Integration of microbial kinetics and fluid dynamics toward model-driven scale-up of industrial bioprocesses

Engineering in Life Sciences

Volumn 15, Issue 1, 2015, Pages 20-29

  Wang, Guan ^a   Tang, Wenjun ^a   Xia, Jianye ^a   Chu, Ju ^a   Noorman, Henk ^b   van Gulik, Walter M ^c  

^a EAST CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b DSM BIOTECHNOLOGY CENTER   (Netherlands)

^c DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

Computational fluid dynamics; Heterogeneity; Mathematical model; Scale down; Scale up

Indexed keywords

BATCH DATA PROCESSING; CARBON DIOXIDE; COMPUTATIONAL FLUID DYNAMICS; FERMENTERS; KINETICS; MASS TRANSFER; MATHEMATICAL MODELS; METABOLIC ENGINEERING; METABOLISM; MIXING;

CONCENTRATION GRADIENTS; EXTERNAL PERTURBATIONS; HETEROGENEITY; IN-DEPTH UNDERSTANDING; INDUSTRIAL BIOPROCESSES; MASS TRANSFER LIMITATION; SCALE DOWN; SCALE-UP;

FLOW OF FLUIDS;

ADENINE NUCLEOTIDE; AMINO ACID; DRUG METABOLITE; GLUCOSE;

AEROBIC CELL CULTURE; BIOMECHANICS; BIOPROCESS; BIOREACTOR; CELL HETEROGENEITY; CELL METABOLISM; COMPUTATIONAL FLUID DYNAMICS; CONCENTRATION PROCESS; EXPERIMENTATION; FERMENTATION OPTIMIZATION; FLUID FLOW; HYDRODYNAMICS; IN VIVO STUDY; INDUSTRIAL PRODUCTION; LARGE SCALE PRODUCTION; MATHEMATICAL MODEL; METABOLIC ENGINEERING; MICROBIAL KINETICS; MIXER; NERVE CELL; NONHUMAN; PROCESS OPTIMIZATION; PULSE RESPONSE EXPERIMENTATION; RESPONSE MECHANISM; REVIEW; SCALE UP; STIMULUS RESPONSE; TIME FACTOR; TURNOVER TIME;

EID: 84920253032     PISSN: 16180240     EISSN: 16182863     Source Type: Journal    
DOI: 10.1002/elsc.201400172     Document Type: Review

References (81)

