Integration of clinical data with a genome-scale metabolic model of the human adipocyte
Artikel i vetenskaplig tidskrift, 2013

We evaluated the presence/absence of proteins encoded by 14 077 genes in adipocytes obtained from different tissue samples using immunohistochemistry. By combining this with previously published adipocyte-specific proteome data, we identified proteins associated with 7340 genes in human adipocytes. This information was used to reconstruct a comprehensive and functional genome-scale metabolic model of adipocyte metabolism. The resulting metabolic model, iAdipocytes1809, enables mechanistic insights into adipocyte metabolism on a genome-wide level, and can serve as a scaffold for integration of omics data to understand the genotype-phenotype relationship in obese subjects. By integrating human transcriptome and fluxome data, we found an increase in the metabolic activity around androsterone, ganglioside GM2 and degradation products of heparan sulfate and keratan sulfate, and a decrease in mitochondrial metabolic activities in obese subjects compared with lean subjects. Our study hereby shows a path to identify new therapeutic targets for treating obesity through combination of high throughput patient data and metabolic modeling.

genome-scale metabolic model

obesity

adipocyte

flux balance analysis

proteome

Författare

Adil Mardinoglu

Kemi- och bioteknik, Livsvetenskaper, Systembiologi

Rasmus Ågren

Kemi- och bioteknik, Livsvetenskaper, Systembiologi

C. Kampf

Uppsala universitet

A. Asplund

Uppsala universitet

Intawat Nookaew

Kemi- och bioteknik, Livsvetenskaper, Systembiologi

Peter Jacobson

Göteborgs universitet

A. J. Walley

Hammersmith Hospital

P. Froguel

Hammersmith Hospital

CNRS Centre National de la Recherche Scientifique

Lena M S Carlsson

Göteborgs universitet

M. Uhlen

AlbaNova University Center

Jens B Nielsen

Kemi- och bioteknik, Livsvetenskaper, Systembiologi

Molecular Systems Biology

1744-4292 (ISSN)

Vol. 9 649-

Infrastruktur

C3SE (Chalmers Centre for Computational Science and Engineering)

Styrkeområden

Livsvetenskaper och teknik

Ämneskategorier

Bioinformatik och systembiologi

DOI

10.1038/msb.2013.5