Probing the performance limits of the Escherichia coli metabolic network subject to gene additions or deletions

An optimization‐based procedure for studying the response of metabolic networks after gene knockouts or additions is introduced and applied to a linear flux balance analysis (FBA) Escherichia coli model. Both the gene addition problem of optimally selecting which foreign genes to recombine into E. c...

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Published inBiotechnology and bioengineering Vol. 74; no. 5; pp. 364 - 375
Main Authors Burgard, Anthony P., Maranas, Costas D.
Format Journal Article
LanguageEnglish
Published New York John Wiley & Sons, Inc 05.09.2001
Wiley
Subjects
Online AccessGet full text
ISSN0006-3592
1097-0290
1097-0290
DOI10.1002/bit.1127

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Abstract An optimization‐based procedure for studying the response of metabolic networks after gene knockouts or additions is introduced and applied to a linear flux balance analysis (FBA) Escherichia coli model. Both the gene addition problem of optimally selecting which foreign genes to recombine into E. coli, as well as the gene deletion problem of removing a given number of existing ones, are formulated as mixed‐integer optimization problems using binary 0–1 variables. The developed modeling and optimization framework is tested by investigating the effect of gene deletions on biomass production and addressing the maximum theoretical production of the 20 amino acids for aerobic growth on glucose and acetate substrates. In the gene deletion study, the smallest gene set necessary to achieve maximum biomass production in E. coli is determined for aerobic growth on glucose. The subsequent gene knockout analysis indicates that biomass production decreases monotonically, rendering the metabolic network incapable of growth after only 18 gene deletions. In the gene addition study, the E. coli flux balance model is augmented with 3,400 non‐E. coli reactions from the KEGG database to form a multispecies model. This model is referred to as the Universal model. This study reveals that the maximum theoretical production of six amino acids could be improved by the addition of only one or two genes to the native amino acid production pathway of E. coli, even though the model could choose from 3,400 foreign reaction candidates. Specifically, manipulation of the arginine production pathway showed the most promise with 8.75% and 9.05% predicted increases with the addition of genes for growth on glucose and acetate, respectively. The mechanism of all suggested enhancements is either by: 1) improving the energy efficiency and/or 2) increasing the carbon conversion efficiency of the production route. © 2001 John Wiley & Sons, Inc. Biotechnol Bioeng 74: 364–375, 2001.
AbstractList An optimization‐based procedure for studying the response of metabolic networks after gene knockouts or additions is introduced and applied to a linear flux balance analysis (FBA) Escherichia coli model. Both the gene addition problem of optimally selecting which foreign genes to recombine into E. coli, as well as the gene deletion problem of removing a given number of existing ones, are formulated as mixed‐integer optimization problems using binary 0–1 variables. The developed modeling and optimization framework is tested by investigating the effect of gene deletions on biomass production and addressing the maximum theoretical production of the 20 amino acids for aerobic growth on glucose and acetate substrates. In the gene deletion study, the smallest gene set necessary to achieve maximum biomass production in E. coli is determined for aerobic growth on glucose. The subsequent gene knockout analysis indicates that biomass production decreases monotonically, rendering the metabolic network incapable of growth after only 18 gene deletions. In the gene addition study, the E. coli flux balance model is augmented with 3,400 non‐ E. coli reactions from the KEGG database to form a multispecies model. This model is referred to as the Universal model. This study reveals that the maximum theoretical production of six amino acids could be improved by the addition of only one or two genes to the native amino acid production pathway of E. coli , even though the model could choose from 3,400 foreign reaction candidates. Specifically, manipulation of the arginine production pathway showed the most promise with 8.75% and 9.05% predicted increases with the addition of genes for growth on glucose and acetate, respectively. The mechanism of all suggested enhancements is either by: 1) improving the energy efficiency and/or 2) increasing the carbon conversion efficiency of the production route. © 2001 John Wiley & Sons, Inc. Biotechnol Bioeng 74: 364–375, 2001.
