Two-photon spectral imaging with high temporal and spectral resolution.

Abstract

We introduce a fast spectral imaging system using an electron-multiplying charge-coupled device (EM-CCD) as a detector. Our system is combined with a custom-built two-photon excitation laser scanning microscope and has 80 detection channels, which allow for high spectral resolution and fast frame acquisition without any loss of spectral information. To demonstrate the efficiency of our approach, we applied this technology to monitor fluorescent proteins and quantum dot-labeled G protein-coupled receptors in living cells as well as autofluorescence in tissue samples.

Full text

Page 1

Two-photon spectral imaging with high temporal
and spectral resolution
Kang-Bin Im,1,2 Moon-Sik Kang,1,2 Jiho Kim,1 Felix Bestvater,2,3 Zahir Seghiri,2
Malte Wachsmuth,2,4,5 and Regis Grailhe1,5,*
1Neurodegeneration and Applied Microscopy, Institut Pasteur Korea, Seongnam, Gyeonggi-do, 463-400 Korea
2Cell Biophysics Group, Institut Pasteur Korea, Seongnam, Gyeonggi-do, 463-400 Korea
3Light Microscopy Core Facility, German Cancer Research Center, 69120 Heidelberg, Germany
4Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
5Corresponding authors
*regis.grailhe@ip-korea.org
Abstract: We introduce a fast spectral imaging system using an electron-
multiplying charge-coupled device (EM-CCD) as a detector. Our system is
combined with a custom-built two-photon excitation laser scanning
microscope and has 80 detection channels, which allow for high spectral
resolution and fast frame acquisition without any loss of spectral
information. To demonstrate the efficiency of our approach, we applied this
technology to monitor fluorescent proteins and quantum dot-labeled G
protein-coupled receptors in living cells as well as autofluorescence in tissue
samples.
©2010 Optical Society of America
OCIS codes: (040.1520) CCD, charge-coupled device; (180.4315) Nonlinear microscopy;
(300.6410) Spectroscopy, fluorescence and luminescence.
References and links
1. J. A. Conchello, and J. W. Lichtman, “Optical sectioning microscopy,” Nat. Methods 2(12), 920–931 (2005).
2. E. Wang, C. M. Babbey, and K. W. Dunn, “Performance comparison between the high-speed Yokogawa
spinning disc confocal system and single-point scanning confocal systems,” J. Microsc. 218(2), 148–159 (2005).
3. F. Helmchen, and W. Denk, “Deep tissue two-photon microscopy,” Nat. Methods 2(12), 932–940 (2005).
4. M. Wachsmuth, and K. Weisshart, “Fluorescence photobleaching and fluorescence correlation spectroscopy: two
complementary technologies to study molecular dynamics in living cells,” in Imaging Cellular and Molecular
Biological Functions (Springer Verlag, Heidelberg, 2007).
5. T. Misteli, and R. D. Phair, “High mobility of proteins in the mammalian cell nucleus,” Nature 404(6778), 604–
609 (2000).
6. P. Indovina, M. Collini, G. Chirico, and M. T. Santini, “Three-dimensional cell organization leads to almost
immediate HRE activity as demonstrated by molecular imaging of MG-63 spheroids using two-photon excitation
microscopy,” FEBS Lett. 581(4), 719–726 (2007).
7. A. Hayek, A. Grichine, T. Huault, C. Ricard, F. Bolze, B. Van Der Sanden, J. C. Vial, Y. Mély, A. Duperray, P.
L. Baldeck, and J. F. Nicoud, “Cell-permeant cytoplasmic blue fluorophores optimized for in vivo two-photon
microscopy with low-power excitation,” Microsc. Res. Tech. 70(10), 880–885 (2007).
8. C. Li, R. K. Pastila, C. Pitsillides, J. M. Runnels, M. Puoris‟haag, D. Côté, and C. P. Lin, “Imaging leukocyte
trafficking in vivo with two-photon-excited endogenous tryptophan fluorescence,” Opt. Express 18(2), 988–999
(2010).
9. R. Cicchi, A. Crisci, A. Cosci, G. Nesi, D. Kapsokalyvas, S. Giancane, M. Carini, and F. S. Pavone, “Time- and
Spectral-resolved two-photon imaging of healthy bladder mucosa and carcinoma in situ,” Opt. Express 18(4),
3840–3849 (2010).
10. Y. Hiraoka, T. Shimi, and T. Haraguchi, “Multispectral imaging fluorescence microscopy for living cells,” Cell
Struct. Funct. 27(5), 367–374 (2002).
11. R. H. Berg, “Evaluation of spectral imaging for plant cell analysis,” J. Microsc. 214(2), 174–181 (2004).
12. P. D. Beule, D. M. Owen, H. B. Manning, C. B. Talbot, J. Requejo-Isidro, C. Dunsby, J. Mcginty, R. K. P.
Benninger, D. S. Elson, I. Munro, M. John Lever, P. Anand, M. A. A. Neil, and P. M. W. French, “Rapid
hyperspectral fluorescence lifetime imaging,” Microsc. Res. Tech. 70(5), 481–484 (2007).
13. M. B. Sinclair, D. M. Haaland, J. A. Timlin, and H. D. T. Jones, “Hyperspectral confocal microscope,” Appl.
Opt. 45(24), 6283–6291 (2006).
14. S. Kumazaki, M. Hasegawa, M. Ghoneim, Y. Shimizu, K. Okamoto, M. Nishiyama, H. Oh-Oka, and M.
Terazima, “A line-scanning semi-confocal multi-photon fluorescence microscope with a simultaneous broadband
spectral acquisition and its application to the study of the thylakoid membrane of a cyanobacterium Anabaena
PCC7120,” J. Microsc. 228(2), 240–254 (2007).
#137258 - $15.00 USD
(C) 2010 OSA
Received 27 Oct 2010; revised 27 Nov 2010; accepted 30 Nov 2010; published 7 Dec 2010
20 December 2010 / Vol. 18, No. 26 / OPTICS EXPRESS 26905

