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Ministerio de Universidades - Gobierno de España

Título: DEVELOPING STRATEGIES FOR SYSTEMS METABOLIC ENGINEERING OF PICHIA PASTORIS
Autor: Tomàs Gamisans, Màrius
Universidad: Universidad Autónoma de Barcelona
Departamento: Enginyeria Química, Biològica i Ambiental
Fecha de Lectura: 22/09/2017
Mención Europeo / Mención Internacional: Concedido
Programa de doctorado: Programa Oficial de Doctorado en Biotecnología
Dirección:
- Albiol Sala, Joan (DIRECTOR)
- Ferrer Alegre, Pau (DIRECTOR)
Tribunal:
- Solà, Carles (PRESIDENTE)
- de Almeida Pereira da Rocha, Isabel Cristina (SECRETARIO)
- Wahl, Aljoscha (VOCAL)
Descriptores:
- BIOTECNOLOGIA
- INGENIERIA BIOQUIMICA
- METABOLISMO MICROBIANO
- BIOQUIMICA
Localización: UNIVERSITAT AUTONOMA DE BARCELONA
Marcador: https://www.educacion.gob.es/teseo/mostrarRef.do?ref=1493319Añadir a favoritos.
Resumen:
Pichia pastoris has become one of the most extensively used cell platforms for recombinant protein and high-value added metabolite production. In the past recent years, important breakthroughs in the systems-level quantitative analysis of its physiology have been achieved. This wealth of information has allowed the development of genome-scale metabolic models, which make new approaches possible for host cell and bioprocess engineering. Previous to this work, three different genome-scale metabolic models were available for P. pastoris. Nevertheless, these models showed some inconsistencies regarding certain pathways, including the terminology for both metabolites and reactions and annotations. Furthermore, some P. pastoris specific metabolic traits were misrepresented. Therefore, in this study, a consensus genome-scale metabolic model has been developed, thereby integrating the prior models. In addition, a comprehensive revision of metabolic pathways was performed and several pathways were curated and updated according to the currently available literature. As a result, the new model, iMT1026, is able to more accurately reproduce experimental growth parameters using glucose as carbon source and different oxygen availability conditions. In order to expand the capabilities of the consensus model, new physiological datasets of cells growing on two of the most relevant substrates for this cell factory were generated. Specifically, a series of chemostat cultivations were performed to characterise the physiologic profile and macromolecular biomass composition of P. pastoris growing on glycerol and methanol as sole carbon sources. Also, macromolecular biomass composition was analysed, allowing us to incorporate new carbon-source specific stoichiometric biomass equations into the model, as well as to estimate the associated energetic parameters. Overall, a new version of the model (iMT1026 v3.0) was validated for these growing conditions. In addition to the validation of iMT1026 v3.0 for a wider range of carbon sources and growth conditions, we have further tested its performance in two different applications, namely, the generation of reduced metabolic models suitable for 13C-based metabolic flux analysis and, assisting the interpretation of physiological growth parameters of redox-cofactor engineered strains. In particular, the genome-scale metabolic model has been reduced into a core model and used for 13C-based metabolic flux analysis of cells growing on glycerol at different growth rates. To our knowledge, this is the first study ever reported of 13C-MFA using glycerol as sole carbon source. Notably, flux analyses are highly consistent with pioneering 13C-based metabolic profiling studies of P. pastoris growing on glycerol. iMT1026 v3.0 was also employed for assisting the interpretation of the physiological profiles obtained for redox-cofactor engineered strains. A recombinant strain producing an antibody fragment was engineered to overexpress a heterologous NADH kinase, aiming at increased NADPH regeneration rates. Notably, the redox-engineered strains showed an increase in recombinant protein production and altered macroscopic growing profiles. In silico analysis of the impact of NADH kinase overexpression using the iMT1026 model predicted possible metabolic changes associated to the redox cofactor imbalance that were in agreement with the observed physiological phenotypes. Overall, a refined tool for systems metabolic engineering is provided in the present study. Moreover, such tool has been validated for a wide range of environmental conditions and employed in two different applications, confirming its reliability.

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