An optimization-based procedure for studying the response of metabolic networks after gene knockouts or additions is introduced and applied to a linear flux balance analysis (FBA) Escherichia coli model. Both the gene addition problem of optimally selecting which foreign genes to recombine into E. coli, as well as the gene deletion problem of removing a given number of existing ones, are formulated as mixed-integer optimization problems using binary 0-1 variables. The developed modeling and optimization framework is tested by investigating the effect of gene deletions on biomass production and addressing the maximum theoretical production of the 20 amino acids for aerobic growth on glucose and acetate substrates. In the gene deletion study, the smallest gene set necessary to achieve maximum biomass production in E. coli is determined for aerobic growth on glucose. The subsequent gene knockout analysis indicates that biomass production decreases monotonically, rendering the metabolic network incapable of growth after only 18 gene deletions. In the gene addition study, the E. coli flux balance model is augmented with 3,400 non-E. coli reactions from the KEGG database to form a multispecies model. This model is referred to as the Universal model. This study reveals that the maximum theoretical production of six amino acids could be improved by the addition of only one or two genes to the native amino acid production pathway of E. coli, even though the model could choose from 3,400 foreign reaction candidates. Specifically, manipulation of the arginine production pathway showed the most promise with 8.75% and 9.05% predicted increases with the addition of genes for growth on glucose and acetate, respectively. The mechanism of all suggested enhancements is either by: 1) improving the energy efficiency and/or 2) increasing the carbon conversion efficiency of the production route.An optimization-based procedure for studying the response of metabolic networks after gene knockouts or additions is introduced and applied to a linear flux balance analysis (FBA) Escherichia coli model. Both the gene addition problem of optimally selecting which foreign genes to recombine into E. coli, as well as the gene deletion problem of removing a given number of existing ones, are formulated as mixed-integer optimization problems using binary 0-1 variables. The developed modeling and optimization framework is tested by investigating the effect of gene deletions on biomass production and addressing the maximum theoretical production of the 20 amino acids for aerobic growth on glucose and acetate substrates. In the gene deletion study, the smallest gene set necessary to achieve maximum biomass production in E. coli is determined for aerobic growth on glucose. The subsequent gene knockout analysis indicates that biomass production decreases monotonically, rendering the metabolic network incapable of growth after only 18 gene deletions. In the gene addition study, the E. coli flux balance model is augmented with 3,400 non-E. coli reactions from the KEGG database to form a multispecies model. This model is referred to as the Universal model. This study reveals that the maximum theoretical production of six amino acids could be improved by the addition of only one or two genes to the native amino acid production pathway of E. coli, even though the model could choose from 3,400 foreign reaction candidates. Specifically, manipulation of the arginine production pathway showed the most promise with 8.75% and 9.05% predicted increases with the addition of genes for growth on glucose and acetate, respectively. The mechanism of all suggested enhancements is either by: 1) improving the energy efficiency and/or 2) increasing the carbon conversion efficiency of the production route.
An optimization-based procedure for studying the response of metabolic networks after gene knockouts or additions is introduced and applied to a linear flux balance analysis (FBA) Escherichia coli model. Both the gene addition problem of optimally selecting which foreign genes to recombine into E. coli, as well as the gene deletion problem of removing a given number of existing ones, are formulated as mixed-integer optimization problems using binary 0-1 variables. The developed modeling and optimization framework is tested by investigating the effect of gene deletions on biomass production and addressing the maximum theoretical production of the 20 amino acids for aerobic growth on glucose and acetate substrates. In the gene deletion study, the smallest gene set necessary to achieve maximum biomass production in E. coli is determined for aerobic growth on glucose. The subsequent gene knockout analysis indicates that biomass production decreases monotonically, rendering the metabolic network incapable of growth after only 18 gene deletions. In the gene addition study, the E. coli flux balance model is augmented with 3,400 non-E. coli reactions from the KEGG database to form a multispecies model. This model is referred to as the Universal model. This study reveals that the maximum theoretical production of six amino acids could be improved by the addition of only one or two genes to the native amino acid production pathway of E. coli, even though the model could choose from 3,400 foreign reaction candidates. Specifically, manipulation of the arginine production pathway showed the most promise with 8.75% and 9.05% predicted increases with the addition of genes for growth on glucose and acetate, respectively. The mechanism of all suggested enhancements is either by: 1) improving the energy efficiency and/or 2) increasing the carbon conversion efficiency of the production route.
