Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

BMC Systems Biology

Volumn 5, Issue , 2011, Pages

  Pozo, Carlos ^a   Marín Sanguino, Alberto ^b   Alves, Rui ^c   Guillén Gosálbez, Gonzalo ^a   Jiménez, Laureano ^a   Sorribas, Albert ^c  

^a UNIVERSITAT ROVIRA I VIRGILI   (Spain)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^c UNIVERSITY OF LLEIDA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTATION; ALGORITHM; ARTICLE; BIOLOGICAL MODEL; BIOTECHNOLOGY; COMPUTER SIMULATION; EVOLUTION; KINETICS; METABOLISM; METHODOLOGY; PHYSIOLOGY;

ADAPTATION, BIOLOGICAL; ALGORITHMS; BIOLOGICAL EVOLUTION; BIOTECHNOLOGY; COMPUTER SIMULATION; KINETICS; METABOLIC NETWORKS AND PATHWAYS; MODELS, BIOLOGICAL;

EID: 80052023331     PISSN: None     EISSN: 17520509     Source Type: Journal    
DOI: 10.1186/1752-0509-5-137     Document Type: Article

References (52)

1. Voit EO. Optimization in integrated biochemical systems. Biotechnol Bioeng 1992, 40(5):572-82. 10.1002/bit.260400504, 18601153.
2. Alvarez-Vasquez F, Gonzalez-Alcon C, Torres NV. Metabolism of citric acid production by Aspergillus niger: model definition, steady-state analysis and constrained optimization of citric acid production rate. Biotechnol Bioeng 2000, 70:82-108. 10.1002/1097-0290(20001005)70:1<82::AID-BIT10>3.0.CO;2-V, 10940866.
3. Banga JR. Optimization in computational systems biology. BMC Syst Biol 2008, 2:47. 10.1186/1752-0509-2-47, 2435524, 18507829.
4. Rodriguez-Prados JC, de Atauri P, Maury J, Ortega F, Portais JC, Chassagnole C, Acerenza L, Lindley ND, Cascante M. In silico strategy to rationally engineer metabolite production: A case study for threonine in Escherichia coli. Biotechnology and bioengineering 2009, 103(3):609-620. 10.1002/bit.22271, 19219914.
5. Scheer M, Grote A, Chang A, Schomburg I, Munaretto C, Rother aSC M, Stelzer M, JT, DS. BRENDA, the enzyme information system in 2011. Nucleic Acids Res 2011, 39:670-676.
6. Rojas I, Golebiewski M, Kania R, Krebs O, Mir S, Weidemann A, Wittig U. SABIO-RK: a database for biochemical reactions and their kinetics. BMC Systems Biology 2007, 1:S6.
7. Shiraishi F, Savageau MA. The tricarboxylic acid cycle in Dictyostelium discoideum. I. Formulation of alternative kinetic representations. The Journal of biological chemistry 1992, 267(32):22912-22918.
8. Shiraishi F, Savageau MA. The tricarboxylic acid cycle in Dictyostelium discoideum. II. Evaluation of model consistency and robustness. The Journal of biological chemistry 1992, 267(32):22919-22925.
9. Shiraishi F, Savageau MA. The tricarboxylic acid cycle in Dictyostelium discoideum. III. Analysis of steady state and dynamic behavior. The Journal of biological chemistry 1992, 267(32):22926-22933.
10. Shiraishi F, Savageau MA. The tricarboxylic acid cycle in Dictyostelium discoideum. IV. Resolution of discrepancies between alternative methods of analysis. The Journal of biological chemistry 1992, 267(32):22934-22943.
11. Fonseca LL, Sanchez C, Santos H, Voit EO. Complex coordination of multi-scale cellular responses to environmental stress. Molecular bioSystems 2010,
12. Sorribas A, Cascante M. Structure identifiability in metabolic pathways: parameter estimation in models based on the power-law formalism. The Biochemical journal 1994, 298(Pt 2):303-311. 1137940, 8135735.
13. Chou IC, Voit EO. Recent developments in parameter estimation and structure identification of biochemical and genomic systems. Mathematical Biosciences 2009, 219(2):57-83. 10.1016/j.mbs.2009.03.002, 2693292, 19327372.
14. Grossmann I, Biegler LT. Part II. Future perspective on optimization. Computers and Chemical Engineering 2004, 28:1193-1218.
15. Terzer M, Maynard ND, Covert MW, Stelling J. Genome-scale metabolic networks. Wiley interdisciplinary reviews. Systems biology and medicine 2009, 1(3):285-297. 10.1002/wsbm.37, 20835998.
