Recent advances in fluorescence correlation spectroscopy

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Recent advances in fluorescence correlation spectroscopy Nancy L Thompson*‡, Alena M Lieto*† and Noah W Allen* Fluorescence correlation spectroscopy is a method in which fluctuations in the fluorescence arising from a very small sample volume are correlated to obtain information about the processes giving rise to the fluctuations. Recent progress has been made in methodologies such as two-photon excitation, photon counting histogram analysis, cross-correlation, image correlation and evanescent excitation. Fluorescence correlation spectroscopy techniques have been applied to several biological processes, including fluorescent protein photodynamics, binding equilibria and kinetics, protein oligomerization, nucleic acid interactions, and membrane and intracellular dynamics. Addresses *Department of Chemistry, Campus Box 3290, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-3290, USA †Department of Physics & Astronomy, Campus Box 3255, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3255, USA ‡e-mail: [email protected] Current Opinion in Structural Biology 2002, 12:634–641 0959-440X/02/$ — see front matter © 2002 Elsevier Science Ltd. All rights reserved. Abbreviations FCS fluorescence correlation spectroscopy FIDA fluorescence intensity distribution analysis GFP green fluorescent protein GUV giant unilamellar vesicle HCV hepatitis C virus PCH photon counting histogram TIR-FCS total internal reflection with fluorescence correlation spectroscopy

Introduction Fluorescence correlation spectroscopy (FCS) is a method in which the fluorescence intensity arising from a very small volume containing fluorescent molecules is correlated to obtain information about the processes that give rise to fluctuations in the fluorescence. In the conventional form of this method [1], the sample volume is defined by a focused laser beam and a confocal pinhole. The fluorescence is collected with a high aperture microscope objective and monitored by a sensitive single-photon counting detector. The measured fluorescence fluctuates with time and these temporal fluctuations are autocorrelated (Figure 1). The normalized fluorescence fluctuation autocorrelation function provides two types of information — the magnitude is inversely related to the average number of observed fluorescent molecules, and the rate and shape of the temporal decay reflect the dynamic properties of the observed molecules. The initial development of FCS was comprehensively reviewed several years ago [2,3]. These earlier summaries are complemented by a series of more recent reviews [4•,5–8], as well as by a very thorough, recently published book [9••].

Here, we describe recent developments in the methodology of FCS, as well as applications to biological systems.

Methodologies Two-photon excitation

The use of two-photon excitation in FCS continues to show considerable promise in expanding the versatility of FCS as a method for examining biological systems. Excitation by two-photon absorption is approximately proportional to the square of the illumination intensity; therefore, fluorescence excitation is confined to a very small volume near the focal plane of an appropriately intense, focused laser beam. In conventional one-photon FCS, even though the excitation laser beam is almost always focused, a large region of the sample is still excited along the optical axis and the sample volume must therefore be defined in part by a confocal pinhole. With two-photon excitation, out-of-focus fluorescence is dramatically reduced due to lower excitation probabilities, thereby eliminating the need for a pinhole. The inherent optical-axis sectioning effect in two-photon FCS decreases background fluorescence levels and minimizes sample photodamage. Two-photon excitation also provides a large spectral separation between excitation and emission wavelengths, allowing for decreased detection of scattered excitation light. One of the first applications of two-photon FCS was to demonstrate its ability to examine molecular dynamics in the interiors of live cells [10]. Two-photon FCS has recently been used to examine a variety of biological processes [11,12•–15•,16–23] and has been incorporated into dual-color cross-correlation FCS [12•], imaging FCS [13•] and UV- FCS [21]. Photon counting histogram

For single-component samples, the magnitude of the normalized fluorescence fluctuation autocorrelation function is inversely related to the average number of fluorescent molecules in the sample volume and can be used to obtain absolute number densities. A complementary method for measuring fluorophore concentrations is photon counting histogram (PCH) analysis, also known as fluorescence intensity distribution analysis (FIDA). In this method, the temporal series of detected photons is used to generate a histogram reflecting the probability of measuring a given number of photons in a given sample time and the shape of the histogram is fit to appropriate theoretical forms to obtain the number density [16,24]. PCH is rapidly becoming a standard complement to many FCS measurements in part because the histogram can readily be calculated from the same data used to generate the autocorrelation functions [17,22,25•,26]. In conventional FCS for multicomponent samples, the autocorrelation function magnitude depends jointly on all of the concentrations of the different fluorescent species and on their relative

