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Automated quantification of budding Saccharomyces cerevisiae using a novel image cytometry method
Authors:Daniel J Laverty  Alexandria L Kury  Dmitry Kuksin  Alnoor Pirani  Kevin Flanagan  Leo Li-Ying Chan
Institution:1. Department of Technology R&D, Nexcelom Bioscience LLC, 360 Merrimack St. Building 9, Lawrence, MA, 01843, USA
4. Center for Biotechnology and Biomedical Sciences, Merrimack College, North Andover, MA, 01845, USA
2. Department of Applications, Nexcelom Bioscience LLC, Lawrence, MA, 01843, USA
3. Department of Software Development, Nexcelom Bioscience LLC, Lawrence, MA, 01843, USA
Abstract:The measurements of concentration, viability, and budding percentages of Saccharomyces cerevisiae are performed on a routine basis in the brewing and biofuel industries. Generation of these parameters is of great importance in a manufacturing setting, where they can aid in the estimation of product quality, quantity, and fermentation time of the manufacturing process. Specifically, budding percentages can be used to estimate the reproduction rate of yeast populations, which directly correlates with metabolism of polysaccharides and bioethanol production, and can be monitored to maximize production of bioethanol during fermentation. The traditional method involves manual counting using a hemacytometer, but this is time-consuming and prone to human error. In this study, we developed a novel automated method for the quantification of yeast budding percentages using Cellometer image cytometry. The automated method utilizes a dual-fluorescent nucleic acid dye to specifically stain live cells for imaging analysis of unique morphological characteristics of budding yeast. In addition, cell cycle analysis is performed as an alternative method for budding analysis. We were able to show comparable yeast budding percentages between manual and automated counting, as well as cell cycle analysis. The automated image cytometry method is used to analyze and characterize corn mash samples directly from fermenters during standard fermentation. Since concentration, viability, and budding percentages can be obtained simultaneously, the automated method can be integrated into the fermentation quality assurance protocol, which may improve the quality and efficiency of beer and bioethanol production processes.
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