Diseño in silico de una plataforma biológica para la producción de etilenglicol a partir de glicerol crudo mediante herramientas de ingeniería metabólica y principios de la termodinámica
ilustraciones, diagramas
- Autores:
-
Cano Zapata, Edgar Alejandro
- Tipo de recurso:
- Fecha de publicación:
- 2022
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/84239
- Palabra clave:
- 540 - Química y ciencias afines::547 - Química orgánica
Synthetic products
Productos sintéticos
Análisis de balance de flujos
Etilenglicol
Glicerol
Metanol
Modelo metabólico
Termodinámica
Flux balance analysis
Ethylene glycol
Glycerol
Methanol
Metabolic model
Thermodynamics
- Rights
- openAccess
- License
- Atribución-SinDerivadas 4.0 Internacional
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Diseño in silico de una plataforma biológica para la producción de etilenglicol a partir de glicerol crudo mediante herramientas de ingeniería metabólica y principios de la termodinámica |
| dc.title.translated.eng.fl_str_mv |
In silico design of a biological platform to produce Ethylene Glycol from crude Glycerol using tools of the metabolic engineering and thermodynamics |
| title |
Diseño in silico de una plataforma biológica para la producción de etilenglicol a partir de glicerol crudo mediante herramientas de ingeniería metabólica y principios de la termodinámica |
| spellingShingle |
Diseño in silico de una plataforma biológica para la producción de etilenglicol a partir de glicerol crudo mediante herramientas de ingeniería metabólica y principios de la termodinámica 540 - Química y ciencias afines::547 - Química orgánica Synthetic products Productos sintéticos Análisis de balance de flujos Etilenglicol Glicerol Metanol Modelo metabólico Termodinámica Flux balance analysis Ethylene glycol Glycerol Methanol Metabolic model Thermodynamics |
| title_short |
Diseño in silico de una plataforma biológica para la producción de etilenglicol a partir de glicerol crudo mediante herramientas de ingeniería metabólica y principios de la termodinámica |
| title_full |
Diseño in silico de una plataforma biológica para la producción de etilenglicol a partir de glicerol crudo mediante herramientas de ingeniería metabólica y principios de la termodinámica |
| title_fullStr |
Diseño in silico de una plataforma biológica para la producción de etilenglicol a partir de glicerol crudo mediante herramientas de ingeniería metabólica y principios de la termodinámica |
| title_full_unstemmed |
Diseño in silico de una plataforma biológica para la producción de etilenglicol a partir de glicerol crudo mediante herramientas de ingeniería metabólica y principios de la termodinámica |
| title_sort |
Diseño in silico de una plataforma biológica para la producción de etilenglicol a partir de glicerol crudo mediante herramientas de ingeniería metabólica y principios de la termodinámica |
| dc.creator.fl_str_mv |
Cano Zapata, Edgar Alejandro |
| dc.contributor.advisor.none.fl_str_mv |
Suárez Méndez, Camilo Alberto |
| dc.contributor.author.none.fl_str_mv |
Cano Zapata, Edgar Alejandro |
| dc.contributor.researchgroup.spa.fl_str_mv |
Bioprocesos y Flujos Reactivos |
| dc.contributor.orcid.spa.fl_str_mv |
Suárez Méndez, Camilo Alberto [0000-0002-5345-9662] |
| dc.subject.ddc.spa.fl_str_mv |
540 - Química y ciencias afines::547 - Química orgánica |
| topic |
540 - Química y ciencias afines::547 - Química orgánica Synthetic products Productos sintéticos Análisis de balance de flujos Etilenglicol Glicerol Metanol Modelo metabólico Termodinámica Flux balance analysis Ethylene glycol Glycerol Methanol Metabolic model Thermodynamics |
| dc.subject.lemb.eng.fl_str_mv |
Synthetic products |
| dc.subject.lemb.spa.fl_str_mv |
Productos sintéticos |
| dc.subject.proposal.spa.fl_str_mv |
Análisis de balance de flujos Etilenglicol Glicerol Metanol Modelo metabólico Termodinámica |
| dc.subject.proposal.eng.fl_str_mv |
Flux balance analysis Ethylene glycol Glycerol Methanol Metabolic model Thermodynamics |
| description |
ilustraciones, diagramas |
| publishDate |
2022 |
| dc.date.issued.none.fl_str_mv |
2022 |
| dc.date.accessioned.none.fl_str_mv |
2023-07-21T14:45:23Z |
| dc.date.available.none.fl_str_mv |
2023-07-21T14:45:23Z |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/masterThesis |
| dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
| dc.type.content.spa.fl_str_mv |
Text |
| dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/TM |
| status_str |
acceptedVersion |
| dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/84239 |
| dc.identifier.instname.spa.fl_str_mv |
Universidad Nacional de Colombia |
| dc.identifier.reponame.spa.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
| dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.unal.edu.co/ |
| url |
https://repositorio.unal.edu.co/handle/unal/84239 https://repositorio.unal.edu.co/ |
| identifier_str_mv |
Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
| dc.language.iso.spa.fl_str_mv |
spa |
| language |
spa |
| dc.relation.indexed.spa.fl_str_mv |
RedCol LaReferencia |
| dc.relation.references.spa.fl_str_mv |
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Chen et al., “Synthetic methanol auxotrophy of Escherichia coli for methanoldependent growth and production,” Metab Eng, vol. 49, no. June, pp. 257–266, 2018, doi: 10.1016/j.ymben.2018.08.010 B. M. Woolston, J. R. King, M. Reiter, B. van Hove, and G. Stephanopoulos, “Improving formaldehyde consumption drives methanol assimilation in engineered E. coli,” Nat Commun, vol. 9, no. 1, 2018, doi: 10.1038/s41467-018-04795-4. Z. Dai et al., “Metabolic construction strategies for direct methanol utilization in Saccharomyces cerevisiae,” Bioresour Technol, 2017, doi: 10.1016/j.biortech.2017.05.100. H. O. Kammen and R. Koo, “Phosphopentomutases,” Journal of Biological Chemistry, vol. 244, no. 18, pp. 4888–4893, 1969, doi: 10.1016/s0021- 9258(18)94286-9. K. Hammer-Jespersen and A. Munch-Petersem, “Phosphodeoxyribomutase from Escharichia coli.,” Eur J Biochem, vol. 17, pp. 9–25, 2019. R. K. Murray, D. A. Bender, K. M. Botham, P. J. Kennelly, V. W. Rodwell, and P. A. Weil, Harper. Bioquímica ilustrada. Mc Graw Hill Education, 2010. A. Kümmel, S. Panke, and M. Heinemann, “Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data,” Mol Syst Biol, vol. 2, pp. 1–10, 2006, doi: 10.1038/msb4100074. |
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Atribución-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Suárez Méndez, Camilo Alberto997598635d63c1552bb6d43d1091be66Cano Zapata, Edgar Alejandro55e19f70ca507c7e00aa3e0f339dba49Bioprocesos y Flujos ReactivosSuárez Méndez, Camilo Alberto [0000-0002-5345-9662]2023-07-21T14:45:23Z2023-07-21T14:45:23Z2022https://repositorio.unal.edu.co/handle/unal/84239Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramasEl objetivo del presente estudio es diseñar una plataforma biológica in silico para la producción de etilenglicol a partir de glicerol crudo a través de un análisis termodinámico, el cual permitirá establecer la máxima producción teórica que sería posible obtener, y herramientas de la ingeniería metabólica, las cuales permiten evaluar e implementar las diferentes rutas metabólicas y genes heterólogos relacionados para llevar a cabo este proceso. Inicialmente se construyeron modelos de caja negra que representaran la producción biológica de etilenglicol a partir de las principales fuentes de carbono que se encuentran en el glicerol crudo, glicerol y metanol. Estos modelos se construyeron primero para cada sustrato por separado, considerando diferentes aceptores de electrones incluido el etilenglicol. Debido a que se tiene un interés en realizar este proceso utilizando ambos sustratos al mismo tiempo, se resalta la importancia de implementar una metodología que permita construir modelos de caja negra para múltiples sustratos. Más adelante, se construyeron diferentes modelos metabólicos para tres diferentes microorganismos (E. coli, S. cerevisiae, P. pastoris) con el fin de representar la producción de etilenglicol a través de diferentes rutas de biosíntesis (SDP y P1PDP), y las diferentes rutas de asimilación de glicerol y metanol. Estos modelos se utilizaron para estudiar el rendimiento por mol de carbono utilizado y la cantidad de intermediarios energéticos (ATP, NADH, NADPH) generados por mol de etilenglicol producido a partir de diferentes proporciones de glicerol y metanol. Finalmente, se selecciona uno de estos modelos para estudiar el efecto de la velocidad de crecimiento en la síntesis de