Analytical chemistry 2013 qian liu

Label-Free Method for Cell Counting in Crude Biological Samples via
Paramagnetic Bead Aggregation
Jingyi Li,†,∥,■
Qian Liu,†,∥
Li Xiao,†
Doris M. Haverstick,‡
Alison Dewald,†,▲
Linda Columbus,†
Kimberly Kelly,§
and James P. Landers*,†,‡,⊥,∥
†
Department of Chemistry, ‡
Department of Pathology, §
Department of Biomedical Engineering, ⊥
Department of Mechanical and
Aerospace Engineering, ∥
Center for Microsystems for the Life Sciences, University of Virginia, Charlottesville, VA 22904
*S Supporting Information
ABSTRACT: Under chaotropic conditions, DNA released from lysed cells
causes the aggregation of paramagnetic beads in a rotating magnetic field in a
manner that is independent of the presence of other cellular components. The
extent of aggregation correlates with the mass of DNA in a quantitative manner
(Leslie, D. C. et al., J. Am. Chem. Soc. 2012, 134, 5689−96), and from this, the
number of DNA-containing cells in the sample can be enumerated. Microbial
growth testing is demonstrated by monitoring bead aggregation with E. coli in
the presence of ampicillin. Without the need for fluorescent labeling or Coulter
counting, the white blood cell count can be defined directly from a microliter of
crude whole blood. Specificity is brought to the process by coupling bead-based
immunocapture with DNA−bead aggregation allowing for the enumeration of
CD4+ T cells from human blood samples. The results of DNA-induced bead
aggregation had a 95% correlation with those generated by flow cytometry. With the process requiring only inexpensive, widely
available benchtop laboratory hardware, a digital camera, and a simple algorithm, this provided a highly accessible alternative to
more expensive cell-counting techniques.
For decades, cell counting has been the modern workhorse
of biomedical science and molecular biological research.
Flow cytometry is regarded as the gold standard for counting
cells, primarily due to its speed, throughput and accuracy.
However, its cost, large footprint, maintenance, cost per
sample, and complexity of operation limit its widespread use.
Microscopy is a low-cost alternative for counting cells, but it is a
laborious procedure, subjective in nature, and often does not
meet the throughput needs of laboratories. Coulter counting
provides an intermediate technology that bridges the complex
but highly automated flow cytometry and the low-tech, manual
light microscopy. Efforts to miniaturize cell counting have been
explored by a number of groups. Chung et al. reviewed
miniaturized flow cytometry, including cell transport and
detection in a microfluidic system, either optical or
impedometric.1
Rodriguez et al. reported the use of a
membrane in miniaturized flow cell to capture cells of interest,
which can be enumerated with microscopic imaging.2
Cheng et
al. developed a similar strategy, where cells were isolated with
immunoseparation in a microfluidic chamber before enumer-
ation under a microscope,3,4
and later reported the use of cell
lysate impedance spectroscopy as the detection module.5
Moon
et al. integrated microfluidic chips with a lensless imaging
system to shorten the time required for the whole process.6
Wang et al. labeled the captured cells with chemiluminescence
in a microfluidic chip and correlated the intensity with cell
number.7
Despite the promising progress, high cost and
complexity remain as issues. This is due not only to the use
of fluorescent labels that are inherently unstable but also to the
need for complex detection systems.
In clinical settings, Coulter counting suffices for generic
white blood cell (WBC) and red blood cell (RBC) counting,
and it is reasonably fast and cost-effective. For more specific cell
quantification, flow cytometry is the dominating technology.
For example, the level of CD4+ T cells is often quantified in
whole blood from patients infected with the human
immunodeficiency virus (HIV) or suspected of HIV infection
based on symptomology. In addition to providing a snapshot of
the status of the immune system, specific quantification of
CD4+ T cells is a critical metric for evaluating the response to
antiretroviral therapy (ART). In fact, a 2007 UNAIDS study
estimated that only ∼30% of eligible HIV patients had access to
antiretroviral therapy (ART), with one of the main reasons
being the lack of accessible cell counting facilities in resource-
limited areas. Interestingly, Redd and Quinn suggest that
simple, accurate, and cost-effective technologies for quantifying
whole blood CD4+ cell levels is a critical component in
expanding the access to ART.8
This single example brings to
light the deficit that exists in cell-counting chemistries and
instrumentation that are portable, simple, and cost-effective for
use at the point-of-care.
