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Elementary Metabolite Units (EMU)

Metabolic Flux Analysis (MFA) has emerged as a tool of great significance for metabolic engineering and quantitative cell physiology. An important limitation of MFA, as carried out via stable isotope labeling and GC-MS measurements, is the large number of isotopomer/cumomer equations that need to be solved, especially when multiple isotopic tracers are used for the labeling of the system. This restriction reduces the ability of MFA to fully utilize the power of multiple isotopic tracers in elucidating the physiology of realistic situations comprising complex bioreaction networks.


Elementary Metabolite Units Decomposition

Fig 1. Decomposition of atom transition network into EMU networks


To address this limitation, we have developed a novel framework for modeling of isotopic tracer distributions that significantly reduces the number of variables, without any loss of information. The EMU framework is based on a highly efficient decomposition method that identifies the minimum amount of information needed to simulate isotopic labeling within a reaction network using the knowledge of atomic transitions occurring in the network reactions. The functional units generated by the decomposition algorithm, called elementary metabolite units (EMUs), form the new basis for generating system equations that describe the relationship between fluxes and isotopomer abundances.

The EMU decomposition algorithm is completely unsupervised and converges within seconds even for very genome-wide network models. Isotopomer abundances simulated using the EMU framework are identical to those obtained using the isotopomer and cumomer frameworks, however, requiring significantly less computation time. For a typical carbon labeling system the total number of equations that needs to be solved is reduced by one order-of-magnitude (100s EMUs vs. 1000s cumomers). As such, the EMU framework is most efficient for the analysis of labeling by multiple isotopic tracers. For example, the analysis of gluconeogenesis network model with 2H, 13C, and 18O tracers requires only 354 EMUs compared to >2,000,000 isotopomers.


Isotopomers vs EMUs

Fig 2. EMU method dramatically reduces the number of variables in metabolic flux analysis



References

Antoniewicz MR, Kelleher JK, Stephanopoulos G.
Elementary Metabolite Units (EMU): A novel framework for modeling isotopic distributions. Metab Eng 9(1): 68-86, 2007

Young JD, Walther JL, Antoniewicz MR, Yoo H, Stephanopoulos G.
An Elementary Metabolite Unit (EMU) based method of isotopically nonstationary flux analysis. Biotechnol Bioeng, 2007

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EMU IN NEWS
  • Sep 18, 2008
    Prof. Antoniewicz wins Jay Bailey Award in Metabolic Engineering for developing EMU framework [pdf]
  • Feb, 2008
    ScienceWatch identifies EMU modeling as an important Emerging Research Front [pdf]
  • Dec 19, 2007
    Biotech Bioeng highlights our dynamic EMU modeling work in Spotlight [pdf]
  • Apr 18, 2007
    Faculty of 1000 Biology recommends our EMU modeling framework [pdf]