Abstract

Single plane illumination microscopy based fluorescence correlation spectroscopy (SPIM-FCS) is a new method for imaging FCS in 3D samples, providing diffusion coefficients, transport, flow velocities and concentrations in an imaging mode. SPIM-FCS records correlation functions over a whole plane in a sample, which requires array detectors for recording the fluorescence signal. Several types of image sensors are suitable for FCS. They differ in properties such as effective area per pixel, quantum efficiency, noise level and read-out speed. Here we compare the performance of several low light array detectors based on three different technologies: (1) Single-photon avalanche diode (SPAD) arrays, (2) passive-pixel electron multiplying charge coupled device (EMCCD) and (3) active-pixel scientific-grade complementary metal oxide semiconductor cameras (sCMOS). We discuss the influence of the detector characteristics on the effective FCS observation volume, and demonstrate that light sheet based SPIM-FCS provides absolute diffusion coefficients. This is verified by parallel measurements with confocal FCS, single particle tracking (SPT), and the determination of concentration gradients in space and time. While EMCCD cameras have a temporal resolution in the millisecond range, sCMOS cameras and SPAD arrays can extend the time resolution of SPIM-FCS down to 10 μs or lower.

© 2013 OSA

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2012

M. K. Landsberg, G. Herbomel, I. Wang, J. Derouard, C. Vourc’h, Y. Usson, C. Souchier, and A. Delon, “Cellular response to heat shock studied by multiconfocal fluorescence correlation spectroscopy,” Biophy. J.103, 1110–1119 (2012).
[CrossRef]

G. Mocsár, B. Kreith, J. Buchholz, J. W. Krieger, J. Langowski, and G. Vámosi, “Note: multiplexed multiple-tau auto- and cross-correlators on a single field programmable gate array,” Rev. Sci. Instrum.83, 046101 (2012).
[CrossRef] [PubMed]

S. Kalinin, R. Kühnemuth, H. Vardanyan, and C. a. M. Seidel, “Note: A 4 ns hardware photon correlator based on a general-purpose field-programmable gate array development board implemented in a compact setup for fluorescence correlation spectroscopy,” Rev. Sci. Instrum.83, 096105 (2012).
[CrossRef] [PubMed]

N. Bag, J. Sankaran, A. Paul, R. S. Kraut, and T. Wohland, “Calibration and limits of camera-based fluorescence correlation spectroscopy: a supported lipid bilayer study,” ChemPhysChem.13, 2784–2794 (2012).
[CrossRef] [PubMed]

S. Cox, E. Rosten, J. Monypenny, T. Jovanovic-Talisman, D. T. Burnette, J. Lippincott-Schwartz, G. E. Jones, and R. Heintzmann, “Bayesian localization microscopy reveals nanoscale podosome dynamics,” Nat. Methods9, 195–200 (2012).
[CrossRef]

J. Buchholz, J. W. Krieger, G. Mocsár, B. Kreith, E. Charbon, G. Vámosi, U. Kebschull, and J. Langowski, “FPGA implementation of a 32×32 autocorrelator array for analysis of fast image series,” Opt. Express20, 17767 (2012).
[CrossRef] [PubMed]

E. Baumgart and U. Kubitscheck, “Scanned light sheet microscopy with confocal slit detection,” Opt. Express20, 21805–21814 (2012).
[CrossRef] [PubMed]

2011

D. Broboana, C. Mihai, Balan, T. Wohland, and C. Balan, “Investigations of the unsteady diffusion process in microchannels,” Chem. Eng. Sci.66, 1962–1972 (2011).
[CrossRef]

D. Oh, A. Zidovska, Y. Xu, and D. J. Needleman, “Development of time-integrated multipoint moment analysis for spatially resolved fluctuation spectroscopy with high time resolution,” Biophy. J.101, 1546–1554 (2011).
[CrossRef]

J. Capoulade, M. Wachsmuth, L. Hufnagel, and M. Knop, “Quantitative fluorescence imaging of protein diffusion and interaction in living cells,” Nat. Biotechnol.29, 835–839 (2011).
[CrossRef] [PubMed]

S. C. P. Norris, J. Humpolíčková, E. Amler, M. Huranová, M. Buzgo, R. Machán, D. Lukáš, and M. Hof, “Raster image correlation spectroscopy as a novel tool to study interactions of macromolecules with nanofiber scaffolds,” Acta Biomater.7, 4195–4203 (2011).
[CrossRef] [PubMed]

R. A. Colyer, G. Scalia, F. a. Villa, F. Guerrieri, S. Tisa, F. Zappa, S. Cova, S. Weiss, and X. Michalet, “Ultra high-throughput single molecule spectroscopy with a 1024 pixel SPAD,” in “Proc. SPIE,” vol. 7905790503–1 (2011).

