Literature DB >> 21364298

Dynamic modeling of lactic acid fermentation metabolism with Lactococcus lactis.

Euhlim Oh1, Mingshou Lu, Changhun Park, Changhun Park, Han Bin Oh, Sang Yup Lee, Jinwon Lee.   

Abstract

A dynamic model of lactic acid fermentation using Lactococcus lactis was constructed, and a metabolic flux analysis (MFA) and metabolic control analysis (MCA) were performed to reveal an intensive metabolic understanding of lactic acid bacteria (LAB). The parameter estimation was conducted with COPASI software to construct a more accurate metabolic model. The experimental data used in the parameter estimation were obtained from an LC-MS/ MS analysis and time-course simulation study. The MFA results were a reasonable explanation of the experimental data. Through the parameter estimation, the metabolic system of lactic acid bacteria can be thoroughly understood through comparisons with the original parameters. The coefficients derived from the MCA indicated that the reaction rate of L-lactate dehydrogenase was activated by fructose 1,6-bisphosphate and pyruvate, and pyruvate appeared to be a stronger activator of L-lactate dehydrogenase than fructose 1,6-bisphosphate. Additionally, pyruvate acted as an inhibitor to pyruvate kinase and the phosphotransferase system. Glucose 6-phosphate and phosphoenolpyruvate showed activation effects on pyruvate kinase. Hexose transporter was the strongest effector on the flux through L-lactate dehydrogenase. The concentration control coefficient (CCC) showed similar results to the flux control coefficient (FCC).

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Year:  2011        PMID: 21364298     DOI: 10.4014/jmb.1007.07066

Source DB:  PubMed          Journal:  J Microbiol Biotechnol        ISSN: 1017-7825            Impact factor:   2.351


  5 in total

1.  Analysis of primary metabolites of Morchella fruit bodies and mycelium based on widely targeted metabolomics.

Authors:  Yuhong Yang; Jian Yang; Hongling Wang; Yusong Jin; Jing Liu; Ranran Jia; Zhuo Wang; Zongli Kang
Journal:  Arch Microbiol       Date:  2021-12-29       Impact factor: 2.552

2.  Monte-Carlo modeling of the central carbon metabolism of Lactococcus lactis: insights into metabolic regulation.

Authors:  Ettore Murabito; Malkhey Verma; Martijn Bekker; Domenico Bellomo; Hans V Westerhoff; Bas Teusink; Ralf Steuer
Journal:  PLoS One       Date:  2014-09-30       Impact factor: 3.240

3.  Systematic applications of metabolomics in metabolic engineering.

Authors:  Robert A Dromms; Mark P Styczynski
Journal:  Metabolites       Date:  2012-12-14

4.  Diverse classes of constraints enable broader applicability of a linear programming-based dynamic metabolic modeling framework.

Authors:  Justin Y Lee; Mark P Styczynski
Journal:  Sci Rep       Date:  2022-01-14       Impact factor: 4.379

5.  Tracing regulatory routes in metabolism using generalised supply-demand analysis.

Authors:  Carl D Christensen; Jan-Hendrik S Hofmeyr; Johann M Rohwer
Journal:  BMC Syst Biol       Date:  2015-12-03
  5 in total

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