A community-driven global reconstruction of human metabolism
Artikel i vetenskaplig tidskrift, 2013

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/.

Författare

I. Thiele

Háskóli Íslands

N. Swainston

University of Manchester

R. M. T. Fleming

Háskóli Íslands

A. Hoppe

Charité Universitätsmedizin Berlin

S. Sahoo

Háskóli Íslands

M. K. Aurich

Háskóli Íslands

H. Haraldsdottir

Háskóli Íslands

M. L. Mo

University of California

O. Rolfsson

Háskóli Íslands

M. D. Stobbe

Netherlands Bioinformatics Centre - NBIC

Universiteit Van Amsterdam

S. G. Thorleifsson

Háskóli Íslands

Rasmus Ågren

Chalmers, Kemi- och bioteknik, Livsvetenskaper, Systembiologi

C. Bolling

Charité Universitätsmedizin Berlin

Sergio Velasco

Chalmers, Kemi- och bioteknik, Livsvetenskaper, Systembiologi

A. K. Chavali

University of Virginia

P. Dobson

University of Sheffield

W. B. Dunn

Christie Hospital NHS Foundation Trust

University of Manchester

L. Endler

Universität Wien

D. Hala

University of North Texas

M. Hucka

CalTech

D. Hull

University of Manchester

D. Jameson

University of Manchester

N. Jamshidi

University of California

J. J. Jonsson

Háskóli Íslands

N. Juty

European Bioinformatics Institute

S. Keating

European Bioinformatics Institute

Intawat Nookaew

Chalmers, Kemi- och bioteknik, Livsvetenskaper, Systembiologi

N. Le Novere

European Bioinformatics Institute

The Babraham Institute

N. Malys

The University of Warwick

University of Manchester

A. Mazein

University of Edinburgh

J. A. Papin

University of Virginia

N. D. Price

Institute for Systems Biology

E. Selkov

Genome Designs, Inc.

M. I. Sigurdsson

Háskóli Íslands

E. Simeonidis

Université du Luxembourg

Institute for Systems Biology

N. Sonnenschein

Jacobs University Bremen

K. Smallbone

University of Manchester

A. Sorokin

Russian Academy of Sciences

University of Edinburgh

Jhgm van Beek

Netherlands Consortium for Systems Biology

VU University Medical Center

VU University Amsterdam

D. Weichart

University of Manchester

I. Goryanin

University of Edinburgh

Okinawa Institute of Science and Technology Graduate University

Jens B Nielsen

Chalmers, Kemi- och bioteknik, Livsvetenskaper, Systembiologi

H.V. Westerhoff

VU University Amsterdam

University of Manchester

Swammerdam Institute for Life Sciences

D. B. Kell

University of Manchester

P. Mendes

Virginia Polytechnic Institute and State University

University of Manchester

B. O. Palsson

University of California

Háskóli Íslands

Nature Biotechnology

1087-0156 (ISSN)

Vol. 31 5 419-+

Styrkeområden

Informations- och kommunikationsteknik

Livsvetenskaper och teknik

Ämneskategorier

Mikrobiologi

DOI

10.1038/nbt.2488