Received: May 9, 2013
Accepted: November 4, 2013
Published: November 4, 2013
Article
pubs.acs.org/ac
© 2013 American Chemical Society 11233 dx.doi.org/10.1021/ac401402h | Anal. Chem. 2013, 85, 11233−11239

Paramagnetic beads have been extensively studied for their
unique magnetic properties9
and application to a wide array of
bioanalytical processes; these include immunoseparation,10
transportation,11
mixing,12
and the detection13,14
of select
analytes of interest. Recently, we reported the “pinwheel
effect”,8
which describes chaotropic-driven adsorption of DNA
onto paramagnetic silica beads in a quantitative manner.
Captured images of the induced bead−DNA aggregates
followed by image analysis (using a simple algorithm) allows
for direct quantification of DNA in crude biological samples.
The simplicity of the chemistry (guanidine + beads + sample),
the instrumentation (magnetic field + digital camera), and the
method (pipet + magnetize + capture image) make this a cost-
effective, low-tech method for quantifying DNA in microliter
samples with a picogram limit of detection. We showed
preliminary evidence for the potential to count WBCs in whole
blood, and this spawned a more in-depth exploration of the
capabilities of the pinwheel effect for cell counting.
In this report, we show that the same assay can be used to
monitor the growth of cultured cells using only a few
microliters of sample. We also demonstrate that leukocytes
can be directly enumerated in whole blood without labeling or
purification with an accuracy and precision that compares
favorably with Coulter counting. Finally, we make quantifica-
tion cell-specific by coupling pinwheel with immunomagnetic
cell capture, demonstrating that CD4+ T cells can be
enumerated with sufficient sensitivity and accuracy to monitor
HIV/AIDS patients. As such, the pinwheel assay represents a
new, label-free method for cell counting where the simple
protocol and cost-effective instrumentation provides a highly
accessible alternative to more expensive counting techniques.
■ METHODS AND MATERIALS
Reagents. MagneSil paramagnetic particles were purchased
from Promega (Madison, WI). GdnHCl was bought from MP
Biomedicals (Solon, OH). MES was bought from Acros
Organics. Tris base was bought from Fisher Scientific. EDTA
was bought from Sigma-Aldrich. Human SH-SY5Y cells and
mouse RAW 264.7 cells were obtained from ATCC. E. coli
BL21(DE3) and D29 bacteriophage were obtained from New
England Biolabs (Ipswich, MA). Whole blood samples were
donated by consenting donors. CD4 isolation kit was bought
from Life Technologies. All solutions were prepared in
Nanopure water (Barnstead/Thermolyne, Dubuque, IA).
Reagent Preparation. Thirty microliters of stock Magnesil
beads was washed once with deionized, distilled water
(Nanopure) followed by one wash with GdnHCl solution (8
M, 1× TE, adjusted to pH 6.1 with 100 mM MES) and
resuspended in 1 mL of GdnHCl solution to make the
suspension.
Microwell Fabrication, Assay Instrumentation, and
Magnetic Field Application. Details have been described
previously. The system, with a rotating magnetic field (RMF),
of the pinwheel assay for DNA quantification was employed for
cell counting without any modifications.15
Image Processing. A gray level threshold was set in the
images of magnetic beads and aggregates by an isodata
algorithm written in Mathematica software, which identifies
the pixels representing the beads and aggregates. The total
number of these pixels in the photograph without DNA is
defined as 100%, and as more DNA molecules are released
from cells, tighter aggregation evolves, corresponding to a
smaller percentage. The change of the percentage is defined as
degree of aggregation (DA). More DNA molecules result in
tighter bead aggregation and higher DA values.
