Literature DB >> 20219606

Dynamic modeling of Escherichia coli metabolic and regulatory systems for amino-acid production.

Yoshihiro Usuda1, Yosuke Nishio, Shintaro Iwatani, Stephen J Van Dien, Akira Imaizumi, Kazutaka Shimbo, Naoko Kageyama, Daigo Iwahata, Hiroshi Miyano, Kazuhiko Matsui.   

Abstract

Our aim is to construct a practical dynamic-simulation system that can model the metabolic and regulatory processes involved in the production of primary metabolites, such as amino acids. We have simulated the production of glutamate by transient batch-cultivation using a model of Escherichia coli central metabolism. Kinetic data were used to produce both the metabolic parts of the model, including the phosphotransferase system, glycolysis, the pentose-phosphate pathway, the tricarboxylic acid cycle, the glyoxylate shunt, and the anaplerotic pathways, and the regulatory parts of the model, including regulation by transcription factors, cyclic AMP receptor protein (CRP), making large colonies protein (Mlc), catabolite repressor/activator (Cra), pyruvate dehydrogenase complex repressor (PdhR), and acetate operon repressor (IclR). RNA polymerase and ribosome concentrations were expressed as a function of the specific growth rate, mu, corresponding to the changes in the growth rate during batch cultivation. Parameter fitting was performed using both extracellular concentration measurements and in vivo enzyme activities determined by (13)C flux analysis. By manual adjustment of the parameters, we simulated the batch fermentation of glucose or fructose by a wild-type strain (MG1655) and a glutamate-producing strain (MG1655 Delta sucA). The differences caused by the carbon source, and by wild-type and glutamate-producing strains, were clearly shown by the simulation. A sensitivity analysis revealed the factors that could be altered to improve the production process. Furthermore, an in silico deletion experiments could suggested the existence of uncharacterized regulation. We concluded that our simulation model could function as a new tool for the rational improvement and design of metabolic and regulatory networks. 2010 Elsevier B.V. All rights reserved.

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Year:  2010        PMID: 20219606     DOI: 10.1016/j.jbiotec.2010.02.018

Source DB:  PubMed          Journal:  J Biotechnol        ISSN: 0168-1656            Impact factor:   3.307


  14 in total

1.  Proteomic Analysis of Vibrio parahaemolyticus Under Cold Stress.

Authors:  Jing Tang; Juntao Jia; Ying Chen; Xiaohua Huang; Xiaoliang Zhang; Liqing Zhao; Wei Hu; Changjun Wang; Chao Lin; Zhenxing Wu
Journal:  Curr Microbiol       Date:  2017-08-22       Impact factor: 2.188

Review 2.  L-valine production in Corynebacterium glutamicum based on systematic metabolic engineering: progress and prospects.

Authors:  Jie Liu; Jian-Zhong Xu; Bingbing Wang; Zhi-Ming Rao; Wei-Guo Zhang
Journal:  Amino Acids       Date:  2021-08-16       Impact factor: 3.520

3.  Modeling and simulation of the main metabolism in Escherichia coli and its several single-gene knockout mutants with experimental verification.

Authors:  Tuty Asmawaty Abdul Kadir; Ahmad A Mannan; Andrzej M Kierzek; Johnjoe McFadden; Kazuyuki Shimizu
Journal:  Microb Cell Fact       Date:  2010-11-19       Impact factor: 5.328

4.  Condition-dependent cell volume and concentration of Escherichia coli to facilitate data conversion for systems biology modeling.

Authors:  Benjamin Volkmer; Matthias Heinemann
Journal:  PLoS One       Date:  2011-07-29       Impact factor: 3.240

5.  Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism.

Authors:  Ahmad A Mannan; Yoshihiro Toya; Kazuyuki Shimizu; Johnjoe McFadden; Andrzej M Kierzek; Andrea Rocco
Journal:  PLoS One       Date:  2015-10-15       Impact factor: 3.240

6.  Analysis of L-glutamic acid fermentation by using a dynamic metabolic simulation model of Escherichia coli.

Authors:  Yousuke Nishio; Soichi Ogishima; Masao Ichikawa; Yohei Yamada; Yoshihiro Usuda; Tadashi Masuda; Hiroshi Tanaka
Journal:  BMC Syst Biol       Date:  2013-09-22

7.  Optimizing metabolite production using periodic oscillations.

Authors:  Steven W Sowa; Michael Baldea; Lydia M Contreras
Journal:  PLoS Comput Biol       Date:  2014-06-05       Impact factor: 4.475

8.  Identification of key regulators in glycogen utilization in E. coli based on the simulations from a hybrid functional Petri net model.

Authors:  Zhongyuan Tian; Adrien Fauré; Hirotada Mori; Hiroshi Matsuno
Journal:  BMC Syst Biol       Date:  2013-12-13

9.  Simultaneous parameters identifiability and estimation of an E. coli metabolic network model.

Authors:  Kese Pontes Freitas Alberton; André Luís Alberton; Jimena Andrea Di Maggio; Vanina Gisela Estrada; María Soledad Díaz; Argimiro Resende Secchi
Journal:  Biomed Res Int       Date:  2015-01-06       Impact factor: 3.411

10.  Development of an accurate kinetic model for the central carbon metabolism of Escherichia coli.

Authors:  Nusrat Jahan; Kazuhiro Maeda; Yu Matsuoka; Yurie Sugimoto; Hiroyuki Kurata
Journal:  Microb Cell Fact       Date:  2016-06-21       Impact factor: 5.328

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