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Applications of Metabolic Modeling to Drive Bioprocess Development for the Production of Value-added Chemicals  

Mahadevan, Radhakrishnan (Genomatica, Inc.)
Burgard, Anthony P. (Genomatica, Inc.)
Famili, Iman (Genomatica, Inc.)
Dien, Steve Van (Genomatica, Inc.)
Schilling, Christophe H. (Genomatica, Inc.)
Publication Information
Biotechnology and Bioprocess Engineering:BBE / v.10, no.5, 2005 , pp. 408-417 More about this Journal
Abstract
Increasing numbers of value added chemicals are being produced using microbial fermentation strategies. Computational modeling and simulation of microbial metabolism is rapidly becoming an enabling technology that is driving a new paradigm to accelerate the bioprocess development cycle. In particular, constraint-based modeling and the development of genome-scale models of industrial microbes are finding increasing utility across many phases of the bioprocess development workflow. Herein, we review and discuss the requirements and trends in the industrial application of this technology as we build toward integrated computational/experimental platforms for bioprocess engineering. Specifically we cover the following topics: (1) genome-scale models as genetically and biochemically consistent representations of metabolic networks; (2) the ability of these models to predict, assess, and interpret metabolic physiology and flux states of metabolism; (3) the model-guided integrative analysis of high throughput 'omics' data; (4) the reconciliation and analysis of on- and off-line fermentation data as well as flux tracing data; (5) model-aided strain design strategies and the integration of calculated biotransformation routes; and (6) control and optimization of the fermentation processes. Collectively, constraint-based modeling strategies are impacting the iterative characterization of metabolic flux states throughout the bioprocess development cycle, while also driving metabolic engineering strategies and fermentation optimization.
Keywords
bioprocess development; constraint-based modeling; metabolic engineering; $SimPheny^{(R)}$;
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1 Dauner, M. and U. Sauer (2001) Stoichiometric growth model for riboflavin-producing Bacillus subtilis. Biotechnol. Bioeng. 76: 132-143   DOI   ScienceOn
2 Hong, S. H., J. S. Kim, S. Y. Lee, Y. H. In, S. S. Choi, J. K. Rih, C. H. Kim, H. Jeong, C. G. Hur, and J. J. Kim (2004) The genome sequence of the capnophilic rumen bacterium Mannheimia succiniciproducens. Nat. Biotechnol. 22: 1275-1281   DOI   ScienceOn
3 Schilling, C. H., M. W. Covert, I. Famili, G. M. Church, J. S. Edwards, and B. O. Palsson (2002) Genome-scale metabolic model of Helicobacter pylori 26695. J. Bacteriol. 184: 4582-4593   DOI   ScienceOn
4 Varma, A., B. W. Boesch, and B. O. Palsson (1993) Stoichiometric interpretation of Escherichia coli glucose catabolism under various oxygenation rates. Appl. Environ. Microbiol. 59: 2465-2473
5 Edwards, J. S. and B. O. Palsson (2000) Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions. BMC Bioinformatics 1:1
6 Segre, D., D. Vitkup, and G. M. Church (2002) Analysis of optimality in natural and perturbed metabolic networks. Proc. Natl. Acad. Sci. USA 99: 15112-15117   DOI   ScienceOn
7 Mahadevan, R. and B. O. Palsson (2005) Properties of metabolic networks: Structure versus function. Biophys. J. 88: L07-L09   DOI   ScienceOn
8 Churchill, G. A. (2004) Using ANOVA to analyze microarray data. Biotechniques 37: 173-177
9 Mahadevan, R. and C. H. Schilling (2003) The effects of alternate optimal solutions in constraint-based genomescale metabolic models. Metab. Eng. 5: 264-276   DOI   ScienceOn
10 Vallino, J. J. and G. Stephanopoulos (1993) Metabolic fluc distributions in Corynebacterium glutamicum during growth and lysine overproduction. Biotechnol. Bioeng. 41: 633-646   DOI   PUBMED
11 Schmidt, K., M. Carlsen, J. Nielsen, and J. Villadsen (1997) Modeling isotopomer distributions in biochemical networks using isotopomer mapping matrices. Biotechnol. Bioeng. 55: 831-840   DOI   ScienceOn
12 Walsh, K. and D. E. Jr. Koshland (1984) Determination of flux through the branch point of two metabolic cycles. The tricarboxylic acid cycle and the glyoxylate shunt. J. Biol. Chem. 259: 9646-9654
13 Wilson, E. K. (2005) Engineering cell-based factories. Chem. Eng. News 83: 41-44
14 Wendisch, V. F., A. A. de Graaf, H. Sahm, and B. J. Eikmanns (2000) Quantitative determination of metabolic fluxes during coutilization of two carbon sources: Comparative analyses with Corynebacterium glutamicum during growth on acetate and/or glucose. J. Bacteriol. 182: 3088-3096   DOI   ScienceOn
15 Wittmann, C., H. M. Kim, and E. Heinzle (2004) Metabolic network analysis of lysine producing Corynebacterium glutamicum at a miniaturized scale. Biotechnol. Bioeng. 87: 1-6   DOI   ScienceOn
16 Fong, S. S. and B. O. Palsson (2004) Metabolic genedeletion strains of Escherichia coli evolve to computationally predicted growth phenotypes. Nat. Genet. 36: 1056-1058   DOI   ScienceOn
17 Broadbelt, L. J., S. M. Stark, and M. T. Klein (1995) Termination of computer-generated reaction-mechanismsspecies rank-based convergence criterion. Ind. Eng. Chem. Res. 34: 2566-2573   DOI   ScienceOn
18 Hatzimanikatis, V., C. Li, J. A. Ionita, C. S. Henry, M. D. Jankowski, and L. J. Broadbelt (2005) Exploring the diversity of complex metabolic networks. Bioinformatics 21: 1603-1609   DOI   ScienceOn
19 Mahadevan, R. and F. J. Doyle (2003) On-line optimization of recombinant product in a fed-batch bioreactor. Biotechnol. Prog. 19: 639-646   DOI   ScienceOn
20 Beard, D. A. and H. Qian (2005) Thermodynamic-based computational profiling of cellular regulatory control in hepatocyte metabolism. Am. J. Physiol. Endocrinol. Metab. 288: E633-E644   DOI   ScienceOn
21 Varma, A., B. W. Boesch, and B. O. Palsson (1993) Biochemical production capabilities of Escherichia coli. Biotechnol. Bioeng. 42: 59-73   DOI   ScienceOn
22 Segre, D., A. Deluna, G. M. Church, and R. Kishony (2005) Modular epistasis in yeast metabolism. Nat. Genet. 37: 77-83   DOI
23 DeRisi, J. L., V. R. Iyer, and P. O. Brown (1997) Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 278: 680-686   DOI   PUBMED   ScienceOn
24 Kanehisa, M., S. Goto, S. Kawashima, Y. Okuno, and M. Hattori (2004) The KEGG resource for deciphering the genome. Nucleic Acids Res. 32 Database issue: D277-D280   DOI   ScienceOn
25 Covert, M. W., E. M. Knight, J. L. Reed, M. J. Herrgard, and B. O. Palsson (2004) Integrating high-throughput and computational data elucidates bacterial networks. Nature 429: 92-96   DOI   ScienceOn
26 Varma, A. and B. O. Palsson (1994) Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110. Appl. Environ. Microbiol. 60: 3724-3731
27 Sharan, R., R. Elkon, and R. Shamir (2002) Cluster analysis and its applications to gene expression data. Ernst. Schering. Res Found. Workshop 83-108
28 Marx, A., A. A. de Graaf, W. Wiechert, L. Eggeling, and H. Sahm (1996) Determination of the fluxes in central metabolism of Corynebacterium glutamicum by NMR spectroscopy combined with metabolite balancing. Biotechnol. Bioeng. 49: 111-129   DOI   PUBMED   ScienceOn
29 Edwards, J. S. and B. O. Palsson (2000) The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities. Proc. Natl. Acad. Sci. USA 97: 5528-5533   DOI   ScienceOn
30 Gadkar, K. G., F. J. Doyle, III, T. J. Crowley, and J. D. Varner (2003) Cybernetic model predictive control of a continuous bioreactor with cell recycle. Biotechnol Prog. 19: 1487-1497   DOI   ScienceOn
31 Ibarra, R. U., J. S. Edwards, and B. O. Palsson (2002) Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth. Nature 420: 186-189   DOI   ScienceOn
32 van der Heijden, R. T. J. M., J. J. Heijnen, C. Hellinga, B. Romein, and K. C. A. M. Luyben (1994) Linear constraint relations in biochemical reaction systems: II. Diagnosis and estimation of gross measurement errors. Biotechnol. Bioeng. 43: 11-20   DOI   ScienceOn
33 Wiechert, W. and A. A. de Graaf (1997) Bidirectional reaction steps in metabolic networks: I. Modeling and simulation of carbon isotope labeling experiments. Biotechnol. Bioeng. 55: 101-117   DOI   ScienceOn
34 Carlson, R., D. Fell, and F. Srienc (2002) Metabolic pathway analysis of a recombinant yeast for rational strain development. Biotechnol. Bioeng. 79: 121-34   DOI   ScienceOn
35 Famili, I., J. Forster, J. Nielsen, and B. O. Palsson (2003) Saccharomyces cerevisiae phenotypes can be predicted by using constraint-based analysis of a genome-scale reconstructed metabolic network. Proc. Natl. Acad. Sci. USA 100: 13134-13139   DOI   ScienceOn
36 Shimizu, H., N. Takiguchi, H. Tanaka, and S. Shioya (1999) A maximum production strategy of lysine based on a simplified model derived from a metabolic reaction network. Metab. Eng. 1: 299-308   DOI   ScienceOn
37 Wittmann, C. and E. Heinzle (1999) Mass spectrometry for metabolic flux analysis. Biotechnol. Bioeng. 62: 739-750   DOI   ScienceOn
38 Pharkya, P., A. P. Burgard, and C. D. Maranas (2003) Exploring the overproduction of amino acids using the bilevel optimization framework OptKnock. Biotechnol. Bioeng. 84: 887-899   DOI   ScienceOn
39 Gadkar, K. G., F. J. Doyle, J. S. Edwards, and R. Mahadevan (2005) Estimating optimal profiles of genetic alterations using constraint-based models. Biotechnol. Bioeng. 89: 243-251   DOI   ScienceOn
40 Lovley, D. R. (2003) Cleaning up with genomics: Applying molecular biology to bioremediation. Nat. Rev. Microbiol. 1: 35-44   DOI   PUBMED   ScienceOn
41 Tao, H., R. Gonzalez, A. Martinez, M. Rodriguez, L. O. Ingram, J. F. Preston, and K. T. Shanmugam (2001) Engineering a homo-ethanol pathway in Escherichia coli: Increased glycolytic flux and levels of expression of glycolytic genes during xylose fermentation. J. Bacteriol. 183: 2979-2988   DOI   ScienceOn
42 Covert, M. W. and B. O. Palsson (2002) Transcriptional regulation in constraints-based metabolic models of Escherichia coli. J. Biol. Chem. 277: 28058-28064   DOI   ScienceOn
43 Petersen, S., A. A. de Graaf, L. Eggeling, M. Mollney, W. Wiechert, and H. Sahm (2000) In vivo quantification of parallel and bidirectional fluxes in the anaplerosis of Corynebacterium glutamicum. Metab. Eng. 3: 195-206   DOI   PUBMED   ScienceOn
44 Parekh, S., V. A. Vinci, and R. J. Strobel (2000) Improvement of microbial strains and fermentation processes. Appl. Microbiol. Biotechnol. 54: 287-301   DOI   ScienceOn