Establishment of Calibration Curves. Samples were first
incubated with GdnHCl solution in 1:100 volume ratio at room
temperature for 30 min. The samples were then serially diluted
in GdnHCl solution to appropriate concentrations as shown in
the figures. Five microliters of diluted sample, 3 μL of bead
suspension, and 12 μL of GdnHCl were mixed and exposed to
the RMF for 5 min, after which three photographs of the beads
and aggregates were acquired for image analysis. The
calibration curve was generated by correlating the mean DA
value of three images for each diluted sample with the
corresponding final cell concentration in the pinwheel assay.
Microbial Growth Testing. E. coli strain BL21(DE3) was
cultured in 1000 mL of liquid LB medium and incubated at 37
°C. Samples (1 mL) were collected at hour intervals for 5 h.
The culture was split into two equal volumes at t = 3 h, and one
volume was treated with 0.1 mg/mL ampicillin. Cell counting
based on absorbance measurements at 600 nm was obtained
with a UV/Visible spectrophotomer (Beckman Coulter,
DU800) in a 1 mL plastic cuvette at room temperature.
White Blood Cell Counting for Unknown Samples.
Raw blood samples were first incubated with GdnHCl solution
in 1:100 volume ratio at room temperature for 30 min. The
samples were diluted by 2000 fold. Five μL of diluted sample, 3
μL of bead suspension, and 12 μL of GdnHCl were mixed and
exposed to the RMF for 5 min, after which photographs of the
beads and aggregates were acquired for image analysis.
Considering mixing sample and beads results in another 4-
fold dilution, the samples were diluted by 8000 fold from raw
blood to the pinwheel assay. The concentration of white blood
cells in blood was acquired by comparing DA value with the
calibration curve (Figure 4). For the samples with WBC count
lower than 4 × 103
per μL, a final 4000-fold dilution was
performed in the pinwheel assay, and more accurate results
were acquired because of an optimized dynamic range.
Immunomagnetic Separation of CD4+ T Cells from
Blood. CD4+ T cells were isolated by a Dynal T4 Quant kit
following its protocols. Briefly, whole blood was incubated and
rotated with CD14-coated beads for 10 min, followed by
another 10 min incubation and rotation with CD4-coated
beads. Samples were then washed three times with PBS buffer.
Enumeration of CD4+ T Cells with Hemocytometer.
Isolated CD4+ T cells were lysed by the lysis solution provided
in the Dynal T4 Quant kit. The lysed cells were stained with
Sternheimer−Malbin solution and loaded on a hemocytometer,
and the nuclei were counted using a conventional white light
microscope.
Enumeration of CD4+ T Cells with the Pinwheel
Assay. After immunomagnetic separation, the isolated CD4+
T cells were incubated in 100 μL of 8 M GdnHCl solutions for
30 min, and the solution was further diluted 20, 40, 80, and
160-fold with 8 M GdnHCl. These four aliquots were then
loaded into the pinwheel microwell following the same
procedure as white blood cell counting.
