This paper reports the four-part differential leukocyte

count (DLC) of human blood using a MEMS

microflow (μflow) cytometer. It is achieved with a

two-color laser-induced fluorescence (LIF) detection

scheme. Four types of leukocytes including

neutrophils, eosinophils, lymphocytes and monocytes

are identified in blood samples, which are stained by

fluorescein isothiocyanate (FITC) and propidium

iodide (PI). The DLC results show good correlation

with the count from a commercial hematology

analyzer. The whole system is also implemented into a

portable instrument for space application

Fridge, Alan

Kasdan, Harvey L.

Shi, Wendian

Tai, Yu-Chong

English

Caltech Authors - Main

FOUR-PART DIFFERENTIAL LEUKOCYTE COUNT USING FLOW 
CYTOMETER 
Wendian Shi1, Harvey L. Kasdan2, Alan Fridge2 and Yu-Chong Tai1 
1California Institute of Technology, Pasadena, California, USA 
2IRIS Diagnostics Division, IRIS International Inc., Chatsworth, California, USA 
 
ABSTRACT 
This paper reports the four-part differential leukocyte 
count (DLC) of human blood using a MEMS 
microflow (flow) cytometer. It is achieved with a 
two-color laser-induced fluorescence (LIF) detection 
scheme. Four types of leukocytes including 
neutrophils, eosinophils, lymphocytes and monocytes 
are identified in blood samples, which are stained by 
fluorescein isothiocyanate (FITC) and propidium 
iodide (PI). The DLC results show good correlation 
with the count from a commercial hematology 
analyzer. The whole system is also implemented into a 
portable instrument for space application. 
INTRODUCTION 
For NASA’s long-term space missions, it’s an 
emerging issue that how to handle health care of 
astronauts. During flights there’s a lack of access to 
diagnosis capabilities. Differential leukocyte count 
(DLC), an important clinical capability providing 
diagnostics of infection, radiation exposure and other 
diseases astronauts might face [1], is one useful 
approach among the effects of solving this problem. 
Unfortunately, in-space DLC is still not available 
because commercial DLC analyzers are too bulky and 
not qualified for space use.  
On the other hand, in-space DLC using flow 
cytometers is attractive for the portable package size 
and the small sample volume. There are approaches 
measuring single cell impedance [2] or light scattering 
[3] to count leukocyte. However, so far only three-part 
differential (i.e., lymphocytes, monocytes, and 
neutrophils) has been reported using flow cytometers 
[2], whereas the detection of eosinophils and basophils 
has not. Besides, the reported methods all require a 
significant dilution of blood sample. 
This work uses the approach of fluorescent dye 
staining. Dye staining is a very common technique to 
identify biological tissues. It mainly targets 
intracellular features and there exist many types of 
dyes for leukocyte staining. The cost is also low, 
typically in the range of a few cents for each test.   
However, one common problem of dye staining is the 
poor selectivity, which makes it challenging for 
multi-part DLC. For instance, the nucleic acid dyes 
stain all nucleuses of different leukocytes with similar 
affinity. In our previous work [4], we encountered this 
problem with Acridine Orange dye and could only do a 
two–part DLC (i.e., lymphocytes and neutrophils).  
In this work, we improve the approach by using the 
cocktail of two different dyes (i.e., FITC and PI) 
together with the laser-induced fluorescence (LIF) 
detection. This allows us to achieve the first four-part 
DLC (i.e., lymphocytes, monocytes, neutrophils and 
eosinophils) using MEMS flow cytometers.  
DETECTION PRINCIPLE 
As shown in Fig.1, a two-color LIF detection scheme 
is adopted for the flow cytometer. A microfluidic 
channel is used as a flow cell, where dye-stained blood 
sample is measured for fluorescence emission [4]. The 
blood sample is illuminated by an excitation laser 
(488nm) at the sensing zone, and the emission is 
measured in two color ranges, green (510nm~560nm) 
and red (>590nm), which accommodate the emission 
peaks of FITC (520nm) and PI (617nm). 
 
