B-cell ligand processing pathways detected by large-scale comparative analysis.
The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies. We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses. We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands. First, we compared the degree distributions of the generated networks. Second, we utilized a pairwise network alignment algorithm, BiNA, to align the networks based on the hubs in the networks. Third, we aligned the networks based on a set of KEGG pathways. We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition. The resulting pathways were further validated through literature for their common physiological responses. Collectively, the results based on our comparative analyses of degree distributions, alignment of hubs, and alignment based on KEGG pathways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches (e.g., gene coexpression network alignment algorithms) in elucidating biochemical pathways involved in complex signaling events in cells.
Bioinformatics and Computational Biology Graduate Program, Iowa State University, Ames, IA 50010, USA. ftowfic@iastate.edu
Fadi
F
Towfic
Shakti
S
Gupta
Vasant
V
Honavar
Shankar
S
Subramaniam
D000465:Algorithms; D000818:Animals; D001402:B-Lymphocytes / Q000276:immunology* / Q000378:metabolism; D004194:Disease / Q000235:genetics; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D006801:Humans; D008024:Ligands; D051379:Mice; D015398:Signal Transduction
D008024:Ligands