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Advances in the Identification of Apoptotic Cells
With the ImageStream® Multispectral Imaging System
Advances in the Identification of Apoptotic Cells
Background and Summary
The ImageStream system combines the capabilities of microscopy and flow cytometry in a single
platform for quantitative image-based cellular assays
in large and heterogeneous cell populations. In the
experiment presented here, we used the capabilities
of the ImageStream system to measure both BRDU
staining and nuclear fragmentation in a TUNEL
assay a traditional assay for apoptosis. Using the
ImageStream system, we were able to identify a
common cell preparation artifact that leads to falsepositive results in non-imaging systems and thus enhance the utility of the TUNEL assay. We also independently identified apoptotic cells by their unique
nuclear morphologies as an independent validation
of the assay. These results offer one example of the
unique power of analytical morphometry.
The ImageStream system is operationally similar to
a flow cytometer but it has the ability to generate
six simultaneous images of each cell at a rate of approximately 300 cells per second, with resolution
similar to that of a fluorescence microscope. Each
cell is represented by a brightfield image, a darkfield
image and up to four different fluorescence images.
The ImageStream can thus be used to provide quantitative information about not just the prevalence of
target molecules, but also their localization within
the cell, and in statistically meaningful numbers.
The combination of these two capabilities brings
statistical robustness to image-based assays.
Apoptosis
Apoptosis, or programmed cell death, is an organized physiological process that is characterized by
significant levels of plasma membrane convolution,
cytoplasmic blebbing, and nuclear condensation and
fragmentation. This process occurs normally during cellular differentiation (e.g., embryogenesis), homeostatic regulation, and in response to insults to
cellular integrity (e.g., viral infection, DNA damage). There has been considerable interest in analyzing the various stages of apoptosis to understand the
cellular mechanisms involved. Certainly, the ability
to selectively induce or block apoptosis by pharmaceutical intervention is an area of active research.
The TUNEL Assay
The TUNEL assay (Terminal deoxynucleotide
transferase dUTP Nick End Labeling) takes advantage of the reactive 3’OH groups found on the ends
of damaged DNA and DNA undergoing degradation. In the standard assay protocol cells are fixed
and permeabilized, incubated with terminal deoxynucleotidyl transferase in the presence of bromodeoxyuridine triphosphate, and then stained simulta- Figure 1. (A) Photomicrographs of representative cell imagery (brightfield, FITC and PI) and (B) examples of dot plots showing PI intensity
(FL2) vs PRB-1 FITC intensity (FL1).
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neously with the DNA intercalating dye propidium
iodide (PI) and a FITC conjugated antibody to the
Br-dUTP (PRB-1). Since the cells are fixed, all cells
stain with PI, but only the later stage apoptotic cells
(i.e., those cells with DNA strand breaks) show up
as FITC positive. This method can be used to quantify the population of cells undergoing each stage of
apoptosis, and thus can be correlated to treatments
the cells have received. In this experiment apoptosis
was induced in human lymphoma cells, which were
then stained with the reagents provided in a commercially available reagent kit (Phoenix Flow Systems). Imagery was acquired on the ImageStream
system.
Results
Representative photomicrographs and an example
of TUNEL FACS data are shown in Figures 1A and
1B.
Occurance of False Positives in the Standard Assay
Using the typical analysis of DNA content vs.
BRDU incorporation, about 30% of the cells were
found to be TUNEL positive and therefore classified
as apoptotic. However, visual analysis of the images
associated with the TUNEL positive cells revealed a
number of false positive events (i.e., apparently viable
cells with small apoptotic bodies adhered to the cell
surface; Figure 2). Using the IDEAS® image analysis
software, we created a new morphometric feature
to identify and separate the false positives from the
overall population of cells originally identified as
apoptotic by conventional flow cytometric intensity
parameters. We also demonstrate a high degree of
correlation of cells identified as apoptotic by nuclear
morphology with those identified as TUNEL positive.
Separation of False Positive Cells
By using the morphological feature sets included in
the IDEAS software package we were able to separate
the typical apoptotic cells from the seemingly false
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Figure 2. Image galleries of apoptotic cells. A.) Representative im-
age galleries from typical apoptotic cells demonstrating cell membrane
blebbing (bright field) and pyknotic DNA (PI) as well as being BRDU
(PRB-1) positive. B.) Morphologically normal cells negative for nuclear
BRDU associated with PRB-1 positive material. The bright field image
is shown with a composite image constructed from channel 3 (PRB-1
FITC) and channel 5 (PI)
positive and clumped cells. This was accomplished
by co-localizing the signals in the PI channel and
BRDU (PRB-1) channel. Since TUNEL positive
cells are identified by DNA strand break staining,
it is expected that the location of the PRB-1 FITC
stain will overlap the PI staining. The stains will not
overlap on non-apoptotic cells that have PRB-1
material attached to their cell membranes. To distinguish these cells from TUNEL positive apoptotic
cells we plotted the difference in centroids between
the nuclear and PRB-1 images (Figure 3). Apoptotic TUNEL positive cells have PI – FITC image
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Centroid X and Centroid Y differences close to zero,
while cell clumps and non-apoptotic cells with attached PRB-1 fragments have large absolute values
for at least one of these features. It should be noted
that the centroid values are automatically calculated
by the IDEAS software, and a plot can be generated
and included as part of the analysis.
