Integration of clinical data with a genome‐scale metabolic model of the human adipocyte

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....

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Bibliographic Details
Published inMolecular systems biology Vol. 9; no. 1; pp. 649 - n/a
Main Authors Mardinoglu, Adil, Agren, Rasmus, Kampf, Caroline, Asplund, Anna, Nookaew, Intawat, Jacobson, Peter, Walley, Andrew J, Froguel, Philippe, Carlsson, Lena M, Uhlen, Mathias, Nielsen, Jens
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 2013
John Wiley & Sons, Ltd
EMBO Press
Nature Publishing Group
Springer Nature
Subjects
adipocyte
Adipocytes
Adipocytes - metabolism
Androsterone - metabolism
Bioinformatics and Computational Biology
Bioinformatik och beräkningsbiologi
Biomarkers
Body Mass Index
Cardiovascular disease
Degradation products
Diabetes
EMBO21
EMBO24
flux balance analysis
G(M2) Ganglioside - metabolism
Ganglioside GM2
Gene expression
Genes
Genome, Human
genome-scale metabolic model
Genomes
Genotypes
Heparan sulfate
Heparitin Sulfate - metabolism
Humans
Identification
Immunoglobulins
Immunohistochemistry
Immunohistochemistry - methods
Integration
Keratan sulfate
Keratan Sulfate - metabolism
Lipids
Localization
Metabolism
Metabolites
Mitochondria
Mitochondria - metabolism
Models, Biological
Obesity
Obesity - genetics
Obesity - metabolism
Phenotypes
Precision medicine
Proteins
proteome
Proteome - genetics
Proteome - metabolism
Proteomes
Reproducibility of Results
Software
Sulfates
Target recognition
Therapeutic applications
Transcriptome
genome‐scale metabolic model
flux balance analysis
obesity
adipocyte
proteome
Online AccessGet full text
ISSN1744-4292
1744-4292
DOI10.1038/msb.2013.5

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Abstract 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. Combining large‐scale immunohistochemical analysis and proteomics data, 7340 gene products are identified in human adipocytes. Based on this data, a genome‐scale metabolic model is reconstructed and used to integrate clinical and transcriptome data from lean and obese subjects. Synopsis Combining large‐scale immunohistochemical analysis and proteomics data, 7340 gene products are identified in human adipocytes. Based on this data, a genome‐scale metabolic model is reconstructed and used to integrate clinical and transcriptome data from lean and obese subjects. We simulated the metabolic differences between the individuals with different body mass indexes (BMIs) using transcriptome and fluxome data. 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 are found in obese subjects compared with lean subjects. We simulated the change in lipid droplet (LD) size and found that lean subjects have large dynamic changes in LD formation compared with obese subjects. Besides enabling patient stratification, our study allows the identification of novel therapeutic targets for obesity.
AbstractList 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.
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.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.
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. Combining large‐scale immunohistochemical analysis and proteomics data, 7340 gene products are identified in human adipocytes. Based on this data, a genome‐scale metabolic model is reconstructed and used to integrate clinical and transcriptome data from lean and obese subjects. Combining large‐scale immunohistochemical analysis and proteomics data, 7340 gene products are identified in human adipocytes. Based on this data, a genome‐scale metabolic model is reconstructed and used to integrate clinical and transcriptome data from lean and obese subjects. image We simulated the metabolic differences between the individuals with different body mass indexes (BMIs) using transcriptome and fluxome data. 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 are found in obese subjects compared with lean subjects. We simulated the change in lipid droplet (LD) size and found that lean subjects have large dynamic changes in LD formation compared with obese subjects. Besides enabling patient stratification, our study allows the identification of novel therapeutic targets for obesity.
Abstract 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.