■ RESULTS AND DISCUSSION
Paramagnetic Bead Aggregation Enables Cell Enu-
meration. With the pinwheel effect, DNA adsorbs to silica-
coated paramagnetic beads under chaotropic conditions, and
driven by a rotating magnetic field (RMF), the beads are
intertwined by DNA and rapidly aggregate (in seconds to
minutes) (Figure 1A). The degree of aggregation correlates
Analytical Chemistry Article
dx.doi.org/10.1021/ac401402h | Anal. Chem. 2013, 85, 11233−1123911234

well with the concentration of DNA, allowing for fast DNA
quantification without the need of fluorescent labels.15
Owing
to the specificity of the chaotrope-driven DNA adsorption on
silica,16
bead aggregation induced by DNA released from the
cell lysate is unaffected by protein, lipid, and other cellular
components present at concentrations orders of magnitude
higher; this is the case for even a few cells (Figure 1B). Given
that each DNA-containing cell in a blood sample releases the
same mass of DNA (6.25 pg), the extent of bead aggregation
defines the number of cells in the sample. Figure 1 panels B2−
B4 show images of beads that have been aggregated by 13, 52,
and 195 pg of DNA, respectively. While the protein released
from 30 cells is ∼15 ng, it is noteworthy that augmenting the
solution with additional protein (BSA; to a final concentration
of 1 μg/μL) does not adversely affect aggregation.17
An inherent advantage of the chemistry that induces the
pinwheel effect (i.e., guanidine) is that it also lyses cells
effectively; thus, no additional reagents are required for direct
cell counting. A cell solution added to 8 M GdnHCl at a 1:100
volume ratio induces bead aggregation immediately following
vortexing, which is key to the pinwheel assay enabling the
enumeration of cells. The rapidity with which cell lysis occurs is
supported by the fact that aggregate formation (visually
detectable aggregates in seconds) does not improve with
longer incubation times (e.g., up to 60 min) (see Supporting
Information Figure S1). This yields a simple protocol for cell
enumeration: (a) lyse cells in 8 M GdnHCl to release DNA,
(b) bring the sample DNA concentration within the dynamic
range of the assay through sample dilution, (c) mix the sample
with silica-coated magnetic beads in a RMF to induce
aggregation, (d) capture digital images and process the images
through an algorithm to generate a % DA and, finally, (e)
compare resultant value to a standard curve to calculate cell
concentration (details are provided in the experimental
section). As DNA begins to entangle with the beads,15
small
bead aggregates evolve from the initial dispersed state, growing
through nucleation with other beads, allowing smaller
aggregates to coalesce into larger ones. The higher the DNA
concentration, the more aggressive the aggregate formation and
subsequent coalescing become. Overall, the beads experience a
transition from the dispersed state in the negative control (i.e.,
without DNA) to a condensed aggregation state with sufficient
DNA. Even with only a few cells, aggregation induced by
released DNA leads to a decrease of the total number of pixels
representing the beads and/or bead aggregates; this we refer to
as dark area.15
A threshold is set by an isodata algorithm15
to
separate the beads and/or aggregates from image background,
shown as the black line in the histogram (Figure 1C). The peak
area below the threshold stands for the dark area, and the
decrease of dark area represents the loss of dispersed beads due
to aggregation. Therefore, we define the decrease of dark area
that is normalized against the negative control as DA.
Correlating DNA concentration and DA generates a calibration
curve for DNA quantification. With each somatic cell
containing 6.25 pg DNA (discussed earlier), a simple
calculation allows for plotting DA against the number of cells
in a particular volume (typically 1 μL). Regardless of the source
of DNA, the higher the DNA concentration, the larger the DA.
This provides a quantitative correlation between the extent of
aggregation and the number of cells in a specific volume of
sample, for example, as in Figure 2.
Pinwheel assay standard curves for the enumeration of: (a)
eukaryotic cells (human WBCs and mouse cells), (b)
prokaryotic cells (E. coli), and (c) bacteriophage (D29) are
given in Figure 2. While not a “cell”, phage are virus-like
macromolecular assemblies of protein and nucleic acid, with an
intact genome of length of 49 × 103
base pairs. The DNA
extracted from this phage is double-stranded, and with a 49 kbp
length, a rough estimate of the length is ∼16 μm.18
As shown in
Figure 2, it is still capable of inducing aggregates, but it does so
with an effectiveness that is roughly an order of magnitude less
than E. coli, whose genome is 4.6 Mb. There is a 3 order of
Figure 1. Schematic of the pinwheel effect induced by lysed cells. (A) GdnHCl lyses the cells and drives the released DNA to adsorb on to silica-
coated paramagnetic beads, which form aggregates in a rotating magnetic field (RMF). Images of the aggregation are digitized, from which the initial
concentration of cells can be measured. (B) Photographs of the same amount of beads with different amounts of DNA that are equivalent to 0, 2, 8,
and 32 cells, respectively. Magnetic beads, which remain dispersed in RMF, form visually detectable aggregates within minutes upon mixture with
lysed human cells. (C) Gray level histogram of the four photographs. Three regions are identified as aggregates, dispersed beads, and background,
respectively, on the basis of the gray level value. The change of the histogram clearly illustrates the loss of dispersed beads and the formation of
aggregates.

