Comprehensive clone screening and evaluation of fed-batch strategies in a microbioreactor and lab scale stirred tank bioreactor system: application on Pichia pastoris producing Rhizopus oryzae lipase

Microbial Cell Factories

Research

José Manuel Barrigón¹  Xavier Ponte¹  Pau Ferrer¹  Núria Adelantado¹  Francisco Valero¹  Astrid Hörmann²  Johannes Hemmerich³  Frank Kensy³ 

[1] Department of Chemical Engineering, Escola d’Enginyeria, Universitat Autònoma de Barcelona, Bellaterra, 08193, Barcelona, Spain;Department of Chemical Engineering, Escola d’Enginyeria, Universitat Autònoma de Barcelona, Bellaterra, 08193, Barcelona, Spain;Centre for Genomic Regulation, Barcelona, Spain;m2p-labs GmbH, Arnold-Sommerfeld-Ring 2, 52499, Baesweiler, Germany;

关键词: Pichia pastoris;    Clone screening;    Rhizopus oryzae;    Fed-batch fermentation;    Feeding strategies;    Microbioreactor;    Scale-up;    Bioprocess development;   

DOI  :  10.1186/1475-2859-13-36

 received in 2013-10-18, accepted in 2014-02-27,  发布年份 2014

来源: Springer

【 摘 要 】

BackgroundIn Pichia pastoris bioprocess engineering, classic approaches for clone selection and bioprocess optimization at small/micro scale using the promoter of the alcohol oxidase 1 gene (PAOX1), induced by methanol, present low reproducibility leading to high time and resource consumption.ResultsAn automated microfermentation platform (RoboLector) was successfully tested to overcome the chronic problems of clone selection and optimization of fed-batch strategies. Different clones from Mut+P. pastoris phenotype strains expressing heterologous Rhizopus oryzae lipase (ROL), including a subset also overexpressing the transcription factor HAC1, were tested to select the most promising clones.The RoboLector showed high performance for the selection and optimization of cultivation media with minimal cost and time. Syn6 medium was better than conventional YNB medium in terms of production of heterologous protein.The RoboLector microbioreactor was also tested for different fed-batch strategies with three clones producing different lipase levels. Two mixed substrates fed-batch strategies were evaluated. The first strategy was the enzymatic release of glucose from a soluble glucose polymer by a glucosidase, and methanol addition every 24 hours. The second strategy used glycerol as co-substrate jointly with methanol at two different feeding rates. The implementation of these simple fed-batch strategies increased the levels of lipolytic activity 80-fold compared to classical batch strategies used in clone selection. Thus, these strategies minimize the risk of errors in the clone selection and increase the detection level of the desired product.Finally, the performance of two fed-batch strategies was compared for lipase production between the RoboLector microbioreactor and 5 liter stirred tank bioreactor for three selected clones. In both scales, the same clone ranking was achieved.ConclusionThe RoboLector showed excellent performance in clone selection of P. pastoris Mut+ phenotype. The use of fed-batch strategies using mixed substrate feeds resulted in increased biomass and lipolytic activity. The automated processing of fed-batch strategies by the RoboLector considerably facilitates the operation of fermentation processes, while reducing error-prone clone selection by increasing product titers.The scale-up from microbioreactor to lab scale stirred tank bioreactor showed an excellent correlation, validating the use of microbioreactor as a powerful tool for evaluating fed-batch operational strategies.

【 授权许可】

Unknown   
© Hemmerich et al.; licensee BioMed Central Ltd. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.