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Fed-batch processes are commonly used in industry to obtain sufficient biomass and associated recombinant protein or plasmids. In research laboratories, it is more common to use batch cultures, as the setup of fed-batch processes can be challenging. This method outlines a robust and reliable means to generate Escherichia coli biomass in a minimum amount of fermentation time using a standardized fed-batch process. Final cell densities can reach over 50g dry cell weight per liter (g dcw/L) depending on the strain. This method uses a predefined exponential feeding strategy and conservative induction protocol to achieve these targets without multiple trial and error studies. If desired, productivity can be optimized by balancing the induction time and feed rates. This method utilizes cost-efficient defined media, minimizes process control complexity, and potentially aids downstream purification.
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Optimization of nutrient utilization efficiency and productivity for algal cultures under light and dark cycles using genome-scale model process control
Abstract Algal cultivations are strongly influenced by light and dark cycles. In this study, genome-scale metabolic models were applied to optimize nutrient supply during alternating light and dark cycles ofChlorella vulgaris. This approach lowered the glucose requirement by 75% and nitrate requirement by 23%, respectively, while maintaining high final biomass densities that were more than 80% of glucose-fed heterotrophic culture. Furthermore, by strictly controlling glucose feeding during the alternating cycles based on model-input, yields of biomass, lutein, and fatty acids per gram of glucose were more than threefold higher with cycling compared to heterotrophic cultivation. Next, the model was incorporated into open-loop and closed-loop control systems and compared with traditional fed-batch systems. Closed-loop systems which incorporated a feed-optimizing algorithm increased biomass yield on glucose more than twofold compared to standard fed-batch cultures for cycling cultures. Finally, the performance was compared to conventional proportional-integral-derivative (PID) controllers. Both simulation and experimental results exhibited superior performance for genome-scale model process control (GMPC) compared to traditional PID systems, reducing the overall measured value and setpoint error by 80% over 8 h. Overall, this approach provides researchers with the capability to enhance nutrient utilization and productivity of cell factories systematically by combining genome-scale models and controllers into an integrated platform with superior performance to conventional fed-batch and PID methodologies.
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- Award ID(s):
- 1804733
- PAR ID:
- 10653529
- Publisher / Repository:
- Springer Nature
- Date Published:
- Journal Name:
- npj Systems Biology and Applications
- Volume:
- 9
- Issue:
- 1
- ISSN:
- 2056-7189
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1038/s41540-022-00260-7