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Figure 1 (a)

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Schematic of conventional, diffusional FCS. (a) Fluorescent molecules diffuse through a focused laser beam. The fluorescence arising from illuminated molecules is collected with a high aperture objective on an optical microscope, through a confocal pinhole, which defines the extent of the detection volume along the optical axis (oval). (b) The fluorescence is measured with a sensitive single-photon counting detector and fluctuates with time. Typical collection periods are 1 s to

10 min. (c,d) The fluorescence fluctuations are autocorrelated and normalized by the average fluorescence squared. These plots show the theoretical shape of the normalized autocorrelation function G(τ), as a function of the correlation time τ, when the sample volume contains an average of 20 molecules, the diffusion coefficient (D) is 2 × 10−6 cm2/s, the 1/e2 - radius of the sample volume (s) is 0.45 µm and the half-time for decay is s2/4D ≅ 0.25 ms.

fluorescence yields [2,3]. One approach for resolving the magnitude into its different components is to use PCH. In this method, the histogram is fit to functions accounting for the presence of multiple species [27•]. FIDA has recently been extended to the dual-color cross-correlation regime [28•], as well as to the time domain, by generating multiple histograms with different sample time durations [29•].

is particularly sensitive to the presence of complexes formed by the two components. One of the first demonstrations of this method was to monitor the renaturation of complementary DNA oligonucleotides [30]. In many cases, the two fluorophores are spatially and spectrally separated to the extent that energy transfer between them is negligible. However, if the experimental system is designed to facilitate transfer [31], temporal fluctuations in the transfer efficiency can be used to characterize structural dynamics, such as in DNA hairpin-loop opening and closing [32•]. One limitation of cross-correlation FCS is the difficulty of aligning the volumes defined by the two focused excitation beams, which is complicated both by chromatic aberrations present in most microscope objectives and by differences in the focused spot sizes resulting from the wavelength difference. A recently proposed method for addressing this difficulty is to use two-photon absorption, which can excite fluorophores

Cross-correlation

In principle, significantly more information can be obtained in FCS by cross-correlating in addition to autocorrelating. In the simplest form of this method, called dual-color cross-correlation FCS, two species are labeled with different fluorophores, the two fluorophores are excited by different laser lines and their respective emissions are recorded by separate detectors. The signal measured by each detector is autocorrelated and the two signals are also cross-correlated. The cross-correlation function

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with spectrally separated emission spectra using a single laser line. This principle has been demonstrated for systems containing two different rhodamine derivatives [12•] and also in imaging FCS on live cells [13•]. An alternative scheme for distinguishing multiple species, which does not require dual excitation wavelengths and detectors, is to use pulsed excitation and a time-gated approach in which photons arriving at the detector within a certain time after excitation are suppressed [33,34]. If different species have different lifetimes, their relative fluorescence intensities and therefore relative contributions to the autocorrelation function can be altered by changing the gating duration. Image correlation spectroscopy

In conventional FCS with a single fluorescent species, the magnitude of the fluorescence fluctuation autocorrelation function is inversely related to the average number of independently mobile fluorophores in the sample volume. This characteristic was recognized early as a feature that might make FCS particularly well suited to detecting and characterizing molecular self-association and, in particular, receptor oligomerization or other spatial inhomogeneities on cell membranes [2,3]. However, the initial approach, in which fluctuations in the fluorescence arising from a small illuminated region of the membrane were to be generated by diffusion, was problematic because, frequently, a significant fraction of the fluorescent molecules of interest was translationally immobile or only very slowly mobile. This problem was successfully addressed by the development of imaging FCS, in which confocal scanning laser microscopy is used to generate high-resolution images and the pixel-to-pixel fluorescence fluctuations are spatially autocorrelated [35]. Imaging FCS is particularly applicable to quantifying cluster densities and sizes, and has been used to characterize a variety of structural and dynamic features on cell and model membranes [35–38]. Imaging FCS has been extended to the time domain by correlating successively acquired images [39]. In another methodological advance, dual-color cross-correlation analysis was combined with imaging FCS to examine co-localization of membrane components [40]. These very significant technological improvements were further advanced by implementing two-photon excitation [13•]. Total internal reflection excitation