2010

T. Wohland, X. Shi, J. Sankaran, and E. H. K. Stelzer, “Single plane illumination fluorescence correlation spectroscopy (SPIM-FCS) probes inhomogeneous three-dimensional environments,” Opt. Express18, 1317–1327 (2010).
[CrossRef]

P. Kapusta, “Absolute diffusion coefficients: compilation of reference data for FCS calibration,” Pico-Quant pp. 0–1 (2010).

P. J. Keller, A. D. Schmidt, A. Santella, K. Khairy, Z. Bao, J. Wittbrodt, and E. H. K. Stelzer, “Fast, high-contrast imaging of animal development with scanned light sheet-based structured-illumination microscopy,” Nat. Methods7, 637–642 (2010).
[CrossRef] [PubMed]

E. Charbon and S. Donati, “SPAD sensors come of age,” Optics & Photonics News21, 35–41 (2010).
[CrossRef]

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. Express18, 23818–23828 (2010).
[CrossRef] [PubMed]

R. A. Colyer, G. Scalia, I. Rech, A. Gulinatti, M. Ghioni, S. Cova, S. Weiss, and X. Michalet, “High-throughput FCS using an LCOS spatial light modulator and an 8 × 1 SPAD array,” Biomed. Opt. Express1, 1408–1431 (2010).
[CrossRef]

J. Sankaran, X. Shi, L. Y. Ho, E. H. K. Stelzer, and T. Wohland, “ImFCS: a software for imaging FCS data analysis and visualization,” Opt. Express18, 25468–25481 (2010).
[CrossRef] [PubMed]

2009

D. J. Needleman, Y. Xu, and T. J. Mitchison, “Pin-hole array correlation imaging: Highly parallel fluorescence correlation spectroscopy,” Biophy. J.96, 5050–5059 (2009).
[CrossRef]

N. Dross, C. Spriet, M. Zwerger, G. Müller, W. Waldeck, and J. Langowski, “Mapping EGFP oligomer mobility in living cell nuclei,” PLoS ONE4, e5041 (2009).
[CrossRef]

T. Dertinger, R. Colyer, G. Iyer, S. Weiss, and J. Enderlein, “Fast, background-free, 3D super-resolution optical fluctuation imaging (SOFI),” Proc. Natl. Acad. Sci. U.S.A.106, 22287–22292 (2009).
[CrossRef] [PubMed]

J. Sankaran, M. Manna, L. Guo, R. Kraut, and T. Wohland, “Diffusion, transport, and cell membrane organization investigated by imaging fluorescence cross-correlation spectroscopy,” Biophy. J.97, 2630–2639 (2009).
[CrossRef]

X. Shi, Y. H. Foo, T. Sudhaharan, S. W. Chong, V. Korzh, S. Ahmed, and T. Wohland, “Determination of dissociation constants in living zebrafish embryos with single wavelength fluorescence cross-correlation spectroscopy,” Biophy. J.97, 678–786 (2009).
[CrossRef]

X. Shi, L. S. Teo, X. Pan, S. W. Chong, R. Kraut, V. Korzh, and T. Wohland, “Probing events with single molecule sensitivity in zebrafish and Drosophila embryos by fluorescence correlation spectroscopy,” Dev. Dyn.238, 3156–3167 (2009).
[CrossRef] [PubMed]

2008

J. R. Unruh and E. Gratton, “Analysis of molecular concentration and brightness from fluorescence fluctuation data with an electron multiplied CCD camera,” Biophy. J.95, 5385–5398 (2008).
[CrossRef]

Z. Petrásek, P. Schwille, and Z. Petrášek, “Precise measurement of diffusion coefficients using scanning fluorescence correlation spectroscopy,” Biophy. J.94, 1437–1448 (2008).
[CrossRef]

2007

X. Pan, W. Foo, W. Lim, M. H. Y. Fok, P. Liu, H. Yu, I. Maruyama, and T. Wohland, “Multifunctional fluorescence correlation microscope for intracellular and microfluidic measurements,” Rev. Sci. Instrum.78, 053711 (2007).
[CrossRef] [PubMed]

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Figures (5)

Fig. 1
Fig. 1

Schematic Sketches of [A] a selective plane illumination and [B] a confocal microscope.

