Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Integration of clinical data with a genome-scale metabolic model of the human adipocyte
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular and Morphological Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular and Morphological Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Show others and affiliations
2013 (English)In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 9, 649- p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2013. Vol. 9, 649- p.
Keyword [en]
adipocyte, flux balance analysis, genome-scale metabolic model, obesity, proteome
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:uu:diva-199737DOI: 10.1038/msb.2013.5ISI: 000316960700003OAI: oai:DiVA.org:uu-199737DiVA: diva2:621009
Available from: 2013-05-13 Created: 2013-05-13 Last updated: 2017-12-06Bibliographically approved

Open Access in DiVA

fulltext(3826 kB)327 downloads
File information
File name FULLTEXT01.pdfFile size 3826 kBChecksum SHA-512
a964c8ce94d1dd1eecd300faf3977a15cc61d901462ff70821bb0b4a842174d692d0b53b7b58b2eb03c3d717d02a16e836ece71925d4a81a56df9e78b710a11a
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Authority records BETA

Kampf, CarolineAsplund, Anna

Search in DiVA

By author/editor
Kampf, CarolineAsplund, Anna
By organisation
Molecular and Morphological PathologyScience for Life Laboratory, SciLifeLab
In the same journal
Molecular Systems Biology
Medical and Health Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 327 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 413 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf