Literature DB >> 14612591

Metabolic and transcriptional patterns accompanying glutamine depletion and repletion in mouse hepatoma cells: a model for physiological regulatory networks.

Matthew S Wong1, R Michael Raab, Isidore Rigoutsos, Gregory N Stephanopoulos, Joanne K Kelleher.   

Abstract

An important objective in postgenomic biology is to link gene expression to function by developing physiological networks that include data from the genomic and functional levels. Here, we develop a model for the analysis of time-dependent changes in metabolites, fluxes, and gene expression in a hepatic model system. The experimental framework chosen was modulation of extracellular glutamine in confluent cultures of mouse Hepa1-6 cells. The importance of glutamine has been demonstrated previously in mammalian cell culture by precipitating metabolic shifts with glutamine depletion and repletion. Our protocol removed glutamine from the medium for 24 h and returned it for a second 24 h. Flux assays of glycolysis, the tricarboxylic acid (TCA) cycle, and lipogenesis were used at specified intervals. All of these fluxes declined in the absence of glutamine and were restored when glutamine was repleted. Isotopomer spectral analysis identified glucose and glutamine as equal sources of lipogenic carbon. Metabolite measurements of organic acids and amino acids indicated that most metabolites changed in parallel with the fluxes. Experiments with actinomycin D indicated that de novo mRNA synthesis was required for observed flux changes during the depletion/repletion of glutamine. Analysis of gene expression data from DNA microarrays revealed that many more genes were anticorrelated with the glycolytic flux and glutamine level than were correlated with these indicators. In conclusion, this model may be useful as a prototype physiological regulatory network where gene expression profiles are analyzed in concert with changes in cell function.

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Year:  2004        PMID: 14612591     DOI: 10.1152/physiolgenomics.00088.2003

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


  10 in total

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Authors:  Ganesh Sriram; Lola Rahib; Jian-Sen He; Allison E Campos; Lilly S Parr; James C Liao; Katrina M Dipple
Journal:  Mol Genet Metab       Date:  2007-10-29       Impact factor: 4.797

2.  Modulation of polyamine metabolic flux in adipose tissue alters the accumulation of body fat by affecting glucose homeostasis.

Authors:  Chunli Liu; Oscar Perez-Leal; Carlos Barrero; Kamyar Zahedi; Manoocher Soleimani; Carl Porter; Salim Merali
Journal:  Amino Acids       Date:  2013-07-24       Impact factor: 3.520

3.  Soft constraints-based multiobjective framework for flux balance analysis.

Authors:  Deepak Nagrath; Marco Avila-Elchiver; François Berthiaume; Arno W Tilles; Achille Messac; Martin L Yarmush
Journal:  Metab Eng       Date:  2010-05-27       Impact factor: 9.783

4.  Contribution of gene expression to metabolic fluxes in hypermetabolic livers induced through burn injury and cecal ligation and puncture in rats.

Authors:  Scott Banta; Murali Vemula; Tadaaki Yokoyama; Arul Jayaraman; François Berthiaume; Martin L Yarmush
Journal:  Biotechnol Bioeng       Date:  2007-05-01       Impact factor: 4.530

Review 5.  Stable isotope-resolved metabolomics (SIRM) in cancer research with clinical application to nonsmall cell lung cancer.

Authors:  Andrew N Lane; Teresa W-M Fan; Michael Bousamra; Richard M Higashi; Jun Yan; Donald M Miller
Journal:  OMICS       Date:  2011-02-17

6.  Effect of anaplerotic fluxes and amino acid availability on hepatic lipoapoptosis.

Authors:  Yasushi Noguchi; Jamey D Young; Jose O Aleman; Michael E Hansen; Joanne K Kelleher; Gregory Stephanopoulos
Journal:  J Biol Chem       Date:  2009-09-16       Impact factor: 5.157

7.  Large-scale analysis of expression signatures reveals hidden links among diverse cellular processes.

Authors:  Steven X Ge
Journal:  BMC Syst Biol       Date:  2011-05-29

8.  Incorporating genome-scale tools for studying energy homeostasis.

Authors:  R Michael Raab
Journal:  Nutr Metab (Lond)       Date:  2006-11-03       Impact factor: 4.169

9.  IKKβ promotes metabolic adaptation to glutamine deprivation via phosphorylation and inhibition of PFKFB3.

Authors:  Michael A Reid; Xazmin H Lowman; Min Pan; Thai Q Tran; Marc O Warmoes; Mari B Ishak Gabra; Ying Yang; Jason W Locasale; Mei Kong
Journal:  Genes Dev       Date:  2016-09-01       Impact factor: 11.361

10.  DDIT3 Directs a Dual Mechanism to Balance Glycolysis and Oxidative Phosphorylation during Glutamine Deprivation.

Authors:  Mingyue Li; Rick Francis Thorne; Ronghua Shi; Xu Dong Zhang; Jingmin Li; Jingtong Li; Qingyuan Zhang; Mian Wu; Lianxin Liu
Journal:  Adv Sci (Weinh)       Date:  2021-03-27       Impact factor: 16.806

  10 in total

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