magnitude differential in the size of the E. coli DNA versus
mouse or human DNA. As the curve in Figure 2 (a semilog
plot) shifts from left to right, the sensitivity decreases over 3
orders of magnitude; not surprisingly, this roughly correlates
with the decrease in genome size with each cell type. For
human cells, ∼8 cells in 20 μL corresponds to 0.4 cells/μL and
a DNA concentration of 2.5 pg/μL. Despite this miniscule
mass, the induced aggregation is still visually detectable (Figure
1B), with the limit of detection (through image analysis)
approaching 0.1 cell/μL, that is, 2 cells in a total of 20 μL
(Figure 2). The concept that sensitivity is proportional to DNA
length is consistent with our previous observations15
and is
rationalized as longer strands of DNA induce bead aggregation
more effectively than shorter ones. As a result, each cell type
should be calibrated individually in order to acquire accurate
results. To further study the size dependence, the actual DNA
size distribution should be measured by other techniques such
as electrophoresis and correlated more quantitatively with the
sensitivity of the pinwheel assay.
Microbial Growth Testing with the Pinwheel Assay.
Accurate and quick determination of bacteria concentration is
essential in microbiology studies. To test the effectiveness of
measuring microbial growth with the pinwheel assay, E. coli was
cultured in media, and the time evolution of growth was
monitored by two methods: light scattering (spectrophotom-
etry at 600 nm) and the pinwheel assay. From the liquid
culture, 1 mL was sampled every hour, and after 3 h, the cells
were split, where half were dosed with buffer and the other half
with ampicillin (0.1 mg/mL). Monitoring the bacterial growth
conventionally by absorbance at 600 nm (Figure 3A), bacterial
cell doubling is apparent (from a 1 mL sample) by the increase
of cell number up to the 3 h point. However, addition of
ampicillin retards E. coli growth, and not only levels the growth
curve (i.e., no further doubling), but the addition of ampicillin
actually leads to a reduction in the bacterial concentration.19
Similar evaluation was carried out by pipetting 5 μL aliquots
from the growth medium into microwells containing GdnHCl
and paramagnetic beads. As given in Figure 3B, the results
acquired from the pinwheel assay also illustrate a comparable
trend of bacterial growth. For the sake of simplicity, DA is
directly compared to illustrate the change of cell concentration.
Because DA does not increase linearly with cell count (Figure
2), the difference of DA between “with ampicillin” and “without
ampicillin” does not appear to be as substantial as that of the
absorbance measurement. A closer match between the
absorbance measurement and the pinwheel assay can be
obtained by converting the signals in both methods to cell
counts.
Enumeration of White Blood Cells in Whole Blood.
WBCs (leukocytes) are critical components in our defense
against foreign bodies and infectious agents. The white blood
cell count can be a generic indicator of immune system status
and is useful for clinical testing, in particular with molecular
diagnostics. The pinwheel assay has the potential to provide a
simple and rapid method for determining of WBC count.
To generate the calibration curve for WBC counting, blood
samples were drawn from four normal patients on the day of
the analysis, and the WBC counts were determined by Coulter
counter. The samples were lysed with 8 M GdnHCl and serially
diluted for pinwheel analysis. Figure 4 illustrates the correlation
between degree of aggregation and WBC count after dilution.
Curves derived from 4.1, 10.1, and 20.3 (× 103
WBCs/μL
predilution) samples overlap well with each other. The 2.3 ×
103
WBCs/μL sample, however, reproducibly yields a higher
Figure 2. Calibration curve of the pinwheel assay for cell counting. DA
is correlated with cell (or phage) concentration and fitted into an
exponential model. The sensitivity decreases from human and mouse
cells (eukaryote) to phage D29 (although not a cell), which can be
attributed to the decrease of DNA length and genome size. The x-axis
is plotted in log scale in order to illustrate the difference of calibration
curves between human and mouse cells, which have similar genome
sizes. The solid line represents an exponential calibration function
fitted to the data at logarithmic scale; the shaded area and gray lines
show the 95% and 99% confidence bands (the same for all curve
fitting, unless otherwise noted).