16. Gianchandani EP, Chavali AK, Papin JA. The application of flux balance analysis in systems biology. Wiley interdisciplinary reviews. Systems biology and medicine 2010, 2(3):372-382. [JID: 101516550; ppublish], 10.1002/wsbm.60, 20836035.
17. Voit EO. Design principles and operating principles: the yin and yang of optimal functioning. Math Biosci 2003, 182:81-92. 10.1016/S0025-5564(02)00162-1, 12547041.
18. Jamshidi N, Palsson BO. Formulating genome-scale kinetic models in the post-genome era. Molecular systems biology 2008, 4:171. 2290940, 18319723.
19. Savageau MA. Biochemical systems analysis. I. Some mathematical properties of the rate law for the component enzymatic reactions. Journal of theoretical biology 1969, 25(3):365-369. 10.1016/S0022-5193(69)80026-3, 5387046.
20. Savageau MA. Biochemical systems analysis. II. The steady-state solutions for an n-pool system using a power-law approximation. Journal of theoretical biology 1969, 25(3):370-379. 10.1016/S0022-5193(69)80027-5, 5387047.
21. Savageau MA. Biochemical systems analysis. 3. Dynamic solutions using a power-law approximation. Journal of theoretical biology 1970, 26(2):215-226. 10.1016/S0022-5193(70)80013-3, 5434343.
22. Savageau MA. Biochemical Systems Analysis: A Study of Function and Design in Molecular Biology 1976, Reading, Mass.: Addison-Wesley.
23. Sorribas A, Hernandez-Bermejo B, Vilaprinyo E, Alves R. Cooperativity and saturation in biochemical networks: a saturable formalism using Taylor series approximations. Biotechnology and bioengineering 2007, 97(5):1259-1277. 10.1002/bit.21316, 17187441.
24. Liebermeister W, Klipp E. Bringing metabolic networks to life: convenience rate law and thermodynamic constraints. Theoretical biology & medical modelling 2006, 3:41. 10.1186/1742-4682-3-41, 3157093, 21886880.
25. Goel G, Chou IC, Voit EO. System Estimation from Metabolic Time Series Data. Bioinformatics (Oxford, England) 2008,
26. Ni T, Savageau M. Model assessment and refinement using strategies from biochemical systems theory: Application to metabolism in human red blood cells. Journal of Theoretical Biology 1996, 179(4):329-368. 10.1006/jtbi.1996.0072, 8763353.
27. Arkin A, Ross J, McAdams H. Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells. Genetics 1998, 149(4):1633-1648. 1460268, 9691025.
28. Polisetty PK, Gatzke EP, Voit EO. Yield optimization of regulated metabolic systems using deterministic branch-and-reduce methods. Biotechnol Bioeng 2008, 99(5):1154-69. 10.1002/bit.21679, 18064703.
29. Guillén-Gosálbez G, Sorribas A. Identifying quantitative operation principles in metabolic pathways: A systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses. BMC Bioinformatics 2009, 10.
30. Guillén-Gosálbez G, Pozo C, Jiménez L, Sorribas A. A global optimization strategy to identify quantitative design principles for gene expression in yeast adaptation to heat shock. Computer Aided Chemical Engineering 2009, 26:1045-1050.
31. Voit EO. Computational Analysis of Biochemical Systems. A Practical Guide for Biochemists and Molecular Biologists 2000, Cambridge, U.K.: Cambridge University Press.
32. Pozo C, Guillén-Gosálbez G, Sorribas A, Jiménez L. A Spatial Branch-and-Bound Framework for the Global Optimization of Kinetic Models of Metabolic Networks. Industrial and Engineering Chemistry Research 2010,
33. Sorribas A, Pozo C, Vilaprinyo E, Guillén-Gosálbez G, Jiménez L, Alves R. Optimization and evolution in metabolic pathways: global optimization techniques in Generalized Mass Action models. Journal of Biotechnology 2010, 149(3):141-153. 10.1016/j.jbiotec.2010.01.026, 20152867.
