Applied Biochemistry and Microbiology

, Volume 53, Issue 7, pp 733–753 | Cite as

Metabolic Flux Analysis Using 13C Isotopes (13C-MFA). 1. Experimental Basis of the Method and the Present State of Investigations

  • L. I. GolubevaEmail author
  • M. S. Shupletsov
  • S. V. Mashko
Problems, Prospects


Quantitatively characterizing the intracellular carbon flux distribution provides useful information for both fundamental and applied investigations into the cellular metabolism at the system level, such as the roles of different metabolic pathways and individual reactions, metabolic state characterization, metabolic differences between the strains, and clues regarding strategies for producer-strain improvement. A variety of methods have been developed to characterize the metabolic state of the cell by determining its intracellular flux distribution, and together, they are called metabolic flux analysis (MFA) or fluxomics. These methods, in addition to other X-omics technologies (i.e., genomics, transcriptomics, proteomics, and metabolomics) constitute a recent arsenal of the system biology estimation approaches. One of the most well-developed approaches for intracellular carbon flux estimation in vivo in (quasi) steady-state conditions is 13C-MFA, which uses substrates that are labeled with a heavy carbon (13C). Applying 13C-MFA requires the coordination of experts in biochemistry, applied mathematics and nuclear magnetic resonance (NMR) or mass spectrometry. Therefore, the authors have prepared a three-part review highlighting the different but equally important aspects of 13C-MFA. In the first part, which is presented below, the focus is on the basic principles of 13C-MFA, such as stoichiometric model development, labeling experiments and experimental data extraction. The principles of the labeling experiments modeling and quantitative carbon flux estimation and statistics are discussed in the second part. The final part reviews recent achievements in fundamental and applied investigations of bacterial metabolism achieved using 13C-MFA.


stoichiometric metabolic model isotopomer carbon labeling experiment 



atomic mass unit


coenzyme A


molecular weight






central metabolism


nuclear magnetic resonance


adenosine triphosphate


collision-induced dissociation


carbon-labeling experiment


Entner–Doudoroff Pathway (ED pathway)


elector impact ionization


Embden–Meyerhof–Parnas pathway


electrospray ionization


constraints-based flux balance analysis




genome-scale model


gas chromatography


isotropomer distribution vector


liquid chromatography


metabolite activity vector


mass distribution vector


metabolic flux analysis


mass spectrometry


phosphoenol pyruvate


pentose-phosphate cycle (PP-pathway)




tricarboxylic acid cycle


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Copyright information

© Pleiades Publishing, Inc. 2017

Authors and Affiliations

  • L. I. Golubeva
    • 1
    Email author
  • M. S. Shupletsov
    • 1
    • 2
  • S. V. Mashko
    • 1
    • 3
  1. 1.The Closed Joint-Stock Company Ajinomoto-GenetikaMoscowRussia
  2. 2.The Faculty of Computational Mathematics and CyberneticsLomonosov Moscow State UniversityMoscowRussia
  3. 3.The Faculty of BiologyLomonosov Moscow State UniversityMoscowRussia

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