Figure 3. Microbial growth testing of E. coli in the presence of
ampicillin. At the 3 h mark, half the cells were dosed with buffer, while
the other half were dosed with ampicillin, as growth monitoring
continued.
Figure 4. Calibration curve of the pinwheel assay for WBC counting
directly in raw blood samples. Four blood samples, with their WBC
counts determined with Coulter counter, were analyzed with the
pinwheel assay, as represented by ▽ = 2.3, Δ = 4.1, □ = 10.1, and • =
20.3 (× 103
per μL) with associated error bar denoting the standard
deviation of three experiments on each sample. The symbol • and the
corresponding error bar denote the mean and standard deviation of
the four samples.

DA at the same [WBC]; this is because it falls outside the
dynamic range of the assay and, thus, results in a larger standard
deviation for the mean values above 40% DA. This may be
caused by components in the blood other than WBCs (e.g.,
proteins such as albumin, or a combination of protein and
divalent cations like Ca2+
), of which the concentration remains
relatively high after dilution due to the low initial WBC
concentration and low dilution factor. Elucidation of the
mechanism is currently ongoing and will be the topic of a
separate report when completed. As a result, only the region
above a DA of 60% is regarded as the effective calibration range
for WBC quantification. Therefore, DA values in that range
(>60%) must be obtained for accurate cell counting.
To evaluate the ability of the pinwheel process to enumerate
the WBCs in unknown samples, dilution is needed so that the
DA falls in the effective calibration range. By comparing the
measured value with the calibration curve, the WBC count can
be estimated following dilution ([WBC]dil), which is then
converted to the initial WBC count ([WBC]init) by multiplying
by the dilution factor. Given that the calibration curve covers
from 0.5 to 5 WBCs/μL, a 4000-fold dilution enables
quantification of blood samples with WBC count between
2000 and 20 000 per μL. Since the WBC count of adults
typically varies between 4000 and 11 000 per μL, a 4000-fold or
8000-fold dilution would be sufficient to cover the normal
range and to identify samples with abnormal WBC count.
To test accuracy of the pinwheel-derived WBC counting,
nine raw blood samples with unknown WBC counts were
acquired, lysed, and diluted appropriately. Three replicates were
performed on each sample, and the mean DA was compared to
the standard curve to determine initial WBC count. These
values were compared to those independently obtained by a
Coulter counter, and the results are given in Figure 5A. The
counts from both compare favorably for the samples with
[WBC]init ranging from 2 × 103
per μL to 14 × 103
per μL; this
covers the normal range for WBC count and suffices for
samples where there is a need to identify counts outside the
normal range (bracketed by the two dashed lines). Figure 5B
provides graphical representation of the excellent correlation
between the pinwheel results and those from Coulter counter
(R2
= 0.97).
Counting CD4+ T Cells with the Pinwheel Assay. While
effective for WBC counting, the pinwheel effect is generic
because the adsorption of DNA on silica is not specific to
genomic sequence; hence, subtyping of cells in a complex
mixture is not possible without invoking the use of a “selective”
step. We chose CD4+ T cells, a WBC subtype, as a model to
demonstrate that selectivity and pinwheel sensitivity could be
coupled in a powerful way. CD4+ T-cell levels are critical in
Figure 5. WBC counts of nine raw blood samples determined by the pinwheel assay are shown in (A) and compared with the results from Coulter
counter. (B) The WBC counts of the nine samples determined with the pinwheel assay correlate well with the results from Coulter counter. The
data points represent the mean results of three experiments on each sample, and the error bars denote the standard deviation. The solid blue line
represents a linear calibration function fitted to the data with R2
= 0.97, and the black dashed line shows y = x.
