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8/14/2019 Single Molecule Microscopy in Living Cells
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Single Molecule Microscopy in Living Cells:
Subtraction of Autofluorescence Based onTwo Color Recording
Manuel MrtelmaierA), Eva J. KglerB), Jan Hesse A), Max SonnleitnerC), Lukas A.HuberB) and Gerhard J. Schtz A)
A) Biophysics Institute
Johannes Kepler University Linz
Altenbergerstr.69
A-4040 Linz, Austria
B) IMP, Research Institute of Molecular Pathology
A-1030 Vienna, Austria
C) Center for Biomedical Nanotechnology
Upper Austrian Research GmbH
Scharitzerstr.6-8
A-4020 Linz, Austria
Correspondence to
Gerhard J. Schtz
Biophysics Institute, Johannes Kepler University Linz,
Altenbergerstr.69, A-4040 Linz, Austria
phone +43-732-2468-9265
fax +43-732-2468-9280
email gerhard.schuetz@jku.at
submitted 02 May 2002
acepted 17 Jul 2002
published 02 Aug 2002
keywords: single fluorophore detection, image processing,CD44, spectroscopy, singular value decomposition
Abstract
A significant limitation of ultra-sensitive microscopy on living
cells is set by background signal arising from cellular
autofluorescence. Up to now, most strategies to circumvent
this limitation were based on choosing long-wavelength dyes
and selecting cell lines with reduced metabolism. In this
article, we present a new strategy to identify and eliminate
signal arising from autofluorescence. Two images are
recorded simultaneously in distinct spectral channels. An
algorithm, based on singular value decomposition, separates
the contributions by the fluorophore of interest and
autofluorescence. A first application of the method for imaging
CD44-YFP in living cells is given.
Introduction
In recent years, single fluorophore detection has become a
standard technique for the investigation of a wide range of
molecular properties (for reviews see [1,2]). In synthetic
environments, the identification of single molecule signals can
be achieved routinely due to full control over environmental
parameters. The study of biomolecules, however, requires
experiments under physiological conditions; the ultimate goal
would be the investigation of biological processes in the living
cell. The frequent occurrence of many species of endogenous
fluorescent molecules inside cells makes such studies
difficult. Up to now, successful detection of single molecules
in vivo has been achieved through the deliberate choice of celltype, metabolic state, and excitation wavelength [3-11]. Such
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a strategy severely limits the range of addressable biological
questions; most standard cell lines and primary cells show a
significant level of background fluorescence ([12]; see also
Fig.2).Cellular autofluorescence has been well characterized in
terms of spectral properties [12], lifetime [13], and spatial
distribution [14]. In the visible regime, flavins [12] and
lipofuscin [15] are currently regarded as the major source of
endogenous fluorescence. Flavins are mainly located in
mitochondria, while lipofuscins predominantly reside in
lysosomes. In fluorescence images, both organelles appear as
diffraction-limited spots randomly distributed in the cytoplasm
of the cell. The high variability of the fluorescence intensity of
such spots, even within one cell, makes unambiguous
distinction between fluorophores and autofluorescence a
challenging task.Up to now, the most prominent strategy has been based
on choosing long excitation wavelengths. It has been shown
that the signal of cellular autofluorescence in HASM cells was
low enough for single fluorophore detection upon excitation at
633nm and detection at typical Cy5 filter settings [5]. Still,
lipofuscin-like autofluorescent pigments were shown to be
visible under fluorescent filters for UV, fluorescein, rhodamine
and Cy5 [15]. In general, autofluorescence spectra are broad,
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Single Single Mol. 3 (2002) 4226
Fig. 1. a) Schematic overview of
the microscope. Laser light withwavelengths of 633nm (red)
and 514nm (green) is combined
to a single beam using a
dichroic beamsplitter. Electronic
shutter elements and
Acousto-Optical-Modulators
(AOMs) allow for precise control
of illumination times. Excitation
of the target molecules in the
sample takes place in a spot of
approximately 20m in
diameter (wide field
illumination). This beam
geometry is achieved by placing
a defocusing lens between the
lasers and the objective.
Emitted fluorescence light
originating from the sample is
collected via an oil immersion
objective (100x, NA=1.4), and,
after appropriate filters,
reflected by a dichroic wedge.
Light with l630nm is
reflected from the rear surface
(red channel). The tilt angle of
~1 between front and rear
surface leads to two separate
images on the CCD camera
one for each spectral region
with a distance of ~100m on
the chip. b) Reflection coef-
ficient of the dichroic wedge for
the green channel and the
red channel. Superimposed isthe emission spectrum of YFP
(dashed line).
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ranging from 500nm to 700nm upon excitation at 488nm
[12], a wavelength typically used for fluorescein or GFP
imaging. The broad emission cannot be blocked by filters,
making ratiometric techniques the method of choice for
correction of contributions due to autofluorescence.
