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Network-based prediction of human tissue-specific metabolism

Nature Biotechnology volume 26, pages 10031010 (2008) | Download Citation

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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.

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Acknowledgements

We are grateful to Shiri Freilich and Ben Sandbank for helpful comments and suggestions. We wish to thank the reviewers for their constructive remarks that helped improve this manuscript considerably. T.S. is supported by an Eshkol Fellowship from the Israeli Ministry of Science. M.C. is a fellow of the Edmond J. Safra Program in Tel-Aviv University. M.J.H. was supported by National Institutes of Health grant no. GM071808. This research was supported by grants from the Israeli Science Foundation, the German-Israeli Foundation and the Tauber fund to E.R.

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Author notes

    • Tomer Shlomi
    •  & Moran N Cabili

    These authors contributed equally to this work.

Affiliations

  1. School of Computer Science, Tel-Aviv University, Tel-Aviv 69978, Israel.

    • Tomer Shlomi
    • , Moran N Cabili
    •  & Eytan Ruppin
  2. Department of Bioengineering, University of California, San Diego, La Jolla, California 92093-0412, USA.

    • Markus J Herrgård
    •  & Bernhard Ø Palsson
  3. School of Medicine, Tel-Aviv University, Tel-Aviv 69978, Israel.

    • Eytan Ruppin

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Correspondence to Tomer Shlomi or Eytan Ruppin.

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DOI

https://doi.org/10.1038/nbt.1487