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Nature Research, Nature Biotechnology, 5(31), p. 419-425, 2013

DOI: 10.1038/nbt.2488

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A community-driven global reconstruction of human metabolism

Journal article published in 2013 by Ines Thiele ORCID, Neil Swainston, Ronan M. T. Fleming, Andreas Hoppe, Swagatika Sahoo, Maike K. Aurich, Hulda Haraldsdottir, Monica L. Mo, Ottar Rolfsson, Miranda D. Stobbe, Stefan G. Thorleifsson, Rasmus Agren, Christian Bölling, Sergio Bordel, Arvind K. Chavali and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including similar to 2x more reactions and similar to 1.7x more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/. ; Times Cited: 0