Several years ago, the combination of total internal reflection illumination with FCS (TIR-FCS) was demonstrated as a method for examining the nonspecific adsorption/desorption kinetics of fluorescently labeled proteins with surfaces, as well as for measuring the translational mobility of molecules very close to surfaces [41]. In this method, the sample volume is defined by the thin, surface-associated evanescent field created by internal reflection and a pinhole placed at an intermediate image plane of an optical microscope. Several years later, TIR-FCS was revived and used to characterize the reversible interactions of small molecules with chromatographic surfaces [42]. More recently, this method has been used to examine the local concentration

and diffusion of fluorescently labeled proteins very close to substrate-supported phospholipid bilayers [43•]. Significant progress has also been made in the development of analytical expressions for quantitative analysis of TIR-FCS data [44]. Areas for future development include the use of very high refractive index substrates to generate extremely thin evanescent waves [45] and the use of TIR-FCS to examine association/dissociation kinetics of soluble ligands with specific, surface-bound receptors. Ultraviolet fluorophores

Because the signal-to-noise ratio of FCS autocorrelation functions depends, to a certain extent, on the number of photons detected per molecule per sample time, fluorophores with high absorptivities, high fluorescence quantum yields and low photodegradation rates have been preferred for use in FCS. This requirement has restricted FCS primarily to the visible region, for which highly fluorescent molecules are readily available, and has, in many cases, necessitated covalent conjugation of an extrinsic fluorophore to the molecule of interest. Recently, however, FCS in which the fluorescence was both excited and detected in the UV region was successfully used to examine the modified nucleotide 2-aminopurine [46]. In a related study, the intrinsic fluorescence of proteins and protein assemblies containing multiple tryptophan residues was monitored and autocorrelated after two-photon excitation [21]. FCS in the UV region is severely limited by decreased absorption coefficients and fluorophore quantum yields, lower light transmission through conventional microscope optical components and lower detector efficiencies. However, the possible development of UV-FCS as a broadly applicable method is particularly important for both protein and nucleic acid studies because it would remove the need for extrinsically conjugated, visible-spectrum probes. This would thereby eliminate deleterious structural effects induced by the probes and reduce contributions arising from independent probe mobility in studies of conformational dynamics and rotational motions.

Applications Photodynamics of green fluorescent proteins

The clonable green fluorescent protein (GFP) from the Aequorea jellyfish and related mutants have become some of the most commonly used fluorescent tags in cellular applications due to their high quantum yield, photostability and minimal interference within the cell. FCS is a useful technique for investigations of photodynamic processes that cause fluctuations in the fluorescence intensity on a timescale much faster than translational diffusion. In mutants of GFP, as well as in other fluorescent molecules, these processes include reversible transitions to dark, nonfluorescing states that may be an electronic state of the same molecule (triplet state), a protonated form of the fluorescent state or perhaps a photoinduced isomer. Correlation functions of GFP mutants have been studied as a function of pH to examine internal and external protonation processes [47], and as a function of excitation

Fluorescence correlation spectroscopy Thompson, Lieto and Allen

intensity to investigate photoinduced isomerization of the chromophore [48]. A similar excitation intensity dependence is seen for trans-cis isomerization of the cyanine dye Cy5 [49•]. Similarly, yellow-shifted GFP mutants exhibit intensity-dependent flickering at high pH, as well as pH-dependent quenching by external protonation at low pH [50]. Light-induced flickering of a red-emitting counterpart of GFP (DsRed) has also been observed and evidence suggests that at least one of its ‘dark’ states is also fluorescent, with altered excitation and emission properties [14•]. In this study, a two-color excitation technique previously applied to a GFP mutant [51] was employed to determine spectroscopic information about the dark states. A second exciting laser beam was used to probe the population of dark (or dim) states that absorb at a shifted wavelength and repopulation of the ground state was observed [14•,51]. In many of these studies, evidence was found for at least two independent flicker processes, other than triplet-state dynamics, indicating that there are multiple dark states [14•,47,48,50]. Binding equilibria

