Mathematical modelling of metabolism

Current Opinion in Biotechnology

Volumn 11, Issue 2, 2000, Pages 180-186

  Gombert, Andreas Karoly ^a   Nielsen, Jens ^b  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

^b TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

DNA;

BIOTECHNOLOGY; CELL FUNCTION; CELL KINETICS; CELL LINE; CELL METABOLISM; DNA MODIFICATION; DNA SEQUENCE; FERMENTATION; GENETIC ENGINEERING; GENOME; MATHEMATICAL MODEL; NONHUMAN; PRIORITY JOURNAL; REVIEW; STOICHIOMETRY;

EID: 0034125501     PISSN: 09581669     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0958-1669(00)00079-3     Document Type: Review

References (55)

1. Gershenfeld N.A. The Nature of Mathematical Modeling. 1999;Cambridge University Press, Cambridge.
2. Bailey J.E. Mathematical modeling and analysis in biochemical engineering: past accomplishments and future opportunities. Biotechnol Prog. 14:1998;8-20.
3. Bailey J.E. Toward a science of metabolic enginering. Science. 252:1991;1668-1675.
4. Stephanopoulos G. Metabolic fluxes and metabolic engineering. Metab Eng. 1:1999;1-11.
5. Vallino J.J., Stephanopoulos G. Flux determination in cellular bioreaction networks: applications to lysine fermentations. Sikdar S.K., Bier M., Todd P. Frontiers in Bioprocessing. 1990;205-219 CRC Press, Boca Raton.
6. Varma A., Palsson B.O. Metabolic flux balancing: basic concepts, scientific and practical use. Bio/Technology. 12:1994;994-998.
7. Marx A., De Graaf A.A., Wiechert W., Eggeling L., Sahm H. Determination of the fluxes in the central metabolism of Corynebacterium glutamicum by nuclear magnetic resonance spectroscopy combined with metabolic balancing. Biotechnol Bioeng. 49:1996;111-129.
8. 13C-NMR, MS and metabolic flux balancing in biotechnology research. Q Rev Biophys. 31:1998;41-106. An excellent review on flux balancing combined with labelling experiments.
9. Christensen B., Nielsen J. Isotopomer analysis unsing GC-MS. Metab Eng. 1:1999;282-290.
10. Wiechert W., De Graaf A.A. Bidirectional reaction steps in metabolic networks: I. modeling and simulation of carbon isotope labeling experiments. Biotechnol Bioeng. 55:1997;101-117.
11. Wiechert W., Siefke C., De Graaf A.A., Marx A. Bidirectional reaction steps in metabolic networks: II. Flux estimation and statistical analysis. Biotechnol Bioeng. 55:1997;118-135.
12. Schmidt K., Carlsen M., Nielsen J., Villadsen J. Modeling isotopomer distributions in biochemical networks using isotopomer mapping matrices. Biotechnol Bioeng. 55:1997;831-840.
13. Schmidt K., Nielsen J., Villadsen J. Quantitative analysis of metabolic fluxes in Escherichia coli, using two-dimensional NMR spectroscopy and complete isotopomer models. J Biotechnol. 71:1999;175-190.
14. Christensen B., Nielsen J. Metabolic network analysis: a powerful tool in metabolic engineering. Adv Biochem Eng Biotechnol. 66:1999;209-231. A very clear review on the applications of isotopic tracer experiments for the investigation of metabolic networks.
15. Schilling C.H., Edwards J.S., Palsson B.O. Toward metabolic phenomics: analysis of genomic data using flux balances. Biotechnol Prog. 15:1999;288-295. A good example of how a stoichiometric model can be applied for the analysis of metabolic genotypes and the possible role of flux balancing in functional genomics.
16. Schuster S., Dankekar T., Fell D.A. Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering. Trends Biotechnol. 17:1999;53-60.
17. Schilling C.H., Schuster S., Palsson B.O., Heinrich R. Metabolic pathway analysis: basic concepts and scientific applications in the post-genomic era. Biotechnol Prog. 15:1999;296-303. A comparison of two very promising approaches for the analysis of pathway structures: the calculation of base vectors for the null space; and the determination of elementary flux modes by convex analysis.
