ncbi.nlm.nih.gov/).

Figure 2

A screenshot of the InnateDB interaction search results page. Each interaction is shown alongside the interaction type (e.g. phosphorylation), the supporting publications column, which shows the number of publications in the database that support the interaction, and links to the interaction details page. This page provides further information on each interaction including annotation on the experiment, the cell type, the tissue type and links to the original publication describing the interaction. Interactions can be downloaded in a variety of formats or one can click on the Cerebral button to interactively visualize the interactions (see Figure 4).

Figure 3

A screenshot of the InnateDB pathway batch search results page. Each gene in a user-uploaded list is linked to its associated pathways. If fold changes in gene expression values are included in the uploaded file, they are shown alongside each gene and can subsequently be used in the pathway over-representation analysis (by clicking the red Pathway ORA button at the top of the page) to determine which pathways are significantly associated with differentially regulated genes.

Figure 4

Cerebral enables the overlay of quantitative data in a molecular interaction network context. To facilitate the side-by-side comparison of specific experimental conditions, Cerebral uses a series of small, linked views to visualize quantitative data (gene expression values, for example) across multiple conditions simultaneously, alongside a larger central window, which permits more detailed investigation of particular conditions or regions of the network. Nodes (i.e. molecules) are colored according to user-defined thresholds of fold change in gene expression (red, significantly upregulated; green, significantly downregulated). The small multiple windows and the larger overview window are linked––if one zooms in or out, pans, mouses over or selects a node in one of the views, the same action will be perpetuated across all views. By selecting one of the small multiple windows, the expression values for that condition will be promoted to the larger overview window. If two small multiple windows are selected simultaneously, the difference in gene expression in the two conditions is computed and displayed in the main window. In this view, the nodes in the main window are colored according to the magnitude of the change between the two conditions. InnateDB uses the number of pieces of evidence supporting an interaction, usually separate publications or experiments, as a measure of confidence in the interaction. Cerebral uses weighted lines in its display to represent these confidence scores (heavier weighted lines=higher confidence). By right clicking on a node or edge, one may interactively link to the relevant pages in InnateDB for more detailed annotation regarding the gene, protein or interaction of interest.