Literature DB >> 22209989

Selection of tracers for 13C-metabolic flux analysis using elementary metabolite units (EMU) basis vector methodology.

Scott B Crown1, Maciek R Antoniewicz.   

Abstract

Metabolic flux analysis (MFA) is a powerful technique for elucidating in vivo fluxes in microbial and mammalian systems. A key step in (13)C-MFA is the selection of an appropriate isotopic tracer to observe fluxes in a proposed network model. Despite the importance of MFA in metabolic engineering and beyond, current approaches for tracer experiment design are still largely based on trial-and-error. The lack of a rational methodology for selecting isotopic tracers prevents MFA from achieving its full potential. Here, we introduce a new technique for tracer experiment design based on the concept of elementary metabolite unit (EMU) basis vectors. We demonstrate that any metabolite in a network model can be expressed as a linear combination of so-called EMU basis vectors, where the corresponding coefficients indicate the fractional contribution of the EMU basis vector to the product metabolite. The strength of this approach is the decoupling of substrate labeling, i.e. the EMU basis vectors, from the dependence on free fluxes, i.e. the coefficients. In this work, we demonstrate that flux observability inherently depends on the number of independent EMU basis vectors and the sensitivities of coefficients with respect to free fluxes. Specifically, the number of independent EMU basis vectors places hard limits on how many free fluxes can be determined in a model. This constraint is used as a guide for selecting feasible substrate labeling. In three example models, we demonstrate that by maximizing the number of independent EMU basis vectors the observability of a system is improved. Inspection of sensitivities of coefficients with respect to free fluxes provides additional constraints for proper selection of tracers. The present contribution provides a fresh perspective on an important topic in metabolic engineering, and gives practical guidelines and design principles for a priori selection of isotopic tracers for (13)C-MFA studies.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 22209989      PMCID: PMC6474252          DOI: 10.1016/j.ymben.2011.12.005

Source DB:  PubMed          Journal:  Metab Eng        ISSN: 1096-7176            Impact factor:   9.783


  25 in total

Review 1.  Metabolic flux analysis of Escherichia coli knockouts: lessons from the Keio collection and future outlook.

Authors:  Christopher P Long; Maciek R Antoniewicz
Journal:  Curr Opin Biotechnol       Date:  2014-03-28       Impact factor: 9.740

Review 2.  Publishing 13C metabolic flux analysis studies: a review and future perspectives.

Authors:  Scott B Crown; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2013-09-08       Impact factor: 9.783

Review 3.  Methods and advances in metabolic flux analysis: a mini-review.

Authors:  Maciek R Antoniewicz
Journal:  J Ind Microbiol Biotechnol       Date:  2015-01-23       Impact factor: 3.346

Review 4.  Chemical approaches to study metabolic networks.

Authors:  Daniel Medina-Cleghorn; Daniel K Nomura
Journal:  Pflugers Arch       Date:  2013-01-08       Impact factor: 3.657

5.  Comprehensive analysis of glucose and xylose metabolism in Escherichia coli under aerobic and anaerobic conditions by 13C metabolic flux analysis.

Authors:  Jacqueline E Gonzalez; Christopher P Long; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2016-11-11       Impact factor: 9.783

6.  Evidence for transketolase-like TKTL1 flux in CHO cells based on parallel labeling experiments and (13)C-metabolic flux analysis.

Authors:  Woo Suk Ahn; Scott B Crown; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2016-05-10       Impact factor: 9.783

Review 7.  A roadmap for interpreting (13)C metabolite labeling patterns from cells.

Authors:  Joerg M Buescher; Maciek R Antoniewicz; Laszlo G Boros; Shawn C Burgess; Henri Brunengraber; Clary B Clish; Ralph J DeBerardinis; Olivier Feron; Christian Frezza; Bart Ghesquiere; Eyal Gottlieb; Karsten Hiller; Russell G Jones; Jurre J Kamphorst; Richard G Kibbey; Alec C Kimmelman; Jason W Locasale; Sophia Y Lunt; Oliver D K Maddocks; Craig Malloy; Christian M Metallo; Emmanuelle J Meuillet; Joshua Munger; Katharina Nöh; Joshua D Rabinowitz; Markus Ralser; Uwe Sauer; Gregory Stephanopoulos; Julie St-Pierre; Daniel A Tennant; Christoph Wittmann; Matthew G Vander Heiden; Alexei Vazquez; Karen Vousden; Jamey D Young; Nicola Zamboni; Sarah-Maria Fendt
Journal:  Curr Opin Biotechnol       Date:  2015-02-28       Impact factor: 9.740

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

Authors:  Ziwei Dai; Jason W Locasale
Journal:  Metab Eng       Date:  2016-09-22       Impact factor: 9.783

9.  13C metabolic flux analysis of microbial and mammalian systems is enhanced with GC-MS measurements of glycogen and RNA labeling.

Authors:  Christopher P Long; Jennifer Au; Jacqueline E Gonzalez; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2016-06-22       Impact factor: 9.783

10.  (13)C-metabolic flux analysis of co-cultures: A novel approach.

Authors:  Nikodimos A Gebreselassie; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2015-07-26       Impact factor: 9.783

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