Author Burgard, Anthony P.
Maranas, Costas D.
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Issue 5
Keywords Recombinant microorganism
Recombination
Escherichia coli
Metabolic pathway
Metabolism
Optimization
Gene
Aminoacid
Production
Deletion
Bacteria
Metabolic engineering
Mutation
Mathematical model
Enterobacteriaceae
Language English
License http://onlinelibrary.wiley.com/termsAndConditions#vor
CC BY 4.0
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References Papoutsakis E, Meyer C. 1985a. Equations and calculations of product yields and preferred pathways for butanediol and mixed-acid fermentations. Biotechnol Bioeng 27:50-66.
Schilling CH, Edwards JS, Palsson BO. 1999. Toward metabolic phenomics: analysis of genomic data using flux balances. Biotechnol Progr 15:288-295.
Karp PD, Riley M, Paley SM, Pelligrinitoole A, Krummenacker M. 1999. EcoCyc: encyclopedia of Escherichia coli genes and metabolism. Nucleic Acids Res 27:55.
Hatzimanikatis V, Floudas CA, Bailey JE. 1996a. Analysis and design of metabolic reaction networks via mixed-integer linear optimization. AICHE J 42:1277-1292.
Dedhia NN, Hottinger T, Bailey JE. 1994. Overproduction of glycogen in Escherichia coli blocked in the acetate pathway improves cell growth. Biotechnol Bioeng 44:132-139.
Xie L, Wang D. 1996c. High cell density and high monoclonal antibody production through medium design and rational control in a bioreactor. Biotechnol Bioeng 51:725-729.
Pramanik J, Keasling JD. 1997. Stoichiometric model of Escherichia coli metabolism: incorporation of growth-rate dependent biomass composition and mechanistic energy requirements. Biotechnol Bioeng 56:398-421.
Vallino, JJ, Stephanopoulos, G. 1994a. Carbon flux distribution at the glucose 6-phosphate branch point in Corynebacterium glutamicum during lysine overproduction. Biotechnol Progr 10:327-334.
Ramakrishna R, Edwards JS, McCulloch A, Palsson BO. 2001 Flux-balar analysis of mitochondrial energy metabolism: consequences of systemic stoichiometric constraints. Am J Physiol Regulatory Integrative Comp Physiol 280:R695-R704.
Savageau MA. 1969a. Biochemical systems analysis. I. Some mathematical properties of the arte law for the component enzymatic reactions. J Theor Biol 25:365-369.
Torres NV, Voit EO, Gonzales-Alcon C. 1996. Optimization of nonlinear biotechnological processes with linear programming: application to citric acid production by Aspergillus niger. Biotechnol Bioeng 49:247-258.
Keasling JD, Van Dien SJ, Pramanik J. 1998. Engineering polyphosphate metabolism in Escherichia coli: implications for bioremediation of inorganic contaminants. Biotechnol Bioeng 58:231-239.
Wang CL, et al. 1997. Cadmium removal by a new strain Pseudomonas aeruginosa in aerobic culture. Appl Environ Microb 63:4075-4078.
Chou CH, Bennett GN, San KY. 1994. Effect of modified glucose uptake using genetic engineering techniques on high-level recombinant protein production in Escherichia coli dense cultures. Biotechnol Bioeng 44:952-960.
Edwards JS, Palsson BO. 2000a. The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities. P. Natl. Acad. Sci. USA 97:5528-5533.
Winter RB, Yen KM, Ensley BD. 1989. Efficient degradation of trichloroethylene by a recombinant Escherichia coli. Bio/Technology 7:282-285.
Van Dien SJ, Keasling JD. 1998. Optimization of polyphosphate degradation and phosphate secretion using hybrid metabolic pathways and engineering host strains. Biotechnol Bioeng 59:754-761.
