Evaluación del impacto de gradientes de concentración sobre el metabolismo del carbono central microbiano mediante un enfoque de modelamiento multiescala

dc.contributor.advisorSuárez Méndez, Camilo Alberto
dc.contributor.authorMoreno Otálvaro, Sebastián
dc.contributor.researchgroupBioprocesos y Flujos Reactivosspa
dc.date.accessioned2023-08-01T19:19:52Z
dc.date.available2023-08-01T19:19:52Z
dc.date.issued2022-12-04
dc.descriptionIlustracionesspa
dc.description.abstractModelar un bioproceso es crucial para tener un entendimiento y predecir variables de operación importantes en la industria. Para hacerlo no solo es pertinente modelar el biorreactor con sus fenómenos de transporte sino también algunos procesos intracelulares que transforman el sustrato disponible. De esta forma, el objetivo general de esta tesis es realizar un modelamiento multiescala que comprende la escala macro (reactor) y la escala micro (metabolismo celular). La descripción matemática del biorreactor consistió en un modelo de compartimentos, con el fin de calcular los gradientes de concentración. Para la configuración dada del reactor se calculó un tiempo de mezcla de 70s si la alimentación es en el medio del tanque. Por otro lado, se construyó un modelo cinético para predecir datos experimentales del metabolismo de carbono central de Saccharomyces cerevisiae; específicamente para la glucólisis, la ruta de las pentosas fosfato y el metabolismo de trehalosa y glucógeno. Se realizó la estimación de parámetros y se obtuvo diferentes respuestas. Por ejemplo, para la glucosa intracelular el error fue del 3.8% y para fructosa 6-fosfato del 1%. Además, el modelo derivado aquí para el pool de glucógeno funcionará como base para trabajos futuros, ya que su modelamiento no ha sido lo suficientemente explorado en la literatura. Después, se acoplaron ambos modelos a través de la tasa de consumo de sustrato 𝑞���𝑠��� . Se simuló un pulso de alimento y se construyeron mapas de calor que muestran los gradientes de concentración en el reactor para la glucosa extracelular, metabolitos intracelulares y 𝑞���𝑠��� . Por último, se hizo un análisis de sensibilidad según la velocidad de agitación y el número de pulsos. Se obtuvo que a una velocidad de 180 o 240 rpm se disminuyen en gran medida los gradientes. Con el segundo análisis, se concluyó que tanto la trehalosa como el glucógeno son pooles de carbono que funcionan como buffer frente a perturbaciones de concentración en el entorno del microorganismo. (texto tomado de la fuente)spa
dc.description.abstractModelling a bioprocess is key for general understanding and predicting important operation variables at industry level. To do so, it is not only relevant to model the bioreactor and the associated transport phenomena, but also to model intracellular processes in charge of converting the available substrate. In this direction, the general objective of this thesis is to perform multiscale modeling considering the macroscale (reactor) and the microscale (cellular metabolism). The mathematical description of the bioreactor consists of a compartment model to compute concentration gradients. For the chosen reactor configuration, a mixing time of 70s is estimated when the feeding point is located somewhere at the middle section of the vessel. On the other hand, a kinetic model is built to predict experimental data from central carbon metabolism of Saccharomyces cerevisiae; specifically, glycolysis, pentose phosphate pathway and the trehalose