Figure 6. Immunomagnetic separation of CD4+ T cells from blood and the calibration curve for quantification. (A) Schematic of immunomagnetic
separation of CD4+ T cells from crude blood samples. Monocytes, which also express the CD4 antigen, are depleted prior to CD4+ T cells. (B)
Purified samples are serially diluted after lysis, and the calibration curve is established by correlating degree of aggregation with the CD4 count
determined by microscopy.

assessing the progress of AIDS and also in monitoring anti-HIV
treatment. CD4+ T-cell quantitation is currently accomplished
using flow cytometry, where the obvious drawbacks are high
cost, high maintenance, and poor portability. A rapid,
substantially less expensive and less complex methodology for
CD4+ T-cell counting could be valuable, especially if point-of-
care applications are to be considered. One solution to this
involves a commercial immunomagnetic separation kit. This kit
exploits antiCD4+-coated magnetic beads for isolating CD4+ T
cells from blood, but also captures monocytes (they express
CD4). However, monocytes also express CD14 on their
surface,4
allowing for antiCD14-coated beads to deplete the
sample of monoctyes, prior to the capture of CD4+ T cells
(Figure 6A). In the protocol described by the manufacturer, the
captured CD4+ T cells are partially lysed so that their nuclei
can be released and enumerated with a hemocytometer under a
microscope after staining. While labor-intensive and, in some
ways, subjective, immunocapture with microscope-based
counting certainly provides a cost-effective alternative to flow
cytometry. Studies of normal and HIV-positive individuals have
shown a correlation coefficient of 0.97 for CD4+ cell levels
relative to values from hemacytometer.
To circumvent the microscopic counting of stained cells, we
substituted this step with the pinwheel assay. With the pinwheel
process, the isolated cells are completely lysed, and pinwheel
aggregation is induced by the released DNA, allowing for
quantification of cells. The correlation between DA and cell
concentration is illustrated in Figure 6B, which provides the
calibration curve to determine the CD4+ T-cell count in blood
samples. Since the enumeration of CD4+ T cells involves
preassay isolation of the cells, the effectiveness of this process
relies on the efficient and consistent CD4+ T-cell isolation. The
mean isolation yield that was observed (calculated by dividing
the microscopic cell count with the flow cytometry count of the
original sample) was found to be 91.5 ± 4.3% for four blood
samples when the blood samples were withdrawn within 24 h.
To evaluate the accuracy of the pinwheel assay, two aliquots of
purified cells were acquired from each unknown sample, with
one partially lysed for microscopy quantification and the other
completely lysed for the pinwheel assay. Comparison shows a
good correlation between the two methods with 13 patient
blood samples (see Supporting Information Figure S2), which
suggests that the pinwheel assay can, indeed, enumerate the
isolated cells accurately.
In the clinical setting, CD4+ T-cell count can be indicative of
the immune status of a patient. When the CD4+ T-cell count is
lower, along with other factors, it can represent the progress of
HIV infection; when the count is higher, it can indicate
recovery from immunodeficiency through decreased viral load.
The pinwheel CD4+ levels in 21 blood samples following
immunomagnetic separation were compared with the results
from flow cytometry (Figure 7A,C). The collective data is from
two sample groups from two sources (8 samples analyzed same
day as blood draw; 13 samples analyzed >24 h after blood
draw). A good correlation was observed between the
immunocapture−pinwheel assay and flow cytometry, when
the samples were analyzed within 24 h of the blood draw
(Figure 7A,B). Dramatically poorer correlation between the
pinwheel and flow cytometry methods was observed with
samples analyzed more than 24 h postdraw (Figure 7C). This
observation is consistent with the observation by Diagbouga et
al. that 31%−69% of blood samples exhibit more than a 20%
decrease of CD4 count after a 24 h delay,20
which directly
affects the accuracy of the pinwheel assay.