For the data plotted in Figure 3, the centroid of
the PRB-1 image was subtracted from the centroid
of the PI image. The light green population “TUNEL true positive” are cells where the FITC and PI
staining are both coming from the cell’s fragmented
nucleus (centroid difference value of 0) indicating
they are true apoptotic events.The dark green populations are cells where the TUNEL staining does not
overlap the PI staining and indicates either clumps
of cells and debris or apoptotic bodies adhering to
viable cells.
Figure 3 Centroid difference plot for PRB-1 FITC and PI images.
TUNEL true positive cells were identified by plotting the difference
in the centroid values for PI and FITC images. True apoptotic cells
where the signals overlap are centered around the 0 value on the plot.
If the populations identified in the centroid analysis defined above are backgated onto the bivariate
plot typically obtained by standard flow cytometry
(Figure 4) one can see that the true apoptotic population would be an overestimate due to the population with adhered apoptotic DNA fragments. In this
experiment, the fraction of false positive events was
approximately 15%. However, although this artifact
is likely to occur in most TUNEL assays, the fraction
of false positive cells will tend to vary significantly
with variations in sample preparation.
Identification of Apoptosis by Nuclear
Morphometry
Historically, apoptotic cells have been identified on
the basis of morphology. In particular, the condensed, fragmented nuclei of apoptotic cells can
readily be viaually distinguished from the uniform
nuclei of healthy cells. We used two morphometric
features of the PI nuclear image to identify apoptotic
cells (Figure 5). The peak-to-mean ratio measures
the ratio between the brightest pixel and the overall
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Figure 4 Bivariate dot plot of PRB 1-FITC intensity and PI-in-
tensity. PRB-1 intensity is plotted on the Y axis and PI intensity
on the X axis. Non-apoptotic events are shaded red, true apoptotic
events in light green and morphologically normal cells associated
with apoptotic nuclear fragments in dark green.
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mean intensity of the nuclear image.This feature can
be useful for identifying cells that have condensed
chromatin or pyknotic DNA, instances where the
nuclear image has high PI peak intensities. The Ch5
Small Spot Total is a morphometric feature that measures the fluorescence intensity of small local signal
maxima in the nuclear image. Apoptotic cells that
have undergone nuclear condensation and fragmentation will have higher intensities in localized regions
throughout the nucleus than normal cells where the
DNA distribution tends to be more uniform. True
TUNEL positive cells (in green) are measurably
apoptotic by nuclear morphology, demonstrating a
high degree of correlation between visually apparent
nuclear fragmentation and BRDU staining.
Figure 5 Identification of apoptotic cells by nuclear morphology.
Nuclear condensation results in high Ch5 (PI) Peak to Mean Pixel
Intensity Ratio (x-axis) values and nuclear fragmentation results in
high Ch5 Small Spot Total Intensities. TUNEL positive cells are
displayed in green.
Conclusions
The quantitative analysis of digital cell images has
grown more powerful in recent years and is already
making significant contributions to basic research
and medicine. The development of classification
algorithms allows the objective analysis of imagebased data with good statistical power.
In this study we used the quantitative power of
Flow Imaging to improve the reliability and accuracy of the TUNEL assay, a well established assay for
apoptosis. Typically, the assay results are evaluated
either with a fluorescent microscope or standard
flow cytometer. Standard flow cytometry offers the
advantage over microscopy of acquiring large numbers of events, thereby providing a strong foundation for statistical analysis. However, the fact that
a flow cytometer cannot localize signal to regions
of the cell can confound analysis. The present study
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V1
offers a clear case in point. Here, using quantitative morphometry provided by the ImageStream
100 and IDEAS image analysis software, we were
able to discriminate true TUNEL positive apoptotic cells from false positive normal cells attached to
TUNEL fragments . The discrimination depended
entirely on our visual analysis of the cells and thus
would not have been possible with a conventional
flow cytometer. We also measured apoptosis on the
basis of nuclear image morphology and were able to
correlate TUNEL positive staining with measurable
nuclear fragmentation. Again, this would not have
been possible with any other flow cytometer. The
addition of imaging capability to flow cytometry
not only enables many new applications, but can, as
in the present case, improve the accuracy, reliability
and informative value of existing applications.
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