- Wiley Online Library

q 2006 International Society for Analytical Cytology
Cytometry Part A 69A:691–703 (2006)
Hyperchromatic Cytometry Principles
for Cytomics Using Slide Based Cytometry
Anja Mittag,1 Dominik Lenz,2 Andreas O. H. Gerstner,3 and Attila T
arnok1*
2
1
Department of Pediatric Cardiology, Cardiac Center Leipzig GmbH, University of Leipzig, Leipzig, Germany
Department of Basic Medical Sciences, School of Veterinary Medicine, Purdue University, West Lafayette, Indiana
3
Department of Otorhinolaryngology/Head and Neck Surgery, University of Bonn, Bonn, Germany
Background: Polychromatic analysis of biological specimens has become increasingly important because of the
emerging new fields of high-content and high-throughput
single cell analysis for systems biology and cytomics. Combining different technologies and staining methods, multicolor analysis can be pushed forward to measure anything
stainable in a cell. We term this approach hyperchromatic
cytometry and present different components suitable for
achieving this task. For cell analysis, slide based cytometry
(SBC) technologies are ideal as, unlike flow cytometry,
they are non-consumptive, i.e. the analyzed sample is
fixed on the slide and can be reanalyzed following restaining of the object.
Methods and Results: We demonstrate various approaches for hyperchromatic analysis on a SBC instrument, the Laser Scanning Cytometer. The different components demonstrated here include (1) polychromatic cytometry (staining of the specimen with eight or more
different fluorochromes simultaneously), (2) iterative restaining (using the same fluorochrome for restaining and
In the post-genomic era, multicolor analysis of biological specimens has become increasingly important in various fields of biology, in particular because of the emerging
new fields of high-content and high-throughput single cell
analysis for systems biology (1–6) and cytomics (7,8).
Areas of research and diagnosis with the demand to virtually measure ‘‘anything’’ in the cell include immunophenotyping, rare cell detection, and characterization in the
case of stem cells and residual tumor cells, tissue analysis,
and drug discovery. Often only small sample volumes are
available or samples are very precious. In these cases, multicolor analysis enables ideally to determine all cellular
constituents of interest in a single analytical run.
The development of fluorescent dyes of organic and
inorganic origin in the recent years greatly facilitated multicolor approach. Fluorochromes emitting in the near infrared, like tandem dyes (PE-Cy7, APC-Cy7) (9–11), as well as
fluorescent nanoparticles or quantum dots (QDs) (12,13)
offer the opportunity to increase the number of simultaneously measurable fluorochromes. These developments
subsequent reanalysis), (3) differential photobleaching
(differentiating fluorochromes by their different photostability), (4) photoactivation (activating fluorescent nanoparticles or photocaged dyes), and (5) photodestruction
(destruction of FRET dyes). Based on the ability to relocate
cells that are immobilized on a microscope slide with a
precision of 1 lm, identical cells can be reanalyzed on
the single cell level after manipulation steps.
Conclusion: With the intelligent combination of several
different techniques, the hyperchromatic cytometry approach allows to quantify and analyze all components of
relevance on the single cell level. The information gained
per specimen is only limited by the number of available
antibodies and sterical hindrance. q 2006 International Society for Analytical Cytology
Key terms: cytome; iterative restaining; LSC; photobleaching; photodestruction; photoactivation; photoconversion
initially led to polychromatic cytometry, i.e., the ability to
perform up to 17-color immunophenotyping by three
laser flow cytometry (FCM) (12) or eight-color immunophenotyping using a dual laser equipped Laser Scanning
Cytometer (LSC) (14), a Slide Based Cytometry (SBC)
instrument. These approaches revealed the existence of
new cell phenotypes with discrete combinations of antigen expression or cytokine production patterns. Our group
has demonstrated that differentiation between Cy5 and
Cy5.5 tandem conjugates with close emission spectra is
possible via optical filter change and subsequent remeasurement. This method allows to simultaneously analyze
eight fluorochromes (FITC, PE, PE-Cy5, PE-Cy5.5, PE-Cy7,
*Correspondence to: Dr. Attila Tarnok, PhD, Assistant Professor, Department of Pediatric Cardiology, Cardiac Center, University of Leipzig,
Str€
umpellstr. 39, D-04289 Leipzig, Germany.
E-mail: [email protected]
Published online 5 May 2006 in Wiley InterScience (www.interscience.
wiley.com).
DOI: 10.1002/cyto.a.20285
692
MITTAG ET AL.
APC, APC-Cy5.5, and APC-Cy7) (14). The relatively low
number of cells measured by SBC as compared to FCM is
out-weighted by specific advantages. For example in SBC,
stained artifacts and debris can be excluded unequivocally
from the analysis (15) as each measured event can be visualized by relocation in order to verify results either according to forward scatter and fluorescence images or by direct
evaluation through the eyepiece of the microscope.
Furthermore, the precise storage of the location of each
measured event on the slide allows reanalysis after modifications of the specimen, e.g., restaining, or changes of
instrument settings. Both analyses e.g., before and after
restaining, can then be fused to one data file (a feature of
the LSC software called ‘‘merging’’). This approach has
been used to restain cell nuclei after immunophenotyping
(16), to combine alive and dead information (17), to analyze destaining kinetics (18), and to restain surface antigens with second and third sets of antibodies (19). A specific feature of SBC that cannot be covered by FCM is the
quantitative analysis of tissue sections. Steiner et al. (20)
demonstrated that immunophenotyping of leukocytes in
tissue sections is possible with confocal microscopy.
Gerstner et al. (21) showed three- and four-color immunophenotyping of tonsil sections, Lenz et al. (22) established
quantitative two- and three-dimensional analysis of the distribution of nuclei and neurons in brain tissue sections by
LSC. Recently, approaches have been proposed towards
the concept of 3D-cytometry of tissue sections and in tissue cultures termed Tissomics (23–25).
Polychromatic cytometry of cells by fluorescence microscopy is of special importance in two different settings:
First, in patients with low blood volume such as neonates
and in critically ill infants for whom every effort has to be
taken to reduce the blood volume needed for diagnostics.
This, for instance, can be achieved by increasing the
amount of analyzed antigens (i.e. CD or activation markers)
per sample. Second, since our view of cellular systems gets
more complex, the characterization of cell subsets makes
the use of more parameters necessary and even unavoidable (11,12,14). Therefore, highly multiplexed characterization of cells on the single cell level is a pivotal technology for single cell genomics, protemics, and cytomics
(1,2,4,7,8,26–28). With the increased number of measurable characteristics of a cell in addition with its morphological evaluation, SBC multiplexed cell analysis is a powerful
analytical and diagnostic tool. Its most important impact
can be expected in drug discovery in the pharmaceutical
research (3,29) and in predictive medicine (4,27,30–32).
In our view, SBC instruments are the ones best suited to
perform hyperchromatic analysis. Although FCM instrumentation equipped with a multitude of lasers and applying the plethora of presently available fluorescent dyes for
labeling is able to simultaneously measure 17 or probably
even more colors (12), it is hampered by its inability to
measure the identical cell repeatedly. In addition, the analysis of each individual cell’s morphology is only possible
after time consuming cell sorting or with specialized imaging flow cytometers (33) wherein the number of colors
measurable in a single run is limited. Finally, FCM systems
FIG. 1. Schematic hyperchromatic cytometry. The scheme summarizes
the different components of hyperchromatic cytometry and how these
components can be combined sequentially. At the end of one cycle and
following iterative restaining new analytical cycles can follow. The combination of these methods enables the step from polychromatic to hyperchromatic cytometry. [Color figure can be viewed in the online issue,
which is available at www.interscience.wiley.com.]
are by principle unable to analyze cells in their natural
environment (e.g. tissues, cell cultures).