45 Price, N. D., J. L. Reed, and B. O. Palsson (2004) Genome-scale models of microbial cells: Evaluating the consequences of constraints. Nat. Rev. Microbiol. 2: 886-897   DOI   ScienceOn
46 Covert, M. W., C. H. Schilling, and B. Palsson (2001) Regulation of gene expression in flux balance models of metabolism. J. Theor. Biol. 213: 73-88   DOI   ScienceOn
47 Mahadevan, R., J. S. Edwards, and F. J. Doyle (2002) Dynamic flux balance analysis of diauxic growth in Escherichia coli. Biophysical J. 83: 1331-1340   DOI   ScienceOn
48 Shlomi, T., O. Berkman, and E. Ruppin (2005) Regulatory on/off minimization of metabolic flux changes after genetic perturbations. Proc. Natl. Acad. Sci. USA 102: 7695-7700   DOI   ScienceOn
49 Raghunathan, A. U., J. R. Perez-Correa, and L. T. Biegler (2003) Data reconciliation and parameter estimation in flux-balance analysis. Biotechnol. Bioeng. 84: 700-708   DOI   ScienceOn
50 Zhang, S., J. Chu, and Y. Zhuang (2004) A multi-scale study of industrial fermentation processes and their optimization. Adv. Biochem. Eng. Biotechnol. 87: 97-150
51 Schilling, C. H., J. S. Edwards, and B. O. Palsson (1999) Toward metabolic phenomics: Analysis of genomic data using flux balances. Biotechnol. Prog. 15: 288-295   DOI   ScienceOn
52 Sauer, U., D. R. Lasko, J. Fiaux, M. Hochuli, R. Glaser, T. Szyperski, K. Wuthrich, and J. E. Bailey (1999) Metabolic flux ratio analysis of genetic and environmental modulations of Escherichia coli central carbon metabolism. J. Bacteriol. 181: 6679-6688
53 Burgard, A. P., E. V. Nikolaev, C. H. Schilling, and C. D. Maranas (2004) Flux coupling analysis of genome-scale metabolic network reconstructions. Genome Res. 14: 301-312   DOI   ScienceOn
54 Oh, M. K. and J. C. Liao (2000) Gene expression profiling by DNA microarrays and metabolic fluxes in Escherichia coli. Biotechnol. Prog. 16: 278-286   DOI   ScienceOn
55 Wiechert, W (2001) $^{13}C$ metabolic flux analysis. Metab. Eng. 195-206
56 Ciaramella, M., A. Napoli, and M. Rossi (2005) Another extreme genome: How to live at pH 0. Trends Microbiol. 13: 49-51   DOI   ScienceOn
57 Christensen, B. and J. Nielsen (2000) Metabolic network analysis of Penicillium chrysogenum using $^{13}C$-labeled glucose. Biotechnol. Bioeng. 68: 652-659   DOI   ScienceOn
58 Jensen, N. B. S., B. Christensen, J. Nielsen, and J. Villadsen (2002) The simultaneous biosynthesis and uptake of amino acids by Lactococcus lactis studied by $^{13}C$-labeling experiments. Biotechnol. Bioeng. 78: 11-16   DOI   ScienceOn
59 Ideker, T., V. Thorsson, J. A. Ranish, R. Christmas, J. Buhler, J. K. Eng, R. Bumgarner, D. R. Goodlett, R. Aebersold, and L. Hood (2001) Integrated genomic and proteomic analyses of a systematically perturbed metabolic network. Science 292: 929-934   DOI   PUBMED   ScienceOn
60 Wahl, A., M. El Massaoudi, D. Schipper, W. Wiechert, and R. Takors (2004) Serial $^{13}C$-based flux analysis of an L-phenylalanine-producing E. coli strain using a sensor reactor. Biotechnol. Prog. 20: 706-714   DOI   PUBMED   ScienceOn
61 Edwards, J. S., R. U. Ibarra, and B. O. Palsson (2001) In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data. Nat. Biotechnol. 19: 125-130   DOI   ScienceOn
62 Dauner, M. and U. Sauer (2000) GC-MS analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Prog. 16: 642-649   DOI   ScienceOn
63 Reed, J. L., T. D. Vo, C. H. Schilling, and B. Palsson (2003) Escherichia coli iJR904: An expanded genomescale model of E. coli K-12. Genome Biol. 4: R54.1-R54.12.