and glycogen metabolism. Parameter estimation is performed resulting in different responses. For instance, for intracellular glucose an error of approximately 3.8% is obtained while for fructose 6-phosphate the error is about 1%. In addition, the model derived here for the glycogen pool might serve as a basis for future work, because its modelling has not yet been explored enough in literature. Then, both models are coupled by the substrate consumption velocity 𝑞��𝑠�� . A feeding pulse is simulated, and heat maps are constructed showing concentration gradients throughout the reactor for the extracellular glucose, intracellular metabolites and 𝑞��𝑠�� . Finally, a sensitivity analysis is performed according to the agitation speed and the number of pulses. As a result, the observed concentration gradients are significantly reduced when a stirring speed of 180 or 240 rpm is used. From the second analysis, a notable remark is that both, trehalose, and glycogen carbon pools, seem to buffer the carbon flux against concentration perturbations in the microorganism environment.eng
dc.description.curricularareaÁrea curricular de Ingeniería Química e Ingeniería de Petróleosspa
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagíster en Ingeniería - Ingeniería Químicaspa
dc.format.extent166 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/84402
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Medellínspa
dc.publisher.facultyFacultad de Minasspa
dc.publisher.placeMedellín, Colombiaspa
dc.publisher.programMedellín - Minas - Maestría en Ingeniería - Ingeniería Químicaspa
dc.relation.referencesAntoniewicz, M. R. (2021). A guide to metabolic flux analysis in metabolic engineering: Methods, tools and applications. Metabolic Engineering, 63(November 2020), 2–12. https://doi.org/10.1016/j.ymben.2020.11.002spa
dc.relation.referencesAscanio, G. (2015). Mixing time in stirred vessels: A review of experimental techniques. Chinese Journal of Chemical Engineering, 23(7), 1065–1076. https://doi.org/10.1016/j.cjche.2014.10.022spa
dc.relation.referencesBaskaran, S. (2010). Structure and Regulation of Yeast Glycogen Synthase (Issue August) [Indiana University]. https://doi.org/10.1007/978-3-319-43589-3_1spa
dc.relation.referencesBond, C. J., Jurica, M. S., Mesecar, A., & Stoddard, B. L. (2000). Determinants of allosteric activation of yeast pyruvate kinase and identification of novel effectors using computational screening. Biochemistry, 39(50), 15333–15343. https://doi.org/10.1021/bi001443ispa
dc.relation.referencesChan, C. Y., & Parra, K. J. (2014). Yeast phosphofructokinase-1 subunit Pfk2p is necessary for pH homeostasis and glucose-dependent vacuolar ATPase reassembly. Journal of Biological Chemistry, 289(28), 19448–19457. https://doi.org/10.1074/jbc.M114.569855spa
dc.relation.referencesCharpentier, J. C. (2009). Perspective on multiscale methodology for product design and engineering. Computers and Chemical Engineering, 33(5), 936–946. https://doi.org/10.1016/j.compchemeng.2008.11.007spa
dc.relation.referencesCleland, W. W. (1963a). Biochimica Et Biophysica Acta the Kinetics of Enzyme-Catalyzed Re Ti With Two or More Substrates or Pr D Ct I. Nomen Clature a Td Rate Equatio. Biochirn. Biophys. Acta, 67(2), 67. https://doi.org/10.1016/0926-6569(63)90211-6spa
dc.relation.referencesCleland, W. W. (1963b). The kinetics of enzyme-catalyzed reactions with two or more substrates or products. II. Inhibition: Nomenclature and theory. BBA - Biochimica et Biophysica Acta, 67(C), 173–187. https://doi.org/10.1016/0006-3002(63)91815-8spa
