Ethanol fed-batch bioreactor operation to enhance therapeutic protein production in Pichia pastoris under hybrid-architectured ADH2 promoter

Continuous Process Verification 4.0 application in upstream: adaptiveness implementation managed by AI in the hypoxic bioprocess of the Pichia pastoris cell factory

The experimental approach developed in this research demonstrated how the cloud, the Internet of Things (IoT), edge computing, and Artificial Intelligence (AI), considered key technologies in Industry 4.0, provide the expected horizon for adaptive vision in Continued Process Verification (CPV), the final stage of Process Validation (PV). Pichia pastoris producing Candida rugosa lipase 1 under the regulation of the constitutive GAP promoter was selected as an experimental bioprocess. The bioprocess worked under hypoxic conditions in carbon-limited fed-batch cultures through a physiological control based on the respiratory quotient (RQ). In this novel bioprocess, a digital twin (DT) was built and successfully tested. The implementation of online sensors worked as a bridge between the microorganism and AI models, to provide predictions from the edge and the cloud. AI models emulated the metabolism of Pichia based on critical process parameters and actionable factors to achieve the expected quality attributes. This innovative AI-aided Adaptive-Proportional Control strategy (AI-APC) improved the reproducibility comparing to a Manual-Heuristic Control strategy (MHC), showing better performance than the Boolean-Logic-Controller (BLC) tested. The accuracy, indicated by the Mean Relative Error (MRE), was for the AI-APC lower than 4%, better than the obtained for MHC (10%) and BLC (5%). Moreover, in terms of precision, the same trend was observed when comparing the Root Mean Square Deviation (RMSD) values, becoming lower as the complexity of the controller increases. The successful automatic real time control of the bioprocess orchestrated by AI models proved the 4.0 capabilities brought by the adaptive concept and its validity in biopharmaceutical upstream operations.

Innovative Bioprocess Strategies Combining Physiological Control and Strain Engineering of Pichia pastoris to Improve Recombinant Protein Production

The combination of strain and bioprocess engineering strategies should be considered to obtain the highest levels of recombinant protein production (RPP) while assuring product quality and process reproducibility of heterologous products. In this work, two complementary approaches were investigated to improve bioprocess efficiency based on the yeast P. pastoris. Firstly, the performance of two Candida rugosa lipase 1 producer clones with different gene dosage under the regulation of the constitutive P_GAP were compared in chemostat cultures with different oxygen-limiting conditions. Secondly, hypoxic conditions in carbon-limited fed-batch cultures were applied by means of a physiological control based on the respiratory quotient (RQ). Stirring rate was selected to maintain RQ between 1.4 and 1.6, since it was found to be the most favorable in chemostat. As the major outcome, between 2-fold and 4-fold higher specific production rate (q_P) values were observed when comparing multicopy clone (MCC) and single-copy clone (SCC), both in chemostat and fed-batch. Additionally, when applying oxygen limitation, between 1.5-fold and 3-fold higher q_P values were obtained compared with normoxic conditions. Thus, notable increases of up to 9-fold in the production rates were reached. Furthermore, transcriptional analysis of certain key genes related to RPP and central carbon metabolism were performed. Results seem to indicate the presence of a limitation in post-transcriptional protein processing steps and a possible transcription attenuation of the target gene in the strains with high gene dosage. The entire approach, including both strain and bioprocess engineering, represents a relevant novelty involving physiological control in Pichia cell factory and is of crucial interest in bioprocess optimization, boosting RPP, allowing bioproducts to be economically competitive in the market, and helping develop the bioeconomy.

Recombinant protein production in Pichia pastoris: From transcriptionally redesigned strains to bioprocess optimization and metabolic modelling

Pichia pastoris is one of the most widely used host for the production of recombinant proteins. Expression systems that rely mostly on promoters from genes encoding alcohol oxidase 1 or glyceraldehyde-3-phosphate dehydrogenase have been developed together with related bioreactor operation strategies based on carbon sources such as methanol, glycerol, or glucose. Although, these processes are relatively efficient and easy to use, there have been notable improvements over the last twenty years to better control gene expression from these promoters and their engineered variants. Methanol-free and more efficient protein production platforms have been developed by engineering promoters and transcription factors. The production window of P. pastoris has been also extended by using alternative feedstocks including ethanol, lactic acid, mannitol, sorbitol, sucrose, xylose, gluconate, formate, or rhamnose. Herein, the specific aspects that are emerging as key parameters for recombinant protein synthesis are discussed. For this purpose, a holistic approach has been considered to scrutinize protein production processes from strain design to bioprocess optimization, particularly focusing on promoter engineering, transcriptional circuitry redesign. This review also considers the optimization of bioprocess based on alternative carbon sources and derived co-feeding strategies. Optimization strategies for recombinant protein synthesis through metabolic modelling are also discussed.