In the following, we will brief on SBC technology and
then review various components of measurement or labeling that are suitable for performing hyperchromatic cytometry (Figs. 1 and 2), starting with the established technique of polychromatic cytometry. We will primarily
emphasize those components of hyperchromatic cytometry that have been tested in our laboratory. In the last
chapter, the application areas and usefulness of additional
various components will be discussed.
SLIDE BASED POLYCHROMATIC CYTOMETRY
Principle
SBC with fluorescence microscope based instruments is
an analytical technique that allows rapid quantitative analysis of a high number of individual cells in suspension, in
culture, or in tissue sections tagged with fluorescent dyes
and immobilized on a slide. Today, several SBC systems are
commercially available or under development. Some of
them rely on lasers (23,34,35) others on Arc-lamps as excitation light sources (36,37).
In the following, we will demonstrate the feasibility of
the components for hyperchromatic cytometry, using the
first commercially available SBC instrument, the LSC. The
LSC and its function is detailed elsewhere (23,38–40). LSC
Cytometry Part A DOI 10.1002/cyto.a
HYPERCHROMATIC CYTOMETRY
FIG. 2. Components of hyperchromatic cytometry. This
figure shows schematically how the different components
of hyperchromatic cytometry outlined in Figure 1 work. (1)
Analysis with different filter settings. Samples stained with
fluorochromes with similar emission spectra (e.g. PE-Cy5
and PE-Cy5.5) cannot be distinguished with one set of filters. Using different filters and subsequent merging of both
analyses enables their discrimination. (A) Schematically
stained cells seen by a filter optimal for detection of PECy5. (B) The same cells with a ‘‘Cy5.5-filter’’. (C) By merging both analyses a combined data file results with the fluorescence information from both filter sets. Also double
positive cells can be detected (e.g. Fig. 3). (2) Iterative
restaining. The sample is stained repeatedly with different
antibodies conjugated to the same fluorochrome. (A) The
first staining of a sample, (B) same sample restained with
the same fluorochrome but conjugated to another antibody,
and (C) third staining with the same fluorochrome and yet
another antibody. In a merged file, these cells can be displayed before vs. after iterative restaining. The new
emerged fluorescence shifts off the diagonal and can be
identified as a new population (e.g. Fig. 4). Cells are labeled
with arrows that receive an additional staining in the subsequent staining step, i.e., cell in A (arrow) is in (B) double labeled with two different antibodies; cell in (B, left arrow) is
triple labeled in (C). (3) Differential photobleaching. Fluorochromes differ in their photostability (e.g. Fig. 5). These
differences allow to combine fluorochromes with different
photostability. Sensitive fluorochromes can be bleached,
e.g. by laser light, and the residual fluorescence belongs to
the photostable fluorochrome. In a file that combines the
data before (A) and after bleaching (B), both fluorochromes
can be distinguished unequivocally. Arrow marked cells
demonstrate cells labeled with photosensitive fluorochromes (e.g. Fig. 6). (4) Photoactivation. Specific fluorescent dyes such as QDs can be activated to fluoresce by
light. Initial measurements generate only weak signals (A)
but after repeated scanning with the laser the fluorescence
signals increase (B). (e.g. Fig. 7). (5) Photodestruction. Tandem dyes that rely on fluorescence resonance energy transfer (FRET) produce in most cases a fluorescence signal not
only in the acceptor (A) but also in the donor channel (B).
By exposure to light, the FRET is destroyed so that the
acceptor fluorescence disappears (C), whereas that of the
donor dye increases (D). Photodestruction of FRET can
help to discriminate between FRET and non-FRET fluorescence. (e.g. Fig. 7). (6) Photoconversion. By direct exposure to light the color of certain fluorescent proteins can be
switched, e.g., the protein KAEDE turns it emission after
UV illumination from green to red. (7) Spectral fingerprinting. A completely different approach for hyperchromatic
cytometry demonstrates spectral fingerprinting where the
entire fluorescence spectrum of the cell is detected.
Cytometry Part A DOI 10.1002/cyto.a
693
694
MITTAG ET AL.
FIG. 3. Analysis with different filter settings. (A) Human peripheral blood leukocytes (PBL) were stained with CD14-PE-Cy5 and CD4-PE-Cy5.5. A differentiation of these fluorochromes emitting in a similar spectrum is possible because of the merge feature of the LSC. The 1st measurement was performed with
a filter suitable for the detection of PE-Cy5. For the 2nd measurement a ‘‘PE-Cy5.5’’ filter was used. In the merged file, one can discriminate both fluorochromes in a dotplot displaying first vs. second measurement. (B) The same sample was stained with three fluorochromes with similar emission spectra
(PE-TR, PE-Cy5, PE-Cy5.5). Three measurements were performed, each one with a different filter suitable for one of the fluorochromes. By gating for PE-TR
fluorescence and excluding the PE-Cy5 fluorescence (left dotplot) the PE-Cy5.5 and PE-TR stained cells can be differentiated in a second dotplot (right). All
figures show ungated data, measurement was triggered on forward scatter and cell size >20 lm ID. [Color figure can be viewed in the online issue, which
is available at www.interscience.wiley.com.]
like other flow and slide based technologies measures stoichiometrically expression levels of multiple cellular components simultaneously. The LSC setup is built around a conventional epi-fluorescence microscope. Fluorescence is
excited by laser light that is reflected by mirrors onto the
specimen. The laser sources used are an Argon laser for
blue light (488 nm) excitation and a red light emitting Helium–Neon laser (633 nm). Optionally, also a violet (405
nm) or a green laser (543 nm) can be included. The slide is
scanned by the laser light and the emitted fluorescence is
collected by up to four photomultiplier tubes (PMTs) each
detecting light of a certain bandwidth defined by optical filters. Additionally, the light scattered by the objects on the
slide is detected by a photodiode. The measured signals of
a scanned field are reconstructed to pixel-per-pixel-maps
(i.e. images) for all fluorescence or scatter channels. These
images are used to define the objects of interest and to acquire cytometric data on a single-cell basis in the various
channels. After one field has been analyzed by the software,
the microscope stage moves to the next field to be
scanned, performs the next analysis and so on, until the
whole scan area has been analyzed.
The system produces data similar to FCM in listmode
3.0 format, with the unique feature that also the x- and ycoordinates of the cells’ position are stored with the fluorescence and forward scatter data; based on this feature,
cells can be relocalized any time after the measurement.
The advantage of this relocalization feature is obvious, for
example, the same specimen can be measured several
times with different instrument setups or after restaining
with new labels. These separate measurements can be
brought together into a single data file by a calculation
process named ‘‘merging’’. This merging process creates a
virtual data file where all cells with identical x–y-coordinates in the different analyses are identified as being the
same cell. With this feature, the information density
gained for each cell is increased. This approach has been
used by us to restain slides after immunophenotyping by a
conventional morphological hematoxylin-eosin stain and
to relocalize single cells for morphological analysis in solid
tumors (41), fine needle aspirate biopsies (42), cytological
swabs (43), and peripheral blood leukocytes (44).