Fig. 2
Fig. 2

Exemplary light sheet characterization of SPIM1: [A] illustrates the scanning of a 45° mirror to image the light sheet. [B] The intensity profile of the light sheet (blue line) at the central region of the field of view and a Gaussian fit to the profile (red dashed line). [C] The light sheet intensity profile at different regions of the camera along the illumination direction. [D] Thickness variation (obtained from the Gaussian fit) along the illumination axis. The grey box marks the central region (∼ 8 μm wide) with approximately constant light sheet thickness.

Fig. 3
Fig. 3

Exemplary normalized ACFs (red), 2f-FCCS (blue) plots and fit results (black dashed) for 0.1 μm diameter fluorescent microspheres at fastest read-out speed: [A] SPAD array detector with minimal lag time τmin = 3 μs, [B] SA-05 CMOS τmin = 16.6 μs, [C] ORCA-Flash4.0 sCMOS: τmin = 38.9 μs, [D] pco.edge sCMOS: τmin = 495 μs, [E] Andor iXon X3 860 EMCCD: τmin = 495 μs and [F] Evolve 512 EMCCD: τmin = 2380 μs. All curves are normalized for the zero-lag amplitude obtained from the fits.

Fig. 4
Fig. 4

Absolute diffusion coefficient determination for 0.2 μm diameter fluorescent microspheres by four different methods. Each subplot shows measured data (red, blue) and a fit to the data (dashed lines). [A] exemplary SPIM-FCS measurement, [B] Confocal FCS Measurement, [C] Mean-squared displacement curve (MSD) from a single particle tracking experiment, [D] intensity profile across the microchannel at two positions, [E] exemplary SPIM-FCS fit and velocity distribution used to determine the flow speed for [D].

Fig. 5
Fig. 5

Results of a dilution series measurement of 0.1 μm diameter fluorescent microspheres in water. The plot shows the expected value Cset plotted agains the measured value Cmeasured (circles) and linear fits to these (dashed lines, intercept at Cset = Cmeasured = 0). Data was acquired on different setups: A confocal microscope (black), and on a SPIM with four different detectors (green: ORCA-Flash4.0, red: iXon X3 860, brown: Radhard2, blue: pco.edge). datapoints are average ±standard deviation as in Table 1. The fitting has been weighted with satandard deviation.

Tables (2)

Tables Icon

Table 1 Summary of the results obtained with all types of array detectors for a sample of 0.1 μm fluorescent latex beads in water. All diffusion coefficients are renormalized to 20°C and average ± standard deviation over the specified number of pixels are given. The table also contains the camera specifications (as provided by the manufacturers) and focus parameters.

Tables Icon

Table 2 Diffusion coefficient D of 0.2 μm microsphere determined with SPIM-FCS, Confocal FCS, single particle tracking (SPIM-SPT) and measuring the lateral diffusive mixing in a Y-shaped microchannel (“SPIM-FCS”).

Equations (10)

Equations on this page are rendered with MathJax. Learn more.

G ( τ ) = I ( t ) I ( t + τ ) I ( t ) 2
G ( τ ) = 1 π w z a 2 C ( 4 D τ + w xy 2 π a ( e ( a 2 4 D τ w xy 2 ) 1 ) + erf ( a 4 D τ + w xy 2 ) ) 2 ( 1 + 4 D τ w z 2 ) 1 / 2 + G
MDE ( x ) = CEF ( x ) I ill ( x ) ,
1 w z 2 = 1 w ill 2 + 1 w det 2
V eff : ( MDE ( x ) d V ) 2 MDE 2 ( x ) d V = π a 2 w z ( erf ( a w xy ) + w xy π a ( e ( a / w xy ) 2 1 ) ) 2
g ( τ ) = G + 1 N ( 1 + 4 D τ w xy 2 ) 1 ( 1 + 4 D τ K 2 w xy 2 ) 1 / 2
c = N V eff ( confocal ) = N π 3 / 2 w xy 3 K
c ( x ) = b + c 0 erf ( x x 0 4 D t )
G ( 0 ) G = δ I 2 ( t ) I ( t ) 2 = N N 2 = 1 N = V eff C ,
C measured ( C set ) = C 0 + α C set

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