Literature DB >> 20833526

13C metabolic flux analysis in complex systems.

Nicola Zamboni1.   

Abstract

Experimental determination of in vivo metabolic rates by methods of (13)C metabolic flux analysis is a pivotal approach to unravel structure and regulation of metabolic networks, in particular with microorganisms grown in minimal media. However, the study of real-life and eukaryotic systems calls for the quantification of fluxes also in cellular compartments, rich media, cell-wide metabolic networks, dynamic systems or single cells. These scenarios drastically increase the complexity of the task, which is only partly dealt by existing approaches that rely on rigorous simulations of label propagation through metabolic networks and require multiple labeling experiments or a priori information on pathway inactivity to simplify the problem. Albeit qualitative and largely driven by human interpretation, statistical analysis of measured (13)C-patterns remains the exclusive alternative to comprehensively handle such complex systems. In the future, this practice will be complemented by novel modeling frameworks to assay particular fluxes within a network by stable isotopic tracer for targeted validation of well-defined hypotheses.
Copyright © 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20833526     DOI: 10.1016/j.copbio.2010.08.009

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


  62 in total

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Journal:  J Ind Microbiol Biotechnol       Date:  2015-01-23       Impact factor: 3.346

7.  Quantifying Dynamic Regulation in Metabolic Pathways with Nonparametric Flux Inference.

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Journal:  Biophys J       Date:  2019-04-19       Impact factor: 4.033

Review 8.  Understanding metabolism with flux analysis: From theory to application.

Authors:  Ziwei Dai; Jason W Locasale
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Review 9.  After the feature presentation: technologies bridging untargeted metabolomics and biology.

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Review 10.  Global profiling strategies for mapping dysregulated metabolic pathways in cancer.

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