283430 Flux and Reflux: Metabolite Back-Mixing in Plant Cell Suspensions and Its Implications On Isotope-Assisted Metabolic Flux Analysis

Wednesday, October 31, 2012: 2:18 PM
Westmoreland East (Westin )
Xiaofeng Zhang1, Ashish Misra2, Shilpa Nargund2, Gary D. Coleman3 and Ganesh Sriram2, (1)Chemical and Biomolecular Engineering, University of Maryland, College Park, College Park, MD, (2)Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, (3)Plant Science and Landscape Architecture, University of Maryland, College Park, College Park, MD

Isotope-assisted metabolic flux analysis (isotopic MFA) is a powerful tool for studying plant metabolism as it quantifies carbon flow (fluxes) through metabolic networks. It involves feeding an isotopically labeled substrate to cell or tissue culture and measuring the labeling patterns of the products using nuclear magnetic resonance (NMR) or mass spectrometry (MS). Metabolic fluxes are estimated by fitting these measurements to a mathematical flux-isotopomer model.

An intrinsic problem in steady state isotopic MFA, particularly in plants and eukaryotic systems, is that the metabolites in the initially present naturally labeled (1.1% 13C) biomass (e.g. the initial cell culture or embryo) back-mix with those in the de novo-synthesized biomass (usually >> 1.1% 13C) in a nontrivial manner. This back-mixing affects the final labeling patterns of the biomass components and confuses their interpretation. Therefore, it has to be accounted for to obtain accurate flux estimates. Previous MFA studies on plant systems accounted for this 13C dilution by introducing an additional parameter amongst the parameters estimated in the flux evaluation procedure. Here, we endeavor to accurately model the back-mixing by incorporating it into the metabolic network model.

We performed this study on cell suspensions of poplar, a potential biofuel crop that efficiently recycles nitrogen from its leaves during winter senescence. Our isotope labeling experiment results clearly point to significant back-mixing of de novo-synthesized biomass by unlabeled initial biomass. Therefore, we established a metabolic model that included back-mixing fluxes of initially present proteinogenic amino acids and sugars, as well as the pool sizes (concentrations) of these metabolites. Simulation results using metabolic network models with the back-mixing fluxes show a better fit of MS-derived isotopomer data than models without back-mixing. Besides, the results surprisingly indicate that different amino acids may have very different extent of cycling, even when they originate from the same metabolic precursor(s). We anticipate that our methodology that incorporates back-mixing of initial biomass will benefit plant metabolic flux analysis by helping us obtain more accurate flux estimation and a more holistic view of plant metabolism.


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