Literature DB >> 18629859

Pathway analysis, engineering, and physiological considerations for redirecting central metabolism.

J C Liao1, S Y Hou, Y P Chao.   

Abstract

The rate and yield of producing a metabolite is ultimately limited by the ability to channel metabolic fluxes from central metabolism to the desired biosynthesis pathway. Redirection of central metabolism thus is essential to high-efficiency production of biochemicals. This task begins with pathway analysis, which considers only the stoichiometry of the reaction networks but not the regulatory mechanisms. An approach extended from convex analysis is used to determine the basic reaction modes, which allows the determination of optimal and suboptimal flux distributions, yield, and the dispensable sets of reactions. Genes responsible for reactions in the same dispensable set can be deleted simultaneously. This analysis serves as an initial guideline for pathway engineering. Using this analysis, we successfully constructed an Escherichia coli strain that can channel the metabolic flow from carbohydrate to the aromatic pathway with theoretical yield. This analysis also predicts a novel cycle involving phosphoenolpyruvate (PEP) carboxykinase (Pck) and the glyoxylate shunt, which can substitute the tricarboxylic acid cycle with only slightly less efficiency. However, the full cycle could not be confirmed in vivo, possibly because of the regulatory mechanism not considered in the pathway analysis.In addition to the kinetic regulation, we have obtained evidence suggesting that central metabolites are involved in specific regulons in E. coli. Overexpression of PEP-forming enzymes (phosphoenolpyruvate synthase [Pps] and Pck) stimulates the glucose consumption rate, represses the heat shock response, and negatively regulates the Ntr regulon. These results suggest that some glycolytic intermediates may serve as a signal in the regulation of the phosphotransferase system, heat shock response, and nitrogen regulation. However, the role of central metabolites in these regulations has not been determined conclusively. (c) 1996 John Wiley & Sons, Inc.

Entities:  

Year:  1996        PMID: 18629859     DOI: 10.1002/(SICI)1097-0290(19961005)52:1<129::AID-BIT13>3.0.CO;2-J

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  45 in total

1.  The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities.

Authors:  J S Edwards; B O Palsson
Journal:  Proc Natl Acad Sci U S A       Date:  2000-05-09       Impact factor: 11.205

Review 2.  Thirteen years of building constraint-based in silico models of Escherichia coli.

Authors:  Jennifer L Reed; Bernhard Ø Palsson
Journal:  J Bacteriol       Date:  2003-05       Impact factor: 3.490

3.  Extreme pathway lengths and reaction participation in genome-scale metabolic networks.

Authors:  Jason A Papin; Nathan D Price; Bernhard Ø Palsson
Journal:  Genome Res       Date:  2002-12       Impact factor: 9.043

4.  Dynamic generation and qualitative analysis of metabolic pathways by a joint database/graph theoretical approach.

Authors:  F Ehrentreich; D Schomburg
Journal:  Funct Integr Genomics       Date:  2003-10-16       Impact factor: 3.410

5.  Analysis of metabolic capabilities using singular value decomposition of extreme pathway matrices.

Authors:  Nathan D Price; Jennifer L Reed; Jason A Papin; Iman Famili; Bernhard O Palsson
Journal:  Biophys J       Date:  2003-02       Impact factor: 4.033

6.  The JAK-STAT signaling network in the human B-cell: an extreme signaling pathway analysis.

Authors:  Jason A Papin; Bernhard O Palsson
Journal:  Biophys J       Date:  2004-07       Impact factor: 4.033

Review 7.  The acetate switch.

Authors:  Alan J Wolfe
Journal:  Microbiol Mol Biol Rev       Date:  2005-03       Impact factor: 11.056

8.  Construction of a switchable synthetic Escherichia coli for aromatic amino acids by a tunable switch.

Authors:  Xiaozhen Liu; Hao Niu; Zhaosong Huang; Qiang Li; Pengfei Gu
Journal:  J Ind Microbiol Biotechnol       Date:  2020-01-27       Impact factor: 3.346

9.  Ensemble modeling of metabolic networks.

Authors:  Linh M Tran; Matthew L Rizk; James C Liao
Journal:  Biophys J       Date:  2008-09-26       Impact factor: 4.033

10.  Metabolic flux analysis of Escherichia coli creB and arcA mutants reveals shared control of carbon catabolism under microaerobic growth conditions.

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

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