Automated yeast cultivation control using a biosensor and flow cytometry.

Area of Science:

• Biotechnology and Bioprocessing
• Microbial Physiology
• Synthetic Biology

Background:

• Effective microbial bioprocessing requires precise control over cellular performance and robustness.
• Traditional monitoring methods often lack the sensitivity to detect subtle physiological changes.
• Environmental stressors like furfural can negatively impact microbial cultivation efficiency.

Purpose of the Study:

• To evaluate an automated fed-batch cultivation control system.
• To utilize at-line flow cytometry with a redox biosensor for monitoring yeast cell physiology.
• To assess the system's ability to maintain cellular fitness under furfural stress.

Main Methods:

• Development of a fed-batch cultivation control system employing at-line flow cytometry.
• Use of intact yeast cells with a fluorescent transcription factor-based redox biosensor (TRX2p-yEGFP).
• Monitoring of the NADPH/NADP+ ratio in response to furfural exposure.

Main Results:

• The control system successfully detected biosensor output and automatically adjusted furfural feed rate.
• Physiological fitness of the yeast strain was maintained even at high furfural concentrations.
• Single-cell measurements allowed for the monitoring of subpopulation dynamics, improving control precision.

Conclusions:

• Automated control systems combining biosensors and flow cytometry offer robust microbial cultivation.
• Leveraging intracellular properties as control inputs enhances system performance.
• This approach holds significant potential for optimizing industrial bioprocessing applications.