Majewski RA, Domach MM. 1990. Simple constrained optimization view of acetate overflow in Escherichia coli. Biotechnol Bioeng 35:732-738.
Hatzimanikatis V, Emmerling M, Sauer U, Bailey, JE. 1998. Application of mathematical tools for metabolic design of microbial ethanol production. Biotechnol Bioeng 58:154-161.
Pennisi E. 1997. Laboratory workhorse decoded. Science 277:1432-1434.
Vallino J, Stephanopoulos G. 1993. Metabolic flux distributions in Corynebacterium glutamicum during growth and lysine overproduction. Biotechnol Bioeng 41:633-646.
Kacser H, Burns JA. 1973. The control of flux. Symp Soc Exp Biol 27:65-104.
Xie L, Wang D. 1996a. Material balance studies on animal cell metabolism using stoichiometrically based reaction network. Biotechnol Bioeng 52:579-590.
Varma A, Palsson BO. 1994. Metabolic flux balancing: basic concepts, scientific and practical use. Bio/Technology 12:994-998.
Savageau MA. 1969b. Biochemical systems analysis. II. The steady state solutions for an n-pool system using a power-law approximation. J Theor Biol 25:370-379.
Henriksen CM, Christensen LH, Nielsen J, Villadsen J. 1996. Growth energetics and metabolic fluxes in continuous cultures of Penicillium chrysogenum. J Biotechnol 45:149-164.
Pons A, Dussap C, Pequignot C, et al. 1996. Metabolic flux distribution in Cornybacterium melassecola ATCC 17965 for various carbon sources. Biotechnol Bioeng 51:177-189.
Xie L, Wang D. 1994b. Stoichiometric analysis of animal cell growth and its application in medium design. Biotechnol Bioeng 43:1164-1174.
Xie L, Wang D. 1997. Integrated approaches to the design of media and feeding strategies for fed-batch cultures of animal cells. Trends Biotechnol 15:109-113.
Hatzimanikatis V, Floudas CA, Bailey JE. 1996b. Optimization of regulatory architectures in metabolic reaction networks. Biotechnol Bioeng 52:485-500.
Aristidou A, San KY, Bennett GN. 1994. Modification of central metabolic pathway in Escherichia coli to reduce acetate accumulation by heterologous expression of the Bacillus subtilis acetolactate synthase gene. Biotechnol Bioeng 44:944-951.
Xie L, Wang D. 1996b. Energy metabolism and ATP balance in animal cell cultivation using a stoichiometrically based reaction network. Biotechnol Bioeng 52:591-601.
Xie L, Wang D. 1994a. Applications if improved stoichiometric model in medium design and fed-batch cultivation of animal cells in bioreactor. Cytotechnology 15:17-29.
Jorgensen H, Nielsen J, Villadsen J. 1995. Metabolic flux distributions in Penicillium chrysogenum during fed-batch cultivations. Biotechnol Bioeng 46:117-131.
Edwards JS, Palsson, BO. 2000b. Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions. BMC Bioinformatics 1:1.
Varma A, Palsson BO. 1993. Metabolic capabilities of Escherichia coli. II. Optimal growth patterns. J Theor Biol 165:503-522.
Hutchison CA, et al. 1999. Global transposon mutagenesis and a minimal mycoplasma genome. Science 286:2165-2169.
Savageau MA. 1970. Biochemical systems analysis. III. Dynamic solutions using a power-law approximation. J Theor Biol 26:215-226.
Varma A, Boesch BW, Palsson, BO. 1993b. Biochemical production capabilities of Escherichia coli. Biotechnol Bioeng 42:59-73.
Mushegian AR, Koonin EV. 1996. A minimal gene set for cellular life derived by comparison of complete bacterial genomes. P Natl Acad Sci USA 93:10268-10273.
Lee S, Phalakornkule C, Domach MM, Grossman IE. 2000. Recursive MILP model for finding all the alternate optima in LP models for metabolic networks. Comput Chem Eng 24:711-716.