LSC Settings
Instrumentation and software of the LSC is explained in
detail elsewhere (38–40). In the standard instrumentation,
the following bandpass filters are used: 530/DF30 (green),
580/DF30 (orange), 625/DF28 (red), and a 650 nm long
pass filter (far red). For the detection of Cy5.5 and Cy7
tandems, filter cubes in position No. 3 and No. 4 were
replaced as described in detail by Mittag et al. (14). In
brief, filter configurations of the LSC for the detection of
these dyes are 530/30 nm (No. 1, green), 580/30 nm (No.
2, orange), 670/20 nm (No. 3, red, detection of PE-Cy5/
APC), 710/20 nm (No. 3, red, detection of PE-Cy5.5/APCCy5.5), and 810/90 nm (No. 4, far red). This filter configuration enables simultaneous measurement of eight different fluorochromes.
Analysis with Different Filter
Settings—Polychromatic SBC
Originally, the filter settings of the LSC were adapted for
the detection and differentiation of up to five different
fluorochromes in a single run. With slightly modified filter
configurations, adapted for the detection of Cy7 tandems,
six different fluorochromes per analysis can be analyzed on
a 2-laser LSC (FITC, PE, PE-Cy5, PE-Cy7, APC, APC-Cy7)
(45). Distinguishing more fluorochromes is not possible
Cytometry Part A DOI 10.1002/cyto.a
HYPERCHROMATIC CYTOMETRY
with a single scan because of the limited number of PMTs
and spectral overlap of dyes with close-by emission spectra.
With two new tandem dyes, i.e. PE-Cy5.5 and APCCy5.5 (46), with an emission spectrum between Cy5 and
Cy7, fluorochrome number could be increased. Emission
spectra of the Cy5.5 conjugates are very similar to those
of their Cy5 equivalents. Those colors would normally not
be distinguishable with the standard filter settings of the
LSC. With different filters and subsequent remeasurement,
however, discrimination of Cy5 and Cy5.5 are possible by
LSC (Fig. 3A). This method is used for eight color immunophenotyping (14) by adding PE-Cy5.5 and APC-Cy5.5 to
the original six color panel (37). To this end, a blood sample is simultaneously stained with all eight fluorochromes
conjugated to different antibodies. The first measurement
is performed using a filter suitable for both PE-Cy5 or APC
fluorescences (670/20 nm); with these filter settings it is
not possible to distinguish between Cy5 and Cy5.5 conjugated antibodies. For the second measurement instead a
filter optimized for the detection of Cy5.5 tandems (710/
20 nm) is used and the identical sample is measured again.
All other instrument settings except the filter change are
kept identically throughout both measurements. Finally,
to combine the data of both measurements, both the *.fcs
data files are merged by the software (Fig. 2.1). The technique of subsequent filter changing from polychromatic
cytometry can be included to further increase fluorescence number.
With filter changing other fluorochromes can also be
added, without major modifications to the instrument,
e.g. PE-Texas Red (Fig. 3B) for nine-color polychromatic
SBC. To this end, either a third measurement can be performed with a bandpass filter suitable for the detection of
this fluorochrome (625/28 nm) or the second measurement can be performed with the ‘‘PE-TexasRed filter’’ in
position No. 2 and the ‘‘Cy5.5 filter’’ in position No. 3 in
order to reduce the time needed for analysis.
METHODOLOGICAL APPROACHES TOWARDS
HYPERCHROMATIC CYTOMETRY
Although eight to nine colors can be used for the simultaneous quantitation of cellular components and functions
(14), this number of parameters is far too low for unraveling the cytome (26,28). Because of its limitations (in general 4 PMTs), a multicolor analysis by LSC with a single
scan is difficult. The major advantage of any SBC system is
that the samples are not lost after analysis. This allows reanalyzing the same specimen, resulting in two or more
measurements of the identical specimen. These different
measurements can be combined based on the x–y-positions of every measured event. A new, merged *.fcs data
file is generated with the fluorescence information for
each cell from both measurements. These data can be displayed as separate parameters, i.e. virtual colors. There
are several ways to exploit the relocation and merge feature in order to generate virtual colors, and we termed the
combination of these different methods hyperchromatic
SBC (a scheme of the hyperchromatic cytometry concept
is shown in Fig. 1). In the following sections, the various
Cytometry Part A DOI 10.1002/cyto.a
695
FIG. 4. Iterative restaining. Human PBLs were stained with CD14-PE
and the 1st measurement was performed. Thereafter, the coverslip was
removed and the sample was restained with CD4-PE as described by Laffers et al. (10). The 2nd measurement was merged with the first. When
plotting the 1st vs. the 2nd PE-fluorescence, monocytes (CD141) line up
along the diagonal whereas the CD41 cells shift off the diagonal because
of their newly labeled 2nd staining (arrow).
components of hyperchromatic SBC are described in
detail. Figure 2 shows schematically the different components for hyperchromatic cytometry.
Different Antibodies with Identical
Dyes—Iterative Restaining
For substantially increasing the density of information
obtained from a sample, iterative restaining can be performed (19). Iterative restaining has already been included
by Schubert and coworkers into their location toponomics
analysis, a highly multiplexed analysis of tissues (47,48),
and was termed iterative fluorescence tagging. For this
approach, a 1st staining with directly labeled antibodies
and a 1st analysis is performed. Then a 2nd staining with
different antibodies labeled with the same fluorochromes
and a subsequent 2nd analysis is done. These steps can be
repeated (i.e. iterative restaining) for a 3rd staining with a
3rd analysis and so on (Fig. 2.2). The files of the analyses
are merged. In this merged data file, the identical colors
appear as different parameters according to the respective
measurement/analysis (e.g. ‘‘PE 1st staining’’ and ‘‘PE 2nd
staining’’). For data display, the intensity of a dye in the 1st
staining is plotted against its intensity in the 2nd staining
(Fig. 4); cells with unchanged fluorescence in the 1st and
the 2nd staining will line up in a diagonal. In contrast,
cells that were newly labeled in the 2nd staining shift off
that diagonal. The same analysis can be applied for the 3rd
staining. In conclusion, this approach is unique to SBC
and yields new virtual colors that are not available to
696
MITTAG ET AL.
ALEXA Dyes—Differential Photobleaching
FIG. 5. Differences in photostability. ALEXA dyes are less susceptible to
photobleaching by laser excitation than their commonly used analogs.
This allows to combine FITC and ALEXA488, PE and ALEXA532, or APC
and ALEXA633. The fluorescence intensity of the ALEXA dyes decreases
only very slightly, whereas their analogs loose 40–80% of their fluorescence after 17 scans. Because of these substantial differences in photostability, it is possible to discriminate ALEXA from its color analogue in
the same channel after 5–10 scan steps (e.g. Fig. 6). Data were determined on human PBL labeled with CD3-biotin and streptavidin conjugated to one of the aforementioned fluorochromes.
FCM. The advantage is that the need to compensate for
fluorescence spill-over is reduced, since only three or four
fluorochromes are used; compensation is far more complicated when running polychromatic assays (49). By iterative restaining, experimental protocols can be improved
in that each cell serves as its unlabelled control, thereby
improving the detection sensitivity. In addition, a bleaching step can be included before each restaining to further
improve sensitivity (47,48).