64 Akesson, M., J. Forster, and J. Nielsen (2004) Integration of gene expression data into genome-scale metabolic models. Metab. Eng. 6: 285-293   DOI   ScienceOn
65 van Dien, S. J., T. Strovas, and M. E. Lidstrom (2003) Quantification of central metabolic fluxes in the facultative methylotroph methylobacterium extorquens AM1 using $^{13}C$-label tracing and mass spectrometry. Biotechnol. Bioeng. 84: 45-55   DOI   ScienceOn
66 Alper, H., Y. S. Jin, J. F. Moxley, and G. Stephanopoulos (2005) Identifying gene targets for the metabolic engineering of lycopene biosynthesis in Escherichia coli. Metab. Eng. 7: 155-164   DOI   ScienceOn
67 Kell, D. B (2004) Metabolomics and systems biology: making sense of the soup. Curr. Opin. Microbiol. 7: 296-307   DOI   PUBMED   ScienceOn
68 Burgard, A. P. and C. D. Maranas (2001) Probing the performance limits of the Escherichia coli metabolic network subject to gene additions or deletions. Biotechnol. Bioeng. 74: 364-375   DOI   ScienceOn
69 Pharkya, P., A. P. Burgard, and C. D. Maranas (2004) OptStrain: A computational framework for redesign of microbial production systems. Genome Res. 14: 2367-2376   DOI   ScienceOn
70 Forster, J., I. Famili, P. Fu, B. O. Palsson, and J. Nielsen (2003) Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. Genome Res. 13: 244-253   DOI   ScienceOn
71 Patterson, S. D. and R. H. Aebersold (2003) Proteomics: The first decade and beyond. Nat. Genet. 33 Suppl: 311-323   DOI   PUBMED   ScienceOn
72 Patil, K. R. and J. Nielsen (2005) Uncovering transcriptional regulation of metabolism by using metabolic network topology. Proc. Natl. Acad. Sci. USA 102: 2685-2689   DOI   ScienceOn
73 Broadbelt, L. J., S. M. Stark, and M. T. Klein (1996) Computer generated reaction modelling: Decomposition and encoding algorithms for determining species uniqueness. Comput. Chem. Eng. 20: 113-129   DOI   ScienceOn
74 Wiechert, W., C. Siefke, A. A. de Graaf, and A. Marx (1997) Bidirectional reaction steps in metabolic networks: II. Flux estimation and statistical analysis. Biotechnol. Bioeng. 55: 118-135   DOI   ScienceOn
75 Karp, P. D., M. Riley, M. Saier, I. T. Paulsen, S. M. Paley, and A. Pellegrini-Toole (2000) The EcoCyc and MetaCyc databases. Nucleic Acids Res. 28: 56-59   DOI   PUBMED
76 Krieger, C. J., P. Zhang, L. A. Mueller, A. Wang, S. Paley, M. Arnaud, J. Pick, S. Y. Rhee, and P. D. Karp (2004) MetaCyc: A multiorganism database of metabolic pathways and enzymes. Nucleic Acids Res. 32 Database issue: D438-D442   DOI   ScienceOn
77 Burgard, A. P., P. Pharkya, and C. D. Maranas (2003) OptKnock: A bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnol. Bioeng. 84: 647-657   DOI   ScienceOn
78 Komives, C. and R. S. Parker (2003) Bioreactor state estimation and control. Curr. Opin. Biotechnol. 14: 468-474   DOI   ScienceOn
79 Park, S. M., M. I. Klapa, A. J. Sinskey, and G. N. Stephanopoulos (1999) Metabolite and isotopomer balancing in the analysis of metabolic cycles: II. Applications. Biotechnol. Bioeng. 62: 392-401   DOI   ScienceOn
80 Sauer, U., V. Hatzimanikatis, J. E. Bailey, M. Hochuli, T. Szyperski, and K. Wuthrich (1997) Metabolic fluxes in riboflavin-producing Bacillus subtilis. Nat. Biotechnol. 15: 448-452   DOI   ScienceOn
81 Li, C., C. S. Henry, M. D. Jankowski, J. A. Ionita, V. Hatzimanikatis, and L. J. Broadbelt (2004) Computational discovery of biochemical routes to specialty chemicals. Chem. Eng. Sci. 59: 5051-5060   DOI   ScienceOn
82 Gombert, A. K., S. M. Moreira dos, B. Christensen, and J. Nielsen (2001) Network identification and flux quantification in the central metabolism of Saccharomyces cerevisiae under different conditions of glucose repression. J. Bacteriol. 183: 1441-1451   DOI   ScienceOn
83 Broadbelt, L. J., S. M. Stark, and M. T. Klein (1994) Computer-generated pyrolysis modeling-on-the-fly generation of species, reactions, and rates. Ind. Eng. Chem. Res. 33: 790-799   DOI   ScienceOn
84 Papp, B., C. Pal, and L. D. Hurst (2004) Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast. Nature 429: 661-664   DOI   ScienceOn
85 van Gulik, W. M., W. T. de Laat, J. L. Vinke, and J. J. Heijnen (2000) Application of metabolic flux analysis for the identification of metabolic bottlenecks in the biosynthesis of penicillin-G. Biotechnol. Bioeng. 68: 602-618   DOI   ScienceOn
86 Hatzimanikatis, V., C. Li, J. A. Ionita, and L. J. Broadbelt (2004) Metabolic networks: Enzyme function and metabolite structure. Curr. Opin. Struct. Biol. 14: 300-306   DOI   ScienceOn