The innate immune system represents the first line of defense against attack by viral, bacterial, and parasitic infections. Dendritic cells (DCs), which are found in abundance in peripheral tissues such as skin, lung, and mucosal surfaces, act as a bridge between the innate and adaptive immune systems: recognition of a 'danger' signal initiates the maturation of DCs, which ultimately activate cells of the adaptive arm of the immune system, B and T cells [1
]. DCs express receptors that recognize and bind a large array of epitopes or antigens common to many bacterial or viral pathogens; once an antigen is recognized, it is internalized, processed, and presented at the cell surface in association with molecules of the major histocompatibility complex (MHC). DC maturation is characterized by up-regulation of the MHC molecules, production of cytokines, chemokines and co-stimulatory molecules, and migration of DCs to lymphoid tissues, i.e. the spleen and the lymph nodes (for review, see [3
]). Research efforts have aimed at understanding the DC signaling and effector pathways that direct this cell's crucial role in immunity. A graphical representation of those signaling pathways as a biological system would provide an easily accessible, integrated view of the literature in this field to the scientific community.
DCs detect pathogens via pattern recognition receptors (PRRs), which recognize various molecular structures referred to as pathogen-associated molecular patterns (PAMPs), e.g. lipopolysaccharides, lipoteichoic acids, flagellin and nucleic acids. Membrane-associated PRRs, like the Toll-like receptors (TLRs) and C-type lectin receptors (CLRs) respond to extracellular pathogens, while cytosolic PRRs, including RIG-I-like receptors (RLRs) and NOD-like receptors (NLRs) sense intracellular pathogens [5
]. Pathogen recognition activates an intracellular signaling cascade, which results in the expression of type I interferons (IFNs), as well as other inflammatory response genes. Secreted IFNs bind to cell surface receptors and activate the JAK-STAT pathway in an autocrine and paracrine fashion [8
]. A resource that facilitates access to information on the molecular networks that underlie DC signaling responses to various pathogens would assist research on antibacterial and antiviral therapy. Furthermore, it might benefit the development of DC vaccines against cancers and autoimmune diseases, as manipulating DCs in vitro
and rendering them responsive to tumor antigens may lead to tumor regression [10
]. Traditional representations of molecular pathways may be found in reviews. A web-based pathway diagram complements these reviews by giving more direct access to continually updated literature information in a pathway format. Also a pathway-based resource can be used directly for computational studies. SBML is a computer-readable format for representing models of biological processes [11
]. Therefore, an optimal pathway diagram should focus on a whole biological system rather than a part of it, comply with a standard format, such as the Systems Biology Mark-up Language (SBML; http://sbml.org/
), and be accessible to the community for updates and corrections.
Current databases of signaling networks of the innate immune response include free online resources such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway database http://www.genome.jp/kegg/pathway.html
], Reactome, which is a curated knowledgebase of biological pathways http://www.reactome.org/cgi-bin/frontpage?DB=gk_current
], Science's Signal Transduction Knowledge Environment (STKE; http://stke.sciencemag.org/cm/
) biological pathways database, and Ingenuity Systems, a commercial subscription-based knowledgebase. The KEGG pathways do not integrate all PRRs, but rather depict each type of PRR-derived pathway separately and with little detail. Although Reactome is abundantly annotated and organism-specific, it does not provide cell-type specific information. STKE features 19 immunity-related pathways, the majority of which, however, have not been updated in recent years. Similar to Reactome, Ingenuity Systems offers a great diversity of annotations, including literature references from various biological models and many other database resources, yet it presents a fairly basic version of each signaling network and is not cell-type specific. In contrast, the group of Kitano [14
] constructed a comprehensive map of TLRs and interleukin 1 receptor signaling networks based on published literature; the TLR pathway map, created in CellDesigner [15
], is comprised of 652 species and 444 reactions and complies with SBML. However, it lacks a means for community-wide feedback, which would considerably help experts in the field to directly participate in the map update, and is not cell-type specific.
Based on a manual curation of the published literature, we have assembled an extensive and detailed map of the signaling pathways involved in DC response to pathogens, as described in human DCs and mouse models. The DC pathway map, which is web-accessible, includes the following annotations: a list of interactions, GeneIDs, PubMed IDs (PMIDs), along with summary notes. In order to provide a discussion forum for the community and an opportunity for direct feedback and contribution, we have linked the DC map to a public wiki. Thus, it should represent a valuable resource for the research community, and conceivably initiate a community-wide interactive process. Additionally, using computational methods we delineated the regulatory motifs that are present in the DC signaling network.