As introduced by Panchuk-Voloshina et al. (50), the series
of so called ALEXA dyes have emission spectra similar to
commonly used fluorochromes. However, ALEXA dyes and
their conjugates are more photostable than their conventional analogs (Fig. 5). In SBC these differences in photostability can be exploited as additional parameters for
increasing the simultaneously measurable fluorochromes
(51). To this end, the sample is stained together with conventional fluorochromes such as FITC, PE, or APC, and analog ALEXA dyes (ALEXA488, ALEXA532, ALEXA647). The
sample is then analyzed using the appropriate filters. This
1st measurement does not allow discrimination between
conventional and ALEXA dyes. As a next step, the sample is
photobleached by repeated scanning with the laser.
Because of the differences in the photostability, this step
will differentially bleach the conventional dyes but the
ALEXA dyes will remain almost unchanged. After photobleaching, the sample is measured for a 2nd time (Fig. 2.3).
The pre- and post-bleaching data are merged into a new
*.fcs-file. Per channel a dotplot is created displaying the respective fluorescence before versus after photobleaching.
Since ALEXA-stained cells keep their signal unchanged or
are only moderately affected by photobleaching, these cells
will line up in a diagonal; cells stained with conventional
dyes, however, lost their signal by photobleaching and
therefore drop off the diagonal. This is exemplified for the
pair of PE vs. ALEXA 532 in Figure 6.
Quantum Dots—Photoactivation
In the previous years, fluorescent nanoparticles or QDs
that are based on semiconductor technology became of eminent importance for staining of biological material (52–54).
FIG. 6. Differential photobleaching. Merged file of the first and the second measurement of cells stained with CD3-ALEXA532 and CD4-PE. All stained
cells are located near a diagonal. After 10 scans the intensity of the PE fluorescence is decreased substantially more than the fluorescence of ALEXA532.
ALEXA5321 cells are still located near the diagonal, whereas the PE1 cells differ towards the axis of the last measurement (B, merge of measurement 1 and
12). In this example CD4 cells can be distinguished in the CD3 subset (CD3141, arrow) and a CD41 subset with low CD4-expression level and lack of CD3
is detectable (lower arrow).
Cytometry Part A DOI 10.1002/cyto.a
HYPERCHROMATIC CYTOMETRY
697
FIG. 7. QDs—photoactivation. In this experiment, peripheral blood leukocytes were labeled with antiCD3-biotin followed by labeling the biotin with
Streptavidin QD 605. This should label all T-lymphocytes that make about 30% of all cells. However, excitation with the Argon laser (488 nm, 10 mW) leads
to a very weak signal (black curve in A; left dotplot in B) and the labeled T-cells are hardly detectable. The fluorescence intensity increases following
repeated excitation with the same laser. After 15 remeasurements, the QD labeled cells become brighter and a small population of cells is now visible (dotplot in B right, population to the right of the gray curve in A). Note: The residual unlabelled cells become slightly dimmer, probably due to bleaching of
autofluorescence. QDs are excitable in the blue range, but their optimal absorption is in the UV range. Therefore, photoactivation seems to be more efficient in the UV as also preliminary experiments from our lab suggest. [Color figure can be viewed in the online issue, which is available at www.interscience.
wiley.com.]
QDs are of high relevance to polychromatic analysis as on
the one hand their fluorescence exhibits an eminent Stoke’s
shift (excitation maximum in the UV but emission up to near
IR depending on the QD type) and on the other hand they
can be produced in many different colors (the QD color is
directly correlated with their size). Their high Stoke’s shift
allows measuring the specific fluorescence far away from the
cells autofluorescence signal and without interference from
organic fluorochromes. The fluorescence emission spectra
have a Gaussian shape. This property reduces spill-over
between near-by colors and allows the use of tighter and
more specific bandpass filters in front of the PMTs. Presently,
about 10 different QD color flavors are commercially available ranging from violet to near IR. This number could be
substantially increased by producing particles of very homogenous size, thus much smaller bandwidth of fluorescence
emission.
There is an additional special feature of Qdots that makes
them of particular relevance to hyperchromatic cytometry
by offering an additional possibility to generate virtual colors: QD fluorescence can be photoactivated. We observed
with QDs that by an initial scan, only a very weak emission
could be excited by the Argon-laser (Fig. 7A, black line).
However, after repeatedly scanning the same sample with
the Argon-laser, a substantial increase of the fluorescence
intensity was detected in that subset of cells that was labeled with the antibody (scheme in Fig. 2.4, example in Figure 7A, gray line and dotplots in Fig. 7B). This phenomenon,
termed photoactivation, was observed by us and others
(55,56). Both components of hyperchromatic cytometry, differential photobleaching, and photoactivation can be implemented simultaneously to generate virtual colors. To this
end, a sample is stained with antibodies conjugated to sets
of three fluorochromes of similar spectra (e.g. APC,
ALEXA647, and QD655). Analysis is identical to that
Cytometry Part A DOI 10.1002/cyto.a
described for differential photobleaching. The first analysis
before photobleaching and photoactivation and the second
analysis afterwards are merged to one file. Again, per channel, a dot plot is generated displaying the fluorescence before
versus after photobleaching and photoactivation. In this plot,
cells with unchanged signal (i.e. ALEXA stained cells) will line
up in a diagonal, cells with bleached signal (conventional
dyes) will drop off the diagonal, and cells with activated fluorescence (QD stained cells) will shift off the diagonal. This
allows detecting and differentiating three fluorochromes with
similar spectra in one channel, yielding three virtual colors.
Utilization of Tandem Dyes—Photodestruction
Tandem dyes are a formation of two different fluorochromes in very close proximity (<10 nm). Between these
fluorochromes a fluorescence resonance energy transfer
(FRET) from the donor dye exited by the laser to an appropriate acceptor dye occurs; as a result the emission of the
donor serves as excitation of the acceptor. This transfer
can be destroyed by repeated excitation with laser or UVlight. Especially, Cy7 tandems are very susceptible to light.
Photodestruction of FRET results in an increased fluorescence emission of the donor and a decreased fluorescence
emission of the acceptor (Fig. 2.5). This can be exploited
to obtain virtual colors: A sample is stained with a tandem
dye. In the first measurement, not only the fluorescence
of the acceptor dye (e.g. Cy7) is detectable but to some
extent also the fluorescence of the donor dye (e.g. PE). After photodestruction of FRET, the sample is analyzed again
and the two .fcs-files are merged. In two displays plotting
the fluorescence of the donor and acceptor, respectively,
before versus after photodestruction cells stained with
FRET-dyes will exhibit loss of acceptor emission and gain
of donor emission (Fig. 8).
MITTAG ET AL.
698
Experimental Dyes—Photoconversion
and Photocaging
Recent research has led to the development of fluorescent proteins that change their conformation upon excitation with light of a given wavelength. This phenomenon
called photoconversion is exemplified by the protein
KAEDE (57); its emission turns from green to red after UV
illumination (Fig. 2.6). Although initially developed for the
study of living cells, it could be exploited to generate virtual colors for multicolor immunophenotyping. The same
might apply for the technique of photocaging (58–60); in
this maneuver a fluorochrome is ‘‘caged’’ in a substance
that quenches its emission. However, the caging substance is itself photosensible and can be destroyed by illumination. This can be used to free the fluorochrome that
previously was hidden.
