Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Chénard, Thierry, Guénard, Frédéric, Vohl, Marie-Claude, Carpentier, André, Tchernof, André, Najmanovich, Rafael J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
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
_version_ 1783243489058750464
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
work_keys_str_mv AT chenardthierry remodelingadiposetissuethroughinsilicomodulationoffatstorageforthepreventionoftype2diabetes
AT guenardfrederic remodelingadiposetissuethroughinsilicomodulationoffatstorageforthepreventionoftype2diabetes
AT vohlmarieclaude remodelingadiposetissuethroughinsilicomodulationoffatstorageforthepreventionoftype2diabetes
AT carpentierandre remodelingadiposetissuethroughinsilicomodulationoffatstorageforthepreventionoftype2diabetes
AT tchernofandre remodelingadiposetissuethroughinsilicomodulationoffatstorageforthepreventionoftype2diabetes
AT najmanovichrafaelj remodelingadiposetissuethroughinsilicomodulationoffatstorageforthepreventionoftype2diabetes