dc.relation.referencesCui, Y. Q., Van der Lans, R. G. J. M., & Luyben, K. C. A. M. (1996). Local Power Uptake in Gas-Liquid Systems With Single and Multiple Rushton Turbines. 51(1), 2631– 2636.spa
dc.relation.referencesDoran, P. M. (2012). Bioprocess engineering principles: Second edition. In Bioprocess Engineering Principles: Second Edition (Vol. 9780080917).spa
dc.relation.referencesFlamholz, A. (2018). eQuilibrator. https://equilibrator.weizmann.ac.il/spa
dc.relation.referencesFrançois, J., & Parrou, J. L. (2001). Reserve carbohydrates metabolism in the yeast Saccharomyces cerevisiae. FEMS Microbiology Reviews, 25(1), 125–145. https://doi.org/10.1016/S0168-6445(00)00059-0spa
dc.relation.referencesGao, H., & Leary, J. A. (2003). Multiplex inhibitor screening and kinetic constant determinations for yeast hexokinase using mass spectrometry based assays. Journal of the American Society for Mass Spectrometry, 14(3), 173–181. https://doi.org/10.1016/S1044-0305(02)00867-Xspa
dc.relation.referencesGeerlof, A., Travers, F., Barman, T., & Lionne, C. (2005). Perturbation of yeast 3- phosphoglycerate kinase reaction mixtures with ADP: Transient kinetics of formation of ATP from bound 1,3-bisphosphoglycerate. Biochemistry, 44(45), 14948–14955. https://doi.org/10.1021/bi0512290spa
dc.relation.referencesGelves, R., Dietrich, A., & Takors, R. (2014). Modeling of gas-liquid mass transfer in a stirred tank bioreactor agitated by a Rushton turbine or a new pitched blade impeller. Bioprocess and Biosystems Engineering, 37(3), 365–375. https://doi.org/10.1007/s00449-013-1001-8spa
dc.relation.referencesGikas, P., & Livingston, A. G. (1998). Use of specific ATP concentration and specific oxygen uptake rate to determine parameters of a structured model of biomass growth. Enzyme and Microbial Technology, 22(6), 500–510. https://doi.org/10.1016/S0141-0229(97)00242-1spa
dc.relation.referencesHahn, J. (2020). From Parts to the Whole A Whole-Cell Model for Saccharomyces cerevisiae. Humboldt-university Berlinspa
dc.relation.referencesHajian, C. S. S., Haringa, C., Noorman, H., & Takors, R. (2020). Predicting by-product gradients of baker’s yeast production at industrial scale: A practical simulation approach. Processes, 8(12), 1–19. https://doi.org/10.3390/pr8121554spa
dc.relation.referencesHaringa, C., Tang, W., Deshmukh, A. T., Xia, J., Reuss, M., Heijnen, J. J., Mudde, R. F., & Noorman, H. J. (2016). Euler-Lagrange computational fluid dynamics for (bio)reactor scale down: An analysis of organism lifelines. Engineering in Life Sciences, 16(7), 652–663. https://doi.org/10.1002/elsc.201600061spa
dc.relation.referencesHaringa, C., Tang, W., Wang, G., Deshmukh, A. T., van Winden, W. A., Chu, J., van Gulik, W. M., Heijnen, J. J., Mudde, R. F., & Noorman, H. J. (2018). Computational fluid dynamics simulation of an industrial P. chrysogenum fermentation with a coupled 9-pool metabolic model: Towards rational scale-down and design optimization. Chemical Engineering Science, 175, 12–24. https://doi.org/10.1016/j.ces.2017.09.020spa
dc.relation.referencesHess, B., & Plesser, T. (1979). Temporal and Spatial Order in Biochemical Systems. Annals of the New York Academy of Sciences, 316(1), 203–213. https://doi.org/10.1111/j.1749-6632.1979.tb29470.xspa
dc.relation.referencesHori, K., & Unno, H. (2011). Integrated Production and Separation. In Comprehensive Biotechnology, Second Edition (Second Edi, Vol. 2). Elsevier B.V. https://doi.org/10.1016/B978-0-08-088504-9.00116-1spa