34. Chassagnole C, Noisommit-Rizzi N, Schmid J, Mauch K, Reuss M. Dynamic modeling of the central carbon metabolism of Escherichia coli. Biotechnol Bioeng 2002, 79:53-73. 10.1002/bit.10288, 17590932.
35. Nikolaev E. The elucidation of metabolic pathways and their improvements using stable optimization of large-scale kinetic models of cellular systems. Metab Eng 2010, 12:26-38. 10.1016/j.ymben.2009.08.010, 19733253.
36. Savageau MA, Voit EO. Recasting nonlinear differential equations as S-systems: a canonical nonlinear form. Mathematical Biosciences 1987, 87:83-115.
37. Voit EO. Recasting nonlinear models as S-systems. Mathematical and Computer Modelling 1988, 11(C):140-145.
38. Smith EMB, Pantelides CC. A symbolic reformulation/spatial branch-and-bound algorithm for the global optimisation of nonconvex MINLPs. Computers and Chemical Engineering 1999, 23(4-5):457-478.
39. Vera J, de Atauri P, Cascante M, Torres NV. Multicriteria optimization of biochemical systems by linear programming: application to production of ethanol by Saccharomyces cerevisiae. Biotechnol Bioeng 2003, 83(3):335-43. 10.1002/bit.10676, 12783489.
40. Vilaprinyo E, Alves R, Sorribas A. Use of physiological constraints to identify quantitative design principles for gene expression in yeast adaptation to heat shock. BMC Bioinformatics 2006, 7:184. 10.1186/1471-2105-7-184, 1524994, 16584550.
41. Ehrgott M. Multicriteria Optimization 2005, Springer.
42. Famili I, Forster J, Nielsen J, Palsson BO. Saccharomyces cerevisiae phenotypes can be predicted by using constraint-based analysis of a genome-scale reconstructed metabolic network. Proc Natl Acad Sci USA 2003, 100(23):13134-9. 10.1073/pnas.2235812100, 263729, 14578455.
43. Famili I, Mahadevan R, Palsson BO. k-Cone analysis: determining all candidate values for kinetic parameters on a network scale. Biophys J 2005, 88(3):1616-25. 10.1529/biophysj.104.050385, 1305218, 15626710.
44. Price ND, Papin JA, Schilling CH, Palsson BO. Genome-scale microbial in silico models: the constraints-based approach. Trends Biotechnol 2003, 21(4):162-9. 10.1016/S0167-7799(03)00030-1, 12679064.
45. Savageau MA. Influence of fractal kinetics on molecular recognition. Journal of Molecular Recognition: JMR 1993, 6(4):149-157. 10.1002/jmr.300060403, 7917410.
46. Savageau MA. Michaelis-Menten mechanism reconsidered: implications of fractal kinetics. Journal of theoretical biology 1995, 176:115-124. 10.1006/jtbi.1995.0181, 7475096.
47. Savageau MA. Development of fractal kinetic theory for enzyme-catalysed reactions and implications for the design of biochemical pathways. Bio Systems 1998, 47(1-2):9-36. 10.1016/S0303-2647(98)00020-3, 9715749.
48. Hernandez-Bermejo B, Fairen V, Sorribas A. Power-law modeling based on least-squares minimization criteria. Mathematical biosciences 1999, 161(1-2):83-94. 10.1016/S0025-5564(99)00035-8, 10546442.
49. Hernandez-Bermejo B, Fairen V, Sorribas A. Power-law modeling based on least-squares criteria: consequences for system analysis and simulation. Mathematical biosciences 2000, 167(2):87-107. 10.1016/S0025-5564(00)00039-0, 10998483.
50. Alves R, Vilaprinyo E, Hernandez-Bermejo B, Sorribas A. Mathematical formalisms based on approximated kinetic representations for modeling genetic and metabolic pathways. Biotechnology and Genetic Engineering Reviews 2008, 25:1-40. 10.5661/bger-25-1, 21412348.
51. Marin-Sanguino A, Torres NV. Optimization of biochemical systems by linear programming and general mass action model representations. Math Biosci 2003, 184(2):187-200. 10.1016/S0025-5564(03)00046-4, 12832147.
52. Marin-Sanguino A, Voit EO, Gonzalez-Alcon C, Torres NV. Optimization of biotechnological systems through geometric programming. Theor Biol Med Model 2007, 4:38. 10.1186/1742-4682-4-38, 2231360, 17897440.