1. Festel, G., Industrial biotechnology: Market size, company types, business models, and growth strategies. Ind. Biotechnol. 2010, 6, 88-94.
2. Otero, J. M., Nielsen, J., Industrial systems biology. Biotechnol. Bioeng. 2010, 105, 439-460.
3. Rokem, J. S., Lantz, A. E., Nielsen, J., Systems biology of antibiotic production by microorganisms. Nat. Prod. Rep. 2007, 24, 1262-1287.
4. Jorgensen, H., Nielsen, J., Villadsen, J., Mollgaard, H., Metabolic flux distributions in Penicillium chrysogenum during fed-batch cultivations. Biotechnol. Bioeng. 1995, 46, 117-131.
5. van Gulik, W. M., Antoniewicz, M. R., De Laat, W. T. A. M., Vinke, J. L. et al., Energetics of growth and penicillin production in a high-producing strain of Penicillium chrysogenum. Biotechnol. Bioeng. 2001, 72, 185-193.
6. Van Gulik, W. M., De Laat, W. T. A. M., Vinke, J. L., Heijnen, J. J., Application of metabolic flux analysis for the identification of metabolic bottlenecks in the biosynthesis of penicillin-G. Biotechnol. Bioeng. 2000, 68, 602-618.
7. Spadiut, O., Rittmann, S., Dietzsch, C., Herwig, C., Dynamic process conditions in bioprocess development. Eng. Life. Sci. 2013, 13, 88-101.
8. Lara, A. R., Galindo, E., Ramirez, O. T., Palomares, L. A., Living with heterogeneities in bioreactors: Understanding the effects of environmental gradients on cells. Mol. Biotechnol. 2006, 34, 355-381.
9. Bhargava, S., Wenger, K. S., Marten, M. R., Pulsed addition of limiting-carbon during Aspergillus oryzae fermentation leads to improved productivity of a recombinant enzyme. Biotechnol. Bioeng. 2003, 82, 111-117.
10. Bylund, F., Collet, E., Enfors, S-O., Larsson, G., Substrate gradient formation in the large-scale bioreactor lowers cell yield and increases by-product formation. Bioprocess. Eng. 1998, 18, 171-180.
11. Jazini, M., Herwig, C., Two-compartment processing as a tool to boost recombinant protein production. Eng. Life. Sci. 2014, 14, 118-128.
12. Noorman, H., An industrial perspective on bioreactor scale-down: What we can learn from combined large-scale bioprocess and model fluid studies. Biotechnol. J. 2011, 6, 934-943.
13. Zou, X., Xia, J. Y., Chu, J., Zhuang, Y. P. et al., Real-time fluid dynamics investigation and physiological response for erythromycin fermentation scale-up from 50 L to 132 m(3) fermenter. Bioproc. Biosyst. Eng. 2012, 35, 789-800.
14. Yang, Y. M., Xia, J. Y., Li, J. H., Chu, J. et al., A novel impeller configuration to improve fungal physiology performance and energy conservation for cephalosporin C production. J. Biotechnol. 2012, 161, 250-256.
15. Bao, Y., Chen, L., Gao, Z., Chen, J., Local void fraction and bubble size distributions in cold-gassed and hot-sparged stirred reactors. Chem. Eng. Sci. 2010, 65, 976-984.
16. Rampure, M. R., Kulkarni, A. A., Ranade, V. V., Hydrodynamics of bubble column reactors at high gas velocity: Experiments and computational fluid dynamics (CFD) simulations. Ind. Eng. Chem. Res. 2007, 46, 8431-8447.
17. Gimbun, J., Rielly, C. D., Nagy, Z. K., Modelling of mass transfer in gas-liquid stirred tanks agitated by Rushton turbine and CD-6 impeller: A scale-up study. Chem. Eng. Res. Des. 2009, 87, 437-451.
18. Ranganathan, P., Sivaraman, S., Investigations on hydrodynamics and mass transfer in gas-liquid stirred reactor using computational fluid dynamics. Chem. Eng. Sci. 2011, 66, 3108-3124.
19. Wang, G., Chu, J., Noorman, H., Xia, J. Y. et al., Prelude to rational scale-up of penicillin production: A scale-down study. Appl. Microbiol. Biotechnol. 2014, 98, 2359-2369.
20. Bannari, R., Kerdouss, F., Selma, B., Bannari, A. et al., Three-dimensional mathematical modeling of dispersed two-phase flow using class method of population balance in bubble columns. Comput. Chem. Eng. 2008, 32, 3224-3237.