Spectral Fingerprinting
A completely different approach could be achieved by
detecting the entire fluorescence spectra instead of separated spectral windows. To perform this type of analysis,
PMTs must be replaced by a spectrometer. The information obtained would then consist of the entire fluorescence spectrum of each cell (Fig. 2.7). This can be
achieved by a standard confocal laser scanning microscope where the pinholes are opened so that it is running
a non focal mode, i.e. depth of focus should be around
30–50 lm to collect whole cell, cytometric information
(35). An alternative approach could be to replace optical
filters by acoustic optical tunable filters (AOTF) that
allows changing the property of the detected light by the
PMTs within subseconds (61).
Including Structural Resolution—Location
Proteomics, Toponomics
The aim of cytometric analysis is to collect stoichiometric
information of cell constituents based on the fluorescence
intensity of labeled reporter molecules. Therefore, in SBC,
samples are measured with high speed, relatively low resolution and high focal depth to avoid photobleaching that
hampers quantitative analysis and for increased throughput.
However, the stained objects also contain structural information that is of importance to understand relationships of cells
within a tissue and of molecules inside and outside a cell.
This information can be obtained by going to higher resolutions and for example include confocal microscopic analysis.
Higher resolution images may need longer exposure times
and higher excitation power and have lower focal depth, so
that confocal analysis (unless the depth of focus is increased
to the cells hight) is not strictly cytometric. Therefore, the
samples should be analyzed first in a cytometric setup and
then reanalyzed with high structural resolution. In the end,
both sets of information need to be merged on a cell-by-cell
basis by appropriate software solutions.
Several other groups have started to take morphology
into account for systems biology and cytomics. Murphy
and coworkers (62,63) use the distribution of molecules
within the cell for automated cataloguing of cell pheno-
types and activity states. On the basis of 2D and 3D
images, they developed hierarchical trees of structural
relations (Location Proteomics) by which the software
automatically recognizes and classifies different molecules
in different states of the cells development. Schubert
(47,48) presented a method to monitor and catalogue the
relationship of dozens of antigens in the identical specimen for their MELK (Multi Epitope Ligand ‘‘Kartographie’’)
technology. To automatically and unequivocally recognize
individual cells within tissues — a task still difficult to be
performed by image analysis — different technological
approaches are applied, including machine vision (25,64),
tissue cytometry (65), object-oriented image analysis for
high content screening (66) and on the LSC multiple
thresholding (21) and phantom contouring (67). Finally,
monitoring and cataloguing of multicellular arrangements
and 3D interrelationship of cells in tissues or even in living
objects by concepts like Tissomics (24,64) is the last challenge for quantitative analysis.
DISCUSSION
Hyperchromatic cytometry is a novel analytical approach
intended to significantly increase the depth of information
gained on the basis of individual cells by the intelligent combination of different analytical and preparation steps (Figs. 1
and 2). In this paper we have presented different components of the method that can be combined appropriately to
achieve this highly multiplexed cell analysis. The ideal
instrument for hyperchromatic cytometry is the fluorescent
microscope with an imaging system that enables for SBC
analysis and repositioning capabilities. Identical cells can be
reanalyzed for getting more (virtual) colors, and on the
other hand an in-depth view of the detailed morphology of
every individual cell can be obtained.
FCM can distinguish more fluorochromes in a single analysis than any SBC instrument. As published by Perfetto et al.
in 2004 (12), it allows nowadays to differentiate up to 17 colors and two light scatter signals per measurement. This
result is achieved by the use of three lasers (an additional UV
laser is applied) for excitation. SBC seemed still far away
from these possibilities: the highest number of fluorochromes that can be differentiated with LSC was recently
increased to eight (14) in an SBC instrument and also to 8
with a confocal microscope combined with spectral deconvolution (35,65). Up to now this was the highest number of
fluorochromes that could be used for immunophenotyping
in a quantitative fluorescence microscopic assay.
By hyperchromatic cytomery, however, virtually anything
in one cell becomes measurable.
Polychromatic cytometry (14) is the basis of hyperchromatic cytometry and can be combined with one or more
of the other components like iterative restaining, differential photobleaching, photoactivation, photodestruction,
photoconversion, and structural analysis. Special features
of each of these components are outlined below. Careful
calibration and standardization (see also below) needs to
be performed while setting up these types of analysis.
Iterative restaining is an elegant way to measure subsequently a high number of antigens in the identical speciCytometry Part A DOI 10.1002/cyto.a
HYPERCHROMATIC CYTOMETRY
699
FIG. 8. Tandem dyes—photodestruction. Some tandem dyes are very susceptible to light. The FRET from the donor to the acceptor dye is destroyed by
several excitations with a laser. This results in a changed ratio of donor and acceptor fluorescence as shown in the following. (A) Cy7 fluorescence (acceptor) is decreased after six measurements, whereas the fluorescence of the donor (PE) is increased. (B) Merged file of measurement 1 and 6 of a sample
stained with CD4-PE-Cy7: the Cy7 fluorescence is barely detectable after six measurements whereas a strong PE signal has appeared. [Color figure can be
viewed in the online issue, which is available at www.interscience.wiley.com.]
Cytometry Part A DOI 10.1002/cyto.a
700
MITTAG ET AL.
men. By using just a few fluorochromes at each step and
intermittent bleaching steps to get rid of the undesired fluorescence from the previous staining step fluorescence
spill-over can be limited to a minimum. This approach was
led to the extreme by Schubert, using a single fluorochrome (FITC) (47) or the combination of two chromosomes (FITC and PE) at each step (48) for measuring up to
20 antigens in the identical cell. The author discussed that
measuring subsequently up to 100 antigens for Toponomics is feasible. One has here to take into account that
after each staining step the detected antigen expression
level may appear lower due to altered antigenecity induced
by photodestruction, reduced stainability, or other reasons.
Concurrently, the authors stressed that controls have to be
carefully performed using the same antibody at various
steps of iterative restaining in order to ascertain that the
antigen is stained similarly independent if it is used in the
first or in the last run. We demonstrated for human peripheral blood leukocytes (19) that for most antigens tested fluorescence intensity is clearly reduced in subsequent staining steps. Still, in the case of highly expressed antigens,
brightness was sufficient for phenotyping.
Iterative restaining can easily be combined with polychromatic cytometry, i.e. at each step six or more fluorochome labeled detector molecules are applied simultaneously. In order to keep the advantage of low spill-over,
dyes that are excited by different lasers should be combined (e.g. blue excitation (FITC, PE, PE-Cy7), green excitation (Texas Red), red excitation (APC, APC-Cy7)). By this
improvement, the time needed to analyze the same number
of antigens could be reduced by an order of magnitude.
Best suited for iterative restaining are specimens that
are sticking strongly to the microscope slide and will not
be washed away during restaining (i.e. sections, adherent
cells, tissue cultures). Non-adherent cells such as peripheral blood leukocytes as we have used in our experiments
are less well suited. These cells have to be immobilized either by centrifugation or by embedding into highly viscous mounting media. Both processes may affect the availability of their antigens for staining.
Differential photobleaching, photoactivation,
photodestruction, and photoconversion
The beauty of all methods where fluorescences are modified by light is that no mechanical manipulation is included.
This method is not only technically simpler to perform but
also non-adherent cells can be easily analyzed hyperchromatically by combinations of polychromatic staining and
methods manipulating fluorescences with light.
Differential photobleaching has been first applied in microscopic imaging to combine analysis of two dyes with
similar emission spectra (FITC with ALEXA488) (50). We
were the first to demonstrate that this approach is also feasible for SBC (51). Differential photobleaching is very conveniently combined with polychromatic cytometry as
ALEXA or Cy analogues, with higher photosensitivity
existing to virtually all standard organic fluorochromes.