FCS can be used to monitor bimolecular interactions if the bound and free states can be differentiated on the basis of a property reflected in the autocorrelation function (e.g. the diffusion coefficient or molecular brightness). For example, when a small fluorescent molecule binds to a much larger nonfluorescent molecule, an increase in the diffusion time through the sample volume alters the temporal nature of the fluorescence fluctuations. The relative fractions of bound and free components, as well as the total number of fluorescent particles, can be monitored via the autocorrelation function magnitude and temporal decay. Using this approach, the binding constants of several fluorescent ligands with a solubilized form of a 5-hydroxytryptamine receptor have been determined [52]. This study also demonstrated that the interaction of a nonfluorescent competitor with the receptor could be monitored by using an FCS competition assay. The rotary enzyme ATP synthase has been investigated to determine whether the strength of binding between subunits making up the stator would be sufficient to hold against the elastic strain generated during its operation [53]. Specific interactions between phage with displayed fragments of antibodies specific for hepatitis C virus (HCV) and HCV antigens have been characterized by using two-color FCS in which the antigens were labeled with one fluorophore and the phage were labeled with anti-phage antibodies conjugated to a different fluorophore [54]. One complication of using diffusional FCS for ligand-binding studies is that, if the transit time through the sample volume is fast enough and the excitation intensity high enough, contributions to the autocorrelation function from excited-state kinetics can overlap with contributions from diffusional dynamics; the two contributions must be separated [52,55]. PCH analysis is also useful in binding studies and has been used to determine the stoichiometry of the interaction between human estrogen receptor α and a fragment of its coactivator

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protein SRC-1 in the presence of ligands such as estradiol [26]. A related statistical technique, moment analysis, has been used to characterize the binding of a fluorescent ligand that is quenched upon binding to its antibody [56]. Another statistical method has been developed to analyze fluorescence fluctuations with bright spikes, such as those due to fluorescent ligands interacting with receptors with multiple binding sites [57]. Binding kinetics

Examining the temporal characteristics of the fluorescence fluctuations arising from transitions between molecular states with different intensities was proposed in the 1970s as a method for measuring kinetic rate constants [1]. This approach has recently been used to monitor the interaction kinetics between the dye ANS and apomyogloblin [58]. A limitation of this approach is that the fluorescence fluctuations arising from kinetic transitions must be faster than the transit time by diffusion through the sample volume. In the reverse case, if the kinetics are slow enough, they can be monitored by acquiring temporally successive autocorrelation functions, thereby following the rate of change in the concentrations of the interacting species [30]. This approach has recently been used to monitor the association and dissociation kinetics of labeled transferrin with its receptor [55], and to monitor the exchange rate of tubulin dimers with microtubules [59]. For kinetic processes that are neither very fast nor very slow, TIR-FCS may be useful [41]. In this method, one of the interacting species is immobilized on a surface while the other fluorescent species is free in solution, and evanescent illumination is used to selectively excite the bound state. The temporal fluctuations in the fluorescence monitored from a small surface area depend directly on the association and dissociation rate constants [44]. Protein oligomerization

The sensitivity of the magnitude of the diffusional autocorrelation function to large fluorescence spikes and of its temporal decay to changes in molecular size [2,3] are features that make FCS particularly amenable to the study of protein oligomerization. FCS has recently been used to detect the aggregation of a fluorescently labeled synthetic amyloid β-protein probe, as induced by amyloid β-protein ‘seeds’ present in human cerebrospinal fluid [60], and to demonstrate that the formation of amyloid β-protein oligomers precedes the formation of fibrils [61]. The oligomerization of prion proteins, which are associated with several diseases including Creutzfeldt–Jakob disease and bovine spongiform encephalopathy [62––64], and the dimerization of a phospholipase A2 from venom and the effect of lipids on this process [23] have also been characterized. Nucleic acids