Figure 1: Schematic view of the two-color LIF 
detection used for leukocyte differential. 
FITC is a protein staining dye which is mostly used as 
the fluorophore for antibody labeling. In permeable 
cells, it stains all the intracellular protein contents. It 
was reported that the FITC stains eosinophils with an 
affinity much stronger than other leukocytes [5]. In 
comparison, PI is a nucleic acid staining dye which has 
20-fold enhanced fluorescence when binding to 
DNA/RNA. Only leukocytes have significant amount 
of nucleic acid contents among blood cells [6], so they 
can be selectively counted by PI fluorescence. The 
green fluorescence from protein staining by FITC and 
red fluorescence from nucleic acid staining by PI are 
 
 
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measured simultaneously to identify different types of 
leukocytes.  
The volume of the detection zone (Fig.2) in the micro 
flow cell is designed to reduce cell coincidence which 
limits counting accuracy. In macro-size flow 
cytometer sheath flow is needed to reduce coincidence, 
where a sample is guided into narrow stream by 
hydrodynamic focusing. In flow cytometer, the 
sample flow is constrained by the microfluidic channel 
dimension [4]. It can achieve a low coincidence rate 
without sheath flow, thus avoid using a large volume 
of buffer. 
FLOW CYTOMETER SYSTEM  
Fig.2 shows the whole cytometer system we build and 
the flow cartridge. The disposable cartridge is 
fabricated in a soft lithography process introduced 
before, where a PDMS block is bonded to a glass 
substrate to form the microfluidic channel [4]. The 
detection zone is 28m high and 32m wide, and its 
length is 40m defined by the size of excitation spot. 
This dimension is designed to be big enough to flow all 
blood cells through but small enough to reduce the 
coincidence error. 
 
 
 
 
 
Figure 2: Top view of the fabricated flow chip (left) 
and the portable flow cytometer (right). 
The system is built with off-shelf components except 
the flow cell. The excitation source is a 20mW, 488nm 
solid-state laser module. The optical components, such 
as the condensers, the dichroic mirror (HP580nm) and 
the emission filters (BP 510nm-560nm for green, HP 
590nm for red) as shown in Fig.1, are assembled inside 
a black housing to be shielded from environmental 
light. Two photomultiplier tubes (PMTs) measure the 
green fluorescence and the red fluorescence separately 
but simultaneously. Blood sample is loaded by a 
pipette tip, and driven by a mini peristaltic pump for 
test. 
The whole system, including the data acquisition 
module, is enclosed within an aluminum case (12” x 9” 
x 5”). It could be powered by either the 110V AC or a 
5V DC source, and the recorded data is read out by a 
USB port. The portable system is suitable both for 
spaceflight applications and point-of-care applications.  
EXPERIMENTAL RESULTS 
Human whole blood (with EDTA anticoagulant) were 
purchased from HemaCare Corp. (CA, USA) and 
tested within 24 hours after delivery. Blood samples 
were stained with the following recipe. First, 5l blood 
was mixed with 5l Cal-Lyse reagent (Invitrogen, 
USA) for 5 minutes to permeabilize all cells. The 
solution was then diluted by 50l distilled water to 
stop the permeabilization. Note that most erythrocytes 
were readily lysed at this point and the remaining ones 
were too diluted to interfere with the leukocytes count. 
After 3 minutes, 8l 10X PBS buffer (Invitrogen) was 
added to stop the lysis. Then the sample was stained 
with 6l FITC solution (0.08mg/ml in water) and 6l 
PI solution (0.1mg/ml in water) for 10 minutes and 
finally loaded for test. The volumes were measured by 
adjustable-volume precision micropipettes. 
 
