Literature DB >> 23142542

Tandem mass spectrometry for measuring stable-isotope labeling.

Maciek R Antoniewicz1.   

Abstract

Measuring metabolic rates by (13)C-metabolic flux analysis ((13)C-MFA) is of central importance for metabolic engineers and biomedical investigators. Enhanced knowledge of in vivo fluxes can be applied to reengineer the metabolic, regulatory, and phenotypic characteristics of organisms and help uncover the mechanisms of human ailments such as cancer and diabetes. To determine accurate and precise fluxes by (13)C-MFA advanced methods for measuring stable-isotope labeling are needed. The application of tandem mass spectrometry is emerging as a new promising technique that has significant advantages over traditional MS and NMR based methods. With further refinement, tandem MS has the potential to become the new gold standard for measuring isotopic labeling for (13)C-flux studies.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 23142542     DOI: 10.1016/j.copbio.2012.10.011

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


  17 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.  Metabolomic signature of brain cancer.

Authors:  Renu Pandey; Laura Caflisch; Alessia Lodi; Andrew J Brenner; Stefano Tiziani
Journal:  Mol Carcinog       Date:  2017-07-17       Impact factor: 4.784

Review 4.  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 5.  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

6.  Integrated 13C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia coli.

Authors:  Scott B Crown; Christopher P Long; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2015-01-14       Impact factor: 9.783

7.  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

8.  Optimal tracers for parallel labeling experiments and 13C metabolic flux analysis: A new precision and synergy scoring system.

Authors:  Scott B Crown; Christopher P Long; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2016-06-04       Impact factor: 9.783

9.  High-resolution 13C metabolic flux analysis.

Authors:  Christopher P Long; Maciek R Antoniewicz
Journal:  Nat Protoc       Date:  2019-08-30       Impact factor: 13.491

10.  Pool size measurements facilitate the determination of fluxes at branching points in non-stationary metabolic flux analysis: the case of Arabidopsis thaliana.

Authors:  Robert Heise; Alisdair R Fernie; Mark Stitt; Zoran Nikoloski
Journal:  Front Plant Sci       Date:  2015-06-02       Impact factor: 5.753

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