Page 2

15. J. Rietdorf, and E. H. K. Stelzer, “Special optical elements,” in Handbook of biological confocal microscopy, J.
B. Pawley, 3ed. (Springer, 2006), pp. 43–58.
16. F. Bestvater, Z. Seghiri, M. S. Kang, N. Gröner, J. Y. Lee, K. B. Im, and M. Wachsmuth, “EMCCD-based
spectrally resolved fluorescence correlation spectroscopy,” Opt. Express 18(23), 23818–23828 (2010).
17. G. Heuvelman, F. Erdel, M. Wachsmuth, and K. Rippe, “Analysis of protein mobilities and interactions in living
cells by multifocal fluorescence fluctuation microscopy,” Eur. Biophys. J. 38(6), 813–828 (2009).
18. A. D. Keefe, D. S. Wilson, B. Seelig, and J. W. Szostak, “One-step purification of recombinant proteins using a
nanomolar-affinity streptavidin-binding peptide, the SBP-Tag,” Protein Expr. Purif. 23(3), 440–446 (2001).
19. S. Schlachter, S. Schwedler, A. Esposito, G. S. Kaminski Schierle, G. D. Moggridge, and C. F. Kaminski, “A
method to unmix multiple fluorophores in microscopy images with minimal a priori information,” Opt. Express
17(25), 22747–22760 (2009).
20. K. Svoboda, and R. Yasuda, “Principles of two-photon excitation microscopy and its applications to
neuroscience,” Neuron 50(6), 823–839 (2006).
1. Introduction
Since the advent of commercial confocal laser scanning microscopes, new fluorescence
microscopy systems [1–3] and techniques derived therefrom [4,5] have been developed. One
of them is two-photon excitation (2PE) laser scanning microscopy, which is well suited for
imaging not only of single cells [6,7] but also and especially of thick tissue [8,9]. As two-
photon microscopy provides deeper penetration depth, less photobleaching, less scattering and
reduced noise level compared to single photon excitation confocal microscopes due to the use
of an infrared excitation source far away from the visible emissions, it is a very powerful tool
for numerous biological applications.
With the increasing use of fluorescence microscopy especially in biology [1–5], demand
for the simultaneous acquisition of multiple fluorescent probes is growing. Especially for a
quantitative systems biology approach to study molecular functions in living cells and tissues,
the simultaneous readout of multiple parameters is essential. Among the spectral imaging
point scanning systems that have been developed or are commercially available [10,11],
typical implementations employ a grating or prism to disperse the confocal signal from each
scanned point over a linear photomultiplier tube (PMT) array [7] or a charge-coupled device
(CCD) chip [12–14] or use one or several large sensitive area PMTs combined with moving
slits. In terms of temporal and spectral resolution, PMT array-based systems enable fast
acquisition but can suffer either from loss of spectral information due to the dead zone
between neighboring PMT elements or from low spectral resolution due to a small number of
detection channels (Fig. 1) [11,15]. On the other hand, moving slit-based systems can provide
very high spectral resolution, especially when reducing the slit width, but require relatively
long recording times because of the inherent sequential image acquisition scheme. In addition,
photobleaching might play a larger role due to the long exposure time. A promising approach
is the use of CCD-based detection [12–14], but the read-out speed of CCD cameras still
presents a limiting factor to the pixel dwell time. These drawbacks limit the broader use of
spectral imaging for biological applications that require simultaneously high spectral
resolution and fast acquisition times. Furthermore, the low quantum efficiency of PMT arrays
especially towards the red end of the spectrum and the need for dedicated hardware for data
acquisition and processing of PMT signals make these approaches challenging.
Recently, electron-multiplying charge-coupled device (EM-CCD) detectors have found
their way into fluorescence microscopy and spectroscopy, not least due to their substantially
higher sensitivity compared to conventional PMTs. As an EM-CCD is typically composed of
several hundreds of pixels in each dimension arranged with a fill factor close to unity, it can
be used as a spectrometer detector to provide higher spectral resolution than typical PMT
array-based systems (Fig. 1). We could show previously that EM-CCDs can be used for
spatially or spectrally resolved fluorescence correlation spectroscopy (FCS) based on single
photon excitation laser scanning microscopy [16,17].
To overcome the drawbacks of current spectral imaging systems, we developed an EM-
CCD-based spectral detection system and a 2PE laser scanning microscope for imaging with
fast acquisition speed, high spectral resolution and high sensitivity. Here, we introduce the
setup and show its application to biological systems such as cells expressing fluorescent
#137258 - $15.00 USD
(C) 2010 OSA
Received 27 Oct 2010; revised 27 Nov 2010; accepted 30 Nov 2010; published 7 Dec 2010
20 December 2010 / Vol. 18, No. 26 / OPTICS EXPRESS 26906

