Literature DB >> 10935929

Quantification of intracellular metabolic fluxes from fractional enrichment and 13C-13C coupling constraints on the isotopomer distribution in labeled biomass components.

K Schmidt1, L C Nørregaard, B Pedersen, A Meissner, J O Duus, J O Nielsen, J Villadsen.   

Abstract

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.

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Year:  1999        PMID: 10935929     DOI: 10.1006/mben.1999.0114

Source DB:  PubMed          Journal:  Metab Eng        ISSN: 1096-7176            Impact factor:   9.783


  18 in total

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Authors:  Pablo I Nikel; Jiangfeng Zhu; Ka-Yiu San; Beatriz S Méndez; George N Bennett
Journal:  J Bacteriol       Date:  2009-06-26       Impact factor: 3.490

2.  Bacillus subtilis metabolism and energetics in carbon-limited and excess-carbon chemostat culture.

Authors:  M Dauner; T Storni; U Sauer
Journal:  J Bacteriol       Date:  2001-12       Impact factor: 3.490

3.  Metabolic flux responses to pyruvate kinase knockout in Escherichia coli.

Authors:  Marcel Emmerling; Michael Dauner; Aaron Ponti; Jocelyne Fiaux; Michel Hochuli; Thomas Szyperski; Kurt Wüthrich; J E Bailey; Uwe Sauer
Journal:  J Bacteriol       Date:  2002-01       Impact factor: 3.490

4.  Kinetic isotope effects significantly influence intracellular metabolite (13) C labeling patterns and flux determination.

Authors:  Thomas M Wasylenko; Gregory Stephanopoulos
Journal:  Biotechnol J       Date:  2013-08-05       Impact factor: 4.677

5.  Genealogy profiling through strain improvement by using metabolic network analysis: metabolic flux genealogy of several generations of lysine-producing corynebacteria.

Authors:  Christoph Wittmann; Elmar Heinzle
Journal:  Appl Environ Microbiol       Date:  2002-12       Impact factor: 4.792

6.  Quantification of compartmented metabolic fluxes in developing soybean embryos by employing biosynthetically directed fractional (13)C labeling, two-dimensional [(13)C, (1)H] nuclear magnetic resonance, and comprehensive isotopomer balancing.

Authors:  Ganesh Sriram; D Bruce Fulton; Vidya V Iyer; Joan Marie Peterson; Ruilian Zhou; Mark E Westgate; Martin H Spalding; Jacqueline V Shanks
Journal:  Plant Physiol       Date:  2004-10-01       Impact factor: 8.340

7.  Kinetic flux profiling for quantitation of cellular metabolic fluxes.

Authors:  Jie Yuan; Bryson D Bennett; Joshua D Rabinowitz
Journal:  Nat Protoc       Date:  2008       Impact factor: 13.491

8.  A possibilistic framework for constraint-based metabolic flux analysis.

Authors:  Francisco Llaneras; Antonio Sala; Jesús Picó
Journal:  BMC Syst Biol       Date:  2009-07-31

9.  Macromolecular and elemental composition analysis and extracellular metabolite balances of Pichia pastoris growing at different oxygen levels.

Authors:  Marc Carnicer; Kristin Baumann; Isabelle Töplitz; Francesc Sánchez-Ferrando; Diethard Mattanovich; Pau Ferrer; Joan Albiol
Journal:  Microb Cell Fact       Date:  2009-12-09       Impact factor: 5.328

10.  Flux Design: In silico design of cell factories based on correlation of pathway fluxes to desired properties.

Authors:  Guido Melzer; Manely Eslahpazir Esfandabadi; Ezequiel Franco-Lara; Christoph Wittmann
Journal:  BMC Syst Biol       Date:  2009-12-25
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