18. Rizzi M., Baltes M., Theobald U., Reuss M. In vivo analysis of metabolic dynamics in Saccharomyces cerevisiae: II. mathematical model. Biotechnol Bioeng. 55:1997;592-608.
19. Vaseghi S., Baumeister A., Rizzi M., Reuss M. In vivo dynamics of the pentose phosphate pathway in Saccharomyces cerevisiae. Metab Eng. 1:1999;128-140. This paper gives a very detailed kinetic analysis of the pentose phosphate pathway, including all enzymatic reactions. It follows a previous work done on the Enbden-Meyerhof-Parnas pathway [18].
20. Pissara P.N., 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. 51:1996;168-176.
21. Nielsen J., Jørgensen H.S. A kinetic model for the penicillin biosynthetic pathway in Penicillium chrysogenum. Control Eng Practice. 4:1996;765-771.
22. Theilgaard H., Nielsen J. Metabolic control analysis of the penicillin biosynthetic pathway: the influence of the LLD-ACV : bisACV ratio on the flux control. Anton Leeuw Int J G. 75:1999;145-154.
23. Van Riel N.A.W., Giuseppin M.L.F., TerSchure E.G., Verrips T. A structured, minimal parameter model of the central nitrogen metabolism in Saccharomyces cerevisiae: the prediction of the behaviour of mutants. J Theor Biol. 191:1998;397-414.
24. Varner J., Ramkrishna D. Metabolic engineering from a cybernetic perspective. 1. Theoretical preliminaries. Biotechnol Prog. 15:1999;407-425.
25. Varner J., Ramkrishna D. Metabolic engineering from a cybernetic perspective. 2. Qualitative investigation of nodal architectures and their response to genetic perturbation. Biotechnol Prog. 15:1999;426-438.
26. Varner J., Ramkrishna D. Metabolic engineering from a cybernetic perspective: aspartate family of amino acids. Metabol Eng. 1:1999;88-116.
27. Hatzimanikatis V., Floudas C.A., Bailey J.E. Analysis and design of metabolic reaction networks via mixed-integer linear optimization. AIChE J. 42:1996;1277-1292.
28. Hatzimanikatis V., Emmerling M., Sauer U., Bailey J.E. Application of mathematical tools for metabolic design of microbial ethanol production. Biotechnol Bioeng. 58:1998;154-161. A practical application of log linear models combined with mixed integer non-linear programming for the design of improved ethanol production.
29. van Can H.J.L., te Braake H.A.B., Hellinga C., Luyben K.C.A.M., Heijnen J.J. An efficient model development strategy for bioprocesses based on neural networks in macroscopic balances. Biotechnol Bioeng. 54:1997;549-566.
30. van Can H.J.L., te Braake H.A.B., Bijman A., Hellinga C., Luyben K.C.A.M., Heijnen J.J. An efficient model development strategy for bioprocesses based on neural networks in macroscopic balances: part II. Biotechnol Bioeng. 62:1999;666-680.
31. Lee B., Yen J., Yang L., Liao J.C. Incorporating qualitative knowledge in enzyme kinetic models using fuzzy logic. Biotechnol Bioeng. 62:1999;722-729.
32. Babuška R., Verbruggen H.B., van Can H.J.L. Fuzzy modeling of enzymatic penicillin-G conversion. Eng Applic Artif Intell. 12:1999;79-92.
33. Wong P., Gladney S., Keasling J.D. Mathematical model for the lac operon: inducer exclusion, catabolite repression, and diauxic growth on glucose and lactose. Biotechnol Prog. 13:1997;132-143.
34. Peper A., Grimbergen C.A., Spaan J.A.E., Souren J.E.M., van Wijk R. A mathematical model of the hsp70 regulation in the cell. Int J Hyperthermia. 14:1998;97-124.
35. Wang J., Ellwood K., Lehman A., Carey M.F., She Z.S. A mathematical model for synergistic eukaryotic gene activation. J Mol Biol. 286:1999;315-325. A nice example of a detailed mechanistic description of eukaryotic gene expression.
