Abstract

The production of recombinant proteins in bioreactors requires real-time process monitoring and control to increase process efficiency and to meet the requirements for a comprehensive audit trail. The combination of optical near-infrared turbidity sensors and dielectric spectroscopy provides diverse system information because different measurement principles are exploited. We used this combination of techniques to monitor and control the growth and protein production of stably transformed Drosophila melanogaster S2 cells expressing antimicrobial proteins. The in situ monitoring system was suitable in batch, fed-batch and perfusion modes, and was particularly useful for the online determination of cell concentration, specific growth rate (µ) and cell viability. These data were used to pinpoint the optimal timing of the key transitional events (induction and harvest) during batch and fed-batch cultivation, achieving a total protein yield of ~25 mg at the 1-L scale. During cultivation in perfusion mode, the OD880 signal was used to control the bleed line in order to maintain a constant cell concentration of 5 × 107 cells/mL, thus establishing a turbidostat/permittistat culture. With this setup, a five-fold increase in productivity was achieved and 130 mg of protein was recovered after 2 days of induced perfusion. Our results demonstrate that both sensors are suitable for advanced monitoring and integration into online control strategies.

Highlights

  • Sophisticated control strategies are needed to run bioprocesses within a specified operational window and to ensure system stability [1]

  • Calibration is generally required to relate a parameter of interest to the corresponding sensor output

  • 230 and sensorssensors confirmed their suitability for the monitoring monitoring rS2 cells

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Summary

Introduction

Sophisticated control strategies are needed to run bioprocesses within a specified operational window and to ensure system stability [1]. This includes the measurement and control of physicochemical parameters such as temperature, pH, dissolved oxygen, pressure and stirrer speed. A more detailed understanding of the process is necessary, combined with the ability to exert tighter control This requires the online acquisition of data beyond standard parameters, especially information about cell growth and physiological status. In this context, various direct and indirect measurement principles have been evaluated and commercialized

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