Photobleaching can also be easily combined with photo-
activation and photoconversion, as in the latter, fluorescence
does either not change or increase.
Photoacivation of QDs has several important aspects for
hyperchromatic cytometry as detailed in the methodology.
Background fluorescence is virtually absent because high
Stoke’s shift and QDs are virtually unbleachable. The tendency to blink in an irregular fashion at least of some types
of QDs (13) may hamper quantitation of fluorescence intensity and requires careful testing. Another aspect of QDs is
probably more critical for hyperchromatic analysis. We
have observed that excitation of QDs for a long period of
time not only increases their brightness but also induces a
shift of the emission to shorter wavelengths. The exact reason for this behavior is unclear and may be due to destruction of the outer shell of the particle. Again, careful testing
is required when setting up an experimental protocol.
Photodestruction is useful for distinguishing signals of
FRET-dyes from those of other conventional fluorochromes.
Although the latter will get dimmer, for FRET dyes the fluorescence intensity ratio of donor to acceptor will increase.
Thereby a signal of a PE labeled antibody can be distinguished from the PE signal of a PE-Cy5, PE-Cy5.5, or PE-Cy7
labeled antibody. This signal can be subtracted from the original (unbleached) PE signal to yield the PE-only fluorescence intensity.
Photoconversion like photoactivation have both the
enchanting properties that signals are virtually invisible
before conversion or activation takes place. Because after
photocenversion conventional organic dyes fluoresce the
problems discussed for QDs will not apply. A photoconversion step can be applied after the original fluorescence
from the organic dyes was bleached (and documented) so
that the photoconverted signal appears in a background
free environment.
By spectral fingerprinting one gets rid of the uncertainty
as to what extent a given dye spills over into the emission
signal from another dye. This approach was successfully
applied by Ecker and Steiner (65) who were able to distinguish up to eight different colors in tissue sections. However, there is also an advantage in using different PMTs for
the different colors. In many spectral imaging microscopes the fluorescence spectrum is detected by an array
of PMTs that are set to the same sensitivity. If now a bright
signal from one cell constituent is measured in parallel
with a dim signal from another, the first may be out of
range if we want to detect the second or vice versa. With
multiple separate PMTs, the sensitivity of each of them
can be set to fit the brightness of the signal in the cell.
Calibration and standardization are key issues and special
care needs to be taken for them in hyperchromatic cytomery. By principle, all (optical) manipulations that affect the
fluorescence emission are contradictory to cytometric analysis because the measured fluorescence intensities will be
modified and will not strictly represent antigen expression
levels. When samples are iteratively restained, those antigens that are stained in later steps may artificially present
reduced fluorescence intensity (19). This is either due to
loss of antigen availability, photodamaging of the antigen,
or other reasons. Therefore, we recommend using the fluoCytometry Part A DOI 10.1002/cyto.a
HYPERCHROMATIC CYTOMETRY
rescence intensity signals before further manipulation to
quantify expression levels. The signals detected after manipulation serve as phenotypic markers in order to pin-point
to which sub-type the cells belong.
With some additional effort, however, these signals may
be standardized to yield cytometric data. To this end, one
can apply control cells of known antigen expression that
are treated identically to the unknown specimen. For
example, samples from healthy individuals can be used for
the calibration of antigen expression levels on human leukocytes (68). Alternatively, all antigen expressions are
tested in a permutating order within the flow of the hyperchromatic staining and changes are precisely recorded
(i.e. without manipulation vs. after manipulation). These
data serve for each antigen as a calibration data base that
then can be used to recalibrate fluorescence intensities.
Essential is that all preparation and manipulation steps are
strictly standardized and reproducible. This demand could
be fulfilled by automating the whole process of hyperchromatic preparation steps.
One can expect that there will be a natural upper limit
of the number of parameters that can be measured in a cell.
This is not so much due to the technical limitations of the
instruments but to sterical hindrance of the reporter molecules that are placed into the cell. Using non-saturating concentrations of antibodies or other markers can help to
avoid this problem (48), but it has to be taken into account
that fluorescence intensities may be affected. It would be
useful for iterative restaining to remove all previous markers from the cell before the staining step. But this will
need the use of proteases or detergents with the unpredictable side-effect of destructing antigens of interest.
Another possible problem that could occur in hyperchromatic cytometry and may need careful analysis is the
phenomenon of unwanted FRET in the case that two different molecules are located very close to each other. If
the expression level of each of the molecules should be
recorded this is clearly not desired. Therefore, careful
experiments have to be done to rule out fluorescence
quenching (or enhancement) by FRET.
Repositioning of the objects after manipulation with a
precision of 61 lm is sufficient if measurements are performed in a low resolution as is the case with the LSC.
Here, the major issue is that cells from two measurements
are identified as being identical based on their position in
an area of about 5 lm. If, however, a high structural resolution is required as in the case of toponomics or location
proteomics, a highly precise pixel based recognition of
identical positions from different images of the same
object is crucial. Because of imprecision of motorized
microscope stages errors in repositioning will naturally
accumulate the more often we reanalyze the sample. This
will even become worse if we have to remove the specimen from the stage for staining and then replace it again.
Obviously, intelligent software solutions are necessary to
unequivocally combine the different images acquired by
hyperchromatic cytometry.
The advantages of SBC systems for high-content cytomics
analysis by hyperchromatic cytometry are evident. The
Cytometry Part A DOI 10.1002/cyto.a
701
cells of interest remain immobilized on the slide. This on
the one hand is pivotal to make hyperchomatic detection
possible at all. On the other hand, relocation is important
for the visual inspection of cells of interest and their morphological documentation. This forms an input for the
automated high-resolution structural analysis of the specimen. Structural analysis requires high spatial resolution but
only to a lesser extent unperturbed fluorescence intensity.
Therefore, cytometric data should be obtained first, followed by structural analysis. The combination of both cytometric and quantitative structural data tremendously boosts
the information gained per cell.
To perform hyperchromatic cytometry as a routine
technique in future, new instruments and new computational solutions are required. Instruments have to be
developed that enable automatize staining, analysis, and
photo-manipulation. Presently, several slide based instruments are under development that can at least partially
fulfill this demand [e.g. 34]. New fluorochromes that have
very specific features (e.g. photoconversion at very specific wavelengths) need to be developed to more specifically modify fluorescences. New detection molecules
smaller in size such as RNA aptamers (69) are essential
to reduce sterical hindrance. Finally, solutions for combining, analyzing, and documenting the tremendous
amount of data collected by hyperchromatic analysis
have to be found [examples approaching this point in
Refs. 48,62,70].
The possibility to analyze genomic and proteomic properties of whole cell populations on the single cell level in
their natural environment is important to unravel the complexity of cells and cell systems. It opens the way to better
understand complex processes in health and disease and
could be an important tool for predictive and preventative
medicine. Cytomics and systems biology can show information of the present status and diagnosis, and consequently
allow an individualized therapy as a general practice of
medicine (2,4,7,31,32,71). Furthermore, with hyperchromatic cytometry novel cell types might be recognized not
detectable with presently available methods. With the proposed methods in theory, the amount of detectable cell
characteristics is only limited by sterical hindrance. Hyperchromatic cytometry is, therefore, conceived as a joint
cross-disciplinary effort for cytomics, systems biology, and
high-throughput-oriented research for basic, clinical, and
industry scientists [1–4,7,8,26,30–32].
