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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