dc.relation.referencesIngram, G. D., Cameron, I. T., & Hangos, K. M. (2004). Classification and analysis of integrating frameworks in multiscale modelling. Chemical Engineering Science, 59(11), 2171–2187. https://doi.org/10.1016/j.ces.2004.02.010spa
dc.relation.referencesJohnson, K. A., & Goody, R. S. (2011). The original Michaelis constant: Translation of the 1913 Michaelis-Menten Paper. Biochemistry, 50(39), 8264–8269. https://doi.org/10.1021/bi201284uspa
dc.relation.referencesJourdan, N., Neveux, T., Potier, O., Kanniche, M., Wicks, J., Nopens, I., Rehman, U., & Le Moullec, Y. (2019). Compartmental Modelling in chemical engineering: A critical review. Chemical Engineering Science, 210, 115196. https://doi.org/10.1016/j.ces.2019.115196spa
dc.relation.referencesKesten, D., Kummer, U., Sahle, S., & Hübner, K. (2015). A new model for the aerobic metabolism of yeast allows the detailed analysis of the metabolic regulation during glucose pulse. Biophysical Chemistry, 206, 40–57. https://doi.org/10.1016/j.bpc.2015.06.010spa
dc.relation.referencesKing, E. L., & Altman, C. (1956). A schematic method of deriving the rate laws for enzyme-catalyzed reactions. Journal of Physical Chemistry, 60(10), 1375–1378. https://doi.org/10.1021/j150544a010spa
dc.relation.referencesKlipp, E., Herwig, P., Kowald, A., Wierling, C., & Lehrach, H. (2005). Systems Biology in Practice.spa
dc.relation.referencesLam, C. F., & Priest, D. G. (1972). Enzyme Kinetics: Systematic Generation of Valid KingAltman Patterns. Biophysical Journal, 12(3), 248–256. https://doi.org/10.1016/S0006-3495(72)86084-3spa
dc.relation.referencesLapin, A., Schmid, J., & Reuss, M. (2006). Modeling the dynamics of E. coli populations in the three-dimensional turbulent field of a stirred-tank bioreactor-A structuredsegregated approach. Chemical Engineering Science, 61(14), 4783–4797. https://doi.org/10.1016/j.ces.2006.03.003spa
dc.relation.referencesLarsson, C., Påhlman, I. L., & Gustafsson, L. (2000). The importance of ATP as a regulator of glycolytic flux in Saccharomyces cerevisiae. Yeast, 16(9), 797–809. https://doi.org/10.1002/1097-0061(20000630)16:9<797::AID-YEA553>3.0.CO;2-5spa
dc.relation.referencesLarsson, M., & Arvidsson, L. (1971). Inhibition of Phosphoglycerate Kinase by Products and Product Homologues. 22, 506–512.spa
dc.relation.referencesLeskovac, V. (2004). COMPREHENSIVE ENZYME KINETICS. Kluwer Academic Publishers, 438. https://doi.org/10.1007/0-306-48390-4_5spa
dc.relation.referencesLuo, Y., Kurian, V., & Ogunnaike, B. A. (2021). Bioprocess systems analysis, modeling, estimation, and control. Current Opinion in Chemical Engineering, 33, 100705. https://doi.org/10.1016/j.coche.2021.100705spa
dc.relation.referencesMayr, B., Horvat, P., Nagy, E., & Moser, A. (1993). Mixing-models applied to industrial batch bioreactors. Bioprocess Engineering, 9(1), 1–12. https://doi.org/10.1007/BF00389534spa
dc.relation.referencesMessiha, H., Kent, E., Malys, N., Carroll, K., Mendes, P., & Smallbone, K. (2014). Enzyme characterisation and kinetic modelling of the pentose phosphate pathway in yeast. PeerJ PrePrints, April. https://doi.org/10.7287/peerj.preprints.146v4spa
dc.relation.referencesMoisset, P., Vaisman, D., Cintolesi, A., Urrutia, J., Rapaport, I., Andrews, B. A., & Asenjo, J. A. (2012). Continuous modeling of metabolic networks with gene regulation in yeast and in vivo determination of rate parameters. Biotechnology and Bioengineering, 109(9), 2325–2339. https://doi.org/10.1002/bit.24503spa
