1. Validation of Yeast Cell Analysis Using Automated Image Cytometry
Andrew Yourick, Will Pelland, Kelsey Wahl
Department of Food Science & Human Nutrition, Colorado State University, Fort Collins, CO
Abstract
Test samples of Saccharomyces cerevisiae are routinely procured in
breweries all over the world in order to be analyzed for viability, vitality,
and to conduct cell counts. While these analyses are typically done
manually with a hemocytometer and microscope, new, more automated
technology is gaining popularity. This study looked to validate the
measurements of viability, vitality, and cell counts by comparing the results
of flow cytometry to that of a Nexcelom Cellometer. Methods of
measurement were developed according to the manufacturer of each
instrument. Each instrument was tested using yeast samples of the same
treatment prior to analysis. Data was acquired then evaluated using
Analysis of Variance statistical methods to determine how each yeast
analysis instrument compared to the other.
Introduction
Consistent fermentation and yeast parameters are crucial in maintaining
quality standards in a brewery. This Includes:
• Concentration:
o The amount of yeast cells that are held in a given yeast slurry.
Measured in cells/mL.
• Viability:
o A percentage of living vs. dead cells in a yeast solution, quantified by
the amount of yeast with intact membranes. Measured with
propidium iodide (PI).
• Vitality:
o Yeast that has a measurable level of metabolic activity and the ability
to proliferate. Measured with carboxyfluorescein diacetate (CFDA).
Special Thanks To:
Jeff Biegert – New Belgium Brewery, Colorado State University (adjunct
faculty)
Chris Allen – Colorado State University (Flow Cytometry)
Katie Fromuth –Colorado State University (Brewing Laboratory)
References
1. Laverty D, et al. Journal of Industrial Microbiology & Biotechnology. June 2013; 40(6):581-588.
2.Chan L, et al. Journal Of Industrial Microbiology & Biotechnology. November 2012; 39(11):1615-1623.
3.Saldi S, et al. Journal of the American Society of Brewing Chemists. 2014; 72(4):253-260.
4.Boyd, Andrew, et al. FEMS Yeast Research. ELSEVIER, 10 July 2002.
5.Yeast Concentration and Viability using Image-Based Fluorescence Analysis. Nexcelcom, (2013).
6.Briggs DE, Boulton CA, Brookes PA, Stevens R. Brewing: Science And Practice. Boca Raton: CRC Press; 2004.
7.User’s Manual for Cellometer, X2. Lawrence, MA. Nexcelcom (2013)
Results
• Cell concentration measurements are higher when using the
Cellometer compared to the flow cytometer.
• PI and CFDA measurements are higher when using the Cellometer
compared to the flow cytometer
• PI + CFDA percentages for the flow cytometer are near 100% for
every sample
Methods
• Three yeast samples were taken from yeast storage tanks at New
Belgium Brewery (NBB). One thin slurry (S4), one thick slurry
(S2), and one medium slurry (S3).
• Samples were transported to CSU for processing and testing in
sterile 1L bottles.
• Two more yeast samples were created, one by diluting 4:1 S4:PBS
(S1) and the other via centrifugation of S2 (S5).
• All five yeast samples were then diluted 1:25 with 50mM
EDTA+PBS by one operator to minimize multi-user error.
• See Figure 1 for dilution schematic.
• 110µL of each yeast sample was aliquoted in triplicate into micro-
centrifuge tubes where 110µL of either CFDA or PI were added.
• The CFDA samples were incubated for 45 minutes at 30°C.
• 40µL of each sample was aliquoted off for use by the Cellometer,
the remaining 180µL was used for Flow Cytometry.
• Unstained yeast samples plus counting beads were used for cell
concentration measurement by the Flow Cytometer.
• 20µL of dyed sample is loaded onto a Cellometer counting
chamber and loaded into the machine.
• All Cellometer settings were the same settings used at NBB.
Conclusion
When compared to the flow cytometer, the Cellometer over-
estimated cell counts, viability, and vitality measurements. The
vitality measurement is measuring dead yeast cells where viability is
measuring live cells. Theoretically, if these measurements are
added together the result should be 100% of cells in a sample being
accounted for. Figure 5 shows that the flow cytometer is near 100%
when the data is added; whereas the Cellometer is consistently
higher than 100%. One other factor that is apparent in the data is
the amount of human error introduced by pipetting. The raw data
is highly variable for the Cellometer, even though one person
performed all of the pipetting. Future experiments need to be
performed on ways to reduce the number of dilutions and pipetting
to minimize this error. If the Cellometer overestimates cell counts,
viability, and vitality it could result in underpitching yeast. However,
it may be possible to determine different settings so that the
Cellometer is more accurate, as this technology is more affordable
and accessible for breweries. Future research also needs to be
done with different models of flow cytometery to accurately
calculate cell counts. This is currently done with counting beads
and a calculation, however, this can be variable with human and
pipetting error. Another model of flow cytometer will be used that
accurately measures the volume of a sample and removes the
counting beads.
Figure 3 Graph showing the percentage of yeast cells positive for PI. These cells
are considered dead or metabolically inactive.
Figure 4 Graph showing the percentage of yeast cells positive for CFDA. These cells
are considered metabolically active.
Figure 5 Graph showing the additive percentage of yeast cells positive for both PI
and CFDA. Theoretically, the percentages should be 100%, accounting for all cells
in the sample.
Figure 6 Graph showing the cell concentrations for each sample and yeast
measurement machine. The Cellometer is much higher for cell counts for every
sample compared to the flow cytometer.
Figure 2 Picture of Cellometer bright field image. Green circled cells are
being counted for cell concentrations. Yellow circles are not counted and
indicate cells larger than indicated settings.