1. Kendra Liu, Narine Arabyan, Nguyet Kong, Marie-Pierre Forquin Gomez, and Bart C. Weimer
Department of Population Health and Reproduction
School of Veterinary Medicine, University of California – Davis, CA, USA
ACKNOWLEDGMENTS
I am grateful to Dr. Weimer for his guidance and helpful
discussions. I also acknowledge and appreciate all the help and
support received from everyone in the Weimer Lab.
CONCLUSION
Alternative method to quantify bacterial and eukaryotic cells.
Numbers determined by this new method were similar to
those obtained from traditional methods of plating the cells for
bacteria or hemocytometer for eukaryotic cells.
The physiological state of the cells were differentiated into
live and dead cells with the dyes SYTO62 and SYTOX,
respectively.
INTRODUCTION
Quantification and detection of the physiological state of the
cells is fundamental to microbiological studies. Traditional
methods of bacterial enumeration and detection of
physiological state via microscopic observations are labor and
time intensive (Ikeda et al. 2009). Using traditional culturing
methods, compromised or dead cells would not be able to be
enumerated. Therefore, a new, fast, and accurate method of
cell enumeration and detection of physiological state of the
cell is necessary to develop. This new method needs to be
culture independent. One suitable way is the use of
fluorescent dyes to stain the cells and flow cytometry. This
instrument uses two-color fluorescence detection. The red
laser diode has an excitation range of 620-645nm with max
emission of 630nm and detection range of 674-696nm
(Sakamoto et al. 2005). The blue LED has an excitation range
of 458-482nm with max emission of 470nm and detection
range of 510-540nm (Sakamoto et al. 2005).
Microchip based analysis has many advantages over the
conventional methods (Müller & Nebe‐von‐Caron 2010). This
provides a rapid, sensitive, and reliable quantification of
individual cells. The analysis is small scale and is completed
in a shorter time period. The assay takes only thirty minutes to
run six samples and it counts 2500 cells in four minutes
(Sakamoto et al. 2005). The consumption of the samples and
reagents are low. Lastly, preparation of samples is simple and
the analysis is performed with high reproducibility.
The aim of this investigation was to develop an assay that will
quantify and detect the physiological state of the cells: Madin-
Darby Canine Kidney (MDCK) epithelial cell line and
Salmonella enterica Typhimurium ST14028 using Agilent
2100 Bioanalyzer System on-chip flow cytometry.
ABSTRACT
This study describes the use of cell fluorescence assays
on the Agilent 2100 Bioanalyzer System. The Agilent
2100 Bioanalyzer System is the first commercially
available instrument capable of measuring cell
fluorescence for cell sorting. This instrument uses two-
color fluorescence detection—the red laser diode and
blue LED. The cell assay makes use of microfluidic chip-
based flow cytometry to quantify and detect the
physiological state of the cells. Salmonella enterica spp.
enterica serovar Typhimurium ST14028 and Madin-Darby
Canine Kidney (MDCK) epithelial cells were quantified
using the Agilent 2100 Bioanalyzer System . The
physiological states of the cells were detected using
SYTO62 and SYTOX dyes for live and dead cells,
respectively. Numbers determined by this method were
similar to those obtained by CFU counts from plates and
microscopic count using a hemocytometer, respectively.
With low cell and reagent consumption and running up to
six samples at a time, data analysis using the software on
the Agilent 2100 Bioanalyzer is quick and simple.
.
EXPERIMENTAL APPROACH RESULTS
Figure 1. Detection of live bacterial cells
with SYTO62 red fluorescent dye. 10µM is
the optimum concentration of SYTO62 to
detect live bacterial cells.
Figure 3. Optimization of SYTOX green
fluorescent dye. 5µM is the optimum
concentration of SYTOX to detect dead
bacterial cells.
Grow cells to mid-
exponential phase
Development of an assay to quantify and detect the physiological state of the cells
CONTACT INFORMATION
Bart C. Weimer, Ph.D. (bcweimer@ucdavis.edu)
Narine Arabyan (narabyan@ucdavis.edu)
Kendra Liu (kkliu@ucdavis.edu)
UC Davis (VM:PHR) VetMed3B – Room 4016
1089 Veterinary Medicine Dr. Davis, CA 95616
(530) 752-6426
http://weimermicrolab.wix.com/thelab
REFERENCES
Ikeda, M., Yamaguchi, Nobuyasu & Nasu, Masao, 2009. Rapid On-chip flow Cytometric
Detection of Listeria monocytogenes in Milk. Journal of Health Science, 55(5), pp.851-856.
Johnson, S., Nguyen, V. & Coder, D., 2001 Assessment of Cell Viability. Current Protocols in
Cytometry.
Müller, S. & Nebe-von-Caron, G., 2010. Functional single-cell analyses: flow cytometry and cell
sorting of microbial populations and communities. FEMS Microbiology Reviews, 34(4), pp.554-
587.
Sakamoto, C., Yamaguchi, N. & Nasu, M., 2005. Rapid and Simple Quantification of Bacterial
Cells by Using a Microfluidic Device. Applied and Environmental Microbiology, 71(2), pp.1117-
1121.
Figure 4. Quantification of dead
bacterial cells.
Figure 7. Differentiation of live and dead
MDCK cells when new and old/overgrown
MDCK cells were used with both 1 µM
SYTOX and 2 µM SYTO62.
Figure 8. Quantification of MDCK cells.
Bacterial cells
Salmonella enterica
Typhimurium ST14028
Grow cells for 14 hours
Eukaryotic cells
Madin-Darby Canine
Kidney epithelial cells
Incubate with SYTO62 / SYTOX for 1 hour at room
temperature in the dark
Count cells using
hemocytometer
Grow cells for 24 hours
30 minutes for
6 samples
Dilute cells to 106 cell/mL
Live Cells: SYTO62 Dead Cells: SYTOX
Load onto the cell chip
Calculate number of cells from event number
Red laser diode Blue LED
Detection of Live Bacterial Cells With SYTO62
Detection of Dead Bacterial Cells With SYTOX
Figure 2. Quantification of live cells from
event numbers.
Detection of Live and Dead MDCK Cells With
Both SYTO62 and SYTOX
Detection of Live and Dead Bacterial Cells With
Both SYTO62 and SYTOX
Figure 5. Detection of Live and Dead cells
with 10 µM SYTO62 and 5 µM SYTOX.
Figure 6. Quantification of Live and
Dead cells with 10 µM SYTO62 and 5
µM SYTOX.
FUTURE DIRECTIONS
Identify the different populations of cells during
Salmonella infection