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)

Vol. 36 3 272-281

Subject Categories

Biochemistry and Molecular Biology

Bioinformatics (Computational Biology)

Bioinformatics and Systems Biology

DOI

10.1038/nbt.4072

More information

Latest update

4/4/2018 9