Literature DB >> 23279205

Fluxomics - connecting 'omics analysis and phenotypes.

Gal Winter1, Jens O Krömer.   

Abstract

In our modern 'omics era, metabolic flux analysis (fluxomics) represents the physiological counterpart of its siblings transcriptomics, proteomics and metabolomics. Fluxomics integrates in vivo measurements of metabolic fluxes with stoichiometric network models to allow the determination of absolute flux through large networks of the central carbon metabolism. There are many approaches to implement fluxomics including flux balance analysis (FBA), (13) C fluxomics and (13) C-constrained FBA as well as many experimental settings for flux measurement including dynamic, stationary and semi-stationary. Here we outline the principles of the different approaches and their relative advantages. We demonstrate the unique contribution of flux analysis for phenotype elucidation using a thoroughly studied metabolic reaction as a case study, the microbial aerobic/anaerobic shift, highlighting the importance of flux analysis as a single layer of data as well as interlaced in multi-omics studies.
© 2012 John Wiley & Sons Ltd and Society for Applied Microbiology.

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Year:  2013        PMID: 23279205     DOI: 10.1111/1462-2920.12064

Source DB:  PubMed          Journal:  Environ Microbiol        ISSN: 1462-2912            Impact factor:   5.491


  27 in total

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5.  Integrated Multiomics, Bioinformatics, and Computational Modeling Approaches to Central Metabolism in Organs.

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6.  Comprehensive Isotopic Targeted Mass Spectrometry: Reliable Metabolic Flux Analysis with Broad Coverage.

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Review 7.  Metabolic engineering of yeast to produce fatty acid-derived biofuels: bottlenecks and solutions.

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Journal:  Front Microbiol       Date:  2015-06-08       Impact factor: 5.640

8.  Functional genomics of Plasmodium falciparum using metabolic modelling and analysis.

Authors:  Stepan Tymoshenko; Rebecca D Oppenheim; Dominique Soldati-Favre; Vassily Hatzimanikatis
Journal:  Brief Funct Genomics       Date:  2013-06-22       Impact factor: 4.241

9.  Predicting Ecological Roles in the Rhizosphere Using Metabolome and Transportome Modeling.

Authors:  Peter E Larsen; Frank R Collart; Yang Dai
Journal:  PLoS One       Date:  2015-09-02       Impact factor: 3.240

10.  Mapping cancer cell metabolism with(13)C flux analysis: Recent progress and future challenges.

Authors:  Casey Scott Duckwall; Taylor Athanasaw Murphy; Jamey Dale Young
Journal:  J Carcinog       Date:  2013-07-24
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