21. Kenty, B., Li, Z., Vanden, T., Lee, S., Mixing in laboratory-scale bioreactors used for mammalian cell culture. Presented at the 229th American Chemical Society National Meeting, San Diego, CA, 2005.
22. Leckie, F., Scragg, A. H., Cliffe, K. C., Effect of bioreactor design and agitator speed on the growth and alkaloid accumulation by cultures of Catharanthus roseus. Enzyme Microb. Tech. 1991, 13, 296-305.
23. Jolicoeur, M., Chavarie, C., Carreau, P. J., Archambault, J., Development of a helical-ribbon impeller bioreactor for high-density plant cell suspension culture. Biotechnol. Bioeng. 1992, 39, 511-521.
24. 3 in volume Food Bioprod. Process. 1998, 76, 107-116.
25. Doran, P. M., Design of Reactors for Plant Cells and Organs. Bioprocess Design and Control, Springer, Berlin, Heidelberg 1993, pp. 115-168.
26. Kiss, R., Croughan, M., Trask, J., Polastri, G., Groenhout, M., Banka, A., Paul, J., Koning-Bastiaan, H., Mixing time characterization in large scale mammalian cell bioreactors. AIChE Annual Meeting. Paper No. 55c. San Francisco, CA, 1994.
27. Jem, J., Fateen, S., Michaels, J., Mixing Phenomena in Industrial Bioreactor with Perfusion Spin Filters. Butterworth Heinemann, Oxford, UK 1994, pp. 392-396.
28. Curtis, W. R., Hairy roots, bioreactor growth, in: Spier, R. E. (Ed.), Encyclopedia of Cell Technology, John Wiley & Sons, New York 2000, Vol. 2, pp. 827-841.
29. Vrabel, P., van der Lans, RG, Luyben, K. C. A., Boon, L. et al., Mixing in large-scale vessels stirred with multiple radial or radial and axial up-pumping impellers: Modelling and measurements. Chem. Eng. Sci. 2000, 55, 5881-5896.
30. Schügerl, K., Comparison of different bioreactor performances. Bioprocess. Eng. 1993, 9, 215-233.
31. Sweere, A. P. J., Luyben, K., Ch, A. M., Kossen, N. W. F., Regime analysis and scale-down: Tools to investigate the performance of bioreactors. Enzyme Microb. Tech. 1987, 9, 386-398.
32. Canelas, A. B., van Gulik, W. M., Heijnen, J. J., Determination of the cytosolic free NAD/NADH ratio in Saccharomyces cerevisiae under steady-state and highly dynamic conditions. Biotechnol. Bioeng. 2008, 100, 734-743.
33. Nasution, U., Van Gulik, W. M., Kleijn, R. J., Van Winden, W. A. et al., Measurement of intracellular metabolites of primary metabolism and adenine nucleotides in chemostat cultivated Penicillium chrysogenum. Biotechnol. Bioeng. 2006, 94, 159-166.
34. Nasution, U., van Gulik, W. M., Proell, A., van Winden, W. A. et al., Generating short-term kinetic responses of primary metabolism of Penicillium chrysogenum through glucose perturbation in the bioscope mini reactor. Metab. Eng. 2006, 8, 395-405.
35. Taymaz-Nikerel, H., de Mey, M., Ras, C., ten Pierick, A. et al., Development and application of a differential method for reliable metabolome analysis in Escherichia coli. Anal. Biochem. 2009, 386, 9-19.
36. Heijnen, J. J., Impact of thermodynamic principles in systems biology. Adv. Biochem. Eng. Biotechnol. 2010, 121, 139-162.
37. Nasution, U., A dynamic and steady state metabolome study of central metabolism and its relation with the penicillin biosynthesis pathway in Penicillium chrysogenum. Ph. D. Thesis, Delft University of Technology, Delft, 2007.
38. Larsson, G., Törnkvist, M., Wernersson, E. S., Trägårdh, C. et al., Substrate gradients in bioreactors: Origin and consequences. Bioprocess. Eng. 1996, 14, 281-289.
39. Enfors, S. O., Jahic, M., Rozkov, A., Xu, B. et al., Physiological responses to mixing in large scale bioreactors. J. Biotechnol. 2001, 85, 175-185.
40. Amanullah, A., McFarlane, C., Emery, A., Nienow, A., Scale-down model to simulate spatial pH variations in large-scale bioreactors. Biotechnol. Bioeng. 2001, 73, 390-399.
41. Baez, A., Flores, N., Bolivar, F., Ramirez, O. T., Simulation of dissolved CO(2) gradients in a scale-down system: A metabolic and transcriptional study of recombinant Escherichia coli. Biotechnol. J. 2011, 6, 959-967.