Page 3

proteins, tissue sample exhibiting autofluorescence and cells carrying quantum dot-labeled G
protein-coupled receptors (GPCR).
2. Experimental setup
Figure 2A depicts schematically our custom-built 2PE laser scanning microscope setup. A
tunable Ti-Sapphire laser (MIRA900, Coherent) is used for two-photon excitation in the range
of 700-980 nm. The laser pulse width is set to ~130 fs and the repetition rate to 76 MHz.
Using two convex lenses, the light is expanded to a full width at half maximum (FWHM) of
2.4 mm (laser and beam expander are omitted in Fig. 2A). The scan head is composed of two
galvanometer mirrors (VM500, GSI). The light is expanded again by a scan and a tube lens to
overfill the back aperture of an oil-immersion objective lens (HCX PL APO 63 × , NA 1.4,
Leica) used to focus the light onto the sample and mounted on an inverted microscope (DM
IRBE, Leica).
Fluorescent light emitted from the sample passes objective, tube and scan lenses, and the
galvanometer scanners. It is then reflected by a dichroic mirror, dispersed spectrally by a
Pellin-Broca prism and focused onto a single line of an EM-CCD sensor (SamBa SE-34,
Sensovation). As a result, we can obtain a full spectrum from any spatial point of the acquired
image (Fig. 2B).
To enhance the image acquisition speed, we increased the readout frequency of the EM-
CCD by restricting the recorded area to 1 × 80 pixels and operating it in fractional line-
readout mode, i.e., pixel intensities were transferred line-by-line instead of frame-by-frame to
the frame grabber (Fig. 2C). When setting the integration time of the camera to zero, ~84,000
spectra of 80 pixels could be recorded per second (Fig. 2D). Thus, the pixel dwell time was
decreased to ~12 μs, which is an order of magnitude faster compared to using a full line of the
chip [13]. Both the frame grabber and the galvanometer scanners were synchronized using the
pixel clock of the EM-CCD, and the pixel dwell time was set to match the reciprocal of the
readout frequency of the EM-CCD. For rapid assessment of the data, the measurements were
monitored on a computer screen in real time.