Diffusional FCS has been employed to examine the interactions between DNA and proteins such as the p53

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transcription factor [65] and the helicase RepA [66]. Dual-color cross-correlation FCS has been used to monitor the kinetics of DNA hybridization [30], as well as cleavage by restriction endonucleases [12•]. Fluctuations arising from energy transfer between two fluorophores have been examined with FCS to characterize both the dynamics of DNA hairpin-loop fluctuations [32•,67] and RNA structural transitions [68]. In a more biotechnological context, dual-color cross-correlation FCS was used to follow the time course of the appearance of amplified DNA during PCR by using primers tagged with different fluorophores [69]. The promise of this procedure is that it may provide a convenient, reliable and very sensitive method for viral detection; the protocol has been used to quantify HCV in serum [70]. A related approach was developed for human platelet antigen-1 genotyping [71]. FCS has also been explored as a method for sequencing single DNA molecules by identifying single fluorescently labeled mononucleotides as they are released by exonucleases from DNA strands [72,73]. Model membranes

FCS has been used to investigate the translational diffusion of lipids in single bilayer systems, such as supported [74] and unsupported [75] planar bilayers, and giant unilamellar vesicles (GUVs) [76–78]. The diffusive behavior of fluorescent lipid analogues in GUVs and in rat basophilic leukemia cell membranes was compared and evidence was presented for either anomalous subdiffusion or pure diffusion with at least two components in both cholesterolcontaining model membranes and cell membranes [77]. GUVs have also been used to study in more detail the diffusion of lipids incorporated into fluid, spatially ordered and high-cholesterol-content phases [76]. A recent protocol based on peptide-induced vesicle fusion has allowed the investigation of the lateral diffusion of the integral membrane protein bacteriorhodopsin after functional reconstitution into GUVs [78]. It is also possible to use FCS to determine the diffusion coefficients, and thus hydrodynamic radii, of vesicles that are smaller than the detection volume element [74,79]. This strategy has been used to demonstrate that the peptide melittin forms channels in vesicles, releasing the contents, whereas the peptide magainin breaks vesicle membranes into pieces; this raises the possibility of using FCS to test vesicles as drug carriers [79]. Cell-surface receptors

One area of recent activity has been the use of FCS to characterize structural and dynamic features of membrane receptors on intact, viable cells. Imaging FCS has been demonstrated as a viable methodology by characterizing cell-surface receptor distributions [13•,35,39], the abundance of dendritic spines located in neurons from brain tissue slices [36], membrane inhomogeneities associated with virus attachment [38,40] and the self-association of antibodies specifically bound to substrate-supported planar membranes [37]. Diffusional FCS has been used to

examine the binding of proinsulin C-peptide to specific G-protein-coupled receptors [80], as well as the diffusional heterogeneity of ligand-labeled insulin receptors [81], epidermal growth factor receptors [82] and galanin receptors [83] in cell membranes. In a different approach, dual-color cross-correlation FCS has been used to examine the oligomerization states of somatostatin receptors expressed on CHO cells [20]. Intracellular dynamics

The use of FCS to probe intracellular dynamics is challenging because of the presence of significant autofluorescence, as well as possible photobleaching, fluorescence flickering or simple cell movement. Therefore, to establish feasibility, initial investigations primarily addressed the concentration and translational mobility of GFP constructs and microinjected or imported fluorescent molecules in intracellular environments [10,25•,84–88]. Comparisons of one-photon versus twophoton FCS [11], as well as FCS versus PCH [25•], for examining intracellular dynamics have also been carried out. Recently, several novel applications of diffusional FCS to transport measurements in intracellular environments have been reported, including its use in correlating the concentration of an intracellular chemotactic signaling protein with flagellar motor activity in Escherichia coli [89•], in monitoring and separating active versus diffusive transport of GFP within plastid tubules and the cytosol of plant cells [15•] and in characterizing the mode of transport of tubulin in squid giant axons [90•].

