The regulatory software of cellular metabolism.

Understanding the regulation of metabolic pathways in the cell is like unraveling the 'software' that is running on the 'hardware' of the metabolic network. Transcriptional regulation of enzymes is an important component of this software. A recent systematic analysis of metabolic gene-expression data in Saccharomyces cerevisiae reveals a complex modular organization of co-expressed genes, which could increase our ability to understand and engineer cellular metabolic functions.

[1]  Edda Klipp,et al.  Prediction of temporal gene expression. Metabolic opimization by re-distribution of enzyme activities. , 2002, European journal of biochemistry.

[2]  J. Pronk,et al.  Role of Transcriptional Regulation in Controlling Fluxes in Central Carbon Metabolism of Saccharomyces cerevisiae , 2004, Journal of Biological Chemistry.

[3]  Yaniv Ziv,et al.  Revealing modular organization in the yeast transcriptional network , 2002, Nature Genetics.

[4]  Susumu Goto,et al.  The KEGG resource for deciphering the genome , 2004, Nucleic Acids Res..

[5]  C. Moorehead.  All rights reserved , 1997 .

[6]  J. Hopfield,et al.  From molecular to modular cell biology , 1999, Nature.

[7]  D E Koshland,et al.  The branch point effect. Ultrasensitivity and subsensitivity to metabolic control. , 1984, The Journal of biological chemistry.

[8]  J. Broach,et al.  The Molecular biology of the yeast Saccharomyces : metabolism and gene expression , 1982 .

[9]  D. Pe’er,et al.  Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data , 2003, Nature Genetics.

[10]  H. Westerhoff,et al.  Transcriptome meets metabolome: hierarchical and metabolic regulation of the glycolytic pathway , 2001, FEBS letters.

[11]  U. Sauer,et al.  Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. , 2003, European journal of biochemistry.

[12]  J. Bailey,et al.  Optimization of regulatory architectures in metabolic reaction networks , 1996, Biotechnology and bioengineering.

[13]  Jason A. Papin,et al.  Analysis of metabolic capabilities using singular value decomposition of extreme pathway matrices. , 2003, Biophysical journal.

[14]  Peter D. Karp,et al.  MetaCyc: a multiorganism database of metabolic pathways and enzymes. , 2004, Nucleic acids research.

[15]  Markus J. Herrgård,et al.  Reconciling gene expression data with known genome-scale regulatory network structures. , 2003, Genome research.

[16]  A. Barabasi,et al.  Hierarchical Organization of Modularity in Metabolic Networks , 2002, Science.

[17]  B. Palsson,et al.  Toward Metabolic Phenomics: Analysis of Genomic Data Using Flux Balances , 1999, Biotechnology progress.

[18]  S. Schuster,et al.  Metabolic network structure determines key aspects of functionality and regulation , 2002, Nature.

[19]  Sven Bergmann,et al.  Iterative signature algorithm for the analysis of large-scale gene expression data. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[20]  Michel Werner,et al.  Sulfur sparing in the yeast proteome in response to sulfur demand. , 2002, Molecular cell.

[21]  D. Fraenkel.  The top genes: on the distance from transcript to function in yeast glycolysis. , 2003, Current opinion in microbiology.

[22]  David A. Fell,et al.  Increasing the flux in metabolic pathways: A metabolic control analysis perspective , 1998, Biotechnology and bioengineering.

[23]  Thomas Szyperski,et al.  Metabolic-Flux Profiling of the Yeasts Saccharomyces cerevisiae and Pichia stipitis , 2003, Eukaryotic Cell.

[24]  Jan Ihmels,et al.  Principles of transcriptional control in the metabolic network of Saccharomyces cerevisiae , 2004, Nature Biotechnology.

[25]  G. Stephanopoulos,et al.  Systematic quantification of complex metabolic flux networks using stable isotopes and mass spectrometry. , 2003, European journal of biochemistry.

[26]  A. DeLuna,et al.  NADP-Glutamate Dehydrogenase Isoenzymes of Saccharomyces cerevisiae , 2001, The Journal of Biological Chemistry.

[27]  Michael A. Savageau,et al.  Application of Biochemical Systems Theory to Metabolism in Human Red Blood Cells , 1996, The Journal of Biological Chemistry.