Recon3D enables a three-dimensional view of gene variation in human metabolism
Journal article, 2018
Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. These data provide a unique resource for investigating molecular mechanisms of human metabolism. Recon3D is available at http://vmh.life.
Author
Elizabeth Brunk
University of California
Technical University of Denmark (DTU)
S. Sahoo
University of Luxembourg
Daniel C. Zielinski
University of California
Ali Altunkaya
Arizona State University
San Diego Supercomputer Center
Andreas Dräger
University of Tübingen
Nathan Mih
University of California
Francesco Gatto
University of California
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Avlant Nilsson
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
German Andres Preciat Gonzalez
University of Luxembourg
M. K. Aurich
University of Luxembourg
Andreas Prlic
San Diego Supercomputer Center
Anand Sastry
University of California
Anna D. Danielsdottir
University of Luxembourg
Almut Heinken
University of Luxembourg
Alberto Noronha
University of Luxembourg
Peter W. Rose
San Diego Supercomputer Center
Stephen K. Burley
San Diego Supercomputer Center
Rutgers Cancer Institute of New Jersey
R. M. T. Fleming
Leiden University
University of Luxembourg
Jens Christian Froslev Nielsen
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Technical University of Denmark (DTU)
I. Thiele
University of Luxembourg
B. O. Palsson
Technical University of Denmark (DTU)
University of California
Nature Biotechnology
1087-0156 (ISSN) 15461696 (eISSN)
Vol. 36 3 272-281Subject Categories
Biochemistry and Molecular Biology
Bioinformatics (Computational Biology)
Bioinformatics and Systems Biology
DOI
10.1038/nbt.4072