Conclusions FCS has continued to experience considerable development as a method for examining a wide variety of physical phenomena in biology. These phenomena include thermodynamic and kinetics aspects of molecular interactions, transport processes and excited-state dynamics. Recent methodological improvements have significantly increased the versatility of FCS, including the use of two-photon excitation, PCH analysis, cross-correlation, image correlation and evanescent illumination. FCS has now been effectively applied to a large variety of biological systems, such as ligand–receptor interactions, protein aggregation associated with disease, DNA–protein interactions, membrane domains and cell-surface receptor clustering. A body of recent work has addressed the excited-state dynamics of GFP and other probes potentially suitable for in vivo use. This work significantly increases the likelihood that FCS will prove to be broadly applicable as a method not only for characterizing processes in solution but also for examining processes in intact cells and their membranes, as illustrated by several recent and novel studies.

Acknowledgements This work was supported by National Science Foundation grant MCB-0130589, American Chemical Society Petroleum Research Fund grant 35376-AC5-7 and North Carolina Biotechnology Center grant 2000-ARG-0026.

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Haupts U, Maiti S, Schwille P, Webb WW: Dynamics of fluorescence fluctuations in green fluorescent protein observed by fluorescence correlation spectroscopy. Proc Natl Acad Sci USA 1998, 95:13573-13578.

48. Widengren J, Mets G, Rigler R: Photodynamic properties of green fluorescent proteins investigated by fluorescence correlation spectroscopy. Chem Phys 1999, 250:171-186. 49. Widengren J, Schwille P: Characterization of photoinduced • isomerization and back-isomerization of the cyanine dye Cy5 by fluorescence correlation spectroscopy. J Phys Chem A 2000, 104:6416-6428. FCS is used to investigate the isomerization properties of Cy5 over a broad range of experimental conditions, such as solvent viscosity, polarity and temperature, excitation intensity and wavelength, and conjugation to different macromolecules. 50. Schwille P, Kummer S, Heikal AA, Moerner WE, Webb WW: Fluorescence correlation spectroscopy reveals fast optical excitation-driven intramolecular dynamics of yellow fluorescent proteins. Proc Natl Acad Sci USA 2000, 97:151-156. 51. Jung G, Bräuchle C, Zumbusch A: Two-color fluorescence correlation spectroscopy of one chromophore: application to the E222Q mutant of the green fluorescent protein. J Chem Phys 2001, 114:3149-3156.

52. Wohland T, Friedrich K, Hovius R, Vogel H: Study of ligand-receptor interactions by fluorescence correlation spectroscopy with different fluorophores: evidence that the homopentameric 5-hydroxytryptamine type 3As receptor binds only one ligand. Biochemistry 1999, 38:8671-8681. 53. Häsler K, Pänke O, Junge W: On the stator of rotary ATP synthase: αβ)3 as determined by The binding strength of subunit δ to (α fluorescence correlation spectroscopy. Biochemistry 1999, 38:13759-13765. 54. Lagerkvist AC, Földes-Papp Z, Persson MAA, Rigler R: Fluorescence correlation spectroscopy as a method for assessment of interactions between phage displaying antibodies and soluble antigen. Protein Sci 2001, 10:1522-1528. 55. Schhler J, Frank J, Trier U, Schäfer-Korting M, Saenger W: Interaction kinetics of tetramethylrhodamine transferrin with human transferrin receptor studied by fluorescence correlation spectroscopy. Biochemistry 1999, 38:8402-8408. 56. Chen Y, Müller JD, Tetin SY, Tyner JD, Gratton E: Probing ligand protein binding equilibria with fluorescence fluctuation spectroscopy. Biophys J 2000, 79:1074-1084. 57.

Van Craenenbroeck E, Vercammen J, Matthys G, Beirlant J, Marot C, Hoebeke J, Strobbe R, Engelborghs Y: Heuristic statistical analysis of fluorescence fluctuation data with bright spikes: application to ligand binding to the human serotonin receptor expressed in Escherichia coli cells. Biol Chem 2001, 382:355-361.