In this article, we present a method which allows
unambiguous distinction of ultra-low signals arising from
YFP-molecules and cellular background fluorescence. The
method is based on parallel imaging in two distinct spectral
channels: a green channel, containing signals from both YFP
and autofluorescence, and a red channel, with only
autofluorescence contributions. Even at signal levels typicalfor single molecule microscopy, clear discrimination was
feasible. The method was used to image CD44-YFP in living
EpH4 and cos7 cells [16,17].
Experimental
Cell Culture
EpH4 cells are a spontaneously immortalized mouse
mammary epithelial cell which displays a fully polarized
epithelial cell phenotype [18, 19]. Cells were cultivated in high
Glucose DMEM (Dulbecos modified Eagles medium)
supplemented with 10mM Hepes pH 7.3, 1%
Penicillin/Streptomycin and 5% FCS (Gibco BRL and
Boehringer Mannheim Corp.) at 37C, 5% CO2, and 98%humidity. For transfections, Lipofectamine Plus Reagent was
obtained from Life Technologies. Transfected cells express the
standard murine CD44-EYFP (cytoplasmic tagged) receptor
under a PGK promotor. All experiments were performed at
room temperature in PBS (phosphate buffered saline)
supplemented with 1mM MgCl2 and 1mM CaCl2.
Microscopy
The apparatus for two color microscopy is shown in Fig.1a.
Samples were illuminated for 5-20ms by 514nm light from an
Ar+-laser (Model 2020, Spectra Physics) or 633nm light from
a dye laser (Model 375B, Spectra Physics), using a 100-times
objective (PlanApochromat, NA=1.4, Zeiss) in an
epi-fluorescence microscope (Axiovert 135TV, Zeiss). The
laser beam was defocused to an area of 255m2 at a mean
intensity of 40W/cm2. Rayleigh scattered light was effectively
blocked by appropriate filter combinations (custom TRITC/Cy5
dichroic and emission filter, Chroma). Images were obtained
by a liquid-nitrogen cooled slow-scan CCD-camera system
(ST-138, Roper Scientific, N.J., equipped with an EEV
1340x1300-chip) and stored on a PC. A dichroic wedge (1
separation, Chroma) was mounted in the parallel beam path,
which allows simultaneous recording of two color channels. The spectral properties of the two channels are depicted in
Fig.1b. Effectively all emission from YFP (dashed line) falls into
the green channel.
Results
We present here a method for the decomposition of optical
signals originating from two distinct spectral components: a
specific fluorophore, and cellular autofluorescence. It is based
on the more general algorithm of singular valuedecomposition [20]. The method allows to distinguish
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227
Fig. 2. Autofluorescence image of a cos7 cell. (a) The light
image shows a living, unstained cos7 cell. The red square
indicates the region of observation for subsequent
fluorescence images. b and c show false-color fluorescence
images of the red (b) and green (c) channel. Both
images were obtained simultaneously with the apparatus
described in figure 1, using excitation at 514nm. The
fluorescence images show close resemblance, indicating a
spatially homogenous spectral composition of
autofluorescence. Scale bar 5m.
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between image features originating from the fluorophore andfrom autofluorescence. In addition, the relative contribution of
the two signal sources to the overall signal strength in each
pixel can be quantified, thus allowing to obtain an optimum
estimation of the background-free image.
Each fluorescence image was recorded simultaneously in
two spectral channels, which are sensitive for emission up to
~650nm (green channel), and for emission above 660nm
(red channel). Fig.2 shows the light image and a
two-channel fluorescence image of a cos7 cell. In both
channels, structures with a size beyond the diffraction limit are
visible. The spatial patterns of autofluorescence appear to be
very similar in both wavelength regions. This agrees well withprevious reports of broad spectral profiles of cellular
autofluorescence [12, 15]. Moreover, the signal of each pixelin the green channel, Sg, is highly correlated with the
respective signal of the same pixel in the red channel, Sr, as
shown in Fig.3a. When F1 denotes the total autofluorescence
emission in a pixel, andr
= ( , )g r1 1 the detection efficiencies
for autofluorescence in the green and red channel,
respectively,r
S S Sg r= ( , ) can be written asr
r
S F= 1 , with
r g r1 1 1= =const; here, the index in uppercase specifies
autofluorescence as the source for the signal. In other words,
a specific color can be ascribed to cellular
autofluorescence, for the chosen settings characterized by a
slope r1 1 . The following method is based on thedetermination of the characteristic color of a fluorophore,
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Single Single Mol. 3 (2002) 4228
Fig. 3. YFP image of a cos7
cell. The false-color
fluorescence images show a
cos7 cell overexpressing
CD44-YFP in the red (a) and
green (b) channel upon
excitation at 514nm. Clearly,
the signal in the green,
short-wavelength channel is
much more pronounced than its
counterpart on the left. For
illustration, the scaling of the
red channel was increased by
a factor of 10. Effectively all
emission from CD44-YFP falls
into the green channel. Scale
bar 5m.
