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Volumn 15, Issue 1, 2004, Pages 64-69

Use of genome-scale microbial models for metabolic engineering

Author keywords

[No Author keywords available]

Indexed keywords

ADSORPTION KINETICS; ALGORITHM; COMPARTMENT MODEL; ESCHERICHIA COLI; HAEMOPHILUS INFLUENZAE; HELICOBACTER PYLORI; INTRACELLULAR MEMBRANE; METABOLIC ENGINEERING; MOLECULAR DYNAMICS; PHENOTYPE; PREDICTION; PRIORITY JOURNAL; REVIEW; SACCHAROMYCES CEREVISIAE; STOICHIOMETRY;

EID: 1242283921     PISSN: 09581669     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.copbio.2003.11.003     Document Type: Review
Times cited : (138)

References (53)
  • 3
    • 0037075690 scopus 로고    scopus 로고
    • Modeling and simulation: Tools for metabolic engineering
    • A critical review of different modeling approaches with respect to their potential for metabolic engineering.
    • Wiechert W. Modeling and simulation: tools for metabolic engineering. J. Biotechnol. 94:2002;37-63 A critical review of different modeling approaches with respect to their potential for metabolic engineering.
    • (2002) J. Biotechnol. , vol.94 , pp. 37-63
    • Wiechert, W.1
  • 4
    • 33749133230 scopus 로고    scopus 로고
    • Metabolic flux distributions in Corynebacterium glutamicum during growth and lysine overproduction
    • Reprinted from Biotechnology and Bioengineering, Vol. 41, pp 633-646 (1993)
    • Vallino JJ, Stephanopoulos G: Metabolic flux distributions in Corynebacterium glutamicum during growth and lysine overproduction. [Reprinted from Biotechnology and Bioengineering, Vol. 41, pp 633-646 (1993).] Biotechnol Bioeng 2000, 67:872-885.
    • (2000) Biotechnol Bioeng , vol.67 , pp. 872-885
    • Vallino, J.J.1    Stephanopoulos, G.2
  • 5
    • 0032600888 scopus 로고    scopus 로고
    • Metabolic fluxes and metabolic engineering
    • Stephanopoulos G. Metabolic fluxes and metabolic engineering. Metab. Eng. 1:1999;1-11.
    • (1999) Metab. Eng. , vol.1 , pp. 1-11
    • Stephanopoulos, G.1
  • 6
    • 0033987329 scopus 로고    scopus 로고
    • Metabolic network analysis. A powerful tool in metabolic engineering
    • Christensen B., Nielsen J. Metabolic network analysis. A powerful tool in metabolic engineering. Adv. Biochem. Eng. Biotechnol. 66:2000;209-231.
    • (2000) Adv. Biochem. Eng. Biotechnol. , vol.66 , pp. 209-231
    • Christensen, B.1    Nielsen, J.2
  • 7
    • 0042825675 scopus 로고    scopus 로고
    • Systematic quantification of complex metabolic flux networks using stable isotopes and mass spectrometry
    • Klapa M.I., Aon J.C., Stephanopoulos G. Systematic quantification of complex metabolic flux networks using stable isotopes and mass spectrometry. Eur. J. Biochem. 270:2003;3525-3542.
    • (2003) Eur. J. Biochem. , vol.270 , pp. 3525-3542
    • Klapa, M.I.1    Aon, J.C.2    Stephanopoulos, G.3
  • 9
    • 0027223982 scopus 로고
    • Stoichiometric interpretation of Escherichia coli glucose catabolism under various oxygenation rates
    • Varma A., Boesch B.W., Palsson B.O. Stoichiometric interpretation of Escherichia coli glucose catabolism under various oxygenation rates. Appl. Environ. Microbiol. 59:1993;2465-2473.
    • (1993) Appl. Environ. Microbiol. , vol.59 , pp. 2465-2473
    • Varma, A.1    Boesch, B.W.2    Palsson, B.O.3
  • 11
    • 0034064689 scopus 로고    scopus 로고
    • A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks
    • Schuster S., Fell D.A., Dandekar T. A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks. Nat. Biotechnol. 18:2000;326-332.
    • (2000) Nat. Biotechnol. , vol.18 , pp. 326-332
    • Schuster, S.1    Fell, D.A.2    Dandekar, T.3
  • 12
    • 0034615791 scopus 로고    scopus 로고
    • Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective
    • Schilling C.H., Letscher D., Palsson B.O. Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective. J. Theor. Biol. 203:2000;229-248.