Sabatie J, et al. 1991. Biotin formation by recombinant strains of Escherichia coli: influence of the host physiology. J Biotechnol 20:29-50.
Vallino, JJ, Stephanopoulos, G. 1994b. Carbon flux distribution at the pyruvate branch point in Corynebacterium glutamicum during lysine overproduction. Biotechnol Progr 10:320-326.
Voit EO. 1992. Optimization of integrated biochemical systems. Biotechnol Bioeng 40:572-582.
Heinrich R, Rapoport TA. 1974. A linear steady-state treatment of enzymatic chains. Eur J Biochem 42:89-95.
Papoutsakis E, Meyer C. 1985b. Fermentation equations for propionic acid bacteria and production of assorted oxychemicals from various sugars. Biotechnol Bioeng 27:67-80.
Blattner FR, et al. 1997. The complete genome sequence of Escherichia coli K-12. Science 277:1453-1474.
Delgado J, Liao JC. 1997. Inverse flux analysis for reduction of acetate excretion in Escherichia coli. Biotechnol Progr 13:361-367.
Hatzimanikatis V, Bailey JE. 1997. Effects of spatiotemporal variations on metabolic control: approximate analysis using (log)linear kinetic models. Biotechnol Bioeng 54:91-104.
Varma A, Boesch BW, Palsson BO. 1993a. Stoichiometric interpretation of Escherichia coli glucose catabolism under various oxygenation rates. Appl Environ Microb 59:2465-2473.
Regan L, Bogle IDL, Dunnill P. 1993. Simulation and optimization of metabolic pathways. Comput Chem Eng 17:627-637.
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References_xml – reference: Wang CL, et al. 1997. Cadmium removal by a new strain Pseudomonas aeruginosa in aerobic culture. Appl Environ Microb 63:4075-4078.
– reference: Henriksen CM, Christensen LH, Nielsen J, Villadsen J. 1996. Growth energetics and metabolic fluxes in continuous cultures of Penicillium chrysogenum. J Biotechnol 45:149-164.
– reference: Majewski RA, Domach MM. 1990. Simple constrained optimization view of acetate overflow in Escherichia coli. Biotechnol Bioeng 35:732-738.
– reference: Pramanik J, Keasling JD. 1997. Stoichiometric model of Escherichia coli metabolism: incorporation of growth-rate dependent biomass composition and mechanistic energy requirements. Biotechnol Bioeng 56:398-421.
– reference: Hatzimanikatis V, Emmerling M, Sauer U, Bailey, JE. 1998. Application of mathematical tools for metabolic design of microbial ethanol production. Biotechnol Bioeng 58:154-161.
– reference: Heinrich R, Rapoport TA. 1974. A linear steady-state treatment of enzymatic chains. Eur J Biochem 42:89-95.
– reference: Jorgensen H, Nielsen J, Villadsen J. 1995. Metabolic flux distributions in Penicillium chrysogenum during fed-batch cultivations. Biotechnol Bioeng 46:117-131.
– reference: Papoutsakis E, Meyer C. 1985a. Equations and calculations of product yields and preferred pathways for butanediol and mixed-acid fermentations. Biotechnol Bioeng 27:50-66.
– reference: Varma A, Palsson BO. 1993. Metabolic capabilities of Escherichia coli. II. Optimal growth patterns. J Theor Biol 165:503-522.
– reference: Savageau MA. 1969b. Biochemical systems analysis. II. The steady state solutions for an n-pool system using a power-law approximation. J Theor Biol 25:370-379.
– reference: Dedhia NN, Hottinger T, Bailey JE. 1994. Overproduction of glycogen in Escherichia coli blocked in the acetate pathway improves cell growth. Biotechnol Bioeng 44:132-139.
– reference: Savageau MA. 1970. Biochemical systems analysis. III. Dynamic solutions using a power-law approximation. J Theor Biol 26:215-226.
– reference: Winter RB, Yen KM, Ensley BD. 1989. Efficient degradation of trichloroethylene by a recombinant Escherichia coli. Bio/Technology 7:282-285.
