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O-29. Automated quantification of budding Saccharomyces cerevisiae using a novel image cytometry method

Presenter: Leo L. Chan, Nexcelom Bioscience, Lawrence, MA Coauthors: Daniel J. Laverty, Alexandria Kury, Dmitry Kuksin, Alnoor Pirani, and Kevin Flanagan, Nexcelom Bioscience, Lawrence, MA

Concentration, viability, and budding percentages of Saccharomyces cerevisiae are routinely measured in the biofuel and brewing industries. Measurement of these parameters is of great importance in a manufacturing setting because they can aid in the estimation of the 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 yeast budding percentages that were comparable between manual and automated counting, as well as cell cycle analysis. The automated image cytometry method was 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 the bioethanol production process.

Leo Chan currently serves as the technology R&D manager and senior scientist at Nexcelom Bioscience LLC, Lawrence, MA. His research involves the development of instruments and applications for the Cellometer image cytometry system for detection and analysis of yeasts used in the brewing and biofuel industries. He is a member of MBAA. He received his B.S., M.S., and Ph.D. degrees in electrical and computer engineering from the University of Illinois at Urbana-Champaign (2000– 2008).

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