etilenglicol, y cómo las condiciones intracelulares afectan la viabilidad termodinámica de las rutas de biosíntesis consideradas. En el presente estudio se observó cómo el etilenglicol no resulta adecuado cómo aceptor de electrones en el catabolismo debido la baja cantidad de energía libre obtenida a partir de cada sustrato. Por lo tanto, se consideró el uso de otros aceptores de electrones y se plantean otras reacciones catabólicas alternas que permitan la producción de etilenglicol a partir de un consumo parcial de oxígeno para la obtención de energía. Posteriormente, se presenta una propuesta preliminar para la construcción de un modelo de caja negra para un proceso con múltiples sustratos partiendo de una metodología ya propuesta para un único sustrato. En esta se resalta la presencia de nuevos parámetros que consideran el efecto de la presencia de múltiples sustratos en los diferentes procesos celulares. Estos, sin embargo, quedan pendientes por determinar dado a que no se logró establecer una correlación matemática que permitiera calcularlos. Por otra parte, se observó a partir del análisis de los modelos metabólicos cómo el modelo para E. coli proporciona el mejor escenario para la obtención de etilenglicol dado el mayor rendimiento obtenido y a la cantidad de intermediarios energéticos generados durante el proceso. Para este modelo, se encontró cómo la producción de etilenglicol se da principalmente a bajas velocidades de crecimiento de la biomasa, demostrando que ambos procesos compiten directamente por el flujo de carbono que entra al metabolismo. Finalmente, se encontró que algunas reacciones dentro de las rutas de síntesis de etilenglicol son sensibles a las variaciones de concentración intracelulares, lo que provocaría la generación de cuellos de botella en el proceso disminuyendo el rendimiento en la producción de etilenglicol. Mediante estos análisis se pudo validar que la producción biológica de etilenglicol es posible a partir de las principales fuentes de carbono del glicerol crudo. Para llevar a cabo este proceso, se deben cumplir determinadas condiciones a nivel del metabolismo para dirigir el flujo de carbono hacia el producto de interés y hacer el factible el proceso. Sin embargo, es necesario seguir realizando estudios posteriores para determinar a profundidad las modificaciones a nivel genético que permitan acoplar la producción de biomasa con la síntesis de etilenglicol, implementar otras rutas de síntesis alternas, y finalizar la construcción del modelo de caja negra para múltiples sustratos para evaluar con más detalle que tiene la presencia de cada uno de estos en los diferentes procesos celulares de interés. (Texto tomado de la fuente)This study aims at designing an in silico biological platform to produce ethylene glycol from crude glycerol through a thermodynamic analysis to determine the maximum theoretical yield, and the use of metabolic engineering approaches to assess and implementing different metabolic pathways and the associated heterologous genes to carry out this process. Initially, black-box models were constructed to represent the biological production of ethylene glycol from primary carbon sources present in crude glycerol, glycerol, and methanol. These models were first built separately for each substrate while considering different electron acceptors including ethylene glycol. The significance of establishing a methodology that permits the construction of black box models for multiple substrates is highlighted because there is an interest in carrying out this procedure using both substrates at the same time. To depict the formation of ethylene glycol through several biosynthetic routes (SDP and P1PDP), as well as the various routes of glycerol and methanol assimilation, several metabolic models were created for three distinct microorganisms (E. coli, S. cerevisiae, and P. pastoris). Here, a study was performed by using these models to estimate the yield per mole of carbon consumed and the quantity of energy intermediates (ATP, NADH, and NADPH) generated per mole of produced ethylene glycol under different glycerol to methanol ratios. Finally, one of these models is chosen to investigate the impact of growth rate on the production of ethylene glycol. Likewise, the impact