    • (2000) J. Theor. Biol. , vol.203 , pp. 229-248
    • Schilling, C.H.1    Letscher, D.2    Palsson, B.O.3
  • 13
    • 0037308505 scopus 로고    scopus 로고
    • Two approaches for metabolic pathway analysis?
    • Klamt S., Stelling J. Two approaches for metabolic pathway analysis? Trends Biotechnol. 21:2003;64-69.
    • (2003) Trends Biotechnol , vol.21 , pp. 64-69
    • Klamt, S.1    Stelling, J.2
  • 14
    • 0037406237 scopus 로고    scopus 로고
    • Development of network-based pathway definitions: The need to analyze real metabolic networks
    • Palsson B.O., Price N.D., Papin J.A. Development of network-based pathway definitions: the need to analyze real metabolic networks. Trends Biotechnol. 21:2003;195-198.
    • (2003) Trends Biotechnol. , vol.21 , pp. 195-198
    • Palsson, B.O.1    Price, N.D.2    Papin, J.A.3
  • 15
    • 0036713452 scopus 로고    scopus 로고
    • Metabolic control analysis of glycerol synthesis in Saccharomyces cerevisiae
    • Cronwright G.R., Rohwer J.M., Prior B.A. Metabolic control analysis of glycerol synthesis in Saccharomyces cerevisiae. Appl. Environ. Microbiol. 68:2002;4448-4456.
    • (2002) Appl. Environ. Microbiol. , vol.68 , pp. 4448-4456
    • Cronwright, G.R.1    Rohwer, J.M.2    Prior, B.A.3
  • 17
    • 0034625143 scopus 로고    scopus 로고
    • The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
    • Edwards J.S., Palsson B.O. The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities. Proc. Natl. Acad. Sci. USA. 97:2000;5528-5533.
    • (2000) Proc. Natl. Acad. Sci. USA , vol.97 , pp. 5528-5533
    • Edwards, J.S.1    Palsson, B.O.2
  • 18
    • 0344328817 scopus 로고    scopus 로고
    • An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR)
    • Reed J.L., Vo T.D., Schilling C.H., Palsson B.O. An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Genome Biol. 4:2003;R54.
    • (2003) Genome Biol. , vol.4 , pp. 54
    • Reed, J.L.1    Vo, T.D.2    Schilling, C.H.3    Palsson, B.O.4
  • 19
    • 0033580813 scopus 로고    scopus 로고
    • Systems properties of the Haemophilus influenzae Rd metabolic genotype
    • Edwards J.S., Palsson B.O. Systems properties of the Haemophilus influenzae Rd metabolic genotype. J. Biol. Chem. 274:1999;17410-17416.
    • (1999) J. Biol. Chem. , vol.274 , pp. 17410-17416
    • Edwards, J.S.1    Palsson, B.O.2
  • 21
    • 0037313750 scopus 로고    scopus 로고
    • Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network
    • The first genome-scale model of a eukaryotic organism, which also demonstrates the reconstruction of the largest stoichiometric model to date.
    • Forster J., Famili I., Fu P., Palsson B.O., Nielsen J. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. Genome Res. 13:2003;244-253 The first genome-scale model of a eukaryotic organism, which also demonstrates the reconstruction of the largest stoichiometric model to date.
    • (2003) Genome Res. , vol.13 , pp. 244-253
    • Forster, J.1    Famili, I.2    Fu, P.3    Palsson, B.O.4    Nielsen, J.5
  • 22
    • 0037385718 scopus 로고    scopus 로고
    • Genome-scale microbial in silico models: The constraints-based approach
    • Price N.D., Papin J.A., Schilling C.H., Palsson B.O. Genome-scale microbial in silico models: the constraints-based approach. Trends Biotechnol. 21:2003;162-169.
    • (2003) Trends Biotechnol. , vol.21 , pp. 162-169
    • Price, N.D.1    Papin, J.A.2    Schilling, C.H.3    Palsson, B.O.4
  • 23
    • 0037079050 scopus 로고    scopus 로고
    • Metabolic network structure determines key aspects of functionality and regulation
    • Using pathway analysis, the authors have devised a theoretical method for predicting key aspects of regulation in the metabolic network from network structure alone.
    • Stelling J., Klamt S., Bettenbrock K., Schuster S., Gilles E.D. Metabolic network structure determines key aspects of functionality and regulation. Nature. 420:2002;190-193 Using pathway analysis, the authors have devised a theoretical method for predicting key aspects of regulation in the metabolic network from network structure alone.
    • (2002) Nature , vol.420 , pp. 190-193
    • Stelling, J.1    Klamt, S.2    Bettenbrock, K.3    Schuster, S.4    Gilles, E.D.5
  • 24
    • 0036286631 scopus 로고    scopus 로고
    • Energy balance for analysis of complex metabolic networks
    • Incorporation of explicit thermodynamic constraints into FBA reduces the solution space and leads to improved physiological predictions.
