Pichia pastoris is a preferred host for heterologous protein production. Expression cassettes are usually integrated into the genome of this methylotrophic yeast. This manuscript describes a method for fast and reliable gene copy number determinations for P. pastoris expression strains. We believe that gene copy number determinations are important for all researchers working with P. pastoris and also many other research groups using similar gene integration techniques for the transformation of other yeasts. The described method uses real-time PCR to quantify the integrated expression cassettes. Similar methods were employed previously for other host systems such as animal and plant cells but no such method comparing different detection methods and describing details for yeast analysis by quantitative PCR is known to us, especially for methylotrophic yeasts such as P. pastoris. Neglecting gene copy numbers can easily lead to false interpretations of experimental results from codon optimization or promoter studies and co-expression of helper proteins as demonstrated in an application example, which is also described here.
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.
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