of intracellular conditions on the thermodynamic feasibility was assessed for the biosynthetic pathways under consideration. In the present study, it was observed how ethylene glycol is not suitable as an electron acceptor for catabolism due to the low amount of free energy obtained. Therefore, the use of alternative electron acceptors was considered, and alternative catabolic reactions allowing the production of ethylene glycol from a partial consumption of oxygen for energy production are proposed. Following that, a preliminary proposal is suggested for the construction of a black-box model for a process using multiple substrates based on a sound methodology already proposed for a single substrate. Emphasis is made on the use of new parameters considering the effect of each substrate on the different cellular processes. However, these parameters have yet to be determined because a mathematical correlation to calculate them could not yet be developed here. The analysis of the metabolic models, on the other hand, revealed that the model for E. coli provides the best scenario for obtaining ethylene glycol due to a higher yield obtained and the amount of energy intermediates generated during the process. It was found that ethylene glycol production occurred primarily at low biomass growth rates in this model, demonstrating that both processes compete directly for the carbon flow into the metabolism. Finally, it was found that some reactions within the pathways for ethylene glycol synthesis are sensitive to intracellular concentration variations, resulting in the development of bottlenecks in the process as well as a reduction in the ethylene glycol production yield. These analyses showed that biological production of ethylene glycol is possible from the main carbon sources derived from crude glycerol. Certain conditions must be met at the metabolic level to redirect the carbon flow to the product of interest, and to make the process feasible. However, more research is still needed to determine in depth the required genetic modifications to couple biomass production with ethylene glycol synthesis, to implement other alternative synthesis routes, and to complete the construction of the blackbox model for multiple substrates in order to evaluate in greater detail the effects of each of these substrates on the various cellular processes of interest.MaestríaDiseño Racional e Intensificación de BioprocesosÁrea curricular de Ingeniería Química e Ingeniería de Petróleosxxiv, 104 páginasapplication/pdfspa540 - Química y ciencias afines::547 - Química orgánicaSynthetic productsProductos sintéticosAnálisis de balance de flujosEtilenglicolGlicerolMetanolModelo metabólicoTermodinámicaFlux balance analysisEthylene glycolGlycerolMethanolMetabolic modelThermodynamicsDiseño in silico de una plataforma biológica para la producción de etilenglicol a partir de glicerol crudo mediante herramientas de ingeniería metabólica y principios de la termodinámicaIn silico design of a biological platform to produce Ethylene Glycol from crude Glycerol using tools of the metabolic engineering and thermodynamicsTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMMedellín - Minas - Maestría en Ingeniería - Ingeniería QuímicaFacultad de MinasMedellín, ColombiaUniversidad Nacional de Colombia - Sede MedellínRedColLaReferenciaJ. 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Heinemann, “Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data,” Mol Syst Biol, vol. 2, pp. 1–10, 2006, doi: 10.1038/msb4100074.EstudiantesInvestigadoresMaestrosLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/84239/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL1152703489.2022.pdf1152703489.2022.pdfTesis de Maestría en Ingeniería - Ingeniería Químicaapplication/pdf1896206https://repositorio.unal.edu.co/bitstream/unal/84239/2/1152703489.2022.pdfff23e92b3033116caef9058c38f0e8f4MD52THUMBNAIL1152703489.2022.pdf.jpg1152703489.2022.pdf.jpgGenerated Thumbnailimage/jpeg6036https://repositorio.unal.edu.co/bitstream/unal/84239/3/1152703489.2022.pdf.jpga792d517a6a9bf016a43459396f719bcMD53unal/84239oai:repositorio.unal.edu.co:unal/842392024-08-14 23:41:34.912Repositorio Institucional Universidad Nacional de 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