Instantaneous and overall indicators for determination of bottleneck ranking in metabolic reaction networks

Industrial and Engineering Chemistry Research

Volumn 49, Issue 5, 2010, Pages 2122-2129

  Sriyudthsak, Kansuporn ^a   Shiraishi, Fumihide ^a  

^a KYUSHU UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

DEPENDENT VARIABLES; EFFECTIVE MEASURES; ETHANOL FERMENTATION; INDEPENDENT VARIABLES; METABOLIC REACTIONS; METABOLITE CONCENTRATIONS; PENICILLIN V; TIME-AVERAGED;

DYNAMIC RESPONSE; ENZYMES; ETHANOL; FERMENTATION; MATHEMATICAL MODELS; METABOLISM; METABOLITES;

ENZYME ACTIVITY;

EID: 77749337515     PISSN: 08885885     EISSN: 15205045     Source Type: Journal    
DOI: 10.1021/ie901531d     Document Type: Article

References (23)

1. Hilge-Rotmann, B.; Rehm, H.-J. Relationship between fermentation capability and fatty acid composition of free and immobilized Saccharomyces cereVisiae. Appl. Microbiol. Biotechnol. 1991, 34, 502-508.
2. Ingram, L. O.; Gomez, P. F.; Lai, X.; Moniruzzaman, M.; Wood, B. E.; Yomano, L. P.; York, S. W. Metabolic engineering of bacteria for ethanol production. Biotechnol. Bioeng. 1997, 58 (2&3), 204-214.
3. Lei, F.; Olsson, L.; Jorgensen, S. B. Experimental investigations of multiple steady-states in aerobic continuous cultivations of Saccharomyces cereVisiae. Biotechnol. Bioeng. 2003, 87 (7), 766-776.
4. Nissen, T. L.; Kielland-Brandt, M. C.; Nielsen, J.; Villadsen, J. Optimization of ethanol production in Saccharomyces cereVisiae by metabolic engineering of the ammonium assimilation. Metab. Eng. 2000, 2, 69-77.
5. Westerhoff, H. V.; Kell, D. B. Matrix method for determining steps most rate-limiting to metabolic fluxes in biotechnological processes. Biotechnol. Bioeng. 1987, 30, 101-107.
6. Conejeros, R.; Vassiliadis, V. S. Analysis and optimization of biochemical process reaction pathways. 1. Pathway sensitivities and identification of limiting steps. Ind. Eng. Chem. Res. 1998, 37, 4699-4708.
7. Shiraishi, F.; Suzuki, Y. Method for determination of the main bottleneck enzyme in a metabolic reaction network by dynamic sensitivity analysis. Ind. Eng. Chem. Res. 2009, 48, 415-423.
8. Jorgensen, H.; Nielsen, J.; Villadsen, J.; Mollgaad, H. Analysis of penicillin V biosynthesis during fed-batch cultivations with a high-yielding strain of Penicillium chrysogenum. Appl. Microbiol. Biotechnol. 1995, 43, 123-130.
9. Nielsen, J.; Jorgensen, H. S. Metabolic control analysis of the penicillin biosynthetic pathway in a high-yielding strain of Penicillium chrysogenum. Biotechnol. Prog. 1995, 11, 299-305.
10. Nielsen, J.; Jorgensen, H. S. A kinetic model for the penicillin biosynthetic pathway in Penicillium chrysogenum. Control Eng. Pract. 1996, 4 (6), 765-771.
11. de Noronha Pissara, P.; Nielsen, J.; Bazin, M. J. Pathway kinetics and metabolic control analysis of a high-yielding strain of Penicillium chrysogenum during fed-batch cultivations. Biotechnol. Bioeng. 1996, 51, 168-176.
12. Shiraishi, F.; Suzuki, Y. Method for Determination of the Main Bottleneck Enzyme in a Metabolic Reaction Network by Dynamic Sensitivity Analysis. Ind. Eng. Chem. Res. 2009, 48, 415-423.
13. Curto, R.; Sorribas, A.; Cascante, M. Comparative characterization of the fermentation pathway of Saccharomyces cereVisiae using biochemical systems theory and metabolic control analysis: Model definition and nomenclature. Math. Biosci. 1995, 130, 25-50.
14. Shiraishi, F.; Hatoh, Y.; Irie, T. An efficient method for calculation of dynamic logarithmic gains in biochemical systems theory. J. Theor. Biol. 2005, 234, 79-85.
15. Shiraishi, F.; Tomita, T.; Iwata, M.; Berrada, A. A. A reliable Taylor series-based computational method for the calculation of dynamic sensitivities in large-scale metabolic reaction systems: Algorithmic and software evaluation. Math. Biosci. 2009, 222, 73-85.
16. Shiraishi, F.; Tomita, T.; Hirayama, H. A rapid and highly-reliable method for calculation of dynamic sensitivities in a large-scale metabolic reaction system. In Proceedings of the 9th International Conference on Molecular Systems Biology (ICMSB-2006); Munchen, 2006.
17. Atkinson, K. Elementary Numerical Analysis, 2nd ed.; John Wiley & Sons, Inc.: New York, 1993; p 425.
18. Press, W. H.; Teukolsky, S. A.; Vetterling, W. T.; Flannery, B. P. Numerical Recipes: The Art of Scientific Computing, 3rd ed.; Cambridge University Press: New York, 2007; p 1235.
19. Galazzo, J. L.; Bailey, J. E. Fermentation pathway kinetics and metabolic flux control in suspended and immobilized Saccharomyces cereVisiae. Enzyme Microb. Technol. 1990, 12, 162-172.
20. Galazzo, J. L.; Bailey, J. E. Fermentation pathway kinetics and metabolic flux control in suspended and immobilized Saccharomyces cereVisiae, Errata. Enzyme Microb. Technol. 1991, 13, 363.
21. Cascante, M.; Curto, R.; Sorribas, A. Comparative characterization of the fermentation pathway of Saccharomyces cereVisiae using Biochemical Systems Theory and Metabolic Control Analysis: Steady-state analysis. Math. Biosci. 1995, 130, 51-69.
22. Torres, N. V.; Voit, E. O. Pathway Analysis and Optimization in Metabolic Engineering; Cambridge University Press: Cambridge, U.K., 2002.
23. Voit, E. O. Computational Analysis of Biochemical Systems: A Practical Guide for Biochemists and Molecular Biologists; Cambridge University Press: Cambridge, U.K., 2000; p 531.