No abstract

This work proposes an innovative methodology to control high density fed-batch cultures of E. coli, based on measurements of the concentration of dissolved oxygen and on estimations of the cellular specific growth rate (µ), of the yield of biomass/limiting substrate (Y (xs)) and of the maintenance coefficient (m). The underlying idea is to allow cells to grow according to their metabolic capacity, without the constraints inherent to pre-set growth rates. Cellular concentration was assessed on-line through a capacitance probe. Three configurations of the control system were compared: (1) pre-set value for the three control parameters; (2) continuously updating µ; (3) updating µ, Y (xs) and m. Implementation of an efficient noise filter for the signal of the capacitance probe was essential for a good performance of the control system. The third control strategy, within the framework of an adaptive model-based control, led to the best results, with biomass productivity reaching 9.2 g(DCW)/L/h.

-High cell density cultivations of recombinant E. coli have been increasingly used for the production of heterologous proteins. However, it is a challenge to maintain these cultivations within the desired conditions, given that some variables such as dissolved oxygen concentration (DOC) and feed flow rate are difficult to control. This paper describes the software SUPERSYS_HCDC, a tool developed to supervise fed-batch cultures of rE. coli with biomass concentrations up to 150 g DCW /L and cell productivities up to 9 g DCW .L -1 .h -1 . The tool includes automatic control of the DOC by integrated action of the stirrer speed as well as of the air and oxygen flow rates; automatic start-up of the feed flow of fresh medium (system based on a neural network committee); and automatic slowdown of feeding when oxygen consumption exceeds the maximum capacity of the oxygen supply.

Background Fine-tuning the aeration for cultivations when oxygen-limited conditions are demanded (such as the production of vaccines, isobutanol, 2–3 butanediol, acetone, and bioethanol) is still a challenge in the area of bioreactor automation and advanced control. In this work, an innovative control strategy based on metabolic fluxes was implemented and evaluated in a case study: micro-aerated ethanol fermentation. Results The experiments were carried out in fed-batch mode, using commercial Saccharomyces cerevisiae , defined medium, and glucose as carbon source. Simulations of a genome-scale metabolic model for Saccharomyces cerevisiae were used to identify the range of oxygen and substrate fluxes that would maximize ethanol fluxes. Oxygen supply and feed flow rate were manipulated to control oxygen and substrate fluxes, as well as the respiratory quotient (RQ). The performance of the controlled cultivation was compared to two other fermentation strategies: a conventional “Brazilian fuel-ethanol plant” fermentation and a strictly anaerobic fermentation (with ultra-pure nitrogen used as the inlet gas). The cultivation carried out under the proposed control strategy showed the best average volumetric ethanol productivity (7.0 g L −1 h −1 ), with a final ethanol concentration of 87 g L −1 and yield of 0.46 g ethanol g substrate −1 . The other fermentation strategies showed lower yields (close to 0.40 g ethanol g substrate −1 ) and ethanol productivity around 4.0 g L −1 h −1 . Conclusion The control system based on fluxes was successfully implemented. The proposed approach could also be adapted to control several bioprocesses that require restrict aeration.