The Bioinformatics Core is located in the Center for Computational and Integrative Biology (CCIB) at Massachusetts General Hospital, and at the Broad Institute of MIT and Harvard. The core has expertise in the analysis of large-scale datasets and facilitates integrative systems biology approaches.
The specific aims of the Bioinformatics Core in the MGH/Harvard AADCRC Program are to provide the necessary expertise: 1) To analyze gene expression data generated in Projects 1, 2 and 3 and determine transcriptional patterns across clinically relevant phenotypic states to identify context-specific biological networks and pathway modules underlying these states. For project 1, comparative expression profiling will be conducted to identify differentially expressed genes between allergen-specific versus bulk CD4[+] T cells in allergic asthmatics versus allergic non-asthmatics. For project 2, longitudinal expression analysis will be performed across multiple CD4[+] T cell subsets during oral immunotherapy. For project 3, differential expression will be examined across stimulation conditions and time-points for each of the four DC subpopulations (towards becoming tolerogenic itDC), and then across the DC subpopulations for each stimulation condition and time-point. A similar analysis will also be conducted for T cell subsets following exposure to itDCs. A number of analytical methods will be implemented as appropriate, and these include dynamic factor analysis, analysis of factorial design or nearest neighborhood (correlation) analysis. 2) To define core expression signatures to facilitate the development of NanoString code sets for further highly multiplexed quantitative expression analyses and prospective data collection. 3) To integrate multiple data types to facilitate a 'systems-wide' understanding. Clusters of differentially expressed genes identified in the respective comparisons will be examined for enrichment of functional gene sets such as those associated with biological processes and pathways. The Bioinformatics Core will identify pathway-associated network modules and build functional enrichment maps to guide experimentally focused investigations into the complex molecular mechanisms underpinning asthma, allergic diseases and allergen-specific tolerance induction. The integration of orthogonal data interrogated from multiple sources, including protein-protein interactions, transcription factor-binding data and other publicly available expression datasets will allow us to extend our analysis to gain additional 'systems-wide'insights about the structure of regulatory circuits, signaling networks and pathways involved in the pathogenesis of asthma and food allergy.
The sophisticated analysis offered by the Bioinformatics Core will also allow Center investigators to identify previously unrecognized T cell and DCs phenotypes associated with driving allergic airways inflammation and airways hyper-reactivity as well as allergen-specific tolerance induction in oral immunotherapy and following tolerogenic DC therapy.
|Riol-Blanco, Lorena; Ordovas-Montanes, Jose; Perro, Mario et al. (2014) Nociceptive sensory neurons drive interleukin-23-mediated psoriasiform skin inflammation. Nature 510:157-61|
|Millet, Yves A; Alvarez, David; Ringgaard, Simon et al. (2014) Insights into Vibrio cholerae intestinal colonization from monitoring fluorescently labeled bacteria. PLoS Pathog 10:e1004405|
|Griffith, Jason W; Luster, Andrew D (2013) Targeting cells in motion: migrating toward improved therapies. Eur J Immunol 43:1430-5|
|Sperandio, Markus; Quackenbush, Elizabeth J; Sushkova, Natalia et al. (2013) Ontogenetic regulation of leukocyte recruitment in mouse yolk sac vessels. Blood 121:e118-28|
|Islam, Sabina A; Ling, Morris F; Leung, John et al. (2013) Identification of human CCR8 as a CCL18 receptor. J Exp Med 210:1889-98|
|Wang, Chen; Yi, Tai; Qin, Lingfeng et al. (2013) Rapamycin-treated human endothelial cells preferentially activate allogeneic regulatory T cells. J Clin Invest 123:1677-93|
|Hariri, Lida P; Applegate, Matthew B; Mino-Kenudson, Mari et al. (2013) Volumetric optical frequency domain imaging of pulmonary pathology with precise correlation to histopathology. Chest 143:64-74|
|Giallourakis, Cosmas C; Benita, Yair; Molinie, Benoit et al. (2013) Genome-wide analysis of immune system genes by expressed sequence Tag profiling. J Immunol 190:5578-87|
|Afshar, Roshi; Strassner, James P; Seung, Edward et al. (2013) Compartmentalized chemokine-dependent regulatory T-cell inhibition of allergic pulmonary inflammation. J Allergy Clin Immunol 131:1644-52|
|Harris, R Scott; Venegas, Jose G; Wongviriyawong, Chanikarn et al. (2011) 18F-FDG uptake rate is a biomarker of eosinophilic inflammation and airway response in asthma. J Nucl Med 52:1713-20|