    • Beard D.A., Liang S.D., Qian H. Energy balance for analysis of complex metabolic networks. Biophys. J. 83:2002;79-86 Incorporation of explicit thermodynamic constraints into FBA reduces the solution space and leads to improved physiological predictions.
    • (2002) Biophys. J. , vol.83 , pp. 79-86
    • Beard, D.A.1    Liang, S.D.2    Qian, H.3
  • 26
    • 0035125986 scopus 로고    scopus 로고
    • In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data
    • Edwards J.S., Ibarra R.U., Palsson B.O. In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data. Nat. Biotechnol. 19:2001;125-130.
    • (2001) Nat. Biotechnol. , vol.19 , pp. 125-130
    • Edwards, J.S.1    Ibarra, R.U.2    Palsson, B.O.3
  • 27
    • 0037079023 scopus 로고    scopus 로고
    • Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth
    • Evidence that the E. coli metabolic network has evolved for optimum growth is presented. Experiments show that evolution of a suboptimal network is in the direction of metabolic state determined a priori using in silico analysis.
    • Ibarra R.U., Edwards J.S., Palsson B.O. Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth. Nature. 420:2002;186-189 Evidence that the E. coli metabolic network has evolved for optimum growth is presented. Experiments show that evolution of a suboptimal network is in the direction of metabolic state determined a priori using in silico analysis.
    • (2002) Nature , vol.420 , pp. 186-189
    • Ibarra, R.U.1    Edwards, J.S.2    Palsson, B.O.3
  • 28
    • 0344824417 scopus 로고    scopus 로고
    • Saccharomyces cerevisiae phenotype can be predicted by using constraint-based analysis of a genome-scale reconstructed metabolic network
    • Famili I, Forster J, Nielsen J, Palsson BO: Saccharomyces cerevisiae phenotype can be predicted by using constraint-based analysis of a genome-scale reconstructed metabolic network. Proc Natl Acad Sci USA 2003, 100:13134-13139.
    • (2003) Proc Natl Acad Sci USA , vol.100 , pp. 13134-13139
    • Famili, I.1    Forster, J.2    Nielsen, J.3    Palsson, B.O.4
  • 29
    • 0038293216 scopus 로고    scopus 로고
    • Optimization-based framework for inferring and testing hypothesized metabolic objective functions
    • Using an optimization approach the authors developed a mathematical framework to test whether experimental flux data are consistent with hypothesized objective function.
    • Burgard A.P., Maranas C.D. Optimization-based framework for inferring and testing hypothesized metabolic objective functions. Biotechnol. Bioeng. 82:2003;670-677 Using an optimization approach the authors developed a mathematical framework to test whether experimental flux data are consistent with hypothesized objective function.
    • (2003) Biotechnol. Bioeng. , vol.82 , pp. 670-677
    • Burgard, A.P.1    Maranas, C.D.2
  • 30
    • 0037069467 scopus 로고    scopus 로고
    • Analysis of optimality in natural and perturbed metabolic networks
    • Using experimental flux data from E. coli, the authors demonstrate that the metabolic network of genetically modified strains does not necessarily operate in an optimum growth regime.
    • Segre D., Vitkup D., Church G.M. Analysis of optimality in natural and perturbed metabolic networks. Proc. Natl. Acad. Sci. USA. 99:2002;15112-15117 Using experimental flux data from E. coli, the authors demonstrate that the metabolic network of genetically modified strains does not necessarily operate in an optimum growth regime.
    • (2002) Proc. Natl. Acad. Sci. USA , vol.99 , pp. 15112-15117
    • Segre, D.1    Vitkup, D.2    Church, G.M.3
  • 31
    • 0042816453 scopus 로고    scopus 로고
    • Large-scale evaluation of in silico gene deletions in Saccharomyces cerevisiae
    • Forster J., Famili I., Palsson B.O., Nielsen J. Large-scale evaluation of in silico gene deletions in Saccharomyces cerevisiae. OMICS. 7:2003;193-202.
    • (2003) OMICS , vol.7 , pp. 193-202
    • Forster, J.1    Famili, I.2    Palsson, B.O.3    Nielsen, J.4
  • 32
    • 0036284760 scopus 로고    scopus 로고
    • An expanded role for microbial physiology in metabolic engineering and functional genomics: Moving towards systems biology(1)
    • Nielsen J., Olsson L. An expanded role for microbial physiology in metabolic engineering and functional genomics: moving towards systems biology(1). FEM Yeast Res. 2:2002;175-181.