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. Combining large‐scale immunohistochemical analysis and proteomics data, 7340 gene products are identified in human adipocytes. Based on this data, a genome‐scale metabolic model is reconstructed and used to integrate clinical and transcriptome data from lean and obese subjects. Synopsis Combining large‐scale immunohistochemical analysis and proteomics data, 7340 gene products are identified in human adipocytes. Based on this data, a genome‐scale metabolic model is reconstructed and used to integrate clinical and transcriptome data from lean and obese subjects. We simulated the metabolic differences between the individuals with different body mass indexes (BMIs) using transcriptome and fluxome data. 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 are found in obese subjects compared with lean subjects. We simulated the change in lipid droplet (LD) size and found that lean subjects have large dynamic changes in LD formation compared with obese subjects. Besides enabling patient stratification, our study allows the identification of novel therapeutic targets for obesity.
Combining large-scale immunohistochemical analysis and proteomics data, 7340 gene products are identified in human adipocytes. Based on this data, a genome-scale metabolic model is reconstructed and used to integrate clinical and transcriptome data from lean and obese subjects. We simulated the metabolic differences between the individuals with different body mass indexes (BMIs) using transcriptome and fluxome data. 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 are found in obese subjects compared with lean subjects. We simulated the change in lipid droplet (LD) size and found that lean subjects have large dynamic changes in LD formation compared with obese subjects. Besides enabling patient stratification, our study allows the identification of novel therapeutic targets for obesity. 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.
We evaluated the presence/absence of proteins encoded by 14077 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. Combining large-scale immunohistochemical analysis and proteomics data, 7340 gene products are identified in human adipocytes. Based on this data, a genome-scale metabolic model is reconstructed and used to integrate clinical and transcriptome data from lean and obese subjects.
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. Combining large‐scale immunohistochemical analysis and proteomics data, 7340 gene products are identified in human adipocytes. Based on this data, a genome‐scale metabolic model is reconstructed and used to integrate clinical and transcriptome data from lean and obese subjects. Synopsis Combining large‐scale immunohistochemical analysis and proteomics data, 7340 gene products are identified in human adipocytes. Based on this data, a genome‐scale metabolic model is reconstructed and used to integrate clinical and transcriptome data from lean and obese subjects. We simulated the metabolic differences between the individuals with different body mass indexes (BMIs) using transcriptome and fluxome data. 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 are found in obese subjects compared with lean subjects. We simulated the change in lipid droplet (LD) size and found that lean subjects have large dynamic changes in LD formation compared with obese subjects. Besides enabling patient stratification, our study allows the identification of novel therapeutic targets for obesity.
Author Mardinoglu, Adil
Jacobson, Peter
Kampf, Caroline
Nielsen, Jens
Carlsson, Lena M
Uhlen, Mathias
Walley, Andrew J
Asplund, Anna
Nookaew, Intawat
Agren, Rasmus
Froguel, Philippe
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  givenname: Adil
  surname: Mardinoglu
  fullname: Mardinoglu, Adil
  organization: Department of Chemical and Biological Engineering, Chalmers University of Technology
– sequence: 2
  givenname: Rasmus
  surname: Agren
  fullname: Agren, Rasmus
  organization: Department of Chemical and Biological Engineering, Chalmers University of Technology
– sequence: 3
  givenname: Caroline
  surname: Kampf
  fullname: Kampf, Caroline
  organization: Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University
– sequence: 4
  givenname: Anna
  surname: Asplund
  fullname: Asplund, Anna
  organization: Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University
– sequence: 5
  givenname: Intawat
  surname: Nookaew
  fullname: Nookaew, Intawat
  organization: Department of Chemical and Biological Engineering, Chalmers University of Technology
– sequence: 6
  givenname: Peter
  surname: Jacobson
  fullname: Jacobson, Peter
