Network-based prediction of human tissue-specific metabolism.

Abstract

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.

DOI: 10.1038/nbt.1487

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@article{Shlomi2008NetworkbasedPO, title={Network-based prediction of human tissue-specific metabolism.}, author={Tomer Shlomi and Moran N. Cabili and Markus J. Herrg{\aa}rd and Bernhard O. Palsson and Eytan Ruppin}, journal={Nature biotechnology}, year={2008}, volume={26 9}, pages={1003-10} }