dc.relation.referencesMonod, J., Wyman, J., & Changeux, J. P. (1965). On the nature of allosteric transitions: A plausible model. Journal of Molecular Biology, 12(1), 88–118. https://doi.org/10.1016/S0022-2836(65)80285-6spa
dc.relation.referencesMorchain, J. (2017a). Bioreactor Modeling. In Bioreaction Engineering Principles. Elsevier. https://doi.org/10.1007/978-1-4757-4645-7_9spa
dc.relation.referencesMorchain, J. (2017b). Numerical Tools for Scaling Up Bioreactors. Current Developments in Biotechnology and Bioengineering: Bioprocesses, Bioreactors and Controls, 495– 523. https://doi.org/10.1016/B978-0-444-63663-8.00017-3spa
dc.relation.referencesMulcahy, P., O’Flaherty, M., Jennings, L., & Griffin, T. (2002). Application of kinetic-based biospecific affinity chromatographic systems to ATP-dependent enzymes: Studies with yeast hexokinase. Analytical Biochemistry, 309(2), 279–292. https://doi.org/10.1016/S0003-2697(02)00307-Xspa
dc.relation.referencesMuloiwa, M., Nyende-Byakika, S., & Dinka, M. (2020). Comparison of unstructured kinetic bacterial growth models. South African Journal of Chemical Engineering, 33(July), 141–150. https://doi.org/10.1016/j.sajce.2020.07.006spa
dc.relation.referencesNadal-Rey, G., McClure, D. D., Kavanagh, J. M., Cornelissen, S., Fletcher, D. F., & Gernaey, K. V. (2021). Understanding gradients in industrial bioreactors. Biotechnology Advances, 46(October 2020), 107660. https://doi.org/10.1016/j.biotechadv.2020.107660spa
dc.relation.referencesNeet, K. E. (1995). Cooperativity in enzyme function: Equilibrium and kinetic aspects. Methods in Enzymology, 249(C), 519–567. https://doi.org/10.1016/0076- 6879(95)49048-5spa
dc.relation.referencesNielsen, J. (2014). Bioreaction Engineering Principles. In Psychological Science (Vol. 25, Issue 9).spa
dc.relation.referencesNienow, A. W. (1998). Hydrodynamics of stirred bioreactors. Applied Mechanics Reviews, 51(1), 3–32. https://doi.org/10.1115/1.3098990spa
dc.relation.referencesNoorman, H. J., & Heijnen, J. J. (2017). Biochemical engineering’s grand adventure. Chemical Engineering Science, 170, 677–693. https://doi.org/10.1016/j.ces.2016.12.065spa
dc.relation.referencesOide, S., & Inui, M. (2017). Trehalose acts as a uridine 5′-diphosphoglucose-competitive inhibitor of trehalose 6-phosphate synthase in Corynebacterium glutamicum. FEBS Journal, 284(24), 4298–4313. https://doi.org/10.1111/febs.14309spa
dc.relation.referencesPapagianni, M. (2012). Recent advances in engineering the central carbon metabolism of industrially important bacteria. Microbial Cell Factories, 11, 1–13. https://doi.org/10.1186/1475-2859-11-50spa
dc.relation.referencesPigou, M., & Morchain, J. (2015). Investigating the interactions between physical and biological heterogeneities in bioreactors using compartment, population balance and metabolic models. Chemical Engineering Science, 126(April), 267–282. https://doi.org/10.1016/j.ces.2014.11.035spa
dc.relation.referencesPurich, D. L. (2009). Contemporary Enzyme Kinetics and Mechanism: Reliable Lab Solutions. http://books.google.com/books?hl=en&lr=&id=Pr3V80HZLpkC&pgis=1spa
dc.relation.referencesRichter, O., Betz, A., & Giersch, C. (1975). The response of oscillating glycolysis to perturbations in the NADH/NAD system: A comparison between experiments and a computer model. BioSystems, 7(1), 137–146. https://doi.org/10.1016/0303- 2647(75)90051-9spa