42. Sandoval-Basurto, E. A., Gosset, G., Bolivar, F., Ramirez, O. T., Culture of Escherichia coli under dissolved oxygen gradients simulated in a two-compartment scale-down system: Metabolic response and production of recombinant protein. Biotechnol. Bioeng. 2005, 89, 453-463.
43. Junne, S., Klingner, A., Kabisch, J., Schweder, T. et al., A two-compartment bioreactor system made of commercial parts for bioprocess scale-down studies: Impact of oscillations on Bacillus subtilis fed-batch cultivations. Biotechnol. J. 2011, 6, 1009-1017.
44. Lorantfy, B., Jazini, M., Herwig, C., Investigation of the physiological response to oxygen limited process conditions of Pichia pastoris Mut(+) strain using a two-compartment scale-down system. J. Biosci. Bioeng. 2013, 116, 371-379.
45. Nienow, A. W., Scott, W. H., Hewitt, C. J., Thomas, C. R. et al., Scale-down studies for assessing the impact of different stress parameters on growth and product quality during animal cell culture. Chem. Eng. Res. Des. 2013, 91, 2265-2274.
46. Neubauer, P., Junne, S., Scale-down simulators for metabolic analysis of large-scale bioprocesses. Curr. Opin. Biotechnol. 2010, 21, 114-121.
47. Kä, F., Junne, S., Neubauer, P., Wiechert, W. et al., Process inhomogeneity leads to rapid side product turnover in cultivation of Corynebacterium glutamicum. Microb. Cell. Fact. 2014, 13, 6.
48. de Jonge, L. P., Buijs, N. A., ten Pierick, A., Deshmukh, A. et al., Scale-down of penicillin production in Penicillium chrysogenum. Biotechnol. J. 2011, 6, 944-958.
49. Teusink, B., Smid, E. J., Modelling strategies for the industrial exploitation of lactic acid bacteria. Nat. Rev. Microbiol. 2006, 4, 46-56.
50. Visser, D., van Zuylen, G. A., van Dam, J. C., Eman M. R. et al. Analysis of in vivo kinetics of glycolysis in aerobic Saccharomyces cerevisiae by application of glucose and ethanol pulses. Biotechnol. Bioeng. 2004, 88, 157-167.
51. Almquist, J., Cvijovic, M., Hatzimanikatis, V., Nielsen, J. et al., Kinetic models in industrial biotechnology-Improving cell factory performance. Metab. Eng. 2014, 24, 38-60.
52. Heijnen, J. J., Approximative kinetic formats used in metabolic network modeling. Biotechnol. Bioeng. 2005, 91, 534-545.
53. Van Gulik, W. M., Canelas, A. B., Taymaz-Nikerel H., Douma R. D. et al., Fast sampling of the cellular metabolome. Methods Mol. Biol. 2012, 881, 279-306.
54. 13C-labeled extracts. A new method for accurate quantification of changes in concentrations of intracellular metabolites. Biotechnol. Bioeng. 2004, 85, 620-628.
55. Vemuri, G. N., Eiteman, M. A., McEwen, J. E., Olsson, L. et al., Increasing NADH oxidation reduces overflow metabolism in Saccharomyces cerevisiae. Proc. Natl. Acad. Sci. USA. 2007, 104, 2402-2407.
56. Stelling, J., Sauer, U., Szallasi, Z., Doyle, F. J. et al., Robustness of cellular functions. Cell 2004, 118, 675-685.
57. Mashego, M. R., van Gulik, W. M., Vinke, J. L., Visser, D. et al., In vivo kinetics with rapid perturbation experiments in Saccharomyces cerevisiae using a second-generation BioScope. Metab. Eng. 2006, 8, 370-383.
58. Flamholz, A., Noor, E., Bar-Even, A., Liebermeister, W. et al., Glycolytic strategy as a tradeoff between energy yield and protein cost. Proc. Natl. Acad. Sci. USA. 2013, 110, 10039-10044.
59. de Jonge, L. P., Buijs, N. A., Heijnen, J. J., van Gulik, W. M. et al., Flux response of glycolysis and storage metabolism during rapid feast/famine conditions in Penicillium chrysogenum using dynamic (13) C labeling. Biotechnol. J. 2014, 9, 372-385.
60. Zhao, Z., ten Pierick, A., de Jonge, L. P., Heijnen, J. J. et al., Substrate cycles in Penicillium chrysogenum quantified by isotopic non-stationary flux analysis. Microb. Cell. Fact. 2012, 11, 140.