58. Bismuto E, Gratton E, Lamb DC: Dynamics of ANS binding to tuna apomyoglobin measured with fluorescence correlation spectroscopy. Biophys J 2001, 81:3510-3521. 59. Neumann T, Kirschstein SO, Camacho-Gomez JA, Kittler L, Unger E: Determination of the net exchange rate of tubulin dimers in steady-state microtubules by fluorescence correlation spectroscopy. Biol Chem 2001, 382:387-391. 60. Pitschke M, Prior R, Haupt M, Riesner D: Detection of single amyloid β-protein aggregates in the cerebrospinal fluid of Alzheimer’s patients by fluorescence correlation spectroscopy. Nat Med 1998, 4:832-834. 61. Tjernberg LO, Pramanik A, Björling S, Thyberg P, Thyberg J, Nordstedt C, Berndt KD, Terenius L, Rigler R: Amyloid β-peptide polymerization studied using fluorescence correlation spectroscopy. Chem Biol 1999, 6:53-62. 62. Post K, Pitschke M, Schäfer O, Wille H, Appel TR, Kirsch D, Mehlhorn I, Serban H, Prusiner SB, Riesner D: Rapid acquisition of β-sheet structure in the prion protein prior to multimer formation. Biol Chem 1998, 379:1307-1317. 63. Jansen K, Schäfer O, Birkmann E, Post K, Serban H, Prusiner SB, Riesner D: Structural intermediates in the putative pathway from the cellular prion protein to the pathogenic form. Biol Chem 2001, 382:683-691. 64. Bieschke J, Giese A, Schulz-Schaeffer W, Zerr I, Poser S, Eigen M, Kretzschmar H: Ultrasensitive detection of pathological prion protein aggregates by dual-color scanning for intensely fluorescent targets. Proc Natl Acad Sci USA 2000, 97:5468-5473. 65. Yakovleva T, Pramanik A, Kawasaki T, Tan-No K, Gileva I, Lindegren H, Langel G, Ekström TJ, Rigler R, Terenius L, Bakalkin G: p53 latency: C-terminal domain prevents binding of p53 core to target but not to nonspecific DNA sequences. J Biol Chem 2001, 276:15650-15658. 66. Xu H, Frank J, Trier U, Hammer S, Schröder W, Behlke J, Schäfer-Korting M, Holzwarth JF, Saenger W: Interaction of fluorescence labeled single-stranded DNA with hexameric DNA-helicase RepA: a photon and fluorescence correlation spectroscopy study. Biochemistry 2001, 40:7211-7218. 67.

Goddard NL, Bonnet G, Krichevsky O, Libchaber A: Sequence dependent rigidity of single stranded DNA. Phys Rev Lett 2000, 85:2400-2403.

68. Kim HD, Nienhaus GU, Ha T, Orr JW, Williamson JR, Chu S: Mg2+-dependent conformational change of RNA studied by fluorescence correlation and FRET on immobilized single molecules. Proc Natl Acad Sci USA 2002, 99:4284-4289. 69. Földes-Papp Z, Rigler R: Quantitative two-color fluorescence cross-correlation spectroscopy in the analysis of polymerase chain reaction. Biol Chem 2001, 382:473-478.

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70. Weiner OH, Alt M, Dürr R, Noegel AA, Caselmann WH: Rapid and reproducible quantification of hepatitis C virus cDNA by fluorescence correlation spectroscopy. Digestion 2000, 61:84-89.

81. Zhong ZH, Pramanik A, Ekberg K, Jansson OT, Jörnvall H, Wahren J, Rigler R: Insulin binding monitored by fluorescence correlation spectroscopy. Diabetologia 2001, 44:1184-1188.

71. Weber S, Hummel SA, Weber AA, Zirwes RF, Weinter OH, Reuber BE: Genotyping of human platelet antigen-1 by gene amplification and labelling in one system and automated fluorescence correlation spectroscopy. Br J Haematol 2002, 116:839-843.

82. Pramanik A, Rigler R: Ligand-receptor interactions in the membrane of cultured cells monitored by fluorescence correlation spectroscopy. Biol Chem 2001, 382:371-378.