dc.relation.referencesRizzi, M., Baltes, M., Theobald, U., & Reuss, M. (1997). In vivo analysis of metabolic dynamics in Saccharomyces cerevisiae: II. Mathematical model. Biotechnology and Bioengineering, 55(4), 592–608. https://doi.org/10.1002/(SICI)1097- 0290(19970820)55:4<592::AID-BIT2>3.0.CO;2-Cspa
dc.relation.referencesRothman, L. B., & Cabib, E. (1967a). Allosteric Properties of Yeast Glycogen Synthetase. I. General Kinetic Study. Biochemical and Biophysical Research Communications, 6(7), 644–650. https://doi.org/10.1016/0006-291X(66)90503-1spa
dc.relation.referencesRothman, L. B., & Cabib, E. (1967b). Allosteric Properties of Yeast Glycogen Synthetase. II. The Effect of pH on Inhibition and Its Physiological Implications. Biochemistry, 6(7), 2107–2112.spa
dc.relation.referencesRudolph, F. B., & Fromm, H. J. (1971). Computer simulation studies with yeast hexokinase and additional evidence for the random Bi Bi mechanism. Journal of Biological Chemistry, 246(21), 6611–6619. https://doi.org/10.1016/s0021- 9258(19)34158-4spa
dc.relation.referencesSaa, P. A., & Nielsen, L. K. (2017). Formulation, construction and analysis of kinetic models of metabolism: A review of modelling frameworks. Biotechnology Advances, 35(8), 981–1003. https://doi.org/10.1016/j.biotechadv.2017.09.005spa
dc.relation.referencesSiebler, F., Lapin, A., Hermann, M., & Takors, R. (2019). The impact of CO gradients on C. ljungdahlii in a 125 m3 bubble column: Mass transfer, circulation time and lifeline analysis. Chemical Engineering Science, 207, 410–423. https://doi.org/10.1016/j.ces.2019.06.018spa
dc.relation.referencesSmallbone, K., Malys, N., Messiha, H. L., Wishart, J. A., & Simeonidis, E. (2011). Building a kinetic model of trehalose biosynthesis in Saccharomyces cerevisiae. In Methods in Enzymology (1st ed., Vol. 500). Elsevier Inc. https://doi.org/10.1016/B978-0-12- 385118-5.00018-9spa
dc.relation.referencesSmallbone, K., Messiha, H. L., Carroll, K. M., Winder, C. L., Malys, N., Dunn, W. B., Murabito, E., Swainston, N., Dada, J. O., Khan, F., Pir, P., Simeonidis, E., Spasić, I., Wishart, J., Weichart, D., Hayes, N. W., Jameson, D., Broomhead, D. S., Oliver, S. G., … Mendes, P. (2013). A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes. FEBS Letters, 587(17), 2832–2841. https://doi.org/10.1016/j.febslet.2013.06.043spa
dc.relation.referencesSuarez-Mendez, C. a. (2015). Dynamics of Storage Carbohydrates Metabolism in Saccharomyces cerevisiae: A Quantitative (Issue december).spa
dc.relation.referencesTanabe, S., Kobayashi, M., & Matsuda, K. (1987a). Yeast Glycogen Phosphorylase: Characterization of the Dimeric Form and Its Activation. Agricultural and Biological Chemistry, 51(9), 2465–2471. https://doi.org/10.1271/bbb1961.51.2465spa
dc.relation.referencesTanabe, S., Kobayashi, M., & Matsuda, K. (1987b). Yeast Glycogen Phosphorylase: Kinetic Properties Compared with Muscle and Potato Enzymes. Agricultural and Biological Chemistry, 52(3), 757–764. https://doi.org/10.1271/bbb1961.52.757spa
dc.relation.referencesTang, W., Deshmukh, A. T., Haringa, C., Wang, G., van Gulik, W., van Winden, W., Reuss, M., Heijnen, J. J., Xia, J., Chu, J., & Noorman, H. J. (2017). A 9-pool metabolic structured kinetic model describing days to seconds dynamics of growth and product formation by Penicillium chrysogenum. In Biotechnology and Bioengineering (Vol. 114, Issue 8). https://doi.org/10.1002/bit.26294spa
