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Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes
BACKGROUND: Type 2 diabetes is one of the leading non-infectious diseases worldwide and closely relates to excess adipose tissue accumulation as seen in obesity. Specifically, hypertrophic expansion of adipose tissues is related to increased cardiometabolic risk leading to type 2 diabetes. Studying...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5468946/ https://www.ncbi.nlm.nih.gov/pubmed/28606124 http://dx.doi.org/10.1186/s12918-017-0438-9 |
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author | Chénard, Thierry Guénard, Frédéric Vohl, Marie-Claude Carpentier, André Tchernof, André Najmanovich, Rafael J. |
author_facet | Chénard, Thierry Guénard, Frédéric Vohl, Marie-Claude Carpentier, André Tchernof, André Najmanovich, Rafael J. |
author_sort | Chénard, Thierry |
collection | PubMed |
description | BACKGROUND: Type 2 diabetes is one of the leading non-infectious diseases worldwide and closely relates to excess adipose tissue accumulation as seen in obesity. Specifically, hypertrophic expansion of adipose tissues is related to increased cardiometabolic risk leading to type 2 diabetes. Studying mechanisms underlying adipocyte hypertrophy could lead to the identification of potential targets for the treatment of these conditions. RESULTS: We present iTC1390adip, a highly curated metabolic network of the human adipocyte presenting various improvements over the previously published iAdipocytes1809. iTC1390adip contains 1390 genes, 4519 reactions and 3664 metabolites. We validated the network obtaining 92.6% accuracy by comparing experimental gene essentiality in various cell lines to our predictions of biomass production. Using flux balance analysis under various test conditions, we predict the effect of gene deletion on both lipid droplet and biomass production, resulting in the identification of 27 genes that could reduce adipocyte hypertrophy. We also used expression data from visceral and subcutaneous adipose tissues to compare the effect of single gene deletions between adipocytes from each compartment. CONCLUSIONS: We generated a highly curated metabolic network of the human adipose tissue and used it to identify potential targets for adipose tissue metabolic dysfunction leading to the development of type 2 diabetes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-017-0438-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5468946 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54689462017-06-14 Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes Chénard, Thierry Guénard, Frédéric Vohl, Marie-Claude Carpentier, André Tchernof, André Najmanovich, Rafael J. BMC Syst Biol Research Article BACKGROUND: Type 2 diabetes is one of the leading non-infectious diseases worldwide and closely relates to excess adipose tissue accumulation as seen in obesity. Specifically, hypertrophic expansion of adipose tissues is related to increased cardiometabolic risk leading to type 2 diabetes. Studying mechanisms underlying adipocyte hypertrophy could lead to the identification of potential targets for the treatment of these conditions. RESULTS: We present iTC1390adip, a highly curated metabolic network of the human adipocyte presenting various improvements over the previously published iAdipocytes1809. iTC1390adip contains 1390 genes, 4519 reactions and 3664 metabolites. We validated the network obtaining 92.6% accuracy by comparing experimental gene essentiality in various cell lines to our predictions of biomass production. Using flux balance analysis under various test conditions, we predict the effect of gene deletion on both lipid droplet and biomass production, resulting in the identification of 27 genes that could reduce adipocyte hypertrophy. We also used expression data from visceral and subcutaneous adipose tissues to compare the effect of single gene deletions between adipocytes from each compartment. CONCLUSIONS: We generated a highly curated metabolic network of the human adipose tissue and used it to identify potential targets for adipose tissue metabolic dysfunction leading to the development of type 2 diabetes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-017-0438-9) contains supplementary material, which is available to authorized users. BioMed Central 2017-06-12 /pmc/articles/PMC5468946/ /pubmed/28606124 http://dx.doi.org/10.1186/s12918-017-0438-9 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Chénard, Thierry Guénard, Frédéric Vohl, Marie-Claude Carpentier, André Tchernof, André Najmanovich, Rafael J. Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes |
title | Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes |
title_full | Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes |
title_fullStr | Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes |
title_full_unstemmed | Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes |
title_short | Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes |
title_sort | remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5468946/ https://www.ncbi.nlm.nih.gov/pubmed/28606124 http://dx.doi.org/10.1186/s12918-017-0438-9 |
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