61. Nasution, U., van Gulik, W. M., Ras, C., Proell, A. et al., A metabolome study of the steady-state relation between central metabolism, amino acid biosynthesis and penicillin production in Penicillium chrysogenum. Metab. Eng. 2008, 10, 10-23.
62. Aboka, F. O., Heijnen, J. J., van Winden, W. A., Dynamic 13C-tracer study of storage carbohydrate pools in aerobic glucose-limited Saccharomyces cerevisiae confirms a rapid steady-state turnover and fast mobilization during a modest stepup in the glucose uptake rate. FEMS Yeast Res. 2009, 9, 191-201.
63. van Heerden, J. H., Wortel, M. T., Bruggeman, F. J., Heijnen, J. J. et al., Lost in transition: Start-up of glycolysis yields subpopulations of nongrowing cells. Science 2014, 343, 1245114.
64. Buffo, A., Vanni, M., Marchisio, D. L., Multidimensional population balance model for the simulation of turbulent gas-liquid systems in stirred tank reactors. Chem. Eng. Sci. 2012, 70, 31-44.
65. Zhang, D., Deen, N. G., Kuipers, J., Euler-Euler modeling of flow, mass transfer, and chemical reaction in a bubble column. Ind. Eng. Chem. Res. 2008, 48, 47-57.
66. Kerdouss, F., Bannari, A., Proulx, P., CFD modeling of gas dispersion and bubble size in a double turbine stirred tank. Chem. Eng. Sci. 2006, 61, 3313-3322.
67. Sousa, T., Rangel, C., A dynamic two phase flow model for a pilot scale sodium borohydride hydrogen generation reactor. Int. J. Hydrogen. Energ. 2014, 39, 5291-5300.
68. Kurz, D., Schnell, U., Scheffknecht, G., CFD simulation of wood chip combustion on a grate using an Euler-Euler approach. Combust. Theor. Model. 2012, 16, 251-273.
69. Elqotbi, M., Vlaev, S., Montastruc, L., Nikov, I., CFD modelling of two-phase stirred bioreaction systems by segregated solution of the Euler-Euler model. Comput. Chem. Eng. 2013, 48, 113-120.
70. Moilanen, P., Laakkonen, M., Aittamaa, J., Modeling aerated fermenters with computational fluid dynamics. Ind. Eng. Chem. Res. 2006, 45, 8656-8663.
71. Bannari, R., Bannari, A., Vermette, P., Proulx, P., A model for cellulase production from Trichoderma reesei in an airlift reactor. Biotechnol. Bioeng. 2012, 109, 2025-2038.
72. Morchain, J., Gabelle, J. C., Cockx, A., Coupling of biokinetic and population balance models to account for biological heterogeneity in bioreactors. AIChE J. 2013, 59, 369-379.
73. Morchain, J., Gabelle, J. C., Cockx, A., A coupled population balance model and CFD approach for the simulation of mixing issues in lab-scale and industrial bioreactors. AIChE J. 2014, 60, 27-40.
74. Henson, M., Muller, D., Reuss, M., Cell population modelling of yeast glycolytic oscillations. Biochem. J. 2002, 368, 433-446.
75. Fernandes, R. L., Nierychlo, M., Lundin, L., Pedersen, A. E. et al., Experimental methods and modeling techniques for description of cell population heterogeneity. Biotechnol. Adv. 2011, 29, 575-599.
76. Lapin, A., Klann, M., Reuss, M., Multi-scale spatio-temporal modeling: Lifelines of microorganisms in bioreactors and tracking molecules in cells. Biosyst. Eng. II 2010, 121, 23-43.
77. Wolf, J., Heinrich, R., Effect of cellular interaction on glycolytic oscillations in yeast: A theoretical investigation. Biochem. J. 2000, 345, 321-334.
78. Lapin, A., Reuss, M., Dynamic behavior of microbial populations in stirred bioreactors simulated with Euler-Lagrange methods: Traveling along the Lifelines Of Single Cells. Ind. Eng. Chem. Res. 2004, 43, 4647-4656
79. Chassagnole, C., Noisommit-Rizzi, N., Schmid, J. W., Mauch, K. et al., Dynamic modeling of the central carbon metabolism of Escherichia coli. Biotechnol. Bioeng. 2002, 79, 53-73.
80. Lapin, A., Schmid, J., Reuss, M., Modeling the dynamics of E. coli populations in the three-dimensional turbulent field of a stirred-tank bioreactor-A structured-segregated approach. Chem. Eng. Sci. 2006, 61, 4783-4797.
81. Müller, S., Harms, H., Bley, T., Origin and analysis of microbial population heterogeneity in bioprocesses. Curr. Opin. Biotechnol. 2010, 21, 100-113.