dc.relation.referencesTeusink, B., Passarge, J., Reijenga, C. A., Esgalhado, E., Van Der Weijden, C. C., Schepper, M., Walsh, M. C., Bakker, B. M., Van Dam, K., Westerhoff, H. V., & Snoep, J. L. (2000). Can yeast glycolysis be understood terms of vitro kinetics of the constituent enzymes? Testing biochemistry. European Journal of Biochemistry, 267(17), 5313–5329. https://doi.org/10.1046/j.1432-1327.2000.01527.xspa
dc.relation.referencesTraut, T. (2008). Regulatory Allosteric Enzymes. Springer US.spa
dc.relation.referencesTrevisol, E. T. V., Panek, A. D., De Mesquita, J. F., & Eleutherio, E. C. A. (2014). Regulation of the yeast trehalose-synthase complex by cyclic AMP-dependent phosphorylation. Biochimica et Biophysica Acta - General Subjects, 1840(6), 1646– 1650. https://doi.org/10.1016/j.bbagen.2013.12.010spa
dc.relation.referencesTripodi, F., Nicastro, R., Reghellin, V., & Coccetti, P. (2015). Post-translational modifications on yeast carbon metabolism: Regulatory mechanisms beyond transcriptional control. Biochimica et Biophysica Acta - General Subjects, 1850(4), 620–627. https://doi.org/10.1016/j.bbagen.2014.12.010spa
dc.relation.referencesTurnquist, R., & Hansen, G. (1973). Uridine Diphosphoryl Glucose Pyrophosphorylase. 1, 51–71.spa
dc.relation.referencesVan’t Riet, K. (1991). Basic Bioreactor Design. Marcel Dekker, Inc.spa
dc.relation.referencesvan Boekel, M. A. J. S., & Tijskens, L. M. M. (2001). Kinetic modelling. Food Process Modelling, December, 35–59. https://doi.org/10.1533/9781855736375.1.35spa
dc.relation.referencesvan Leer, B., & Powell, K. G. (2010). Introduction to Computational Fluid Dynamics. Encyclopedia of Aerospace Engineering, October. https://doi.org/10.1002/9780470686652.eae048spa
dc.relation.referencesVandercammen, A., François, J., & Hers, H. -G. (1989). Characterization of trehalose-6- phosphate synthase and trehalose-6-phosphate phosphatase of Saccharomyces cerevisiae. European Journal of Biochemistry, 182(3), 613–620. https://doi.org/10.1111/j.1432-1033.1989.tb14870.xspa
dc.relation.referencesVasconcelos, J. M. T., Alves, S. S., & Barata, J. M. (1995). Mixing in gas-liquid contactors agitated by multiple turbines. Chemical Engineering Science, 50(14), 2343–2354. https://doi.org/10.1016/0009-2509(95)00090-Rspa
dc.relation.referencesVaseghi, S., Baumeister, A., Rizzi, M., & Reuss, M. (1999). In vivo dynamics of the pentose phosphate pathway in Saccharomyces cerevisiae. Metabolic Engineering, 1(2), 128–140. https://doi.org/10.1006/mben.1998.0110spa
dc.relation.referencesvon Stockar, U. (2013). Biothermodynamics: Role, The Engineering, Biochemical. EPFL Press.spa
dc.relation.referencesVrábel, P., Van Der Lans, R. G. J. M., Cui, Y. Q., & Luyben, K. C. A. M. (1999). Compartment model approach: Mixing in large scale aerated reactors with multiple impellers. Chemical Engineering Research and Design, 77(4), 291–302. https://doi.org/10.1205/026387699526223spa
dc.relation.referencesVrábel, P., Van Der Lans, R. G. J. M., Luyben, K. C. A. M., Boon, L., & Nienow, A. W. (2000). Mixing in large-scale vessels stirred with multiple radial or radial and axial uppumping impellers: Modelling and measurements. Chemical Engineering Science, 55(23), 5881–5896. https://doi.org/10.1016/S0009-2509(00)00175-5spa
dc.relation.referencesVrábel, P., Van der Lans, R. G. J. M., Van der Schot, F. N., Luyben, K. C. A. M., Xu, B., & Enfors, S. O. (2001). CMA: Integration of fluid dynamics and microbial kinetics in modelling of large-scale fermentations. Chemical Engineering Journal, 84(3), 463– 474. https://doi.org/10.1016/S1385-8947(00)00271-0spa