72. Sauer M, Angerer B, Ankenbauer W, Földes-Papp Z, Göbel F, Han KT, Rigler R, Schulz A, Wolfrum J, Zander C: Single molecule DNA sequencing in submicroliter channels: state of the art and future prospects. J Biotechnol 2001, 86:181-201. 73. Földes-Papp Z, Angerer B, Thyberg P, Hinz M, Wennmalm S, Ankenbauer W, Seliger H, Holmgren A, Rigler R: Fluorescently labeled model DNA sequences for exonucleolytic sequencing. J Biotechnol 2001, 86:203-224. 74. Beneš M, Billy D, Hermens WT, Hof M: Muscovite (mica) allows the characterisation of supported bilayers by ellipsometry and confocal fluorescence correlation spectroscopy. Biol Chem 2002, 383:337-341. 75. Burden DL, Kasianowicz JJ: Diffusion bias and photophysical dynamics of single molecules in unsupported lipid bilayer membranes probed with confocal microscopy. J Phys Chem B 2000, 104:6103-6107. 76. Korlach J, Schwille P, Webb WW, Feigenson GW: Characterization of lipid bilayer phases by confocal microscopy and fluorescence correlation spectroscopy. Proc Natl Acad Sci USA 1999, 96:8461-8466. 77.

Schwille P, Korlach J, Webb WW: Fluorescence correlation spectroscopy with single-molecule sensitivity on cell and model membranes. Cytometry 1999, 36:176-182.

78. Kahya N, Pécheur EI, de Boeij WP, Wiersma DA, Hoekstra D: Reconstitution of membrane proteins into giant unilamellar vesicles via peptide-induced fusion. Biophys J 2001, 81:1464-1474. 79. Pramanik A, Thyberg P, Rigler R: Molecular interactions of peptides with phospholipid vesicle membranes as studied by fluorescence correlation spectroscopy. Chem Phys Lipids 2000, 104:35-47. 80. Rigler R, Pramanik A, Jonasson P, Kratz G, Jansson OT, Nygren PA, Ståhl S, Ekberg K, Johansson BL, Uhlén S et al.: Specific binding of proinsulin C-peptide to human cell membranes. Proc Natl Acad Sci USA 1999, 96:13318-13323.

83. Pramanik A, Olsson M, Langel G, Bartfai T, Rigler R: Fluorescence correlation spectroscopy detects galanin receptor diversity on insulinoma cells. Biochemistry 2001, 40:10839-10845. 84. Wachsmuth M, Waldeck W, Langowski J: Anomalous diffusion of fluorescent probes inside living cell nuclei investigated by spatially-resolved fluorescence correlation spectroscopy. J Mol Biol 2000, 298:677-689. 85. Dittrich P, Malvezzi-Campeggi F, Jahnz M, Schwille P: Accessing molecular dynamics in cells by fluorescence correlation spectroscopy. Biol Chem 2001, 382:491-494. 86. Nomura Y, Tanaka H, Poellinger L, Higashino F, Kinjo M: Monitoring of in vitro and in vivo translation of green fluorescent protein and its fusion proteins by fluorescence correlation spectroscopy. Cytometry 2001, 44:1-6. 87.

Waizenegger T, Fischer R, Brock R: Intracellular concentration measurements in adherent cells: a comparison of import efficiencies of cell-permeable peptides. Biol Chem 2002, 383:291-299.

88. Braun K, Peschke P, Pipkorn R, Lampel S, Wachsmuth M, Waldeck W, Friedrich E, Debus J: A biological transporter for the delivery of peptide nucleic acids (PNAs) to the nuclear compartment of living cells. J Mol Biol 2002, 318:237-243. 89. Cluzel P, Surette M, Leibler S: An ultrasensitive bacterial motor • revealed by monitoring signaling proteins in single cells. Science 2000, 287:1652-1655. FCS is used to measure the intracellular concentration of a GFP-labeled chemotactic signaling protein in E. coli. The concentration is correlated with flagellar activity. 90. Terada S, Kinjo M, Hirokawa N: Oligomeric tubulin in large • transporting complex is transported via kinesin in squid giant axons. Cell 2000, 103:141-155. In one of the first applications of FCS to intracellular dynamics, the diffusive motions of microinjected, labeled tubulin in squid giant axons are characterized.