Fig. 4. Pixel-per-pixel
correlation between spectral
channels for autofluorescence
(a) and CD44-YFP (b). The plots
were generated using the
images depicted in figure 2 and
3, respectively.
Autofluorescence signal in thered channel Sr (see main text)
is highly correlated with its
counterpart in the green, Sg.
YFP fluorescence, however, is
present almost exclusively in the
green channel. The difference in
the slope of the data was
exploited for subsequent image
correction.
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which is in general different from the color of
autofluorescence.
Fig. 3. shows the fluorescence image of a cell
overexpressing the YFP-labeled transmembrane protein
CD44. The detail shows the targeting of the molecule to the
plasma membrane of the cell. Due to the high signal
amplitude, no significant contribution of autofluorescence to
the signal was observed; the red image appears dark when
compared to the green image. The color of YFP is
characterized by a large slope r2 20> (Fig. 4b). This figure willbe used as a standard for YFP-fluorescence inside a cell.
In general, both emission from the fluorophore and
autofluorescence contribute to the signal obtained in one
pixel. In this case, the signal is given byr
r r
S F F = 1 1 2 2 . Forconvenience, we introduce here vector notation:
r rt
S F= , withr
F F F= ( , )1 2 andt
=
g r
g r
1 1
2 2 . In order to decompose the
contributions of the individual fluorescent species,r
F, the
matrix has to be inverted:r r
t
F S= 1. The matrixt
can bemeasured on purified substances, or, if such purification is not
feasible, can be determined iteratively by minimizing the
correlation between the two resulting estimations ofr
F. Fig.5
shows an arbitrary region of an EpH4 cell expressing
CD44-YFP. Fig.5a and b show the original red (Sr) and
green channel (Sg), respectively. The corrected image of the
YFP-channel, F2, is shown in Fig.5c. Evidently, the most
intensive spots have been identified as autofluorescence by
the algorithm and have vanished in the corrected image.
Besides these bright spots, Fig.5b contains a number of spots
with an intensity similar to that expected for CD44-YFP
clusters. However, even within such spots of heterogeneous
origin, the algorithm clearly identified those corresponding to
CD44-YFP clusters.
The most challenging test case for the presented
methodology is the regime of single fluorophore detection. It is
evident that signals arising from single fluorophores can onlybe identified in the presence of autofluorescent background
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SingleM. Mrtelmaier et al. 229
Fig. 5. Fluorescence images of
EpH4 cells expressing
CD44-YFP. The false-color
fluorescence images show a
EpH4 cell expressing CD44-YFP
in the red (a) and green (b)
channel upon excitation at
514nm. The image in the
green channel contains many
structures indicative of
CD44-YFP clustering. These
structures are of highly variable
size and brightness, and show
no specific distributional
pattern, leaving only their
spectral profile as a practical
discriminatory feature. Indeed,some of those structures are
also observed in the red
channel, and can thus be
unmasked as autofluorescence.
(c) shows the reconstructed
YFP-signal. Contributions of
autofluorescence to the overall
signal have been removed
successfully, thereby
dramatically increasing the
information content of the
image. d and e further illustratethe working principle of the
decomposition algorithm. (d) shows the pixel-per-pixel correlation between the two images a and b. The contributions of both
CD44-YFP and autofluorescence become obvious as two branches of the data set. The different colors of fluorophore
emission and autofluorescence are reflected by the different slopes of the branches (green lines). Application of the algorithm
minimizes the correlation between the resulting images, as shown in (e). Now, the green and red channel represent the
color of the two fluorescence contributions. Scale bar 5m.
Single Molecule Microscopy in Living Cells:Subtraction of Autofluorescence
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when their amplitude exceeds the shot noise of the
background. Moreover, since the source of autofluorescence
is heterogeneous and might vary from cell to cell, even from
organelle to organelle, the ratio S Sg r
shows slight variations
within an image, rendering the identification of weak signals
on a high background difficult. However, for most studies the
major problem is not the detection of weak signals on high
background, but the unambiguous assignment of individual
fluorescent spots to either autofluorescence or the
fluorophores of interest. Fig.6a and b show fluorescence
images of EpH4 cells expressing CD44-YFP, which have been
extensively photobleached to a level where individual
fluorophores can be resolved. A multitude of fluorescence
spots can be observed in the green channel. It is likely that
those spots are of heterogeneous origin: some represent
CD44-YFP clusters, while other spots might occur due to the
presence of autofluorescence. Indeed, some of the structures
observed in Fig.6b are also clearly visible in the red channel
(Fig.6a). Application of the above algorithm yields the image
of the genuine fluorophore distribution, shown in Fig.6c. The
picture improved in two ways: first, autofluorescent structures
have been removed, and second, the homogenous
background in the interior of the cell has been lowered
remarkably. Now the preferential location of CD44-YFP in the
plasma membrane is clearly visible.