dc.relation.referencesWilson, W. A., Boyer, M. P., Davis, K. D., Burke, M., & Roach, P. J. (2010). The subcellular localization of yeast glycogen synthase is dependent upon glycogen content. Canadian Journal of Microbiology, 56(5), 408–420. https://doi.org/10.1139/W10-027spa
dc.relation.referencesWilson, W. A., Roach, P. J., Montero, M., Baroja-Fernández, E., Muñoz, F. J., Eydallin, G., Viale, A. M., & Pozueta-Romero, J. (2010). Regulation of glycogen metabolism in yeast and bacteria. FEMS Microbiology Reviews, 34(6), 952–985. https://doi.org/10.1111/j.1574-6976.2010.00220.xspa
dc.relation.referencesXia, J., Wang, G., Lin, J., Wang, Y., Chu, J., Zhuang, Y., & Zhang, S. (2015). Advances and Practices of Bioprocess Scale-up. Advances in Biochemical Engineering/Biotechnology, January 2015. https://doi.org/10.1007/10spa
dc.relation.referencesYavari, M., Ebrahimi, S., Aghazadeh, V., & Ghashghaee, M. (2019). Kinetics of different bioreactor systems with Acidithiobacillus ferrooxidans for ferrous iron oxidation. Reaction Kinetics, Mechanisms and Catalysis, 128(2), 611–627. https://doi.org/10.1007/s11144-019-01660-3spa
dc.relation.referencesZahradník, J., Mann, R., Fialová, M., Vlaev, D., Vlaev, S. D., Lossev, V., & Seichter, P. (2001). A networks-of-zones analysis of mixing and mass transfer in three industrial bioreactors. Chemical Engineering Science, 56(2), 485–492. https://doi.org/10.1016/S0009-2509(00)00252-9spa
dc.relation.referencesZhong, J. J. (2011). Bioreactor Engineering. In Comprehensive Biotechnology, Second Edition (Second Edi, Vol. 2). Elsevier B.V. https://doi.org/10.1016/B978-0-08- 088504-9.00097-0spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-NoComercial 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/spa
dc.subject.ddc620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingenieríaspa
dc.subject.lembBioreactores
dc.subject.lembControl de procesos biotecnológicos
dc.subject.proposalModelamiento multiescalaspa
dc.subject.proposalModelo de compartimentosspa
dc.subject.proposalModelo cinéticospa
dc.subject.proposalCarbohidratos de reservaspa
dc.subject.proposalSaccharomyces cerevisiaeother
dc.subject.proposalMetabolismo de carbono centralspa
dc.subject.proposalMultiscale modelingeng
dc.subject.proposalCompartment modeleng
dc.subject.proposalKinetic modeleng
dc.subject.proposalStorage carbohydrateseng
dc.subject.proposalCentral carbon metabolismeng
dc.titleEvaluación del impacto de gradientes de concentración sobre el metabolismo del carbono central microbiano mediante un enfoque de modelamiento multiescalaspa
dc.title.translatedEvaluation of the impact of concentration gradients on the microbial carbon central metabolism by a multiscale modelling approacheng
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TMspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audience.professionaldevelopmentEstudiantesspa
dcterms.audience.professionaldevelopmentInvestigadoresspa
dcterms.audience.professionaldevelopmentMaestrosspa
dcterms.audience.professionaldevelopmentPúblico generalspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

Archivos

Bloque original

Mostrando 1 - 1 de 1
Cargando...
Miniatura
Nombre:
1036954383.2022.pdf
Tamaño:
5.72 MB
Formato:
Adobe Portable Document Format
Descripción:
Tesis de Maestría en Ingeniería - Ingeniería Química

Bloque de licencias

Mostrando 1 - 1 de 1
Cargando...
Miniatura
Nombre:
license.txt
Tamaño:
5.74 KB
Formato:
Item-specific license agreed upon to submission
Descripción: