Optimization and modeling of recombinant protein production in Pichia pastoris

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Mollerup, Filip
dc.contributor.advisor Usvalampi, Anne
dc.contributor.author Fita Pizarro, Laia
dc.date.accessioned 2016-06-17T12:36:42Z
dc.date.available 2016-06-17T12:36:42Z
dc.date.issued 2016-06-14
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/20934
dc.description.abstract Recombinant proteins, produced in heterologous expression systems, have currently multiple industrial applications and potential to further improve the chemical industry. However, their main drawback is the high production costs, and thus efficient, cost-effective and well-controlled production processes are of importance to the bioeconomy. Some novel biocatalyst, used for the development of sustainable materials, are yet to be expressed with a significant yield and efficiency thus require further development of the production processes. Accordingly, the aim of this thesis was to optimize the expression of recombinant proteins in the methylotrophic yeast Pichia pastoris through optimization of expression conditions and optimizing substrate feed-rate in bioreactor fed-batch cultivations. This thesis features a comprehensive literature review of the yeast Pichia pastoris and compares Prokaryotic to Eukaryotic expression systems in terms of their cell structures. Furthermore, the bioreactor processes and the cultivation parameters are presented. Additionally, fed-batch cultivation strategies are also explained. The experimental part of this thesis examines the expression of a member of the carbohydrate active enzyme family AA5 from the fungus Penicillium Wisconsin in Pichia pastoris using a bioreactor system. Initially, the best expression strain was identified along with the best temperature and pH conditions. The main part focused on the development of new strategies for methanol feeding in bioreactor cultivation process of the chosen expression strain. Subsequently, the two best strategies were tested for the expression of the α-fucosidase SMDfucA in P. pastoris for comparison with another fungal gene. The recombinant protein expression in Pichia pastoris was simulated using commonly verified and published algorithms from the literature (Carlsson, 2012) (Kargi & Shuler, 2008) (Maurer, Kühleitner, Gasser, & Mattanovich, 2006). Simulation work was performed on the Matlab™ software and parameters and initial conditions were based on the experimental strategies. Although the simulation gave coherent results, the model has certain limitations as the methanol feed rate in the model only accounted for a constant feed rate. Finally, the two best strategies were: modified Invitrogen guidelines and constant profile with a feed rate of (3.6 ml MeOH·h-1) because of their better performance between activity and cellular concentration. Moreover, these two strategies were the ones yielding the highest specific growth rate, extracellular activity and cellular productivity. With another carbohydrate active enzyme, the alpha-fucosidase, using the same P. pastoris SMD1168H strain, the modified Invitrogen guidelines was selected as the best strategy because in both cases the activity and soluble protein analysis gave higher values than with the other strategies tested. en
dc.format.extent 63 + 10
dc.language.iso en en
dc.title Optimization and modeling of recombinant protein production in Pichia pastoris en
dc.type G2 Pro gradu, diplomityö fi
dc.contributor.school Kemian tekniikan korkeakoulu fi
dc.subject.keyword Pichia pastoris en
dc.subject.keyword protein production en
dc.subject.keyword yeast fermentation en
dc.subject.keyword fed-batch en
dc.subject.keyword modeling en
dc.identifier.urn URN:NBN:fi:aalto-201606172542
dc.programme.major Biotechnology and Food Technology fi
dc.programme.mcode KE 3002 fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Diplomityö fi
dc.contributor.supervisor Frey, Alexander
dc.programme Master's Programme in Chemical Technology fi
dc.location PK fi


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