The methodical framework described here can easily be
generalized to a higher number of fluorophores and recording
channels. In general, images consisting of pixels recorded in n
channels can be regarded as a dataset of points in ann-dimensional space. The spectra of m fluorophores with
distinct spectral properties this includes the endogenous
fluorophores responsible for autofluorescence span an
m-dimensional subspace within this n-dimensional space. For
each pixel, the best estimate of the intensity contributed by
each fluorophore can be obtained by orthogonal subspace
projection [20]. This methodological extension will allow for
the simultaneous discrimination of several fluorophores
against autofluorescence, and for unambiguous quantification
of the concentration of fluorophores, even with similar
emission and absorption spectra, e.g. GFP and YFP.
Acknowledgement This work was funded by the Austrian
Research Funds, grant P15053.
References
[1] S. Weiss, Science 283 (1999) 1676.
[2] W. E. Moerner and M. Orrit, Science 283 (1999) 1670.
[3] M. Ueda, Y. Sako, T. Tanaka, et al., Science 294
(2001) 864.
[4] G. Seisenberger, M. U. Ried, T. Endress, et al., Science
294 (2001) 1929.
[5] G. J. Schutz, G. Kada, V. P. Pastushenko, et al., Embo J
19 (2000) 892.
[6] G. J. Schutz, V. P. Pastushenko, H. J. Gruber, et al.,
Single Mol. 1 (2000) 25.
[7] Y. Sako, S. Minoghchi, and T. Yanagida, Nat Cell Biol 2(2000) 168.
RESEARCH PAPERMolecules
Single Single Mol. 3 (2002) 4230
Fig. 6. Fluorescence images of EpH4 cells expressing CD44-YFP at a low signal level. The false-color fluorescence images
show a EpH4cell expressing CD44-YFP in the red (a) and green (b) channel upon excitation at 514nm. In comparison to
Figure 5, however, the YFP-signal has been artificially reduced by extensive photobleaching. This photobleaching procedure
did not affect the signal of the autofluorescence significantly. Spots occurring in b represent both CD44-YFP clusters of only a
few active fluorophores, and autofluorescence. Even in this case of low signal amplitude, spots originating from
autofluorescence have been clearly identified and removed (c). In addition, the overall image quality was improved due to
subtraction of a homogenous autofluorescence background.
8/14/2019 Single Molecule Microscopy in Living Cells
7/7
[8] T. Kues, R. Peters, and U. Kubitscheck, Biophys J 80
(2001) 2954.
[9] T. Kues, A. Dickmanns, R. Luhrmann, et al., Proc Natl
Acad Sci U S A 98 (2001) 12021.
[10] R. Iino, I. Koyama, and A. Kusumi, Biophys J 80
(2001) 2667.
[11] G. S. Harms, L. Cognet, P. H. Lommerse, et al.,
Biophys J 81 (2001) 2639.
[12] R. C. Benson, R. A. Meyer, M. E. Zaruba, et al., J
Histochem Cytochem 27 (1979) 44.
[13] K. Konig, P. T. So, W. W. Mantulin, et al., J Microsc
183 (1996) 197.
[14] H. Andersson, T. Baechi, M. Hoechl, et al., J Microsc
191 (1998) 1.
[15] S. A. Schnell, W. A. Staines, and M. W. Wessendorf, J
Histochem Cytochem 47 (1999) 719.[16] S. Oliferenko, K. Paiha, T. Harder, et al., J Cell Biol
146 (1999) 843.
[17] S. Oliferenko, I. Kaverina, J. V. Small, et al., J Cell Biol
148 (2000) 1159.
[18] I. Fialka, H. Schwarz, E. Reichmann, et al., J Cell Biol
132 (1996) 1115.
[19] I. Fialka, M. Oft, E. Reichmann, et al., in Cell Biology:
A laboratory handbook, edited by J. E. Celis (Academic
Press, San Diego, CA, 1997), Vol. 1, p. 107.
[20] P. L. T. M. Frederix, M. A. H. Asselbergs, W. G. J. H.
M. van Sark, et al., Appl. Spectr. 55 (2001) 1005.
RESEARCH PAPER Molecules
SingleM. Mrtelmaier et al. 231Single Molecule Microscopy in Living Cells:Subtraction of Autofluorescence
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