Journal article
Quantification of intracellular metabolic fluxes from fractional enrichment measurements and isotopomer analysis of 13C labelled biomass components
A method for the quantification of intracellular metabolic flux distributions from steady-state mass balance constraints and from the constraints posed by the measured 13C labeling state of biomass components is presented. Two-dimensional NMR spectroscopy is used to analyze the labeling state of cell protein hydrolysate and cell wall components.
No separation of the biomass hydrolysate is required to measure the degree of 13C-13C coupling and the fractional 13C enrichment in various carbon atom positions. A mixture of [1-13C]glucose and uniformly labeled [13C6]glucose is applied to make fractional 13C enrichment data and measurements of the degree of 13C-13C coupling informative with respect to the intracellular flux distribution.
Simulation models that calculate the complete isotopomer distribution in biomass components on the basis of isotopomer mapping matrices are used for the estimation of intracellular fluxes by least-squares minimization. The statistical quality of the estimated intracellular flux distributions is assessed by Monte Carlo methods.
Principal component analysis is performed on the outcome of the Monte Carlo procedure to identify groups of fluxes that contribute major parts to the total variance in the multiple flux estimations. The methods described are applied to a steady-state culture of a glucoamylase-producing recombinant Aspergillus niger strain.
Language: | English |
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Year: | 1999 |
Pages: | 166-179 |
ISSN: | 10967184 and 10967176 |
Types: | Journal article |
DOI: | 10.1006/mben.1999.0114 |
ORCIDs: | Villadsen, John |
2D NMR spectroscopy Aspergillus niger Biomass Carbon Isotopes Chitin Citric Acid Cycle Computer Simulation Glucan 1,4-alpha-Glucosidase Isotope Labeling Magnetic Resonance Spectroscopy Monte Carlo Method Monte Carlo simulation PCA Pentose Phosphate Pathway Substrate Cycling isotopomer mapping matrices isotopomer modeling metabolic flux analysis