Metabolic fluxes-oriented control of bioreactors: a novel approach to tune micro-aeration and substrate feeding in fermentations.

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 gethanol g substrate -1 . The other fermentation strategies showed lower yields (close to 0.40 gethanol 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.

Oxygen transfer in a pressurized airlift bioreactor.

Airlift bioreactors (ALBs) offer advantages over conventional systems, such as simplicity of construction, reduced risk of contamination, and efficient gas-liquid dispersion with low power consumption. ALBs are usually operated under atmospheric pressure. However, in bioprocesses with high oxygen demand, such as high cell density cultures, oxygen limitation may occur even when operating with high superficial gas velocity and air enriched with oxygen. One way of overcoming this drawback is to pressurize the reactor. In this configuration, it is important to assess the influence of bioreactor internal pressure on the gas hold-up, volumetric oxygen transfer coefficient (k(L)a), and volumetric oxygen transfer rate (OTR). Experiments were carried out in a concentric-tube airlift bioreactor with a 5 dm(3) working volume, equipped with a system for automatic monitoring and control of the pressure, temperature, and inlet gas flow rate. The results showed that, in disagreement with previous published results for bubble column and external loop airlift reactors, overpressure did not significantly affect k(L)a within the studied ranges of pressure (0.1-0.4 MPa) and superficial gas velocity in the riser (0.032-0.065 m s(-1)). Nevertheless, a positive effect on OTR was observed: it increased up to 5.4 times, surpassing by 2.3 times the oxygen transfer in a 4 dm(3) stirred tank reactor operated under standard cultivation conditions. These results contribute to the development of non-conventional reactors, especially pneumatic bioreactors operated using novel strategies for oxygen control.

Non-conventional induction strategies for production of subunit swine erysipelas vaccine antigen in rE. coli fed-batch cultures.

In spite of the large number of reports on fed-batch cultivation of E. coli, alternative cultivation/induction strategies remain to be more deeply exploited. Among these strategies, it could be mentioned the use of complex media with combination of different carbon sources, novel induction procedures and feed flow rate control matching the actual cell growth rate. Here, four different carbon source combinations (glucose, glycerol, glucose + glycerol and auto-induction) in batch media formulation were compared. A balanced combination of glucose and glycerol in a complex medium formulation led to: fast growth in the batch-phase; reduced plasmid instability by preventing early expression leakage; and protein volumetric productivity of 0.40 g.L(-1).h(-1). Alternative induction strategies were also investigated. A mixture of lactose and glycerol as supplementary medium fully induced a high biomass population, reaching a good balance between specific protein production (0.148 gprot.gDCW (-1)) and volumetric productivity (0.32 g.L(-1).h(-1)). The auto-induction protocol showed excellent results on specific protein production (0.158 gprot.gDCW (-1)) in simple batch cultivations. An automated feed control based on the on-line estimated growth rate was implemented, which allowed cells to grow at higher rates than those generally used to avoid metabolic overflow, without leading to acetate accumulation. Some of the protocols described here may provide a useful alternative to standard cultivation and recombinant protein production processes, depending on the performance index that is expected to be optimized. The protocols using glycerol as carbon source and induction by lactose feeding, or glycerol plus glucose in batch medium and induction by lactose pulse led to rSpaA production in the range of 6 g.L(-1), in short fed-batch processes (16 to 20 h) with low accumulation of undesired side metabolites.

Enhanced production of recombinant thermo-stable lipase in Escherichia coli at high induction temperature.

Thermostable microbial lipases are potential candidates for industrial applications such as specialty organic syntheses as well as hydrolysis of fats and oils. In this work, basic biochemical engineering tools were applied to enhance the production of BTL2 lipase cloned in Escherichia coli BL321 under control of the strong temperature-inducible λP(L) promoter. Initially, surface response analysis was used to assess the influence of growth and induction temperatures on enzyme production, in flask experiments. The results showed that temperatures of 30 and 45°C were the most suitable for growth and induction, respectively, and led to an enzyme specific activity of 706,000 U/gDCW. The most promising induction conditions previously identified were validated in fed-batch cultivation, carried out in a 2L bioreactor. Specific enzyme activity reached 770,000 U/gDCW, corresponding to 13,000 U/L of culture medium and a lipase protein concentration of 10.8 g/L. This superior performance on enzyme production was a consequence of the improved response of λP(L) promoter triggered by the high induction temperature applied (45°C). These results point out to the importance of taking into account protein structure and stability to adequately design the recombinant protein production strategy for thermally induced promoters.

Intensification of high cell-density cultivations of rE. coli for production of S. pneumoniae antigenic surface protein, PspA3, using model-based adaptive control.

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.

Robust artificial intelligence tool for automatic start-up of the supplementary medium feeding in recombinant E. coli cultivations.

One of the most important events in fed-batch fermentations is the definition of the moment to start the feeding. This paper presents a methodology for a rational selection of the architecture of an artificial intelligence (AI) system, based on a neural network committee (NNC), which identifies the end of the batch phase. The AI system was successfully used during high cell density cultivations of recombinant Escherichia coli. The AI algorithm was validated for different systems, expressing three antigens to be used in human and animal vaccines: fragments of surface proteins of Streptococcus pneumoniae (PspA), clades 1 and 3, and of Erysipelothrix rhusiopathiae (SpaA). Standard feed-forward neural networks (NNs), with a single hidden layer, were the basis for the NNC. The NN architecture with best performance had the following inputs: stirrer speed, inlet air, and oxygen flow rates, carbon dioxide evolution rate, and CO2 molar fraction in the exhaust gas.

Robust artificial intelligence tool for automatic start-up of the supplementary medium feeding in recombinant E. colicultivations

One of the most important events in fed-batch fermentations is the definition of the moment to start the feeding. This paper presents a methodology for a rational selection of the architecture of an artificial intelligence (AI)system, based on a neural network committee (NNC),which identifies the end of the batch phase. The AI systemwas successfully used during high cell density cultivations of recombinant Escherichia coli. The AI algorithm wasvalidated for different systems, expressing three antigens to be used in human and animal vaccines: fragments of surface proteins of Streptococcus pneumoniae (PspA), clades 1 and 3, and of Erysipelothrix rhusiopathiae (SpaA). Standard feed-forward neural networks (NNs), with a single hidden layer, were the basis for the NNC. The NN architecture with best performance had the following inputs: stirrer speed, inlet air, and oxygen flow rates, carbon dioxide evolution rate, and CO2 molar fraction in the exhaust gas.