For HIV-infected patients, initiation of ART is determined by
a CD4+ T-cell count that drops below 350 cells/μL. What we
have demonstrated here is that, with the 21 whole blood
samples evaluated from HIV patients, the pinwheel assay
correctly categorized those determined by flow cytometry to be
above or below the 350 cells/μL cut off. Only one sample (one
Figure 7. Quantification of CD4+ T cells. The pinwheel result correlates well with flow cytometry when the post-drawn time of blood is less than 24
h, as shown in (A) and (B). For the samples with post-drawn time over 24 h, the accuracy of the pinwheel assay is compromised due to the
deterioration of sample quality, as shown in (C) and (D). The solid blue lines in (B) and (D) represent linear calibration functions, and the black
dashed lines show y = x. The gray dashed lines represent the threshold (350 cells per μL) that defines the starting time of ARV for HIV patients (for
(B), R2
= 0.997; for (D), R2
= 0.775). The arrows in (C) and (D) point to the only sample that generated a false result in the pinwheel assay.

from the >24 h storage time group) was categorized as false
positive, and this point is labeled with a gray arrow in Figure
7D. Despite the asynchrony in the storage history of these
samples, this still represents a >95% correlation between the
immunocapture−pinwheel assay and flow cytometry. This is
remarkable and points to the obvious merit of a method that
does not require fluorescent reagents, microscopy, or
cytometric counting.
■ CONCLUSIONS
In conclusion, we have extended the application of the
pinwheel assay from nucleic acid quantification to cell counting,
and demonstrated (1) microbial growth testing, (2) cell
counting in a complex medium (WBC quantification in raw
blood), as well as (3) isolation and enumeration of a specific
subtype of cells from a mixture (CD4+ T cells). While we have
a simple methodology for generic cell counting, specificity was
brought to the method by coupling with immunocapture.
These examples show the versatility of the pinwheel assay (i.e.,
that the assay has the potential to be applied in various fields),
although we do not anticipate that the pinwheel assay will
replace all the conventional methods. As the aggregation of
magnetic particles only requires microliter volume of samples
and a digital camera as the detection modality, the pinwheel
assay could serve as a portable and cost-effective alternative to
conventional technologies for point-of-care applications.
One of the main advantages is that the pinwheel assay does
not require fluorescent labels and complex optics or expensive
instrumentation to enumerate cells. Fluorescence provides
accurate and sensitive quantification of analytes in various
applications, but the labels are often subject to photobleaching,
resulting in unstable optical properties, which increases the cost
for reagent storage and induces the need for repetitive
calibration. By avoiding fluorescent labels, the pinwheel assay
offers enhanced simplicity and cost-effectiveness compared to
conventional techniques, which are always desired when
applying a new technique in resource-limited regions. One of
the major drawbacks of the pinwheel assay is that the cells are
lysed after counting, and thus will not be available to other cell
analyses, which may be problematic if sample availability is
limited.
Day-to-day variability with the pinwheel method was low, a
likely result of the simplicity of the method. User-to-user
variability is more likely to be significant, but this can be
overcome by building a larger database for calibration of the
assay independent of the user. We are currently exploring
designs for integrating all of these processes on a single
microfluidic device to minimize hands-on operation and user-
to-user variabilitythis is essential for progressing toward a cell
counting device with sample-in-answer-out capability. Progress
on device development has been made in terms of enhancing
assay throughput21
and process automation.22
Successful
employment of the pinwheel assay in an integrated microfluidic
system will not only benefit basic biomedical research but also
offer capability to a wide range of clinical applications.
■ ASSOCIATED CONTENT
*S Supporting Information
Additional information as noted in the text. This material is
available free of charge via the Internet at http://pubs.acs.org.
■ AUTHOR INFORMATION
Corresponding Author
*E-mail: jpl5e@virginia.edu.
Present Addresses
■
Microlab Horizon, LLC, 705-D Dale Ave., Charlottesville, VA
22903 (J.L.)
▲
Salisbury University, 1101 Camden Ave., Salisbury, MD
21801 (A.D.)
Notes
The authors declare no competing financial interest.
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