Fig. 1. Overview and comparison of spectral acquisition using an EM-CCD with common
schemes using linear PMT arrays and moving slits. The effective detection areas are indicated
in gray.
#137258 - $15.00 USD
(C) 2010 OSA
Received 27 Oct 2010; revised 27 Nov 2010; accepted 30 Nov 2010; published 7 Dec 2010
20 December 2010 / Vol. 18, No. 26 / OPTICS EXPRESS 26907

Page 4

Fig. 2. (A) Schematics of the 2PE spectral fluorescence imaging setup using an EM-CCD
camera. (B) Upon 2PE point-scanning excitation of the fluorescent sample, a spectral data
stack comprised of 80 images is generated. B: blue, G: green, R: red. (C) Only 80 pixels in the
bottom-most line of the detection area of the EM-CCD chip are illuminated with the spectrally
dispersed fluorescence light at least for the time required to amplify and read out 80 pixels.
Then a rapid single line shift is applied to move the photoelectrons to the first line of the
storage area while the galvanometer scanner moves the focus to the next pixel. Eventually the
photoelectrons from the 80 illuminated pixels arrive at the bottom-most line of the storage area.
Only the 80 pixels of interest instead of the full line of 656 pixels are transferred to the charge
amplifiers, the analog-to-digital converter and to the frame grabber. This is repeated for all
pixels of an image frame and the recorded spectra are assigned appropriately to the respective
pixels. (D) Line readout rate as a function of pixels per line that are read out. The pixel
number/readout rate combination used in this study is highlighted.
Even though the flyback of the galvanometer scanning along the line is not used for data
recording, the gain of speed is reflected in the acquisition time of full spectral stacks of 80
frames: our system operates in a low sampling mode (205 × 205 pixels) with an acquisition
time of ~1 s per stack and in a high sampling mode (458 × 458 pixels) with an acquisition
time of ~5 s per stack, allowing for full spectral time-lapse imaging and proving to be a fast
yet spectrally well resolved alternative to other point scanning instruments: In [13], a setup
with a higher spectral resolution of 512 channels but a longer pixel dwell time of 240 μs is
presented with an anticipated acquisition time of ~5-10 s for a 208 × 208 pixel stack. A
typical commercial confocal microscope employing a „moving slit‟ spectral detection system
(e.g. Leica TCS SP2 AOBS, Leica Microsystems) would require ~10 s for the acquisition of
40 spectral channels with a speed of 4 frames (256 × 256 pixels) per second.
In summary our spectral imaging system features a simple yet powerful and robust optical
setup and is a good compromise between acquisition speed and spectral resolution adapted to
imaging of living biological samples.
#137258 - $15.00 USD
(C) 2010 OSA
Received 27 Oct 2010; revised 27 Nov 2010; accepted 30 Nov 2010; published 7 Dec 2010
20 December 2010 / Vol. 18, No. 26 / OPTICS EXPRESS 26908

