Upstream processes are rather complex and the productivity of cells in suited cultivation conditions is hard to predict. The method of choice for creating a large pool of data is performing high-throughput cultivation screenings in micro-scale format. For many downstream processes, in contrast, various predictive in silico models have developed, leading to a reduction in time and material costs. Here, we describe an integrated optimization approach for bioprocess development based on high-throughput micro-scale cultivation experiments and feed stock characterization by chromatography modelling. The overall optimized system must not necessarily be the one yielding in highest product titers but the one resulting in an overall superior process performance in up- and downstream. The methodology is presented in a case study for the Cherry-tagged enzyme Glutathione-S-Transferase from Escherichia coli. The Cherry-TagTM (Delphi Genetics, Belgium), which can be fused to any target protein, makes direct product analytics accessible by VIS absorption measurements. High-throughput cultivations were carried out in 48-well format in a BioLector micro-cultivation system (m2p-Labs, Germany). The product titers were determined by Cherry-TagTM specific absorption measurements and validated by capillary gel electrophoresis. The downstream process optimization and feed stock characterization for a set of high-yielding, randomly picked upstream conditions, was performed in silico using a chromatography modelling software developed in-house (ChromX). The suggested in silico optimized operational modes for product capturing were subsequently validated. The overall best system was chosen based on a combination of excellent up- and downstream performance.

Integrated bioprocess development based on microscale cultivations and feed stock characterization by chromatography modeling

249th National Meeting (2015)

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