Automated quantification of budding Saccharomyces cerevisiae using a novel image cytometry method

Area of Science:

• Biotechnology
• Industrial Microbiology
• Analytical Chemistry

Background:

• Accurate measurement of yeast concentration, viability, and budding is crucial for brewing and biofuel production.
• Traditional manual counting methods are labor-intensive and prone to errors.
• Budding percentage directly correlates with yeast reproduction, metabolism, and bioethanol yield.

Purpose of the Study:

• To develop and validate a novel automated method for quantifying yeast budding percentages.
• To compare the automated method with traditional manual counting and cell cycle analysis.
• To assess the applicability of the automated method in real-time industrial fermentation monitoring.

Main Methods:

• Development of an automated quantification method using Cellometer image cytometry.
• Utilization of a dual-fluorescent nucleic acid dye for live cell staining and morphological analysis.
• Inclusion of cell cycle analysis as a complementary budding analysis technique.

Main Results:

• The automated image cytometry method demonstrated comparable results to manual counting and cell cycle analysis for yeast budding percentages.
• The method successfully analyzed corn mash samples directly from fermenters.
• Simultaneous measurement of concentration, viability, and budding percentages was achieved.

Conclusions:

• The automated Cellometer image cytometry method offers a reliable and efficient alternative to manual yeast budding quantification.
• This automated approach can be integrated into quality assurance protocols for enhanced beer and bioethanol production.
• The method holds potential for improving the overall quality and efficiency of fermentation processes.