  organization: Department of Molecular and Clinical Medicine and Center for Cardiovascular and Metabolic Research, Sahlgrenska Academy, University of Gothenburg
– sequence: 7
  givenname: Andrew J
  surname: Walley
  fullname: Walley, Andrew J
  organization: Department of Genomics of Common Diseases, School of Public Health, Imperial College London, Hammersmith Hospital
– sequence: 8
  givenname: Philippe
  surname: Froguel
  fullname: Froguel, Philippe
  organization: Department of Genomics of Common Diseases, School of Public Health, Imperial College London, Hammersmith Hospital, Unité Mixte de Recherche 8199, Centre National de Recherche Scientifique (CNRS) and Pasteur Institute
– sequence: 9
  givenname: Lena M
  surname: Carlsson
  fullname: Carlsson, Lena M
  organization: Department of Molecular and Clinical Medicine and Center for Cardiovascular and Metabolic Research, Sahlgrenska Academy, University of Gothenburg
– sequence: 10
  givenname: Mathias
  surname: Uhlen
  fullname: Uhlen, Mathias
  organization: Department of Proteomics, School of Biotechnology, AlbaNova University Center, Royal Institute of Technology (KTH)
– sequence: 11
  givenname: Jens
  surname: Nielsen
  fullname: Nielsen, Jens
  email: nielsenj@chalmers.se
  organization: Department of Chemical and Biological Engineering, Chalmers University of Technology, Department of Chemical and Biological Engineering, Chalmers University of Technology
BackLink https://www.ncbi.nlm.nih.gov/pubmed/23511207$$D View this record in MEDLINE/PubMed
https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-122122$$DView record from Swedish Publication Index
https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-199737$$DView record from Swedish Publication Index
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Issue 1
Keywords genome‐scale metabolic model
flux balance analysis
obesity
adipocyte
proteome
Language English
License Attribution-NonCommercial-ShareAlike
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SSID ssj0038182
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Snippet We evaluated the presence/absence of proteins encoded by 14 077 genes in adipocytes obtained from different tissue samples using immunohistochemistry. By...
We evaluated the presence/absence of proteins encoded by 14077 genes in adipocytes obtained from different tissue samples using immunohistochemistry. By...
Combining large-scale immunohistochemical analysis and proteomics data, 7340 gene products are identified in human adipocytes. Based on this data, a...
We evaluated the presence/absence of proteins encoded by 14 077 genes in adipocytes obtained from different tissue samples using immunohistochemistry. By...
Abstract We evaluated the presence/absence of proteins encoded by 14 077 genes in adipocytes obtained from different tissue samples using immunohistochemistry....
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SubjectTerms adipocyte
Adipocytes
Adipocytes - metabolism
Androsterone - metabolism
Bioinformatics and Computational Biology
Bioinformatik och beräkningsbiologi
Biomarkers
Body Mass Index
Cardiovascular disease
Degradation products
Diabetes
EMBO21
EMBO24
flux balance analysis
G(M2) Ganglioside - metabolism
Ganglioside GM2
Gene expression
Genes
Genome, Human
genome-scale metabolic model
Genomes
Genotypes
Heparan sulfate
Heparitin Sulfate - metabolism
Humans
Identification
Immunoglobulins
Immunohistochemistry
Immunohistochemistry - methods
Integration
Keratan sulfate
Keratan Sulfate - metabolism
Lipids
Localization
Metabolism
Metabolites
Mitochondria
Mitochondria - metabolism
Models, Biological
Obesity
Obesity - genetics
Obesity - metabolism
Phenotypes
Precision medicine
Proteins
proteome
Proteome - genetics
Proteome - metabolism
Proteomes
Reproducibility of Results
Software
Sulfates
Target recognition
Therapeutic applications
Transcriptome
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Title Integration of clinical data with a genome‐scale metabolic model of the human adipocyte
URI https://link.springer.com/article/10.1038/msb.2013.5
https://onlinelibrary.wiley.com/doi/abs/10.1038%2Fmsb.2013.5
https://www.ncbi.nlm.nih.gov/pubmed/23511207
https://www.proquest.com/docview/2299139892
https://www.proquest.com/docview/1318690229
https://www.proquest.com/docview/1566854266
https://pubmed.ncbi.nlm.nih.gov/PMC3619940
https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-122122
https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-199737
https://gup.ub.gu.se/publication/175876
https://research.chalmers.se/publication/175876
https://doaj.org/article/3332ad59306f4ff98728e767dafd58b4
Volume 9
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