Figure 3: Recorded data of the measured fluorescence 
signals. Green and red are measured simultaneously.  
Fig.3 shows a portion of the signals measured on the 
flow cytometer. Each peak of the red fluorescence 
(PI) represents a leukocyte being counted, and the peak 
height indicates the amount of nucleic acid content. 
For each leukocyte event, the corresponding peak of 
the green fluorescence (FITC) measures the protein 
content. Some overlapped peaks caused by cell 
coincidence were observed during experiments, but 
the total number of overlapped peaks depicted a 
coincidence error of less than 1% for the given recipe. 
Fig.4 is a typical scatter plot of 10,000 leukocyte 
events (green intensity versus red intensity), where 
each point represents one leukocyte. The scatter plot 
shows clearly four separated clusters. The cluster with 
highest green intensity is eosinophil, as they have 
strongest affinity to FITC among leukocytes [5]. The 
cluster with medium green intensity is neutrophil. 
Neutrophils contain many intracellular granules rich of 
protein, whereas mononuclear leukocytes 
Inlet 
Outlet 
Detection 
Zone 
1m
m
PMT1 
PMT2 
Mini Peristaltic 
Pump 
Laser 
Fiber
flow 
chip 
10cm
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(lymphocytes and monocytes) don’t. Therefore they 
have a relatively stronger FITC staining. This is 
consistent with the observations from reference [5]. 
The bottom left cluster is lymphocyte and the bottom 
right one is monocyte. Their green intensities are 
similar, but monocytes have more nucleic acid content 
thus higher red intensities than those of lymphocytes 
[6]. 
 
Figure 4: Scatter plot of recorded fluorescence 
intensities of leukocytes, green vs. red. 10,000 
leukocytes were counted. 
Reference 4-Part DLC 
  
 
Lymphocyte
Monocyte
Eosinophil
Neutrophil
6,000 cells/ml 5,800 cells/ml Leukocyte 
Figure 5: Summary of the 4-part DLC results. The 
reference is obtained from the same blood sample 
counted by a commercial hematology analyzer (i.e., 
Beckman Coulter LH750). 
Fig.5 summarizes the results from a typical test 
including the concentration of total leukocyte and the 
percentages of each type (lymphocyte, monocyte, 
neutrophil and eosinophil), which constitute a 
complete four-part DLC report. 
The accuracy test was carried out on blood samples 
from seven donors chosen randomly. Each sample was 
tested five times, which measured the average value 
and the maximum deviation. The results were then 
compared to the data measured from a commercial 
analyzer (Beckman Coulter LH750). Fig.6 shows the 
results of leukocytes concentration with a correlation 
coefficient r=0.98 and a maximum error of 7% against 
reference values. Fig.7 shows the counted percentages 
of each type. The percentages of neutrophil, eosinophil 
and lymphocyte show good correlations (r≥0.97) with 
the reference values, whereas the monocyte correlation 
(r=0.76) is not satisfactory and this is further studied in 
the DISCUSSION section bellow. 
 
Figure 6: Results of leukocyte concentration compared 
to reference values. Correlation coefficient and 
maximum error are calculated. Error bars show 
maximum deviations from five repeated tests of the 
same blood sample.  
 
Figure 7: Correlation between the counted percentages 
and the reference values. For each leukocyte type, the 
linear regression and correlation coefficient are 
calculated. Error bars show the maximum deviations 
from five repeated tests. 
 
Figure 8: Leukocyte count repeatability for three 
samples in different concentration ranges. Each 
sample was used to repeat 10 tests. 
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The repeatability of counting leukocyte concentration 
was evaluated on three samples, and each sample was 
used to repeat 10 tests. Here the three samples were 
chosen to cover different concentrations ranges. Fig.8 
shows the repeatability is reasonable with a maximum 
deviation less than 9%. Table 1 further illustrates the 
repeatability results on the percentage distribution 
from one sample.  
Table 1: Test repeatability of the percentage 
distribution for one sample. The mean value (Mean) 
and the maximum deviation (MD) from ten repeated 
tests are listed. The reference values were obtained 
from the commercial analyzer.   
 Tested Reference 
Mean MD 
Neutrophil (%) 56.3 1.9 58.4 
Eosinophil (%) 2.1 0.2 2.3 
Lymphocyte (%) 36.8 1.8 33.8 
Monocyte (%) 4.8 1.2 5.5 
DISCUSSION 
As mentioned above the monocyte percentage 
measurement shows a less ideal correlation (r=0.76). 
This is a common and generic issue for monocyte 
count caused by the similarity between some large 
lymphocytes and monocytes. To study this issue, we 
did a separate experiment to verify the cluster 
identification of monocytes using an immunostaining 
specific for monocytes (i.e., anti-CD14-FITC from 
Invitrogen). 
 