36. Hatzimanikatis V., Lee K.H., Bailey J.E. A mathematical description of regulation of the G1-S transition of the mammalian cell cycle. Biotechnol Bioeng. 65:1999;631-637.
37. Bhalla U.S., Iyengar R. Emergent properties of networks of biological signaling pathways. Science. 283:1999;381-387.
38. Agger T., Nielsen J. Genetically structured modelling of protein production in filamentous fungi. Biotechnol Bioeng. 66:1999;164-170. The authors present a general framework that can be used to describe eukaryotic gene expression in a complex regulon.
39. Hatzimanikatis V., Choe L.H., Lee K.H. Proteomics: theoretical and experimental considerations. Biotechnol Prog. 15:1999;312-318.
40. Gygi S.P., Rochon Y., Franza B.R., Aebersold R. Correlation between protein and mRNA abundance in yeast. Mol Cell Biol. 19:1999;1720-1730.
41. Hatzimanikatis V., Lee K.H. Dynamical analysis of gene networks requires both mRNA and protein expression information. Metab Eng. 1:1999;275-281. A nice example of how modelling of protein levels can be combined with proteomic data for functional analysis.
42. Çalik P., Çalik G., Takaç S., Özdamar T.H. Metabolic flux analysis for serine alkaline protease fermentation by Bacillus licheniformis in a defined medium: effects of the oxygen transfer rate. Biotechnol Bioeng. 64:1999;151-167.
43. Yang Y.T., Bennett G.N., San K.Y. Effect of inactivation of nuo and ackA-pta on redistribution of metabolic fluxes in Escherichia coli. Biotechnol Bioeng. 65:1999;291-297.
44. Aristidou A.A., San K.Y., Bennett G.N. Metabolic flux analysis of Escherichia coli expressing the Bacillus subtilis acetolactate synthase in batch and continuous cultures. Biotechnol Bioeng. 63:1999;737-749.
45. Shi H., Nikawa J., Shimizu K. Effect of modifying metabolic network on poly-3-hydroxybutyrate biosynthesis in recombinant Escherichia coli. J Biosci Bioeng. 87:1999;666-677.
46. Hua Q., Yang C., Shimizu K. Metabolic flux analysis for efficient pyruvate fermentation using vitamin-auxotrophic yeast of Torulopsis glabrata. J Biosci Bioeng. 87:1999;206-213.
47. Follstad B.D., Balcarcel R.R., Stephanopoulos G., Wang D.I.C. Metabolic flux analysis of hybridoma continuous culture steady state multiplicity. Biotechnol Bioeng. 63:1999;675-683.
48. 31P-NMR spectroscopy. Arch Microbiol. 171:1999;371-385.
49. Katoh T., Yuguchi D., Yoshii H., Shi H., Shimizu K. Dynamics and modeling on fermentative production of poly (β-hydroxybutyric acid) from sugars via lactate by a mixed culture of Lactobacillus delbrueckii and Alcaligenes eutrophus. J Biotechnol. 67:1999;113-134.
50. Goel A., Lee J., Domach M.M., Ataai M.M. Metabolic fluxes, pools, and enzyme measurements suggest a tighter coupling of energetics and biosynthetic reactions associated with reduced pyruvate kinase flux. Biotechnol Bioeng. 64:1999;129-134.
51. Pramanik J., Trelstad P.L., Schuler A.J., Jenkins D., Keasling J.D. Development and validation of a flux-based stoichiometric model for enhanced biological phosphorus removal metabolism. Wat Res. 33:1999;462-476.
52. Leaf T.A., Srienc F. Metabolic modeling of polyhydroxybutyrate biosynthesis. Biotechnol Bioeng. 57:1998;557-570.
53. Zafiri C., Kornaros M., Lyberatos G. Kinetic modelling of biological phosphorus removal with a pure culture of Acinetobacter sp. under aerobic, anaerobic and transient operating conditions. Wat Res. 33:1999;2769-2788.
54. Cooney M.J., Goh L.T., Lee P.L., Johns M.R. Structured model-based analysis and control of the hyaluronic acid fermentation by Streptococcus zooepidemicus: physiological implications of glucose and complex-nitrogen-limited growth. Biotechnol Prog. 15:1999;898-910.
55. Tholudur A., Ramirez W.F., McMillan J.D. Mathematical modeling and optimization of cellulase protein production using Trichoderma reesei RL-P37. Biotechnol Bioeng. 66:1999;1-16.