– reference: Xie L, Wang D. 1996c. High cell density and high monoclonal antibody production through medium design and rational control in a bioreactor. Biotechnol Bioeng 51:725-729.
– reference: Xie L, Wang D. 1994a. Applications if improved stoichiometric model in medium design and fed-batch cultivation of animal cells in bioreactor. Cytotechnology 15:17-29.
– reference: Xie L, Wang D. 1996b. Energy metabolism and ATP balance in animal cell cultivation using a stoichiometrically based reaction network. Biotechnol Bioeng 52:591-601.
– reference: Pennisi E. 1997. Laboratory workhorse decoded. Science 277:1432-1434.
– reference: Regan L, Bogle IDL, Dunnill P. 1993. Simulation and optimization of metabolic pathways. Comput Chem Eng 17:627-637.
– reference: Keasling JD, Van Dien SJ, Pramanik J. 1998. Engineering polyphosphate metabolism in Escherichia coli: implications for bioremediation of inorganic contaminants. Biotechnol Bioeng 58:231-239.
– reference: Savageau MA. 1969a. Biochemical systems analysis. I. Some mathematical properties of the arte law for the component enzymatic reactions. J Theor Biol 25:365-369.
– reference: Ramakrishna R, Edwards JS, McCulloch A, Palsson BO. 2001 Flux-balar analysis of mitochondrial energy metabolism: consequences of systemic stoichiometric constraints. Am J Physiol Regulatory Integrative Comp Physiol 280:R695-R704.
– reference: Edwards JS, Palsson BO. 2000a. The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities. P. Natl. Acad. Sci. USA 97:5528-5533.
– reference: Varma A, Palsson BO. 1994. Metabolic flux balancing: basic concepts, scientific and practical use. Bio/Technology 12:994-998.
– reference: Aristidou A, San KY, Bennett GN. 1994. Modification of central metabolic pathway in Escherichia coli to reduce acetate accumulation by heterologous expression of the Bacillus subtilis acetolactate synthase gene. Biotechnol Bioeng 44:944-951.
– reference: Hatzimanikatis V, Floudas CA, Bailey JE. 1996a. Analysis and design of metabolic reaction networks via mixed-integer linear optimization. AICHE J 42:1277-1292.
– reference: Hutchison CA, et al. 1999. Global transposon mutagenesis and a minimal mycoplasma genome. Science 286:2165-2169.
– reference: Papoutsakis E, Meyer C. 1985b. Fermentation equations for propionic acid bacteria and production of assorted oxychemicals from various sugars. Biotechnol Bioeng 27:67-80.
– reference: Vallino, JJ, Stephanopoulos, G. 1994a. Carbon flux distribution at the glucose 6-phosphate branch point in Corynebacterium glutamicum during lysine overproduction. Biotechnol Progr 10:327-334.
– reference: Edwards JS, Palsson, BO. 2000b. Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions. BMC Bioinformatics 1:1.
– reference: Schilling CH, Edwards JS, Palsson BO. 1999. Toward metabolic phenomics: analysis of genomic data using flux balances. Biotechnol Progr 15:288-295.
– reference: Sabatie J, et al. 1991. Biotin formation by recombinant strains of Escherichia coli: influence of the host physiology. J Biotechnol 20:29-50.
– reference: Van Dien SJ, Keasling JD. 1998. Optimization of polyphosphate degradation and phosphate secretion using hybrid metabolic pathways and engineering host strains. Biotechnol Bioeng 59:754-761.
– reference: Lee S, Phalakornkule C, Domach MM, Grossman IE. 2000. Recursive MILP model for finding all the alternate optima in LP models for metabolic networks. Comput Chem Eng 24:711-716.
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– reference: Varma A, Boesch BW, Palsson BO. 1993a. Stoichiometric interpretation of Escherichia coli glucose catabolism under various oxygenation rates. Appl Environ Microb 59:2465-2473.
– reference: Delgado J, Liao JC. 1997. Inverse flux analysis for reduction of acetate excretion in Escherichia coli. Biotechnol Progr 13:361-367.
