Literature DB >> 15102468

High-throughput phenomics: experimental methods for mapping fluxomes.

Uwe Sauer1.   

Abstract

Many technologies have been developed to help explain the phenotypic consequences of genetic and/or environmental modifications in areas like functional genomics, pharmaceutical research and metabolic engineering. The missing link in contemporary functional analyses that focus on the analysis of cellular components is the capacity to directly observe functional units. By linking genes and proteins to higher level biological functions, the molecular fluxes through metabolic networks (the fluxome) determine the cellular phenotype. Quantitative monitoring of such whole network operations by methods of metabolic flux analysis, thus bridges the gap by providing a global perspective of the integrated regulation at the transcriptional, translational and metabolic level. This review highlights recent developments towards high-throughput flux analysis.

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Year:  2004        PMID: 15102468     DOI: 10.1016/j.copbio.2003.11.001

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  48 in total

Review 1.  Systems biology from micro-organisms to human metabolic diseases: the role of detailed kinetic models.

Authors:  Barbara M Bakker; Karen van Eunen; Jeroen A L Jeneson; Natal A W van Riel; Frank J Bruggeman; Bas Teusink
Journal:  Biochem Soc Trans       Date:  2010-10       Impact factor: 5.407

2.  Experimental identification and quantification of glucose metabolism in seven bacterial species.

Authors:  Tobias Fuhrer; Eliane Fischer; Uwe Sauer
Journal:  J Bacteriol       Date:  2005-03       Impact factor: 3.490

Review 3.  Metabolic engineering in the -omics era: elucidating and modulating regulatory networks.

Authors:  Goutham N Vemuri; Aristos A Aristidou
Journal:  Microbiol Mol Biol Rev       Date:  2005-06       Impact factor: 11.056

4.  A rant against jargon and neologisms.

Authors:  Simon N Young
Journal:  J Psychiatry Neurosci       Date:  2006-05       Impact factor: 6.186

Review 5.  Mass spectrometry-based metabolomics.

Authors:  Katja Dettmer; Pavel A Aronov; Bruce D Hammock
Journal:  Mass Spectrom Rev       Date:  2007 Jan-Feb       Impact factor: 10.946

6.  Global metabolic effects of glycerol kinase overexpression in rat hepatoma cells.

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

Review 7.  Biochemical and statistical network models for systems biology.

Authors:  Nathan D Price; Ilya Shmulevich
Journal:  Curr Opin Biotechnol       Date:  2007-08-03       Impact factor: 9.740

8.  (13)C-based metabolic flux analysis.

Authors:  Nicola Zamboni; Sarah-Maria Fendt; Martin Rühl; Uwe Sauer
Journal:  Nat Protoc       Date:  2009-05-21       Impact factor: 13.491

9.  Linking high-resolution metabolic flux phenotypes and transcriptional regulation in yeast modulated by the global regulator Gcn4p.

Authors:  Joel F Moxley; Michael C Jewett; Maciek R Antoniewicz; Silas G Villas-Boas; Hal Alper; Robert T Wheeler; Lily Tong; Alan G Hinnebusch; Trey Ideker; Jens Nielsen; Gregory Stephanopoulos
Journal:  Proc Natl Acad Sci U S A       Date:  2009-04-03       Impact factor: 11.205

10.  Characterization of the central metabolic pathways in Thermoanaerobacter sp. strain X514 via isotopomer-assisted metabolite analysis.

Authors:  Xueyang Feng; Housna Mouttaki; Lu Lin; Rick Huang; Bing Wu; Christopher L Hemme; Zhili He; Baichen Zhang; Leslie M Hicks; Jian Xu; Jizhong Zhou; Yinjie J Tang
Journal:  Appl Environ Microbiol       Date:  2009-06-12       Impact factor: 4.792

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