Predicting sporulation events in a bioreactor using an electronic nose

Area of Science:

• Biotechnology
• Biosensors
• Microbial Monitoring

Background:

• Bacillus subtilis sporulation is critical in bioprocesses.
• Accurate monitoring of sporulation events and spore concentration is essential for process control.
• Traditional methods for spore enumeration can be time-consuming.

Purpose of the Study:

• To develop and validate an electronic nose (EN) system for real-time monitoring of Bacillus subtilis sporulation.
• To correlate EN sensor data with off-line spore concentration measurements.
• To assess the utility of EN for bioprocess monitoring.

Main Methods:

• Utilized a non-specific multi-sensor array including metal oxide sensors (MOS), MOSFETs, CO2, and humidity sensors.
• Monitored gas emissions from B. subtilis bioreactions (batch and fed-batch).
• Applied principal component analysis (PCA) to sensor signal patterns and developed a predictive model.

Main Results:

• Established a strong linear correlation (R² = 0.992) between PCA trajectory arc length and off-line spore counts.
• Demonstrated successful estimation of sporulation events and spore concentration.
• Showcased fast sensor responses and robust correlation with spore concentration.

Conclusions:

• The developed electronic nose is a convenient and accurate tool for monitoring Bacillus subtilis sporulation.
• This EN system offers real-time insights into bioprocesses, improving efficiency.
• The study highlights the potential of EN technology in microbial bioprocess monitoring.