Literature DB >> 17284573

Flux profile and modularity analysis of time-dependent metabolic changes of de novo adipocyte formation.

Yaguang Si1, Jeongah Yoon, Kyongbum Lee.   

Abstract

White adipose tissue (WAT) mass is the main determinant of obesity and associated health risks. WAT expansion results from increases in white adipocyte cell number and size, which in turn reflect a series of shifts in the cellular metabolic state. To quantitatively profile the metabolic alterations occurring during de novo adipocyte formation, metabolic flux analysis (MFA) was used in conjunction with a novel modularity analysis algorithm on differentiating 3T3-L1 preadipocytes. Use of a type I collagen gel as an effective long-term culture substrate was also assessed. The calculated flux distributions predicted the sequential activation of several intracellular cross-compartmental pathways, including lipogenesis, the pentose phosphate pathway, and the malate cycle, in good agreement with earlier isotopic tracer experiments and gene profiling studies. Partition of the adipocyte metabolic network into highly interacting reaction subgroups suggested a functional reorganization of the major pathways consistent with the lipid-loading phenotype of the adipocyte. Flux and modularity analysis results together point to the flux distribution around pyruvate as a key indicator of adipocyte lipid accumulation.

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Year:  2007        PMID: 17284573     DOI: 10.1152/ajpendo.00670.2006

Source DB:  PubMed          Journal:  Am J Physiol Endocrinol Metab        ISSN: 0193-1849            Impact factor:   4.310


  21 in total

1.  Automated Image Processing for Spatially Resolved Analysis of Lipid Droplets in Cultured 3T3-L1 Adipocytes.

Authors:  James Kenneth Sims; Brian Rohr; Eric Miller; Kyongbum Lee
Journal:  Tissue Eng Part C Methods       Date:  2014-12-18       Impact factor: 3.056

2.  Adipocyte induction of preadipocyte differentiation in a gradient chamber.

Authors:  Ning Lai; James K Sims; Noo Li Jeon; Kyongbum Lee
Journal:  Tissue Eng Part C Methods       Date:  2012-09-20       Impact factor: 3.056

Review 3.  Towards high resolution analysis of metabolic flux in cells and tissues.

Authors:  James K Sims; Sara Manteiga; Kyongbum Lee
Journal:  Curr Opin Biotechnol       Date:  2013-07-29       Impact factor: 9.740

Review 4.  Advanced stoichiometric analysis of metabolic networks of mammalian systems.

Authors:  Mehmet A Orman; Francois Berthiaume; Ioannis P Androulakis; Marianthi G Ierapetritou
Journal:  Crit Rev Biomed Eng       Date:  2011

5.  Enhanced proliferation of human umbilical vein endothelial cells and differentiation of 3T3-L1 adipocytes in coculture.

Authors:  Ning Lai; Arul Jayaraman; Kyongbum Lee
Journal:  Tissue Eng Part A       Date:  2009-05       Impact factor: 3.845

6.  Malic enzyme tracers reveal hypoxia-induced switch in adipocyte NADPH pathway usage.

Authors:  Ling Liu; Supriya Shah; Jing Fan; Junyoung O Park; Kathryn E Wellen; Joshua D Rabinowitz
Journal:  Nat Chem Biol       Date:  2016-03-21       Impact factor: 15.040

7.  Effect of uncoupling protein-1 expression on 3T3-L1 adipocyte gene expression.

Authors:  Fatih S Senocak; Yaguang Si; Colby Moya; William K Russell; David H Russell; Kyongbum Lee; Arul Jayaraman
Journal:  FEBS Lett       Date:  2007-12-03       Impact factor: 4.124

8.  Impact of perturbed pyruvate metabolism on adipocyte triglyceride accumulation.

Authors:  Yaguang Si; Hai Shi; Kyongbum Lee
Journal:  Metab Eng       Date:  2009-08-14       Impact factor: 9.783

9.  Characterization of metabolic changes associated with the functional development of 3D engineered tissues by non-invasive, dynamic measurement of individual cell redox ratios.

Authors:  Kyle P Quinn; Evangelia Bellas; Nikolaos Fourligas; Kyongbum Lee; David L Kaplan; Irene Georgakoudi
Journal:  Biomaterials       Date:  2012-05-04       Impact factor: 12.479

10.  Metabolic flux analysis of mitochondrial uncoupling in 3T3-L1 adipocytes.

Authors:  Yaguang Si; Hai Shi; Kyongbum Lee
Journal:  PLoS One       Date:  2009-09-10       Impact factor: 3.240

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