Abstract
Genome-wide gene-expression data from DNA-microarray technology and molecular-network data from computational text-mining have led to a paradigm shift in biological research. However, interpretation of the huge amount of data is a bottleneck. We have developed an informatics system, which we refer to as bioSpace Explorer, that can extract pathways and molecules of interest from genome-wide data and show the mutual relationships among these pathways and molecules. Differentiation of 3T3-L1 cells into adipocytes and the action of a peroxisome proliferator-activated receptor gamma (PPARγ) agonist or α-linolenic acid on this process was analyzed with bioSpace Explorer. The results suggested a biological basis for adipocyte differentiation and a strategy to enhance lipid oxidation in adipocytes. Clustered changes of molecules were apparent in the insulin, Wnt, and PPARγ signaling pathways and in the lipogenesis, lipid oxidation, and lipid transport pathways during cell differentiation. A PPARγ agonist enhanced lipid oxidation in adipocytes and α-linolenic acid gave similar results to the PPARγ agonist. An analysis of sex hormone and thyroid hormone, in addition to PPARγ signaling, suggested that these molecules are important for enhancement of lipid oxidation in adipocytes. The results indicate the utility of bioSpace Explorer for biological research on genome-wide molecular networks.
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