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Automatic bioprocess control. 4. A prototype batch of Saccharomyces cerevisiae
G Locher1, U Hahnemann, B Sonnleitner
1Institute of Biotechnology, ETH Hönggerberg, Zürich, Switzerland.
Journal of Biotechnology
|May 1, 1993
Summary
Investigating bioreactor conditions is crucial for cell growth. Saccharomyces cerevisiae cultivation revealed seven distinct metabolic phases based on environmental sensor data.
Area of Science:
- Biotechnology
- Cellular Biology
- Biochemical Engineering
Background:
- Living cells exhibit high sensitivity to physical-chemical environmental conditions within bioreactors.
- Understanding the bioreactor-cell relationship is essential to determine if bioreactor parameters limit cultivation or if environmental changes can steer cellular physiology.
- Saccharomyces cerevisiae, a well-characterized organism, serves as a suitable model for studying cellular responses to controlled environments.
Purpose of the Study:
- To investigate the intricate relationship between bioreactor conditions and living cells.
- To assess the influence of bioreactor characteristics on cell cultivation.
- To explore the potential of controlled environmental changes to induce desired cellular physiological states.
Main Methods:
- Utilized high-performance bioreactors for cell cultivation experiments.
- Employed Saccharomyces cerevisiae as the biological test organism.
- Collected data from approximately 300 batch cultivation experiments on glucose, analyzing around 20 sensor signals.
Main Results:
- Distinguished seven distinct phases during batch cultivation of Saccharomyces cerevisiae based on metabolite production/consumption.
- Correlated these phases with approximately 20 sensor signals, providing insights into metabolic backgrounds.
- Successfully achieved exhaustive knowledge of extracellular conditions using highly automated equipment.
Conclusions:
- The study highlights the critical sensitivity of cells to bioreactor environments.
- Identified distinct metabolic phases in Saccharomyces cerevisiae batch cultivation, linked to environmental parameters.
- Demonstrated the feasibility of detailed cellular environment analysis for understanding cell behavior in bioreactors.
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