    • (2002) FEM Yeast Res. , vol.2 , pp. 175-181
    • Nielsen, J.1    Olsson, L.2
  • 33
    • 0035812464 scopus 로고    scopus 로고
    • Probing the performance limits of the Escherichia coli metabolic network subject to gene additions or deletions
    • Burgard A.P., Maranas C.D. Probing the performance limits of the Escherichia coli metabolic network subject to gene additions or deletions. Biotechnol. Bioeng. 74:2001;364-375.
    • (2001) Biotechnol. Bioeng. , vol.74 , pp. 364-375
    • Burgard, A.P.1    Maranas, C.D.2
  • 34
    • 0343035686 scopus 로고    scopus 로고
    • Stoichiometric model of Escherichia coli metabolism: Incorporation of growth-rate dependent biomass composition and mechanistic energy requirements
    • Pramanik J., Keasling J.D. Stoichiometric model of Escherichia coli metabolism: incorporation of growth-rate dependent biomass composition and mechanistic energy requirements. Biotechnol. Bioeng. 56:1997;398-421.
    • (1997) Biotechnol. Bioeng. , vol.56 , pp. 398-421
    • Pramanik, J.1    Keasling, J.D.2
  • 35
    • 0031015551 scopus 로고    scopus 로고
    • Flux distributions in anaerobic, glucose-limited continuous cultures of Saccharomyces cerevisiae
    • Nissen T.L., Schulze U., Nielsen J., Villadsen J. Flux distributions in anaerobic, glucose-limited continuous cultures of Saccharomyces cerevisiae. Microbiol. 143:1997;203-218.
    • (1997) Microbiol. , vol.143 , pp. 203-218
    • Nissen, T.L.1    Schulze, U.2    Nielsen, J.3    Villadsen, J.4
  • 36
    • 0035824029 scopus 로고    scopus 로고
    • Regulation of gene expression in flux balance models of metabolism
    • Covert M.W., Schilling C.H., Palsson B.O. Regulation of gene expression in flux balance models of metabolism. J. Theor. Biol. 213:2001;73-88.
    • (2001) J. Theor. Biol. , vol.213 , pp. 73-88
    • Covert, M.W.1    Schilling, C.H.2    Palsson, B.O.3
  • 37
    • 0037008673 scopus 로고    scopus 로고
    • Transcriptional regulation in constraints-based metabolic models of Escherichia coli
    • A step towards incorporation of transcriptional regulation into stoichiometric models to obtain improved predictions of phenotypes.
    • Covert M.W., Palsson B.O. Transcriptional regulation in constraints-based metabolic models of Escherichia coli. J. Biol. Chem. 277:2002;28058-28064 A step towards incorporation of transcriptional regulation into stoichiometric models to obtain improved predictions of phenotypes.
    • (2002) J. Biol. Chem. , vol.277 , pp. 28058-28064
    • Covert, M.W.1    Palsson, B.O.2
  • 38
    • 0037424661 scopus 로고    scopus 로고
    • Constraints-based models: Regulation of gene expression reduces the steady-state solution space
    • Covert M.W., Palsson B.O. Constraints-based models: regulation of gene expression reduces the steady-state solution space. J. Theor. Biol. 221:2003;309-325.
    • (2003) J. Theor. Biol. , vol.221 , pp. 309-325
    • Covert, M.W.1    Palsson, B.O.2
  • 39
    • 0036708443 scopus 로고    scopus 로고
    • Dynamic flux balance analysis of diauxic growth in Escherichia coli
    • Mahadevan R., Edwards J.S., Doyle F.J. III Dynamic flux balance analysis of diauxic growth in Escherichia coli. Biophys. J. 83:2002;1331-1340.
    • (2002) Biophys. J. , vol.83 , pp. 1331-1340
    • Mahadevan, R.1    Edwards, J.S.2    Doyle III, F.J.3
  • 40
    • 0030571222 scopus 로고    scopus 로고
    • Pathway analysis, engineering, and physiological considerations for redirecting central metabolism
    • Liao J.C., Hou S.-Y., Chao Y.-P. Pathway analysis, engineering, and physiological considerations for redirecting central metabolism. Biotechnol. Bioeng. 52:1996;129-140.
    • (1996) Biotechnol. Bioeng. , vol.52 , pp. 129-140
    • Liao, J.C.1    Hou, S.-Y.2    Chao, Y.-P.3
  • 41
    • 0037142769 scopus 로고    scopus 로고
    • Metabolic pathway analysis of a recombinant yeast for rational strain development
    • Carlson R., Fell D., Srienc F. Metabolic pathway analysis of a recombinant yeast for rational strain development. Biotechnol. Bioeng. 79:2002;121-134.
    • (2002) Biotechnol. Bioeng. , vol.79 , pp. 121-134
    • Carlson, R.1    Fell, D.2    Srienc, F.3
  • 42
    • 0036039060 scopus 로고    scopus 로고
    • Combinatorial complexity of pathway analysis in metabolic networks
    • Klamt S., Stelling J. Combinatorial complexity of pathway analysis in metabolic networks. Mol. Biol. Rep. 29:2002;233-236.
    • (2002) Mol. Biol. Rep. , vol.29 , pp. 233-236
    • Klamt, S.1    Stelling, J.2
  • 44
    • 0242267924 scopus 로고    scopus 로고
    • Reconstruction of the central carbon metabolism of Aspergillus niger
    • David H., Åkesson M., Nielsen J. Reconstruction of the central carbon metabolism of Aspergillus niger. Eur. J. Biochem. 270:2003;4243-4253.
    • (2003) Eur. J. Biochem. , vol.270 , pp. 4243-4253
    • David, H.1    Åkesson, M.2    Nielsen, J.3
  • 45
    • 0242487787 scopus 로고    scopus 로고
    • Optknock: A bilevel programming framework for identifying gene knockout strategies for microbial strain optimization
    • Burgard A.P., Pharkya P., Maranas C.D. Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnol. Bioeng. 84:2003;647-657.
    • (2003) Biotechnol. Bioeng. , vol.84 , pp. 647-657
    • Burgard, A.P.1    Pharkya, P.2    Maranas, C.D.3
  • 47
    • 0036469172 scopus 로고    scopus 로고
    • Metabolomics and microarrays for improved understanding of phenotypic characteristics controlled by both genomics and environmental constraints
    • Phelps T.J., Palumbo A.V., Beliaev A.S. Metabolomics and microarrays for improved understanding of phenotypic characteristics controlled by both genomics and environmental constraints. Curr. Opin. Biotechnol. 13:2002;20-24.
    • (2002) Curr. Opin. Biotechnol. , vol.13 , pp. 20-24
    • Phelps, T.J.1    Palumbo, A.V.2    Beliaev, A.S.3
  • 48
    • 0037716676 scopus 로고    scopus 로고
    • Building with a scaffold: Emerging strategies for high- to low-level cellular modeling
    • Ideker T., Lauffenburger D. Building with a scaffold: emerging strategies for high- to low-level cellular modeling. Trends Biotechnol. 21:2003;255-262.
    • (2003) Trends Biotechnol. , vol.21 , pp. 255-262
    • Ideker, T.1    Lauffenburger, D.2
  • 49
    • 0038014879 scopus 로고    scopus 로고
    • Co-clustering of biological networks and gene expression data
    • Hanisch D., Zien A., Zimmer R., Lengauer T. Co-clustering of biological networks and gene expression data. Bioinformatics. 18:2002;S145-S154.
    • (2002) Bioinformatics , vol.18
    • Hanisch, D.1    Zien, A.2    Zimmer, R.3    Lengauer, T.4
  • 50
    • 0033670135 scopus 로고    scopus 로고
    • Pathway analysis in metabolic databases via differential metabolic display (DMD)
    • Kuffner R., Zimmer R., Lengauer T. Pathway analysis in metabolic databases via differential metabolic display (DMD). Bioinformatics. 16:2000;825-836.
    • (2000) Bioinformatics , vol.16 , pp. 825-836
    • Kuffner, R.1    Zimmer, R.2    Lengauer, T.3
  • 51
    • 0000801240 scopus 로고    scopus 로고
    • Discovering regulatory and signalling circuits in molecular interaction networks
    • A framework for analysis of different level omics data to extract biologically relevant information.
    • Ideker T., Ozier O., Schwikowski B., Siegel A.F. Discovering regulatory and signalling circuits in molecular interaction networks. Bioinformatics. 18:2002;S233-S240 A framework for analysis of different level omics data to extract biologically relevant information.
    • (2002) Bioinformatics , vol.18
    • Ideker, T.1    Ozier, O.2    Schwikowski, B.3    Siegel, A.F.4
  • 52
    • 0037200931 scopus 로고    scopus 로고
    • A functional genomics approach using metabolomics and in silico pathway analysis
    • Forster J., Gombert A.K., Nielsen J. A functional genomics approach using metabolomics and in silico pathway analysis. Biotechnol. Bioeng. 79:2002;703-712.
    • (2002) Biotechnol. Bioeng. , vol.79 , pp. 703-712
    • Forster, J.1    Gombert, A.K.2    Nielsen, J.3


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