Page 5

3. Sample preparation
3.1 Constructs and cell culture
The plasmids encoding for the cyan and yellow fluorescent proteins (CFP, YFP) derived from
the Aequorea Victoria jellyfish and for the DsRed fluorescent protein originating from
Discosoma Striata sea coral were obtained from Clontech. The streptavidin binding protein-
tagged serotonin 5-HT2C receptor expression vector was generated upon insertion, after the
signal sequence of the human 5-HT2C, of an SBP-tag sequence [18]. The SBP-5-HT2C was
stably expressed in HEK-293 cell lines, and the fluorescent proteins (CFP, YFP, DsRed) were
transiently expressed in HEK-293 cells.
3.2 Quantum-dot cell labeling
Cells stably expressing the SBP-5-HT2C construct were seeded 72 hours before imaging in 4
well LabTek chambered coverglasses (Nunc). 24 hours post cell seeding, the cell culture
medium was replaced with DMEM supplemented with 1% FBS, which promotes the 5-HT2C
translocation at the plasmalemma cellular compartment. Three different types of streptavidin-
conjugated quantum dots (QD 525, QD 585 and QD 655, Invitrogen) were incubated
sequentially for 30 minutes at 24, 6 and 1 hour(s), respectively, prior to spectral image
acquisition (see Fig. 7A). One hour after each QD treatment, the cells were carefully washed
with phenol red-free DMEM.
4. Characterization of the setup
4.1 Spatial resolution
In order to measure the point spread function (PSF) of our two-photon spectral imaging
system we performed a 3D scanning of 0.17 μm diameter yellow-green fluorescent beads
(P7220, Molecular Probes), with an excitation wavelength of 900 nm. The pixel interval was
set to 0.14 μm and sequential images were taken by moving the objective lens with steps of
0.05 μm. Figure 3A and 3B show a lateral section of a fluorescent bead and its fluorescence
spectrum, respectively. Figure 3C and 3D show the intensity profiles of axial and lateral line
scans obtained by averaging 10 beads. The FWHMs of axial and lateral line profiles are 0.51
μm and 0.36 μm, respectively, i.e., our setup provides close-to diffraction-limited axial and
lateral resolution.
#137258 - $15.00 USD
(C) 2010 OSA
Received 27 Oct 2010; revised 27 Nov 2010; accepted 30 Nov 2010; published 7 Dec 2010
20 December 2010 / Vol. 18, No. 26 / OPTICS EXPRESS 26909

Page 6

Fig. 3. Point spread function measurement. (A) Lateral section of a 0.17 μm diameter
fluorescent bead excited at 900 nm. (B) Emission spectrum of the bead. The FWHM values of
the beads obtained from axial (C) and lateral (D) line scans are 0.51 and 0.36 μm, respectively.
The red curves indicate Gaussian fits.
4.2 Spectral resolution and calibration
The optical system was designed to distribute fluorescent light, ranging from 400 to 750 nm,
with an almost uniform diffraction-limited spot size on the detector throughout the entire
detection range of 1.2 pixels (FWHM). The spectral detection was calibrated using Ar ion and
He-Ne laser lines (458, 488 and 633 nm) and quantum dots. Because of the nonlinear
dispersion of the prism, the spectral sampling given in nm per channel was found to be
nonuniform (Fig. 4A), resulting in a corresponding nonuniform spectral resolution. Figure 4B
and 4C show the acquired spectra of three laser lines using a commercial spectrometer
(USB4000, Ocean Optics) and our spectral imaging system, respectively. The measured
bandwidths of the three laser lines at 458, 488 and 633 nm were 1.35, 1.32 and 1.80 nm,
respectively (Fig. 4B), i.e., they were narrow enough to evaluate the spectral resolution of our
system. The wavelength verification of the three laser lines (Fig. 4B) was performed using the
commercial spectrometer. We calibrated our spectral imaging system based on the wavelength
values obtained (Fig. 4C). The FWHMs of the spectra were 1.8, 1.5 and 1.6 pixels
corresponding to 6, 5.7 and 13 nm (Fig. 4D–4F), i.e., the spot sizes on the chip were a bit
larger than expected but relatively constant throughout the spectral range. We found that the
spectral resolution of the imaging system decreases with increasing wavelength as expected
due to the nonlinear dispersion and the close-to diffraction-limited spot size. Fortunately, this
effect is partially compensated by the observation that the bandwidth of emission spectra is
broader for typical reddish compared to typical bluish fluorophores. The spectral calibration
was additionally confirmed using quantum dots (Invitrogen).
With the combination of sampling and resolution chosen for our setup, ~5-10 data points
per emission bandwidth of a typical organic fluorophore or fluorescent protein and still ~3-6
data points for quantum dots are obtained, i.e., the spectra are sufficiently oversampled to
allow for advanced spectral unmixing/deconvolution approaches [19].
#137258 - $15.00 USD
(C) 2010 OSA
Received 27 Oct 2010; revised 27 Nov 2010; accepted 30 Nov 2010; published 7 Dec 2010
20 December 2010 / Vol. 18, No. 26 / OPTICS EXPRESS 26910

Page 7

Fig. 4. Calibration and characterization of the EM-CCD spectral imaging system. (A) Spectral
sampling of our setup as calculated with Zemax (Zemax Development Corp.). The three
wavelengths used for calibration are highlighted, anticipating a FWHM of 3.9, 4.8 and 9.6 nm
when taking a diffraction-limited spot size of 1.2 pixels into consideration. The three laser lines
(458, 488 and 633 nm) were measured using (B) a commercial spectrometer under the same
conditions and (C) our setup. Based on (B), (C) was calibrated, and a wavelength range was
assigned to each channel. A Gaussian function was fitted to the spectrum of each laser line to
measure its bandwidth. The emission bandwidths of the three laser lines were sufficiently
narrow (~1 nm) for a proper estimation of the spectral resolution of our system. The full widths
at half maximum were 6, 5.7 and 13 nm at 458, 488 and 633 nm, respectively. In (D)-(F), the
circles indicate the measured spectra from (A), and the red curves show Gaussian fits.
4.3 Sensitivity
We could show previously [16] the photon-counting capabilities of our spectrometer setup,
which features a mean quantum yield of ~30% in the visible range and an effective readout
noise of 0.6 photoelectrons (RMS). Therefore, the recorded intensities values obey mainly
Poisson statistics for single pixels as well as for rebinned spectral windows, i.e., the spectra
can be compared immediately to a distribution one would obtain with linear dispersion. Thus,
the signal-to-noise ratio does not show any spectral dependence except for the impact of the
spectral dependence of the quantum yield.
5. Spectrally resolved imaging of cells and tissue
Since spectral imaging allows for the simultaneous recording of both spectral and spatial
information, it enables to identify multiple fluorescence and autofluorescence signatures from
labeled and unlabeled cells as well as tissues in a single acquisition step. To demonstrate the
usability of this technology, we conducted experiments on various biological samples: first,
we studied the spectral signature of fluorescent proteins covering the visible spectrum, i.e., the
cyan fluorescent protein CFP, the yellow fluorescent protein YFP, and the red fluorescent
protein DsRed (Fig. 5A–5C). Reduced single-channel images, acquired from HEK-293 cells
transiently expressing one of the fluorescent molecules, were reconstructed by binning several
channels around the peak of the spectrum. The main peaks for CFP, YFP and DsRed were
found at 513, 531 and 588 nm, respectively, in good agreement with previously reported
values (Fig. 5D) [20].
#137258 - $15.00 USD
(C) 2010 OSA
Received 27 Oct 2010; revised 27 Nov 2010; accepted 30 Nov 2010; published 7 Dec 2010
20 December 2010 / Vol. 18, No. 26 / OPTICS EXPRESS 26911

Page 8

Fig. 5. Spectral images of HEK-293 cells expressing (A) CFP, (B) YFP and (C) DsRed were
acquired at excitation wavelengths of (A) 800, (B) 900, and (C) 940 nm, and detected at (A)
486-560, (B) 508-588 and (C) 560-654 nm, respectively. The spectra in the regions of interest
are shown in (D). The scale bar represents 20 μm.
As a second application, we acquired an autofluorescence spectral image stack from the
rhizome of Convallaria Majalis tissue. Upon screening at various excitation wavelengths
within the 700-950 nm range, we found a specific excitation wavelength at 758 nm that
showed distinctive autofluorescence spectra in two subcellular compartments. As shown in
the overlay image (Fig. 6A) composed of distinct single spectral images (Fig. 6B–6E), the cell
wall (Fig. 6B) could be easily distinguished from the plasma membrane (Fig. 6E). Here, the
images (Fig. 6B–6E) were taken from single channels with the spectral width of 8-9 nm. We
found that cell wall (a) and plasma membrane (b) have their own distinctive autofluorescence
spectra as shown in Fig. 6F.

Fig. 6. Spectral autofluorescence images of Convallaria Majalis tissue. Multiple spectral
signatures reveal subcellular compartments (B-F) as seen in the overlay image (A) taken from
single channels at (B) 639-647, (C) 661-669, (D) 693-701 and (E) 719-728 nm. The spectra of
cell wall (a) and plasma membrane (b) are shown in (F). The scale bar represents 20 μm.
In a third application, we visualized quantum dots (QDs), which are promising labels for
2PE spectral microscopy. QDs are co-excitable with a single excitation source and emit
narrow emission spectra throughout the visible and near-infrared spectral ranges. Using
multiple QD staining at various time points, we tracked the redistribution of GPCR along the
endocytotic internalization process. To accomplish this, we incorporated an SBP-tag (a short
sequence of 38 amino acids that recognizes the biotin-binding site of streptavidin, SA) at the
#137258 - $15.00 USD
(C) 2010 OSA
Received 27 Oct 2010; revised 27 Nov 2010; accepted 30 Nov 2010; published 7 Dec 2010
20 December 2010 / Vol. 18, No. 26 / OPTICS EXPRESS 26912