LITERATURE CITED
1. Kitano H. Computational systems biology. Nature 2002;420(6912):206–
210.
2. Kriete A, Eils R, editors. Computational Systems Biology. Burlington:
Elsevier Academic Press; 2006.
3. Hood L, Perlmutter RM. The impact of systems approaches on biological problems in drug discovery. Nat Biotechnol 2004;22:1215–1217.
4. Hood L, Heath JR, Phelps ME, Lin B. Systems biology and new technologies enable predictive and preventative medicine. Science 2004;
306:640–643.
5. Sachs K, Perez O, Pe’er D, Lauffenburger DA, Nolan GP. Causal protein-signaling networks derived from multiparameter single-cell data.
Science 2005;308(5721):523–529.
6. Pelkmans L, Fava E, Grabner H, Hannus M, Habermann B, Krausz E,
Zerial M. Genome-wide analysis of human kinases in clathrin- and
caveolae/raft-mediated endocytosis. Nature 2005;436(7047):78–86.
702
MITTAG ET AL.
7. Valet G. Cytomics: An entry to biomedical cell systems biology. Cytometry A 2005;63A:67–68.
8. Kriete A. Cytomics in the realm of systems biology. Cytometry A
2005;68A:19–20.
9. Beavis AJ, Pennline KJ. ALLO-7: A new fluorescent tandem dye for use
in flow cytometry. Cytometry 1996;24:390–394.
10. Roederer M, Kantor AB, Parks DR, Herzenberg LA. Cy7PE and Cy7APC:
Bright new probes for immunofluorescence. Cytometry 1996;24:191–
197.
11. Roederer M, De Rosa S, Gerstein S, Anderson M, Bigos M, Stovel R,
Nozaki T, Parks D, Herzenberg L, Herzenberg L. 8-Color, 10-parameter
flow cytometry to elucidate complex leukocyte heterogeneity. Cytometry 1997;29:328–339.
12. Perfetto SP, Chattopadhyay PK, Roederer M. Seventeen-colour flow
cytometry: Unravelling the immune system. Nat Rev Immunol 2004;
4:648–655.
13. Jaiswal JK, Simon SM. Potentials and pitfalls of fluorescent quantum
dots for biological imaging. Trends Cell Biol 2004;14:497–504.
14. Mittag A, Lenz D, Gerstner AOH, Sack U, Steinbrecher M, Koksch M,
Raffael A, Bocsi J, Tarnok A. Polychromatic eight color slide-based
cytometry for the characterization of NK NK-T subsets. Cytometry A
2005;65A:103–115.
15. Bedner E, Halicka HD, Cheng W, Salomon T, Deptala A, Gorczyca W,
Melamed MR, Darzynkiewicz Z. High affinity binding of fluorescein
isothiocyanate to eosinophils detected by laser scanning cytometry.
Cytometry 1999;36:77–82.
16. Clatch RJ, Foreman JR. Five-color immunophenotyping plus DNA content analysis by laser scanning cytometry. Cytometry 1998;34:36–38.
17. Li X, Darzynkiewicz Z. The Schrodinger’s cat quandary in cell biology:
Integration of live cell functional assays with measurements of fixed
cells in analysis of apoptosis. Exp Cell Res 1999;249:404–412.
18. Bedner E, Du L, Traganos F, Darzynkiewicz Z. Caffeine dissociates
complexes between DNA and intercalating dyes: Application for
bleaching fluorochrome-stained cells for their subsequent restaining
and analysis by laser scanning cytometry. Cytometry 2001;43:38–45.
19. Laffers W, Mittag A, Lenz D, Gerstner AOH. Iterative re-staining as a
pivotal tool for n-color immunophenotyping by slide-based cytometry. Cytometry A 2006;69A:127–130.
20. Steiner GE, Ecker RC, Kramer G, Stockenhuber F, Marberger MJ. Automated data acquisition by confocal laser scanning microscopy and
image analysis of triple stained immunofluorescent leukocytes in tissue. J Immunol Methods 2000;237:39–50.
21. Gerstner AOH, Trumpfheller C, Racz P, Osmancik P, Tenner-Racz K,
Tarnok A. Quantitative histology by multicolor slides-based cytometry. Cytometry A 2004;59A:210–219.
22. Lenz D, Mittag A, Mosch B, Bocsi J, Arendt T, Tarnok A. Tissomics:
Two- and three-dimensional distribution of nuclei in brain tissue using
Laser Scanning Cytometry (LSC). In: Conchello J-A, Cogswell CJ,
Wilson T, editors. Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XII. Proceedings of the SPIE;
2005. Vol. 5701, pp 101–111.
23. Tarnok A, Gerstner AO. Clinical applications of laser scanning cytometry. Cytometry 2002;50:133–143.
24. Ecker RC, Tarnok A. Cytomics goes 3D: Toward tissomics. Cytometry
A 2005;65A:1–3.
25. Kriete A, Boyce K. Automated tissue analysis-a bioinformatics perspective. Methods Inf Med 2005;44:32–37.
26. Tarnok A. New technologies for the human cytome project. J Biol
Regul Homeost Agents 2004;18:92–95.
27. Valet GK, Tarnok A. Cytomics in predictive medicine. Cytometry B
Clinical Cytometry 2003;53B:1–3.
28. Valet G, Leary JF, Tarnok A. Cytomics—new technologies: Towards a
human cytome project. Cytometry A 2004;59:167–171.
29. Van Osta P, Ver Donck K, Bols L, Geysen J. Cytomics and drug discovery. Cytometry A 2006;69A:117–118.
30. Valet G, Tarnok A. Potential and challenges of a human cytome project. J Biol Regul Homeost Agents 2004;18:87–91.
31. Valet G. Cytomics, the human cytome project and systems biology:
Top-down resolution of the molecular biocomplexity of organisms by
single cell analysis. Cell Prolif 2005;38:171–174.
32. Valet G. Human cytome project, cytomics, and systems biology: The
incentive for new horizons in cytometry. Cytometry A 2005;64A:1–2.
33. George TC, Basiji DA, Hall BE, Lynch DH, Ortyn WE, Perry DJ, Seo MJ,
Zimmerman CA, Morrissey PJ. Distinguishing modes of cell death
using the ImageStream multispectral imaging flow cytometer. Cytometry A 2004;59A:237–245.
34. Jager S, Garbow N, Kirsch A, Preckel H, Gandenberger FU, Herrenknecht K, Rudiger M, Hutchinson JP, Bingham RP, Ramon F, Bardera
A, Martin J. A modular, fully integrated ultra-high-throughput screening system based on confocal fluorescence analysis techniques. J Biomol Screen 2003;8:648–659.
35. Ecker RC, de Martin R, Steiner GE, Schmid JA. Application of spectral
imaging microscopy in cytomics and fluorescence resonance energy
transfer (FRET) analysis. Cytometry A 2004;59A:172–181.
36. Bocsi J, Varga VS, Molnar B, Sipos F, Tulassay Z, Tarnok A. Scanning
fluorescent microscopy analysis is applicable for absolute and relative
cell frequency determinations. Cytometry A 2004;61A:1–8.
37. Bajaj S, Welsh JB, Leif RC, Price JH. Ultra-rare-event detection performance of a custom scanning cytometer on a model preparation of fetal
nRBCs. Cytometry 2000;39(4):285–294.