– reference: Xie L, Wang D. 1996a. Material balance studies on animal cell metabolism using stoichiometrically based reaction network. Biotechnol Bioeng 52:579-590.
– reference: Varma A, Boesch BW, Palsson, BO. 1993b. Biochemical production capabilities of Escherichia coli. Biotechnol Bioeng 42:59-73.
– reference: Xie L, Wang D. 1997. Integrated approaches to the design of media and feeding strategies for fed-batch cultures of animal cells. Trends Biotechnol 15:109-113.
– reference: Hatzimanikatis V, Bailey JE. 1997. Effects of spatiotemporal variations on metabolic control: approximate analysis using (log)linear kinetic models. Biotechnol Bioeng 54:91-104.
– reference: Kacser H, Burns JA. 1973. The control of flux. Symp Soc Exp Biol 27:65-104.
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– reference: Xie L, Wang D. 1994b. Stoichiometric analysis of animal cell growth and its application in medium design. Biotechnol Bioeng 43:1164-1174.
– reference: Mushegian AR, Koonin EV. 1996. A minimal gene set for cellular life derived by comparison of complete bacterial genomes. P Natl Acad Sci USA 93:10268-10273.
– reference: Chou CH, Bennett GN, San KY. 1994. Effect of modified glucose uptake using genetic engineering techniques on high-level recombinant protein production in Escherichia coli dense cultures. Biotechnol Bioeng 44:952-960.
– reference: Vallino J, Stephanopoulos G. 1993. Metabolic flux distributions in Corynebacterium glutamicum during growth and lysine overproduction. Biotechnol Bioeng 41:633-646.
– reference: Voit EO. 1992. Optimization of integrated biochemical systems. Biotechnol Bioeng 40:572-582.
– reference: Blattner FR, et al. 1997. The complete genome sequence of Escherichia coli K-12. Science 277:1453-1474.
– reference: Hatzimanikatis V, Floudas CA, Bailey JE. 1996b. Optimization of regulatory architectures in metabolic reaction networks. Biotechnol Bioeng 52:485-500.
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  start-page: 370
  year: 1969b
  end-page: 379
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– volume: 26
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– volume: 54
  start-page: 91
  year: 1997
  end-page: 104
  article-title: Effects of spatiotemporal variations on metabolic control: approximate analysis using (log)linear kinetic models
  publication-title: Biotechnol Bioeng
– volume: 44
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  publication-title: Biotechnol Bioeng
– volume: 10
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  year: 1994a
  end-page: 334
  article-title: Carbon flux distribution at the glucose 6‐phosphate branch point in during lysine overproduction
  publication-title: Biotechnol Progr
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  year: 1993b
  end-page: 73
  article-title: Biochemical production capabilities of
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  year: 1996a
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  article-title: Material balance studies on animal cell metabolism using stoichiometrically based reaction network
  publication-title: Biotechnol Bioeng
– volume: 44
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  year: 1994
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  article-title: Overproduction of glycogen in blocked in the acetate pathway improves cell growth
  publication-title: Biotechnol Bioeng
– volume: 42
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  year: 2001
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Snippet An optimization‐based procedure for studying the response of metabolic networks after gene knockouts or additions is introduced and applied to a linear flux...
An optimization-based procedure for studying the response of metabolic networks after gene knockouts or additions is introduced and applied to a linear flux...
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SubjectTerms acetic acid
Aerobiosis - physiology
Amino Acids - biosynthesis
Arginine - biosynthesis
Biological and medical sciences
Biomass
Biotechnology
E. coli metabolism
Escherichia coli
Escherichia coli - genetics
Escherichia coli - metabolism
flux balance models
Fundamental and applied biological sciences. Psychology
Gene Deletion
gene recombination
Genetic engineering
Genetic technics
glucose
Glucose - metabolism
Methods. Procedures. Technologies
Models, Biological
Modification of gene expression level
Mutagenesis, Insertional - genetics
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Title Probing the performance limits of the Escherichia coli metabolic network subject to gene additions or deletions
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