Page 9

N-terminus of the 5-HT2C serotonin receptor (Fig. 7A). SA-linked labels are ideal markers
for receptors because they do not cross the cell membrane and can access more sterically
restricted spaces than antibodies (8-53 kDa versus 150 kDa). We labeled selectively the
surface-associated pools of 5-HT2C receptors at different times (24 h, 6 h and 1 h prior to
imaging) by successively using three SA-conjugated, spectrally distinctive fluorescent QDs
(Fig. 7A). Due to their broad absorption spectra, all three QDs (quantum dots 525, 585 and
655) were simultaneously excited at a wavelength of 800 nm. Figure 7B shows the overlay
image of the SBP-5-HT2C expressing cell line labeled with three QDs (Fig. 7C–7E).
Figure 7F–7H shows the spectra of the regions indicated in Fig. 7B and representing different
subcellular locations. The 5-HT2C receptors that had been labeled at 24 and 6 h before
imaging with QDs 525 and 585 were located mostly in the cellular interior (Fig. 7C and 7D).
In contrast, the QD 655 nm spectral signature remained exclusively at the plasmalemma
(Fig. 7E). This result proves the feasibility to study the life cycle of receptors using GPCR
staining with multiple QDs and 2PE spectral imaging. Figure 7 corroborates the usability of
our system for imaging samples labeled with multiple probes or showing complex
autofluorescence.

Fig. 7. Multiple QD pulse-chase staining of 5-HT2C receptors undergoing endocytosis and
spectral images. (A) SBP-tagged 5-HT2C receptors were incubated sequentially, washed and
kept in the chamber at 37°C until the next pulse-chase staining. This took place at 24 hours, 6
hours and 1 hour, and used three different streptavidin-conjugated QDs for 30 minutes. Image
stacks were acquired 30 minutes after the last staining (B). The images representing (C) QD
525, (D) QD 585 and (E) QD 655 were obtained from the channels specific to each peak,
ranging from 526 to 535 nm for QD 525, 576-588 nm for QD 585 and 635-647 nm for QD 655.
The scale bar represents 20 μm. In the overlay image (B), spectrally different QD-labeled 5-
HT2C can be found in intracellular compartments (F and G) and in the plasmalemma (H) based
on the receptor internalization rate and depending on the pulse chase time point.
6. Conclusion
We have developed a simple and useful method and setup that enables the acquisition of full
spectral fluorescence images of biological samples with high spectral and temporal resolution
#137258 - $15.00 USD
(C) 2010 OSA
Received 27 Oct 2010; revised 27 Nov 2010; accepted 30 Nov 2010; published 7 Dec 2010
20 December 2010 / Vol. 18, No. 26 / OPTICS EXPRESS 26913

Page 10

and high sensitivity. We could show that coupled with a 2PE laser scanning microscope, our
spectral detection system provides a high signal-to-noise ratio and good spectral distinction of
the emitted light from the excitation source and of different fluorophores from each other over
the full detection range of the visible spectrum. As an outlook, our setup should allow to
obtain information about diffusion and interaction properties of biomolecules in living cells or
tissue using FCS [16]. Moreover, advanced unmixing methods [19] will enable an even better
decomposition of multiple fluorophores especially when their emission spectra overlap. We
expect that our approach, coupled with robust and fast image analysis, will advance high
content microscopy of complex samples beyond single cells.
Acknowledgments
This research was supported by the Basic Science Research Program of the National Research
Foundation of Korea (NRF), funded by the Ministry of Education, Science and Technology
(2010-0013312).
#137258 - $15.00 USD
(C) 2010 OSA
Received 27 Oct 2010; revised 27 Nov 2010; accepted 30 Nov 2010; published 7 Dec 2010
20 December 2010 / Vol. 18, No. 26 / OPTICS EXPRESS 26914