38. Kamentsky L, Kamentsky L. Microscope based multiparameter laser
scanning cytometer yielding data comparable to flow cytometry data.
Cytometry 1991;12:381–387.
39. Kamentsky L, Burger D, Gershman R, Kamentsky L, Luther E. Slide
based laser scanning cytometry. Acta Cytol 1997;11:123–143.
40. Martin-Reay D, Kamentsky L, Weinberg D, Hollister K, Cibas E. Evaluation of a new slide-based laser scanning cytometer for DNA analysis of
tumors. Comparison with flow cytometry and image analysis. Am J
Clin Pathol 1994;102:432–438.
41. Gerstner AOH, Machlitt J, Laffers W, Tarnok A, Bootz F. Analysis of
minimal sample volumes from head and neck cancer by laser scanning cytometry. Onkologie 2002;25:40–46.
42. Gerstner AOH, M€
uller AK, Machlitt J, Tarnok A, Tannapfel A, Weber
A, Bootz F. Slide-based cytometry for predicting malignancy in solid
salivary gland tumors by fine needle aspirate biopsies. Cytometry B
Clinical Cytometry 2003;53B:20–25.
43. Gerstner AOH, Thiele A, Tarnok A, Machlitt J, Oeken J, Tannapfel A,
Weber A, Bootz F. Preoperative detection of laryngeal cancer in mucosal swabs by slide-based cytometry. Eur J Cancer 2005;41:445–452.
44. Gerstner A, Laffers W, Bootz F, Tarnok A. Immunophenotyping of peripheral blood leukocytes by laser scanning cytometry. J Immunol
Methods 2000;246:175–185.
45. Gerstner A, Lenz D, Laffers W, Hoffmann R, Steinbrecher M, Bootz F,
Tarnok A. Near-infrared dyes for six-color immunophenotyping by
laser scanning cytometry. Cytometry 2002;48:115–123.
46. Tjioe I, Legerton T, Wegstein J, Herzenberg LA, Roederer M. Phycoerythrin-allophycocyanin: A resonance energy transfer fluorochrome for
immunofluorescence. Cytometry 2001;44:24–29.
47. Schubert W. Topological proteomics, toponomics, MELK-technology.
Adv Biochem Eng Biotechnol 2003;83:189–209.
48. Schubert W. A three-symbol code for organized proteomes based on
cyclical imaging of protein locations. Cytometry A In this issue.
49. Roederer M. Spectral compensation for flow cytometry: Visualization
artifacts, limitations, and caveats. Cytometry 2001;45(3):194–205.
50. Panchuk-Voloshina N, Haugland RP, Bishop-Stewart J, Bhalgat MK,
Millard PJ, Mao F, Leung W-Y, Haugland RP. Alexa dyes, a series of new
fluorescent dyes that yield exceptionally bright, photostable conjugates. J Histochem Cytochem 1999;47:1179–1188.
51. Mittag A, Lenz D, Bocsi J, Sack U, Gerstner AOH, Tarnok A. Sequential
photobleaching of fluorochromes for polychromatic Slide based Cytometry. Cytometry A 2006;69A:139–141.
52. Alivisatos AP. Semiconductor clusters, nanocrystals, and quantum
dots. Science 1996;271:933–937.
53. Michalet X, Pinaud FF, Bentolila LA, Tsay JM, Doose S, Li JJ, Sundaresan G, Wu AM, Ganbhir SS, Weiss S. Quantum dots for live cells, in
vivo imaging, and diagnostics. Science 2005;307:538–544.
54. Bruchez M, Moronne M, Gin P, Weiss S, Alivisatos AP. Semiconductor
nanocrystals as fluorescent biological labels. Science 1998;281:2013–
2016.
55. Jaiswal JK, Mattoussi H, Mauro JM, Simon SM. Long-term multiple
color imaging of live cells using quantum dot bioconjugates. Nat Biotechnol 2003;21:47–51.
56. Silver J, Ou W. Photoactivation of quantum dot fluorescence following
endocytosis. Nano Lett 2005;5:1445–1449.
57. Ando R, Hama H, Yamamoto-Hino M, Mizuno H, Miyawaki A. An optical marker based on the UV-induced green-to-red photoconversion of
a fluorescent protein. Proc Natl Acad Sci USA 2002;99:12651–12656.
58. Stoddard BL, Cohen BE, Brubaker M, Mesecar AD, Koshland DE. Millisecond Laue structures of an enzyme-product complex using photocaged substrate analogs. Nat Struct Biol 1998;5:891–897.
59. Lukeman M, Scaiano JC. Carbanion-mediated photocages: Rapid and
efficient photorelease with aqueous compatibility. J Am Chem Soc
2005;127:7698–7699.
60. Zhao Y, Zheng Q, Dakin K, Xu K, Martinez ML, Li W-H. New caged coumarin fluorohores with extraordinary uncaging cross sections suitable
for biological imaging applications. J Am Chem Soc 2004;126:4653–
4663.
61. Wachman ES, Niu W, Farkas DL. AOTF microscope for imaging with
increased speed and spectral versatility. Biophys J 1997;73:1215–1222.
62. Chen X, Velliste M, Murphy RF. Automated interpretation of subcellular patterns in fluorescence microscope images for location proteomics. Cytometry A In this issue.
Cytometry Part A DOI 10.1002/cyto.a
HYPERCHROMATIC CYTOMETRY
63. Zhao T, Velliste M, Boland MV, Murphy RF. Object type recognition for
automated analysis of protein subcellular location. IEEE Trans Image
Process 2005;14:1351–1359.
64. Kriete A, Boyce K, Love B. System-wide analysis of hepatotoxicological responses: Tissomics is key. Cytometry A In this issue.
65. Ecker RC, Steiner GE. Microscopy-based multicolor tissue cytometry
at the single-cell level. Cytometry A 2004;59:182–190.
66. Baatz M, Arini N, Sch€ape A, Binnig G, Linssen B. Object-oriented image
analysis for high content screening: Detailed quantification of cells and sub
cellular structures with the cellenger software. Cytometry A In this issue.
67. Megyeri A, Bacso Z, Shields A, Eliason JF. Development of a stereological method to measure levels of fluoropyrimidine metabolizing
enzymes in tumor sections using laser scanning cytometry. Cytometry
A 2005;64A:62–71.
Cytometry Part A DOI 10.1002/cyto.a
703
68. Gratama JW, D’hautcourt JL, Mandy F, Rothe G, Barnett D, Janossy G,
Papa S, Schmitz G, Lenkei R. Flow cytometric quantitation of immunofluorescence intensity: Problems and perspectives. European Working Group on Clinical Cell Analysis. Cytometry 1998;33:166–178.
69. Martins AH, Resende RR, Majumder P, Faria M, Casarini DE, Tarnok A,
Colli W, Pesquero JB, Ulrich H. Neuronal differentiation of P19 embryonal carcinoma cells modulates kinin B2 receptor gene expression
and function. J Biol Chem 2005;280:19576–19586.
€
70. Streit M, Ecker RC, Osterreicher
K, Steiner GE, Bischof H, Bangert Ch,
Kopp T, Rogojanu R. 3D parallel coordinate systems—A new data
visualization method in the context of microscopy-based multicolor
tissue cytometry (MMTC). Cytometry A In this issue.
71. Farkas DL. Invention and commercialization in optical bioimaging.
Nat Biotechnol 2003;21:1269–1271.