|Title||Network-based prediction of human tissue-specific metabolism.|
|Publication Type||Journal Article|
|Year of Publication||2008|
|Authors||Shlomi T, Cabili MN, Herrgard MJ, Palsson BØ, Ruppin E|
|PubMed Date||2008 Sep|
|Keywords||Cell Physiological Phenomena, Computational Biology, Databases, Protein, Gene Expression Profiling, Gene Expression Regulation, Genome, Human, Humans, Metabolic Networks and Pathways, Models, Genetic, Models, Statistical, Reproducibility of Results, Software|
Direct in vivo investigation of mammalian metabolism is complicated by the distinct metabolic functions of different tissues. We present a computational method that successfully describes the tissue specificity of human metabolism on a large scale. By integrating tissue-specific gene- and protein-expression data with an existing comprehensive reconstruction of the global human metabolic network, we predict tissue-specific metabolic activity in ten human tissues. This reveals a central role for post-transcriptional regulation in shaping tissue-specific metabolic activity profiles. The predicted tissue specificity of genes responsible for metabolic diseases and tissue-specific differences in metabolite exchange with biofluids extend markedly beyond tissue-specific differences manifest in enzyme-expression data, and are validated by large-scale mining of tissue-specificity data. Our results establish a computational basis for the genome-wide study of normal and abnormal human metabolism in a tissue-specific manner.
|Alternate Journal||Nat. Biotechnol.|