Figure 9: Identification of monocytes cluster. (a) The 
control result where monocytes (red dot) identified by 
PI fluorescence only. (b) The experimental result 
where monocytes identified by both PI fluorescence 
and green fluorescence from the anti-CD14 staining. 
The control blood sample (Fig.9a) was stained with PI. 
The experimental sample (Fig.9b) was stained both 
with PI and the immunostaining. As expected, the 
green fluorescence of the immunostaining moves the 
monocyte cluster (marked red) up in the scatter plot 
(Fig.9b), so that the monocyte cluster is completely 
separated from the lymphocyte cluster. Fig.9b clearly 
shows that monocytes and lymphocytes do overlap in 
the zone of high PI intensity. This is consistent with the 
4-part differential (Fig.4). As a result, the lymphocytes 
having strong red intensity are likely to be mistakenly 
counted as monocytes. Those cells were believed to be 
large lymphocytes [6]. Interestingly, the lymphocyte 
count itself is not affected by much because the total 
number of lymphocytes is much larger than that of the 
large lymphocytes.  
CONCLUSION 
Four-part differential leukocyte count was 
demonstrated on a MEMS flow cytometer. A 
two-color LIF detection scheme was used to identify 
lymphocytes, monocytes, neutrophils and eosinophils 
in human blood with fluorescent dyes FITC and PI 
staining. Blood samples from different donors are 
tested, and the results show good accuracy and 
repeatability. 
ACKNOWLEDGMENT 
This work was supported by NSBRI under the Award 
Number TD01301. The authors thank all members of 
Caltech Micromachining Group for the helpful 
discussions.  
REFERENCES 
[1] B. Houwen, “The Differential Cell Count”, 
Laboratory Hematology, vol. 7, pp. 89-100, 2001. 
[2] D. Holmes, D. Pettigrew, C. H. Reccius, J. D. 
Gwyer, C. Berkel, J. Holloway, D. E. Davies and H. 
Morgan, “Leukocyte Analysis and Differentiation 
Using High Speed Microfluidic Single Cell Impedance 
Cytometry”, Lab Chip, vol. 9, pp. 2881-2889, 2009. 
[3] E. Altendorf, D. Zebert, M. Holl and P. Yager, 
“Differential Blood Cell Counts Obtained Using a 
Microchannel Based Flow Cytometer”, Tech. Digest 
Transducers’97, Chicago, pp. 531-534. 
[4] W. Shi, S. Zheng, H. L. Kasdan, A. Fridge and Y.C. 
Tai, “Leukocyte Count and Two-Part Differential in 
Whole Blood Based on a Portable Microflow 
Cytometer”, Tech. Digest Transducers’09., Denver, 
pp. 616-619. 
[5] E. Bedner, H. D. Halicka, W. Cheng, T. Salomon, 
A. Deptala, W. Gorczyca, M. R. Melamed and Z. 
Darzynkiewicz, “High Affinity Binding of Fluorescein 
Isothiocyanate to Eosinophils Detected by Laser 
Scanning Cytometry: A Potential Source of Error in 
Analysis of Blood Samples Utilizing 
Fluorescein-Conjugated Reagents in Flow 
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[6] V. A. Loiko, G. I. Ruban, O. A. Gritsai, V. V. 
Berdnik, N. V. Goncharova, “Mononuclear Cells 
Morphology for Cells Discrimination by the Angular 
Structure of Scattered Light”, Proc. 10th Conf. on 
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Non-spherical Particles, Bodrum, 2007, pp. 105-108.  
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Four-part differential leukocyte count using μflow cytometer

Differential Blood Cell Counts Obtained Using a Microchannel Based Flow Cytometer”,

High Affinity Binding of Fluorescein Isothiocyanate to Eosinophils Detected by Laser Scanning Cytometry: A Potential Source of Error in Analysis of Blood Samples Utilizing Fluorescein-Conjugated Reagents in Flow Cytometry”,

Leukocyte Analysis and Differentiation Using High Speed Microfluidic Single Cell Impedance Cytometry”,

Mononuclear Cells Morphology for Cells Discrimination by the Angular Structure of Scattered Light”,

The Differential Cell Count”,

http://authors.library.caltech.edu/19038/1/Shi2010p10684Mems_2008_21St_Ieee_International_Conference_On_Micro_Electro_Mechanical_Systems_Technical_Digest.pdf

Four-part differential leukocyte count using μflow cytometer

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