Aryl-alcohol oxidase (AAO) plays a fundamental role in the fungal ligninolytic secretome, acting as a supplier of H O . Despite its highly selective mechanism of action, the presence of this flavooxidase in different biotechnological settings has hitherto been hampered by the lack of appropriate heterologous expression systems. We recently described the functional expression of the AAO from Pleurotus eryngii in Saccharomyces cerevisiae by fusing a chimeric signal peptide (preαproK) and applying structure-guided evolution. Here, we have obtained an AAO secretion variant that is readily expressed in S. cerevisiae and overproduced in Pichia pastoris. First, the functional expression of AAO in S. cerevisiae was enhanced through the in vivo shuffling of a panel of secretion variants, followed by the focused evolution of the preαproK peptide. The outcome of this evolutionary campaign-an expression variant that accumulated 4 mutations in the chimeric signal peptide, plus two mutations in the mature protein- showed 350-fold improved secretion (4.5 mg/L) and was stable. This secretion mutant was cloned into P. pastoris and fermented in a fed-batch bioreactor to enhance production to 25 mg/L. While both recombinant AAO from S. cerevisiae and P. pastoris were subjected to the same N-terminal processing and had a similar pH activity profile, they differed in their kinetic parameters and thermostability. The strong glycosylation observed in the evolved AAO from S. cerevisiae underpinned this effect, since when the mutant was produced in the glycosylation-deficient S. cerevisiae strain Δkre2, its kinetic parameters and thermostability were comparable to its poorly glycosylated P. pastoris recombinant counterpart.
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.
BACKGROUND To improve the efficiency of a bioprocess, key parameters, such as yield, titer and productivity, must be considered. They are mainly dependent on the specific rates for product (qP) and cell growth (μ), and their correlation determines the most suitable feeding polices that should be applied. RESULTS The mathematical description of the Pichia pastoris (Komagataella spp) PAOX1‐based system (Mut+) expressing recombinant Rhizopus oryzae lipase (ROL), which includes cell growth, substrate consumption and product formation kinetics, was used to define the optimal profiles regarding methanol feeding‐rate (F), residual methanol concentration (S) and specific growth rate (μ). Optimal trajectories obtained using numerical optimization and algorithms based on S‐profile determination were first applied to manage the multiplicity of S‐states with both μ and qP. Once the S‐profile was determined, the F and μ profiles were obtained in a straightforward manner from mass balances and growth kinetics. From experimental results, the bioprocess efficiency improvement was confirmed in terms of a 2.2‐fold higher final titer and 3.4‐fold higher productivity compared with the best standard pre‐programmed exponential substrate feeding strategy. Additionally, 1.2‐fold higher productivity and 1.1‐fold higher final titer relative to the most promising feedback control of the methanol concentration strategy were obtained. CONCLUSION The whole model‐based approach was established as a versatile and simple platform, which would then be transferable to alternative modes of operation and even to produce other proteins of interest. © 2018 Society of Chemical Industry
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