Research
DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells
1 Department of Pharmacology, University of Firenze, Firenze, Italy
2 Department of Tumor Immunology, NCMLS, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
3 Department of Biology, University of Padua, Padova, Italy
4 Department of Cell Biology and Neurosciences, Istituto Superiore di Sanità, Roma, Italy
5 Department of Pathology and Immunology, Faculty of Medicine, University of Geneva, Geneva, Switzerland
6 Department of Dermatology, University of Erlangen, Erlangen, Germany
7 Leaf Bioscience, Milano, Italy
8 Novartis Vaccines, Siena, Italy
9 Department of Computer Science, Wayne State University, Michigan, USA
10 Marseille-Luminy Immunology Center, Université de la Méditerranée, Marseille, France
11 Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milano, Italy
12 Department of Gastroenterology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
13 Institute of Immunology, University of Debrecen, Debrecen, Hungary
14 Department of Immunohematology and Bloodtransfusion, Leiden University Medical Center, Leiden, The Netherlands
15 Miravtech Corporation, Michigan, USA
16 Department of Immunology, Institute Curie, Paris, France
17 Department of Clinic Physiopathology, University of Firenze, Firenze, Italy
18 Nuffield Department of Surgery, University of Oxford, Oxford, UK
Immunome Research 2010, 6:10 doi:10.1186/1745-7580-6-10
Published: 19 November 2010Abstract
Background
The advent of Systems Biology has been accompanied by the blooming of pathway databases. Currently pathways are defined generically with respect to the organ or cell type where a reaction takes place. The cell type specificity of the reactions is the foundation of immunological research, and capturing this specificity is of paramount importance when using pathway-based analyses to decipher complex immunological datasets. Here, we present DC-ATLAS, a novel and versatile resource for the interpretation of high-throughput data generated perturbing the signaling network of dendritic cells (DCs).
Results
Pathways are annotated using a novel data model, the Biological Connection Markup Language (BCML), a SBGN-compliant data format developed to store the large amount of information collected. The application of DC-ATLAS to pathway-based analysis of the transcriptional program of DCs stimulated with agonists of the toll-like receptor family allows an integrated description of the flow of information from the cellular sensors to the functional outcome, capturing the temporal series of activation events by grouping sets of reactions that occur at different time points in well-defined functional modules.
Conclusions
The initiative significantly improves our understanding of DC biology and regulatory networks. Developing a systems biology approach for immune system holds the promise of translating knowledge on the immune system into more successful immunotherapy strategies.
